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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Trajectory of GFR Decline and Fluctuation in Albuminuria Leading to End-Stage Kidney Disease in Patients With Biopsy-Confirmed Diabetic Kidney Disease by Masayuki Yamanouchi, Naoki Sawa, Tadashi Toyama, Miho Shimizu, Megumi Oshima, Yusuke Yoshimura, Hisashi Sugimoto, Shigekazu Kurihara, Yuki Oba, Daisuke Ikuma, Hiroki Mizuno, Akinari Sekine, Tatsuya Suwabe, Junichi Hoshino, Yoshifumi Ubara, Shigeko Hara, Kengo Furuichi, Takashi Wada

“…Among these patients, 91.6% exhibited a curvilinear pattern in their eGFR trajectory. The median coefficient of variation for ACR, representing the variability in ACR measurements, was 48.9 (interquartile range: 36.9, 68.2). …”
Get full text

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. …”
Get full text

Skin hyperspectral imaging and machine learning to accurately predict the muscular poly-unsaturated fatty acids contents in fish by Yi-Ming Cao, Yan Zhang, Qi Wang, Ran Zhao, Mingxi Hou, Shuang-Ting Yu, Kai-Kuo Wang, Ying-Jie Chen, Xiao-Qing Sun, Shijing Liu, Jiong-Tang Li

“…With the skin spectra of fish, five ML methods, including the extreme learning machine (ELM), random forest (RF), radial basis function (RBF), back propagation (BP), and least squares support vector machine (LS-SVM) methods, were used to predict the PUFAs and EPA + DHA contents. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography by Ziwei Zhu, Ke Fan, Shuyuan Zhang, Tingting Hu, Jingyi Li, Ze Zhao, Ye Jin, Shuyang Zhang

“…Abstract Cardiomyopathy often alters left ventricular geometry (LVG), impairing cardiac function. We developed a deep learning (DL) model to estimate left ventricular ejection fraction (LVEF) from echocardiographic images while accounting for LVG variability and assessed prognostic factors across LVG subtypes. …”
Get full text

Differentiation and correlation of regional uptake heterogeneity with cardiac dysfunction in biopsy-proven transthyretin amyloid cardiomyopathy using quantitative single-photon emi... by Masakazu Tsujimoto, Hideki Kawai, Shingo Tanahashi, Masayoshi Sarai, Yasuki Asada, Hideo Izawa

“…Polar maps were analyzed to assess local SUV distribution in patients with ATTR-CM. The coefficient of variation (COV) of myocardial uptake, difference score between the septum and lateral wall (%DS), base-to-apex variability, and total cardiac SUV were calculated and compared with echocardiographic parameters. …”
Get full text

GAN-based image prediction of maize growth across varieties and developmental stages by Xinyi Wang, Shilong Liu, Zhihao Wang, Zedong Geng, Weikun Li, Chengxiu Wu, Yingjie Xiao, Wanneng Yang, Lingfeng Duan

“…Results This article proposed a visualized growth prediction method based on an improved Pix2PixHD network, incorporating spatial attention mechanisms, an improved loss function, and a modified dropout strategy to enhance prediction accuracy and visual fidelity. …”
Get full text

A Comprehensive Performance Evaluation Method Based on Dynamic Weight Analytic Hierarchy Process for In-Loop Automatic Emergency Braking System in Intelligent Connected Vehicles by Dongying Liu, Wanyou Huang, Ruixia Chu, Yanyan Fan, Wenjun Fu, Xiangchen Tang, Zhenyu Li, Xiaoyue Jin, Hongtao Zhang, Yan Wang

“…At the criterion level, a bivariate variable–weight function, incorporating the vehicle speed and road surface adhesion coefficient, was developed to enable the dynamic coupling modeling of road environment parameters. …”
Get full text

Characterizing Performance on a Suite of English-Language NeuroUX Mobile Cognitive Tests in a US Adult Sample: Ecological Momentary Cognitive Testing Study by Emily W Paolillo, Jessica Bomyea, Colin A Depp, Ashley M Henneghan, Anunay Raj, Raeanne C Moore

“…The tests tapped the domains of executive function, processing speed, reaction time, recognition memory, and working memory. …”
Get full text

Engineering safe anti-CD19-CD28ζ CAR T cells with CD8a hinge domain in serum-free media for adoptive immunotherapy by Muthuganesh Muthuvel, Muthuganesh Muthuvel, Thamizhselvi Ganapathy, Trent Spencer, Sunil S. Raikar, Saravanabhavan Thangavel, Alok Srivastava, Alok Srivastava, Alok Srivastava, Sunil Martin

“…CARs are modular synthetic antigen receptors integrating the single-chain variable fragment (scFv) of an immunoglobulin molecule to the TCR signaling. …”
Get full text