Monitoring and assessment of well quality of water   infiltration intakes in water reservoirs in the   south‐east of Belarus by D. V. Makarov, E. A. Kantor, N. A. Krasulina, Z. Z. Berezhnova, Yu. S. Savicheva

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Early Ultrasound Signs of Splenomegaly in Neonates by S. A. Perepelitsa, S. V. Alekseeva, О. V. Vozgoment

“…The purpose of the study is to determine early non-invasive (ultrasound) diagnostic criteria of splenomegaly in neonates with a high risk of congenital or postnatal infection.Materials and methods. …”
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Regional Inequities in the Distribution of the Nursing Workforce in Italy by Ippolito Notarnicola, Blerina Duka, Eriola Grosha, Giovanni Gioiello, Maurizio Zega, Rosario Caruso, Sara Carrodano, Gennaro Rocco, Alessandro Stievano

“…This study investigates the extent and determinants of regional inequality in the distribution of the nursing workforce in Italy. …”
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Results of experimental studies of the roughness of geomats filled with crushed stone with a binder filler and soil with sprouted ryegrass by Tatyana Yu. Zhukova, Andrey V. Eremeev, Nartmir V. Khanov, Daniil A. Alekseev, Anastasia A. Kadyseva

“…As a result of the research, the average values of roughness coefficients for two coatings were found. Conclusions. …”
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DIFFUSION-WEIGHTED IMAGING FOR DIFFERENTIATING MALIGNANT FROM BENIGN MEDIASTINAL LYMPHADENOPATHY by A. V. Sudarkina, A. P. Dergilev, N. A. Gorbunov, V. V. Kozlov, Yu. A. Fokina, I. P. Klimova, P. A. Yagubkin

“…Mediastinal lymphadenopathy can be caused by a wide range of benign and malignant states. Determination of the genesis of lymphadenopathy is crucial for treatment planning and prognosis of the disease.The purpose of the study was to evaluate the diagnostic accuracy of diffusion weighted imaging (DWI) with apparent diffusion coefficient (ADC) measurements in differentiating malignant versus benign mediastinal lymphadenopathy. …”
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PHENOLIC COMPOUNDS AND PECTIC SUBSTANCES OF EUROPEAN GOOSEBERRY LEAVES ΈGROSSULARIA RECLINATA ΈL.Ή MILL.Ή by S. L. Adjiahmetova, D. I. Pozdnyakov, N. M. Chervonnaya, L. P. Myikots, A. V. Voronkov, E. T. Oganesyan

“…Kochetkov and M. Sinner’s method. When determining the distribution coefficient from organic solvents, diethyl ether and n-octanol, in which the objects under study are readily soluble, have been used. …”
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Diagnostic Value of ADC in Distinguishing Endometrial Cancer from Atypical Endometrial Hyperplasia and Within Molecular Subtypes by Xu S, Abdifatah Mohamed R, Xu J, Yao Y, Gu Y, Tang W, Jia X

“…Shengjie Xu,1,* Ridwan Abdifatah Mohamed,1,* Juan Xu,1,2 Yao Yao,3 Yun Gu,4 Wenwei Tang,3 Xuemei Jia1,2 1Department of Gynecology, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing, 210004, People’s Republic of China; 2Nanjing Medical Key Laboratory of Female Fertility Preservation and Restoration, Nanjing, 210004, People’s Republic of China; 3Department of Radiology, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing, 210004, People’s Republic of China; 4Department of Pathology, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing, 210004, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wenwei Tang, Department of Radiology, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing, 210004, People’s Republic of China, Email tww3077@163.com Xuemei Jia, Department of Gynecology, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, No. 123 Mochou Road, Nanjing, 210004, People’s Republic of China, Email xmjia@njmu.edu.cnPurpose: The study aimed to evaluate the effectiveness of using specific indicators, particularly the apparent diffusion coefficient (ADC), alone or in combination to differentiate endometrial cancer (EC) from atypical endometrial hyperplasia (AEH) and to explore non-invasive biomarkers for the molecular classification of EC.Methods: A retrospective analysis was conducted on 300 EC and 126 AEH cases who had undergone preoperative magnetic resonance imaging, complete blood count, coagulation profile testing, and tumor biomarkers assessment. …”
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Prediction of Parkinson Disease Using Long-Term, Short-Term Acoustic Features Based on Machine Learning by Mehdi Rashidi, Serena Arima, Andrea Claudio Stetco, Chiara Coppola, Debora Musarò, Marco Greco, Marina Damato, Filomena My, Angela Lupo, Marta Lorenzo, Antonio Danieli, Giuseppe Maruccio, Alberto Argentiero, Andrea Buccoliero, Marcello Dorian Donzella, Michele Maffia

“…That is why, the voice can be nominated as the non-invasive method to detect PD from healthy subjects (HS). <b>Methods:</b> Our study was based on cross-sectional study to analysis voice impairment. …”
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Applying multi-theory model to determine intentions to smoking cessation among male health worker smokers in Kabul, Afghanistan by Mousa Bashir, Farkhondeh Amin Shokravi, Anoshirvan Kazemnejad

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Evaluation Method for Remaining Life of XLPE Insulated Power Cable by MA Hanchao, GAO Baoqi, LI Xiangyang, WU Suzhou, ZHANG Xiaojun

“…First, the fault tree analysis method is used to determine the evaluation factors from the two perspectives of electrical aging and thermal aging, construct a remaining life evaluation model, and determine the aging coefficient of the cable. …”
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Determining the Heterotic Groups of Selected Grain Maize (Zea mays L.) Inbred Lines using Morphological and Phenological Traits by Mahnaz Oroojloo, Sara Dezhsetan, Behzad Ahmadi, Mohammadreza Shiri, Ali Moghaddam

“…Moreover, this research also seeks to classify the selected Iranian maize inbred lines into early, medium, and late ripening groups based on the phenological traits. Methods: Aiming at producing hybrid maize and determining the heterotic groups in this research, 50 selected maize inbred lines produced in Seed and Plant Improvement Institute (SPII) were chosen and evaluated based on their kernel yields, and morphological and phenological traits in a randomized complete block design with three replications in the research field of the Seed and Plant Improvement Institute. …”
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Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex by Zili Gao, Yuzhen Zhang, Laura C. Harrington, Courtney C. Murdock, Elisabeth Martin, Dalton Manbeck-Mosig, Steve Vetrone, Nicolas Tremblay, Christopher M. Barker, John M. Clark, Lili He, Wei Zhu

“…However, traditional methods, such as tracheole morphology analysis, are labor-intensive and have limited scalability. …”
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Determination of Cortisol Levels in a Small Volume of Saliva of COVID-19-Recovering Patients During Treatment with Psychotropic Drugs by Ewelina Dziurkowska, Grażyna Guz-Rzeniecka, Maciej Dziurkowski

“…<b>Results</b>: The developed method was validated. Its linearity was determined to be in the range of 4–500 ng/mL (R² > 0.9986) and the intra- and inter-day precision expressed as coefficient of variation (CV%) did not exceed 12%. …”
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Determination of chemical composition, in vitro dry matter digestibility and in vitro gas production of forage by near-infrared reflectance spectroscopy by Andrej LAVRENČIČ, Bruno STEFANON, Barbara TOSO, Piero SUSMEL

“…NIRS predicted the main chemical components, such as crude protein, crude fibre, neutral detergent fibre, acid detergent fibre, with a very high degree of accuracy (i.e. the determination coefficient (R2) varied from 93.5 % for ADF to 98,2 % for NDF), while the coefficients of determination of crude ash, ether extract and acid detergent lignin were 79.6, 85.1 and 82.3 %, respectively, with standard errors of cross validation (SECV) exceeding 9.0 %. …”
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Skin Cancer Preventive Behaviors and Its Determinants among High School Students in Sanandaj, Iran: An Application of PRECEDE Model by Athareh Najafi, Elahe Nadrian, Gona Bakri, Haidar Nadrian, Asaad Fathipour

“…Regarding this, the present study aimed to investigate the determinants of skin cancer preventive behaviors (SCPBs) among the high school students of Sanandaj, Iran, using the PRECEDE model. …”
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The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks by Zhichun Yang, Fan Yang, Yu Liu, Huaidong Min, Zhiqiang Zhou, Bin Zhou, Yang Lei, Wei Hu

“…Then, a multi-objective planning model of the network structure is established, and the weighted coefficient transformation method is used to convert reliability benefits and investment costs into the total cost of power supply per unit load. …”
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Investigating Resulting Surface Topography and Residual Stresses in Bending DC01 Sheet Under Tension Friction Test by Krzysztof Szwajka, Tomasz Trzepieciński, Marek Szewczyk, Joanna Zielińska-Szwajka, Marek Barlak

“…This article presents the results of experimental studies aimed at determining the values of residual stresses and coefficient of friction (CoF) in bending under tension friction test, which simulates friction conditions in sheet metal forming. …”
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AUTOMATED DEVICE FOR ICE SURFACE QUALITY ASSESSMENT by M. V. Davydov, P. A. Belous

“…The purpose of the study is to determine the dependence of the sliding friction coefficient on the parameters of water treatment, the conditions for freezing the ice surface, the temperature of the ice surface, hardness and other parameters. …”
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Threshold and Asymmetric Effects of Foreign Direct Investment on Inclusive Growth in Shanghai Cooperation Member Countries by marziyeh hosini, monireh Rafat

“…The study will use income as a determinant of opportunity. As it is the most common and widely used measure of determining individuals’ access to certain other kinds of opportunities. …”
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The Application of Near-Infrared Spectroscopy Combined with Chemometrics in the Determination of the Nutrient Composition in Chinese <i>Cyperus esculentus</i> L. by Xiaobo Jiao, Dongliang Guo, Xinjun Zhang, Yunpeng Su, Rong Ma, Lewen Chen, Kun Tian, Jingyu Su, Tangnuer Sahati, Xiahenazi Aierkenjiang, Jingjing Xia, Liqiong Xie

“…The optimal models for CO, CP, and TS exhibited coefficient of determination (R²) values of 0.8946, 0.8525, and 0.8778, with root mean square error of prediction (RMSEP) values of 1.1764, 0.7470, and 1.4601, respectively. …”
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