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

“…Future capsules will feature AI-driven lesion detection and therapeutic functions, higher-resolution imaging, wider fields of view, controllable movement bringing the concept of "swallowing the gastroenterologist" closer to reality. …”
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Adult education and training for the development of problem-solving skills by I. A. Korshunov, S. V. Lubnikov, N. N. Shirkova

“…Currently, the presence of employees with developed basic skills of working with textual and numerical information can no longer explain how effectively a person functions in society and the professional sphere. This is due to the rapid transformation of the innovative economy and the renewal of production technologies and business processes. …”
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Monitoring Abiotic Stressors in Rainfed Vineyards Involves Combining UAV and Field Monitoring Techniques to Enhance Precision Management by Federico Valerio Moresi, Pasquale Cirigliano, Andrea Rengo, Elena Brunori, Rita Biasi, Giuseppe Scarascia Mugnozza, Mauro Maesano

“…However, precise vineyard management is a crucial component of adaptation strategies aimed at optimizing resource efficiency, which is essential for sustainable farming practices. …”
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Signatures of Rapidly Rotating Stars with Chemically Homogeneous Evolution in the First Galaxies by Boyuan Liu, Yves Sibony, Georges Meynet, Volker Bromm

“…We find that the rest-frame UV luminosity of star-forming galaxies can be significantly enhanced by a factor of  ∼3−6 when CHE stars above a minimum initial mass of ${m}_{\star ,\min }^{\mathrm{CHE}}\sim 2-10\,{M}_{\odot }$ account for more than half of the total stellar mass following a Salpeter initial mass function. As a result, the UV luminosity functions observed at z  ∼ 12−16 can be reproduced with less extreme values of star formation efficiency and UV luminosity stochastic variability. …”
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Codesign of Transmit Waveform and Receive Filter with Similarity Constraints for FDA-MIMO Radar by Qiping Zhang, Jinfeng Hu, Xin Tai, Yongfeng Zuo, Huiyong Li, Kai Zhong, Chaohai Li

“…Finally, the Riemannian limited-memory Broyden–Fletcher–Goldfarb–Shanno (RL-BFGS) algorithm is employed to optimize the variables in parallel. Simulation results demonstrate that our method achieves a 0.6 dB improvement in SINR compared to existing methods while maintaining competitive computational efficiency. …”
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Algorithm for Dynamic Reactive Power Optimization of Regional Power Grid Based on Interior Point Method and Neighborhood Search Decoupling Dynamic Programming Method by Jie ZHANG, Hengfeng WANG, Shengchun LIU, Huabiao WANG, Canghai WANG, Yao RAN, Xianmin WANG, Yongfei MA, Wei YAN

“…The two-stage method could not only ensure the quality of the optimal solution, but also avoid solving the state combination explosion problem with discrete variables, which greatly improves the computational efficiency. …”
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Development and validation of a novel prediction model for osteoporosis: from serotonin to fat-soluble vitamins by Jinpeng Wang, Lianfeng Shan, Jing Hang, Hongyang Li, Yan Meng, Wenhai Cao, Chunjian Gu, Jinna Dai, Lin Tao

“…Stepwise discriminant analysis was performed to identify efficient predictors for osteoporosis. The prediction model was developed based on Bayes and Fisher’s discriminant functions, and validated via leave-one-out cross-validation. …”
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Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures by Shi Guanghui, Bao Yuhao, Wu Wenhua, Guo Guiqiang, Lin Ye, Zhang Xiaopeng, Tao Ran

“…To efficiently analyze and optimize the structural performance of rudder structures, a parametric optimization model for the radial configuration of reinforcement ribs is constructed. …”
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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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Robust Optimization Research of Cyber–Physical Power System Considering Wind Power Uncertainty and Coupled Relationship by Jiuling Dong, Zilong Song, Yuanshuo Zheng, Jingtang Luo, Min Zhang, Xiaolong Yang, Hongbing Ma

“…Furthermore, the deterministic power balance constraints are relaxed into inequality constraints that account for wind power forecasting errors through fuzzy variables. The lower-level model focuses on minimizing traffic load shedding by establishing a topology–function-constrained information network traffic model based on the maximum flow principle in graph theory, thereby improving the efficiency of network flow transmission. …”
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Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model by Moses Oluwatobi Fajobi, Olumuyiwa Ajani Lasode, Adekunle Akanni Adeleke, Peter Pelumi Ikubanni, Ayokunle Olubusayo Balogun, Prabhu Paramasivam

“…The Gaussian membership function (Gauss-mf) was implemented for the fuzzification of input variables, while the hybrid algorithm was selected for the learning and mapping of the input-output dataset. …”
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Retrieval of carbon and inorganic phosphorus during hydrothermal carbonization: ANN and RSM modeling by Abolfazl Shokri, Mohammad Amin Larki, Ahad Ghaemi

“…Next, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were used to compare the results and improve the model fit. …”
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Support vector regression model for the prediction of buildings’ maximum seismic response based on real monitoring data by Dongwang Tao, Shizhe Fang, Haixu Liu, Jianqi Lu, Jiang Wang, Qiang Ma

“…Our results demonstrate that SVR-MDR model outperform other machine learning models such as kernel ridge regression and decision tree models, and SVR-MDR and RSVR-MDR models outperform conventional loglinear regression and multinomial models, because SVR can map the complex nonlinear function of multiple variables and consider the available information of buildings especially the fundamental frequency. …”
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Accurate Sugarcane Detection and Row Fitting Using SugarRow-YOLO and Clustering-Based Spline Methods for Autonomous Agricultural Operations by Guiqing Deng, Fangyue Zhou, Huan Dong, Zhihao Xu, Yanzhou Li

“…This model introduces the WTConv convolutional modules to expand the sensory field and improve computational efficiency, adopts the iRMB inverted residual block attention mechanism to enhance the modeling capability of crop spatial structure, and uses the UIOU loss function to effectively mitigate the misdetection and omission problem in the region of dense and overlapping targets. …”
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Biomechanical Analysis of <i>Camellia oleifera</i> Branches for Optimized Vibratory Harvesting by Rui Pan, Ziping Wan, Mingliang Wu, Shikui Lu, Lewei Tang

“…The nonlinear least squares method, based on the hyperbolic tangent function, was employed to fit the bending load–deflection curves of the branches. …”
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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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Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer by Chiara Furio, Luciano Lamberti, Catalin I. Pruncu

“…The proposed SHGWJA was tested very successfully in seven “real-world” engineering optimization problems taken from various fields, such as civil engineering, aeronautical engineering, mechanical engineering (included in the CEC 2020 test suite on real-world constrained optimization problems) and robotics; these problems include up to 14 optimization variables and 721 nonlinear constraints. Two representative mathematical optimization problems (i.e., Rosenbrock and Rastrigin functions) including up to 1000 variables were also solved. …”
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Safety Assessment of Loop Closing in Active Distribution Networks Based on Probabilistic Power Flow by Wenchao Cai, Yuan Gao, Xiping Zhang, Qin Si, Jiaoxin Jia, Bingzhen Li

“…By modeling DGs and loads as random variables, their cumulants are efficiently obtained through LHS. …”
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Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction by Min-Juan Zeng, Yan-Quan Liu, Ping Pang, Xiao-Jun Chen, He Huang, Rui-Na Huang, Shi-Sen Li, He-Hui Zhang, Yue Yin, Chang-Sen Wang, Jin-Da Lin, Lin Lin, Shao-Peng Chen, Li Xu, Liang-Qing Zhang

“…Conclusion The newly constructed function [f (Hcy-Hb)], integrating Hcy and Hb levels, exhibits robust diagnostic and prognostic value in CRS. …”
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Investigating the relationship between the monetary policy shock through the exchange rate channel on the management quality index in the banking system: by examining the productiv... by Farhad Sharifi Bagha, Jafar Haqiqat, Zahra Karimi Takanloo

“…During this time, the number of changes in the target variables by the variables themselves decreases and the changes in the variables caused by the shock of the exchange rate channel increase. …”
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