Results 91 to 100 of about 72,357 (237)

Safeguarding Merit: Citizen Support for Civil Service Protections Against Political Interference

Public Administration Review, EarlyView.
ABSTRACT President Trump altered the U.S. federal civil service system by reducing merit‐based protections for bureaucratic expertise and expanding the scope of political appointments, shifting the balance long established under the Pendleton Act of 1883. Similar reforms have occurred at the state level with moves to at‐will employment.
Colt Jensen, Jaclyn Piatak
wiley   +1 more source

Detecting Electrocardiogram Arrhythmia Empowered With Weighted Federated Learning

IEEE Access
In this study, a weighted federated learning approach is proposed for electrocardiogram (ECG) arrhythmia classification. The proposed approach considers the heterogeneity of data distribution among multiple clients in federated learning settings.
Rizwana Naz Asif, Allah Ditta, Hani Alquhayz, Sagheer Abbas, Muhammad Adnan Khan, Taher M. Ghazal, Sang-Woong Lee   +6 more
doaj   +1 more source

GPT-FL: Generative Pre-trained Model-Assisted Federated Learning

, 2023
In this work, we propose GPT-FL, a generative pre-trained model-assisted federated learning (FL) framework. At its core, GPT-FL leverages generative pre-trained models to generate diversified synthetic data. These generated data are used to train a downstream model on the server, which is then fine-tuned with private client data under the standard FL ...
Zhang, Tuo, Feng, Tiantian, Alam, Samiul, Dimitriadis, Dimitrios, Lee, Sunwoo, Zhang, Mi, Narayanan, Shrikanth S., Avestimehr, Salman   +7 more
openaire   +2 more sources

Large language models for bioinformatics

Quantitative Biology, Volume 14, Issue 1, March 2026.
Abstract With the rapid advancements in large language model technology and the emergence of bioinformatics‐specific language models (BioLMs), there is a growing need for a comprehensive analysis of the current landscape, computational characteristics, and diverse applications.
Wei Ruan, Yanjun Lyu, Jing Zhang, Jiazhang Cai, Peng Shu, Yang Ge, Yao Lu, Shang Gao, Yue Wang, Peilong Wang, Lin Zhao, Tao Wang, Yufang Liu, Luyang Fang, Ziyu Liu, Zhengliang Liu, Yiwei Li, Zihao Wu, Junhao Chen, Hanqi Jiang, Yi Pan, Zhenyuan Yang, Jingyuan Chen, Shizhe Liang, Wei Zhang, Terry Ma, Yuan Dou, Jianli Zhang, Xinyu Gong, Qi Gan, Yusong Zou, Zebang Chen, Yuanxin Qian, Shuo Yu, Jin Lu, Kenan Song, Xianqiao Wang, Andrea Sikora, Gang Li, Xiang Li, Quanzheng Li, Yingfeng Wang, Lu Zhang, Yohannes Abate, Lifang He, Wenxuan Zhong, Rongjie Liu, Chao Huang, Wei Liu, Ye Shen, Ping Ma, Hongtu Zhu, Yajun Yan, Dajiang Zhu, Tianming Liu   +54 more
wiley   +1 more source

A Trusted Federated Learning Method Based on Consortium Blockchain

Information
Federated learning (FL) has gained significant attention in distributed machine learning due to its ability to protect data privacy while enabling model training across decentralized data sources.
Xiaojun Yin, Xijun Wu, Xinming Zhang
doaj   +1 more source

A Novel, Low‐Cost, Nonbiological Phantom for Training in Ultrasound‐Guided Regional Anesthesia

Sonography, Volume 13, Issue 1, March 2026.
ABSTRACT Background Trainees of ultrasound‐guided regional anesthesia (UGRA) should begin with phantoms before use on patients. The phantoms currently available have substantial drawbacks. Our aim was to develop a low‐cost homemade UGRA phantom without perishable parts, which shows sonoanatomical details and hydrodissection when injecting fluid—the ...
Marco R. Zugaj, Martin Ertmer, Jessica Schleifer, Raoul Breitkreutz   +3 more
wiley   +1 more source

Federated Active Learning (F-AL): An Efficient Annotation Strategy for Federated Learning

IEEE Access
Federated learning (FL) has been intensively investigated in terms of communication efficiency, privacy, and fairness. However, efficient annotation, which is a pain point in real-world FL applications, is less studied.
Jin-Hyun Ahn, Yeeun Ma, Seoyun Park, Cheolwoo You   +3 more
doaj   +1 more source

Next‐Generation Bio‐Reducible Lipids Enable Enhanced Vaccine Efficacy in Malaria and Primate Models

Advanced Functional Materials, Volume 36, Issue 11, 5 February 2026.
Structure–activity relationship (SAR) optimization of bio‐reducible ionizable lipids enables the development of highly effective lipid nanoparticle (LNP) mRNA vaccines. Lead LNPs show superior tolerability and antibody responses in rodents and primates, outperforming approved COVID‐19 vaccine lipids.
Ruben De Coen, Sabah Kasmi, Shrinivas Dumbre, Lies Baekens, Elise Seynaeve, Louise Van den Hauwe, Niccolò Cantini, Aello Garantoudi, Filipe Branco Madeira, Alain Marrot, Emma Tuypens, Sofie Seghers, Anna Kuchmiy, Elisabeth Brabants, Bart Vanderborght, Ine Maes, Sarah Vandenberghe, Jessica Filtjens, Alícia Gordún Peiró, Daliya Kancheva, Ayla Debraekeleer, Florence Lambolez, Emily De Lombaerde, Yong Chen, Rafael Miyazawa Martins, Pauline Formaglio, Damya Laoui, Sofie Deschoemaeker, Bruno G. De Geest, Rogerio Amino, Stefaan De Koker   +30 more
wiley   +1 more source

Federated learning for predicting compound mechanism of action based on image-data from cell painting

Artificial Intelligence in the Life Sciences
Having access to sufficient data is essential in order to train accurate machine learning models, but much data is not publicly available. In drug discovery this is particularly evident, as much data is withheld at pharmaceutical companies for various ...
Li Ju, Andreas Hellander, Ola Spjuth
doaj   +1 more source

An Aggregation-Free Federated Learning for Tackling Data Heterogeneity [PDF]

Computer Vision and Pattern Recognition
The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework, where clients update local models based on a global model aggregated ...
Yuan Wang, Huazhu Fu, Renuga Kanagavelu, Qingsong Wei, Yong Liu, R. Goh   +5 more
semanticscholar   +1 more source