Drug Release Analysis and Optimization for Drug-Eluting Stents by Hongxia Li, Yihao Zhang, Bao Zhu, Jinying Wu, Xicheng Wang

“…The results demonstrate that the optimized design can efficiently improve the efficacy of drug deposition and penetration into the arterial walls.…”
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Experiments in globalisation, food security and land use decision making. by Calum Brown, Dave Murray-Rust, Jasper van Vliet, Shah Jamal Alam, Peter H Verburg, Mark D Rounsevell

“…Both outcomes are subject to the responses of individual land managers to economic and environmental stimuli, and these responses are known to be variable and often (economically) irrational. We investigate the consequences of stylised food security policies and globalisation of agricultural markets on land use patterns under a variety of modelled forms of land manager behaviour, including variation in production levels, tenacity, land use intensity and multi-functionality. …”
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eDNAjoint: An R package for interpreting paired or semi‐paired environmental DNA and traditional survey data in a Bayesian framework by Abigail G. Keller, Ryan P. Kelly

“…Abstract Environmental DNA (eDNA) sampling is increasingly used in surveys of species distribution as a potentially sensitive and efficient monitoring method. Yet access to modelling tools designed specifically for interpreting this new data type lags behind its ubiquity. …”
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Automated Geographic Information System Multi-Criteria Decision Tool to Assess Urban Road Suitability for Active Mobility by Bertha Santos, Sandro Ferreira, Pollyanna Lucena

“…As a result, a flexible and automated GIS-based tool was obtained to support urban space and mobility managers in the implementation of efficient measures compatible with each city’s scenario.…”
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Deep Reinforcement Learning With Dueling DQN for Partial Computation Offloading and Resource Allocation in Mobile Edge Computing by Ehzaz Mustafa, Junaid Shuja, Faisal Rehman, Abdallah Namoun, Mazhar Ali, Abdullah Alourani

“…The Dueling DQN alleviates the complexity of simultaneous offloading and resource allocation decisions, with each branch independently controlling a subset of the decision variables to scale efficiently with an increasing number of IoT devices, thereby avoiding the combinatorial explosion of potential actions. …”
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An Optimization Strategy for Generator Start-up Sequence After Blackouts Considering the Cyber System Fault by Mingming LI, Lei SUN, Yinghao MA

“…An optimal start-up sequence model of generators is proposed with the expectation of maximum power systems’ total generation as objective function, and taking into account the constraints including the start-up time constraint of generator units, the auxiliary variables constraint related to the cyber system fault, and the start-up power constraint of generator units. …”
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Effects of two types of repetitive transcranial magnetic stimulation on brain network in Parkinson’s disease by Shuo Liu, Shuo Yang, Chen Wang, Jiarui Li, Lei Wang

“…The iTBS group showed post-treatment changes involving more brain regions in spatiotemporal variability. This study demonstrates that compared to 10Hz-rTMS, iTBS can reduce treatment time while providing superior improvement in functional brain connectivity for PD patients.…”
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Genome Microscale Heterogeneity among Wild Potatoes Revealed by Diversity Arrays Technology Marker Sequences by Alessandra Traini, Massimo Iorizzo, Harpartap Mann, James M. Bradeen, Domenico Carputo, Luigi Frusciante, Maria Luisa Chiusano

“…However, scant information is available for these species in terms of genome organization, gene function, and regulatory networks. Consequently, genomic tools to assist breeding are meager, and efficient exploitation of these species has been limited so far. …”
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Revolutionizing Lung Segmentation with Machine Learning: A Critical Review of Techniques in Medical Imaging by Momina Aisha, Moazma Ijaz, Nimra Tariq, Sehar Anjum, Sidra Siddiqui, Usman Hashmi

“…Techniques such as X-rays, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET) play essential roles in identifying the physical and functional aspects of the lungs. Manual lung segmentation by radiologists, while adjustable, is time-consuming and subject to variability. …”
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ETHNOPEDAGOGICAL COMPONENT OF PHYSICAL TRAINING OF SCHOOLCHILDREN by M. M. Kolokoltsev

“…The following indexes were calculated: Pignet’s index that defines proportionality of development and strength of a constitution; vital and power indexes. The efficiency of the ethnopedagogical technologies included in the program of physical training came to light by means of the quantitative and qualitative analysis of the obtained experimental data. …”
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Energy management of microgrid coalitions considering renewable energy prediction based on machine learning algorithms by Negar Dehghani Mahmoudabadi, Mehran Khalaj, Davood Jafari, Ali Taghizadeh Herat, Parisa Mousavi Ahranjani

“…First, a systematic management framework is established by defining the functions of various management units throughout the multi-microgrid system. …”
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Adaptive Exploration Artificial Bee Colony for Mathematical Optimization by Shaymaa Alsamia, Edina Koch, Hazim Albedran, Richard Ray

“…The performance of AEABC was evaluated against 33 state-of-the-art metaheuristics across twenty-five benchmark functions and an engineering application. AEABC consistently outperformed its counterparts, demonstrating superior efficiency and accuracy. …”
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SDKU-Net: A Novel Architecture with Dynamic Kernels and Optimizer Switching for Enhanced Shadow Detection in Remote Sensing by Gilberto Alvarado-Robles, Isac Andres Espinosa-Vizcaino, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes

“…Additionally, the model’s efficient training process, requiring only 75 epochs, highlights its potential for resource-constrained applications. …”
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Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

“…One of the critical innovations within this design is a class of trainable activation functions that eliminate the need for traditional weight parameters, thereby providing scalable and computationally efficient solutions. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…This approach improved the accuracy and robustness of structural parameter identification while maintaining computational efficiency.MethodsMOMDBA is an enhanced version of the Directional Bat Algorithm （DBA）， a swarm intelligence optimization technique inspired by the echolocation behavior of bats. …”
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Distributionally Robust Variational Quantum Algorithms With Shifted Noise by Zichang He, Bo Peng, Yuri Alexeev, Zheng Zhang

“…We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. …”
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Predicting heat transfer Performance in transient flow of CNT nanomaterials with thermal radiation past a heated spinning sphere using an artificial neural network: A machine learn... by S.R. Mishra, P.K. Pattnaik, Rupa Baithalu, P.K. Ratha, Subhajit Panda

“…An efficient heat transfer phenomenon using nanofluid have greater challenges in various industries, engineering application the recent trend. …”
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Multimodality Data Integration in Epilepsy by Otto Muzik, Diane C. Chugani, Guangyu Zou, Jing Hua, Yi Lu, Shiyong Lu, Eishi Asano, Harry T. Chugani

“…Moreover, an effort was made to derive quantitative variables (such as the spatial proximity index, SPI) characterizing the relationship between complementing modalities on a more generic level as a prerequisite for efficient data mining strategies. …”
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Multi-Scale Multi-Domain Hybrid Finite Element Modeling of Light Propagation by Jingwei Wang, Zhanwen Wang, Lida Liu, Yuntian Chen

“…We revisit finite element method of modeling multi-scale photonic/electromagnetic devices via the proposed beam basis function, in combination with domain decompositions. …”
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Gross Tonnage-Based Statistical Modeling and Calculation of Shipping Emissions for the Bosphorus Strait by Kaan Ünlügençoğlu

“…These EPA-estimated values served as dependent variables in the modeling process. The modeling framework followed a three-step strategy: (1) outlier detection using Rosner’s test to reduce the influence of outliers on model accuracy, (2) curve fitting with 12 regression models representing four curve types—polynomial (e.g., linear, quadratic), concave/convex (e.g., exponential, logarithmic), sigmoidal (e.g., logistic, Gompertz, Weibull), and spline-based (e.g., cubic spline, natural spline)—to capture diverse functional relationships between GT and emissions, and (3) model comparison using difference performance metrics to ensure a comprehensive assessment of predictive accuracy, consistency, and bias. …”
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