FVPNet: A Fuzzy Visual Positioning Perception Network for Small Object Segmentation in Remote Sensing Images by Yu Yan, Jindong Xu, Qianpeng Chong, Guangyi Wei, Zhixiang Wang

“…Furthermore, grayscale variability intensifies boundary uncertainty, complicating accurate segmentation. …”
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Assessment of soil fertility and nutrient distribution for enhanced soil health and field management through an innovative approach by Amir Bostani, Amin Mohebbi Tafreshi, Mohammad Hosein Bijeh Keshavarzi

“…Total nitrogen ranged from 0.02% to 0.82%. Highly variable macronutrient variation coefficient. Thus, the critical limits for elements and physicochemical characteristics were 4.5, 6, 0.7, and 0.8 mg/kg. …”
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Animal welfare and biosecurity correlation in buffalo farm evaluated by ClassyFarm system by Domenico Vecchio

“…The two variables were positively correlated (Spearman’s Rho=0.501; p<0.001). …”
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Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction by Bohang Chen, Mingwei Hai, Gaojian Di, Bin Zhou, Qi Zhang, Miao Wang, Yanxiu Guo

“…The model utilizes the pile length, pile diameter, average effective vertical stress, and undrained shear strength as input variables, with the bearing capacity serving as the output variable. …”
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Combined Surfactant and Enzyme-Assisted Extraction of Pectin from Hawthorn (Crataegus monogyna Jacq.) Fruits by Anastasia E. Novikova, Liubov N. Skrypnik

“…The hawthorn pectin can be used to develop new functional products.…”
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Monitoring of Biodiversity in the Erbil Governorate -Iraq Using Remote Sensing Data by Shwan Othman Hussein, Daban Kadhim Omar, Karzan Ahmed Abdulwahid

“…Biologists don't even fully understand the basic organ-level functions of this system, so knowing how a system as complex as this one work and understanding its dynamics are crucial for effective conservation and management of its constituent ecosystems. …”
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Developing a novel layer network structure for a LSTM model to predict mean monthly river streamflow by Amin Gharehbaghi, Redvan Ghasemlounia, Shahaboddin Daneshvar, Farshad Ahmadi

“…For doing so, to select the most effective parameters on MRSF m , the Pearson’s correlation coefficient (PCC) and Cosine amplitude sensitivity (CAS) as features selection process are carried out for potential meteorological variables in the study area (i.e., average monthly temperature (T m ), evaporation (ET m ), and precipitation (P m )) and target (MRSF m ). …”
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End-to-End Stroke Imaging Analysis Using Effective Connectivity and Interpretable Artificial Intelligence by Wojciech Ciezobka, Joan Falco-Roget, Cemal Koba, Alessandro Crimi

“…The goal of this pipeline is to define an efficient brain representation for connectivity in stroke data derived from magnetic resonance imaging. …”
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Forecasting Electricity Production in a Small Hydropower Plant (SHP) Using Artificial Intelligence (AI) by Dawid Maciejewski, Krzysztof Mudryk, Maciej Sporysz

“…Renewable Energy Sources (RESs) are difficult to predict due to weather variability. Electricity production by a run-of-river SHP is marked by the variability related to the access to instantaneous flow in the river and weather conditions. …”
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High expression of SOX9 is a diagnostic and prognostic indicator of glioma by Libo Xu, Zhenhao Wang, Mao Li, Qingsong Li

“…Screening was performed by LASSO coefficients to select non-zero variables that satisfied the coefficients of lambda. min, and four genes were screened out. …”
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Nonlinear Creep Constitutive Model of Rock Considering Hardening Effect by Dipeng Zhu, Zhiyong Hu, Shuguang Zhang, Wei Qiu, Yijie Wang, Donglan Chen, Fan Mingzhuo, Shutian Zhao, Ye Sun, Wenbo Liu

“…To precisely capture the nonlinearity of rock creep and the law of accelerated deformation, a hardening function and a damage variable are introduced. Based on traditional rheological models, creep mechanisms, and damage laws, an accelerated creep constitutive model integrating hardening and damage effects is established. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…Based on the spectral principal components, three classifiers were built to classify the maturity level: support vector machine, backpropagation neural network, and radial basis function neural network. Excellent results with a classification accuracy of 100% were obtained. …”
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Approximation by interpolation spectral subspaces of operators with discrete spectrum by M.I. Dmytryshyn

“…Applications to spectral approximations of the regular elliptic operators with variable smooth coefficients in the space $L_q(\Omega)$ over an open bounded set $\Omega\subset\mathbb{R}^n$ and some self-adjoint ordinary elliptic differential operators in a bounded interval $\Omega=(a,b)$ are shown.…”
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Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

“…This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. …”
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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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Family Resilience and Its Influencing Factors Among Patients With Lung Cancer Based on Double ABC‐X Theoretical Framework by Ziyi Shen, Yan Fang, Chengcheng Li, Xin Luo, Junling Cui, Yanchang Liu, Jingfang Hong

“…Relationships between variables and pathways were also explored based on the Double ABC‐X as the theoretical framework. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…The results revealed a significant negative correlation between SWHC and the smoothed leaf spectral reflectance, with the best correlation coefficient was r = − 0.59. The use of third-order derivatives and logarithmic second-order derivatives further enhanced this correlation, yielding optimal coefficients of r = − 0.78 and r = − 0.72, respectively. …”
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Maximising Achievable Rate Using Intelligent Reflecting Surface in 6G Wireless Communication Systems by Afrin Jahan Eva, Md. Sahal, Rabita Amin, Muhammad R. A. Khandaker, Risala Tasin Khan, Faisal Tariq, ASM Ashraf Mahmud

“…Intelligent reflecting surface (IRS) is a promising technique which aims to shift the paradigm of uncontrollable wireless environment to a controllable one by adding the function of reconfigurability using multiple passive reflecting elements. …”
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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 mathematical model developed in this research is of mixed integer linear programming type, which is implemented in GAMS software to solve it and find Pareto optimal solutions.Findings: The accuracy of the overall performance of the proposed model has been evaluated with four examples (based on the coefficients of the objective functions) from a case study in the aluminium industry. …”
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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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