Avaliação comparativa e evolutiva dos protocolos de atendimento dos pacientes fissurados Comparative and evolutive evaluation of attendance protocols of patients with clef lip and... by Nivaldo Alonso, Daniela Yukie Sakai Tanikawa, Jonas Eraldo de Lima Junior, Marcus Castro Ferreira

“…Eight surgical categories were related, palate repair (35.18%) was the most utilized one, followed by lip repair (unilateral and bilateral), keeping the same distribution pattern. Secondary procedures had persisted with high rates (approximately 30%), however the number of complications decreased (no fistulae). …”
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Multiple sclerosis mortality trends in Spain from 1981 to 2020 by L. Cayuela, A. de Albóniga-Chindurza, S. Gómez Enjuto, J. Lapeña-Motilva, S. Sainz de la Maza, A. González García, A. Cayuela

“…Age-standardised mortality rates (ASMR) and trend analysis were performed using joinpoint regression software. …”
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Clinical characteristics of obsessive-compulsive disorder comorbid with obsessive -compulsive personality disorder: subtype implications by Ayse Dondu, Levent Sevincok

“…The severity of current OC symptoms was assessed using the Yale–Brown Obsessive Compulsive Scale (Y-BOCS), while depressive symptoms were measured with the Hamilton Depression Rating Scale (HDRS). Anxiety symptoms were also evaluated using the Hamilton Anxiety Rating Scale (HARS).ResultsAmong 148 OCD patients, 58.8% met the diagnostic criteria for OCPD. …”
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SOH Estimation Method for Lithium-Ion Batteries Using Partial Discharge Curves Based on CGKAN by Shengfeng He, Wenhu Qin, Zhonghua Yun, Chao Wu, Chongbin Sun

“…Next, a SOH estimation framework based on the CGKAN model is developed, where 1-Dimensional-Convolutional Neural Networks (1D-CNN) are used to extract deep features from the original data, Bidirectional Gated Recurrent Unit (BiGRU) captures the bidirectional dependencies of the time series, and Kolmogorov–Arnold Networks (KAN) enhances the modeling of complex nonlinear features through its nonlinear mapping capabilities, thereby improving the accuracy of SOH estimation. …”
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Development of oculomotor digital biomarkers using clinical examinations as “Ground Truth” by Brittany Trotter, Melissa Hunfalvay, Melissa Hunfalvay, Nicholas P. Murray, Greg C. Mathews, Frederick Robert Carrick, Frederick Robert Carrick, Frederick Robert Carrick, Frederick Robert Carrick

“…A board-certified neurologist with 16 years of experience also conducted an oculomotor examination to mirror eye movement patterns.ResultsData analysis included a series of single-block logistic regressions to examine the scoring of the six eye-tracking tests (RightEye, LLC) to predict clinician-rated eye movement classifications (i.e., normal or abnormal). …”
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Valley-filling Potential Evaluation of Urban Public Charging Stations Based on Price Incentive by Dawei SU, Yihui FAN, Tianhui ZHAO, Hongjin PAN, Youhui HUANG, Gang WANG, Yongyong JIA

“…Then, the typical load characteristic indicators including valley-period and flat-period load rates are proposed, and the charging load valley-filling potential evaluation parameters are introduced to carry out valley-filling potential evaluation of urban public charging stations. …”
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Gut Microbiota Contribute to Heterosis for Growth Trait and Muscle Nutrient Composition in Hybrid Largemouth Bass (<i>Micropterus salmoides</i>) by Jixiang Hua, Qingchun Wang, Yifan Tao, Hui Sun, Siqi Lu, Yan Zhuge, Wenhua Chen, Kai Liu, Jie He, Jun Qiang

“…Growth, digestive enzyme activity, and muscle nutrient composition were compared between the hybrid groups (NC and CN) and the purebred groups (NN and CC), and the gut microbiota was investigated. The heterosis rates of body length, body height, and body thickness in hybrid largemouth bass were statistically significant. …”
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Global psychiatrists' opinions about hikikomori from biopsychosocial perspectives: International case vignette survey by Marcus P. J. Tan, Kohei Hayakawa, Yukako Nakagami, Victor Pereira‐Sanchez, Seon Cheol Park, Yong Chon Park, Seok Woo Moon, Tae Young Choi, Yu‐Tao Xiang, Kang Sim, Toru Horinouchi, Ajit Avasthi, Sandeep Grover, Roy Abraham Kallivayalil, Yugesh Rai, Mohammadreza Shalbafan, Pavita Chongsuksiri, Pichet Udomratn, Samudra T. Kathriarachchi, Afzal Javed, Mian‐Yoon Chong, Tan Chay‐Hoon, Toshiya Inada, Toshiya Murai, Tomohiro Nakao, Shigenobu Kanba, Shih‐Ku Lin, Norman Sartorius, Naotaka Shinfuku, Takahiro A. Kato

“…Most respondents felt the case could be treated by an outpatient visit, while others preferred hospitalization. Psychotherapy was rated highly as an intervention; Iran, South Korea, and “others” also rated pharmacotherapy highly. …”
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AEMS: Adaptive Ensemble GNNs for Multibehavior Stream Recommendation by Ritchie Natuan Caibigan, Punyaphol Horata, Pusadee Seresangtakul

“…The AEMS synergizes long-term preference patterns (derived from historical interactions) with real-time user intents and item attributes (captured through multibehavior signals), integrating them via an adaptive ensemble neural gating mechanism. …”
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Development of approaches to the evaluation of pharmacotherapy effectiveness for chronic hepatitis C by I. A. Narkevich, E. A. Tsitlionok

“…Objective: to analyse the consumption pattern of antiviral therapy (AVT) for chronic hepatitis C on the example of an infectious hospital.Material and methods. …”
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Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels by Zeping Yang, Zhikai Cheng, Da Wu

“…The methodology incorporates quadratic exponential smoothing for outlier mitigation, followed by sequential feature extraction using convolutional neural networks (CNNs) and bidirectional gated recurrent units (GRUs). Comparative experiments demonstrate the model’s superiority over conventional architectures including RNN, LSTM, GRU, and CNN-GRU. …”
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Forecasting Sales in Live-Streaming Cross-Border E-Commerce in the UK Using the Temporal Fusion Transformer Model by Qi Zhang, Xue Li, Pengbin Gao

“…Our multimodal approach integrates diverse time series data, including historical sales, key opinion leader (KOL) influence, and seasonal patterns. The Temporal Fusion Transformer (TFT) model demonstrated consistently lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Squared Error (MSE) across all forecasting horizons compared to other machine learning approaches, including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Gated Recurrent Unit(GPU)-accelerated architectures. …”
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A clustering-based federated deep learning approach for enhancing diabetes management with privacy-preserving edge artificial intelligence by Xinyi Yang, Juan Li

“…We develop tailored models that enhance prediction accuracy by clustering patients based on carbohydrate (CHO) intake patterns. Utilizing Simple Recurrent Neural Network (SimpleRNN) and Gated Recurrent Unit (GRU) methods, the study evaluates the performance of local patients who contribute to training the cluster and global (non-cluster) models. …”
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Anomaly Detection in Network Traffic via Cross-Domain Federated Graph Representation Learning by Yanli Zhao, Zongduo Liu, Junjie Pang

“…Traditional detection approaches typically rely on statistical features while overlooking the interaction patterns and structural dependencies among traffic flows. …”
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Disentangling the roles of natural variability and climate change in Canada’s 2023 fire season by Clair Barnes, Piyush Jain, Theodore R Keeping, Nathan Gillett, Jonathan Boucher, Philippe Gachon, Dorothy Heinrich, Megan Kirchmeier-Young, Yan Boulanger

“…We find that the annual accumulated daily severity rating (DSR), a measure of weather-related fire risk) is increasing in most ecozones in response to global warming, with the largest increases in the early months of the fire season; although temperatures are increasing everywhere, this effect is offset in some regions by increased precipitation. …”
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Deep Temporal and Structural Embeddings for Robust Unsupervised Anomaly Detection in Dynamic Graphs by Samir Abdaljalil, Hasan Kurban, Rachad Atat, Erchin Serpedin, Khalid Qaraqe

“…We introduce Temporal Structural Graph Anomaly Detection (<sc>T-StructGAD</sc>), an unsupervised framework that leverages Graph Convolutional Gated Recurrent Units (<monospace>GConvGRU</monospace>s) and Long Short-Term Memory networks (<monospace>LSTM</monospace>s) to jointly model both structural and temporal dynamics in graph node embeddings. …”
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Levels and types of physical activity in Russia according to the ESSE-RF study: is there a trace of the COVID-19 pandemic? by M. B. Kotova, S. A. Maksimov, S. A. Shalnova, A. V. Kontsevaya, Yu. A. Balanova, A. E. Imaeva, V. A. Kutsenko, G. A. Muromtseva, N. S. Karamnova, S. E. Evstifeeva, A. V. Kapustina, O. A. Litinskaya, M. S. Pokrovskaya, E. B. Yarovaya, T. V. Repkina, T. O. Gonoshilova, A. V. Kudryavtsev, N. I. Belova, L. L. Shagrov, M. A. Samotrueva, A. L. Yasenyavskaya, E. N. Chernysheva, S. V. Glukhovskaya, I. A. Levina, E. A. Shirshova, E. B. Dorzhieva, E. Z. Urbanova, N. Yu. Borovkova, V. K. Kurashin, A. D. Tokareva, Yu. I. Ragino, G. I. Simonova, A. D. Khudyakova, V. N. Nikulin, O. R. Aslyamov, G. V. Khokhlova, A. V. Solovyova, A. A. Rodionov, O. V. Kryachkova, Yu. Yu. Shamurova, I. V. Tantsyreva, I. N. Baryshnikova, M. G. Ataev, M. O. Radjabov, M. M. Isakhanova, M. A. Umetov, L. V. Elgarova, I. A. Khakuasheva, E. I. Yamashkina, M. V. Esina, T. A. Kunyaeva, A. M. Nikitina, N. V. Savvina, Yu. E. Spiridonova, E. A. Naumova, A. A. Keskinov, V. S. Yudin, S. M. Yudin, O. M. Drapkina

“…Compared to the urban population, rural residents have higher physical activity rates (23,9 vs 20,3%, p&lt;0,001). The proportion of people with high physical activity is also higher among people with higher income levels (p&lt;0,001). …”
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Coping and positive mental health in Canada among youth and adults: findings from a population-based nationally representative survey by Mihojana Jhumi, Laura L. Ooi, Karen C. Roberts, Melanie Varin

“…MethodsWe analyzed data from the 2019 Canadian Community Health Survey on the self-rated ability of adults and youth (N = 60 643; 12+ years) to cope with unexpected or difficult problems and day-to-day demands along with three PMH outcomes: selfrated mental health (SRMH), happiness and life satisfaction. …”
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Evaluating the efficacy of Internet-Based Exercise programme Aimed at Treating knee Osteoarthritis (iBEAT-OA) in the community: a study protocol for a randomised controlled trial by Abhishek Abhishek, Sameer Akram Gohir, Paul Greenhaff, Ana M. Valdes

“…The participants will be assessed using a Numerical Rating Scale, the Western Ontario and McMaster Universities Osteoarthritis Index, the Arthritis Research UK Musculoskeletal Health Questionnaire, the Pittsburgh Sleep Quality Index, 30 s sit to stand test, timed up and go test, quantitative sensory testing, musculoskeletal ultrasound scan, muscle thickness assessment of the vastus lateralis, and quadriceps muscles force generation during an isokinetic maximum voluntary contraction (MVC). …”
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Subjective Performance Expectations From and Demographic and Categorical Differences in the Acceptance of Virtual Reality or AI Technologies in Rehabilitation Programs: Cross-Secti... by Guido Waldmann, Dominik Raab

“…A significant rank correlation was observed for 103 out of 105 pairwise comparisons of the therapeutic fields, with distinct patterns of effects sizes within the chosen categories. …”
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