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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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Book
01 Jul 1978
TL;DR: This volume intended to serve as a text for upper undergraduate and graduate level students and special emphasis is given to the role of algebraic techniques in formal language theory through a chapter devoted to the fixed point approach to the analysis of context-free languages.
Abstract: From the Publisher: Formal language theory was fist developed in the mid 1950's in an attempt to develop theories of natural language acquisition. It was soon realized that this theory (particularly the context-free portion) was quite relevant to the artificial languages that had originated in computer science. Since those days, the theory of formal languages has been developed extensively, and has several discernible trends, which include applications to the syntactic analysis of programming languages, program schemes, models of biological systems, and relationships with natural languages.

1,415 citations

Journal ArticleDOI
TL;DR: In this paper, a weak solution of the nonlinear PDE is proposed, which asserts each level set evolves in time according to its mean curvature, existing for all time.
Abstract: We construct a unique weak solution of the nonlinear PDE which asserts each level set evolves in time according to its mean curvature. This weak solution allows us then to define for any compact set ⌈0 a unique generalized motion by mean curvature, existing for all time. We investigate the various geometric properties and pathologies of this evolution.

1,415 citations

Book ChapterDOI
TL;DR: In this article, the authors examined the relation between two or more actions that were assumed to reflect the same underlying disposition, and provided little evidence to support the postulated existence of stable, underlying attitudes within the individual, which influence both verbal expressions and actions.
Abstract: Publisher Summary In the domain of personality psychology, the trait concept has carried the burden of dispositional explanation. A multitude of personality traits has been identified and new trait dimensions continue to join the growing list. In a similar fashion, the concept of attitude has been the focus of attention in the explanations of human behavior offered by social psychologists. Numerous attitudes have been assessed over the years and, as new social issues emerge, additional attitudinal domains are explored. The chapter provides little evidence to support the postulated existence of stable, underlying attitudes within the individual, which influence both verbal expressions and actions. It examines the relation between two or more actions that were assumed to reflect the same underlying disposition. The aggregation of responses across time, contexts, targets, or actions or across a combination of these elements permits the inferences of dispositions at varying levels of generality.

1,411 citations

Journal ArticleDOI
TL;DR: This Review provides an introduction to nanoparticle–biomolecular interactions as well as recent applications of nanoparticles in biological sensing, delivery, and imaging of live cells and tissues.
Abstract: The wide variety of core materials available, coupled with tunable surface properties, make nanoparticles an excellent platform for a broad range of biological and biomedical applications. This Review provides an introduction to nanoparticle–biomolecular interactions as well as recent applications of nanoparticles in biological sensing, delivery, and imaging of live cells and tissues.

1,399 citations

Journal ArticleDOI
TL;DR: This amended and improved digestion method (INFOGEST 2.0) avoids challenges associated with the original method, such as the inclusion of the oral phase and the use of gastric lipase.
Abstract: Developing a mechanistic understanding of the impact of food structure and composition on human health has increasingly involved simulating digestion in the upper gastrointestinal tract. These simulations have used a wide range of different conditions that often have very little physiological relevance, and this impedes the meaningful comparison of results. The standardized protocol presented here is based on an international consensus developed by the COST INFOGEST network. The method is designed to be used with standard laboratory equipment and requires limited experience to encourage a wide range of researchers to adopt it. It is a static digestion method that uses constant ratios of meal to digestive fluids and a constant pH for each step of digestion. This makes the method simple to use but not suitable for simulating digestion kinetics. Using this method, food samples are subjected to sequential oral, gastric and intestinal digestion while parameters such as electrolytes, enzymes, bile, dilution, pH and time of digestion are based on available physiological data. This amended and improved digestion method (INFOGEST 2.0) avoids challenges associated with the original method, such as the inclusion of the oral phase and the use of gastric lipase. The method can be used to assess the endpoints resulting from digestion of foods by analyzing the digestion products (e.g., peptides/amino acids, fatty acids, simple sugars) and evaluating the release of micronutrients from the food matrix. The whole protocol can be completed in ~7 d, including ~5 d required for the determination of enzyme activities.

1,394 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