A novel end-to-end learning framework for inferring lncRNA-disease associations based on convolution neural network by Shunxian Zhou, Sisi Chen, Jinhai Le, Yangtai Xu, Lei Wang

“…IntroductionIn recent years, lots of computational models have been proposed to infer potential lncRNA-disease associations.MethodsIn this manuscript, we introduced a novel end-to-end learning framework named CNMCLDA, in which, we first adopted two convolutional neural networks to extract hidden features of diseases and lncRNAs separately. …”
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An efficient supervised framework for music mood recognition using autoencoder‐based optimised support vector regression model by Gaurav Agarwal, Hari Om

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An analytics-driven model for identifying autism spectrum disorder using eye tracking by Deblina Mazumder Setu

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A Hybrid Deep Transfer Learning-based Approach for COVID-19 Classification in Chest X-ray Images by Khosro Rezaee, Afsoon Badiei, Hossein Ghayoumi Zadeh, Saeed Meshgini

“…In this paper, we presented an approach to diagnosis COVID-19 using CXR images based on the concatenated features vector of the three DTL structures and soft-voting feature selection procedure, including Receiver of Curve (ROC), Entropy, and signal-to-noise ratio (SNR) techniques. …”
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Small object detection algorithm based on improved YOLOv10 for traffic sign by Yukang Zou, Scarlett Liu

“…Our approach introduces Omni-Dimensional Dynamic Convolution (ODConv), which utilizes a four-dimensional dynamic convolution mechanism to improve the capture of multi-scale and complex background features. Additionally, we integrate an attention-guided bidirectional feature pyramid network (EMA-BiFPN) to enhance feature fusion, further improving the detection accuracy for small objects. …”
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Predicting cardiovascular risk with hybrid ensemble learning and explainable AI by Pooja Shah, Madhu Shukla, Neel H. Dholakia, Himanshu Gupta

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Attention-Driven Emotion Recognition in EEG: A Transformer-Based Approach With Cross-Dataset Fine-Tuning by Ghulam Ghous, Shaheryar Najam, Mohammed Alshehri, Abdulmonem Alshahrani, Yahya AlQahtani, Ahmad Jalal, Hui Liu

“…This phase employs optimized feature extraction from key EEG frequency bands (Delta, Theta, Alpha, Beta, Gamma) using techniques such as MFCC, GFCC, power spectral density, and Hjorth parameters. …”
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Machine Learning Models Informed by Connected Mixture Components for Short- and Medium-Term Time Series Forecasting by Andrey K. Gorshenin, Anton L. Vilyaev

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Prediction of the elastic properties and strength of unidirectional carbon fiber reinforced polymers based on representative volume element simulation by Miao Su, Lei Liu, Yuxi Xie, Hui Peng, Chongjie Kang

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Multiscale modeling of powder materials processing for additive manufacturing in inductively coupled plasma by I. V. Tsivilsky, A. S. Melnikov, A. Kh. Gilmutdinov

“…The features of different regimes of vaporization and condensation were described. …”
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Comprehensive Evaluation of the Massively Parallel Direct Simulation Monte Carlo Kernel “Stochastic Parallel Rarefied-Gas Time-Accurate Analyzer” in Rarefied Hypersonic Flows—Part... by Angelos Klothakis, Ioannis K. Nikolos

“…These scenarios have been extensively used by researchers to validate prominent parallel DSMC solvers, due to the challenging nature of the flow features involved. The validation requires meticulous selection of simulation parameters, including particle count, grid density, and time steps. …”
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The Orthotropy Effect of Underground Inclusion on the Seismic Response of Ground Surface by S. Mojtabazadeh-Hasanlouei, M. Panji, M. Kamalian

“…This method is easily implemented in a time-domain computer code for analyzing seismic homogeneous orthotropic mediums. …”
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Adaptive clustering for medical image analysis using the improved separation index by Mojtaba Jahanian, Abbas Karimi, Nafiseh Osati Eraghi, Faraneh Zarafshan

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Clinical analysis of histiocytic necrotizing lymphadenitis in adults with fever of unknown origin: a retrospective study by Nana Xie, Wencong Zhang, Fangbing Tian, Jia Chen, Wenyuan Zhang, Qiurong Ruan, Jianxin Song

“…The analysis encompassed clinical manifestations, laboratory parameters 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (18F-FDG PET/CT) imaging profiles, pathological features and therapeutic responses. …”
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Prostate-specific antigen and prostate-specific antigen kinetics in predicting 18F-sodium fluoride positron emission tomography-computed tomography positivity forfirst bone metasta... by James Yoon, Leslie Ballas, Bhushan Desai, Hossein Jadvar

“…We evaluated the association between serum prostate specific antigen (PSA) level and kinetics to predict 18F-sodium fluoride positron emission tomography-computed tomography (18F-NaF PET-CT) positivity forfirst bone metastases in men with biochemical recurrence after radical prostatectomy. …”
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EDPNet: A Transmission Line Ice-Thickness Recognition End-Side Network Based on Efficient Dynamic Perception by Yangyang Jiao, Yu Zhang, Yinke Dou, Liangliang Zhao, Qiang Liu

“…The model is deployed on an OrangePi5 Plus edge computing board. Compared with the baseline model, the maximum ice-thickness detection error is 4.2%, the model parameters are reduced by 86.1%, and the detection speed is increased by 74.6%. …”
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RL-Net: a rapid and lightweight network for detecting tiny vehicle targets in remote sensing images by Yaoyao Du, Li Chen, Xingxing Hao

“…Second, the Lightweight Spatial Pyramid Pooling Fast (LSPPF) structure is designed to enhance multiscale feature extraction while accelerating computational speed. …”
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Enhancing Structural Health Monitoring of Super-Tall Buildings Using Support Vector Machines, MEMD, and Wavelet Transform by Rouzbeh Doroudi, Seyed Hossein Hosseini Lavasani, Mohsen Shahrouzi, Aref Afshar

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DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects by Lihua Chen, Qi Sun, Ziyang Han, Fengwen Zhai

“…Additionally, the optimized architecture reduces parameters by 1.3% and computational load by 15.19%. …”
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Significance of the Lesion–Pleura Relationship in Differentiating Peripheral Inflammatory Lesions and Lung Cancers by Tao Y, Zhang WT, Ding C, Fu BJ, Lv FJ, Chu ZG

“…Additionally, the lesion–pleura relationship was one of independent indicators for differentiation (odds ratio, 9.433; P < 0.001).Conclusion: When differentiating peripheral lesions (≥ 1.5 cm), it is crucial to consider the basement-to-pleura and lesion-pleura distance besides patients’ clinical characteristics, laboratory parameters and morphological features.Keywords: lung neoplasms, diagnosis, differential, tomography, X-ray computed…”
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