Clustering Library Loan Books Using K-Means Clustering by Mawar Indah Tanjung, Sriani Sriani

“…This study aims to classify books based on borrowing patterns to provide insights into library collection management. …”
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The Neural Basis of Salt Perception: A Focus on Potassium Chloride as a Sodium Alternative by Emilia Iannilli, Raffaela Fürer, Antje Welge-Lüssen, Thomas Hummel

“…High-density EEG data revealed distinct microstate patterns associated with each condition, particularly in the later stages of processing, which align with the endogenous phases of taste perception. …”
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Optimizing jacket design for two-wheeler delivery workers during rainy conditions by Sujin Lim, Jisoo Ha

“…Also riders to make as many deliveries as possible and receive good ratings, most work more than 8 h. This complex work environment and long working hours expose them to physical fatigue, scrapes, bumps, falls, and other accidents, making it more necessary than ever to pay attention to the health and safety of delivery riders. …”
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Who underreports smoking on birth records: a Monte Carlo predictive model with validation. by Thomas G Land, Anna S Landau, Susan E Manning, Jane K Purtill, Kate Pickett, Lauren Wakschlag, Vanja M Dukic

“…Our results illustrate non-uniform patterns of underreporting of smoking during pregnancy among different populations. …”
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Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm by Chandragandhi S, Arvind C, Srihari K

“…Experimental evaluations demonstrate TANEA’s superior performance over traditional methods, achieving improved accuracy, reduced computational overhead, and faster convergence rates. The algorithm’s adaptability to various biomedical data patterns enables more effective real-time monitoring and decision-making in IoT-based healthcare environments. …”
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Joint estimation of hand-foot-mouth disease model and prediction in korea using the ensemble kalman filter. by Wasim Abbas, Sieun Lee, Sangil Kim

“…The implications of our findings suggest a notable shift in transmission and recovery rates, starting in 2015.<h4>Discussion</h4>The model successfully predicted the peak and magnitude of HFMD outbreaks occurring between June and December, closely matching the observed epidemic patterns. …”
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Regional Pathways to Internationalization: The Role of Erasmus+ in European HEIs by Eleni Georgoudaki, Spyridon Stavropoulos, Dimitris Skuras

“…Employing hotspot analysis and a two-level random intercept model, this research analyses spatial patterns and the influences of regional characteristics and institutional variables on Erasmus mobility rates. …”
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A Comprehensive Assessment of Ayurvedic Patient Care Services in a Modern Medicine Public Tertiary Care Hospital by Renuka Munshi, Santosh Kadam

“…Over five years patient retention rates exhibited a gradual increase signifying a higher level of patient satisfaction and loyalty towards Ayurvedic treatments. …”
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Transdiagnostic body dissatisfaction: comparing adolescents with anorexia nervosa and depression during body exposure by Valeska Stonawski, Lena Sasse, Laura Derks, Gunther H. Moll, Oliver Kratz, Tanja Legenbauer, Stefanie Horndasch

“…BD was assessed with questionnaires; valence ratings were obtained for different body parts. Emotion ratings and gaze patterns towards the own body were assessed during each session via rating scales and eye-tracking. …”
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Variations in healthcare utilization for mental health problems prior to suicide by socioeconomic status: a Norwegian register-based population study by Carine Øien-Ødegaard, Solveig Tobie Glestad Christiansen, Lars Johan Hauge, Kim Stene-Larsen, Sissel Marguerite Bélanger, Espen Bjertness, Anne Reneflot

“…Notably, the SES groups exhibit heterogeneity, with gendered patterns. Targeted interventions for low consultation rates among employed men, and men with high income and lower education are needed, while women, and men in at-risk groups, such as the non-employed and those with low income, demonstrate higher mental healthcare utilization, warranting comprehensive suicide prevention measures.…”
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Accurate hourly AQI prediction using temporal CNN-LSTM-MHA+GRU: A case study of seasonal variations and pollution extremes in Visakhapatnam, India by Sreenivasulu T, Mokesh Rayalu G

“…The framework amalgamates one-dimensional Convolutional Neural Networks (1D CNN) for the extraction of short-term patterns, Long Short-Term Memory (LSTM) integrated with Multi-Head Attention (MHA) to encapsulate long-term dependencies, and Gated Recurrent Unit (GRU) for the refinement of residual errors. …”
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Integrated OVMD-BiGRU-SMAC Framework for Forecasting Construction Accidents in the Kingdom of Saudi Arabia by Badr T. Alsulami, Afaq Khattak

“…These IMFs are individually forecasted using Bidirectional Gated Recurrent Unit (BiGRU) models, which are capable of learning sequential patterns in both temporal directions. …”
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Memory-augment graph transformer based unsupervised detection model for identifying performance anomalies in highly-dynamic cloud environments by Huangyining Gao, Ruyue Xin, Peng Chen, Xi Li, Ning Lu, Peng You

“…Additionally, we introduce a novel dynamic gated memory module to guide the Transformer encoder in extracting hidden features, thereby enhancing the model’s robustness to varying data patterns in dynamic cloud environments. …”
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Spatial and spatio-temporal analysis of cancer mortality in Iran: gender disparities and implications for health policy by Alireza Zangeneh, Arash Ziapour, Seyede Negin Hoseini, Babak Nazari, Homa Molavi, Farid Najafi, Ardeshir Khosravi, Reza Heidari Moghadam

“…The standard deviation ellipse indicated a transition in cancer mortality distribution from a northwest-southeast alignment in 2017 to predominantly western and eastern orientations in subsequent years, with varied hotspot patterns across Iran. Conclusions: The study highlights rising cancer mortality rates, particularly among men and premenopausal women, underscoring the need for targeted public health interventions and improved medical infrastructure to enhance prevention and treatment efforts.…”
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An Experimental Investigation on the Energy Signature Associated With Multiphase Flow in Porous Media Displacement Regimes by Shuangmei Zou, Dong Chen, Nong Kang, Congjiao Xie, Ryan T. Armstrong, Jianchao Cai

“…The findings highlight the importance of wettability and flow rates in determining the efficiency of fluid‐fluid displacement in porous media. …”
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Inflammatory Bowel Disease in Australasian Children and Adolescents by A. S. Day, D. A. Lemberg, R. B. Gearry

“…Many reports indicate increasing rates of inflammatory bowel disease, with data also showing changing patterns of this chronic disease in children and adolescents. …”
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Missing The Forest For The Trees: A Lack Of Upper Extremity Physical Performance Testing In Sports Physical Therapy by Matthew L Gauthier, Casey A Unverzagt, Luciana De Michelis Mendonça, Amee L Seitz

“…# Background Despite shoulder and elbow injuries being common in athletics, return to sport and reinjury rates are less than ideal. These outcomes may be driven by the absence of evidence-informed testing to determine an athlete's readiness for sport…”
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Occurrence and Genetic Variation of <i>Monolepta hieroglyphica</i> (Motschulsky, 1858) (Coleoptera: Chrysomelidae), a Newly Emerging Pest, Among Hosts in Northeast China by Wei Sun, Xiuhua Zhang, Jiachun Zhou, Yuebo Gao

“…High gene flow rates were observed, likely contributing to decreased genetic variation. …”
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Arrhythmia detection with transfer learning architecture integrating the developed optimization algorithm and regularization method by Fatma Akalın, Pınar Dervişoğlu Çavdaroğlu, Mehmet Fatih Orhan

“…In addition, since the ECG patterns in pediatric patients are different from the ECG patterns in adults, physicians consider it a difficult and complex task. …”
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Smart deep learning model for enhanced IoT intrusion detection by Faisal S. Alsubaei

“…This superb performance of the OSNN model can be explained by the careful optimization of hyperparameters like strong activation functions (ReLU, GeLU, LeakyReLU), learning rates, dropout rates, and regularization techniques that enable it to learn intricate intrusion patterns efficiently using various datasets. …”
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