High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…IntroductionImmunophenotyping is a powerful tool for grading disease severity, aiding in diagnosis, predicting clinical response, and guiding the development of novel therapeutics.MethodsThis pilot study employs high parameter immunophenotyping panels (15 markers for dog, 12 for cat) and leverages unsupervised clustering to identify immune cell populations. …”
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Advanced Soft Computing Ensemble for Modeling Contaminant Transport in River Systems: A Comparative Analysis and Ecological Impact Assessment by Jafar Chabokpour

“…The research employed various techniques, including Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Support Vector Regression (SVR), and Genetic Algorithms (GA), to predict pollutant concentrations and estimate transport parameters. …”
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A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…The proposed model combines an Artificial Neural Network and Support Vector Machine as base classifiers and employs a Random Forest as a meta-classifier to fuse predictions, improving detection performance. Recursive Feature Elimination is utilized for optimal feature selection, while SHapley Additive exPlanations (SHAP) provide both global and local interpretability of the model’s decisions. …”
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Resolving Covid-19 with Blockchain and AI by Suyogita Singh, Satya Bhushan Verma

“…In that review, many potential blockchain applications were discovered; however, the majority of them were still in their infancy, and it couldn’t yet be predicted how they could contribute to the fight against COVID-19 through the use of platforms, access kinds, and consensus algorithms. …”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Improving survival time and predicting prognosis for distinct molecular profiles is substantial. …”
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Driver drowsiness shield (DDSH): a real-time driver drowsiness detection system by Archita Bhanja, Dibyajyoti Parhi, Dipankar Gajendra, Kreetish Sinha, Arup Kumar Sahoo

“…An algorithm has been proposed to classify eye states as open or closed using Transfer Learning based on the MobileNet architecture. …”
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Identification of common genetic variation that modulates alternative splicing. by Jeremy Hull, Susana Campino, Kate Rowlands, Man-Suen Chan, Richard R Copley, Martin S Taylor, Kirk Rockett, Gareth Elvidge, Brendan Keating, Julian Knight, Dominic Kwiatkowski

“…The functional consequences of these SNPs could not be predicted using bioinformatic algorithms. Our findings suggest that phenotypic variation in splicing patterns is determined by the presence of SNPs within flanking introns or exons. …”
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Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…The primary aim is to identify the most effective model for predicting energy consumption based on historical data, contributing to the relationship between energy systems and urban well-being. …”
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Improving Sharpness-Aware Minimization Using Label Smoothing and Adaptive Adversarial Cross-Entropy Loss by Tanapat Ratchatorn, Masayuki Tanaka

“…Recent advances in learning algorithms have identified loss surface sharpness as an effective metric for reducing the generalization gap. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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AIoT-Driven Human Activity Recognition for Versatile Framework on Multipurpose Applications by Nanik Triwahyuni, Eni Wardihani, Aminuddin Rizal, Samuel Beta, Ricky Sambora, Rindang Oktaviani

“…The framework integrates sensor data from wearable IoT devices, which is then processed by AI algorithms to classify and predict human activities in real-time. …”
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Parametric Optimization of Train Brake Pad Using Reverse Engineering with Digital Photogrammetry 3D Modeling Method by P Paryanto, Muhammad Faizin, R Rusnaldy

“…Additionally, RE and parametric modeling could assist in creating durable, cost-effective alternatives, and predicting appropriate replacements.…”
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Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina by Džana Bašić-Čičak, Jasminka Hasić Telalović, Lejla Pašić

“…Additionally, we developed machine learning classifiers to differentiate between the two groups using microbial abundance and predicted functional pathways. Methods: A total of 60 gut microbiome samples (16S rRNA sequences) were analyzed, with 44 from children with ASD and 16 from neurotypical children. …”
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COVID-19 REINFECTION: DOES IT MATTER? by E. Füsun Karaşahin, Ömer Karaşahin, Mehtap Hülya Aslan

“…Conclusion: This study demonstrated that the frequency of COVID-19 reinfection is higher than predicted. The complex algorithms recommended by international health institutions make it difficult to detect these cases. …”
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Treatment Tactics and Complications After Surgical Treatment of HIV-Infected Patients With Extra-Articular Fractures of the Long Bones of Extremities by N. G. Doronin, S. N. Khoroshkov, M. V. Naumenko

“…Expansion of research in this area with an increase in the number of observed contingents will make it possible to develop a scientifically based scale for predicting the development of possible postoperative complications in this category of patients.…”
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Hydrologic model calibration approaches for highly regulated river basin: A comprehensive assessment by Md Rasel Sheikh, Paulin Coulibaly

“…The study highlights the challenges of using reservoir outflow as an operational control, which leads to poor water level predictions, reinforcing the need for more region-specific operational constraints. …”
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Coupled memory sampled-data control for fractional stochastic wind energy conversion models by Girija Panneerselvam, Prakash Mani

“…Theoretically, this paper introduces a permanent magnet synchronous generator (PMSG)-based WECS, which is crucial in predicting and optimizing system behavior without physical implementation and also useful in analyzing the various operating conditions. …”
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ML-Enabled Millimeter-Wave Software-Defined Radio With Programmable Directionality by Marc Jean, Murat Yuksel, Xun Gong

“…We design and implement Q-learning, Double Q-learning, and Deep Q-learning algorithms that passively inspect the Received Signal Strength (RSS) of the mmWave beam and autonomously determine the predicted AoA. …”
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AgrUNet: A Multi-GPU UNet Based Model for Crops Classification by Andrea Miola, Enrico Calore, Sebastiano Fabio Schifano

“…The deployment of high-resolution satellite missions, like LandSat and Copernicus Sentinel, combined with AI Deep Learning (DL) methodologies has revolutionized Earth Observation science, enabling studies on yield predictions, soil classifications, and crop mappings on large areas, and the analysis and processing of Big Data using innovative approaches. …”
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Evaluation of underground hard rock mine pillar stability using gene expression programming and decision tree‐support vector machine models by Mohammad H. Kadkhodaei, Ebrahim Ghasemi, Jian Zhou, Melika Zahraei

“…This study mainly focuses on developing two practical models to predict pillar stability status. For this purpose, two robust models were developed using a database including 236 case histories from seven underground hard rock mines, based on gene expression programming (GEP) and decision tree‐support vector machine (DT‐SVM) hybrid algorithms. …”
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