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21,330 results on '"A. Serre"'

103. Mission, Organization, and Future Direction of the Serological Sciences Network for COVID-19 (SeroNet) Epidemiologic Cohort Studies

Author

Figueiredo, Jane C, Hirsch, Fred R, Kushi, Lawrence H, Nembhard, Wendy N, Crawford, James M, Mantis, Nicholas, Finster, Laurel, Merin, Noah M, Merchant, Akil, Reckamp, Karen L, Melmed, Gil Y, Braun, Jonathan, McGovern, Dermot, Parekh, Samir, Corley, Douglas A, Zohoori, Namvar, Amick, Benjamin C, Du, Ruofei, Gregersen, Peter K, Diamond, Betty, Taioli, Emanuela, Sariol, Carlos, Espino, Ana, Weiskopf, Daniela, Gifoni, Alba, Brien, James, Hanege, William, Lipsitch, Marc, Zidar, David A, McAlearney, Ann Scheck, Wajnberg, Ania, LaBaer, Joshua, Lewis, E Yvonne, Binder, Raquel A, Moormann, Ann M, Forconi, Catherine, Forrester, Sarah, Batista, Jennifer, Schieffelin, John, Kim, Dongjoo, Biancon, Giulia, VanOudenhove, Jennifer, Halene, Stephanie, Fan, Rong, Barouch, Dan H, Alter, Galit, Pinninti, Swetha, Boppana, Suresh B, Pati, Sunil K, Latting, Misty, Karaba, Andrew H, Roback, John, Sekaly, Rafick, Neish, Andrew, Brincks, Ahnalee M, Granger, Douglas A, Karger, Amy B, Thyagarajan, Bharat, Thomas, Stefani N, Klein, Sabra L, Cox, Andrea L, Lucas, Todd, Furr-Holden, Debra, Key, Kent, Jones, Nicole, Wrammerr, Jens, Suthar, Mehul, Wong, Serre Yu, Bowman, Natalie M, Simon, Viviana, Richardson, Lynne D, McBride, Russell, Krammer, Florian, Rana, Meenakshi, Kennedy, Joshua, Boehme, Karl, Forrest, Craig, Granger, Steve W, Heaney, Christopher D, Lapinski, Maria Knight, Wallet, Shannon, Baric, Ralph S, Schifanella, Luca, Lopez, Marcos, Fernández, Soledad, Kenah, Eben, Panchal, Ashish R, Britt, William J, Sanz, Iñaki, Dhodapkar, Madhav, Ahmed, Rafi, Bartelt, Luther A, Markmann, Alena J, Lin, Jessica T, Hagan, Robert S, Wolfgang, Matthew C, and Skarbinski, Jacek

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Pneumonia & Influenza, Vaccine Related, Emerging Infectious Diseases, Biodefense, Lung, Digestive Diseases, Infectious Diseases, Clinical Research, Pneumonia, Cancer, Pediatric, Prevention, Aetiology, 2.4 Surveillance and distribution, Good Health and Well Being, cohort, COVID-19, epidemiology, SARS-CoV-2, serosurveillance, SeroNet, Clinical sciences, Medical microbiology
Abstract

BackgroundGlobal efforts are needed to elucidate the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the underlying cause of coronavirus disease 2019 (COVID-19), including seroprevalence, risk factors, and long-term sequelae, as well as immune responses after vaccination across populations and the social dimensions of prevention and treatment strategies.MethodsIn the United States, the National Cancer Institute in partnership with the National Institute of Allergy and Infectious Diseases, established the SARS-CoV-2 Serological Sciences Network (SeroNet) as the nation's largest coordinated effort to study coronavirus disease 2019. The network comprises multidisciplinary researchers bridging gaps and fostering collaborations among immunologists, epidemiologists, virologists, clinicians and clinical laboratories, social and behavioral scientists, policymakers, data scientists, and community members. In total, 49 institutions form the SeroNet consortium to study individuals with cancer, autoimmune disease, inflammatory bowel diseases, cardiovascular diseases, human immunodeficiency virus, transplant recipients, as well as otherwise healthy pregnant women, children, college students, and high-risk occupational workers (including healthcare workers and first responders).ResultsSeveral studies focus on underrepresented populations, including ethnic minorities and rural communities. To support integrative data analyses across SeroNet studies, efforts are underway to define common data elements for standardized serology measurements, cellular and molecular assays, self-reported data, treatment, and clinical outcomes.ConclusionsIn this paper, we discuss the overarching framework for SeroNet epidemiology studies, critical research questions under investigation, and data accessibility for the worldwide scientific community. Lessons learned will help inform preparedness and responsiveness to future emerging diseases.

Published
2022

107. Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis

Author

Fel, Thomas, Cadene, Remi, Chalvidal, Mathieu, Cord, Matthieu, Vigouroux, David, and Serre, Thomas

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

We describe a novel attribution method which is grounded in Sensitivity Analysis and uses Sobol indices. Beyond modeling the individual contributions of image regions, Sobol indices provide an efficient way to capture higher-order interactions between image regions and their contributions to a neural network's prediction through the lens of variance. We describe an approach that makes the computation of these indices efficient for high-dimensional problems by using perturbation masks coupled with efficient estimators to handle the high dimensionality of images. Importantly, we show that the proposed method leads to favorable scores on standard benchmarks for vision (and language models) while drastically reducing the computing time compared to other black-box methods -- even surpassing the accuracy of state-of-the-art white-box methods which require access to internal representations. Our code is freely available: https://github.com/fel-thomas/Sobol-Attribution-Method, Comment: NeurIPS2021

Published
2021

108. The Challenge of Appearance-Free Object Tracking with Feedforward Neural Networks

Author

Malik, Girik, Linsley, Drew, Serre, Thomas, and Mingolla, Ennio

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

Nearly all models for object tracking with artificial neural networks depend on appearance features extracted from a "backbone" architecture, designed for object recognition. Indeed, significant progress on object tracking has been spurred by introducing backbones that are better able to discriminate objects by their appearance. However, extensive neurophysiology and psychophysics evidence suggests that biological visual systems track objects using both appearance and motion features. Here, we introduce $\textit{PathTracker}$, a visual challenge inspired by cognitive psychology, which tests the ability of observers to learn to track objects solely by their motion. We find that standard 3D-convolutional deep network models struggle to solve this task when clutter is introduced into the generated scenes, or when objects travel long distances. This challenge reveals that tracing the path of object motion is a blind spot of feedforward neural networks. We expect that strategies for appearance-free object tracking from biological vision can inspire solutions these failures of deep neural networks., Comment: Accepted at CVPR Workshop on Dynamic Neural Networks Meet Computer Vision

Published
2021

109. Validation of edge turbulence codes against the TCV-X21 diverted L-mode reference case

Author

Oliveira, D. S., Body, T., Galassi, D., Theiler, C., Laribi, E., Tamain, P., Stegmeir, A., Giacomin, M., Zholobenko, W., Ricci, P., Bufferand, H., Boedo, J. A., Ciraolo, G., Colandrea, C., Coster, D., de Oliveira, H., Fourestey, G., Gorno, S., Imbeaux, F., Jenko, F., Naulin, V., Offeddu, N., Reimerdes, H., Serre, E., Tsui, C. K., Varini, N., Vianello, N., Wiesenberger, M., Wüthrich, C., and Team, the TCV

Subjects
Physics - Plasma Physics
Abstract

Self-consistent full-size turbulent-transport simulations of the divertor and SOL of existing tokamaks have recently become feasible. This enables the direct comparison of turbulence simulations against experimental measurements. In this work, we perform a series of diverted Ohmic L-mode discharges on the TCV tokamak, building a first-of-a-kind dataset for the validation of edge turbulence models. This dataset, referred to as TCV-X21, contains measurements from 5 diagnostic systems -- giving a total of 45 1- and 2-D comparison observables in two toroidal magnetic field directions. The dataset is used to validate three flux-driven 3D fluid-turbulence models: GBS, GRILLIX and TOKAM3X. With each model, we perform simulations of the TCV-X21 scenario, tuning the particle and power source rates to achieve a reasonable match of the upstream separatrix value of density and electron temperature. We find that the simulations match the experimental profiles for most observables at the OMP -- both in terms of profile shape and absolute magnitude -- while a poorer agreement is found towards the divertor targets. The match between simulation and experiment is seen to be sensitive to the value of the resistivity, the heat conductivities, the power injection rate and the choice of sheath boundary conditions. Additionally, despite targeting a sheath-limited regime, the discrepancy between simulations and experiment also suggests that the neutral dynamics should be included. The results of this validation show that turbulence models are able to perform simulations of existing devices and achieve reasonable agreement with experimental measurements. Where disagreement is found, the validation helps to identify how the models can be improved. By publicly releasing the experimental dataset, this work should help to guide and accelerate the development of predictive turbulence simulations of the edge and SOL.

Published
2021
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110. Symmetric Divergence-free tensors in the calculus of variations

Author

Serre, Denis

Subjects
Mathematics - Analysis of PDEs, Mathematical Physics, Physics - Classical Physics
Abstract

Divergence-free symmetric tensors seem ubiquitous in Mathematical Physics. We show that this structure occurs in models that are described by the so-called "second" variational principle, where the argument of the Lagrangian is a closed differential form. Divergence-free tensors are nothing but the second form of the Euler--Lagrange equations. The symmetry is associated with the invariance of the Lagrangian density upon the action of some orthogonal group.

Published
2021

112. Development of tuberculosis treatment decision algorithms in children below 5 years hospitalised with severe acute malnutrition in Zambia and Uganda: a prospective diagnostic cohort study

Author

Marcy, Olivier, Serre, Angeline, Badrichani, Anne, Razafimanantsoa, Manoa, Poublan, Julien, Vessière, Aurélia, Roucher, Clémentine, Occelli, Estelle, Beuscart, Aurélie, Charpin, Aurélie, Habiyambere, Gemma, Mesnier, Salomé, Balestre, Eric, Koskas, Nicolas, D'Elbée, Marc, Font, Hélène, Ton Nu Nguyet, Minh Huyen, Bonnet, Maryline, Lounnas, Manon, Espérou, Hélène, Couffin-Cadiergues, Sandrine, Kuppers, Alexis, Hamze, Benjamin, Wobudeya, Eric, Businge, Gerald Bright, Namulinda, Faith, Sserunjogi, Robert, Nassozi, Rashidah, Barungi, Charlotte, Hellen, Aanyu, Doreen, Muwonge, Kagoya, Eva, Aciparu, Serene, Sophia, Chemutai, Ntambi, Samuel, Wasswa, Amir, Nangozi, Juliet, Chabala, Chishala, Mulenga, Veronica, Shankalala, Perfect, Hambulo, Chimuka, Kapotwe, Vincent, Ngambi, Marjory, Kasakwa, Kunda, Kanyama, Mirriam, Chirwa, Uzima, Chifunda, Kapula, Mundundu, Gae, Zulu, Susan, Nawakwi, Grace, Siasulingana, Teddy, Himwaze, Diana Attan, Chilonga, Jessy, Chimbini, Maria, Chilanga, Mutinta, Chola, Daniel, Mwango, Eustace, Nduna, Bwendo, Inambao, Muleya, Pumbwe, Mwamba, Mwambazi, Mwate, Halende, Barbara, Mumba, Wyclef, Mankunshe, Endreen, Silavwe, Maureen, Chakopo, Moses, Moono, Roy, Chungu, Chalilwe, Zimba, Kevin, Kapasa, Monica, Zyambo, Khozya, Babirekere, Esther, Businge, Gerald, Kapula, Chifunda, and Graham, Stephen

Published
2024
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113. Imported schistosomiasis in travelers: Experience from a referral tropical medicine unit in Barcelona, Spain

Author

Salvador, Fernando, Bocanegra, Cristina, Treviño, Begoña, Sulleiro, Elena, Sánchez-Montalvá, Adrián, Serre-Delcor, Núria, Bosch-Nicolau, Pau, Aznar, M<ce:sup loc='post">a</ce:sup> Luisa, Goterris, Lidia, Pou, Diana, Espiau, María, Martínez-Campreciós, Joan, Espinosa-Pereiro, Juan, Oliveira, Inés, Zarzuela, Francesc, Martínez-Vallejo, Patricia, and Molina, Israel

Published
2024
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115. SNX27: A trans-species cognitive modulator with implications for anxiety and stress susceptibility

Author

Gisela Armada, Susana Roque, Cláudia Serre-Miranda, Liliana Ferreira, Ana Vale, Ana João Rodrigues, Wanjin Hong, Margarida Correia-Neves, and Neide Vieira

Subjects
Nervous system, Cognition, Mood, Sorting Nexin 27, Stress, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429, Neurophysiology and neuropsychology, QP351-495
Abstract

Sorting Nexin 27 (SNX27) is a brain-enriched endosome-associated cargo adaptor that shapes excitatory control, being relevant for cognitive and reward processing, and for several neurological conditions. Despite this, SNX27's role in the nervous system remains poorly explored. To further understand SNX27 function, we performed an extensive behavioral characterization comprising motor, cognitive and emotional dimensions of SNX27+/− mice. Furthermore, attending on the recently described association between SNX27 function and cellular stress signaling mechanisms in vitro, we explored SNX27-stress interplay using a Caenorhabditis elegans Δsnx-27 mutant and wild-type (WT) rodents after stress exposure.SNX27+/− mice, as C. elegans Δsnx-27 mutants, present cognitive impairments, highlighting a conserved role for SNX27 in cognitive modulation across species. Interestingly, SNX27 downmodulation leads to anxiety-like behavior in mice evaluated in the Elevated Plus Maze (EPM). This anxious phenotype is associated with increased dendritic complexity of the bed nucleus of the stria terminalis (BNST) neurons, and increased complexity of the basolateral amygdala (BLA) pyramidal neurons. These findings highlight the still unknown role of SNX27 in anxiety regulation.Moreover, we uncovered a direct link between SNX27 dysfunction and stress susceptibility in C. elegans and found that stress-exposed rodents display decreased SNX27 levels in stress-susceptible brain regions.Altogether, we provided new insights on SNX27's relevance in anxiety-related behaviors and neuronal structure in stress-associated brain regions.

Published
2024
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116. Improving climate change resilience knowledge through a gaming approach: Application to marine submersion in the city of Punaauia, Tahiti

Author

Charlotte Heinzlef, Yoann Lamaury, and Damien Serre

Subjects
Resilience knowledge, Risk knowledge, Knowledge co-production, Decision support tool, Serious game, Resilience observatory, Environmental sciences, GE1-350
Abstract

French Polynesia is a French overseas territory extremely vulnerable to climate risks. However, local risk management strategies focus on crisis management to the detriment of long-term resilience strategies, without integrating the pre-crisis, crisis and post-crisis periods. Through a decision support process, a serious game, intended for local residents, has been developed within a risk and resilience observatory. The objectives of this serious game are multiple: to increase knowledge of risks and resilience in local communities; to develop an understanding of the systemic complexity of resilient risk management; to develop an entertaining and educational tool. This prototype has been developed and tested in French Polynesia. This prototype allowed the players to create links between their sensitive experiences and their theoretical knowledge, allowing them to associate these two dimensions for a better understanding, acceptance and adoption of complex notions, concepts and processes.

Published
2024
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117. Synergistic effect of Panax ginseng, Polygonatum cyrtonema, Epiphyllum oxypetalum, Nelumbo nucifera and Osmanthus fragrans extracts on skin aging regulation. From in silico predictions to in vitro outcome

Author

Chunbo Feng, Catherine Serre, Weimiao Chen, Isabelle Imbert, Le Zhu, and Feng Ling

Subjects
Phytochemicals, Plant extract combination, In silico analysis, skin anti-aging, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Intrinsic and extrinsic aging affect the health of human skin. Extracellular matrix protein degradation, DNA damage and oxidative stress are known to disturb skin architecture and skin homeostasis leading to skin aging. Traditional Chinese Medicine (TCM) delivers a large amount of knowledge regarding the phytotherapeutic power of diverse plants. Panax ginseng, Polygonatum cyrtonema, Epiphyllum oxypetalum, Nelumbo nucifera and Osmanthus fragrans are five plants used in TCM for their protective effect. In this study, several combinations of these TCM plants were explored: first, an in silico analysis was performed to predict their potential to target biological activities in the skin and then, some predictions were verified with in vitro studies to underline the synergistic effect of plant extracts. The results showed a stronger anti-aging activity for the combination with the five plants compared to the combination with Panax ginseng, Polygonatum cyrtonema, Epiphyllum oxypetalum and, compared to Panax ginseng alone.

Published
2024
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118. Epidemiological and clinical trends of imported strongyloidiasis in a referral international health unit, Barcelona, Spain: A 12-year period experience

Author

Fernando Salvador, Begoña Treviño, Elena Sulleiro, Pau Bosch-Nicolau, Ma Luisa Aznar, Lidia Goterris, Juan Espinosa-Pereiro, Diana Pou, Adrián Sánchez-Montalvá, Inés Oliveira, Joan Martínez-Campreciós, Núria Serre-Delcor, Augusto Sao-Avilés, and Israel Molina

Subjects
Strongyloidiasis, Strongyloides stercoralis, Imported, Screening, Arctic medicine. Tropical medicine, RC955-962, Infectious and parasitic diseases, RC109-216
Abstract

Background: Imported strongyloidiasis in non-endemic countries has increasingly been diagnosed. The aim of the present study is to describe the main epidemiological and clinical characteristics of patients with imported strongyloidiasis attended in a referral International Health Unit and to detect trend changes over a 12-year period. Methods: This is an observational retrospective study including all imported strongyloidiasis cases seen at the International Health Unit Vall d’Hebron-Drassanes (Barcelona, Spain) from January 2009 to December 2020. Epidemiological and clinical characteristics from included patients were collected. Results: Overall, 865 cases of imported strongyloidiasis were diagnosed, of whom 472 (54.6 %) were men and mean age was 38.7 (SD 13.4) years. Most cases were diagnosed in migrants (830, 96 %). The distribution of the geographic origin was: Latin America (561, 67.6 %), Sub-Saharan Africa (148, 17.8 %), Asia (113, 13.6 %), North Africa (5, 0.6 %), Eastern Europe (2, 0.2 %), and North America (1, 0.1 %). The main reasons for consultation at the Unit were screening of health status (371, 42.9 %), laboratory test alteration (367, 42.4 %), gastrointestinal symptoms (56, 6.5 %), cutaneous symptoms (26, 3 %), and other clinical symptoms (45, 5.2 %). An increase in the number of cases was observed in the last years of the study period. Conclusions: Imported strongyloidiasis has increasingly been diagnosed in our referral unit, mostly due to screening strategies implementation. Most of the patients were young migrants coming from Latin America, with no symptoms at the time of diagnosis. The optimization of screening strategies will increase the detection and treatment of cases, reducing potential complications.

Published
2024
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119. Racial/Ethnic Disparities in Alzheimer’s Disease Risk: Role of Exposure to Ambient Fine Particles

Author

Younan, Diana, Wang, Xinhui, Gruenewald, Tara, Gatz, Margaret, Serre, Marc L, Vizuete, William, Braskie, Meredith N, Woods, Nancy F, Kahe, Ka, Garcia, Lorena, Lurmann, Fred, Manson, JoAnn E, Chui, Helena C, Wallace, Robert B, Espeland, Mark A, and Chen, Jiu-Chiuan

Subjects
Dementia, Behavioral and Social Science, Alzheimer's Disease, Aging, Mental Health, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurosciences, Acquired Cognitive Impairment, Brain Disorders, Neurodegenerative, Cardiovascular, Prevention, Clinical Research, Good Health and Well Being, Aged, Air Pollutants, Air Pollution, Alzheimer Disease, Environmental Exposure, Female, Humans, Particulate Matter, Prospective Studies, Air pollution, Epidemiology, Incidence, Clinical Sciences, Gerontology
Abstract

BackgroundWhether racial/ethnic disparities in Alzheimer's disease (AD) risk may be explained by ambient fine particles (PM2.5) has not been studied.MethodWe conducted a prospective, population-based study on a cohort of Black (n = 481) and White (n = 6 004) older women (aged 65-79) without dementia at enrollment (1995-1998). Cox models accounting for competing risk were used to estimate the hazard ratio (HR) for racial/ethnic disparities in AD (1996-2010) defined by Diagnostic and Statistical Manual of Mental Disorders, 4th edition and the association with time-varying annual average PM2.5 (1999-2010) estimated by spatiotemporal model.ResultsOver an average follow-up of 8.3 (±3.5) years with 158 incident cases (21 in Black women), the racial disparities in AD risk (range of adjusted HRBlack women = 1.85-2.41) observed in various models could not be explained by geographic region, age, socioeconomic characteristics, lifestyle factors, cardiovascular risk factors, and hormone therapy assignment. Estimated PM2.5 exposure was higher in Black (14.38 ± 2.21 µg/m3) than in White (12.55 ± 2.76 µg/m3) women, and further adjustment for the association between PM2.5 and AD (adjusted HRPM2.5 = 1.18-1.28) slightly reduced the racial disparities by 2%-6% (HRBlack women = 1.81-2.26). The observed association between PM2.5 and AD risk was ~2 times greater in Black (HRPM2.5 = 2.10-2.60) than in White (HRPM2.5 = 1.07-1.15) women (range of interaction ps:

Published
2022

120. Understanding the computational demands underlying visual reasoning

Author

Vaishnav, Mohit, Cadene, Remi, Alamia, Andrea, Linsley, Drew, VanRullen, Rufin, and Serre, Thomas

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Visual understanding requires comprehending complex visual relations between objects within a scene. Here, we seek to characterize the computational demands for abstract visual reasoning. We do this by systematically assessing the ability of modern deep convolutional neural networks (CNNs) to learn to solve the "Synthetic Visual Reasoning Test" (SVRT) challenge, a collection of twenty-three visual reasoning problems. Our analysis reveals a novel taxonomy of visual reasoning tasks, which can be primarily explained by both the type of relations (same-different vs. spatial-relation judgments) and the number of relations used to compose the underlying rules. Prior cognitive neuroscience work suggests that attention plays a key role in humans' visual reasoning ability. To test this hypothesis, we extended the CNNs with spatial and feature-based attention mechanisms. In a second series of experiments, we evaluated the ability of these attention networks to learn to solve the SVRT challenge and found the resulting architectures to be much more efficient at solving the hardest of these visual reasoning tasks. Most importantly, the corresponding improvements on individual tasks partially explained our novel taxonomy. Overall, this work provides an granular computational account of visual reasoning and yields testable neuroscience predictions regarding the differential need for feature-based vs. spatial attention depending on the type of visual reasoning problem., Comment: 26 pages, 16 figures

Published
2021
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121. Projective properties of Divergence-free symmetric tensors, and new dispersive estimates in gas dynamics

Author

Serre, Denis

Subjects
Mathematics - Analysis of PDEs, Physics - Classical Physics
Abstract

The class of Divergence-free symmetric tensors is ubiquitous in Continuum Mechanics. We show its invariance under projective transformations of the independent variables. This action, which preserves the positiveness, extends Sophus Lie's group analysis of Newtonian dynamics.When applied to models of gas dynamics --~such as Euler system or Boltzmann equation,~-- in combination with Compensated Integrability, this yields new dispersive estimates. The most accurate one is obtained for mono-atomic gases. Then the space-time integral of $t\rho^\frac1d p$ is bounded in terms of the total mass and moment of inertia alone.

Published
2021

122. Multi-temperature Generalized Zhdanov Closure for Scrape-Off Layer/Edge Applications

Author

Raghunathan, Madhusudan, Marandet, Yannick, Bufferand, Hugo, Ciraolo, Guido, Ghendrih, Philippe, Tamain, Patrick, and Serre, Eric

Subjects
Physics - Plasma Physics
Abstract

The derivation of the multi-temperature generalized Zhdanov closure is provided starting from the most general form of the left hand side of the moment averaged kinetic equation with the Sonine-Hermite polynomial ansatz for an arbitrary number of moments. The process of arriving at the reduced higher-order moment equations, with its assumptions and approximations, is explicitly outlined. The generalized multi-species, multi-temperature coefficients from the authors' previous article are used to compute values of higher order moments such as heat flux in terms of the lower order moments. Transport coefficients and the friction and thermal forces for magnetic confinement fusion relevant cases with the generalized coefficients are compared to the scheme with the single-temperature coefficients previously provided by Zhdanov et al. It is found that the 21N-moment multi-temperature coefficients are adequate for most cases relevant to fusion. Furthermore, the 21N-moment scheme is also tested against the trace approximation to determine the range of validity of the trace approximation with respect to fusion relevant plasmas. Possible refinements to the closure scheme are illustrated as well, in order to account for quantities which might be significant in certain schemes such as the drift approximation., Comment: Submitted to Plasma Physics and Controlled Fusion, July 15, 2021

Published
2021
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125. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author

Brauer, Michael, Roth, Gregory A, Aravkin, Aleksandr Y, Zheng, Peng, Abate, Kalkidan Hassen, Abate, Yohannes Habtegiorgis, Abbafati, Cristiana, Abbasgholizadeh, Rouzbeh, Abbasi, Madineh Akram, Abbasian, Mohammadreza, Abbasifard, Mitra, Abbasi-Kangevari, Mohsen, Abd ElHafeez, Samar, Abd-Elsalam, Sherief, Abdi, Parsa, Abdollahi, Mohammad, Abdoun, Meriem, Abdulah, Deldar Morad, Abdullahi, Auwal, Abebe, Mesfin, Abedi, Aidin, Abedi, Armita, Abegaz, Tadesse M, Abeldaño Zuñiga, Roberto Ariel, Abiodun, Olumide, Abiso, Temesgen Lera, Aboagye, Richard Gyan, Abolhassani, Hassan, Abouzid, Mohamed, Aboye, Girma Beressa, Abreu, Lucas Guimarães, Abualruz, Hasan, Abubakar, Bilyaminu, Abu-Gharbieh, Eman, Abukhadijah, Hana Jihad Jihad, Aburuz, Salahdein, Abu-Zaid, Ahmed, Adane, Mesafint Molla, Addo, Isaac Yeboah, Addolorato, Giovanni, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Aden, Bashir, Adetunji, Juliana Bunmi, Adeyeoluwa, Temitayo Esther, Adha, Rishan, Adibi, Amin, Adnani, Qorinah Estiningtyas Sakilah, Adzigbli, Leticia Akua, Afolabi, Aanuoluwapo Adeyimika, Afolabi, Rotimi Felix, Afshin, Ashkan, Afyouni, Shadi, Afzal, Muhammad Sohail, Afzal, Saira, Agampodi, Suneth Buddhika, Agbozo, Faith, Aghamiri, Shahin, Agodi, Antonella, Agrawal, Anurag, Agyemang-Duah, Williams, Ahinkorah, Bright Opoku, Ahmad, Aqeel, Ahmad, Danish, Ahmad, Firdos, Ahmad, Noah, Ahmad, Shahzaib, Ahmad, Tauseef, Ahmed, Ali, Ahmed, Anisuddin, Ahmed, Ayman, Ahmed, Luai A, Ahmed, Muktar Beshir, Ahmed, Safoora, Ahmed, Syed Anees, Ajami, Marjan, Akalu, Gizachew Taddesse, Akara, Essona Matatom, Akbarialiabad, Hossein, Akhlaghi, Shiva, Akinosoglou, Karolina, Akinyemiju, Tomi, Akkaif, Mohammed Ahmed, Akkala, Sreelatha, Akombi-Inyang, Blessing, Al Awaidy, Salah, Al Hasan, Syed Mahfuz, Alahdab, Fares, AL-Ahdal, Tareq Mohammed Ali, Alalalmeh, Samer O, Alalwan, Tariq A, Al-Aly, Ziyad, Alam, Khurshid, Alam, Nazmul, Alanezi, Fahad Mashhour, Alanzi, Turki M, Albakri, Almaza, AlBataineh, Mohammad T, Aldhaleei, Wafa A, Aldridge, Robert W, Alemayohu, Mulubirhan Assefa, Alemu, Yihun Mulugeta, Al-Fatly, Bassam, Al-Gheethi, Adel Ali Saeed, Al-Habbal, Khairat, Alhabib, Khalid F, Alhassan, Robert Kaba, Ali, Abid, Ali, Amjad, Ali, Beriwan Abdulqadir, Ali, Iman, Ali, Liaqat, Ali, Mohammed Usman, Ali, Rafat, Ali, Syed Shujait Shujait, Ali, Waad, Alicandro, Gianfranco, Alif, Sheikh Mohammad, Aljunid, Syed Mohamed, Alla, François, Al-Marwani, Sabah, Al-Mekhlafi, Hesham M, Almustanyir, Sami, Alomari, Mahmoud A, Alonso, Jordi, Alqahtani, Jaber S, Alqutaibi, Ahmed Yaseen, Al-Raddadi, Rajaa M, Alrawashdeh, Ahmad, Al-Rifai, Rami Hani, Alrousan, Sahel Majed, Al-Sabah, Salman Khalifah, Alshahrani, Najim Z, Altaany, Zaid, Altaf, Awais, Al-Tawfiq, Jaffar A, Altirkawi, Khalid A, Aluh, Deborah Oyine, Alvis-Guzman, Nelson, Alvis-Zakzuk, Nelson J, Alwafi, Hassan, Al-Wardat, Mohammad Sami, Al-Worafi, Yaser Mohammed, Aly, Hany, Aly, Safwat, Alzoubi, Karem H, Al-Zyoud, Walid, Amaechi, Uchenna Anderson, Aman Mohammadi, Masous, 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Malik, Ahmad Azam, Malik, Iram, Malinga, Lesibana Anthony, Malta, Deborah Carvalho, Mamun, Abdullah A, Manda, Ana Laura, Manla, Yosef, Mansour, Ali, Mansouri, Borhan, Mansouri, Pejman, Mansourian, Marjan, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Manu, Emmanuel, Marateb, Hamid Reza, Maravilla, Joemer C, Marsh, Elizabeth, Martinez, Gabriel, Martinez-Piedra, Ramon, Martini, Santi, Martins-Melo, Francisco Rogerlândio, Martorell, Miquel, Marx, Wolfgang, Maryam, Sharmeen, Mathangasinghe, Yasith, Mathioudakis, Alexander G, Matozinhos, Fernanda Penido, Mattumpuram, Jishanth, Maugeri, Andrea, Maulik, Pallab K, Mayeli, Mahsa, Mazidi, Mohsen, Mazzotti, Antonio, McGrath, John J, McKee, Martin, McKowen, Anna Laura W, McLaughlin, Susan A, McPhail, Michael A, McPhail, Steven M, Mechili, Enkeleint A, Mehmood, Asim, Mehmood, Khalid, Mehrabani-Zeinabad, Kamran, Mehrabi Nasab, Entezar, Meier, Toni, Mejia-Rodriguez, Fabiola, Mekene Meto, Tesfahun, Mekonnen, Birye Dessalegn, Menezes, Ritesh 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Mondello, Stefania, Moni, Mohammad Ali, Moodi Ghalibaf, AmirAli, Moore, Catrin E, Moradi, Maryam, Moradi, Yousef, Moraga, Paula, Morawska, Lidia, Moreira, Rafael Silveira, Morovatdar, Negar, Morrison, Shane Douglas, Morze, Jakub, Mosaddeghi Heris, Reza, Mossialos, Elias, Motappa, Rohith, Mougin, Vincent, Mousavi, Parsa, Msherghi, Ahmed, Mubarik, Sumaira, Muccioli, Lorenzo, Mueller, Ulrich Otto, Mulita, Francesk, Mullany, Erin C, Munjal, Kavita, Murillo-Zamora, Efrén, Murlimanju, BV, Musina, Ana-Maria, Mustafa, Ghulam, Muthu, Sathish, Muthupandian, Saravanan, Muthusamy, Raman, Muzaffar, Muhammad, Myung, Woojae, Nafei, Ayoub, Nagarajan, Ahamarshan Jayaraman, Nagaraju, Shankar Prasad, Nagel, Gabriele, Naghavi, Mohsen, Naghavi, Pirouz, Naik, Ganesh R, Naik, Gurudatta, Nainu, Firzan, Nair, Tapas Sadasivan, Najdaghi, Soroush, Nakhostin Ansari, Noureddin, Nanavaty, Dhairya P, Nangia, Vinay, Narasimha Swamy, Sreenivas, Narimani Davani, Delaram, Nascimento, Bruno Ramos, Nascimento, Gustavo G, Nashwan, Abdulqadir J, Natto, Zuhair S, Nauman, Javaid, Navaratna, Samidi N K, Naveed, Muhammad, Nayak, Biswa Prakash, Nayak, Vinod C, Ndejjo, Rawlance, Nduaguba, Sabina Onyinye, Negash, Hadush, Negoi, Ionut, Negoi, Ruxandra Irina, Nejadghaderi, Seyed Aria, Nejjari, Chakib, Nematollahi, Mohammad Hadi, Nepal, Samata, Neupane, Subas, Ng, Marie, Nguefack-Tsague, Georges, Ngunjiri, Josephine W, Nguyen, Dang H, Nguyen, Nhien Ngoc Y, Nguyen, Phat Tuan, Nguyen, Phuong The, Nguyen, Van Thanh, Nguyen Tran Minh, Duc, Niazi, Robina Khan, Nicholson, Sneha Ingle, Nie, Jing, Nikoobar, Ali, Nikpoor, Amin Reza, Ningrum, Dina Nur Anggraini, Nnaji, Chukwudi A, Noman, Efaq Ali, Nomura, Shuhei, Noroozi, Nafise, Norrving, Bo, Noubiap, Jean Jacques, Nri-Ezedi, Chisom Adaobi, Ntaios, George, Ntsekhe, Mpiko, Nunemo, Mengistu H, Nurrika, Dieta, Nutor, Jerry John, Oancea, Bogdan, O'Connell, Erin M, Odetokun, Ismail A, O'Donnell, Martin James, Oduro, Michael Safo, Ogunfowokan, Adesola Adenike, Ogunkoya, Abiola, Oh, In-Hwan, Okati-Aliabad, Hassan, Okeke, Sylvester Reuben, Okekunle, Akinkunmi Paul, Okonji, Osaretin Christabel, Olagunju, Andrew T, Olasupo, Omotola O, Olatubi, Matthew Idowu, Oliveira, Arão Belitardo, Oliveira, Gláucia Maria Moraes, Olorukooba, Abdulhakeem Abayomi, Olufadewa, Isaac Iyinoluwa, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Oluwafemi, Yinka Doris, Omar, Hany A, Omar Bali, Ahmed, Omer, Goran Latif, Ong, Kanyin Liane, Ong, Sokking, Onwujekwe, Obinna E, Onyedibe, Kenneth Ikenna, Oppong, Anita Frimpomaa, Ordak, Michal, Orish, Verner N, Ornello, Raffaele, Orpana, Heather M, Ortiz, Alberto, Ortiz-Prado, Esteban, Osman, Wael M S, Ostroff, Samuel M, Osuagwu, Uchechukwu Levi, Otoiu, Adrian, Otstavnov, Nikita, Otstavnov, Stanislav S, Ouyahia, Amel, Owolabi, Mayowa O, Oyeyemi, Ifeoluwa Temitayo, Oyeyemi, Oyetunde T, P A, Mahesh Padukudru, Pacheco-Barrios, Kevin, Padron-Monedero, Alicia, Padubidri, Jagadish Rao, Pal, Pramod Kumar, Palicz, Tamás, Pan, Feng, Pan, Hai-Feng, Pana, Adrian, Panda, Sujogya K, Panda-Jonas, Songhomitra, Pandey, Ashok, Pandi-Perumal, Seithikurippu R, Pangaribuan, Helena Ullyartha, Pantazopoulos, Ioannis, Pantea Stoian, Anca Mihaela, Papadopoulou, Paraskevi, Parent, Marie C, Parija, Pragyan Paramita, Parikh, Romil R, Park, Seoyeon, Park, Sungchul, Parsons, Nicholas, Pashaei, Ava, Pasovic, Maja, Passera, Roberto, Patil, Shankargouda, Patoulias, Dimitrios, Patthipati, Venkata Suresh, Paudel, Uttam, Pawar, Shrikant, Pazoki Toroudi, Hamidreza, Peden, Amy E, Pedersini, Paolo, Peng, Minjin, Pensato, Umberto, Pepito, Veincent Christian Filipino, Peprah, Emmanuel K, Peprah, Prince, Peres, Mario F P, Perianayagam, Arokiasamy, Perico, Norberto, Perna, Simone, Pesudovs, Konrad, Petcu, Ionela-Roxana, Petermann-Rocha, Fanny Emily, Pham, Hoang Tran, Philip, Anil K, Phillips, Michael R, Pickering, Brandon V, Pierannunzio, Daniela, Pigeolet, Manon, Pigott, David M, Piracha, Zahra Zahid, Piradov, Michael A, Pisoni, Enrico, Piyasena, Mapa Prabhath, Plass, Dietrich, Plotnikov, Evgenii, Poddighe, Dimitri, Polkinghorne, Kevan R, Poluru, Ramesh, Pond, Constance Dimity, Popovic, Djordje S, Porru, Fabio, Postma, Maarten J, Poudel, Govinda Raj, Pour-Rashidi, Ahmad, Pourshams, Akram, Pourtaheri, Naeimeh, Prabhu, Disha, Prada, Sergio I, Pradhan, Jalandhar, Pradhan, Pranil Man Singh, Prasad, Manya, Prates, Elton Junio Sady, Purnobasuki, Hery, Purohit, Bharathi M, Puvvula, Jagadeesh, Qasim, Nameer Hashim, Qattea, Ibrahim, Qazi, Asma Saleem, Qian, Gangzhen, Qiu, Suli, Rabiee Rad, Mehrdad, Radfar, Amir, Radhakrishnan, Raghu Anekal, Radhakrishnan, Venkatraman, Raeisi Shahraki, Hadi, Rafferty, Quinn, Rafiei, Alireza, Raggi, Alberto, Raghav, Pankaja Raghav, Raheem, Nasiru, Rahim, Fakher, Rahim, Md Jillur, Rahimifard, Mahban, Rahimi-Movaghar, Vafa, Rahman, Md Obaidur, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Rahmani, Bita, Rahmanian, Mohammad, Rahmanian, Nazanin, Rahmanian, Vahid, Rahmati, Masoud, Rahmawaty, Setyaningrum, Raimondo, Diego, Rajaa, Sathish, Rajendran, Vinoth, Rajput, Prashant, Ramadan, Mahmoud Mohammed, Ramasamy, Shakthi Kumaran, Ramasubramani, Premkumar, Ramazanu, Sheena, Ramteke, Pramod W, Rana, Juwel, Rana, Kritika, Ranabhat, Chhabi Lal, Rane, Amey, Rani, Usha, Ranta, Annemarei, Rao, Chythra R, Rao, Mithun, Rao, Puja C, Rao, Sowmya J, Rasella, Davide, Rashedi, Sina, Rashedi, Vahid, Rashidi, Mahsa, Rashidi, Mohammad-Mahdi, Rasouli-Saravani, Ashkan, Ratan, Zubair Ahmed, Rathnaiah Babu, Giridhara, Rauniyar, Santosh Kumar, Rautalin, Ilari, Rawaf, David Laith, Rawaf, Salman, Rawassizadeh, Reza, Razo, Christian, Reda, Zinabu Ferede Ferede, Reddy, Murali Mohan Rama Krishna, Redwan, Elrashdy Moustafa Mohamed, Reifels, Lennart, Reitsma, Marissa B, Remuzzi, Giuseppe, Reshmi, Bhageerathy, Resnikoff, Serge, Restaino, Stefano, Reyes, Luis Felipe, Rezaei, Maryam, Rezaei, Nazila, Rezaei, Negar, Rezaeian, Mohsen, Rhee, Taeho Gregory, Riaz, Mavra A, Ribeiro, Antonio Luiz P, Rickard, Jennifer, Robinson-Oden, Hannah Elizabeth, Rodrigues, Célia Fortuna, Rodrigues, Mónica, Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo, Romadlon, Debby Syahru, Ronfani, Luca, Rosauer, Jennifer Jacqueline, Roshandel, Gholamreza, Rostamian, Morteza, Rotimi, Kunle, Rout, Himanshu Sekhar, Roy, Bedanta, Roy, Nitai, Rubagotti, Enrico, Ruela, Guilherme de Andrade, Rumisha, Susan Fred, Runghien, Tilleye, Russo, Michele, Ruzzante, Sacha Walde, S N, Chandan, Saad, Aly M A, Saber, Korosh, Saber-Ayad, Maha Mohamed, Sabour, Siamak, Sacco, Simona, Sachdev, Perminder S, Sachdeva, Rajesh, Saddik, Basema, Saddler, Adam, Sadee, Bashdar Abuzed, Sadeghi, Ehsan, Sadeghi, Masoumeh, Sadeghi Majd, Elham, Saeb, Mohammad Reza, Saeed, Umar, Safari, Mehdi, Safi, Sare, Safi, Sher Zaman, Sagar, Rajesh, Sagoe, Dominic, Saheb Sharif-Askari, Fatemeh, Saheb Sharif-Askari, Narjes, Sahebkar, Amirhossein, Sahoo, Soumya Swaroop, Sahu, Monalisha, Saif, Zahra, Sajid, Mirza Rizwan, Sakshaug, Joseph W, Salam, Nasir, Salamati, Payman, Salami, Afeez Abolarinwa, Salaroli, Luciane B, Salehi, Leili, Salehi, Sana, Salem, Marwa Rashad, Salem, Mohammed Z Y, Salihu, Dauda, Salimi, Sohrab, Salum, Giovanni A, Samadi Kafil, Hossein, Samadzadeh, Sara, Samodra, Yoseph Leonardo, Samuel, Vijaya Paul, Samy, Abdallah M, Sanabria, Juan, Sanjeev, Rama Krishna, Sanna, Francesca, Santomauro, Damian Francesco, Santric-Milicevic, Milena M, Sarasmita, Made Ary, Saraswathy, Sivan Yegnanarayana Iyer, Saravanan, Aswini, Saravi, Babak, Sarikhani, Yaser, Sarmiento-Suárez, Rodrigo, Sarode, Gargi Sachin, Sarode, Sachin C, Sartorius, Benn, Sarveazad, Arash, Sathian, Brijesh, Sattin, Davide, Sawhney, Monika, Saya, Ganesh Kumar, Sayeed, Abu, Sayeed, Md Abu, Sayyah, Mehdi, Schinckus, Christophe, Schmidt, Maria Inês, Schuermans, Art, Schumacher, Austin E, Schutte, Aletta Elisabeth, Schwarzinger, Michaël, Schwebel, David C, Schwendicke, Falk, Selvaraj, Siddharthan, Semreen, Mohammad H, Senthilkumaran, Subramanian, Serban, Dragos, Serre, Marc L, Sethi, Yashendra, Shafie, Mahan, Shah, Humaira, Shah, Nilay S, Shah, Pritik A, Shah, Syed Mahboob, Shahbandi, Ataollah, Shaheen, Amira A, Shahid, Samiah, Shahid, Wajeehah, Shahsavari, Hamid R, Shahwan, Moyad Jamal, Shaikh, Masood Ali, Shaikh, Summaiya Zareen, Shalash, Ali S, Sham, Sunder, Shamim, Muhammad Aaqib, Shams-Beyranvand, Mehran, Shamshirgaran, Mohammad Ali, Shamsi, Mohammad Anas, Shanawaz, Mohd, Shankar, Abhishek, Sharfaei, Sadaf, Sharifan, Amin, Sharifi-Rad, Javad, Sharma, Manoj, Sharma, Ujjawal, Sharma, Vishal, Shastry, Rajesh P, Shavandi, Amin, Shehabeldine, Amr Mohamed Elsayed, Shehzadi, Somia, Sheikh, Aziz, Shen, Jiabin, Shetty, Adithi, Shetty, B Suresh Kumar, Shetty, Pavanchand H, Shiani, Amir, Shiferaw, Desalegn, Shigematsu, Mika, Shin, Min-Jeong, Shiri, Rahman, Shittu, Aminu, Shiue, Ivy, Shivakumar, K M, Shivarov, Velizar, Shool, Sina, Shorofi, Seyed Afshin, Shrestha, Rajan, Shrestha, Sunil, Shuja, Kanwar Hamza, Shuval, Kerem, Si, Yafei, Siddig, Emmanuel Edwar, Silva, Diego Augusto Santos, Silva, Luís Manuel Lopes Rodrigues, Silva, Soraia, Silva, Thales Philipe R, Simpson, Colin R, Singh, Abhinav, Singh, Balbir Bagicha, Singh, Baljinder, Singh, Garima, Singh, Harmanjit, Singh, Jasvinder A, Singh, Mahendra, Singh, Narinder Pal, Singh, Paramdeep, Singh, Surjit, Sinto, Robert, Sivakumar, Shravan, Siwal, Samarjeet Singh, Skhvitaridze, Natia, Skou, Søren T, Sleet, David A, Sobia, Farrukh, Soboka, Matiwos, Socea, Bogdan, Solaimanian, Shahabaddin, Solanki, Ranjan, Solanki, Shipra, Soliman, Sameh S M, Somayaji, Ranjani, Song, Yi, Sorensen, Reed J D, Soriano, Joan B, Soyiri, Ireneous N, Spartalis, Michael, Spearman, Sandra, Spencer, Cory N, Sreeramareddy, Chandrashekhar T, Stachteas, Panagiotis, Stafford, Lauryn K, Stanaway, Jeffrey D, Stanikzai, Muhammad Haroon, Stein, Caroline, Stein, Dan J, Steinbeis, Fridolin, Steiner, Caitlyn, Steinke, Sabine, Steiropoulos, Paschalis, Stockfelt, Leo, Stokes, Mark A, Straif, Kurt, Stranges, Saverio, Subedi, Narayan, Subramaniyan, Vetriselvan, Suleman, Muhammad, Suliankatchi Abdulkader, Rizwan, Sundström, Johan, Sunkersing, David, Sunnerhagen, Katharina S, Suresh, Vinay, Swain, Chandan Kumar, Szarpak, Lukasz, Szeto, Mindy D, Tabaee Damavandi, Payam, Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabatabaei Malazy, Ozra, Tabatabaeizadeh, Seyed-Amir, Tabatabai, Shima, Tabche, Celine, Tabish, Mohammad, Tadakamadla, Santosh Kumar, Taheri Abkenar, Yasaman, Taheri Soodejani, Moslem, Taherkhani, Amir, Taiba, Jabeen, Takahashi, Ken, Talaat, Iman M, Tamuzi, Jacques Lukenze, Tan, Ker-Kan, Tang, Haosu, Tat, Nathan Y, Taveira, Nuno, Tefera, Yibekal Manaye, Tehrani-Banihashemi, Arash, Temesgen, Worku Animaw, Temsah, Mohamad-Hani, Teramoto, Masayuki, Terefa, Dufera Rikitu, Teye-Kwadjo, Enoch, Thakur, Ramna, Thangaraju, Pugazhenthan, Thankappan, Kavumpurathu Raman, Thapar, Rekha, Thayakaran, Rasiah, Thirunavukkarasu, Sathish, Thomas, Nihal, Thomas, Nikhil Kenny, Tian, Jing, Tichopad, Ales, Ticoalu, Jansje Henny Vera, Tiruye, Tenaw Yimer, Tobe-Gai, Ruoyan, Tolani, Musliu Adetola, Tolossa, Tadesse, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Fotis, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Trabelsi, Khaled, Tran, Jasmine T, Tran, Mai Thi Ngoc, Tran, Nghia Minh, Trico, Domenico, Trihandini, Indang, Troeger, Christopher E, Tromans, Samuel Joseph, Truyen, Thien Tan Tri Tai, Tsatsakis, Aristidis, Tsermpini, Evangelia Eirini, Tumurkhuu, Munkhtuya, Udoakang, Aniefiok John, Udoh, Arit, Ullah, Atta, Ullah, Saeed, Ullah, Sana, Umair, Muhammad, Umakanthan, Srikanth, Unim, Brigid, Unnikrishnan, Bhaskaran, Upadhyay, Era, Urso, Daniele, Usman, Jibrin Sammani, Vaithinathan, Asokan Govindaraj, Vakili, Omid, Valenti, Mario, Valizadeh, Rohollah, Van den Eynde, Jef, van Donkelaar, Aaron, Varga, Orsolya, Vart, Priya, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vasic, Milena, Vaziri, Siavash, Venketasubramanian, Narayanaswamy, Verghese, Nicholas Alexander, Verma, Madhur, Veroux, Massimiliano, Verras, Georgios-Ioannis, Vervoort, Dominique, Villafañe, Jorge Hugo, Villalobos-Daniel, Victor E, Villani, Leonardo, Villanueva, Gabriela Ines, Vinayak, Manish, Violante, Francesco S, Vlassov, Vasily, Vo, Bay, Vollset, Stein Emil, Volovat, Simona Ruxandra, Vos, Theo, Vujcic, Isidora S, Waheed, Yasir, Wang, Cong, Wang, Fang, Wang, Shu, Wang, Yanzhong, Wang, Yuan-Pang, Wanjau, Mary Njeri, Waqas, Muhammad, Ward, Paul, Waris, Abdul, Wassie, Emebet Gashaw, Weerakoon, Kosala Gayan, Weintraub, Robert G, Weiss, Daniel J, Weiss, Eli J, Weldetinsaa, Haftom Legese Legese, Wells, Katherine M, Wen, Yi Feng, Wiangkham, Taweewat, Wickramasinghe, Nuwan Darshana, Wilkerson, Caroline, Willeit, Peter, Wilson, Shadrach, Wong, Yen Jun, Wongsin, Utoomporn, Wozniak, Sarah, Wu, Chenkai, Wu, Dongze, Wu, Felicia, Wu, Zenghong, Xia, Juan, Xiao, Hong, Xu, Suowen, Xu, Xiaoyue, Xu, Yvonne Yiru, Yadav, Mukesh Kumar, Yaghoubi, Sajad, Yamagishi, Kazumasa, Yang, Lin, Yano, Yuichiro, Yaribeygi, Habib, Yasufuku, Yuichi, Ye, Pengpeng, Yesodharan, Renjulal, Yesuf, Subah Abderehim, Yezli, Saber, Yi, Siyan, Yiğit, Arzu, Yigzaw, Zeamanuel Anteneh, Yin, Dehui, Yip, Paul, Yismaw, Malede Berihun, Yon, Dong Keon, Yonemoto, Naohiro, You, Yuyi, Younis, Mustafa Z, Yousefi, Zabihollah, Yu, Chuanhua, Yu, Yong, Zadey, Siddhesh, Zadnik, Vesna, Zakham, Fathiah, Zaki, Nazar, Zakzuk, Josefina, Zamagni, Giulia, Zaman, Sojib Bin, Zandieh, Ghazal G Z, Zanghì, Aurora, Zar, Heather J, Zare, Iman, Zarimeidani, Fatemeh, Zastrozhin, Mikhail Sergeevich, Zeng, Youjie, Zhai, Chunxia, Zhang, Anthony Lin, Zhang, Haijun, Zhang, Liqun, Zhang, Meixin, Zhang, Yunquan, Zhang, Zhenyu, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhao, Jeff T, Zhao, Xiu-Ju George, Zhao, Yang, Zhao, Yong, Zhong, Chenwen, Zhou, Jingjing, Zhou, Juexiao, Zhou, Shangcheng, Zhu, Bin, Zhu, Lei, Zhu, Zhaohua, Ziaeian, Boback, Ziafati, Makan, Zielińska, Magdalena, Zimsen, Stephanie R M, Zoghi, Ghazal, Zoller, Thomas, Zumla, Alimuddin, Zyoud, Sa'ed H, Zyoud, Samer H, Murray, Christopher J L, and Gakidou, Emmanuela

Published
2024
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131. Efficacy of three benznidazole dosing strategies for adults living with chronic Chagas disease (MULTIBENZ): an international, randomised, double-blind, phase 2b trial

Author

Bosch-Nicolau, Pau, Fernández, Marisa L, Sulleiro, Elena, Villar, Juan Carlos, Perez-Molina, José A, Correa-Oliveira, Rodrigo, Sosa-Estani, Sergio, Sánchez-Montalvá, Adrián, del Carmen Bangher, Maria, Moreira, Otacilio C, Salvador, Fernando, Mota Ferreira, Ariela, Eloi-Santos, Silvana Maria, Serre-Delcor, Núria, Ramírez, Juan Carlos, Silgado, Aroa, Oliveira, Inés, Martín, Oihane, Aznar, Maria Luisa, Ribeiro, Antonio Luiz P, Almeida, Paulo Emilio Clementino, Chamorro-Tojeiro, Sandra, Espinosa-Pereiro, Juan, de Paula, Alfredo Mauricio Batista, Váquiro-Herrera, Eliana, Tur, Carmen, and Molina, Israel

Published
2024
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138. Tracking Without Re-recognition in Humans and Machines

Author

Linsley, Drew, Malik, Girik, Kim, Junkyung, Govindarajan, Lakshmi N, Mingolla, Ennio, and Serre, Thomas

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Imagine trying to track one particular fruitfly in a swarm of hundreds. Higher biological visual systems have evolved to track moving objects by relying on both appearance and motion features. We investigate if state-of-the-art deep neural networks for visual tracking are capable of the same. For this, we introduce PathTracker, a synthetic visual challenge that asks human observers and machines to track a target object in the midst of identical-looking "distractor" objects. While humans effortlessly learn PathTracker and generalize to systematic variations in task design, state-of-the-art deep networks struggle. To address this limitation, we identify and model circuit mechanisms in biological brains that are implicated in tracking objects based on motion cues. When instantiated as a recurrent network, our circuit model learns to solve PathTracker with a robust visual strategy that rivals human performance and explains a significant proportion of their decision-making on the challenge. We also show that the success of this circuit model extends to object tracking in natural videos. Adding it to a transformer-based architecture for object tracking builds tolerance to visual nuisances that affect object appearance, resulting in a new state-of-the-art performance on the large-scale TrackingNet object tracking challenge. Our work highlights the importance of building artificial vision models that can help us better understand human vision and improve computer vision.

Published
2021

139. KuraNet: Systems of Coupled Oscillators that Learn to Synchronize

Author

Ricci, Matthew, Jung, Minju, Zhang, Yuwei, Chalvidal, Mathieu, Soni, Aneri, and Serre, Thomas

Subjects
Nonlinear Sciences - Adaptation and Self-Organizing Systems, Computer Science - Machine Learning
Abstract

Networks of coupled oscillators are some of the most studied objects in the theory of dynamical systems. Two important areas of current interest are the study of synchrony in highly disordered systems and the modeling of systems with adaptive network structures. Here, we present a single approach to both of these problems in the form of "KuraNet", a deep-learning-based system of coupled oscillators that can learn to synchronize across a distribution of disordered network conditions. The key feature of the model is the replacement of the traditionally static couplings with a coupling function which can learn optimal interactions within heterogeneous oscillator populations. We apply our approach to the eponymous Kuramoto model and demonstrate how KuraNet can learn data-dependent coupling structures that promote either global or cluster synchrony. For example, we show how KuraNet can be used to empirically explore the conditions of global synchrony in analytically impenetrable models with disordered natural frequencies, external field strengths, and interaction delays. In a sequence of cluster synchrony experiments, we further show how KuraNet can function as a data classifier by synchronizing into coherent assemblies. In all cases, we show how KuraNet can generalize to both new data and new network scales, making it easy to work with small systems and form hypotheses about the thermodynamic limit. Our proposed learning-based approach is broadly applicable to arbitrary dynamical systems with wide-ranging relevance to modeling in physics and systems biology., Comment: 9 pages, 4 figures, 5 videos, supplementary information and figures

Published
2021

140. Asymptotic stability of scalar multi-D inviscid shock waves

Author

Serre, Denis

Subjects
Mathematics - Analysis of PDEs
Abstract

In several space dimensions, scalar shock waves between two constant states u $\pm$ are not necessarily planar. We describe them in detail. Then we prove their asymptotic stability, assuming that they are uniformly non-characteristic. Our result is conditional for a general flux, while unconditional for the multi-D Burgers equation.

Published
2021

141. Generalized Collisional Fluid Theory for Multi-Component, Multi-Temperature Plasma Using The Linearized Boltzmann Collision Operator for Scrape-Off Layer/Edge Applications

Author

Raghunathan, Madhusudan, Marandet, Yannick, Bufferand, Hugo, Ciraolo, Guido, Ghendrih, Philippe, Tamain, Patrick, and Serre, Eric

Subjects
Physics - Plasma Physics
Abstract

Grad's method is used on the linearized Boltzmann collision operator to derive the most general expressions for the collision coefficients for a multi-component, multi-temperature plasma up to rank-2. In doing so, the collision coefficients then get expressed as series sum of pure coefficients of temperature and mass ratios multiplied by the cross-section dependent Chapman-Cowling integrals. These collisional coefficients are compared to previously obtained coefficients by Zhdanov et al [Zhdanov V.M., Transport processes in multi-component plasma, Taylor and Francis (2002)] for 13N-moment multi-temperature scheme. First, the differences in coefficients are compared directly, and then the differences in first approximation to viscosity and friction force are compared. For the 13N-moment multi-temperature coefficients, it is found that they behave reasonably similarly for small temperature differences, but display substantial differences in the coefficients when the temperature differences are high, both for the coefficients and for viscosity and friction force values. Furthermore, the obtained coefficients are compared to the 21N-moment single-temperature approximation provided by Zhdanov et al, and it is seen that the differences are higher than the 13N-moment multi-temperature coefficients, and have substantial differences even in the vicinity of equal temperatures, especially for the viscosity and friction force calculations., Comment: Corrected some typos from the previous version. Accepted by Plasma Physics and Controlled Fusion (April 9,2021)

Published
2021
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142. Superhuman cell death detection with biomarker-optimized neural networks

Author

Linsley, Jeremy W, Linsley, Drew A, Lamstein, Josh, Ryan, Gennadi, Shah, Kevan, Castello, Nicholas A, Oza, Viral, Kalra, Jaslin, Wang, Shijie, Tokuno, Zachary, Javaherian, Ashkan, Serre, Thomas, and Finkbeiner, Steven

Subjects
Neurosciences
Abstract

Cellular events underlying neurodegenerative disease may be captured by longitudinal live microscopy of neurons. While the advent of robot-assisted microscopy has helped scale such efforts to high-throughput regimes with the statistical power to detect transient events, time-intensive human annotation is required. We addressed this fundamental limitation with biomarker-optimized convolutional neural networks (BO-CNNs): interpretable computer vision models trained directly on biosensor activity. We demonstrate the ability of BO-CNNs to detect cell death, which is typically measured by trained annotators. BO-CNNs detected cell death with superhuman accuracy and speed by learning to identify subcellular morphology associated with cell vitality, despite receiving no explicit supervision to rely on these features. These models also revealed an intranuclear morphology signal that is difficult to spot by eye and had not previously been linked to cell death, but that reliably indicates death. BO-CNNs are broadly useful for analyzing live microscopy and essential for interpreting high-throughput experiments.

Published
2021

143. Effect of Cyclin-Dependent Kinase 4/6 Inhibitors on Circulating Cells in Patients with Metastatic Breast Cancer

Author

Soraia Lobo-Martins, Patrícia Corredeira, Ana Cavaco, Carolina Rodrigues, Paulina Piairo, Cláudia Lopes, Joana Fraga, Madalena Silva, Patrícia Alves, Lisiana Wachholz Szeneszi, Ana Barradas, Camila Castro Duran, Marília Antunes, Gonçalo Nogueira-Costa, Rita Sousa, Conceição Pinto, Leonor Ribeiro, Catarina Abreu, Sofia Torres, António Quintela, Gadea Mata, Diego Megías, Julie Ribot, Karine Serre, Sandra Casimiro, Bruno Silva-Santos, Lorena Diéguez, and Luís Costa

Subjects
advanced breast cancer, CDK4/6 inhibitor, circulating tumor cell, ER+/HER2− breast cancer, immunomodulation, metastatic breast cancer, Cytology, QH573-671
Abstract

The combination of cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) with endocrine therapy (ET) is the standard-of-care for estrogen receptor (ER)-positive, HER2-negative (ER+/HER2− advanced/metastatic breast cancer (mBC). However, the impact of CDK4/6i on circulating immune cells and circulating tumor cells (CTCs) in patients receiving CDK4/6i and ET (CDK4/6i+ET) remains poorly understood. This was a prospective cohort study including 44 patients with ER+/HER2− mBC treated with CDK4/6i+ET in either first or second line. Peripheral blood samples were collected before (baseline) and 3 months (t2) after therapy. Immune cell’s subsets were quantified by flow cytometry, and microfluidic-captured CTCs were counted and classified according to the expression of cytokeratin and/or vimentin. Patients were categorized according to response as responders (progression-free survival [PFS] ≥ 6.0 months; 79.1%) and non-responders (PFS < 6.0 months; 20.9%). CDK4/6i+ET resulted in significant changes in the hematological parameters, including decreased hemoglobin levels and increased mean corpuscular volume, as well as reductions in neutrophil, eosinophil, and basophil counts. Specific immune cell subsets, such as early-stage myeloid-derived suppressor cells, central memory CD4+ T cells, and Vδ2+ T cells expressing NKG2D, decreased 3 months after CDK4/6i+ET. Additionally, correlations between the presence of CTCs and immune cell populations were observed, highlighting the interplay between immune dysfunction and tumor dissemination. This study provides insights into the immunomodulatory effects of CDK4/6i+ET, underscoring the importance of considering immune dynamics in the management of ER+/HER2− mBC.

Published
2024
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144. Groupes de Coxeter finis: involutions et cubes

Author

Serre, Jean-Pierre

Subjects
Mathematics - Group Theory
Abstract

We review the properties of the finite Coxeter groups which are most useful for applications to cohomological invariants, namely their classes of involutions and their "cubes" (abelian subgroups generated by reflections)., Comment: 31 pages (in French). Added references. Shortened title. Minor corrections. To be published in l'Enseignement Math

Published
2020

145. Iterative VAE as a predictive brain model for out-of-distribution generalization

Author

Boutin, Victor, Zerroug, Aimen, Jung, Minju, and Serre, Thomas

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Our ability to generalize beyond training data to novel, out-of-distribution, image degradations is a hallmark of primate vision. The predictive brain, exemplified by predictive coding networks (PCNs), has become a prominent neuroscience theory of neural computation. Motivated by the recent successes of variational autoencoders (VAEs) in machine learning, we rigorously derive a correspondence between PCNs and VAEs. This motivates us to consider iterative extensions of VAEs (iVAEs) as plausible variational extensions of the PCNs. We further demonstrate that iVAEs generalize to distributional shifts significantly better than both PCNs and VAEs. In addition, we propose a novel measure of recognizability for individual samples which can be tested against human psychophysical data. Overall, we hope this work will spur interest in iVAEs as a promising new direction for modeling in neuroscience.

Published
2020

149. Groupes de Coxeter finis: Centralisateurs d’involutions

Author

Serre, Jean-Pierre, Morel, Jean-Michel, Editor-in-Chief, Teissier, Bernard, Editor-in-Chief, Baur, Karin, Series Editor, Brion, Michel, Series Editor, Huber, Annette, Series Editor, Khoshnevisan, Davar, Series Editor, Kontoyiannis, Ioannis, Series Editor, Kunoth, Angela, Series Editor, Mézard, Ariane, Series Editor, Podolskij, Mark, Series Editor, Policott, Mark, Series Editor, Serfaty, Sylvia, Series Editor, Székelyhidi, László, Series Editor, Vezzosi, Gabriele, Series Editor, and Wienhard, Anna, Series Editor

Published
2023
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150. Divergence-Free Tensors and Cofactors in Geometry and Fluid Dynamics

Author

Serre, Denis, Morel, Jean-Michel, Editor-in-Chief, Teissier, Bernard, Editor-in-Chief, Baur, Karin, Series Editor, Brion, Michel, Series Editor, Huber, Annette, Series Editor, Khoshnevisan, Davar, Series Editor, Kontoyiannis, Ioannis, Series Editor, Kunoth, Angela, Series Editor, Mézard, Ariane, Series Editor, Podolskij, Mark, Series Editor, Policott, Mark, Series Editor, Serfaty, Sylvia, Series Editor, Székelyhidi, László, Series Editor, Vezzosi, Gabriele, Series Editor, and Wienhard, Anna, Series Editor

Published
2023
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