{"results":[{"id":"ss_c39cb1d30420c0af70f0b1f72ace1c05a9d06e84","title":"A meta-analysis of projected global food demand and population at risk of hunger for the period 2010–2050","authors":[{"name":"Michiel van Dijk"},{"name":"Tomas Morley"},{"name":"M. Rau"},{"name":"Y. Saghai"}],"abstract":"","source":"Semantic Scholar","year":2021,"language":"en","subjects":["Medicine","Geography"],"doi":"10.1038/s43016-021-00322-9","url":"https://www.semanticscholar.org/paper/c39cb1d30420c0af70f0b1f72ace1c05a9d06e84","pdf_url":"https://www.nature.com/articles/s43016-021-00322-9.pdf","is_open_access":true,"citations":1632,"published_at":"","score":95},{"id":"ss_00d4f4b2e38a2fbe15c672c21c522e2f95264cb0","title":"The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application","authors":[{"name":"S. Lauer"},{"name":"K. Grantz"},{"name":"Qifang Bi"},{"name":"Forrest K. Jones"},{"name":"Qulu Zheng"},{"name":"Hannah R. Meredith"},{"name":"A. Azman"},{"name":"N. Reich"},{"name":"J. Lessler"}],"abstract":"Background: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities. Objective: To estimate the length of the incubation period of COVID-19 and describe its public health implications. Design: Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020. Setting: News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China. Participants: Persons with confirmed SARS-CoV-2 infection outside Hubei province, China. Measurements: Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization. Results: There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine. Limitation: Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases. Conclusion: This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases. Primary Funding Source: U.S. Centers for Disease Control and Prevention, National Institute of Allergy and Infectious Diseases, National Institute of General Medical Sciences, and Alexander von Humboldt Foundation.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Medicine"],"doi":"10.7326/M20-0504","url":"https://www.semanticscholar.org/paper/00d4f4b2e38a2fbe15c672c21c522e2f95264cb0","pdf_url":"https://europepmc.org/articles/pmc7081172?pdf=render","is_open_access":true,"citations":5438,"published_at":"","score":94},{"id":"ss_1ed719cd5dc1c519547fb7266bdafc63f11c225c","title":"Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period","authors":[{"name":"S. Kissler"},{"name":"C. Tedijanto"},{"name":"E. Goldstein"},{"name":"Y. Grad"},{"name":"M. Lipsitch"}],"abstract":"What happens next? Four months into the severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) outbreak, we still do not know enough about postrecovery immune protection and environmental and seasonal influences on transmission to predict transmission dynamics accurately. However, we do know that humans are seasonally afflicted by other, less severe coronaviruses. Kissler et al. used existing data to build a deterministic model of multiyear interactions between existing coronaviruses, with a focus on the United States, and used this to project the potential epidemic dynamics and pressures on critical care capacity over the next 5 years. The long-term dynamics of SARS-CoV-2 strongly depends on immune responses and immune cross-reactions between the coronaviruses, as well as the timing of introduction of the new virus into a population. One scenario is that a resurgence in SARS-CoV-2 could occur as far into the future as 2025. Science, this issue p. 860 If immunity wanes, SARS-CoV-2 could cause recurrent wintertime peaks and require sustained surveillance and intermittent social distancing. It is urgent to understand the future of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, and cross-immunity for human coronavirus OC43 (HCoV-OC43) and HCoV-HKU1 using time-series data from the United States to inform a model of SARS-CoV-2 transmission. We projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave. Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022. Additional interventions, including expanded critical care capacity and an effective therapeutic, would improve the success of intermittent distancing and hasten the acquisition of herd immunity. Longitudinal serological studies are urgently needed to determine the extent and duration of immunity to SARS-CoV-2. Even in the event of apparent elimination, SARS-CoV-2 surveillance should be maintained because a resurgence in contagion could be possible as late as 2024.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Medicine","Biology"],"doi":"10.1126/science.abb5793","url":"https://www.semanticscholar.org/paper/1ed719cd5dc1c519547fb7266bdafc63f11c225c","pdf_url":"https://www.fda.gov/media/136625/download","is_open_access":true,"citations":2477,"published_at":"","score":94},{"id":"ss_543e9279c746bdf000d477a19502d82e535d54e6","title":"Online teaching-learning in higher education during lockdown period of COVID-19 pandemic","authors":[{"name":"L. Mishra"},{"name":"Tushar Gupta"},{"name":"A. Shree"}],"abstract":"The whole educational system from elementary to tertiary level has been collapsed during the lockdown period of the novel coronavirus disease 2019 (COVID-19) not only in India but across the globe. This study is a portrayal of online teaching-learning modes adopted by the Mizoram University for the teaching-learning process and subsequent semester examinations. It looks forward to an intellectually enriched opportunity for further future academic decision-making during any adversity. The intended purpose of this paper seeks to address the required essentialities of online teaching-learning in education amid the COVID-19 pandemic and how can existing resources of educational institutions effectively transform formal education into online education with the help of virtual classes and other pivotal online tools in this continually shifting educational landscape. The paper employs both quantitative and qualitative approach to study the perceptions of teachers and students on online teaching-learning modes and also highlighted the implementation process of online teaching-learning modes. The value of this paper is to draw a holistic picture of ongoing online teaching-learning activities during the lockdown period including establishing the linkage between change management process and online teaching-learning process in education system amid the COVID-19 outbreak so as to overcome the persisting academic disturbance and consequently ensure the resumption of educational activities and discourses as a normal course of procedure in the education system.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Sociology","Medicine"],"doi":"10.1016/j.ijedro.2020.100012","url":"https://www.semanticscholar.org/paper/543e9279c746bdf000d477a19502d82e535d54e6","pdf_url":"https://doi.org/10.1016/j.ijedro.2020.100012","is_open_access":true,"citations":1709,"published_at":"","score":94},{"id":"ss_87761cfa527227abe00aa2b91672339ff048eda3","title":"COVID-19: 20 countries’ higher education intra-period digital pedagogy responses","authors":[{"name":"J. Crawford"},{"name":"K. Butler-Henderson"},{"name":"J. Rudolph"},{"name":"B. Malkawi"},{"name":"M. Glowatz"},{"name":"R. Burton"},{"name":"P. Magni"},{"name":"Sin Manw Sophia Lam"}],"abstract":"The Coronavirus 2019 (COVID-19) pandemic has created significant challenges for the global higher education community. Through a desktop analysis leveraging university and government sources where possible, we provide a timely map of the intra-period higher education responses to COVID-19 across 20 countries. We found that the responses by higher education providers have been diverse from having no response through to social isolation strategies on campus and rapid curriculum redevelopment for fully online offerings. We provide in our discussion a typology of the types of responses currently undertaken and assess the agility of higher education in preparing for the pandemic. We believe there are significant opportunities to learn from the pedagogical developments of other universities, in order to strengthen our collective response to COVID-19 now and into the future.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Political Science"],"doi":"10.37074/jalt.2020.3.1.7","url":"https://www.semanticscholar.org/paper/87761cfa527227abe00aa2b91672339ff048eda3","pdf_url":"https://journals.sfu.ca/jalt/index.php/jalt/article/download/191/163","is_open_access":true,"citations":1696,"published_at":"","score":94},{"id":"ss_ee9ecf938304f7f068074ccc6271845eb6128c76","title":"Clinical characteristics and outcomes of patients undergoing surgeries during the incubation period of COVID-19 infection","authors":[{"name":"S. Lei"},{"name":"Fang Jiang"},{"name":"Wating Su"},{"name":"Chang Chen"},{"name":"Jingli Chen"},{"name":"W. Mei"},{"name":"Liying Zhan"},{"name":"Yifan Jia"},{"name":"Liangqing Zhang"},{"name":"Danyong Liu"},{"name":"Zhong-yuan Xia"},{"name":"Z. Xia"}],"abstract":"Abstract Background The outbreak of 2019 novel coronavirus disease (COVID-19) in Wuhan, China, has spread rapidly worldwide. In the early stage, we encountered a small but meaningful number of patients who were unintentionally scheduled for elective surgeries during the incubation period of COVID-19. We intended to describe their clinical characteristics and outcomes. Methods We retrospectively analyzed the clinical data of 34 patients underwent elective surgeries during the incubation period of COVID-19 at Renmin Hospital, Zhongnan Hospital, Tongji Hospital and Central Hospital in Wuhan, from January 1 to February 5, 2020. Findings Of the 34 operative patients, the median age was 55 years (IQR, 43–63), and 20 (58·8%) patients were women. All patients developed COVID-19 pneumonia shortly after surgery with abnormal findings on chest computed tomographic scans. Common symptoms included fever (31 [91·2%]), fatigue (25 [73·5%]) and dry cough (18 [52·9%]). 15 (44·1%) patients required admission to intensive care unit (ICU) during disease progression, and 7 patients (20·5%) died after admission to ICU. Compared with non-ICU patients, ICU patients were older, were more likely to have underlying comorbidities, underwent more difficult surgeries, as well as more severe laboratory abnormalities (eg, hyperleukocytemia, lymphopenia). The most common complications in non-survivors included ARDS, shock, arrhythmia and acute cardiac injury. Interpretation In this retrospective cohort study of 34 operative patients with confirmed COVID-19, 15 (44·1%) patients needed ICU care, and the mortality rate was 20·5%. Funding National Natural Science Foundation of China.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Medicine"],"doi":"10.1016/j.eclinm.2020.100331","url":"https://www.semanticscholar.org/paper/ee9ecf938304f7f068074ccc6271845eb6128c76","pdf_url":"https://europepmc.org/articles/pmc7128617?pdf=render","is_open_access":true,"citations":1003,"published_at":"","score":94},{"id":"ss_b6b8a0ad1dc614fd081d1971ead7adb6535e7c6d","title":"Review and analysis of current responses to COVID-19 in Indonesia: Period of January to March 2020","authors":[{"name":"R. Djalante"},{"name":"Jonatan A. Lassa"},{"name":"Davin H. E. Setiamarga"},{"name":"Aruminingsih Sudjatma"},{"name":"M. Indrawan"},{"name":"B. Haryanto"},{"name":"Choirul Mahfud"},{"name":"M. S. Sinapoy"},{"name":"Susanti Djalante"},{"name":"I. Rafliana"},{"name":"L. Gunawan"},{"name":"G. A. K. Surtiari"},{"name":"Henny Warsilah"}],"abstract":"The world is under pressure from the novel COVID-19 pandemic. Indonesia is the fourth most populous country in the world and predicted to be affected significantly over a longer time period. Our paper aims to provide detailed reporting and analyses of the present rapid responses to COVID-19, between January and March 2020, in Indonesia. We particularly highlight responses taken by the governments, non-government organisations and the community. We outline gaps and limitations in the responses, based on our rapid analysis of media contents, from government speeches and reports, social and mass media platforms. We present five recommendations toward more rapid, effective, and comprehensive responses.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Political Science","Medicine"],"doi":"10.1016/j.pdisas.2020.100091","url":"https://www.semanticscholar.org/paper/b6b8a0ad1dc614fd081d1971ead7adb6535e7c6d","pdf_url":"https://doi.org/10.1016/j.pdisas.2020.100091","is_open_access":true,"citations":986,"published_at":"","score":93.58},{"id":"ss_edc719cfce26135cb1d5c6e8708204e77676abe7","title":"Prevalence of eating disorders over the 2000-2018 period: a systematic literature review.","authors":[{"name":"M. Galmiche"},{"name":"P. Déchelotte"},{"name":"G. Lambert"},{"name":"M. Tavolacci"}],"abstract":"BACKGROUND Eating disorders (EDs) lead to multiple psychiatric and somatic complications and thus constitute a major public health concern. OBJECTIVES The aim of this study was to give an exhaustive view of the studies reporting the prevalence of the different EDs or total EDs and to study their evolution. METHODS A literature search following PRISMA Guidelines and limited to studies in English or French published between 2000 and 2018 was performed and relevant studies were included in this systematic review on the prevalence of EDs. The literature search revealed 94 studies with accurate ED diagnosis and 27 with broad ED diagnosis. RESULTS In 94 studies with accurate ED diagnosis, the weighted means (ranges) of lifetime ED were 8.4% (3.3-18.6%) for women and 2.2% (0.8-6.5%) for men. The weighted means (ranges) of 12-month ED prevalence were 2.2% (0.8-13.1%) for women and 0.7% (0.3-0.9%) for men. The weighted means (ranges) of point prevalence were 5.7% (0.9-13.5%) for women and 2.2% (0.2-7.3%) for men. According to continents, the weighted means (ranges) of point prevalence were 4.6% (2.0-13.5%) in America, 2.2% (0.2-13.1%) in Europe, and 3.5% (0.6-7.8%) in Asia.In addition to the former, 27 other studies reported the prevalence of EDs as broad categories resulting in weighted means (ranges) of total point prevalence of any EDs of 19.4% (6.5-36.0%) for women and 13.8% (3.6-27.1%) for men. CONCLUSIONS Despite the complexity of integrating all ED prevalence data, the most recent studies confirm that EDs are highly prevalent worldwide, especially in women. Moreover, the weighted means of point ED prevalence increased over the study period from 3.5% for the 2000-2006 period to 7.8% for the 2013-2018 period. This highlights a real challenge for public health and healthcare providers.","source":"Semantic Scholar","year":2019,"language":"en","subjects":["Medicine"],"doi":"10.1093/ajcn/nqy342","url":"https://www.semanticscholar.org/paper/edc719cfce26135cb1d5c6e8708204e77676abe7","pdf_url":"https://academic.oup.com/ajcn/article-pdf/109/5/1402/28888027/nqy342.pdf","is_open_access":true,"citations":1261,"published_at":"","score":93},{"id":"ss_ea006a9a8a371e96c2eb486c5202f9bba292e73b","title":"Age, Period, and Cohort Trends in Mood Disorder Indicators and Suicide-Related Outcomes in a Nationally Representative Dataset, 2005–2017","authors":[{"name":"J. Twenge"},{"name":"A. Cooper"},{"name":"Thomas E. Joiner"},{"name":"Mary E. Duffy"},{"name":"Sarah G. Binau"}],"abstract":"Drawing from the National Survey on Drug Use and Health (NSDUH; N = 611,880), a nationally representative survey of U.S. adolescents and adults, we assess age, period, and cohort trends in mood disorders and suicide-related outcomes since the mid-2000s. Rates of major depressive episode in the last year increased 52% 2005–2017 (from 8.7% to 13.2%) among adolescents aged 12 to 17 and 63% 2009–2017 (from 8.1% to 13.2%) among young adults 18–25. Serious psychological distress in the last month and suicide-related outcomes (suicidal ideation, plans, attempts, and deaths by suicide) in the last year also increased among young adults 18–25 from 2008–2017 (with a 71% increase in serious psychological distress), with less consistent and weaker increases among adults ages 26 and over. Hierarchical linear modeling analyses separating the effects of age, period, and birth cohort suggest the trends among adults are primarily due to cohort, with a steady rise in mood disorder and suicide-related outcomes between cohorts born from the early 1980s (Millennials) to the late 1990s (iGen). Cultural trends contributing to an increase in mood disorders and suicidal thoughts and behaviors since the mid-2000s, including the rise of electronic communication and digital media and declines in sleep duration, may have had a larger impact on younger people, creating a cohort effect.","source":"Semantic Scholar","year":2019,"language":"en","subjects":["Psychology","Medicine"],"doi":"10.1037/abn0000410","url":"https://www.semanticscholar.org/paper/ea006a9a8a371e96c2eb486c5202f9bba292e73b","pdf_url":"https://doi.org/10.1037/abn0000410","is_open_access":true,"citations":1122,"published_at":"","score":93},{"id":"ss_d325506ddf66e472c1ea44b2361b0a47896da0bb","title":"The influence of education on health: an empirical assessment of OECD countries for the period 1995–2015","authors":[{"name":"V. Raghupathi"},{"name":"W. Raghupathi"}],"abstract":"Background A clear understanding of the macro-level contexts in which education impacts health is integral to improving national health administration and policy. In this research, we use a visual analytic approach to explore the association between education and health over a 20-year period for countries around the world. Method Using empirical data from the OECD and the World Bank for 26 OECD countries for the years 1995–2015, we identify patterns/associations between education and health indicators. By incorporating pre- and post-educational attainment indicators, we highlight the dual role of education as both a driver of opportunity as well as of inequality. Results Adults with higher educational attainment have better health and lifespans compared to their less-educated peers. We highlight that tertiary education, particularly, is critical in influencing infant mortality, life expectancy, child vaccination, and enrollment rates. In addition, an economy needs to consider potential years of life lost (premature mortality) as a measure of health quality. Conclusions We bring to light the health disparities across countries and suggest implications for governments to target educational interventions that can reduce inequalities and improve health. Our country-level findings on NEET (Not in Employment, Education or Training) rates offer implications for economies to address a broad array of vulnerabilities ranging from unemployment, school life expectancy, and labor market discouragement. The health effects of education are at the grass roots-creating better overall self-awareness on personal health and making healthcare more accessible.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Political Science","Medicine"],"doi":"10.1186/s13690-020-00402-5","url":"https://www.semanticscholar.org/paper/d325506ddf66e472c1ea44b2361b0a47896da0bb","pdf_url":"https://archpublichealth.biomedcentral.com/track/pdf/10.1186/s13690-020-00402-5","is_open_access":true,"citations":796,"published_at":"","score":87.88},{"id":"ss_580d2c6519ea5d9a5eb515ba2fd170506cdac0a2","title":"Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2","authors":[{"name":"M. Crippa"},{"name":"D. Guizzardi"},{"name":"M. Muntean"},{"name":"E. Schaaf"},{"name":"F. Dentener"},{"name":"J. V. van Aardenne"},{"name":"S. Monni"},{"name":"U. Doering"},{"name":"J. Olivier"},{"name":"V. Pagliari"},{"name":"G. Janssens‑Maenhout"}],"abstract":"Abstract. The new version of the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) compiles gaseous and particulate air pollutant emissions, making use of the same anthropogenic sectors, time period (1970–2012), and international activity data that is used for estimating GHG emissions, as described in a companion paper (Janssens-Maenhout et al., 2017). All human activities, except large scale biomass burning and land use, land-use change, and forestry are included in the emissions calculation. The bottom-up compilation methodology of sector-specific emissions was applied consistently for all world countries, providing methodological transparency and comparability between countries. In addition to the activity data used to estimate GHG emissions, air pollutant emissions are determined by the process technology and end-of-pipe emission reduction abatements. Region-specific emission factors and abatement measures were selected from recent available scientific literature and reports. Compared to previous versions of EDGAR, the EDGAR v4.3.2 dataset covers all gaseous and particulate air pollutants, has extended time series (1970–2012), and has been evaluated with quality control and quality assurance (QC and QA) procedures both for the emission time series (e.g. particulate matter – PM – mass balance, gap-filling for missing data, the split-up of countries over time, few updates in the emission factors, etc.) and grid maps (full coverage of the world, complete mapping of EDGAR emissions with sector-specific proxies, etc.). This publication focuses on the gaseous air pollutants of CO, NOx, SO2, total non-methane volatile organic compounds (NMVOCs), NH3, and the aerosols PM10, PM2.5, black carbon (BC), and organic carbon (OC). Considering the 1970–2012 time period, global emissions of SO2 increased from 99 to 103 Mt, CO from 441 to 562 Mt, NOx from 68 to 122 Mt, NMVOC from 119 to 170 Mt, NH3 from 25 to 59 Mt, PM10 from 37 to 65 Mt, PM2.5 from 24 to 41 Mt, BC from 2.7 to 4.5 Mt, and OC from 9 to 11 Mt. We present the country-specific emission totals and analyze the larger emitting countries (including the European Union) to provide insights on major sector contributions. In addition, per capita and per GDP emissions and implied emission factors – the apparent emissions per unit of production or energy consumption – are presented. We find that the implied emission factors (EFs) are higher for low-income countries compared to high-income countries, but in both cases decrease from 1970 to 2012. The comparison with other global inventories, such as the Hemispheric Transport of Air Pollution Inventory (HTAP v2.2) and the Community Emission Data System (CEDS), reveals insights on the uncertainties as well as the impact of data revisions (e.g. activity data, emission factors, etc.). As an additional metric, we analyze the emission ratios of some pollutants to CO2 (e.g. CO∕CO2, NOx∕CO2, NOx∕CO, and SO2∕CO2) by sector, region, and time to identify any decoupling of air pollutant emissions from energy production activities and to demonstrate the potential of such ratios to compare to satellite-derived emission data. Gridded emissions are also made available for the 1970–2012 historic time series, disaggregated for 26 anthropogenic sectors using updated spatial proxies. The analysis of the evolution of hot spots over time allowed us to identify areas with growing emissions and where emissions should be constrained to improve global air quality (e.g. China, India, the Middle East, and some South American countries are often characterized by high emitting areas that are changing rapidly compared to Europe or the USA, where stable or decreasing emissions are evaluated). Sector- and component-specific contributions to grid-cell emissions may help the modelling and satellite communities to disaggregate atmospheric column amounts and concentrations into main emitting sectors. This work addresses not only the emission inventory and modelling communities, but also aims to broaden the usefulness of information available in a global emission inventory such as EDGAR to also include the measurement community. Data are publicly available online through the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432_AP and registered under https://doi.org/10.2904/JRC_DATASET_EDGAR.","source":"Semantic Scholar","year":2018,"language":"en","subjects":["Environmental Science"],"doi":"10.5194/ESSD-10-1987-2018","url":"https://www.semanticscholar.org/paper/580d2c6519ea5d9a5eb515ba2fd170506cdac0a2","pdf_url":"https://essd.copernicus.org/articles/10/1987/2018/essd-10-1987-2018.pdf","is_open_access":true,"citations":662,"published_at":"","score":81.86},{"id":"ss_6cbfeff5e9d4b10b78cbe58171bf0ad13cc3e97d","title":"The Performance of Mutual Funds in the Period 1945-1964","authors":[{"name":"Michael C. Jensen"}],"abstract":"","source":"Semantic Scholar","year":1968,"language":"en","subjects":["Business","Economics"],"doi":"10.2139/SSRN.244153","url":"https://www.semanticscholar.org/paper/6cbfeff5e9d4b10b78cbe58171bf0ad13cc3e97d","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/j.1540-6261.1968.tb00815.x","is_open_access":true,"citations":5449,"published_at":"","score":80},{"id":"ss_144be7a4c12d40f45aca578292d353d74d00e3ab","title":"Period Three Implies Chaos","authors":[{"name":"Tien-Yien Li"},{"name":"J. Yorke"}],"abstract":"","source":"Semantic Scholar","year":1975,"language":"en","subjects":["Mathematics"],"doi":"10.1007/978-0-387-21830-4_6","url":"https://www.semanticscholar.org/paper/144be7a4c12d40f45aca578292d353d74d00e3ab","is_open_access":true,"citations":3602,"published_at":"","score":80},{"id":"ss_4c4ed42eee888239a82837ecc0e361772211d6b5","title":"Classification of Bulk Metallic Glasses by Atomic Size Difference, Heat of Mixing and Period of Constituent Elements and Its Application to Characterization of the Main Alloying Element","authors":[{"name":"A. Takeuchi"},{"name":"A. Inoue"}],"abstract":"","source":"Semantic Scholar","year":2005,"language":"en","subjects":["Materials Science"],"doi":"10.2320/MATERTRANS.46.2817","url":"https://www.semanticscholar.org/paper/4c4ed42eee888239a82837ecc0e361772211d6b5","pdf_url":"https://www.jstage.jst.go.jp/article/matertrans/46/12/46_12_2817/_pdf","is_open_access":true,"citations":4195,"published_at":"","score":80},{"id":"ss_4d508675ee414f4a8041a7270f63f3307ce50476","title":"A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect","authors":[{"name":"J. Robins"}],"abstract":"","source":"Semantic Scholar","year":1986,"language":"en","subjects":["Medicine"],"doi":"10.1016/0270-0255(86)90088-6","url":"https://www.semanticscholar.org/paper/4d508675ee414f4a8041a7270f63f3307ce50476","pdf_url":"https://doi.org/10.1016/0270-0255(86)90088-6","is_open_access":true,"citations":2716,"published_at":"","score":80},{"id":"ss_81d1d25b4b63c612306c6c22ae0a54b0e6da14e0","title":"Natural products as sources of new drugs over the period 1981-2002.","authors":[{"name":"D. Newman"},{"name":"G. Cragg"},{"name":"K. Snader"}],"abstract":"","source":"Semantic Scholar","year":2003,"language":"en","subjects":["Biology","Medicine"],"doi":"10.1021/NP030096L","url":"https://www.semanticscholar.org/paper/81d1d25b4b63c612306c6c22ae0a54b0e6da14e0","is_open_access":true,"citations":3528,"published_at":"","score":80},{"id":"ss_be5a30c950daa063b437f76551d8556f91605478","title":"Critical period effects in second language learning: the influence of maturational state on the acquisition of English as a second language.","authors":[{"name":"Jacqueline S. Johnson"},{"name":"E. Newport"}],"abstract":"","source":"Semantic Scholar","year":1989,"language":"en","subjects":["Psychology","Medicine"],"doi":"10.1016/0010-0285(89)90003-0","url":"https://www.semanticscholar.org/paper/be5a30c950daa063b437f76551d8556f91605478","is_open_access":true,"citations":2774,"published_at":"","score":80},{"id":"ss_c710a105eda480b665bec4b09a6af2acdcde5e55","title":"The role of autophagy during the early neonatal starvation period","authors":[{"name":"Akiko Kuma"},{"name":"M. Hatano"},{"name":"M. Matsui"},{"name":"A. Yamamoto"},{"name":"H. Nakaya"},{"name":"T. Yoshimori"},{"name":"Y. Ohsumi"},{"name":"T. Tokuhisa"},{"name":"N. Mizushima"}],"abstract":"","source":"Semantic Scholar","year":2004,"language":"en","subjects":["Medicine","Biology"],"doi":"10.1038/nature03029","url":"https://www.semanticscholar.org/paper/c710a105eda480b665bec4b09a6af2acdcde5e55","is_open_access":true,"citations":3003,"published_at":"","score":80},{"id":"ss_bdc97359da016cd36b56952cd24a2aab2fe1b0b0","title":"Incubation Period of COVID-19 Caused by Unique SARS-CoV-2 Strains","authors":[{"name":"Yu Wu"},{"name":"Liangyu Kang"},{"name":"Zirui Guo"},{"name":"Jue Liu"},{"name":"Min Liu"},{"name":"Wannian Liang"}],"abstract":"Key Points Question What are the incubation periods of COVID-19 caused by different SARS-CoV-2 strains? Findings In this systematic review and meta-analysis of 141 articles, the pooled incubation period was 6.57 days. The incubation periods of COVID-19 caused by the Alpha, Beta, Delta, and Omicron variants were 5.00, 4.50, 4.41, and 3.42 days, respectively. Meaning These results suggest that with the evolution of mutant strains, the incubation period of COVID-19 decreased gradually from Alpha variant to Omicron variant.","source":"Semantic Scholar","year":2022,"language":"en","subjects":["Medicine"],"doi":"10.1001/jamanetworkopen.2022.28008","url":"https://www.semanticscholar.org/paper/bdc97359da016cd36b56952cd24a2aab2fe1b0b0","pdf_url":"https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2795489/wu_2022_oi_220797_1663007037.14007.pdf","is_open_access":true,"citations":303,"published_at":"","score":75.09},{"id":"ss_cedfdf46ff47b700fc1f388a6facbc48ce9007d7","title":"Psychedelics reopen the social reward learning critical period","authors":[{"name":"Romain Nardou"},{"name":"E. Sawyer"},{"name":"Young Jun Song"},{"name":"Makenzie Wilkinson"},{"name":"Yasmin Padovan-Hernandez"},{"name":"J. L. de Deus"},{"name":"Noelle G Wright"},{"name":"Carine Lama"},{"name":"Sehr Faltin"},{"name":"L. Goff"},{"name":"Genevieve Stein-O’Brien"},{"name":"Gül Dölen"}],"abstract":"Behavioural electrophysiological and transcriptomic studies in mice show that psychedelic drugs reopen the social reward learning critical period and suggest that this involves reorganization of the extracellular matrix. Psychedelics are a broad class of drugs defined by their ability to induce an altered state of consciousness^ 1 , 2 . These drugs have been used for millennia in both spiritual and medicinal contexts, and a number of recent clinical successes have spurred a renewed interest in developing psychedelic therapies^ 3 – 9 . Nevertheless, a unifying mechanism that can account for these shared phenomenological and therapeutic properties remains unknown. Here we demonstrate in mice that the ability to reopen the social reward learning critical period is a shared property across psychedelic drugs. Notably, the time course of critical period reopening is proportional to the duration of acute subjective effects reported in humans. Furthermore, the ability to reinstate social reward learning in adulthood is paralleled by metaplastic restoration of oxytocin-mediated long-term depression in the nucleus accumbens. Finally, identification of differentially expressed genes in the ‘open state’ versus the ‘closed state’ provides evidence that reorganization of the extracellular matrix is a common downstream mechanism underlying psychedelic drug-mediated critical period reopening. Together these results have important implications for the implementation of psychedelics in clinical practice, as well as the design of novel compounds for the treatment of neuropsychiatric disease.","source":"Semantic Scholar","year":2023,"language":"en","subjects":["Medicine"],"doi":"10.1038/s41586-023-06204-3","url":"https://www.semanticscholar.org/paper/cedfdf46ff47b700fc1f388a6facbc48ce9007d7","pdf_url":"https://www.nature.com/articles/s41586-023-06204-3.pdf","is_open_access":true,"citations":237,"published_at":"","score":74.11}],"total":6433295,"page":1,"page_size":20,"sources":["DOAJ","arXiv","Semantic Scholar"],"query":"By period"}