Data-Driven Insights into LEED Certification Trends: Saudi Arabia's Path to Sustainability by Hala Sirror, Zeinab Alhassan, Malathe Hamid

“…It analyzes trends over the past decade, focusing on certification growth, building types, rating levels (Certified, Silver, Gold, Platinum), and regional distribution. …”
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Potential role of a cognitive rehabilitation program following left temporal lobe epilepsy surgery by Camila de Vasconcelos Geraldi, Sara Escorsi-Rosset, Pamela Thompson, Ana C. Gargaro Silva, Américo Ceiki Sakamoto

“…Changes in fMRI activation patterns were seen in the rehabilitation group over the long term. …”
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From Decline to Rebound: Analyzing the Dynamics of Fertility Trends in Sleman Regency Amid Global Shocks, 2018-2022 by Muhammad Arif Fahrudin Alfana

“…This quantitative study aims to examine the trends of live birth rates in Sleman Regency over a five-year period (2018-2022). …”
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The past, present, and future evolution of Aurora Subglacial Basin’s subglacial drainage system by Anna-Mireilla Hayden, Tyler Pelle, Christine F. Dow

“…Since subglacial drainage accounts for up to 70% of ice shelf melt, our results imply that subglacial hydrology could trigger higher rates of mass loss than previously suggested.…”
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Time series analysis of construction accidents in Saudi Arabia with consideration of COVID19 lockdown effects by Badr T. Alsulami

“…The analysis identifies recurring seasonal patterns, long-term trends, and quantifies the impact of the COVID-19 lockdown on accident rates. …”
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Pursuit of entertainment or self-expression? Research on adventure tourism by Mustafa Gülmez, Ayşe Nur Soysal, Naci Büyükdağ, Ayşegül Acar, Burak Türten, Cenk Murat Koçoğlu

“…Abstract This study explores the behavioral patterns of tourists in adventure tourism, focusing on the roles of push factors, self-image congruity, word-of-mouth (WOM), and intentions to revisit while considering the variations attributed to the rafting experience (first-time vs. repeated) and gender. …”
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Using the Active Faults of Eurasia Database for solving tectonic problems by D. M. Bachmanov, E. A. Zelenin, A. I. Kozhurin, V. G. Trifonov

“…This new database contains more than 30000 objects that are geographically linked, equipped with attributes of the kinematic type, estimated movement rates and activity confidence ranks. As an exam‐ ple, we consider processing of the data on several tectonic regions of the Alpine‐Himalayan mobile belt and construction of rose‐diagrams of faults for a comparative analysis of their Late Cenozoic kinematics. …”
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Subtle alteration in transcriptional memory governs the lineage-level cell cycle duration heterogeneities of mammalian cells by Kajal Charan, Sandip Kar

“…Herein, we perform a computational modeling study to demonstrate that correlated fluctuations of the inherited transcription rates during cell cycle progression and their random resetting in mitosis are sufficient to account for the experimentally observed cell cycle duration correlation patterns for cell lineage pairs. …”
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Examining Deep Learning Techniques for Ethical Artificial Intelligence: Cleansing Malicious Comments from Users by Ji Woong Yoo, Kyoung Jun Lee, Arum Park

“…Our findings demonstrate that deep learning models surpass CleanBot in accuracy and block rates for handling negative user comments, including malicious ones, enabling organizations to effectively manage such comments in online communities using AI-based methods. …”
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Gradience and optionality in the syntactic realization of focus by Silvio Cruschina, Laia Mayol

“…Casted as weighted soft constraints, they do not cause ungrammaticality when violated, but the greater their weight, the more unacceptable their violation becomes, which can explain the observed patterns.  …”
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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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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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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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Geospatial Analytics of Urban Bus Network Evolution Based on Multi-Source Spatiotemporal Data Fusion: A Case Study of Beijing, China by Xiao Li, Shaohua Wang, Liang Zhou, Yeran Sun, Jiayi Zheng, Chang Liu, Junyuan Zhou, Cheng Su, Dachuan Xu

“…By analyzing spatial coverage rates of transit stations using road network and administrative division data, the study reveals the convenience of bus networks in different regions. …”
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Analysis of influencing factors on recurrence and metastasis of pT1b ~ pT4aNOM0 esophageal squamous cell carcinoma after radical surgery in Northeast Sichuan region by Wenxia Ren, Lei Yu, Yu Cui, Daiyuan Ma

“…Abstract Background The incidence and mortality rates of esophageal cancer are high, yet public awareness of this disease remains low, particularly in the northeastern Sichuan region. …”
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The association between four dietary indices and mortality risk in cardiovascular disease patients by Mengshan Pan, Tongle Yin, Ying Yang, Feiyun Zhu, Jiamin Xu, Rucheng Chen, Weijun Zheng

“…Abstract Background The Planetary Healthy Diet Index-United States, the Healthy Diet Index, the Mediterranean Diet, and the Dietary Inflammation Index were linked to mortality rates in cardiovascular patients. This study investigated the relationship between these dietary patterns and all-cause mortality risk in U.S. cardiovascular patients from 2005 to 2006 to 2017–2018. …”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…Our machine learning approach established an activity threshold, above which divergent wavefront patterns—termed “significant sources”—predicted AF recurrence. …”
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Integrative single‐cell transcriptomic analysis deciphers heterogeneous characteristics of gastrointestinal tract cancer by Chuwen Sun, Tong Li, Xin Jin, Zhihui Xiu, Hang Su, Huanming Yang, Ming Liu, Kui Wu

“…Abstract Background Gastrointestinal tract cancer (GIC), including oesophageal cancer (EC), gastric cancer (GC) and colorectal cancer (CRC), is characterised with high global incidence and mortality rates, with similar tumourigenic processes. However, the common and heterogeneous molecular features among GIC at single‐cell level remain poorly characterised. …”
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Effect of attentional bias modification on pre-competition anxiety in athletes by Jing Zhao, Yuhan Yang, Heng Zhang, Yu Nie, Qiulin Wang

“…Attentional bias correction training (ABMT) aims to modify these attention patterns with the aim of alleviating anxiety symptoms. …”
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