bluuebunny/crossref_metadata_2025_split huggingface dataset:
In Vitro and In Silico Profiling of Phenolics in Pentaclethra Macrophylla Leaf Extract on Key Proteins Linked to Erectile Dysfunction
Authors: Nwagwe O. R. , Adefegha S. A. , Oboh G. , Adewale I. O. , Fatoki T. H. 
Published: October 2024

Abstract

Introduction
Erectile dysfunction (ED) which is the inability to maintain an erection during sexual activity, is one of the most prevalent sexual dysfunctions, with mild to severe ED affecting an estimated 5-20% of men globally and about 322 million men may be affected globally by 2025.

Aim
The present study was carried out to explore the phenolic constituents of Pentaclethra macrophylla, its antioxidant properties and potential binding mechanism on the key proteins linked to erectile dysfunction.

Method
The method used included phytochemical screening, high-performance liquid chromatography coupled with diode array detector (HPLC-DAD) quantification, in vitro analyses as well as in silico analyses such as target prediction, molecular docking and molecular dynamics (MD) simulation.

Results
The phytochemical screening revealed that the extract contains various phytochemicals such as alkaloids, flavonoids, tannins, saponins and terpenoids. The total flavonoid and total phenolic contents were increased with increasing concentrations of the extract while DPPH and nitric oxide percentage scavenged activities were not significantly changed across the concentrations. The chromatogram of the phenolic contents of P. macrophyla obtained from HPLC-DAD indicated the presence of major compounds such as naringin, ellagic acid, epicatechin, epigallocatechin gallate, quercetin, myricetin, and rutin. The results of the target prediction showed that compounds relevant to ED are naringin, kaempferol, quercetin, and myricetin. Molecular docking results indicated that they have affinity for myeloperoxidase, followed by phosphodiesterase 5 (PDE5) and acetylcholinesterase. Naringin has the highest binding affinity (-11.040 kcal.mol-1) for myeloperoxidase, and 9.333 kcal.mol-1 for PDE5. The results of MDS indicate changes in the binding energy and stability of the complex of PDE5 with naringin as well as myeloperoxidase with naringin.

Conclusion
Overall, the results proposed naringin as the potential bioactive compound in P. macrophylla that could be useful for treatment of erectile dysfunction.
Molecular Insights on Binding Interactions of Cyclooxygenase and Lipoxygenase Activities on Malondialdehyde in Naphthalene-Exposed Wistar Rats
Authors: Olaoye I. , Akhigbe G. , Awotula A. , Oso B. , Agboola O. , Adebayo A. , Banwo R. 
Published: October 2024

Abstract

Background
Naphthalene (NA), a polycyclic aromatic hydrocarbon, is an environmental pollutant from different sources exhibiting toxicities via free radical generation. However, NA has been used in the industry as surfactants, solvents, resins, and in medicine – as an anti-viral, anti-bacterial, and antiinflammatory drug. Malondialdehyde (MDA), a by-product in lipid peroxidation and prostaglandin synthesis, is a biomarker in lipid peroxidation evaluation and cyclooxygenase (COX) and lipoxygenase (LOX) activities assessment via inhibition.

Results
The twenty-four adult male Wistar rats were randomly divided into six groups of four rats each. The animals in the control groups were given food and water only while the NA-exposed groups: group 3 (N1) rats exposed to NA at 0.75 mg/m3 for 2 hours, group 4 (N2) rats exposed to NA at 1.5 mg/m3 for 2 hours, group 5 (N3) rats exposed to NA at 0.75 mg/m3 for 4 hours and group 6 (N4) rats exposed to NA at 1.5 mg/m3 for 4 hours. In addition, in silico work was carried out on the homologs of COX and LOX with NA and its selected metabolites. The in vivo result revealed a significant increase (7.50 ± 0.29) in MDA synthesis at the lower dose (0.75 g/m3) during the 2 hrs exposure time compared to the control while the higher dose (1.50 g/m3) showed a significant reduction in MDA level (1.00 ± 0.01) compared to the control. Furthermore, docking result depicted highest binding score for 1-nitronaphthalene towards COX and LOX.

Conclusions
This study suggested that NA could reduce the synthesis of MDA in the in vivo work, and 1-nitronaphthalene showed the highest binding affinity in the in silico work.
Motion graphics design for visual communication in virtual simulation environments
Authors: Wang Hui 
Published: October 2024

Abstract
This study introduces a dynamic graphic feature extraction algorithm rooted in the design principles of dynamic visuals. Utilizing visual perception algorithms, it establishes a priori frames to accurately extract image features through a minimized loss function, enhancing the precision of the extraction process. Concurrently, it advances a refined geometric constraint-solving algorithm that employs trigonometric columnar equations to facilitate the generation and transformation of dynamic graphics, thereby effectively capturing the dynamic attributes of geometric visuals. Additionally, this paper presents a specialized pathway for applying dynamic graphics, including a practical analysis of the dynamic illustration portfolio by Chinese illustrator Lu Tao. In terms of user satisfaction, the dimensions of interestingness and aesthetics garnered mean scores of 3.98 and 3.92, respectively, while the dissemination tendency dimension achieved a notably high mean score of 4.17. This suggests that dynamic illustration design possesses significant aesthetic appeal and can effectively encourage viewer engagement and sharing. Overall, the comprehensive evaluation indicates a generally positive reception among viewers, with all indicators, except for the emotional identity connotation—which scored slightly lower at 3.87—receiving ratings above 4. This reflects a broadly affirmative attitude toward the dynamic illustration portfolio within the realm of dynamic graphic design.
Research on automatic control and servo control technology of industrial robots for high-precision assembly requirements
Authors: Liu Shukai 
Published: October 2024

Abstract
Industrial robots find widespread application in machining, part assembly, and welding processes. This paper focuses on the precise control of industrial robots, using the permanent magnet synchronous motor (PMSM) as the driving device of the manipulator. By constructing a mathematical model of the PMSM and implementing a vector control strategy, we design an adaptive control algorithm based on the feature model. We also introduce the golden section adaptive control and the position outer-loop control, which are based on the nonlinear proportional regulator. This approach enables the creation of industrial robots that utilize high-precision servo control technology. After analyzing the response speed and positional accuracy of the servo control technology through testing experiments, we integrated this technology into the design of the automatic control system for industrial robots and conducted simulation tests to explore its performance in various applications. The results demonstrate the superior speed response speed and position control accuracy of the servo control technology; the response times for speed and position are approximately 0.2 seconds and 1 second, respectively, with a maximum deviation of 31.75 rpm when the speed remains constant. The industrial robot control system’s structural displacement and tool switching time are both within 2.88 mm and 0.65 s, and it has a large torque. The study confirms that servo control technology and automatic control of industrial robots have superior performance.
To study the development path of museum intangible cultural heritage tourism industry in the era of digital economy
Authors: Su Le , Ismail Noor Hafiza 
Published: October 2024

Abstract
The museum incorporates historical resources, stores them in a systematic classification, and then presents them as objects for viewing and learning training. Intangible cultural heritage is the aesthetic crystallization of the wisdom and aesthetics of ancient Chinese people. Combining museums and intangible cultural heritage culture and developing the intangible cultural heritage cultural tourism industry of museums can fully utilize the advantages of museums in terms of location and dissemination, as well as achieve high-quality promotion of intangible cultural heritage culture. The digital era has brought new changes and numerous challenges to the development environment and spatial design methods of the intangible cultural heritage tourism industry in museums. This paper builds a museum intangible cultural heritage cultural tourism platform based on digital tour interaction technology. It considers the advantages of the development of the cultural tourism industry from the “museum + intangible cultural heritage” model, establishes a digital resource management system for museums, digital talent training, and management mode, and digital branding in light of the current development status and challenges of the museum intangible cultural heritage cultural tourism industry. Additionally, we will create a digital resource management system for museums, a digital talent training and management model, and a digital brand marketing system to boost the industry’s ecological development.
Research on the Integration of Civic and Political Elements and Student Engagement in University English Classes Driven by Artificial Intelligence Algorithms
Authors: Li Lingling 
Published: October 2024

Abstract
The integration of civic and political elements into the English classroom is an innovative way to give full play to the role of college education in cultivating students’ worldview, outlook on life, and values, while student participation is an effective way to measure the quality of English civic and political courses. This paper incorporates artificial intelligence algorithms into the design of English Civics and Politics courses while examining student participation to foster the intelligent advancement of civics and politics reforms in college English classrooms. This paper combines artificial intelligence technology to construct a civics and politics teaching system for university English courses at various levels, catering to both teaching purposes and other learning objectives. It adopts critical technologies such as face detection, head posture detection, etc., and proposes a student participation evaluation model based on attention and fatigue state criteria. The civics and artificial intelligence elements were integrated into the “Comprehensive English” course to design the civics course of college English and carry out the teaching practice for one semester. The practice improved the student’s scores on the questionnaires in the areas of knowledge and skills, civic awareness, teamwork, and values by 84.64%, 104.74%, 58.92%, and 86.27%, respectively, compared to their pre-practice scores of 58.92% and 86.27%. The results of selecting students’ classroom videos and detecting their attention, fatigue state, and cognitive state show that students’ overall participation in the university English Civics classroom designed in this paper is high.
An Artificial Intelligence Prediction Approach for Behavioral Intentions of Health Tourism: a Protection Motivation Theory-based Perspective
Authors: Dai Haijian , Lee See-Nie , Chong Kim Mee 
Published: October 2024

Abstract
This study applies an artificial intelligence (AI) method, informed by the Protection Motivation Theory (PMT), to predict the behavioral intentions of tourists in a healthy town in Yunnan. This study looks at online search data to guess when a lot of tourists will come by combining text mining with the SPCA-LSTM model. This model combines seasonal and trend decomposition using Loess (STL) with Long Short-Term Memory (LSTM) networks. The model is more accurate than traditional forecasting methods and provides a daily average tourist flow estimate of 3,247 with minimal prediction errors. The average absolute error of 806.4074 and the root mean square error (RMSE) of 959.775 further highlight the model’s performance. This research contributes significantly to tourism management and strategic planning, particularly in health-related destinations. The model provides a reliable benchmark for predicting tourist flows enhancing decision-making processes in the tourism sector.
Research on Intelligent Recommendation of Teaching Resources for Civics and Political Science Courses for Smart Education Platforms
Authors: Zhu Fang 
Published: October 2024

Abstract
This paper integrates memory-based and SVD-based collaborative filtering algorithms to realize the recommendation of Civic and Political education resources. With the methods of case study and data analysis, a sample study on the construction of a Civic and Political Smart Classroom in WL College is launched to explore the use of intelligent recommendations to obtain Civic and Political education resources in colleges and universities. From the perspective of learning analysis, combined with the social network analysis method, the learning data and interaction of students are analyzed. Based on the feedback from the analysis results, it is convenient for teachers to intervene in students’ learning behavior at the right time. The method in this paper has a recall and accuracy rate of above 95%, which is of good application value, as shown in the results. More than 70% of students and teachers think it can meet their daily personalized learning needs. In terms of independent learning, 43 students exceeded 10 points, accounting for more than 80%. Most students are able to actively participate in classroom interactions as well as online learning discussions, although some of them may not be highly motivated. Therefore, teachers need to understand and personalize instruction for the different situations of their students.
A Model Study on the Development of Intercultural Competence of Business English Majors in the Context of One Belt and One Road
Authors: Hu Rongbing 
Published: October 2024

Abstract
Under the background of Belt and Road, many colleges and universities pay more and more attention to the cultivation and development of cross-cultural competence of business English majors. Based on relevant theoretical research on the framework of intercultural competence development, the article proposes a fuzzy comprehensive evaluation model for the intercultural competence development model of business English majors. The results of the study found that the final comprehensive calculated value of the cross-cultural competence development model of business English majors is (0.48, 0.25, 0.17, 0.08, 0.02), and the cross-cultural competence development model of business English majors has a good application effect. After the implementation of the students’ intercultural competence development model constructed in this paper, the total intercultural competence of the fourth-year students is higher than that of the first-year students as a whole, and in terms of knowledge mastery, it is 3.2±0.35 for the first-year freshmen. At the same time, it is 3.25±0.45 for the fourth-year students.
A computer simulation study of the impact of the oil crisis on the structure of the world economy in the 1970s
Authors: Hou Rui , Gao Liang 
Published: October 2024

Abstract
The outbreak of the oil crisis in the 1970s had an extremely profound impact on the world economy. The use of computer simulation is employed in this paper to explore how the oil crisis led to the restructuring of the world economy in the 1970s. Taking the United States as a representative, we study its main economic characteristics, such as price and currency in the 1970s oil crisis, and analyze the changes in economic characteristics before and after the oil crisis to provide data support for this paper to simulate the impact of the oil crisis on the structure of the world economy. Adopt the VAR model for computer simulation research. The GDP and CPI data of the United States, Europe, Japan, and other countries in the 1970s are selected to construct the variables of the world economic structure. After analyzing the processed data in terms of the Granger causality test, impulse response, and variance decomposition, this paper concludes that the oil crisis triggered by the increase of oil prices in the 1970s has had a significant impact on the world economic structure and the long-term oil crisis will force countries around the world to actively adjust their economic structure in order to cope with the downturn of the economy caused by the oil crisis.
Research on the Analysis of Influencing Factors of Undergraduate Academic Achievement in Local Colleges and Universities and Establishment of Predictive Models
Authors: Chen Juan 
Published: October 2024

Abstract
The quality of higher education directly points to the academic achievement of college students, and clarifying the influencing factors related to college students’ academic achievement is a prerequisite to helping college students improve their academic achievement. In this paper, structural equation modeling is used to analyze the influencing factors of the academic achievement of undergraduates in local colleges and universities, and then the PSO-WRF model is constructed to predict the academic achievement of undergraduates in local colleges and universities. Path analysis and direct effect analysis are carried out on the influencing factors model. Finally, the PSO-WRF model is empirically analyzed and integrated into the influencing factor model to compare its prediction effect and obtain the best model. The study hypothesized that the critical ratios C.R. of H1~H6 are all greater than 1.96, the P-values are all less than 0.01, and the estimates reach the 0.05 level of significance, which indicates that all hypotheses are valid, i.e., there is a significant and positive Emotional Intelligence to Learning Motivation, Emotional Intelligence to Academic Achievement, Emotional Intelligence to Learning Strategies, Learning Motivation to Academic Achievement, Learning Motivation to Learning Strategies, and Learning Strategies to Academic Achievement The relationship between emotional intelligence and academic achievement The mediation effect test concluded that there is a mediating effect of learning motivation in the effect of emotional intelligence on academic achievement. Its prediction effect was optimal after incorporating the influencing factor model in the multi-period academic achievement prediction model considering historical information, and its prediction accuracy was 0.904, which was improved by 0.033 compared with that when it was not incorporated. In this paper, the influencing paths of the factors on undergraduates’ academic achievement were verified, and their incorporation into the prediction model was of great significance in the study of academic achievement prediction.
Simulation of Dynamic Characteristics of Buildings under Wind Loads and Innovative Design Methods for Wind-Resistant Structures
Authors: Guo Xiaofang 
Published: October 2024

Abstract
The dynamic characteristics of buildings are the basis for studying the vibration of buildings under wind loads, while the innovative design of wind-resistant structures is an important guarantee for the safety and comfort of buildings under wind loads. In this paper, we calculate the building’s dynamic characteristics by establishing the vibration equations of the structure. We then convert the wind load into an equivalent static load and establish the necessary conditions to construct an optimized wind-resistant structural design model. The finite element modeling method is used to generate the building model of this paper and conduct research on its dynamic characteristics and wind-resistant design. In this paper, the model in the vicinity of 0.6Hz and the wind load along the parallel direction of the building, x direction appears to reach the peak amplitude response of 4.22cm. The pressure coefficients at each measurement point of the building are found to increase gradually with the increase of Re and reach the critical condition at Re = 1.02×106 under 0° wind angle. Through the implementation of simulated wind tunnel tests on the building, this paper provides a preliminary assessment of the existing wind design methods and highlights the problems in these methods. Using the comparative analysis method, it can be obtained that the optimized wind-resistant structure model of the building designed in this paper reduces the base shear force in the crosswind direction by 3.73% and the base shear force in the downwind direction by 5.53%. At the same time, the inter-story displacement angle of the building is significantly reduced after optimizing the wind-resistant design.
The Effectiveness of Educational Resource Optimization Based on Big Data Technology on Enhancing Students’ Creative Ability
Authors: Jiang Lijie 
Published: October 2024

Abstract
The personalized recommendation method is an efficient and effective solution to optimize educational resources, which can effectively extract learners’ preference characteristics and select suitable high-quality educational resources for them to improve teaching efficiency. In this paper, we construct a confidence-aware recommendation model for educational resources. In order to reduce the sparsity problem of rating data, a constraint method based on the implicit factor of user-object interaction is designed to construct the implicit factor of item-user interaction by using the information of a single review. Meanwhile, a confidence matrix is introduced to improve the accuracy of recommendations, and a loss function is constructed using the maximum a posteriori estimation theory. The loss function is optimized by introducing a small batch gradient descent algorithm at the end. Two datasets are used to verify the model’s performance, and the impact on students’ innovation ability is assessed in teaching practice. It is found that the model in this paper outperforms the other three classification models, and the test results on the two datasets of online_shopping_10_cats and Course Classify achieve an accuracy of more than 0.95. The experimental class’s innovation ability increased by 37.6% from 46.25 to 63.63, while the control class’s pre- and post-scores of 46.36 and 47.88 were not significantly different. It can be seen that the experimental class has progressed differently in the four dimensions after applying the model of this paper. This study proposes new ideas and feasible paths for combining the optimal allocation of educational resources with cutting-edge information technology, empowering students’ innovation ability through big data technology.