Showing papers by "Dartmouth College published in 2018"
Gregory A. Roth1, Gregory A. Roth2, Degu Abate3, Kalkidan Hassen Abate4 +1025 more•Institutions (333)
TL;DR: Non-communicable diseases comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5–74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional causes accounted for 18·6% (17·9–19·6), and injuries 8·0% (7·7–8·2).
5,211 citations
12 Apr 2018
TL;DR: In this article, a new spatio-temporal convolutional block "R(2+1)D" was proposed, which achieved state-of-the-art performance on Sports-1M, Kinetics, UCF101, and HMDB51.
Abstract: In this paper we discuss several forms of spatiotemporal convolutions for video analysis and study their effects on action recognition. Our motivation stems from the observation that 2D CNNs applied to individual frames of the video have remained solid performers in action recognition. In this work we empirically demonstrate the accuracy advantages of 3D CNNs over 2D CNNs within the framework of residual learning. Furthermore, we show that factorizing the 3D convolutional filters into separate spatial and temporal components yields significantly gains in accuracy. Our empirical study leads to the design of a new spatiotemporal convolutional block "R(2+1)D" which produces CNNs that achieve results comparable or superior to the state-of-the-art on Sports-1M, Kinetics, UCF101, and HMDB51.
1,827 citations
University of Southern California1, Duke University2, Stockholm School of Economics3, University of Virginia4, Center for Open Science5, University of Amsterdam6, University of Pennsylvania7, University of North Carolina at Chapel Hill8, University of Regensburg9, California Institute of Technology10, Research Institute of Industrial Economics11, New York University12, Cardiff University13, Northwestern University14, Mathematica Policy Research15, Ohio State University16, University of Sussex17, Texas A&M University18, Royal Holloway, University of London19, University of Zurich20, University of Melbourne21, University of Wisconsin-Madison22, University of Michigan23, Stanford University24, Rutgers University25, Columbia University26, University of Washington27, University of Edinburgh28, National University of Singapore29, Utrecht University30, Arizona State University31, Princeton University32, University of California, Los Angeles33, Imperial College London34, University of Innsbruck35, Harvard University36, University of Chicago37, University of Pittsburgh38, University of Notre Dame39, University of California, Berkeley40, Johns Hopkins University41, University of Bristol42, University of New South Wales43, Dartmouth College44, Whitman College45, University of Puerto Rico46, University of Milan47, University of California, Irvine48, Paris Dauphine University49, University of British Columbia50, Ludwig Maximilian University of Munich51, Purdue University52, Washington University in St. Louis53, University of California, Davis54, Microsoft55
TL;DR: The default P-value threshold for statistical significance is proposed to be changed from 0.05 to 0.005 for claims of new discoveries in order to reduce uncertainty in the number of discoveries.
Abstract: We propose to change the default P-value threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries.
1,586 citations
TL;DR: This updated clinical report provides more practice-based quality improvement guidance on key elements of transition planning, transfer, and integration into adult care for all youth and young adults.
Abstract: Risk and vulnerability encompass many dimensions of the transition from adolescence to adulthood. Transition from pediatric, parent-supervised health care to more independent, patient-centered adult health care is no exception. The tenets and algorithm of the original 2011 clinical report, “Supporting the Health Care Transition from Adolescence to Adulthood in the Medical Home,” are unchanged. This updated clinical report provides more practice-based quality improvement guidance on key elements of transition planning, transfer, and integration into adult care for all youth and young adults. It also includes new and updated sections on definition and guiding principles, the status of health care transition preparation among youth, barriers, outcome evidence, recommended health care transition processes and implementation strategies using quality improvement methods, special populations, education and training in pediatric onset conditions, and payment options. The clinical report also includes new recommendations pertaining to infrastructure, education and training, payment, and research.
1,002 citations
Institute for Health Metrics and Evaluation1, University of Louisville2, Karolinska Institutet3, Kermanshah University of Medical Sciences4, University of Queensland5, Centre for Mental Health6, Tehran University of Medical Sciences7, University of KwaZulu-Natal8, South African Medical Research Council9, University of Colorado Boulder10, University of California, Irvine11, Fred Hutchinson Cancer Research Center12, Montefiore Medical Center13, Northeastern University14, University of Alabama at Birmingham15, Brown University16, San Diego State University17, University of Melbourne18, Albert Einstein College of Medicine19, Cambridge Health Alliance20, Johns Hopkins University21, University of Pittsburgh22, University of Cape Town23, Case Western Reserve University24, Marshall University25, University of London26, University of Illinois at Urbana–Champaign27, National Drug and Alcohol Research Centre28, Harvard University29, University of California, San Diego30, Yale University31, Veterans Health Administration32, Georgetown University33, Jackson State University34, University of Massachusetts Boston35, State University of New York System36, Simmons College37, Charles R. Drew University of Medicine and Science38, University of California, Los Angeles39, University of Oxford40, Norwegian Institute of Public Health41, Curtin University42, Pacific Institute43, Heidelberg University44, Jimma University45, Northwestern University46, Washington University in St. Louis47, Howard University48, University of New Mexico49, University at Buffalo50, University of Washington51, University of South Florida52, Tufts University53, University of Rochester Medical Center54, Kosin University55, Central South University56, Michigan State University57, Ball State University58, Nova Southeastern University59, Dalhousie University60, Mayo Clinic61, University of British Columbia62, Ohio State University63, Baylor University64, Wrocław Medical University65, Jagiellonian University Medical College66, Dartmouth College67, University of Western Ontario68, Oregon Health & Science University69, Virginia Commonwealth University70, Columbia University71, University of Canberra72, Aga Khan University73
TL;DR: There are wide differences in the burden of disease at the state level and specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention.
Abstract: Introduction Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. Objective To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. Design and Setting A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. Main Outcomes and Measures Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. Results Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). Conclusions and Relevance There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.
962 citations
TL;DR: It is shown that the widely used commercial risk assessment software COMPAS is no more accurate or fair than predictions made by people with little or no criminal justice expertise.
Abstract: Algorithms for predicting recidivism are commonly used to assess a criminal defendant's likelihood of committing a crime. These predictions are used in pretrial, parole, and sentencing decisions. Proponents of these systems argue that big data and advanced machine learning make these analyses more accurate and less biased than humans. We show, however, that the widely used commercial risk assessment software COMPAS is no more accurate or fair than predictions made by people with little or no criminal justice expertise. We further show that a simple linear predictor provided with only two features is nearly equivalent to COMPAS with its 137 features.
633 citations
Fredrick R. Schumacher1, Ali Amin Al Olama2, Sonja I. Berndt3, Sara Benlloch2 +204 more•Institutions (79)
TL;DR: A large meta-analysis combining genome-wide and custom high-density genotyping array data identifies 63 new susceptibility loci for prostate cancer, enhancing fine-mapping efforts and providing insights into the underlying biology of PrCa1.
Abstract: Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10−9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55–2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04–6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1. A large meta-analysis combining genome-wide and custom high-density genotyping array data identifies 63 new susceptibility loci for prostate cancer, enhancing fine-mapping efforts and providing insights into the underlying biology.
585 citations
TL;DR: This article develops a meta-framework that specifies antecedents, dimensions, mechanisms, moderators, and outcomes of dynamic capabilities identified in the literature to date and proposes a forward-looking research agenda that outlines directions for future research.
Abstract: Although the dynamic capabilities perspective has become one of the most frequently used theoretical lenses in management research, critics have repeatedly voiced their frustration with this literature, particularly bemoaning the lack of empirical knowledge and the underspecification of the construct of dynamic capabilities. But research on dynamic capabilities has advanced considerably since its early years, in which most contributions to this literature were purely conceptual. A plethora of empirical studies as well as further theoretical elaborations have shed substantial light on a variety of specific, measurable factors connected to dynamic capabilities. Our article starts out by analyzing these studies to develop a meta-framework that specifies antecedents, dimensions, mechanisms, moderators, and outcomes of dynamic capabilities identified in the literature to date. This framework provides a comprehensive and systematic synthesis of the dynamic capabilities perspective that reflects the richness of the research while at the same time unifying it into a cohesive, overarching model. Such an analysis has not yet been undertaken; no comprehensive framework with this level of detail has previously been presented for dynamic capabilities. Our analysis shows where research has made the most progress and where gaps and unresolved tensions remain. Based on this analysis, we propose a forward-looking research agenda that outlines directions for future research.
524 citations
Hofstra University1, Charité2, University of Verona3, King's College London4, Lundbeck5, Copenhagen University Hospital6, Yale University7, Maastricht University8, University of Hong Kong9, The Feinstein Institute for Medical Research10, SUNY Downstate Medical Center11, Dartmouth College12, Boston University13, University of Calgary14, University of North Carolina at Chapel Hill15, Nathan Kline Institute for Psychiatric Research16, National Institutes of Health17
TL;DR: In this paper, the authors compared early intervention services (EIS) with treatment as usual (TAU) for early-phase psychosis and found that EIS was associated with better outcomes than TAU at the end of treatment for all 13 meta-analyzable outcomes.
Abstract: Importance The value of early intervention in psychosis and allocation of public resources has long been debated because outcomes in people with schizophrenia spectrum disorders have remained suboptimal. Objective To compare early intervention services (EIS) with treatment as usual (TAU) for early-phase psychosis. Data Sources Systematic literature search of PubMed, PsycINFO, EMBASE, and ClinicalTrials.gov without language restrictions through June 6, 2017. Study Selection Randomized trials comparing EIS vs TAU in first-episode psychosis or early-phase schizophrenia spectrum disorders. Data Extraction and Synthesis This systematic review was conducted according to PRISMA guidelines. Three independent investigators extracted data for a random-effects meta-analysis and prespecified subgroup and meta-regression analyses. Main Outcomes and Measures The coprimary outcomes were all-cause treatment discontinuation and at least 1 psychiatric hospitalization during the treatment period. Results Across 10 randomized clinical trials (mean [SD] trial duration, 16.2 [7.4] months; range, 9-24 months) among 2176 patients (mean [SD] age, 27.5 [4.6] years; 1355 [62.3%] male), EIS was associated with better outcomes than TAU at the end of treatment for all 13 meta-analyzable outcomes. These outcomes included the following: all-cause treatment discontinuation (risk ratio [RR], 0.70; 95% CI, 0.61-0.80; P P = .003), involvement in school or work (RR, 1.13; 95% CI, 1.03-1.24; P = .01), total symptom severity (standardized mean difference [SMD], −0.32; 95% CI, −0.47 to −0.17; P P P Conclusions and Relevance In early-phase psychosis, EIS are superior to TAU across all meta-analyzable outcomes. These results support the need for funding and use of EIS in patients with early-phase psychosis.
445 citations
TL;DR: This editorial reviews key insights from the literature on digital infrastructures and platforms, present emerging research themes, highlight the contributions developed from each of the six articles in this special issue, and conclude with suggestions for further research.
Abstract: In the last few years, leading-edge research from information systems, strategic management, and economics have separately informed our understanding of platforms and infrastructures in the digital age. Our motivation for undertaking this special issue rests in the conviction that it is significant to discuss platforms and infrastructures concomitantly, while enabling knowledge from diverse disciplines to cross-pollinate to address critical, pressing policy challenges and inform strategic thinking across both social and business spheres. In this editorial, we review key insights from the literature on digital infrastructures and platforms, present emerging research themes, highlight the contributions developed from each of the six articles in this special issue, and conclude with suggestions for further research.
442 citations
TL;DR: It is proposed that three types of dynamic capabilities at a minimum are critical for platform leaders: innovation capabilities, environmental scanning and sensing capabilities, and integrative capabilities for ecosystem orchestration.
Proceedings Article•
30 Jun 2018TL;DR: It is demonstrated that a calibrated curriculum learning scheme, a careful choice of negative examples, and the use of a contrastive loss are critical ingredients to obtain powerful multi-sensory representations from models optimized to discern temporal synchronization of audio-video pairs.
Abstract: There is a natural correlation between the visual and auditive elements of a video. In this work we leverage this connection to learn general and effective models for both audio and video analysis from self-supervised temporal synchronization. We demonstrate that a calibrated curriculum learning scheme, a careful choice of negative examples, and the use of a contrastive loss are critical ingredients to obtain powerful multi-sensory representations from models optimized to discern temporal synchronization of audio-video pairs. Without further fine-tuning, the resulting audio features achieve performance superior or comparable to the state-of-the-art on established audio classification benchmarks (DCASE2014 and ESC-50). At the same time, our visual subnet provides a very effective initialization to improve the accuracy of video-based action recognition models: compared to learning from scratch, our self-supervised pretraining yields a remarkable gain of +19.9% in action recognition accuracy on UCF101 and a boost of +17.7% on HMDB51.
TL;DR: Cryo-EM analyses of a stabilized trimeric SARS-CoV S, as well as the trypsin-cleaved, stabilized S, and its interactions with ACE2 are presented, finding that neither binding to ACE2 nor cleavage bytrypsin at the S1/S2 cleavage site impart large conformational changes within stabilized SARV S.
Abstract: Severe acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 as a highly transmissible pathogenic human betacoronavirus. The viral spike glycoprotein (S) utilizes angiotensin-converting enzyme 2 (ACE2) as a host protein receptor and mediates fusion of the viral and host membranes, making S essential to viral entry into host cells and host species tropism. As SARS-CoV enters host cells, the viral S is believed to undergo a number of conformational transitions as it is cleaved by host proteases and binds to host receptors. We recently developed stabilizing mutations for coronavirus spikes that prevent the transition from the pre-fusion to post-fusion states. Here, we present cryo-EM analyses of a stabilized trimeric SARS-CoV S, as well as the trypsin-cleaved, stabilized S, and its interactions with ACE2. Neither binding to ACE2 nor cleavage by trypsin at the S1/S2 cleavage site impart large conformational changes within stabilized SARS-CoV S or expose the secondary cleavage site, S2′.
TL;DR: The authors demonstrate the severity of experimental post-treatment bias analytically and document the magnitude of the potential distortions it induces using visualizations and reanalyses of real-world data.
Abstract: In principle, experiments o↵er a straightforward method for social scientists to accurately estimate causal e↵ects. However, scholars often unwittingly distort treatment e↵ect estimates by conditioning on variables that could be a↵ected by their experimental manipulation. Typical examples include controlling for post-treatment variables in statistical models, eliminating observations based on post-treatment criteria, or subsetting the data based on post-treatment variables. Though these modeling choices are intended to address common problems encountered when conducting experiments, they can bias estimates of causal e↵ects. Moreover, problems associated with conditioning on post-treatment variables remain largely unrecognized in the field, which we show frequently publishes experimental studies using these practices in our discipline’s most prestigious journals. We demonstrate the severity of experimental post-treatment bias analytically and document the magnitude of the potential distortions it induces using visualizations and reanalyses of real-world data. We conclude by providing applied researchers with recommendations for best practice. ⇤Authors are listed in alphabetical order. The data, code, and any additional materials required to replicate all analyses in this article are available on the American Journal of Political Science Dataverse within the Harvard Dataverse Network at http://dx.doi.org/10.7910/DVN/EZSJ1S. We thank David Broockman, Daniel Butler, Eric S. Dickson, Sanford Gordon, and Gregory Huber for sharing replication data and Ryden Butler, Lindsay Keare, Jake McNichol, Ramtin Rahmani, Rebecca Rodriguez, Erin Rossiter, and Caroline Sohr for research assistance. We are also grateful to Dan Butler, Jake Bowers, Scott Cli↵ord, Eric S. Dickson, D.J. Flynn, Sanford Gordon, Gregory Huber, Jonathan Ladd, David Nickerson, Efrén O. Pérez, Julian Schuessler, Molly Roberts, and three anonymous reviewers for helpful comments. All errors are our own.
Book•
01 Mar 2018TL;DR: The first complete account of the physics of the creep and fracture of ice, and their interconnectivity is given in this paper, where the deformation of low-pressure ice is investigated.
Abstract: This is the first complete account of the physics of the creep and fracture of ice, and their interconnectivity It investigates the deformation of low-pressure ice, which is fundamental to glaciers, polar ice sheets and the uppermost region of icy moons of the outer Solar System The book discusses ice structure and its defects, and describes the relationship between structure and mechanical properties It reviews observations and measurements, and then interprets them in terms of physical mechanisms The book provides a road-map to future studies of ice mechanics, such as the behaviour of glaciers and ice sheets in relation to climate change and the dating of deep ice cores It also highlights how this knowledge is transferable into an understanding of other crystalline materials Written by experts in the field, it is ideal for graduate students, engineers and scientists in Earth and planetary science, and materials science
TL;DR: The current understanding of cytokinin metabolism, transport and signaling is summarized, and how this phytohormone regulates changes in gene expression to mediate its pleiotropic effects is discussed.
Abstract: The phytohormone cytokinin plays diverse roles in plant development, influencing many agriculturally important processes, including growth, nutrient responses and the response to biotic and abiotic stresses. Cytokinin levels in plants are regulated by biosynthesis and inactivation pathways. Cytokinins are perceived by membrane-localized histidine-kinase receptors and are transduced through a His-Asp phosphorelay to activate a family of transcription factors in the nucleus. Here, and in the accompanying poster, we summarize the current understanding of cytokinin metabolism, transport and signaling, and discuss how this phytohormone regulates changes in gene expression to mediate its pleiotropic effects.
University of Arizona1, United States Forest Service2, University of Colorado Boulder3, University of Massachusetts Amherst4, United States Geological Survey5, University of California, Merced6, University of Hawaii at Manoa7, University of Illinois at Urbana–Champaign8, Dartmouth College9, University of Wisconsin-Madison10, University of Pennsylvania11, Northern Arizona University12, University of California, Santa Barbara13, Max Planck Society14, University of Georgia15
TL;DR: In this article, the authors demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power, whereas with increasing moisture availability and acidity, iron-and aluminum-oxyhydroxides emerged as better predictors.
Abstract: Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO2 to the atmosphere Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling
Mayo Clinic1, Yale University2, Johns Hopkins University3, Rhode Island Hospital4, University of North Carolina at Chapel Hill5, Medical College of Wisconsin6, Cleveland Clinic7, Beaumont Health8, Dartmouth College9, University of Louisville10, Tufts University11, NorthShore University HealthSystem12, Rutgers University13
TL;DR: This document, developed by experts in laboratory and adult and pediatric clinical medicine, provides information on which tests are valuable and in which contexts, and on tests that add little or no value for diagnostic decisions.
Abstract: The critical nature of the microbiology laboratory in infectious disease diagnosis calls for a close, positive working relationship between the physician/advanced practice provider and the microbiologists who provide enormous value to the healthcare team. This document, developed by experts in laboratory and adult and pediatric clinical medicine, provides information on which tests are valuable and in which contexts, and on tests that add little or no value for diagnostic decisions. This document presents a system-based approach rather than specimen-based approach, and includes bloodstream and cardiovascular system infections, central nervous system infections, ocular infections, soft tissue infections of the head and neck, upper and lower respiratory infections, infections of the gastrointestinal tract, intra-abdominal infections, bone and joint infections, urinary tract infections, genital infections, and other skin and soft tissue infections; or into etiologic agent groups, including arthropod-borne infections, viral syndromes, and blood and tissue parasite infections. Each section contains introductory concepts, a summary of key points, and detailed tables that list suspected agents; the most reliable tests to order; the samples (and volumes) to collect in order of preference; specimen transport devices, procedures, times, and temperatures; and detailed notes on specific issues regarding the test methods, such as when tests are likely to require a specialized laboratory or have prolonged turnaround times. In addition, the pediatric needs of specimen management are also emphasized. There is intentional redundancy among the tables and sections, as many agents and assay choices overlap. The document is intended to serve as a guidance for physicians in choosing tests that will aid them to quickly and accurately diagnose infectious diseases in their patients.
TL;DR: A sequential innovation model is developed that allows for optimal levels of openness and of intellectual property IP duration in a platform ecosystem and can inform innovation strategy, choice of organizational form, IP noncompete decisions, and regulation policy.
Abstract: Suppose that a firm in charge of a business ecosystem is a firm in charge of a microeconomy. To achieve the highest growth rate, how open should that economy be? To encourage third-party developers, how long should their intellectual property interests last? We develop a sequential innovation model that addresses the trade-offs inherent in these two decisions: i Closing the platform increases the sponsor's ability to charge for access, while opening the platform increases developer ability to build upon it. ii The longer third-party developers retain rights to their innovations, the higher the royalties they and the sponsor earn, but the sooner those developers' rights expire, the sooner their innovations become a public good upon which other developers can build. Our model allows us to characterize the optimal levels of openness and of intellectual property IP duration in a platform ecosystem. We use standard Cobb-Douglas production technologies to derive our results. These findings can inform innovation strategy, choice of organizational form, IP noncompete decisions, and regulation policy.
This paper was accepted by Chris Forman, information systems.
TL;DR: The progress in the development of 2D conductive MOFs with emphasis on synthetic modularity, device integration strategies, and multifunctional properties is summarized.
TL;DR: Gaur et al. as discussed by the authors investigated the impact of showrooms on demand generation and operational efficiency of online-first retailers and found that showrooms increase demand overall and in the online channel as well, and generate operational spillovers to other channels by attracting customers who have a higher cost-to-serve.
Abstract: Omnichannel environments where customers shop online and offline at the same retailer are ubiquitous, and are deployed by online-first and traditional retailers alike. We focus on the relatively understudied domain of online-first retailers and the engagement of a key omnichannel tactic; specifically, introduction of showrooms physical locations where customers can view and try products in combination with online fulfillment that uses centralized inventory management. We ask whether, and if so, how, showrooms benefit the two most basic retail objectives: demand generation and operational efficiency. Using quasi-experimental data on showroom openings by WarbyParker.com , the leading and iconic online-first eyewear retailer, we find that showrooms: 1 increase demand overall and in the online channel as well; 2 generate operational spillovers to the other channels by attracting customers who, on average, have a higher cost-to-serve; 3 improve overall operational efficiency by increasing conversion in a sampling channel and by decreasing returns; and 4 amplify these demand and operational benefits in dealing with customers who have the most acute need for the firm's products. Moreover, the effects we document strengthen with time as showrooms contribute not only to brand awareness but also to what we term channel awareness as well. We conclude by elaborating the underlying customer dynamics driving our findings and by offering implications for how online-first retailers might deploy omnichannel tactics.
This paper was accepted by Vishal Gaur, operations management.
TL;DR: Active galactic nuclei (AGN) are powered by the accretion of material onto a supermassive black hole (SMBH) and are among the most luminous objects in the Universe.
Abstract: Active galactic nuclei (AGN) are powered by the accretion of material onto a supermassive black hole (SMBH) and are among the most luminous objects in the Universe. However, the huge radiative powe...
University of California, Berkeley1, Imperial College London2, University of Delaware3, University of Maryland, College Park4, Dartmouth College5, West Virginia University6, Southwest Research Institute7, University of New Hampshire8, Goddard Space Flight Center9, The Catholic University of America10, Swedish Institute of Space Physics11, University of Toulouse12, University of Colorado Boulder13, École Polytechnique14, University of California, Los Angeles15, Royal Institute of Technology16, Austrian Academy of Sciences17
TL;DR: Observations of electron-scale current sheets in Earth’s turbulent magnetosheath reveal electron reconnection without ion coupling, contrary to expectations from the standard model of magnetic reconnection.
Abstract: Magnetic reconnection in current sheets is a magnetic-to-particle energy conversion process that is fundamental to many space and laboratory plasma systems. In the standard model of reconnection, this process occurs in a minuscule electron-scale diffusion region1,2. On larger scales, ions couple to the newly reconnected magnetic-field lines and are ejected away from the diffusion region in the form of bi-directional ion jets at the ion Alfven speed3-5. Much of the energy conversion occurs in spatially extended ion exhausts downstream of the diffusion region 6 . In turbulent plasmas, which contain a large number of small-scale current sheets, reconnection has long been suggested to have a major role in the dissipation of turbulent energy at kinetic scales7-11. However, evidence for reconnection plasma jetting in small-scale turbulent plasmas has so far been lacking. Here we report observations made in Earth's turbulent magnetosheath region (downstream of the bow shock) of an electron-scale current sheet in which diverging bi-directional super-ion-Alfvenic electron jets, parallel electric fields and enhanced magnetic-to-particle energy conversion were detected. Contrary to the standard model of reconnection, the thin reconnecting current sheet was not embedded in a wider ion-scale current layer and no ion jets were detected. Observations of this and other similar, but unidirectional, electron jet events without signatures of ion reconnection reveal a form of reconnection that can drive turbulent energy transfer and dissipation in electron-scale current sheets without ion coupling.
12 May 2018
TL;DR: A review of recent advances in understanding of drought dynamics, drawing from studies of paleoclimate, the historical record, and model simulations of the past and future, can be found in this paper.
Abstract: Drought is a complex and multivariate phenomenon influenced by diverse physical and biological processes. Such complexity precludes simplistic explanations of cause and effect, making investigations of climate change and drought a challenging task. Here, we review important recent advances in our understanding of drought dynamics, drawing from studies of paleoclimate, the historical record, and model simulations of the past and future. Paleoclimate studies of drought variability over the last two millennia have progressed considerably through the development of new reconstructions and analyses combining reconstructions with process-based models. This work has generated new evidence for tropical Pacific forcing of megadroughts in Southwest North America, provided additional constraints for interpreting climate change projections in poorly characterized regions like East Africa, and demonstrated the exceptional magnitude of many modern era droughts. Development of high resolution proxy networks has lagged in many regions (e.g., South America, Africa), however, and quantitative comparisons between the paleoclimate record, models, and observations remain challenging. Fingerprints of anthropogenic climate change consistent with long-term warming projections have been identified for droughts in California, the Pacific Northwest, Western North America, and the Mediterranean. In other regions (e.g., Southwest North America, Australia, Africa), however, the degree to which climate change has affected recent droughts is more uncertain. While climate change-forced declines in precipitation have been detected for the Mediterranean, in most regions, the climate change signal has manifested through warmer temperatures that have increased evaporative losses and reduced snowfall and snowpack levels, amplifying deficits in soil moisture and runoff despite uncertain precipitation changes. Over the next century, projections indicate that warming will increase drought risk and severity across much of the subtropics and mid-latitudes in both hemispheres, a consequence of regional precipitation declines and widespread warming. For many regions, however, the magnitude, robustness, and even direction of climate change-forced trends in drought depends on how drought is defined, with often large differences across indicators of precipitation, soil moisture, runoff, and vegetation health. Increasing confidence in climate change projections of drought and the associated impacts will likely depend on resolving uncertainties in processes that are currently poorly constrained (e.g., land-atmosphere interactions, terrestrial vegetation) and improved consideration of the role for human policies and management in ameliorating and adapting to changes in drought risk.
02 Feb 2018
TL;DR: The REV2 algorithm is developed, a system to identify fraudulent users and outperforms nine existing algorithms in detecting fair and unfair users and is guaranteed to converge and has linear time complexity.
Abstract: Rating platforms enable large-scale collection of user opinion about items(e.g., products or other users). However, untrustworthy users give fraudulent ratings for excessive monetary gains. In this paper, we present REV2, a system to identify such fraudulent users. We propose three interdependent intrinsic quality metrics---fairness of a user, reliability of a rating and goodness of a product. The fairness and reliability quantify the trustworthiness of a user and rating, respectively, and goodness quantifies the quality of a product. Intuitively, a user is fair if it provides reliable scores that are close to the goodness of products. We propose six axioms to establish the interdependency between the scores, and then, formulate a mutually recursive definition that satisfies these axioms. We extend the formulation to address cold start problem and incorporate behavior properties. We develop the REV2 algorithm to calculate these intrinsic quality scores for all users, ratings, and products. We show that this algorithm is guaranteed to converge and has linear time complexity. By conducting extensive experiments on five rating datasets, we show that REV2 outperforms nine existing algorithms in detecting fair and unfair users. We reported the 150 most unfair users in the Flipkart network to their review fraud investigators, and 127 users were identified as being fraudulent(84.6% accuracy). The REV2 algorithm is being deployed at Flipkart.
TL;DR: A novel correlation metric, capable of distinguishing MBL from AL in high-temperature spin systems, is presented and the use of this metric is demonstrated to detect localization in a natural solid-state spin system using nuclear magnetic resonance (NMR).
Abstract: Characterizing out-of-equilibrium many-body dynamics is a complex but crucial task for quantum applications and understanding fundamental phenomena. A central question is the role of localization in quenching thermalization in many-body systems and whether such localization survives in the presence of interactions. Probing this question in real systems necessitates the development of an experimentally measurable metric that can distinguish between different types of localization. While it is known that the localized phase of interacting systems [many-body localization (MBL)] exhibits a long-time logarithmic growth in entanglement entropy that distinguishes it from the noninteracting case of Anderson localization (AL), entanglement entropy is difficult to measure experimentally. Here, we present a novel correlation metric, capable of distinguishing MBL from AL in high-temperature spin systems. We demonstrate the use of this metric to detect localization in a natural solid-state spin system using nuclear magnetic resonance (NMR). We engineer the natural Hamiltonian to controllably introduce disorder and interactions, and observe the emergence of localization. In particular, while our correlation metric saturates for AL, it slowly keeps increasing for MBL, demonstrating analogous features to entanglement entropy, as we show in simulations. Our results show that our NMR techniques, akin to measuring out-of-time correlations, are well suited for studying localization in spin systems.
TL;DR: This comprehensive review summarizes the most important and recent developments of microalgae use as supplement or feed additive to replace fishmeal and fish oil for use in aquaculture.
Abstract: Due to the rapid global expansion of the aquaculture industry, access to key feedstuffs (fishmeal and fish oil) is becoming increasingly limited because of the finite resources available for wild fish harvesting. This has resulted in other sources of feedstuffs being investigated, namely plant origin substitutes for fishmeal and fish oil for aquafeed. Conventional land-based crops have been favored for some applications as substitutes for a portion of the fishmeal, but they can result in changes in the nutritional quality of the fish produced. Microalgae can be regarded as a promising alternative that can replace fishmeal and fish oil and ensure sustainability standards in aquaculture. They have a potential for use in aquaculture as they are sources of protein, lipid, vitamins, minerals, pigments, etc. This comprehensive review summarizes the most important and recent developments of microalgae use as supplement or feed additive to replace fishmeal and fish oil for use in aquaculture. It also reflects the microalgal nutritional quality and digestibility of microalgae-based aquafeed. Simultaneously, safety and regulatory aspects of microalgae feed applications, major challenges on the use microalgae in aquafeed in commercial production, and future research and development perspective are also presented in a critical manner. This review will serve as a useful guide to present current status of knowledge and highlight key areas for future development of a microalgae-based aquafeed industry and overall development of a sustainable aquaculture industry.
18 Jun 2018
TL;DR: In this paper, the authors propose an extremely lightweight yet highly effective approach that operates in two-stages: keypoint estimation in frames or short clips, followed by lightweight tracking to generate keypoint predictions linked over the entire video.
Abstract: This paper addresses the problem of estimating and tracking human body keypoints in complex, multi-person video. We propose an extremely lightweight yet highly effective approach that builds upon the latest advancements in human detection [17] and video understanding [5]. Our method operates in two-stages: keypoint estimation in frames or short clips, followed by lightweight tracking to generate keypoint predictions linked over the entire video. For frame-level pose estimation we experiment with Mask R-CNN, as well as our own proposed 3D extension of this model, which leverages temporal information over small clips to generate more robust frame predictions. We conduct extensive ablative experiments on the newly released multi-person video pose estimation benchmark, PoseTrack, to validate various design choices of our model. Our approach achieves an accuracy of 55.2% on the validation and 51.8% on the test set using the Multi-Object Tracking Accuracy (MOTA) metric, and achieves state of the art performance on the ICCV 2017 PoseTrack keypoint tracking challenge [1].
TL;DR: A closed-loop system is used to decode and stimulate periods of ineffective encoding, showing that stimulation of lateral temporal cortex can enhance memory and suggesting that such systems may provide a therapeutic approach for treating memory dysfunction.
Abstract: Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct brain recordings in humans. We apply targeted stimulation to lateral temporal cortex and report that this stimulation rescues periods of poor memory encoding. This system also improves later recall, revealing that the lateral temporal cortex is a reliable target for memory enhancement. Taken together, our results suggest that such systems may provide a therapeutic approach for treating memory dysfunction.
TL;DR: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time to enable users to calculate temporal trends in biodiversity within and amongst assemblage using a broad range of metrics.
Abstract: Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)).Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.