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| http://dx.doi.org/10.1016/j.mib.2021.06.001 | DOI Listing |
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Mining microbial and metabolic dark matter in extreme environments: a roadmap for harnessing the power of multi-omics data.
Adv Biotechnol (Singap)
August 2024
State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Stress Biology and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, PR China.
Extreme environments such as hyperarid, hypersaline, hyperthermal environments, and the deep sea harbor diverse microbial communities, which are specially adapted to extreme conditions and are known as extremophiles. These extremophilic organisms have developed unique survival strategies, making them ideal models for studying microbial diversity, evolution, and adaptation to adversity. They also play critical roles in biogeochemical cycles.
View Article and Find Full Text PDFEvolution of artificial intelligence in healthcare: a 30-year bibliometric study.
Front Med (Lausanne)
January 2025
Department of Cardiology, Heart Center, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Introduction: In recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered increasing attention from medical experts. This study undertakes a dynamic and longitudinal bibliometric analysis of AI publications within the healthcare sector over the past three decades to investigate the current status and trends of the fusion between medicine and artificial intelligence.
View Article and Find Full Text PDFA novel interval sparse evolutionary algorithm for efficient spectral variable selection.
Anal Chim Acta
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School of Automation, Central South University, 410083, Changsha, China. Electronic address:
In spectral analysis, selecting the right spectral variables is crucial for effective modeling. It reduces data dimensionality, removes irrelevant wavelength points, and improves both the generalization ability and computational efficiency of the model. However, the number of available samples often falls short of the total possible combinations of wavelengths, making variable selection a non-deterministic polynomial-time (NP) hard optimization problem.
View Article and Find Full Text PDFDynamic graph based weakly supervised deep hashing for whole slide image classification and retrieval.
Med Image Anal
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School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Recently, a multi-scale representation attention based deep multiple instance learning method has proposed to directly extract patch-level image features from gigapixel whole slide images (WSIs), and achieved promising performance on multiple popular WSI datasets. However, it still has two major limitations: (i) without considering the relations among patches, thereby possibly restricting the model performance; (ii) unable to handle retrieval tasks, which is very important in clinic diagnosis. To overcome these limitations, in this paper, we propose a novel end-to-end MIL-based deep hashing framework, which is composed of a multi-scale representation attention based deep network as the backbone, patch-based dynamic graphs and hashing encoding layers, to simultaneously handle classification and retrieval tasks.
View Article and Find Full Text PDFσ-Electrons rather than π-Electrons Inducing Sensitive Nonlinear Optical Responses in Planar and Quasi-Planar Boron Clusters.
J Phys Chem A
January 2025
School of Materials Science and Physics, China University of Mining and Technology, Xuzhou, Jiangsu Province 221116, China.
Geometries and electronic structures of planar and quasi-planar boron clusters resemble those of aromatic hydrocarbons, providing opportunities for designing novel nonlinear optical materials. However, the nonlinear optical properties, optical-response mechanisms, and optimal optical-response geometries of boron clusters remain unclear. Accordingly, this study addresses these uncertainties.
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