Peel of pumpkin (Cucurbita pepo) diets boost growth, digestive-absorptive functions, immune-antioxidant indices, and regulate immunomodulatory genes and mTOR/MAPK-P38/apoptosis sig... by Rowida E. Ibrahim, Gehad E. Elshopakey, Elsayed M. Younis, Abdelwahab A. Abdelwarith, Asmaa Yaseen, Tarek Khamis, Simon J. Davies, Afaf N. Abdel Rahman

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Constructing potassium and hydroxyl co-doped dual-dipole structures on highly active 3D g-C3N4 surfaces for highly boosting photocatalytic hydrogen peroxide production efficiency i... by Jiaxing Wu, Jiajie Yu, Fan Fan, Runhua Li, Mengxiang Wang, Gang Li, Yuting Wang, Yongpeng Cui, Daoqing Liu, Yajun Wang, Wenqing Yao

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Causes of baseflow variation in an inland river watershed of Northwest China by Mengwei Song, Hailong Liu, Quanlong Wu, Aminjon Gulakhmadov, Firdavs Shaimuradov

“…Furthermore, the impacts of hydroclimatic variables and vegetation conditions on baseflow were quantitatively evaluated through explainable machine learning approaches, specifically Categorical Boosting (CatBoost) coupled with SHapley Additive exPlanations (SHAP) analysis. …”
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Enhancing Crop Type Mapping in Data-Scarce Regions Through Transfer Learning: A Case Study of the Hexi Corridor by Jingjing Mai, Qisheng Feng, Shuai Fu, Ruijing Wang, Shuhui Zhang, Ruoqi Zhang, Tiangang Liang

“…Various algorithms, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and TrAdaBoost, were employed to transfer knowledge from the source domain to the target domain for crop type mapping. …”
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Fuel prices and economic activity: time and frequency analysis for selected European countries by Andrzej Geise, Mariola Piłatowska

“… The effects of fuel prices on economic activity are still being investigated, as oil and gas are critical inputs in the production process. This study examines the relationship between fuel prices and macroeconomic aggregates both in the time domain and frequency domain in three selected countries of Germany and Poland as net oil importers and Norway as a net oil exporter for the period 1995Q1–2021Q3. …”
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An Interpretable Machine Learning-Based Hurdle Model for Zero-Inflated Road Crash Frequency Data Analysis: Real-World Assessment and Validation by Moataz Bellah Ben Khedher, Dukgeun Yun

“…The research employs a two-stage modeling process using CatBoost. The first stage uses binary classification to identify road segments with potential crash occurrences, applying a customized loss function to tackle data imbalance. …”
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A novel data processing approach to detect fraudulent insurance claims for physical damage to cars by Ahmet Yücel

“…The main objective of this manuscript is to demonstrate a novel data processing system and its potential for use in data classification. …”
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Analysis of Data and Feature Processing on Stroke Prediction using Wide Range Machine Learning Model by Untari Novia Wisesty, Tjokorda Agung Budi Wirayuda, Febryanti Sthevanie, Rita Rismala

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Power Converter Design for Pulsed Electric Field-Based Milk Processing: A Proof of Concept by Julieta Domínguez-Soberanes, Omar F. Ruiz-Martinez, Fernando Davalos Hernandez

“…The proposed converter is simulated using PLECS software (4.9.6 version) under impedance change scenarios that emulate variations in milk throughout the entire process. This research proposes the modification of a classic Vienna rectifier (adding an MBC—Multilevel Boost Converter structure) to supply a pulsating signal that could be used for low-temperature processes of milk to guarantee proper pasteurization. …”
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A pipeline for processing hyperspectral images, with a case of melanin-containing barley grains as an example by I. D. Busov, M. A. Genaev, E. G. Komyshev, V. S. Koval, T. E. Zykova, A. Y. Glagoleva, D. A. Afonnikov

“…Nowadays, this analysis is used more and more widely, so the development of hyperspectral image processing methods is an urgent task. This paper presents a hyperspectral image processing pipeline that includes: preprocessing, basic statistical analysis, visualization of a multichannel hyperspectral image, and solving classification and clustering problems using machine learning methods. …”
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Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang, Xintian Liu

“…Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the welding material and welding process, the weld seam is prone to various defects such as cracks, pores, undercutting, and incomplete fusion, which can weaken the joint and even lead to product failure. …”
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Processes of Commercial Territorialization in the Polycentric Region of the Marche. New Commercial Hierarchies in the Doric Capital by Carmelo Maria Porto

“…Understanding these new commercial hierarchies represents a valid tool for planning proper territorial policies and boosting more resilient-based processes which aim at restoring the primary role of a city center that has slowly lost its social appeal and its functional status-quo within the city’s metropolitan area and in the urban network of the Marche.…”
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The Role of Mineral Sea Water Bonding Process with Graphite-Aluminum Electrodes as Electric Generator by Satryo B. Utomo, Winarto, Agung S. Widodo, I. N. G. Wardana

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Data-driven price trends prediction of Ethereum: A hybrid machine learning and signal processing approach by Ebenezer Fiifi Emire Atta Mills, Yuexin Liao, Zihui Deng

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Implementing and evaluating the quality 4.0 PMQ framework for process monitoring in automotive manufacturing by Fathy Alkhatib, Mohamed Allam, Vikas Swarnakar, Juman Alsadi, Maher Maalouf

“…The study relied on various ML algorithms, such as Decision Trees (DT), Random Forest (RF), Gradient Boosting Machine (GBM), Logistic Regression (LR), Support Vector Machine (SVM), and Artificial Neural Networks (ANN), to classify and predict defects in engine valves during manufacturing processes. …”
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A Novel Optimized Hybrid VMD-PCA-XGBoost Model for Forecasting Precipitation: Exemplified by the Beijing-Tianjin-Hebei Study Region in China by Qiaoli Kong, Qian Li, Qi Bai, Xiaolong Mi, Joseph Awange, Shi Wang, Yi Yang, Guoli Bo

“…In this study, we propose a novel hybrid model, variational mode decomposition-principal component analysis-extreme gradient boosting (VMD-PCA-XGBoost), which integrates VMD for effective signal processing, PCA for dimensionality reduction, and XGBoost for enhancing predictive accuracy. …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…The QoS modeling task was carried out using MBPerf pre-processed dataset. Three (3) classification algorithms including Random Forest (RF), Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) were trained using the QoS dataset and then evaluated in order to determine the most effective model based on certain evaluation metrics – accuracy, precision, F1-Score and recall. …”
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Does tourist generated content (TGC) boost tourist motivation better? Dual verification via ISM-DEMATEL approach and experimental study(旅游者照片更能提升人们的旅游意愿吗？)... by 张若愚(ZHANG Ruoyu), 张高军(ZHANG Gaojun), 蒋婧怡(JIANG Jingyi), 程泷(CHENG Long)

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Document Relevance Filtering by Natural Language Processing and Machine Learning: A Multidisciplinary Case Study of Patents by Raj Bridgelall

“…These models include extreme gradient boosting, random forest, and support vector machines; a deep artificial neural network; and three natural language processing methods: latent Dirichlet allocation, non-negative matrix factorization, and k-means clustering of a manifold-learned reduced feature dimension. …”
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A Quality Soft Sensing Method Designed for Complex Multi-process Manufacturing Procedures by Kaixiang PENG, Xin QIN, Jiahao WANG, Hui YANG

“…Multi-sensor process variables are segmented by the procedure according to the process knowledge. …”
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