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Institution

University of California, Santa Cruz

EducationSanta Cruz, California, United States
About: University of California, Santa Cruz is a education organization based out in Santa Cruz, California, United States. It is known for research contribution in the topics: Galaxy & Population. The organization has 15541 authors who have published 44120 publications receiving 2759983 citations. The organization is also known as: UCSC & UC, Santa Cruz.
Topics: Galaxy, Population, Stars, Redshift, Star formation


Papers
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Journal ArticleDOI
TL;DR: The knowledge of mammary gland development and mammary stem cell biology has significantly contributed to the understanding of breast cancer and has advanced the discovery of therapies to treat this disease.
Abstract: The mammary gland develops through several distinct stages. The first transpires in the embryo as the ectoderm forms a mammary line that resolves into placodes. Regulated by epithelial–mesenchymal interactions, the placodes descend into the underlying mesenchyme and produce the rudimentary ductal structure of the gland present at birth. Subsequent stages of development—pubertal growth, pregnancy, lactation, and involution—occur postnatally under the regulation of hormones. Puberty initiates branching morphogenesis, which requires growth hormone (GH) and estrogen, as well as insulin-like growth factor 1 (IGF1), to create a ductal tree that fills the fat pad. Upon pregnancy, the combined actions of progesterone and prolactin generate alveoli, which secrete milk during lactation. Lack of demand for milk at weaning initiates the process of involution whereby the gland is remodeled back to its prepregnancy state. These processes require numerous signaling pathways that have distinct regulatory functions at different stages of gland development. Signaling pathways also regulate a specialized subpopulation of mammary stem cells that fuel the dramatic changes in the gland occurring with each pregnancy. Our knowledge of mammary gland development and mammary stem cell biology has significantly contributed to our understanding of breast cancer and has advanced the discovery of therapies to treat this disease.

577 citations

Journal ArticleDOI
TL;DR: In this paper, the authors explore nucleosynthesis in the dynamic ejecta of compact binary mergers and compare the results with those from two simulations of a neutron star black hole merger.
Abstract: In this study we explore nucleosynthesis in the dynamic ejecta of compact binary mergers. We are particularly interested in the question how sensitive the resulting abundance patterns are to the parameters of the merging system. Therefore, we systematically investigate combinations of neutron star masses in the range from 1.0 to 2.0 M? and, for completeness, we compare the results with those from two simulations of a neutron star black hole merger. The ejecta masses vary by a factor of 5 for the studied systems, but all amounts are (within the uncertainties of the merger rates) compatible with being a major source of the cosmic r-process. The ejecta undergo robust r-process nucleosynthesis which produces all the elements from the second to the third peak in close-to-solar ratios. Most strikingly, this r-process is extremely robust, and all 23 investigated binary systems yield practically identical abundance patterns. This is mainly the result of the ejecta being extremely neutron rich (Ye similar to 0.04) and the r-process path meandering along the neutron drip line so that the abundances are determined entirely by nuclear rather than astrophysical properties. While further questions related to galactic chemical evolution need to be explored in future studies, we consider this robustness together with the ease with which both the second and third peak are reproduced as strong indications that compact binary mergers are prime candidates for the sources of the observed unique heavy r-process component.

577 citations

Journal ArticleDOI
TL;DR: A practical and accessible framework is presented to understand some of the basic underpinnings of algorithms in wide use such as block-matching and three-dimensional filtering (BM3D), and methods for their iterative improvement (or nonexistence thereof) are discussed.
Abstract: In this article, the author presents a practical and accessible framework to understand some of the basic underpinnings of these methods, with the intention of leading the reader to a broad understanding of how they interrelate. The author also illustrates connections between these techniques and more classical (empirical) Bayesian approaches. The proposed framework is used to arrive at new insights and methods, both practical and theoretical. In particular, several novel optimality properties of algorithms in wide use such as block-matching and three-dimensional (3-D) filtering (BM3D), and methods for their iterative improvement (or nonexistence thereof) are discussed. A general approach is laid out to enable the performance analysis and subsequent improvement of many existing filtering algorithms. While much of the material discussed is applicable to the wider class of linear degradation models beyond noise (e.g., blur,) to keep matters focused, we consider the problem of denoising here.

576 citations

Journal ArticleDOI
TL;DR: The authors examines some recent analyses of alternative agro-food networks (AAFNs) and claims that these innovative modes of food provisioning are emblematic of a new rural development paradigm in Western Europe.
Abstract: This paper examines some recent analyses of alternative agro-food networks (AAFNs) and claims that these innovative modes of food provisioning are emblematic of a new rural development paradigm in Western Europe. A political-economic critique of the territorialised, farm-centric value added strategies underlying these claims suggests that this characterisation is overdrawn and premature. The neglect of the consumption side of the rural development equation also argues for a more modest assessment of AAFNs and their paradigmatic potential.

576 citations

Journal ArticleDOI
TL;DR: This paper presented a sample of 340 planetary systems that contain 851 planets that are validated to substantially better than the 99% confidence level; the vast majority of these have not been previously verified as planets.
Abstract: The Kepler mission has discovered more than 2500 exoplanet candidates in the first two years of spacecraft data, with approximately 40% of those in candidate multi-planet systems. The high rate of multiplicity combined with the low rate of identified false positives indicates that the multiplanet systems contain very few false positive signals due to other systems not gravitationally bound to the target star. False positives in the multi-planet systems are identified and removed, leaving behind a residual population of candidate multi-planet transiting systems expected to have a false positive rate less than 1%. We present a sample of 340 planetary systems that contain 851 planets that are validated to substantially better than the 99% confidence level; the vast majority of these have not been previously verified as planets. We expect ~two unidentified false positives making our sample of planet very reliable. We present fundamental planetary properties of our sample based on a comprehensive analysis of Kepler light curves, ground-based spectroscopy, and high-resolution imaging. Since we do not require spectroscopy or high-resolution imaging for validation, some of our derived parameters for a planetary system may be systematically incorrect due to dilution from light due to additional stars in the photometric aperture. Nonetheless, our result nearly doubles the number verified exoplanets.

576 citations


Authors

Showing all 15733 results

NameH-indexPapersCitations
David J. Schlegel193600193972
David R. Williams1782034138789
John R. Yates1771036129029
David Haussler172488224960
Evan E. Eichler170567150409
Anton M. Koekemoer1681127106796
Mark Gerstein168751149578
Alexander S. Szalay166936145745
Charles M. Lieber165521132811
Jorge E. Cortes1632784124154
M. Razzano155515106357
Lars Hernquist14859888554
Aaron Dominguez1471968113224
Taeghwan Hyeon13956375814
Garth D. Illingworth13750561793
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202351
2022328
20212,157
20202,353
20192,209
20182,157