bluuebunny/crossref_metadata_2025_split huggingface dataset:
Teaching reform of university botany courses based on discrete regression algorithm
Authors: Li Zhuowei , Liu Junyuan , Lu Liuwanwan , Wang Yafang , Yan Xiaowei , Han Chunyang 
Published: September 2023

Abstract
Under the digitalization of big data information, the traditional way of teaching botany courses faces challenges and opportunities, and using big data technology to improve the quality of botany teaching becomes a key research problem. Firstly, based on the big data technology and the teaching objectives of botany in colleges and universities, the teaching system platform is proposed to be constructed by a discrete regression algorithm and Hadoop platform. Then the structure and functions of the teaching system are designed according to the needs of teachers and students and course objectives, and the teaching system is realized for practical application in botany courses. Finally, starting from students as learning subjects, biological engineering students of Guizhou University were identified as the research objects, and the teaching system platform based on the discrete regression algorithm was used to conduct weight analysis on the teaching of botany courses in colleges and universities. The results showed that the mean values of the botany course, bacteriology course, zoology course and microbiology weight were 25.64%, 25.32%, 24.57% and 24.47%, respectively, and the overall weight means performance showed that botany was better than the other three types of biology courses with the mean value of 25.64%. This study has helped improve botany teaching quality and curriculum reform by increasing the participation of students in classroom teaching.
The Innovation of GIS Service Mode Based on “Grid Integration” and “Elastic Cloud”
Authors: Wang Chenchun , Ma Shenglong , Hui Zi 
Published: September 2023

Abstract
This paper firstly investigates the theory and method of geospatial information services and grid integration model in the geographic information grid, intending to locate the parameter coordinates of the grid integration model into the GeoSOT-3D profiling framework. Secondly, the framework of the consumption structure between its services and cloud resources is established by the elastic cloud model based on the computation and storage capabilities provided by the shared grid infrastructure. And use the steady-state theoretical foundation for analysis to assess the service quality of each type of service and reflect the service quality of the GIS service model as a whole. Finally, a GIS service platform based on the grid integration model and elastic cloud model is constructed based on the existing open geographic information standards, service technology system, and grid technology. The research results show that the operation speed of the GIS service platform proposed in this paper is increased by 16.3%, the estimated cost has been reduced by 23.3%, and the service evaluation of the platform is improved by 43.6%. The GIS service platform based on the grid integration model and elastic cloud model has the advantages of global uniformity, multi-scale and spatial 2-3D consistency, which provides a new model with high economy and rapid response time for geographic information processing.
Distributed optical fiber sensing technology in operation status monitoring of GIL equipment
Authors: Du Wenjiao , Hu Zhong , Li Chenmeng , Chen Zihui , Chen Wenhong , Qiu Shiyan 
Published: September 2023

Abstract
This paper firstly proposes distributed fiber optic sensing technology based on big data technology and physics, distributed fiber optic sensing technology includes distributed fiber optic sensing technology based on interference type and distributed fiber optic sensing technology based on the scattering principle. Then investigated the demand for remote monitoring of distributed fiber optic sensing systems and the demand for large sensing networks in the Internet of Things and designed a long-distance distributed fiber optic sensing-based intelligent monitoring system. Finally, the vibration acceleration signal of the metal shell when partial discharge occurs is collected, and the high-frequency components in the vibration acceleration signal are used to diagnose and analyze the discharging faults caused by the metal particles of GIL. The results show that: when the rated current is loaded on the GIL, the main frequency distribution of the vibration acceleration signal on the surface of the metal shell is from 0 to 1 kHz, and the percentage of the signal energy in this frequency band is greater than 99% of the total energy in the range of 0 to 20 kHz. In the frequency range of 1 kHz to 20 kHz, the percentage of the signal energy in the total energy does not exceed 1%, and there is almost no high-frequency vibration acceleration signal. This study and the combination of these two technologies is a great contribution to the further development of each, but also more favorable for application in work and life.
Optimization of Innovative Teaching Model of College English Reading Based on Perceptual Machine Model
Authors: Wang Lang 
Published: September 2023

Abstract
Reading is an essential part of English learning and one of the basic elements of language proficiency. This paper proposes a joint analysis model based on multilayer perceptron, which uses an LSTM network model suitable for text processing. Using the BiLSTM network can obtain all the contexts before and after the current word and avoid the problems of gradient disappearance and gradient explosion that exist in ordinary recurrent neural networks. Two multilayer perceptrons are used, one for predicting lexical annotations and the other for predicting the relationship types of dependency arcs, and the model accuracy is further improved by continuously optimizing the parameters in the model. The English corpus is divided into a training set and a test set, and the prediction rate of the model in this paper reaches 96.02% in the English corpus. To test the effectiveness of this method for college English reading instruction, this model was implemented in the experimental class, while the traditional PWP teaching model was still used in the control class. The mean reading post-test score of the experimental class was 31.54, and the mean post-test score of the control class was 26.35. The mean reading post-test score of the experimental class was 7.7 points higher than the mean score of the pre-test. Therefore, the method in this paper is effective in teaching English reading and can improve college students’ reading performance.
Identification of Key Factors Influencing Consumer Purchase in Livestreaming Based on Principal Component Analysis and Combination Weighting
Authors: Zhu Xiaoping , Yang Li 
Published: September 2023

Abstract
Based on the livestreaming of the e-commerce platform Taobao, this paper studied the consumers’ online live streaming purchase decision behavior, taking causal snacks purchase as an example. In the paper, the principal component analysis (PCA) was applied to reduce dimension of the evaluation indicators of consumers purchase decision, and an evaluation index system for consumers’ purchase of casual snacks under livestreaming was established, which consists of 5 first-level indicators and 20 sub-level indicators. In view of the uncertainty of expert evaluation, Using Fuzzy-DEMATEL analysis the evaluation index’s logical relationships and influence relationships, and an Analytic Network Process (ANP) network based on the importance and relevance of consumer purchase influence was constructed. The weighted method of Fuzzy-DEMATEL and ANP combination is used to improve the objectivity of indexing importance. The experimental results showed that the amount of transaction guided by anchors, popularity of anchors, teamwork ability of livestreaming, brand awareness of snack and selection ability of livestreaming team were the key factors for consumers’ purchasing decisions of snack under livestreaming. This research could help livestreaming e-commerce platforms, businesses and livestreaming marketing teams understand the consumers behavior better, thus improve the purchase intention of consumers from the key factors affecting their decision-making, increase the sales volume and the amount of attention of the products, and increase the volume of guided transactions and the number of fans for the livestreaming marketing teams.
A hybrid physics-data-driven optimization model for grassland grazing management
Authors: Yu Bo , Li Yulong 
Published: September 2023

Abstract
This paper presents a hybrid physics-data-driven optimization model for grassland grazing management. It comprehensively assesses essential factors in the Abaga Banner grassland ecosystem, including soil moisture, vegetation biomass, desertification degree index, and soil compaction. Through a thorough analysis, the impacts of grazing patterns and intensity on the grassland’s physical characteristics and biomass are studied. Employing genetic algorithms, an optimal grazing model is formulated to minimize soil desertification throughout the year. The paper aims to contribute to grassland ecology restoration and ensure sustainable livelihoods for local herdsmen, offering a scientific foundation for promoting the sustainable growth of grassland husbandry.
China’s Image in German Media in Major Epidemic Prevention and Control Based on Mathematical Statistics
Authors: Jingjing Liu , Xiaoyan Zhang 
Published: September 2023

Abstract
National image is an important symbol of national cultural soft power. Adhering to ideas and methods of mathematical statistics, this paper focuses on the construction of China’s image in German media from the perspective of epidemic prevention and control. Taking Deutschlandfunk as the retrieval object, texts are analyzed by AntConc corpus analysis toolkit to construct China’s image and German media attitude tendency under the background. The study found that, the German media exoticised and politicised the event through a series of discursive devices, constructing a biased image of China, although giving positive comments on China’s anti-epidemic measures and foreign aid.
Research on the influence of key audit matters on the audit quality of commercial banks-Evidence from China
Authors: Wei Xiaoyan , Zhang Lifang , Li Jing , Zhou Xiyu Thomas 
Published: September 2023

Abstract
In this paper, multiple linear regression model is used to predict and test the effect of audit policy changes in the capital markets. In 2016, China issued a new reporting guideline which included the addition of key audit matters (KAMs) as the core focus. It was required that all A+H-share companies should implement these in their reporting in 2017, as well as all domestic listed companies in 2018. In order to study the impact of the KAMs standard on the audit quality of Chinese commercial banks, we analysed the KAMs as disclosed by commercial banks as well as any further change in audit quality at these banks before and after implementation of the new auditing reporting standards. The results show that the disclosure of KAMs significantly promotes the improvement of loan impairment provisions in commercial banks, thus inhibiting potential earnings manipulation by management and improving the quality of financial information. The level of loan impairment provision plays an intermediary role in the improvement of bank audit quality in the new reporting standards.
Does Work Engagement Effectively Predict Subjective Well-Being? : A Meta-Analysis Using R Statistical Software
Authors: Ding Hui , Si Shoujing 
Published: September 2023

Abstract
Does work engagement effectively predict subjective well-being? In this paper, we investigated the relationship between work engagement and subjective well-being by synthesizing 176 effects from 59 studies involving 21927 subjects. The results showed that work engagement were positively correlated with subjective well-being, while job burnout were negatively correlated with subjective well-being. Literature sources significantly adjusted the relationship among work engagement, job burnout and subjective well-being. The paper proved that work engagement and subjective well-being are closely related, and literature sources may play a moderating role.
Performance Evaluations of Audit Institutions That Purchase Social Audit Services
Authors: Wei Xiaoyan , Wang Hua 
Published: September 2023

AbstractThe technical characteristics of government audits make the purchase of social audit services different from the purchase of other public services. Carrying out performance evaluations of outsourced social audit services is important for ensuring effective social audit service outsourcing and for completing comprehensive high-quality audits. On the basis of constructing a conceptual framework for performance evaluations of social audit service purchases under the background of comprehensive audit coverage, the objectives, principles, processes, models, and steps of performance evaluations are clarified. From the perspective of performance evaluation theory, a performance evaluation model and an index system are constructed. On this basis, the evaluation framework is applied to performance evaluations of audit institutions that purchase social audit services. Although outsourcing social audit services solves the problem of coverage quantity relatively economically, there is still room for improvement in terms of efficiency and effectiveness. Audit institutions can continuously improve the performance of outsourced social audit services by building and continuously optimizing the pool of institutions and social audit personnel, constructing a real-time management system for outsourced social audit services, and improving the management incentive system for and performance of outsourced social audit services.
Forecasting Stock Market Volatility via Causal Reasoning
Authors: Yang Dan , Lu Di 
Published: September 2023

Abstract
Studies have shown that Internet financial news has become an important reference for investors in investment behavior. In order to simulate trading experiments that mimic the real stock market, this paper develops a stock volatility prediction model based on causal reasoning. It also gathers and cleans news and stock market data from the Internet, such as opening price, closing price, and change. The findings of the study indicate that the level of stock market volatility can be significantly influenced by online financial news. The proposed model can analyze the effects of news and stock market data in an explainable manner.
Difference-in-Differences Test for the Effect of Extreme Weather upon Enterprise Productivity
Authors: Li Guiping , Zhang Xiaohua , He Qian , Xiao Zheng 
Published: September 2023

Abstract
This paper establishes DID and PSM-DID models to examine the effect of extreme weather on enterprise productivity, using empirical evidence from natural experiments of torrential rainstorm in Zhengzhou of China. Based on analysis of empirical results, we find that extreme weather has a negative impact on enterprise productivity, psychological capital plays a regulatory role in this influence, and decrements of enterprise productivity with high psychological capital is smaller than enterprises with low psychological capital. The results of this study provide empirical data support to understand the negative effect of extreme weather upon enterprise productivity and the positive role of employee psychological capital.
The impact of industrial-university-research collaborations on innovation output in China’s petroleum and petrochemical industry
Authors: Zhu Zhihong , Zhang Shuang 
Published: September 2023

Abstract
To increase the capacity and production of the petroleum and petrochemical industries, it is helpful to investigate the features of industry-university-research collaborative innovation networks. Using the DEA model as a research object, listed companies in China’s petroleum and petrochemical industries are assessed for their innovation output, Moreover, we examined the structural holes in a Co-innovation network between industry and university. We have also assessed the network’s density, the strength of its connections, and the quality of its links. The strength of network relationships was negatively correlated with innovation output, but network density was positively correlated with structural holes. As a result of the research, relevant policy recommendations are made, including actively building industry-university-research collaborative innovation platforms, improving the depth and breadth of collaboration between innovation entities within the industry-university-research network, by connecting industry and universities to collaborate on innovative projects, petroleum and petrochemical companies can better compete.
Research on the influence of new media on ideological and political education in colleges
Authors: Liu Erting , Zhao Lanwei 
Published: September 2023

Abstract
This study aims to investigate the effectiveness of new media on ideological and political education in higher education institutions and utilizes data analysis methods to uncover the role and impact mechanism of new media in this context. To gather data and gain a deeper understanding, grounded theory and a questionnaire survey based on the Diffusion of Innovations Model were employed. The survey targeted university students and provided insights into the information dissemination and influence pathways of new media in ideological and political education at universities. The survey findings shed light on the positive role of new media in enhancing students’ learning outcomes in ideological and political theory and their willingness to participate in civic and political affairs. In addition to the survey, the study utilized literature visualization analysis using Citespace to identify research directions and approaches related to the influence of new media on ideological and political education in higher education institutions. The analysis results revealed research trends in this area. In conclusion, the study’s findings highlight the effectiveness of new media in ideological and political education in higher education institutions and contribute to a deeper understanding of its role and impact
The Role of Modern Techniques in Preservation of Archaeological Sites
Authors: Chabuk Mahmood , Al-Amiri Shatha 
Published: September 2023

Abstract
Archaeological sites have always suffered from loss and degradation due to many human and natural hazards. In recent decades, interest in preserving archaeological sites has increased dramatically. Many modern techniques have emerged from the different disciplines that can be used in preservation works, and a large number of the techniques and their capability made it difficult for decision-makers and specialists to determine the appropriate technique that gives the best results in preserving the archaeological site. The research aims to identify the project needed to preserve the archaeological site and then choose the appropriate technique for it, based on the opinions of experts using the analytic hierarchy process (AHP) method, which helps decision-makers and specialists to choose the most appropriate technology. The archaeological site of Babylon was chosen as a case study. As a result of applying the AHP method, the priority weights of preservation stages for the archaeological site of Babylon were determined as follows: (diagnosis and monitoring 30.8 %), (intervention 21.2 %), and (tourism and media 16.6 %), while the appropriate technique was determined as follows: (infrared thermography 29.4 %), (maintenance 49.3 %), and (augmented reality 38.7 %).
Virtual 3D Tour Assistance in Real Estate Management
Authors: Leimontaitė Lina , Naimavičienė Jurga 
Published: September 2023

Abstract
Over the past decades, more efficient real estate management opportunities have significantly expanded and improved. Complex methods, innovative techniques, and a constantly evolving spectrum of information technology have become readily available for common use. When managing real estate for short-term or medium-term rentals, planning, servicing, and ensuring accommodation quality are inseparable aspects, as is providing suitable housing. This process begins at the very first step when potential tenants request a viewing of the preferred property. The situation of the past few years demonstrated that the real estate business was one of the most affected economic sectors by the COVID-19 pandemic. Potential buyers or tenants could no longer physically visit and experience the space as before. Faced with this new reality, there was a need to find a tool to enhance the real estate management strategy by presenting the property. One such tool became the 360-degree photography and virtual tour. The aim of this study is to assess the practical applicability of 3D video tours and evaluate the advantages and drawbacks in short- and medium-term rental business.
The Dollar and Gold: Which is the Safest Haven? COVID-19 Evidence
Authors: Bousbia Salah Rahima , Beggat Hanane , Debbar Abdelkerim 
Published: September 2023

Abstract
This paper examines the dynamic correlation between the US dollar and gold prices during the coronavirus pandemic to determine which of the two assets is a safer haven from an investor’s perspective. The research utilises methods of analysis and synthesis of theoretical knowledge from published articles, literature, and official statistics websites. Data covering the period from January 1, 2020 to May 26, 2021, were primarily collected from the latest versions of these websites. The study includes a quantitative analysis of variables, including the Johansen cointegration test, the Granger causality test, and the error correction model. Our empirical analysis reveals a long-term equilibrium relationship between the US dollar and gold price. There is a oneway inverse causality relationship between the dollar and gold price. The results indicate that gold can be considered the safest haven from the investors’ perspective.
Effect of the GHRL gene (rs696217) polymorphism on the metabolic disorders in patients with obesity in the Ukrainian population
Authors: Prodan Andrii , Dzubanovsky Ihor , Kamyshnyi Oleksandr , Melnyk Natalia , Grytsenko Stepan , Voloshyn Stanislava 
Published: September 2023

Abstract

Objective. Over the past four decades, the prevalence of obesity has tripled and limited genetic studies with specific SNPs have been conducted, but no investigations using ghrelin and obestatin prepropeptide (GHRL) gene have been reported in the Ukrainians population. The aim of this study was to evaluate changes in the level of metabolic hormones in the blood of obese patients in relation to the GHRL (rs696217) polymorphism.

Methods. The study involved 53 obesity cases and 48 non-obesity subjects (controls). The GHRL (rs696217) polymorphism was genotyped using a TaqMan real-time polymerase chain reaction method. Blood hormones were determined with commercially available kits using a Multi-skan FC analyzer.

Results. Carriers of the T allele of the GHRL (rs696217) polymorphism were statistically significantly more in patients diagnosed with obesity compared to controls indicating a genetically determined cause of obesity. We also established a significant effect of the presence of the T allele of the GHRL (rs696217) polymorphism on the decrease in the adiponectin level and the increase of resistin level in obese patients. The study of the effect of genotypes (TT, GT, GG) of the GHRL (rs696217) polymorphism on the metabolic hormone levels in the blood of obese patients did not show reliably significant differences.

Conclusions. The presence of the T allele of the GHRL (rs696217) polymorphism in Ukrainian population indicates an increased risk of the obesity development regardless on the homozygous or heterozygous genotype.