bluuebunny/crossref_metadata_2025 huggingface dataset:
Alcohol Intake, Drinking Pattern, and Risk of Type 2 Diabetes in Three Prospective Cohorts of U.S. Women and Men
Authors: Li Xinyi , Hur Jinhee , Smith-Warner Stephanie A. , Song Mingyang , Liang Liming , Mukamal Kenneth J. , Rimm Eric B. , Giovannucci Edward L.
Published: February 2025

OBJECTIVE

Although the adverse effects of excessive alcohol consumption are well established, the association between light to moderate alcohol consumption (≤30 g ethanol per day) and risk of type 2 diabetes (T2D) remains controversial and holds substantial public health implications. We aimed to examine the association of total alcohol intake and drinking pattern with T2D among three cohorts, Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), and Health Professionals Follow-up Study (HPFS).

RESEARCH DESIGN AND METHODS

Former regular drinkers were excluded from baseline nondrinkers. Hazard ratios (HRs) and 95% CIs were estimated by Cox models.

RESULTS

Over 3 decades of follow-up, 20,551 T2D cases were documented among 200,969 participants. Total alcohol intake was associated with a lower risk of T2D, either using nondrinkers or 0.1–4.9 g/day as the reference. The association was robust to extended latency periods and alternative modeling of exposure. Drinking frequency was associated with a lower T2D risk. For example, compared with drinking 1–2 days per week, the HRs (95% CIs) for drinking 5–6 days were 0.73 (0.65, 0.83), 0.73 (0.62, 0.86), and 0.76 (0.67, 0.86) in the NHS, NHSII, and HPFS cohorts, respectively. When modeled jointly, the lower risk of T2D among drinkers was primarily driven by the drinking frequency. The inverse association began at drinking 1–2 days per week in women and 3–4 days per week in men and was strongest for ≥5 days per week, regardless of drinking <10 g or ≥30 g per drinking day.

CONCLUSIONS

Light to moderate alcohol consumption, especially regular light drinking, was associated with a lower risk of T2D in both men and women.
In vitro assessment of needle and irrigant penetration when using different irrigation needle tips
Authors: Hussain Saleha , Bjørndal Lars , Markvart Merete
Published: February 2025

Objective: The aim of this study was to compare the needle and irrigant penetration depth of a newly developed multi-vented polymer needle (30G), with three established needle designs – an open-ended metal needle (30G), a side-vented polymer needle (30G), and a notched metal needle (27G) used as a reference control. The effect of manual dynamic activation (MDA) was also measured. The null hypotheses were that the irrigant penetration would be the same regardless of needle tip, and the addition of MDA would make no difference in terms of irrigant penetration.
Materials and methods: A total of 120 mesial roots from mandibular molars were instrumented to a size 25/07, with reciprocating files. The maximum needle penetration depth was measured for each needle tip, using a rubber stop. Syringe irrigation was performed using a sodium diatrizoate solution, first with needle placement halfway down the root canal (working length subtracted from the canal length), and then 1 mm from the working length. MDA was performed. A digital radiograph was taken before the initial irrigation, after the initial irrigation, after the final irrigation, and after MDA. Digital subtraction was performed, and irrigant penetration was measured by a blinded operator. Non-parametric statistical tests were conducted using Mann–Whitney U-test and Wilcoxon signed-rank test.
Results: The multi-vented polymer needle had a significantly deeper needle penetration (mean value: 99%), compared to other test needles. The deepest irrigant penetration was achieved using the multi-vented polymer needle (mean value: 98%) and the open-ended metal needle (mean value: 99%). A significantly deeper irrigant penetration, was achieved by adding MDA, regardless of needle tip.
Conclusions: The multi-vented polymer needle and the open-ended metal needle showed superior performance in terms of irrigant penetration. However, the irrigant penetration only managed to reach the working length when MDA was added.
EUDAIMONIC WELL-BEING ACTIVITY: FULFILLMENT OF BASIC PSYCHOLOGICAL NEEDS AND SUBJECTIVE WELL-BEING IN ADOLESCENTS
Authors: Fikra Hidayatul , Abidin Fitri Ariyanti
Published: February 2025

The adolescent phase is a vulnerable period in human life because it is a transition period from childhood to adulthood. In this phase, good subjective well-being is needed so that adolescents can fulfill their developmental tasks. One of the efforts to fulfill subjective well-being is through adolescent eudaimonic activities that refer to three components of basic psychological needs, namely the need to be independent, the need to be competent and the need to connect with others. The purpose of this study is to analyze eudaimonic activities that meet the three components of basic psychological needs and subjective well-being. This study used a concurrent mixed method approach with four qualitative questions and the SPANE and BPNFS scales. The results showed there were 21 eudaimonic activities grouped into six activity categories, namely physical activities, entertainment, skills, spiritual, learning and favorite habits. This study recommends further research with explorative methods and a larger sample size. As an implication for adolescent life, parents or families can study eudaimonic activities in adolescents so that the approach and supervision given to adolescents becomes more appropriate.
EXPERIENCES AMONG DOCTORS WHO HAVE AUTISTIC CHILDREN IN OBTAINING DIAGNOSIS AND THERAPY: A PHENOMENOLOGICAL STUDY
Authors: Arneliza Arneliza , Adetya Sandra , Muti’ah Rahma , Sutadi Rudy , Rahayu Anizar
Published: February 2025

Penelitian ini bertujuan untuk mengeksplorasi pengalaman dokter yang memiliki anak dengan Gangguan Spektrum Autisme (ASD) dalam proses mendapatkan diagnosis dan terapi. Penelitian ini menggunakan metode kualitatif dengan pendekatan fenomenologis. Informan dalam penelitian ini adalah tiga orang dokter yang memiliki anak dengan ASD. Wawancara mendalam dilakukan untuk menyelidiki pengalaman, tantangan, dan strategi mereka dalam mendapatkan diagnosis dan terapi yang akurat bagi anak-anak mereka. Hasil penelitian menunjukkan bahwa meskipun memiliki pengetahuan medis yang memadai, pengalaman pribadi mereka sebagai orang tua dari anak-anak dengan ASD menghadirkan banyak kendala dan tantangan dalam mendapatkan diagnosis dan terapi. Penelitian ini mengidentifikasi tujuh tema: pengetahuan tentang autisme, kecurigaan autisme, mencari diagnosis dan terapi tanpa diagnosis formal, mekanisme koping dan ketahanan, terapi integrasi sensori (SI), terapi okupasi (OT), terapi wicara (TW), dan hasilnya, terapi Smart ABA dan Smart BIT dan hasilnya, serta sekolah reguler. Temuan ini memberikan wawasan baru dan penting tentang perlunya pemahaman yang lebih dalam tentang diagnosis dan terapi autisme di kalangan dokter. Diharapkan penelitian ini dapat memberi kontribusi pada ilmu pengetahuan di bidang autisme, khususnya bagi para profesional medis.
Synthetic fuels in the traffic of the future
Authors: Artz Jens , Ruff Philip
Published: February 2025

Ignition off, fuel cap out, nozzle in and off you go. This scenario happens millions of without thinking about whether the fuel is suitable for our car in the first place. Even when boarding an airplane or ship, we don’t waste a thought on the fuel. This is made possible by a complex structure of standards, directives, regulations, and laws, which ensures that all available fuels meet strict quality requirements.
Diseño y Simulación de UAS de Ala Fija Tipo Zagi para la Fuerza Aérea Colombiana
Authors: Ardila Marulanda George Mauricio , Prieto Bohórquez Juan Manuel , Macías Castillo Paula Rocío , Rincón Otálora Miguel Ángel , Rubiano Esmeral María Betzabe , Casallas Moreno Edwin Alexander , Sánchez Rojas Jorge Ernesto , Cantor Santana Daniel Felipe
Published: February 2025

Este estudio presenta el proceso de diseño de un Sistema Aéreo no Tripulado (UAS por sus siglas en inglés) de ala fija tipo Zagi para el Centro Investigación y Desarrollo Tecnológico de Innovación Aeronáutica (CETIA), un centro de investigación de la Fuerza Aérea Colombiana (FAC) que reconoció la necesidad de desarrollar su propio UAS adaptado a los requisitos específicos de la organización en una época en la que la demanda de estos dispositivos aumenta en el espacio aéreo colombiano. El estudio empieza con la definición de las especificaciones iniciales, la selección de los componentes electrónicos relacionados con estas especificaciones, el cálculo del consumo de corriente (A) a velocidad de crucero y capacidad de la batería, avanzando hacia el diseño del fuselaje para finalmente seleccionar el perfil aerodinámico del ala y cola para las condiciones de Bogotá, validando su selección mediante simulación CFD. La investigación tiene como objetivo abordar las necesidades operativas únicas de CETIA en el contexto del panorama en evolución de las UAS.
Computer-aided engineering: an innovative methodology for the design of agricultural tools for family farming
Authors: Montoya Fernández Juan Martin , García Monsalve Germán Leonardo , Arango Correa Mauricio , Parada Duque Santiago
Published: February 2025

In this study, a manual agricultural tool was optimized using computer-aided design (CAD), computer-aided manufacturing (CAM), and finite element analysis (FEA) technologies, which were carried out in different complementary design stages. The process began with an existing physical prototype, which, through reverse engineering processes, generated a detailed and scaled CAD model with functional design specifications. Subsequently, a low-cost additive manufacturing process (3D printing) was used to create a functional prototype from the previous CAD model. To estimate the mechanical performance and durability of the tool prototype, a Finite Element Analysis (FEA) was performed, simulating the loads it would be subjected to during use. The results obtained through the FEA simulation provided an optimal design for the tool and validated its performance. The tool prototype optimized by these FEA processes was again subjected to 3D printing to generate a functional model for the manufacturing of the agricultural tool through sand casting processes. The tools manufactured in the casting processes were used in conventional agricultural activities, closing the design cycle established in this study. It is concluded that the innovative approach, which combined the stages of computational design and additive manufacturing, offered multiple advantages due to the rapid and economical design iterations before constructing the first tool by casting. Additionally, it facilitated the optimization of the geometry, size, and weight of the tool prototype, considering ergonomic aspects and performance in the projected agricultural activities. Finally, the implemented methodology is viable for the creation of new agricultural tools, avoiding additional high-cost manufacturing processes, such as chip removal machining or mold manufacturing for forging or stamping processes, optimizing the design cost.
Laboratorio flexible para probar dispositivos eléctricos y emular microrredes
Authors: Saavedra Montes Andrés Julián , Hernández Lenis Christian , Ramos Paja Carlos Andrés
Published: February 2025

El análisis del comportamiento eléctrico de microrredes que incluyan fuentes renovables, dispositivos de almacenamiento, cargas no lineales y componentes tradicionales, es de suma importancia para investigar y formar nuevos profesionales en sistemas de energía. Este artículo presenta el diseño e implementación de un laboratorio flexible para probar dispositivos eléctricos modernos y emular microrredes reales. El diseño del laboratorio comienza con el diseño de varios dispositivos, seguido de la estructuración e implementación de un bus para conectar los dispositivos. La integración incluye interruptores, contactores, barras de cobre, conexión a tierra, PLC y conectores de seguridad. El laboratorio flexible se valida experimentalmente probando un convertidor monofásico, cargando y descargando tres baterías VRLA, replicando un perfil de descarga y emulando una microrred real instalada en Isla Fuerte, Colombia. Los resultados se utilizan para evaluar la operación de los dispositivos y para analizar el comportamiento de una microrred real, demostrando la utilidad del laboratorio en contextos de educación e investigación.
Hackers in duty of cyberterrorism
Authors: Bartko Robert , Kelemen Roland
Published: February 2025

The fight against terrorism has been at the heart of the international security policy for decades. The latest forms of terrorism are now being committed in cyberspace, making detection even more difficult. Alongside traditional forms of terrorism cyberterrorism have appeared as an element of the so-called ABC-Terrorism, exploiting the potential of cyberspace. The perpetrators of cyberspace operations, some of whom are hackers, are difficult to detect. Therefore, for an effective investigation it is very important to identify—in a scientific way—hackers and types of hackers who could become perpetrators of a terrorist attack. The opportunities afforded by globalisation and the revolution of the Internet make terrorists able to exploit the possibilities offered by the industrial and internet-based society. It shall be emphasized that the internet has become an integral part of our life, rendering us and the potential terrorist targets more vulnerable. Therefore, the paper aims to identify the concept of cyberterrorism on a scientific bases and to place it in the system of cybercrimes. Furthermore, identifying potential perpetrators by describing the different types of hackers is also an aim of the article. The result of the study may contribute to more effective prevention and response by the authorities. The paper concentrates only on criminal legal perspectives and avoid the political, military legal or ethical approaches.
Do fingerprints reveal the future of children or is it the intersection of dermatological science and health?
Authors: Torun Furkan , Yardımcı Figen
Published: February 2025

Dermatoglyphic patterns are lines formed by different patterns of epidermal structures located on the inner surface of the hands and feet. Epidermal patterns begin to form in the sixth week of pregnancy and once formed, they remain unchanged throughout life except for their size. Since finger patterns and our nervous system develop from the same ectoderm layer, scientists have begun to examine the relationship between fingerprint pattern anomalies and various diseases based on the idea that negativities in various systems, especially neurological disorders, may be reflected in fingerprint patterns. Studies have reported significant relationships between fingerprint anomalies and various diseases. As a result, it is expected that taking dermatoglyphic pattern samples will contribute significantly to the independent roles of pediatric nurses, supporting children’s physical, cognitive and social healthy growth and development, detecting diseases at an early stage and maximizing health with appropriate guidance, and providing genetic counseling to parents.
Warszawa i bunt. Studium postrzegania II Rzeczpospolitej w książce Zamach Stanu autorstwa Curzio Malapartego
Authors: Smoczyk Bartosz
Published: February 2025

The subject of the following work is to look at the way of perceiving the Second Polish Republic present in the work of the Italian author, publicist and diplomat: Curzio Malaparte. On the pages of his book Coup d'état, he described, among others: ‑ the Battle of Warsaw. With reference to this event and the narrative led by the Italian, in the article I focused on discussing the theoretical framework that is strongly related to the process of presenting the Second Polish Republic, in a way that marginalizes it and presents it as a peripheral country, on a bipolar west‑east axis, as well as with perspectives of the fascist understanding of the state. The text further presents the source and author, followed by an analysis of selected fragments of the book Coup d'etat, relating to how Curzio Malaparte wrote about the Second Polish Republic, including it among the countries of the cultural East, distinguished from the West, which is a model and point of reference.
Public Health Risks of Environmental Contaminants: Heavy Metals and Industrial Chemicals
Authors: Koller Loren D.
Published: February 2025

HEAVY METALS and industrial chemicals are environmental contaminants that affect man and other animals. Chemicals considered here include lead, cadmium, methylmercury, polychlorinated biphenyls (pcb), polybrominated biphenyls (pbb), asbestos, and vinyl chloride, most of which have produced comparable disease in man and other animals. However, this review will be devoted to the hazards that these compounds present to human health.
Sarcocystosis in Cattle in Kentucky
Authors: Giles Ralph C. , Tramontin Robert , Kadel Wade L. , Whitaker Kent , Miksch Duane , Bryant Donald W. , Fayer Ronald
Published: February 2025

Sarcocystosis was diagnosed in 41 eighteen-month-old heifers and steers. Clinical signs included anorexia, severe weight loss, nervousness, hypersalivation, lameness, and hair loss on the extremities. Hair loss was noticed especially at the end of the tail, where there was complete loss of the switch, giving the animals a “rat-tail” appearance. Consistent gross changes observed at necropsy of four affected animals included generalized lymphadenopathy, erosions and ulcerations in the oral cavity and esophagus, and severe laminitis. Microscopically, young cysts of Sarcocystis sp were disseminated in the heart, skeletal muscle, and brain. Ultrastructural examination indicated that the cysts were young because they contained metrocytes. Affected animals had moderate to severe nonsuppurative myocarditis and myositis, with focal degeneration of myofibers and infiltration by macrophages, lymphocytes, and plasma cells. Indirect hemagglutination of sera from 19 animals revealed a mean antibody titer of 1:24,000 against Sarcocystis bovicanis antigen. Epidemiologic investigation incriminated resident farm dogs that had been housed in a farm hayloft as the source of infection. Hay contaminated with sporocysts in dog feces was thought to have been fed to the heifers and steers.
Neoplasia of the larynx in the dog
Authors: Wheeldon Eric B. , Suter Peter F. , Jenkins Thomas
Published: February 2025

The clinical, radiographic, gross pathologic, and histologic findings in 4 dogs with primary laryngeal neoplasia and 1 dog with secondary laryngeal neoplasia were reviewed. The clinical and radiographic findings were compared with those for proliferative inflammatory laryngeal conditions, since such conditions pose a problem in differential diagnosis. The most common clinical sign was hoarse bark or loss of voice, with subsequent onset of exertional dyspnea and cough.
Intelligent Analytics for Educational Big Data and Its Application to Instructional Management
Authors: Zhang Nan
Published: February 2025

In today’s rapid development of information technology, the use of big data to carry out educational management work in colleges and universities has gradually become the main model for the development of educational management in colleges and universities. Based on data mining technology, this paper constructs a model for student academic early warning and designs an academic early warning system using an XGBoost model. The study analyzes the student achievement and behavior data from Lanzhou University of Technology, clusters the student-generated in-school behaviors using the DBSCAN method, and examines the relationship between borrowing behavior, consumption behavior, and student achievement. It was concluded that there exists a difference between students with good grades and those with failing grades. The performance of the XGB model proposed in this paper was tested with an accuracy of 96%. Subsequently, the distribution of students’ academic performance was studied from different majors and courses, and the Pearson coefficient was used to study the correlation between different semester GPAs and students’ grades. Moreover, finally, it was concluded that second-semester learning indexes have a greater impact on students’ academic performance through feature correlation.
The Role of Cloud Computing Platform in Civic Education Resource Sharing in Colleges and Universities
Authors: Yang Ting
Published: February 2025

In order to improve the efficiency of resource sharing, this paper introduces cloud computing technology and develops a sharing platform for Civics and Political Science teaching resources based on cloud computing technology. A specific implementation of the cloud computing-based educational resource sharing program is carried out, starting with the hardware and software environment, then moving on to network configuration, and finally verifying the operation results. By comparing the performance with other sharing platforms, the number of requests processed per unit of time and the average response time of the sharing platform designed in this paper is higher than the data of the traditional control platform. The average value of resource sharing agility is higher than the traditional sharing system by 0.128. The average value of the resource sharing degree of the design sharing system in this paper is higher than the traditional sharing system by 0.2, and the efficiency, breadth, as well as depth of resource sharing are significantly better than the traditional sharing system. A questionnaire survey was conducted to examine the perception and use of the cloud computing platform for sharing. 61.67% of the students were interested in the employment examination and research column, which indicates that the educational sharing resources of the platform are in line with the student’s situation and meet their demand.
Research on the Application of Machine Learning for Marxist Education Integrating Chinese Excellent Traditional Culture
Authors: Wang Handong
Published: February 2025

The rapid development of artificial intelligence has brought a profound impact on college education, and is triggering a profound change in educational concepts and educational methods. This project starts from the two dimensions of teaching assessment and resource recommendation of Marxist education, and centers on the application of machine learning technology in it. Based on the evaluation of Marxist education integrating Chinese traditional culture, an improved cuckoo search algorithm is used to optimize the number of hidden layer nodes of the extreme learning machine, and the ICS-ELM model is proposed. Combining similarity calculation and the k-means clustering algorithm, a recommendation model for Marxist education resources is constructed using data mining. Through experiments, it has been found that the ICS-ELM model performs better in terms of RMSE value and R value, and can better evaluate the effects of Marxist education. The response time of the Marxist education resource recommendation model is within 210ms, and the MAE and RMSE are within 0.677 and 0.823, respectively, which shows fast response speed and high accuracy of resource recommendation, which can improve the cognitive level of teachers and students and students’ learning interest. The application of machine learning technology provides a more intelligent, personalized, and efficient teaching mode for Marxist education.
Study on the Role of Blockchain Technology in Supply Chain Carbon Emission Transparency Enhancement and Financial Regulation
Authors: Zhou Xingyao , Wan Fujun , Wang Qiaohui , Song Wenting
Published: February 2025

Combined with related literature, this paper argues that the application of blockchain technology to supply chain carbon emissions and financial regulation can play a role in reducing the credit risk of corporate supply chain finance. To verify the inference, the initial model of supply chain financial credit risk assessment is constructed using factor analysis and logistic regression analysis. The study selects 105 sample enterprises that utilize blockchain technology in supply chain carbon emissions and financial regulation to construct a final model for supply chain financial credit risk assessment as

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. The risk-taking capacity of Enterprise Z, which utilizes blockchain technology for supply chain management, is calculated at 92.05% using this model, which is 32.05% higher than the standard value. The conclusion supports the inference of this paper.
The role of digital media technology in promoting the reform of traditional curricula in higher music education
Authors: Xiao Yuyang
Published: February 2025

In the era of rapid development of science and technology, the traditional music education mode can no longer meet the needs of the times. Therefore, the study introduces digital media technology such as virtual reality and augmented reality in the reform of traditional music course teaching and proposes a higher music education method based on digital media technology, with a view to promoting the current reform process of higher music education courses. Taking instrumental music performance and music aesthetics as examples, we study the teaching effect of the music teaching methods proposed in this paper. In this way, the advantages of digital media technology in the reform of the traditional curriculum of higher music are explored. Before the teaching experiment, the experimental group and the control group had the same level of instrumental performance and music aesthetics, with no obvious difference. After the teaching experiment, the experimental group made more significant progress in instrumental performance and music aesthetics, while the post-test instrumental performance and music aesthetics of the control group remained similar to the results of the pre-test, and the p-value of the post-test results of the two groups in instrumental performance and music aesthetics were all less than 0.05. This paper’s method of higher music education based on digital media enhances the sense of scene of the music curriculum through VR and AR technologies, which is beneficial to the students’ learning. The sense of scene is conducive to students’ better sense of presence and immersion in learning, mobilizing students’ learning enthusiasm, changing the mode of traditional music teaching in which students passively receive knowledge, which has an important role to play in promoting students’ music development, and also provides insights for reforming the traditional music education mechanism.
Research on Multimodal Image Tampering Detection and Counterfeit Image Recognition Techniques under Deep Learning Framework
Authors: Zhang Meijing , Ding Qiang , Yan Xiafei
Published: February 2025

The continuous development of deep forgery technology has led to the proliferation of image tampering and forgery, which contributes to the spread of false information. In order to achieve the detection and recognition of forged images, a forged image feature recognition method and an image tampering detection model are proposed. Among them, the forged image feature recognition method transforms the image into YCbCr colour space and performs DCT transform and LBP transform on the divided image blocks to achieve the description of edge texture and feature learning. The image tampering detection model with improved Faster R-CNN, on the other hand, uses deep learning techniques to learn the features of the original tampered image and introduces an attention mechanism to optimize the classical network. The forged image feature recognition method achieves a reduction in training time consumption (319.9s) while maintaining higher accuracy in feature recognition. The image tampering monitoring model achieves a localisation accuracy (F1) of 0.835 and 0.818 for the two datasets, respectively. Compared with the initial two-stream Faster R-CNN algorithm, the accuracy of splicing detection has improved by 2.7%, copy-movement detection by 2.7%, and tampering detection by removal has improved by 3%, and it has better robustness.
Study on the extension path of agricultural products live marketing mode of rural e-commerce platform based on network traffic analysis
Authors: Zhou Zhengxi , Luo Zhiming
Published: February 2025

In rural e-commerce live streaming scenarios, network traffic analysis has an important impact on the consumer viewing experience. This paper builds a theoretical model of how viewers’ viewing experiences affect their buying habits in agricultural e-commerce live streaming scenarios. It also looks at the role of network traffic analysis and the live streaming marketing model as moderators. Finally, it uses sample data from merchant accounts on rural e-commerce platforms to do real-world analyses. Consumers’ viewing experience significantly affects their purchasing behavior (regression coefficient = 1.832, p<0.05). Web traffic analysis mediates between consumer viewing experience and purchase behavior. The live streaming marketing model moderates the positive relationship between consumer viewing experience and web traffic analysis. Because of this, this paper suggests that live marketing of agricultural products on rural e-commerce platforms based on network traffic analysis can broaden the marketing model by making basic network facilities better, using the power of local universities, working together with farmers’ chambers of commerce and leading businesses, and creating unique brands.
Multi-scale spatio-temporal data modelling and brain-like intelligent optimisation strategies in power equipment operation and inspection
Authors: Zhang Guoliang , Zhang Peng , Zhou Fei , Kong Qingyu , Fan Xiaoyu , Chu Zongbo , Xia Weishang
Published: February 2025

Aiming at the problem that the fault samples of UHV converter equipment are few and cannot effectively support the intelligent operation and inspection of the equipment, this paper proposes a brain-like learning sample spatio-temporal correlation generation technique for the operation and inspection of UHV converter equipment. In this technique, GPNN fuses the temporal evolution law and similarity of nearby samples to intercept typical fault samples and then combines the SNNs model of brain-like computing to construct an intelligent diagnosis model for UHV converter equipment. The improved K-SVD dictionary learning algorithm is used to extract the time-domain features of the UHV converter faults, combined with the empirical wavelet singular entropy to obtain the frequency-domain features, and the KPCA algorithm is used to fuse the multiscale time-frequency features to obtain the multiscale spatial and temporal features of the faults of UHV converter equipment. The GPNN model for generating multi-scale spatio-temporal sequence fault samples is constructed by combining GAN with the nearest neighbor interpolation algorithm. The fault samples generated by the GPNN model are used as inputs and combined with the SNNs model for intelligent diagnosis of UHV converter equipment faults. The consistency between the fault samples generated by the GPNN model and the actual samples reaches more than 90.57%, the accuracy of the brain-like intelligent fault recognition model reaches up to 98.06%, and its training time is only 37.14 seconds. Learning the multi-scale features of the samples through the GPNN model, combined with brain-like computing technology, can support the training of brain-like models for health assessment, fault diagnosis, and trend prediction of UHV converter equipment.
Exploring the dynamic relationship between oil painting art and modern social values by combining data mining techniques
Authors: Zeng Maoquan
Published: February 2025

Oil painting is a kind of mass medium with unique charm and influence, which has a wide dissemination effect. If social values can be spread through oil painting, they can have a wider and more effective effect. In this paper, the Fisher score algorithm is used to assess the degree of correlation between the color features of oil paintings and the classes they belong to. The grey scale co-production matrix is used to extract texture features of oil paintings. The regularized limit learning machine model is introduced to improve the accuracy of algorithmic feature extraction. The oil painting artworks’ feature vectors are calculated, the RELM model is employed to recognize them, and the plain Bayesian classifier confirms the accuracy of the recognition results. A simulation analysis of the oil paintings is carried out. The highest pixel value is 1880 when the luminance of the red histogram is between 10-15 in the oil painting of “Sleeping Venus”, and the lowest pixel value is 184 in this interval in the “Unknown Woman”. The four grey gradient covariance matrices eigenmeans of the oil paintings are calculated, and the eigenquantities ASM, CON, CORRLN, and IDM are rotated by 90°. The eigenmeans are 0.047, 28.766, 0.125, 0.18. Based on the results of the experimental analysis, the correlation between the characteristics of oil painting art and the values of modern society is discussed.
Reform of Traditional Music Teaching Methods and Cultivation of Students’ Musical Creativity on Digital Platforms
Authors: Zhang Qingru , Wang Yan , Du Yuelin , Li Wei , Li Hua
Published: February 2025

Due to the rapid development of modern science and technology, the teaching methods and modes in traditional music have become increasingly obsolete and outdated, and digital teaching resources are the key to the reform of traditional music teaching methods. In this study, after extracting musical features such as range and average energy of music sounds during the teaching process, it is used as input data for the recurrent neural network model. The model is then optimized using a long-term memory artificial neural network and a self-attention mechanism, and the proposed combinatorial neural network CLSA model is used to visualize the music sounds. Subsequently, a digital music teaching platform is constructed based on the theory of multiple intelligences and the proposed model to assist in the reform and innovation of traditional music teaching methods. After research, the CLSA model proposed in this paper shows good performance in separating vocals and accompaniment, which has reached the performance of the current mainstream model. It is also found that after one semester of experimental teaching, the musical creativity of the students in the experimental class is significantly improved compared with the level before the semester (P<0.05), which indicates that the music teaching based on the digital platform has a good effect. This study provides a reference for relevant music teachers so that the level and teaching effect of digital music teaching can be improved and the deep integration of digital teaching resources and music teaching can be realised.
A Study on Sentiment Visual Analysis of Educational Public Opinion Based on Online Big Data
Authors: Wei Xiong
Published: February 2025

With the rapid development of the Internet, the Internet has become a new platform for gathering public opinion. Therefore, studying the sentiment of public opinion regarding education on the Internet is of great value in understanding the current situation of education. In this study, a web crawler is used to collect data related to education public opinion online, and an attention mechanism is used to extract data related to the sentiment of education public opinion. Subsequently, the convolutional neural network is used to extract sentiment features, and the sentiment features are classified and processed by the softmax classifier. Finally, the sentiment visualisation system for educational public opinion is designed by combining the sentiment analysis method. It is verified that the accuracy and F1 value of the sentiment analysis model proposed in this paper are the highest compared to the comparative models. The period of 2021-2022 is the high incidence period of online education public opinion events, and there are two obvious peaks of sentiment intensity in the typical cases of education public opinion A and B, which are the early stage of the outbreak of the online public opinion and the period of the official investigation and update, respectively. In this paper, we use visualization to show changes in people’s emotions related to education public opinion, hoping that it can provide a reference for managing education public opinion by relevant departments.
Research on data visualisation strategies for online information dissemination based on user experience
Authors: Wei Xiong
Published: February 2025

Information data visualisation is a new technology and trend emerging from the development of online information dissemination. This paper integrates the cross-field knowledge of journalism and communication, cognitive psychology and computer science, conducts two information visualisation experiments of colour symbols and cognitive load under the guidance of dual coding theory, and finds that contrasting colour schemes and symbol markers with meaningful associations help the audience’s cognition and memory of infographics. The errors caused by pie charts were much more significant than those caused by line and bar charts, and the errors caused by bar charts were much smaller than those caused by line charts. The cognitive load that pie charts cause is significantly higher than that of line and bar charts. Based on the visual representation of information visualisation, the principle of dual coding theory information processing and the results of two experiments, this paper proposes three principles of data visualisation strategy for information dissemination. This study provides theoretical support for the information visualisation design of data visualisation products, and the research conclusions and design methods can be applied to related information visualisation interfaces, which have good theoretical research value and practical significance.
Predicting HR Management Strategies and Employee Satisfaction in Enterprises Based on Deep Generative Models
Authors: Kang Ping
Published: February 2025

With the arrival of the digital era, the digital environment has brought new operation modes and work styles for enterprises, and at the same time, it also requires enterprises to make innovations and reforms in human resource management. The use of a deep generative model is used to generate facial expression recognition technology after optimizing the human resource management strategy in this paper. This technology extracts the facial expression features of employees and analyzes their emotional predictions in various simulated scenarios, all within the context of the optimized enterprise human resource management strategy. This, in turn, reflects the employees’ satisfaction with their work. Firstly, in order to verify the accuracy of the recognition technology proposed in this paper, recognition experiments are carried out on the Cohn-Kanade expression library, and from the analysis results, it is known that the recognition technology of this paper achieves a recognition rate of 98.25% in the Cohn-Kanade expression library, which is a high recognition rate. Finally, the selected 618 subjects were divided into 4 groups for the context simulation experiment to analyze mood prediction. The findings show that subjects’ positive mood is higher in different contexts, which suggests that employees are more content with their jobs in an optimized enterprise management environment.
Design of Learning Progress Tracking and Feedback Mechanism Based on Data Visualisation Technology in Music Teaching
Authors: Lin Peihan
Published: February 2025

In this paper, we first constructed a knowledge tracking model and embedded a self-attention mechanism to optimise the model and overcome the problem of data sparsity. Subsequently, the structures of the input layer, embedding layer, and hidden layer are sequentially designed to build the knowledge tracking model. Using neurons, the learning matrix was passed into a linear transformation, and a linear model was employed to obtain the predicted values. Individual student feedback on learning progress is calculated using the EVA evaluation model, and the timeliness feedback for all teaching subjects is compiled into an ensemble that constitutes the overall immediate feedback. Stage feedback is established in the same way to constitute a feedback mechanism for music teaching, and a strategy for supporting feedback teaching decisions is proposed. The experimental samples are selected, the teaching practice environment is established, and the results of visual tracking of learning progress are analyzed. The mean values of the total music learning strategy scores of the experimental class and the control class were 26.4136 and 19.229, respectively. Further analyses showed that there was a significant difference between the experimental class and the control class under the 95% confidence intervals of the music learning dimensions, assuming that the ANOVA values were all 0.05. The number of irrelevant learning behaviours of the students in the experimental and control classes was 95 and 137, respectively, and overall it seems that feedback on students’ learning progress can reduce the number of invalid behaviours.
Research on Intelligent BS Forms Drag-and-Drop Layout Generation Technology
Authors: Liu Yujiao
Published: February 2025

The digital information era is experiencing a daily increase in data, making the optimization of forms for data recording and processing an urgent problem. This paper addresses this need by designing intelligent dynamic forms using B/S architecture and adding drag-and-drop designs to optimize the form layout. Dynamic forms are created using virtual tables and displayed on the browser. The reported data in the server is used to calculate the variance to find out the method to make the increase in the data volume of each data table close to the average value and complete the optimized storage of the reported data. Drag-and-drop layout of the form is achieved by clicking and dragging the form components to the form design area using the APIs such as mousedown, mousemove, and mouseup. Dynamic form layout evaluation metrics are established through subjects’ eye movement data and questionnaire results. The drag-and-drop layout designed in this paper can significantly reduce the total gaze time, the number of gaze points, and the number of eye jumps of the subjects, in which the total gaze time is reduced by 29.06% and 26.70% compared with the waterfall and distributed layouts. The operation satisfaction score for the drag-and-drop layout is 80.26, which is a significant improvement from the other two layout methods. The drag-and-drop layout in this paper effectively reduces the cognitive load of users, which is obviously helpful for them to process the relevant data.
Construction of tourism investment risk management model combining big data
Authors: He Xifang
Published: February 2025

In recent years, the development of tourism has been in full swing, attracting a large number of investment institutions. This paper manages the risk of tourism investment using the VaR model based on big data. Taking Literature and Tourism Fund A as the research object, the VaR model is used to measure the risk of its investment portfolio, analyse the risk of Literature and Tourism Fund A’s investment portfolio, and make corresponding adjustments accordingly to construct a simulation fund. Then, the simulated fund is compared with the pre-adjusted Venture Capital Fund A in terms of return and risk to judge whether the portfolio adjusted according to the VaR measure has better results. Of the eight stocks in the Venturing Fund A, Stock 1, Stock 3, and Stock 6 have the highest risk contributions of 22.58%, 15.26%, and 13.78% respectively, for a combined risk contribution of 51.62%. Stock 1 was the main source of risk. The fund’s return rally is anchored by Equity 2 and Equity 5, whose investment weightings are significantly higher than their risk contributions. With a long-term return of 25.64 per cent and an average VaR of 1.049 per cent, the simulated fund portfolio had a higher return than the pre-adjusted Venture Capital Fund A and the benchmark index while being much less risky than the Venture Capital Fund A and the benchmark index.
The Construction of Blended Teaching Model of College English in Applied Colleges and Universities Based on Neural Networks
Authors: Jia Manli
Published: February 2025

This paper provides strong support for the construction of online and offline blended English teaching modes. Firstly, it applies the parallel K-means clustering algorithm of the adaptive cuckoo search to cluster and analyze the data related to blended English teaching. This process results in a series of processed teaching data, which is then used to design a blended English teaching evaluation index system for college students. The teaching data obtained is used to design the system. Aiming at the shortcoming that there is no theoretical basis for the selection of many parameters in the training process of the BP neural network, a teaching quality evaluation model based on the GA-BP neural network is constructed. Then, the blended teaching model is constructed based on this evaluation model. Through empirical experiments, it was found that the overall mean English achievement of the experimental group increased by 19.2% after the implementation of the hybrid teaching model, which was 6.7% higher than that of the benchmark group. The results demonstrate that the blended teaching model, which is based on the GA-BP blended teaching quality evaluation model, enhances college students’ English performance and is suitable for widespread application in college English teaching.
Automatic Obstacle Avoidance Path Planning Optimisation for Intelligent Vehicles Based on Optimal Control Theory
Authors: Jiang Nenghui , Li Cheng
Published: February 2025

Self-driving intelligent vehicles are an important part of the future intelligent transport system, and the study of path planning and automatic obstacle avoidance is also a key technology for the realization of self-driving vehicles. In this paper, we first constructed a dynamics model of an intelligent car, and then, using the optimal control theory, we designed the performance index function of automated obstacle avoidance path planning. This function took into account factors such as driving efficiency, energy consumption, and ride comfort. Consequently, we constructed an optimization algorithm model for automated obstacle avoidance path planning for intelligent cars and experimentally verified its effectiveness. The obstacle avoidance experiments conducted on straight and curved roads demonstrate that the path planning performance index function, which is based on optimal control theory and the optimal path planning method in this paper, can meet the obstacle avoidance requirements of local path planning while ensuring ride comfort. In the static obstacle experiment, the vehicle speed is 63 km/h and 84 km/h in two cases. This paper proposes a path planning function for obstacle avoidance that uses a smaller swing angle and maximum distance away from the obstacle than the traditional approach. The performance of the obstacle avoidance function based on optimal control theory in this paper is 47% higher than that of the traditional obstacle avoidance function. This verifies the effectiveness of optimal control theory in automatic obstacle avoidance path planning optimization for intelligent vehicles.