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We correct one typographical error of three equations in Appl. Opt.56, 1447 (2017)APOPAI0003-693510.1364/AO.56.001447.
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http://dx.doi.org/10.1364/AO.57.007942 | DOI Listing |
J Chem Phys
September 2025
Department of Chemistry, McGill University, Montreal, Quebec H3A 0G4, Canada.
Semiconductor quantum dots (QDs) are well known to give rise to a quantum confined structure of excitons. Because of this quantum confinement, new physics of hot exciton relaxation dynamics arises. Decades of work using transient absorption (TA) spectroscopy have yielded initial simple observations, such as estimates of the cooling rate from single pump photon energy experiments.
View Article and Find Full Text PDFInfect Drug Resist
September 2025
Department of Nephrology, Children's Hospital of Fudan University, Shanghai, People's Republic of China.
Purpose: To analyze the distribution of pathogens and drug resistance in children with urinary tract infections (UTIs) in a single center in Xiamen and to guide the selection of empirical antibiotics in the clinic.
Methods: Clinical data of 2001 children with UTIs in Xiamen Children's Hospital between 2014 and 2022 were retrospectively analyzed, grouped by age and comorbidities. Differences in pathogen distribution and drug sensitivity were compared with the chi-square test applied and significance set at p < 0.
J Biomech Eng
September 2025
Department of Biomedical Engineering, Schulich School of engineering, University of Calgary, AB, Canada; Cumming School of Medicine, University of Calgary, AB, Canada.
Using a powered simple walking model (point mass with rigid massless legs), the optimal analytical push-off was derived based on walking speed and step elevation changes. It was observed that higher speeds increased the available push-off to attain greater step-up e.g.
View Article and Find Full Text PDFPLoS Comput Biol
September 2025
Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America.
Real-world decision-making often involves navigating large action spaces with state-dependent action values, taxing the limited cognitive resources at our disposal. While previous studies have explored cognitive constraints on generating action consideration sets or refining state-action mappings (policy complexity), their interplay remains underexplored. In this work, we present a resource-rational framework for policy compression that integrates both constraints, offering a unified perspective on decision-making under cognitive limitations.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, United States, 1 2122416500.
Background: The growing adoption of diagnostic and prognostic algorithms in health care has led to concerns about the perpetuation of algorithmic bias against disadvantaged groups of individuals. Deep learning methods to detect and mitigate bias have revolved around modifying models, optimization strategies, and threshold calibration with varying levels of success and tradeoffs. However, there have been limited substantive efforts to address bias at the level of the data used to generate algorithms in health care datasets.
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