A human single-neuron dataset for object recognition by Runnan Cao, Peter Brunner, Nicholas J. Brandmeir, Jon T. Willie, Shuo Wang

“…We employed two sets of naturalistic object images from leading datasets extensively used in primate neural recordings and computer vision models: we recorded 1204 neurons using the ImageNet stimuli, which included broader object categories (10 different images per category for 50 categories), and we recorded 512 neurons using the Microsoft COCO stimuli, which featured a higher number of images per category (50 different images per category for 10 categories). …”
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Miniaturized Near-Infrared Analyzer for Quantitative Detection of Trace Water in Ethylene Glycol by Qunling Luo, Zhiqiang Guo, Danping Lin, Boxue Chang, Yinlan Ruan

“…To enhance predictive accuracy of water trace, spectral data were preprocessed using smoothing combined with first-derivative processing, and optimal selection of absorption wavelength feature was performed using interval Partial Least Squares (iPLS). …”
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The Willingness to Pay for Cider Products: Results of a Survey on Habits and Consumption Behavior by Eric Le Fur, J. François Outreville

“…To accommodate the feature of a significant proportion of zero or negative premiums in dependent variables, the Heckman two-stage estimation procedure is performed…”
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Complex Microphthalmia due to a Homozygous Novel Variant in SIX Homeobox 6 Gene by Mayank Nilay, Amita Moirangthem

“…In silico structural modeling showed that the c.549C>G variant which lies in the homeobox domain might alter the SIX6 protein structure. …”
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Joint Prediction of U.S. Rice Yields and Methane Emissions: A Machine Learning Approach by Jameson Augustin, Munisamy Gopinath, Berna Karali, Yuhan Rao

“…We use eight different machine learning models for predictions. XGBoost and EBM emerge as top performers, accurately predicting yields and emissions, individually, without overfitting. …”
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Exploring the role of technology through collaborative learning in Ecuadorian language education by Heidi Marlen Marriott Toledo, Jose Miguel Campuzano Díaz

“…As a result, many advantages were found to the potential replication of these models in the Ecuadorian EFL classroom. Similarly, some criteria were developed to properly assess their feasibility for a more accurate outcome of the potential effectiveness of these models in the Ecuadorian EFL classrooms. …”
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RUL forecasting for wind turbine predictive maintenance based on deep learning by Syed Shazaib Shah, Tan Daoliang, Sah Chandan Kumar

“…By employing a multi-parametric attention-based DL approach that bypasses feature engineering, thereby minimizing the risk of human error, two models—ForeNet-2d and ForeNet-3d—are proposed. …”
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Determination of fracture mechanics parameters on a base of local displacement measurements by Yu. G. Matvienko, V.S. Pisarev, S. I. Eleonsky

“…A verification of the technique is performed by comparing experimental results with analogous data of FEM modelling. …”
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Analysis of multiple faults in induction motor using machine learning techniques by Puja Pohakar, Ravi Gandhi, Surender Hans, Gulshan Sharma, Pitshou N. Bokoro

“…Through ensemble learning and feature selection, the models cope well with big data sets with enhanced fault classification accuracy and robustness against noise. …”
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Two-Phase Multi-Point Design Exploration of Submerged Nacelles for Marine Propulsive Pump Installation by Filippo Avanzi, Andrea Magrini, Francesco De Vanna

“…Outboard Dynamic-inlet Waterjets (ODW) are axisymmetric units, powered by a self-contained pump, that, by processing a uniform undisturbed streamtube, can operate more efficiently than conventional marine propulsors. This feature also provides methodological convenience, enabling accurate numerical investigations of the system alone using 2D axisymmetric models. …”
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Unveiling the impact of bisphenol a exposure on gene expression and immune response in diabetic nephropathy through integrative toxicogenomics and molecular dynamics approaches by Yan Zhang, Shan Lu, Yijun Dong, Jin Shang

“…Enrichment analyses were performed to elucidate the functional implications of these genes, and machine learning models (LASSO, RF, SVM-RFE) were employed to identify key feature genes. …”
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Economic Aspects of Cash Access Problems by Arkadiusz Manikowski

“…Further research should include econometric modeling using logit/probit models. Originality/value: The obtained results are the first on the impact of access to cash on financial exclusion in Poland and consistent with the situation in other European countries. …”
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Domain adaptive English aspect word extraction method based on bidirectional long and short-term memory network and multi-head attention mechanism by Tianxiao Wang

“…Experimental results show that the proposed method performs better than multiple baseline models.…”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…Abstract Hearing loss poses immense burden worldwide and early detection is crucial. The accurate models identify high-risk groups, enabling timely intervention to improve quality of life. …”
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A systematic benchmark of integrative strategies for microbiome-metabolome data by Loïc Mangnier, Antoine Bodein, Margaux Mariaz, Alban Mathieu, Marie-Pier Scott-Boyer, Neerja Vashist, Matthew S. Bramble, Arnaud Droit

“…These methods address key research goals, including global associations, data summarization, individual associations, and feature selection. Through realistic simulations, we identified the best-performing methods and validated them on real gut microbiome datasets, revealing complementary biological processes across the two omic layers. …”
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Aflatoxin contamination level estimation in food using reflectance multispectral imaging based system by H.M.P.S. Madushan, H.L.P. Malshan, K.K. Abewickrama, H.M.V.R. Herath, Roshan Godaliyadda, M.P.B. Ekanayake, A.D.S.N.P. Athukorala, M.D.H.M. Kumari, Darsha Udayanga

“…A functional relationship between the Bhattacharyya distance of noncontaminated samples to contaminated samples and aflatoxin contamination levels was modeled as a first order polynomial with an R2 value of 0.9723.…”
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Intervention of machine learning in bladder cancer research using multi-omics datasets: systematic review on biomarker identification by Blessy Kiruba, P. S. Athul Narayan, Badhari Raj, S. Rohieth Raj, Sam George Mathew, Sudhakaran Sajitha Lulu, Vino Sundararajan

“…A substantial amount of multi-omics data collected from clinics and laboratories are utilized to train powerful ML models such as Support Vector Machines (SVM), random forests (RF), decision trees (DT), and gradient boosting methods (e.g., XGBoost) to perform complex tasks, including biomarker discovery, classification of subtypes and feature selection. …”
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A Search for FDA Approved Drugs with Multiple Antiemetic Targets: A Computational-Based Drug Repositioning Study by Abdulmajeed Yunusa*1, Albashir Tahir1,2

“…The ligand-based pharmacophore modelling further emphasized the distinct characteristics of these drugs, and the most common pharmacophore feature shared among these compounds is the hydrogen bond acceptor. …”
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SYNTHESIS OF VOLTAGES OF UNIFORM PWM IN TIME REGULATION by A. G. Stryzhniou, A. N. Rusakovich, A. A. Shykhau

“…It is specified that harmonic frequencies wi = w0/q change in inverse proportion to magnitude of parameter q during a process of regulation and there is a replacement of a fundamental frequency by frequencies of higher harmonics.The offered approach allows to synthesize voltage of uniform single and multiple PWM pulses and to perform their comparative and qualitative analysis and the obtained expressions can be used at modeling of AC motor work. …”
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The association between immune cells and acute kidney injury: insights from Mendelian randomization by Xianzhen Yang, XiaoLei Zhang, Denglu Zhang, Shengtian Zhao

“…Sensitivity analyses, including leave-one-out and other MR analysis models, were performed.Results At the significance level corrected by Bonferroni, 9 immune phenotypes, including CD25 on IgD + CD24- B cell, were associated with ARF; 4 immune phenotypes, including SSC-A on plasmacytoid dendritic cell, were associated with rapid kidney function decline. …”
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