Institution
University of Luxembourg
Education•Luxembourg, Luxembourg•
About: University of Luxembourg is a education organization based out in Luxembourg, Luxembourg. It is known for research contribution in the topics: Population & European union. The organization has 4744 authors who have published 22175 publications receiving 381824 citations.
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TL;DR: Estimates the number of daily trips from publicly available data for 75 BSS case studies across the world and provides trips per bike per day scores as a comparison of performance and success reveal that a third of case studies have fewer than the psychologically important one trip per bicycle per day.
Abstract: Many municipalities assert bicycle sharing systems (BSS) as having many benefits, justifying their adoption, yet few explicitly state the purpose of their system making comparison or determination of success impossible. In addition, the apprehension of many BSS operators to share data further hinders comparison. This paper estimates the number of daily trips from publicly available data for 75 BSS case studies across the world and provides trips per bike per day scores as a comparison of performance and success. Results reveal that a third of case studies have fewer than the psychologically important one trip per bicycle per day. To ascertain what factors are associated with this metric we estimate models with independent variables related to system attributes, station density, weather, geography and transportation infrastructure. Our analysis provides strong evidence undermining the ‘network effect’ promoted by influential BSS policy makers that expanding system size increases performance. Finally our results describe and discuss causal variables associated with higher BSS performance.
145 citations
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COMSATS Institute of Information Technology1, North Dakota State University2, Chinese Academy of Sciences3, University of South Florida4, University of Sydney5, Wayne State University6, Argonne National Laboratory7, Pacific Northwest National Laboratory8, University of Luxembourg9, University of Louisville10, China University of Geosciences (Wuhan)11, Cisco Systems, Inc.12
TL;DR: In this study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported and the system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.
Abstract: Classification of high performance computing (HPC) systems is provided.Current HPC paradigms and industrial application suites are discussed.State of the art in HPC resource allocation is reported.Hardware and software solutions are discussed for optimized HPC systems. An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.
145 citations
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TL;DR: In this paper, the authors show that the band-tailing originates mainly from band-gap fluctuations attributable to chemical composition variations at nanoscale; while electrostatic fluctuations play a lesser role.
145 citations
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TL;DR: In this paper, a review of the geophysical questions that can be addressed by ground gravimeters used to monitor time-variable gravity is presented, in relation to the instrumental characteristics, noise sources, and good practices.
Abstract: In a context of global change and increasing anthropic pressure on the environment, monitoring the Earth system and its evolution has become one of the key missions of geosciences. Geodesy is the geoscience that measures the geometric shape of the Earth, its orientation in space, and gravity field. Time-variable gravity, because of its high accuracy, can be used to build an enhanced picture and understanding of the changing Earth. Ground-based gravimetry can determine the change in gravity related to the Earth rotation fluctuation, to celestial body and Earth attractions, to the mass in the direct vicinity of the instruments, and to vertical displacement of the instrument itself on the ground. In this paper, we review the geophysical questions that can be addressed by ground gravimeters used to monitor time-variable gravity. This is done in relation to the instrumental characteristics, noise sources, and good practices. We also discuss the next challenges to be met by ground gravimetry, the place that terrestrial gravimetry should hold in the Earth observation system, and perspectives and recommendations about the future of ground gravity instrumentation.
Plain Language Summary: In a context of global change and increased human vulnerability to terrestrial hazard, monitoring the Earth system is one of the key challenges of geoscience. In particular, terrestrial gravimetry, with its precision at the level of one part of a billion, allows the monitoring of many phenomena, from water resource availability to volcanic activity. This paper reviews the technique, its advantages and limitations, how it has been used in the Earth monitoring, and the next challenges to be met by ground gravimetry.
145 citations
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TL;DR: The analysis of gene expression in the human foetal heart reveals stage- and chamber-specific genes and provides a dataset that can be used for benchmarking human PSC-derived heart cells.
Abstract: Differentiated derivatives of human pluripotent stem cells (hPSCs) are often considered immature because they resemble foetal cells more than adult, with hPSC-derived cardiomyocytes (hPSC-CMs) being no exception. Many functional features of these cardiomyocytes, such as their cell morphology, electrophysiological characteristics, sarcomere organization and contraction force, are underdeveloped compared with adult cardiomyocytes. However, relatively little is known about how their gene expression profiles compare with the human foetal heart, in part because of the paucity of data on the human foetal heart at different stages of development. Here, we collected samples of matched ventricles and atria from human foetuses during the first and second trimester of development. This presented a rare opportunity to perform gene expression analysis on the individual chambers of the heart at various stages of development, allowing us to identify not only genes involved in the formation of the heart, but also specific genes upregulated in each of the four chambers and at different stages of development. The data showed that hPSC-CMs had a gene expression profile similar to first trimester foetal heart, but after culture in conditions shown previously to induce maturation, they cluster closer to the second trimester foetal heart samples. In summary, we demonstrate how the gene expression profiles of human foetal heart samples can be used for benchmarking hPSC-CMs and also contribute to determining their equivalent stage of development.
145 citations
Authors
Showing all 4893 results
Name | H-index | Papers | Citations |
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Jun Wang | 166 | 1093 | 141621 |
Leroy Hood | 158 | 853 | 128452 |
Andreas Heinz | 108 | 1078 | 45002 |
Philippe Dubois | 101 | 1098 | 48086 |
John W. Berry | 97 | 351 | 52470 |
Michael Müller | 91 | 333 | 26237 |
Bart Preneel | 82 | 844 | 25572 |
Bjorn Ottersten | 81 | 1058 | 28359 |
Sander Kersten | 79 | 246 | 23985 |
Alexandre Tkatchenko | 77 | 271 | 26863 |
Rudi Balling | 75 | 238 | 19529 |
Lionel C. Briand | 75 | 380 | 24519 |
Min Wang | 72 | 716 | 19197 |
Stephen H. Friend | 70 | 184 | 53422 |
Ekhard K. H. Salje | 70 | 581 | 19938 |