Linguocultural Aspect of Chinese and English Kinship Terms by H. Bingbing

“…The cultural differences determining the differences in the use of kinship terms in English and Chinese are studied. …”
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The Conversion Polymorphism of Perovskite Phases in the BiCrO₃–BiFeO₃ System by Alexei A. Belik

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Segmentation and particle size analysis of coal particles based on ISUNet by Deqiang CHENG, Rui ZHANG, Tongxi XIE, Jingjing LIU, Lijuan ZHENG, Qiqi KOU, He JIANG

“…The ISUNet model introduces a compressed excitation atrous spatial pyramid pooling module and a Transformer-based multi-path iterative encoder. The compressed excitation atrous spatial pyramid pooling module enhances channel information and global context information of features at different scales, solving the problem of over-segmentation of coal particles. …”
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NETWORK SOCIETY AND ITS REALITIES: DIGITAL ETIQUETTE by R. I. Mamina, E. E. Yelkina

“…The basis of network society is formed by the Internet and social and media networks infrastructure that transform social reality and methods of social communication at individual, group and global levels. …”
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On Self-Positioning and Self-Fixation of Parts Made of Alloys with Shape Memory Effect under Component Assembling by E. Yu. O. Balaev

“…Disadvantages of these methods include assembly, residual and other stresses, engineering constraints, etc. …”
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Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations by Jin LI, Kemeng LIU, Danli XU, Weiju GAO, Lei HUANG, Haoxing WU, Haochen HUA

“…Subsequently, the Hong's (2m+1) point estimation method is used to quantify the uncertainty of wind and solar power, and the two-layer nonlinear optimization model is transformed into a single-layer mixed-integer optimization model using the KKT conditions and Big-M method. …”
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Utilizing Machine Learning Techniques for Cancer Prediction and Classification based on Gene Expression Data by Mariwan Mahmood Hama Aziz, Sozan Abdullah Mahmood

“…It holds the promise of delivering systematic, precise, and scientifically backed diagnoses for different types of cancer. Lately, several studies have delved into cancer classification by leveraging data mining techniques, machine learning algorithms, and statistical methods to thoroughly analyze high-dimensional datasets. …”
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Remote Sensing Image Scene Classification Based on Mutual Learning With Complementary Multi-Features by Anzhi Chen, Mengyang Xu

“…In addition, a Swin transformer module (STM) is employed to extract global image features. …”
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Analyzing the ecologicality and functionality of kiln architecture in China through KH coder data mining algorithm and hierarchical event coding by Runze Liu, Xiang Wang, Lin Yuan, Yunting Gao, Yan Zhang, Mengsi Yang, Weicong Li

“…Based on constructing ecologicality-architecture-cultural resilience theory, this study analyzes the structural features, ecological technologies, and conservation status of kiln architecture across various regions in China through KH Coder data mining and hierarchical event coding method and proposes a new protective framework. Findings: (1) Kiln architecture has evolved from built-against-the-mountain to semi-buried, fully-buried, reinforced earth-covered, and independent forms, as functional demands have changed from hazard avoidance to climate adaptability, functional expansion, and energy-saving design; (2) Climate, topography, and soil conditions are key factors driving the emergence of built-against-the-mountain, along-the-valley, sunken courtyard, and independent kiln architecture types; (3) Geological characteristics and material availability significantly shape the vaulted structural features of kiln architecture across different regions. …”
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Biological role and use of L-glutamic acid and its influence on the body by O. O. Korytko

“…L-glutamic acid is transformed in the cells of the intestinal mucosa into alanine, and in the liver – into glucose and lactate. …”
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DEVELOPMENT OF A DISCRETE MATHEMATICAL MODEL OF THE HYDROTREATING DIESEL FUEL REACTOR by Ksenia Igorevna Netsvetaeva

“…The article gives an example of the transformation of the initial mathematical model of the hydrotreating diesel fuel reactor which is a system of algebraic equations into its discrete analogue, using the method of "nets" (finite difference method). …”
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Probing the diversity of kink solitons in nonlinear generalised Zakharov-Kuznetsov-Benjamin-Bona-Mahony dynamical model by Naher Mohammed A. Alsafri, Hamad Zogan

“…This equation models the physical phenomena of long waves with small and finite amplitude in magnetic plasma. Using a wave transformation, the employed transformative technique first converts GZK-BBME to a nonlinear ordinary differential equation (NODE). …”
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DECODING OF STRUCTURALLY AND LOGICAL CODES by Yu. D. Ivanov, I. N. Nikolov, B. V. Lozka

“…There are shown the basic points of the generalized algorithm of decoding SLC, which is based on the method of perfect matrix arrangement (PMA) of the n-dimensional cube vertices for adequate representation and transformation of boolean functions, which is based on the method of generating sequences of variables for building the maximum coverage of the cube vertices. …”
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CdZnTe- and TlBr-detectors response simulation for registration of the mixed beta- and gamma-radiation by A. I. Skrypnyk

“…Firstly, DFT properties are accurate, have their own specificity and significantly differ from the properties of the Fourier transform of continuous signals. …”
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Thermal dynamics of nanofluids with aggregating nanoparticles and magnetic heating: Utilization of Maxwell-Bruggeman and Kreiger-Dougherty models by Muhammad Idrees Afridi, Abdullah Alhushaybari, Ali J. Chamkha

“…Furthermore, it is found that as the values of the transformed stream-wise coordinate, Hartman number and temperature difference parameter grew, Bejan's number profile diminished.…”
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Soliton solutions, bifurcations, and sensitivity analysis to the higher-order nonlinear fractional Schrödinger equation in optical fibers by Md. Al Amin, M. Ali Akbar, M. Ashrafuzzaman Khan, Md. Sagib

“…We apply a traveling wave transformation with the Beta derivative to convert the nonlinear fractional differential equation into a standard nonlinear differential equation. …”
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Hidrograma de projeto em função da metodologia utilizada na obtenção da precipitação Runoff hydrogram resulting from the methodology employed to record precipitation by Rita de C. F. Damé, Claudia F. A. Teixeira, Viviane S. S. Terra, José L. C. Rosskoff

“…This often constitutes a limitation for hydrological applications such as the rainfall-runoff transformation, which needs to feed on short duration precipitation data. …”
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Investigating the stochastic higher dimensional nonlinear Schrodinger equation to telecommunication engineering by Aziz Khan, Jan Muhammad, Usman Younas, Rajermani Thinakaran, Thabet Abdeljawad, Manar A. Alqudah

“…To acquire the proposed results, we use advanced analytical approaches such as modified F-expansion technique, the Riccati extended modified simple equation technique, and the generalized $$(G^{\prime }/G)$$ -expansion method. The nonlinear partial differential equation is transformed into its corresponding ordinary differential equation by means of the wave transformation to investigate the required soliton solutions. …”
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Comparative Results of Emergency Carotid Endarterectomy and Emergency Carotid Angioplasty With Stenting in the Acute Period of Ischemic Stroke. Multicenter Study Results by A. N. Kazantsev, V. A. Porkhanov, G. G. Khubulava, R. A. Vinogradov, V. N. Kravchuk, M. A. Chernyavsky, E. Y. Kachesov, A. A. Erofeyev, V. V. Matusevich, K. P. Chernykh, N. E. Zarkua, G. S. Bagdavadze, R. Y. Lider, M. S. Bayandin, A. V. Khudetskaya, A. P. Chernykh, A. G. Baryshev, A. R. Shabayev, V. A. Lutsenko, R. V. Sultanov, D. V. Fattakhov, A. V. Kutsenko, L. V. Timchenko, A. E. Chikin, E. Y. Kalinin, S. V. Artyukhov, T. E. Zaitseva, Y. P. Linets

“…However, the vast majority of hemorrhagic transformations (group 1: n=2 (0.64%); group 2:  n=13 (3.6%); p=0.018; OR=0.17; 95% CI 0.03–0.76) and all “mute” hemorrhagic transformations (group 1: n=0; group 2: n=26 (7.3%); p=0.001;  OR=0.02; 95% CI 0.001–0.33) were observed only in the CEE group, which was reflected in the maximum values of the combined end point: group 1: n=22 (7.05%); group 2: n=73 (20.4%); p<0.0001; OR=0.29; 95% CI 0.17–0.48). …”
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The impact of environmental tax policies on artificial intelligence investment: evidence from agri-food, food processing, and other industries by Guangxing Hu, Bin Li, Juhao Lai

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