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Deep visual proteomics reveals DNA replication stress as a hallmark of signet ring cell carcinoma
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Comparison of fit of poly (etheretherketone) and cobalt-chromium removable partial denture frames: an in-vitro study.
Published 2023-06-01“…Eighty VPS samples were made to present the gap between rest and rest seats; these samples were measured using a digital micrometre under a microscope with a magnification of 40x. The data were analysed using SPSS programs with an independent T-test. …”
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Diversity and abundance of butterflies in urban areas of Bankura district, Bankura, West Bengal, India
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An Intelligent Approach for the Challenges in the Evaluation of Public Accountant Firms Under Uncertainties
Published 2025-01-01“…Flexibility evaluation is additionally built into the framework to guarantee the findings’ reliability and pinpoint ideal factor setups. …”
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Patient satisfaction toward doctor communication in medical clinics: a study from northern Sri Lanka
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Healthcare Resource Utilization Associated with Leukopenia and Neutropenia in Kidney Transplant Recipients Receiving Valganciclovir in the United States
Published 2025-01-01“…**Methods:** Using TriNetX Dataworks-USA, a federated, de-identified electronic medical record database, we identified adult KTRs who underwent their first kidney transplant from January 2012 to September 2020. …”
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THE IMPACT OF CORPORATE SOCIAL RESPONSIBILITY ON BANK PERFORMANCE IN NIGERIA
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Most oncological pancreas resections must consider the mesopancreas
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Impact of empiric antibiotics on risk of Clostridioides difficile—a causal inference observational analysis
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Prediction of Soil Organic Carbon Content in <italic>Spartina alterniflora</italic> by Using UAV Multispectral and LiDAR Data
Published 2025-01-01“…The results show that the following. 1) The prediction accuracy is improved by classifying the data into three types: unlodging <italic>S. alterniflora</italic> (ULSA), lodging <italic>S. alterniflora</italic> (LSA), and mudflats. 2) XGBoost outperformed RF and SVM in accurately predicting SOC content, with <italic>R</italic><sup>2</sup>; values of 0.743 for ULSA, 0.731 for LSA, and 0.705 for mudflats; 3) In the XGBoost models constructed for ULSA, LSA, and mudflats, spectral features contributed 75.7%, 73.1%, and 63.1%, respectively, with the normalized difference vegetation index emerging as the most critical spectral feature. …”
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