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Assessing the impacts of forest cover change on carbon stock and soil moisture dynamics using geospatial techniques: a case study of Nensebo forest, Southern Ethiopia.
Environ Monit Assess
January 2025
Department of Natural Resource Management, College of Agriculture and Veterinary Medicine, Jimma University, Jimma, Ethiopia.
Assessing the impacts of forest cover change on carbon stock and soil moisture dynamics is critical for understanding environmental degradation and guiding sustainable land management. This study evaluates the effects of forest cover change on carbon stock and soil moisture dynamics in Nensebo Forest from 1993 to 2023 using geospatial techniques. Landsat imagery including TM (1993), ETM + (2009), and OLI/TIRS (2023) were used.
View Article and Find Full Text PDFCu-Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and TEM Study.
Nano Lett
January 2025
Department of Mechanical Engineering & Materials Science, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.
The development of accurate methods for determining how alloy surfaces spontaneously restructure under reactive and corrosive environments is a key, long-standing, grand challenge in materials science. Using machine learning-accelerated density functional theory and rare-event methods, in conjunction with environmental transmission electron microscopy (ETEM), we examine the interplay between surface reconstructions and preferential segregation tendencies of CuNi(100) surfaces under oxidation conditions. Our modeling approach predicts that oxygen-induced Ni segregation in CuNi alloys favors Cu(100)-O c(2 × 2) reconstruction and destabilizes the Cu(100)-O (2√2 × √2)45° missing row reconstruction (MRR).
View Article and Find Full Text PDFIdentifying cancer prognosis genes through causal learning.
Brief Bioinform
November 2024
School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, 130012 Changchun, China.
Accurate identification of causal genes for cancer prognosis is critical for estimating disease progression and guiding treatment interventions. In this study, we propose CPCG (Cancer Prognosis's Causal Gene), a two-stage framework identifying gene sets causally associated with patient prognosis across diverse cancer types using transcriptomic data. Initially, an ensemble approach models gene expression's impact on survival with parametric and semiparametric hazard models.
View Article and Find Full Text PDFQOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics.
Brief Bioinform
November 2024
Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, United States.
Single-cell technologies have enabled the high-dimensional characterization of cell populations at an unprecedented scale. The innate complexity and increasing volume of data pose significant computational and analytical challenges, especially in comparative studies delineating cellular architectures across various biological conditions (i.e.
View Article and Find Full Text PDFContributions of short- and long-range white matter tracts in dynamic compensation with aging.
Cereb Cortex
January 2025
School of AIDE, Center for Brain Science and Applications, IIT Jodhpur, NH-62, Surpura Bypass Rd, Karwar, Rajasthan 342030, India.
Optimal brain function is shaped by a combination of global information integration, facilitated by long-range connections, and local processing, which relies on short-range connections and underlying biological factors. With aging, anatomical connectivity undergoes significant deterioration, which affects the brain's overall function. Despite the structural loss, previous research has shown that normative patterns of functions remain intact across the lifespan, defined as the compensatory mechanism of the aging brain.
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