An ecosystem approach to the evaluation and impact analysis of heterogeneous preventive and/or early interventions projects for veterans and first responders in seven countries by S. Lukersmith, L. Salvador-Carulla, C. Woods, T. Niyonsenga, M.R. Gutierrez-Colosia, I. Mohanty, C.R. Garcia-Alonso, D. Diaz-Milanes, J.A. Salinas-Perez, R. Davey, A. Aryani

“…Our ecosystem approach and novel evaluation methodology will reduce the uncertainty around real world implementation, provide key learnings for project stakeholders and more broadly implementation researchers.…”
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Universal conditional networks (UniCoN) for multi-age embryonic cartilage segmentation with Sparsely annotated data by Nishchal Sapkota, Yejia Zhang, Zihao Zhao, Maria Jose Gomez, Yuhan Hsi, Jordan A. Wilson, Kazuhiko Kawasaki, Greg Holmes, Meng Wu, Ethylin Wang Jabs, Joan T. Richtsmeier, Susan M. Motch Perrine, Danny Z. Chen

“…Tackling this segmentation task with deep learning (DL) methods is laborious due to the big burden of manual image annotation, expensive due to the high acquisition costs of 3D micro-CT images, and difficult due to embryonic cartilage’s complex and rapidly changing shapes. …”
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Decision support systems for waste-to-energy technologies: A systematic literature review of methods and future directions for sustainable implementation in Ghana by Theophilus Frimpong Adu, Lena Dzifa Mensah, Mizpah Ama Dziedzorm Rockson, Francis Kemausuor

“…Future research directions identified by this study include the development of Ghana-specific DSS models, integration of real-time data collection methodologies, creation of user-friendly interfaces for local decision-makers, and exploration of emerging technologies such as blockchain and IoT or Machine learning (ML) for enhancing DSS in WtE management.…”
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Patient-Generated Collections for Organizing Electronic Health Record Data to Elevate Personal Meaning, Improve Actionability, and Support Patient–Health Care Provider Communicatio... by Drashko Nakikj, David Kreda, Karan Luthria, Nils Gehlenborg

“…By observing how patients used features to select records and assemble them into collections, our goal was to learn about their preferred mechanisms to complete these tasks and the challenges they would face in the wild. …”
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Data-driven modeling of open circuit voltage hysteresis for LiFePO4 batteries with conditional generative adversarial network by Lisen Yan, Jun Peng, Zeyu Zhu, Heng Li, Zhiwu Huang, Dirk Uwe Sauer, Weihan Li

“…This paper proposes a data-driven approach with adversarial learning to model hysteresis under diverse conditions, addressing the intricate dependencies on SOC, temperature, and battery aging. …”
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Information Security and Artificial Intelligence–Assisted Diagnosis in an Internet of Medical Thing System (IoMTS) by Pi-Yun Chen, Yu-Cheng Cheng, Zi-Heng Zhong, Feng-Zhou Zhang, Neng-Sheng Pai, Chien-Ming Li, Chia-Hung Lin

“…For a symmetric cryptography scheme, this study proposed a key generator combining a chaotic map and Bell inequality and generating unordered numbers and unrepeated 256 secret keys in the key space. Then, a machine learning - based model was employed to train the encryptor and decryptor for both biosignals and image infosecurity. …”
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Evaluation of Phytochemical, Antioxidant, and Memory-Enhancing Activity of Garuga pinnata Roxb. Bark and Bryophyllum pinnatum (Lam) Oken. Leaves by Ravin Bhandari, Sabina Gyawali, Nisha Aryal, Devika Gaire, Kalpana Paudyal, Abaru Panta, Pooja Panth, Dirgha Raj Joshi, Rabindra Kumar Rokaya, Pramod Aryal, Jitendra Pandey

“…DPPH assay method and the Folin–Ciocalteu method were employed to determine antioxidant potency and total phenol amount, respectively. 400 mg/kg of the methanolic B. pinnatum bark extract significantly improved memory and learning of mice with transfer latency (TL) of 32.75 s, which is comparable to that of standard Piracetam (21.78 s) and Shankhpushpi (27.83 s). …”
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Association between the subclinical level of problematic internet use and habenula volume: a look at mediation effect of neuroticism by Toshiya Murai, Hironobu Fujiwara, Qi Dai, Halwa Zakia, Yusuke Kyuragi, Naoya Oishi, Yuzuki Ishikawa, Lichang Yao, Morio Aki

“…Hb segmentation was performed using a deep learning technique. The Internet Addiction Test (IAT) and the NEO Five-Factor Inventory were used to assess the PIU level and personality, respectively. …”
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Multi-Feature Driver Variable Fusion Downscaling TROPOMI Solar-Induced Chlorophyll Fluorescence Approach by Jinrui Fan, Xiaoping Lu, Guosheng Cai, Zhengfang Lou, Jing Wen

“…Using the Random Forest (RF) model, we downscaled SIF data from 0.05° to 1 km based on invariant spatial scaling theory, focusing on the winter wheat growth cycle. Various machine learning models, including CNN, Stacking, Extreme Random Trees, AdaBoost, and GBDT, were compared, with Random Forest yielding the best performance, achieving R² = 0.931, RMSE = 0.052 mW/m²/nm/sr, and MAE = 0.031 mW/m²/nm/sr for 2018–2019 and R² = 0.926, RMSE = 0.058 mW/m²/nm/sr, and MAE = 0.034 mW/m²/nm/sr for 2019–2020. …”
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Comparison of diet and exercise on cardiometabolic factors in young adults with overweight/obesity: multiomics analysis and gut microbiota prediction, a randomized controlled trial by Zongyu Lin, Tianze Li, Fenglian Huang, Miao Wu, Lewei Zhu, Yueqin Zhou, Ying‐An Ming, Zhijun Lu, Wei Peng, Fei Gao, Yanna Zhu

“…Additionally, we used machine learning algorithms to further predict individual responses based on baseline gut microbiota composition, with specific microbial genera guiding targeted intervention selection. …”
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Teknologi Realitas Virtual pada Perangkat Bergerak untuk Media Pengenalan Lingkungan Haji by Usaid Syawahidul Chaq, Febriliyan Samopa

“…However, to learn and practice Hajj rituals directly on a regular basis certainly requires extra money and energy. …”
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Towards PErsonalised PRognosis for children with traumatic brain injury: the PEPR study protocol by Jaap Oosterlaan, Marsh Königs, Job B M van Woensel, Marc Engelen, Marjan E Steenweg, Petra J W Pouwels, Cece C Kooper, Hilgo Bruining, Arne Popma, Dennis R Buis, Maayke Hunfeld

“…In addition, the potential added value of advanced neuroimaging data and the use of machine learning algorithms in the development of prognostic models will be assessed.Methods and analysis 210 children aged 4–18 years diagnosed with mild-to-severe TBI will be prospectively recruited from a research network of Dutch hospitals. …”
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Dataset of aerial photographs acquired with UAV using a multispectral (green, red and near-infrared) camera for cherry tomato (Solanum lycopersicum var. cerasiforme) monitoringDrya... by Osiris Chávez-Martínez, Sergio Alberto Monjardin-Armenta, Jesús Gabriel Rangel-Peraza, Zuriel Dathan Mora-Felix, Antonio Jesus Sanhouse-García

“…However, this multispectral imagery dataset can also have various uses, such as creating training datasets with accurate labels or classes which can then be used to develop, train, and/or validate machine learning algorithms for image classification, object detection tasks, or change detection analysis.…”
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Personality characteristics of students in the regulation of network activity by S. E. Panshina, N. L. Sungurova, N. B. Karabushchenko

“…The research results can be used to improve distance learning programmes, additional education courses, as well as to increase the efficacy of regulation of student's network activity in order to prevent Internet addiction.…”
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Minimally Invasive Mitral Valve Surgery: Initial One-team Experience and Short Review. by Selman Dumani, Ermal Likaj, Laureta Dibra, Saimir Kuci, Edlira Rruci, Alfred Ibrahimi, Aferdita Veseli, Fjorba Mana, Devis Pellumbi, Alessia Mehmeti, Ali Refatllari, Altin Veshti

“…We need a more extensive study to confirm the other advantages, but minimal-invasive should be pushed to become a standard approach for mitral valve surgery. An adequate learning curve is mandatory for all the operative teams to achieve all the benefits for the patients. …”
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Compact Quantum Cascade Laser-Based Noninvasive Glucose Sensor Upgraded with Direct Comb Data-Mining by Liying Song, Zhiqiang Han, Hengyong Nie, Woon-Ming Lau

“…The sensor data-mines 164 sets of critical singularity strengths, each comprising 4 critical singularity strengths directly from the 9840 million raw signal datapoints, and the 656 critical singularity strengths are subjected to a machine-learning regression model analysis, which yields 164 glucose concentrations. …”
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Diagnosis of lung cancer using salivary miRNAs expression and clinical characteristics by Negar Alizadeh, Hoda Zahedi, Maryam Koopaie, Mahnaz Fatahzadeh, Reza Mousavi, Sajad Kolahdooz

“…Receiver operating characteristic (ROC) curve was utilized to assess the potential significance of miRNAs in saliva for lung cancer diagnosis with the use of multiple logistic regression (MLR), principal component analysis, and machine learning methods. Results Diagnostic odds ratio (DOR) of miR-20a in lung adenocarcinoma diagnosis versus healthy control was higher than miR-221, and DOR of miR-221 was higher than let-7a-2. miR-20a demonstrated a higher DOR for small cell lung carcinoma versus healthy control compared to let-7a-2, which in turn exhibited a higher DOR than miR-221. …”
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Emotional regulation as a transdiagnostic category through clinical problems: a narrative study by Alvaro Paredes-Rivera, Geraldine F Coria-Palomino, Alexandra Y Marcos-Lescano, Sthefany Sedano-Alejandro

“…Especially from the biological and contextual points and taking into account the learning for its maintenance.…”
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Improving the Detection, Assessment, Management and Prevention of Delirium in Hospices (the DAMPen-D study): protocol for a co-design and feasibility study of a flexible and scalab... by Najma Siddiqi, Chao Huang, Maureen Twiddy, Miriam Johnson, Margaret Ogden, Kathryn Sartain, Imogen Featherstone, Jason Boland, Mark Pearson, Catriona Jackson, Gillian Jackson

“…The primary objective of this study is to demonstrate the feasibility of an implementation strategy (designed to help deliver good practice delirium guidelines), participant recruitment and data collection.Methods and analysis Three work packages in three hospices in the UK with public involvement in codesign, study management and stakeholder groups: (1) experience-based codesign to adapt an existing theoretically-informed implementation strategy (Creating Learning Environments for Compassionate Care (CLECC)) to implement delirium guidelines in hospices; (2) feasibility study to explore ability to collect demographic, diagnostic and delirium management data from clinical records (n=300), explanatory process data (number of staff engaged in CLECC activities and reasons for non-engagement) and cost data (staff and volunteer hours and pay-grades engaged in implementation activities) and (3) realist process evaluation to assess the acceptability and flexibility of the implementation strategy (preimplementation and postimplementation surveys with hospice staff and management, n=30 at each time point; interviews with hospice staff and management, n=15). …”
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Reflexive Methods of Knowledge in Educational Activities: Phenomenological Hermeneutics by T. N. Korneenko

“…Knowledge is one of the most important human needs. Today, lifelong learning and self-education individual skills are of paramount importance for each representative of the society in relation to the world trends of a post-industrial era: economic domination in the innovative sector, progressive increase of intensity of information flows and rates of distribution of high technologies, rapid development of science and industry of knowledge, quickly changing and becoming tougher requirements to professionalism, qualification and creativity of experts irrespective of the sphere of employment. …”
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