(Meta)verse as the next escaper from competition public enforcement by Luca Megale

“…Moving on, it is asserted as tacit collusion might be a crucial issue due to algorithms and blockchain. Metaverse might also be characterized by repeating concerns. …”
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Unravelling NK cell subset dynamics and specific gene signatures post-ibrutinib therapy in chronic lymphocytic leukaemia via single-cell transcriptomics by Chunlan Liu, Tianjian Ding, Rong Zou, Aili Zhang, Zhengzhuo Zhi, Sili Wang

“…A cell subset-specific novel index (CNI) was constructed based on these core genes and was shown to be capable of predicting responses to immunotherapy. Oncopredictive algorithms and molecular docking screenings further identified semaxanib and ulixertinib as potential therapeutic candidates for CLL. …”
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Machine learning-based prognostic modeling integrating PANoptosis in head and neck squamous cell carcinoma by Chen Li, Jiajing Lu, Jialin Zhu, Tao Zhou, Qijie Shen, Bikun Huang, Qingsong Li

“…A prognostic model was constructed using 101 machine learning algorithms and their combinations, with TCGA-HNSCC as the training set and GSE41613 and GSE65858 as validation sets. …”
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Integrative multi-omics analysis reveals the role of toll-like receptor signaling in pancreatic cancer by Jie Peng, Jiaao Sun, Youfeng Yu, Qihang Yuan, Yong Zhang

“…The model showed strong performance in predicting the survival state of pancreatic cancer samples. …”
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Effective Machine Learning Techniques for Dealing with Poor Credit Data by Dumisani Selby Nkambule, Bhekisipho Twala, Jan Harm Christiaan Pretorius

“…The differences in performance of all seven machine learning algorithms are significant at the 95% level.…”
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Мethods of Machine Learning in Ophthalmology: Review by D. D. Garri, S. V. Saakyan, I. P. Khoroshilova-Maslova, A. Yu. Tsygankov, O. I. Nikitin, G. Yu. Tarasov

“…Machine learning includes models and algorithms that mimic the architecture of biological neural networks. …”
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Identification and experimental validation of BMX as a crucial PANoptosis‑related gene for immune response in Spinal Cord Injury. by Tianbao Feng, Jiating Hu, Mi Xie, Guodong Shi, Qi Wang, Jingyuan Yao, Xiaoqin Liu

“…Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. BMX and CASP5 were consistently identified across all algorithms. …”
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Delivering data: A real-world dataset for last-mile delivery optimizationZenodo by Anna Vrani, Savvas D. Apostolidis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos

“…The collected matrices were processed and structured for direct use in VRP algorithms.The dataset offers substantial reuse potential by serving as a benchmark for evaluating VRP algorithms, enabling the comparison of optimization methods based on real-world logistics problems. …”
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Machine Learning-Based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction by Jayroop Ramesh, Donthi Sankalpa, Rohan Mitra, Salam Dhou

“…Moreover, a novel regression predictive modeling approach is also proposed to achieve the same objective. …”
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Few-Shot Learning With Prototypical Networks for Improved Memory Forensics by Muhammad Fahad Malik, Ammara Gul, Ayesha Saadia, Faeiz M. Alserhani

“…Prototypical networks are a type of few-shot learning algorithm that excels at classifying new categories with minimal examples. …”
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Comprehensive protein datasets and benchmarking for liquid–liquid phase separation studies by Carlos Pintado-Grima, Oriol Bárcenas, Eva Arribas-Ruiz, Valentín Iglesias, Michał Burdukiewicz, Salvador Ventura

“…Moreover, we describe limitations in classical and state-of-the-art predictive algorithms by providing the most comprehensive benchmark to date. …”
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Applications of artificial intelligence and computational intelligence in hydraulic optimization of centrifugal pumps: a comprehensive review by Yuanhui Xu, Xingcheng Gan, Ji Pei, Wenjie Wang, Jia Chen, Shouqi Yuan

“…Ultimately, such progress will contribute to more sustainable and reliable energy utilisation in diverse industrial applications.Highlights Comprehensive review of AI and CI applications in centrifugal pump hydraulic optimisation.Analysis of machine learning methods for predictive modelling and optimisation.Insights into integrating intelligent algorithms with CFD for high-dimensional, multi-objective optimisation.Identification of future research directions to enhance precision and efficiency in pump design methodologies.…”
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Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks by Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He

“…Finally, the particle swarm optimization algorithm is used for hyperparameter optimization to improve the prediction accuracy. …”
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Synergistic feature selection and distributed classification framework for high-dimensional medical data analysis by D. Dhinakaran, L. Srinivasan, S. Edwin Raja, K. Valarmathi, M. Gomathy Nayagam

“…In order to overcome these drawbacks, the new integrated algorithm is presented here: Synergistic Kruskal-RFE Selector and Distributed Multi-Kernel Classification Framework (SKR-DMKCF). …”
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Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators by Qin Yan, Jinxin Wang, Tao Lin, Archie James Johnston

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A Capacitated Vehicle Routing Model for Distribution and Repair with a Service Center by Irma-Delia Rojas-Cuevas, Elias Olivares-Benitez, Alfredo S. Ramos, Samuel Nucamendi-Guillén

“…<i>Results:</i> The model was applied to a real-world case study, achieving a 40% reduction in fuel costs, a reduction from 5 to 3 routes, and a sustainable logistics operations model with potential reductions of greenhouse gas emissions and item disposals. …”
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Channel estimation method of massive MIMO-OFDM system based on adaptive compressed sensing by Yiyang HU, Lina QI

“…Massive multiple-input multiple-output (MIMO) is a solution for efficiently providing connection services for a variety of machine equipment in the Internet of things (IoT), and efficient connection services require accurate channel estimation.Aimed at the problems of high pilot overhead and poor performance of normalized mean square error (NMSE) estimation in downlink channel estimation of massive MIMO systems, based on the compressed sensing (CS) theory, the common sparsity of the channel space domain was combined while using the feature of lower sparsity of adjacent time slot differential channel impulse response (CIR), which leaded to a significant reduction in pilot overhead.In the reconstruction algorithm, a two-stage differential estimation algorithm, which divided the channel estimation in consecutive time slots with time correlation into two stages, was proposed and the idea of adaptive compressed sensing was combined to achieve fast and accurate CIR estimate.The simulation results show that the proposed two-stage differential channel estimation algorithm not only has a significant improvement in the estimated NMSE performance and data transmission rate compared to the existing CS-based multiple measurement vector (MMV) algorithm, but also show a certain reduction in runtime complexity.…”
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Denoising of acoustic emission signals from rock failure processes through ICEEMDAN combined with multiple criteria and wavelet transform by Tao Wang, Weiwei Ye, Liyuan Liu, Zhihui Zhao, Wei Huang

“…Quantitative analysis of denoising effects on typical rock uniaxial compression fracture AE signals reveals that the optimized method has a positive impact on high-frequency noise reduction. The peak frequency range is unaffected before and after optimization, while the main amplitude reduction is concentrated in the high-frequency range. …”
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Hyperneutron Stars from an Ab Initio Calculation by Hui Tong, Serdar Elhatisari, Ulf-G. Meißner​

“…At sufficient densities, the appearance of hyperons generally softens the EOS, leading to a reduction in the maximum mass of neutron stars well below the observed values of about 2 M _⊙ . …”
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Abnormality detection and privacy protection strategies for power marketing inspection business of cyber–physical–social systems using big data and artificial intelligence by Li Kai, Mo Pingyan, Yang Yongjiao, Xie Hanyang, Shen Zhixiong

“…The proposed model incorporates a work order correlation matching algorithm, a fault interval detection algorithm, an electricity consumption prediction algorithm, and a business anomaly identification algorithm. …”
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