Digital twin based deep learning framework for personalized thermal comfort prediction and energy efficient operation in smart buildings by Ahmad Almadhor, Nejib Ghazouani, Belgacem Bouallegue, Natalia Kryvinska, Shtwai Alsubai, Moez Krichen, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…Next, the Digital Twin enables the real-time simulation of indoor environments and occupant responses, facilitating proactive comfort management. We utilise a subset of the ASHRAE Global Thermal Comfort Database II, and extensive pre-processing, including median-based data imputation and feature normalisation, is conducted. …”
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CIRA-Cyber Intelligent Risk Assessment Methodology for Industrial Internet of Things Based on Machine Learning by Ghulam Abbas, Mushtaq Ali, Muneer Ahmad, Ajmal Khan

“…Risk assessment is a proactive approach to identifying, analyzing, and mitigating potential cybersecurity threats. …”
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Raw-Data Driven Functional Data Analysis with Multi-Adaptive Functional Neural Networks for Ergonomic Risk Classification Using Facial and Bio-Signal Time-Series Data by Suyeon Kim, Afrooz Shakeri, Seyed Shayan Darabi, Eunsik Kim, Kyongwon Kim

“…The proposed model introduces a novel adaptive basis layer composed of micro-networks tailored to each individual time-series feature, enabling end-to-end learning of discriminative temporal patterns directly from raw data. …”
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When months matter; modelling the impact of the COVID-19 pandemic on the diagnostic pathway of Motor Neurone Disease (MND). by Ella Burchill, Vishal Rawji, Katy Styles, Siobhan Rooney, Patrick Stone, Ronan Astin, Nikhil Sharma

“…<h4>Results</h4>The pre-COVID model reproduced known features of the MND diagnostic pathway, with a median time to diagnosis of 399 days and predicting 5.2% of MND patients present as undiagnosed emergencies. …”
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IoT BotScan: Ultra-Lightweight AI Defense Against Botnet Threats by Sapna Sadhwani, Urvi Kavan Modi, Raja Muthalagu, Pranav M. Pawar, Alavikunhu Panthakkan, Wathiq Mansoor

“…A key contribution of this study is the lightweight RF approach, which minimizes the number of features to reduce complexity. The insights gained from this research provide valuable information for academics and cybersecurity practitioners, aiding in the development of proactive defenses against evolving BotNet threats and promoting the advancement of resilient security measures for network infrastructures.…”
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Data-driven machine learning algorithm model for pneumonia prediction and determinant factor stratification among children aged 6–23 months in Ethiopia by Addisalem Workie Demsash, Rediet Abebe, Wubishet Gezimu, Gemeda Wakgari Kitil, Michael Amera Tizazu, Abera Lambebo, Firomsa Bekele, Solomon Seyife Alemu, Mohammedamin Hajure Jarso, Geleta Nenko Dube, Lema Fikadu Wedajo, Sanju Purohit, Mulugeta Hayelom Kalayou

“…The implications of this study are profound for advanced research methodology, tailored to promote effective health interventions such as lifestyle modification and behavioral intervention, based on individuals’ unique features, specifically for stakeholders to take proactive childcare interventions. …”
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Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling by Maqsood Ahmed, Xiang Zhang, Yonglin Shen, Tanveer Ahmed, Shahid Ali, Ayaz Ali, Aminjon Gulakhmadov, Won-Ho Nam, Nengcheng Chen

“…Thus, the model efficiently extracts spatiotemporal features from video and simultaneously performs regression (PM2.5, PM10, and AQI), and classification (AQI) tasks, respectively. …”
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Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…We also evaluated the predictive power of these linguistic features using machine learning and identified key thematic structures through semantic network analysis. …”
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AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts by Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Hong-Ning Dai, Feng Zhao, Jianming Yong

“…Future research will focus on extending predictive capabilities to further enhance proactive healthcare interventions.…”
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PECULIARITIES OF FORMING AN ENTERPRISE RISK MANAGEMENT SYSTEM IN THE CONTEXT OF MODERN TRANSFORMATIONS: THE EXPERIENCE OF EUROPEAN COUNTRIES AND UKRAINE by Maryna Dielini, Marja Nesterova, Wang Yi

“…The objective of this research is to analyse and study the prerequisites and features of the formation of the enterprise risk management system under the conditions of modern transformations in the EU countries and Ukraine. …”
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Social Programs in the Structure of Expenditures of the Consolidated Budget of the Federa-tion Subject by A. S. Dmitriev, A. M. Stash

“…To ensure control over timely and complete budget execution, state audit methods can be used (we are talking about regional and municipal control and accounting bodies), including strategic audit, which allows proactive control of the effectiveness of upcoming events. …”
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Predicting Remaining Useful Life of Induction Motor Bearings from Motor Current Signatures Using Machine Learning by Nurul Zahirah Zulkifli, Bhukya Ramadevi, Kishore Bingi, Rosdiazli Ibrahim, Madiah Omar

“…A machine learning model is employed to classify the health status of motor bearings and estimate their RUL based on extracted signal features. This approach effectively differentiates healthy from faulty bearings, enabling proactive maintenance to reduce failures and boost efficiency.…”
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Clinical Characteristics and Outcomes in Heart Failure Patients with Implantable Pulmonary Artery Pressure Monitors: A Single Centre Irish Experience by Niall Leahy, Cillian O’Brien, Sara Essa Alsubai, Eileen Coen, Darragh Murphy, Faisal Sharif

“…Fluid retention manifesting in dyspnoea and oedema are important clinical features of decompensated heart failure and drive hospital admissions. …”
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Natural language processing to identify suicidal ideation and anhedonia in major depressive disorder by L. Alexander Vance, Leslie Way, Deepali Kulkarni, Emily O. C. Palmer, Abhijit Ghosh, Melissa Unruh, Kelly M. Y. Chan, Amey Girdhari, Joydeep Sarkar

“…Addressing current limitations will further enhance NLP models, enabling more accurate extraction of critical clinical features and supporting personalized, proactive mental health care.…”
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A Novel GRU-Augmented Time-Frequency Estimator for IGBT Remaining Useful Life Prediction by Yuankuang Li, Baohua Tan, Yingjie Zhang, Shuo Wang, Bolin Lian, Yuan Li, Zongming Tan

“…Accurate and efficient prediction of IGBT Remaining Useful Life (RUL) is critical for proactive risk mitigation and ensuring system stability. …”
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Neurofibromatosis-Noonan syndrome: a prospective monocentric study of 26 patients and literature review by Didier Bessis, Dominique Vidaud, Pierre Meyer, Laurence Pacot, de La Villeon G, Adeline Alice Bonnard, Yline Capri, Christine Coubes, Fanchon Herman, Didier Lacombe, Nicolas Molinari, Laura Poujade, Agathe Roubertie, Julien Van Gils, Alain Verloes, David Geneviève, Hélène Cavé, Marjolaine Willems

“…Methods This study aims to better define the clinical and molecular features of NF-NS and compare them with existing literature. …”
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Distributed dynamic mapping scheme based on cost function by Guo-dong GE, Yun-fei GUO, Ju-long LAN, Cai-xia LIU

“…For supporting efficient host mobility and mapping identifiers onto locators,a distributed dynamic mobility mapping scheme based on cost function was proposed.In the scheme,depending on the mobility pattern and communication feature,the communication of mobile node is divided into three communication models,namely,moving update model,balanced transmission model and resolving query model.In order to minimize the total resolving cost,three mapping approach are proposed based on distributed multicast,consistent hash functions and proactive sharing respectively in the mobile domain.For each mapping approach,corresponding registration update,resolution query and packet delivery strategies are designed.Simulation results show that the scheme can achieve the minimum resolving cost,and can have low resolve latency and good adaptability for network topology dynamic changing.…”
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Exploring Smart Health Wearable Adoption Among Singaporean Older Adults Based on Self-Determination Theory: Web-Based Survey Study by Hyunjin Kang, Tingting Yang, Nazira Banu, Sheryl Wei Ting Ng, Jeong Kyu Lee

“…Developers should focus on intuitive design, transparent privacy practices, and social features to encourage adoption, empowering older adults to use smart wearables for proactive health management.…”
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Exploring Pregnancy-Related Information-Sharing Behavior Among First-Time Southeast Asian Fathers: Qualitative Semistructured Interview Study by Kidung Ageng, Anushia Inthiran

“…Furthermore, health practitioners should take a more proactive approach in engaging with first-time fathers, as currently there is a communication gap between them.…”
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The Cortical Spatial Responses and Decoding of Emotion Imagery Toward a Novel fNIRS-Based Affective BCI by Xiaopeng Si, Yumeng Han, Sicheng Li, Shuai Zhang, Dong Ming

“…This holds clinical value for expressing emotions in patients with neurological impairments and serves as a proactive emotion regulation method. However, the fNIRS features of emotion imagery for affective BCI and the discriminability of different emotion categories remain unclear. …”
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