bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Innovative Application of Yangzhou Lacquer Art in Tea Set Design from the Perspective of Non-Heritage Living Inheritance
Authors: Xu Hang
Published: December 2024

Yangzhou lacquer art, as a precious historical and cultural heritage in China, has a high reference value for modern tea set design. In this paper, firstly, the development and design method of the tea set based on Yangzhou Lacquer Art is combined with SIFT and BRISK feature extraction algorithms to screen out the stable image feature points and feature extract the traditional decorative patterns of the tea set, and then the neighborhood pixel gradient distribution of the feature points is counted through the histogram to determine the maximum peak of the neighborhood gradient. Subsequently, the RANSAC algorithm is applied to calculate the coordinate transformation relationship between the feature points of the template image and the corresponding feature points of the image to be matched, and a portion of the matching points with large errors are removed to obtain the correct matching points. Using a Generative Adversarial Network, the efficient hyper-segmented pattern tattoos are reconstructed, and the RMGAN loss function is designed to satisfy the problem of stochastic gradient descent of the image, and the generated image is optimized step by step. Through surface modeling to assist Yangzhou lacquer art tea set shape design modeling and the local shape of the tea set, to realize the physical design of the tea set of Yangzhou lacquer art. Empirical investigation on the market feedback after the design of the tea set, from the results of the survey: different groups of people on the use of the process of satisfying behavior, sensory experience demand is high, especially the youth group, the degree of demand is 0.7456, 0.7655. Users want to use classical colors and traditional painting elements in the design of the tea set, with a response rate of 23.91% and 30.43%, respectively. Combining the technical method developed in this paper with the results of demand analysis, it provides a practical method for applying Yangzhou lacquer art to tea set design.
Research and optimization of cross-border e-commerce logistics model based on big data technology
Authors: Liu Qian , Yao Xuesong , Pei Lei , Lin Mei
Published: December 2024

Cross-border e-commerce is a powerful embodiment of the digital development of foreign trade transactions, but the cross-border logistics model constrains the development of cross-border e-commerce. The article outlines the cross-border e-commerce business process and proposes a smart logistics system for cross-border e-commerce that combines blockchain technology. The transportation cost, cargo damage cost, penalty cost, distribution center cost and information technology cost of cross-border e-commerce logistics transportation are taken as the objective function to construct a logistics distribution path optimization model. Then a genetic algorithm is introduced to solve the model and obtain a cost-effective cross-border e-commerce logistics distribution path optimization scheme. The optimal transportation time obtained in the simulation of the GA algorithm-solving model is only 34.76h, and the total distribution cost of the optimal distribution scheme obtained by the model after 160 iterations is 1068.7 yuan. The cross-border e-commerce logistics path optimization model can obtain the optimal logistics and distribution scheme under the consideration of time window constraints, and combined with the verification of the intelligent logistics system, it can be seen that the total logistics and distribution cost of 10 customers in the distribution area is 10956.02 yuan. The optimization of the cross-border e-commerce logistics model can be realized based on big data technology and blockchain technology, which lay the foundation for high-quality cooperation and the development of international foreign trade transactions.
Exploring and Practicing the Integration of Scientist Spirit into the Cultivation of Young Scientific and Technological Talents in the Era of Big Data
Authors: Tu Shengxue
Published: December 2024

The spirit of a scientist carries rich connotations and important values of the times. The study focuses on integrating the spirit of scientists into the cultivation of young scientific and technological talents. For the cultivation of young scientific and technological talents, relevant input and output indicators are selected and screened using the GRA model, and then the cultivation of young scientific and technological talents in a certain place is taken as an example to be empirically analyzed by combining the DEA model. On this basis, the conceptual model framework of scientists’ spirit and young scientific and technological talent cultivation is constructed; research hypotheses are put forward; and the PLS-SEM model is applied to verify the hypotheses and explore the influence of scientists’ spirit on young scientific and technological talent cultivation. The comprehensive efficiency value of the sample’s young scientific and technological talent cultivation is 0.716, placing it in the upper middle category. 32% of young scientific and technological talent cultivates DEA effectiveness. There is a significant positive effect of the spirit of scientists on the cultivation of young scientific and technological talents at the 1% level, with an influence degree of 0.573, and the most obvious promotion effect of the spirit of innovation on the cultivation of young scientific and technological talents (0.624). In the cultivation of young scientific and technological talents, we must guide young people to practice the spirit of scientists, enhance the cultivation of scientific ethics, foster their ability to seek truth and innovation, and foster the inheritance and development of the spirit of scientists among young scientific and technological talents.
A Modeling Study of Business English Students’ Intercultural Competitiveness and Strategies in the Belt and Road Initiative
Authors: Xi Xiaoxue
Published: December 2024

Intercultural competitiveness is an important guarantee for Business English majors to show their advantages and grasp the opportunities of the times in the Belt and Road Initiative. This paper evaluates the cross-cultural competitiveness of business English majors by constructing the CFCS-TOPSIS model and proposes strategies to improve the cross-cultural competitiveness of business English majors in the Belt and Road Initiative based on the evaluation results. The evaluation system of cross-cultural competitiveness of business English students is constructed, while the CFCS algorithm is used to denazify the fuzzy-valued indexes, and the obtained indexes are used as input factors to calculate the TOPSIS model. The research is conducted on students who major in business English at a university and the current level of their intercultural competitiveness is measured and analyzed using statistical analysis methods. The results indicate that business English majors in this university have a good level of intercultural competitiveness, but their intercultural skills and values still require improvement. Cross-sectional comparison of the cross-cultural competitiveness of business English majors in 15 colleges and universities focusing on the construction of the Belt and Road, the P
i values of U2, U5, U12, and U15 colleges and universities are 0.493, 0.536, 0.748, and 0.645, respectively. The indexes of understanding the international business environment (X1), cross-cultural communication theory (X2), and openness (X7) have the most significant influence on the cross-cultural competitiveness of business English majors. The most significant effect is caused by intercultural competitiveness.
A data-driven evaluation of student health impacts in teaching higher education physical education and health programs
Authors: Xue Jianxin , Zhang Jin
Published: December 2024

In the field of physical education in the 21st century, with the rapid development of information technology, data-driven decision modeling has become an important means to improve the quality of teaching and promote the healthy development of students. The accurate assessment of students’ physical fitness levels and mental health is achieved through the use of fuzzy judgment and clustering algorithms in this paper. A data-driven platform for student health sports has been created by modeling sports users and sports and using the UB-CF recommendation algorithm, which includes personalized recommendations. The platform’s impact on students’ health is evaluated using a university as an example. The platform in this paper can provide students with different physical fitness courses with content that meets their own needs. After the experiment, students in the physical education and health course group saw a decrease in weight and hip circumference, respectively, by 2.59kg and 2.81cm, and their physical health improved further. And the platform presented in this paper can enhance the muscle fitness of students. In the experimental group, the standing long jump distance improved by about 10.25% compared with the preexperiment. The MAE of this paper’s method on the identification of psychological emotion “Depression” is only 0.296, which is much lower than the baseline method. Moreover, the method presented in this paper can accurately classify students according to their psychological problems. The purpose of this paper is to provide practical guidance for the innovative development of physical education in colleges and universities.
Exploring the Teaching Reform of Computer Operating System Course Based on Deep Learning
Authors: Zhao Hui
Published: December 2024

This paper reforms the teaching of an existing computer operating system course based on the deep learning route DELC model and evaluates the teaching effect of the reform by means of empirical research. According to the loop framework of the DELC model, design innovative teaching objectives, teaching environments, and other aspects for the computer operating system course. We selected the control class and the experimental class in the School of Computer as research subjects for our teaching practice. The statistical analysis of the pre-test and post-test questionnaire data collected during the teaching practice was used to compare the questionnaire results of the control and experimental classes. Based on the test scores of the computer operating system course of the 10 classes of 2019–2023, cluster analysis and discriminative information were used to explore the teaching effect after the course reform in depth. The paper concludes that the average post-test scores of the experimental classes are significantly higher than those of the control classes, and they are 17.39% higher in the course recognition dimension compared to the control classes. Students of 2019-2022 are clustered into the “common” category, while students of 2023 who adopted the reform strategy in this paper are clustered into the “better” category. This fully demonstrates the feasibility and effectiveness of the proposed computer operating system course reform based on the DELC model.
Simulation study of the dynamics of carbon storage in a forest ecosystem model
Authors: Zhao Hongfei , Lu Haifei , Zhong Tailin , Cao Zhihua , Wan Guowei
Published: December 2024

Changes in the waxing and waning of carbon pools in forest ecosystems have a profound impact on the global carbon cycle. The study takes forests in a city as an example, uses sample plot survey data and Sentinel-2 and GF-1 satellite remote sensing data as data sources, and after multiple feature extraction, the RBF neural network optimized by the PSO algorithm is used for modeling the dynamic estimation of carbon storage, assessing the accuracy of the model and inverting the estimation of carbon storage in the sample area. The results show that the PSO-RBF model in this paper has the best fit and prediction accuracy for carbon storage estimation, with the highest R² of 0.644 and the smallest RRMSE and MAE of 0.287 and 15.368 in the combination of the two data sources, and the estimated value of forest carbon storage in 2022 in the sample area is 6809451.80t, which differs from the actual value by 0.04% and the difference of predicted and actual values in each subarea is 0.04%. The predicted and measured values in subregions had a difference of less than 0.34%. The forest carbon storage model that utilizes PSO-RBF has a good estimation effect overall. The technical support provided by this study enables accurate monitoring of carbon storage in forest ecosystems.
The classroom interaction and learning effect are enhanced by the intelligent teaching system in the high-quality development of colleges and universities
Authors: Sun Liyan
Published: December 2024

In recent years, Artificial Intelligence (AI) technology has developed rapidly, bringing new opportunities for the innovation of education. This paper adopts Bayesian network and Agent technology to construct an intelligent teaching system, which can formulate and implement guided learning strategies according to the individual, actively collect the most interesting information for the learners through the intelligent Agent proxy server, automatically generate a variety of questions and exercises, and reasonably plan and adjust the learning content and progress. Introducing knowledge points as the foundation of teaching resources, establishing connections between them, constructing dynamic knowledge tree models, and implementing intelligent interactive teaching strategies in the teaching system. Teaching research shows that with the empowerment of the intelligent teaching system, the effective interactive behavior of teachers and students covers up to 92.75% of the classroom time, which is significantly higher than the traditional coverage rate of 78.89%, effectively improving the effect of teacher-student interactions in the university classroom, while the academic performance of the experimental class has also been significantly improved. The intelligent teaching system is more effective in enhancing the high-quality development of universities.
Algorithmic Innovation and Visual Communication Strategies in Digital Visual Effects
Authors: Yan Kuan , Liu Gangtian , Zhang Hui , Zhu Danjun
Published: December 2024

With the popularization of digital mobile devices, the development of new media technology and the Internet, visual media presentation becomes more and more diversified and gradually transforms to digitalization. The article optimizes the digital halftone algorithm using visual model and printer model, and proposes an adaptive digital halftone algorithm for enhancing digital images. The enhanced digital image is input into the dual-tree complex wavelet transform for feature dimensionality reduction and noise processing, and then combined with the HSV color model to establish the optimization algorithm for visual communication effect. The average PSNR of the adaptive digital halftone algorithm is 2.31% higher than that of the Floyd-Steinberg error diffusion method, and the information entropy of the visual communication optimization can be up to 9.29 bits, and when the number of digital images is 100, the optimization time of the proposed method for the visual communication optimization is only 30.71 s. The visual communication design works can be attracted to the audience through the optimization of the visual communication effect. The visual communication design works obtained through digital visual effect optimization can attract more attention from the audience and can also effectively trigger positive emotions from the audience. From the optimization of digital visual effect, it is necessary to further introduce the integration of digital technology and visual communication design, combine cross-border resource sharing and improve the dynamic effect of visual communication design, and then improve the effect of visual communication design works.
Research on the Integration of Innovation and Entrepreneurship and Civic and Political Education in the Context of High-Quality Education in the Internet Era
Authors: Hao Binbin , Guo Yanping , Wang Chunhong
Published: December 2024

This paper first studied the feasibility of the integration of civic education and innovation and entrepreneurship education and constructed the integration pathway of innovation and entrepreneurship education and civic education from three aspects, namely, value leadership, theoretical integration as well as practical integration. A regression analysis model was created, the parameters of the model were evaluated using least squares estimation, and the model was tested for its significance. Finally, based on the regression model, the correlation between entrepreneurship education and ideological and political education in colleges and universities was explored, and the influence of ideological and political education on the self-efficacy of college students’ innovation and entrepreneurship and their values of innovation and entrepreneurship was analyzed. The study shows that ideological and political education, classroom channel, daily education and self-efficacy are significantly positively correlated at the level of 0.05, and the correlation coefficients on students’ entrepreneurial values are 0.722, 0.673, and 0.696, respectively. This study has a reference to the healthy development of innovation and entrepreneurship education, and provides a reference to the reform of innovation and entrepreneurship education undertakings for other local colleges and universities of the same type.
Surface Defect Detection of Mining Automation Equipment Based on Convolutional Neural Networks
Authors: Bian Zeyu
Published: December 2024

Surface defect detection of mining automation equipment is crucial for creating a safe operating environment. This paper analyzes the commonly used target detection techniques and selects a target detection algorithm based on Faster-RCNN to construct a model for surface defect detection in mining automation equipment. In the acquisition of surface defects, the Laplace operator and homomorphic filtering are used to enhance and sharpen the image. The texture defect dataset and metal surface defect dataset are also selected to make the VOC2007 dataset, and the Faster-RCNN network model is utilized for training to obtain the surface defect detection model of mining automation equipment. The model defect detection comparison results show that the Faster-RCNN model has an mAP value of 76.1%, which is the model with the highest detection accuracy. The result confirms the effectiveness of the method presented in this paper and enhances the accuracy of the model’s detection.
A Practical Study of Biological Big Data Base Assisting the Reformed Teaching of Probability Theory and Mathematical Statistics Course
Authors: Zeng Xiang
Published: December 2024

Under the background of the large-scale popularization of “Internet + Education”, personalized education mode based on artificial intelligence and other information technologies has become the trend of teaching reform development. In this paper, we have collected and pre-processed students’ learning behaviors during the teaching of Probability Theory and Mathematical Statistics courses, and established a large biological database based on these behaviors. The features of learning behaviors are extracted using the SHAP method, and the features are fused and processed by the MFCNN module. The Bi-LSTM method is used to warn students of academic risks. Finally, we construct a visualization system to assist in teaching Probability Theory and Mathematical Statistics. The results of practical application show that with the assistance of the system, the average grade of the students’ Probability Theory and Mathematical Statistics course progresses quite obviously, the post-test grade is significantly higher than the pre-test grade, and the student’s ability of critical reflection also improves. In addition, a significant difference (p<0.05) was observed between the students of the experimental class and those of the control class in the learning motivation posttest. This paper provides new ideas for research related to the big database of biology and academic early warning in teaching, which contributes to the further promotion of teaching reform.
Characteristic Development of Teaching Ideology and Politics Courses in Colleges and Universities Based on Convex Optimization
Authors: Chen Chen
Published: December 2024

This study integrates the theory of convex optimization into the teaching of ideology and politics courses in colleges and universities and puts forward the characteristic teaching strategy of constructing the teaching resource management and network teaching platform of ideology and politics courses. It consists of a course resource module, an after-class Q&A module, and my module to compose the function of the Ideological and Political Science course network teaching platform. Model the computational migration resource division problem of the mobile terminal as a convex optimization problem and solve it using the Lagrange multiplier method to optimize energy consumption of the mobile terminal. Design the registration and login, personal center, likes and comments, resource upload, resource recommendation, and platform management modules as the functions of the teaching resource management platform for Ideology and Politics courses. Use the search algorithm to obtain the correspondence of physical nodes, use the time series prediction smoothing exponential model to reduce the probability of hotspot misjudgment, and determine the best form of placing network resources through global search optimization. Teaching practice is being conducted with the 2022 computer science major students at a university in Guangdong Province, China. The overall Ideology and Politics literacy of the subject students increased by 7.02 compared to the pre-experiment, P=0.031<0.05, showing a significant difference. Satisfaction with the teaching of ideology and politics courses also exceeds 3 and is close to 4, making more recognized classrooms for teaching ideology and politics.
Validation of Correlations Between in Situ Investigations and Soil Parameters Using FEM Modeling
Authors: Poenaru Alexandru
Published: December 2024

This paper aims to validate the geotechnical parameters obtained using new proposed correlations [1] with in situ test results by using the finite element method (FEM). To achieve this objective was performed a numerical modelling of a deep excavation built in the Northern area of Bucharest, by using several constitutive models such as Mohr-Coulomb, Hardening Soil and HS-Small. The geotechnical parameters used as input data for the numerical model were determined based on in situ soil investigations and using new proposed correlations described in [1]. The numerical model results in terms of horizontal displacements of the diaphragm walls supporting the deep excavation were compared to the measured displacements obtained from 2 inclinometers. Based on these results useful conclusions regarding the validity of the proposed correlations are drawn. This paper is part of wider doctoral research regarding correlations between in situ tests and geotechnical parameters.
Identification of the Areas at High Pluvial Flood Risk Based on Urban Hydraulic Modelling. Case Study for Tulcea Municipality
Authors: Dan Marinela Teodorescu , Hodson Gavin , Lee Rebecca , Speak Ben , Rădulescu Daniela , Rizea Cristina , Cozma Andrei
Published: December 2024

Pluvial floods are frequent phenomena in Romania occurring during torrential rainfall, causing significant damage. Pluvial floods occur due to extreme rainfall when the natural infiltration of excess water into the ground is artificially reduced and when runoff into urban areas exceeds the capacity of existing drainage systems. In urban areas, pluvial flooding is more frequent due to extended impermeable areas, buildings, and undersized drainage systems. Tulcea municipality is characterized by periodic rainfall flooding events with consequences on properties and communities, infrastructure, and on the economic activities. In the second cycle of implementation of the Floods Directive 2007/60/EC, 17 Areas of Potential Significant Flood Risk (APFSR) pluvial source areas were identified, covering 19 municipalities and towns, for which pluvial hydraulic models were carried out. Tulcea municipality was one of the cities designated as having areas of potential significant pluvial flood risk. Hydraulic modelling results have been used for the construction of pluvial flood hazard and risk maps, these being the first pluvial maps reported by Romania to the European Commission. Based on these maps, critical drainage areas have been identified at the level of Tulcea Municipality and some potential flood risk reduction measures have been recommended.
An Alternative Method for Checking Reinforced Concrete Elements Under Biaxial Bending
Authors: Tudor Marius
Published: December 2024

The article presents an original method for verifying reinforced concrete elements under biaxial bending with axial force, in structures subjected to seismic action. This method was easily implemented in automated calculation programs based on numerical analysis. The nonlinear behavior of the reinforced concrete cross section was considered. More importantly, we propose a new method of presenting the results of numerical analysis. This representation involves a two-dimensional graph that can be printed on paper, and it shows the boundary between the resistance reserve of the analyzed element and the direction of horizontal loading. The described method exhibits a very good convergence, allowing results to be calculated and presented rapidly to the program user. The presented method can be successfully applied to any type of geometry and reinforcement.
The Spatial Variation of Seismic Ground Motions Under the Magnifying Glass of the Coherency Function Regarding the Smart-1 Array Located in Lotung, Taiwan
Authors: Diaconu Adrian-Aurelian
Published: December 2024

The presented topic contains the calculation procedures and the signals processing concepts used in the studies conducted in the presented report. The spatial variation of seismic ground motions is a phenomenon which regards the modification in terms of the frequency content and phase offset. This phenomenon assumes that the waves pass through soil strata that modify the arrival time of the waves. This idea is called wave passage effect. The incoherence of the waves is caused by the fact that when the waves pass through the soil, they encounter objects which determine them to reflect or refract from the main direction of propagation.
Experimental Studies on Glued Laminated Timber Beams Reinforced With Polymer Fibers
Authors: Teodorescu Ioana , Țăpuşi Daniela , Erbaşu Ruxandra , Savu Adrian-Alexandru , Butucescu Răzvan , Papurcu Andrei
Published: December 2024

The use of wood as building material is considered a viable alternative to other materials in the increased seek of means to fight against the severe negative impact of construction sector on the environment.

The study program aims to performing a series of adherence tests on 6 different specimen types composed by glued laminated timber elements (glulam) joined together with different polymeric materials (FRP - fiber reinforced polymer) by means of a series of different adhesives.

The goal of the study is to find the composition of elements (wood, adhesive and FRP) for optimum specimens from both structural and economic point of view.

Furthermore, a detailed analysis has been made on how to implement these new materials in the nowadays construction sector.
Artificial Neural Network Approach to Predict Carbonation Depth in Metakaolin, Brick Powder and Calcined Sediments-Modified Mortars
Authors: Benamar Souheyla , Kameche Zine El Abidine , Mamoune Sidi Mohamed Aissa , Siad Hocine , Houmadi Youcef
Published: December 2024

This research uses Artificial Neural Network (ANN) as a soft computing technique to predict the carbonation depth and service life of cementitious materials with low clinker content. For this purpose, different mortars were prepared with 0, 10, 15, 20, 25 and 30% replacement levels of cement by metakaolin (MK), brick powder (BP) and calcined sediments (CS). The experimental results of the carbonation depth were obtained under natural and accelerated carbonation conditions for exposure periods of 12 months and 28 days respectively. ANN was utilized taking into account the main influential factors on mortars carbonation, including mix proportions and environmental conditions. For the ANN model, seven datasets were considered as inputs, covering mineral admixture content, cement content, curing time, CO2 concentration, relative humidity, temperature and CO2 exposure time, in addition to one output parameter which is the carbonation depth. The results show that the resistance to carbonation of the mortars decreases with the increase of cement substitution by MK, BP or CS. The network model gives good performance values in the validation and testing set with a lower mean square error (MSE) and a higher determination coefficient (R). The predicted carbonation depths are in good agreement with the experimental measurements of carbonation depths, confirming the efficiency of the developed ANN model to be applied to correctly estimate the carbonation depth of cementitious materials with low clinker content.
The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling
Authors: Rugină Andrei Mihai
Published: December 2024

Floods are natural disasters that have a significant impact on everyday human life, both through material losses and loss of life. In the context of climate change, these events may be more frequent or more dangerous. For real-time flood forecasting, fast methods for determining flood hydrographs along watercourses are needed. Classic hydraulic modeling software provides satisfactory results, but in many cases the calculation time can be high. Another approach, different from classical hydraulic modeling is the use of neural networks for forecasting hydrographs. Thus, the present study aims to analyze three different types of recurrent neural networks, including SRNN, RNN-LSTM, RNN-GRU. For each network type, flow hydrographs and level hydrographs resulting from hydraulic modeling were provided as input and training data. Using the deep learning environment, based on previous calibration and validation of recurrent neural networks, flood hydrographs for 2 historical events were modeled. The obtained hydrographs are extremely close to those recorded, while the running time is tens of times smaller.
Synthesis, characterization, and applications of a novel poly(4-[pyrrol-1-yl methyl]benzoic acid)–silver composite
Authors: Benamrani M. I. , Chikouche I. , Zouaoui A.
Published: December 2024

This article describes the manner in which a novel composite compound was synthesized using a novel method and optimized using a poly(4-[pyrrol-1-yl methyl]benzoic acid) (PPy-b) polymer and very little amount of metallic silver microparticles. The deposition of the polymer film on a fluorine-doped tin oxide (FTO) substrate surface was performed by electrochemical oxidation of the monomer in acetonitrile medium at an imposed potential. The incorporation of silver microparticles was carried out by immersing the modified electrode in a solution of silver nitrate to complex the Ag+ ions with the carboxylic group (COOH) present in the backbone of the polymer, followed by an electrochemical reduction of the complex to precipitate the silver in the form of metallic microparticles in the polymer film. Different characterization techniques (cyclic voltammetry, electrochemical impedance spectroscopy, and surface analysis techniques) were used to optimize the prepared material. Despite the very small quantity of silver (a few micrograms), inserted into the polymer film, the composite material thus obtained had good electrical, optical, and catalytic properties.
Pelatihan dan Produksi Konten Audiovisual untuk Mempromosikan Potensi Wisata di Desa Hargowilis, Kulonprogo
Authors: Marwiyati Marwiyati , Sunarsa Sunarsa , Karna Karna , Angkoso Sutanto Prasetyo , Prasetyo Lilik Jatmiko , Wahyudin Ade
Published: December 2024

Desa Hargowilis, Kabupaten Kulonprogo, Daerah Istimewa Yogyakarta memiliki potensi besar sebagai desa wisata berkat keindahan alam dan sumber daya lokalnya, misalnya Waduk Sermo dan produk UMKM seperti gula kelapa. Namun, kurangnya promosi digital dan keterampilan masyarakat dalam pembuatan konten audiovisual menghambat pengembangan potensi tersebut. Program pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi warga desa melalui pelatihan pembuatan konten audiovisual sederhana guna mempromosikan potensi desa dan produk lokal. Kegiatan yang berlangsung selama lima hari melibatkan 6 dosen dan 5 mahasiswa, serta diikuti oleh 20 warga desa dari unsur Karang Taruna dan aparatur desa. Metode pelatihan yang digunakan dalam kegiatan ini bersifat interaktif dan partisipatif, dengan penekanan pada praktik langsung yang didampingi oleh tenaga pengajar yang berkompeten. Hasil dari pelatihan ini adalah tiga karya video yang menampilkan potensi wisata, profil desa, dan UMKM lokal. Meskipun sederhana, karya-karya ini telah menunjukkan peningkatan signifikan dalam keterampilan peserta. Diharapkan melalui pelatihan ini, Desa Hargowilis dapat memanfaatkan teknologi digital untuk mempromosikan potensi lokalnya secara lebih luas. Hargowilis Village, located in Kulonprogo, Yogyakarta, has significant potential as a tourism village due to its natural beauty and local resources, such as Sermo Reservoir and MSME products like Coconut Sugar. However, the lack of digital promotion and residents’ skills in creating audio-visual content has hindered the development of this potential. This community service program aims to enhance the skills of villagers through training in simple audio-visual content production to promote the village’s potential and local products. The five-day program involved 6 lecturers and 5 students, with 20 participants from local youth groups and village officials. The training methods employed in this activity were interactive and participatory, with an emphasis on hands-on practice guided by competent instructors. The result of the training was the production of three videos showcasing the village's tourist attractions, profiles, and local MSME. Although simple, these works demonstrated a significant improvement in participants' skills. It is hoped that through this training, Hargowilis Village can utilize digital technology to promote its local potential more widely.
Possibilities of ultrasound elastography of peripheral nerves in children with type 1 diabetes mellitus
Authors: Fomina S. V. , Zavadovskaya V. D. , Samoilova Iu. G. , Koshmeleva M. V. , Kachanov D. A. , Trifonova E. I. , Zorkaltsev M. A. , Yun V. Е.
Published: December 2024

Diabetic polyneuropathy (DPN) is a complication of diabetes mellitus (DM) that requires special attention in childhood. The search for new methods for assessing peripheral nerves is an urgent task. Shear wave ultrasound elastography offers additional opportunities for assessing peripheral nerve changes in children with type 1 diabetes.

The purpose of the study is to evaluate the parameters of ultrasound elastography of peripheral nerves in children and adolescents with type 1 diabetes mellitus.

Material and methods. The study included data from 213 children aged 7-18 years. Of these, 159 children were diagnosed with type 1 diabetes mellitus of varying duration and the control group included 54 children.

Ultrasound examination of the peripheral nerves of the lower extremities was performed in all patients using B-mode, shear wave elastography mode.

Results. The data obtained during the study indicate the possible use of ultrasound elastography for dynamic monitoring of the condition of peripheral nerves in patients with type 1 diabetes in childhood and adolescence. Peripheral nerves in this category of patients are characterized by higher values of stiffness parameters in ultrasound elastography.
Comparison of diagnostic efficacy of 2D and 3D ultrasound in women under the age of mammography screening
Authors: Garanina A. E. , Kholin A. V.
Published: December 2024

Breast cancer is the most common cancer among women worldwide. Younger women are more likely than older women to have aggressive molecular subtypes and late-stage disease. Mammography has less sensitivity in detecting breast cancer in women with a dense breast, and 2D ultrasound (2D US) has limitations, such as the specialists high level of skill and experience and the time it takes to perform the examination. Nowadays, there is a new technique – automated volumetric ultrasound scanning of the breast (3D US), which allows you to obtain high-resolution images.

Aim. To perform a comparative analysis of the diagnostic efficacy of 2D US and 3D US among women under 40 years of age with high breast tissue density.

Methods. A retro-prospective clinical single-center study. From February 2019 to May 2023, 1511 patients under the age of 40 were examined. The patients were divided into two groups. Patients in group A underwent 2D ultrasound, the results of the study were evaluated according to the BI-RADS classification. In addition to 2D ultrasound, the patients who were placed in group B underwent 3D US also with the BI-RADS category. Based on the results of the study, the positive and negative predictive value, sensitivity, specificity and accuracy, as well as the compilation of a predictive model of the method were determined.

Results. The 2D US in group A showed sensitivity of 0.8, specificity 1, balanced accuracy of 0.9, and area under the predictive model curve of 0.947, US in group B 0.89, 0.98, 0.94, and 0.903, respectively, and US of the entire sample of 0.87, 0.99, 0.93, and 0.916, respectively. The 3D US in group B showed a sensitivity of 0.95, specificity of 0.99 and a balanced accuracy of 0.97 and an area under the predictive model curve of 0.968.

Conclusion. The diagnostic efficiency of 3D US of the mammary glands in patients under 40 years of age is comparable in terms of specificity and is better in terms of accuracy, sensitivity and a better prognostic model of the method compared to US examination in 2D mode. The 3D US method has advantages in comparison with 2D US examination, namely reproducibility, operator independence of the method, reduced examination time, obtaining visualization of the entire organ, improved visualization in multicentric and multifocal processes, the possibility of operational planning, the possibility of “double reading” of the results.
Magnetic-resonance tomography post injection contouring plastic face different type fillers: features of the picture and signal characteristics
Authors: Magomedova S. A. , Vasil´ev A. Yu.
Published: December 2024

Purpose: to study the possibilities of magnetic resonance imaging in characterizing the soft tissues of the face after injection of various types of fillers.

Material and methods. A group of 35 patients with a known cosmetic history was analyzed after combined (15) and non-combined (20) injection injections of fillers into various areas of the face. According to the anamnesis, with combined administration, hyaluronic acid (HA) + Ca hydroxyapatite (CaHA) was used in 10 cases, HA + L­polylactic acid (PLA) in 2 cases, HA + PLA + silicone in 1 case, HA + CaHA + silicone in 1 case, in 1 – HA + silicone. With non-combined administration, 16 patients received HA, 2 received Ca hydroxyapatite, one received L-polylactic acid, and one received polyacrylamide gel (PAGE).

MRI of facial soft tissues was performed at different times after drug administration: HA – from 1 month. up to 4 years, CaHA – from 7 days to 1 year, PLA – from 1 to 8 months, silicone – 10–20 years, PAGE – after 6 months.

The studies were carried out on 1.5 T MRI scanners, using T2-WI, T1-WI, STIR, DWI (b = 1000), T1-FS-WI, 3D-T2-WI sag. The location of the filler was determined, the type of filler was differentiated, and its location in relation to the surrounding structures was assessed.

Results. Areas of the HA preparation were characterized by a hyperintense MR signal on T2-weighted images and Stir, isohypointense on T1-WI. Preparations based on CaHA and PLA were determined by isohypointense on T2, T1-WI, isohyperintense on Stir, iso- and isohyperintense on T1-FS-WI signal. Silicone demonstrated isohypointense signal with a hypointense capsule on T2-WI and Stir isointense on T1-WI; PAGE – isohyperintense on T2-WI and Stir, isohypointense on T1-WI with a hypointense capsule on all PIs.

HA-based fillers were more clearly visualized on Stir and T2-WI. Preparations based on CaHA and PLA had identical signal characteristics on T2-WI, which made differential diagnosis difficult, but in a number of cases the following signal changes were detected on T1-FS-WI: iso- and isohypointense from CaHA, isohyperintense from PLA. The MRI picture varied depending on the timing, technique of administration and dilution of the drug.

Conclusions. MRI allows you to visualize and differentiate the type of filler after injection contouring according to signal characteristics that depend on its chemical composition, timing of administration and mechanisms of biodegradation.
Changes in uterine hemodynamics after treatment of chronic endometritis
Authors: Ozerskaya I. A. , Porkhovaty S. Ya. , Kazaryan G. G. , Ozhogina E. V.
Published: December 2024

Objective: to evaluate the hemodynamics of the uterus and endometrium after therapy for chronic endometritis in women of reproductive age.

Material and methods. A prospective cohort study of 158 patients with a verified diagnosis of “chronic endometritis” was conducted before and after complex etiotropic therapy. Ultrasound examination was performed in the 1st phase of the menstrual cycle with measurements of Vmax, Vmin, Vmean, PI, RI, the diameter of the uterine arteries with subsequent calculation of the arterial perfusion index. The degree of vascularization of the uterus and endometrium was assessed using the VI, FI, VFI indicators obtained during 3D angioscanning.

Results. In the hypoplastic morphotype, there is a persistent decrease in the arterial blood supply to the uterus, which is combined with hypovascularization of the endometrium both before and after treatment. In the hyperplastic morphotype, the arterial blood supply is not impaired, but in the endometrium, hypervascularization detected before therapy is reliably reduced due to the disappearance of venous stasis during treatment. In the mixed morphotype, there are no pronounced disturbances in arterial hemodynamics; the blood supply to the endometrium after treatment significantly increases, which indicates the absence of a violation of venous outflow and the restoration of the macrovascular network of the mucous membrane of the uterine cavity.

Conclusion. Pathological blood supply to the uterus and endometrium is associated with the degree of severity of venous outflow disorder and the reparative capacity of the endometrium, which change against the background of complex etiotropic therapy depending on the morphological type, which allows us to judge the therapeutic effect.
Assessment and Comparison Analysis of Cerebral Perfusion SPECT Parameters in Liquidators of the Chernobyl Accident Suffering from Dyscirculatory Encephalopathy Long After Exposure to Radiation
Authors: Kulikova T. A. , Meshkov N. A. , Solodkiy V. A. , Fomin D. K. , Borisova O. A. , Nudnov N. V.
Published: December 2024

The purpose of the study is to perform comparative analysis of cerebral perfusion SPECT parameters found in liquidators of the Chernobyl accident suffering from dyscirculatory encephalopathy (DEP) long after exposure to radiation and to identify indicators for monitoring their physical condition and assess treatment effectiveness.

Materials and methods. We used cerebral single-photon emission computed tomography (SPECT) to examine a group of liquidators of the Chernobyl accident (LCA) and a group of patients who had not been exposed to radiation, all of them suffering from dyscirculatory encephalopathy (DEP). We examined a total of 147 men, including 93 LCAs aged 69.38 (6.42) (the study group) and 54 patients aged 70.70 (7.25) (the comparison group). No differences by age were identified (p = 0.347). The study was performed using General Electric Healthcare Discovery NM/CT 670 Pro. Cerebral scintigraphy was performed using Russian-made Theoxym, 99mTc. Cerebral perfusion imaging was carried out with the help of diacarb (acetazolamide). We compared a total of 22 SPECT parameters.

Results. Arterial inflow time in the frontal and back views in both groups increased after taking diacarb by 8.37% (p = 0.138) and 6.62% (p = 0.213) in LCAs and by 15.38% (p = 0.035) and 13.63% (p = 0.037) in the comparison group. Regional cerebral blood flow (rCBF) in the right and left brain hemispheres of LCAs was below the age norm (p = 0.001 and p < 0.001), as well as below the rCBF in the frontal, temporal, parietal, and occipital lobes of the brain in healthy subjects of comparable age (p < 0.001). Average cerebrovascular reserve (CVR) in both groups was lower than the lower end of the normal range (31–75%). Only some of the patients from the comparison group fell within this range: 2.94% of those examined – in the temporal and occipital lobes of the right hemisphere and 8.82% – in the occipital lobe of the left hemisphere. CVR was lower in LCAs than in the comparison group by 14.19 and 14.08% in the frontal lobes of both hemispheres and by 16.31% in the temporal lobe of the left hemisphere; in the occipital lobes, however, it was higher by 29.07 and 12.06%. We found a negative correlation between rCBF and CVR and LCAs’ age, as well as between CVR and radiation dose (p < 0.05).

Conclusion. SPECT is a promising method of detecting DEP in LCAs and other patients who have been exposed to radiation, as well as of preventing health complications and assessing treatment effectiveness. A decrease in rCBF and CVR in the frontal and frontotemporal areas of the brain may serve as the criterion for DEP detection.