Increasing effort without noticing: A randomized controlled pilot study about the ergogenic placebo effect in endurance athletes and the role of supplement salience. by Ellen K Broelz, Sebastian Wolf, Patrick Schneeweiss, Andreas M Niess, Paul Enck, Katja Weimer

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Study and application of the energy unit cutting theory and punching-blasting synergy permeability enhancement technology in tectonic anomaly areas of coal mines by Jingyu JIANG, Xiaobin DONG, Mintao WEI, Chenghao WANG, Yuanping CHENG, Xiaoning SHI

“…The unit cutting effectively increases the length of the energy-resistant zone in front of the mining work and reduces the risk of operation in the low-high energy transition zone. ④ A numerical model was constructed based on the fluid-solid coupling algorithm to simulate the synergistic effect of controlled directional energy-focused blasting and punching holes. …”
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Tracking extinction risk trends and patterns in a mega-diverse country: A Red List Index for birds in Colombia. by Luis Miguel Renjifo, Angela María Amaya-Villarreal, Stuart H M Butchart

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Medical care costs of cancer in the last year of life using national health insurance data in Korea. by Mihai Park, Inmyung Song

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Genomic and Transcriptomic Profiles in Smokers and Never-Smokers Lung Squamous Cell Carcinoma Patients by Canale M, Virga A, Angeli D, Fonzi E, Gnetti L, Dubini A, Tedaldi G, Urbini M, Bocchialini G, Petracci E, Verlicchi A, Cravero P, Citarella F, Bennati C, Andrikou K, Delmonte A, Crinò L, Carbognani P, Ulivi P, Ampollini L

“…Enrichment analyses showed that cyclin-dependent protein Ser/Thr kinase activity and PI3K signaling pathways were affected in both groups, while cellular damage response was exclusively altered in never-smokers. …”
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Circadian rhythm abnormalities and autonomic dysfunction in patients with Chronic Fatigue Syndrome/Myalgic Encephalomyelitis. by Trinitat Cambras, Jesús Castro-Marrero, Maria Cleofé Zaragoza, Antoni Díez-Noguera, José Alegre

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Random Natural Gradient by Ioannis Kolotouros, Petros Wallden

“…Hybrid quantum-classical algorithms appear to be the most promising approach for near-term quantum applications. …”
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Leveraging machine learning for analyzing the nexus between land use and land cover change, land surface temperature and biophysical indices in an eco-sensitive region of Brahmani-... by Bhaskar Mandal

“…SVM performed moderately, while CART and MD algorithms struggled to perform in this study. …”
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Comparison of Machine Learning and Statistical Approaches of Detecting Anomalies Using a Simulation Study by Klaudia Lenart

“…Implications and recommendations: For the statistical methods included in the study, knowledge about the distribution of the variables was crucial while the supervised machine learning algorithms required acquiring a training dataset. …”
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Distribution and sources of fallout ¹³⁷Cs and ^239+240Pu in equatorial and Southern Hemisphere reference soils by G. Dicen, G. Dicen, F. Guillevic, S. Gupta, P.-A. Chaboche, P.-A. Chaboche, P.-A. Chaboche, K. Meusburger, P. Sabatier, O. Evrard, C. Alewell

“…Our machine learning algorithm identified the precipitation of the coldest quarter, longitude, and latitude as the strongest predictors of the <span class="inline-formula">¹³⁷</span>Cs inventory. …”
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Determining optimal strategies for primary prevention of cardiovascular disease: a synopsis of an evidence synthesis study by Olalekan A Uthman, Lena Al-Khudairy, Chidozie Nduka, Rachel Court, Jodie Enderby, Seun Anjorin, Hema Mistry, G J Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…A machine learning study developed a parallel Convolutional Neural Network algorithm with 96.4% recall and 99.1% precision for study screening. …”
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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…These advancements also make education more inclusive, helping to bridge accessibility gaps for underserved communities. However, while AI has the potential to improve education significantly, it also introduces challenges, such as ethical concerns, data privacy risks, and algorithmic bias. …”
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Engineering and Technological Advancements in Repetitive Transcranial Magnetic Stimulation (rTMS): A Five-Year Review by Abigail Tubbs, Enrique Alvarez Vazquez

“…A structured review of peer-reviewed studies from 2019 to 2024 focused on technological and clinical advancements in rTMS, including AI-driven personalized treatments, portable devices, and integrated BCIs. AI algorithms have optimized patient-specific protocols, while portable devices have expanded access. …”
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The Integration of Educational Robotics and Artificial Intelligence in Learning AI Concepts by Mohammed FAKIRI, Mohamed KHALDI

“…The integration of these technologies allows students to better understand algorithms and increases their interest in STEM fields. …”
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Improving The Performance of Big Data Databases by Nzar Abdulqadir Ali, Dashne Raouf Arif

“…In SQL (Structured Query Language) databases different algorithms are used for inserting and updating data, such as indexing, bulk insert and multiple updating. …”
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Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

“…Our PEIoT-DS approach offers a reliable intrusion detection system for IoT networks while maintaining privacy.…”
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The effect of lipid accumulation product and its interaction with other factors on hypertension risk in Chinese Han population: A cross-sectional study. by Jian Song, Yingying Zhao, Sumei Nie, Xue Chen, Xuesen Wu, Jing Mi

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Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Ten machine learning (ML) algorithms were applied to construct multi-task prediction models. …”
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Automatic identification of clinically important Aspergillus species by artificial intelligence-based image recognition: proof-of-concept study by Chi-Ching Tsang, Chenyang Zhao, Yueh Liu, Ken P. K. Lin, James Y. M. Tang, Kar-On Cheng, Franklin W. N. Chow, Weiming Yao, Ka-Fai Chan, Sharon N. L. Poon, Kelly Y. C. Wong, Lianyi Zhou, Oscar T. N. Mak, Jeremy C. Y. Lee, Suhui Zhao, Antonio H. Y. Ngan, Alan K. L. Wu, Kitty S. C. Fung, Tak-Lun Que, Jade L. L. Teng, Dirk Schnieders, Siu-Ming Yiu, Susanna K. P. Lau, Patrick C. Y. Woo

“…While morphological examination is the most widely used for Aspergillus identification in clinical laboratories, PCR–sequencing and MALDI–TOF MS are emerging technologies in more financially-competent laboratories. …”
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Endothelial cell activation is attenuated by everolimus via transcriptional and post-transcriptional regulatory mechanisms after drug-eluting coronary stenting. by Zsolt Fejes, Zsolt Czimmerer, Tibor Szük, Szilárd Póliska, Attila Horváth, Enikő Balogh, Viktória Jeney, Judit Váradi, Ferenc Fenyvesi, György Balla, István Édes, József Balla, János Kappelmayer, Béla Nagy

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