Efficiency-optimized 6G: A virtual network resource orchestration strategy by enhanced particle swarm optimization by Sai Zou, Junrui Wu, Haisheng Yu, Wenyong Wang, Lisheng Huang, Wei Ni, Yan Liu

“…In this paper, 6G network resource orchestration is optimized to support customized network slicing of services, and place network functions generated by heterogeneous devices into available resources. …”
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An enhanced time efficient technique for image watermarking using ant colony optimization and light gradient boosting algorithm by Vipul Sharma, Roohie Naaz Mir

“…This paper proposes a time efficient optimization method based on machine learning algorithms to detect the best embedding parameter for image watermarking with both robustness and imperceptibility. …”
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Detection of Incipient Faults in Power Transformers using Fuzzy Logic and Decision Tree Models Based on Dissolved Gas Analysis by Felix Olowolafe, Kehinde Olukunmi Alawode

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MalGEA: A malware analysis framework via matrix factorization based node embedding and graph external attention by Ruisheng Li, Qilong Zhang, Huimin Shen

“…First, MalGEA extracts function call information from malware and constructs corresponding function call graphs. …”
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An object detection method in foggy weather based on novel feature enhancement and fusion by ZHU Lei, ZHAO Han, WANG Weili

“…To further improve the detection accuracy of objects in foggy scenes for deep learning networks, a foggy object detection method called NFF-YOLOX is proposed based on the YOLOX network. …”
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Computational Neuroscience’s Influence on Autism Neuro-Transmission Research: Mapping Serotonin, Dopamine, GABA, and Glutamate by Victoria Bamicha, Pantelis Pergantis, Charalabos Skianis, Athanasios Drigas

“…Neurotransmitters play a crucial role in the function of brain cells, enhancing synaptic conduction and signal transmission. …”
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Accurate prediction of drug-protein interactions by maintaining the original topological relationships among embeddings by Yanfei Li, Xiran Chen, Shuqin Wang, Jinmao Wei

“…Abstract Background Learning-based methods have recently demonstrated strong potential in predicting drug-protein interactions (DPIs). …”
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Openness in Education as a Praxis: From Individual Testimonials to Collective Voices by Aras Bozkurt, Torunn Gjelsvik, Taskeen Adam, Tutaleni I. Asino, Javiera Atenas, Maha Bali, Constance Blomgren, Melissa Bond, Curtis J. Bonk, Mark Brown, Daniel Burgos, Dianne Conrad, Eamon Costello, Catherine Cronin, Laura Czerniewicz, Maren Deepwell, Markus Deimann, Helen J. DeWaard, Tonia A. Dousay, Martin Ebner, Robert Farrow, Inés Gil-Jaurena, Leo Havemann, Andreia Inamorato, Valerie Irvine, Shironica P. Karunanayaka, Michael Kerres, Sarah Lambert, Kyungmee Lee, Mpine Makoe, Victoria I. Marín, Alexander Mikroyannidis, Sanjaya Mishra, Som Naidu, Fabio Nascimbeni, Mark Nichols, Don Olcott, Ebba Ossiannilsson, Daniel Otto, Brenda Cecilia Padilla Rodriguez, Michael Paskevicius, Verena Roberts, Tooba Saleem, Robert Schuwer, Ramesh C. Sharma, Bonnie Stewart, Christian M. Stracke, Alan Tait, Ahmed Tlili, George Ubachs, Joshua Weidlich, Martin Weller, Junhong Xiao, Olaf Zawacki-Richter

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Distinct gut microbiota profiles and network properties in older Korean individuals with subjective cognitive decline, mild cognitive impairment, and Alzheimer’s disease by Sang Joon Son, Xuanga Wu, Hyun Woong Roh, Yong Hyuk Cho, Sunhwa Hong, You Jin Nam, Chang Hyung Hong, Sunmin Park

“…Abstract Background The gut microbiota may influence cognitive function via the gut-brain axis. This study aimed to investigate the gut microbiota profiles of 346 older Korean individuals with subjective cognitive decline but no symptoms (SCD), mild cognitive impairment (MCI), or Alzheimer’s disease (AD). …”
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FAULT DIAGNOSIS OF ROLLING BEARING BASED ON LEARNING SAMPLE SELECTION VIA CORRELATION ENERGY FLUCTUATION EVALUATION AND DEEP BELIEF NEURAL NETWORK (MT) by QIN Bo, LUO QuanYi, FENG WeiWei, ZHANG Peng, ZHAO ZhenHua, LI ZiXian, WANG Zhuo

“…Experimental results show that the proposed method is capable of screening out the intrinsic mode function components of the rolling bearing vibration signal, which contains the main components of the fault and realizes the construction of learning sample sets. …”
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Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study by Hao Ren, Yiying Zheng, Changjin Li, Fengshi Jing, Qiting Wang, Zeyu Luo, Dongxiao Li, Deyi Liang, Weiming Tang, Li Liu, Weibin Cheng

“…ObjectiveThe objective of this study was to explore the application of machine learning (ML) to integrate blood biomarkers, life behaviors, and disease history to predict the decline in cognitive function. …”
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Leader-Following Consensus for Second-Order Nonlinear Multiagent Systems with Input Saturation via Distributed Adaptive Neural Network Iterative Learning Control by Xiongfeng Deng, Xiuxia Sun, Shuguang Liu, Boyang Zhang

“…A new Lyapunov function is constructed to analyze the validity of the presented control protocol. …”
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Construction of regulatory T cells specific genes predictive models of prostate cancer patients based on machine learning: a computational analysis and in vitro experiments by Zhengrong Zhou, Chaozhao Liang

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Spatial resources in pre-service teachers’ instructional practices in VR tandems: co-constructing shared spaces and embodied spatial scaffolding by Milica Lazovic

“…The analysis focuses on pre-service teachers’ use of spatial resources and their practices of embodied spatial scaffolding to support learning in three key areas: instructing on app functionality, developing new embodied action patterns, and fostering a functional understanding of virtual objects. …”
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Schizophrenia Detection and Classification: A Systematic Review of the Last Decade by Arghyasree Saha, Seungmin Park, Zong Woo Geem, Pawan Kumar Singh

“…The review evaluates the use of both Machine Learning (ML) and Deep Learning (DL) methods across multiple modalities, including Electroencephalography (EEG), Structural Magnetic Resonance Imaging (sMRI), and Functional Magnetic Resonance Imaging (fMRI). …”
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Ulcer detection in Wireless Capsule Endoscopy images using deep CNN by Vani V, K.V. Mahendra Prashanth

“…The test results were subjected to hyper-parameter optimization for various tweaking parameters such as epochs, pooling schemes, learning rate, number of layers, optimizer, activation functions and drop out scheme. …”
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The neural underpinnings of repeated skill transfer in human cultural evolution by Heidi Øhrn, Heidi Øhrn, Emilie Pettersen Sjursen, Karsten Specht, Karsten Specht, Kenneth Hugdahl, Kenneth Hugdahl, Kenneth Hugdahl, Larissa Mendoza Straffon, Larissa Mendoza Straffon, Andrea Bender, Andrea Bender

“…Our study further shows the potential of brain imaging as a viable technique for investigating CCE. By applying functional MRI to track neural activity during the acquisition of knot-tying skills, we provide a novel approach for understanding the cognitive mechanisms that underlie cultural knowledge transfer. …”
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Toward Reliable Post-Disaster Assessment: Advancing Building Damage Detection Using You Only Look Once Convolutional Neural Network and Satellite Imagery by César Luis Moreno González, Germán A. Montoya, Carlos Lozano Garzón

“…These findings contribute to machine learning-based disaster response, offering an efficient, cost-effective framework for large-scale damage assessment and reinforcing the importance of model selection, hyperparameter tuning, and optimization functions in critical real-world applications.…”
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BREAST-RANKNet: a fuzzy rank-based ensemble of CNNs with residual learning for enhanced breast cancer detection from ultrasound and mammogram images by Sohaib Asif, Lingying Zhu, Dane Yan, Luman Xu, Zhengqiu Huang, Haimin Xu, Ruxuan Yan, Linghong Cai, Changfu Zheng, Jiamei Lin, Enyu Wang

“…Furthermore, we extract probabilities from these models and aggregate them using fuzzy rank-based fusion strategy, utilize three non-linear functions: an exponentially decaying function $$\left( {exp} \right)$$ exp , the $$tanh$$ tanh function, and the $$sigmoid$$ sigmoid function, allowing for adaptive integration based on model confidence. …”
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Single-cell technology for drug discovery and development by Anzhuo Zhang, Jiawei Zou, Yue Xi, Lianchong Gao, Fulan Deng, Yujun Liu, Pengfei Gao, Henry H. Y. Tong, Lianjiang Tan, Xin Zou, Xin Zou, Jie Hao

“…The development of deep learning technology has provided a powerful tool for research in drug discovery based on single-cell techniques, which has evolved with the advent of large-scale public databases to predict drug responses and targets. …”
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