Institution
National Research University – Higher School of Economics
Education•Moscow, Russia•
About: National Research University – Higher School of Economics is a education organization based out in Moscow, Russia. It is known for research contribution in the topics: Population & Politics. The organization has 12873 authors who have published 23376 publications receiving 256396 citations.
Papers published on a yearly basis
Papers
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TL;DR: In this article, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula for high-mass-resolution imaging mass spectrometry is presented.
Abstract: High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry (https://github.com/alexandrovteam/pySM). We introduce a metabolite-signal match score and a target-decoy FDR estimate for spatial metabolomics.
270 citations
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TL;DR: In this paper, the role of ICTs and big data in intra-and interorganizational ties and the consequent effects on enterprises' innovation performance is investigated via structural equation modeling (SEM).
Abstract: The literature suggests that increasing investments in information and communication technologies (ICTs), knowledge exchange and sharing help SMEs tackle the current global and dynamic environment. Given that much of the useful knowledge resides outside the enterprises’ boundaries, these technological tools foster the gathering of big data and information. Despite these premises, few studies have considered the role of ICTs and big data in intra- and inter-organizational ties and the consequent effects on enterprises’ innovation performance. The paper investigates whether ICTs oriented to intra-organizational (in-house research and development [R&D]) and inter-organizational (open innovation) processes improve SMEs’ innovation performance. Therefore, via structural equation modelling (SEM), the study analyses a sample of 239 knowledge-intensive SMEs located in Italy. The noteworthy results are that ICTs oriented to intra- and inter-organizational innovation processes improve both these processes in generating new products and/or services. On this basis, managerial and academic implications are provided, along with avenues for further research.
269 citations
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TL;DR: In this article, a review of the literature in industrial economics and strategic management that deals with RJV partner motives and RJV outcomes is presented, and the state-of-the-art, synthesizes important understandings, and suggests key nodes of a future research agenda.
Abstract: Inter-firm collaboration is not new. What is new is that such collaboration has exploded during the past couple of decades, in parallel to the intensification of international competition. Moreover, the nature of collaboration has changed, shifting from peripheral interests to the very core functions of the corporation, and from equity to non-equity forms of collaboration. Importantly, cooperation focusing on the generation, exchange, and/or adaptation of new technologies has risen at very fast rates. Research joint ventures, the focus of this paper, belong in the latter category. The proliferation of RJVs has created extensive interest among economists, business analysts, and policy decision-makers and led to the profusion of literature on the topic. This paper critically reviews the literature in industrial economics and strategic management that deals with RJV partner motives and RJV outcomes. The paper categorizes the different streams of this literature and indicates the state-of-the-art, synthesizes important understandings, and suggests key nodes of a future research agenda.
265 citations
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TL;DR: This material is based upon work supported by the National Science Foundation, Riksbankens Jubileumsfond, the Swedish Research Council, and the University of Gothenburg as well as internal grants from the Vice-Chancellor's office, the Dean of the College of Social Sciences and the Department of Political Science at University of Gethenburg.
Abstract: This material is based upon work supported by the National Science Foundation (SES-1423944, PI: Daniel Pemstein), Riksbankens Jubileumsfond (Grant M13-0559:1, PI: Staffan I. Lindberg), the Swedish Research Council (2013.0166, PI: Staffan I. Lindberg and Jan Teorell), the Knut and Alice Wallenberg Foundation (PI: Staffan I. Lindberg), and the University of Gothenburg (E 2013/43); as well as internal grants from the Vice-Chancellor’s office, the Dean of the College of Social Sciences, and the Department of Political Science at University of Gothenburg. Marquardt acknowledges research support from the Russian Academic Excellence Project ‘5-100.’ We performed simulations and other computational tasks using resources provided by the Notre Dame Center for Research Computing (CRC) through the High Performance Computing section and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre in Sweden (SNIC 2016/1-382, SNIC 2017/1-406 and 2017/1-68). We specifically acknowledge the assistance of In-Saeng Suh at CRC and Johan Raber and Peter Mu nger at SNIC in facilitating our use of their respective systems.
262 citations
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Institute for Health Metrics and Evaluation1, University of Washington2, Jimma University3, Cairo University4, University of Western Australia5, University of Cartagena6, Karolinska Institutet7, Mekelle University8, Public Health Foundation of India9, University of Gondar10, University of Belgrade11, Harvard University12, Jazan University13, University of Oxford14, University of São Paulo15, University of Valencia16, Kazakh National Medical University17, University of Peradeniya18, International Institute for Population Sciences19, University of the Philippines Manila20, University of Louisville21, Auckland University of Technology22, Catholic University of Portugal23, Wageningen University and Research Centre24, University of Massachusetts Boston25, Mizan–Tepi University26, Debre markos University27, Tehran University of Medical Sciences28, New York Medical College29, Islamic University30, Ball State University31, Northeastern University32, Brown University33, Uppsala University34, University of Haifa35, Mansoura University36, Chinese Academy of Sciences37, Martin Luther University of Halle-Wittenberg38, United Nations Population Fund39, National Institutes of Health40, University of Melbourne41, Kyrgyz State Medical Academy42, Ahmadu Bello University43, Columbia University44, University of Ibadan45, University of British Columbia46, BRAC47, University of Sydney48, University of Maragheh49, University of KwaZulu-Natal50, Universidade Federal de Santa Catarina51, University of Western Ontario52, Addis Ababa University53, Post Graduate Institute of Medical Education and Research54, Jagiellonian University Medical College55, University of Copenhagen56, Cleveland Clinic57, Hospital Sant Joan de Déu Barcelona58, National Research University – Higher School of Economics59, Norwegian Institute of Public Health60, Royal Children's Hospital61, King's College London62, Nanjing University63, University of Mississippi Medical Center64, University of Hong Kong65, Kyoto University66, Jackson State University67, Wuhan University68
TL;DR: Large disparities in total burden of CVD persist between US states despite marked improvements in CVD burden, and increases in risk-deleted CVD DALY rates between 2006 and 2016 in 16 states suggest additional unmeasured risks beyond these traditional factors.
Abstract: Importance Cardiovascular disease (CVD) is the leading cause of death in the United States, but regional variation within the United States is large. Comparable and consistent state-level measures of total CVD burden and risk factors have not been produced previously. Objective To quantify and describe levels and trends of lost health due to CVD within the United States from 1990 to 2016 as well as risk factors driving these changes. Design, Setting, and Participants Using the Global Burden of Disease methodology, cardiovascular disease mortality, nonfatal health outcomes, and associated risk factors were analyzed by age group, sex, and year from 1990 to 2016 for all residents in the United States using standardized approaches for data processing and statistical modeling. Burden of disease was estimated for 10 groupings of CVD, and comparative risk analysis was performed. Data were analyzed from August 2016 to July 2017. Exposures Residing in the United States. Main Outcomes and Measures Cardiovascular disease disability-adjusted life-years (DALYs). Results Between 1990 and 2016, age-standardized CVD DALYs for all states decreased. Several states had large rises in their relative rank ordering for total CVD DALYs among states, including Arkansas, Oklahoma, Alabama, Kentucky, Missouri, Indiana, Kansas, Alaska, and Iowa. The rate of decline varied widely across states, and CVD burden increased for a small number of states in the most recent years. Cardiovascular disease DALYs remained twice as large among men compared with women. Ischemic heart disease was the leading cause of CVD DALYs in all states, but the second most common varied by state. Trends were driven by 12 groups of risk factors, with the largest attributable CVD burden due to dietary risk exposures followed by high systolic blood pressure, high body mass index, high total cholesterol level, high fasting plasma glucose level, tobacco smoking, and low levels of physical activity. Increases in risk-deleted CVD DALY rates between 2006 and 2016 in 16 states suggest additional unmeasured risks beyond these traditional factors. Conclusions and Relevance Large disparities in total burden of CVD persist between US states despite marked improvements in CVD burden. Differences in CVD burden are largely attributable to modifiable risk exposures.
261 citations
Authors
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Name | H-index | Papers | Citations |
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Rasmus Nielsen | 135 | 556 | 84898 |
Matthew Jones | 125 | 1161 | 96909 |
Fedor Ratnikov | 123 | 1104 | 67091 |
Kenneth J. Arrow | 113 | 411 | 111221 |
Wil M. P. van der Aalst | 108 | 725 | 42429 |
Peter Schmidt | 105 | 638 | 61822 |
Roel Aaij | 98 | 1071 | 44234 |
John W. Berry | 97 | 351 | 52470 |
Federico Alessio | 96 | 1054 | 42300 |
Denis Derkach | 96 | 1184 | 45772 |
Marco Adinolfi | 95 | 831 | 40777 |
Michael Alexander | 95 | 881 | 38749 |
Alexey Boldyrev | 94 | 439 | 32000 |
Shalom H. Schwartz | 94 | 220 | 67609 |
Richard Blundell | 93 | 487 | 61730 |