bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Hydrocarbon Geochemical Anomalies in the Dailekh Region of Nepal
Authors: Tan Jie , Zhou Qiming , Huang Xueqiang , Zhao Junhong , Li Li , Zhao Like
Published: June 2024

Analyzing the geochemical characteristics of hydrocarbons in Nepal is important to promote the exploration and development of hydrocarbons in Nepal. In this thesis, significant hydrocarbon geochemical anomalies in the Dailekh area of Nepal were revealed by comprehensive analysis of 12 indicators, including soil acid-dissolved hydrocarbons, post-generated carbonates (ΔC), conductivity (Ks), and adsorbed phase mercury (Hg). The analysis shows that the correlation between the indicators is good, and two anomalous zones are identified, located in the northwest and west-central part of the survey area, respectively, and the indicator anomalies in these zones show ring-in-ring top halo characteristics, especially Hg shows weak ring-strong top halo characteristics. These anomalies reflect the real geochemical activity information of the reservoir and verify the validity of this set of geochemical indicator combinations. The study further shows that these anomalies are mainly formed by the escape of underground oil and gas to the surface, and the favorable areas of anomalies No. I and No. II are presumed to be oil-type oil and gas reservoirs by the clustering analysis and hydrocarbon ratio method, indicating that this area has a good prospect for oil and gas exploration.
U.S. Imports Price of Goods Forecasting by Customs Basis from China using SARIMA Model
Authors: Li Yanrui
Published: June 2024

Changes in the import price of goods will have an influence on the global economy and trade, corporate decision-making, and many other aspects. Therefore, the aim of this research is to forecast the future customs prices of US imports from China. The data comes from the Bureau of Economic Analysis. It can provide an important reference for enterprises, government, and academia to make better decisions. In this paper, due to the strong seasonality, the Seasonal Autoregressive Integrated Moving Average (SARIMA) model is a common technique that is generally used in analyzing and predicting seasonality and stationary time series data. Using the Sarima model to predict U.S. imports of goods from January 1986 to December 2016 and to compare the predicted data with original data. To identify the best model and find out the highest accuracy of the model, this paper utilizes the Grid Search method and calculates Akaike's Information Criterion (AIC), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and adapted MAPE (AMAPE) value as the criterion for selection. The result shows that in the next six months, the amount will still be seasonal, but the overall trend will show small fluctuations and will not change much.
Diffusion of the Air Pollutants Based on Random Walk
Authors: He Siyuan
Published: June 2024

As a matter of fact, air pollutants prediction serves as a key issue for environment analysis in recent years. In consideration of the stochastic motion of the air particles, it is crucial to implement numerical simulation tools to analyze the random effects. With this in mind, random walk is utilized as a typical scheme to simulate the diffusion process incorporated with concepts of Monte Carlo simulations. On this basis, this paper will present a systematical analysis for simulation of pollution diffusion by means of random walk. To be specific, the calculation principle, formulae and process will be demonstrated. Subsequently, the simulation results will be given in the meantime. In addition, the application scenarios will be discussed and illustrate. At the same time, the evaluations of the results will also be presented and the current limitations will be estimated with suggestions for further research. Overall, these results shed light on guiding further exploration of air pollution.
Optimization of vegetable commodity pricing based on particle swarm algorithm and sparrow search algorithm
Authors: Sun Xiaofeng , Lv Yulei , Li Hao
Published: June 2024

With the improvement of people's living standards, small and medium-sized supermarkets have become important places for people to buy groceries in their daily lives due to their complete range of product categories, guaranteed quality, and accessibility to residential areas. However, due to the characteristics of vegetables being greatly affected by weather, difficult to store, and having a large regional preference, most small and medium-sized supermarkets need to purchase them daily and maximize profits within limited sales space. Therefore, building a model to meet the needs of short-term pricing and replenishment strategies for small and medium-sized businesses has important practical significance. This article establishes a multi-objective programming model based on historical sales data of supermarkets, and uses sparrow search algorithm and particle swarm optimization algorithm to improve the accuracy of results, making scientific and reasonable strategic planning for small and medium-sized supermarkets to purchase goods.
Research on the optimisation problem of goods allocation in logistics network based on simulated annealing algorithm
Authors: Dai Junchao , Wang Jiangrui , Yang Mengzhou , Wu Jun , Yue Xiangjun , Zhang Hongju
Published: June 2024

When certain logistics nodes are out of service, based on the processing capacity of the remaining logistics nodes and the transport capacity of the transport routes, it is necessary to design a logistics adjustment scheme to minimise the impact of logistics node shutdown on the logistics network and to guarantee the normal operation of the logistics network. This paper establishes a cargo distribution optimisation model to study the cargo adjustment scheme after the shutdown of logistics node DC5, and uses the simulated annealing algorithm to solve the problem with the objective function of minimising the total amount of cargo change. The final result is: in all the adjusted routes, there is no overloading, and a total of three routes have a load rate of 100 per cent, respectively: 69→8, 69→14, 69→62, of which the load rate of 0 accounted for 66.49 per cent of the routes, and the average load rate is 5.29 per cent. This study helps to improve the emergency response capability of the logistics system and provides scientific support for cargo distribution decisions.
Bioinformatics Analysis of Core Genes Related to Sarcopenia
Authors: Lin Qing , Wei Fengxu
Published: June 2024

Objective: To analyze the genes related to the pathogenesis of sarcopenia (SA) and find the potential therapeutic targets. Methods: GSE1428 data set downloaded from GEO gene expression omnibus, GEO) was taken as the analysis object. The data were standardized by R software, and the differential genes were screened. The GO and KEGG function enrichment analysis of the differential genes was carried out by Metascape, and the PPI analysis was carried out by String. The results were imported into Cytoscape software to screen out the core genes, which were imported into BioGPS database for tissue localization. Results: 117 differential genes were obtained, including 54 down-regulated genes and 63 up-regulated genes. GO and KEGG analysis showed that GO was mainly enriched in ethanol reaction, carboxylic acid transport, cell secretion regulation, vitamin metabolism, leukocyte chemotaxis regulation and bone marrow cell differentiation regulation, while KEGG was mainly enriched in viral carcinogenesis pathway. There are 108 nodes and 44 connections in the PPI network. According to the PPI results, Cytoscape screened out core genes such as RPE65, TOPORS, IMPG2 and IMPDH1, among which RPE65, TOPORS and IMPDH1 were down-regulated and IMPG2 was up-regulated. The localization of gene tissue suggested that RPE65 was located in retina. Conclusion: Screening the core genes and related signal pathways is helpful to understand the pathogenesis of SA and provide new ideas for drug therapy research of SA.
Diverse Applications and Eco-Friendly Catalysts for Michael Addition Reaction
Authors: Chen Ziyang
Published: June 2024

Michael addition reaction, renowned for its mild reaction conditions facilitated by the absence of small molecule release, has become indispensable in creating numerous substances. It is a focal point in chemical research, fostering avenues for significant advancements. In tandem, the rise of green chemistry has emerged as a pivotal approach in modern chemical research, emphasizing pollution prevention at the source rather than remediation post-contamination. This innovative methodology advocates for developing technologies that substantially mitigate or eliminate waste detrimental to the environment, ensuring that the chemicals synthesized do not negatively impact the ecosystem. This principle has garnered widespread acclaim and utilization among researchers, heralding a new era of environmentally conscious chemical production. This paper meticulously explores the applications of various Michael addition reactions in green chemistry, spotlighting the integration of specialized green catalysts, including enzyme catalysts, in the process. While delineating the multifaceted applications of these reactions, it critically evaluates the current limitations of existing catalysts, thereby setting the stage for prospective research trajectories. As the author delves deeper into this domain, the paper accentuates the necessity to cultivate innovations that amplify the efficiency of these reactions and adhere to the principles of environmental preservation, thus fostering a harmonious balance between scientific progression and ecological sustainability.
The Development and Prospects of ESG Implementation in Chinese Enterprises
Authors: Xu Xinyu
Published: June 2024

The fundamentals of Environment, Society, and Governance (ESG) are becoming more essential for organisations across all industries [1]. The United Nations Global Compact established governance in 2004 as a collection of principles and criteria used by firms to examine and show their commitment to environmentally friendly growth, social accountability, and ethical business practises [2]. To attain their goals, Chinese businesses must embrace low-carbon business strategies. Increasing carbon emissions to zero by 2030 and achieving carbon neutral by 2060 [3]. China's Ministry of Ecology and Environment (MOE) has lately been able to execute the Measures for Enterprise Environmental Information Disclosure in line with the Law. This programme attempts to increase environmental transparency and responsibility across industry. This programme intends to increase environmental transparency and responsibility across industries [4]. These include key polluting enterprises, enterprises subject to mandatory liquidation review, publicly traded companies and their subsidiaries at all levels, businesses issuing bond issues and non-financial corporate debt financing instruments, and other organisations required by law and regulation to report environmental information. In recent years, China has experienced an increase in the quantity of unfavourable news articles as corporations prioritise turnover over all other aspects. For example, the "Wei Zexi Incident"[5], which occurred between April and May 2016, involved fraudulent medical advertisements as well as the "maliciousness" of the search platform bidding system, resulting in online search service companies' inability to meet their corporate social responsibility (CSR). Furthermore, many online community operators highlight hotspots and controversies in their algorithms, and related industries are under strict regulatory scrutiny; the public is very dissatisfied with the business behaviour of companies that are solely concerned with their own profitability, and the introduction of negative news frequently leads to regulatory action [6]. The public is seeking for a more useful valuation criteria than a single guide to company profitability, and ESG represents that value proposition. In this study, analyses the development prospects and feasibility of ESG concepts in Chinese companies are analyses, and introduces mainstream international ESG assessment systems and examples of ESG implementation in Japanese companies. The study also summarises the strengths and weaknesses of ESG implementation in Chinese companies are also summarized and puts forward.
Heterogeneity In Stock Price Forecasting-Based on the ARIMA-GARCH Model And PCA-LSTM Model
Authors: Cheng Sirui
Published: June 2024

Financial theory suggests stock prices are mainly influenced by factors such as interest rates, market behavior, technical indicators, and firm value. Traditional approaches to stock price forecasting have been augmented by machine learning algorithms and time series models. Deep learning has experienced rapid development in the field of time series analysis and is becoming more mature. Therefore, this article delves into two prominent prediction methods: the ARIMA-GARCH model and Long Short-Term Memory network to compare their prediction performance and to analyze the heterogeneity in the effectiveness evaluation. The combination of the ARIMA and GARCH models makes it possible to account for both short-term fluctuations and long-term trends. And LSTM networks can capture the temporal relationships and diversified features of data, making it a popular choice for financial time series analysis. This study examines the forecasting of daily closing prices of representative individual stocks in Shanghai and Shenzhen A-shares and analyzes the factors that may cause heterogeneity in the prediction results. In addition to being affected by the chosen forecasting indicators, the differences in the forecasting results of individual stock prices can also be related to the company's economic information. Differences in the market structure of the industry and the effects of policy implementation can also lead to differences in forecasting results. These heterogeneity analyses provide references and suggestions for selecting models and variables in the financial field to improve prediction effectiveness.
Big Data Analysis for Consumer Behavior: Evidence from User Segmentation, Recommendation and Opinion Monitoring.
Authors: Chen Quanfu , Lei Qianru , Zheng Ailun
Published: June 2024

As a matter of fact, digitisation in the 21st century has brought with it an infinitely growing volume of data in recent years. On this basis, the cost of storing data has become less expensive than cleaning it, marking the dawn of the Big Data era. On this occasion, for consumer behavior, big data analytics (BDA) can greatly improve the efficiency of sub-consumer behavior analysis as well as the volume of data, making the research results more accurate. With this in mind, this paper will analyze the applications and implementations of bigdata analysis in the field of consumer behavior. To be specific, this paper is divided into three main parts: first, a brief overview of the background of consumer behavior and BDA; second, a detailed description of the three BDA applications in consumer applied science, and finally, an outlook on the future of BDA in this field. Overall, these results shed light on guiding further exploration of consumer behavior analysis.
Current Status and Demand Patterns of Shared Bicycles in Jersey City
Authors: Yan Mengshi
Published: June 2024

This paper, using New Jersey as a case study, examines the spatial allocation issues of shared bicycles. Utilizing data from New Jersey City for the months of January to July 2023 and employing Python scientific computing libraries, we conducted kernel density analysis to generate visualizations and analyze demand patterns in the selected New Jersey shared bicycle data. Three key findings emerged from our research, categorized as geographical demand, temporal trends, and cross-regional cycling. Regarding the geographical demand, it was evident that the demand for shared bicycles in the city center exceeded that at the city's outskirts, potentially linked to urban planning within the city. The temporal trends, showed a steady increase in bicycle rides to New York from January to July, with the peak demand occurring during the summer months. This aligns with existing research and common knowledge, as riders tend to prefer cycling in more comfortable weather conditions, which are prevalent in the summer. The phenomenon of cross-regional cycling is particularly intriguing, the destination points were often in New York. The significance of this phenomenon lies in the potential resource shortage within the shared bicycle system if a large number of bicycles are ridden in New Jersey but left in New York for extended periods. This issue could result in spatial allocation challenges and may also incur substantial costs for bicycle redistribution and management by the government. Therefore, this paper presents recommendations and suggestions for coordinating the allocation of shared bicycles between New Jersey and New York City.
Momentum analysis of tennis players based on entropy weight method and personal’s correlation coefficient
Authors: Wang Cong , Wang Kairan , Hu Yumo
Published: June 2024

In sports, a player or team may feel "powerful" at a certain stage of the game, and the momen-tum of the game may be shifted to a certain side, and the analysis of game momentum and player momentum has been an important topic in the field of sports research. In this paper, we use the data from the final of the 2023 Wimbledon Tennis Championships to first construct a comprehensive model that includes the analysis of players' performance during the match, in order to understand the reasons for the shift in the momentum of the match and its impact on the final outcome of the match. The model utilizes a modified entropy weighting method to quantify the performance of tennis players, and constructs "momentum" characteristics to quantify the cumulative advantage among tennis players and its effect on the momentum of the match. The relationship between the performance of the players and the match result is then analyzed by using the personal correlation coefficient, and a strong positive correlation is found between the two, which indicates that momentum and momentum play a key role in de-termining the winner of the match.
Research on insurance model based on different mathematical models and algorithms
Authors: Liao Cailin , Hu Nan
Published: June 2024

This article presents a risk assessment and prediction model for specific areas using the ARIMA model, entropy weight method, and AGNES algorithm. The model assists insurers in determining coverage and adjusting premiums based on economic losses predicted by the ARIMA model. It also aids real estate companies in deciding whether to develop in certain areas. The ERM model considers human, weather, and geographical factors to assess risks and predict potential property damage caused by extreme weather. The AGNES algorithm clusters similar samples to identify regions with higher risks. This helps real estate companies make informed decisions about development projects. The entropy weight method is used to adjust insurance premiums by calculating changes in regional risk coefficients. Continuous monitoring and analysis of risk coefficients improve risk assessment accuracy and enable reasonable premium adjustments.
The Evolution and Research Prospect of TOD Theory
Authors: Chai Ziyi
Published: June 2024

The essay explores the evolution and research prospects of Transit-oriented development (TOD) theory in sustainable urban planning. The TOD theory emphasizes integrating land use and transportation planning to create walkable communities around efficient public transit systems. The essay discusses the background and significance of TOD, highlighting its relevance in a rapidly urbanizing world. It delves into the development of TOD theory, its practical applications, and the consensus and challenges it faces. The case studies of Denver and Chengdu exemplify the adaptability of TOD principles to diverse urban contexts. Furthermore, the essay explores the potential of integrating emerging technologies into TOD research, showcasing how advancements like big data analytics and artificial intelligence can refine urban planning strategies. This exploration underscores the importance of TOD theory as a strategy to shape sustainable and flexible urban environments.
Measures Taken to Reduce the Dominant Air Pollutant
Authors: Tan Siyuan
Published: June 2024

In recent years, with the growing concentration of air pollutants, as for how to improve the air quality, draws the attention from all over the world. In general, there are two sources of air pollutants, one is natural disasters, the other is improper human activities. The air pollution caused by human activities, has emerged as a huge challenge on various aspects, including climate change, health impact to human body, living conditions for flora and fauna, ecosystems damage and the economy loss. In comparison, the solutions to reduce the density of pollutants and improve the air quality are divided into separate aspects which are intersected with different social and environmental situations. The aim of setting and publishing of the laws and legislations is to regulate the daily human behaviors which are possible to cause the air pollution. The analysis for the consistence of the major air pollutants will be beneficial to figure out the direction of how to improve the air quality and how hazard of each air pollutant would be. For instance, PM2.5 will primarily cause the decrease of the clearance in the air, further cause the increasing of human diseases such as respiratory and cardiovascular diseases. The utilization of advanced technology would not only improve the efficiency of reducing the air pollutions, but also make the future disasters more foreseeable so that it is now possible to prevent and block them. All these listings are aiming to find the future trend of air quality and improve the measures we are taking currently.
Social Issues Caused by Lithium-ion Batteries
Authors: Zhang Peisen
Published: June 2024

Human civilization is often intertwined with natural resources, and with the progress of human civilization, the demand for resources continues to increase. For centuries, oil, gas and coal mines have been the main resources for industrial production. However, while bringing vigorous productivity to human beings, it also brings irreversible harm to the environment. The letting of the carbon dioxide causes the global warming, the using of oil produce much toxic gas which cause the atmosphere pollution, and so on. Battery is a major new energy source invented by human beings, and safety, cost and work efficiency are worth considering. Thus, this paper is focus on summarizing the working principle, the application, the main issues and the future forecast of the lithium-ion batteries. This paper firstly introduces the battery itself. Then this paper will talk about the advantages and disadvantages, which is followed by several main issues. Finally, I am going to dope out the of the lithium-ion batteries. All in all, the research significance of this paper is to summarize the social problem and sort out its solution and application feasibility.
Evaluation Of Property Insurance Risk Caused by Disasters Based on Analytic Hierarchy Process and Entropy Weight Method
Authors: Lv Haolin
Published: June 2024

In recent years, the frequent occurrence of natural disasters and extreme weather events has become a crisis for insurance companies, as the choice of underwriting policies can greatly impact their interests. In order to comprehensively assess the risks underwritten in a specific region, this paper establishes a model for evaluating the insurance risks of natural disaster property. Firstly, it analyzes the premium amount based on the relationship between demand and price. Then, by employing multiple indicators, it evaluates the severity of disasters in a region using Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM). Furthermore, it utilizes the Grey Prediction Theory to forecast the frequency of disasters and assess the compensation in that region. Finally, the underwriting risks are analyzed by combining premiums and compensation. Japan and Chile are taken as examples in this study, both exhibiting high underwritten risks, with Chile surpassing Japan. Because Japan has more Emergency Relief Funds, a higher level of disaster prevention education and a significantly larger population than Chile, resulting in smaller losses from disasters and higher insurance payouts.
Research on Roof Cutting and Pressure Relief Technology of Deep Hole Pre-cracking Blasting
Authors: Qin Jilong , Zhu Peng
Published: June 2024

The dynamic pressure gob-side entry is affected by the whole mining process of the working face, and the cause of the large deformation is the additional stress generated during the rotary sinking process of the key block. Therefore, in order to alleviate the deformation of surrounding rock of roadway along goaf. The deep hole pre-splitting blasting roof cutting pressure relief method is used to relieve the pressure of the test roadway. In this study, finite element and discrete element models were established by means of numerical simulation and theoretical analysis, and the law of influence of cutting top height and Angle on roof cutting effect is studied. The optimal cutting height and angle are 15 m and 10° towards the gob, respectively. The industrial test results show that the deformation of surrounding rock of the test roadway is controlled within a reasonable range after pressure relief, and the roadway section meets the production demand.
Methods to Find the Closed form of ζ(2) and ζ(2n)
Authors: Dong Wenfei
Published: June 2024

Finding the closed form of the celebrated special function is not an easy task. For this purpose, this article deals with the Riemann zeta function. The Riemann zeta function is one of the most important functions in mathematics, and it mainly relates to the area of analytic number theory. Based on this function, the Riemann hypothesis was also proposed. This function is defined as , with . In this article, several methods are provided to calculate specific values of Riemann zeta function. Specifically, the value when  and, more generally, when . Finding the value of the function at two was used to be a world-class challenge, named Basel Problem. No one had solved this problem until Euler appeared, and since then many ways had appeared. In this article, two ways to solve the Basel problem are firstly provided. Afterwards, method involving Bernoulli numbers to calculate all the -values at even arguments is also shown.
Feasibility Analysis of China's Electricity Supply and Carbon Neutrality Using LSTM-ARIMA Model
Authors: Guo Chang , Bao Tianyi , Ma Ding
Published: June 2024

This article focuses on the modeling and algorithm design of China's photovoltaic power generation industry. This article mainly uses ARIMA-LSTM to study the influencing factors of China's power supply and predict its development trend; Using the GPCA-EWM evaluation model to evaluate the possibility of constructing a photovoltaic power station in a certain area. In terms of factor selection, The paper integrated the five major indicators of economy, production, consumption, transportation, and population for factor selection and data acquisition. Finally, the paper obtained feasibility score maps for various provinces in China, And based on this analysis, it is more suitable to build photovoltaic power stations in the northwest region of China.
A Study on Pricing and Replenishment Decision of Vegetable Commodity Based on Demand-Volume-Cost Model
Authors: Li Xufeng , Huang Qingxin
Published: June 2024

This paper aims to develop pricing and replenishment strategies for vegetable commodities in superstores. The characteristics of perishability, short life cycles, and other factors make it challenging to determine pricing and replenishment decisions. The study proposes the use of a weighting method to define the price for each vegetable category. Additionally, sub-models are established for market demand prediction, price-volume relationship, and cost-plus pricing. The ARIMA time series forecasting model is used for market demand forecasting, while a logarithmic model, fitted non-linearly using the L-M algorithm, is employed for the price-sales model. Through the derived sub-model expressions, the optimal replenishment volume and markup rate that maximize the superstore's profit are determined. The calculated maximum profit from selling vegetable goods in the coming week is 2179.68 yuan. In this paper, a profit model is constructed by considering the relationship between demand, sales volume, and cost, which can provide suggestions for superstores to improve the economic efficiency of vegetable products.
Application of Bioenergy and Its Impact on Sustainable Development
Authors: Ni Ziqiao , Wang Yangyang , Yang Zhenhe
Published: June 2024

In recent years, the rapid growth of global energy demand and the irreversible impact of traditional fossil energy on the environment have made the need for sustainable energy increasingly urgent, and bioenergy has attracted much attention as an important renewable energy source. However, bioenergy has received far less social attention than other energy sources in China. In this paper, starting from the types, benefits use, and uses of bioenergy development at home and abroad, we study the current misunderstandings and challenges in sustainable development and put forward countermeasures for the sustainable development of clean, low-cost, and high-efficiency bioenergy industry in China. As a kind of clean energy, bioenergy is widely used in power generation, transport, and chemical industries, and thus has economic and social benefits that cannot be ignored. The benefits of bioenergy can only be maximized by solving the problems of coordinating the supply of feedstock resources and food security, introducing internationally advanced technologies and facilities, and improving relevant policies laws, and regulations. This paper broadens the field of research on bioenergy and sustainable development at the macro level and provides new development ideas for China's bioenergy development. Through in-depth research on bioenergy technology, strengthening international cooperation, and optimizing the policy environment, the bioenergy industry can be promoted to develop in a healthier direction and create a better future for human society.
Research On Valuation System with Chinese Characteristics Based on Comprehensive Evaluation Model
Authors: Yang Tianxin
Published: June 2024

Exploring and establishing a valuation system with Chinese characteristics is of great significance to promoting the better performance of the market resource allocation function. This article comprehensively analyzes the valuation system with Chinese characteristics based on a variety of models. First, by analyzing relevant research reports and policy documents, four first-layer characteristics of the special evaluation are selected, namely policy orientation, value investment, industry characteristics, and capital allocation, and then multiple second-layer indicators are selected. The analytic hierarchy process is used to obtain the weights of indicators at all layers, and the characteristic indicators with the smallest weights are eliminated. Finally, after using entropy weight method to correct the weights, eight secondary characteristic indicators were obtained: strategic conformity, reform potential, price-earnings ratio, return on net assets, subsidy preferences, whether it is a state-owned enterprise, industry concentration, and early investment, and a set of appropriate evaluation index systems for medium and special evaluations were established. , define the special evaluation index.
Research Progress of potential solar cells alternative
Authors: Gong Botao
Published: June 2024

With ongoing advancements in solar cell research, new generations of solar cells are increasingly demonstrating superior efficiencies. However, the application of theoretical advancements to practical experiences has seen limited realization, with significant barriers being encountered, notably in the realms of commercialization and manufacturing of novel cells, such as perovskites. This paper analyzed the potentialities and advancements of emerging solar cell technologies, providing a nuanced comparative analysis to assess the technological progression and potentials inherent in them. The exploration commences from the first-generation silicon crystalline cells and navigates through to the innovative third-generation perovskite cells. This journey reveals distinct material properties and sophisticated optimization strategies, each precisely focused on achieving enhanced efficiency. To facilitate a deeper comprehension of the limits and distinctive advantages of each solar cell type, an extensive analysis of their industrial development processes and specific technological attributes is undertaken. A representative comparative illustration will be furnished for each solar cell type, accentuating their stability, material characteristics, supply dynamics, developmental statuses, and environmental impacts. This investigation encompasses a foundational analysis across the three generations of solar cells, attributing to each generation a unique cell type to illuminate possible development directions and existing challenges, thereby, defining prospective pathways to navigate current constraints. The commercialization challenges inherent to alternative solar cells are elaborated, providing reflections on the probable future research trajectories and industrial manufacturing approaches. This discourse aims to afford a thorough and insightful understanding of the potential breakthroughs and impediments in the evolving landscape of solar cell technologies, balancing technological advancements, practical implementations, and environmental considerations.
Effect of COVID-19 Towards Cosmetics in China
Authors: Chen Pengyu
Published: June 2024

The prevalence of COVID-19 had a certain impact on many industries, including the cosmetics market. Accessing this study, we aim to investigate the cosmetics market during COVID-19 and to quantify total profit of this market. We have collected and organized relevant sales data on the Chinese cosmetics market during the epidemic period from 2019 to 2022. Besides, this paper used single factor equation analysis and linear regression methodology to test the collected data. Further more, This paper has depicted the constantly changing characteristics of this industry through statistical analysis of the data. This paper finds the correlation between the cosmetics market and economic data. There is a strong positive correlation between the growth of certain economic data and the growth of the cosmetics market. The findings reveal that the demand for cosmetics did not decrease during the epidemic. Also, the non-contact consumption methods had increased. The study clearly demonstrates the changing characteristics of the industry, and identifies key factors affecting the development of the industry.
The Research of Influence Factors that Contribute to the Airplane Passengers Satisfaction
Authors: Du Yining
Published: June 2024

This paper examines the factors that most significantly influence airline passenger satisfaction using a Binary Probit Regression model. The study uses comprehensive data from over 120,000 international airline passengers, focusing on 10 key factors: age, flight distance, departure delay, arrival delay, ease of online booking, check-in service, online boarding, gate location, on-board service, and baggage handling. The research fills gaps in previous studies that were either too limited in scope or overlooked certain potential factors influencing passenger satisfaction. Findings reveal a significant relationship between passenger satisfaction and flight distance, arrival delay, online booking and boarding, check-in and onboard service, and baggage handling. No correlation is found with age, departure delay, and gate location. The paper emphasizes the importance of digital transition, front-line services, and operational reliability. It achieves an overall prediction accuracy of 85.39%, reflecting a robust model. Despite this, it suggests continual refinement of the model with a more comprehensive dataset for deeper insights into passenger satisfaction dynamics. The outcomes offer airlines valuable knowledge to enhance service quality and establish long-lasting relationships with passengers.
Evaluating Momentum-Weighted LSTM Models for Predicting Tennis Match Outcomes
Authors: Hua Heng , Sun Wenqian
Published: June 2024

In the realm of sports competition, particularly in skill- and strategy-centric sports like tennis, momentum stands out as a pivotal factor influencing match outcomes. Conventional match analysis methods often fall short in capturing the nuanced shifts in momentum and their profound impact on players' psychological states and performances. To precisely forecast momentum changes and their repercussions, we introduce two integrated concepts: momentum and a player's point-winning probability. Weight calculations are optimized through cross-validation, and a model predicting match trends is formulated using the LSTM neural network theory. The results underscore a direct correlation between momentum swings and players' scores, significantly shaping match outcomes. Evaluation metrics reveal the model's high accuracy (87.06%) and minimal loss (0.6655) on the test set, attesting to its robust predictive capabilities. This research not only advances our understanding of momentum dynamics in sports but also showcases a methodological approach with potential applications across various disciplines, fostering a more nuanced comprehension of competitive dynamics.
Design and Simulation Analysis of Green Power Trading Mechanism in Power Market
Authors: Chen Mingyuan , Xuan Peizheng , Li Ling , Yang Xiao , Cheng Lanfen , Yang Youhui , Zhuo Yixin , Zhu Jisong
Published: June 2024

In order to solve the transaction problems of renewable resources such as wind and solar in the mid-to-long term market and spot market conditions, a corresponding green electricity transaction mechanism and its quantitative analysis model are proposed. This paper analyzes the development and current situation of green power trading in my country, analyzes the green power trading mode and trading process in the medium and long-term power market and spot market, establishes a green power trading model, and simulates the green power trading volume. It also compares and analyzes the relationship with the green certificate and CCER, explains the advantages of the transaction mechanism proposed in this paper, and finally demonstrates it by simulation analysis.
Analysis of Planet Searching and Detection Based on Radial Velocity, Direct Imaging and Transit
Authors: Zhang Jian
Published: June 2024

As a matter of fact, significant progress has been made in the discovery and research of exoplanets over the years. In reality, the discovery of thousands of exoplanets outside the solar system are achieved based on the state-of-art approaches as well as detectors. With this in mind, understanding the detection scenarios of the exoplanets are crucial to delve deep into astrophysics as well as cosmology study. Among various approaches, the three prominent techniques used in this pursuit are radial velocity, direct imaging, and transit method. On this basis, this study comprehensively analyzes these methods. To be specific, this study delves into their principles, applications as well as detection features. According to the analysis, the limitations of these methods will be demonstrated in detail. At the same time, the current and future developments for the three approaches will also be presented. Overall, these results shed light on guiding further exploration of planet searching.
La costruzione dell'Identità Professionale Infermieristica: una revisione narrativa della letteratura
Authors: Todisco Maria Cristina , Santamaria Carmela , Zanella Eleonora , Arcadi Paola
Published: June 2024

INTRODUZIONE: L’identità professionale è un costrutto che include l’identità personale, sociale e collettiva di un professionista ma è difficilmente definibile. L’infermiere, oltre ad imbattersi in una difficoltosa costruzione della sua identità professionale (IPI), sta attraversando un forte momento di crisi, nel quale emerge che un fattore determinante sia proprio una debole IPI.
SCOPO: Compendiare le conoscenze relative al processo di identificazione professionale infermieristica, ai momenti cruciali per la sua costruzione e agli elementi costitutivi.
MATERIALI E METODI: E’ stata eseguita una revisione narrativa della letteratura; sono state consultate le banche dati PubMed, CINAHL, SCOPUS con le seguenti parole chiave: “nurse”, “nurses”, “nursing”, “profession”, “professional”, “identity”.
RISULTATI: Sono stati inclusi 18 articoli. L’IPI si delinea come un processo flessibile e dinamico in continuo mutamento. L’infermiere attraversa dei momenti fondamentali nella costruzione della sua IPI, implementati con l’evolvere dell’esperienza professionale. I fattori implicati nella sua costruzione sono sia intriseci che estrinseci all’individuo ed i relativi esiti possono essere sia positivi che negativi.

DISCUSSIONE: Tutti i fattori emersi si influenzano reciprocamente aumentando così anche l’impatto sulla costruzione della IPI e in alcuni casi anche la IPI stessa impatta su determinati fattori. Bisognerebbe considerare e analizzare maggiormente gli elementi individuali implicati nella costruzione dell’IPI. Un notevole impatto deriva dal riconoscimento sociale che risulta ancora distorto e debole.CONCLUSIONI: L’IPI è un costrutto dinamico e di difficile comprensione e analizzare i processi che sono alla base può essere utile, soprattutto per il momento storico-evolutivo che la professione infermieristica sta attraversando
Wat maakt een AI 'katholiek'?
Authors: Bosman Frank
Published: June 2024

Artificiële intelligentie is overal. Dat was al langer zo, maar met de opkomst van en de publiciteit rondom ChatGPT heeft iedereen er ook een mening over. Dit artikel verkent de reacties op Artificial Intelligence en al de daarbij behorende toepassingen binnen de rooms-katholieke kerk en onder (katholieke) theologen.
AI en de ruimte voor menswording in het onderwijs
Authors: Pijpers Remco , Bertram-Troost Gerdien
Published: June 2024

Technologie met AI nestelt zich meer en meer in het leven van kinderen en jongeren. Hun cognitieve en zelfs ook emotionele ontwikkeling kan worden gevolgd via grafieken op een dashboard voor de leraar. AI voorspelt, op een computerscherm, welke opdrachten het beste bij het tempo en het vermogen van een leerling passen. Op sociale media duikt AI op in de vorm van digitale influencers die soms nauwelijks van menselijke influencers te onderscheiden zijn. En dit zou nog maar het begin zijn van de rol van AI in het leven van jeugd. Hier ligt een grote verantwoordelijkheid voor scholen: hoe zet je digitale technologie inclusief de vele verschijningsvormen van AI in? Maar ook: hoe begeleid je leerlingen in deze digitale tijd richting volwassenheid?
Challenge and Strategy to Address the Stability of Perovskite Solar Cells for Commercialization
Authors: Ren Xiaodong , Zhang Jian , Zhang Wen-Hua
Published: June 2024

Halide perovskite solar cells (PSCs) have attracted great interest in both scientific research and industrial communities due to their exceptional power conversion efficiency above 26% and costive solution-processed fabrication. However, the unsatisfied long-term stability of PSCs severely hurdles their commercial application. This review deals with the recent research progress in PSCs in terms of stability, including the degradation mechanism and feasible strategies to improve their stability. Composition manipulation, defect passivation, dimension engineering, charge transport design and encapsulation were discussed. This article concludes optimistically with some recommendations for the future perspectives and research directions to promote the commercialization of PSCs.
Antiferroelectric capacitor for energy storage: a review from the development and perspective
Authors: Zhu Li-Feng
Published: June 2024

With the fast development of the power electronics, dielectric materials with large power densities, low loss, good temperature stability and fast charge and discharge rates are eagerly desired for the potential application in advanced pulsed power-storage system. Especially, antiferroelectric (AFE) capacitors which have been considered as a great potential for electric device applications with high energy density and output power are widely concentrated recently. To propel the development of dielectric capacitors marketization, in this view, we comprehensively summarized the development process of energy storage density and efficiency, improving strategy, raw materials cost and thermal steadily of the typical AFE capacitors, including Pb(Zr, Ti)O3, AgNbO3, (Bi, Na)TiO3, and NaNbO3 AFE systems. Moreover, the advantages and disadvantages of these AFE energy-storage ceramics are compared and discussed, which lay the foundation for the AFE energy storage capacitor early realization of marketization.
The Design of Business Models: What, How and Why
Authors: Massa Lorenzo
Published: June 2024

Over the last decade, management and organisation scholars, practitioners and policymakers alike have increasingly paid attention to business models and variously highlighted the importance of designing them. However, what it means, in essence, to design business models, remains unclear. The received literature reveals a highly fragmented and heterogeneous picture, with different interpretations and implicit meanings of the term ‘design’, leading to varied perspectives on what, how and why business models should be designed. In this editorial I attempt to clarify the meaning of ‘the design of business model’ by providing a framework that will hopefully help synthesise, organise and clarify the multifaceted aspects of designing business models. Additionally, I highlight three emerging meta insights from the nine papers published in this Special Issue: 1) the (importance of) integration of design principles, 2) the need for specialised, context-dependent design methods and tools and 3) the potential of technology, particularly AI, to reshape business model design. These insights offer pathways for advancing the understanding and practice of designing business models that, combined with an appreciation of the different aspects of designing business models, will hopefully encourage and shape future research directions and cumulative progress in this field.