Hybrid intelligence framework for optimizing shear capacity of lightweight FRP-reinforced concrete beams by Iman Faridmehr, Moncef L. Nehdi, Mohammad Ali Sahraei, Kiyanets Aleksandr Valerievich, Chiara Bedon

“…The hybrid intelligence models reached superior predictive accuracy over traditional codes, achieving R2 values of 0.89. …”
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Comprehensive analysis of pyroptosis-related genes in psoriasis and targeted gene editing of CASP1 and CASP5 using lipid nanoparticles to alleviate skin inflammation by Gexiao Xu, Guanyi Ma, Jiachen Sun, Xiaoyan Yu, Jie Sun, Bing Gao

“…The generated risk score model demonstrated robust performance in external validation datasets, showing strong predictive power for psoriasis severity and immune infiltration. …”
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Multimodal fusion radiomic-immunologic scoring model: accurate identification of prostate cancer progression by Zhonglin Zhang, Huan Liu, Xiling Gu, Yang Qiu, Jiangqing Ma, Guangyong Ai, Xiaojing He

“…The RDIS model demonstrates good specificity in further predicting bone metastases and castration-resistant prostate cancer (CRPC). …”
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Critical structural and functional roles for the N-terminal insertion sequence in surfactant protein B analogs. by Frans J Walther, Alan J Waring, Jose M Hernandez-Juviel, Larry M Gordon, Zhengdong Wang, Chun-Ling Jung, Piotr Ruchala, Andrew P Clark, Wesley M Smith, Shantanu Sharma, Robert H Notter

“…Surface plasmon resonance (SPR), predictive aggregation algorithms, and molecular dynamics (MD) and docking simulations further suggested a preliminary model for dimeric Super Mini-B, in which monomers self-associate to form a dimer peptide with a "saposin-like" fold. …”
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A prospective, multicenter analysis of the integrated 31-gene expression profile test for sentinel lymph node biopsy (i31-GEP for SLNB) test demonstrates reduced number of unnecess... by J. Michael Guenther, Andrew Ward, Brian J. Martin, Mark Cripe, Rohit Sharma, Stanley P. Leong, Joseph I. Clark, John Hamner, Timothy Beard

“…Results No patients with < 5% i31-GEP predicted risk had a positive SLNB (0/35). Propensity matching demonstrated an 18.5% reduction in SLNBs performed (43.7% vs. 62.2%. p < 0.001). …”
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Deciphering the role of metal ion transport-related genes in T2D pathogenesis and immune cell infiltration via scRNA-seq and machine learning by Zuhui Pu, Zuhui Pu, Tony Bowei Wang, Ying Lu, Ying Lu, Zijing Wu, Zijing Wu, Yuxian Chen, Ziqi Luo, Xinyu Wang, Lisha Mou, Lisha Mou

“…We employed 12 machine learning algorithms to develop predictive models and assessed immune cell infiltration using single-sample gene set enrichment analysis (ssGSEA). …”
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Combined endodontic treatment: microbiological aspects by using scanning electronical microscopy by V. N. Tsarev, A. V. Mitronin, M. S. Podporin, D. A. Ostanina, E. V. Ippolitov, V. A. Mitronin

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Enhancing noninvasive pancreatic cystic neoplasm diagnosis with multimodal machine learning by Wei Huang, Yue Xu, Zhao Li, Jun Li, Qing Chen, Qiang Huang, Yaping Wu, Hongtan Chen

“…The study’s results indicate that our multimodal machine learning algorithm, which integrates both clinical and imaging data, significantly outperforms single-source data algorithms. …”
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Fractional Optimizers for LSTM Networks in Financial Time Series Forecasting by Mustapha Ez-zaiym, Yassine Senhaji, Meriem Rachid, Karim El Moutaouakil, Vasile Palade

“…Considering four metrics (Sharpe ratio, directional accuracy, cumulative return, and MSE), the results show that fractional orders can significantly enhance prediction accuracy for moderately volatile stocks, especially among lower-cap assets. …”
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The Performance of an ML-Based Weigh-in-Motion System in the Context of a Network Arch Bridge Structural Specificity by Dawid Piotrowski, Marcin Jasiński, Artur Nowoświat, Piotr Łaziński, Stefan Pradelok

“…In civil and bridge engineering, they can facilitate the identification of specific patterns through the analysis of data acquired from structural health monitoring (SHM) systems. To evaluate the prediction capabilities of ML, this study examines the performance of several ML algorithms in estimating the total weight and location of vehicles on a bridge using strain sensing. …”
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Review of Urban Rail Transit Ticket Clearing Methods by WANG Yao, LI Jiming, GAO Shen, LIU Guangjie, XU Zhongquan

“…A more scientific and reasonable clearing scheme needs to further strengthen big data research on the AFC (automatic fare collection) system, and more importantly, relying on existing technologies and computing models is required to strengthen the real-time analysis and overtime prediction accuracy of passengers′ path selection behavior, so as to enable the clearing mechanism accurately make adaptive dynamic adjustments according to actual operating conditions.…”
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MFGC-Net: Bridging and Fusing Multiscale Features and Global Contexts for Multitask Sea Ice Fine Segmentation by Tianen Ma, Xinwei Chen, Linlin Xu, Pengfei Ma, Peilin Yu

“…Sea ice segmentation from synthetic aperture radar (SAR) imagery is a key task in polar sea ice monitoring, which is crucial for global climate prediction and polar route planning. However, the existing sea ice segmentation algorithms for SAR images often fail to consider long-range contextual dependencies when capturing multiscale features, resulting in an inability to fully exploit multiscale global contextual information. …”
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Zooming into Berlin: tracking street-scale CO2 emissions based on high-resolution traffic modeling using machine learning by Max Anjos, Fred Meier

“…Using data-driven algorithms, traffic counts, spatio-temporal features, and meteorological data, our model predicted hourly traffic flow, average speed, and CO2 emissions for passenger cars (PC) and heavy-duty trucks (HDT) at the street scale in Berlin. …”
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Identifying and mapping open-boll cotton fields in the southeastern United States with time series PhenoCam, Sentinel-2 and Sentinel-1 images by Fang Liu, Xiangming Xiao, Yuanwei Qin, Luo Liu

“…Timely and accurate information on the spatial distribution of cotton fields is vital for cotton management and production prediction. In this study, we combined hourly PhenoCam pictures and time series Sentinel-2 images and identified the unique white feature in the cotton open-boll period from spectroscopy analysis. …”
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Hierarchical Sensing Framework for Polymer Degradation Monitoring: A Physics-Constrained Reinforcement Learning Framework for Programmable Material Discovery by Xiaoyu Hu, Xiuyuan Zhao, Wenhe Liu

“…This paper introduces a novel physics-informed deep learning framework that integrates multi-scale molecular sensing data with reinforcement learning algorithms to enable intelligent characterization and prediction of polymer degradation dynamics. …”
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Real-Time Anomaly Detection in IoMT Networks Using Stacking Model and a Healthcare- Specific Dataset by Hadjer Goumidi, Samuel Pierre

“…The proposed model was evaluated on both the UNSW-NB15 and the new medical dataset, achieving significant improvements across key metrics such as accuracy, precision, recall, and F1-score. A real-time prediction analysis further demonstrated its ability to detect anomalies efficiently during live data transmission, validating its suitability for detecting anomalies in real-time scenarios.…”
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Performance Statistics of Autoregressive Short and Ultrashort Signal Detectors by V. M. Kutuzov, V. P. Ipatov, S. S. Sokolov

“…The obtained detection and noise immunity characteristics for ultrashort and short signal samples allow us to recommend the parametric Burg harmonic mean method, implemented on the basis of a forward and backward linear prediction algorithm, as an independent signal processing method under strict restrictions imposed on the size of the analyzed sample of spatial-temporal signals.…”
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Exploring the binding potential of natural compounds to carbonic anhydrase of cyanobacteria through computer-based simulations by Archana Padhiary, Showkat Ahmad Mir, Aiswarya Pati, Binata Nayak

“…Strategically we explore the Structural-Activity Relationship (SAR) of natural compounds to the reported sulphonamide inhibitors. Further, prediction-based online web servers such as pkCSM and SwissADME were used to determine the ADMET properties of the SAR molecules. …”
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Technological Advancements in Human Navigation for the Visually Impaired: A Systematic Review by Edgar Casanova, Diego Guffanti, Luis Hidalgo

“…Current navigation algorithms were also identified in the review with methods including obstacle detection, path planning, and trajectory prediction, applied to technologies such as ultrasonic sensors, RGB-D cameras, and LiDAR for indoor navigation, as well as stereo cameras and GPS for outdoor navigation. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

“…The average accuracy with augmentation and optimal fine-tuning is 98%. In addition, prediction scores in terms of precision, recall, and F1-score are obtained to visualize the rate of mispredictions across the disease classes. …”
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