Showing papers by "University of Reading published in 2021"
University College London1, International Institute for Applied Systems Analysis2, University of Reading3, United Nations University4, University of London5, University of Colorado Boulder6, Umeå University7, Tsinghua University8, World Health Organization9, Cardiff University10, University of Geneva11, University of New England (United States)12, University of Birmingham13, Yale University14, University of Washington15, Northeastern University16, Virginia Tech17, University of Oxford18, University of York19, International Livestock Research Institute20, Cayetano Heredia University21, Harvard University22, Boston University23, University of Sussex24, Nelson Marlborough Institute of Technology25, Emory University26, Columbia University27, Autonomous University of Barcelona28, Technische Universität München29, University of Melbourne30, Iran University of Medical Sciences31, University of Exeter32, Imperial College London33, University of Sheffield34, European Centre for Disease Prevention and Control35, Universiti Malaysia Terengganu36, University of Santiago de Compostela37
TL;DR: TRANSLATIONS For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.
886 citations
University College London1, University of Reading2, University of York3, United Nations University4, University of London5, Tsinghua University6, World Health Organization7, Cardiff University8, Yale University9, University of Birmingham10, University of Greenwich11, University of Washington12, Northeastern University13, Virginia Tech14, International Livestock Research Institute15, National University of Singapore16, Cayetano Heredia University17, Harvard University18, International Institute for Applied Systems Analysis19, Boston University20, University of Sussex21, Nelson Marlborough Institute of Technology22, Emory University23, Columbia University24, Autonomous University of Barcelona25, Technische Universität München26, University of Melbourne27, University of Copenhagen28, Iran University of Medical Sciences29, Technical University of Denmark30, Umeå University31, Max Planck Society32, University of Colorado Boulder33, University of Exeter34, University of Oxford35, Universiti Malaysia Terengganu36, University of Santiago de Compostela37, University of Hong Kong38
TL;DR: The 2021 report of the Lancet Countdown on health and climate change : code red for a healthy future as mentioned in this paper, is the most recent publication of the Countdown on Health and Climate Change, 2019.
491 citations
Manchester Metropolitan University1, National Oceanic and Atmospheric Administration2, University of Oxford3, German Aerospace Center4, Peking University5, Cooperative Institute for Research in Environmental Sciences6, University of Leeds7, National Center for Atmospheric Research8, Committee on Climate Change9, University of Michigan10, University of California, Irvine11, University of Reading12
TL;DR: CO2-warming-equivalent emissions based on global warming potentials (GWP* method) indicate that aviation emissions are currently warming the climate at approximately three times the rate of that associated with aviation CO2 emissions alone.
437 citations
TL;DR: A systematic review of quantitative and qualitative studies reporting barriers and facilitators to children and adolescents seeking and accessing professional help for mental health problems highlighted the complex array of internal and external factors that determine whether young people seek and access help formental health difficulties.
Abstract: Mental health disorders in children and adolescents are highly prevalent yet undertreated. A detailed understanding of the reasons for not seeking or accessing help as perceived by young people is crucial to address this gap. We conducted a systematic review (PROSPERO 42018088591) of quantitative and qualitative studies reporting barriers and facilitators to children and adolescents seeking and accessing professional help for mental health problems. We identified 53 eligible studies; 22 provided quantitative data, 30 provided qualitative data, and one provided both. Four main barrier/facilitator themes were identified. Almost all studies (96%) reported barriers related to young people’s individual factors, such as limited mental health knowledge and broader perceptions of help-seeking. The second most commonly (92%) reported theme related to social factors, for example, perceived social stigma and embarrassment. The third theme captured young people’s perceptions of the therapeutic relationship with professionals (68%) including perceived confidentiality and the ability to trust an unknown person. The fourth theme related to systemic and structural barriers and facilitators (58%), such as financial costs associated with mental health services, logistical barriers, and the availability of professional help. The findings highlight the complex array of internal and external factors that determine whether young people seek and access help for mental health difficulties. In addition to making effective support more available, targeted evidence-based interventions are required to reduce perceived public stigma and improve young people’s knowledge of mental health problems and available support, including what to expect from professionals and services.
241 citations
228 citations
University of Exeter1, Complutense University of Madrid2, Ludwig Maximilian University of Munich3, German Aerospace Center4, Met Office5, National Oceanic and Atmospheric Administration6, University of Reading7, ETH Zurich8, Hebrew University of Jerusalem9, Courant Institute of Mathematical Sciences10, Free University of Berlin11, National Center for Atmospheric Research12
TL;DR: Sudden stratospheric warmings (SSWs) are impressive fluid dynamical events in which large and rapid temperature increases in the winter polar stratosphere (10−50km) are associated with a complete reversal of the climatological wintertime westerly winds.
Abstract: Sudden stratospheric warmings (SSWs) are impressive fluid dynamical events in which large and rapid temperature increases in the winter polar stratosphere (⁓10‐50km) are associated with a complete reversal of the climatological wintertime westerly winds. SSWs are caused by the breaking of planetary‐scale waves that propagate upwards from the troposphere. During an SSW, the polar vortex breaks down, accompanied by rapid descent and warming of air in polar latitudes, mirrored by ascent and cooling above the warming. The rapid warming and descent of the polar air column affects tropospheric weather, shifting jet streams, storm tracks, and the Northern Annular Mode, making cold air outbreaks over North America and Eurasia more likely. SSWs affect the atmosphere above the stratosphere, producing widespread effects on atmospheric chemistry, temperatures, winds, neutral (non‐ionized) particles and electron densities, and electric fields. These effects span both hemispheres. Given their crucial role in the whole atmosphere, SSWs are also seen as a key process to analyze in climate change studies and subseasonal to seasonal prediction. This work reviews the current knowledge on the most important aspects of SSWs, from the historical background to dynamical processes, modelling, chemistry, and impact on other atmospheric layers.
216 citations
University of Saskatchewan1, Open University of Catalonia2, Bocconi University3, Clausthal University of Technology4, University of Reading5, Sandia National Laboratories6, University of Arizona7, University of Pavia8, Hohai University9, University of Oxford10, University of Manitoba11, University of Bergen12, Princeton University13, Imperial College London14, University of Adelaide15
TL;DR: A multidisciplinary group of researchers and practitioners revisit the current status of Sensitivity analysis, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems.
Abstract: Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of researchers and practitioners revisit the current status of SA, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems. Six areas are discussed that warrant further attention, including (1) structuring and standardizing SA as a discipline, (2) realizing the untapped potential of SA for systems modeling, (3) addressing the computational burden of SA, (4) progressing SA in the context of machine learning, (5) clarifying the relationship and role of SA to uncertainty quantification, and (6) evolving the use of SA in support of decision making. An outlook for the future of SA is provided that underlines how SA must underpin a wide variety of activities to better serve science and society.
207 citations
Centre national de la recherche scientifique1, University of Montpellier2, Agricultural Research Service3, University of Dundee4, James Hutton Institute5, University of Natural Resources and Life Sciences, Vienna6, University of Manchester7, Wageningen University and Research Centre8, University of Reading9, Czech University of Life Sciences Prague10, Morton Arboretum11, University of Hamburg12, University of Göttingen13, Macquarie University14, Forschungszentrum Jülich15, Spanish National Research Council16, University of Georgia17, Polish Academy of Sciences18, Adam Mickiewicz University in Poznań19, ETH Zurich20, University of Minnesota21, Oak Ridge National Laboratory22, University of Auvergne23, Laurentian University24, University of Freiburg25, Leiden University26, Chinese Academy of Sciences27, Florida International University28, Leipzig University29
TL;DR: It is found that below-ground traits with widest importance in plant and ecosystem functioning are not those most commonly measured, and advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with strongest influence on the functions, and to link genotypes to plant andcosystem functioning.
Abstract: The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. We also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.
205 citations
TL;DR: A review of recent, emerging, and anticipated trends in probiotic and prebiotic science, and a vision for broad areas of developing influence in the field can be found in this article.
191 citations
Newcastle University1, Royal Netherlands Meteorological Institute2, National Center for Atmospheric Research3, University of Adelaide4, University of Reading5, University of Innsbruck6, Swedish Meteorological and Hydrological Institute7, Ho Chi Minh City University of Agriculture and Forestry8, University of Michigan9, University of Copenhagen10, Jacobs University Bremen11, Met Office12, ETH Zurich13, University of New South Wales14, University of Iowa15, University of Melbourne16
TL;DR: In this paper, the authors examined evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding and concluded that short-duration and long-duration (>1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture.
Abstract: Short-duration (1–3 h) rainfall extremes can cause serious damage to societies through rapidly developing (flash) flooding and are determined by complex, multifaceted processes that are altering as Earth’s climate warms. In this Review, we examine evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding. Both short-duration and long-duration (>1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture (~7% K−1), while in some regions, increases in short-duration extreme rainfall intensities are stronger than expected from moisture increases alone. These stronger local increases are related to feedbacks in convective clouds, but their exact role is uncertain because of the very small scales involved. Future extreme rainfall intensification is also modulated by changes to temperature stratification and large-scale atmospheric circulation. The latter remains a major source of uncertainty. Intensification of short-duration extremes has likely increased the incidence of flash flooding at local scales, and this can further compound with an increase in storm spatial footprint to considerably increase total event rainfall. These findings call for urgent climate change adaptation measures to manage increasing flood risks. Short-duration rainfall extremes are determined by complex processes that are affected by the warming climate. This Review assesses the evidence for the intensification of short-duration rainfall extremes, the associated drivers and the implications for flood risks.
183 citations
TL;DR: In this article, a deep generative model using radar observations is used to create skilful precipitation predictions that are accurate and support real-world utility, using statistical, economic and cognitive measures, which provides improved forecast quality, forecast consistency and forecast value.
Abstract: Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socioeconomic needs of many sectors reliant on weather-dependent decision-making1,2. State-of-the-art operational nowcasting methods typically advect precipitation fields with radar-based wind estimates, and struggle to capture important non-linear events such as convective initiations3,4. Recently introduced deep learning methods use radar to directly predict future rain rates, free of physical constraints5,6. While they accurately predict low-intensity rainfall, their operational utility is limited because their lack of constraints produces blurry nowcasts at longer lead times, yielding poor performance on rarer medium-to-heavy rain events. Here we present a deep generative model for the probabilistic nowcasting of precipitation from radar that addresses these challenges. Using statistical, economic and cognitive measures, we show that our method provides improved forecast quality, forecast consistency and forecast value. Our model produces realistic and spatiotemporally consistent predictions over regions up to 1,536 km × 1,280 km and with lead times from 5–90 min ahead. Using a systematic evaluation by more than 50 expert meteorologists, we show that our generative model ranked first for its accuracy and usefulness in 89% of cases against two competitive methods. When verified quantitatively, these nowcasts are skillful without resorting to blurring. We show that generative nowcasting can provide probabilistic predictions that improve forecast value and support operational utility, and at resolutions and lead times where alternative methods struggle. A deep generative model using radar observations is used to create skilful precipitation predictions that are accurate and support real-world utility.
TL;DR: The music and social bonding (MSB) hypothesis provides the most comprehensive theory to date of the biological and cultural evolution of music.
Abstract: Why do humans make music? Theories of the evolution of musicality have focused mainly on the value of music for specific adaptive contexts such as mate selection, parental care, coalition signaling, and group cohesion. Synthesizing and extending previous proposals, we argue that social bonding is an overarching function that unifies all of these theories, and that musicality enabled social bonding at larger scales than grooming and other bonding mechanisms available in ancestral primate societies. We combine cross-disciplinary evidence from archeology, anthropology, biology, musicology, psychology, and neuroscience into a unified framework that accounts for the biological and cultural evolution of music. We argue that the evolution of musicality involves gene-culture coevolution, through which proto-musical behaviors that initially arose and spread as cultural inventions had feedback effects on biological evolution because of their impact on social bonding. We emphasize the deep links between production, perception, prediction, and social reward arising from repetition, synchronization, and harmonization of rhythms and pitches, and summarize empirical evidence for these links at the levels of brain networks, physiological mechanisms, and behaviors across cultures and across species. Finally, we address potential criticisms and make testable predictions for future research, including neurobiological bases of musicality and relationships between human music, language, animal song, and other domains. The music and social bonding hypothesis provides the most comprehensive theory to date of the biological and cultural evolution of music.
Texas A&M University1, University of Exeter2, University of Helsinki3, Université du Québec à Montréal4, Tanjungpura University5, University of Hawaii at Manoa6, University of Bristol7, Bowdoin College8, Chulalongkorn University9, University of California, Los Angeles10, Max Planck Society11, University of Nottingham12, University of Magallanes13, Oeschger Centre for Climate Change Research14, Université de Montréal15, Lehigh University16, Northeast Normal University17, Mount Holyoke College18, McGill University19, Stockholm University20, University of Leicester21, Katholieke Universiteit Leuven22, University of St Andrews23, Florida State University24, Aarhus University25, University of Toronto26, University of New Hampshire27, University of Łódź28, Centre national de la recherche scientifique29, Cranfield University30, University of Alberta31, Stockholm Environment Institute32, Lawrence Berkeley National Laboratory33, United States Geological Survey34, Texas A&M University at Galveston35, University of Victoria36, Adam Mickiewicz University in Poznań37, Finnish Meteorological Institute38, Royal Holloway, University of London39, University of Queensland40, Lamont–Doherty Earth Observatory41, National Park Service42, University of York43, Hope College44, University of Reading45, Uva Wellassa University46, Queen's University Belfast47, University of California, Berkeley48, Memorial University of Newfoundland49
TL;DR: In this article, the authors define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future.
Abstract: The carbon balance of peatlands is predicted to shift from a sink to a source this century. However, peatland ecosystems are still omitted from the main Earth system models that are used for future climate change projections, and they are not considered in integrated assessment models that are used in impact and mitigation studies. By using evidence synthesized from the literature and an expert elicitation, we define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future. We also identify uncertainties and knowledge gaps in the scientific community and provide insight towards better integration of peatlands into modelling frameworks. Given the importance of the contribution by peatlands to the global carbon cycle, this study shows that peatland science is a critical research area and that we still have a long way to go to fully understand the peatland–carbon–climate nexus. Peatlands are impacted by climate and land-use changes, with feedback to warming by acting as either sources or sinks of carbon. Expert elicitation combined with literature review reveals key drivers of change that alter peatland carbon dynamics, with implications for improving models.
Lamont–Doherty Earth Observatory1, University of St Andrews2, University of Arizona3, Naval Postgraduate School4, University of Texas at Austin5, University of California, Los Angeles6, Federal University of Paraná7, Pusan National University8, Bureau of Meteorology9, Indian Institute of Tropical Meteorology10, Ocean University of China11, Nanjing Normal University12, Stanford University13, University of Connecticut14, National Taiwan University15, University of Reading16, Sun Yat-sen University17, Chinese Academy of Sciences18
TL;DR: This article provided a review on past monsoon changes and their primary drivers, the projected future changes and key physical processes, and discuss challenges of the present and future modeling and outlooks.
Abstract: Monsoon rainfall has profound economic and societal impacts for more than two-thirds of the global population. Here we provide a review on past monsoon changes and their primary drivers, the projected future changes and key physical processes, and discuss challenges of the present and future modeling and outlooks. Continued global warming and urbanization over the past century has already caused a significant rise in the intensity and frequency of extreme rainfall events in all monsoon regions (high confidence). Observed changes in the mean monsoon rainfall vary by region with significant decadal variations. NH land monsoon rainfall as a whole declined from 1950 to 1980 and rebounded after the 1980s, due to the competing influences of internal climate variability and radiative forcing from GHGs and aerosol forcing (high confidence); however, it remains a challenge to quantify their relative contributions. The CMIP6 models simulate better global monsoon intensity and precipitation over CMIP5 models, but common biases and large intermodal spreads persist. Nevertheless, there is high confidence that the frequency and intensity of monsoon extreme rainfall events will increase, alongside an increasing risk of drought over some regions. Also, land monsoon rainfall will increase in South Asia and East Asia (high confidence) and northern Africa (medium confidence), and decrease in North America and unchanged in Southern Hemisphere. Over Asian-Australian monsoon region the rainfall variability is projected to increase on daily to decadal scales. The rainy season will likely be lengthened in the Northern Hemisphere due to late retreat (especially over East Asia), but shortened in the Southern Hemisphere due to delayed onset.
King's College London1, University at Buffalo2, Goddard Space Flight Center3, University of Bremen4, University of Alaska Fairbanks5, University of Oslo6, Bjerknes Centre for Climate Research7, Utrecht University8, Université libre de Bruxelles9, California Institute of Technology10, University of Grenoble11, University of Edinburgh12, University of California, San Diego13, University of St Andrews14, International Institute for Applied Systems Analysis15, University of Leeds16, University of Tokyo17, University of Reading18, Met Office19, National Center for Atmospheric Research20, University of Bristol21, Université Paris-Saclay22, Columbia University23, Goddard Institute for Space Studies24, Potsdam Institute for Climate Impact Research25, Victoria University of Wellington26, Los Alamos National Laboratory27, Colorado State University28, Hokkaido University29, University of California, Irvine30, Universities Space Research Association31, University of Liège32, Nagoya University33, University of Tasmania34, Australian Antarctic Division35, University of Lapland36, University of Tromsø37, Norwegian Polar Institute38, Alfred Wegener Institute for Polar and Marine Research39, ETH Zurich40, University of Fribourg41, Swiss Federal Institute for Forest, Snow and Landscape Research42, Vrije Universiteit Brussel43, GNS Science44, Lawrence Berkeley National Laboratory45, University of Innsbruck46, University of Liverpool47, University of British Columbia48, Carnegie Mellon University49, Memorial University of Newfoundland50, Pennsylvania State University51, University of Potsdam52, Beijing Normal University53, CSC – IT Center for Science54
TL;DR: In this article, the authors estimate probability distributions for these projections under the new scenarios using statistical emulation of the ice sheet and glacier models, and find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges.
Abstract: The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2,3,4,5,6,7,8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.
TL;DR: A systematic review of the literature on the effect of the COVID-19 pandemic on entrepreneurship and small businesses can be found in this paper, with a discussion of four literature strands based on this review and an overview of contributions in this special issue.
Abstract: The existential threat to small businesses, based on their crucial role in the economy, is behind the plethora of scholarly studies in 2020, the first year of the COVID-19 pandemic. Examining the 15 contributions of the special issue on the “Economic effects of the COVID-19 pandemic on entrepreneurship and small businesses,” the paper comprises four parts: a systematic review of the literature on the effect on entrepreneurship and small businesses; a discussion of four literature strands based on this review; an overview of the contributions in this special issue; and some ideas for post-pandemic economic research.
TL;DR: In this paper, the authors highlight the need to incorporate social sustainability (or simply "people") into technological trajectories and outline a framework of multi-actor co-innovation to guide responsible socio-technical transitions.
TL;DR: In this article, the authors used T1-weighted magnetic resonance images to determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.
Abstract: Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.
Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.
Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.
Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls.
Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.
Conclusions and Relevance In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
Saleh Abdalla1, Abdolnabi Abdeh Kolahchi, Michael Ablain, Susheel Adusumilli2 +357 more•Institutions (88)
TL;DR: In 2018, the 25th year of development of radar altimetry was celebrated and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences as discussed by the authors.
TL;DR: In this paper, the effect of face masks on face identification and emotion recognition in Western cultures was investigated, and the results of three experiments were shown to reveal little difference in performance for faces in masks compared with faces in sunglasses.
Abstract: Face masks present a new challenge to face identification (here matching) and emotion recognition in Western cultures. Here, we present the results of three experiments that test the effect of masks, and also the effect of sunglasses (an occlusion that individuals tend to have more experienced with) on (i) familiar face matching, (ii) unfamiliar face matching and (iii) emotion categorization. Occlusion reduced accuracy in all three tasks, with most errors in the mask condition; however, there was little difference in performance for faces in masks compared with faces in sunglasses. Super-recognizers, people who are highly skilled at matching unconcealed faces, were impaired by occlusion, but at the group level, performed with higher accuracy than controls on all tasks. Results inform psychology theory with implications for everyday interactions, security and policing in a mask-wearing society.
TL;DR: The authors found that without a crowd, fewer yellow cards were awarded to the away teams, reducing home advantage, and that the influence of social pressure and crowds on the neutrality of decisions was large and statistically significant on the number of yellow cards issued by referees.
University of Cambridge1, University of East Anglia2, University of Reading3, National University of Comahue4, University of Calcutta5, Bogor Agricultural University6, University of Córdoba (Spain)7, National Scientific and Technical Research Council8, National University of Río Negro9, World Agroforestry Centre10, Prescott College11, Plant & Food Research12, University of São Paulo13, University of KwaZulu-Natal14, Kyungpook National University15, International Centre of Insect Physiology and Ecology16, University of Cape Town17
TL;DR: The authors evaluated the relative regional and global importance of eight drivers of pollinator decline and ten consequent risks to human well-being using a formal expert elicitation process, and concluded that global policy responses should focus on reducing pressure from changes in land cover and configuration, land management and pesticides.
Abstract: Pollinator decline has attracted global attention and substantial efforts are underway to respond through national pollinator strategies and action plans. These policy responses require clarity on what is driving pollinator decline and what risks it generates for society in different parts of the world. Using a formal expert elicitation process, we evaluated the relative regional and global importance of eight drivers of pollinator decline and ten consequent risks to human well-being. Our results indicate that global policy responses should focus on reducing pressure from changes in land cover and configuration, land management and pesticides, as these were considered very important drivers in most regions. We quantify how the importance of drivers and risks from pollinator decline, differ among regions. For example, losing access to managed pollinators was considered a serious risk only for people in North America, whereas yield instability in pollinator-dependent crops was classed as a serious or high risk in four regions but only a moderate risk in Europe and North America. Overall, perceived risks were substantially higher in the Global South. Despite extensive research on pollinator decline, our analysis reveals considerable scientific uncertainty about what this means for human society.
University of Geneva1, Centre national de la recherche scientifique2, École Normale Supérieure3, University of Paris4, University of Reading5, Yale University6, University at Buffalo7, Vilnius University8, University of Lima9, Tilburg University10, Harvard University11, University of Bern12, Charles III University of Madrid13, Pontifical Catholic University of Rio de Janeiro14, University of the Basque Country15, Lawrence University16, Middlebury College17, Washington & Jefferson College18, University of Zurich19, University of Sheffield20, University of Puget Sound21, University of Pittsburgh22, Ghent University23, Queen's University Belfast24, University of Turin25, Paris-Sorbonne University26, Spanish National Research Council27
TL;DR: The X-Phi Replicability Project (XRP) as discussed by the authors was formed to estimate the reproducibility of experimental philosophy (osf.io/dvkpr) studies published between 2003 and 2015 and recruited 20 research teams across 8 countries to conduct a high-quality replication of each study in order to compare the results to the original published findings.
Abstract: Responding to recent concerns about the reliability of the published literature in psychology and other disciplines, we formed the X-Phi Replicability Project (XRP) to estimate the reproducibility of experimental philosophy (osf.io/dvkpr). Drawing on a representative sample of 40 x-phi studies published between 2003 and 2015, we enlisted 20 research teams across 8 countries to conduct a high-quality replication of each study in order to compare the results to the original published findings. We found that x-phi studies – as represented in our sample – successfully replicated about 70% of the time. We discuss possible reasons for this relatively high replication rate in the field of experimental philosophy and offer suggestions for best research practices going forward.
TL;DR: The CLIVAR 2020 ENSO metrics package as mentioned in this paper enables model diagnosis, comparison, and evaluation to highlight aspects that need improvement; monitor progress across model generations; help in selecting models that are well suited for particular analyses; reveal links between various model biases, illuminating the impacts of those biases on the sensitivity to climate change.
Abstract: El Nino–Southern Oscillation (ENSO) is the dominant mode of interannual climate variability on the planet, with far-reaching global impacts. It is therefore key to evaluate ENSO simulations in state-of-the-art numerical models used to study past, present, and future climate. Recently, the Pacific Region Panel of the International Climate and Ocean: Variability, Predictability and Change (CLIVAR) Project, as a part of the World Climate Research Programme (WCRP), led a community-wide effort to evaluate the simulation of ENSO variability, teleconnections, and processes in climate models. The new CLIVAR 2020 ENSO metrics package enables model diagnosis, comparison, and evaluation to 1) highlight aspects that need improvement; 2) monitor progress across model generations; 3) help in selecting models that are well suited for particular analyses; 4) reveal links between various model biases, illuminating the impacts of those biases on ENSO and its sensitivity to climate change; and to 5) advance ENSO literacy. By interfacing with existing model evaluation tools, the ENSO metrics package enables rapid analysis of multipetabyte databases of simulations, such as those generated by the Coupled Model Intercomparison Project phases 5 (CMIP5) and 6 (CMIP6). The CMIP6 models are found to significantly outperform those from CMIP5 for 8 out of 24 ENSO-relevant metrics, with most CMIP6 models showing improved tropical Pacific seasonality and ENSO teleconnections. Only one ENSO metric is significantly degraded in CMIP6, namely, the coupling between the ocean surface and subsurface temperature anomalies, while the majority of metrics remain unchanged.
TL;DR: The authors showed that there is a consensus on the distinction between curiosity and interest by training a Naive Bayes classification algorithm to distinguish between free-text definitions of interest and curiosity and using cross-validation to test the classifier on two sets of data (main n = 196; additional n = 218).
Abstract: Researchers studying curiosity and interest note a lack of consensus in whether and how these important motivations for learning are distinct. Empirical attempts to distinguish them are impeded by this lack of conceptual clarity. Following a recent proposal that curiosity and interest are folk concepts, we sought to determine a non-expert consensus view on their distinction using machine learning methods. In Study 1, we demonstrate that there is a consensus in how they are distinguished, by training a Naive Bayes classification algorithm to distinguish between free-text definitions of curiosity and interest (n = 396 definitions) and using cross-validation to test the classifier on two sets of data (main n = 196; additional n = 218). In Study 2, we demonstrate that the non-expert consensus is shared by experts and can plausibly underscore future empirical work, as the classifier accurately distinguished definitions provided by experts who study curiosity and interest (n = 92). Our results suggest a shared consensus on the distinction between curiosity and interest, providing a basis for much-needed conceptual clarity facilitating future empirical work. This consensus distinguishes curiosity as more active information seeking directed towards specific and previously unknown information. In contrast, interest is more pleasurable, in-depth, less momentary information seeking towards information in domains where people already have knowledge. However, we note that there are similarities between the concepts, as they are both motivating, involve feelings of wanting, and relate to knowledge acquisition.
Université Paris-Saclay1, University of Reading2, Max Planck Society3, University of Arizona4, Yale University5, University of Tokyo6, University of Toronto7, University of Leeds8, University of Bristol9, Goddard Institute for Space Studies10, Russian Academy of Sciences11, Japan Agency for Marine-Earth Science and Technology12, University of Bremen13, VU University Amsterdam14, National Center for Atmospheric Research15
TL;DR: In this article, a new generation of climate models has been used to generate LGM simulations as part of the PMIP contribution to the Coupled model intercomparison project (CMIP).
Abstract: The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.
TL;DR: In this article, the authors examined the digital export drivers as means for firms to exploit opportunities brought about by digital technologies in their B2C digital marketing activities and found that SMEs do not suffer from a weaker propensity to engage with digital export despite resources constraints.
01 Oct 2021
01 Apr 2021
TL;DR: In this article, the authors explored how mental health symptoms in children and adolescents changed over a month of full lockdown in the UK in response to the COVID-19 pandemic.
Abstract: Background
The COVID-19 pandemic has caused extensive disruption to the lives of children and young people. Understanding the psychological effects on children and young people, in the context of known risk factors, is crucial to mitigate the effects of the pandemic. This study set out to explore how mental health symptoms in children and adolescents changed over a month of full lockdown in the UK in response to the pandemic.
Methods
UK-based parents and carers (n = 2,673) of school-aged children and young people aged between 4 and 16 years completed an online survey about their child’s mental health at two time points between March and May 2020, during early lockdown. The survey examined changes in emotional symptoms, conduct problems and hyperactivity/inattention.
Results
The findings highlighted particular deteriorations in mental health symptoms among pre-adolescent children, which translated to a 10% increase in those meeting possible/probable caseness criteria for emotional symptoms, a 20% increase in hyperactivity/inattention, and a 35% increase in conduct problems. In contrast, changes among adolescents were smaller (4% and 8% increase for hyperactivity/inattention and conduct problems respectively) with a small reduction in emotional symptoms (reflecting a 3% reduction in caseness). Overall, there were few differences in change in symptoms or caseness over time according to demographic characteristics, but children and young people in low income households and those with special educational needs and/or neurodevelopmental disorders, exhibited elevated symptoms (and caseness) at both time points.
Conclusions
The findings highlight important areas of concern in terms of the potential impact of the first national lockdown on children and young people’s adjustment. Developing an understanding of who has been most severely affected by the pandemic, and in what ways, is crucial in order to target effective support where it is most needed.