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The present experimental study compared the impact of a total abstinence from smartphone use and of a reduction of daily smartphone use by 1 hr on well-being and healthy lifestyle. Participants (

This study develops and tests a measure for perceived vulnerability to occupational fraud and examines the relationship between organizational capacity and perceived vulnerability to fraud in community sport organizations. Drawing on the opportunity dimension of fraud triangle theory and the concept of organizational capacity, the study identifies a number of risk and protection factors for vulnerability to fraud. Board members of community sport organizations in Australia, Germany, and North America were surveyed (n = 1,256). The results offer a reliable and valid scale assessing vulnerability to fraud in community sport organizations consisting of procedural and financial dimensions. The regression analyses indicate a set of risk factors for vulnerability to fraud, including the presence of paid staff, high annual and unbalanced budgets, and owning sport facilities. Protection factors include strategic planning, relationships with other institutions, and trust within the board. This knowledge can be used to design antifraud education and training resources.

Regarding reactogenicity and immunogenicity, heterologous COVID-19 vaccination regimens are considered as alternative to conventional immunisation schemes.Individuals receiving either heterologous [ChAdOx1-S (AstraZeneca, Cambridge, UK)/BNT162b2 (Pfizer-BioNTech, Mainz, Germany)] (n=306) or homologous [mRNA-1273 (Moderna, Cambridge, Massachusetts, USA] (n=139) vaccination were asked to participate when receiving their second dose. Reactogenicity was assessed after 1 month, immunogenicity after 1, 3 and/or 6 months, including a third dose, via SARS-CoV-2 anti-Spike IgG, surrogate virus neutralisation test (sVNT) and a plaque reduction neutralisation test (PRNT) against the delta (B.1.167.2) and omicron (B.1.1.529; BA.1) variants of concern (VOCs).Overall reactogenicity was lower after heterologous vaccination. In both cohorts, SARS-CoV-2 anti-Spike IgG concentrations waned over time to low neutralising levels in the delta PRNT after 6 months, where heterologous vaccination demonstrated higher neutralising activity than homologous mRNA vaccination. At this point, 3.2% of the heterologous and 11.4% of the homologous cohort yielded low neutralising activity against omicron. After a third dose of an mRNA-vaccine, ≥99% of vaccinees demonstrated positive neutralising activity against delta. Depending on the vaccination scheme and against omicron, 55.6% to 87.5% of vaccinees demonstrated positive neutralising activity.ChAdOx1-S/BNT162b2 vaccination demonstrated an acceptable reactogenicity and immunogenicity profile. A third dose of an mRNA-vaccine is necessary to maintain neutralising activity against SARS-CoV-2. However, VOC adapted versions of the vaccines would be desirable.

Our objective was to investigate the hypothesis that psychological resources, including resilience, social connections, and internal locus of control, separately and in additive combinations, would be associated with selected pain outcomes: 1) days of opioid use and 2) medical/drug expenditures over 2 years. A mailed survey was sent to a stratified sample of older adults age≥65 with diagnosed back pain, osteoarthritis, and/or rheumatoid arthritis. Each of the resources was dichotomized as high/low and/or counted with equal weighting. Among respondents (N=3,131), the prevalence of mild/no and moderate/severe pain severity was 59% and 41%, respectively. As hypothesized, each resource was associated with lower levels of pain; additively, reported pain severity decreased as the number of resources increased. For moderate/severe pain, there was reduced opioid use among those with more resources; and, for mild/no pain, decreased medical/drug expenditures among those with ≥2 resources. Interventions that integrate psychological resources may enhance their effectiveness.

16 Pág., Diploid plant genomes typically contain ~35,000 genes, almost all belonging to highly conserved gene families. Only a small fraction are lineage-specific, which are found in only one or few closely related species. Little is known about how genes arise de novo in plant genomes and how often this occurs; however, they are believed to be important for plants diversification and adaptation. We developed a pipeline to identify lineage-specific genes in Triticeae, using newly available genome assemblies of wheat, barley, and rye. Applying a set of stringent criteria, we identified 5942 candidate Triticeae-specific genes (TSGs), of which 2337 were validated as protein-coding genes in wheat. Differential gene expression analyses revealed that stress-induced wheat TSGs are strongly enriched in putative secreted proteins. Some were previously described to be involved in Triticeae non-host resistance and cold response. Additionally, we show that 1079 TSGs have sequence homology to transposable elements (TEs), ~68% of them deriving from regulatory non-coding regions of Gypsy retrotransposons. Most importantly, we demonstrate that these TSGs are enriched in transmembrane domains and are among the most highly expressed wheat genes overall. To summarize, we conclude that de novo gene formation is relatively rare and that Triticeae probably possess ~779 lineage-specific genes per haploid genome. TSGs, which respond to pathogen and environmental stresses, may be interesting candidates for future targeted resistance breeding in Triticeae. Finally, we propose that non-coding regions of TEs might provide important genetic raw material for the functional innovation of TM domains and the evolution of novel secreted proteins., This work was supported by the Swiss National Foundation grant 31003A_163325.University of Zurich Research Priority Program, Grant/Award Number: U-702-21-01; Swiss National Foundation, Grant/Award Number: 31003A_163325

Die COVID-19-Impfempfehlungen der STIKO ha¬ben seit Beginn der Impfkampagne im Winter 2020/2021 das vordringliche Ziel, schwere Verläufe und Langzeit¬folgen von COVID-19 zu verhindern sowie Beschäf¬tigte in der medizinischen und pflegenden Versor¬gung vor SARS-CoV-2-Infektionen zu schützen. Die STIKO hat ihre COVID-19-Impfempfehlung seit der Erstpublikation im Dezember 2020 unter der Berücksichtigung neuer Daten und wei¬teren Impfstoffzulassungen fortlaufend angepasst. Beim Übergang von der pandemischen in die ende¬mische Phase des Infektionsgeschehens hat sich die STIKO mit der Überführung der bisherigen Emp¬fehlungen in eine längerfristige COVID-19-Impfempfehlung befasst. Im Epidemiologischen Bulletin 21/2023 wird die dazugehörige wissenschaftliche Begründung der aktualisierten Empfehlung und der Integration in den Impfkalender veröffentlicht. Die neue Empfehlung ersetzt die 25. Aktualisierung der COVID-19-Impfempfehlung von Februar 2023, die nicht mehr länger gültig ist.

Background Predicting in advance the behavior of new chemical compounds can support the design process of new products by directing the research toward the most promising candidates and ruling out others. Such predictive models can be data-driven using Machine Learning or based on researchers’ experience and depend on the collection of past results. In either case: models (or researchers) can only make reliable assumptions about compounds that are similar to what they have seen before. Therefore, consequent usage of these predictive models shapes the dataset and causes a continuous specialization shrinking the applicability domain of all trained models on this dataset in the future, and increasingly harming model-based exploration of the space. Proposed solution In this paper, we propose cancels (CounterActiNg Compound spEciaLization biaS), a technique that helps to break the dataset specialization spiral. Aiming for a smooth distribution of the compounds in the dataset, we identify areas in the space that fall short and suggest additional experiments that help bridge the gap. Thereby, we generally improve the dataset quality in an entirely unsupervised manner and create awareness of potential flaws in the data. cancels does not aim to cover the entire compound space and hence retains a desirable degree of specialization to a specified research domain. Results An extensive set of experiments on the use-case of biodegradation pathway prediction not only reveals that the bias spiral can indeed be observed but also that cancels produces meaningful results. Additionally, we demonstrate that mitigating the observed bias is crucial as it cannot only intervene with the continuous specialization process, but also significantly improves a predictor’s performance while reducing the number of required experiments. Overall, we believe that cancels can support researchers in their experimentation process to not only better understand their data and potential flaws, but also to grow the dataset in a sustainable way. All code is available under github.com/KatDost/Cancels.

Case studies of mid-latitude summer heatwaves commonly regard stationary synoptic-scale Rossby waves as the primary dynamical forcing. Whether this relationship between upper-tropospheric Rossby wave phase speed and persistent temperature extremes can be generalized is less clear. Here, we evaluate interannual and intra-seasonal variability of Rossby wave phase speed in reanalysis datasets employing circumglobal spectral analysis and investigate episodes with a low or a high zonal phase speed, respectively. Locally, we find evidence of Rossby wave phase preferences during episodes with a low phase speed, where preferred locations of ridges coincide with regions of increased heatwave frequency, but globally, there is no indication of an increased heatwave frequency. Unexpectedly, the finding of Rossby wave phase preferences and increased heatwave frequency also hold for episodes with a high phase speed, although in different areas of the summer hemisphere mid-latitudes. These findings, in particular about episodes with a zonal phase speed, will improve our mechanistic understanding of the dynamical drivers of heatwaves.

In early 2022, several extreme weather events occurred in the Southern Hemisphere. Devastating floods killed more than 500 people in South Africa (11-12 April) and about 26 people in eastern Australia (24-28 February and 25-31 March), while an unprecedented heatwave broke temperature records in Antarctica (16-22 March). This study presents a multiscale perspective of the atmospheric processes associated with these extreme events from synoptic to planetary scales. Equatorward Rossby wave breaking facilitated the transport of moist air from tropical oceans to the subtropical regions affected by the extreme precipitation events, while poleward Rossby wave breaking forced an intrusion of warm and moist extratropical air masses into the Antarctic Peninsula. Southern hemispheric extratropical wave activity demonstrated relatively normal conditions during February and March, while wave energy reached extremely large values for wave number 5 during April. From a planetary-scale perspective, we investigate how tropical variability, including the El-Nino Southern Oscillation (ENSO; in a La Nina phase) and the Madden-Julian Oscillation (MJO), modulates large-scale atmospheric circulation patterns, extratropical wave activity, and Rossby wave breaking. Overall, this study clarifies the role of regional and remote atmospheric processes in the recent weather extremes in the Southern Hemisphere.

The fungus Blumeria graminis f. sp. tritici causes wheat powdery mildew disease. Here, we study its spread and evolution by analyzing a global sample of 172 mildew genomes. Our analyses show that B.g. tritici emerged in the Fertile Crescent during wheat domestication. After it spread throughout Eurasia, colonization brought it to America, where it hybridized with unknown grass mildew species. Recent trade brought USA strains to Japan, and European strains to China. In both places, they hybridized with local ancestral strains. Thus, although mildew spreads by wind regionally, our results indicate that humans drove its global spread throughout history and that mildew rapidly evolved through hybridization.

Funder: China Scholarship Council, Despite early clinical successes, the mechanisms of action of low-dose interleukin-2 (LD-IL-2) immunotherapy remain only partly understood. Here we examine the effects of interval administration of low-dose recombinant IL-2 (iLD-IL-2) in type 1 diabetes using high-resolution single-cell multiomics and flow cytometry on longitudinally-collected peripheral blood samples. Our results confirm that iLD-IL-2 selectively expands thymic-derived FOXP3+HELIOS+ regulatory T cells and CD56bright NK cells, and show that the treatment reduces the frequency of IL-21-producing CD4+ T cells and of two innate-like mucosal-associated invariant T and Vγ9Vδ2 CD8+ T cell subsets. The cellular changes induced by iLD-IL-2 associate with an anti-inflammatory gene expression signature, which remains detectable in all T and NK cell subsets analysed one month after treatment. These findings warrant investigations into the potential longer-term clinical benefits of iLD-IL-2 in immunotherapy., This work was supported by the Sir Jules Thorn Trust (13/JTA (OCT2013/DR/1044)), the JDRF (1-SRA-2019-657-A-N), and the NIHR Cambridge Biomedical Research Centre. The Diabetes and Inflammation Laboratory was supported by a strategic award from the Wellcome (107212/A/15/Z) and the JDRF (4-SRA-2017-473-A-A). JYZ was supported by the China Scholarship Council-University of Oxford Scholarship. The research was supported by the Wellcome Trust Core Award Grant Number 203141/Z/16/Z with additional support from the NIHR Oxford BRC. The University of Cambridge has received salary support for ME through the National Health Service in the East of England through the Clinical Academic Reserve. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.

Purpose Osteopenia is common in postmenopausal women and effective interventions increasing or stabilizing bone mineral density (BMD) to prevent fractures are urgently needed. Methods Sixty-five postmenopausal women diagnosed with osteopenia (T-score between -1.0 and -2.5) were randomly assigned to either a vibration training group (VT), a resistance training group (RT), or a control group (CG). BMD T-score values (primary endpoint) were assessed at baseline (T0) and after 12 months (T12), secondary endpoints (muscle strength, postural control, and health-related quality of life) at baseline (T0), after 6 months (T6), after 12 months (T12), and as follow-up after 15 months (T15). Results After the intervention period, neither the VT nor the RT showed any significant changes in BMD T-score values compared to the CG. Isokinetic strength improved significantly within all training groups, with the exception of the flexors of VT at an angular velocity of 240°/s. Health-related quality of life as well as postural control improved significantly for the RT only. Conclusions We conclude that participants of all three groups were able to maintain their BMD. The improvements in quality of life and postural control after resistance training are nevertheless meaningful for postmenopausal osteopenic women and support the importance of regular loadings of the musculoskeletal system. This study was retrospectively registered in January 2022 at the DRKS (S00027816) as clinical trial.

This study investigates the relationship between state politics and sport governance based on an institutional framework and the concept of spillover effects. Specifically, it examines whether spillover effects occur from state parliament and government composition to board gender diversity within sport governing bodies. Organizational-level data from German national and state sport governing bodies were collected (n = 930). They were combined with state-level data on the government composition by gender and political party (parliament, ministers) based on the location of each sport governing body’s headquarter. The results show that on average 20.1% of board members in sport governing bodies are women. Regression analyses indicate that the share of parliamentarians from the Social Democrats and the Green party is positively associated with the share of women in sport governance, while the share of Liberals in the parliament is negatively related. The share of women parliamentarians from the Social party and the share of women Conservative ministers are negatively related to women in sport governance. The findings indicate that women representation in sport governance is linked to state politics, suggesting that spillover effects occur from an organizations’ political environment.

Conditional Density Estimation (CDE) has wide-reaching applicability to various real-world problems, such as spatial density estimation and environmental modelling. CDE estimates the probability density of a random variable rather than a single value and can thus model uncertainty and inverse problems. This task is inherently more complex than regression, and many algorithms suffer from overfitting, particularly when modelled with few labelled data points. For applications where unlabelled data is abundant but labelled data is scarce, we propose Wasserstein Laplacian Regularisation, a semi-supervised learning framework that allows CDE algorithms to leverage these unlabelled data. The framework minimises an objective function which ensures that the learned model is smooth along the manifold of the underlying data, as measured by Wasserstein distance. When applying our framework to Mixture Density Networks, the resulting semi-supervised algorithm can achieve similar performance to a supervised model with up to three times as many labelled data points on baseline datasets. We additionally apply our technique to the problem of remote sensing for chlorophyll-a estimation in inland waters.

A multiscale analysis of the significant nocturnal tornado outbreak in Tennessee on 2–3 March 2020 is presented. This outbreak included several significant tornadoes and resulted in the second most fatalities (25) and most injuries (309) of all nocturnal tornado events in Tennessee in 1950–2020. The two deadliest tornadoes struck Nashville (EF3 intensity) and Cookeville (EF4) resulting in 5 and 19 fatalities, respectively. The supercell responsible for the tornado outbreak initiated at 0330 UTC 3 March within a region of warm frontogenesis in western Tennessee. Throughout its life cycle, the supercell was located in a region of convective available potential energy near 1000 J kg−1 and 0–1-km storm-relative helicity over 350 m2 s−2. Retrospective 3-h forecasts from the experimental Warn-on-Forecast System (WoFS) convection-allowing ensemble initialized after the parent supercell initiated indicated a high probability, high severity scenario for tornadoes across Tennessee and into Nashville through 0700 UTC. Earlier WoFS forecasts indicated a low probability, high severity scenario owing to uncertainty in the initiation of supercells. The presence of these supercells was sensitive to the upstream thermodynamic conditions and warm frontogenesis regions that were inherited from the lateral boundary conditions. In all, this study highlights the potential of the WoFS ensemble to contribute useful probabilistic severe weather information to the short-term forecast process during a nocturnal significant tornado outbreak.

Most neutron stars (NSs) and black holes (BHs) are believed to be the final remnants in the evolution of massive stars. In this study, we propose a new formation channel for the formation of BHs and peculiar NSs (specifically, magnetars and Thorne-$\dot{\rm Z}$ytkow objects [T$\dot{\rm Z}$Os]), which we refer to as the core merger-induced collapse (CMIC) model. This model involves the merger at the end of a common-envelope phase of an oxygen/neon/magnesium composition white dwarf and the core of a hydrogen-rich or helium-rich non-degenerate star, leading to the creation of peculiar new types of objects. The results of binary population synthesis simulations show that the CMIC channel could make important contributions to the populations of (millisecond) pulsars, T$\dot{\rm Z}$Os, magnetars and BHs. The possibility of superluminous supernovae powered by T$\dot{\rm Z}$Os, magnetars and BHs formed through the CMIC model is also being investigated. Magnetars with immediate matter surroundings formed after the CMIC might be good sources for fast radio bursts., Comment: 5Figures, 4tables; Accepted for publication in MNRAS, this new accepted version includes new points and new references

C-peptide declines in type 1 diabetes, although many long-duration patients retain low, but detectable levels. Histological analyses confirm that β-cells can remain following type 1 diabetes onset. We explored the trends observed in C-peptide decline in the UK Genetic Resource Investigating Diabetes (UK GRID) cohort (N = 4,079), with β-cell loss in pancreas donors from the network for Pancreatic Organ donors with Diabetes (nPOD) biobank and the Exeter Archival Diabetes Biobank (EADB) (combined N = 235), stratified by recently reported age at diagnosis endotypes (

Refereed/Peer-reviewed Microalgae can add value to biological wastewater treatment processes by capturing carbon and nutrients and producing valuable biomass. Harvesting small cells from liquid media is a challenge easily addressed with biofilm cultivation. Three experimental photobioreactors were constructed from inexpensive materials (e.g. plexiglass, silicone) for hybrid liquid/biofilm cultivation of a microalgal-bacterial consortia in aquaculture effluent. Three light regimes (full-spectrum, blue-white, and red) were implemented to test light spectra as a process control. High-intensity full-spectrum light caused photoinhibition and low biomass yield, but produced the most polyhydroxybutyrate (PHB) (0.14 mg g−1); a renewable bioplastic polymer. Medium-intensity blue-white light was less effective for carbon capture, but removed up to 82 % of phosphorus. Low-intensity red light was the only net carbon-negative regime, but increased phosphorus (+4.98 mg/L) in the culture medium. Light spectra and intensity have potential as easily-implemented process controls for targeted wastewater treatment, biomass production, and PHB synthesis using photosynthetic consortia.

Zusammenfassung Hintergrund Eine standardisierte Erhebung von COVID-19-Infektionen bei Gesundheitspersonal während der laufenden Pandemie war und ist nicht gegeben. Vor allem der Anteil von arbeitsbedingten Infektionen beim Gesundheitspersonal und die Frage, welche Arbeitnehmer/-innen darunter am meisten gefährdet sind, bleiben unklar. Ziel Ziel dieser Studie war es, die gemeldeten COVID-19-Fälle beim Gesundheitspersonal in Frankfurt/Main in den ersten 6 Monaten der Pandemie zu analysieren, die Zahl der arbeitsbedingten Infektionen zu ermitteln und somit eine bessere Interpretation der durch das Robert Koch-Institut veröffentlichten Daten zu ermöglichen. Methoden Die Daten des Gesundheitsamts Frankfurt/Main wurden für den Zeitraum vom 01.03. bis zum 31.08.2020 betrachtet und medizinisches Personal für eine Querschnittserhebung im Rahmen einer Umfrage rekrutiert. Drei Subgruppen wurden nach Ort des Infektionskontakts, am Arbeitsplatz, im Privaten und unbekannt, unterteilt und analysiert. Ergebnisse Medizinisches Personal machte 11,8 % (319/2700) aller gemeldeten COVID-19-Fälle in Frankfurt/Main im untersuchten Zeitraum aus. In der Umfrage gaben 47,2 % der Befragten an, dass ihre Infektion am Arbeitsplatz erworben wurde. Es zeigte sich eine Assoziation von Kontakt zu COVID-19-Patient/-innen sowie der Beschäftigung auf einer internistischen Station und einer arbeitsbedingten Infektion. Ersichtlich wurde außerdem ein Zusammenhang zwischen mutmaßlichen Infektionen am Arbeitsplatz und folglich gestellten Verdachtsanzeigen auf Berufskrankheit. Diskussion und Fazit Gesundheitsämter sind in der Lage, relevante Daten von arbeitsbedingten Transmissionen in Berufen und Arbeitsplätzen im Gesundheitswesen zu erheben, und sollten standardisierte Daten zu infiziertem Gesundheitspersonal generieren. Diese Daten sind notwendig, um gezielte Maßnahmen der Infektionsprävention zu ergreifen, die Gesundheitspersonal und ihre Patient/-innen schützen.

This study applies the wellbeing valuation approach to sport participation and volunteering using data from the German Socio-Economic Panel. Linear regression results show that sport and volunteering hours increase satisfaction with life, health, work, income, and leisure, but with diminishing returns in most models. In a seemingly unrelated regression, some of these effects turn insignificant. The instrumental variable estimates show causal impacts of sporting hours on all wellbeing measures, while volunteering only impacts health satisfaction. The monetary values vary depending on the type of wellbeing measure and estimator, indicating that future studies should consider the employed measures and estimators.

Our objective was to investigate three levels of resilience (low, medium, and high), identify associated characteristics, and measure the impact of increasing resilience on quality of life (QOL), healthcare utilization and expenditures, and preventive services compliance. The study sample was identified from adults age ≥65 who completed surveys during May-June 2019 (N=3,573). Other protective factors, including purpose-in-life, optimism, locus of control, and social connections, were dichotomized as high/low and counted with equal weighting (0 to 4). Among survey respondents, the prevalence of low, medium, and high resilience levels was 27%, 29%, and 44%, respectively. The strongest predictors of medium and high resilience included increasing number of other protective factors, lower stress, and no depression. Individuals with medium and high resilience had significantly higher QOL and lower healthcare utilization and expenditures. Resilience strategies integrated into healthy aging programming could be associated with improvements in QOL and/or healthcare utilization and expenditure outcomes.

The National Severe Storms Laboratory (NSSL) Warn-on-Forecast System (WoFS) is an experimental real-time rapidly updating convection-allowing ensemble that provides probabilistic short-term thunderstorm forecasts. This study evaluates the impacts of reducing the forecast model horizontal grid spacing Δx from 3 to 1.5 km on the WoFS deterministic and probabilistic forecast skill, using 11 case days selected from the 2020 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiment (SFE). Verification methods include (i) subjective forecaster impressions; (ii) a deterministic object-based technique that identifies forecast reflectivity and rotation track storm objects as contiguous local maxima in the composite reflectivity and updraft helicity fields, respectively, and matches them to observed storm objects; and (iii) a recently developed algorithm that matches observed mesocyclones to mesocyclone probability swath objects constructed from the full ensemble of rotation track objects. Reducing Δx fails to systematically improve deterministic skill in forecasting reflectivity object occurrence, as measured by critical success index (CSIDET), a metric that incorporates both probability of detection (PODDET) and false alarm ratio (FARDET). However, compared to the Δx = 3 km configuration, the Δx = 1.5 km WoFS shows improved midlevel mesocyclone detection, as evidenced by its statistically significant (i) higher CSIDET for deterministic midlevel rotation track objects and (ii) higher normalized area under the performance diagram curve (NAUPDC) score for probability swath objects. Comparison between Δx = 3 km and Δx = 1.5 km reflectivity object properties reveals that the latter have 30% stronger mean updraft speeds, 17% stronger median 80-m winds, 67% larger median hail diameter, and 28% higher median near-storm-maximum 0–3-km storm-relative helicity.

Autism is a complex neurodevelopmental condition that manifests in various ways. Autism is often accompanied by other neurological disorders, such as ADHD, anxiety, and schizophrenia, which can complicate diagnosis and management. While research has investigated the role of specific genes in autism, their relationship with co-occurring traits is not fully understood.To address this gap, we conducted a two-sample Mendelian Randomisation analysis and identified four genes located at the 17q21.31 locus that are causally linked to autism in fetal cortical tissue (i.e.LINC02210, LRRC37A4P, RP11-259G18.1, RP11-798G7.6). LINC02210was also identified as being causally related to autism in adult cortical tissue. By integrating data from expression quantitative trait loci [eQTLs], genes, and protein interactions we identified that the 17q21.31 locus contributes to the intersection between autism and other neurological traits and conditions in fetal cortical tissue. We also identified an additional distinct cluster of co-occurring traits, including cognition and worry, linked to genetic loci at 3p21.1.Our results support the hypothesis that an individual’s autism phenotype is partially determined by their genetic risk for co-occurring conditions. Overall, our findings provide insights into the complex relationship between autism and co-occurring conditions, which could be used to develop predictive models for more accurate diagnosis and better clinical management.

We study Individual Fairness (IF) for Bayesian neural networks (BNNs). Specifically, we consider the $\epsilon$-$\delta$-individual fairness notion, which requires that, for any pair of input points that are $\epsilon$-similar according to a given similarity metrics, the output of the BNN is within a given tolerance $\delta>0.$ We leverage bounds on statistical sampling over the input space and the relationship between adversarial robustness and individual fairness to derive a framework for the systematic estimation of $\epsilon$-$\delta$-IF, designing Fair-FGSM and Fair-PGD as global,fairness-aware extensions to gradient-based attacks for BNNs. We empirically study IF of a variety of approximately inferred BNNs with different architectures on fairness benchmarks, and compare against deterministic models learnt using frequentist techniques. Interestingly, we find that BNNs trained by means of approximate Bayesian inference consistently tend to be markedly more individually fair than their deterministic counterparts.

Introduction: Low-intensity endurance training is frequently performed at gradually higher training intensities than intended, resulting in a shift towards threshold training. By restricting oral breathing and only allowing for nasal breathing this shift might be reduced.Methods: Nineteen physically healthy adults (3 females, age: 26.5 ± 5.1 years; height: 1.77 ± 0.08 m; body mass: 77.3 ± 11.4 kg; VO2peak: 53.4 ± 6.6 mL·kg−1 min−1) performed 60 min of self-selected, similar (144.7 ± 56.3 vs. 147.0 ± 54.2 W, p = 0.60) low-intensity cycling with breathing restriction (nasal-only breathing) and without restrictions (oro-nasal breathing). During these sessions heart rate, respiratory gas exchange data and power output data were recorded continuously.Results: Total ventilation (p < 0.001, ηp2 = 0.45), carbon dioxide release (p = 0.02, ηp2 = 0.28), oxygen uptake (p = 0.03, ηp2 = 0.23), and breathing frequency (p = 0.01, ηp2 = 0.35) were lower during nasal-only breathing. Furthermore, lower capillary blood lactate concentrations were found towards the end of the training session during nasal-only breathing (time x condition-interaction effect: p = 0.02, ηp2 = 0.17). Even though discomfort was rated marginally higher during nasal-only breathing (p = 0.03, ηp2 = 0.24), ratings of perceived effort did not differ between the two conditions (p ≥ 0.06, ηp2 = 0.01). No significant “condition” differences were found for intensity distribution (time spent in training zone quantified by power output and heart rate) (p ≥ 0.24, ηp2 ≤ 0.07).Conclusion: Nasal-only breathing seems to be associated with possible physiological changes that may help to maintain physical health in endurance athletes during low intensity endurance training. However, it did not prevent participants from performing low-intensity training at higher intensities than intended. Longitudinal studies are warranted to evaluate longitudinal responses of changes in breathing patterns.

Running complex sets of machine learning experiments is challenging and time-consuming due to the lack of a unified framework. This leaves researchers forced to spend time implementing necessary features such as parallelization, caching, and checkpointing themselves instead of focussing on their project. To simplify the process, in this paper, we introduce Memento, a Python package that is designed to aid researchers and data scientists in the efficient management and execution of computationally intensive experiments. Memento has the capacity to streamline any experimental pipeline by providing a straightforward configuration matrix and the ability to concurrently run experiments across multiple threads. A demonstration of Memento is available at: https://wickerlab.org/publication/memento.

To understand the impact of different assimilated observations on convection-allowing model forecast skill, a diverse range of observing system simulation experiment (OSSE) case studies are required (different storm modes and environments). Many previous convection-allowing OSSEs predicted the evolution of an isolated supercell generated via a warm air perturbation in a horizontally homogenous environment. This study introduces a new methodology in which a quasi-linear convective system is generated in a highly sheared and modestly unstable environment. Wind, temperature, and moisture perturbations superimposed on a horizontally homogeneous environment simulate a cold front that initiates an organized storm system that spawns multiple mesovortices. Mature boundary layer turbulence is also superimposed onto the initial environment to account for typical convective-scale uncertainties. Creating an initial forecast ensemble remains a challenge for convection-allowing OSSEs because mesoscale uncertainties are difficult to quantify and represent. The generation of the forecast ensemble is described in detail. The forecast ensemble is initialized by 24 h full-physics simulations (e.g., radiative forcing, surface friction, and microphysics). The simulations assume different surface conditions to alter surface moisture and heat fluxes and modify the effects of friction. The subsequent forecast ensemble contains robust non-Gaussian errors that persist until corrected by the data assimilation system. This purposely degraded initial forecast ensemble provides an opportunity to assess whether assimilated environmental observations can improve, e.g., the wind profile. An example OSSE suggests that a combination of radar and conventional (surface and soundings) observations are required to produce a skilled quasi-linear convective system forecast, which is consistent with real-world case studies. The OSSE framework introduced in this study will be used to understand the impact of assimilated environmental observations on forecast skill.

Obtaining a faithful probabilistic depiction of moist convection is complicated by unknown errors in subgrid-scale physical parameterization schemes, invalid assumptions made by data assimilation (DA) techniques, and high system dimensionality. As an initial step toward untangling sources of uncertainty in convective weather regimes, we evaluate a novel Bayesian data assimilation methodology based on particle filtering within a WRF ensemble analysis and forecasting system. Unlike most geophysical DA methods, the particle filter (PF) represents prior and posterior error distributions non-parametrically rather than assuming a Gaussian distribution and can accept any type of likelihood function. This approach is known to reduce bias introduced by Gaussian approximations in low dimensional and idealized contexts. The form of PF used in this research adopts a dimension-reduction strategy, making it affordable for typical weather applications. The present study examines posterior ensemble members and forecasts for select severe weather events between 2019 — 2020, comparing results from the PF with those from an Ensemble Kalman Filter (EnKF). We find that assimilating with a PF produces posterior quantities for microphysical variables that are more consistent with model climatology than comparable quantities from an EnKF, which we attribute to a reduction in DA bias. These differences are significant enough to impact the dynamic evolution of convective systems via cold pool strength and propagation, with impacts to forecast verification scores depending on the particular microphysics scheme. Our findings have broad implications for future approaches to the selection of physical parameterization schemes and parameter estimation within pre-existing data assimilation frameworks.

Plant cell growth involves coordination of numerous processes and signaling cascades among the different cellular compartments to concomitantly enlarge the protoplast and the surrounding cell wall. InArabidopsis thaliana, the cell wall integrity-sensing process involves the extracellular LRX (LRR-Extensin) proteins that bind RALF (Rapid ALkalinization Factor) peptide hormones and, in vegetative tissues, interact with the transmembrane receptor kinase FERONIA (FER). This LRX/RALF/FER signaling module influences cell wall composition and regulates cell growth. The numerous proteins involved in or influenced by this module are beginning to be characterized. In a genetic screen, mutations inApyrase 7(APY7) were identified to suppress growth defects observed inlrx1andfermutants.APY7encodes a Golgi-localized NTP-diphosphohydrolase, but opposed to other apyrases of Arabidopsis, APY7 revealed to be a negative regulator of cell growth. APY7 modulates the growth-inhibiting effect of RALF1, influences the cell wall architecture, and alters the pH of the extracellular matrix, all of which affect cell growth. Together, this study reveals a function of APY7 in cell wall formation and cell growth that is connected to growth processes influenced by the LRX/FER/RALF signaling module.

This paper presents a new framework for the seismic loss prediction of residential buildings in Ōtautahi / Christchurch, New Zealand. It employs data science techniques, geospatial tools, and machine learning (ML) trained on insurance claims data from the Earthquake Commission (EQC) collected following the 2010–2011 Canterbury earthquake sequence (CES). The seismic loss prediction obtained from the ML model is shown to outperform the output from existing risk analysis tools for New Zealand for each of the main earthquakes of the CES. In addition to the prediction capabilities, the ML model delivered useful insights into the most important features contributing to losses during the CES. ML correctly highlighted that liquefaction significantly influenced building losses for the 22 February 2011 earthquake. The results are consistent with observations, engineering knowledge, and previous studies, confirming the potential of data science and ML in the analysis of insurance claims data and the development of seismic loss prediction models using empirical loss data.

verb • The systematic lapping of brick in a wall. Or shingles on the portico of a two-faced estate— Asphalt, wood, or rock elements laid lip to incline. Schindle from the German. Meaning roof slate, sun- baked. Meaning blacktop underlayment, AKA stacks of neighbors of...

Purpose. The conversion of waste such as discarded jicama (DJ) to value added starch, offers possibility of local economic development and sustainability. Methods. To evaluate the feasibility of reduced food waste, starch from discarded jicama (DJS) and commercial jicama (CJS) were obtained by a conventional method to compare whether the fact that the discarded product is used influences the yield and characteristics of the starch obtained. Results. Significant differences in extraction yield were obtained, both starches presented a granule size between 1 and 12 µm, a type C diffraction pattern, amylose content around 14%, a gelatinization temperature of 61 °C to DJS and CJS; however, properties such as water solubility index (WSI), swelling power (SP), and pasting did present some differences, WSI and SP are higher for CJS causing a faster gelatinization process than in DJS. Conclusion. There are differences in the characteristics of DJS and CJS, particularly it is suggested that DJ does have a significant impact on the internal structure of the starch granule, on the amylopectin fraction mainly.

Die EU hat am 10.11.2022 den proteinbasierten COVID-19-Impfstoff VidPrevtyn der Firma Sanofi Pasteur für Personen ab 18 Jahren zur Auffrischimpfung nach Grundimmunisierung mit einem mRNA-Impfstoff oder einem adenoviralen Vektorimpfstoff zugelassen. VidPrevtyn Beta ist nach Nuvaxovid (Novavax) der zweite proteinbasierte COVID-19-Impfstoff, der in der EU eine Zulassung erhält. Wie das Epidemiologische Bulletin 8/2023 ausführt, hat die STIKO nach Bewertung der Daten aus den Zulassungsstudien entschieden, die Anwendung von VidPrevtyn Beta für die COVID-19-Auffrischimpfung in Deutschland derzeit nicht zu empfehlen, da die Datenlage äußerst limitiert ist. Da es sich bei VidPrevtyn Beta um einen zugelassenen Impfstoff handelt, kann dieser trotz fehlender STIKO-Empfehlung verwendet werden. Zum Beispiel kann der Einsatz begründet sein, wenn produktspezifische, medizinische Kontraindikationen gegenüber den anderen verfügbaren COVID-19-Impfstoffen bestehen.

In der im Epidemiologischen Bulletin 8/2023 veröffentlichten 25. Aktualisierung der COVID-19-Impfempfehlung grenzt die STIKO unter Berücksichtigung der dynamischen Datenlage zu den derzeit verbreiteten SARS-CoV-2-Varianten und deren Sublinien, der u. U. ausbleibenden Neutrali-sationskapazität von Evusheld gegen einige neuere Sublinien sowie der verfügbaren und nach wie vor wirksamen Optionen zur antiviralen Frühtherapie ihre Empfehlung zur PrEP mit Evusheld weiter ein. Eine PrEP mit Evusheld sollte nur noch in begründeten Einzelfällen in Betracht gezogen werden.

The time spent above 90% of maximal oxygen uptake (V̇O2max) during high-intensity interval training (HIIT) sessions is intended to be maximized to improve V̇O2max. Since uphill running serves as a promising means to increase metabolic cost, we compared even and moderately inclined running in terms of time ≥90% V̇O2max and its corresponding physiological surrogates. Seventeen well-trained runners (8 females & 9 males; 25.8 ± 6.8yrs; 1.75 ± 0.08m; 63.2 ± 8.4kg; V̇O2max: 63.3 ± 4.2 ml/min/kg) randomly completed both a horizontal (1% incline) and uphill (8% incline) HIIT protocol (4-times 5min, with 90s rest). Mean oxygen uptake (V̇O2mean), peak oxygen uptake (V̇O2peak), lactate, heart rate (HR), and perceived exertion (RPE) were measured. Uphill HIIT revealed higher (p ≤ 0.012; partial eta-squared (pes) ≥ 0.351) V̇O2mean (uphill: 3.3 ± 0.6 vs. horizontal: 3.2 ± 0.5 L/min; standardized mean difference (SMD) = 0.15), V̇O2peak (uphill: 4.0 ± 0.7 vs. horizontal: 3.8 ± 0.7 L/min; SMD = 0.19), and accumulated time ≥90% V̇O2max (uphill: 9.1 ± 4.6 vs. horizontal: 6.4 ± 4.0 min; SMD = 0.62) compared to even HIIT. Lactate, HR, and RPE responses did not show mode*time rANOVA interaction effects (p ≥ 0.097; pes ≤0.14). Compared to horizontal HIIT, moderate uphill HIIT revealed higher fractions of V̇O2max at comparable perceived efforts, heartrate and lactate response. Therefore, moderate uphill HiiT notably increased time spent above 90% V̇O2max.