bluuebunny/crossref_metadata_2025_split huggingface dataset:
A hybrid online and offline teaching model of professional English for Internet+ education platform
Authors: Li Lin 
Published: September 2023

Abstract
Blended teaching combines the advantages of online teaching and offline teaching, which breaks the limitation of time and space to a certain extent and is of great significance to helping learners improve their learning efficiency and teachers’ teaching level and quality. This paper firstly designs a blended teaching model for the background of Internet+ education and improves the functional design of each part of the model. Secondly, the extreme gradient prediction model of students’ academic level is proposed for the blended model, and a strong learner is formed by integrating multiple weak learners to correct the misclassification. Finally, the blended model of instruction is evaluated and analyzed. The model achieves an accurate prediction accuracy of 65% for MEDIUM students and 75% for PERFECT students, with an average prediction accuracy of 58.4%, which is more than 50%, and can predict students’ academic level situations more accurately. The functional indicators all scored 74.4, the efficiency indicators all scored 71.35, and the usability of the platform exceeded 70. The Internet+education platform’s professional-type English, the online and offline hybrid teaching model, can effectively improve learners’ learning efficiency, as well as improve teachers’ teaching standards and quality.
Research on online and offline double-loop teaching of college students’ mental health education based on cluster analysis algorithm
Authors: Bai Yang , Ma Yulong 
Published: September 2023

Abstract
In this paper, a knowledge difficulty clustering algorithm (MIBKPC) based on multidimensional time-series data and learning path networks is proposed. The algorithm integrates the cyclic learning sequence, forgetting behavior and system interaction degree formed by learners learning some of the more difficult knowledge points, and constructs a computational model for the difficulty similarity of knowledge points based on system interaction behavior so as to better portray the difficulty similarity of knowledge points based on system interaction behavior. Then a knowledge point difficulty clustering algorithm (MFSKPC) based on multidimensional time-series data and maximum frequent subgraphs is proposed. The algorithm extracts the maximum frequent subgraphs of the atlas based on the learner’s directed learning path atlas using the gSpan-based maximum frequent subgraph mining algorithm and portrays the difficulty similarity of knowledge points based on system interaction behaviors by combining the system interaction degree and the maximum frequent subgraphs. In the accuracy comparison, the clustering accuracy of the MFSKPC algorithm for advanced learners was higher than that of the MIBKPC algorithm for both K=3 and K =5 conditions by 7.89% and 8.29%, respectively. In the comparative analysis of double-loop psychological instruction, the experimental class improved its pre and post-test scores by an average of 2.38 points, while the control group improved by an average of only 1.88 points. The experiment showed that the double-loop teaching based on the MFSKPC algorithm was more effective.
Research on the innovative development model of ideological and political education based on big data and self-media environment
Authors: Li Lu 
Published: September 2023

Abstract
This paper aims to explore the innovative development model of ideological and political education. By establishing a Civic and Political Science teaching platform, two functions of classroom interaction and online dual-teacher interaction are designed under nine ideological and political teaching modules. The VR technology and system framework are analyzed, and the corresponding MDP algorithm is constructed. The algorithm model was used to analyze the percentage of students’ favorite Civics classrooms and the acceptance level of VR teaching classrooms. The result data show that only 27.5% of students like Civics class, 51.53% of students maintain a neutral attitude towards Civics class again emotionally, and 16.36% of students do not like Civics class. 70.1% of students prefer the means of communication of Internet platform tools. 16.58% of students prefer the means of communication of newspapers and magazines, 50.2% of students prefer the means of video communication, and 35.26% of students prefer the means of video communication. 35.26% of students prefer book communication. This paper provides reference data and models for the development of ideological and political education innovation.
Research on the immersive multimedia virtual interactive experience technology of the Great Wall World Heritage based on VR vision system
Authors: Wang Xiaofen , Wang Yanzhen , Yuan Pengjun , Yu Kaiyue 
Published: September 2023

Abstract
This paper constructs an immersive multimedia virtual interactive experience technology with the Great Wall World Heritage Site as the experimental object. By analyzing the VR vision system and algorithm, the process of stereo vision perception and the general algorithm of somatic image production are explained. The distance equation and depth calculation in stereoscopic projection are studied, and the virtual interactive experience technology is constructed and applied to the World Heritage Site of the Great Wall. The result data show that the immersive multimedia virtual interactive experience technology highlights the real feeling of users more, in which the model has 50% of the influence on the real feeling, the mapping has 15%, the lighting has 15%, and the rendering has 10%. The youth population has a higher percentage of interest in the virtual field, accounting for 50%, 65%, and 60%, respectively, while the middle-aged stage has a more average degree of interest in the virtual field, with 50% of the average interest, 30% of happy to experience, 25% of not interested and 50% of interested. This thesis is conducive to enriching the project of the Great Wall World Heritage Site and providing an effective reference for technological innovation of immersive multimedia virtual interactive experience.
Simultaneous localization and mapping of mobile robots with multi-sensor fusion
Authors: Zhang Kui , Cui Haihua , Yan Xiaomei 
Published: September 2023

Abstract
Simultaneous localization and map building of mobile robots is an important research direction in robotics, and multi-sensor fusion is one of the key technologies for mobile robots to achieve autonomous navigation. In this paper, firstly, based on the framework of the SLAM system, we analyze the extraction of FAST feature points and BRIEF feature descriptor matching and propose the CSD-ORB algorithm. Secondly, the FKCS-LD algorithm based on the fusion map key frame and center selection strategy is proposed. The suitable multi-sensor fusion SLAM system is selected to build the back-end optimization algorithm based on the bit-pose map. Finally, we complete the comparison experiments of the multi-sensor fusion SLAM system on standard data sets, robot hardware assembly and software environment construction, and actual field testing. The experimental data show that the trajectory calculation accuracy can be further improved by using local map tracking, i.e., the current frame and local keyframe to calculate the bit pose, in which the maximum error is 6 cm, the root mean square error is reduced to 3.6 cm, the maximum value of local optimization is 0.66034, the minimum value is 0.146232, the average is 0.32812, and the median is 0.33023. The experiment proves that the multi-sensor fusion SLAM system can achieve centimeter-level accuracy and has global consistency and real-time performance, and can effectively complete the task of simultaneous robot positioning and map building.
Study on the optimization of the cultivation path of finance professionals in universities in the digital era
Authors: Yang Xiaoying 
Published: September 2023

Abstract
The rapid development of big data technology is bound to affect the development direction of finance majors in colleges and universities and put forward new challenges to the cultivation of talents. This paper first analyzes the data mining concept, process as well as methods and selects the clustering analysis method, K-means algorithm, and NMF algorithm of big data technology. Secondly, data pre-processing is carried out for students’ learning behavior, learning evaluation, and professional ability data, which makes the subsequent data mining results more reliable. Finally, the judgment matrix is constructed for the training of college finance professionals, and the consistency test of the matrix is carried out to form the absolute indexes of the primary indexes and the relative weight values of the secondary indexes, and the absolute weights of the secondary indexes are obtained through calculation, which finally forms the weights about the student learning behavior, learning evaluation and professional competence evaluation indexes. The learning percentages of student learning clusters are: 16.1%, 19.3%, 30.1%, 34.4%. The innovation and collaboration ability of finance students has been improved, and the deep processing feedback ability of financial knowledge content has been strengthened. Thus, the wide application of big data technology provides a new path for the training of finance professionals in colleges and universities.
The integration of flipped classroom into university physical education teaching reform practice from the perspective of multimedia
Authors: Feng Bin , Zhao Jingjing 
Published: September 2023

Abstract
With the development of multimedia, the flipped classroom is deeply loved by educators with its unique, flexible and efficient features, which meet the requirements of physical education reform from a multimedia perspective. In this paper, we first use a genetic algorithm to arrange the physical education course information in a real number coding way to form chromosomes and initial populations. Then the individual fitness F is determined, the outstanding parent individuals are selected, the chaotic crossover and chaotic mutation operations are performed, and the end conditions are judged. According to the calculation of the fitness function, this ensures the diversity of the population and also eliminates the conflicting course plan programs. Then, 83 students from two classes at Guizhou Normal University were used as experimental subjects to explore the effect of integrating flipped classroom teaching into physical education, and the volleyball skills of students in the experimental and control groups were tested in the form of teaching-examination separation. The results showed that there was a significant difference between the volleyball skill test results of students in the experimental and control groups t=2.071, p=0.042, less than 0.05, indicating that the volleyball skill level of the experimental group was better than that of the control group after experiencing 32 credit hours of volleyball teaching. This study promotes the reform of physical education teaching and is of great significance to the development of physical education.
Construction of a screening and evaluation system for anti-hepatitis B virus drugs based on quadratic exponential smoothing model
Authors: Xu Yangding , Hong Yi , Tong Ying , Xiong Zhixiang 
Published: September 2023

Abstract
Exploring the construction of an anti-hepatitis B virus drug screening and evaluation system is to better develop anti-HBV virus drugs. In this paper, we analyzed the types of hepatitis B virus present in different hepatocytes, starting from the hepatitis B cell line model. Based on the quadratic, exponential smoothing model, a QES-LSTM viral gene detection model was constructed by introducing a long and short term memory neural network, and experimental analysis of the sensitivity and specificity of viral gene detection was conducted for this model. From the sensitivity experiments, the sensitivity of HBV DNA, DHBV DNA and DHBV cccDNA were 60 copies/ml, 60 copies/ml and 10 copies/ml, respectively. From the specificity experiments, the mean values of specificity of HBV DNA, DHBV DNA, and DHBV cccDNA were 0.489, 0.481, 0.429, respectively, 0.429, which showed positive amplification compared to other types. This indicates that effective discrimination of HBV viral genes is needed in the construction of an anti-HBV virus drug screening and evaluation system, which in turn allows targeted screening of drugs for the treatment of the HBV virus.
Research on computer network information image data processing based on machine learning
Authors: Mei Haifeng , Sun Li 
Published: September 2023

Abstract
In this paper, we aim to progress the efficiency and accuracy of information processing and security detection in computer networks by introducing convolutional neural networks in machine learning algorithms that are capable of multi-scaling from the channel attention module and spatial attention module in extracting image information. Global maximum pooling and global averaging are done for the feature maps generated by both modules to get the clearest feature maps by dimensionality reduction. The loss function is used to calculate the feature maps to reduce the data loss generated during data extraction and finally complete the image data processing. To verify the effectiveness of the proposed platform, network images containing different amounts of data are input into the platform, and the accuracy and loss of data extraction are obtained. The results show that the data extraction accuracy of the reduced platform is up to 100%, which is 6% higher than other platforms. The number of data losses in other platforms is more than twice of this paper, while the number of losses in this paper can be controlled within 5. It can be seen that convolutional neural network in machine learning improves the accuracy of data extraction from computer network information images and reduces the loss in data extraction.
Intersection Between Spirituality and Neuroscience: Biological Bases of Transcendental Experiences
Authors: Rodrigues Michele Aparecida Cerqueira , Barbosa Fernando Campos , Lopes Gabriel César Dias , Santacroce Luigì , Lopes Pollyanna Carvalho Pereira 
Published: September 2023

Objective: The objective of this study is to investigate the relationship between religion, spirituality and neuroscience, with a focus on understanding the biological bases of religious experiences. The study aims to analyze how different spiritual practices affect the human brain, identify the brain regions involved, and examine the impact of these practices on mental health and emotional well-being. Furthermore, we seek to discuss the ethical implications of including religious themes in medical and psychological practice.

Method: The study uses a qualitative literature review approach in English and Portuguese, based on national and international sources. Scientific articles, case studies and research related to the neuroscience of religion and spirituality were analyzed. The data was collected and organized to identify the biological foundations of spiritual experiences, the social and psychological implications, as well as the ethical issues associated with this theme.

Results and conclusion: The results indicate that different spiritual practices activate several brain areas, including the frontal cortex, prefrontal cortex, nucleus accumbens and striatum, associated with rewards, emotions, moral reasoning and concentration. The mystical mind is considered an innate capacity of the human brain, enabling transcendental experiences in all cultures. Furthermore, the frequent practice of spirituality can lead to profound brain changes, favoring discernment, empathy and better decisions. Religiosity and spirituality have a positive impact on mental health, helping to cope with anxiety, fears and promoting emotional well-being.

Research implications: This study has significant implications in the area of mental health and clinical practice, highlighting the importance of considering patients' spirituality and religiosity as an integral part of their emotional health. Furthermore, the research paves the way for a greater understanding of the biological bases of religious and spiritual experiences, which may have applications in clinical treatments and the promotion of psychological well-being. The ethical implications raised are also relevant for healthcare professionals, who must approach these issues with sensitivity and respect, avoiding the imposition of personal values. On a broader scale, research contributes to intercultural understanding and peaceful coexistence between different religious groups, promoting tolerance and mutual respect.
Dexametasona no pós-operatório em quadros de náuseas e vômitos
Authors: Assunção Laís Lima , Queiroz Cléria Alves de , Dourado Júnior Evaldo de Castro , Rocha João Aurélio Carvalho da , Oliveira Júnior João Carlos Miranda , Lima Lucas Souza , Dourado Ryan de Souza , Haehner Sygrid , Novaes Júnior Walmir Dias 
Published: September 2023

Objetivo: Entender se há eficácia na utilização da dexametasona nos quadros de náuses e vômitos pós-operatório. Métodos: Trata-se de uma revisão integrativa da literatura, os resultados foram desenvolvidos a partir da coleta de dados que foi realizada nas bases de dados: Google Acadêmico, PubMed e Scientific Eletronic Library Online (SCIELO), com os seguintes termos associados: Dexametasona, Pós-operatório, Náusea e Vômitos, combinados utilizando-se o operador booleano “AND” entre os eles, para compor as estratégias de busca, elaboradas para as bases de dados, com o intuito de selecionar artigos científicos conexos ao tema. Os trabalhos selecionados foram aqueles desenvolvidos entre 2019 e 2023. Resultados: Foi demonstrado a eficácia da dexametasona como um antiemético. Além disso, os benefícios da associação do glicocórticoide com outras classes medicamentosas, como os antagonistas serotoninérgicos - antagonistas seletivos dos receptores 5-HT3, representado pela ondansetrona, confirmando que a utilização de dupla terapia é mais eficaz para diminuição da êmese no pós-operatório. Considerações finais: A combinação de fármacos aque atuam em mecanismos distintos melhoram a eficácia nos resultados encontrados em comparação a monoterapia com dexametasona. Relacionado ao custo-benefício para pacientes e gestão hospitar, a dexametasona é uma boa opção terapeutica, em diversos cenários clínicos.
Pharmacological management of upper respiratory tract infections in children: An assessment of a tertiary institution practice in Nigeria
Authors: Ogbo Patricia U. , Obeka Ifeyinwa C. , Ayeni Foluke A. , Asiegbu Uzoma V. , Ewah Richard L. , Okonkwo Chioma A. 
Published: September 2023

Objectives:
Upper respiratory tract infections (URTIs) are the most common acute RTIs that occur in children. Therapy addressing symptoms is recommended for URTI management. The use of antibiotics without culture and sensitivity tests is a risk factor for antimicrobial resistance.

Materials and Methods:
This study was set to assess the pharmacological management of URTIs in children from a tertiary institution practice. This study was conducted in Alex Ekwueme Federal University Teaching Hospital, Abakaliki Ebonyi State, Nigeria. It was a retrospective review of 275 prescriptions of medicines for URTIs in children, from January to December 2021. A systematic sampling technique was used to collect data. Data were analyzed using the Statistical Package for the Social Sciences version 28.0.

Results:
Of the 275 sampled URTI cases, 157 (57.1%) occurred in male children. No laboratory test was conducted for 265 (96.4%) cases. The majority (207; 75.3%) were diagnosed as non-specific URTI. Other diagnoses include tonsillitis (46; 16.7%), otitis media (8; 2.9%), and rhinitis (6; 2.2%) among others. Antibiotics were the most prescribed medications, (212; 77.1%) followed by antihistamines, (110; 40.0%), vitamins (75; 27.3%), and antimalarials (55; 20.0%). The most prescribed antibiotic was amoxicillin-clavulanic acid (79; 28.7%). There was no statistically significant association between the age category of children and the number of medicines prescribed, whether antibiotics were prescribed, and the number of antibiotics prescribed (P > 0.05).

Conclusion:
Antibiotics were the mainstay for the management of URTIs in the study center. This mode of therapy could lead to antimicrobial resistance since culture and sensitivity tests were not done before the initiation of antibiotic therapy.
Automated intracranial hemorrhage detection in traumatic brain injury using 3D CNN
Authors: Agrawal Deepak , Poonamallee Latha , Joshi Sharwari , Bahel Vaibhav 
Published: September 2023

Objectives:
Intracranial hemorrhage (ICH) is a prevalent and potentially fatal consequence of traumatic brain injury (TBI). Timely identification of ICH is crucial to ensure timely intervention and to optimize better patient outcomes. However, the current methods for diagnosing ICH from head computed tomography (CT) scans require skilled personnel (Radiologists and/or Neurosurgeons) who may be unavailable in all centers, especially in rural areas. The aim of this study is to develop a neurotrauma screening tool for identifying ICH from head CT scans of TBI patients.

Materials and Methods:
We prospectively collected head CT scans from the Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi. Approximately 738 consecutive head CT scans from patients enrolled in the department were collected for this study spanning a duration of 9 months, that is, January 2020 to September 2020. The metadata collected along with the head CT scans consisted of demographic and clinical details and the radiologist’s report which was used as the gold standard. A deep learning-based 3D convolutional neural network (CNN) model was trained on the dataset. The pre-processing, hyperparameters, and augmentation were common for training the 3D CNN model whereas the training modules were set differently. The model was trained along with the save best model option and was monitored by validation metrics. The Institute Ethics Committee permission was taken before starting the study.

Results:
We developed a 3D CNN model for automatically detecting the ICH from head CT scans. The screening tool was tested in 20 cases and trained on 200 head CT scans, with 99 normal head CT and 101 CT scans with some type of ICH. The final model performed with 90% sensitivity, 70% specificity, and 80% accuracy.

Conclusion:
Our study reveals that the automated screening tool exhibits a commendable level of accuracy and sensitivity in detecting ICH from the head CT scans. The results indicate that the 3D CNN approach has a potential for further exploring the TBI-related pathologies.