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Institution

University of California, Irvine

EducationIrvine, California, United States
About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.


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01 Jan 1987
TL;DR: Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human thought processes used to discover scientific laws.
Abstract: Scientific discovery is often regarded as romantic and creative -- and hence unanalyzable -- whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human thought processes used to discover scientific laws. The programs -- BACON, DALTON, GLAUBER, and STAHL -- are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along. Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science.

900 citations

Journal ArticleDOI
TL;DR: This work discovered and validated a set of ten lipids from peripheral blood that predicted phenoconversion to either amnestic mild cognitive impairment or Alzheimer's disease within a 2–3 year timeframe with over 90% accuracy and may be sensitive to early neurodegeneration of preclinical Alzheimer’s disease.
Abstract: Alzheimer's disease causes a progressive dementia that currently affects over 35 million individuals worldwide and is expected to affect 115 million by 2050 (ref. 1). There are no cures or disease-modifying therapies, and this may be due to our inability to detect the disease before it has progressed to produce evident memory loss and functional decline. Biomarkers of preclinical disease will be critical to the development of disease-modifying or even preventative therapies. Unfortunately, current biomarkers for early disease, including cerebrospinal fluid tau and amyloid-β levels, structural and functional magnetic resonance imaging and the recent use of brain amyloid imaging or inflammaging, are limited because they are either invasive, time-consuming or expensive. Blood-based biomarkers may be a more attractive option, but none can currently detect preclinical Alzheimer's disease with the required sensitivity and specificity. Herein, we describe our lipidomic approach to detecting preclinical Alzheimer's disease in a group of cognitively normal older adults. We discovered and validated a set of ten lipids from peripheral blood that predicted phenoconversion to either amnestic mild cognitive impairment or Alzheimer's disease within a 2-3 year timeframe with over 90% accuracy. This biomarker panel, reflecting cell membrane integrity, may be sensitive to early neurodegeneration of preclinical Alzheimer's disease.

899 citations

Journal ArticleDOI
21 Mar 2008-Science
TL;DR: In this paper, the authors used high-resolution (1.5-millimeter isotropic voxels) functional magnetic resonance imaging to measure brain activity during incidental memory encoding.
Abstract: Pattern separation, the process of transforming similar representations or memories into highly dissimilar, nonoverlapping representations, is a key component of many functions ascribed to the hippocampus. Computational models have stressed the role of the hippocampus and, in particular, the dentate gyrus and its projections into the CA3 subregion in pattern separation. We used high-resolution (1.5-millimeter isotropic voxels) functional magnetic resonance imaging to measure brain activity during incidental memory encoding. Although activity consistent with a bias toward pattern completion was observed in CA1, the subiculum, and the entorhinal and parahippocampal cortices, activity consistent with a strong bias toward pattern separation was observed in, and limited to, the CA3/dentate gyrus. These results provide compelling evidence of a key role of the human CA3/dentate gyrus in pattern separation.

899 citations

Journal ArticleDOI
TL;DR: The phasor approach has the potential to simplify the way data are analyzed in FLIM, paving the way for the analysis of large data sets and, in general, making the FLIM technique accessible to the nonexpert in spectroscopy and data analysis.

898 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a complete description of the CHOOZ experiment, including the source and detector, the calibration methods and stability checks, the event reconstruction procedures and the Monte Carlo simulation.
Abstract: This final article about the CHOOZ experiment presents a complete description of the $\bar{ u}_e$ source and detector, the calibration methods and stability checks, the event reconstruction procedures and the Monte Carlo simulation. The data analysis, systematic effects and the methods used to reach our conclusions are fully discussed. Some new remarks are presented on the deduction of the confidence limits and on the correct treatment of systematic errors.

898 citations


Authors

Showing all 47751 results

NameH-indexPapersCitations
Daniel Levy212933194778
Rob Knight2011061253207
Lewis C. Cantley196748169037
Dennis W. Dickson1911243148488
Terrie E. Moffitt182594150609
Joseph Biederman1791012117440
John R. Yates1771036129029
John A. Rogers1771341127390
Avshalom Caspi170524113583
Yang Gao1682047146301
Carl W. Cotman165809105323
John H. Seinfeld165921114911
Gregg C. Fonarow1611676126516
Jerome I. Rotter1561071116296
David Cella1561258106402
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20242
2023252
20221,224
20216,519
20206,348
20195,610