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Cobalt Hexacyanoferrate Cathode with Stable Structure and Fast Kinetics for Aqueous Zinc-Ion Batteries.
ACS Appl Mater Interfaces
January 2025
Center of Nanomaterials for Renewable Energy, State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi'an Jiaotong University, Xìan, Shaanxi 710049, China.
Prussian blue analogues (PBAs) show great promise as cathode candidates for aqueous zinc-ion batteries thanks to their high operating voltage, open-framework structure, and low cost. However, suffering from numerous vacancies and crystal water, the electrochemical performance of PBAs remains unsatisfactory, with limited capacity and poor cycle life. Here, a simple coprecipitation method is shown to synthesize well-crystallized cobalt hexacyanoferrate (CoHCF) with a small amount of water and high specific surface area.
View Article and Find Full Text PDFSpeech Technology for Automatic Recognition and Assessment of Dysarthric Speech: An Overview.
J Speech Lang Hear Res
January 2025
Centre for Language Studies, Radboud University, Nijmegen, the Netherlands.
Purpose: In this review article, we present an extensive overview of recent developments in the area of dysarthric speech research. One of the key objectives of speech technology research is to improve the quality of life of its users, as evidenced by the focus of current research trends on creating inclusive conversational interfaces that cater to pathological speech, out of which dysarthric speech is an important example. Applications of speech technology research for dysarthric speech demand a clear understanding of the acoustics of dysarthric speech as well as of speech technologies, including machine learning and deep neural networks for speech processing.
View Article and Find Full Text PDFMachine learning-based prognostic modeling and surgical value analysis of de novo metastatic invasive ductal carcinoma of the breast.
Updates Surg
January 2025
Department of Radiation Oncology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Whether primary lesion surgery improves survival in patients with de novo metastatic breast cancer (dnMBC) is inconclusive. We aimed to establish a prognostic prediction model for patients with de novo metastatic breast invasive ductal carcinoma (dnMBIDC) based on machine learning algorithms and to investigate the value of primary site surgery. The data used in our study were obtained from the Surveillance, Epidemiology, and End Results database (SEER, 2010-2021) and the First Affiliated Hospital of Nanchang University (1st-NCUH, June 2013-June 2023).
View Article and Find Full Text PDFAttention-guided erasing for enhanced transfer learning in breast abnormality classification.
Int J Comput Assist Radiol Surg
January 2025
Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, Martensstr. 3, 91058, Erlangen, Bayern, Germany.
Purpose: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation technique, attention-guided erasing (AGE), across various transfer learning classification tasks for breast abnormality classification in mammography.
Methods: AGE utilizes attention head visualizations from DINO self-supervised pretraining to weakly localize regions of interest (ROI) in images.
Wearable Biodevices Based on Two-Dimensional Materials: From Flexible Sensors to Smart Integrated Systems.
Nanomicro Lett
January 2025
Key Laboratory of Bio-Inspired Smart Interfacial Science and Technology of Ministry of Education, School of Chemistry, Beihang University, Beijing, 100191, People's Republic of China.
The proliferation of wearable biodevices has boosted the development of soft, innovative, and multifunctional materials for human health monitoring. The integration of wearable sensors with intelligent systems is an overwhelming tendency, providing powerful tools for remote health monitoring and personal health management. Among many candidates, two-dimensional (2D) materials stand out due to several exotic mechanical, electrical, optical, and chemical properties that can be efficiently integrated into atomic-thin films.
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