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A deep learning approach for classifying and predicting children's nutritional status in Ethiopia using LSTM-FC neural networks.
BioData Min
January 2025
Department of Statistics, College of Science, Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia.
Background: This study employs a LSTM-FC neural networks to address the critical public health issue of child undernutrition in Ethiopia. By employing this method, the study aims classify children's nutritional status and predict transitions between different undernutrition states over time. This analysis is based on longitudinal data extracted from the Young Lives cohort study, which tracked 1,997 Ethiopian children across five survey rounds conducted from 2002 to 2016.
View Article and Find Full Text PDFCost-efficient behavioral modeling of antennas by means of global sensitivity analysis and dimensionality reduction.
Sci Rep
January 2025
Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233, Gdansk, Poland.
Computational tools, particularly electromagnetic (EM) solvers, are now commonplace in antenna design. While ensuring reliability, EM simulations are time-consuming, leading to high costs associated with EM-driven procedures like parametric optimization or statistical design. Various techniques have been developed to address this issue, with surrogate modeling methods garnering particular attention due to their potential advantages.
View Article and Find Full Text PDFAn optimized lightweight real-time detection network model for IoT embedded devices.
Sci Rep
January 2025
School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, 510665, China.
With the rapid development of Internet of Things (IoT) technology, embedded devices in various computer vision scenarios can realize real-time target detection and recognition tasks, such as intelligent manufacturing, automatic driving, smart home, and so on. YOLOv8, as an advanced deep learning model in the field of target detection, has attracted much attention for its excellent detection speed, high precision, and multi-task processing capability. However, since IoT embedded devices typically own limited computing resources, direct deployment of YOLOv8 is a big challenge, especially for real-time detection tasks.
View Article and Find Full Text PDFRegulation of circadian gene activity in fibroblasts from ADHD patients through Rosiglitazone: a pilot study.
J Neural Transm (Vienna)
January 2025
Chair of Vascular Neurology, Dementia and Ageing, University Hospital Essen, Essen University Medical School, University of Duisburg-Essen, 45147, Essen, Germany.
Attention-deficit/hyperactivity disorder (ADHD) is a frequently observed condition, with about 70% of individuals diagnosed with ADHD experiencing irregular sleep-wake patterns. Beyond the primary symptoms of ADHD, there is a significant overlap with sleep-related issues, indicating that disrupted sleep patterns may exacerbate ADHD symptoms. ADHD-related sleep problems can be traced to a delayed circadian rhythm and a later onset of melatonin production.
View Article and Find Full Text PDFFactors associated with link workers considering leaving their role: a cross-sectional survey.
BJGP Open
January 2025
University of Exeter, Exeter, United Kingdom.
Background: Social prescribing (SP) link workers (LWs) listen to patients' concerns and difficulties, and connect them to relevant community assets (groups/organisations/charities) that can help with their non-medical issues (eg, loneliness, debt, housing). LW retention is key to sustaining SP within primary care.
Aim: To examine occupational self-efficacy, job discrepancy and other factors as potential predictors of LWs' intentions to leave or remain in their post.
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