Research of fracture mechanism of steel grade P91 on impact bending after preheat treatment before welding by F. I. Panteleenko, V. A. Zelenin, A. L. Minkov

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NEW ORGANIZATION PROCESS OF FEATURE SELECTION BY FILTER WITH CORRELATION-BASED FEATURES SELECTION METHOD by Olga Solovei

“… The subject of the article is feature selection techniques that are used on data preprocessing step before building machine learning models. …”
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Impact wear behavior of austenitic steel bucket teeth based on machine learning by Zhihui Cai, Jianfeng Yan, Yandong Qiao, Rongjie Li, Yanchun Shi, Junping Zhang, Zhixiong Zhang

“…A particle swarm optimization support vector machine was employed to accurately predict wear depth. The mean values of the determination coefficient (R2) before and after feature selection were 0.96294 and 0.98074, respectively, further validating the accuracy of the feature selection process and providing a ranking of importance for identifying key factors to enhance wear resistance.…”
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Introduction: Titanium alloys containing the β phase have much better corrosion resistance. Some alloying elements, such as Mo, stabilize this phase. Among the Ti alloys that conta... by Arezoo Pourshoja, karim Avak, Maziyar Azadbeh, Mohamadreza Etminanfar, Mehdi Ojaghi

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Educational and career aspirations of secondary school students in Poland and Ukraine by Danuta Wosik-Kawala, Teresa Zubrzycka-Maciąg

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Selective Separation of Scandium in Acidic Water Using Carboxyl Functionalized Covalent Phosphonitrile Polymers by Yu BAI, Ayinuer WUSHUER, Lei OUYANG, Lijin HUANG, Qin SHUAI

“…Both materials have the ability to selectively adsorb Sc(III), with Kd values of 5.1×102mL/g and 4.0×103mL/g for Sc(III), respectively. …”
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An Evaluation of the Possibility of Using Buckwheat Hulls as an Addition to Bread by Joanna Maria Klepacka, Marta Czarnowska-Kujawska

“…The test material consisted of a control bread (without the addition of husk), bread with 10 and 20% husk (mixed with flour at the stage of dough preparation), and bread with a surface sprinkled with buckwheat husk (25 g) before baking. The semi-consumer evaluation involved 33 pre-trained persons who determined the degree of acceptance (desirability) of the selected bread’s sensory characteristics (colour, texture, smell and taste) using the nine-point hedonic scale. …”
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Investigating the Effects of Spectroscopic Method in Estimating Soluble Solid Content Values and Firmness of Cherries from an Environmental Point of View: Prediction of Environment... by Shirzad Naim, Shahgholi Gholamhossein, Ardabili Sina, Szymanek Mariusz

“…Next, by combining the feature selection method (relief) and the spectrometry method (vis-NIR), the effective wavelengths were extracted to estimate the soluble solid content (SSC) values and firmness of the cherry product. …”
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Chemical Composition and Sensory Profile of Sauerkraut from Different Cabbage Hybrids by Elena V. Yanchenko, Galina S. Volkova, Elena V. Kuksova, Ivan I. Virchenko, Aleksey V. Yanchenko, Elena M. Serba, Maria I. Ivanova

“…The present research objective was to test several cabbage hybrids for natural fermentation, microbiological parameters, and native sugar content after four months of storage. The study featured twelve new-generation white cabbage hybrids of Russian selection and sauerkraut foods. …”
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Ensemble learning approach for prediction of early complications after radiotherapy for head and neck cancer using CT and MRI radiomic features by Benyamin Khajetash, Seied Rabi Mahdavi, Alireza Nikoofar, Lee Johnson, Meysam Tavakoli

“…Combined $$T_1$$ weighted image-based models RT-BN, RT-LSVM-BN and RT-NN-LSVM-BN also show good performance having AUC values 0.97, 0.92, and 0.90, respectively. These results show that radiomic features from MR images obtained before radiotherapy can be used in addition to other metrics as personalized and unique biomarkers for prediction of early-onset xerostomia. …”
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5-hydroxymethylcytosine sequencing of plasma cell-free DNA identifies epigenomic features in prostate cancer patients receiving androgen deprivation therapies by Qianxia Li, Chiang-Ching Huang, Shane Huang, Yijun Tian, Jinyong Huang, Amirreza Bitaraf, Xiaowei Dong, Marja T. Nevalainen, Manishkumar Patel, Jodie Wong, Jingsong Zhang, Brandon J. Manley, Jong Y. Park, Manish Kohli, Elizabeth M. Gore, Deepak Kilari, Liang Wang

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Effect of repeated pressing on the fracture resistance of heat-pressed glass ceramic crowns by Mohamed Magdy El Shazli, Amr El-Etreby, Fatma Adel Mohamed

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Forecasting yield and market classes of Vidalia sweet onions: A UAV-based multispectral and texture data-driven approach by Marcelo Rodrigues Barbosa Júnior, Lucas de Azevedo Sales, Regimar Garcia dos Santos, Rônega Boa Sorte Vargas, Chris Tyson, Luan Pereira de Oliveira

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Progressive failure behavior and stress evolution characteristics of fractured coal-rock combination structure by Kai WANG, Xiang ZHANG, Feng DU, Yang JU, Kangnan LI, Jiazhi SUN, Yiqiao WANG, Xiaohuan ZUO

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A donor heart scoring model to predict transplant outcomes by E. A. Tenchurina, M. G. Minina

“…In binomial logistic regression, non-selection of heart donor was used as a dependent variable, while donor characteristics were used as factor features. …”
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Identification of exosome-related genes in NSCLC via integrated bioinformatics and machine learning analysis by Zhenjie Sun, Tianyu Du, Guosheng Yang, Yinghuan Sun, Xuyang Xiao

“…However, further experimental verification is required to assess its practical value for NSCLC and other lung cancer subtypes before clinical application.…”
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Prediction of KRAS gene mutations in colorectal cancer using a CT-based radiomic model by Wenjing Wang, Qingbiao Zhang, Shimei Fan, Yuyin Wang, Xingyan Le, Min Ai, Chunqi Du, Junbang Feng, Chuanming Li

“…The Delong test was employed to assess the differences between the various models.ResultsAfter feature selection, the top 8 features with the highest mutual information scores were extracted to construct a prediction model. …”
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Ensemble Machine Learning for the Prediction and Understanding of the Refractive Index in Chalcogenide Glasses by Miruna-Ioana Belciu, Alin Velea

“…This study employs various machine learning models to reliably predict the refractive index at 20 °C using a small dataset of 541 samples extracted from the SciGlass database. The input for the algorithms consists of a selected set of physico-chemical features computed for the chemical composition of each entry. …”
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Révision de l’espèce Homo erectus (Dubois, 1893) by Valéry Zeitoun

“…Before taking measures and calculating indices, reference points must be guaranteed to be anatomically homologous.Statistical methods or descriptive analysis (correspondence analysis, factor analysis) are based on comparisons of individuals and parameters in relation to a barycenter obtained by the calculation of each specimen’s own values. …”
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Evaluation of landslide susceptibility in Nujiang Prefecture based on optimized MaxEnt model by LI Yimin, XIANG Qianying, DENG Xuanlun, FENG Xianjie

“…The MaxEnt model feature combination （FC） and regularization multi⁃plier （RM） parameters were optimized， and the sample of the akaike information criterion（AICc）， Omission Rate （OR） and AUC （Area Under Curve） value before optimization were compared with that after opitimazation，and the occurrence of landslide hazards based on the optimized MaxEnt model was predictedto realize the landslide susceptibility evaluation in Nujiang Prefecture.ResultsThe optimized MaxEnt model has excellent applicability in predicting landslide susceptibility in the study area （AUC=0.913））. …”
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