Institution
Michigan State University
Education•East Lansing, Michigan, United States•
About: Michigan State University is a education organization based out in East Lansing, Michigan, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 60109 authors who have published 137074 publications receiving 5633022 citations. The organization is also known as: MSU & Michigan State.
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TL;DR: This review explains the conventional BP measurement methods and their limitations; presents models to summarize the theory of the PTT-BP relationship; outlines the approach while pinpointing the key challenges; and discusses realistic expectations for the approach.
Abstract: Ubiquitous blood pressure (BP) monitoring is needed to improve hypertension detection and control and is becoming feasible due to recent technological advances such as in wearable sensing. Pulse transit time (PTT) represents a well-known potential approach for ubiquitous BP monitoring. The goal of this review is to facilitate the achievement of reliable ubiquitous BP monitoring via PTT. We explain the conventional BP measurement methods and their limitations; present models to summarize the theory of the PTT-BP relationship; outline the approach while pinpointing the key challenges; overview the previous work toward putting the theory to practice; make suggestions for best practice and future research; and discuss realistic expectations for the approach.
648 citations
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University of Pittsburgh1, University of Colorado Denver2, University of Michigan3, University of Washington4, Veterans Health Administration5, University of California, San Francisco6, George Washington University7, University of California, Los Angeles8, Washington University in St. Louis9, Indiana University10, Michigan State University11
TL;DR: This study is the largest to examine composition of the lower respiratory tract microbiome in healthy individuals and the first to use the neutral model to compare the lung to the mouth, demonstrating that the lung microbiome does not derive entirely from the mouth.
Abstract: Rationale: Results from 16S rDNA-encoding gene sequence–based, culture-independent techniques have led to conflicting conclusions about the composition of the lower respiratory tract microbiome. Objectives: To compare the microbiome of the upper and lower respiratory tract in healthy HIV-uninfected nonsmokers and smokers in a multicenter cohort. Methods: Participants were nonsmokers and smokers without significantcomorbidities.Oralwashesandbronchoscopicalveolarlavages were collected in a standardized manner. Sequence analysis of bacterial 16S rRNA-encoding genes was performed, and the neutral modelincommunityecologywasusedtoidentifybacteriathatwere the most plausible members of a lung microbiome. Measurements and Main Results: Sixty-four participants were enrolled. Mostbacteriaidentifiedinthelungwerealsointhemouth,butspecific bacteria such as Enterobacteriaceae, Haemophilus, Methylobacterium, and Ralstonia species were disproportionally represented in the lungs compared with values predicted by the neutral model. Tropheryma was
648 citations
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TL;DR: In this paper, the authors empirically examined the impact of partner characteristics on the performance of alliances and found that complementarity in partner resources and compatibility in cultural and operational norms have different direct and indirect effects on alliance performance.
Abstract: Value creation through alliances requires the simultaneous pursuit of partners with similar characteristics on certain dimensions and different characteristics on other dimensions. Partnering firms need to have different resource and capability profiles yet share similarities in their social institutions. In this article, the authors empirically examine the impact of partner characteristics on the performance of alliances. In particular, they test hypotheses related to both direct impact of partner characteristics on alliance performance and indirect effects through relational capital aspects of the alliance. Empirical results based on a sample of alliances in the global construction contracting industry suggest that complementarity in partner resources and compatibility in cultural and operational norms have different direct and indirect effects on alliance performance. Accordingly, organizational routines aimed at partner selection need to be complemented by relationship management routines to maximize the potential benefits from an alliance.
647 citations
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23 Dec 2011TL;DR: In this article, the traditional diffusion model was extended to the vector fractional diffusion model, which is the state-of-the-art diffusion model for the problem of diffusion.
Abstract: Preface 1 Introduction 1.1 The traditional diffusion model 1.2 Fractional diffusion 2 Fractional Derivatives 2.1 The Grunwald formula 2.2 More fractional derivatives 2.3 The Caputo derivative 2.4 Time-fractional diffusion 3 Stable Limit Distributions 3.1 Infinitely divisible laws 3.2 Stable characteristic functions 3.3 Semigroups 3.4 Poisson approximation 3.5 Shifted Poisson approximation 3.6 Triangular arrays 3.7 One-sided stable limits 3.8 Two-sided stable limits 4 Continuous Time Random Walks 4.1 Regular variation 4.2 Stable Central Limit Theorem 4.3 Continuous time random walks 4.4 Convergence in Skorokhod space 4.5 CTRW governing equations 5 Computations in R 5.1 R codes for fractional diffusion 5.2 Sample path simulations 6 Vector Fractional Diffusion 6.1 Vector random walks 6.2 Vector random walks with heavy tails 6.3 Triangular arrays of random vectors 6.4 Stable random vectors 6.5 Vector fractional diffusion equation 6.6 Operator stable laws 6.7 Operator regular variation 6.8 Generalized domains of attraction 7 Applications and Extensions 7.1 LePage Series Representation 7.2 Tempered stable laws 7.3 Tempered fractional derivatives 7.4 Pearson Diffusion 7.5 Classification of Pearson diffusions 7.6 Spectral representations of the solutions of Kolmogorov equations 7.7 Fractional Brownian motion 7.8 Fractional random fields 7.9 Applications of fractional diffusion 7.10 Applications of vector fractional diffusion Bibliography Index
647 citations
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TL;DR: The generation of transgenic soybean lines with high oleic acid content represents one way in which plant biotechnology has already contributed to the improvement of biodiesel.
Abstract: Triacylglycerols produced by plants are one of the most energy-rich and abundant forms of reduced carbon available from nature. Given their chemical similarities, plant oils represent a logical substitute for conventional diesel, a non-renewable energy source. However, as plant oils are too viscous for use in modern diesel engines, they are converted to fatty acid esters. The resulting fuel is commonly referred to as biodiesel, and offers many advantages over conventional diesel. Chief among these is that biodiesel is derived from renewable sources. In addition, the production and subsequent consumption of biodiesel results in less greenhouse gas emission compared to conventional diesel. However, the widespread adoption of biodiesel faces a number of challenges. The biggest of these is a limited supply of biodiesel feedstocks. Thus, plant oil production needs to be greatly increased for biodiesel to replace a major proportion of the current and future fuel needs of the world. An increased understanding of how plants synthesize fatty acids and triacylglycerols will ultimately allow the development of novel energy crops. For example, knowledge of the regulation of oil synthesis has suggested ways to produce triacylglycerols in abundant non-seed tissues. Additionally, biodiesel has poor cold-temperature performance and low oxidative stability. Improving the fuel characteristics of biodiesel can be achieved by altering the fatty acid composition. In this regard, the generation of transgenic soybean lines with high oleic acid content represents one way in which plant biotechnology has already contributed to the improvement of biodiesel.
646 citations
Authors
Showing all 60636 results
Name | H-index | Papers | Citations |
---|---|---|---|
David Miller | 203 | 2573 | 204840 |
Anil K. Jain | 183 | 1016 | 192151 |
D. M. Strom | 176 | 3167 | 194314 |
Feng Zhang | 172 | 1278 | 181865 |
Derek R. Lovley | 168 | 582 | 95315 |
Donald G. Truhlar | 165 | 1518 | 157965 |
Donald E. Ingber | 164 | 610 | 100682 |
J. E. Brau | 162 | 1949 | 157675 |
Murray F. Brennan | 161 | 925 | 97087 |
Peter B. Reich | 159 | 790 | 110377 |
Wei Li | 158 | 1855 | 124748 |
Timothy C. Beers | 156 | 934 | 102581 |
Claude Bouchard | 153 | 1076 | 115307 |
Mercouri G. Kanatzidis | 152 | 1854 | 113022 |
James J. Collins | 151 | 669 | 89476 |