bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of computer-assisted teaching mode in universities based on Dijkstra’s algorithm
Authors: Yin Li 
Published: September 2023

Abstract
In the context of digitalizing big data and information, optimizing the teaching model of colleges and universities is a key concern in the education sector. This paper optimizes the shortest path planning of the Dijkstra algorithm around the Floyd algorithm and ant colony algorithm, constructs the model of a computer-aided teaching system in colleges and universities through the Dijkstra algorithm, and constructs the system model indexes from three aspects: students’ cognitive ability, students’ learning performance, and students’ learning interest. A sample of 100 college students was randomly selected, and the accuracy performance of the samples was compared by the Dijkstra algorithm and improved Dijkstra, respectively. The accuracy rate of the improved Dijkstra algorithm fluctuated from 83% to 90%, with a variable rate of 7%, which was relatively small. Then the Dijkstra algorithm was used to analyze the weighting of the cognitive ability index, learning achievement index, and learning interest index. In the cognitive ability index, the memory ability weight of 34% performed better compared with the other five, the good weight in the learning achievement index performed better compared with the other categories, and the more interesting weight in the learning interest index performed better overall compared with the other five categories. This study has guiding reference value for optimizing computer-assisted teaching mode in colleges and universities to improve teaching quality and efficiency of colleges and universities.
A study on the effect of different machine learning algorithms on soccer footwork recognition under trajectory tracking theory
Authors: Li Chengjun , Yang Hao , Wang Jingyan 
Published: September 2023

Abstract
This paper aims to investigate the effectiveness and influencing factors of different machine learning algorithms on soccer footwork recognition. In this paper, we use inertial sensors to obtain the basic data of soccer players’ movements, then convert them into initial data of footwork using pose representation and pose-solving filtering. The value of K mainly influences the classification accuracy of KNN, and the highest accuracy of 67.23% is achieved when K is 5. The classification accuracy of SVM is related to the choice of the distance function. The accuracy of CNN is mainly affected by the size of the convolutional kernel and the convolutional step size, and the highest accuracy is 73.82%. The machine learning-based soccer step recognition can improve the recognition accuracy of traditional physical methods and provide scientific sports guidance for soccer players’ training.
Quantitative Evaluation of Piano Performance Technique and Style Based on Continuous Discretization Method
Authors: Mao Dandan , Liu Sha 
Published: September 2023

Abstract
The piano education industry occupies a huge market. However, the automatic piano performance evaluation function has shortcomings in the existing piano education. In this paper, we first design a piano performance evaluation model based on the continuous discretization method for piano performance audio and improve the piano performance feature filtering and feature extraction methods through cubic spline interpolation and support vector regression, respectively. Secondly, a piano performance evaluation system based on music theory knowledge is studied to evaluate the user’s performance ability based on the rating of rhythm, main melody, and musicality performance of different levels of score performance audio and to achieve the purpose of assisting piano teaching. The results show that the difference between the scoring based on the continuous, discrete model and the actual level value of the player is less than 0.05, and the output of the evaluation system can achieve consistency; in the comparison experiments, the accuracy of three traditional evaluation models, BP, RNN, and LSTM, is 45%, 42%, and 75%, respectively, while the accuracy of the continuous, discrete model is 78%, with an average performance improvement of 23%. The continuous, discrete piano performance evaluation model proposed in this paper is more effective and objective in evaluating users’ piano performance ability and provides a guiding reference for performance evaluation in the piano education industry.
An analysis of the translation process of contemporary Chinese literature based on the Kalman filter algorithm
Authors: Xie Qing 
Published: September 2023

Abstract
Exploring the evolution of translation of contemporary Chinese literature better presents Chinese literary charm to foreign readers. This paper starts with the Kalman filter algorithm and introduces its cost function that satisfies the error minimization and the Kalman filter gain. Then the BP neural network is illustrated, its minimization of mean square error is solved using the backpropagation algorithm, and the momentum factor is introduced to update the weight function of the BP neural network. The correlation between the Kalman gain and the filtering error is fitted using BP neural network to optimize the Kalman filtering algorithm, and the algorithm flow chart of the BP-KF algorithm is given. Finally, the BP-KF algorithm is used to analyze the data on the evolution of translation strategies and translation dissemination channels of contemporary Chinese literature on the Internet. From the evolution of the translation strategy, the number of translated works of additive French literature decreased by 5.28% year-on-year from 2016 to 2020, and the number of translated works of annotated French literature increased by nearly 11 times year-on-year from 2016 to 2020. In terms of the evolution of the translation and dissemination channels, the percentage of using the Internet to disseminate literary translation and mediation works reviews increased from 16.29% in 2017 to 41.65% in 2021, an increase of 25.36 percentage points. Based on the BP-KF algorithm, the evolution of translation of contemporary Chinese literature can be effectively analyzed, and the data can visually show the direction of the evolution of literary translation, thus expanding the influence of contemporary Chinese literature.
Exploring the optimization path of teaching in college piano course based on deep learning
Authors: Li Shanshan 
Published: September 2023

Abstract
Piano teaching should not continue to be limited to the mere cultivation of students’ performance skills but should be integrated into curriculum thinking and politics while following the characteristics of the profession. This paper conducts piano teaching experiments through deep learning LSTM algorithm and extracts a series of Civic and Political elements from them as a fitting point of piano teaching and curriculum Civic and Political to discuss, using multiple teaching modes to strengthen the cultural transmission of piano courses to improve students’ ideological and moral level and comprehensive quality. The experimental results show that the accuracy of the deep learning LSTM algorithm based on the integration of the deep learning piano course curriculum Civics is stable up to 98.17%, the average false detection rate is stable at 1.97%, the average positive recall rate is stable at 94.7%, and the negative recall rate is 73.2%, and the LSTM algorithm improves the integration degree by 31% compared with the traditional SVMSGD and RF algorithms. It shows that carrying out experiments of deep learning based on deep learning for teaching Civics in college piano courses effectively strengthens the cultural transmission of piano courses and improves students’ ideological and moral level and comprehensive quality.
Research on rural employment and entrepreneurship of undergraduates in the context of a rural revitalization strategy
Authors: Chang Liang , Chen Fang , Li Xuchao , He Hai 
Published: September 2023

Abstract
Exploring rural employment and entrepreneurship of undergraduate graduates in the context of rural revitalization strategy is conducive to providing human resources for rural revitalization. This paper starts from the Gaussian mixture model, introduces the specific principle of the Gaussian mixture model, then introduces the EM algorithm under the data mining algorithm, and points out that the EM algorithm is often used as an iterative optimization method for great likelihood estimation, and explains the principle and process steps of the algorithm in detail. The EM algorithm is used to solve the logarithmic great likelihood estimate of the Q function with conditional probability density function, and then the EM algorithm is applied to the Gaussian mixture model to update the values of its parameters, and the performance of the EM-GMM algorithm is also evaluated. Finally, the EM-GMM algorithm analyzes the impact of employment unit preference and employment promotion policies on the undergraduate graduates of four universities in a certain area. From the performance evaluation, the algorithm’s accuracy in this paper is 94.54%, which is 21.29 and 5.02 percentage points higher than that of the K-means-EM algorithm and FCM-EM algorithm, respectively. Regarding employment unit preference, 45.82% and 22.09% of undergraduate graduates are more inclined to be employed in township government agencies, state-owned enterprises, and institutions. Promoting rural employment and entrepreneurship of undergraduate graduates requires strengthening employment guidance and employment concept correction to provide fresh blood for rural revitalization.
Analysis of the framework for realizing core literacy in teaching physical education and health curriculum based on the ordinary differential error approximation method
Authors: Zhu Liang , Gu Rong 
Published: September 2023

Abstract
The key to implementing the fundamental task of establishing moral education is how the abstract and broad physical education and health curriculum core literacy is translated into concrete and visible physical education and health subject curriculum and teaching practice. This paper firstly explains the framework for the realization of core literacy in PE and health curriculum in teaching and learning, specifically from three perspectives: context, health behavior, and physical virtue. Secondly, the abstract core literacy of physical education and health curriculum is transformed into a side problem of ordinary differential equation with unknown parameter initial values by using the method of ordinary differential error approximation, which can obtain the parametric expressions of the approximation of function values at the nodes and realize the concretization. The experimental results show that there is a significant difference between the core literacy of physical education and health curriculum based on the ordinary differential error approximation method before and after the application of the core literacy in teaching, in which the comprehensive improvement of motor ability is 23.7%, the comprehensive improvement of health behavior is 19.2%, and the comprehensive improvement of physical morality is 26.6%. This paper successfully visualized the core literacy issues of physical education and health curriculum based on the ordinary differential error approximation method, which provided a reference for physical education teaching, improved the professional competence and quality of school physical education teachers, and formed the characteristics of school physical education and health curriculum.
The contemporary value and effective application of red education in college Civic and Political Education
Authors: Li Xiushan , Xu Wei , Jiang Lijie , Zhou Rong 
Published: September 2023

Abstract
Exploring the value and application of red education in college civic education is to inherit the red spirit better. Based on big data analysis technology, this paper constructs a wisdom Civic Education platform to analyze the value and application of red education integration in college Civic Education. Firstly, the density peak clustering algorithm is used to classify and analyze the data of college Civic Education, then the improved fruit fly optimization algorithm is used to filter and analyze the data of the density peak clustering algorithm, and finally, the TCFOA-DPC algorithm is used to mine and analyze the application of red education in college Civic Education. To verify the practicality of the wisdom Civic Education platform constructed in this paper, simulation experiments are conducted to analyze it. From the performance evaluation, the detection rate of red education resources by the platform of this paper can reach 98.27%, the false alarm rate is 2.43%, and the leakage rate is only 0.95%. In terms of application value, the platform of this paper taps into the incentive, attractiveness, inquiry, and identity in red education with percentages of 75.84%, 79.08%, 85.40%, and 81.96%, respectively. Thus, the intelligent Civic Education platform based on big data analysis technology can effectively analyze the application of red education in university Civic Education, which is conducive to increasing the transmission and development of the red spirit.
The mechanism of innovation-driven emerging technology generation based on big data fusion in the perspective of technological self-reliance and self-improvement
Authors: Ji Xionnong , Qin Jingran , Wu Juyi , Zhang Yachao 
Published: September 2023

Abstract
Emerging technologies create opportunities for later adopters to achieve technological and economic leapfrogging and are highly valued by governments and enterprises. In this paper, we first screen the key factors influencing innovation drive through data region feature extraction to achieve a synergistic innovation effect between collaborative innovation and R&D subjects. Secondly, the multidimensional data are fused, and the feature extraction is performed using Transformer’s encoder (Encoder) structure, and the bidirectional coding of the input sequence text is realized using the supporting MLM training method. Finally, by comparing the analysis with other multimodal fusion methods in the constructed real dataset, the high performance of this method on emerging technology innovation-driven problems is demonstrated. The experimental results show that the absolute path coefficient of the innovation environment on collaborative innovation capability is 0.728 and the standardized coefficient is 0.835, which indicates that the innovation environment has a significant positive correlation with the innovation capability of emerging technology R&D subjects. The innovation-driven performance of science and technology emerging technology generation mechanism based on big data fusion technology is improved by 34.2%. The innovation-driving model based on big data fusion technology proposed in this paper plays a positive role in promoting the agglomeration of emerging industries and effectively improves the innovation ability and the conversion rate of R&D results of emerging enterprises, which is of great strategic significance for future economic development.
Total and individual PBC-40 scores are reliable for the assessment of health-related quality of life in Greek patients with primary biliary cholangitis
Authors: I. Rigopoulou Eirini , Bakarozi Marianna , Dimas Ioannis , Galanis Konstantinos , Lygoura Vasiliki , K. Gatselis Nikolaos , Koulentaki Mairi , N. Dalekos George 
Published: September 2023

Abstract

Background
Primary biliary cholangitis (PBC) has been long associated with impairment of various aspects of health-related quality of life (HRQoL) with substantial differences among populations. This study evaluated for the first-time the HRQoL in Greek PBC patients in conjunction with clinical and laboratory parameters of patients.

Methods
We analyzed prospectively collected data regarding the HRQoL by using the PBC-40 and SF-36 questionnaires in 374 Greek PBC patients and 131 age- and sex-matched non-PBC controls.

Results
The PBC-40 questionnaire is a reliable tool for HRQoL assessment in Greek PBC patients (Cronbach's α > 0.7 for all domains). Implementation of PBC-40 and SF-36 demonstrated significant impairment of HRQoL in Greek PBC patients compared to controls (P < 0.001 for all comparisons). Emotional dysfunction, social impairment, and fatigue (100%, 80.5% and 78%, respectively) were amongst those with the highest, while cognitive dysfunction (32%) with the least impact on quality of life. Fatigue was associated with female sex (P = 0.02), longer disease duration (P = 0.01), presence of cirrhosis (P = 0.02) and positivity for PBC-specific ANA (P < 0.05), while social dysfunction with increased age (P < 0.001), longer disease duration (P < 0.001) and presence of cirrhosis (P = 0.004). Living in urban areas was linked to impaired social function (P = 0.04), cognition (P = 0.02), fatigue (P = 0.04) and increased total PBC-40 score (P = 0.01).

Conclusions
Implementation of PBC-40 and SF-36 revealed impaired HRQoL in Greek PBC patients with fatigue, social and emotional dysfunction exerting the highest impact. However, total, and individual PBC-40 scores were lower than that reported in studies from Northern/Central Europe and Canada. Deranged HRQoL was associated with severity of liver disease and presence of PBC-specific ANA.
FOSL2 participates in renal fibrosis via SGK1-mediated epithelial-mesenchymal transition of proximal tubular epithelial cells
Authors: Liu Naiquan , Li Dongyang , Liu Dajun , Liu Ying , Lei Jing 
Published: September 2023

Abstract

Background
Fos-related antigen 2 (FOSL2) plays a facilitative role in fibrotic disease; however, its role in renal fibrosis remains unclear. This study aimed to clarify the role and underlying mechanisms of FOSL2 in renal fibrosis.

Methods
Upregulated genes in unilateral ureteral obstruction (UUO)-injured kidneys were screened in Gene Expression Omnibus (GEO) databases, and overlapping genes were identified using Venn diagram software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for these genes. The UUO-induced mouse model and transforming growth factor-β1 (TGF-β1)-induced cell model were used for the in vivo and in vitro studies.

Results
A total of 43 commonly upregulated genes were identified. GO and KEGG pathway analyses indicated that FOSL2 may be involved in fibrosis. Furthermore, FOSL2 was confirmed to be upregulated in UUO-injured kidneys and TGF-β1–induced cells. Knockdown of FOSL2 ameliorated interstitial fibrosis, extracellular matrix deposition, and epithelial-mesenchymal transition via the downregulation of fibronectin, α-smooth muscle actin (α-SMA), collagen type I (Col1a1 and Col1a2), and Col5a1 and upregulation of E-cadherin. Bioinformatics analysis revealed that serum/glucocorticoid regulated kinase 1 (SGK1) may be regulated by FOSL2 and involved in renal fibrosis. Further experiments confirmed that TGF-β1 enhanced SGK1 expression and transcription, which were reversed by FOSL2 silencing. Moreover, FOSL2 was bound to the SGK1 promoter, and SGK1 overexpression reversed the effects of FOSL2 silencing in TGF-β1–induced cells.

Conclusion

FOSL2 plays an essential role in promoting renal fibrosis in an SGK1-dependent manner, and targeting the FOSL2/SGK1 signaling axis may offer a potential strategy for the treatment of renal fibrosis.
Mini-dose methotrexate combined with methylprednisolone as a first-line treatment for acute graft-versus-host disease: A phase 2 trial
Authors: Xu Zhengli , Mo Xiaodong , Kong Yuan , Wen Qi , Han Tingting , Lyu Meng , Xu Lanping , Chang Yingjun , Zhang Xiaohui , Huang Xiaojun , Wang Yu 
Published: September 2023

Abstract

Background and Objectives
Acute graft-versus-host disease (aGvHD) remains a major complication after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methylprednisolone (MP; 1–2 mg/kg/day) remains the standard first-line therapy for aGvHD, although no response is detected in nearly one-half of the patients with aGvHD. This study aimed to investigate the feasibility of mini-dose methotrexate (MTX) combined with standard-dose MP as a front-line therapy for aGvHD.

Materials and Methods
A prospective Phase 2 clinical trial was performed to evaluate the safety and efficacy of 5 mg/m2 MTX combined with 1 mg/kg/day MP as the initial therapy in 31 patients with aGvHD. Moreover, the effects of MTX combined with MP were explored in a humanized xenogeneic murine model of aGvHD.

Results
The overall response and complete response rate at 7 days after the initial treatment were 100% and 83%, respectively. The overall response rate on day 28 was 87%. The complete response rates for aGvHD grades I, II, and III were 100% (6/6), 82% (18/22), and 66% (2/3), respectively. Grade 3 toxicities occurred in only three patients presenting with cytopenia. Importantly, MTX and MP demonstrated synergistic effects on ameliorating aGvHD in humanized xenogeneic murine model.

Conclusion
The current study suggests that mini-dose MTX combined with standard-dose MP could potentially become a novel first-line therapy for patients with aGvHD.
Long-term outcomes of esophageal and gastric cancer patients with cardiovascular and metabolic diseases: A two-center propensity score-matched cohort study
Authors: Zhou Bo , Wang Zhixin , Dou Qifeng , Li Wenbin , Li Yangyang , Yan Zhengqiang , Sun Peisheng , Zhao Baosheng , Li Xiumin , Shen Fangfang , Zhang Bangjie , Guo Mingzhou 
Published: September 2023

Abstract

Background and Objectives
An increased risk of cardiovascular and metabolic diseases (CVMDs) among patients with cancer suggests a potential link between CVMD and cancer. The impact of CVMD on the survival time of patients with esophageal and gastric cancer remains unknown. We aimed to determine the incidence of CVMD and its impact on the longterm outcomes in esophageal and gastric cancer patients.

Methods
A total of 2074 cancer patients were enrolled from January 1, 2007 to December 31, 2017 in two hospitals, including 1205 cases of esophageal cancer and 869 cases of gastric cancer, who were followed up for a median of 79.8 and 79.3 months, respectively. Survival time was analyzed using the Kaplan–Meier method before and after propensity score matching.

Results
The incidence of CVMD in patients with esophageal and gastric cancer was 34.1% (411/1205) and 34.3% (298/869), respectively. The effects of hypertension, diabetes, and stroke on the long-term survival of esophageal and gastric cancer patients were not significant (all P > 0.05). The survival time was significantly longer in esophageal cancer patients without ischemic heart disease than in patients with ischemic heart disease, both before matching (36.5 vs. 29.1 months, P = 0.027) and after matching (37.4 vs. 27.9 months, P = 0.011). The survival time in gastric cancer patients without ischemic heart disease was significantly longer than in patients with ischemic heart disease, both before (28.4 vs.17.5 months, P = 0.032) and after matching (29.5 vs.17.5 months, P = 0.02).

Conclusion
The survival time of esophageal and gastric cancer patients with ischemic heart disease was significantly reduced compared to that of esophageal and gastric cancer patients without ischemic heart disease.