Assessment and evaluation of Chitosan‐Metamizole nanoparticles for the fracture healing and analgesic effect: Preclinical study in rat model by Li Yin, Liyong Yuan, Chunling Peng, Qionghua Wang

“…Abstract To assess and evaluate Chitosan‐Metamizole nanoparticles for fracture healing and analgesic potential, nanoparticles were formulated using the ionotropic gelation method. The nanoparticles were evaluated for particle size, zeta potential, polydispersity index, loading efficiency, surface characteristics and drug release properties. …”
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DISTRIBUTION OF AN AIR STREAM SPEED IN THE DEEP ASPIRATING CHANNEL by V. G. Khamuev

“…The field of air stream speeds in the channel was estimated by distribution factor determined by a probability theory method. The authors were investigated influence of plates-barriers on distribution of air stream speed in the air separating channel and on efficiency of cleaning of the processed material. …”
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Comparative analysis of water-ice cold storage devices by А. V. Baranenko, V. V. Tamarov, M. V. Korolenko

“…Method. The study is based on the methods of thermodynamic analysis of technical characteristics of various modifications of water-ice cold accumulators. …”
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Optimal Layout of the Head Drive for a Self-Supporting Bucket Elevator of High Productivity by Volodymyr Kurhan, Ihor Sydorenko, Viktor Kurgan, Ruslan Dudko, Svetlana Bershak

“…Three bucket elevators with different heights, productivity, and belt width were selected to determine the optimal layout. Four drive options were calculated for each design, and a comparative analysis was carried out using a graphical method. …”
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Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns by Junfeng Sun, Yong Fang, Hu Luo, Zhigang Yao, Long Xiang, Jianfeng Wang, Yubo Wang, Yifan Jiang

“…The results indicate that the proposed model outperforms other deep learning models, achieving favorable root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) values of 0.34 mm, 0.23 mm, and 0.94, respectively. …”
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Measuring. Monitoring. Management. Control by P.G. Mikhaylov, A.P. Mikhaylov, I.N. Paskhin, A.R. Akhmetov, E.D. Fadeev

“…Mathematical models of multilayer film structures are considered and analyzed, the nominal values of strain gages are determined, and methodformation are determined. In particular, an increase in the accuracy and consistency of the electrophysical characteristics of the sensing elements and measuring modules was achieved by 30–40 % compared with well-known Russian sensors.s for minimizing the temperature coefficients of resistive structures are determined. …”

Predicting steady degradation in ship power system: A deep learning approach based on comprehensive monitoring parameters by Xingshan Chang, Xiaojian Xu, Bohua Qiu, Muheng Wei, Xinping Yan, Jie Liu

“…Compared to baseline models, YC2Model demonstrates superior performance on key performance indicators, including the highest coefficient of determination (R2) of 0.960717, and the lowest symmetric mean absolute percentage error of 0.015500, mean square error of 0.707211 × 10−4, root mean square error of 0.008410, and mean absolute error of 0.006519, proving its superior predictive accuracy. …”
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Adaptive hybrid synchronization control of grid-connected converters in renewable power plants and its small-signal stability analysis by GONG Kai, XIAO Huangqing, ZHANG Zhan, HE Hongliang, HUANG Ying, LI Yan

“…Subsequently， the corresponding small-signal model is developed， and based on the analysis results of small-signal stability， a method for determining adaptive parameter values is introduced. …”
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Creep Behavior and Quantitative Prediction of Marine Soft Clay Based on a Nonlinear Elasto-Plastic–Viscous Element Assembly Model by Yajun Liu, Ning Fang, Yang Zheng, Ke Wu, Rong Chen, Haijun Lu, Vu Quoc Vuong

“…The predicted–measured creep difference remained within 10%, and the surface-fit coefficient of determination reached R² = 0.97, enabling rapid estimation of deformation for the given stress and time conditions. …”
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Reverse design of solid propellant grain based on deep learning: Imaging internal ballistic data by Lin Sun, Xiangyu Peng, Yang Liu, Shu Long, Weihua Hui, Ran Wei, Futing Bao

“…While existing reverse design methods are feasible, they often face challenges such as lengthy computation times and limited accuracy. …”
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Machine Vision-Assisted Design of End Effector Pose in Robotic Mixed Depalletizing of Heterogeneous Cargo by Sebastián Valero, Juan Camilo Martinez, Ana María Montes, Cesar Marín, Rubén Bolaños, David Álvarez

“…Automated depalletizing systems aim to offer continuous and efficient operation in warehouse logistics, reducing cycle times and contributing to worker safety. …”
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Discriminating the adulteration of varieties and misrepresentation of vintages of Pu’er tea based on Fourier transform near infrared diffuse reflectance spectroscopy by Zhenfa Yang, Zhenfa Yang, Xiaoping Lu, Lucheng Chen

“…These results illustrated the feasibility to identify the adulteration of varieties and misrepresentation of vintages of Pu’er tea with near infrared spectra and RBFNN model, proving an efficient alternative for Pu’er tea quality inspection, and offering a robust method for combating the pervasive issues within the market.…”
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Validity and reliability of the Turkish version of the infection prevention appraisal scale by Nuray Turan, Cansu Polat Dünya, Meryem Türkoğlu, Ljudmila Linnik

“…Linguistic validity was ensured through the back-translation method, and expert evaluations were used to determine content validity. …”
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Experimental and simulation study on the deformation behavior, mechanical properties and microstructure of Ti–6Al–4V alloy wires fabricated by hot drawing by Zhijie Gao, Yaozong Mao, Zhiqiang Zhang, Chunguang Bai, Li Zhou

“…In this study, a combined experimental and simulation method was proposed to determine the friction coefficient involved in wire drawing processes. …”
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A study on the prediction of mountain slope displacement using a hybrid deep learning model by Yuyang Ma, Xiangxiang Hu, Yuhang Liu, Yaya Shi, Zhiyuan Yu, Xinmin Wang, Liangbai Hu, Shuailing Liu, Dongdong Pang

“…On the long-term prediction task at station JC03, it achieves a 37.9% reduction in Root Mean Square Error (RMSE), a 32.4% decrease in Mean Absolute Error (MAE), and a 4.6% increase in the coefficient of determination (R2) compared to the baseline LSTM. …”
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The Role of Perceived Stress and Social Support among Predicting Anxiety in Pregnant Women by Sajjad Basharpoor, Hadis Heydarirad, Seyed Javad Daryadel, Fazeleh Heydari, Hossein Ghamari Givi, Jugal Kishore

“…Materials and Methods: This is a descriptive-analytical study with correlational design. …”
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Relationship of Health Literacy with Knowledge and Attitude toward the Harms of Cigarette Smoking among University Students by Rahman Panahi, Ali Ramezankhani, Mahmoud Tavousi, Amine Koosehloo, Shamsodin Niknami

“…Materials and Methods: This cross-sectional and correlational study was conducted on 340 dormitory students of Shahid Beheshti University of Medical Sciences, Tehran, Iran, in 2016. …”
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Predictive Model of Granular Fertilizer Spreading Deposition Distribution Based on GA-GRNN Neural Network by Lilian Liu, Guobin Wang, Yubin Lan, Xinyu Xue, Suming Ding, Huizheng Wang, Cancan Song

“…The results show that the prediction accuracy and training effect of the GA-GRNN model are better than those of the GRNN, with a coefficient of determination of 0.839, and that the results of the GA-GRNN model are closer to the actual data when predicting the effective amplitude of the deposition amount, which is more accurate. …”
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The Results of the Study of the Relationship between Viscosity and Mechanical Strength of Bleached Hardwood Kraft Pulp by Tatiana A. Koroleva, Vasily V. Medvedev, Yuri V. Pomelov

“…Since it takes no more than 2 hours to determine the viscosity of a solution of high-molecular polymers, and 8–10 hours to obtain standard mechanical strength characteristics, viscosity analysis can be considered an express method that provides information on the mechanical strength of a semi-finished product. …”
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Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…As expected, the results showed rather poor values of the coefficient of determination (R2) of the artificial neural network (ANN), support vector machine (SVM), and random forest (RF) with pre-adjusted values for their hyperparameters. …”
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