Feasibility of Mental Health Triage Call Priority Prediction Using Machine Learning by Rajib Rana, Niall Higgins, Kazi Nazmul Haque, Kylie Burke, Kathryn Turner, Terry Stedman

“…This study delves into the potential of using machine learning (ML) to estimate call priority from the properties of the callers’ voices rather than evaluating the spoken words. Method: Phone callers’ speech is first isolated using existing APIs, then features or representations are extracted from the raw speech. …”
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RotJoint-Based Action Analyzer: A Robust Pose Comparison Pipeline by Guo Gan, Guang Yang, Zhengrong Liu, Ruiyan Xia, Zhenqing Zhu, Yuke Qiu, Hong Zhou, Yangwei Ying

“…Finally, we propose TemporalRotNet, a Transformer-based network, trained via supervised contrastive learning to capture spatial–temporal motion features. …”
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Cost-effective one-pot fabrication of iron(iii) oxychloride–iron(iii) oxide nanomaterials for supercapacitor charge storage by Aldosari Eman, Elsayed Asmaa M., Abdelazeez Ahmed Adel A., Rabia Mohamed

“…Upon complete analysis of the synthesized material, X-ray photoelectron spectroscopy and X-ray diffraction reinforce that iron(iii) oxychloride and iron(iii) oxide are chemically connected with the PPy network. The core–shell structure features a spherical core approximately 105 nm in diameter, with surface spots ranging from 20 to 30 nm. …”
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A Data-Driven Signal Subspace Approach for Indoor Bluetooth Ranging by Zaid Bin Tariq, Jayson P. Van Marter, Anand G. Dabak, Naofal Al-Dhahir, Murat Torlak

“…We then make use of the output features from the estimated pseudospectrum of the individual eigenvectors, obtained from the enhanced SSD algorithm, as an input to the long–short-term-memory (LSTM) recurrent neural network to obtain a data-driven SSD-LSTM wireless range estimator for the BLE. …”
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Infilling of missing rainfall radar data with a memory-assisted deep learning approach by J. Meuer, L. M. Bouwer, L. M. Bouwer, F. Kaspar, R. Lehmann, W. Karl, T. Ludwig, C. Kadow

“…Our model is trained and evaluated on the hourly RADKLIM dataset, which features 1 km resolution precipitation data derived from combined radar and weather stations across Germany. …”
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Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would by Xiaoyong Qiang, Qiang Wang, Guanjun Liu, Limei Song, Weibin Zhou, Ming Yu, Hang Wu, Hang Wu

“…Life-saving measures must be taken at the scene if a trauma patient has pneumothorax; if the patient is not evaluated and diagnosed right away, their life may be in jeopardy. …”
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Improving Disparity Consistency With Self-Refined Cost Volumes for Deep Learning-Based Satellite Stereo Matching by Jiyong Kim, Seoyeon Cho, Minkyung Chung, Yongil Kim

“…With CVRS, we propose a new model for satellite stereo matching, the self-refined cost volume network (SRCV-Net). We evaluated CVRS and SRCV-Net on the US3D and WHU-Stereo datasets, comparing it using the EPE and D1 metrics. …”
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Optimizing HVAC energy efficiency in low-energy buildings: a comparative analysis of reinforcement learning control strategies under Tehran climate conditions by Mohammad Anvar Adibhesami, Amir Hassanzadeh

“…We conducted comprehensive simulation assessments using the EnergyPlus and HoneybeeGym platforms to evaluate two distinct reinforcement learning models: traditional Q-learning (Model A) and deep reinforcement learning (DRL) with neural networks (Model B). …”
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CBCT-to-CT synthesis using a hybrid U-Net diffusion model based on transformers and information bottleneck theory by Can Hu, Ning Cao, Xiuhan Li, Yang He, Han Zhou

“…This module filters out redundant and irrelevant information while compressing essential input data, thereby enabling more efficient summarization and better feature extraction. Finally, a dynamic modulation factor is introduced to balance the contributions of the main network and skip connections, optimizing the reverse denoising process in the diffusion model. …”
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MedAlmighty: enhancing disease diagnosis with large vision model distillation by Yajing Ren, Zheng Gu, Wen Liu

“…We adopt a hybrid loss function that combines cross-entropy loss (for classification accuracy) and Kullback-Leibler divergence (for distillation), enabling the student model to capture rich semantic features while remaining efficient and domain-aware.ResultsExperimental evaluations reveal that MedAlmighty significantly improves disease diagnosis performance across datasets characterized by sparse and diverse medical data. …”
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MSFNet: A Multi-Source Fusion-Based Method with Enhanced Hierarchical Spectral Semantic Perception for Wheat Disease Region Classification by Wenxu Jia, Ziyang Guo, Wenjing Zhang, Haixi Zhang, Bin Liu

“…To address these challenges, this study proposed MSFNet, a novel multi-source fusion network with enhanced hierarchical spectral semantic perception, to achieve the precise regional classification of wheat diseases. …”
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Estimation of state of health for lithium-ion batteries using advanced data-driven techniques by Smitanjali Rout, Sudhansu Kumar Samal, Demissie Jobir Gelmecha, Satyasis Mishra

“…A comprehensive comparison using performance metrics such as root mean squared error, mean absolute error, and R2 scores highlights the LSTM model’s superiority while evaluating the suitability of other approaches. The proposed method not only improves estimation accuracy but also reduces computational demands through optimized feature selection and model training strategies, making it highly suitable for real-time applications in lightweight electric vehicles with limited computational resources. …”
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Detecting infrared UAVs on edge devices through lightweight instance segmentation. by YuZhi Chen, HaoYue Sun, Liang Tian, Ye Yang, ShenYang Wang, TianYou Wang

“…First, Efficient Adaptive Downsampling (EADown) employs dual-branch processing with grouped convolutions to preserve small-target spatial features during multi-scale fusion. Second, HeteroScale Attention Network (HSAN) implements grouped multi-scale convolutions with joint channel-spatial attention mechanisms for enhanced cross-scale feature representation. …”
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Identification of a mitophagy-related gene signature for predicting overall survival and response to immunotherapy in rectal cancer by Jian Yang, Zhifei Cao, Chengqing Yu, Wenxu Cui, Jian Zhou

“…The model genes were obtained based on prognostic features, and the subgroups were distinguished by risk score. …”
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Chaotic dynamics analysis and digital hardware design of the Izhikevich neuron model by Mehdi Nadiri Andabili, Soheila Nazari, Tohid Moosazadeh

“…Abstract Neuromorphic hardware facilitates the fast and energy-efficient implementation of neural network-based artificial intelligence, making it particularly effective for addressing brain-inspired robotic challenges. …”
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Effect of Kohlrabi Peel Powder as a Dietary Fibre Enrichment on Technological, Nutritional, and Sensory Properties of White Bread by İrem Bilge Tek, Suna Dilara Aktas, Aybüke Karaoğlan

“…The technological and nutritional characteristics of white breads were evaluated, and sensory analysis was conducted. The specific volume values of the samples ranged from 1.486 to 1.861 mL/g. …”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. …”
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GSR-Fusion: A Deep Multimodal Fusion Architecture for Robust Sign Language Recognition Using RGB, Skeleton, and Graph-Based Modalities by Wuttichai Vijitkunsawat, Teeradaj Racharak

“…Unlike traditional unimodal models, GSR-Fusion utilizes gesture initiation and termination detection, along with a cross-modality fusion approach using a merge (network) technique, enabling it to capture both spatial-temporal and relational features from multiple data sources. …”
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Pan-genome-scale metabolic modeling of Bacillus subtilis reveals functionally distinct groups by Maxwell Neal, William Brakewood, Michael Betenbaugh, Karsten Zengler

“…Bacillus subtilis strain 168 is one of the first bacteria for which a metabolic network was reconstructed. Since then, several updated reconstructions have been generated for this model microorganism. …”
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Multitask and Transfer Learning Approach for Joint Classification and Severity Estimation of Dysphonia by Dosti Aziz, Sztaho David

“…Both tasks use a shared representation; network is learned from these shared features. We employed five computer vision models and changed their architecture to support multitask learning. …”
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