Publications by authors named "D C Jones"

The long-term stability of Pt-based catalysts is critical to the reliability of proton exchange membrane fuel cells (PEMFCs), and receives constant attention. However, the current knowledge of Pt oxidation is restricted to unrealistic PEMFC cathode environment or operation, which questions its practical relevance. Herein, Pt oxidation is investigated directly in a PEMFC with stroboscopic operando high energy X-ray scattering.

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Background: The Report and Placement Integrated Data System (RAPIDS) integrates two U.S. national data systems-NCANDS' child maltreatment report (CMR) records and AFCARS' foster care (FC) records-into a single longitudinal dataset spanning 2006-2021.

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The rate at which transcription factors (TFs) bind their cognate sites has long been assumed to be limited by diffusion, and thus independent of binding site sequence. Here, we systematically test this assumption using cell-to-cell variability in gene expression as a window into the in vivo association and dissociation kinetics of the model transcription factor LacI. Using a stochastic model of the relationship between gene expression variability and binding kinetics, we performed single-cell gene expression measurements to infer association and dissociation rates for a set of 35 different LacI binding sites.

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Consolidation of independent hospitals and physician practices into integrated health systems has reshaped the delivery of health care. While the literature suggests that provider consolidation raises prices, few studies have examined the interplay of health systems and insurers in relation to prices. Using negotiated price data that commercial insurers recently released under the Transparency in Coverage Final Rule, we examined the association between hospital concentration under health systems and prices for outpatient procedures in local health care markets with different levels of insurer concentration.

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Nerve conduction F-wave studies contain critical information about subclinical motor dysfunction which may be used to diagnose patients with amyotrophic lateral sclerosis (ALS). However, F-wave responses are highly variable in morphology, making waveform interpretation challenging. Artificial Intelligence techniques can extract time-frequency features to provide new insights into ALS diagnosis and prognosis.

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