Showing papers by "University of Haifa published in 2020"
TL;DR: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates, and there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries.
5,802 citations
Christopher J L Murray1, Christopher J L Murray2, Christopher J L Murray3, Aleksandr Y. Aravkin2 +2269 more•Institutions (286)
TL;DR: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure.
3,059 citations
University of Sydney1, University Hospitals Birmingham NHS Foundation Trust2, Newcastle upon Tyne Hospitals NHS Foundation Trust3, Spanish National Research Council4, University of Haifa5, The Chinese University of Hong Kong6, University of Bern7, University of Mainz8, Kurume University9, Pontifical Catholic University of Chile10, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico11, Mansoura University12, Minerva Foundation Institute for Medical Research13, Shanghai Jiao Tong University14, Aarhus University Hospital15, Marmara University16, University of Lisbon17, University of São Paulo18, Paris Diderot University19, University of Western Australia20, First Affiliated Hospital of Wenzhou Medical University21, Minia University22, University of Malaya23, National Autonomous University of Mexico24, Yonsei University25, University of Paris26, University of Turin27
TL;DR: A panel of international experts from 22 countries propose a new definition of metabolic-dysfunction-associated fatty liver disease that is both comprehensive yet simple for the diagnosis of MAFLD and is independent of other liver diseases.
1,705 citations
University of Haifa1, Fudan University2, Federal University of Bahia3, Israel Ministry of Health4, University of Melbourne5, Christian Michelsen Institute6, University of Zambia7, University of Bergen8, Chulalongkorn University9, Umeå University10, American University of Armenia11, Johns Hopkins University12, Bar-Ilan University13, Monash University14, Thailand Ministry of Public Health15, Ghent University16
TL;DR: To address the challenges to health equity and describe some of the approaches taken by governments and local organizations, 13 country case studies from various regions around the world are compiled.
Abstract: The COVID-19 is disproportionally affecting the poor, minorities and a broad range of vulnerable populations, due to its inequitable spread in areas of dense population and limited mitigation capacity due to high prevalence of chronic conditions or poor access to high quality public health and medical care. Moreover, the collateral effects of the pandemic due to the global economic downturn, and social isolation and movement restriction measures, are unequally affecting those in the lowest power strata of societies. To address the challenges to health equity and describe some of the approaches taken by governments and local organizations, we have compiled 13 country case studies from various regions around the world: China, Brazil, Thailand, Sub Saharan Africa, Nicaragua, Armenia, India, Guatemala, United States of America (USA), Israel, Australia, Colombia, and Belgium. This compilation is by no-means representative or all inclusive, and we encourage researchers to continue advancing global knowledge on COVID-19 health equity related issues, through rigorous research and generation of a strong evidence base of new empirical studies in this field.
430 citations
University of Saskatchewan1, Canadian Grain Commission2, Kansas State University3, Leibniz Association4, National Research Council5, Norwich Research Park6, University of Zurich7, Agriculture and Agri-Food Canada8, ETH Zurich9, Kihara Institute for Biological Research10, Natural History Museum11, University of Minnesota12, Tel Aviv University13, University of Manitoba14, National Institute of Advanced Industrial Science and Technology15, University of Guelph16, Kyoto University17, International Maize and Wheat Improvement Center18, University of Western Australia19, Syngenta20, University of Adelaide21, King Abdullah University of Science and Technology22, Kyoto Prefectural University23, University of Haifa24, Technische Universität München25, University of Göttingen26
TL;DR: Comparative analysis of multiple genome assemblies from wheat reveals extensive diversity that results from the complex breeding history of wheat and provides a basis for further potential improvements to this important food crop.
Abstract: Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat (Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome1, and the lack of genome-assembly data for multiple wheat lines2,3. Here we generated ten chromosome pseudomolecule and five scaffold assemblies of hexaploid wheat to explore the genomic diversity among wheat lines from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions from wild relatives and differences in gene content resulting from complex breeding histories aimed at improving adaptation to diverse environments, grain yield and quality, and resistance to stresses4,5. We provide examples outlining the utility of these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved in disease resistance and the characterization of Sm16, a gene associated with insect resistance. These genome assemblies will provide a basis for functional gene discovery and breeding to deliver the next generation of modern wheat cultivars.
416 citations
Hebrew University of Jerusalem1, University of Queensland2, University of Potsdam3, Leibniz Association4, Sun Yat-sen University5, University of Exeter6, Complutense University of Madrid7, Spanish National Research Council8, Universities Space Research Association9, Wuhan University10, University of Haifa11, Marshall Space Flight Center12, Cooperative Institute for Research in the Atmosphere13, Goddard Space Flight Center14, University of Maryland, College Park15, National Oceanic and Atmospheric Administration16, Colorado School of Mines17
TL;DR: In this article, the authors outline the historical development of night-time optical sensors up to the current state-of-the-art sensors, highlight various applications of night light data, discuss the special challenges associated with remote sensing of night lights with a focus on the limitations of current sensors, and provide an outlook for the future of remote sensing.
369 citations
TL;DR: Loneliness was the main risk factor for depression, anxiety and their comorbidity and adults above 60, displayed greater resilience to psychiatric disorders associated with the COVID-19 crisis.
358 citations
TL;DR: It is demonstrated that Fhb7, when introgressed into diverse wheat backgrounds by distant hybridization, confers broad resistance to both FHB and crown rot without penalizing wheat yield and is suggested a source of Fusarium resistance for wheat improvement.
Abstract: Fusarium head blight (FHB), a fungal disease caused by Fusarium species that produce food toxins, currently devastates wheat production worldwide, yet few resistance resources have been discovered in wheat germplasm. Here, we cloned the FHB resistance gene Fhb7 by assembling the genome of Thinopyrum elongatum, a species used in wheat distant hybridization breeding. Fhb7 encodes a glutathione S-transferase (GST) and confers broad resistance to Fusarium species by detoxifying trichothecenes through de-epoxidation. Fhb7 GST homologs are absent in plants, and our evidence supports that Th. elongatum has gained Fhb7 through horizontal gene transfer (HGT) from an endophytic Epichloe species. Fhb7 introgressions in wheat confers resistance to both FHB and crown rot in diverse wheat backgrounds without yield penalty, providing a solution for Fusarium resistance breeding.
333 citations
TL;DR: To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—the authors estimated additional population equivalents with UHC effective coverage from 2018 to 2023, and quantified frontiers of U HC effective coverage performance on the basis of pooled health spending per capita.
304 citations
TL;DR: Despite its growing prominence in news coverage and public discourse, there is still considerable ambiguity regarding when and how fact-checking affects beliefs as mentioned in this paper, which may be explained by theories of motivated r...
Abstract: Despite its growing prominence in news coverage and public discourse, there is still considerable ambiguity regarding when and how fact-checking affects beliefs. Informed by theories of motivated r...
212 citations
Sage Bionetworks1, Kaiser Permanente2, University of Washington3, Eötvös Loránd University4, University of Michigan5, Tencent6, National University of Singapore7, University Health System8, Spanish National Research Council9, Polytechnic University of Valencia10, University College London11, University of Illinois at Urbana–Champaign12, IBM13, University of Haifa14, Stanford University15, Karolinska Institutet16, Icahn School of Medicine at Mount Sinai17, Fred Hutchinson Cancer Research Center18, Bill & Melinda Gates Foundation19, Center for Devices and Radiological Health20, Karolinska University Hospital21, Microsoft22, North Carolina State University23, University of California, San Francisco24, Emory University25, New York University26, Dortmund University of Applied Sciences and Arts27, Queensland University of Technology28, Institute for Infocomm Research Singapore29, Duke University30, Korea University31
TL;DR: This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms.
Abstract: Importance Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists’ specificity with radiologists’ sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists’ recall assessment was developed and evaluated. Results Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists’ sensitivity, lower than community-practice radiologists’ specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation.
TL;DR: In contemporary high-choice media environments, the issue of media trust and its impact on people's media use has taken on new importance as mentioned in this paper, and the extent to which people trust the new...
Abstract: In contemporary high-choice media environments, the issue of media trust and its impact on people's media use has taken on new importance. At the same time, the extent to which people trust the new...
Columbia University1, Allen Institute for Brain Science2, University of Copenhagen3, Carleton University4, George Mason University5, Technical University of Madrid6, Max Planck Society7, University of Oxford8, Aarhus University9, Harvard University10, University of Edinburgh11, VU University Amsterdam12, Cajal Institute13, Vanderbilt University14, Scuola Normale Superiore di Pisa15, University of Kiel16, École Polytechnique Fédérale de Lausanne17, Ruhr University Bochum18, Novartis19, Karolinska Institutet20, Cold Spring Harbor Laboratory21, Massachusetts Institute of Technology22, RWTH Aachen University23, University of Western Ontario24, Leiden University25, Stanford University26, King's College London27, University of Haifa28, Charles University in Prague29, Bar-Ilan University30, Macquarie University31, J. Craig Venter Institute32, Spanish National Research Council33, University of Göttingen34, University of Szeged35, Baylor College of Medicine36, University of Strathclyde37, New York University38
TL;DR: This work proposes the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex that should be hierarchical and use a standardized nomenclature, and could serve as an example for cell type atlases in other parts of the body.
Abstract: To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.
University of Naples Federico II1, Utrecht University2, University of Liverpool3, University of Veterinary Medicine Vienna4, Free University of Berlin5, Spiru Haret University6, Warsaw University of Life Sciences7, University of Porto8, Spanish National Research Council9, University of Haifa10, SIDI11, Lithuanian University of Health Sciences12, Norwegian University of Life Sciences13, Swedish University of Agricultural Sciences14, Queen's University Belfast15, Ghent University16
TL;DR: A European wide assessment of the economic burden of gastrointestinal nematodes, Fasciola hepatica (common liver fluke) and Dictyocaulus viviparus (bovine lungworm) infections to the ruminant livestock industry is reported.
TL;DR: Parvocellular OT neurons receive particular inputs to control social behavior by coordinating the responses of the much larger population of magnocellular oxytocin neurons, which consequently show coordinated increases in their activity during social interactions between virgin female rats.
Abstract: Oxytocin (OT) is a great facilitator of social life but, although its effects on socially relevant brain regions have been extensively studied, OT neuron activity during actual social interactions remains unexplored. Most OT neurons are magnocellular neurons, which simultaneously project to the pituitary and forebrain regions involved in social behaviors. In the present study, we show that a much smaller population of OT neurons, parvocellular neurons that do not project to the pituitary but synapse onto magnocellular neurons, is preferentially activated by somatosensory stimuli. This activation is transmitted to the larger population of magnocellular neurons, which consequently show coordinated increases in their activity during social interactions between virgin female rats. Selectively activating these parvocellular neurons promotes social motivation, whereas inhibiting them reduces social interactions. Thus, parvocellular OT neurons receive particular inputs to control social behavior by coordinating the responses of the much larger population of magnocellular OT neurons. Charlet, Grinevich et al. show that social touch between female rats activates parvocellular oxytocin neurons; these neurons control social behavior by coordinating the responses of the much larger population of magnocellular oxytocin neurons.
TL;DR: An algorithm based on a non-local prior that recovers the atmospheric light, the distance map and the haze-free image is proposed, which has linear complexity, requires no training, and performs well on a wide variety of images compared to other state-of-the-art methods.
Abstract: Haze often limits visibility and reduces contrast in outdoor images. The degradation varies spatially since it depends on the objects’ distances from the camera. This dependency is expressed in the transmission coefficients, which control the attenuation. Restoring the scene radiance from a single image is a highly ill-posed problem, and thus requires using an image prior. Contrary to methods that use patch-based image priors, we propose an algorithm based on a non-local prior. The algorithm relies on the assumption that colors of a haze-free image are well approximated by a few hundred distinct colors, which form tight clusters in RGB space. Our key observation is that pixels in a given cluster are often non-local, i.e., spread over the entire image plane and located at different distances from the camera. In the presence of haze these varying distances translate to different transmission coefficients. Therefore, each color cluster in the clear image becomes a line in RGB space, that we term a haze-line. Using these haze-lines, our algorithm recovers the atmospheric light, the distance map and the haze-free image. The algorithm has linear complexity, requires no training, and performs well on a wide variety of images compared to other state-of-the-art methods.
TL;DR: The reach of fake news websites is limited to small parts of the population as mentioned in this paper, however, large proportions of the public know about notable fake news sites and are aware of them.
Abstract: Research indicates that the reach of fake news websites is limited to small parts of the population. On the other hand, data demonstrate that large proportions of the public know about notable fake...
TL;DR: In this paper, the sensitivity of human Coronavirus (HCoV-OC43 used as SARS-CoV2 surrogate) was wavelength dependent with 267nm,279nm, and286nm.
Abstract: UV light-emitting diodes (UV LEDs) are an emerging technology and a UV source for pathogen inactivation, however low UV-LED wavelengths are costly and have low fluence rate. Our results suggest that the sensitivity of human Coronavirus (HCoV-OC43 used as SARS-CoV-2 surrogate) was wavelength dependent with 267 nm ~ 279 nm > 286 nm > 297 nm. Other viruses showed similar results, suggesting UV LED with peak emission at ~286 nm could serve as an effective tool in the fight against human Coronaviruses.
Francis Crick Institute1, Queen Mary University of London2, Ludwig Maximilian University of Munich3, University College Dublin4, University of Porto5, Swedish Museum of Natural History6, University of Oxford7, University of Liverpool8, Liverpool John Moores University9, University of Aberdeen10, National Museum of Natural History11, Stockholm University12, University of Gothenburg13, Harvard University14, Hartwick College15, Russian Academy of Sciences16, University of Tehran17, University of Haifa18, Irkutsk State University19, University of Belgrade20, North-Eastern Federal University21, Sapienza University of Rome22, Baylor University23, Royal Belgian Institute of Natural Sciences24, University of Copenhagen25, Lundbeck26, Leiden University27, Hebrew University of Jerusalem28, Tomsk State University29, University of Alberta30, Centre national de la recherche scientifique31, Istanbul University32, University of York33, University College London34, Durham University35, University of Thessaly36, Hellenic Ministry of Culture and Sports37, University of the Basque Country38, Pennsylvania State University39, Texas A&M University40, University of Vienna41
TL;DR: It is found that all dogs share a common ancestry distinct from present-day wolves, with limited gene flow from wolves since domestication but substantial dog-to-wolf gene flow.
Abstract: Dogs were the first domestic animal, but little is known about their population history and to what extent it was linked to humans. We sequenced 27 ancient dog genomes and found that all dogs share a common ancestry distinct from present-day wolves, with limited gene flow from wolves since domestication but substantial dog-to-wolf gene flow. By 11,000 years ago, at least five major ancestry lineages had diversified, demonstrating a deep genetic history of dogs during the Paleolithic. Coanalysis with human genomes reveals aspects of dog population history that mirror humans, including Levant-related ancestry in Africa and early agricultural Europe. Other aspects differ, including the impacts of steppe pastoralist expansions in West and East Eurasia and a near-complete turnover of Neolithic European dog ancestry.
TL;DR: It is estimated that children are less susceptible to infection, which is an additional factor explaining their relatively low rate of occurrence within confirmed cases, and this results indicate that children, when infected, are somewhat less prone to infect others compared to adults.
Abstract: Summary Background One of the significant unanswered questions about COVID-19 epidemiology relates to the role of children in transmission. In this study we estimate susceptibility and infectivity of children compared to those of adults. Understanding the age-structured transmission dynamics of the outbreak provides precious and timely information to guide epidemic modelling and public health policy. Methods Data were collected from households in the city of Bnei Brak, Israel, in which all household members were tested for COVID-19 using PCR. To estimate relative transmission parameters in the absence of data on who infected whom, we developed an estimation method based on a discrete stochastic dynamic model of the spread of the epidemic within a household. The model describes the propagation of the disease between household members allowing for susceptibility and infectivity parameters to vary among two age groups. The parameter estimates are obtained by a maximum likelihood method, where the likelihood function is computed based on the stochastic model via simulations. Findings Inspection of the data reveals that children are less likely to become infected compared to adults (25% of children infected over all households, 44% of adults infected over all households, excluding index cases), and the chances of becoming infected increases with age. An interesting exception is that infants up to age one year are more likely to be infected than children between one and four. Using our modelling approach, we estimate that the susceptibility of children (under 20 years old) is 45% [40%, 55%] of the susceptibility of adults. The infectivity of children was estimated to be 85% [65%, 110%] relative to that of adults. Interpretation It is widely observed that the percentage of children within confirmed cases is low. A common explanation is that children who are infected are less likely to develop symptoms than adults, and thus are less likely to be tested. We estimate that children are less susceptible to infection, which is an additional factor explaining their relatively low rate of occurrence within confirmed cases. Moreover, our results indicate that children, when infected, are somewhat less prone to infect others compared to adults; however, this result is not statistically significant. The resulting estimates of susceptibility and infectivity of children compared to adults are crucial for deciding on appropriate interventions, and for controlling the epidemic outbreak and its progress. These estimates can guide age-dependent public health policy such as school closure and opening. However, while our estimates of children’s susceptibility and infectivity are lower than those of adults within a household, it is important to bear in mind that their role in the spread of COVID-19 outside the household, is also affected by different contact patterns and hygiene habits.
TL;DR: Though both predictors are complex and may be influenced by many factors, given the potential return of COVID-19 threat and other future health pandemic threats to the authors' world, it must rethink and develop ways to reinforce them.
TL;DR: The current state of knowledge regarding MPs, wastewater and relevant policies that could influence the development and deployment of new technologies within WWTPs are described and existing technologies for capturing very small MP particles are reviewed.
TL;DR: Young subjective age may weaken the loneliness-symptom association among older adults during the COVID-19 pandemic, and suggest interventions aimed at ameliorating both loneliness and older subjective ages.
Abstract: Objective The study examined whether subjective age moderated the relationship between loneliness due to the COVID-19 pandemic and psychiatric symptoms. Methods A convenience sample of older adult Israelis (N = 277, mean age = 69.58 ± 6.72) completed web-based questionnaires comprising loneliness, anxiety, depressive, and peritraumatic distress symptoms. They also reported how old they felt. Results The positive relationship between loneliness due to the COVID-19 pandemic and psychiatric symptoms was weak among those who felt younger than their age while this very same relationship was robust among those feeling older. Conclusions Young subjective age may weaken the loneliness-symptom association among older adults during the COVID-19 pandemic. Older adults holding an older age identity are more susceptible to the adverse effects of loneliness. Although preliminary, the findings may inform screening and interventions. Subjective age may help identify those at high risk in suffering from loneliness, and suggest interventions aimed at ameliorating both loneliness and older subjective ages.
University of Illinois at Urbana–Champaign1, Birkbeck, University of London2, Maastricht University3, University of Greifswald4, Ghent University5, University of Pittsburgh6, University of Haifa7, University of Queensland8, University College London9, Katholieke Universiteit Leuven10, University of Potsdam11
TL;DR: This work analyzed the language used to describe attention-related aspects of emotion, and highlighted terms related to domains such as conscious awareness, motivational effects of attention, social attention, and emotion regulation within a broader review of available evidence regarding the neural correlates of emotion-attention interactions.
TL;DR: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017, and future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.
Abstract: Background Past research in population health trends has shown
that injuries form a substantial burden of population health loss.
Regular updates to injury burden assessments are critical. We report
Global Burden of Disease (GBD) 2017 Study estimates on morbidity
and mortality for all injuries.
Methods We reviewed results for injuries from the GBD 2017 study.
GBD 2017 measured injury-specific mortality and years of life lost
(YLLs) using the Cause of Death Ensemble model. To measure non-fatal
injuries, GBD 2017 modelled injury-specific incidence and converted
this to prevalence and years lived with disability (YLDs). YLLs and YLDs
were summed to calculate disability-adjusted life years (DALYs).
Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138)
injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554)
deaths in 2017, while age-standardised mortality decreased from 1079
(1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were
354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802)
new cases of injury globally, which increased to 520 710 288 (493
430 247 to 547 988 635) new cases in 2017. During this time, agestandardised incidence decreased non-significantly from 6824 (6534 to
7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017,
age-standardised DALYs decreased from 4947 (4655 to 5233) per
100 000 to 3267 (3058 to 3505).
Interpretation Injuries are an important cause of health loss
globally, though mortality has declined between 1990 and 2017.
Future research in injury burden should focus on prevention in highburden populations, improving data collection and ensuring access to
medical care.
Proceedings Article•
30 Apr 2020TL;DR: In this paper, a sampling-based approach for generating compact convolutional neural networks (CNNs) by identifying and removing redundant filters from an over-parameterized network is presented.
Abstract: We present a provable, sampling-based approach for generating compact Convolutional Neural Networks (CNNs) by identifying and removing redundant filters from an over-parameterized network. Our algorithm uses a small batch of input data points to assign a saliency score for each filter and constructs an importance sampling distribution where filters that highly affect the output are sampled with correspondingly high probability. Unlike weight pruning approaches that lead to irregular sparsity patterns -- requiring specialized libraries or hardware to enable computational speedups -- our approach compresses the original network to a slimmer subnetwork, which enables accelerated inference with any off-the-shelf deep learning library and hardware. Existing filter pruning methods are generally data-oblivious, rely on heuristics for evaluating the parameter importance, or require manual and tedious hyper-parameter tuning. In contrast, our method is data-informed, exhibits provable guarantees on the size and performance of the pruned network, and is widely applicable to varying network architectures and data sets. Our analytical bounds bridge the notions of compressibility and importance of network structures, which gives rise to a fully-automated procedure for identifying and preserving the filters in layers that are essential to the network's performance. Our experimental results across varying pruning scenarios show that our algorithm consistently generates sparser and more efficient models than those generated by existing filter pruning approaches.
TL;DR: The results demonstrated that both health worries and ageism were positively associated with anxiety symptoms, and the connection between health fears and anxiety symptoms was more pronounced among older adults with high ageism levels.
Abstract: A prominent feature of anxiety in late life is concerns regarding physical health Anxiety symptoms among older adults have been connected with various psychological outcomes, including social isolation and loneliness During the coronavirus disease 2019 (COVID-19) pandemic, many societies have demonstrated increased ageist attitudes, encouraging older adults to distance themselves from society Accordingly, the current study examined the moderating role of COVID-19-related ageism in the connection between COVID-19 health worries and anxiety symptoms among older adults Data were collected from 243 older adults (age range 60-92; M = 6975, SD = 669), who completed scales assessing COVID-19-related health worries and ageism, as well as anxiety symptoms The results demonstrated that both health worries and ageism were positively associated with anxiety symptoms Moreover, the connection between health worries and anxiety symptoms was more pronounced among older adults with high ageism levels The study highlights the vulnerability of older adults in general, and ageist older adults in particular, to the negative consequences of COVID-19-related health worries, and emphasizes the role of the increased ageist stance of society during the pandemic in this regard
University of Otago1, Senckenberg Museum2, Northern Arizona University3, Arizona State University4, Massey University5, University of Adelaide6, Uppsala University7, South Australian Museum8, Humboldt University of Berlin9, Montana State University10, European Bioinformatics Institute11, University of Copenhagen12, Edward Via College of Osteopathic Medicine13, Virginia–Maryland Regional College of Veterinary Medicine14, University of Haifa15, University of Auckland16, Landcare Research17, University of Sydney18, National Museum of Natural History19, Plant & Food Research20, Pontifical Catholic University of Chile21, Iowa State University22, Spanish National Research Council23, Ludwig Maximilian University of Munich24, Pompeu Fabra University25, University of Canterbury26, Austrian Institute of Technology27, AgResearch28, Harvard University29, Johns Hopkins University30, Victoria University of Wellington31
TL;DR: The approximately 5-Gb tuatara ( Sphenodon punctatus) genome assembly provides a resource for analysing amniote evolution, and highlights the imperative for meaningful cultural engagement with Indigenous communities in genome-sequencing endeavours.
Abstract: The tuatara (Sphenodon punctatus)—the only living member of the reptilian order Rhynchocephalia (Sphenodontia), once widespread across Gondwana1,2—is an iconic species that is endemic to New Zealand2,3. A key link to the now-extinct stem reptiles (from which dinosaurs, modern reptiles, birds and mammals evolved), the tuatara provides key insights into the ancestral amniotes2,4. Here we analyse the genome of the tuatara, which—at approximately 5 Gb—is among the largest of the vertebrate genomes yet assembled. Our analyses of this genome, along with comparisons with other vertebrate genomes, reinforce the uniqueness of the tuatara. Phylogenetic analyses indicate that the tuatara lineage diverged from that of snakes and lizards around 250 million years ago. This lineage also shows moderate rates of molecular evolution, with instances of punctuated evolution. Our genome sequence analysis identifies expansions of proteins, non-protein-coding RNA families and repeat elements, the latter of which show an amalgam of reptilian and mammalian features. The sequencing of the tuatara genome provides a valuable resource for deep comparative analyses of tetrapods, as well as for tuatara biology and conservation. Our study also provides important insights into both the technical challenges and the cultural obligations that are associated with genome sequencing. The approximately 5-Gb tuatara (Sphenodon punctatus) genome assembly provides a resource for analysing amniote evolution, and highlights the imperative for meaningful cultural engagement with Indigenous communities in genome-sequencing endeavours.
TL;DR: The overall prevalence of clinical levels of anxiety, depression, and post-traumatic stress was higher than the prevalence outside a pandemic and was higherthan rates reported among healthcare workers and survivors of severe acute respiratory syndrome.
Abstract: Scientific understanding about the psychological impact of the COVID-19 global pandemic is in its nascent stage. Prior research suggests that demographic factors, such as gender and age, are associated with greater distress during a global health crisis. Less is known about how emotion regulation impacts levels of distress during a pandemic. The present study aimed to identify predictors of psychological distress during the COVID-19 pandemic. Participants (N = 2,787) provided demographics, history of adverse childhood experiences, current coping strategies (use of implicit and explicit emotion regulation), and current psychological distress. The overall prevalence of clinical levels of anxiety, depression, and post-traumatic stress was higher than the prevalence outside a pandemic and was higher than rates reported among healthcare workers and survivors of severe acute respiratory syndrome. Younger participants (<45 years), women, and non-binary individuals reported higher prevalence of symptoms across all measures of distress. A random forest machine learning algorithm was used to identify the strongest predictors of distress. Regression trees were developed to identify individuals at greater risk for anxiety, depression, and post-traumatic stress. Somatization and less reliance on adaptive defense mechanisms were associated with greater distress. These findings highlight the importance of assessing individuals' physical experiences of psychological distress and emotion regulation strategies to help mental health providers tailor assessments and treatment during a global health crisis.
TL;DR: The authors found that the consequences of the economic downturn following the coronavirus pandemic for gender equality are harsh, with women's employment and income more severely affected than men's than men.