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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
TL;DR: In this article, the results of a study in which natural microbial biological processes were used to engineer a cemented soil matrix within initially loose, collapsible sand were presented, using the microorganism Bacillus pasteurii, an aerobic bacterium pervasive in natural soil deposits.
Abstract: Current methods to improve the engineering properties of sands are diverse with respect to methodology, treatment uniformity, cost, environmental impact, site accessibility requirements, etc. All of these methods have benefits and drawbacks, and there continues to be a need to explore new possibilities of soil improvement, particularly as suitable land for development becomes more scarce. This paper presents the results of a study in which natural microbial biological processes were used to engineer a cemented soil matrix within initially loose, collapsible sand. Microbially induced calcite precipitation (MICP) was achieved using the microorganism Bacillus pasteurii, an aerobic bacterium pervasive in natural soil deposits. The microbes were introduced to the sand specimens in a liquid growth medium amended with urea and a dissolved calcium source. Subsequent cementation treatments were passed through the specimen to increase the cementation level of the sand particle matrix. The results of both MICP- and ...

1,149 citations

Proceedings ArticleDOI
06 Aug 2006
TL;DR: This paper proposes an LDA-based document model within the language modeling framework, and evaluates it on several TREC collections, and shows that improvements over retrieval using cluster-based models can be obtained with reasonable efficiency.
Abstract: Search algorithms incorporating some form of topic model have a long history in information retrieval. For example, cluster-based retrieval has been studied since the 60s and has recently produced good results in the language model framework. An approach to building topic models based on a formal generative model of documents, Latent Dirichlet Allocation (LDA), is heavily cited in the machine learning literature, but its feasibility and effectiveness in information retrieval is mostly unknown. In this paper, we study how to efficiently use LDA to improve ad-hoc retrieval. We propose an LDA-based document model within the language modeling framework, and evaluate it on several TREC collections. Gibbs sampling is employed to conduct approximate inference in LDA and the computational complexity is analyzed. We show that improvements over retrieval using cluster-based models can be obtained with reasonable efficiency.

1,148 citations

Journal ArticleDOI
24 Apr 1999-Langmuir
TL;DR: In this article, the preparation of ultrahydrophobic and ultralyophobic surfaces using several techniques is described, and the authors emphasize that contact angle hysteresis is more important in characterizing lyophobicity than is the maximum achievable contact angle.
Abstract: The preparation of ultrahydrophobic and ultralyophobic surfaces using several techniques is described. Plasma polymerization of 2,2,3,3,4,4,4-heptafluorobutyl acrylate on poly(ethylene terephthalate) yields surfaces with water contact angles of θA/θR = 174°/173°. Argon plasma etching of polypropylene in the presence of poly(tetrafluoroethylene) renders surfaces with water contact angles as high as θA/θR = 172°/169°. Surfaces of compressed pellets of submicrometer, variable-diameter spherical particles of PTFE oligomers exhibit water contact angles of θA/θR = 177°/177°, methylene iodide contact angles of θA/θR = 140°/138°, and hexadecane contact angles of θA/θR = 140°/125°. We emphasize that contact angle hysteresis is more important in characterizing lyophobicity than is the maximum achievable contact angle. These surfaces are rough at the micrometer and submicrometer scales, and water drops roll easily on all of them. We make an intuitive argument that the topology of the roughness is important and contr...

1,147 citations

Journal ArticleDOI
TL;DR: In this article, the authors identify the drivers of agility and discuss the portfolio of competitive advantages that have emerged over time as a result of the changing requirements of manufacturing, and highlight some of the key enablers of agility.

1,146 citations

Journal ArticleDOI
24 Apr 2009-Science
TL;DR: To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage and provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.
Abstract: To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.

1,144 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
2022536
20213,983
20203,858
20193,712
20183,385