Telecom Fraud Recognition Based on Large Language Model Neuron Selection by Lanlan Jiang, Cheng Zhang, Xingguo Qin, Ya Zhou, Guanglun Huang, Hui Li, Jun Li

“…This strategy effectively mitigates noise originating from non-pertinent neurons, thereby enhancing both the accuracy and computational efficiency of the model. …”
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MAST Kinases’ Function and Regulation: Insights from Structural Modeling and Disease Mutations by Michael C. Lemke, Nithin R. Avala, Michael T. Rader, Stefan R. Hargett, Daniel S. Lank, Brandon D. Seltzer, Thurl E. Harris

“…We also estimate the functional consequences of disease point mutations on protein stability by integrating predictive algorithms and AlphaFold. <b>Results</b>: Higher-order organisms often have multiple MASTs and a single MASTL kinase. …”
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DIGITAL TRANSFORMATION OF BUSINESS MANAGEMENT: INNOVATIVE MODELS, FORECAST SCENARIOS AND CURRENT CHALLENGES OF ECONOMY MODERNIZATION by I.V. Burtnyak, T.V. Khaludilo

“…The scientific novelty has been constituted by the development of a functional concept of digital transformation in management, which takes into account the influence of both external economic conditions and internal innovation processes on enterprises’ adaptability. …”
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A non-sub-sampled shearlet transform-based deep learning sub band enhancement and fusion method for multi-modal images by Sudhakar Sengan, Praveen Gugulothu, Roobaea Alroobaea, Julian L. Webber, Abolfazl Mehbodniya, Amr Yousef

“…Experimental results prove that the proposed method outperforms existing fusion algorithms, achieving approximately 16.5% higher performance in terms of the QAB/F (edge preservation) metric, along with strong results across both subjective visual assessments and objective quality indices.…”
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Nutritional markers of undiagnosed type 2 diabetes in adults: Findings of a machine learning analysis with external validation and benchmarking. by Kushan De Silva, Siew Lim, Aya Mousa, Helena Teede, Andrew Forbes, Ryan T Demmer, Daniel Jönsson, Joanne Enticott

“…We tested three machine learning algorithms on original and resampled training datasets built using three resampling methods. …”
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Resilience evaluation of memristor based PUF against machine learning attacks by Hebatallah M. Ibrahim, Heorhii Skovorodnikov, Hoda Alkhzaimi

“…Memristor-based PUFs are emerging due to the inherent randomness at both the memristor level due to the cycle-to-cycle (C2C) programming variation of the device and the fabrication process level such as the cross-sectional area and variations. …”
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Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images by Ruhul Amin, Md.Shamim Reza, Dewan Ahmed Muhtasim, Jungpil Shin, Md. Maniruzzaman, Md.Mahfujul Hasan

“…Even with the widespread use of deep learning (DL) and machine learning (ML) algorithms, the early diagnosis of osteoporosis patients can still be improved. …”
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Assessing the deep learning based image quality enhancements for the BGO based GE omni legend PET/CT by Meysam Dadgar, Amaryllis Verstraete, Jens Maebe, Yves D’Asseler, Stefaan Vandenberghe

“…The results also indicate a significant improvement in larger spheres when considering both background variability and contrast recovery coefficient. …”
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OCTNet: A Modified Multi-Scale Attention Feature Fusion Network with InceptionV3 for Retinal OCT Image Classification by Irshad Khalil, Asif Mehmood, Hyunchul Kim, Jungsuk Kim

“…In recent years, Deep Learning (DL) and Machine Learning (ML) algorithms have become essential tools, particularly in medical image classification, and are widely used to classify and identify various diseases. …”
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Revolutionize 3D-Chip Design With Open3DFlow, an Open-Source AI-Enhanced Solution by Yifei Zhu, Zhenxuan Luan, Dawei Feng, Weiwei Chen, Lei Ren, Zhangxi Tan

“…<italic>Open3DFlow</italic>&#x2019;s open-source nature allows seamless integration of custom AI optimization algorithms. As a showcase, we leverage large language models (LLMs) to help the bonding pad placement. …”
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Evaluation of the performance of ERA5, ERA5-Land and MERRA-2 reanalysis to estimate snow depth over a mountainous semi-arid region in Iran by Faezehsadat Majidi, Samaneh Sabetghadam, Maryam Gharaylou, Reza Rezaian

“…The evaluation was performed on both temporal and spatial scales, employing statistical indicators such as correlation coefficients, bias, and root mean square error (RMSE). …”
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Experimental and machine learning based analysis of pervious concrete enhanced with fly ash and silica fume by Siva Shanmukha Anjaneya Babu Padavala, Siva Avudaiappan, Venkatesh Noolu

“…This study explores the use of fly ash (FA) and silica fume (SF) as supplementary cementitious materials (SCMs) to enhance both mechanical and environmental performance of PC concrete. …”
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Integrated Analysis of Ferroptosis- and Cellular Senescence-Related Biomarkers in Atherosclerosis Based on Machine Learning and Single-Cell Sequencing Data by Qi X, Cao S, Chen J, Yin X

“…Eight machine learning algorithms were applied to identify hub genes and construct a diagnostic model. …”
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Machine learning-based model for CD4+ conventional T cell genes to predict survival and immune responses in colorectal cancer by Zijing Wang, Zhanyuan Sun, Hengyi Lv, Wenjun Wu, Hai Li, Tao Jiang

“…Abstract Globally, CRC ranks as a principal cause of mortality, with projections indicating a substantial rise in both incidence and mortality by the year 2040. The immunological responses to cancer heavily rely on the function of CD4Tconv. …”
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Risk factors for tuberculosis treatment outcomes: a statistical learning-based exploration using the SINAN database with incomplete observations by Nguyen Ky Phat, Yoonah Lee, Dinh Hoa Vu, Nguyen Phuoc Long, Seongoh Park

“…Methods We exploited the upweighting approach and multiple imputation analysis (MIA) to address the extreme imbalance in responses and missing data. Three algorithms were employed for TB treatment outcome prediction, including logistic regression (LOGIT), random forest, and stochastic gradient boosting. …”
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The relationship between kinship and foster placement on mental health indicators in children and youth seeking treatment by Shannon L. Stewart, Boden Brock, Jordyn Manis, Aadhiya Vasudeva, Jeffrey W. Poss

“…Background: Children living in both kinship and foster care placements often face considerable adversity. …”
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DualTransAttNet: A Hybrid Model with a Dual Attention Mechanism for Corn Seed Classification by Fei Pan, Dawei He, Pengjun Xiang, Mengdie Hu, Daizhuang Yang, Fang Huang, Changmeng Peng

“…Existing classification algorithms often suffer from limitations such as reliance on single information sources, constrained feature extraction capabilities, time consumption, low accuracy, and the potential to cause irreversible damage to seeds. …”
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Markov model of representation of sensual images for the formation of the model of the outside world by A. A. Solodov

“…This approach allows formalizing the processes of representation of sensory images in the cognitive system, taking into account both the internal logic of the system and the interaction of the system with the outside world. …”
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Economic approach for optimal allocation of irrigation water in water-scarce region by Xueliang Zhang, Li Ren, Jianshi Zhao

“…Optimizing irrigation water allocation is critical for maximizing grain yields in water-scarce regions. Traditional algorithms face challenges such as lack of interpretable criteria, the curse of dimensionality, and instability. …”
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The application of statistical methods to assess economic assets by D. V. Dianov

“…Until now, the use of statistical methodology in the practice of economic assessment of assets is only fragmentary. This applies to both Federal Legislation (Federal law № 135 «On valuation activities in the Russian Federation» dated 16.07.1998 in edition 05.07.2016) and the methodological documents and regulations of the estimated activities, in particular, the valuation activities’ standards. …”
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