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Institution

University of Massachusetts Amherst

EducationAmherst Center, Massachusetts, United States
About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.


Papers
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Journal ArticleDOI
08 Jan 1999-Cell
TL;DR: Luciferase reporter gene assays indicate that the transcriptional machinery of the core clockwork directly regulates a clock-controlled output rhythm.

897 citations

Journal ArticleDOI
TL;DR: Consumption of vegetables and fish contaminated with the heavy metals Cu, Zn, Pb, Cd, Hg, and Cr is the most likely route for human exposure in Tianjin, China and health risks associated with these heavy metals were assessed.

896 citations

Journal ArticleDOI
TL;DR: This article showed clinically and statistically significant improvements in subjective and objective symptoms of anxiety and panic following an 8-week outpatient physician-referred group stress reduction intervention based on mindfulness meditation for 22 patients with DSM-III-R-defined anxiety disorders.

895 citations

Proceedings ArticleDOI
17 Jun 2007
TL;DR: This paper has constructed a large number of stereo datasets with ground-truth disparities, and a subset of these datasets are used to learn the parameters of conditional random fields (CRFs) and presents experimental results illustrating the potential of this approach for automatically learning the Parameters of models with richer structure than standard hand-tuned MRF models.
Abstract: State-of-the-art stereo vision algorithms utilize color changes as important cues for object boundaries. Most methods impose heuristic restrictions or priors on disparities, for example by modulating local smoothness costs with intensity gradients. In this paper we seek to replace such heuristics with explicit probabilistic models of disparities and intensities learned from real images. We have constructed a large number of stereo datasets with ground-truth disparities, and we use a subset of these datasets to learn the parameters of conditional random fields (CRFs). We present experimental results illustrating the potential of our approach for automatically learning the parameters of models with richer structure than standard hand-tuned MRF models.

893 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyse the structural flaws in the financial system that helped bring on the current crisis and discuss the prospects for financial reform and discuss possible solutions to these flaws.
Abstract: We are in the midst of the worst financial crisis since the Great Depression. This crisis is the latest phase of the evolution of financial markets under the radical financial deregulation process that began in the late 1970s. This evolution has taken the form of cycles in which deregulation accompanied by rapid financial innovation stimulates powerful financial booms that end in crises. Governments respond to crises with bailouts that allow new expansions to begin. As a result, financial markets have become ever larger and financial crises have become more threatening to society, which forces governments to enact ever larger bailouts. This process culminated in the current global financial crisis, which is so deeply rooted that even unprecedented interventions by affected governments have, thus far, failed to contain it. In this paper we analyse the structural flaws in the financial system that helped bring on the current crisis and discuss prospects for financial reform.

893 citations


Authors

Showing all 37601 results

NameH-indexPapersCitations
George M. Whitesides2401739269833
Joan Massagué189408149951
David H. Weinberg183700171424
David L. Kaplan1771944146082
Michael I. Jordan1761016216204
James F. Sallis169825144836
Bradley T. Hyman169765136098
Anton M. Koekemoer1681127106796
Derek R. Lovley16858295315
Michel C. Nussenzweig16551687665
Alfred L. Goldberg15647488296
Donna Spiegelman15280485428
Susan E. Hankinson15178988297
Bernard Moss14783076991
Roger J. Davis147498103478
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023103
2022535
20213,983
20203,858
20193,712
20183,385