bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of Metformin Transporter Coding Gene (SLC22A1 rs628031 and SLC47A1 rs2289669) in Healthy Indonesian Subject
Authors: Susilowati Endang 
Published: January 2024

Background: Metformin might be a first therapy for Type 2 diabetes; however, it had a lot of variation in glycemic response. Objective: to analyze the frequency of minor alleles of the OCT1 coding gene (SLC22A1 rs628031) and MATE1 coding gene (SLC47A1 rs2289669) as well as the genotypic variation of the interaction of these two genetic polymorphisms in healthy subjects of Indonesia. Material and Methods: Through inclusion criteria, the study employed an observational descriptive technique with 70 Indonesian Javanese healthy individuals. Subject health information was obtained from the complete blood routine test, serum glutamic oxaloacetic transaminase/ serum glutamic-pyruvic transaminase (SGOT/SGPT), complete urine test, and serum creatinine tests. All data were compared to the normal range. Results: The finding shows that the minor allele frequency on SLC22A1 rs628031 A>G and SLC47A1 rs2289669 G>A respectively at 53% and 36%. There are four SLC22A1 rs628031 and SLC47A1 rs2289669 genetic polymorphism interactions; 16 Wt/Wt (16.75%), 24 Wt/M (25%), 32 M/Wt (33.3%) and 24 M/M (25%). The discovery demonstrates that such minor allele frequencies of the SLC22A1 rs628031 OCT1 and SLC47A1 rs2289669 MATE1 genes in healthy Indonesian subjects are relatively high. The SLC22A1 rs628031 A>G and SLC47A1 rs2289669 G>A respectively at 53% and 36%, almost the same as the minor allele frequencies found in several other Asian countries eg. India, Japan, and China. Conclusions: OCT1 coding genes (SLC22A1 rs628031 A>G) were found more dominant than MATE1 coding genes (SLC47A1 rs2289669 G>A) and both alleles are relatively high in healthy subjects of Indonesia, which can be used as information to explore the consequences of different genes' interactions on the Indonesian pharmacokinetic properties, and the efficacy variations of metformin in Type2 DM patients.
Does Fiscal Monitoring Make Better Governments? Evidence from U.S. Municipalities
Authors: Nakhmurina Anya 
Published: January 2024

ABSTRACT
This paper examines the effect of state-level monitoring on municipal governance, focusing on outcomes in financial reporting quality, local corruption, political entrenchment, and municipal financial soundness. I exploit the staggered adoption of fiscal monitoring policies that entail a regular review of municipal financial reports for signs of fiscal distress. I find that introducing these monitoring policies is associated with an increase in the proxies for reporting quality, a decrease in the number of corruption convictions, and a reduction in re-election likelihood for incumbent politicians. Consistent with the purpose of the policies, my evidence shows that fiscal health ratios of municipalities improve after initiating state monitoring. Collectively, my results are consistent with state fiscal monitoring improving several important aspects of municipal governance.
Data Availability: Data are available from the public sources cited in the text.
JEL Classifications: G18; G38; H1; H11; H7; H83; M4.
HARMONI SOSIAL DALAM TRADISI BAKAR TONGKANG DI ROKAN HILIR
Authors: Ernita Mahdar , Rohani Rohani , Depi Fatimah 
Published: January 2024

Tujuan penelitian ini yaitu untuk mendeskripsikan sisi harmoni pada tradisi Bakar Tongkang yang ada di Kabupaten Rokan Hilir. Secara umum, hubungan sosial dalam tradisi Bakar Tongkang dapat ditemukan dalam banyak kegiatan, khususnya kegiatan yang berupa perkumpulan seperti proses iring-iringan. Dengan mengadakan kegiatan secara bersama-sama, itu akan memungkinkan Masyarakat Rokan Hilir menjalin interaksi dan komunikasi satu sama lain. Tidak hanya itu, dengan kegiatan itu pula, masyarakat akan mempunyai kesempatan untuk saling berbagi dan membantu, sehingga akan menghadirkan tatanan sosial kehidupan masyarakat Rokan Hilir yang lebih harmonis, damai, penuh kebersamaan dan persaudaraan
Применение волнового уравнения Шрёдингера к условиям чёрной дыры. Результаты исследования.
Authors: Чернов Андрей 
Published: January 2024

В основе этого исследования лежит волновое уравнение Шрёдингера для функции ψ. Два частных случая этого уравнения, классическая формула гравитационной энергии и формула Эйнштейна E= m_(pa ) c^2 были применены к экстремальным условиям чёрной дыры. В результате преобразования и решения этих уравнений была получена формула частицы массы чёрной дыры (эта частица в исследовании названа протоатомом). Полученная формула протоатома базируется на трёх независимых фундаментальных константах: величине элементарного заряда, величине гравитационной постоянной и скорости света в вакууме. Рассчитанная по этой формуле масса протоатома составила m_(pa )= 1,630740013 ∙〖10〗^(-27)кг. Это на 2,3 % меньше массы атома водорода и на 1,8% меньше атомной единицы массы 1 а.е.м. Это малое расхождение объясняется дефектом массы атомов водорода (и других химических элементов) в результате гравитационного сжатия гигантских звёзд и последующей их эволюции в чёрные дыры.
В исследовании было определено максимальное значение стационарной энергии для протоатомов, где E_(n=1)=-4,824514034 ∙〖10〗^(-15) эВ и минимально возможное расстояние между протоатомами в чёрных дырах, где r_(n=1)= 2,29620792 ∙〖10〗^(-31)м. Полученное значение энергии E_(n=1) уверенно согласуется с известными результатами астрофизических наблюдений гравитационных волн при слиянии чёрных дыр (см. 2 раздел).
Также в исследовании были получены другие результаты, которые имеют научное значение.
The severity of untreated caries in the deciduous and permanent teeth among children aged 6-12 years using PUFA and pufa index: a cross-sectional study
Authors: Suwargiani Anne Agustina , Aripin Dudi , Susilawati Sri , Suryanti Netty , Putri Fidya Meditia , Yolanda Yolanda , Maulidia Ardena Hamdani , Mohd Yusof Zamros Yuzadi 
Published: January 2024

ABSTRACT Introduction: The PUFA Index and pufa are used to measure the severity of dental and oral conditionwhich are not commonly used due to its novelty, and this index can be used to measure untreated dental caries7 and caries activity. The aims of study are to assess the severity of untreated caries in children’s deciduous and permanent teeth by using the PUFA and pufa index. Methods: An observational study using a cross-sectional study design was conducted among children who lived in Puteran village in Pager Ageung district, Tasikmalaya Regent, West Java, Indonesia. Purposive sampling was used, and the children who met the inclusion and exclusion criteria were invited to participate in the study. Severity of caries was assessed using the pufa and PUFA index for deciduous and permanent teeth, respectively. Severity of caries data were analysed using formulas for pufa and PUFA index. Results: A total of 206 children participated in the study. The PUFA assessment showed the severity of caries was high in the deciduous dentition with pufa index of 3.5 with SD 1,9-3,6 However, the PUFA assessment showed a relatively lower severity of caries in permanent teeth, with index PUFA of 0.5 with SD 1,9-3,6. The severity of caries was higher in the maxillary than the mandibular teeth in deciduous teeth. On the other hand, the severity of caries was higher in the mandibular than maxillary teeth in the permanent teeth. Conclusions: Each child aged 6 and 12 years in Puteran village had severe untreated caries in one permanent tooth and severe untreated caries in 3 to 4 of deciduous teeth. The findings of the study will be used to develop caries prevention and oral health promotion programs.KEYWORDS Caries, Severity, Deciduous, Permanent, teeth, PUFA, PUFA index, children
Research on the Change of Talent Cultivation Mode of Undergraduate Law Program of Open University in the Era of Artificial Intelligence
Authors: Liang Wenli , Li Sa , Huang Sui 
Published: January 2024

Abstract
In the era of artificial intelligence, this paper uses big data analysis to construct a data model of the knowledge system of law, with the help of clustering analysis, cluster students and resources to form a structured knowledge system of law. Combined with the natural language model, which accurately extracts important information, it provides personalized learning resources for students. Eventually, the teaching content is dynamically adjusted according to students’ characteristics, resulting in the integrated design of a personalized teaching mode. The comparison found that the achievement improvement of students using the traditional teaching mode only ranged from 1.8% to 12.6%, and the achievement improvement interval was from 1.9 to 12.6 points. After applying the AI model-based instructional model, the relative improvement in student performance ranged from 19.2% to 19.8%, with an improvement interval of 14.2 to 15.7 points. The students showed a significant teaching effect by demonstrating a 25-point increase in their communication skills performance compared to the control class.
The Application of Big Data Technology in University English Teaching Mode Innovation and Effect Analysis
Authors: Hao Xiaoxia 
Published: January 2024

Abstract
In the dynamic planning of reinforcement learning algorithms based on inverse recursion, this research shows how well Q-learning performs in finding the optimal decision function for accurate English teaching intervention in colleges and universities using data simulation. This simultaneously contrasts the two scenarios of calculating the best decision function independently and in a single stage using the Q-learning method. The correlation analysis between the innovative English teaching model and learners’ learning effectiveness was carried out by demonstrating the great clusters of the subset of English teaching data in colleges and universities. The results show that the correlation coefficients of English innovative teaching mode and learning outcomes are 0.385 and 0.276, respectively, in which H2-P1 and H2-P2 involve the structure of students’ personalized learning of English, whether it is an edge or a node, and the learning behaviors are not completely autonomous processes. This study proposes innovative strategies for improving the quality of university English teaching and laying a good educational foundation for students’ English learning.
Analysis of tennis technical movement training strategy in colleges and universities under the background of big data technology
Authors: Huang Hui , Liu Yanxin , Pan Shunlei 
Published: January 2024

Abstract
This paper first explains the tennis technical action representation and matching technology, using the Euler angle method to represent the coordinates of the tennis action gesture, realizing the deconstruction of the action gesture through the gesture-solving algorithm, and then using the weighted Euclidean distance to match the tennis gesture to the action. Secondly, we constructed the tennis technical movement training strategy for colleges and universities based on the task-driven teaching method, and gave the teaching experiment method to analyze the effectiveness of the strategy. Finally, the data was analyzed by examining the muscle characteristics of tennis technical movements and the teaching effect of task-driven teaching. The results showed that the maximal EMG integral value of the muscles was 32.91uV.s in the level 1 group and 87.91uV.s in the level 2 group, and the maximal angular velocity of the ankle-knee-hip joints was 645.23±189.42°/s and the minimum angular velocity of the hip joints was 461.87±115.08°/s in all the landing modes. 115.08°/s. The task-driven teaching method can effectively improve the students’ tennis learning and technical level and enhance the quality of tennis technical teaching in colleges and universities.
Exploring the diversified teaching mode of vocal singing in colleges and universities by integrating audio-visual and multi-sensory senses
Authors: Long Tao 
Published: January 2024

Abstract
In this paper, starting from the fusion of audio-visual multisensory vocal music feature representation, the RAE algorithm is used to represent the music lyrics text in vocal singing teaching. Due to the heterogeneity of the feature space of the audio modality and the lyrics modality, which makes it exceptionally tricky to directly mine the correlation between these two modalities, it is necessary to optimize the research through the fusion of the audio and the textual modality for the representation of the implicit space of the music. According to the SVM’s optimal classification, hyperplane is not limited by the data dimension. Combined with the kernel function parameters and emotional LFSM fusion, a visual multisensory vocal singing teaching emotion model based on SVM is constructed. The parameter environment and dataset are selected, and the comparison method and evaluation criteria are determined to analyze emotional research on vocal singing teaching in colleges and universities. The results show that in terms of model performance, the SVM model in this paper is 8.5% higher than model 6, reaching the highest 0.873, with stronger emotion extraction and recognition ability, greatly improving the emotion classification results of the model. The multimedia type of audio singing material is the least helpful for expression and physical performance in vocal singing teaching, with a total value of 67. This study provides a more comprehensive understanding of the emotional changes of students in teaching activities so as to identify problems, improve and optimize them, and give more students guidance and support in performing vocal singing.
Research on the Reform and Practice of Informatization Mode of Adult Higher and Continuing Education Academic Records Management in the Context of Three-Whole Parenting
Authors: Mei Shiwei 
Published: January 2024

Abstract
Information technology reform is an important way for schools to realize efficient management and information technology should be introduced into the management of student registration files to accelerate the process of informationization of registration file management. This paper builds an informatization database of adult higher continuing education student registration file management based on informatization technology and carries out the design of the main business process of student registration files. The multi-layer stacked LSTM network in the ELMo model is utilized to learn the preprocessing of the text of the school records data, and the CART decision tree algorithm is improved based on the reinforcement learning mechanism in order to improve the classification prediction accuracy of the decision tree in the dataset. In order to verify the feasibility of the school registration file informationization database constructed in this paper, a test analysis is conducted for the application of data mining technology and informationization database. The results show that the check accuracy of the CART decision tree algorithm improved by the reinforcement learning mechanism is around 80%, and the throughput of this paper’s database reaches 4827ops/s when the data writing volume is 1*105GB. When the number of threads reaches 128, the throughput of this paper’s informative database is around 5486ops/s, and when the data volume reaches 12*105 entries, the database in this paper the query response time is around 602ms. Under the background of three-round education, it is necessary to fully integrate information technology with the management of school registration files, which will lead to the innovation of the informationization mode of the management of school registration files in adult higher education.
Research on the Relationship between the Participation Degree and Experience of China’s Intangible cultural heritage Tourism Activation in the Information Age
Authors: Zhao Fengjun 
Published: January 2024

Abstract
With the development of the trend of cultural and tourism integration, intangible cultural heritage has become an important part of the development of experiential tourism. This paper combines information visualization technology to construct a framework for the design of non-heritage information visualization. By constructing a relevant spatio-temporal retrieval function to reduce the redundancy of non-heritage spatial data storage, combined with the base state correction model, the change process of non-heritage spatial features is retraced. GRU is applied as a unit of temporal feature correlation analysis to model the serial data of the degree of participation in non-heritage tourism revitalization. Two gating controls, the reset gate and the update gate, are used to regulate the flow of NRM information. The relationship between participation level in NRH tourism revitalization and experience was focused on in the information visualization design. The results show that the p-value of tourism experience and tourism revitalization is 0.521**, which is the most significant among all p-values, indicating that tourism experience has the closest relationship with tourism revitalization, and there is a significant positive correlation between both. Among the different groups of tourists, most of the experience scores of group C tourists are concentrated in the range of (80,90), while the advanced level of participation brings visual enjoyment to tourists while conveying the cultural spirit and emotional experience.
The Nature of Ideological and Political Education in Colleges and Universities Based on Deep Learning Models and Its Development
Authors: Wu Qiong 
Published: January 2024

Abstract
In this paper, first of all, after extracting the character sequence information, a certain scale of the corpus is obtained by using a crawler, and a corpus in the field of ideological and political education, as well as a participle system, is constructed. Then, the sequence decoding problem is solved by combining the idea of dynamic programming, based on the word level N-gram language algorithm, to design and implement an efficient solution method and calculate the final result of the participle. Finally, the keywords of related literature are classified, the essential dimensions of ideological and political education can be derived, and the essence of ideological and political education is explored and analyzed by using the word division algorithm. The results show that the most important essence of ideological and political education is “educating people’s feelings” with a weight value of 0.46, and among the 24 secondary nodes, there are 19 items with coefficients of variation less than or equal to 0.3, which shows that the degree of consistency is high, indicating that the degree of importance of the essence of ideological and political education is also high.
Exploring the Sustainable Development Path of College Volunteerism with Voluntarism in the Context of Deep Learning
Authors: Cao Yumei , Wang Yanbo 
Published: January 2024

Abstract
This paper first analyzes the pain points and needs of voluntary college student volunteering in conjunction with college volunteering program management. Combined with the logic of generating a sense of acquisition for college students’ volunteer service, it explores the types of motivation that drive their volunteer demand. Based on deep learning, we propose volunteer integrity neural network prediction, classify volunteer integrity, and select different data sources to compare the running time and effectiveness of four classification algorithms, namely artificial neural network, Bayesian network, decision tree and support vector machine. Volunteer portraits are established with two dimensions: natural attributes and interest attributes. Deep feature extraction is utilized to recommend college volunteer activities. Among the sources of volunteering accessibility, 72.2% of college students consider volunteering information sources to be highly important. It can be seen that college volunteer service can help strengthen the construction of volunteer service information channels.
Differential Analysis of Stylistic Features in Chinese-English Interpretation Based on Natural Language Processing
Authors: Sun Weina 
Published: January 2024

Abstract
In this paper, after researching the natural language processing model, we use the knowledge representation technology to construct a knowledge base and use the sequence comparison algorithm to compare the sequences of Chinese and English translations, analyze the similarities and differences between the two sequences, and analyze the entropy of information between English and Chinese translations through the probabilistic theory and mathematical statistics method. On this basis, we analyze the differences between Chinese and English translations in terms of lexical dimension, syntactic dimension and articulation dimension and explore the differences in lexical richness and thematic concentration between Chinese and English based on “entropy”. The results show that Chinese is significantly higher than English translations in terms of language output length, sentence complexity, subordinate structure and phrase structure (p<0.001), and Chinese is significantly higher than English translations in terms of articulation (p<0.05). This paper provides an important reference value for studying the differences in stylistic features in Chinese-English translation.
Research on the Digital Preservation of Intangible Cultural Heritage of Folk Dance Art Category
Authors: Wang Xiaoyi 
Published: January 2024

Abstract
In this paper, based on the rapid head generation technique of the model library, we obtain a frontal 2D face photo, mark 13 feature points selected from 7 parts, such as both eyes, nose, mouth, etc., to determine the approximate position of the whole facial features, simulate the real color of the face according to the texture mapping of the face, and at the same time, we add the texture features of the target face in the to the matching model, to achieve the mapping of overlaying texture to the neutral texture and the fusion of skin color. Using HigherHRNet network extraction to obtain the coordinate information of the joint points of the intangible cultural heritage dance inheritors and their heat maps, the obtained key frames of the dance features are connected in a certain order to obtain the synthesized folk dance video with gesture estimation. Combining semantic segmentation of keyframes and style rendering, the visual image of the dance is designed, and the intangible cultural heritage of folk dance is analyzed through examples. The results show that this paper’s method achieves more than 90% recognition accuracy on all three datasets and more than 94.8% recognition accuracy on the folk dance movement dataset. On the evaluation of folk dance movements, the average distance calculated by this paper’s algorithm is the largest, 95.7, and the average score is the lowest, 43.6. The average distance and average score of this paper’s algorithm are in between the above two cases, i.e., the experimental results verify the effectiveness of this paper’s method. This study promotes the intelligent protection and creative inheritance of Chinese non-heritage dances through digital protection.