Forecasting Delivery Time of Goods in Supply Chains Using Machine Learning Methods by V. K. Rezvanov, O. M. Romakina, E. V. Zaytseva

“…Introduction. Trade development requires the implementation of artificial intelligence and machine learning technologies to improve the accuracy of delivery forecasts. …”
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Morphometric analysis and hydrological implications of the Himalayan River Basin, Goriganga, India, using Remote Sensing and GIS techniques by Parvaiz Ahmad Ganie, Ravindra Posti, Garima, Kishor Kunal, Nityanand Pandey, Pramod Kumar Pandey

“…Thirty-two watersheds within the river basin were delineated to calculate linear, areal, and relief morphometric parameters, covering a total drainage area of 2,183.11 km2. The drainage pattern, primarily dendritic to sub-dendritic, is shaped by the region's topography, geological structure, and precipitation patterns. …”
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Categorical Cross-Recurrence Quantification Analysis Applied to Communicative Interaction during Ainsworth’s Strange Situation by Danitza Lira-Palma, Karolyn González-Rosales, Ramón D. Castillo, Rosario Spencer, Andrés Fresno

“…This procedure is used for assessing children’s attachment quality during early stages of their development. Many studies have demonstrated that communicative interactions share features with complex dynamic systems. …”
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Advances in application of ultrasound in diagnosis of diabetic nephropathy by GUO Juan, YANG Zhifang, JI Ri

“…In DN patients, shear wave velocity (SWV) exhibits a characteristic pattern of "initial increase followed by decrease", which may correlate with histopathological staging. …”
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Fluid Dynamics Exploration in Molten Salt Reactors: A Comprehensive Study of Draining Tank Using the Moving Particle Semi-Implicit Method by Yacobus Yulianto, Asril Pramutadi Andi Mustari, Muhammad Rizqie Arbie

“…Results reveal a consistent discharge pattern across all fluids, characterized by an initial rapid flow phase followed by gradual stabilization. …”
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Modeling Visual Fatigue in Remote Tower Air Traffic Controllers: A Multimodal Physiological Data-Based Approach by Ruihan Liang, Weijun Pan, Qinghai Zuo, Chen Zhang, Shenhao Chen, Sheng Chen, Leilei Deng

“…The model achieved an average balanced accuracy of 0.92 and an F1 score of 0.90 under 12-fold cross-validation, demonstrating excellent predictive performance. The high-ranking features spanned four modalities, revealing typical physiological patterns of visual fatigue across ocular behavior, cortical activity, autonomic regulation, and arousal level. …”
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Spatial and temporal evolution characteristics of apple carbon emissions in China, 1991–2020 by Qiangqiang Zhang, Xixi Gao, Yujie Hu, Zhongwei He, Xiaojing Li

“…Abstract Articulating the spatial and temporal features of apple carbon emissions in China across different years and areas is critical for developing an appropriate and acceptable apple carbon reduction program. …”
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A two phase ensembled deep learning approach of prominent gene extraction and disease risk prediction by Prajna Paramita DEBATA, Alakananda TRIPATHY, Pournamasi PARHI, Smruti Rekha DAS

“… Unlocking novel insights from gene expression of individual patient profiles, clinicians and researchers can discern patterns, biomarkers, and therapies. Moreover, accurate classification enables the development of predictive models for prognosis and treatment response, facilitating personalized medicine approaches. …”
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A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting by Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen

“…Achieving this objective necessitates the development of highly accurate river water level forecasts. …”
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Understanding EMS response times: a machine learning-based analysis by Peter Hill, Jakob Lederman, Daniel Jonsson, Peter Bolin, Veronica Vicente

“…Advanced ML techniques, including Gradient Boosting models, were applied to evaluate the influence of diverse variables such as call handling times, travel times, weather patterns, and resource availability. Feature engineering was employed to extract meaningful insights, and statistical models were used to validate the relationships between key predictors and response times. …”
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BCTDNet: Building Change-Type Detection Networks with the Segment Anything Model in Remote Sensing Images by Wei Zhang, Jinsong Li, Shuaipeng Wang, Jianhua Wan

“…We first construct a dual-feature interaction encoder that employs SAM to extract image features, which are then refined through trainable multi-scale adapters for learning architectural structures and semantic patterns. …”
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Lightweight Deep Learning Model for Fire Classification in Tunnels by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…This model integrates MobileNetV3 for spatial feature extraction, Temporal Convolutional Networks (TCNs) for temporal sequence analysis, and advanced attention mechanisms, including Convolutional Block Attention Modules (CBAMs) and Squeeze-and-Excitation (SE) blocks, to prioritize critical features such as flames and smoke patterns while suppressing irrelevant noise. …”
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Monitoring and deformation of deep excavation engineering based on DFOS technology and hybrid deep learning by Yanli Peng, Jie Zhao, Yijiang Fan, Cheng Fan

“…Concurrently, as neural network models find application and development in deep excavation displacement prediction, traditional models face challenges such as insufficient accuracy and weak generalization capabilities, failing to meet the high-precision warning demands of practical engineering. …”
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SOPHROLOGY, PSYCHOSOMATICS, DEONTOLOGY AND CREATIVITY by Miroslav Prstačić

“…In this context, culture can be considered as a way of life that encompasses beliefs and religiosity, rituals and various arts (music, theatre, poetry, painting, dance…) mentality and patterns of historically transmitted symbols. At the same time, speech is marked by all physical, psychosomatic, psycho-emotional and spiritual manifestations and is the origin of hermeneutics itself. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…Advanced predictive models like logistic Regression and XGBoost analyze critical variables, identify patterns, and perform predictive analysis. These models can identify potential impactions, assess impaction type, and develop treatment plans. …”
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Diagnostics and treatment of gastroesophageal reflux disease: clinical guidelines of the Russian gastroenterological association by V. T. Ivashkin, I. V. Mayev, I. . A.s. Trukhmanov, Ye. K. Baranskaya, O. B. Dronova, O. V. Zayratyants, R. G. Sayfutdinov, A. A. Sheptulin, T. L. Lapina, S. S. Pirogov, Yu. A. Kucheryavy, O. A. Storonova, D. N. Andreyev

“…The treatment of GERD has to be individualized according to the pattern and severity of clinical symptoms. The goal of treatment is symptom relief, at erosive esophagitis - healing of erosions and complication prevention, at Barret's esophagus - prophylaxis of disease progression and dysplasia and adenocarcinoma development. …”
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Spatial Heterogeneity and Temporal Stability of Baseflow Stream Chemistry in an Urban Watershed by Claire Welty, Joel Moore, Daniel J. Bain, Mahdad Talebpour, John T. Kemper, Peter M. Groffman, Jonathan M. Duncan

“…Longitudinal spatial patterns differed across constituents for each survey, but the pattern for each constituent varied little across synoptics. …”
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A Multi-Agent and Attention-Aware Enhanced CNN-BiLSTM Model for Human Activity Recognition for Enhanced Disability Assistance by Mst Alema Khatun, Mohammad Abu Yousuf, Taskin Noor Turna, AKM Azad, Salem A. Alyami, Mohammad Ali Moni

“…Thus, we developed an ensemble activity recognition model, namely “Attention-CNN-BiLSTM with selective ML”. …”
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Sound and mechanical impedance behaviors observed in multifunctional modular bio-inspired lattice metamaterials by Shiyi Wang, Xi Wang, Ruixian Qin, Qijian Li, Bingzhi Chen

“…Recent advancements in decoupled design, additive manufacturing, and optimization technology have led to the development of multifunctional metamaterials. A layered multifunctional bio-inspired lattice metamaterial (MBLM) is presented in this work, drawing on inspiration from the body armor of glyptodonts and the structural features of turtle shells. …”
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Mapping China Aquaculture Ponds: Integrating a New Aquaculture Index With Machine Learning by JianChun Chen, Chen Lin, Kun Xue, Ke Song, ZhiGang Cao, RongHua Ma, DanHua Ma, YiJun Tong

“…Abstract Aquaculture Pond (AP) plays a vital role in ensuring food security, driving economic development, conserving resources, and maintaining ecological balance. …”
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