Establishing strength prediction models for low-carbon rubberized cementitious mortar using advanced AI tools by Fu Limei, Xu Feng

“…Rubberized cementitious composites have emerged as a sustainable alternative in the construction sector by promoting circular economy principles. …”
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An interpretable stacking ensemble model for high-entropy alloy mechanical property prediction by Songpeng Zhao, Zeyuan Li, Changshuai Yin, Zhaofu Zhang, Teng Long, Jingjing Yang, Ruyue Cao, Yuzheng Guo

“…However, accurately predicting their mechanical behavior remains challenging because of the vast compositional design space and complex multi-element interactions. …”
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Hyperspectral Target Detection Based on Macro–Micro Spectrum Contrastive Learning by Jiacheng Tian, Dunbin Shen, Wenfeng Kong, Min Li, Hongyu Wang, Xiaorui Ma

“…Experimental results on four benchmark datasets demonstrate the superior performance of the proposed method over existing State-of-the-Art algorithms.…”
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BlendNet: a blending-based convolutional neural network for effective deep learning of electrocardiogram signals by S. Premanand, Sathiya Narayanan

“…Experimental results and analysis show that, in the case of α = 0.7, BlendNet's performance surpasses the performance of (i) traditional approaches (that do not involve blending) and (ii) state-of-the-art approaches for ECG classification.DiscussionExperimental outcomes show that the proposed BlendNet is flexible regarding dense layer settings and can accommodate faster alternatives [i.e., machine learning (ML) algorithms] for faster convergence. The superior performance at α = 0.7 indicates that alpha blending allows for richer composite feature sets, leading to improved classification accuracy over conventional feature extraction and classification methods.…”
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How Can Spatially Distributed Uncertainties Be Included in FEA and in Parameter Estimation for Model Updating? by M.W. Zehn, A. Saitov

“…The parameter estimation methods used in updating algorithms for FE-models, depend on the choice of a priori to be determined weighting matrices. …”
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Image Matting using Superpixels Centroid by Anam Akbar, Aniqa Shirazi, Mohammad Sarim Farooqui

“… The orientation and focus of this research piece is the extraction of foreground and compositing this extracted region onto a new background region. …”
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Hysteresis in Neuron Models with Adapting Feedback Synapses by Sebastian Thomas Lynch, Stephen Lynch

“…This work has the potential to improve learning algorithms, increase understanding of neural memory formation, and inform neuromorphic engineering research.…”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

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Investigating the relationship between thought interference, somatic passivity and outcomes in patients with psychosis: a natural language processing approach using a clinical reco... by Robert Stewart, Anna Kolliakou, Jyoti Sanyal, Rashmi Patel, Thibault Thierry Magrangeas

“…Objectives We aimed to apply natural language processing algorithms in routine healthcare records to identify reported somatic passivity (external control of sensations, actions and impulses) and thought interference symptoms (thought broadcasting, insertion, withdrawal), first-rank symptoms traditionally central to diagnosing schizophrenia, and determine associations with prognosis by analysing routine outcomes.Design Four algorithms were developed on deidentified mental healthcare data and applied to ascertain recorded symptoms over the 3 months following first presentation to a mental healthcare provider in a cohort of patients with a primary schizophreniform disorder (ICD-10 F20-F29) diagnosis.Setting and participants From the electronic health records of a large secondary mental healthcare provider in south London, 9323 patients were ascertained from 2007 to the data extraction date (25 February 2020).Outcomes The primary binary dependent variable for logistic regression analyses was any negative outcome (Mental Health Act section, >2 antipsychotics prescribed, >22 days spent in crisis care) over the subsequent 2 years.Results Final adjusted models indicated significant associations of this composite outcome with baseline somatic passivity (prevalence 4.9%; adjusted OR 1.61, 95% CI 1.37 to 1.88), thought insertion (10.7%; 1.24, 95% CI 1.15 to 1.55) and thought withdrawal (4.9%; 1.36, 95% CI 1.10 to 1.69), but not independently with thought broadcast (10.3%; 1.05, 95% CI 0.91 to 1.22).Conclusions Symptoms traditionally central to the diagnosis of schizophrenia, but under-represented in current diagnostic frameworks, were thus identified as important predictors of short-term to medium-term prognosis in schizophreniform disorders.…”
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Low-Altitude Unmanned Aerial Vehicle Technology: Current Status and Prospects by Jun Zhang, Lei Chen, Zhijie Gao, Yingxian Duo

“…Through in-depth analysis of the current status and research trends across these three domains, the study proposes future technical directions focusing on bionic configurations, composite materials, multi-source fusion positioning, and hybrid intelligent algorithms. …”
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SERS nose arrays based on a signal differentiation approach for TNT gas detection by Peitao Dong, Haiyang Yang, Tianran Wang, Siyue Xiong, Li Kuang, Weihong Qi, Xiaohua Chen, Lixia Yang, Qiuyun Fan, Dingbang Xiao, Xuezhong Wu

“…Label-free surface-enhanced Raman spectroscopy (SERS) has been demonstrated to be capable of capturing rich compositional information from the sample being tested. …”
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Predicting Index Trend Using Hybrid Neural Networks with a Focus on Multi-Scale Temporal Feature Extraction in the Tehran Stock Exchange by Mohammad Osoolian, Ali Nikmaram, Mahdi Karimi

“…A wide array of predictive modeling techniques have been meticulously investigated, spanning from conventional statistical methodologies to more sophisticated machine learning algorithms. The primary focus of this research endeavor revolves around the predictive analysis of the Tehran Stock Exchange (TSE) Composite Index, wherein a novel hybrid neural network framework is employed. …”
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Sustainable power solutions for next-generation medical devices by Ye Liang, Chi Zhang, Rubing Lin, Junqing Lin, Jishizhan Chen

“…This review uniquely evaluates energy harvesting techniques through the lens of 'functionally cooperating systems'—emphasizing how synergistic integration of smart materials, adaptive algorithms, and physiological interfaces can overcome fundamental trade-offs between biocompatibility, power density, and clinical viability.…”
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Collision Analysis and Motion Control Based on Lift-Type Power Catwalk by Jia Chen, Li Xiong, Honghui Wang, Yi Yang

“…Based on this model, a composite disturbance rejection control law was designed, integrating sliding-mode speed planning with active disturbance rejection speed tracking. …”
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An investigation into the zoning of ecosystem sensitivity control areas in Mentougou District (Beijing, China). by Xiaodan Li, Haoyu Tao, Jing Li, Zhen Liu, Zhiping Liu

“…These values are processed through mathematical overlay algorithms, which generate composite results with different sensitivity levels. …”
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The impact of artificial intelligence on accounting practices: an academic perspective by Talal Fawzi Alruwaili, Mahfoudh Hussein Mgammal

“…Implementation success depends on directed education programs and robust regulations and ethical assessment to handle risks such as algorithmic biases, workforce displacement and integrity concerns. …”
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Machine Learning in Maritime Safety for Autonomous Shipping: A Bibliometric Review and Future Trends by Jie Xue, Peijie Yang, Qianbing Li, Yuanming Song, P. H. A. J. M. van Gelder, Eleonora Papadimitriou, Hao Hu

“…The findings reveal a robust cooperative network among journals, researchers, research institutions, and countries or regions, underscoring the interdisciplinary nature of this research domain. …”
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Dilated cardiomyopathy evaluation with Imagenomics: combining multimodal cardiovascular imaging and genetics by Kristian Galanti, Ghaith Sharaf Dabbagh, Fabrizio Ricci, Sabina Gallina, Roberta Giansante, Ron Jacob, Edmond Obeng‐Gyimah, Leslie T. Cooper Jr, Sanjay K. Prasad, David H. Birnie, Andrew P. Landstrom, Selma F. Mohammed, Saidi Mohiddin, Mohammed Y. Khanji, Anwar A. Chahal

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A data science pipeline applied to Australia's 2022 COVID-19 Omicron waves by James M. Trauer, Angus E. Hughes, David S. Shipman, Michael T. Meehan, Alec S. Henderson, Emma S. McBryde, Romain Ragonnet

“…We developed a package for the construction of infectious disease models, integrated it with several open-source libraries and applied this composite pipeline to multiple data sources that provided insights into Australia's 2022 COVID-19 epidemic. …”
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Multi-focus image fusion using adaptive patch rendering anisotropic diffusion filter by Sandhya Tatekalva, G. Tirumala Vasu, Samreen Fiza, Hanumantharao Bitra

“…The experimental results reveal that APRADF-based fusion outperforms state-of-the-art algorithms in subjective and objective analysis.…”
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