Conformalons: a new class of black hole mimickers by Leonardo Modesto, Ali Akil, Cosimo Bambi

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Application of machine learning in identifying risk factors for low APGAR scores by Haifa Fahad Alhasson, Nagat Elhag, Shuaa Saleem Alharbi, Ishag Adam

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Advances in Multimodal Imaging Techniques for Evaluating and Predicting the Efficacy of Immunotherapy for NSCLC by Liu J, Xie M, Shen J, Yao J, Lin X, Bao X, Zhang X, Liang Y, Yang Y, Jiang G, Diao X, Han W, Du H, Xue X, Wu J

“…Notably, radiomics demonstrates promise in decoding tumor heterogeneity, PD-L1 expression, and immune microenvironment features, while immuno-PET probes targeting immune checkpoints offer novel insights into immune activity in vivo. …”
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Novel Trimethoprim-Based Metal Complexes and Nanoparticle Functionalization: Synthesis, Structural Analysis, and Anticancer Properties by Abbas M. Abbas, Hossam H. Nasrallah, A. Aboelmagd, W. Christopher Boyd, Haitham Kalil, Adel S. Orabi

“…Pharmacokinetic parameters and target enzymes for HD and its complexes were computed using the SwissADME web tool, with the BOILED-Egg model indicating that HD and its Cu complex should be passively permeable via the blood-brain barrier and highly absorbed by the gastrointestinal tract (GIT), unlike the Ni, Co, Ag, and Zn complexes, which are predicted to show low GIT absorption. …”
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The cross-sectional study of hospitalized COVID-19 patients in Xiangyang, Hubei province by Jin-Wei AI, Yong WANG, Jun-Wen CHEN, Xiao-Yun LIU, Wu-Feng FAN, Guo-Xin HUANG, Gao-Jing QU, Mei-Ling ZHANG, Sheng-Duo PEI, Yang LI, Li-Sha WANG, Bin PEI

“…After all data were extracted and analyzed, we summarized the COVID-19 patients epidemiological and clinical features.Results 102 cases were confirmed by real-time RT-PCR, including 52 males and 50 females with an average age of 50.38 years (SD 16.86). …”
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MoSViT: a lightweight vision transformer framework for efficient disease detection via precision attention mechanism by Yuanqi Chen, Aiping Wang, Ziyang Liu, Jie Yue, Enxu Zhang, Fei Li, Ning Zhang

“…This study introduces MoSViT, an innovative classification model leveraging advanced machine learning and computer vision technologies. Built on the MobileViT V2 framework, MoSViT integrates the CLA focus mechanism, DRB module, MoSViT Block, and the LeakyRelu6 activation function to enhance feature extraction accuracy while reducing computational complexity. …”
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Advanced smart assistance with enhancing social interaction and daily activities for visually impaired individuals using deep learning with modified seagull optimization by Sana Alazwari, Hussah Nasser AlEisa, Mohammed Rizwanullah, Radwa Marzouk

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GNSS Precipitable Water Vapor Prediction for Hong Kong Based on ICEEMDAN-SE-LSTM-ARIMA Hybrid Model by Jie Zhao, Xu Lin, Zhengdao Yuan, Nage Du, Xiaolong Cai, Cong Yang, Jun Zhao, Yashi Xu, Lunwei Zhao

“…This process significantly reduces modeling complexity and improves computational efficiency. We propose different modeling strategies tailored to the dynamics of various subsequences. …”
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Star-YOLO: A Lightweight Real-Time Wheat Grain Detection Model for Embedded Deployment by Zhihang Qu, Xiao Liang, Sicheng Liang, Xiumei Guo

“…The model employs StarNet to refine the C3k2 structure, reducing computational complexity without compromising detection accuracy, and integrates the MBConv module into the detection head to boost feature extraction while further minimizing computational load. …”
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Unlocking the clinical potential of paired inspiratory and expiratory CT scans in the differential diagnosis of cystic lung diseases: A systematic review. by Lucas Gabriel R Pinheiro, Carlos Augusto Treviso, Gabriele Carra Forte, Enrico Mattana Muller, Bruno Hochhegger, Rubens Gabriel Feijó Andrade

“…However, the traditionally used inspiratory scan still presents a significant spectrum of overlapping radiological features. Recent studies have demonstrated variation in lesion size between inspiratory and expiratory phases, probably due to cyst-airway communication. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…This study explores the application of advanced machine learning (ML) models to predict CO₂ solubility in NaCl brine, a critical parameter for effective carbon capture, utilization, and storage (CCUS). …”
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A Tensor Space for Multi-View and Multitask Learning Based on Einstein and Hadamard Products: A Case Study on Vehicle Traffic Surveillance Systems by Fernando Hermosillo-Reynoso, Deni Torres-Roman

“…Unfortunately, as the number of views increases, the number of parameters that determine the MV-DTF layer grows exponentially, and consequently, so does its computational complexity. …”
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A Recognition Method for Marigold Picking Points Based on the Lightweight SCS-YOLO-Seg Model by Baojian Ma, Zhenghao Wu, Yun Ge, Bangbang Chen, He Zhang, Hao Xia, Dongyun Wang

“…The approach enhances the baseline YOLOv8n-seg architecture by replacing its backbone with StarNet and introducing C2f-Star, a novel lightweight feature extraction module. These modifications achieve substantial model compression, significantly reducing the model size, parameter count, and computational complexity (GFLOPs). …”
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Organization Learning Oriented Approach with Application to Discrete Flight Control by Lin Yu, Shixing Wang, Yongan Zheng

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SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…First, the StarNet architecture is introduced into the Backbone to enhance the extraction of shallow image features and significantly reduce computational complexity. …”
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The response time to emotional stimuli (including facial expressions photos) during the fMRI scanning in affective disorders: mild and moderate depression and dysthymic disorder by M. Ye. Mel’nikov, D. D. Bezmaternykh, E. D. Petrovskiy, L. I. Kozlova, M. B. Shtark, A. A. Savelov, O. S. Shubina, K. A. Natarova

“…The response time and accuracy were the subjects of analysis.Results. On the most of the computed parameters patients with depressive disorder did not differ from controls. …”
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A binary grasshopper optimization algorithm for solving uncapacitated facility location problem by Ahmet Babalik, Aybuke Babadag

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Simulated Annealing-Based Hyperparameter Optimization of a Convolutional Neural Network for MRI Brain Tumor Classification by Sofia El Amoury, Youssef Smili, Youssef Fakhri

“…Recent advances in deep learning, particularly through the application of Convolutional Neural Networks (CNNs), have transformed medical image analysis by enabling automated, high-accuracy feature extraction. Despite their promise, the performance of CNNs is highly contingent upon optimal hyperparameter tuning, a process that can be both computationally demanding and pivotal for model efficacy. …”
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Androgen Deprivation Therapy–Induced Muscle Loss and Fat Gain Predict Cardiovascular Events in Prostate Cancer Patients by Jie Lee, Yi‐Hsuan Lin, Pai‐Kai Chiang, Jhen‐Bin Lin, Ya‐Ting Jan, Wei‐Kung Tsai, Yu‐Jen Chen, Kun‐Pin Wu

“…The ΔSMI and ΔSATI were the most important features for predicting MACE in both cohorts, whereas ΔVATI and baseline body composition parameters were less influential. …”
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Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors. by Montaser Abdelsattar, Mohamed A Ismeil, Karim Menoufi, Ahmed AbdelMoety, Ahmed Emad-Eldeen

“…Preprocessing techniques, including feature scaling and parameter tuning, improved model performance by enhancing data consistency and optimizing hyperparameters. …”
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