Predictive estimations of health systems resilience using machine learning by Alessandro Jatobá, Paula de Castro-Nunes, Paloma Palmieri, Omara Machado Araujo de Oliveira, Patricia Passos Simões, Valéria da Silva Fonseca, Paulo Victor Rodrigues de Carvalho

“…It was shown that expanding these capacities enhances overall resilience. This research highlights the potential of ML in predictive modeling to inform strategic health decision-making, targeting interventions and more effective resource allocation. …”
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Autonomous platform for solution processing of electronic polymers by Chengshi Wang, Yeon-Ju Kim, Aikaterini Vriza, Rohit Batra, Arun Baskaran, Naisong Shan, Nan Li, Pierre Darancet, Logan Ward, Yuzi Liu, Maria K. Y. Chan, Subramanian K.R.S. Sankaranarayanan, H. Christopher Fry, C. Suzanne Miller, Henry Chan, Jie Xu

“…Abstract The manipulation of electronic polymers’ solid-state properties through processing is crucial in electronics and energy research. Yet, efficiently processing electronic polymer solutions into thin films with specific properties remains a formidable challenge. …”
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Liquid-liquid equilibrium data prediction using large margin nearest neighbor by mohsen pirdashti, kamyar movagharnejad, silvia Curteanu, Florin Leon, Farshad Rahimpour

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Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance by Goksu Tuysuzoglu, Yunus Dogan, Elife Ozturk Kiyak, Mustafa Ersahin, Bita Ghasemkhani, Kokten Ulas Birant, Derya Birant

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Extended homogeneous field correction method based on oblique projection in OPM-MEG by Fulong Wang, Fuzhi Cao, Yujie Ma, Ruochen Zhao, Ruonan Wang, Nan An, Min Xiang, Dawei Wang, Xiaolin Ning

“…Subspace projection algorithms are widely used in MEG to suppress noise. …”
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Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe by Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
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Harnessing Machine Learning for Intelligent Networking in 5G Technology and Beyond: Advancements, Applications and Challenges by Kristi Dulaj, Abdulraqeb Alhammadi, Ibraheem Shayea, Ayman A. El-Saleh, Mohammad Alnakhli

“…By leveraging ML algorithms, 5G networks can forecast user behavior, allocate resources optimally, and dynamically adjust to changing conditions, enhancing performance and dependability. …”
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Castleman Disease: Insights from a Case Series and Literature Review by Jerin James, Sanudev Sadanandan Vadakke Puthiyottil, Johan George, Arathi Edayattil, Vivek Mathew James, Swapna Dominic, Supriya N. K.

“…By integrating clinical experiences with literature, it advocates for refined diagnostic criteria and context-specific therapeutic algorithms, urging further research to address gaps in managing this complex disease.…”
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Continuum Robots: Current Trends in Design, Control, and Applications by Marina Kalekeyeva, Zarina Konakbay, Meiramgul Imanbekova, Aliya Shakbutova, Olga Garmash, Gulzhan Muratbekova, Doszhan Mambetalin

“…The presence of a multi-segmented and malleable structure makes continuum robot (CR) promising for use in medicine, industry, space, and deep-sea research. This trend encourages researchers worldwide to create fundamentally new types of continuously deformable CR structures suitable for various applications and delicate manipulations. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…The proposed approach employs Decision Tree (DT) algorithms to uncover patterns linked to service failures. …”
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Drone Navigation and Target Interception Using Deep Reinforcement Learning: A Cascade Reward Approach by Ali A. Darwish, Arie Nakhmani

“…Unlike the traditional methods relying on complex controllers, our approach uses deep reinforcement learning with cascade rewards, enabling a single drone to navigate obstacles and intercept targets using only a forward-facing depth–RGB camera. This research has significant implications for robotics, as it demonstrates how complex tasks can be tackled using deep reinforcement learning. …”
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MMPred: a tool to predict peptide mimicry events in MHC class II recognition by Filippo Guerri, Filippo Guerri, Valentin Junet, Valentin Junet, Judith Farrés, Xavier Daura, Xavier Daura, Xavier Daura

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Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management by Thein Oak Kyaw Zaw, Kalaiarasi Sonai Muthu Anbananthen, Saravanan Muthaiyah, Baarathi Balasubramaniam, Suraya Mohammad, Yunus Yusoff, Khairul Shafee Kalid

“…The framework leverages enterprise architecture principles to integrate learning algorithms, image detection, and systematic plantation mapping within a structured approach that enhances data organization, rust severity visualization, and predictive analysis. …”
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A Novel Dataset for Experimentation With Intrusion Detection Systems in SCADA Networks Using IEC 60870-5-104 Standard by M. Agus Syamsul Arifin, Deris Stiawan, Bhakti Yudho Suprapto, Susanto, Tasmi Salim, Mohd Yazid Idris, Mohamed Shenify, Rahmat Budiarto

“…This dataset aims to support further research and development of robust IDS solutions for SCADA systems.…”
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A Survey of Data Stream-Based Intrusion Detection Systems by Rodrigo Sanches Miani, Gustavo Di Giovanni Bernardo, Guilherme Weigert Cassales, Hermes Senger, Elaine Ribeiro de Faria

“…Advances in the field have led to the development of several algorithms that approach the problem under the view of a data stream machine learning task. …”
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A Pilot Study: Sleep and Activity Monitoring of Newborn Infants by GRU-Stack-Based Model Using Video Actigraphy and Pulse Rate Variability Features by Ádám Nagy, Zita Lilla Róka, Imre Jánoki, Máté Siket, Péter Földesy, Judit Varga, Miklós Szabó, Ákos Zarándy

“…While vital signs are routinely monitored, the previously mentioned assessments require labor-intensive direct observation. Research so far has already introduced non- and minimally invasive solutions. …”
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Optimizing solar energy utilization in facilities using machine learning-based scheduling techniques: A case study by Hussam J. Khasawneh, Waseem M. Al-Khatib, Zaid A. Ghazal, Ahmad M. Al-Hadi, Zaid M. Arabiyat, Osama Habahbeh

“…Our approach overcomes these limitations by employing ML algorithms to accurately predict solar generation patterns, enabling more efficient scheduling of electrical appliances. …”
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A comparative assessment of reference genes in mouse brown adipocyte differentiation and thermogenesis in vitro by Trang Huyen Lai, Jin Seok Hwang, Quang Nhat Ngo, Dong-Kun Lee, Hyun Joon Kim, Deok Ryong Kim

“…This study focused on identifying suitable reference genes for mouse brown adipocyte research, utilizing brown adipocytes from the Ucp1-luciferase ThermoMouse model. …”
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Decoding Schizophrenia: How AI-Enhanced fMRI Unlocks New Pathways for Precision Psychiatry by Valeria Di Stefano, Martina D’Angelo, Francesco Monaco, Annarita Vignapiano, Vassilis Martiadis, Eugenia Barone, Michele Fornaro, Luca Steardo, Marco Solmi, Mirko Manchia, Luca Steardo

“…Moreover, ethical considerations surrounding data integrity, algorithmic transparency, and patient individuality must guide AI’s integration into psychiatry. …”
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Metrology of Multicarrier-Based Delay-Doppler Channel Sounding for Sub-THz Frequencies by Jonas Gedschold, Diego Dupleich, Sebastian Semper, Michael Dobereiner, Alexander Ebert, Giovanni Del Galdo, Reiner S. Thoma

“…Developing channel models typically requires aggregating channel measurements and the corresponding extracted propagation parameters from different research institutions to form a sufficiently large data basis. …”
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