A multi-objective robust possibilistic programming approach to designing sustainable and reliable closed-loop supply chain network (case study: aluminum industry) by Sajad Amirian, Maghsoud Amiri, Mohammad Taghi Taghavifard

“…The sensitivity analysis of the demand parameter showed that the proposed model achieved more economic profit, less social responsibility, and less reliability with increasing demand.Originality/Value: The variability of the justified decision space in the Me criterion has helped to solve the supply chain network design problem more flexibly and closer to reality through the possibility of exchange between the objective function and the risk-taking level of the managers.…”
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Assessing the Accuracy and Reliability of the Monitored Augmented Rehabilitation System for Measuring Shoulder and Elbow Range of Motion by Samuel T. Lauman, Lindsey J. Patton, Pauline Chen, Shreya Ravi, Stephen J. Kimatian, Sarah E. Rebstock

“…Accurate range of motion (ROM) assessment is essential for evaluating musculoskeletal function and guiding rehabilitation, particularly in pediatric populations. …”
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On the added value of sequential deep learning for the upscaling of evapotranspiration by B. Kraft, B. Kraft, B. Kraft, J. A. Nelson, S. Walther, F. Gans, U. Weber, G. Duveiller, M. Reichstein, W. Zhang, M. Rußwurm, D. Tuia, M. Körner, Z. Hamdi, M. Jung

“…</p> <p>When using only meteorological covariates, we found that the sequential models (LSTM and TCN) performed better (each with a Nash–Sutcliffe efficiency (NSE) of 0.73) than the instantaneous models (FCN and XGBoost), both with an NSE of 0.70, in site-level cross-validation at the hourly scale. …”
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Cardiometabolic risk factors in predicting obstructive coronary artery disease in patients with non-ST-segment elevation acute coronary syndrome by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, E. D. Emtseva, A. A. Vishnevskiy

“…The predictors of this model were 7 categorical (total cholesterol (CS) ≥5,9 mmol/L, low-density lipoprotein cholesterol &gt;3,5 mmol/L, waist-to-hip ratio ≥0,9, waist-to-height ratio ≥0,69, atherogenic index ≥3,4, lipid accumulation product index ≥38,5 cm*mmol/L, uric acid ≥356 pmol/L) and 2 continuous (high density lipoprotein cholesterol and insulin resistance index) variables.Conclusion. The developed algorithm for selecting predictors made it possible to determine their significant predictive threshold values and weighting coefficients characterizing the degree of influence on endpoints. …”
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Influence of Migratory Strategy, Group Size, and Environmental Conditions on the Movements of Caribou in Eastern Alaska by Kyle Joly

“…Migration is a diverse behavior exhibited by a wide array of organisms. Variability in the type of movements is rooted in their purpose, environmental factors, demographics, and individual physiological condition. …”
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Mobile machine design through dynamic load simulation on their drive units by S. A. Partko, L. M. Groshev, A. N. Sirotenko

“…The root cause for the occurrence of vibration effects is the profile irregularity of the mobile machine path, and the variability of physicomechanical characteristics of the soil. …”
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Intelligent Field Sensor Station for Monitoring Agrophysical Parameters and Phenotyping in Precision Agriculture System by S. A. Vasilyev, S. Ye. Limonov, S. A. Mishin

“…(Results and discussion) The intelligent field sensor station successfully demonstrated its efficiency, confirming both its functionality and reliability in simultaneous data collection. …”
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Observational partitioning of water and CO₂ fluxes at National Ecological Observatory Network (NEON) sites: a 5-year dataset of soil and plant components for spatial... by E. Zahn, E. Bou-Zeid

“…<p>Long-term time series of transpiration, evaporation, plant net photosynthesis, and soil respiration are essential for addressing numerous research questions related to ecosystem functioning. However, quantifying these fluxes is challenging due to the lack of reliable and direct measurement techniques, which has left gaps in the understanding of their temporal cycles and spatial variability. …”
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Artificial intelligence Defect Detection Robustness inReal-time Non-Destructive Testing of Metal Surfaces by Chaoyu Dong, Jovian Sanjaya Putra, Andrew A. Malcolm

“… Artificial intelligence (AI) is revolutionizing defect detection by employing advanced computational techniques to enhance accuracy and efficiency. Through machine learning methods and deep neural networks, it is possible for AI systems to learn from diverse datasets and accurately identify defects across various applications. …”
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Genome-wide association study of blood vitamin D metabolites and bone remodelling markers in pigs by Dipanwita Paul, Michael Oster, Siriluck Ponsuksili, Klaus Wimmers, Henry Reyer

“…Hence, mineral utilization efficiency might be indirectly improved which remains to be empirically demonstrated through further research.…”
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Reliability of radiomic analysis on multiparametric MRI for patients affected by autosomal dominant polycystic kidney disease by Francesca Lussana, Ettore Lanzarone, Giulia Villa, Alfonso Mastropietro, Anna Caroli, Elisa Scalco

“…The impact of segmentation variability on radiomic reproducibility was assessed through Intraclass Correlation Coefficients (ICC), and a preliminary correlation analysis with relevant clinical parameters, such as age and eGFR, was also performed. …”
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The accuracy of a simple, low-cost GPS data logger/receiver to study outdoor human walking in view of health and clinical studies. by Bénédicte Noury-Desvaux, Pierre Abraham, Guillaume Mahé, Thomas Sauvaget, Georges Leftheriotis, Alexis Le Faucheur

“…<h4>Introduction</h4>Accurate and objective measurements of physical activity and lower-extremity function are important in health and disease monitoring, particularly given the current epidemic of chronic diseases and their related functional impairment.…”
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Feasibility, reliability and validity of smartphone administered cognitive ecological momentary assessments in breast cancer survivors by Ashley M. Henneghan, Ashley M. Henneghan, Emily W. Paolillo, Kathleen M. Van Dyk, Kathleen M. Van Dyk, Oscar Y. Franco-Rocha, Mansi Patel, So Hyeon Bang, Raeanne C. Moore

“…Test–retest reliability was examined using intraclass correlation coefficients for each cognitive EMA (tests and self-report questions), and Pearson's correlation was used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive variables.Results105 breast cancer survivors completed the EMA protocol with high adherence (87.3%) and high satisfaction (mean 87%). …”
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Hierarchical GraphCut Phase Unwrapping Based on Invariance of Diffeomorphisms Framework by Xiang Gao, Xinmu Wang, Zhou Zhao, Junqi Huang, Xianfeng David Gu

“…The resulting label maps are fused via majority voting to efficiently and robustly estimate the unwrapped phase count <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> at each pixel, using an odd number of votes to break ties. …”
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AER-Net: Attention-Enhanced Residual Refinement Network for Nuclei Segmentation and Classification in Histology Images by Ruifen Cao, Qingbin Meng, Dayu Tan, Pijing Wei, Yun Ding, Chunhou Zheng

“…Moreover, the coarse predictions and refined predictions are combined by using a loss function that employs cross-entropy loss and generalized dice loss to efficiently tackle the challenge of class imbalance among nuclei in histology images. …”
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Drying kinetics and thermodynamic analysis; enhancing quinoa (Chenopodium quinoa Willd.) quality profile via pre-treatments assisted germination and processing by Jabir Khan, Palwasha Gul, Qingyun Li, Kunlun Liu

“…Principal Component Analysis revealed significant correlations between analyses, explaining 80.37 % variability. The intensity of functional groups decreased in the infrared spectra, although the transmission of signals was greater in pretreated samples than in control. …”
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Emerging Healthcare Technologies in Gastrointestinal Endoscopy: 75 Years of Evolution by Irina Florina CHERCIU HARBIYELI, Elena Daniela BURTEA, Vlad IOVANESCU, Dan Nicolae FLORESCU, Ion ROGOVEANU, Dan Ionut GHEONEA, Adrian SAFTOIU

“…Machine learning algorithms assist in real-time polyp detection, classification, and predictive analytics, enhancing diagnostic accuracy while reducing inter-observer variability and human error. Machine learning is advancing rapidly, but clinical implementation faces challenges, such as algorithm validation, interpretability, and regulatory concerns. …”
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Novel variant alters splicing of TGFB2 in family with features of Loeys-Dietz syndrome by Emily R. Gordon, Stephanie A. Felker, Stephanie A. Felker, Tanner F. Coleman, Tanner F. Coleman, Nadiya Sosonkina, Jada Pugh, Jada Pugh, Meagan E. Cochran, Meagan E. Cochran, Anna C. E. Hurst, Sara J. Cooper

“…Significant clinical variability has been noted for both related and unrelated individuals with the same pathogenic variant. …”
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Prediction of 5-year survival in patients with heart failure and implanted cardiac resynchronization therapy devices by A. M. Soldatova, V. A. Kuznetsov, E. A. Gorbatenko, T. N. Enina, L. M. Malishevsky

“…All variables were scored based on the в-coefficients. …”
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Natural Diversity of <i>Crataegus monogyna</i> Jacq. in Northeastern Türkiye Encompassing Morphological, Biochemical, and Molecular Features by Bora Erkek, Mehmet Yaman, Ahmet Sümbül, Serap Demirel, Fatih Demirel, Ömer Faruk Coşkun, Ahmet Say, Barış Eren, Adnan Aydin, Ayten Eroglu

“…The Jaccard similarity coefficient ranged from 0.04 (M9 and M16) to 0.63 (M17 and M3), indicating substantial genetic variability. …”
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