Enhancing molecular property prediction with quantized GNN models by Areen Rasool, Jamshaid Ul Rahman, Rongin Uwitije

“…This paper presents a systematic approach to molecular networks by integrating GNN models with the DoReFa-Net quantization algorithm. The proposed method aims to enhance computational efficiency while maintaining predictive performance, enabling lightweight yet effective models suitable for molecular task. …”
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Clinical applications of photon-counting CT in neuroimaging by LÜ Haiying, LU Yong, HE Naying

“…Photon-counting computed tomography (PCCT) is a next-generation CT imaging technology that markedly improves image quality while reducing radiation dose and image noise through single-photon detection and energy discrimination by photon detectors. …”
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Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping by Oluwatobi Emmanuel Dare, Kennedy Okokpujie, Emmanuel Adetiba, Olabode Idowu-Bismark, Abdultaofeek Abayomi, Raymond Jules Kala, Emmanuel Owolabi, Udeme Christopher Ukpong

“…The U-Net generator is a 3-channel input, 16-layer architecture while the PatchGan discriminator is a 6-channel input, 7-layer architecture. …”
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Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation by Liang Liu, Xige Zhang, Jiahui Zhou, Kai Niu, Zixuan Guo, Yawen Zhao, Meng Zhang

“…Additionally, by analyzing the relationship between performance and reliability, we proposed optimization methods to improve reliability while ensuring a high performance was maintained. …”
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Deep reinforcement learning applications and prospects in industrial scenarios by JING TAN, Ligang YANG, Xiaorui LI, Zhaolin YUAN, Yunduan CUI, Chao YAO, Zongjie WANG, Xiaojuan BAN

“…Current research is categorized into three domains: (1) adaptive optimization in dynamic environments, enabling systems to respond to changes such as market fluctuations, equipment degradation, and operational disturbances; (2) decision-making under multi-objective and constrained conditions, with DRL balancing competing goals such as efficiency, cost, and sustainability while adhering to technical constraints; and (3) performance enhancement in complex systems, whereby DRL tackles high-dimensional, nonlinear, and coupled processes to improve stability, scalability, and operational excellence. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…The combination of evolutionary algorithms with full-wave electromagnetic (EM) simulation software is an effective method for antenna optimal design. …”
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A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks. by Shaowei Sun, Mingzhou Liu

“…To address these limitations, we propose a framework based on multimodal deep fusion and heterogeneous graph neural networks (HGNNs), incorporating an Ensemble Contrastive Pessimistic Likelihood Estimation (CPLE) algorithm to optimize performance. The framework integrates static and dynamic traffic data, such as video images, traffic flow, vehicle speed, and tunnel weather conditions. …”
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Hybrid Recurrent Neural Network and Decision Tree Scheduling for Energy-Efficient Resource Allocation in Cloud Computing by Sefati Seyed Salar, Vulpe Alexandru, Popovici Eduard, Fratu Octavian

“…Efficient resource allocation in cloud computing is critical for optimizing execution time, minimizing delays, and improving system reliability. …”
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Myocardial revascularization in diabetic patients presenting with critical limbischemia by Ivan Ivanovich Dedov, Victor Yur'evich Kalashnikov, Konstantin Vladimirovich Melkozerov

“…The frequency of diabetic complications remains high despite the development of improved therapeutic modalities. Macroangiopathy continues to bethe predominant complication while coronary heart disease is the main cause of mortality.This paper considers clinical features of diabetic patientswith coronary heart disease and critical limb ischemia; various aspects of optimal drug therapy, preoperative examination and diagnostics precedingvascular non-cardiac surgery; preoperative risk assessment; indications for coronary angiography and myocardial revascularization. …”
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ST-YOLOv8: Small-Target Ship Detection in SAR Images Targeting Specific Marine Environments by Fei Gao, Yang Tian, Yongliang Wu, Yunxia Zhang

“…Furthermore, the ST-YOLOv8 model outperforms several state-of-the-art multi-scale ship detection algorithms on both datasets. In summary, the ST-YOLOv8 model, by integrating advanced neural network architectures and optimization techniques, significantly improves detection accuracy and reduces false detection rates. …”
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Surface Soil Organic Carbon Estimation Based on Habitat Patches in Southwest China by Jieyun Xiao, Wei Zhou, Ting Wang, Yao Peng, Zhan Shi, Saibo Li, Yang Li, Tianxiang Yue

“…Using the RF feature selection (FS) method to select optimal factors as model input variables improved simulation accuracy compared with using all factors or selecting based on Pearson correlation analysis (R² increased by 1.75%–64.71%). …”
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A Blockchain-Based Architecture of Web3.0: A Comprehensive Decentralized Model With Relay Nodes, Unique IDs and P2P by Hyunjoo Yang, Sejin Park

“…In experimental evaluations, the system demonstrated a detection rate improvement of up to 1.9 times faster compared to traditional models in identifying and isolating malicious nodes, while maintaining consistent trust evaluations for legitimate nodes. …”
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The effect of implementing parenteral nutrition guideline on growth and clinical outcomes in preterm infants: a comparative study by Majid Mahallei, Lida Gorbani, Mohammad Bagher Hoseini, Elnaz Shaseb, Bahareh Mehramuz, Khatereh Rezazadeh

“…The PRE group received individualized PN formulations based on clinician discretion, while the POST group received PN guided by a newly introduced, stepwise algorithmic protocol aiming to optimize early protein and energy intake. …”
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Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground” by Wu Nile, Su Rina, Na Mula, Cha Ersi, Yulong Bao, Jiquan Zhang, Zhijun Tong, Xingpeng Liu, Chunli Zhao

“…This study proposes an improved method based on multi-source data, combining the Sentinel-2A spectral response function (SRF) and computer algorithms, to overcome the limitations of traditional methods. …”
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Trading off Iodine and Radiation Dose in Coronary Computed Tomography by Guillaume Fahrni, Thomas Saliba, Damien Racine, Marianna Gulizia, Georgios Tzimas, Chiara Pozzessere, David C. Rotzinger

“…This review explores the balance between radiation and CM volumes, emphasizing patient-specific protocol optimization to improve diagnostic accuracy while minimizing risks. …”
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Hydrofoil Installation and Performance Optimisation for Ship Resistance Reduction in Trimaran Through Particle Swarm Optimisation Method by Ghadimi Aliakbar, Ghadimi Parviz, Ghassemi Hassan

“…The optimisation method integrates STAR-CCM+ software with the particle swarm optimisation (PSO) algorithm as the optimiser. The flow field and wave patterns around the trimaran are analysed to assess resistance improvements. …”
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Estimating the Risk of Lower Extremity Complications in Adults Newly Diagnosed With Diabetic Polyneuropathy: Retrospective Cohort Study by Alyce S Adams, Catherine Lee, Gabriel Escobar, Elizabeth A Bayliss, Brian Callaghan, Michael Horberg, Julie A Schmittdiel, Connie Trinacty, Lisa K Gilliam, Eileen Kim, Nima S Hejazi, Lin Ma, Romain Neugebauer

“…Methods for early detection of individuals at high risk remain elusive. While data-driven diabetic polyneuropathy algorithms exist, high-performing, clinically useful tools to assess risk are needed to improve clinical care. …”
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SMART DShot: Secure Machine-Learning-Based Adaptive Real-Time Timing Correction by Hyunmin Kim, Zahid Basha Shaik Kadu, Kyusuk Han

“…The Hybrid Adaptive Timing Correction algorithm achieves 31.01% success rate (95% CI: [30.2%, 31.8%]), representing a 26.5% improvement over baseline approaches through intelligent meta-learning-based algorithm selection. …”
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Adaptive sequential estimator for InSAR time series phase estimation by Guanya Wang, Zhiwei Li, Han Gao, Jun Hu, Mi Jiang, Peng Ren, Jie Zhang

“…Based on these, the ASE method adaptively prioritizes coherent information while minimizing the impact of decorrelation noise, thereby improving phase estimation accuracy. …”
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Machine Learning Based Flexible Transmission Time Interval Scheduling for eMBB and uRLLC Coexistence Scenario by Jingxuan Zhang, Xiaodong Xu, Kangjie Zhang, Bufang Zhang, Xiaofeng Tao, Ping Zhang

“…Compared with the existing ML methods, the proposed algorithm has a performance improvement in selecting TTI, especially for the uRLLC services. …”
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