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493 results on '"Distributions"'

1. Convergence of forecast distributions in a 100,000‐member idealised convective‐scale ensemble

Author: Tempest, Kirsten I., Craig, George C., and Brehmer, Jonas R.
Subjects: weather prediction, Atmospheric Science, ddc:551.6, distributions, asymptotic convergence, ensembles, idealised model, sampling uncertainty
Abstract: Many operational weather services use ensembles of forecasts to generate probabilistic predictions. Computational costs generally limit the size of the ensemble to fewer than 100 members, although the large number of degrees of freedom in the forecast model would suggest that a vastly larger ensemble would be required to represent the forecast probability distribution accurately. In this study, we use a computationally efficient idealised model that replicates key properties of the dynamics and statistics of cumulus convection to identify how the sampling uncertainty of statistical quantities converges with ensemble size. Convergence is quantified by computing the width of the 95% confidence interval of the sampling distribution of random variables, using bootstrapping on the ensemble distributions at individual time and grid points. Using ensemble sizes of up to 100,000 members, it was found that for all computed distribution properties, including mean, variance, skew, kurtosis, and several quantiles, the sampling uncertainty scaled as n−1/2 for sufficiently large ensemble size n. This behaviour is expected from the Central Limit Theorem, which further predicts that the magnitude of the uncertainty depends on the distribution shape, with a large uncertainty for statistics that depend on rare events. This prediction was also confirmed, with the additional observation that such statistics also required larger ensemble sizes before entering the asymptotic regime. By considering two methods for evaluating asymptotic behaviour in small ensembles, we show that the large‐n theory can be applied usefully for some forecast quantities even for the ensemble sizes in operational use today., An idealised ensemble that replicates key properties of the dynamics and statistics of cumulus convection is used to identify how sampling uncertainty of statistical quantities converges with ensemble size. A universal asymptotic scaling for this convergence was found, which was dependent on the statistic and the distribution shape, with largest uncertainty for statistics that depend on rare events. This is demonstrated in the figure below for a Gaussian distributed model variable, where the sampling uncertainty (y‐axis) for 5 quantiles (red lines) indicates that after a certain ensemble size, it begins converging asymptotically (grey lines), and the more extreme the quantile, the more members it requires for this to be the case., Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659, Klaus Tschira Stiftung http://dx.doi.org/10.13039/501100007316
Published: 2023
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2. First record of saucer scallop Ylistrum balloti (Bernardi, 1861) from equatorial South China Sea

Author: Wan Zabidii Wan Morni, Lirong Yu Abit, Kamil Latif, Sayali Nerurkar, Ruhana Hassan, and Abdulla-Al-Asif
Subjects: Alpha biodiversity, Malaysian Borneo, Saucer scallop, By-catch, Distributions, Animal Science and Zoology, Range extension
Abstract: Ylistrum balloti is one of the Pectinidae species distributed within the Indo-Pacific region. Recently, 15 live specimens ofY. ballotiwere recorded from the continental shelf of Sarawak, Malaysia. The main morphological characteristics were displayed on the outer valve, these being a brown-red colour and a clear concentric pattern of thin brown lines. The prominent internal ribbing numbers on both valves also helped species identification. The preliminary report ofY. ballotirevealed that the species is present in Sarawak waters and can be further explored in the future.
Published: 2023
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3. Range shifts of overwintering birds depend on habitat type, snow conditions and habitat specialization

Author: Laura Bosco, Yanjie Xu, Purabi Deshpande, Aleksi Lehikoinen, Finnish Museum of Natural History, Zoology, Helsinki Institute of Life Science HiLIFE, Joint Activities, Helsinki Institute of Urban and Regional Studies (Urbaria), Evolution, Sociality & Behaviour, Faculty Common Matters (Faculty of Biology and Environmental Sciences), and Helsinki Institute of Sustainability Science (HELSUS)
Subjects: IMPACTS, CLIMATE-CHANGE, NORTH, Climate Change, Global warming, Distribution shifts, FINLAND, Birds, TAXONOMIC GROUPS, DENSITY SHIFTS, Climate niche, Habitat use, FUTURE, Snow, 1181 Ecology, evolutionary biology, Bird monitoring, PATTERNS, Animals, DISTRIBUTIONS, POPULATIONS, Ecosystem, Ecology, Evolution, Behavior and Systematics
Abstract: Climatic warming is forcing species to shift their ranges poleward, which has been demonstrated for many taxa globally. Yet, the influence of habitat types on within- and among-species variations of distribution shifts has rarely been studied, especially during the non-breeding season. Here, we investigated habitat-specific shift distances of northern range margins and directions of the distribution center based on long-term data of overwintering birds in Finland. Specifically, we explored influences of habitat type, species’ snow depth tolerance, species’ climatic niche and habitat specialization on range shifts during the past 40 years in 81 bird species. Birds overwintering in arable land shifted more clearly toward north compared to birds of the same species in rural and forest habitats, while the northern range margin shift distances did not significantly differ among the habitat types. Range shifts were more linked with the species’ snow depth tolerance rather than species’ climatic niche. Snow depth tolerance of species was negatively associated with the eastward shift direction across all habitats, while we found habitat-specific patterns with snow depth for northward shift directions and northern margin shift distances. Species with stronger habitat specializations shifted more strongly toward north as compared to generalist species, whereas the climatic niche of bird species only marginally correlated with range shifts, so that cold-dwelling species shifted longer distances and more clearly eastward. Our study reveals habitat-specific patterns linked to snow conditions for overwintering boreal birds and highlights the importance of habitat availability and preference in climate driven range shifts.
Published: 2022
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4. Continuous characterizations of inhomogeneous Besov and Triebel-Lizorkin spaces associated to non-negative self-adjoint operators

Author: Qing Hong and Guorong Hu
Subjects: DECOMPOSITION, LIPSCHITZ, Mathematics::Functional Analysis, MAXIMAL-FUNCTION CHARACTERIZATION, HARDY-SPACES, General Mathematics, Mathematics::Classical Analysis and ODEs, 46E35, 42B25, 42B35, Mathematics and Statistics, DUALITY, Mathematics - Classical Analysis and ODEs, TEMPERATURES, Classical Analysis and ODEs (math.CA), FOS: Mathematics, DISTRIBUTIONS, WEIGHTED BESOV
Abstract: Let $(M,\rho,\mu)$ be a metric measure space satisfying the doubling, reverse doubling and non-collapsing conditions, and $\mathscr{L}$ be a self-adjoint operator on $L^2 (M, d\mu)$ whose heat kernel $p_t (x,y)$ satisfy the small-time Gaussian upper bound, H\"{o}lder continuity and Markov property. In this paper, we give characterizations of inhomogeneous "classical" and "non-classical" Besov and Triebel-Lizorkin spaces associated to $\mathscr{L}$ in terms of continuous Littlewood-Paley and Lusin area functions defined by the heat semigroup, for complete range of indices. This extends related classical results for Besov and Triebel-Lizorkin spaces on $\mathbb{R}^n$ to more general setting, and extends corresponding results in [Trans. Amer. Math Soc. 367 (2015), 121-189] to complete range of indices., Comment: 31 pages
Published: 2022
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5. Spatial patterns of light‐demanding tree species in the Yangambi rainforest (Democratic Republic of Congo)

Author: Nestor K. Luambua, Wannes Hubau, Kolawolé Valère Salako, Christian Amani, Bernard Bonyoma, Donatien Musepena, Mélissa Rousseau, Nils Bourland, Hippolyte S.M. Nshimba, Corneille Ewango, Hans Beeckman, and Olivier J. Hardy
Subjects: CANONICAL CORRESPONDENCE-ANALYSIS, light-demanding species, spatial analysis, Ecology, Evolution, Biology and Life Sciences, BIOTIC INTERACTIONS, forest composition, ENVIRONMENTAL HETEROGENEITY, COMMUNITY, Behavior and Systematics, SOIL NUTRIENTS, DISPERSAL, African forest ecology, DISTRIBUTIONS, TROPICAL TREES, PLANT, Yangambi biosphere reserve, light‐demanding species, QH540-549.5, Research Articles, DROUGHT, Ecology, Evolution, Behavior and Systematics, Research Article, Nature and Landscape Conservation
Abstract: Most Central African rainforests are characterized by a remarkable abundance of light‐demanding canopy species: long‐lived pioneers (LLP) and non‐pioneer light demanders (NPLD). A popular explanation is that these forests are still recovering from intense slash‐and‐burn farming activities, which abruptly ended in the 19th century. This “human disturbance” hypothesis has never been tested against spatial distribution patterns of these light demanders. Here, we focus on the 28 most abundant LLP and NPLD from 250 one‐ha plots distributed along eight parallel transects (~50 km) in the Yangambi forest. Four species of short‐lived pioneers (SLP) and a single abundant shade‐tolerant species (Gilbertiodendron dewevrei) were used as reference because they are known to be strongly aggregated in recently disturbed patches (SLP) or along watercourses (G. dewevrei). Results show that SLP species are strongly aggregated with clear spatial autocorrelation of their diameter. This confirms that they colonized the patch following a one‐time disturbance event. In contrast, LLP and NPLD species have random or weakly aggregated distribution, mostly without spatial autocorrelation of their diameter. This does not unambiguously confirm the “human disturbance” hypothesis. Alternatively, their abundance might be explained by their deciduousness, which gave them a competitive advantage during long‐term drying of the late Holocene. Additionally, a canonical correspondence analysis showed that the observed LLP and NPLD distributions are not explained by environmental variables, strongly contrasting with the results for the reference species G. dewevrei, which is clearly aggregated along watercourses. We conclude that the abundance of LLP and NPLD species in Yangambi cannot be unambiguously attributed to past human disturbances or environmental variables. An alternative explanation is that present‐day forest composition is a result of adaptation to late‐Holocene drying. However, results are inconclusive and additional data are needed to confirm this alternative hypothesis., The objective of this paper was to contribute to the elucidation of the light‐demanding species persistence puzzle in the Congo Basin rainforest canopy. Three hypotheses have been tested, which suggest: (H1) legacy of past disturbances, (H2) legacy of adaptation to a drier climate, and (H3) consequence of heterogeneity of the environment. Our results clearly support H1 for the species of short‐lived pioneer guild and do not unambiguously support a single hypothesis for the long‐lived pioneer and non‐pioneer light‐demanding guilds, although they seem to favor H2.
Published: 2021
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6. A new version of bienergies and biangles for curves framed by extended darboux frame

Author: Yasin Ünlütürk and Talat Körpinar
Subjects: ED-frame field, Pure mathematics, Darboux frame, Association (object-oriented programming), Computational intelligence, Bending, Theoretical Computer Science, Interpretation (model theory), Bienergy, Hypersurface, Vector fields, Bending energy, Mathematics::Differential Geometry, Geometry and Topology, Biharmonic Particles, Optical-Fiber, Energy, Distributions, Software, Mathematics
Abstract: In this work, we research geometrical interpretation involved with the bienergy by ED-frame fields of the first and second types on an orientable hypersurface in $$\mathbb {E}^{4}$$ . We explore the geometric features of some charts by means of bienergy in $$\mathbb {E}^{4}$$ . We implement totally diverse discussion and reach to clarify bending functional of bienergy for ED-frame fields of the first and second types. Moreover, we find a novel and adequate association among bienergies of a curve on an orientable hypersurface in $$\mathbb {E}^{4}$$ .
Published: 2021
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7. Automated treatment planning of prostate stereotactic body radiotherapy with focal boosting on a fast‐rotating O‐ring linac: Plan quality comparison with C‐arm linacs

Author: Tom Depuydt, Cédric Draulans, Karin Haustermans, Kenneth Poels, Wouter Crijns, Bertrand Dewit, and Robin De Roover
Subjects: Male, GLEASON SCORE, medicine.medical_specialty, O‐ring linac, Boosting (machine learning), Computer science, ONLINE, GUIDELINES, Radiosurgery, TOXICITY, Linear particle accelerator, FAILURES, Prostate, RADIATION-THERAPY, medicine, DISTRIBUTIONS, Humans, Radiation Oncology Physics, Dosimetry, Radiology, Nuclear Medicine and imaging, Medical physics, Adaptive radiotherapy, Radiation treatment planning, Instrumentation, automation, Science & Technology, SBRT, Radiation, COMPLICATION PROBABILITY, Radiotherapy Planning, Computer-Assisted, Radiology, Nuclear Medicine & Medical Imaging, Truebeam, Radiotherapy Dosage, plan quality, prostate cancer, CANCER, DELINEATION, medicine.anatomical_structure, focal boost, O-ring linac, Radiotherapy, Intensity-Modulated, Life Sciences & Biomedicine, Stereotactic body radiotherapy
Abstract: PURPOSE: The integration of auto-segmentation and automated treatment planning methods on a fast-rotating O-ring linac may improve the time efficiency of online adaptive radiotherapy workflows. This study investigates whether automated treatment planning of prostate SBRT with focal boosting on the O-ring linac could generate plans that are of similar quality as those obtained through manual planning on clinical C-arm linacs. METHODS: For 20 men with prostate cancer, reference treatment plans were generated on a TrueBeam STx C-arm linac with HD120 MLC and a TrueBeam C-arm linac with Millennium 120 MLC using 6 MV flattened dual arc VMAT. Manual planning on the Halcyon fast-rotating O-ring linac was performed using 6 MV FFF dual arc VMAT (HA2-DL10) and triple arc VMAT (HA3-DL10) to investigate the performance of the dual-layer MLC system. Automated planning was performed for triple arc VMAT on the Halcyon linac (ET3-DL10) using the automated planning algorithms of Ethos Treatment Planning. The prescribed dose was 35 Gy to the prostate and 30 Gy to the seminal vesicles in five fractions. The iso-toxic focal boost to the intraprostatic tumor nodule(s) was aimed to receive up to 50 Gy. Plan deliverability was verified using portal image dosimetry measurements. RESULTS: Compared to the C-arm linacs, ET3-DL10 shows increased seminal vesicles PTV coverage (D99% ) and reduced high-dose spillage to the bladder (V37Gy ) and urethra (D0.035cc ) but this came at the cost of increased high-dose spillage to the rectum (V38Gy ) and a higher intermediate dose spillage (D2cm). No statistically significant differences were found when benchmarking HA2-DL10 and HA3-DL10 with the C-arm linacs. All plans passed the patient-specific QA tolerance limit. CONCLUSIONS: Automated planning of prostate SBRT with focal boosting on the fast-rotating O-ring linac is feasible and achieves similar plan quality as those obtained on clinical C-arm linacs using manual planning. ispartof: Journal Of Applied Clinical Medical Physics vol:22 issue:9 ispartof: location:United States status: Published online
Published: 2021
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8. Preliminary Study on the Distribution, Source, and Ecological Risk of Typical Microplastics in Karst Groundwater in Guizhou Province, China

Author: Xianjin An, Wei Li, Jiacheng Lan, and Muhammad Adnan
Subjects: Health, Toxicology and Mutagenesis, Microplastics, Public Health, Environmental and Occupational Health, Humans, Water, karst, groundwater, microplastics, distributions, risk assessment, Plastics, Groundwater, Ecosystem, Environmental Monitoring
Abstract: Karst groundwater is one of the important drinking water sources in karst areas, and it has an important role in maintaining the regional ecosystem and human health. The study of microplastics (MPs) in karst groundwater has rarely been reported, and the occurrence and migration behavior of MPs under the unique environmental conditions of karst is unclear. This study selected cave groundwater and common MPs in karst areas to explore the occurrence characteristics of MPs in groundwater to clarify the factors affecting the distribution and migration of MPs. The results showed that the abundance of MPs in karst groundwater was between 2.33 and 9.50 items·L−1, with an average abundance of 4.50 items·L−1. The microplastic size, type, color, and chemical composition were primarily 1~5 mm, film and fiber, color and transparent, and PS and PE, respectively. The risk characterization ratio (RCR) index results indicated that 80% of the samples were at a low ecological risk level, whereas 60% of the sampling points after concentrated rainfall in June were a medium ecological risk. The study showed that rainfall events significantly changed the abundance and migration of MPs in karst groundwater. The Pearson analysis showed a positive correlation between microplastic distribution and suspended particles (SP), total organic carbon (TOC), and water velocity (WV) in water. The study indicated that strong soil erosion in karst areas may also be one of the main sources of MPs in karst groundwater, and that karst groundwater microplastic pollution is an environmental problem that should not be ignored.
Published: 2022

9. Climate change impact on cultivated and wild cacao in Peru and the search of climate change‐tolerant genotypes

Author: Viviana Ceccarelli, Wilbert Cruz Hilacondo, Sixto Imán Correa, Carlos Armando Rodriguez, Sphyros Lastra, Enrique Arévalo-Gardini, Evert Thomas, Diego Zavaleta, and Tobias Fremout
Subjects: AGRICULTURE, Biodiversity & Conservation, Climate change, Environmental Sciences & Ecology, Biology, ensemble modelling, FUTURE, Genotype, CONTRASTING GENOTYPES, DISTRIBUTIONS, Gene–environment interaction, cacao genotypes, habitat suitability modelling, TEMPERATURE, Ecology, Evolution, Behavior and Systematics, Science & Technology, Ecology, Impact assessment, COCOA THEOBROMA-CACAO, breeding for climate change adaptation, SPECIES DISTRIBUTION MODELS, PHYSIOLOGICAL-RESPONSES, L, AGROFORESTRY, Biodiversity Conservation, Life Sciences & Biomedicine
Abstract: ispartof: DIVERSITY AND DISTRIBUTIONS vol:27 issue:8 pages:1462-1476 status: published
Published: 2021
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10. Good Behaviour of Lie Bracket at a Superdensity Point of the Tangency Set of a Submanifold With Respect to a Rank 2 Distribution

Author: S. Delladio
Subjects: tangency set of a submanifold with respect to a distribution, Physics, distributions, Frobenius theorem, integral manifold, superdensity, Mathematics::Complex Variables, General Mathematics, 010102 general mathematics, Tangent, 010103 numerical & computational mathematics, Rank (differential topology), Submanifold, 01 natural sciences, Combinatorics, Distribution (mathematics), Lie algebra, 0101 mathematics
Abstract: Let H, K be a couple of vector fields of class C1 in an open set U ⊂ ℝN+m, $${\cal M}$$ be a N-dimensional C1 submanifold of U and define $${\cal T}: = \left\{{z \in {\cal M}:H\left(z \right),K\left(z \right) \in {T_z}{\cal M}} \right\}$$ . Then the obvious property If z0 ∈ $${\cal M}$$ is an interior point (relative to $${\cal M}$$ )of $${\cal T}$$ then $$\left[{H,K} \right]\left({{z_0}} \right) \in {T_{{z_0}}}{\cal M}$$ admits the following generalization: If z0 ∈ $${\cal M}$$ is a superdensity point (relative to $${\cal M}$$ )of $${\cal T}$$ then $$\left[{H,K} \right]\left({{z_0}} \right) \in {T_{{z_0}}}{\cal M}$$ . As a corollary we get very easily the following result of [7]: Let $${\cal D}$$ be a C1 distribution of rank N on an open set U ⊂ ℝN+m and let $${\cal M}$$ be a N-dimensional C1 submanifold of U. If z0 ∈ $${\cal M}$$ is a superdensity point (relative to $${\cal M}$$ )of the tangency set $$\left\{{z \in {\cal M}:{T_z}{\cal M} = {\cal D}\left(z \right)} \right\}$$ then $${\cal D}$$ is involutive at z0.
Published: 2021
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11. Measurements of W+W−+ ≥ 1 jet production cross-sections in pp collisions at √s = 13 TeV with the ATLAS detector

Author: Aaboud, M, Aad, G, Abbott, B, Abdinov, O, Abeloos, B, Abhayasinghe, DK, Abidi, SH, AbouZeid, OS, Abraham, NL, Abramowicz, H, Abreu, H, Abulaiti, Y, Acharya, BS, Adachi, S, Adamczyk, L, Adelman, J, Adersberger, M, Adiguzel, A, Adye, T, Affolder, AA, Afik, Y, Agheorghiesei, C, Aguilar-Saavedra, JA, Ahmadov, F, Aielli, G, Akatsuka, S, Akesson, TPA, Akilli, E, Akimov, AV, Alberghi, GL, Albert, J, Albicocco, P, Verzini, MJA, Alderweireldt, S, Aleksa, M, Aleksandrov, IN, Alexa, C, Alexopoulos, T, Alhroob, M, Ali, B, Alimonti, G, Alison, J, Alkire, SP, Allaire, C, Allbrooke, BMM, Allen, BW, Allport, PP, Aloisio, A, Alonso, A, Alonso, F, Alpigiani, C, Alshehri, AA, Alstaty, MI, Gonzalez, BA, Alvarez Piqueras, D, Alviggi, MG, Amadio, BT, Coutinho, YA, Ambroz, L, Amelung, C, Amidei, D, Amor Dos Santos, SP, Amoroso, S, Amrouche, CS, Anastopoulos, C, Ancu, LS, Andari, N, Andeen, T, Anders, CF, Anders, JK, Anderson, KJ, Andreazza, A, Andrei, V, Anelli, CR, Angelidakis, S, Angelozzi, I, Angerami, A, Anisenkov, AV, Annovi, A, Antel, C, Anthony, MT, Antonelli, M, Antrim, DJA, Anulli, F, Aoki, M, Aparisi Pozo, JA, Aperio Bella, L, Arabidze, G, Araque, JP, Araujo Ferraz, V, Araujo Pereira, R, Arce, ATH, Ardell, RE, Arduh, FA, Arguin, J-F, Argyropoulos, S, Armbruster, AJ, Armitage, LJ, Armstrong, A, Arnaez, O, Arnold, H, Arratia, M, Arslan, O, Artamonov, A, Artoni, G, Artz, S, Asai, S, Asbah, N, Ashkenazi, A, Asimakopoulou, EM, Asquith, L, Assamagan, K, Astalos, R, Atkin, RJ, Atkinson, M, Atlay, NB, Augsten, K, Avolio, G, Avramidou, R, Ayoub, MK, Azuelos, G, Baas, AE, Baca, MJ, Bachacou, H, Bachas, K, Backes, M, Bagnaia, P, Bahmani, M, Bahrasemani, H, Bailey, AJ, Baines, JT, Bajic, M, Bakalis, C, Baker, OK, Bakker, PJ, Gupta, DB, Baldin, EM, Balek, P, Balli, F, Balunas, WK, Balz, J, Banas, E, Bandyopadhyay, A, Banerjee, S, Bannoura, AAE, Barak, L, Barbe, WM, Barberio, EL, Barberis, D, Barbero, M, Barillari, T, Barisits, M-S, Barkeloo, J, Barklow, T, Barlow, N, Barnea, R, Barnes, SL, Barnett, BM, Barnett, RM, Barnovska-Blenessy, Z, Baroncelli, A, Barone, G, Barr, AJ, Barranco Navarro, L, Barreiro, F, Barreiro Guimaraes da Costa, J, Bartoldus, R, Barton, AE, Bartos, P, Basalaev, A, Bassalat, A, Bates, RL, Batista, SJ, Batlamous, S, Batley, JR, Battaglia, M, Bauce, M, Bauer, F, Bauer, KT, Bawa, HS, Beacham, JB, Beau, T, Beauchemin, PH, Bechtle, P, Beck, HC, Beck, HP, Becker, K, Becker, M, Becot, C, Beddall, A, Beddall, AJ, Bednyakov, VA, Bedognetti, M, Bee, CP, Beermann, TA, Begalli, M, Begel, M, Behera, A, Behr, JK, Bell, AS, Bella, G, Bellagamba, L, Bellerive, A, Bellomo, M, Bellos, P, Belotskiy, K, Belyaev, NL, Benary, O, Benchekroun, D, Bender, M, Benekos, N, Benhammou, Y, Benhar Noccioli, E, Benitez, J, Benjamin, DP, Benoit, M, Bensinger, JR, Bentvelsen, S, Beresford, L, Beretta, M, Berge, D, Bergeaas Kuutmann, E, Berger, N, Bergsten, LJ, Beringer, J, Berlendis, S, Bernard, NR, Bernardi, G, Bernius, C, Bernlochner, FU, Berry, T, Berta, P, Bertella, C, Bertoli, G, Bertram, IA, Besjes, GJ, Bessidskaia Bylund, O, Bessner, M, Besson, N, Bethani, A, Bethke, S, Betti, A, Bevan, AJ, Beyer, J, Bianchi, RM, Biebel, O, Biedermann, D, Bielski, R, Bierwagen, K, Biesuz, NV, Biglietti, M, Billoud, TRV, Bindi, M, Bingul, A, Bini, C, Biondi, S, Birman, M, Bisanz, T, Biswal, JP, Bittrich, C, Bjergaard, DM, Black, JE, Black, KM, Blazek, T, Bloch, I, Blocker, C, Blue, A, Blumenschein, U, Blunier, D, Bobbink, GJ, Bobrovnikov, VS, Bocchetta, SS, Bocci, A, Boerner, D, Bogavac, D, Bogdanchikov, AG, Bohm, C, Boisvert, V, Bokan, P, Bold, T, Boldyrev, AS, Bolz, AE, Bomben, M, Bona, M, Bonilla, JS, Boonekamp, M, Borisov, A, Borissov, G, Bortfeldt, J, Bortoletto, D, Bortolotto, V, Boscherini, D, Bosman, M, Bossio Sola, JD, Bouaouda, K, Boudreau, J, Bouhova-Thacker, EV, Boumediene, D, Bourdarios, C, Boutle, SK, Boveia, A, Boyd, J, Boye, D, Boyko, IR, Bozson, AJ, Bracinik, J, Brahimi, N, Brandt, A, Brandt, G, Brandt, O, Braren, F, Bratzler, U, Brau, B, Brau, JE, Madden, WDB, Brendlinger, K, Brennan, AJ, Brenner, L, Brenner, R, Bressler, S, Brickwedde, B, Briglin, DL, Britton, D, Britzger, D, Brock, I, Brock, R, Brooijmans, G, Brooks, T, Brooks, WK, Brost, E, Broughton, JH, Bruckman de Renstrom, PA, Bruncko, D, Bruni, A, Bruni, G, Bruni, LS, Bruno, S, Brunt, BH, Bruschi, M, Bruscino, N, Bryant, P, Bryngemark, L, Buanes, T, Buat, Q, Buchholz, P, Buckley, AG, Budagov, IA, Bugge, MK, Buehrer, F, Bulekov, O, Bullock, D, Burch, TJ, Burdin, S, Burgard, CD, Burger, AM, Burghgrave, B, Burka, K, Burke, S, Burmeister, I, Burr, JTP, Buescher, D, Buescher, V, Buschmann, E, Bussey, P, Butler, JM, Buttar, CM, Butterworth, JM, Butti, P, Buttinger, W, Buzatu, A, Buzykaev, AR, Cabras, G, Cabrera Urban, S, Caforio, D, Cai, H, Cairo, VMM, Cakir, O, Calace, N, Calafiura, P, Calandri, A, Calderini, G, Calfayan, P, Callea, G, Caloba, LP, Calvente Lopez, S, Calvet, D, Calvet, S, Calvet, TP, Calvetti, M, Toro, RC, Camarda, S, Camarri, P, Cameron, D, Armadans, RC, Camincher, C, Campana, S, Campanelli, M, Camplani, A, Campoverde, A, Canale, V, Bret, MC, Cantero, J, Cao, T, Cao, Y, Capeans Garrido, MDM, Caprini, I, Caprini, M, Capua, M, Carbone, RM, Cardarelli, R, Cardillo, FC, Carli, I, Carli, T, Carlino, G, Carlson, BT, Carminati, L, Carney, RMD, Caron, S, Carquin, E, Carra, S, Carrillo-Montoya, GD, Casadei, D, Casado, MP, Casha, AF, Casper, DW, Castelijn, R, Castillo, FL, Castillo Gimenez, V, Castro, NF, Catinaccio, A, Catmore, JR, Cattai, A, Caudron, J, Cavaliere, V, Cavallaro, E, Cavalli, D, Cavalli-Sforza, M, Cavasinni, V, Celebi, E, Ceradini, F, Cerda Alberich, L, Cerqueira, AS, Cerri, A, Cerrito, L, Cerutti, F, Cervelli, A, Cetin, SA, Chafaq, A, Chakraborty, D, Chan, SK, Chan, WS, Chan, YL, Chapman, JD, Chargeishvili, B, Charlton, DG, Chau, CC, Barajas, CAC, Che, S, Chegwidden, A, Chekanov, S, Chekulaev, SV, Chelkov, GA, Chelstowska, MA, Chen, C, Chen, CH, Chen, H, Chen, J, Chen, S, Chen, SJ, Chen, X, Chen, Y, Chen, Y-H, Cheng, HC, Cheng, HJ, Cheplakov, A, Cheremushkina, E, El Moursli, RC, Cheu, E, Cheung, K, Chevalier, L, Chiarella, V, Chiarelli, G, Chiodini, G, Chisholm, AS, Chitan, A, Chiu, I, Chiu, YH, Chizhov, MV, Choi, K, Chomont, AR, Chouridou, S, Chow, YS, Christodoulou, V, Chu, MC, Chudoba, J, Chuinard, AJ, Chwastowski, JJ, Chytka, L, Cinca, D, Cindro, V, Cioara, IA, Ciocio, A, Cirotto, F, Citron, ZH, Citterio, M, Clark, A, Clark, MR, Clark, PJ, Clement, C, Coadou, Y, Cobal, M, Coccaro, A, Cochran, J, Cohen, H, Coimbra, AEC, Colasurdo, L, Cole, B, Colijn, AP, Collot, J, Muino, PC, Coniavitis, E, Connell, SH, Connelly, IA, Constantinescu, S, Conventi, F, Cooper-Sarkar, AM, Cormier, F, Cormier, KJR, Corpe, LD, Corradi, M, Corrigan, EE, Corriveau, F, Cortes-Gonzalez, A, Costa, MJ, Costanzo, D, Cottin, G, Cowan, G, Cox, BE, Crane, J, Cranmer, K, Crawley, SJ, Creager, RA, Cree, G, Crepe-Renaudin, S, Crescioli, F, Cristinziani, M, Croft, V, Crosetti, G, Cueto, A, Donszelmann, TC, Cukierman, AR, Cuth, J, Czekierda, S, 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ATLAS Collaboration, And, Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre de Calcul de l'IN2P3 (CC-IN2P3), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), ATLAS, Współautorami artykułu są członkowie ATLAS Collaboration w liczbie 2885, Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), ATLAS (IHEF, IoP, FNWI), XENON (IHEF, IoP, FNWI), Other Research IHEF (IoP, FNWI), UAM. Departamento de Física Teórica, Aad, G. [0000-0002-6665-4934], Abbott, B. [0000-0002-5888-2734], Abbott, D. C. [0000-0002-7248-3203], Abed Abud, A. [0000-0002-2788-3822], Abeling, K. [0000-0002-1002-1652], Abhayasinghe, D. K. [0000-0002-2987-4006], Abidi, S. H. [0000-0002-8496-9294], AbouZeid, O. S. [0000-0002-8279-9324], Abramowicz, H. [0000-0001-5329-6640], Abreu, H. [0000-0002-1599-2896], Abulaiti, Y. [0000-0003-0403-3697], Abusleme Hoffman, A. C. [0000-0003-0762-7204], Acharya, B. S. [0000-0002-8588-9157], Achkar, B. [0000-0002-0288-2567], Adam, L. [0000-0001-6005-2812], Adam Bourdarios, C. [0000-0002-2634-4958], Adamczyk, L. [0000-0002-5859-2075], Adamek, L. [0000-0003-1562-3502], Adelman, J. [0000-0002-1041-3496], Adiguzel, A. [0000-0001-6644-0517], Adorni, S. [0000-0003-3620-1149], Adye, T. [0000-0003-0627-5059], Affolder, A. A. [0000-0002-9058-7217], Afik, Y. [0000-0001-8102-356X], Agapopoulou, C. [0000-0002-2368-0147], Agaras, M. N. [0000-0002-4355-5589], Aggarwal, A. [0000-0002-1922-2039], Agheorghiesei, C. [0000-0003-3695-1847], Aguilar-Saavedra, J. A. [0000-0002-5475-8920], Ahmad, A. [0000-0001-8638-0582], Ahmadov, F. [0000-0003-3644-540X], Ahmed, W. S. [0000-0003-0128-3279], Ai, X. [0000-0003-3856-2415], Aielli, G. [0000-0002-0573-8114], Akatsuka, S. [0000-0002-1681-6405], Akbiyik, M. [0000-0002-7342-3130], Åkesson, T. P. A. [0000-0003-4141-5408], Akilli, E. [0000-0003-1309-5937], Akimov, A. V. [0000-0002-2846-2958], Al Khoury, K. [0000-0002-0547-8199], Alberghi, G. L. [0000-0003-2388-987X], Albert, J. [0000-0003-0253-2505], Alconada Verzini, M. J. [0000-0003-2212-7830], Alderweireldt, S. [0000-0002-8224-7036], Aleksa, M. [0000-0002-1936-9217], Aleksandrov, I. N. [0000-0001-7381-6762], Alexa, C. [0000-0003-0922-7669], Alexopoulos, T. [0000-0002-8977-279X], Alfonsi, A. [0000-0001-7406-4531], Alfonsi, F. [0000-0002-0966-0211], Alhroob, M. [0000-0001-7569-7111], Ali, B. [0000-0001-8653-5556], Ali, S. [0000-0001-5216-3133], Aliev, M. [0000-0002-9012-3746], Alimonti, G. [0000-0002-7128-9046], Allaire, C. [0000-0003-4745-538X], Allbrooke, B. M. M. [0000-0002-5738-2471], Allport, P. P. [0000-0001-7303-2570], Aloisio, A. [0000-0002-3883-6693], Alonso, F. [0000-0001-9431-8156], Alpigiani, C. [0000-0002-7641-5814], Alvarez Estevez, M. [0000-0002-8181-6532], Alviggi, M. G. [0000-0003-0026-982X], Amaral Coutinho, Y. [0000-0002-1798-7230], Ambler, A. [0000-0003-2184-3480], Ambroz, L. [0000-0002-0987-6637], Amidei, D. [0000-0002-6814-0355], Amor Dos Santos, S. P. [0000-0001-7566-6067], Amoroso, S. [0000-0001-5450-0447], Anastopoulos, C. [0000-0003-1587-5830], Andari, N. [0000-0002-4935-4753], Andeen, T. [0000-0002-4413-871X], Anders, J. K. [0000-0002-1846-0262], Andrean, S. Y. [0000-0002-9766-2670], Andreazza, A. [0000-0001-5161-5759], Angelidakis, S. [0000-0002-8274-6118], Angerami, A. [0000-0001-7834-8750], Anisenkov, A. V. [0000-0002-7201-5936], Annovi, A. [0000-0002-4649-4398], Antel, C. 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G., Zou, R., Zou, W., Zwalinski, L., Aloisio, Alberto, Alviggi, Mariagrazia, Canale, Vincenzo, Della Pietra, Massimo, Merola, Leonardo, Massarotti, Paolo, Conventi, Francesco, Rossi, Elvira, Carlino, Giampaolo, de Asmundis, Riccardo, Di Donato, Camilla, Doria, Alessandra, Iengo, Paolo, Izzo, Vincenzo, Perrella, Sabrina, Sekhniaidze, Givi, Cirotto, Francesco, Lavorgna, Marco, Giannini, Antonio, Atlas, Collaboration, De Castro , S., Fabbri , L., Gabrielli , A., Rinaldi , L., Semprini Cesari , N., Sioli , M., Villa , M., Zoccoli , A., Bellagamba , L., Boscherini , D., Bruni , A., Bruni , G., Giacobbe , B., Polini , A., Sbarra , C., Sidoti , A., Franchini , M., Romano , M., Valentinetti , S., Alberghi , G. L., Lasagni Manghi , F, Massa , L., Vittori , C., Alfonsi , F, Cabras , G., Cervelli , A., Negrini , M., Todome , K., Carratta , G., Cavalli , N., Clissa , L., and ATLAS collaboration
Subjects: Plus Plus, 13000 GeV-cms, ((n)jet dilepton) [final state], QC770-798, transverse momentum [jet], 01 natural sciences, Subatomär fysik, Hadron-Hadron scattering (experiments), scattering [p p], Nuclear Experiment, Settore FIS/01, Electroweak interaction, hadronic [jet], mass dependence, upper limit [coupling constant], CERN LHC Coll, kinematics, Distributions, colliding beams [p p], p p: scattering, Astrophysics::High Energy Astrophysical Phenomena, coupling constant: upper limit, jet: multiplicity, Nuclear physics, phase space, Atlas (anatomy), quantum chromodynamics, muon: pair, coupling: (3gauge boson), TeV, ddc:530, Rapidity, High Energy Physics, 010306 general physics, Particle Physics, Particle Physics, LHC, ATLAS, Parton Distributions, final state: ((n)jet dilepton), 010308 nuclear & particles physics, jet: hadronic, Hadron Colliders, Automatic Keywords, dependence [multiplicity], Experimental High Energy Physics, p p: colliding beams, electron, Kjerne- og elementærpartikkelfysikk: 431 [VDP], Atlas detector, (3gauge boson) [coupling], Hadron, jet: transverse momentum, GeV, transverse momentum dependence, High Energy Physics - Experiment, gauge [coupling], W: pair production, High Energy Physics - Experiment (hep-ex), Subatomic Physics, [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex], Pair Production, Quantum chromodynamics, Physics, Jet (fluid), mass: transverse, multiplicity: dependence, lepton: transverse momentum, ATLAS, Zz Production, Nuclear and elementary particle physics: 431 [VDP], medicine.anatomical_structure, jet: production, pair production [W], Subtraction, differential cross section, LHC, multiplicity [jet], anomaly [coupling], Particle Physics - Experiment, perturbation theory [quantum chromodynamics], Nuclear and High Energy Physics, topology, Regular Article - Experimental Physics, 530 Physics, coupling: gauge, jet: associated production, interference, FOS: Physical sciences, differential cross section: measured, measured [differential cross section], Nuclear and particle physics. Atomic energy. Radioactivity, electron muon, 0103 physical sciences, medicine, associated production [jet], quantum chromodynamics: perturbation theory, coupling: anomaly, electroweak interaction, background, High Energy Physics::Phenomenology, Física, W bosons, production [jet], pair [muon], rapidity, Pair production, transverse [mass], High Energy Physics::Experiment, Hadron-hadron collisions, transverse momentum [lepton], experimental results
Abstract: We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRT, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MES of Russia and NRC KI, Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZS, Slovenia; DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada, CRC and IVADO, Canada; Beijing Municipal Science & Technology Commission, China; COST, ERC, ERDF, Horizon 2020 and Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom., Fiducial and differential cross-section measurements of W+W− production in association with at least one hadronic jet are presented. These measurements are sensitive to the properties of electroweak-boson self-interactions and provide a test of perturbative quantum chromodynamics and the electroweak theory. The analysis is performed using proton-proton collision data collected at p s = 13TeV with the ATLAS experiment, corresponding to an integrated luminosity of 139 fb−1. Events are selected with exactly one oppositely charged electron-muon pair and at least one hadronic jet with a transverse momentum of pT > 30 GeV and a pseudorapidity of | | < 4.5. After subtracting the background contributions and correcting for detector effects, the jet-inclusive W+W−+ 1 jet fiducial cross-section and W+W−+ jets differential cross-sections with respect to several kinematic variables are measured. These measurements include leptonic quantities, such as the lepton transverse momenta and the transverse mass of the W+W− system, as well as jet-related observables such as the leading jet transverse momentum and the jet multiplicity. Limits on anomalous triple-gauge-boson couplings are obtained in a phase space where interference between the Standard Model amplitude and the anomalous amplitude is enhanced., ANPCyT, YerPhI, Armenia, Australian Research Council, BMWFW, Austria, Austrian Science Fund (FWF), Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Natural Sciences and Engineering Research Council of Canada (NSERC), NRC, Canada, Canada Foundation for Innovation, CERN, ANID, Chile, Chinese Academy of Sciences, Ministry of Science and Technology, China, National Natural Science Foundation of China (NSFC), Departamento Administrativo de Ciencia, Tecnologia e Innovacion Colciencias, Ministry of Education, Youth & Sports - Czech Republic Czech Republic Government Czech Republic Government, DNRF, Denmark Danish Natural Science Research Council, Centre National de la Recherche Scientifique (CNRS) CEA-DRF/IRFU, France, SRNSFG, Georgia, Federal Ministry of Education & Research (BMBF), HGF, Germany Max Planck Society, Greek Ministry of Development-GSRT, RGC, China Hong Kong SAR, China, Israel Science Foundation Benoziyo Center, Israel, Istituto Nazionale di Fisica Nucleare (INFN), Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of Science, CNRST, Morocco, Netherlands Organization for Scientific Research (NWO) Netherlands Government, RCN, Norway, Ministry of Science and Higher Education, Poland NCN, Poland, Portuguese Foundation for Science and Technology European Commission, MNE/IFA, Romania, JINR, Russian Federation NRC KI, Russian Federation, Ministry of Education, Science & Technological Development, Serbia, MSSR, Slovakia, Slovenian Research Agency - Slovenia MIZS, Slovenia, DST/NRF, South Africa, Spanish Government, SRC, Sweden Wallenberg Foundation, Sweden, SERI, Switzerland Swiss National Science Foundation (SNSF), Canton of Bern, Switzerland Canton of Geneva, Switzerland, Ministry of Science and Technology, Taiwan, Ministry of Energy & Natural Resources - Turkey, UK Research & Innovation (UKRI), Science & Technology Facilities Council (STFC), United States Department of Energy (DOE) National Science Foundation (NSF), BCKDF, Canada CANARIE, Canada Compute Canada, Canada CRC, Canada IVADO, Canada, Beijing Municipal Science AMP; Technology Commission, China, COST, European Union European Research Council (ERC) ERDF, European Union Horizon 2020, European Union Marie Sklodowska-Curie Actions, European Union, French National Research Agency (ANR), German Research Foundation (DFG), Alexander von Humboldt Foundation, Herakleitos programme - EU-ESF, Greece Thales Group Aristeia programme - EU-ESF, Greece Greek NSRF, Greece, BSF-NSF, Israel, German-Israeli Foundation for Scientific Research and Development, La Caixa Banking Foundation, Spain CERCA Programme Generalitat de Catalunya, Spain PROMETEO Programme Generalitat Valenciana, Spain GenT Programme Generalitat Valenciana, Spain, Goran Gustafssons Stiftelse, Sweden, Royal Society of London, Leverhulme Trust, Azerbaijan National Academy of Sciences (ANAS), SSTC, Belarus, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ)
Published: 2021
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12. A Gravitational-wave Measurement of the Hubble Constant Following the Second Observing Run of Advanced LIGO and Virgo

Author: G. Pagliaroli, Kevin Barkett, Denis Martynov, Marco Bazzan, C. Ingram, L. Pinard, Nicolas Sanchis-Gual, I. Belahcene, A. K. Y. Li, Archana Pai, F. Paoletti, P. Ruggi, G. Vajente, S. M. Gaebel, C. Kr mer, K. W. Chung, I. Dorrington, I. Di Palma, A. Mullavey, T. J. N. Nelson, Filip Morawski, Xiaohui Fan, Richard O'Shaughnessy, B. Barr, B. D. Lackey, G. Eddolls, A. Cumming, P. Grassia, Kipp Cannon, F. Di Renzo, M. Steinke, Francesco Pannarale, Soichiro Morisaki, D. Ugolini, P. Clearwater, M. Haney, T. A. Callister, Zhihui Du, G. Ciani, Alessandro Bertolini, Olivier Minazzoli, M. Razzano, Mairi Sakellariadou, G. Pillant, S. H. R. Yuen, O. de Varona, A. L. Stuver, R. De Rosa, I. Nardecchia, M. Kasprzack, J. Baird, Frances Hellman, M. B. Shaner, Manel Molina-Ruiz, S. B. Coughlin, Jessica Steinlechner, A. Neunzert, M. Heurs, Reed Essick, S. Kandhasamy, B. Sorazu, A. Kutynia, Andrea Chincarini, T. Z. Summerscales, Tenglin Li, Robert J. McCarthy, Linqing Wen, D. Meacher, Leo Tsukada, E. Z. Hamilton, A. Parida, S. S. Eikenberry, E. Genin, D. Estevez, W. Katzman, B. Grace, S. M. Aronson, M. Llorens-Monteagudo, M. Nery, Ryan Lynch, Ettore Majorana, D. M. Wilken, A. Rocchi, B. Goncharov, R. Birney, P. Ehrens, Paul M. Ricker, E. J. Fauchon-Jones, M. Lormand, William Parker, D. J. Stops, J. S. H. Lee, Felix Wellmann, Shreya Anand, D. Huet, S. H. Huttner, Z. Tornasi, Andrew Melatos, M. Lorenzini, M. Bitossi, J.-G. Ducoin, J. Neilson, G. Bergmann, K. Wette, John J. Oh, Timothy Evans, M. G. Benjamin, E. Payne, Rory Smith, C. Adams, R. M. Blair, D. Sigg, S. W. Ballmer, Z. Yang, D. M. Shoemaker, Michelle E. Walker, J. Eichholz, G. Moreno, H. Inchauspe, J. Liu, A. Pasqualetti, M. Tse, D. M. Macleod, B. L. Swinkels, J. Warner, R. Passaquieti, C. Rajan, O. Durante, N. Krupinski, F. Martelli, Karan Jani, Jade Powell, V. Mangano, H. K. Gulati, David H. Reitze, Rahul Kashyap, C. McIsaac, Nergis Mavalvala, A. K. Lenon, S. Mastrogiovanni, P. A. Altin, Piotr Jaranowski, Florent Robinet, J. Zhang, F. Baldaccini, L. F. Ortega, Jerome Degallaix, R. C. Walet, V. P. Mitrofanov, Rosa Poggiani, V. Frey, T. Sadecki, V. Tiwari, Yann Bouffanais, A. C. Green, C. Casentini, R. Shink, E. Goetz, F. Magaña-Sandoval, J. McIver, Sebastian Khan, B. C. Barish, J. H. Briggs, Mark Hannam, L. Rei, Gijs Nelemans, Tanja Hinderer, Alejandro Torres-Forné, A. K. Zadrożny, P.H. Nguyen, V. Boschi, E. J. Son, M. van Beuzekom, S. Grunewald, R. Prasanna, A. Ain, Shubhanshu Tiwari, G. A. Prodi, R. DeSalvo, V. Kondrashov, F. Frasconi, A. K. Mehta, E. D. Hall, S. Farinon, E. Mejuto Villa, D. Barker, A. Samajdar, Jolien D. E. Creighton, A. Pele, D. Singh, Arunava Mukherjee, Fausto Acernese, J. C. Barayoga, B. F. Neil, R. Flaminio, Richard J. Abbott, D. W. Yeeles, Hartmut Grote, D. C. Vander-Hyde, P. Puppo, W. Del Pozzo, Y. Minenkov, P. Bacon, P. F. Cohadon, H. Heitmann, A. Strunk, N. Kijbunchoo, Piero Rettegno, K. A. Santiago, P. J. Sutton, M. Cieślar, Maria Ilaria Del Principe, P. Raffai, J. C. Bayley, H. Wittel, M. Deenadayalan, G. H. Ogin, T. J. Shaffer, Marcus E. Lower, L. Glover, G. Losurdo, S. Biscoveanu, O. V. Palashov, Sean T. McWilliams, F. Piergiovanni, Chang-Hwan Lee, D. E. Cohen, M. Agathos, J. H. Romie, S. Sitmukhambetov, G. Kuehn, K. Merfeld, M. Ar ne, M. Phelps, Archisman Ghosh, R. G. Ormiston, Andrew Matas, A. Chiummo, K. Holt, M. Mantovani, E. A. Huerta, A. Ramos-Buades, S. L. Danilishin, Tristan Briant, R. K. Lanza, P. Dupej, Sheelu Abraham, Eric B. Flynn, J. Betzwieser, Antoine Heidmann, J. Hanks, A. Sur, H. Overmier, R. Goetz, Tarun Souradeep, J. P. Zendri, L. Sun, C. De Rossi, D. Buskulic, Odylio D. Aguiar, James Healy, P. Brockill, Luca Gammaitoni, R. Fittipaldi, C. Horst, Alberto Vecchio, F. Cipriano, Michael Thomas, R. Tenorio, N. A. Holland, D. Sellers, P. Popolizio, Koji Arai, F. J. Raab, Devon S. Johnson, N. Mukund, L. R. Cominsky, Neil J. Cornish, Colm Talbot, Andreas Freise, M. Davier, Sebastiano Bernuzzi, O. Halim, S. Koley, M. Brinkmann, C. Affeldt, S. Appert, Y. Setyawati, E. J. Sanchez, Nicholas Demos, J. D. Lough, D. Pascucci, H. S. Chen, L. E. H. Datrier, M. Bawaj, R. L. Savage, A. S. Bell, M. Laxen, Anchal Gupta, J. Meidam, M. Gosselin, Riccardo Sturani, M. K. M. Bader, O. Chaibi, Wolfango Plastino, R. Taylor, C. L. Romel, Giovanni Carapella, P. Shawhan, I. Ferrante, Soma Mukherjee, Charalampos Markakis, G. Mo, J. K. Blackburn, C. J. Richardson, F. L. Linde, E. Chassande-Mottin, Sylvain Marsat, Sheila Rowan, B. Gateley, Howard Pan, Aaron Buikema, R. Kirchhoff, B. L. Pearlstone, V. Fafone, Paul D. Lasky, R. K. Hasskew, Jordan Camp, D. Tao, M. Muratore, M. C. Heintze, D. Sentenac, F. Carbognani, Patrick Brady, P. Fulda, J. M. Fishner, Will M. Farr, M. Montani, Nancy Aggarwal, R. Gustafson, A. Grimaldi, J. W. Westhouse, Matthew Pitkin, F. Lin, Tania Regimbau, Serena Vinciguerra, F. Garufi, Chandra Kant Mishra, Joseph D. Romano, R. Bhandare, R. Pedurand, Benno Willke, C. C. Wipf, V. Pierro, M. J. Cowart, I. Dave, Lee McCuller, O. J. Piccinni, Takuya Tsutsui, T. D. Abbott, Zoheyr Doctor, M. Fletcher, B. Hughey, K. W. Tsang, P. J. Veitch, M. Rakhmanov, Surendra Nadh Somala, Gregorio Carullo, R. Xu, C. Buy, M. Oliver, Kazuhiro Agatsuma, T. J. Hansen, N. Bode, Christopher P. L. Berry, T. Harder, Rico K. L. Lo, P. Charlton, Kejia Lee, Patrick Das Gupta, S. E. Barclay, J. L. Willis, M. Eisenmann, Ofek Birnholtz, John A. Clark, Ben Farr, W. S. Kim, Christophe Collette, L. Kuo, H. Yamamoto, J. C. Driggers, A. Schönbeck, B. Rajbhandari, Daniel Wysocki, J. Prasad, A. J. Pedersen, S. B. Anderson, Tim Dietrich, M. Pürrer, S. Kwang, Frank Ohme, Vicky Kalogera, K. Rose, M. Tonelli, E. Katsavounidis, Xiuling Li, R. Gray, Patrick Godwin, M. C. Araya, Srishti Tiwari, S. Frasca, Jonathan Richardson, Tyson Littenberg, Kai Staats, L. Conti, M. Chaturvedi, Yu Huang, Geert Raaijmakers, F. Y. Khalili, R. P. Fisher, A. Allocca, D. I. Jones, Guoying Zhao, Kendall Ackley, R. K. Nayak, S. Raja, H. Y. Chia, Sascha Husa, S. E. Strigin, S. Mitra, M. Granata, H. J. Bulten, Minchuan Zhou, Shao-Jiang Wang, T. D. Creighton, S. E. Gossan, Dániel Barta, G. Venugopalan, Karl Gill, V. Srivastava, M. Fays, S. Barnum, S. C. Tait, K. Shukla, Zifan Zhou, I. A. Bilenko, L. Haegel, D.B. DeBra, David J. Ottaway, C. J. Perez, Matthew Evans, B. D. O'Brien, Marek Szczepanczyk, C. Bradaschia, M. Standke, Deep Jariwala, C. Cahillane, Otto A. Hannuksela, C. Gray, H. Estelles, W. A. Campbell, H. Radkins, A. Bozzi, N. N. Janthalur, L. Wallace, A. Królak, R. Frey, E. A. Muñiz, B. Sassolas, S. Brunett, Monica Colpi, Albino Perego, A. Bisht, M. Boer, J. B. Kanner, Andrew Lundgren, S. Xiao, J. V. Vanheijningen, D. Fiorucci, Zachariah B. Etienne, D. Moraru, E. Floden, Jennifer Watchi, A. K. Prajapati, Gianpietro Cagnoli, A. R. Wade, A. Di Lieto, S. J. Chamberlin, M. Vasúth, C. M. Mow-Lowry, Sergey P. Vyatchanin, Jonathan Cripe, V. Bossilkov, A. Paoli, Ik Siong Heng, A. Rüdiger, R. Inta, Steven Bloemen, Jonathan R. Gair, S. Klimenko, Eric Howell, E. Cesarini, S. Márka, N. Sennett, Stephen Fairhurst, Carl Blair, V. Fiumara, M. F. Carney, C. Lazzaro, Patricia Schmidt, Ajay Kumar, Y. K. Lecoeuche, M. J. Yap, C. Whittle, Bala R. Iyer, Stefan Grimm, D. B. Tanner, Kevin M. Ryan, S. McCormick, C. Difronzo, G. M. Harry, C. Palomba, S. Ascenzi, A. L. Miller, K. Venkateswara, L. Aiello, R. Green, Giuseppe Intini, Kenneth A. Strain, Jimin George, M. Sieniawska, Gregory Ashton, K. Chakravarti, G. Valdes, Ken K. Y. Ng, E. E. Cowan, B. D'Angelo, Hongyu Shen, D. C. Coyne, T. Dal Canton, J. Casanueva Diaz, P. Couvares, H. Fong, G. Greco, J. Zweizig, M. S. Shahriar, M. Korobko, J. Brooks, K. Siellez, Shiuh Chao, C. Périgois, P. Astone, Carlos O. Lousto, T. Hardwick, D. Steinmeyer, David Coward, A. Miani, R. Cotesta, Rakesh Kumar, F. Travasso, Yuri Levin, T. P. Downes, Gor Oganesyan, A. F. Brooks, P. J. Quinonez, Fabio Marchesoni, P. Hello, J. Gniesmer, Kyungmin Kim, Debarati Chatterjee, A. Trovato, B. O'Reilly, P. Gruning, Sheon Chua, R. Bonnand, C. North, Mariana Fazio, F. Vetrano, Samuele Cortese, Thomas Dent, P. Corban, S. J. Cooper, S. Leavey, Hai-Ping Cheng, A. Iess, M. Pedraza, M. Chan, Francesco Chiadini, Michał Bejger, Charlie Hoy, P. Schale, J. Jiang, J. Hennig, J. Junker, C. Van Den Broeck, E. Sowell, V. Gayathri, V. Hui, S. Walsh, Miriam Cabero, Alexander C. Jenkins, A. Markowitz, Robert Stone, M. Was, M. M. Hanke, G. Cho, James Whelan, P. Ajith, P. Booker, A. Perreca, G. Gemme, M. Drago, M. Di Giovanni, A. Malik, S. Gaudio, G. Dálya, T. Prestegard, J. Scott, L. K. Nuttall, A. W. Jones, Alessandro Nagar, R. De Pietri, Rocco Romano, M. Kinley-Hanlon, Lindsay DeMarchi, K. A. Thorne, E. L. Merilh, S. E. Dwyer, David Keitel, L. Matone, Mandar Patil, Guenakh Mitselmakher, B. A. Boom, A. M. Sergeev, Karsten Danzmann, A. R. Williamson, H. Vocca, Mario Spera, Peter Aufmuth, Andrea H. Tapia, Hua Wang, F. Cavalier, A. 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Lartaux-Vollard, A, Lasky, P, Laxen, M, Lazzarini, A, Lazzaro, C, Leaci, P, Leavey, S, Lecoeuche, Y, Lee, C, Lee, H, Lee, J, Lee, K, Lehmann, J, Lenon, A, Leroy, N, Letendre, N, Levin, Y, Li, A, Li, J, Li, K, Li, T, Li, X, Lin, F, Linde, F, Linker, S, Littenberg, T, Liu, J, Liu, X, Llorens-Monteagudo, M, Lo, R, London, L, Longo, A, Lorenzini, M, Loriette, V, Lormand, M, Losurdo, G, Lough, J, Lousto, C, Lovelace, G, Lower, M, Luck, H, Lumaca, D, Lundgren, A, Lynch, R, Ma, Y, Macas, R, Macfoy, S, Macinnis, M, Macleod, D, Macquet, A, Hernandez, I, Magana-Sandoval, F, Magee, R, Majorana, E, Maksimovic, I, Malik, A, Man, N, Mandic, V, Mangano, V, Mansell, G, Manske, M, Mantovani, M, Mapelli, M, Marchesoni, F, Marion, F, Marka, S, Marka, Z, Markakis, C, Markosyan, A, Markowitz, A, Maros, E, Marquina, A, Marsat, S, Martelli, F, Martin, I, Martin, R, Martinez, V, Martynov, D, Masalehdan, H, Mason, K, Massera, E, Masserot, A, Massinger, T, Masso-Reid, M, Mastrogiovanni, S, Matas, A, Matichard, F, Matone, L, Mavalvala, N, Mccann, J, Mccarthy, R, Mcclelland, D, Mccormick, S, Mcculler, L, Mcguire, S, Mcisaac, C, Mciver, J, Mcmanus, D, Mcrae, T, Mcwilliams, S, Meacher, D, Meadors, G, Mehmet, M, Mehta, A, Meidam, J, Villa, E, Melatos, A, Mendell, G, Mercer, R, Mereni, L, Merfeld, K, Merilh, E, Merzougui, M, Meshkov, S, Messenger, C, Messick, C, Messina, F, Metzdorff, R, Meyers, P, Meylahn, F, Miani, A, Miao, H, Michel, C, Middleton, H, Milano, L, Miller, A, Millhouse, M, Mills, J, Milovich-Goff, M, Minazzoli, O, Minenkov, Y, Mishkin, A, Mishra, C, Mistry, T, Mitra, S, Mitrofanov, V, Mitselmakher, G, Mittleman, R, Mo, G, Moffa, D, Mogushi, K, Mohapatra, S, Molina-Ruiz, M, Mondin, M, Montani, M, Moore, C, Moraru, D, Morawski, F, Moreno, G, Morisaki, S, Mours, B, Mow-Lowry, C, Muciaccia, F, Mukherjee, A, Mukherjee, D, Mukherjee, S, Mukund, N, Mullavey, A, Munch, J, Muniz, E, Muratore, M, Murray, P, Nagar, A, Nardecchia, I, Naticchioni, L, Nayak, R, Neil, B, Neilson, J, Nelemans, G, Nelson, T, Nery, M, Neunzert, A, Nevin, L, Ng, K, Ng, S, Nguyen, C, Nguyen, P, Nichols, D, Nichols, S, Nissanke, S, Nocera, F, North, C, Nuttall, L, Obergaulinger, M, Oberling, J, O'Brien, B, Oganesyan, G, Ogin, G, Oh, J, Oh, S, Ohme, F, Ohta, H, Okada, M, Oliver, M, Oppermann, P, Oram, R, O'Reilly, B, Ormiston, R, Ortega, L, O'Shaughnessy, R, Ossokine, S, Ottaway, D, Overmier, H, Owen, B, Pace, A, Pagano, G, Page, M, Pagliaroli, G, Pai, A, Pai, S, Palamos, J, Palashov, O, Palomba, C, Pan, H, Panda, P, Pang, P, Pankow, C, Pannarale, F, Pant, B, Paoletti, F, Paoli, A, Parida, A, Parker, W, Pascucci, D, Pasqualetti, A, Passaquieti, R, Passuello, D, Patil, M, Patricelli, B, Payne, E, Pearlstone, B, Pechsiri, T, Pedersen, A, Pedraza, M, Pedurand, R, Pele, A, Penn, S, Perego, A, Perez, C, Perigois, C, Perreca, A, Petermann, J, Pfeiffer, H, Phelps, M, Phukon, K, Piccinni, O, Pichot, M, Piergiovanni, F, Pierro, V, Pillant, G, Pinard, L, Pinto, I, Pirello, M, Pitkin, M, Plastino, W, Poggiani, R, Pong, D, Ponrathnam, S, Popolizio, P, Porter, E, Powell, J, Prajapati, A, Prasad, J, Prasai, K, Prasanna, R, Pratten, G, Prestegard, T, Principe, M, Prodi, G, Prokhorov, L, Punturo, M, Puppo, P, Purrer, M, Qi, H, Quetschke, V, Quinonez, P, Raab, F, Raaijmakers, G, Radkins, H, Radulesco, N, Raffai, P, Raja, S, Rajan, C, Rajbhandari, B, Rakhmanov, M, Ramirez, K, Ramos-Buades, A, Rana, J, Rao, K, Rapagnani, P, Raymond, V, Razzano, M, Read, J, Regimbau, T, Rei, L, Reid, S, Reitze, D, Rettegno, P, Ricci, F, Richardson, C, Richardson, J, Ricker, P, Riemenschneider, G, Riles, K, Rizzo, M, Robertson, N, Robinet, F, Rocchi, A, Rolland, L, Rollins, J, Roma, V, Romanelli, M, Romano, J, Romano, R, Romel, C, Romie, J, Rose, C, Rose, D, Rose, K, Rosinska, D, Rosofsky, S, Ross, M, Rowan, S, Rudiger, A, Ruggi, P, Rutins, G, Ryan, K, Sachdev, S, Sadecki, T, Sakellariadou, M, Salafia, O, Salconi, L, Saleem, M, Samajdar, A, Sammut, L, Sanchez, E, Sanchez, L, Sanchis-Gual, N, Sanders, J, Santiago, K, Santos, E, Sarin, N, Sassolas, B, Sathyaprakash, B, Sauter, O, Savage, R, Schale, P, Scheel, M, Scheuer, J, Schmidt, P, Schnabel, R, Schofield, R, Schonbeck, A, Schreiber, E, Schulte, B, Schutz, B, Scott, J, Scott, S, Seidel, E, Sellers, D, Sengupta, A, Sennett, N, Sentenac, D, Sequino, V, Sergeev, A, Setyawati, Y, Shaddock, D, Shaffer, T, Shahriar, M, Shaner, M, Sharma, A, Sharma, P, Shawhan, P, Shen, H, Shink, R, Shoemaker, D, Shukla, K, Shyamsundar, S, Siellez, K, Sieniawska, M, Sigg, D, Singer, L, Singh, D, Singh, N, Singhal, A, Sintes, A, Sitmukhambetov, S, Skliris, V, Slagmolen, B, Slaven-Blair, T, Smith, J, Smith, R, Somala, S, Son, E, Soni, S, Sorazu, B, Sorrentino, F, Souradeep, T, Sowell, E, Spencer, A, Spera, M, Srivastava, A, Srivastava, V, Staats, K, Stachie, C, Standke, M, Steer, D, Steinke, M, Steinlechner, J, Steinlechner, S, Steinmeyer, D, Stevenson, S, Stocks, D, Stone, R, Stops, D, Strain, K, Stratta, G, Strigin, S, Strunk, A, Sturani, R, Stuver, A, Sudhir, V, Summerscales, T, Sun, L, Sunil, S, Sur, A, Suresh, J, Sutton, P, Swinkels, B, Szczepanczyk, M, Tacca, M, Tait, S, Talbot, C, Tanner, D, Tao, D, Tapai, M, Tapia, A, Tasson, J, Taylor, R, Tenorio, R, Terkowski, L, Thomas, M, Thomas, P, Thondapu, S, Thorne, K, Thrane, E, Tiwari, S, Tiwari, V, Toland, K, Tonelli, M, Tornasi, Z, Torres-Forne, A, Torrie, C, Toyr, D, Travasso, F, Traylor, G, Tringali, M, Tripathee, A, Trovato, A, Trozzo, L, Tsang, K, Tse, M, Tso, R, Tsukada, L, Tsuna, D, Tsutsui, T, Tuyenbayev, D, Ueno, K, Ugolini, D, Unnikrishnan, C, Urban, A, Usman, S, Vahlbruch, H, Vajente, G, Valdes, G, Valentini, M, Bakel, N, Beuzekom, M, Brand, J, Broeck, C, Vander-Hyde, D, Schaaf, L, Vanheijningen, J, Veggel, A, Vardaro, M, Varma, V, Vass, S, Vasuth, M, Vecchio, A, Vedovato, G, Veitch, J, Veitch, P, Venkateswara, K, Venugopalan, G, Verkindt, D, Vetrano, F, Vicere, A, Viets, A, Vinciguerra, S, Vine, D, Vinet, J, Vitale, S, Vo, T, Vocca, H, Vorvick, C, Vyatchanin, S, Wade, A, Wade, L, Wade, M, Walet, R, Walker, M, Wallace, L, Walsh, S, Wang, H, Wang, J, Wang, S, Wang, W, Wang, Y, Ward, R, Warden, Z, Warner, J, Was, M, Watchi, J, Weaver, B, Wei, L, Weinert, M, Weinstein, A, Weiss, R, Wellmann, F, Wen, L, Wessel, E, Wessels, P, Westhouse, J, Wette, K, Whelan, J, Whiting, B, Whittle, C, Wilken, D, Williams, D, Williamson, A, Willis, J, Willke, B, Winkler, W, Wipf, C, Wittel, H, Woan, G, Woehler, J, Wofford, J, Wright, J, Wu, D, Wysocki, D, Xiao, S, Xu, R, Yamamoto, H, Yancey, C, Yang, L, Yang, Y, Yang, Z, Yap, M, Yazback, M, Yeeles, D, Yu, H, Yuen, S, Zadrozny, A, Zanolin, M, Zelenova, T, Zendri, J, Zevin, M, Zhang, J, Zhang, L, Zhang, T, Zhao, C, Zhao, G, Zhou, M, Zhou, Z, Zhu, X, Zimmerman, A, Zucker, M, Zweizig, J, Laboratoire des matériaux avancés (LMA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), AstroParticule et Cosmologie (APC (UMR_7164)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7), Laboratoire de l'Accélérateur Linéaire (LAL), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Annecy de Physique des Particules (LAPP/Laboratoire d'Annecy-le-Vieux de Physique des Particules), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Astrophysique Relativiste Théories Expériences Métrologie Instrumentation Signaux (ARTEMIS), Université Nice Sophia Antipolis (... - 2019) (UNS), Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Institut des Fonctions Optiques pour les Technologies de l'informatiON (Institut FOTON), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École Nationale Supérieure des Sciences Appliquées et de Technologie (ENSSAT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire Kastler Brossel (LKB [Collège de France]), Fédération de recherche du Département de physique de l'Ecole Normale Supérieure - ENS Paris (FRDPENS), Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris)-Collège de France (CdF)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut Lumière Matière [Villeurbanne] (ILM), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), ESPCI ParisTech, Institut des Hautes Etudes Scientifiques (IHES), IHES, Institut de Physique Nucléaire de Lyon (IPNL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), LIGO Scientific, Virgo, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire d'Annecy de Physique des Particules (LAPP), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École Nationale Supérieure des Sciences Appliquées et de Technologie (ENSSAT)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Collège de France (CdF (institution))-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL), Institut des Hautes Études Scientifiques (IHES), VIRGO, (Astro)-Particles Physics, COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), Centre National de la Recherche Scientifique (CNRS)-Observatoire de la Côte d'Azur, COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École Nationale Supérieure des Sciences Appliquées et de Technologie (ENSSAT)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Fédération de recherche du Département de physique de l'Ecole Normale Supérieure - ENS Paris (FRDPENS), Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Collège de France (CdF (institution)), Spectroscopies optiques des matériaux verres, amorphes et à nanoparticules (SOPRANO), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), LIGO Scientific Collaboration, Virgo Collaboration, Arène, M., Bécsy, B., Bustillo, J. Calderón, Diaz, J. Casanueva, Cavaglià, M., Cerdá-Durán, P., Cieślar, M., Cordero-Carrión, I., Dálya, G., D’Angelo, B., D’Antonio, S., Deléglise, S., Pozzo, W. Del, de Varona, O., Díaz, M. C., Vivanco, Francisco Hernandez, Fronzè, G., García-Quirós, C., Ghosh, Abhirup, Ghosh, Archisman, González, G., Gupta, Anchal, Hübner, M. T., Kéfélian, F., Kim, Chunglee, Krämer, C., Królak, A., Kumar, Rahul, Kumar, Rakesh, Lück, H., Hernandez, I. Magaña, Magaña-Sandoval, F., Márka, S., Márka, Z., Villa, E. Mejuto, Mukherjee, Arunava, Mukherjee, Subroto, Muñiz, E. A., O’Brien, B. D., Oram, Richard J., O’Reilly, B., O’Shaughnessy, R., Périgois, C., Pinto, I. M., Pürrer, M., Rana, Javed, Rosińska, D., Rüdiger, A., Schönbeck, A., Szczepańczyk, M. J., Tápai, M., Tiwari, Shubhanshu, Tiwari, Srishti, Torres-Forné, A., Töyrä, D., Bakel, N. van, Beuzekom, M. van, Brand, J. F. J. van den, Broeck, C. Van Den, Schaaf, L. van der, Veggel, A. A. van, Vasúth, M., Viceré, A., Weßels, P., Yu, Hang, Yu, Haocun, Zadrożny, A. K., Zadrożny, A., RS: FSE MSP, Grav. waves and fundamental physics, RS: FSE Grav. waves and fundamental physics, Faculty of Science, Gravitation and Astroparticle Physics Amsterdam, Other Research IHEF (IoP, FNWI), IoP (FNWI), and Astroparticle Physics (IHEF, IoP, FNWI)
Subjects: Gravitació, neutron star: binary, cosmological model, 010504 meteorology & atmospheric sciences, Astronomy, Gravitational Waves, Hubble constant, O2, LIGO, Virgo, detector: network, 01 natural sciences, Cosmology, General Relativity and Quantum Cosmology, LIGO, dark energy, 010303 astronomy & astrophysics, QC, Physics, Settore FIS/01, Hubble constant, Settore FIS/05, CATALOG, Physical Sciences, symbols, [PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc], Astrophysics - Cosmology and Nongalactic Astrophysics, Cosmology and Nongalactic Astrophysics (astro-ph.CO), DATA RELEASE, COSMOLOGICAL PARAMETERS, FOS: Physical sciences, O2, General Relativity and Quantum Cosmology (gr-qc), Astrophysics::Cosmology and Extragalactic Astrophysics, Astronomy & Astrophysics, LUMINOSITY FUNCTIONS, gravitational radiation: direct detection, Gravitational-wave astronomy, 1ST, Article, electromagnetic field: production, symbols.namesake, Binary black hole, 0103 physical sciences, DISTRIBUTIONS, K-CORRECTIONS, SDG 7 - Affordable and Clean Energy, Astrophysique, STFC, 0105 earth and related environmental sciences, Gravitational Waves, Science & Technology, Gravitational wave, Virgo, RCUK, Astronomy and Astrophysics, cosmology, gravitational waves, 310 Galaxies and Cosmology, Galaxy, EVOLUTION, Dewey Decimal Classification::500 | Naturwissenschaften::520 | Astronomie, Kartographie, gravitational radiation detector, VIRGO, black hole: binary, Space and Planetary Science, [SDU]Sciences of the Universe [physics], DENSITY, gravitational radiation: emission, Dark energy, Astronomia, ddc:520, galaxy, Gravitational wave astronomy, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Hubble's law
Abstract: This paper presents the gravitational-wave measurement of the Hubble constant (H 0) using the detections from the first and second observing runs of the Advanced LIGO and Virgo detector network. The presence of the transient electromagnetic counterpart of the binary neutron star GW170817 led to the first standard-siren measurement of H 0. Here we additionally use binary black hole detections in conjunction with galaxy catalogs and report a joint measurement. Our updated measurement is H 0 = km s-1 Mpc-1 (68.3% of the highest density posterior interval with a flat-in-log prior) which is an improvement by a factor of 1.04 (about 4%) over the GW170817-only value of km s-1 Mpc-1. A significant additional contribution currently comes from GW170814, a loud and well-localized detection from a part of the sky thoroughly covered by the Dark Energy Survey. With numerous detections anticipated over the upcoming years, an exhaustive understanding of other systematic effects are also going to become increasingly important. These results establish the path to cosmology using gravitational-wave observations with and without transient electromagnetic counterparts., 0, info:eu-repo/semantics/published
Published: 2021
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13. Identités de Bézout pour des fonctions de transfert pseudo-rationnelles

Author: Yutaka Yamamoto, Catherine Bonnet, Graduate School of Informatics [Kyoto], Kyoto University, Dynamical Interconnected Systems in COmplex Environments (DISCO), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire des signaux et systèmes (L2S), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Kyoto University [Kyoto]
Subjects: 0209 industrial biotechnology, Pure mathematics, Ring (mathematics), Bézout identity, Coprime integers, distributions, 020208 electrical & electronic engineering, 02 engineering and technology, Transfer function, Controllability, 020901 industrial engineering & automation, delay-differential systems AMS subject classification: 46F10, Control and Systems Engineering, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, 0202 electrical engineering, electronic engineering, information engineering, State space, pseudorationality, Gel'fand representation, Bézout's identity, Mathematics
Abstract: International audience; Coprime factorizations of transfer functions play various important roles, e.g., minimality of realizations, stabilizability of systems, etc. This paper studies the Bézout condition over the ring E (R −) of distributions of compact support and the ring M(R −) of measures with compact support. These spaces are known to play crucial roles in minimality of state space representations and controllability of behaviors. We give a detailed review of the results obtained thus far, as well as discussions on a new attempt of deriving general results from that for measures. It is clarified that there is a technical gap in generalizing the result for M(R −) to that for E (R −). A detailed study of a concrete example is given.
Published: 2021
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14. Involutivity degree of a distribution at superdensity points of its tangencies

Author: Silvano Delladio
Subjects: tangency set, distributions, superdensity, integral manifold, Frobenius theorem, Distribution (number theory), General Mathematics, Mathematical analysis, Degree (temperature), Mathematics
Published: 2021
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15. Range Size and Niche Breadth as Predictors of Climate-Induced Habitat Change in Epipactis (Orchidaceae)

Author: Hans Jacquemyn and Alexandra Evans
Subjects: ENMTools, Science & Technology, POPULATION-DYNAMICS, Ecology, CONSERVATION, DIVERSITY, SHIFTS, Environmental Sciences & Ecology, HELLEBORINE, climate change, PLANT-RESPONSES, ECOLOGICAL NICHE, SPECIES DISTRIBUTION, DISTRIBUTIONS, Epipactis, Maxent, Life Sciences & Biomedicine, range size, Ecology, Evolution, Behavior and Systematics, GERMINATION
Abstract: While there is mounting evidence that ongoing changes in the climate system are shifting species ranges poleward and to higher altitudes, responses to climate change vary considerably between species. In general, it can be expected that species responses to climate change largely depend on how broad their ecological niches are, but evidence is still scant. In this study, we investigated the effects of predicted future climate change on the availability of suitable habitat for 14 Epipactis (Orchidaceae) species, and tested whether habitat specialists would experience greater changes in the extent of their habitats than habitat generalists. We used Maxent to model the ecological niche of each species in terms of climate, soil, elevation and land-use and projected it onto climate scenarios predicted for 2061–2080. To test the hypothesis that temperate terrestrial orchid species with small ranges or small niche breadths may be at greater risk under climate change than species with wide ranges or large niche breadths, we related niche breadth in both geographic and environmental space to changes in size and location of suitable habitat. The habitat distributions of half of the species shifted northwards in future projections. The area of suitable habitat increased for eight species but decreased for the remaining six species. If expansion at the leading edge of the distribution was not possible, the area of suitable habitat decreased for 12 species. Species with wide niche breadth in geographic space experienced greater northwards expansions and higher habitat suitability scores than species with small niche breadth. Niche breadth in environmental space was not significantly related to change in habitat distribution. Overall, these results indicate that terrestrial orchid species with a wide distribution will be more capable of shifting their distributions under climate change than species with a limited distribution, but only if they are fully able to expand into habitats at the leading edge of their distributions.
Published: 2022
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16. The importance of Indigenous Peoples’ lands for the conservation of terrestrial mammals

Author: Oscar Venter, Christopher J. O'Bryan, Ian Leiper, Kerstin K. Zander, James E. M. Watson, Harry Jonas, Neil D. Burgess, Eduardo S. Brondizio, John E. Fa, Catherine Robinson, Jose Rehbein, Micha V. Jackson, Stephen T. Garnett, Álvaro Fernández-Llamazares, Organismal and Evolutionary Biology Research Programme, Helsinki Institute of Sustainability Science (HELSUS), and Global Change and Conservation Lab
Subjects: 0106 biological sciences, 濒危物种, Range (biology), distributions, Biodiversity, 01 natural sciences, 传统所有者, Ecosystem services, distribuciones, metas de desarrollo sustentable, 11. Sustainability, 可持续发展目标, 栖息地范围 (AOH), Contributed Papers, conservación del paisaje, Mammals, Ecology, Agroforestry, 生物多样性保护, landscape conservation, Geography, Habitat, 1181 Ecology, evolutionary biology, área del hábitat, especies en peligro, traditional owners, Conservation of Natural Resources, 010603 evolutionary biology, Indigenous, dueños tradicionales, 景观保护, AOH, Animals, Humans, Indigenous Peoples, Ecosystem, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation, Sustainable development, conservación de la biodiversidad, 010604 marine biology & hydrobiology, endangered species, 15. Life on land, sustainable development goals, 物种分布, Contributed Paper, 13. Climate action, Threatened species, ADH, Mammal, biodiversity conservation, area of habitat
Abstract: Indigenous Peoples’ lands cover over one‐quarter of Earth's surface, a significant proportion of which is still free from industrial‐level human impacts. As a result, Indigenous Peoples and their lands are crucial for the long‐term persistence of Earth's biodiversity and ecosystem services. Yet, information on species composition on these lands globally remains largely unknown. We conducted the first comprehensive analysis of terrestrial mammal composition across mapped Indigenous lands based on data on area of habitat (AOH) for 4460 mammal species assessed by the International Union for Conservation of Nature. We overlaid each species’ AOH on a current map of Indigenous lands and found that 2695 species (60% of assessed mammals) had ≥10% of their ranges on Indigenous Peoples’ lands and 1009 species (23%) had >50% of their ranges on these lands. For threatened species, 473 (47%) occurred on Indigenous lands with 26% having >50% of their habitat on these lands. We also found that 935 mammal species (131 categorized as threatened) had ≥ 10% of their range on Indigenous Peoples’ lands that had low human pressure. Our results show how important Indigenous Peoples’ lands are to the successful implementation of conservation and sustainable development agendas worldwide., Article impact statement: Indigenous Peoples’ lands are important for the successful implementation of international conservation and sustainable development agendas.
Published: 2020
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17. Approximate Bayesian computation for finite mixture models

Author: Umberto Simola, Robert L. Wolpert, Jessi Cisewski-Kehe, and Department of Mathematics and Statistics
Subjects: FOS: Computer and information sciences, Statistics and Probability, Finite mixture, 0211 other engineering and technologies, Inference, DENSITY-ESTIMATION, 02 engineering and technology, 01 natural sciences, Methodology (stat.ME), 010104 statistics & probability, 111 Mathematics, DISTRIBUTIONS, Applied mathematics, SEQUENTIAL MONTE-CARLO, perturbation kernels, 0101 mathematics, summary statistics, 112 Statistics and probability, Statistics - Methodology, finite mixture models, Mathematics, 021103 operations research, Applied Mathematics, Mixture model, Statistics::Computation, ComputingMilieux_GENERAL, ComputingMethodologies_PATTERNRECOGNITION, Modeling and Simulation, Label switching, Approximate Bayesian computation, label switching, INFERENCE, Statistics, Probability and Uncertainty, Likelihood function
Abstract: Finite mixture models are used in statistics and other disciplines, but inference for mixture models is challenging due, in part, to the multimodality of the likelihood function and the so-called label switching problem. We propose extensions of the Approximate Bayesian Computation-Population Monte Carlo (ABC-PMC) algorithm as an alternative framework for inference on finite mixture models. There are several decisions to make when implementing an ABC-PMC algorithm for finite mixture models, including the selection of the kernels used for moving the particles through the iterations, how to address the label switching problem, and the choice of informative summary statistics. Examples are presented to demonstrate the performance of the proposed ABC-PMC algorithm for mixture modeling. The performance of the proposed method is evaluated in a simulation study and for the popular recessional velocity galaxy data., 21 pages, 4 figures
Published: 2020
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18. Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research

Author: D. R. N. Vos, Shane R. Ellis, Benjamin Balluff, and Ron M. A. Heeren
Subjects: Data Analysis, Proteomics, Molecular complexity, Cancer Research, Biomedical Research, Resolution (mass spectrometry), Computer science, Review Article, 01 natural sciences, MALDI-MS, Experimental set-up, Mass spectrometry imaging, 03 medical and health sciences, Imaging, Three-Dimensional, 3D imaging, DISTRIBUTIONS, Animals, Humans, RECONSTRUCTION, Radiology, Nuclear Medicine and imaging, 030304 developmental biology, MOUSE-BRAIN, 0303 health sciences, Volumetric data, 010401 analytical chemistry, SAMPLE PREPARATION, Analytic Sample Preparation Methods, Full sample, Molecular Imaging, 0104 chemical sciences, Visualization, FIDUCIAL MARKERS, RESOLUTION, Oncology, TISSUE, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization, CELLS, Biological system, Fiducial marker, SIMS, Tissue volume
Abstract: Mass spectrometry imaging (MSI) enables the visualization of molecular distributions on complex surfaces. It has been extensively used in the field of biomedical research to investigate healthy and diseased tissues. Most of the MSI studies are conducted in a 2D fashion where only a single slice of the full sample volume is investigated. However, biological processes occur within a tissue volume and would ideally be investigated as a whole to gain a more comprehensive understanding of the spatial and molecular complexity of biological samples such as tissues and cells. Mass spectrometry imaging has therefore been expanded to the 3D realm whereby molecular distributions within a 3D sample can be visualized. The benefit of investigating volumetric data has led to a quick rise in the application of single-sample 3D-MSI investigations. Several experimental and data analysis aspects need to be considered to perform successful 3D-MSI studies. In this review, we discuss these aspects as well as ongoing developments that enable 3D-MSI to be routinely applied to multi-sample studies.
Published: 2020
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19. Suitable habitats of fish species in the Barents Sea

Author: Anatoly Filin, Grégoire Certain, Bérengère Husson, Benjamin Planque, Laboratoire Environnement Profond (LEP), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut de Recherche pour le Développement (IRD), Tromsø department (IMR), Institute of Marine Research [Bergen] (IMR), and University of Bergen (UiB)-University of Bergen (UiB)
Subjects: 0106 biological sciences, quantile regression, 010504 meteorology & atmospheric sciences, spatial-distribution, [SDE.MCG]Environmental Sciences/Global Changes, distributions, Species distribution, Climate change, limiting factors, Aquatic Science, Oceanography, 010603 evolutionary biology, 01 natural sciences, generalized additive models, demersal fish, Abundance (ecology), 14. Life underwater, species shifts, environmental gradients, habitat suitability models, 0105 earth and related environmental sciences, Biomass (ecology), biology, Ecology, 010604 marine biology & hydrobiology, environmental niche, distribution models, biology.organism_classification, climate change, Arctic, Habitat, Boreal, 13. Climate action, marine fish, climate-change, environmental drivers, Environmental science, species distribution, movement, ecology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Atlantic cod
Abstract: Many marine species are shifting their distribution poleward in response to climate change. The Barents Sea, as a doorstep to the fast-warming Arctic, is experiencing large scale changes in its environment and its communities. This paper aims at understanding what environmental predictors limit fish species habitats in the Barents Sea and discuss their possible evolution in response to the warming of the Arctic.Species distribution models usually aim at predicting the probability of presence or the average abundance of a species, conditional on environmental drivers. A complementary approach is to determine suitable habitats by modelling the upper limit of a species’ response to environmental factors. Using quantile regressions, we model the upper limit of biomass for 33 fish species in the Barents Sea in response to 10 environmental predictors. Boreal species are mainly limited by temperatures and most of them are expected to be able to expand their distribution in the Barents Sea when new thermally suitable habitats become available, in the limit of bathymetric constraints. Artic species are often limited by several predictors, mainly depth, bottom and surface temperature and ice cover, and future habitats are hard to predict qualitatively. Widespread species like the Atlantic cod are not strongly limited by the selected variables at the scale of the study, and current and future suitable habitats are harder to predict. These models can be used as input to integrative tools like end-to-end models on the habitat preference and tolerance at the species scale to inform resource management and conservation.
Published: 2020
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20. Non-locality of Earth's quasi-parallel bow shock: injection of thermal protons in a hybrid-Vlasov simulation

Author: Thiago Brito, Maxime Grandin, Yann Pfau-Kempf, Minna Palmroth, Markus Battarbee, Lucile Turc, Urs Ganse, Tuomas Koskela, Space Physics Research Group, Particle Physics and Astrophysics, and Department of Physics
Subjects: REFORMATION, REFLECTION, Atmospheric Science, 010504 meteorology & atmospheric sciences, Astrophysics::High Energy Astrophysical Phenomena, WAVES, FORESHOCK, TRANSIENT, HOT FLOW ANOMALIES, Curvature, 01 natural sciences, DRIFT ACCELERATION, LEAKAGE, Shock position, 0103 physical sciences, Earth and Planetary Sciences (miscellaneous), DISTRIBUTIONS, Bow shock (aerodynamics), lcsh:Science, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, IONS UPSTREAM, 0105 earth and related environmental sciences, Physics, lcsh:QC801-809, Geology, Astronomy and Astrophysics, Plasma, Mechanics, 115 Astronomy, Space science, lcsh:QC1-999, Foreshock, Magnetic field, Shock (mechanics), lcsh:Geophysics. Cosmic physics, Solar wind, 13. Climate action, Space and Planetary Science, Physics::Space Physics, lcsh:Q, lcsh:Physics
Abstract: We study the interaction of solar wind protons with Earth's quasi-parallel bow shock using a hybrid-Vlasov simulation. We employ the global hybrid model Vlasiator to include effects due to bow shock curvature, tenuous upstream populations, and foreshock waves. We investigate the uncertainty of the position of the quasi-parallel bow shock as a function of several plasma properties and find that regions of non-locality or uncertainty of the shock position form and propagate away from the shock nose. Our results support the notion of upstream structures causing the patchwork reconstruction of the quasi-parallel shock front in a non-uniform manner. We propose a novel method for spacecraft data to be used to analyse this quasi-parallel reformation. We combine our hybrid-Vlasov results with test-particle studies and show that proton energization, which is required for injection, takes place throughout a larger shock transition zone. The energization of particles is found regardless of the instantaneous non-locality of the shock front, in agreement with it taking place over a larger region. Distortion of magnetic fields in front of and at the shock is shown to have a significant effect on proton injection. We additionally show that the density of suprathermal reflected particles upstream of the shock may not be a useful metric for the probability of injection at the shock, as foreshock dynamics and particle trapping appear to have a significant effect on energetic-particle accumulation at a given position in space. Our results have implications for statistical and spacecraft studies of the shock injection problem.
Published: 2020
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21. Human ecodynamics in the north-west coast of Finland 10,000–2000 years ago

Author: Miikka Tallavaara, Petro Pesonen, University of Helsinki, Department of Geosciences and Geography, Department of Geosciences and Geography, and Hominin Ecology
Subjects: 010506 paleontology, POPULATION-DYNAMICS, Population dynamics, Conflicts, Population, Archaeological record, Climate change, 010502 geochemistry & geophysics, 01 natural sciences, SOUTHWESTERN FRANCE, HISTORY, DEMOGRAPHY, DISTRIBUTIONS, RECONSTRUCTION, education, Finland, Holocene, 0105 earth and related environmental sciences, Earth-Surface Processes, Mobility, Shore, geography, education.field_of_study, geography.geographical_feature_category, Population size, SITE, RADIOCARBON-DATES, 15. Life on land, HUNTER-GATHERERS, VARIABILITY, Productivity (ecology), 13. Climate action, 519 Social and economic geography, Physical geography, Frequency distribution
Abstract: High-quality palaeoenvironmental proxies and well-preserved archaeological record make Fennoscandia as an excellent area for the studies of long-term human-environment interaction in high-latitude settings. Here, we use palaeoenvironmental data and temporal frequency distributions of 754 shoreline dated hunter-gatherer sites to analyse the relationship between environmental changes and hunter-gatherer population dynamics, mobility, social organisation, and conflicts in the Baltic Sea coast of western Finland. Our results suggest, firstly, that hunter-gatherer population dynamics were strongly influenced by changes in the productivity of terrestrial and marine environments. Secondly, the degree of residential mobility, as indicated by the frequency of house pit sites, was correlated with population size. Thirdly, large villages and large co-residential units were tightly associated with the highest population size and their frequency dropped sharply when population size started to decrease. Fourthly, intensity of conflicts, as indicated by frequency of defensive structures, was the highest slightly after the highest population sizes, when environmental productivity had started to decline. Increased conflicts were probably caused by the imbalance between human population and its resources. Lastly, dramatic population crash (76% within 200 years) occurred just after the intensity peak in conflicts. The crash was partly density dependent (conflicts) and partly density independent phenomenon as it coincided with the onset of the Late Holocene acceleration in the cooling trend in climate. Continuing decline in the environmental productivity during the Late Holocene did not allow hunter-gatherer population to recover from the collapse. All this highlights the importance of environmental forcing on hunter-gatherer populations in northern Europe.
Published: 2020
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22. Trends in platelet distributions from 2008 to 2017: a survey of twelve national and regional blood collectors

Author: Dirk de Korte, Peter Flanagan, Alfredo Mendrone, Mark Rashleigh, Cath O’Brien, Colby Schmitt, Karin van den Berg, Gerry Devin, Minoko Takanashi, Eka Tian, Beth H. Shaz, Stephen Field, Dana V. Devine, Joanne Pink, Mark H. Yazer, Cheryl Doncaster, Eilat Shinar, Torunn Oveland Apelseth, Julie Huet, Jansen N. Seheult, Pierre Tiberghien, and Academic Medical Center
Subjects: Blood Platelets, distributions, apheresis, Blood Donors, Massive haemorrhage, Buffy coat, 030204 cardiovascular system & hematology, 03 medical and health sciences, 0302 clinical medicine, Animal science, Surveys and Questionnaires, Humans, Medicine, Platelet, whole blood-derived platelet, Collection methods, blood collector, business.industry, Hematology, General Medicine, Transplantation, Apheresis, platelets, Blood Component Removal, business, buffy coat, 030215 immunology
Abstract: Background This multi-national study evaluated changes in platelet (PLT) unit distributions at 12 national or regional blood collectors over a 10-year period. Methods Data on the total number of PLT distributions, the collection method, that is apheresis vs whole blood-derived (WBD), the PLT unit characteristics and post-collection modifications were obtained from 12 national or regional blood collectors from 2008 through 2017. Individual WBD PLT units were converted to apheresis equivalent units (i.e. a dose of PLTs) by dividing by 4, the typical pool size; WBD units that were pooled before distribution were counted as a single dose. Results Overall at these 12 blood collectors, the total number of PLTs distributed in 2008 was 1 373 200, which rose by 10·2% to 1 513 803 in 2017. The Japanese Red Cross, which distributes only apheresis PLTs, had a 13·4% increase in the number of distributions between the years 2008 and 2017, while the other 11 blood collectors combined demonstrated a 6·8% increase in distributions between these two years. Between the years 2008 and 2017, the changes in the proportion of apheresis, platelet-rich plasma and buffy coat PLT distributions were -29·9%, -70·7% and 80·0%, respectively. Conclusion The number of PLT distributions increased during the 10-year study period despite prophylactic PLT transfusion thresholds having remained fairly consistent over the last decade. Perhaps this increase is in part driven by increased administration of platelets to patients with massive haemorrhage or an increase in stem cell transplantation. The use of buffy coat PLTs is increasing at these collectors.
Published: 2020
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23. Island properties dominate species traits in determining plant colonizations in an archipelago system

Author: Sami Aikio, Satu Ramula, Mikael von Numers, Anne Muola, Biosciences, Botany, and Finnish Museum of Natural History
Subjects: 0106 biological sciences, DISTRIBUTION PATTERNS, media_common.quotation_subject, INVASION, DIVERSITY, islands, Biology, GENERAL COEFFICIENT, 010603 evolutionary biology, 01 natural sciences, RICHNESS, DISTRIBUTIONS, Colonization, functional traits, Ecology, Evolution, Behavior and Systematics, RESTORATION, media_common, geography, geography.geographical_feature_category, species diversity, Ecology, Species diversity, 15. Life on land, colonization, SW ARCHIPELAGO, community properties, 1181 Ecology, evolutionary biology, Archipelago, insular ecology, VASCULAR PLANTS, Species richness, LONG-TERM CHANGES, 010606 plant biology & botany, Diversity (politics)
Abstract: The extrinsic determinants hypothesis emphasizes the essential role of environmental heterogeneity in species' colonization. Consequently, high resident species diversity can increase community susceptibility to colonizations because good habitats may support more species that are functionally similar to colonizers. On the other hand, colonization success is also likely to depend on species traits. We tested the relative importance of environmental characteristics and species traits in determining colonization success using census data of 587 vascular plant species collected about 70 yr apart from 471 islands in the archipelago of SW Finland. More specifically, we explored potential new colonization as a function of island properties (e.g. location, area, habitat diversity, number of resident species per unit area), species traits (e.g. plant height, life-form, dispersal vector, Ellenberg indicator values, association with human impact), and species' historical distributions (number of inhabited islands, nearest occurrence). Island properties and species' historical distributions were more effective than plant traits in explaining colonization outcomes. Contrary to the extrinsic determinants hypothesis, colonization success was neither associated with resident species diversity nor habitat diversity per se, although colonization was lowest on sparsely vegetated islands. Our findings lead us to propose that while plant traits related to dispersal and establishment may enhance colonization, predictions of plant colonizations primarily require understanding of habitat properties and species' historical distributions.
Published: 2020
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24. A Markov jump process modelling animal group size statistics

Author: Robert L. Pego, Maximilian Engel, Jian-Guo Liu, Pierre Degond, Mathématiques pour l'Industrie et la Physique (MIP), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), department of mathematics, University of Maryland [College Park], University of Maryland System-University of Maryland System, Center for Nonlinear Analysis [Pittsburgh] (CNA), Carnegie Mellon University [Pittsburgh] (CMU), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), The Royal Society, and Engineering & Physical Science Research Council (EPSRC)
Subjects: POPULATION BALANCE-EQUATIONS, DYNAMICS, Work (thermodynamics), Population dynamics, q-bio.PE, General Mathematics, Population, Mathematics, Applied, self-consistent Markov process, COAGULATION, jump process, 01 natural sciences, 0101 Pure Mathematics, 010104 statistics & probability, Stochastic differential equation, 92D50, Simple (abstract algebra), 0102 Applied Mathematics, CONVERGENCE, DISTRIBUTIONS, 65C30, Statistical physics, [MATH]Mathematics [math], 0101 mathematics, Quantitative Biology - Populations and Evolution, education, 65C35, Mathematics, 45J05, education.field_of_study, Science & Technology, fish schools, SCHEME, Applied Mathematics, 010102 general mathematics, Populations and Evolution (q-bio.PE), 1502 Banking, Finance and Investment, 70F45, AGGREGATION, self-consistent Markov process Mathematics Subject Classification (2010): 60J75, Connection (mathematics), Nonlinear system, Distribution (mathematics), FOS: Biological sciences, Physical Sciences, Jump process, numerics
Abstract: International audience; We translate a coagulation-framentation model, describing the dynamics of animal group size distributions , into a model for the population distribution and associate the nonlinear evolution equation with a Markov jump process of a type introduced in classic work of H. McKean. In particular this formalizes a model suggested by H.-S. Niwa [J. Theo. Biol. 224 (2003)] with simple coagulation and fragmentation rates. Based on the jump process, we develop a numerical scheme that allows us to approximate the equilibrium for the Niwa model, validated by comparison to analytical results by Degond et al. [J. Nonlinear Sci. 27 (2017)], and study the population and size distributions for more complicated rates. Furthermore, the simulations are used to describe statistical properties of the underlying jump process. We additionally discuss the relation of the jump process to models expressed in stochastic differential equations and demonstrate that such a connection is justified in the case of nearest-neighbour interactions, as opposed to global interactions as in the Niwa model.
Published: 2020
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25. Embeddings between Triebel-Lizorkin Spaces on Metric Spaces Associated with Operators

Author: George Kyriazis and Athanasios G. Georgiadis
Subjects: besov spaces, doubling volume property, QA299.6-433, Mathematics::Functional Analysis, Pure mathematics, metric spaces, Applied Mathematics, distributions, 010102 general mathematics, triebel-lizorkin spaces, Mathematics::Classical Analysis and ODEs, 010103 numerical & computational mathematics, secondary: 42b35, 42b25, 42b15, 46f10, 01 natural sciences, primary: 58j35, 58j40, Metric space, heat kernel, Geometry and Topology, 0101 mathematics, embeddings, Analysis, Mathematics
Abstract: We consider the general framework of a metric measure space satisfying the doubling volume property, associated with a non-negative self-adjoint operator, whose heat kernel enjoys standard Gaussian localization. We prove embedding theorems between Triebel-Lizorkin spaces associated with operators. Embeddings for non-classical Triebel-Lizorkin and (both classical and non-classical) Besov spaces are proved as well. Our result generalize the Euclidean case and are new for many settings of independent interest such as the ball, the interval and Riemannian manifolds.
Published: 2020
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26. To the knowledge of species of the genus Bisnius Stephens, 1829 (Coleoptera: Staphylinidae: Staphylininae) in the Eastern Ukraine and Southern Russia

Author: A.V. Gontarenko and E.A. Khachikov
Subjects: new synonym, Staphylininae, biology, QH301-705.5, distributions, Zoology, Staphylinidae, Bisnius, new synonym, misidentification, distributions, biology.organism_classification, staphylinidae, новый синоним, ошибочная идентификация, распространение, Geography, Genus, bisnius, Insect Science, misidentification, Biology (General), Ecology, Evolution, Behavior and Systematics
Abstract: The study of specimens previously identified as Bisnius scribae (Fauvel, 1867) or B. scribae var. heidenreichi Hubenthal, 1911 from Russia and Ukraine revealed their identity as B.pentheri (Ganglbauer, 1905) which was hitherto known from Turkey and Armenia. Comparison of B.nigriventris (Thomson, 1867) with the type material of B.pseudoparcus kasatkini Khachikov, 2003, described from the Northern Caucasus, revealed their complete identity. As a result, the following new synonymy is established: Bisniusnigriventris (Thomson, 1867)= B.pseudoparcus kasatkiniKhachikov, 2003,syn.n., and B.nigriventris is recorded for the North Caucasus for the first time. Currently, the following 16species from the genus Bisnius Stephens, 1829 are known from the territory of southeastern Ukraine and the south of the European part of Russia: B.cephalotes (Gravenhorst, 1802), B.manytchensis Hatchikov, 2003, B.nitidulus (Gravenhorst, 1802), B.parcus (Sharp, 1874), B.pseudoparcus (Brunne, 1976), B.pentheri, B.nigriventris, B.scribae (Fauvel, 1867), B.puella (Nordmann, 1837), B.spermophili (Ganglbauer, 1897), B.fimetarius (Gravenhorst, 1802), B.reitteri (Eppelsheim, 1889), B.sordidus (Gravenhorst, 1802), B.subuliformis (Gravenhorst, 1802), B.speculicollis Solodovnikov et Schillhammer, 2000 and B.zhuk (Gusarov, 1995).
Published: 2020
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27. Using water age to explore hydrological processes in contrasting environments

Author: Botter, Gianluca, Benettin, Paolo, and Soulsby, Chris
Subjects: scale, model, fractions, connectivity, transport, distributions, mean transit times, catchment, storage dynamics, solute, Water Science and Technology
Published: 2022
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28. Risk factors relate to the variability of health outcomes as well as the mean: A GAMLSS tutorial

Author: David Bann, Liam Wright, and Tim J Cole
Subjects: Adult, Male, QH301-705.5, Science, distributions, body mass index, General Biochemistry, Genetics and Molecular Biology, Cohort Studies, Risk Factors, GAMLSS, Outcome Assessment, Health Care, Humans, Biology (General), General Immunology and Microbiology, epidemiological methods, General Neuroscience, General Medicine, Middle Aged, United Kingdom, Epidemiology and Global Health, Medicine, Birth Cohort, Female, mental health, Research Article, Human
Abstract: Background:Risk factors or interventions may affect the variability as well as the mean of health outcomes. Understanding this can aid aetiological understanding and public health translation, in that interventions which shift the outcome mean and reduce variability are typically preferable to those which affect only the mean. However, most commonly used statistical tools do not test for differences in variability. Tools that do have few epidemiological applications to date, and fewer applications still have attempted to explain their resulting findings. We thus provide a tutorial for investigating this using GAMLSS (Generalised Additive Models for Location, Scale and Shape).Methods:The 1970 British birth cohort study was used, with body mass index (BMI; N = 6007) and mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale; N = 7104) measured in midlife (42–46 years) as outcomes. We used GAMLSS to investigate how multiple risk factors (sex, childhood social class, and midlife physical inactivity) related to differences in health outcome mean and variability.Results:Risk factors were related to sizable differences in outcome variability—for example males had marginally higher mean BMI yet 28% lower variability; lower social class and physical inactivity were each associated with higher mean and higher variability (6.1% and 13.5% higher variability, respectively). For mental wellbeing, gender was not associated with the mean while males had lower variability (–3.9%); lower social class and physical inactivity were each associated with lower mean yet higher variability (7.2% and 10.9% higher variability, respectively).Conclusions:The results highlight how GAMLSS can be used to investigate how risk factors or interventions may influence the variability in health outcomes. This underutilised approach to the analysis of continuously distributed outcomes may have broader utility in epidemiologic, medical, and psychological sciences. A tutorial and replication syntax is provided online to facilitate this (https://osf.io/5tvz6/).Funding:DB is supported by the Economic and Social Research Council (grant number ES/M001660/1), The Academy of Medical Sciences / Wellcome Trust (“Springboard Health of the Public in 2040” award: HOP001/1025); DB and LW are supported by the Medical Research Council (MR/V002147/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Published: 2022
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29. A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Author: Bohra, Pakshal, Pla, Pol del Aguila, Giovannelli, Jean-François, and Unser, Michael
Subjects: regularization, Signal Processing (eess.SP), algorithm, minimum mean-square error, inverse problems, convolutional neural networks, distributions, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, sparse stochastic processes, cnn
Abstract: We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizations of sparse stochastic processes, which makes them ideally matched to variational sparsity-promoting techniques. We derive Gibbs sampling schemes to compute the minimum mean-square error estimators for processes with Laplace, Student's t, and Bernoulli-Laplace innovations. These allow our framework to provide quantitative measures of the degree of optimality (in the mean-square-error sense) for any given reconstruction method. We showcase our framework by benchmarking the performance of some well-known variational methods and convolutional neural network architectures that perform direct nonlinear reconstructions in the context of deconvolution and Fourier sampling. Our experimental results support the understanding that, while these neural networks outperform the variational methods and achieve near-optimal results in many settings, their performance deteriorates severely for signals associated with heavy-tailed distributions.
Published: 2022
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30. Testing Distributions of Huge Objects

Author: Goldreich, Oded, Ron, Dana, and Braverman, Mark
Subjects: FOS: Computer and information sciences, Theory of computation �� Streaming, sublinear and near linear time algorithms, Computer Science - Data Structures and Algorithms, Theory of computation → Streaming, sublinear and near linear time algorithms, Data Structures and Algorithms (cs.DS), Distributions, Property Testing
Abstract: We initiate a study of a new model of property testing that is a hybrid of testing properties of distributions and testing properties of strings. Specifically, the new model refers to testing properties of distributions, but these are distributions over huge objects (i.e., very long strings). Accordingly, the model accounts for the total number of local probes into these objects (resp., queries to the strings) as well as for the distance between objects (resp., strings). Specifically, the distance between distributions is defined as the earth mover��s distance with respect to the relative Hamming distance between strings. We study the query complexity of testing in this new model, focusing on three directions. First, we try to relate the query complexity of testing properties in the new model to the sample complexity of testing these properties in the standard distribution testing model. Second, we consider the complexity of testing properties that arise naturally in the new model (e.g., distributions that capture random variations of fixed strings). Third, we consider the complexity of testing properties that were extensively studied in the standard distribution testing model: Two such cases are uniform distributions and pairs of identical distributions, where we obtain the following results. - Testing whether a distribution over n-bit long strings is uniform on some set of size m can be done with query complexity ��(m/��), where �� > (log��m)/n is the proximity parameter. - Testing whether two distribution over n-bit long strings that have support size at most m are identical can be done with query complexity ��(m^{2/3}/��). Both upper bounds are quite tight; that is, for �� = ��(1), the first task requires ��(m^c) queries for any c < 1 and n = ��(log m), whereas the second task requires ��(m^{2/3}) queries. Note that the query complexity of the first task is higher than the sample complexity of the corresponding task in the standard distribution testing model, whereas in the case of the second task the bounds almost match., LIPIcs, Vol. 215, 13th Innovations in Theoretical Computer Science Conference (ITCS 2022), pages 78:1-78:19
Published: 2022
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31. New strong lensing modelling of SDSS J2222+2745 enhanced with VLT/MUSE spectroscopy

Author: A. Acebron, C. Grillo, P. Bergamini, G. B. Caminha, P. Tozzi, A. Mercurio, P. Rosati, G. Brammer, M. Meneghetti, M. Nonino, and E. Vanzella
Subjects: Cosmology and Nongalactic Astrophysics (astro-ph.CO), LENSED SEXTUPLE QUASAR, FOS: Physical sciences, Astronomy and Astrophysics, CLASH-VLT, Astrophysics - Astrophysics of Galaxies, GIANT ARCS, dark matter, clusters: individual: SDSS J2222+2745 [galaxies], ELLIPTIC GALAXIES, Space and Planetary Science, strong [gravitational lensing], FUNDAMENTAL PLANE, Astrophysics of Galaxies (astro-ph.GA), DIGITAL SKY SURVEY, DISTRIBUTIONS, SPECTRA, CLUSTER MACS J0416.1-2403, Astrophysics - Cosmology and Nongalactic Astrophysics, MASS-DISTRIBUTION
Abstract: SDSS J2222+2745, at z = 0.489, is one of the few currently known lens clusters with multiple images of a background (z = 2.801) quasar with measured time delays. We combine imaging from the Hubble Space Telescope (HST) with recent Multi Unit Spectroscopic Explorer (MUSE) spectroscopic data to securely identify 34 cluster members and 12 multiple images from 3 background sources. We measure the stellar velocity dispersions of 13 cluster galaxies, enabling an independent estimate of the contribution of the sub-halo mass component to the lens total mass. The projected total mass distribution of the lens cluster is best modelled with a single large-scale mass component, a galaxy-scale component, anchored by the MUSE kinematic information, and an external shear. The best-fit strong lensing model yields a root mean square separation between the model-predicted and observed positions of the multiple images of 0".29. When analysing the impact of systematic uncertainties, stemming from modelling assumptions and used observables, we find that the projected total mass profile, relative weight of the sub-halo mass component, and critical lines are consistent, within the statistical uncertainties. The predicted magnification and time delay values are, instead, more sensitive to the local details of the lens total mass distribution, and vary significantly among lens models that are similarly good at reproducing the observed multiple image positions. Due to its complex morphology, the low number of point-like multiple images, and current model degeneracies, it becomes clear that additional information (from the observed surface brightness distribution of lensed sources and the measured time delays) needs to be included in the modelling of SDSS J2222+2745 for accurate and precise cosmological measurements. The full MUSE secure spectroscopic catalogue presented in this work is made publicly available., Comment: 17 pages, 9 Figures, 5 Tables. Accepted for publication in Astronomy & Astrophysics. The full MUSE spectroscopic catalogue presented in this work is made publicly available at www.fe.infn.it/astro/lensing
Published: 2022
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32. Some comments on integrals involving the Dirac delta function

Author: Jayme Vaz Jr.
Subjects: Physics, QC1-999, distributions, value of a distribution at a point, Dirac delta function, General Physics and Astronomy, Education
Abstract: There are two different but equivalent ways of interpreting the integration of the Dirac delta function within the context of the theory of distributions. We discuss both of them and argue that the least known is the most suitable one for handling problems where integrals involving the Dirac delta function appear in physics and engineering. Examples are given to illustrate this point.
Published: 2022
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33. A measurement of Hubble's Constant using Fast Radio Bursts

Author: C W James, E M Ghosh, J X Prochaska, K W Bannister, S Bhandari, C K Day, A T Deller, M Glowacki, A C Gordon, K E Heintz, L Marnoch, S D Ryder, D R Scott, R M Shannon, and N Tejos
Subjects: High Energy Astrophysical Phenomena (astro-ph.HE), Cosmology and Nongalactic Astrophysics (astro-ph.CO), REDSHIFT, UNIVERSE, CONSTRAINTS, TRANSIENTS, FOS: Physical sciences, Astronomy and Astrophysics, fast radio bursts, FRB 121102, HOST GALAXY, DISPERSION, Space and Planetary Science, DISTRIBUTIONS, EVENT RATE COUNTS, cosmological parameters, Astrophysics - High Energy Astrophysical Phenomena, EMISSION, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We constrain the Hubble constant H$_0$ using Fast Radio Burst (FRB) observations from the Australian Square Kilometre Array Pathfinder (ASKAP) and Murriyang (Parkes) radio telescopes. We use the redshift-dispersion measure (`Macquart') relationship, accounting for the intrinsic luminosity function, cosmological gas distribution, population evolution, host galaxy contributions to the dispersion measure (DM$_{\rm host}$), and observational biases due to burst duration and telescope beamshape. Using an updated sample of 16 ASKAP FRBs detected by the Commensal Real-time ASKAP Fast Transients (CRAFT) Survey and localised to their host galaxies, and 60 unlocalised FRBs from Parkes and ASKAP, our best-fitting value of H$_0$ is calculated to be $73_{-8}^{+12}$ km s$^{-1}$ Mpc$^{-1}$. Uncertainties in FRB energetics and DM$_{\rm host}$ produce larger uncertainties in the inferred value of H$_0$ compared to previous FRB-based estimates. Using a prior on H$_0$ covering the 67--74 km s$^{-1}$ Mpc$^{-1}$ range, we estimate a median DM$_{\rm host} = 186_{-48}^{+59}$ km s$^{-1}$ Mpc$^{-1}$, exceeding previous estimates. We confirm that the FRB population evolves with redshift similarly to the star-formation rate. We use a Schechter luminosity function to constrain the maximum FRB energy to be $\log_{10} E_{\rm max}=41.26_{-0.22}^{+0.27}$ erg assuming a characteristic FRB emission bandwidth of 1 GHz at 1.3 GHz, and the cumulative luminosity index to be $\gamma=-0.95_{-0.15}^{+0.18}$. We demonstrate with a sample of 100 mock FRBs that H$_0$ can be measured with an uncertainty of $\pm 2.5$ km s$^{-1}$ Mpc$^{-1}$, demonstrating the potential for clarifying the Hubble tension with an upgraded ASKAP FRB search system. Last, we explore a range of sample and selection biases that affect FRB analyses., Comment: 21 pages, 19 figures, 6 tables, accepted by MNRAS, updated Table 5 and Figure 5
Published: 2022
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34. Super-short fission mode in fermium isotopes

Author: M. Albertsson, B. G. Carlsson, T. Døssing, P. Möller, J. Randrup, and S. Åberg
Subjects: NEUTRON-INDUCED FISSION, Nuclear Theory, MULTIPLICITY, MD-258, Molecular, MASS, SYSTEMATICS, Atomic, Nuclear & Particles Physics, Particle and Plasma Physics, SYMMETRIC FISSION, DISTRIBUTIONS, Nuclear, HEAVY, Nuclear Experiment, KINETIC-ENERGY
Abstract: The so-called super-short fission mode, in which a nucleus divides nearly symmetrically into two unusually energetic fragments, competes favorably with the standard asymmetric fission mode for spontaneous fission of a limited number of nuclei near 264Fm but it quickly fades away at finite excitations. We investigate the energy-dependent competition between those two fission modes for even fermium isotopes from 254Fm to 268Fm, using the Metropolis method to simulate the strongly damped fission dynamics being driven by shape- and energy-dependent level densities. The origin of the super-short mode is discussed and its effects on the fragment mass distribution, the total fragment kinetic energy, and the neutron multiplicity are calculated. Generally good agreement with the available data is obtained.
Published: 2021
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35. Asymptotic theory for the inference of the latent trawl model for extreme values

Author: Almut Veraart and Valentin Courgeau
Subjects: Statistics and Probability, Asymptotic analysis, EXCEEDANCES, Statistics & Probability, central limit theorem, ROBUST, Inference, Method of moments (probability theory), trawl process, Statistical inference, Applied mathematics, DISTRIBUTIONS, GMM, Extreme value theory, Mathematics, Central limit theorem, Science & Technology, generalized Pareto distribution, 0104 Statistics, generalized method of moments, TIME, Delta method, Autocovariance, Physical Sciences, Statistics, Probability and Uncertainty, pairwise likelihood estimation
Abstract: This article develops statistical inference methods and their asymptotic theory for the so-called latent trawl model for extremes, which captures serial dependence in the time series of exceedances above a threshold. We review two inference methods based on the pairwise likelihood (PL) approach, a classical single-stage and a two-stage estimation; in the latter, we first estimate the marginal parameters, then the parameters describing the serial dependence. We derive the asymptotic theory in both cases and find that the asymptotic behaviour and goodness-of-fit are similar to the two-stage method being slightly preferred in our empirical work. However, we also show that PL-based approaches tend to underestimate the serial dependence in the extremes, and we propose a generalised method of moments procedure (both a single-stage and a two-stage procedure) based on autocovariance matching to overcome this shortcoming. We prove the strong mixing property of our model and provide central limit theorems for the four inference approaches. For single-stage approaches, the convergence is shown in the sense of weakly approaching sequences of distributions for strongly mixing sequences. For the two-stage strategies, we provide an asymptotic variance for the serial parameter which takes the estimation error arising from the first stage into account. In an empirical illustration using London air pollution data featuring six pollutants, we find that the two-stage autocovariance matching scheme seems to be performing best.
Published: 2021

36. Further support for a trio of mass-to-light deviations in Abell 370: free-form grale lens inversion using BUFFALO strong lensing data

Author: Agniva Ghosh, Liliya L R Williams, Jori Liesenborgs, Ana Acebron, Mathilde Jauzac, Anton M Koekemoer, Guillaume Mahler, Anna Niemiec, Charles Steinhardt, Andreas L Faisst, David Lagattuta, Priyamvada Natarajan, Ghosh, Agniva, Williams, Liliya L.R., LIESENBORGS, Jori, Acebron, Ana, Jauzac, Mathilde, Koekemoer, Anton M., Mahler, Guillaume, Niemiec, Ana, Steinhardt, Charles, Faisst, Andreas L., Lagattuta, David, and Priyamvada, Natarajan
Subjects: Cosmology and Nongalactic Astrophysics (astro-ph.CO), NONPARAMETRIC INVERSION, DEGENERACIES, MODELS, MAGNIFICATION, gravitational lensing: strong, FOS: Physical sciences, Astronomy and Astrophysics, clusters: individual: Abell 370 [galaxies], Astrophysics::Cosmology and Extragalactic Astrophysics, HUBBLE-FRONTIER-FIELDS, GALAXIES, Space and Planetary Science, LUMINOSITY FUNCTION, strong [gravitational lensing], DARK-MATTER, DISTRIBUTIONS, DISTANT CLUSTER, Astrophysics::Galaxy Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, galaxies: clusters: individual: Abell 370
Abstract: We use the Beyond Ultra-deep Frontier Fields and Legacy Observations (BUFFALO) strong lensing image catalog of the merging galaxy cluster Abell 370 to obtain a mass model using the free-form lens inversion algorithm GRALE. The improvement of the strong lensing data quality results in a lens plane rms of only 0.45 arcsec, about a factor of two lower than that of our existing HFF v4 reconstruction. We attribute the improvement to spectroscopic data and use of the full reprocessed HST mosaics. In our reconstructed mass model, we found indications of three distinct mass features in Abell 370: (i) a $\sim 35$ kpc offset between the northern BCG and the nearest mass peak, (ii) a $\sim 100$ kpc mass concentration of roughly critical density $\sim 250$ kpc east of the main cluster, and (iii) a probable filament-like structure passing N-S through the cluster. While (i) is present in some form in most publicly available reconstructions spanning the range of modeling techniques: parametric, hybrid, and free-form, (ii) and (iii) are recovered by only about half of the reconstructions. We tested our hypothesis on the presence of the filament-like structure by creating a synthetic cluster - Irtysh IIIc - mocking the situation of a cluster with external mass. We also computed the source plane magnification distributions. Using them we estimated the probabilities of magnifications in the source plane, and scrutinized their redshift dependence. Finally, we explored the lensing effects of Abell 370 on the luminosity functions of sources at $z_s=9.0$, finding it consistent with published results., Comment: 16 pages, 13 figures
Published: 2021
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37. A Look at the Primary Order Preserving Properties of Stochastic Orders: Theorems, Counterexamples and Applications in Cognitive Psychology

Author: Mohsen Soltanifar
Subjects: General Mathematics, Computer Science (miscellaneous), Engineering (miscellaneous), distributions, Ex-Gaussian, Ex-Wald, inequalities, reaction times, stochastic orders, Wald
Abstract: In this paper, we prove that for a set of ten univariate stochastic orders including the usual order, a univariate stochastic order preserves either both, one or none of additivity and multiplication properties over the vector space of real-valued random variables. Then, classifying participant’s quickness in a mental chronometry trial to “weakly faster” and “strongly faster”, we use the above results for the usual stochastic order to establish necessary and sufficient conditions for a participant to be strongly faster than the other in terms of the fitted Wald, Exponentially modified Wald(ExW), and Exponentially modified Gaussian(ExG) distributional parameters. This research field remains uncultivated for other univariate stochastic orders and in several directions.
Published: 2022
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38. Consistent predator-prey biomass scaling in complex food webs

Author: Daniel M. Perkins, Ian A. Hatton, Benoit Gauzens, Andrew D. Barnes, David Ott, Benjamin Rosenbaum, Catarina Vinagre, and Ulrich Brose
Subjects: Metabolic theory, Multidisciplinary, Food Chain, Ecology, General Physics and Astronomy, Fresh Water, General Chemistry, General Biochemistry, Genetics and Molecular Biology, Predatory Behavior, Animals, Distributions, Biomass, Patterns, Ecosystem, Pyramids
Abstract: The ratio of predator-to-prey biomass is a key element in food webs. Here, the authors report a unified analysis of predator-prey biomass scaling in complex food webs, finding general patterns of sub-linear scaling across ecosystems and levels of organization. The ratio of predator-to-prey biomass is a key element of trophic structure that is typically investigated from a food chain perspective, ignoring channels of energy transfer (e.g. omnivory) that may govern community structure. Here, we address this shortcoming by characterising the biomass structure of 141 freshwater, marine and terrestrial food webs, spanning a broad gradient in community biomass. We test whether sub-linear scaling between predator and prey biomass (a potential signal of density-dependent processes) emerges within ecosystem types and across levels of biological organisation. We find a consistent, sub-linear scaling pattern whereby predator biomass scales with the total biomass of their prey with a near 3/4-power exponent within food webs - i.e. more prey biomass supports proportionally less predator biomass. Across food webs, a similar sub-linear scaling pattern emerges between total predator biomass and the combined biomass of all prey within a food web. These general patterns in trophic structure are compatible with a systematic form of density dependence that holds among complex feeding interactions across levels of organization, irrespective of ecosystem type. info:eu-repo/semantics/publishedVersion
Published: 2021

39. Optimal application of fluid viscous dampers in tall buildings incorporating integrated damping systems

Author: Ahmed Y. Elghazouli and Miguel Martinez-Paneda
Subjects: VIBRATION CONTROL, Technology, Engineering, Civil, Computer science, fluid viscous dampers, multistory structures, mass dampers, Civil Engineering, 0905 Civil Engineering, tall buildings, Engineering, Architecture, damper arrangement, DISTRIBUTIONS, CONTROLLERS, ALGORITHM, Civil and Structural Engineering, dynamic response, Science & Technology, Viscous damper, business.industry, Building and Construction, Structural engineering, PERFORMANCE, OPTIMAL-DESIGN, damping systems, FRAMED STRUCTURES, PLACEMENT, Construction & Building Technology, passive damping, business, COEFFICIENTS
Abstract: This paper examines the detailed performance of an Integrated-Damping-System (IDS) approach which was recently introduced to provide large damping levels by enabling two parts of a building to move independently through a parallel arrangement of springs and fluid viscous dampers. Extensive assessments into the characteristics and distribution of constituent dampers are illustrated through the dynamic response of a typical 300m central-core building. Besides examining the system performance under typical wind conditions and selected seismic excitations, five damper placement methods are assessed for various linear and nonlinear damper exponents. It is shown that intermediate exponents provide the best overall response. However, when the design targets a particular damping, deformation or acceleration related performance parameter, specific combinations of damper exponent and distribution can result in an optimal application. Most importantly, due to the underlying IDS nature, which acts as an inherent large-mass damper, the findings show that the overall performance is not highly sensitive to the damper placement and does not necessitate the use of an advanced distribution. Whilst specific placements can be adopted to refine targeted performance aspects where necessary, simple and practical uniform or stiffness proportional arrangements can be consistently employed with the IDS to provide a highly effective solution.
Published: 2021

40. Likelihood theory for the Graph Ornstein-Uhlenbeck process

Author: Valentin Courgeau and Almut E. D. Veraart
Subjects: Statistics and Probability, 62F12, 62F86, 62-09, Statistics & Probability, Central limit theorem, Adaptive Lasso, MODELS, Mathematics - Statistics Theory, Ornstein-Uhlenbeck processes, Statistics Theory (math.ST), VOLATILITY MATRIX ESTIMATION, Lévy process, FOS: Mathematics, DISTRIBUTIONS, Uniqueness, COVARIANCE, Mathematics, Discrete mathematics, Science & Technology, Stochastic volatility, 0104 Statistics, Estimator, Ornstein–Uhlenbeck process, Directed graph, DRIVEN, Continuous-time likelihood, ERGODICITY, STATISTICS, Multivariate Levy process, Graphical modelling, Physical Sciences, Maximum likelihood estimator, Graph (abstract data type)
Abstract: We consider the problem of modelling restricted interactions between continuously-observed time series as given by a known static graph (or network) structure. For this purpose, we define a parametric multivariate Graph Ornstein-Uhlenbeck (GrOU) process driven by a general \Levy process to study the momentum and network effects amongst nodes. We distinguish the cases of the \emph{network-level} GrOU and the \emph{node-level} GrOU processes where the latter allows for the directed graph edges to be node-dependent. Given general likelihood frameworks, we derive maximum likelihood estimators and their usual properties (existence, uniqueness, consistency and efficiency). To quantify the estimation uncertainty, we present two novel central limit theorems under general assumptions with closed-form covariance matrices as the time horizon goes to infinity. Finally, we extend the \levy-driven case to include a stochastic volatility modulation term and show that the central limit theorems still hold.
Published: 2021

41. Two-particle azimuthal correlations in photonuclear ultraperipheral Pb+Pb collisions at 5.02 TeV with ATLAS

Author: Aad, Georges, Abbott, Braden Keim, Abbott, Brad, Abbott, Dale, Abed Abud, Adam, Abeling, Kira, Abhayasinghe, Deshan Kavishka, Abidi, Haider, Abouzeid, Hass, Abouzeid, Ossama, Abraham, Nicola Louise, Abramowicz, Halina, Abreu, Henso, Abulaiti, Yiming, Abusleme, Angel, Acharya, Bobby Samir, Achkar, Baida, Adam, Lennart, Adam Bourdarios, Claire, Adamczyk, Leszek, Adamek, Lukas, Adelman, Jahred, Adiguzel, Aytul, Adorni Braccesi Chiassi, Sofia, Adye, Tim, Affolder, A.A., Affolder, Tony, Afik, Yoav, Agapopoulou, Christina, Agaras, Merve Nazlim, Aggarwal, Anamika, Agheorghiesei, Catalin, Aguilar Saavedra, Juan Antonio, Ahmad, Ammara, Ahmadov, Faig, Ahmed, Waleed Syed, Ai, Xiaocong, Aielli, Giulio, Akatsuka, Shunichi, Akbiyik, Melike, Akesson, Torsten, Akilli, Ece, Akimov, Andrei, Al Khoury, Konie, Alberghi, Gian Luigi, Albert, Justin, Alconada, Josefina, Alderweireldt, Sara, Aleksa, Martin, Alexandrov, Igor, Alexa, Calin, Alexopoulos, Theodoros, Alfonsi, Alice, Alfonsi, Fabrizio, Alhroob, Muhammad, Ali, Babar, Ali, Shahzad, Aliev, Malik, Alimonti, Gianluca, Allaire, Corentin, Allbrooke, Benedict, Allport, Philip Patrick, Aloisio, Alberto, Alonso, Francisco, Alpigiani, Cristiano, Alunno Camelia, Elio, Alvarez Estevez, Manuel, Alviggi, Mariagrazia, Do Amaral Coutinho, Yara, Ambler, Alessandro, Ambroz, Luca, Amelung, Christoph, Amidei, Dante, Amor dos Santos, Susana Patricia, Amoroso, Simone, Amrouche, Cherifa Sabrina, Anastopoulos, Christos, Andari, Nansi, Andeen, Timothy Robert, Anders, John Kenneth, Andrean, Stefio Yosse, Andreazza, Attilio, Andrei, Victor, Anelli, Christopher Ryan, Angelidakis, Stylianos, Angerami, Aaron, Anisenkov, Alexey, Annovi, Alberto, Antel, Claire, Anthony, Matthew Thomas, Antipov, Egor, Antonelli, Mario, Antrim, Daniel Joseph, Anulli, Fabio, Aoki, Masato, Aparisi Pozo, Javier Alberto, Aparo, Marco, Aperio Bella, Ludovica, Aranzabal Barrio, Nordin, Araujo Ferraz, Victor, Arcangeletti, Chiara, Arce, Ayana Tamu, Arguin, Jean-Francois, Argyropoulos, Spyros, Argyropoulos, Spyridon, Arling, Jan-Hendrik, Armbruster, Aaron James, Armstrong, Alexander, Arnaez, Olivier, Arnold, Hannah, Arrubarrena Tame, Zulit Paola, Artoni, Giacomo, Asada, Haruka, Asai, Kanae, Asai, Shoji, Asbah, Nedaa Alexandra, Asimakopoulou, Eleni Myrto, Asquith, Lily, Assahsah, Jihad, Assamagan, Ketevi Adikle, Astalos, Robert, Atkin, Ryan Justin, Atkinson, Markus Julian, Atlay, Naim Bora, Atmani, Hicham, Atmasiddha, Prachi, Augsten, Kamil, Austrup, Volker Andreas, Avolio, Giuseppe, Ayoub, Mohamad Kassem, Azuelos, Georges, Babal, Dominik, Bachacou, Henri, Bachas, Dinos, Bachas, Konstantinos, Backman, Karl Filip, Bagnaia, Paolo, Bahrasemani, H., Bahmani, Marzieh, Bahrasemani, Sina, Bailey, Adam, Bailey, Virginia, Baines, John, Bakalis, Christos, Baker, Keith, Bakker, Pepijn Johannes, Bakos, Evelin, Bakshi Gupta, Debottam, Balaji, Shyam, Balasubramanian, Rahul, Baldin, Evgenii, Balek, Petr, Balli, Fabrice, Balunas, William Keaton, Balz, Johannes, Banas, Elzbieta, Bandieramonte, Marilena, Bandyopadhyay, Anjishnu, Barak, Liron, Barbe, William Mickael, Barberio, Elisabetta, Barberis, Dario, Barbero, Marlon Benoit, Barbour, Gregory, Barends, Kevin Nicholas, Barillari, Teresa, Barisits, Martin, Barkeloo, Jason Tyler Colt, Barklow, Tim, Barklow, Timothy, Barnett, Bruce M, Barnett, Michael, Barnovska-Blenessy, Z., Baroncelli, Toni, Baroncelli, Antonio, Barone, Gaetano, Barr, Alan, Barranco Navarro, Laura, Barreiro Alonso, Fernando, Barreiro Guimaraes da Costa, Joao, Barron, Uriel, Barsov, Sergey, Bartels, Falk, Bartoldus, Rainer, Bartolini, Giovanni, Barton, Adam Edward, Bartos, Pavol, Basalaev, Artem, Basan, Alexander, Bassalat, Ahmed, Basso, Matthew Joseph, Basson, Candice Ruth, Bates, Richard, Batlamous, Souad, Batley, Richard, Batool, Binish, Battaglia, Marco, Bauce, Matteo, Bauer, Florian, Bauer, Patrick, Bawa, Harinder Singh, Bayirli, Arif, Beacham, James, Beau, Tristan, Beauchemin, Pierre-Hugues, Becherer, Fabian, Bechtle, Philip, Beck, Hans Peter, Becker, Kathrin, Becot, Cyril Pascal, Beddall, Andrew, Bednyakov, Vadim, Bee, Chris, Bee, Christopher, Beermann, Thomas, Begalli, Marcia, Begel, Michael, Behera, Arabinda, Behr, Janna Katharina, Beirer, Joshua Falco, Beisiegel, Florian, Belfkir, Mohamed, Bella, Gideon, Bellagamba, Lorenzo, Bellerive, Alain, Bellos, Panagiotis, Beloborodov, Konstantin, Belotskiy, Konstantin, Belyaev, Nikita, Benchekroun, Driss, Benekos, Nectarios, Benhammou, Yan, Benjamin, Doug, Benjamin, Douglas, Benoit, Mathieu, Bensinger, Jim, Bensinger, James, Bentvelsen, Stan, Beresford, Lydia Audrey, Beretta, Matteo Mario, Berge, David, Bergeaas Kuutmann, Elin, Berger, Nicolas, Bergmann, Benedikt Ludwig, Bergsten, Laura Jean, Beringer, Juerg, Berlendis, Simon, Bernardi, Gregorio, Bernius, Catrin, Bernlochner, Florian Urs, Berry, Tracey, Berta, Peter, Berthold, Anne-Sophie, Bertram, Iain, Bessidskaia Bylund, Olga, Bethke, Siegfried, Betti, Alessandra, Bevan, Adrian, Bhatta, Somadutta, Bhattacharya, Deb Sankar, Bhattarai, Prajita, Bhopatkar, Vallary Shashikant, Bi, Runyu, Bianchi, Riccardo Maria, Biebel, Otmar, Bielski, Rafal, Bierwagen, Katharina, Biesuz, Nicolo Vladi, Biglietti, Michela, Billoud, Thomas, Bindi, Marcello, Bingul, Ahmet, Bini, Cesare, Biondi, Silvia, Birch-Sykes, Callum Jacob, Birman, Mattias, Bisanz, Tobias, Biswal, Jyoti Prakash, Biswas, Diptaparna, Bitadze, Alexander, Bittrich, Carsten, Bjoerke, Kristian, Blazek, Tomas, Bloch, Ingo, Blocker, Craig, Blue, Andrew James, Blumenschein, Ulla, Blumenschein, Ulrike, Bobbink, Gerjan, Bobrovnikov, Viktor, Bogavac, Danijela, Bogdanchikov, Alexander, Bohm, Christian, Boisvert, Veronique, Bokan, Petar, Bold, Tomasz, Bomben, Marco, Bona, Marcella, Bonilla, Johan Sebastian, Boonekamp, Maarten, Booth, Callum Dale, Borbely, Albert Gyorgy, Borecka-Bielska, Hanna Maria, Borgna, Lucas Santiago, Borissov, Guennadi, Bortoletto, Daniela, Boscherini, Davide, Fernandez-Bosman, Martine, Bossio, Jonathan, Bouaouda, Khalil, Boudreau, Joseph, Bouhova-Thacker, Eva, Bouhova-Thacker, Evelina Vassileva, Boumediene, Djamel Eddine, Bouquet, Romain, Boveia, Antonio, Boyd, Jamie, Boyd, James, Boye, Diallo, Boyko, Igor, Bozson, Adam, Bracinik, Juraj, Brahimi, Nihal, Brandt, Gerhard Immanuel, Brandt, Oleg, Braren, Frued Erik, Brau, Benjamin Paul, Brau, Jim, Breaden Madden, Will, Brau, James, Breaden Madden, William Dmitri, Brendlinger, Kurt, Schimmel Brener, Roy, Brenner, Lydia, Brenner, Richard, Bressler, Shikma, Brickwedde, Bernard, Briglin, Daniel Lawrence, Britton, David, Britton, Dave, Britzger, Daniel Andreas, Brock, Ian, Brock, Raymond, Brooijmans, Gustaaf, Brooks, William King, Brost, Elizabeth, Bruckman de Renstrom, Pawel, Bruers, Ben, Bruncko, Dusan, Bruni, Alessia, Bruni, Graziano, Bruschi, Marco, Bruscino, Nello, Bryngemark, Lene Kristian, Buanes, Trygve, Buat, Quentin, Buchholz, Peter, Buckley, Andy, Buckley, Andrew, Budagov, Ioulian, Bugge, Magnar Kopangen, Bulekov, Oleg, Bullard, Brendon, Burch, Tyler James, Burdin, Sergey, Burgard, Carsten Daniel, Burger, Angela Maria, Burghgrave, Blake Oliver, Burr, Jon, Burr, Jonathan Thomas, Burton, Charles, Burzynski, Jackson Carl, Buescher, Volker, Buschmann, Eric, Bussey, Peter John, Butler, John Mark, Buttar, Craig, Butterworth, Jonathan, Buttinger, Will, Buttinger, William, Buxo Vazquez, Carlos Josue, Buzykaev, Alexey, Buzykaev, Aleksey, Cabras, Grazia, Cabrera Urban, Susana, Caforio, Davide, Cai, Huacheng, Cairo, Valentina, Cakir, Orhan, Calace, Noemi, Calafiura, Paolo, Calderini, Giovanni, Calfayan, Philippe, Callea, Giuseppe, Caloba, Luiz, Caltabiano, Alessandro, Calvente Lopez, Sergio, Calvet, David, Calvet, Samuel, Calvet, Thomas Philippe, Calvetti, Milene, Camacho Toro, Reina Coromoto, Camarda, Stefano, Camarero Munoz, Daniel, Camarri, Paolo, Camerlingo, Maria Teresa, Cameron, David, Camincher, Clement, Campanelli, Mario, Camplani, Alessandra, Canale, Vincenzo, Canesse, Auriane, Bret Cano, Marc, Cantero Garcia, Josu, Cao, Yumeng, Capua, Marcella, Cardarelli, Roberto, Cardillo, Fabio, Carducci, Giovandomenico, Carli, Tancredi, Carlino, Giampaolo, Carlson, Ben, Carlson, Benjamin Taylor, Carlson, Evan Michael, Carminati, Leonardo, Carnesale, Maria, Carney, Rebecca, Caron, Sascha, Carquin Lopez, Edson, Carra, Sonia, Carratta, Giuseppe, Carter, Joseph, Carter, Thomas Michael, Casado Lechuga, Pilar, Casado, Maria Pilar, Casha, Albert Francis, Castiglia, Emma Grace, Castillo, Florencia Luciana, Castillo Garcia, Lucia, Castillo Gimenez, Victoria, Castro, Nuno, Catinaccio, Andrea, Catmore, James, Cattai, Ariella, Cavaliere, Viviana, Cavasinni, Vincenzo, Celebi, Emre, Celli, Federico, Cerny, Karel, Santiago Cerqueira, Augusto, Cerri, Alex, Cerri, Alessandro, Cerrito, Lucio, Cerutti, Fabio, Cervelli, Alberto, Cetin, Serkant, Chadi, Zakaria, Chakraborty, Dhiman, Chala, Mikael, Chan, Jay, Chan, Terry Ws, Chan, Wing Sheung, Chan, Wai Yuen, Chapman, John Derek, Chargeishvili, Bakar, Charlton, Dave, Charman, Thomas Paul, 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Sousa, Mario Jose, da Fonseca Pinto, Joao Victor, da Via, Cinzia, Dabrowski, Wladyslaw, Dado, Tomas, Dahbi, Salah-Eddine, Dai, Tiesheng, Dallapiccola, Carlo, Dam, Mogens, d'Amen, Gabriele, d'Amico, Valerio, Damp, Johannes Frederic, Dandoy, Jeff, Daneri, Maria Florencia, Danninger, Matthias, Dao, Valerio, Darbo, Nanni, Dattagupta, Aparajita, d'Auria, Saverio, David, Claire, Davidek, Tomas, Davis, Douglas Raymond, Dawson, Ian, De, Kaushik, de Asmundis, Riccardo, de Beurs, Marcus, de Castro, Stefano, de Groot, Nicolo, de Jong, Paul, de la Torre Perez, Hector, de Maria, Antonio, de Pedis, Daniele, de Salvo, Alessandro, de Sanctis, Umberto, de Santis, Maurizio, de Santo, Antonella, de Vivie de Regie, Jean-Baptiste, Dedovich, Dmitri, Degens, Jordy, Deiana, Allison Mccarn, del Peso, Jose, Delabat Diaz, Yasiel, Deliot, Frederic, Delitzsch, Chris Malena, Della Pietra, Massimo, Della Volpe, Domenico, Dell'Acqua, Andrea, Dell'Asta, Lidia, Delmastro, Marco, Delporte, Charles Eliaz, Delsart, Pierre 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Andrei Alexandru, Gee, Carolyn, Gee, Norman, Geisen, Jannik, Geisen, Marc, Gemme, Claudia, Genest, Marie-Helene, Geng, Cong, Gentile, Simonetta, George, Simon, Geralis, Theodoros, Gerlach, Lino Oscar, Gessinger-Befurt, Paul, Gessner, Gregor, Ghasemi Bostanabad, Meisam, Ghneimat, Mazuza, Ghosh, Aishik, Ghosh, Anindya, Giacobbe, Benedetto, Giagu, Stefano, Giangiacomi, Nico, Giannetti, Paola, Giannini, Antonio, Gibson, Stephen, Gignac, Matthew, Gil, Damian Tomasz, Gilbert, Benjamin Jacob, Gillberg, Dag, Gilles, Geoffrey, Gillwald, Nils, Gingrich, Douglas, Giordani, Mariopaolo, Gingrich, Doug, Giordani, Mapo, Giraud, Pierre-Francois, Giugliarelli, Gilberto, Giugni, Danilo, Giuli, Francesco, Gkaitatzis, Stamatios, Gkialas, Ioannis, Gkougkousis, Evangelos, Gkougkousis, Vagelis, Gkountoumis, Panagiotis, Gladilin, Leonid, Glasman, Claudia, Gledhill, Galen Rhodes, Gnesi, Ivan, Goblirsch-Kolb, Maximilian Emanuel, Godin, Dominique, Goldfarb, Steven, Golling, Tobias, Golubkov, Dmitry, da Silva Gomes, Agostinho, Goncalves Gama, Rafael, Morais Silva Goncalo, Ricardo Jose, Gonella, Giulia, Gonella, Laura, Gongadze, Alexi, Gonnella, Francesco, Gonski, Julia Lynne, Gonzalez de la Hoz, Santiago, Gonzalez Fernandez, Sergio, Gonzalez Lopez, Ricardo, Gonzalez Renteria, Cesar, Gonzalez Suarez, Rebeca, Gonzalez Sevilla, Sergio, Gonzalvo Rodriguez, Galo Rafael, Goossens, Luc, Gorasia, Nandish Arjan, Gorbounov, Petr, Gordon, Howard, Gorini, Benedetto, Gorini, Edoardo, Gorisek, Andrej, Goshaw, Alfred, Goshaw, Al, Gostkin, Mikhail, Gottardo, Carlo Alberto, Gouighri, Mohamed, Goussiou, Anna, Govender, Nicolin, Goy, Corinne, Grabowska-Bold, Iwona, Gramstad, Eirik, Grancagnolo, Sergio, Grandi, Mario, Grachev, Vadim, Gravila, Paul, Gravili, Francesco Giuseppe, Gray, Chloe, Gray, Heather, Grefe, Christian, Gregor, Ingrid, Grenier, Philippe, Grevtsov, Kirill, Grieco, Chiara, Grieser, Nathan Allen, Grillo, Alexander, Guest, Daniel, Grillo, Alex, Grimm, Kathryn, Grinstein, Sebastian, Grivaz, 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Jonathan, Janas, Krzysztof, Janus, Piotr Andrzej, Jarlskog, Goran, Jaspan, Adam Elliott, Javadov, Namig, Javurek, Tomas, Javurkova, Martina, Jeanneau, Fabien, Jeanty, Laura, Jejelava, Juansher, Jenni, Peter, Jezequel, Stephane, Jia, Jiangyong, Jia, Zihang, Jiang, Yi, Jiggins, Stephen, Jimenez Morales, Fabricio Andres, Jimenez Pena, Javier, Jin, Shan, Jinaru, Adam, Jinnouchi, Osamu, Jivan, Harshna, Johansson, Per Daniel Conny, Johns, Kenneth, Johnson, Christian, Jones, Eleanor, Jones, R.W.L., Jones, T.J., Jovicevic, Jelena, Ju, Xiangyang, Junggeburth, Johannes Josef, Juste Rozas, Aurelio, Kaczmarska, Anna, Kado, Marumi, Kagan, Harris, Kagan, Michael Aaron, Kahn, Alan Mathew, Kahra, Christian, Kaji, Toshiaki, Kajomovitz Must, Enrique, Kartvelishvili, Vakhtang, Kaya, Fikriye Idil, Kalderon, Will, Kalderon, Charles William, Kaluza, Adam, Kamenshchikov, Andrey, Kaneda, Michiru, Kang, Nathan Jihoon, Kang, Shuaiyan, Kano, Yuya, Kanzaki, Junichi, Kar, Deepak, Karava, Kla, Kareem, Mohammad, 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Kvam, Audrey Katherine, Kvita, Jiri, Kwan, Tony, Lacasta Llacer, Carlos, Lacava, Francesco, Lack, David Philip John, Lacker, Heiko Markus, Lacour, Didier, Ladygin, Evgueni, Lafaye, Remi, Laforge, Bertrand, Lagouri, Theodota, Lai, Stanley, Lai, Stan, Lakomiec, Inga Katarzyna, Lambert, Joseph Earl, Lammers, Sabine Wedam, Lampl, Walter, Lampoudis, Christos, Lancon, Eric Christian, Landgraf, Ulrich, Landon, Murrough, Lang, Valerie, Lange, Joern, Langenberg, Robert Johannes, Lankford, Andrew James, Lanni, Francesco, Lantzsch, Kerstin, Lanza, Agostino, Lapertosa, Alessandro, Laporte, Jean-Francois, Lari, Tommaso, Lasagni Manghi, Federico, Lassnig, Mario, Latonova, Vera, Lau, Tak Shun, Laudrain, Antoine, Laurier, Alexandre, Lavorgna, Marco, Lawlor, Sean Dean, Lazzaroni, Massimo, Le, Brian, Lebedev, Alexandre, Leblanc, Matthew Edgar, Lecompte, Thomas, Leblanc, Matt, Le Compte, Tom, Ledroit, Fabienne, Lee, Ava Chloe Audrey, Lee, Claire, Lee, Graham Richard, Lee, Lawrence, Lee, Shih-Chang, Lee, Songkyo, Leeuw, Lerothodi Leonard, Lefebvre, Benoit, Lefebvre, Helena, Lefebvre, Michel, Leggett, Charles, Lehmann, Konstantin, Lehmann, Niklaus, Lehmann Miotto, Giovanna, Leight, William Axel, Leisos, Antonios, Lisboa Leite, Marco, Leitgeb, Clara Elisabeth, Leitner, Rupert, Leney, Katharine, Lenz, Tatjana, Leone, Sandra, Leonidopoulos, Christos, Leopold, Alexander, Leroy, Claude, Les, Robert, Lester, Christopher, Levchenko, Mikhail, Leveque, Jessica, Levin, Daniel, Levin, Dan, Levinson, Lorne, Lewis, Daniel James, Li, Boyang, Li, Bing, Li, Changqiao, Li, Fan, Li, Heng, Li, Haifeng, Li, Jing, Li, Ke, Li, Liang, Li, Mengran, Li, Quanyin, Li, Shu, Li, Xingguo, Li, Yichen, Li, Zhi, Li, Zhiying, Li, Zhelun, Li, Zhiyuan, Liang, Zhijun, Liberatore, Marianna, Liberti, Barbara, Lie, Ki, Lin, Chiao-Ying, Lin, Kuan-Yu, Linck, Rebecca, Lindley, Rachel Elizabeth, Lindon, Jack, Linss, Arthur, Lionti, Anthony, Lipeles, Elliot, Lipniacka, Anna, Liss, Tony, Liss, Anthony Michael, Lister, Alison, 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Departamento de Física Teórica, ATLAS (IHEF, IoP, FNWI), Other Research IHEF (IoP, FNWI), Aad, G., Abbott, B., Abbott, D. C., Abed Abud, A., Abeling, K., Abhayasinghe, D. K., Abidi, S. H., Abouzeid, O. S., Abraham, N. L., Abramowicz, H., Abreu, H., Abulaiti, Y., Abusleme Hoffman, A. C., Acharya, B. S., Achkar, B., Adam, L., Adam Bourdarios, C., Adamczyk, L., Adamek, L., Adelman, J., Adiguzel, A., Adorni, S., Adye, T., Affolder, A. A., Afik, Y., Agapopoulou, C., Agaras, M. N., Aggarwal, A., Agheorghiesei, C., Aguilar-Saavedra, J. A., Ahmad, A., Ahmadov, F., Ahmed, W. S., Ai, X., Aielli, G., Akatsuka, S., Akbiyik, M., Akesson, T. P. A., Akilli, E., Akimov, A. V., Al Khoury, K., Alberghi, G. L., Albert, J., Alconada Verzini, M. J., Alderweireldt, S., Aleksa, M., Aleksandrov, I. N., Alexa, C., Alexopoulos, T., Alfonsi, A., Alfonsi, F., Alhroob, M., Ali, B., Ali, S., Aliev, M., Alimonti, G., Allaire, C., Allbrooke, B. M. M., Allport, P. P., Aloisio, A., Alonso, F., Alpigiani, C., Alunno Camelia, E., Alvarez Estevez, M., Alviggi, M. G., Amaral Coutinho, Y., Ambler, A., Ambroz, L., Amelung, C., Amidei, D., Amor Dos Santos, S. P., Amoroso, S., Amrouche, C. S., Anastopoulos, C., Andari, N., Andeen, T., Anders, J. K., Andrean, S. Y., Andreazza, A., Andrei, V., Anelli, C. R., Angelidakis, S., Angerami, A., Anisenkov, A. V., Annovi, A., Antel, C., Anthony, M. T., Antipov, E., Antonelli, M., Antrim, D. J. A., Anulli, F., Aoki, M., Aparisi Pozo, J. A., Aparo, M. A., Aperio Bella, L., Aranzabal, N., Araujo Ferraz, V., Arcangeletti, C., Arce, A. T. H., Arguin, J. -F., Argyropoulos, S., Arling, J. -H., Armbruster, A. J., Armstrong, A., Arnaez, O., Arnold, H., Arrubarrena Tame, Z. P., Artoni, G., Asada, H., Asai, K., Asai, S., Asbah, N. A., Asimakopoulou, E. M., Asquith, L., Assahsah, J., Assamagan, K., Astalos, R., Atkin, R. J., Atkinson, M., Atlay, N. B., Atmani, H., Atmasiddha, P. A., Augsten, K., Austrup, V. A., Avolio, G., Ayoub, M. K., Azuelos, G., Babal, D., Bachacou, H., Bachas, K., Backman, F., Bagnaia, P., Bahrasemani, H., Bailey, A. J., Bailey, V. R., Baines, J. T., Bakalis, C., Baker, O. K., Bakker, P. J., Bakos, E., Bakshi Gupta, D., Balaji, S., Balasubramanian, R., Baldin, E. M., Balek, P., Balli, F., Balunas, W. K., Balz, J., Banas, E., Bandieramonte, M., Bandyopadhyay, A., Barak, L., Barbe, W. M., Barberio, E. L., Barberis, D., Barbero, M., Barbour, G., Barends, K. N., Barillari, T., Barisits, M. -S., Barkeloo, J., Barklow, T., Barnett, B. M., Barnett, R. M., Barnovska-Blenessy, Z., Baroncelli, A., Barone, G., Barr, A. J., Barranco Navarro, L., Barreiro, F., Barreiro Guimaraes Da Costa, J., Barron, U., Barsov, S., Bartels, F., Bartoldus, R., Bartolini, G., Barton, A. E., Bartos, P., Basalaev, A., Basan, A., Bassalat, A., Basso, M. J., Basson, C. R., Bates, R. L., Batlamous, S., Batley, J. R., Batool, B., Battaglia, M., Bauce, M., Bauer, F., Bauer, P., Bawa, H. S., Bayirli, A., Beacham, J. B., Beau, T., Beauchemin, P. H., Becherer, F., Bechtle, P., Beck, H. P., Becker, K., Becot, C., Beddall, A. J., Bednyakov, V. A., Bee, C. P., Beermann, T. A., Begalli, M., Begel, M., Behera, A., Behr, J. K., Beirer, J. F., Beisiegel, F., Belfkir, M., Bella, G., Bellagamba, L., Bellerive, A., Bellos, P., Beloborodov, K., Belotskiy, K., Belyaev, N. L., Benchekroun, D., Benekos, N., Benhammou, Y., Benjamin, D. P., Benoit, M., Bensinger, J. R., Bentvelsen, S., Beresford, L., Beretta, M., Berge, D., Bergeaas Kuutmann, E., Berger, N., Bergmann, B., Bergsten, L. J., Beringer, J., Berlendis, S., Bernardi, G., Bernius, C., Bernlochner, F. U., Berry, T., Berta, P., Berthold, A., Bertram, I. A., Bessidskaia Bylund, O., Bethke, S., Betti, A., Bevan, A. J., Bhatta, S., Bhattacharya, D. S., Bhattarai, P., Bhopatkar, V. S., Bi, R., Bianchi, R. M., Biebel, O., Bielski, R., Bierwagen, K., Biesuz, N. V., Biglietti, M., Billoud, T. R. V., Bindi, M., Bingul, A., Bini, C., Biondi, S., Birch-Sykes, C. J., Birman, M., Bisanz, T., Biswal, J. P., Biswas, D., Bitadze, A., Bittrich, C., Bjorke, K., Blazek, T., Bloch, I., Blocker, C., Blue, A., Blumenschein, U., Bobbink, G. J., Bobrovnikov, V. S., Bogavac, D., Bogdanchikov, A. G., Bohm, C., Boisvert, V., Bokan, P., Bold, T., Bomben, M., Bona, M., Bonilla, J. S., Boonekamp, M., Booth, C. D., Borbely, A. G., Borecka-Bielska, H. M., Borgna, L. S., Borissov, G., Bortoletto, D., Boscherini, D., Bosman, M., Bossio Sola, J. D., Bouaouda, K., Boudreau, J., Bouhova-Thacker, E. V., Boumediene, D., Bouquet, R., Boveia, A., Boyd, J., Boye, D., Boyko, I. R., Bozson, A. J., Bracinik, J., Brahimi, N., Brandt, G., Brandt, O., Braren, F., Brau, B., Brau, J. E., Breaden Madden, W. D., Brendlinger, K., Brener, R., Brenner, L., Brenner, R., Bressler, S., Brickwedde, B., Briglin, D. L., Britton, D., Britzger, D., Brock, I., Brock, R., Brooijmans, G., Brooks, W. 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T., Cameron, D., Camincher, C., Campanelli, M., Camplani, A., Canale, V., Canesse, A., Cano Bret, M., Cantero, J., Cao, Y., Capua, M., Cardarelli, R., Cardillo, F., Carducci, G., Carli, T., Carlino, G., Carlson, B. T., Carlson, E. M., Carminati, L., Carnesale, M., Carney, R. M. D., Caron, S., Carquin, E., Carra, S., Carratta, G., Carter, J. W. S., Carter, T. M., Casado, M. P., Casha, A. F., Castiglia, E. G., Castillo, F. L., Castillo Garcia, L., Castillo Gimenez, V., Castro, N. F., Catinaccio, A., Catmore, J. R., Cattai, A., Cavaliere, V., Cavasinni, V., Celebi, E., Celli, F., Cerny, K., Cerqueira, A. S., Cerri, A., Cerrito, L., Cerutti, F., Cervelli, A., Cetin, S. A., Chadi, Z., Chakraborty, D., Chala, M., Chan, J., Chan, W. S., Chan, W. Y., Chapman, J. D., Chargeishvili, B., Charlton, D. G., Charman, T. P., Chatterjee, M., Chau, C. C., Chekanov, S., Chekulaev, S. V., Chelkov, G. A., Chen, B., Chen, C., Chen, C. H., Chen, H., Chen, J., Chen, S., Chen, S. J., Chen, X., Chen, Y., Chen, Y. -H., Cheng, C. L., Cheng, H. C., Cheng, H. J., Cheplakov, A., Cheremushkina, E., Cherkaoui El Moursli, R., Cheu, E., Cheung, K., Chevalier, L., Chiarella, V., Chiarelli, G., Chiodini, G., Chisholm, A. S., Chitan, A., Chiu, I., Chiu, Y. H., Chizhov, M. V., Choi, K., Chomont, A. R., Chou, Y., Chow, Y. S., Christopher, L. D., Chu, M. C., Chu, X., Chudoba, J., Chwastowski, J. J., Cieri, D., Ciesla, K. M., Cindro, V., Cioara, I. A., Ciocio, A., Cirotto, F., Citron, Z. H., Citterio, M., Ciubotaru, D. A., Ciungu, B. M., Clark, A., Clark, P. J., Clawson, S. E., Clement, C., Clissa, L., Coadou, Y., Cobal, M., Coccaro, A., Cochran, J., Coelho Lopes De Sa, R., Coelli, S., Cohen, H., Coimbra, A. E. C., Cole, B., Collot, J., Conde Muino, P., Connell, S. H., Connelly, I. A., Conventi, F., Cooper-Sarkar, A. M., Cormier, F., Corpe, L. D., Corradi, M., Corrigan, E. E., Corriveau, F., Costa, M. J., Costanza, F., Costanzo, D., Cowan, G., Cowley, J. W., Crane, J., Cranmer, K., Creager, R. A., Crepe-Renaudin, S., Crescioli, F., Cristinziani, M., Cristoforetti, M., Croft, V., Crosetti, G., Cueto, A., Cuhadar Donszelmann, T., Cui, H., Cukierman, A. R., Cunningham, W. R., Czekierda, S., Czodrowski, P., Czurylo, M. M., De Sousa, M. J. D. C. S., Da Fonseca Pinto, J. V., Da Via, C., Dabrowski, W., Dado, T., Dahbi, S., Dai, T., Dallapiccola, C., Dam, M., D'Amen, G., D'Amico, V., Damp, J., Dandoy, J. R., Daneri, M. F., Danninger, M., Dao, V., Darbo, G., Dattagupta, A., D'Auria, S., David, C., Davidek, T., Davis, D. R., Dawson, I., De, K., De Asmundis, R., De Beurs, M., De Castro, S., De Groot, N., De Jong, P., De La Torre, H., De Maria, A., De Pedis, D., De Salvo, A., De Sanctis, U., De Santis, M., De Santo, A., De Vivie De Regie, J. B., Dedovich, D. V., Degens, J., Deiana, A. M., Del Peso, J., Delabat Diaz, Y., Deliot, F., Delitzsch, C. M., Della Pietra, M., Della Volpe, D., Dell'Acqua, A., Dell'Asta, L., Delmastro, M., Delporte, C., Delsart, P. A., Demers, S., Demichev, M., Demontigny, G., Denisov, S. P., D'Eramo, L., Derendarz, D., Derkaoui, J. E., Derue, F., Dervan, P., Desch, K., Dette, K., Deutsch, C., Deviveiros, P. O., Di Bello, F. A., Di Ciaccio, A., Di Ciaccio, L., Di Donato, C., Di Girolamo, A., Di Gregorio, G., Di Luca, A., Di Micco, B., Di Nardo, R., Diaconu, C., Dias, F. A., Vale, T. D. D., Diaz, M. A., Diaz Capriles, F. G., Dickinson, J., Didenko, M., Diehl, E. B., Dietrich, J., Diez Cornell, S., Diez Pardos, C., Dimitrievska, A., Ding, W., Dingfelder, J., Dittmeier, S. J., Dittus, F., Djama, F., Djobava, T., Djuvsland, J. I., Do Vale, M. A. B., Dobre, M., Dodsworth, D., Doglioni, C., Dolejsi, J., Dolezal, Z., Donadelli, M., Dong, B., Donini, J., D'Onofrio, A., D'Onofrio, M., Dopke, J., Doria, A., Dova, M. T., Doyle, A. T., Drechsler, E., Dreyer, E., Dreyer, T., Drobac, A. S., Du, D., Du Pree, T. A., Duan, Y., Dubinin, F., Dubovsky, M., Dubreuil, A., Duchovni, E., Duckeck, G., Ducu, O. A., Duda, D., Dudarev, A., Dudder, A. C., D'Uffizi, M., Duflot, L., Duhrssen, M., Dulsen, C., Dumancic, M., Dumitriu, A. E., Dunford, M., Dungs, S., Duperrin, A., Yildiz, H. D., Duren, M., Durglishvili, A., Dutta, B., Duvnjak, D., Dyckes, G. I., Dyndal, M., Dysch, S., Dziedzic, B. S., Eckerova, B., Eggleston, M. G., Egidio Purcino De Souza, E., Ehrke, L. F., Eifert, T., Eigen, G., Einsweiler, K., Ekelof, T., El Jarrari, H., El Moussaouy, A., Ellajosyula, V., Ellert, M., Ellinghaus, F., Elliot, A. A., Ellis, N., Elmsheuser, J., Elsing, M., Emeliyanov, D., Emerman, A., Enari, Y., Erdmann, J., Ereditato, A., Erland, P. A., Errenst, M., Escalier, M., Escobar, C., Estrada Pastor, O., Etzion, E., Evans, G., Evans, H., Evans, M. O., Ezhilov, A., Fabbri, F., Fabbri, L., Fabiani, V., Facini, G., Fakhrutdinov, R. M., Falciano, S., Falke, P. 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G., Zou, R., Zou, W., Zwalinski, L., Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre de Calcul de l'IN2P3 (CC-IN2P3), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), ATLAS, Aloisio, Alberto, Alviggi, Mariagrazia, Canale, Vincenzo, Della Pietra, Massimo, Merola, Leonardo, Massarotti, Paolo, Conventi, Francesco, Rossi, Elvira, Carlino, Giampaolo, de Asmundis, Riccardo, Di Donato, Camilla, Doria, Alessandra, Iengo, Paolo, Izzo, Vincenzo, Perrella, Sabrina, Sekhniaidze, Givi, Cirotto, Francesco, Lavorgna, Marco, Giannini, Antonio, Atlas, Collaboration, Współautorami artykułu są członkowie ATLAS Collaboration w liczbie 2851, De Castro , S., Fabbri , L., Gabrielli , A., Rinaldi , L., Semprini Cesari , N., Sioli , M., Villa , M., Zoccoli , A., Bellagamba , L., Boscherini , D., Bruni , A., Bruni , G., Giacobbe , B., Polini , A., Sbarra , C., Sidoti , A., Franchini , M., Romano , M., Valentinetti , S., Alberghi , G. L., Lasagni Manghi , F, Massa , L., Vittori , C., Alfonsi , F, Cabras , G., Cervelli , A., Negrini , M., Todome , K., Carratta , G., Cavalli , N., Clissa , L., ATLAS collaboration, Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Aad, G, Bachas, K, Chiodini, G, Gorini, E, Gravili, F, Longo, L, Primavera, M, Reale, M, Schioppa, E, Spagnolo, S, Ventura, A, and ATLAS Collaboration, And
Subjects: System, gap [rapidity], heavy ion: scattering, Kjerne- og elementærpartikkelfysikk: 431 [VDP], Performance, angular correlation: long-range, Hadron, Monte Carlo method, 01 natural sciences, High Energy Physics - Experiment, Subatomär fysik, High Energy Physics - Experiment (hep-ex), PpCollisions, correlation function: two-particle, Subatomic Physics, [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex], Nuclear Experiment (nucl-ex), Nuclear Experiment, calorimeter: forward spectrometer, Settore FIS/01, Physics, angular correlation: two-particle, two-particle [correlation function], Large Hadron Collider, 4. Education, ATLAS experiment, Heavy-Ion Collisions, Monte Carlo [numerical calculations], ATLAS, Calorimeter, forward spectrometer [calorimeter], CERN LHC Coll, Nuclear and elementary particle physics: 431 [VDP], medicine.anatomical_structure, Multiplicity, flow, Pseudorapidity, Distributions, Lhc, numerical calculations: Monte Carlo, Particle Physics - Experiment, charged particle: tracks, 530 Physics, collective, FOS: Physical sciences, LHC, ATLAS, High Energy Physics, transverse momentum, [PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex], Relativistic heavy ions, charged particle: multiplicity, Nuclear physics, multiplicity [charged particle], scattering [heavy ion], Atlas (anatomy), long-range [angular correlation], 0103 physical sciences, medicine, Fluctuations, Nuclear Physics - Experiment, ddc:530, 5020 GeV-cms/nucleon, High Energy Physics, peripheral, 010306 general physics, hadron hadron: interaction, interaction [hadron hadron], LHC, Particle Physics, Photonuclear interactions, two-particle [angular correlation], tracks [charged particle], 010308 nuclear & particles physics, Física, Detector, Multiplicity (mathematics), boundary condition, rapidity: gap, correlation, Experimental High Energy Physics, experimental results, Model
Abstract: We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina, YerPhI, Armenia, ARC, Australia, BMWFW and FWF, Austria, ANAS, Azerbaijan, SSTC, Belarus, CNPq and FAPESP, Brazil, NSERC, NRC, and CFI, Canada, CERN and ANID, Chile, CAS, MOST, and NSFC, China, COLCIENCIAS, Colombia, MSMT CR, MPO CR, and VSC CR, Czech Republic, DNRF and DNSRC, Denmark, IN2P3-CNRS and CEA-DRF/IRFU, France, SRNSFG, Georgia, BMBF, HGF, and MPG, Germany, GSRT, Greece, RGC and Hong Kong SAR, China, ISF and Benoziyo Center, Israel, INFN, Italy, MEXT and JSPS, Japan, CNRST, Morocco, NWO, Netherlands, RCN, Norway, MNiSW and NCN, Poland, FCT, Portugal, MNE/IFA, Romania, JINR, MES of Russia, and NRC KI, Russian Federation, MESTD, Serbia, MSSR, Slovakia, ARRS and MIZS, Slovenia, DST/NRF, South Africa, MICINN, Spain, SRC and Wallenberg Foundation, Sweden, SERI, SNSF, and Cantons of Bern and Geneva, Switzerland, MOST, Taiwan, TAEK, Turkey, STFC, United Kingdom, DOE and NSF, USA. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada, CRC and IVADO, Canada, Beijing Municipal Science & Technology Commission, China, COST, ERC, ERDF, Horizon 2020, and Marie Sklodowska-Curie Actions, European Union, Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France, DFG and AvH Foundation, Germany, Herakleitos, Thales, and Aristeia programs cofinanced by EU-ESF and the Greek NSRF, Greece, BSF-NSF and GIF, Israel, La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya, and PROMETEO and GenT Programmes Generalitat Valenciana, Spain, Goran Gustafssons Stiftelse, Sweden, The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK), and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [67]., Two-particle long-range azimuthal correlations are measured in photonuclear collisions using 1.7 nb−1 of 5.02 TeV Pb+Pb collision data collected by the ATLAS experiment at the CERN Large Hadron Collider. Candidate events are selected using a dedicated high-multiplicity photonuclear event trigger, a combination of information from the zero-degree calorimeters and forward calorimeters, and from pseudorapidity gaps constructed using calorimeter energy clusters and charged-particle tracks. Distributions of event properties are compared between data and Monte Carlo simulations of photonuclear processes. Two-particle correlation functions are formed using charged-particle tracks in the selected events, and a template-fitting method is employed to subtract the nonflow contribution to the correlation. Significant nonzero values of the secondand third-order flow coefficients are observed and presented as a function of charged-particle multiplicity and transverse momentum. The results are compared with flow coefficients obtained in proton-proton and proton-lead collisions in similar multiplicity ranges, and with theoretical expectations. The unique initial conditions present in this measurement provide a new way to probe the origin of the collective signatures previously observed only in hadronic collisions., ANPCyT, Australian Research Council, Austrian Science Fund (FWF), SSTC, Belarus, Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Natural Sciences and Engineering Research Council of Canada (NSERC) Canada Foundation for Innovation, National Natural Science Foundation of China (NSFC), Departamento Administrativo de Ciencia, Tecnologia e Innovacion Colciencias, Ministry of Education, Youth & Sports - Czech Republic Czech Republic Government Czech Republic Government, Danish Natural Science Research Council, CEA-DRF/IRFU, France, Max Planck Society, RGC and Hong Kong SAR, China, Israel Science Foundation Benoziyo Center, Israel, Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of Science, CNRST, Morocco, Ministry of Science and Higher Education, Poland NCN, Poland, Portuguese Foundation for Science and Technology European Commission, Ministry of Education, Science & Technological Development, Serbia, Slovenian Research Agency - Slovenia MIZS, Slovenia, Spanish Government, Wallenberg Foundation, Sweden, SNSF Geneva, Switzerland, National Science Foundation (NSF), BCKDF, Canada CANARIE, Canada, Beijing Municipal Science & Technology Commission, ERC, France ERDF, France Marie Sklodowska-Curie Actions, France French National Research Agency (ANR), Alexander von Humboldt Foundation, EU-ESF, Greece Greek NSRF, Greece, BSF-NSF, Israel German-Israeli Foundation for Scientific Research and Development, CERCA Programme Generalitat de Catalunya, Spain PROMETEO, Spain GenT Programmes Generalitat Valenciana, Spain, Goran Gustafssons Stiftelse, Sweden, Royal Society of London Leverhulme Trust, YerPhI, Australia Armenia, Australia, BMWFW, Austria, ANAS, Belarus Azerbaijan, Belarus, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ), NRC, Canada, CERN, Chile ANID, Chile, Chinese Academy of Sciences Ministry of Science and Technology, China, DNRF, Denmark, Centre National de la Recherche Scientifique (CNRS), SRNSFG, Germany Georgia, Germany, Federal Ministry of Education & Research (BMBF), HGF, Germany, Greek Ministry of Development-GSRT, Istituto Nazionale di Fisica Nucleare (INFN), Netherlands Organization for Scientific Research (NWO) Netherlands Government, RCN, Norway, MNE/IFA, Romania, JINR, Russia MES of Russia, NRC KI, Serbia Russian Federation, Serbia, MSSR, Slovakia, DST/NRF, South Africa, SRC, Sweden, SERI, Geneva, Switzerland Cantons of Bern Geneva, Switzerland, Ministry of Science and Technology, Taiwan, Ministry of Energy & Natural Resources - Turkey, UK Research & Innovation (UKRI), Science & Technology Facilities Council (STFC), United States Department of Energy (DOE), Compute Canada, Canada CRC, Canada IVADO, Canada, COST, France Horizon 2020, France European Union, France, French National Research Agency (ANR), German Research Foundation (DFG), La Caixa Banking Foundation, Spain
Published: 2021
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42. Climate change jointly with migration ability affect future range shifts of dominant fir species in Southwest China

Author: Bikram Pandey, Kaiwen Pan, Lin Zhang, Ziyan Liao, Mohammed A. Dakhil, Xianglin Tian, Qinli Xiong, Xiaogang Wu, Keqing Wang, Mingxi Du, Michael P. Nobis, Department of Forest Sciences, and Forest Modelling Group
Subjects: 0106 biological sciences, migration ability, Range (biology), Species distribution, Abies squamata, GEOGRAPHICAL-DISTRIBUTION, Climate change, DISTRIBUTION MODELS, 010603 evolutionary biology, 01 natural sciences, Abies forrestii, LIMITED MIGRATION, PLANT-DISTRIBUTION, SDMs, DISTRIBUTIONS, Abies recurvata, mountains of Southwest China, TREE, 1172 Environmental sciences, Ecology, Evolution, Behavior and Systematics, potential distribution, Ecological niche, 4112 Forestry, ABIES-ALBA MILL, GENETIC IMPRINTS, biology, Ecology, 010604 marine biology & hydrobiology, QINGHAI-TIBETAN PLATEAU, 15. Life on land, biology.organism_classification, Biodiversity hotspot, climate change, Geography, 13. Climate action, Abies forest, QUATERNARY CLIMATE
Abstract: Aim As a prominent geographical distribution centre for the dark coniferous forests, mountains of Southwest China (MSWC) is experiencing an unprecedented warming trend, posing severe challenges to the survival of dominant fir (Abies) species. Although plant's migration ability is a prerequisite for its survival in changing environments, it has often been ignored in species distribution models (SDMs). This study aimed to quantify the magnitude and direction of range changes by the year 2080 for six dominant fir species, that is Abies recurvata, Abies faxoniana, Abies squamata, Abies ernestii, Abies forrestii and Abies georgei, with an emphasis on exploring the relationship between migration ability and projected distributions. Location The mountains of Southwest China. Methods We applied the Maximum Entropy (Maxent) algorithm to calibrate ecological niche models and to project the climatically suitable areas (CSAs) of each species under two emission scenarios (RCP 4.5 and RCP 8.5). Additionally, we delimited future species ranges by three migration scenarios (full-, no- and partial-migration scenarios). Results The simulations showed the distinctive responses of the six fir species to anthropogenic climate change (ACC). By 2080, the distribution areas of Abies recurvata were projected to decline only in the no-migration scenario but increase under the full- and partial-migration scenarios, while the other five species were projected to decline in the majority of emission x migration scenarios. Fir species in the southern region were predicted to be more vulnerable to ACC due to the larger losses in CSAs and a stronger effect of the partial-migration scenario on the newly colonized areas of this group. The studied species showed a simulated migration trend (northward and westward) to the interior Qinghai-Tibet Plateau under ACC. Main conclusions Benefits or losses for species under ACC depended on the geographical location, their ecological niches and migration abilities, which provide essential insights for a spatial conservation assessment of biodiversity hotspots in the future.
Published: 2019
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43. Bayesian analysis of differential effects in multi-group regression methods

Author: Geert Verbeke, Luk Bruyneel, Emmanuel Lesaffre, and Adrian Quintero
Subjects: SELECTION, Statistics and Probability, Statistics & Probability, Bayesian probability, Latent variable, 01 natural sciences, differential effects, 010104 statistics & probability, multiple groups, Application areas, Statistics, DISTRIBUTIONS, latent variable, 0101 mathematics, Mathematics, Science & Technology, SUBGROUP ANALYSIS, Group (mathematics), 05 social sciences, 050301 education, Regression analysis, Differential effects, Regression, MODEL, MCMC methods, Physical Sciences, Full interaction model, Statistics, Probability and Uncertainty, 0503 education
Abstract: In regression analysis, the data sample is often composed of diverse sub-populations such as ethnicities and geographical regions. In multiple application areas, it is important to identify the groups where each covariate has a positive, negative or null impact on the response. If the number of sub-populations is small, a full interaction model may be fit with group-specific covariate effects. However, if the number of groups is very large, for example, hospitals or other clustering units, such a model is not identifiable. Therefore, we propose a prior distribution which combines the information across sub-populations with a similar covariate effect. This Bayesian analysis of differential effects (BADE) classifies the group-specific covariate effects as positive, negative or null. Besides allowing the analysis of differential effects for many sub-populations, the proposed approach improves substantially the identification of important interactions in cases with few groups. This is illustrated via simulations. The procedure is motivated on, and applied to, a large study related to patients’ satisfaction with hospitals, where we show that classifying group-specific covariate effects based on methods such as mixed-effects models may be strongly misleading.
Published: 2019
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44. On some graph-based two-sample tests for high dimension, low sample size data

Author: Anil K. Ghosh, Soham Sarkar, and Rahul Biswas
Subjects: nearest neighbor, distributions, high-dimensional consistency, 02 engineering and technology, minimum spanning tree, shortest hamiltonian path, multivariate, Artificial Intelligence, 020204 information systems, Euclidean geometry, 0202 electrical engineering, electronic engineering, information engineering, Two sample, equality, large numbers, laws, Statistical hypothesis testing, Mathematics, non-bipartite matching, Nominal level, Euclidean distance, Sample size determination, Graph (abstract data type), 020201 artificial intelligence & image processing, Pairwise comparison, Algorithm, distance concentration, Software, permutation test
Abstract: Testing for equality of two high-dimensional distributions is a challenging problem, and this becomes even more challenging when the sample size is small. Over the last few decades, several graph-based two-sample tests have been proposed in the literature, which can be used for data of arbitrary dimensions. Most of these test statistics are computed using pairwise Euclidean distances among the observations. But, due to concentration of pairwise Euclidean distances, these tests have poor performance in many high-dimensional problems. Some of them can have powers even below the nominal level when the scale-difference between two distributions dominates the location-difference. To overcome these limitations, we introduce some new dissimilarity indices and use them to modify some popular graph-based tests. These modified tests use the distance concentration phenomenon to their advantage, and as a result, they outperform the corresponding tests based on the Euclidean distance in a wide variety of examples. We establish the high-dimensional consistency of these modified tests under fairly general conditions. Analyzing several simulated as well as real data sets, we demonstrate their usefulness in high dimension, low sample size situations.
Published: 2019
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45. How to evaluate community predictions without thresholding?

Author: Heidi K. Mod, Antoine Guisan, Daniel Scherrer, and Department of Geosciences and Geography
Subjects: 0106 biological sciences, community modelling, Jaccard index, ACCURACY, Species distribution, DIVERSITY, 010603 evolutionary biology, 01 natural sciences, RICHNESS, Statistics, DISTRIBUTIONS, insects, ASSEMBLAGES, Ecology, Evolution, Behavior and Systematics, Sorensen index, Mathematics, Environmental gradient, validation, plants, Null model, Binary outcome, 010604 marine biology & hydrobiology, Ecological Modeling, null model, Elevation, stacked species distribution models, BIOTIC INTERACTIONS, SPECIES DISTRIBUTION MODELS, 15. Life on land, FRAMEWORK, Thresholding, SIMILARITY, 1181 Ecology, evolutionary biology, BIODIVERSITY, Species richness
Abstract: Stacked species distribution models (S-SDM) provide a tool to make spatial predictions about communities by first modelling individual species and then stacking the modelled predictions to form assemblages. The evaluation of the predictive performance is usually based on a comparison of the observed and predicted community properties (e.g. species richness, composition). However, the most available and widely used evaluation metrics require the thresholding of single species' predicted probabilities of occurrence to obtain binary outcomes (i.e. presence/absence). This binarization can introduce unnecessary bias and error. Herein, we present and demonstrate the use of several groups of new or rarely used evaluation approaches and metrics for both species richness and community composition that do not require thresholding but instead directly compare the predicted probabilities of occurrences of species to the presence/absence observations in the assemblages. Community AUC, which is based on traditional AUC, measures the ability of a model to differentiate between species presences or absences at a given site according to their predicted probabilities of occurrence. Summing the probabilities gives the expected species richness and allows the estimation of the probability that the observed species richness is not different from the expected species richness based on the species' probabilities of occurrence. The traditional Sorensen and Jaccard similarity indices (which are based on presences/absences) were adapted to maxSorensen and maxJaccard and to probSorensen and probJaccard (which use probabilities directly). A further approach (improvement over null models) compares the predictions based on S-SDMs with the expectations from the null models to estimate the improvement in both species richness and composition predictions. Additionally, all metrics can be described against the environmental conditions of sites (e.g. elevation) to highlight the abilities of models to detect the variation in the strength of the community assembly processes in different environments. These metrics offer an unbiased view of the performance of community predictions compared to metrics that requiring thresholding. As such, they allow more straightforward comparisons of model performance among studies (i.e. they are not influenced by any subjective thresholding decisions).
Published: 2019
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46. Effects of topography on tropical forest structure depend on climate context

Author: Douglas C. Morton, Samira Kolyaie, María Uriarte, Jess K. Zimmerman, and Robert Muscarella
Subjects: 0106 biological sciences, Tropical and subtropical dry broadleaf forests, canopy height, Skogsvetenskap, PUERTO-RICO, DIVERSITY, Context (language use), Plant Science, FUNCTIONAL CONVERGENCE, 010603 evolutionary biology, 01 natural sciences, HABITAT ASSOCIATIONS, BIOMASS, DISTRIBUTIONS, Biologiska vetenskaper, TEMPERATURE, Biological sciences, MOUNTAIN PASSES, lidar, Ecology, Evolution, Behavior and Systematics, above-ground biomass, Abiotic component, Ecology, Forest Science, Puerto Rico, Biological Sciences, wood density, Tropical forest, Tropical rain forest, HYDRAULIC ARCHITECTURE, climate gradient, TREES, Environmental science, microtopographic heterogeneity, 010606 plant biology & botany
Abstract: 1. Topography affects abiotic conditions which can influence the structure, function and dynamics of ecological communities. An increasing number of studies have demonstrated biological consequences of fine-scale topographic heterogeneity but we have a limited understanding of how these effects depend on the climate context. 2. We merged high-resolution (1 m2) data on topography and canopy height derived from airborne lidar with ground-based data from 15 forest plots in Puerto Rico distributed along a precipitation gradient spanning c. 800?3,500 mm/year. Ground-based data included species composition, estimated above-ground biomass (AGB), and two key functional traits (wood density and leaf mass per area, LMA) that reflect resource-use strategies and a trade-off between hydraulic safety and hydraulic efficiency. We used hierarchical Bayesian models to evaluate how the interaction between topography ? climate is related to metrics of forest structure (i.e. canopy height and AGB), as well as taxonomic and functional alpha- and beta-diversity. 3. Fine-scale topography (characterized with the topographic wetness index, TWI) significantly affected forest structure and the strength (and in some cases direction) of these effects varied across the precipitation gradient. In all plots, canopy height increased with topographic wetness but the effect was much stronger in dry compared to wet forest plots. In dry forest plots, topographically wetter microsites also had higher levels of AGB but in wet forest plots, topographically drier microsites had higher AGB. 4. Fine-scale topography influenced functional composition but had only weak or non-significant effects on taxonomic and functional alpha- and beta-diversity. For instance, community-weighted wood density followed a similar pattern to AGB across plots. We also found a marginally significant association between variation of wood density and topographic heterogeneity that depended on climate context. 5. Synthesis. The effects of fine-scale topographic heterogeneity on tropical forest structure and composition depend on the climate context. Our study demonstrates how a stronger integration of topographic heterogeneity across precipitation gradients could improve estimates of forest structure and biomass, and may provide insight to the ways that topography might mediate species responses to drought and climate change.
Published: 2019
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47. Species and phylogenetic endemism in angiosperm trees across the Northern Hemisphere are jointly shaped by modern climate and glacial–interglacial climate change

Author: Brody Sandel, Ziyu Ma, Alejandro Ordonez, Signe Normand, Jens-Christian Svenning, Lingfeng Mao, and Gang Feng
Subjects: 0106 biological sciences, DIVERSITY, Climate change, climate-richness relationship, 010603 evolutionary biology, 01 natural sciences, RICHNESS, phylogenetic endemism, orbitally forced species' range dynamics hypothesis, PLANT ENDEMISM, DISTRIBUTIONS, EXTINCTIONS, Quaternary-scale climate change, Glacial period, Endemism, Ecology, Evolution, Behavior and Systematics, Northern Hemisphere, Global and Planetary Change, GLOBAL PATTERNS, Ecology, Phylogenetic tree, RANGE, 010604 marine biology & hydrobiology, tree assemblages, Last Glacial Maximum, VELOCITY, EVOLUTION, INSIGHTS, Geography, Taxon, Interglacial
Abstract: Aims: Phylogenetic endemism describes the extent to which unique phylogenetic lineages are constrained to restricted geographic areas. Previous studies indicate that species endemism is related to both past and modern climate, but studies of phylogenetic endemism are relatively rare and mainly focused on smaller regions. Here, we provide the first assessment of the patterns of species and phylogenetic endemism in angiosperm trees across the Northern Hemisphere as well as the relative importance of modern climate and glacial–interglacial climate change as drivers of these patterns. Location: Northern Hemisphere. Major taxa: Angiosperm trees. Methods: Using tree assemblages at the scale of 100 km × 100 km grid cells and simultaneous autoregressive (SAR) models, we assessed the relationships between species endemism, phylogenetic endemism and modern climate variables, Last Glacial Maximum (LGM) to present temperature velocity. Results: Species and phylogenetic endemism were associated with both modern climate and glacial–interglacial climate change, with higher values in areas with stable historical climate and warmer and wetter modern conditions. Notably, the multivariate SAR analyses showed that the combinations of variables with highest Akaike’s information criterion (AIC) weight always included both LGM–present climate instability and modern climate, that is, modern precipitation and temperature. Main conclusions: Our results show that high phylogenetic endemism is partially dependent on long-term climate stability, highlighting the threat posed by future climate changes to the preservation of rare, phylogenetically distinct lineages of trees.
Published: 2019
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48. The effect of publication bias on the Q test and assessment of heterogeneity

Author: Augusteijn, Hilde E.M., van Aert, Robbie C.M., van Assen, Marcel A.L.M., Leerstoel Buskens, Social Networks, Solidarity and Inequality, Leerstoel Buskens, Social Networks, Solidarity and Inequality, and Department of Methodology and Statistics
Subjects: VARIANCE ESTIMATORS, Q test, Heterogeneity, Normal Distribution, Expected value, Publication bias, RECOMMENDATIONS, Meta-Analysis as Topic, 0504 sociology, Statistics, DECISIONS, DISTRIBUTIONS, Humans, EFFECT SIZE, METAANALYSIS, Mathematics, Sampling bias, 05 social sciences, Nonparametric statistics, 050401 social sciences methods, Meta-analysis, Extreme homogeneity, P VALUES, Sample size determination, Data Interpretation, Statistical, Psychology (miscellaneous), Publication Bias, Type I and type II errors
Abstract: One of the main goals of meta-analysis is to test for and estimate the heterogeneity of effect sizes. We examined the effect of publication bias on the Q test and assessments of heterogeneity as a function of true heterogeneity, publication bias, true effect size, number of studies, and variation of sample sizes. The present study has two main contributions and is relevant to all researchers conducting meta-analysis. First, we show when and how publication bias affects the assessment of heterogeneity. The expected values of heterogeneity measures H² and I² were analytically derived, and the power and Type I error rate of the Q test were examined in a Monte Carlo simulation study. Our results show that the effect of publication bias on the Q test and assessment of heterogeneity is large, complex, and nonlinear. Publication bias can both dramatically decrease and increase heterogeneity in true effect size, particularly if the number of studies is large and population effect size is small. We therefore conclude that the Q test of homogeneity and heterogeneity measures H² and I² are generally not valid when publication bias is present. Our second contribution is that we introduce a web application, Q-sense, which can be used to determine the impact of publication bias on the assessment of heterogeneity within a certain meta-analysis and to assess the robustness of the meta-analytic estimate to publication bias. Furthermore, we apply Q-sense to 2 published meta-analyses, showing how publication bias can result in invalid estimates of effect size and heterogeneity. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Published: 2019
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49. The effects of climate change scenarios on Tilia ssp. in Turkey

Author: Ugur Canturk, Şemsettin Kulaç, and [Belirlenecek]
Subjects: Tilia platyphyllos, Turkey, Climate Change, Population, Tilia cordata, Climate change, SSP 585, SSP 245, Management, Monitoring, Policy and Law, Eastern, Suitability, Effects of global warming, Environmental protection, Tilia, Humans, Forest, Characters, education, Tree Species Distribution, Future, Mediterranean Mountains, General Environmental Science, Tilia tomentosa, education.field_of_study, biology, Ecology, Global warming, General Medicine, biology.organism_classification, Pollution, Climate classification, Geography, Impacts, Distributions, Maxent, Environmental Monitoring
Abstract: Global climate change will cause significant changes in climate parameters, especially temperature increases and changes in precipitation regimes worldwide. Since the life of living things is directly related to climate parameters, this process will inevitably affect all living things. The plants will be the most affected living things from this process because they do not have an effective movement and migration mechanism. Therefore, global climate change will cause significant species and population losses in plants. To minimize the potential loss of species and populations, it is necessary to predetermine the potential changes in species' distribution areas and take necessary actions. Therefore, this study was aimed to determine the distribution areas of three Tilia species (Tilia tomentosa, Tilia cordata, and Tilia platyphyllos), which have economic, ecologic, and social value and show the local distribution in Turkey and to determine how they will be affected by global climate change. Within this scope, nineteen bioclimatic variables, Emberger climate classification, aspect, and topographic altitude variable were used in the modeling process. By modeling the scenarios SSP 245 and SSP 585, the projections were made for 2040, 2060, 2080, and 2100 regarding the areas suitable for the growth of these species and how these areas will change compared to their current situation. The results suggest that the distribution areas of all three Tilia species will change due to climate change, and the area of loss will be 43.5 km(2) (4%) for T. tomentosa, 9953.6 km(2) (15%) for T. platyphyllos, and 448.0 km(2) (19%) for T. cordata. Moreover, a more important point here is that increases and decreases will be observed in their distribution areas, and these changes will occur in a short process and at significant levels. In this case, the migration mechanism that these species will require must be provided by humans. WOS:000714603300002 2-s2.0-85118771501 PubMed: 34738174
Published: 2021

50. New genera and species of the Oriental mirine plant bugs from Southeast Asia, with six new combinations (Insecta: Heteroptera: Miridae: Mirinae: Mirini)

Author: Yasunaga, Tomohide, Chérot, Frédéric, and Schwartz, Michael D.
Subjects: Hemiptera, genitalic documentation, scanning electronic micrographs, Insecta, Arthropoda, distributions, Animalia, relationships, Biodiversity, Miridae, Taxonomy
Abstract: Yasunaga, Tomohide, Chérot, Frédéric, Schwartz, Michael D. (2021): New genera and species of the Oriental mirine plant bugs from Southeast Asia, with six new combinations (Insecta: Heteroptera: Miridae: Mirinae: Mirini). Raffles Bulletin of Zoology 69: 137-155, DOI: 10.26107/RBZ-2021-0012
Published: 2021

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