bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Wordle data based on a time-series prediction model
Authors: Zhu Yan
Published: July 2023

Wordle Is a popular word game daily provided by the New York Times. In this paper, we make a further data analysis on Wordle by using the time-series model. First, a time series model was built to predict and test the results, and the correlation of word properties with the degree of difficulty was analyzed. Second, we build multiple multivariate regression models, take the percentages of 1,2,3,4,5,6, and X as output variables, find the relationship between word attributes and the percentage of each attempt and make predictions. Finally, words were classified by difficulty based on the extracted attributes and eerie by the resulting model and evaluated for accuracy.
Research on the impact of AI on college students based on the entropy weight integrated scoring model
Authors: YU Xiaofeng
Published: July 2023

In recent years, artificial intelligence technology is developing continuously, which has had a wide impact on the study of college students. This paper uses scale, independent heat coding and other methods to quantify the questionnaire data, screen the evaluation index system by establishing gradual regression model, correlation model and comprehensive evaluation model of entropy right, and quantify the influence of artificial intelligence on college students' learning. First of all, the raw data was statistically analyzed and visualized. The analysis showed that 93.2% of college students hoped to actively use artificial intelligence tools to improve their academic performance. Then, the influence of artificial intelligence on the learning of college students was studied, and the evaluation index system was determined through the Pearson correlation model and the stepwise regression model. Finally, the effect of AI on undergraduate learning is studied through the entropy weight integrated scoring model.
Performance Evaluation of Financial Industry Related Expense Forecasting Using Various Regression Algorithms for Machine Learning
Authors: Yao Liangyong , Lin Yan , Mo Yalun , Wang Feng
Published: July 2023

Insurance costs refer to the fees charged by insurance companies to customers to pay for possible risks and losses. Insurance costs are usually based on the personal information of the insured, such as age, gender, occupation, health status and so on. For insurance companies, it is very important to accurately predict insurance costs, because it is directly related to the company's profits and risk control capabilities. The purpose of using regression algorithm to predict insurance expenses is to make insurance companies evaluate customers' risks more accurately and make more reasonable insurance expenses, so as to better manage risks and improve the company's profitability. In addition, for individuals, knowing their own insurance cost forecast results will also help them make better decisions and choose the most suitable insurance products to protect themselves and their families.In order to improve the pricing accuracy and profit rate of insurance companies, this study uses regression algorithm to predict insurance costs. It uses real anonymous data sets, which contain information of the insured from different regions, different ages, different sexes and different smoking status. It uses the comparison algorithm function of regression algorithm, which contains dozens of algorithms and covers all regression algorithms and compare their prediction performance. Our data set takes into account various factors that affect the insurance cost, such as age, gender, body mass index, smoking status and so on. And add them to the model as independent variables. It uses cross-validation to evaluate the generalization ability of the model and R2 index to evaluate the prediction performance. The results show that GBR has the best prediction performance, with R2 of 87%. Our research provides an accurate method for insurance companies to predict insurance costs, which is helpful for insurance companies to formulate more reasonable pricing strategies and improve market competitiveness.
Youtube Video TrendingAnalysis Based on Machine Learning
Authors: Liu Zhanbei
Published: July 2023

Social media platforms play an important role in commerce, entertainment, marketing, education, media and communication. YouTube has a large and active user base, making it the center of corporate digital marketing efforts. There are always videos that attract a lot of attention in a short period of time and become trending videos on YouTube, and these videos can be displayed as trending videos on YouTube and updated daily. In this article, we analyzed data on YouTube trending videos in the US region and analyzed the targets that captured the attention of users in a relatively short period of time. We conduct exploratory data analysis on each aspect to gain data insights and find statistical similarities between them to understand viewing patterns across video categories. We present our analysis by measuring, mining, analyzing, and doing ANOVA comparisons of four scales of different categories of likes, dislikes, opinions, and comments. In addition, the study compared the accuracy of three machine learning methods on YouTube data, which counts the number of views and viewer reactions of popular videos on YouTube.
Analysis and Application Research of InfoGAN
Authors: Wang Xinghao
Published: July 2023

Generative Adversarial Networks (GAN) have been a revolutionary development in the field of Artificial Intelligence, particularly in the domain of generative models. The information maximizing generative adversarial nets, or infoGAN, is one of the most recent and promising developments in the world of GAN. InfoGAN focuses on maximizing the mutual information between the generator's output and some input variables. This means that the generated images or data can be controlled more easily while maintaining high-quality results.Apart from these applications, infoGAN has also been used in other areas such as natural language processing, anomaly detection, and even in music generation. With its versatility and robust performance, infoGAN looks set to become an increasingly important tool for researchers and practitioners in the field of machine learning.This paper focuses on the principle of infoGAN (information maximizing generative adversarial nets) and tries to put forward several ways to apply infoGAN to solve different kinds of problems in daily life.
Paddy Disease Classification Based on the Lightweight MobileNet-V2
Authors: Liu Ruifan
Published: July 2023

Paddy, a critical global staple food and economic resource, faces significant challenges in cultivation due to diseases that have devastating effects on crop yield and quality. Accurate and valid classification of these diseases is essential for their effective prevention, management, and timely treatment. Traditional identification methods, which are manual, time-consuming, labor-intensive, and prone to misclassification, fail to efficiently address these concerns. In response to these limitations, this research focuses on designing a lightweight neural network model for rice disease classification, leveraging the power of MobileNet-V2. This deep separable convolution-based neural network architecture is optimized for efficiency and accuracy in image classification tasks, making it well-suited for mobile devices. The approach enables real-time identification of rice diseases in the field, facilitating prompt intervention and treatment, ultimately minimizing the impact on crop yield and quality. The proposed model has undergone rigorous testing and benchmarking against state-of-the-art methods in paddy disease classification. Sufficient and multifaceted results demonstrate that the designed method achieves superior performance, outperforming the state-of-the-art in terms of accuracy and efficiency. The utilization of MobileNet-V2 in this research offers a valuable solution for the rapid and precise diagnosis of rice diseases, significantly contributing to the minimization of their spread and impact on crop yield and quality.
Research and Application Analysis of Correlative Optimization Algorithms for GAN
Authors: Wang Tianmeng
Published: July 2023

Generative Adversarial Networks (GANs) have been one of the most successful deep learning architectures in recent years, providing a powerful way to model high-dimensional data such as images, audio, and text data. GANs use two neural networks, generator and discriminator, to generate samples that resemble real data. The generator tries to create realistic looking samples while the discriminator tries to differentiate the generated samples from real ones. Through this adversarial training process, the generator learns to produce high-quality samples indistinguishable from the real ones.Different optimization algorithms have been utilized in GAN research, including different types of loss functions and regularization techniques, to improve the performance of GANs. Some of the most significant recent developments in GANs include M-DCGAN, which stands for multi-scale deep convolutional generative adversarial network, designed for image dataset augmentation; StackGAN, which is a text-to-image generation technique designed to produce high-resolution images with fine details and BigGAN, a scaled-up version of GAN that has shown improved performance in generating high-fidelity images.Moreover, the potential applications of GANs are vast and cross-disciplinary. They have been applied in various fields such as image and video synthesis, data augmentation, image translation, and style transfer. GANs also show promise in extending their use to healthcare, finance, and creative art fields. Despite their significant advancements and promising applications, GANs face several challenges such as mode collapse, vanishing gradients, and instability, which need to be addressed to achieve better performance and broader applicability.In conclusion, this review gives insights into the current state-of-the-art in GAN research, discussing its core ideas, structure, optimization techniques, applications, and challenges faced. This knowledge aims to help researchers and practitioners alike to understand the current GAN models' strengths and weaknesses and guide future GAN developments. As GANs continue to evolve, they have the potential to transform the way we understand and generate complex datasets across various fields.
A Comprehensive Study on the Use of Multiple Classification Models for the Type Classification Problem of Unknown Artifacts
Authors: Chen Jiajun , Ou Zhenhui , Chen Nuo , Lv Shulong
Published: July 2023

The early glass was often made into bead-shaped ornaments in the West Asian and Egyptian regions and introduced to China. The ancient glass in China was made locally after absorbing its technology, and the appearance of glass products is similar to that of foreign ones, but the chemical composition is different. Therefore, it is a very meaningful task to analyze and identify the composition of ancient glass products. In this paper, based on the known chemical composition data of excavated artifacts, the statistical pattern of whether the artifacts are weathered or not is visualized by using frequency distribution charts, and the interference of random errors on the results is tested through a chi-square test. Subsequently, the two major categories of high potassium glass and lead-barium glass are classified, while the problem of classifying the types of unknown artifacts is solved. In this paper, a scientific, reasonable, and systematic system of glass-type classification is established, the prediction is carried out on this data set, and more accurate results are obtained with a correct rate of 90%, which proves that the model has a strong generalization and practical significance.
Sub-classification of glass products based on discriminant function
Authors: Wang Wenbo , Hou Xiaosen , Jin Wuchen
Published: July 2023

In this pap, that discriminant function is established for the coarse classification of the known glass, and the sub-classification result of the high-potassium glass is as follows: the K2O-Na2O-SiO2 glass, the K2O-CaO-SiO2 glass, the K2O-CuO-SiO2 glass, the sub-classification result of lead-barium glass are PbO-BaO-Na2O-SiO2 glass, the PbO-BaO-Al2O3-SiO2 glass, the PbO-BaO-SrO-SiO2 glass, the PbO-BaO-CaO-SiO2 glass, The subtaxonomic results correspond to the color and ornamentation, which indicates the rationality of subtaxonomic results. Sensitivity analysis showed that the sensitivity was small and the model was robust. It provides a reference for the subsequent study of the weathering and composition of ancient silicate glass.
Application of Organic Coating in Marine Anticorrosion
Authors: Han Lanruo , Pang Qianyi , Yu Xiang
Published: July 2023

The development of navigation technology has increased maritime trade and the corrosion problem of ships has received more and more attention. Marine corrosions are mainly electrochemical, mechanical and biological corrosion. Normally, the countermeasures for marine corrosion include sacrificial anode protection, applied current cathodic protection and anti-corrosion coating. However, the first two still have great shortcomings. The sacrificial anode protection is limited by the potential difference between the metal electrodes, and the protection range is small. The applied current cathodic protection requires continuous external batteries, and the cost of detection and maintenance is high. The anticorrosive coating not only has excellent anticorrosive performance, but also has the advantages of simple operation process and low cost. Hence, anticorrosive coatings have been gradually applied to ship anticorrosion. Finally, this paper reviews the application of organic coating method in ship mooring corrosion protection, and introduces three kinds of epoxy anticorrosive coatings, polyurethane anticorrosive coatings and graphene anticorrosive coatings to meet the increasingly stringent development requirements of marine anticorrosive coatings.
Data analysis of factors related to weathering of ancient Chinese glass
Authors: Xiong Xiaoyu , Zhuang Zhaochun , Luo Peiwen
Published: July 2023

Ancient glass is an important part of the history of cultural relics, and it is important to study the factors related to glass weathering. Ancient Chinese glass is divided into two categories: lead-barium glass and potassium glass, and the excavated glass artifacts are diverse in terms of decoration and color due to the different production processes and the environment in which the glass is located.This paper analyzes data for both types of glass, analyzes the correlation between glass and each index from data and statistics, and uses mathematical methods to establish models to explore the correlation between whether glass is weathered or not and the decoration, color and category to facilitate smoother archaeological research.
The Antioxidant Ability and Extraction Yield of Beta Carotene
Authors: Huang Anqi , Liu Hongshu , Pan Yan
Published: July 2023

Beta carotene (β-Carotene), one of the most abundant carotenoids in fruit and vegetables, is an essential source of antioxidants. The antioxidation ability of β-Carotene has been through in vitro and in vivo tests, which proved that the compound could prevent the oxidation of singlet and triplet oxygen, oil, and fats. Since β-Carotene is unstable and prone to oxidation when exposed to high temperature and high light intensity, various extraction methods have been tested and applied to get to the maximised yield and purity of the extract. Among all the extraction methods, enzyme-assisted extraction (EAE) is the most efficient, with almost 100% extraction yield. The need for antioxidants by the public promoted the production of β-Carotene nutraceuticals and cosmetics. This essay compared the efficacy of different extraction methods and bioactivity of β-Carotene in different research papers and concluded the extraction method with the highest efficiency.
Enhancing the Electrochemical Properties and Processing Techniques of Carbon Nanotubes for Bio pharmacological Applications: A Research Perspective
Authors: Huang Ziyi , Li Xinyu , Sun Yakun , Song Zekai , Wang Lei , Yu Lenian , Wang Zhenning , Liu Jie
Published: July 2023

Compared with other biopharmaceutical technologies, carbon nanotubes not only have unique structure, but also have strong electrochemical properties, which occupy an important position in the fields of chemistry, physics, biopharmaceutics and materials science, and have played an active role in promoting the development of biopharmaceutics and chemical industry in China. Carbon nanotubes (CNTs) are mainly used in the field of biopharmacology for the determination of small biological molecules and drug molecules, the determination of dopamine and thrombin, the determination of high concentrations of ascorbic acid, and the detection of drug formulations. Although carbon nanotubes (CNTs) have many advantages in the field of biopharmaceutics, there are certain limitations that limit the scope of application of carbon tubes, which are mainly the following: one is the high cost of the carbon nanotube material itself and the high technical difficulty of its preparation; the other is that the smooth surface of the material is not conducive to the loading of other particles; finally, although the carbon nanotubes are modified with different groups after treatment, the structure of the material itself is damaged. Finally, although carbon nanotubes are modified with different groups after treatment, their own material structure is destroyed, which reduces their conduction performance. Although the above defects can affect the performance of carbon nanotubes, they can be solved by optimizing the structure of carbon nanotubes, enhancing the plastic mechanical properties of carbon nanotubes and corrosion resistance, in order to give full play to the role of carbon nanotubes in the field of biopharmaceuticals. In this regard, the author briefly analyzes the electrochemical properties of carbon nanotubes in biopharmacology and the application of treatment methods based on relevant literature and work experience, hoping to provide reference value for related scholars and researchers.
Nanotechnology Applications in Cathode and Anode Materials of Li-Ion Battery
Authors: Qiu Yue
Published: July 2023

Lithium-ion batteries (LiBs), with their high energy/specific density, extended cycle life, and minimal self-discharge rate, have gained considerable popularity in the manufacturing of portable devices and electric vehicles, where space and weight constraints are of utmost importance. Additionally, LiBs have played a pivotal role in the advancement of electric vehicles, promoting sustainable energy practices, and reducing greenhouse gas emissions. However, the limitations that stem from the inherent structures and properties of the conventional component materials of batteries might pose obstacles to the application and development of LiBs, despite their numerous advantages. Nevertheless, significant strides have been made towards improving the capacity, cycling performance, and rate performance of these batteries using nanotechnology. This approach leverages the outstanding properties of nanomaterials to enhance the electrochemical performance of battery components, such as cathode materials, which includes NMC, NCA, LMO, LFP, and anode materials such as Silicon and LTO. This paper provides a comprehensive discussion of the applications of nanotechnology in lithium-ion batteries, offering insights into the future of this promising field.
Introduction of LFP and Ternary Cathode Materials of Lithium Battery
Authors: Yue Peng
Published: July 2023

In recent years, with rapid development of mobile devices and electric vehicles, lithium-ion battery as an efficient and clean battery technology has attracted wide attention. Cathode material of Li ion batteries (LIBs) is the core part that determines the battery performance. This paper aims to review the research status and latest progress of cathode materials for Li ion batteries, analyze their advantages and disadvantages, and discuss their application prospects in batteries. The review includes two kinds of cathode materials which are widely used and have the best performance in commercial uses for now: lithium iron phosphate (LFP) cathode material and ternary cathode material. The structure, properties, synthesis and modification methods are analyzed and summarized. Based on the analysis of the two materials respectively, the influence factors and countermeasures on the capacity, cycling life and safety of cathode materials for LIBs are emphatically discussed, and the future development is prospected, too.
Research on Calculating Activities from Binary Phase Diagrams of Ti-Bearing Blast Furnace Slag
Authors: Yao Chunling , Liu Zhennan , Liu Cong , Sun Ying , Li Yadong
Published: July 2023

Based on Kuo-chih Chou formulae of calculating activities from binary phase diagrams, some methods are proposed to improve numerical integration for the formulae. The component activity data of CaO-SiO2, MgO-SiO2 and MnO-TiO2 melts are calculated by the methods under the condition of regular solution’s assumption. The calculation results are in reasonable agreement with experimental data, and the average relative errors between calculated values by using the methods and experimental data are 18%, 18% and 11% respectively. This accuracy is within experimental error range of 10%~30% that Turkdogan proposed. The results show that the new methods are feasible in the practical application. Accordingly, the component activity data of CaO-TiO2, Al2O3-TiO2, SiO2-TiO2 and MgO-TiO2 melts at a given temperature and concentration are calculated by the proposed methods. The relative errors for these systems are comparable to the results of CaO-SiO2, MgO-SiO2 and MnO-TiO2 systems. So the activity data obtained can be used as basic data for thermodynamic study of Ti-bearing blast furnace slag.
Prediction of Chemical Composition Ratio of Ancient Glass before Weathering Based on LASSO Regression
Authors: He Xinyi , Chang Dengpan
Published: July 2023

Ancient glass is highly susceptible to weathering by the environment in which it is buried. During the weathering process, the internal elements of the glass undergo a large exchange with the environmental elements. This phenomenon leads to a change in the proportion of its composition. By analysing the chemical composition of ancient glass before and after weathering, the relationship between the changes can be identified, which means the original chemical composition can be predicted from the chemical composition of the glass after weathering. This is of great significance to the exploration and study of ancient artefacts. This paper first uses Spearman and Kendall correlation coefficient to identify the most influential factor on the weathering condition of glass from ornamentation, type and color, which eventually points to the glass type. This finding is secondly verified using a chi-square test. So the glass is divided into two types: high-potassium and lead-barium. By using the box plot to compare the chemical composition of high-potassium and lead-barium glass before and after weathering, it is found that there is a certain linear relationship between the chemical composition of glass before weathering and after weathering.LASSO regression was eventually applied to find the correspondence between the chemical composition of glass before and after weathering, thus enabling the prediction of the chemical composition of the glass before weathering.
Environmental Friendliness And Availability of Hydrogen Transportation and Future Improvements
Authors: Chen Yutong
Published: July 2023

As civilization develops, so does society's reliance on the earth's resources. New forms of energy are being created in order to limit the usage of nonrenewable resources. The utilization of new, clean energy sources decreases not just reliance on nonrenewable resources, but also pollutant emissions. Hydrogen is a sustainable and environmentally friendly energy source. Hydrogen transport is one of the most important applications of hydrogen energy in civilization. This research compares the differences in energy usage and emissions between hydrogen and traditional transportation. It also exhibits the economic benefits of hydrogen transportation and the adoption of hydrogen transportation in many nations. The current problems of hydrogen transport are analyzed and suggestions for improvement are given. The significance of this paper is to demonstrate the characteristics of hydrogen transport itself and to improve and popularise the use of hydrogen transport in the context of real-life situations.
Opportunities and Potential of CCUS Technology Advancement Under The New Energy and Carbon Neutrality Background
Authors: Hu Yijia
Published: July 2023

Since the Industrial Revolution, human society has gone through a booming development. Accompanied by roaring machines and towering edifices during industrialization, the expanding ozone hole and rising global temperature all ring the alarm for humans. With the strong crisis awareness of protecting the environment, people weigh more importance on the exploitation and application of CCUS technology. This article aims to perform a comprehensive review of the promising technology. Besides, considering new energy, as a crucial part and developing direction of the energy structure, it also hopes to offer a new perspective of combining CCUS technology with new energy. Carbon capture, storage and utilization, the three critical parts together constitute the CCUS. They are conducive to reducing carbon emissions, responding to climate change and transforming environmentally inefficient industries. Though there are several technical and economic difficulties like demanding reaction conditions and high cost, some pertinent and feasible settlements have emerged, which find creative ways like connecting with new energy. According to some cases and future trends, a coupling of CCUS technology and new energy will offer more probability concerning energy conversion and storage. Based on the exposition of these two subjects, the article put forward this assumption.
Environmental Pollution And Effect on Human Health And The Living of Creatures
Authors: Yang Zian
Published: July 2023

Pollution takes many different forms from the atmosphere to the oceans pollution is everywhere and is a global problem. Natural pollution is mainly divided into air pollution, water pollution and land pollution. Air pollution is mainly caused by small particles emitted from large amounts of energy. Water pollution is caused by human-made waste and its impending set of consequences. Land pollution is mainly caused by human activities, especially the use and management of different materials. These three types of pollution are interrelated, and the cause of one type of pollution may become the result of another. This paper discusses the main sources of pollution in the atmosphere, water and land, and the potential dangers that pollution may pose to humans and some other species that may be greatly threatened. The paper suggests that human should now manipulate their destruction of the environment, and act greenly to prevent the aggravation of the polluting process.
Construction of A Light Pollution Evaluation System Based on Subjective and Objective Integration Empowerment
Authors: Zhao Guanqiu , Fu Xiyuan
Published: July 2023

To address light pollution, this study presents an evaluation model designed to precisely quantify the extent of light pollution at a given location. The proposed model utilizes the Analytic Hierarchy Process and Entropy Weight Method (AHP-EWM) to conduct a combined weighted analysis of relevant indicators. Additionally, the Grey Comprehensive Evaluation Model (GCEM) is introduced to establish a broadly applicable measurement system. To demonstrate the model's effectiveness, it is applied to specific cities, with comprehensive explanations provided.
Measurement and Curb of Light Pollution Risk Levels
Authors: Liu Huiwen , Wang Ziyu , Huang Zhengzheng
Published: July 2023

Nowadays, light pollution has become a serious environmental problem. However, there are no clear indicators to assess the level of light pollution risk in a certain area. Firstly, we took 31 provinces and cities in China as the research object, and collected the data of seven indicators that affect the risk level of light pollution, then weighted them using Analytic Hierarchy Process (AHP). Secondly, we used the Topsis method for quantitative calculation, and classified the light pollution risk level into five levels: heavy light pollution (score>0.05), high light pollution (0.04<score<0.05), moderate light pollution (0.03<score<0.04), mild light pollution (0.02<score<0.03), and no light pollution (score<0.02). Thirdly, we linked the light pollution risk level to the Comprehensive Development Level Index (CDCI) of each province and city, and divided the cities into four categories according to the CDCI. Then we used analogy analysis to measure the risk level of light pollution in four land types: protected land(score<0.02), rural area (0.02<score<0.03), suburban area (0.03<score<0.04) and urban area (score>0.04). Fourthly, we propose three intervention strategies to combat light pollution: strengthen urban planning and management, better the ecological design of nightscape lighting and improve the material of glass curtain wall. Finally, we test its rationality and feasibility. Our model can analyze the light pollution risk level of other countries or even continents. This is conducive to the government's future planning and resource control of the region.
Prediction of La Niña Events Based on BP Neural Network Model
Authors: Deng Jie , Wang Xinfeng , Liang Haodong , Cai Siyuan , Shi Hao , Sun Ruoqing
Published: July 2023

As an extreme weather phenomenon, La Niña event will cause low water temperature in the equatorial eastern Pacific Ocean and abnormal longitudinal circulation in East Asia, resulting in widespread and continuous abnormal cooling of sea surface temperature in the eastern and central equatorial Pacific Ocean, which will cause frequent precipitation and flooding in the north and high temperature and low rainfall and frequent droughts in the south[1]. Therefore, it is particularly important to assess the damage and propose response strategies[2]. For the main countries involved in the global triple La Niña event, this paper selects four representative countries located in different regions to analyze, through descriptive analysis and graphical visualization, and selects the relevant index data of the last three years: monthly average maximum and minimum temperatures, monthly average precipitation rate, monthly average precipitation days, monthly average wind speed and monthly average water temperature, and finds that New York City and Brazil were affected by the triple La Niña event at the same time and were affected to a higher degree, and the temperature changes in Malasila and Jakara were stable, and the temperature effects brought by the triple La Niña event were smaller[3]. Then, a BP neural network model was established to predict the probability of future La Niña events in each region by modeling pressure, temperature, and salinity data, and it was found that a total of 110 regions would experience La Niña events in the future, with a general probability of 55%-60%..
Preface: 2023 International Conference on Energy Research and Environmental Technology (ERET 2023)
Authors: Geordie Oswald , Wan Jia
Published: July 2023

The 2023 International Conference on Energy Research and Environmental Technology (ERET 2023) was held during June 10-11, 2023 in Xi'an, China. This conference aims to bring together academic scientists, leading engineers, industry researchers and scholar students to exchange and share their experiences and research results about all aspects of energy research, energy materials, hydrogen and fuel cell, pollution control, environmental technology, and ecological system, and will discuss the practical challenges encountered and the solutions adopted. This conference becomes a platform for the delegates from different countries to meet and gain fruitful results.

Over 70 experts and researchers in related fields attended ERET 2023 to share their innovative ideas, discuss the state-of-art methods, exchange their experiences, and establish beneficial collaborations. Delegates enjoyed the good time they had in the conference. The papers collected for publication are of high quality and related to different areas. The conference ended successfully and all the delegates looked forward to attending the next meeting.

The success of ERET 2023 has relied on many people's efforts and contributions. Many thanks are extended to the colleagues and students for their assistance in organizing the conference. The reviewers have helped not only review the papers but also provide valuable comments to improve the quality of the papers. Their efforts and assistance are prominent in making the conference a success. The success of the conference is a natural outcome of their contributions and assistance.

The ERET Conference Committee

Xi'an, China
Jenseits von Textbeziehungen. Paul Celan bei Yoko Tawada
Authors: Russo Eriberto
Published: July 2023

This article aims at highlighting the metatextual relationships between the works of Yoko Tawada and Paul Celan. The analysis concentrates on Das Tor des Übersetzers oder Celan liest Japanisch and Paul Celan und der chinesische Engel and is carried out in the light of transtextual practices, starting from theoretical premises related to the act of reading (symptomatic reading – surface reading) and including the dimension of transculturality. The encounter between Tawada and Celan generates a multi-faceted textual space, in which texts from different cultures, having the German language as a common denominator, enter into dialogue with each other.
Dealing with Austria’s dark heritage and contemporary extremism. Peter Patzak’s adaptation of Helmut Zenker’s «Kassbach» (1979)
Authors: Gortat Jakub
Published: July 2023

This essay explores one of the films which dealt with the above-mentioned topics and had its cinematic release in the period under discussion – Kassbach, an adaptation of Helmut Zenker’s novel, which was made by Peter Patzak, a prominent Austrian director who passed away in 2021. In this respect, Kassbach would be a work that preceded numerous other Austrian films with a cinematic release in the 1980s and which, even before the Waldheim affair, would touch upon Austria’s difficult past. This article focuses on the film’s message that the lack of de-Nazification at the time, understood not only as a political and bureaucratic, but also as a psychological and social process, facilitates the establishment of right-wing radicalism.
SIOSAR VILLAGE COMMUNITY SOCIO-ECONOMIC ROLE IN REGIONAL DEVELOPMENT EFFORTS
Authors: Herijon Lingga Osland , Sirojulizam Sirojulizam , Purwoko Agus , Siddik Thoha Achmad
Published: July 2023

Regional development planning isaimed at achieving harmony and balance in development between regions in accordance with their natural potential and utilizing this potential in an efficient, orderly and safe manner. The purpose of this study was to see the role of socio-economic impacts on the planning of the Siosar tourism village area. This research method is a quantitative study by testing the hypothesis of the socio-economic influence of the community on regional planning in Siosar Village, Karo Regency. By involving 559 samples of family heads to be distributed research questionnaires and data processing using SEM-PLS. The results of the study stated that there is a Socio-Economic influence of the community (X) on Regional Development (Y) because it has a P value of 0.009 which is smaller than the significant level of 0.05.
Individual-tree growth system for even-aged Aleppo pine plantations in Aragón, Spain
Authors: RODRÍGUEZ-PUERTA Francisco , ALONSO PONCE Rafael , FERNÁNDEZ-TOIRÁN Luz M. , LIZARRALDE Iñigo
Published: July 2023

Aim of study: An individual-tree growth system was developed for Aleppo pine (Pinus halepensis Mill.) plantations.
Area of study: Aragón region (Northeast Spain).
Material and methods: Two datasets were used: Second and Third Spanish National Forest Inventories (104 plots with 1,678 trees), and ad hoc permanent plots (58 plots with 1720 trees, including 36 dead trees). Individual tree growth system was based on nine models. Different combinations of yield classes, initial stocking rates, thinning parameters, rotation periods, and age at first thinning were evaluated through the three most representative scenarios: timber production; soil conservation and biodiversity enhancement.
Main results: The nine models demonstrated a significant explanatory power for the data, with R2 values ranging from 0.71 to 0.99. These findings are consistent with previous research, indicating a strong goodness of fit. Additionally, yield tables were developed for the three prevalent silvicultural scenarios. To enhance usability, all models within the system were seamlessly integrated into a web-based application SIMANFOR.
Research highlights: To date, Aleppo pine forest managers in Aragon could only simulate silvicultural scenarios in natural stands. This study provides a new tool for plantations.
Research on reliability of complementary metal oxide semiconductor integrated circuit
Authors: Wu Chufan
Published: July 2023

Complementary metal oxide semiconductor (CMOS) devices are an important part of integrated circuit (IC), but in the application process, it has many reliability problems, such as negative-bias temperature instability (NBTI), electromigration (EM), time-dependent gate oxide breakdown (TDDB), hot carrier injection (HCI), etc. These reliability problems can affect the threshold voltage and mobility of the device. In order to improve the reliability of integrated circuits, these reliability problems are systematically studied in this paper.
Application and development of artificial intelligence in environmental health
Authors: Wu Tong
Published: July 2023

In recent years, major industries have been hit hard by the COVID-19 pandemic, and people have become more aware of issues such as environmental health. The development of computer programs, artificial intelligence (AI), has gradually entered the vision of researchers. The product of this technology can help people better manage and improve the current environmental conditions. This paper, through a method of literature review, aims to explain the development history of AI and its application in different fields such as the environment. Through the research, the paper concludes that artificial intelligence can observe in real time for long periods of time without getting tired like humans do. Based on the application of big data analysis and intelligent programs, artificial intelligence can make reasonable plans in a much shorter time than human beings. However, the solution is only based on the operation of the system. In the actual situation, there will be many obstacles. Therefore, it is still necessary for humans to make judgments based on the results of an operation rather than relying entirely on artificial intelligence. Complicated weather conditions can also make the results of the calculation inaccurate. So there will still be a need to evolve computer programs or for artificial intelligence to be able to calibrate the data it is monitoring from the past.
Application of corrosion resistance of FRP composites rebar in sea water sea sand concrete
Authors: Li Jiapeng
Published: July 2023

In recent years, Fiber Reinforced Polymer(FRP) has been widely used as a reinforcement material to improve the flexural capacity of beams and slabs, and FRP has good corrosion resistance. And because of the wide variety of fiber materials, so more than the role of ordinary steel.This paper will discuss whether it can replace steel to improve building durability in alkaline environment such as seawater sea sand concrete.Due to the lack of natural river sand and water resources, people have been trying to use sea sand seawater instead in recent years. But there are many safety accidents because of the corrosion of steel bars. Due to the good corrosion resistance of FRP, this paper discusses the feasibility of its service as a steel bar in marine sand concrete, including its failure characteristics after corrosion and the problems and improvement strategies when working with Seawater-Sea Sand Concrete(SWSSC). The research object of this paper is Glass Fiber Reinforced Polymer(GFRP) steel bar and Carbon Fiber Reinforced Polymer(CFRP) steel bar. Glass fiber and carbon fiber are widely used materials in current production activities, mostly in the field of mechanical manufacturing. Although engineering materials have been used in recent years, the time is short. In this paper, it is discussed that in the simulated pore solution of concrete stirred by seawater and sea sand and exposed in the environment of seawater immersion, by increasing the temperature to accelerate the reaction rate, it is found that the corrosion resistance of the two kinds of steel bars is very different, but the corrosion mechanism is similar, both of them are caused by the dissolution of the resin matrix. The fiber is bare, and the internal fiber actually has the bearing capacity, but the ability of the material to bear the force is still reduced due to the loss of the bonding of the resin matrix. Therefore, this paper proposes that it is possible to find a more corrosion-resistant resin matrix or add a layer of medium at the interface between the fiber and the matrix to maximize the role of the fiber.
Performance of recent transition metal cocatalysts under hydrogen evolution reaction
Authors: Liu Taizhe
Published: July 2023

In case clean and renewable energy on earth is urgently needed, converting solar energy into hydrogen is applied. Due to its high efficiency and low cost, photoelectrochemical water splitting (PEC) has become a popular strategy. To achieve this, non-noble metal electrocatalysts as cocatalysts are used to enhance the performance of PEC water splitting. In this review, the recent procedure of the synthesis, performance measurements, and the result of MoSx, TiO2/NiOx, Pt/TiO2/InAs NWs, and CoS are introduced. These materials show a fit onset potential, good current density, and small charge transfer resistance for hydrogen evolution reaction (HER). Compared with TiO2/NiOx, Pt/TiO2/InAs NWs, and CoS, MoSx is the only stable under acidic conditions. Some suggestions for future research on transition metal-based electrocatalysts are also provided.
The mechanism and design strategy of metal-organic frameworks in drug delivery
Authors: Song Wanpeng
Published: July 2023

In the field of drug transport, the traditional drugs used for drug delivery are organic, inorganic, and complex. The organic polymer system and liposome system can have good biocompatibility, but the porosity of the polymer cannot be determined, and the medicine cannot be given a controlled release. In contrast, inorganic materials such as microporous zeolite and mesoporous silicon can achieve controlled drug release due to their definite relative porosity, but their drug-loading capacity and poor biocompatibility cannot be widely used for drug delivery. The materials of the new MOFs can synthesize the advantages of the two, with controlled drug release, biocompatibility, and good flexibility, that is, the performance of targeted drug delivery. This paper focuses on the mechanism of MOFs in drug transport and the related applications of MOFs in transporting small molecules, macromolecular drugs, and the surface modification methods of MOFs. The present paper concludes that MOFs can be widely used to transport macromolecules and small-molecule drugs and that drug targeting can be improved by surface modification. This paper hopes to provide suggestions and guidance for designing future MOF materials for DDS, to promote the application efficiency of nanomaterials in relevant aspects, and to achieve efficient, highly selective and highly stable drug delivery.
The design of metal-organic frameworks (MOFs) in hydrogen storage applications
Authors: Zhou Peiqi
Published: July 2023

Carbon-based energy, when incompletely burned, produces toxic gases, and the earth's environment is irreversibly negatively affected. As a kind of clean energy, hydrogen energy has abundant resources and can be recycled, which is the focus of attention in the 21st century. However, hydrogen production, storage, transport and safety are major problems for the industrialization and large-scale commercialization of hydrogen energy technology. As an emerging nanoporous material, metal-organic frameworks (MOFs) are formed by self-assembly of inorganic metal ions and organic ligands, which have many unique characteristics beyond traditional porous materials, such as the high reversibility and high adsorption and desorption ability of hydrogen gas, which endows MOF materials a broad prospect of application. This paper introduces the MOF materials' application in hydrogen storage and comprehensively summarizes the decisive factors of MOF materials' performance in hydrogen storage. The issue prospects and suggestions are also given accordingly for the future research and promotion of MOF-based materials in hydrogen storage.
Several approaches of making photonic crystal anti-counterfeiting devices for banknotes
Authors: Jia Zhanbo
Published: July 2023

The popularity of counterfeit banknotes in the market will cause serious inflation. Under such circumstances, prices are soaring and paper money is seriously devalued, causing harm to people's livelihood. In recent years, the global circulation tendency offake banknotes has become larger, and counterfeit banknotes have become more and more difficult to distinguish, so several advanced photonic crystal anti-counterfeiting technologies emerged. This review will introduce the working principles of colloidal PC patterns and approaches of making photonic crystal anti-counterfeit banknotes. Then analyze the advantages and shortcomings of colloidal PC patterns.Finally ,make a conclusion to discuss the development prospects and possible challenges they may face.
Estimation of excess Gibbs free energy of multicomponent biofuel mixtures of Butan-1-ol using machine learning methods based on modified Raoults law models
Authors: Buenaobra N. M. , Madlangbayan G. A. , Ong K. T. A. , Rovillos L. A. , Jr. B. Doma
Published: July 2023

In biofuels, the excess Gibbs free energy of mixing is a very important thermodynamic property as it is used in evaluating the efficiency and sustainability in terms of energy conversion. Multiple biofuel systems containing butan-1-ol were examined with oxygenate ether additives such as MTBE and DIPE using isothermal vapour-liquid equilibrium data at different temperatures (298.15K, 313.15K, 318.15K). Two activity coefficient models, Wilson and van Laar model were compared by determining the bubble pressure and vapor mole fractions of each system using Modified Raoults Law and Machine Learning techniques. Besides, mole fractions and activity coefficients were used to identify the excess property. Results showed that Wilson model is appropriate for all the biofuel systems when using the Artificial Neural Network (ANN) resulting in an MSE of 3.2010e-09, 4.6792e-10, 1.6186e-10, and 5.3461e-07. In addition, van Laar model is more acceptable when Rational Quadratic GPR or Fine Tree algorithm were used with an average RMSE of 0.005820.01 and 0.020950.03 respectively. Lastly, the generated data for both activity coefficient models were also used to estimate the systems excess Gibbs free energy of mixing across varying mole fraction of its components.