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MVSLLnc: LncRNA subcellular localization prediction based on multi-source features and two-stage voting strategy.
Methods
January 2025
National Center for Applied Mathematics in Hunan, Xiangtan University, Hunan 411105, China; Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Hunan 411105, China. Electronic address:
The subcellular localization of long non-coding RNAs (lncRNAs) is crucial for understanding the function of lncRNAs. Since the traditional biological experimental methods are time-consuming and some existing computational methods rely on high computing power, we are committed to finding a simple and easy-to-implement method to achieve more efficient prediction of the subcellular localization of lncRNAs. In this work, we proposed a model based on multi-source features and two-stage voting strategy for predicting the subcellular localization of lncRNAs (MVSLLnc).
View Article and Find Full Text PDFA novel machine learning model for screening the risk of obstructive sleep apnea using craniofacial photography with questionnaires.
J Clin Sleep Med
January 2025
Department of Convergence Healthcare Medicine, Ajou University, Suwon, Republic of Korea.
Study Objectives: Undiagnosed or untreated moderate to severe obstructive sleep apnea (OSA) increases cardiovascular risks and mortality. Early and efficient detection is critical, given its high prevalence. We aimed to develop a practical and efficient approach for obstructive sleep apnea screening, using simple facial photography and sleep questionnaires.
View Article and Find Full Text PDFBackground: The full pentavalent (DPT-HepB-Hib) vaccination is the main strategy to prevent five communicable diseases in early childhood, especially in countries with huge communicable disease burdens like Ethiopia. Exploring spatial distributions and determinants of full pentavalent vaccination status in minor ecological areas in Ethiopia is crucial for creating targeted immunization campaigns and monitoring the advancement of accomplishing sustainable development goals. This study aimed to investigate the spatial disparities and determinants of full pentavalent vaccination among 12-23-month-old children in Ethiopia.
View Article and Find Full Text PDFLossless Image Compression Using Context-Dependent Linear Prediction Based on Mean Absolute Error Minimization.
Entropy (Basel)
December 2024
Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, ul. Żołnierska 49, 71-210 Szczecin, Poland.
This paper presents a method for lossless compression of images with fast decoding time and the option to select encoder parameters for individual image characteristics to increase compression efficiency. The data modeling stage was based on linear and nonlinear prediction, which was complemented by a simple block for removing the context-dependent constant component. The prediction was based on the Iterative Reweighted Least Squares () method which allowed the minimization of mean absolute error.
View Article and Find Full Text PDFPreoperative patient teaching practices and associated factors among nurses working at hospitals in West Shoa Zone, Ethiopia, 2022: a cross-sectional study.
Front Public Health
January 2025
Department of Nursing, School of Nursing and Midwifery, Wallaga University, Nekemte, Ethiopia.
Article Synopsis
- Preoperative teaching is a critical nursing activity aimed at preparing patients for surgery by informing them about their procedures and recovery expectations, promoting active involvement in their care.
- A study conducted in 2022 assessed preoperative teaching practices among 267 nurses in the West Shoa region of Ethiopia, finding that only 39.9% demonstrated good teaching practices, hampered by factors like insufficient training and resources.
- The study utilized a structured questionnaire and statistical analysis to evaluate the effectiveness of preoperative education and identify obstacles faced by nurses, indicating a need for improvements in nursing education and support systems.
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