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scSMD: a deep learning method for accurate clustering of single cells based on auto-encoder.
BMC Bioinformatics
January 2025
Department of Surgery, Shanghai Key Laboratory of Gastric Neoplasms, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: Single-cell RNA sequencing (scRNA-seq) has transformed biological research by offering new insights into cellular heterogeneity, developmental processes, and disease mechanisms. As scRNA-seq technology advances, its role in modern biology has become increasingly vital. This study explores the application of deep learning to single-cell data clustering, with a particular focus on managing sparse, high-dimensional data.
View Article and Find Full Text PDFThe impact of carbon emissions trading on green total factor productivity based on evidence from a quasi-natural experiment.
Sci Rep
January 2025
Faculty of Social Sciences, University of Lodz, ul. Prez, prez. Gabriela Narutowicza 68, 90-136, Łódź, Poland.
Based on a balanced panel dataset of 272 prefecture-level cities from 2000 to 2022, this paper systematically investigates the impact of the carbon emissions trading system on green total factor productivity and its underlying mechanisms from an integrated perspective of overall, dynamic, and spatial dimensions. The findings reveal that (1) the carbon emissions trading system significantly enhances regional total factor productivity, primarily by optimizing resource allocation efficiency and strengthening regional competitiveness. (2) From a dynamic perspective, the policy effect exhibited a U-shaped relationship: from 2013 to 2018, green total factor productivity was suppressed due to underdeveloped market mechanisms and the policy environment; after 2018, with market maturation and policy stabilization, the policy effects improved significantly.
View Article and Find Full Text PDFEfficient nonlinear function approximation in analog resistive crossbars for recurrent neural networks.
Nat Commun
January 2025
Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China.
Analog In-memory Computing (IMC) has demonstrated energy-efficient and low latency implementation of convolution and fully-connected layers in deep neural networks (DNN) by using physics for computing in parallel resistive memory arrays. However, recurrent neural networks (RNN) that are widely used for speech-recognition and natural language processing have tasted limited success with this approach. This can be attributed to the significant time and energy penalties incurred in implementing nonlinear activation functions that are abundant in such models.
View Article and Find Full Text PDFThermostable terahertz metasurface enabled by graphene assembly film for plasmon-induced transparency.
Sci Rep
January 2025
State Key Laboratory of New Textile Materials and Advanced Processing Technologies, Wuhan Textile University, Wuhan, 430200, People's Republic of China.
With the increasing demand on high-density integration and better performance of micro-nano optoelectronic devices, the operation temperatures are expected to significantly increase under some extreme conditions, posing a risk of degradation to metal-based micro-/nano-structured metasurfaces due to their low tolerance to high temperature. Therefore, it is urgent to find new materials with high-conductivity and excellent high-temperature resistance to replace traditional micro-nano metal structures. Herein, we have proposed and fabricated a thermally stable graphene assembly film (GAF), which is calcined at ultra-high temperature (~ 3000 ℃) during the reduction of graphite oxide (GO).
View Article and Find Full Text PDFThe value of MRI in differentiating ovarian clear cell carcinoma from other adnexal masses with O-RADS MRI scores of 4-5.
Insights Imaging
January 2025
Department of Radiology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Objective: To assess the utility of clinical and MRI features in distinguishing ovarian clear cell carcinoma (CCC) from adnexal masses with ovarian-adnexal reporting and data system (O-RADS) MRI scores of 4-5.
Methods: This retrospective study included 850 patients with indeterminate adnexal masses on ultrasound. Two radiologists evaluated all preoperative MRIs using the O-RADS MRI risk stratification system.
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