bluuebunny/crossref_metadata_2025 huggingface dataset:
debate legislativo sobre el aborto en la Argentina
Authors: Car Valeria , Romano Silvina , Martínez Ayelén
Published: October 2024

Se aborda en este artículo un estudio comparativo entre dos instancias del debate legislativo sostenido en la Argentina sobre la despenalización del aborto, en 2018 y en 2020. El análisis de ambos corpus, realizado con el método Alceste, muestra para el segundo tratamiento una considerable reducción en los entramados de las cadenas significantes y un adelgazamiento en las tramas del discurso, que redundan en un claro empobrecimiento del debate que se sostuvo en esta ocasión en la que, finalmente, se aprobó la Ley 27610 de Acceso a la Interrupción Voluntaria del Embarazo (IVE).
Interrelation of Etymology and Semantics in Old English Lexis of Authority
Authors:   Lomonosov Moscow State University, Arutunova Inessa
Published: October 2024

The main aim of the article is to investigate the extent to which the meaning and the use of a word, or its semantics, is determined by its etymology in Old English poetry and legal documents. Five lexical items have been selected for analysis, which are commonly used in both types of texts – the designations of a ruler or a noble person, such as cyning, dryhten, hlāford, ealdor(mon) and þegn. For each word, its etymology and etymological meaning (the nomination model) are established. Then, through contextual analysis, the role of etymological meaning in the functioning of the word in the text is explored. Special attention is given to the modes in which etymological meaning is expressed. In conclusion, some deductions are drawn about the interrelation between etymology and semasiology, the degree of their interaction in Old English poetry and legal documents, and the causes of the disparity between these degrees in the two types of texts.
N-acetilcisteína en el síndrome de dificultad respiratoria aguda: análisis de costo-efectividad para Colombia
Authors: Romero-Prada Martín , Gómez-Espitia Lina , Clavijo-Angulo Natalia , Acero-Acero Germán , Pérez-Díaz Carlos
Published: October 2024

Introducción: El síndrome de dificultad respiratoria agudo (SDRA) es un tipo de lesión pulmonar inflamatorio aguda difuso de origen, por lo general, infeccioso que incrementa en exceso el proceso de estrés oxidativo, causa daño tisular pulmonar y repercute negativamente en el estado del paciente e incluso puede provocarle la muerte.
Objetivo: Evaluar el uso temprano de N-acetilcisteína endovenosa en adultos con SDRA severo, secundario a neumonía de cualquier etiología, tratados en unidades de cuidado intensivo (UCI), en función de los días de estancia evitados.
Materiales y métodos: Mediante un árbol de decisión y datos provenientes de prestadores de servicios de salud colombianos, se calcularon los días de estancia en UCI que podrían evitarse al añadir N-acetilcisteína intravenosa temprana al tratamiento estándar de un paciente con SDRA. Además, se analizó la sensibilidad probabilística para evaluar la estabilidad y robustez de los resultados obtenidos en el escenario base.
Resultados: El tiempo promedio de estancia en la UCI fue de 8,38 días para el manejo integral, en comparación con 6,84 días para el manejo integral más la adición de N-acetilcisteína. Esta diferencia implica una reducción promedio en el costo de atención de COP4067125 por paciente. Además, la incorporación temprana de N-acetilcisteína al tratamiento demostró ser dominante, resultado que se mantuvo constante en el análisis de sensibilidad.
Conclusión: La adición temprana de N-acetilcisteína al tratamiento del SDRA podría representar una disminución de los días de estancia en UCI y un ahorro en el costo de la atención hospitalaria.
A mattress suture with pledgets can partially occlude intrahepatic shunts in 23 dogs: evaluation of long-term survival
Authors: Chu Margaret , Marvel Sarah , Monnet Eric
Published: October 2024

OBJECTIVE

To explore the differences in outcomes between dogs with intrahepatic portosystemic shunts (IHPSSs) partially occluded with a mattress suture with pledgets or attenuated with cellophane banding.

METHODS

74 dogs with IHPSSs were included in this retrospective study. Medical records between January 2000 and February 2020 were evaluated for information on dogs undergoing laparotomy with cellophane banding (group C) or mattress suture with pledgets (group P) for treatment of IHPSSs, including specific outcomes of survival time, persistence of clinical signs, and necessity of continued medical management. Primary veterinarians and owners were contacted for long-term follow-up.

RESULTS

51 dogs were entered in group C and 23 in group P. The duration of surgery was 154.6 minutes (136.3 to 170 minutes) for group C and 154.9 minutes (128.9 to 180.9 minutes) for group P. The short-term mortality rate was 2% for group C and 4% for group P. Dogs in group C had a median survival time of 3,537 days, while dogs in group P had a median survival time of 2,141 days. In the long term, dogs in group P received more medications than dogs in group C, but the distribution of the quality-of-life score was not different.

CONCLUSIONS

Mattress suture with pledgets can be used as an alternative to cellophane banding.

CLINICAL RELEVANCE

For dogs with IHPSSs where full surgical dissection for placement of cellophane band is not possible, partial occlusion of the shunt with a mattress suture with pledgets is a viable option with acceptable long-term outcomes.
Ocular Involvement in Children with Beta-Thalassemia Major
Authors: Lubis B. , Lubis S. M. , Sulistyowati B. D.
Published: October 2024

Aim

Thalassemia is a severe genetic blood disorder, and several organs, including eyes, can be affected. The mechanism of ocular abnormalities in thalassemia is multifactorial; one of them is regular blood transfusion, which can cause iron overload. Ocular abnormalities can also occur because of the side effects of iron chelators. This study evaluated ocular involvement in children with Beta-thalassemia major and its association with serum ferritin levels.

Methods

A cross-sectional study was undertaken at the Thalassemia daycare center in a tertiary referral hospital in Medan. All patients' hemoglobin was measured before transfusion, and serum ferritin levels were measured at six-month intervals. A Pediatric Ophthalmologist carried out the ophthalmological assessment, which included a detailed history of visual problems and visual acuity testing. Fisher's Exact test and Spearman test were used for statistical calculation.

Results

Thirty-seven beta-thalassemia major children ranging from three to 18 years old. Visual acuity, anterior segment, fundus, and retina were evaluated. Ophthalmologic examinations showed that ocular involvement increased with age. Visual acuity was reduced in 16.2% of the subjects. Papilledema was the most common ocular finding among the subjects (13.5%), followed by cataracts (8.1%) and optic atrophy (8.1%). A significant correlation between blood transfusion volume and serum ferritin levels was found.

Conclusion

Ocular involvement was found in more than half of the subjects in this study. However, regular ophthalmologic evaluations by serum ferritin examination were required to detect early alterations in their visual system for a better quality of life.
Diagnostic Accuracy of Microalbuminuria in Secondary Nephropathies
Authors: Kostovska I. , Trajkovska K. , Labudovic D. , Cekovska S. , Kostovski O. , Spasovski G.
Published: October 2024

Introduction

Microalbuminuria is an initial indicator of kidney damage in diabetic nephropathy (DN), hypertensive nephropathy (HN), and pre-eclampsia (PE). This study aims to assess the diagnostic accuracy of urinary microalbumin to creatinine ratio (UM/CR) as an early diagnostic tool in patients with DN, HN, and PE.

Materials and methods

In this cross-sectional study we included a total of 143 subjects divided into three groups: first-group patients with DN (n = 30), second-group patients with HN (n = 23), and third-group women with PE (n = 30). Additionally, we included a control group comprising 60 healthy subjects. The study employed fresh urine samples to measure UM/CR by the turbidimetric method and creatinine by the Jaffe reaction. We also estimated the UM/CR and glomerular filtration rate. Some biochemical parameters were measured in blood sera.

Results

We determined the cut-off value of UM/CR to be 30.0 mg/g. For patients with DN, UM/CR had a sensitivity of 41.5%, a specificity of 90%, and an overall diagnostic accuracy of 53.1% for detecting DN. Similarly for patients with HN, UM/CR had a sensitivity of 44.8% and a specificity of 86.1 %, with an overall diagnostic accuracy of 57.8% for detecting HN. In contrast, for women with PE, UM/CR had a sensitivity of 100%, a specificity of 93.3%, and a diagnostic accuracy of 96.7% for predicting PE. Conclusion: UM/CR can be used as a good screening tool for early detection of PE, while it has low sensitivity as an early marker for patients with DN and HN.
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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Feasibility of the development of short videos in vocational education based on the context of deep learning
Authors: Wang Dong , Xu Huaizhi , Wang Zhuo
Published: October 2024

The development of information technology has brought new opportunities for the development of vocational education teaching, and short video, as a product of information technology, breaks through the limitations brought by the traditional teaching mode and provides a new thinking direction for the transformation of the teaching mode. This paper proposes a recommendation system for short videos based on deep learning, where the scene and behavioral features of the target short video are first extracted to obtain the joint features. Then, user and video modeling is realized using deep learning technology. Finally, the similarity and preference are calculated by combining the joint features of the target short video and the user short video preference features. The TOP-N with the highest user preference is obtained according to the actual demand. The recommendation list is generated to complete the intelligent recommendation of short videos based on deep learning. The experimental analysis found that the recommendation system has high performance, with a maximum recommendation accuracy of 98.2%, and is capable of fully comprehending the students’ demand preferences for short videos. The use of short videos in course teaching can make a great positive change in students’ learning attitudes, and the short video recommendation algorithm based on deep learning allows students to more accurately find short videos suitable for their learning conditions, which further improves their learning efficiency.
A Multimodal Grammar Study of Film Adaptations of Traditional Literature in the Information Age
Authors: Wang Xueyuan , Dou Peilin
Published: October 2024

By analyzing the multimodal grammar of films, the deeper concepts that the designers want to express can be better conveyed to the audience, and the expectations of the moviegoers can be enhanced. Therefore, based on the analysis of the classic Zhang Delu’s comprehensive theory of multimodal discourse, the article proposes the multimodal discourse analysis framework used in this paper to explore the ideologies implied in the text and images of movie subtitles and the images they construct and the inspirational meanings they draw from. It is found that among the 150 clauses in the corpus analysis, 28% are material processes, 22% are mental processes, 12% are verbal processes, 14.67% are relational processes, 17.33% are behavioral processes, and 4.67% are existential processes. Through multimodal grammar analysis, the discourse tendencies of the traditional culture-adapted movie can be effectively grasped.
Collegiate Collaborative Piano Innovation Education Model Empowered by Artificial Intelligence
Authors: Yang Linxi
Published: October 2024

In the era of big data, the development of piano education and teaching has irreversibly shifted towards an intelligent piano education model. In order to optimize the effectiveness of piano teaching in colleges and universities, this paper proposes a new model of intelligent piano education for college and university cooperation based on the Bayesian net model of automatic piano composition and dynamic gesture recognition and correction of piano playing. Combined with the rules of piano music accompaniment composition, it outlines the method of playing the piano left and right hand. Propose various genres and features and analyze the detection rate of Bayesian net models for different genres. The Camshaft algorithm is used to track and record the features of piano playing, while the DTW algorithm is used to detect and recognize piano fingering. Combine the DTW algorithm for gesture recognition with two constraints, endpoint fixation, and endpoint relaxation, to further test the recognition advantage of the DTW algorithm for piano fingering. The feasibility of the cooperative piano education model for colleges and universities proposed in this paper can be verified by comparing the students’ comprehensive music literacy scores in traditional piano lessons and intelligent piano lessons. The Bayesian net model and DTW algorithm both have a detection rate of more than 90% for piano music genres. Compared to traditional piano lessons, intelligent piano lessons can improve 25.12% of piano knowledge and 31.75% of piano repertoire scores, with the intelligent college cooperative piano education model demonstrating significant results.
Research on the Impact and Regulation Mechanism of Digital Currency on Economic Policy Combining Blockchain and Smart Contract Technology
Authors: Yang Luyi
Published: October 2024

The emergence of digital currency has had a significant impact on economic policy while increasingly and profoundly changing the lives of the public. The main research object of this paper is the digital currency that incorporates blockchain and smart contract technology, and it deeply examines how its generation and development impact economic policy and the corresponding regulatory mechanism. The application of blockchain and smart contract technology is used to analyze the characteristics and performance of digital currency, and the advantages and shortcomings of using digital currency are briefly explained. Based on the analysis of related research and practical application requirements, digital currency is being introduced into the DSGE model, which includes households, manufacturers, and other sectors. Impulse response and variance decomposition are used to numerically simulate the impact of digital currency on economic policy and the effectiveness of the regulatory mechanism. The economic policy transmission efficiency is the lowest in the no digital currency scenario, while it is significantly higher in the scenario of full use of digital currency, with interest rate shocks into the maximum degree of change in output and inflation of 0.059% and 0.121%. The variance of each macroeconomic variable in the economic policy regulation scenario shows a significant downward trend, and digital currency contributes to the overall regulation effect of macroeconomic policy.
An Experimental Study on Knowledge Transfer of Higher Vocational Accounting Majors by Teacher-Apprentice System--Taking Shanwei Institute of Technology as an Example
Authors: Luo Miaohua , Xie Yushan , Xie Peifeng
Published: October 2024

The Ministry of Education has issued relevant documents to promote the development of vocational education one after another, and vocational education has been raised to an unprecedented height, and has been highly valued by all aspects of local and national. This paper proposes a study on teaching higher vocational accounting using the apprenticeship system as a response to the national education policy. From the development history of the master-apprentice system, the necessity of the “master-apprentice system” in the accounting industry is introduced, and the specific application of the “master-apprentice system” in the teaching of higher vocational accounting is outlined. The students of Shanwei Institute of Technology were selected as the research object, and the data were collected by distributing questionnaires, and the independent samples t-test was applied to experimentally analyze the knowledge transfer of accounting majors in Shanwei Institute of Technology. After the teaching intervention, there were significant differences in accounting skills, accounting knowledge, and comprehensive quality of accounting among the students in Group C and Group D, with P<0.05, which indicated that compared with the traditional teaching mode, the teacher-apprentice teaching mode had a more obvious effect on the students’ enhancement. This study confirms the feasibility of the “mentor-apprentice system” in the education of higher vocational accounting majors.
Innovation of Operation Mode of Traditional Enterprises in the Era of Digital Economy--Taking Traditional Cultural Enterprises as an Example
Authors: Zhou Jianbo
Published: October 2024

The essence of a cultural enterprise’s digital transformation is the process by which it metamorphoses into a new type of cultural enterprise by using new digital technologies to improve its core business and product concepts. This paper delves into the need for digital transformation in traditional cultural enterprises and devises a strategy for this transformation. It applies data mining technology to customer relationship management, analyzing customer value using the K-means algorithm and weighted association rules. The CRM system, built using data mining technology, can categorize customers into four types and implement corresponding marketing strategies for customers with different values. Using Company A as an example, we verify the impact of this innovative model on revenue, profit, and operational capacity. After the digital transformation of Company A, the operating profit maintains a fast growth rate, in which the difference in profit between December and November reaches 31,132 yuan, and the gap between the company’s inventory turnover rate and that of the same industry in December is only 0.1%. The digital transformation of traditional cultural enterprises has facilitated the company’s rapid growth.
Optimization Strategy of Strategic Human Resource Management Based on Big Data in Dynamic Environment
Authors: Liu Shun
Published: October 2024

It is very critical for enterprise human resources to be reasonably and effectively utilized, and information-based human resource management greatly improves enterprise production and work efficiency. The study combines big data algorithms to first optimize the human resource demand in HRM based on a multiple regression model, then optimize the employee performance appraisal with multiple objectives, and finally predict the employee leaving based on the SMOTE-SVM model. The SSH technology framework is combined to construct the strategic human resource management optimization system, and the TJ company is used as an example for instance analysis. After testing, the predicted value of human resource demand based on multiple regression basically matches the actual situation of the enterprise, and the maximum prediction error is only 0.55. After optimization through performance appraisal, the abnormal data decreases from 20 to 6. Employees’ marital status, stock option level, and occupational level are all key factors influencing their departure. Through the optimized human resource management optimization strategy, the enterprise can detect the employee’s status in time and bring better profits.
Research on Monitoring Teaching Activities Based on Image Recognition in Educational Management Informatization Construction of Colleges and Universities
Authors: Liu Zhen , Ran Jingtai
Published: October 2024

Teaching activity monitoring is an important part of the development of educational management informationization in colleges and universities. In this paper, we initially integrate the FDRL model with the self-attention mechanism to create the IMEDRL model, a tool for identifying the micro-expression categories of students during teaching activities. Then, the YOLOv5 model is added with the CA attention mechanism, and the loss function is replaced from CIOU to SIOU to get the IM-YOLOv5 model, which is used to detect the behavioral categories of students in teaching activities. Finally, a teaching activity monitoring system was designed based on these two models and used in actual teaching activity monitoring to explore the application effect of the models in the system. The IMEDRL model achieved an average recognition rate of 95.2% and 91.4% on the two public datasets, CK+ and Oulu-CASIA, respectively. The training and testing convergence on the teaching activity video dataset was superior, and the recognition accuracy rate reached 87.48%, demonstrating the model’s strong practical value. IM-YOLOv5 compared to YOLOv5, the FPS is basically the same, the number of parameters only increases by 8.72%, and the mAP0.5 and mAP0.5:0.95 improve by 0.99% and 1.65%, respectively. Among the 16 indicators of the 8 behaviors, 14 of the 8 behaviors of IM-YOLOv5 are higher than those of YOLOv5, confirming the feasibility of this study to improve YOLOv5. The monitoring system of teaching activities designed in this paper has a strong practicality, which is conducive to promoting informationization in education management in colleges and universities.
Research on the Application of Knowledge Mapping Technology in Vocational Skills Training Demand Forecasting and Curriculum Designing
Authors: Sun Liuyuan , Qi Xin
Published: October 2024

Due to the differences in individual qualifications, training duration, etc., the current vocational skills training is less efficient and cannot rationally arrange the training process and course content design etc. In this paper, we have constructed a model for predicting vocational skills training demand using knowledge mapping and knowledge tracking technology. First, a matrix is constructed to obtain the implicit relationship between knowledge. Reduce the influence weights with time intervals according to the theory of the forgetting curve. Modify the alignment scores of the attention mechanism to pay more attention to the relevant knowledge interactions in the sequence determined by the relationship coefficient g. Comparative analysis of the model and practical application reveals that the model in this paper has a better classification effect and better reflects the deeper recursive relationship and structure between knowledge points. When the professional teacher recommends the knowledge point C, the SVD model predicts the training demand of the trainees only 72.33%, while the model of this paper predicts 94.17% accuracy, which is highly compatible with the judgment of the professional teacher and more accurately identifies the training demand of the majority of trainees for the knowledge point C. The model provides a more scientific and reasonable curriculum and also provides a better classification of knowledge points. The model provides a more scientific and reasonable course design idea. Under the gradual course arrangement, the mastery of the knowledge points of the 20 trainees all shows a steady improvement trend. From the highest score of no more than 17 points in the first week to the 16th week at the end of the semester, all the trainees scored more than 70 points, which maximized the training efficiency. This study develops a reasonable course design based on the relationship between knowledge points, which can ensure gradual and interrelated progress and improve training efficiency and quality.
Understanding English Rhetorical Strategies Based on Neurosemantic Analysis
Authors: Tang Jianfu
Published: October 2024

This paper designs and implements a model for analyzing rhetorical strategies of English texts to address practical needs. This paper combines the true word confusion set and the N meta-model to correct word errors. In addition, a discourse parser is constructed based on the theory of rhetorical structure, which analyzes the semantics of the English text from the intra-sentence and inter-sentence perspectives to extract the key information of the discourse. The information is inputted into a memory network that resembles a tree, and the memory units and gating mechanism are employed to obtain semantic structural features. Finally, a hierarchical network model based on the attention mechanism is designed, using a bidirectional long short-term memory network to extract the global dependency information of the text and adding the attention mechanism to make it adaptively select important features related to English rhetorical strategies. Combining learning of a tree-based long short-term memory network and a hierarchical network based on an attention mechanism is used to generate a model for semantic analysis of English text. This paper’s model has the highest accuracy, recall, and F1 value among the mentioned models in the 20newsgroups dataset, with 93.77%, 91.23%, and 90.15%, respectively. The performance on the three rhetorical strategies of explicit metaphor, personification, and analogy is excellent, with classification accuracy above 90%, which will accomplish the task of analyzing and understanding English modification strategies.