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Institution

San Diego State University

EducationSan Diego, California, United States
About: San Diego State University is a education organization based out in San Diego, California, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 12418 authors who have published 27950 publications receiving 1192375 citations. The organization is also known as: SDSU & San Diego State College.


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Journal ArticleDOI
TL;DR: In this paper, a four-plate compact capacitive coupler and its circuit model for large air gap distance capacitive power transfer (CPT) is presented, where two plates that are on the same side are placed close to each other to maintain a large coupling capacitance, and they are of different sizes to maintain the coupling between the primary and secondary sides.
Abstract: This paper proposes a four-plate compact capacitive coupler and its circuit model for large air-gap distance capacitive power transfer (CPT). The four plates are arranged vertically, instead of horizontally, to save space in the electric vehicle charging application. The two plates that are on the same side are placed close to each other to maintain a large coupling capacitance, and they are of different sizes to maintain the coupling between the primary and secondary sides. The circuit model of the coupler is presented, considering all six coupling capacitors. The LCL compensation topology is used to resonate with the coupler and provide high voltage on the plates to transfer high power. The circuit model of the coupler is simplified to design the parameters of the compensation circuit. Finite-element analysis is employed to simulate the coupling capacitance and design the dimensions of the coupler. The circuit performance is simulated in LTspice to design the specific parameter values. A prototype of the CPT system was designed and constructed with the proposed vertical plate structure. The prototype achieved an efficiency of 85.87% at 1.88-kW output power with a 150-mm air-gap distance.

269 citations

Journal ArticleDOI
TL;DR: In this paper, an improved method for determining the mass of neutron stars in eclipsing X-ray pulsar binaries is presented, based on the assumption that the companion star is spherical with an effective Roche lobe radius.
Abstract: We present an improved method for determining the mass of neutron stars in eclipsing X-ray pulsar binaries and apply the method to six systems, namely, Vela X-1, 4U 1538-52, SMC X-1, LMC X-4, Cen X-3, and Her X-1. In previous studies to determine neutron star mass, the X-ray eclipse duration has been approximated analytically by assuming that the companion star is spherical with an effective Roche lobe radius. We use a numerical code based on Roche geometry with various optimizers to analyze the published data for these systems, which we supplement with new spectroscopic and photometric data for 4U 1538-52. This allows us to model the eclipse duration more accurately and thus calculate an improved value for the neutron star mass. The derived neutron star mass also depends on the assumed Roche lobe filling factor β of the companion star, where β = 1 indicates a completely filled Roche lobe. In previous work a range of β between 0.9 and 1.0 was usually adopted. We use optical ellipsoidal light-curve data to constrain β. We find neutron star masses of 1.77 ± 0.08 M ☉ for Vela X-1, 0.87 ± 0.07 M ☉ for 4U 1538-52 (eccentric orbit), 1.00 ± 0.10 M ☉ for 4U 1538-52 (circular orbit), 1.04 ± 0.09 M ☉ for SMC X-1, 1.29 ± 0.05 M ☉ for LMC X-4, 1.49 ± 0.08 M ☉ for Cen X-3, and 1.07 ± 0.36 M ☉ for Her X-1. We discuss the limits of the approximations that were used to derive the earlier mass determinations, and we comment on the implications our new masses have for observationally refining the upper and lower bounds of the neutron star mass distribution.

269 citations

Journal ArticleDOI
TL;DR: This study aimed to compare prevalence rates of anxiety disorder and depressive disorder in national samples in the U.S. before and during the coronavirus disease 2019 pandemic.
Abstract: Background The disruptions to daily life caused by the coronavirus disease 2019 (COVID-19) pandemic may have impacted mental health, particularly mood disorders. This study aimed to compare prevalence rates of anxiety disorder and depressive disorder in national samples in the U.S. before and during the pandemic. Methods Participants (n = 336,525) were from U.S. Census Bureau-administered nationally representative probability samples, one from the first half of 2019 and four during the pandemic in April and May 2020. All participants completed the Patient Health Questionnaire-2 screening for depressive disorder and the Generalized Anxiety Disorder-2 screening for anxiety disorders. Results Compared to U.S. adults in 2019, U.S. adults in April and May 2020 were more than three times as likely to screen positive for depressive disorders, anxiety disorders, or one or both, with more than one out of three screening positive for one or both. The prevalence of anxiety decreased slightly between the April 23-May 4, 2020 and the May 21-26, 2020 administrations, while the prevalence of depression increased slightly. Conclusions U.S. adults in 2020 are considerably more likely to screen positive for mood disorders than in 2019, with anxiety declining and depression increasing from April to May.

269 citations

Journal ArticleDOI
TL;DR: Bayes factor delimitation of species showed improved performance when species limits are tested by reassigning individuals between species, as opposed to either lumping or splitting lineages, and marginal-likelihood estimates via PS or SS analyses provide a useful and complementary alternative to existing species delimitation methods.
Abstract: Current molecular methods of species delimitation are limited by the types of species delimitation models and scenarios that can be tested. Bayes factors allow for more flexibility in testing non-nested species delimitation models and hypotheses of individual assignment to alternative lineages. Here, we examined the efficacy of Bayes factors in delimiting species through simulations and empirical data from the Sceloporus scalaris species group. Marginal-likelihood scores of competing species delimitation models, from which Bayes factor values were compared, were estimated with four different methods: harmonic mean estimation (HME), smoothed harmonic mean estimation (sHME), path-sampling/thermodynamic integration (PS), and stepping-stone (SS) analysis. We also performed model selection using a posterior simulation-based analog of the Akaike information criterion through Markov chain Monte Carlo analysis (AICM). Bayes factor species delimitation results from the empirical data were then compared with results from the reversible-jump MCMC (rjMCMC) coalescent-based species delimitation method Bayesian Phylogenetics and Phylogeography (BPP *BEAST; BPP incomplete lineage sorting; marginal-likelihood estimation; Mexico; model choice.)

268 citations

Journal ArticleDOI
TL;DR: In this article, the importance of decision specific experience for a multinational firm's foreign ownership structure and establishment mode decisions is examined, and a unique procedure to measure the decision-specific experience construct is developed.
Abstract: In this paper, we examine the importance of decision specific experience for a multinational firm's foreign ownership structure and establishment mode decisions. A unique procedure to measure the decision specific experience construct is developed. Based on data for the period 1969–1991, we find strong empirical evidence from experiences of Japanese firms to support the hypotheses that firms tend to select ownership structures and establishment modes based on their experiences with similar ownership structures and establishment modes in the past.

268 citations


Authors

Showing all 12533 results

NameH-indexPapersCitations
David R. Williams1782034138789
James F. Sallis169825144836
Steven Williams144137586712
Larry R. Squire14347285306
Murray B. Stein12874589513
Robert Edwards12177574552
Roberto Kolter12031552942
Jack E. Dixon11540847201
Sonia Ancoli-Israel11552046045
John D. Lambris11465148203
Igor Grant11379155147
Kenneth H. Nealson10848351100
Mark Westoby10831659095
Eric Courchesne10724041200
Marc A. Schuckit10664343484
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202345
2022168
20211,595
20201,535
20191,454
20181,262