Enhancing Volume Precision in Breast Reconstruction: A BMI-Based Model for Predicting Flap Weight in Profunda Artery Perforator Flaps by Charalampos Varnava, Shaghayegh Gorji, Sascha Wellenbrock, Tobias Hirsch, Maximilian Kückelhaus, Philipp Wiebringhaus

“…The average BMI observed was 23.0, while the mean flap weight was 304.2 g. The predictive model for flap weight was determined as follows: flap weight (g) = (19.252 × BMI) − 143.572. …”
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Viewpoint Selection for 3D Scenes in Map Narratives by Shichuan Liu, Yong Wang, Qing Tang, Yaoyao Han

“…The chaotic particle swarm optimization (CPSO) algorithm is utilized to locate the viewpoint position while maximizing the fitness function, identifying a viewpoint meeting narrative and visual salience requirements. …”
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Nanoparticles Enhanced Laser-Induced Breakdown Spectroscopy for Characterisation and Discrimination of Gemstones by Al-Juboori Haider, Haider Zhaib, Hang Wei, Roslan Sufi

“…Results have shown a significant enhancement in spectral features, i.e., the emergence of several new spectral lines of major gemstone elements in the UV-Vis regions of the NELIBS spectra, while the CLIBS spectra were devoid of any meaningful spectral information. …”
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Mechanistic insights into synergistic effects using coupled PK-PD modeling by Jinzhou Sun, Qianqian Chen, Chumeng Zhuang, Xiaohong Li, Li Yu, Weifeng Jin

“…The model also showed that CA had a larger apparent volume of distribution and clearance in rats, while HSYA had a shorter mean retention time and elimination half-life. …”
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Toward Adaptive Unsupervised and Blind Image Forgery Localization with ViT-VAE and a Gaussian Mixture Model by Haichang Yin, KinTak U, Jing Wang, Wuyue Ma

“…Second, we introduce convolutional neural networks (CNNs) to adaptively estimate the mixing coefficients, enabling an end-to-end architecture while significantly lowering computational costs. …”
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A Deep Reinforcement Learning-Based Resource Scheduler for Massive MIMO Networks by Qing An, Santiago Segarra, Chris Dick, Ashutosh Sabharwal, Rahman Doost-Mohammady

“…As such, it is critical for the base station to schedule a suitable group of users in each time and frequency resource block to achieve maximum spectral efficiency while adhering to fairness constraints among the users. …”
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Lightweight underwater object detection method based on multi-scale edge information selection by Shaobin Cai, Xin Zhou, Wanchen Cai, Liansuo Wei, Yuchang Mo

“…As a result, the YOLO algorithm has been widely applied in underwater object detection. …”
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A Novel Machine Learning Model for the Automated Diagnosis of Nasal Pathology in Canine Patients by Andreea Istrate, Radu Constantinescu, Lithicka Anandavel, Shraddha Rajeshkumar Tandel, Simon Dye, Charlotte Dye

“…Computed tomography (CT) is the imaging method of choice for evaluating the canine nasal cavity, being invaluable in determining disease extent, guiding sampling, and planning treatment. While predictions of pathology type can be made, there is significant overlap between CT changes noted in neoplastic, inflammatory, and infectious nasal disease. …”
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Recurrent Neural-Based Vehicle Demand Forecasting and Relocation Optimization for Car-Sharing System: A Real Use Case in Thailand by Peerapon Vateekul, Panyawut Sri-iesaranusorn, Pawit Aiemvaravutigul, Adsadawut Chanakitkarnchok, Kultida Rojviboonchai

“…Finally, the Minimum Cost Maximum Flow algorithm is deployed to maximize forecasted demands, while minimizing the amount of relocations. …”
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Bottom Plate Damage Localization Method for Storage Tanks Based on Bottom Plate-Wall Plate Synergy by Yunxiu Ma, Linzhi Hu, Yuxuan Dong, Lei Chen, Gang Liu

“…The investigation revealed that guided wave signals processed through data matching effectively preserved damage echo signals while substantially attenuating boundary scattering signals. …”
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Employing a Mixture of Rayleigh and Inverse Gaussian Distributions as SAR Clutter Texture Model in MAP Estimation for Efficient Speckle Suppression by Dheeren Ku Mahapatra, Saurav Gupta, Biswajit Jena, Ravi Prakash Dwivedi

“…We estimate the RIG mixture model parameters by maximum likelihood (ML) with the expectation maximization (EM) algorithm. We also obtain the Crámer-Rao Bounds (CRBs) for these estimators. …”
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Multimodal Fusion Multi-Task Learning Network Based on Federated Averaging for SDB Severity Diagnosis by Songlu Lin, Renzheng Tang, Yuzhe Wang, Zhihong Wang

“…A shared feature extractor is combined with task-specific heads to enable joint diagnosis, while the FedAvg algorithm is employed to facilitate decentralized training across multiple institutions without sharing raw data, thereby preserving privacy and addressing non-IID challenges. …”
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Robust Co-planning of Water-Energy Nexus for Industrial Parks by Zhisong LIU, Tao WANG, Yan FENG, Xiaoyang LIU, Ning GAO, Cheng WANG

“…The column and constraint generation algorithm is used to solve the robust programming model. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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A Robust InSAR-DEM Block Adjustment Method Based on Affine and Polynomial Models for Geometric Distortion by Zhonghua Hong, Ziyuan He, Haiyan Pan, Zhihao Tang, Ruyan Zhou, Yun Zhang, Yanling Han, Jiang Tao

“…The experimental results indicate that elevation errors across different study areas were reduced by approximately 50% to 5%, while the relative planar accuracy improved by around 93% to 17%. …”
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Hybrid active-passive thermal management system for deep wells: Long-term stability and multi-objective optimization by Zongwei Yao, Haomin Li, Hongxu Xu, Hongfei Yang, Qiushi Bi, Tianshuang Xu

“…A multi-objective optimization framework combining Kriging surrogate modeling and NSGA-II algorithm is developed to maximize heat transfer coefficient (h) while minimizing pressure drop (P). …”
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Molecular Identification and Phylogenetic Trees Reconstruction of Blue Swimming Crabs (Decapoda: Portunidae) from Pangpang Bay, Banyuwangi by Sapto Andriyono, Reza Istiqomatul Hidayah, Laksmi Sulmartiwi, Andi Aliah Hidayani, Md. Jobaidul Alam

“…The phylogenetic tree and genetic distance calculations were carried out using Mega X software through the Neighbor-Joining (NJ) Algorithm with the addition of several sequences from the NCBI online database. …”
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Early Detection of Surface Mildew in Maize Kernels Using Machine Vision Coupled with Improved YOLOv5 Deep Learning Model by Yu Xia, Ao Shen, Tianci Che, Wenbo Liu, Jie Kang, Wei Tang

“…In this study, a deep learning YOLOv5s algorithm based on machine vision technology was employed to develop a maize seed surface mildew detection model and to enhance its portability for deployment on additional mobile devices. …”
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Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sl... by Yasmine M Mohamed, José Mancera, Andreas Brandenberg, Stefan Fischli, Michael M Havranek

“…Machine learning (ML) models were built using a tree-based ensemble algorithm to detect hypoglycemic events registered by CGMS. …”
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Physics-informed modeling and process optimization of friction stir welding of AA7075-T6 with a zinc interlayer by Dejene Alemayehu Ifa, Dame Alemayehu Efa, Naol Dessalegn Dejene, Sololo Kebede Nemomsa

“…The ANN model yielded an extremely low prediction error of 0.973 %, while the validation through FEA showed an accuracy with only 1.79 % deviation. …”
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