bluuebunny/crossref_metadata_2025 huggingface dataset:
Soil Health: Concepts, Principles and Road Maps for Management in Regenerative Agriculture
Authors: Panda Narayan , Mohapatra Kiran Kumar , Mohanty Shraddha , Padhan Kshitipati , Sahoo Sanjib Kumar , Dash Prava Kiran , Sethi Debadatta , Mishra Ajay Kumar
Published: December 2024

Soil is a crucial nonrenewable resource for agriculture and has a direct impact on food security. However, the decline in crop yield post-Green Revolution suggested soil health deterioration due to soil degradation through harmful chemicals and anthropogenic activities. Therefore, restoring the health of the land and the environment is very important. In the last ten years, there has been a large increase in interest in soil health around the world. Many government, nongovernmental, and private sector groups are working on developing monitoring and assessment techniques. The concept of soil health is defined as the continuous capacity of soil to function as a vital ecosystem service supporting plants, animals, and humans. Biofertilizers, vermicompost, farmyard and green manure, and biopesticides are natural fertilizers that can be used instead of chemical fertilizers. This can help crops grow well while also being good for the land and climate. This brief study focused on soil health indicators such as soil biological, chemical, and physical properties and the urgent need for soil health restoration through the adoption of regenerative agriculture management practices.
EFFECT OF METAKAOLIN NANOSUSPENSION ON THE PROPERTIES OF GYPSUM CONCRETE WITH WOOD FILLER
Authors:   Bryansk State University of Engineering and Technology, Lukutsova N.P. , Pykin A.A. ,   Bryansk State University of Engineering and Technology, Basharin E.S. ,   Bryansk State University of Engineering and Technology, Dubovskoy P.V. ,   Bryansk State University of Engineering and Technology
Published: December 2024

The article presents the study of physical and mechanical properties of concrete with gypsum binder
and wood filler. The concrete is designed for internal partitions of buildings and contains nanosuspension
obtained by ultrasonic dispersion of metakaolin (MKLN) in aqueous medium of superplasticizer S-3 (SP S-3).
The study represents a mathematical model of the dependence of nanosuspension sedimentation stability on
mass concentration of MKLN, SP S-3 and exposure duration to ultrasound. The sizes and zeta potential of
nanosuspension particles are determined. It is established that the developed nanosuspension allows to increase the strength and water resistance of gypsum concrete with wood filler, as well as to reduce its water
absorption.
EFFECT OF PLASMA THREE-PHASE SERIES REACTOR ON POWER SUPPLY NETWORKS
Authors:   Buryat State University named after. D.Banzarov, Shishulkin S.Yu. , Moskvitin A.A. ,   East Siberian State University of Technology and Management, Tran Ph.L. ,   East Siberian State University of Technology and Management, Cheredov E.N. ,   East Siberian State University of Technology and Management, Starinsky I.V. ,   East Siberian State University of Technology and Management, Nguyen Ngoc Lan ,   State University of Transport and Communication, Hanoi, The Socialist Republic of Vietnam
Published: December 2024

The article describes experiment results analyzing energy characteristics of an installation - a threephase serial plasma reactor operating on principle of electric arc steel-smelting furnaces. Stone castings,
melts from basalt rocks, ash and slag from thermal power plants, and broken glass are obtained with its help.
One of the main tasks is the possibility of designing and configuring industrial installations of greater
power. Since the installation is a non-linear consumer of electricity, it is necessary to conduct a study of power
consumption in operating mode, current and voltage harmonics and their amplitudes at power source input in
order to analyze what effect it has on the quality of electricity. Using the obtained numbers, it becomes possible to select protective switching and control equipment, as well as filters to improve the quality of consumed
electricity.
ANALYSIS OF BIOLOGICALLY ACTIVE SUBSTANCES OF HIPPOPHAE RHAMNOIDES L. FRUIT
Authors:   Kaliningrad State Technical University, Frolova N.A. , Verkhoturov V.V. ,   Kaliningrad State Technical University, Shkrabtak N.V. ,   Amur State University, Veremey E.E. ,   Kaliningrad State Technical University, Grinchuk M.A. ,   Kaliningrad State Technical University
Published: December 2024

The article presents an analysis of some bioactive compounds of sea buckthorn fruit (Hippophae rhamnoides L.), picked up in 2021-2023 in the Amur region, in particular dietary fibers, their fractional, amino
acid and polyphenolic composition. It was found that the fruit of Hippophae rhamnoides L. is a source of
protein, the average value of which in the analyzed samples was 18.37 g/100 mg. It should also be noted that
the content of acid-detergent lignin (5.77 g/100 g) and hemicellulose (8.46 g/100 g) is low, and the content of
polyphenols is high. Thus, the studies conducted have shown that fruit of Hippophae rhamnoides L. is highpotential and physiologically valuable ingredient that can be used to develop functional products.
WORKING PROCESS OF TECHNICAL FEEDERS FOR SOLID ORGANIC FERTILIZERS SPREADING
Authors:   Irkutsk state agrarian university, Shukhanov S.N. , Kuzmin A.V. ,   Irkutsk state agrarian university, Agafonov S.V. ,   Irkutsk state agrarian university, Sukhaeva A.R. ,   Irkutsk state agrarian university, Kosareva A.V. ,   Irkutsk state agrarian university
Published: December 2024

Agricultural science contributes to the functioning of agricultural production at competitive level. Key
importance is given to technical support for agro-industrial complex. At the same time, technical means and
technologies for agricultural production are important, as well as for new high-yielding crop varieties, including potted crops. Effectiveness of plant breeding work largely depends on its volume and intensity. The best way to obtain new crop varieties is to promote formation of plant breeding and seed-growing greenhouse
complexes. The unsatisfactory level of mechanization of production processes is a significant limiting factor.
The task of preparing soil and filling pots with it is especially acute. The problem of creating an installation
for dispensing bulk material has been solved at the level of patentability and is reflected in the publication. To
justify its design parameters, as well as optimal operating modes, it is necessary to review and analyze process
studies of machine feeders for spreading solid organic fertilizers. It allows to make correct choice of feeder
type. Despite some positive results of scientific researches of feeders and spreaders of solid organic fertilizers,
the problem of steady movement through bunker with subsequent bulk mass dosing has not been solved yet.
Therefore, review and analysis of feeders for solid organic fertilizer spreaders, as well as experiment results on dosing bunker functioning for peat dosing prove belt feeder to be the most promising in terms of dosing and feeding stability.
PHYSICAL AND MECHANICAL PROPERTIES OF WOOD-POLYMER COMPOSITE BASED ON POLYLACTIDE AND WOOD WASTE
Authors:   East Siberian State University of Technology and Management, Dorzhieva E.V. , Ayurova O.Zh. ,   Buryat State University named after D. Banzarov, Shestakov N.I. ,   NRU MGSU, Tsydenova A.B. ,   East Siberian State University of Technology and Management, Dorzhieva A.A. ,   East Siberian State University of Technology and Management
Published: December 2024

This article discusses development of wood-polymer composites based on polylactide and wood waste
intended for use in building materials. It has studied physical, mechanical and thermal properties of composites with different component ratios. It is determined that the best performance characteristics are demonstrated by composites containing 75 wt. % polylactide and 25 wt. % wood chips. This composition provides
optimal bending strength (42 MPa), thermal stability and minimal water absorption.
RUBBER-ASPHALT CONCRETE BASED ON RECYCLED INDUSTRIAL WASTE
Authors:   Federal State Budgetary Educational Institution of Higher Education T. F. Gorbachev Kuzbass State Technical University, Ivanov S.A.
Published: December 2024

In world practice, asphalt concrete mixtures are most widely used for the construction of road surfaces. Constantly increasing axle loads and increased traffic intensity require the consideration of new materials to prolong the service life of public roads between repairs. Constantly growing number of road transport
and consequently car tires number require new ways of their disposal, since their accumulation leads to increasing environment pollution.
This article discusses possibility of using asphalt concrete mixtures based on modified bitumen with
crumb rubber obtained by processing worn-out car tires and other rubber products. It gives characteristics of
the materials making up the asphalt concrete mixture, as well as operational experience with asphalt concrete
pavements based on crumb rubber.
The ILIRIA Model
Authors: Lipaj Xhavit
Published: December 2024

The ILIRIA model - A culturally anchored approach to caring for people with dementia
The ILIRIA model presents an innovative approach to caring for people with dementia that combines cultural values
with modern care science. This model is based on six central principles: Preserving Individuality, Showing Love and
Humanity, Promoting Community Integration, Respect for Dignity and Identity, Inspiration from Cultural Roots and
Activating Potential. It offers a holistic, flexible and culturally anchored framework that can be applied in both care facilities
and family contexts.
Research on the stability of grid-connected wind and solar power generation
Authors: Wang Youzi
Published: December 2024

This paper mainly introduces multiple strategies to enhance the stability of wind and solar power grid integration. Firstly, considering the impact on the environment, mechanical energy storage systems such as FESS, PHES and CAES are introduced and analyzed. These energy storage systems cope well with wind and solar demand fluctuations. Then three kinds of GFM control techniques are introduced. For VF control, single-loop control leads to better stability of the grid. VOC is one of the more efficient in terms of power sharing and synchronization speed. Finally, three types of uncertainty that need to be considered in VPP are introduced, such as the uncertainty of renewable energy, the uncertainty of market price and the uncertainty of load demand. Considering the uncertainty of renewable energy, two VPP optimization methods are given to improve the stability of power grid. This paper hopes to consider the possibility of combining these methods in future VPP research.
The Psychological Analysis of the Blind Box Craze in the Chinese Market: A Case Study of POP MART
Authors: Chen Shoufeng
Published: December 2024

In recent years, blind box culture has quickly become popular in China, attracting many young consumers, with POP MART leading the market. POP MART has used unique designs, limited edition products, and uncertainty-based sales to successfully dominate the blind box market in China. This study aims to explore why POP MART’s blind boxes have become so popular, focusing on consumer behavior and psychology. The study will use Prospect Theory, Cognitive Dissonance, and Maslow’s Hierarchy of Needs to looks at why people are motivated to buy products when there is uncertainty and scarcity, especially the satisfaction they feel when getting rare items. The study also looks at how social media and community culture influence consumer choices, showing the importance of brand loyalty. Based on the findings, this paper gives suggestions for POP MART on product innovation, improving customer experience, and expanding globally to strengthen its market position.
Research on Delayed Retirement Policies Amid the Trend of Population Aging: Challenges and Countermeasures
Authors: Huang Jiawei
Published: December 2024

As China enters society with an aging population, the reduction of the labor force and the increasing burden of pensions have become urgent issues that need to be addressed. As one of the measures to cope with the aging population, the delayed retirement policy has occupied an important position in policy discussions. This study explores the necessity and challenges of implementing the delayed retirement policy in China. By analyzing the trend of changes in China's population structure and the impact of delayed retirement on society and the economy, this paper summarizes this policy's possible positive effects and potential problems. The study believes that although delayed retirement can alleviate some of the labor shortages and pressure on social security funds, its impact on the employment market, family structure, and the quality of life of the elderly cannot be ignored. To ensure the successful implementation of the policy, the government should provide flexible retirement options and a complete social security system.
The Reconstruction of The Talent Training Model Integrating Industry and Education in Higher Vocational Colleges Majoring in Tourism Management.
Authors: Chen Haiming
Published: December 2024

This paper further reveals the specific manifestations of these issues through current situation analysis, such as an excessive proportion of theoretical courses, predominant classroom theoretical teaching, teacher-centered lectures, in-school teaching as the main mode, assessment methods based on examinations and assignments, and graduation projects primarily focused on paper writing. In response to the above problems, this study proposes a restructuring strategy for the talent cultivation model of higher vocational tourism management majors that integrates industry and education. That is, adjusting from "theoretical courses as the main" to "increasing the proportion of practical courses", from "classroom theoretical teaching as the main" to "integration of theory and practice", from "teacher-centered lectures" to "student-centered", from "in-school teaching as the main" to "complementary in-school and off-campus teaching", from "assessment methods based on examinations and assignments" to "assessment methods based on production", and from "paper writing as the main focus of graduation projects" to "significantly increasing the proportion of graduation projects". These strategies aim to adapt to industry changes, enhance students' practical abilities and professional qualities, and cultivate high-quality tourism management talents that meet market demands.
Optimization of Visual Communication Design Courses in Chinese Colleges and Universities under the Background of Digitalization
Authors: Qiu Yajin
Published: December 2024

The development of digitalization has had an impact on all aspects of our lives, including education. In China, digital technology such as interactive whiteboards and artificial intelligence has been gradually introduced, opening up new opportunities for the advancement of education Therefore, universities need to update their visual communication design curriculum to keep up with the society's needs. This paper primarily utilizes a literature review to analyze the use of digital tools in visual communication design courses both domestically and internationally. It also examines the various impacts of these tools on teaching and discusses the potential for their application in visual design courses in China. This paper proposes integrating emerging technologies, advanced tools, and interdisciplinary education into the visual communication design curriculum. The use of new media technologies and advanced tools can boost students' creativity and classroom engagement, ultimately enhancing the effectiveness of teaching visual communication design in colleges and universities. Incorporating interdisciplinary education can add diversity to visual communication design courses and equip students with relevant skills for the digital age. Additionally, it is recommended to collaborate with design companies on projects to provide students with real-world experiences beyond the classroom.
Comparative Analysis of Predicting Diabetes in Senior Age Group Based on Machine Learning Models
Authors: Zhang Mengyuan
Published: December 2024

The study investigated the contributing factors to risk for diabetes among older populations and their impact on the onset of diabetes. Analyzing a dataset from Kaggle comprising 18, 100 older adults, the study revealed significant associations between diabetes and age, Body Mass Index (BMI), HbA1c levels, blood sugar levels, high blood pressure, heart disease, and smoking history. Comparison of logistic regression, random forest, and K-nearest neighbor (KNN) prediction models demonstrated that the random forest model exhibited superior performance, with a ROC-AUC value of 0.88, an out-of-pocket error rate of 7.58%, a sensitivity of 99%, and a specificity of 92.3%. This outperformed both the logistic regression (ROC-AUC value 0.85) and KNN (ROC-AUC value 0.80) models. The study indicated that the random forest model is advantageous for processing nonlinear data and multi-variable interactions, making it suitable for predicting diabetes risk in the elderly. Future research could incorporate lifestyle factors to enhance prediction accuracy.
Research on the Integration of Localized Communication and Marketing Strategies of Global Brands in a Cross-cultural Context: Taking Starbucks as an Example
Authors: Shu Chang
Published: December 2024

Under the impetus of globalization, more and more international brands choose to enter different cultural markets, and it becomes imperative to explore how brands can adopt localization strategies in the communication process to maintain their global consistency and enhance local adaptability. This study focuses on integrating localized communication and marketing strategies of global brands in cross-cultural contexts and explores in depth how global brands adapt and integrate into local cultures through localized communication and marketing strategies when entering different cultural markets. This study uses literature analysis, process tracking method, and comparative analysis method, combining Starbucks' localized communication strategies in China, Japan, the United States, and other markets to analyse the brand's communication methods in different cultural backgrounds and their impact on consumer cultural identity. The study found that the localized communication of global brands in a cross-cultural context needs to maintain the consistency of the core value of the brand while making corresponding adjustments based on local culture, consumer preferences, market environment, and other factors to effectively enhance the brand's localized adaptability and consumer recognition. This study shows that successful localization lies not only in language and product adjustments but also in deep cultural integration and localized expression of brand value. Global brands should create a brand image with cultural sensitivity through continuous cultural adaptation and innovative communication strategies, to achieve long-term brand development and success in the cross-cultural market.
Applications of AI-powered Conversational Chatbot for Mental Health
Authors: Chang Yiyi
Published: December 2024

Psychological issues have become a pervasive problem affecting the quality of life for many individuals. However, the scarcity of professional psychotherapists and the high threshold for receiving human psychological counselling prevent most people from obtaining timely, high-quality psychological help. To address this issue, chatbots have been developed to participate in the promotion of public mental health. Empowered by Artificial Intelligence (AI), especially Large Language Models (LLMs), chatbots have the potential to revolutionize the field of mental health by offering personalized and full-time support. Moreover, AI-powered chatbots can assist researchers in collecting more data to understand mental health better and develop more effective treatments. This paper categorizes and summarizes the recent applications of conversational chatbot technology in the mental health field, including human-robot relationships, the use of conversational chatbots with mental health tasks in counselling and online settings, the generation of counselling dialogue data, and the evaluation of datasets and models. The advantages and disadvantages of these technologies are explored, along with the current technical shortcomings of conversational chatbots. Additionally, the challenges to their widespread adoption and use, as well as future directions for development, are discussed.
Experimental Study of a Schiff Base as Corrosion Inhibitor for Mild Steel in 1M HCl
Authors: Zhou Jing , Li Yue , Wei Yutong , Long Chaozheng , Yi Bin , Sun Xiaoli , Ren Boyan , Deng Keqian , Fan Fangde
Published: December 2024

In this paper, salicylaldehyde ethylenediamine Schiff base (SESB) was prepared by reaction of salicylaldehyde and ethylenediamine at 60℃ for 4 h. The structure of SESB was characterized by hydrogen magnetic resonance spectroscopy. The corrosion inhibition effect of SESB on mild steel in 1mol L-1HCl was studied by weight loss method and electrochemical method. The results showed that the corrosion inhibition effect of SESB on mild steel at 1mol L-1 HCl was negatively correlated with the test temperature at 25℃ to 45℃, and positively correlated with the concentration of SESB at 0mmol L-1 to 5mmol L-1. The results showed that the maximum corrosion inhibition efficiency of SESB at 25℃, 30℃, 35℃, 40℃ and 45℃ were 70.73%, 58.42%, 54.68%, 37.73% and 25.12%, respectively. The results of electrochemical impedance test and electrochemical polarization test show that SESB can not only inhibit the anode metal dissolution of mild steel in 1mol L-1 HCl, but also inhibit the cathode hydrogen precipitation, which is a mixed corrosion inhibitor.
Research on the Effect of Interaction between Artificial Intelligence and Conventional Education on Improving Teaching Effectiveness under the Background of Big Data
Authors: Liu Xinyu
Published: December 2024

The popularity of AI technology has been widely focused on all walks of life, from the pharmaceutical sector to the industry, it is one of the most famous technologies of modern society. However, there are few examples of AI technology used in the education area. Educators mostly prefer to explore its influence on the educators and learners, rather than popularizing this technology to the whole area. Combining this phenomenon with the problems of the current education system-conventional education, this article aims to discuss the influence of AI technology on the education area and the possibility of integrating AI technology with conventional education. By analyzing the pros and cons of AI used in education, this article concluded that even with some problems, AI technology can still bring huge potential to improve the education area and make conventional education more effective. Based on the conclusion, this article suggests that the education area should pay more attention to AI technology and try to integrate it with the current education system instead of waiting for the technology to mature, which will make the integration easier and more efficient.
Improvement Of CAR-T Therapy with Gene Editing Technologies
Authors: Chen Jinsi , Xiao Tengyang , Zhang Dongsheng
Published: December 2024

In recent decades, after some breakthroughs in field of immunology, the numbers of studies related to cancer immunotherapy are exploding and growing. As a promising branch, adoptive cell therapy, has been shown to have a very high remission rate in patients with hematologic tumors as well as patients with metastatic and multi-therapy resistant melanoma by engineering T cell or natural killer (NK) cells outside the body. CAR-T therapy has gained significant recognition as a cancer treatment due to its exceptional effectiveness in treating hematologic malignancies. Consequently, there are researchers that wish to apply this technology to solid tumor therapy. But throughout this process, some solid tumor traits as well as the therapy's adverse effects constitute a significant challenge. With the advancement of gene editing technology, some researchers are able to alter the structure of CAR-T cells to increase the effectiveness of CAR-T treatment and address some drawbacks, such as the potential to cause GVHD and immunological rejection. Subsequent examples will illustrate this point broadly. By using TALENs to disrupt the TRAC gene or HLA-A locus of the MHC gene complex, the risk of GVHD and immunological rejection can be decreased. CRISPR/Cas9-mediated PD-1 protein knockout can extend the lifespan of CAR-T cells within the body. When toxicity manifests, appropriate staff may be able to eradicate every CAR-T cell in the patient's body by introducing a suicide gene or introducing a safety switch into CAR-T cells using CRISPR.
Emotional-driven: The Function of Experiential Consumption in Improving Consumers' Purchase Intentions —— Take JELLYCAT as an Example
Authors: Cai Ji
Published: December 2024

With the rise of a series of "emotional" economy, the traditional marketing model has been difficult to comply with the current mainstream trend of consumption, and the competition between brands has gradually turned to emotional competition and experience competition. Consumers no longer just pay attention to the basic performance of goods, but seek a brand that fits their emotions and values, and experiential emotional marketing has become one of the mainstream ways of the current marketing mode. Focusing on experiential marketing, this study mainly analyzes the impact of this marketing model on consumers' purchase intention and explores the path to build a close relationship between brands and consumers. The process tracking method of case study and documental analysis method are adopted to discuss. This study analyzes how experiential marketing makes an emotional connection with consumers driven by emotion, extracts the interaction between the two and the role of brands in the operation process, and affirms the positive influence of experiential marketing in enhancing the brand loyalty and consumer stickiness. However, there are still some problems in the experience design of online marketing. As well as the problem of how to apply the theory in different markets without detailed expansion, it is expected to be improved in future research.
Research on the Application Status of Large Language Models in China's New Energy Vehicle Industry: Taking Huawei's NLP Large Model and XPENG 's XGPT as Examples
Authors: Liu Zhenyu
Published: December 2024

In the era of rapid development of artificial intelligence, large language models are widely used in various industries due to their powerful natural language processing and text generation capabilities, including intelligent manufacturing, intelligent services, voice interaction, and even music box text creation. In this article, I will use literature review and case analysis methods, using the Huawei NLP large model and XPENG XGPT model as examples, mainly focusing on two aspects: intelligent driving and intelligent cockpit. Deeply explore the advantages of big language models in the new energy vehicle industry, the feasibility and necessity of their application, and their future prospects. In my research, I found that previous studies on this topic mainly focused on the technical principles of intelligent driving and intelligent cockpit, model optimization solutions, and market and user feedback. In intelligent driving systems, large language models can achieve timely and accurate takeover of driving, precise navigation, and efficient scene learning through scene simulation and generation techniques. In terms of intelligent cockpit, I believe that the main approach is to utilize natural language recognition and text processing capabilities to timely complete user instructions and engage in efficient language interaction. Helping enterprises create intelligent cockpit systems that are personalized and emotional processing for users.
The Impact of Green Finance on Carbon Emission Reduction under the "Dual Carbon" Goals
Authors: Chen Jinyiran
Published: December 2024

Since the Industrial Revolution, environmental challenges stemming from social development have escalated into a pressing global challenge. To address this crisis, green finance has emerged as an innovative financial tool designed to channel funds into low-carbon and eco-friendly sectors, thereby effectively curbing the rise in carbon emissions. This paper investigates how green finance stimulates capital investment in carbon emission reduction efforts, how carbon markets manage emission quotas across various economies, the broad societal attention, and the proactive implementation of carbon reduction policies by governments. The study elucidates the operation and impact of these mechanisms in controlling and guiding carbon emission reductions. Furthermore, this paper puts forward strategic solutions and recommendations to optimize the green finance ecosystem and bolster its impact on carbon emission reduction. Through detailed analysis and strategic recommendations, this paper seeks to provide theoretical underpinnings and practical guidance for the healthy development of green finance and the achievement of global carbon reduction targets.
Comparative Analysis of Predictive Models for Heart Disease: Evaluating Accuracy and Clinical Applicability
Authors: Niu Hanmeng
Published: December 2024

Heart disease remains the leading cause of death globally, a reality driven by a complex interplay of genetic, environmental, and lifestyle factors. Recent advancements in technology and data science have dramatically enhanced our ability to analyze large datasets, facilitating the development of predictive models that can accurately estimate the risk of heart attacks. This capability is instrumental in preempting the onset of cardiovascular diseases and formulating preventive strategies. In this context, researchers have conducted extensive evaluations of different predictive models, scrutinizing their operational principles and accuracy. The study meticulously compared the performance metrics, specifically the precision and area under the curve (AUC), of four distinct models. It was found that each model presents unique advantages and limitations, which are reflected in their respective levels of accuracy and effectiveness in different scenarios. This analysis not only highlights the potential of machine learning in medical diagnostics but also underscores the need for ongoing refinement of computational approaches to enhance their applicability and reliability in clinical settings.
Advances in Proppant Transport and Placement in Unconventional Reservoirs: A Review
Authors: Zhang Qiang
Published: December 2024

This comprehensive review delineates the advancements in the pivotal domain of hydraulic fracturing within the realm of unconventional oil and gas reservoir exploitation, specifically focusing on the dynamics of proppant conveyance and positioning. Through a meticulous synthesis of empirical investigations and computational modeling techniques, this discourse aspires to furnish a theoretical framework for the refinement of proppant selection and injection protocols, thereby amplifying the efficacy of oil and gas well stimulation. The research underscores that the intrinsic attributes of proppant, the behavior of fluid flow, and the characteristics of the reservoir are paramount in influencing proppant migration and deposition. The paper also projects prospective advancements in proppant material innovation and simulation methodologies, underscoring the pivotal role of intelligent surveillance in augmenting the precision of fracture stimulation assessments.
The Application and Production of Carbon-based Materials
Authors: Zhang Zihan
Published: December 2024

With the advancement of technology, the field of materials science also flourishing and developing. This article explores the characteristics and properties of carbon-based materials, elaborates on relevant experiments, and provides prospects. Nowadays, many technological powers in the world have taken action, with some cutting-edge carbon-based materials being invented and used in various fields, especially in aerospace. Whenever a new type of carbon-based material is invented, it is a small step in scientific research, but a big step for humanity. The generation of chemical products is based on their own conditions and resource abundance. The excellent characteristics of carbon-based materials and carbon’s high reserves on Earth make them popular chemical materials. Unfortunately, the types of carbon-based materials that humans can currently produce and manufacture are limited. Carbon-based materials, a special chemical material, are closely related to the future of humanity. They comply with the United Nations' initiatives on sustainable development and can also bring huge benefits to users. Additionally, they are one of the indispensable contributors to the human development process.
The Collaboration of Knowing-How and The Safety Principle
Authors: Ding Yankai
Published: December 2024

Nowadays, the challenge of defining JTB (Justified True Belief) by Gettier's cases has not had a satisfying solution. Considering the difficulties caused by the K =df. True belief + X paradigm, this paper replaces belief with competence as a more fundamental component of knowledge. Moreover, by the way of using the safety principle to illustrate knowing-how,  necessary conditions for knowledge definition are obtained. This paper aligns with Pritchard's anti-luck virtue epistemology, specifically elaborating on the concept of ability-based knowledge as a robust necessary condition for defining knowledge. Therefore, the main findings of this paper are: 1) taking knowing-how as the basic element of knowledge can strengthen the reliability of the knowledge definition and get closer to the essence of knowledge; 2) the safety principle is compatible with knowing-how; 3) the collaboration of the safety principle and knowing-how as a necessary condition for knowledge definition can effectively avoid the Gettier problem. Through establishing a reliable method for testing knowledge, this approach may ultimately deepen readers’ understanding of what knowledge truly entails.
Value exploration and analysis of game companies
Authors: Feng Chujun
Published: December 2024

The rapid development of society, the cost of living increases, so that people’s life pressure increases sharply. Some people want to play some electronic games to reduce stress, because some games don’t have to be bought. Some people charge money in the game for a better experience. In real life ,most people are always compared, but also than others, in the game, money can get the envy of others, so as to get a feeling of pride, let people after a hard day ,go home to open the game found that they are great, they also can be compared to others, they can get confidence in the games. This paper analyzes which game company is the most suitable for investment by comparing the net profit, water flow and revenue of Tencent games, Netease games, Mihoyo games. Through analysis, this paper analyzes the financial data and finds that although Tencent Games has the highest debt, its net profit and revenue are also the highest, and finally comes to the conclusion that Tencent Games is suitable for investment.
Advances In CPU Scheduling Algorithms in Operating Systems
Authors: Li Lei
Published: December 2024

CPU scheduling algorithms significantly influence Operating System (OS) performance. Many studies have proposed optimized scheduling algorithms. This paper outlines the main characteristics of common scheduling algorithms, including First Come First Served (FCFS), Shortest Job First (SJF), Round Robin (RR), Priority Scheduling, and Highest Response Ratio Next (HRRN). It reviews comparative performance research on these algorithms and mentions their optimizations to summarize the progress in this field. This paper also analyses two specific operating systems - Time-Sharing Systems and Embedded Systems, and introduces scheduling algorithms applicable to these two systems and their typical applications. The review finds that SJF & SPTF perform better than FCFS and RR in terms of waiting time, while HRRN also significantly outperforms RR. The optimization of the scheduling algorithm mainly focuses on RR, by clustering techniques and dynamically resizing the quantum time. For time-sharing systems, RR is the most common strategy, while the Linux kernel adopts the Completely Fair Scheduler (CFS). For embedded systems, the real-time scheduling algorithms, Earliest Deadline First(EDF) and Least Slack Time(LST), are applicable to soft real-time systems.
Application of Reinforcement Learning in Complex Environmental Decision-making Problems
Authors: Zhao Chenchen
Published: December 2024

This paper provides an in-depth discussion on the application of reinforcement learning in decision-making problems in complex environments, focusing on the challenges it faces such as data sparsity and the balance between exploration and utilization, and proposes corresponding solutions. The study realizes an integrated process from data collection to decision support by developing a decision support system for sustainable enterprise management based on big data. Meanwhile, the exploration strategies and optimization algorithms in reinforcement learning are used to improve decision-making efficiency and accuracy. An application case in an intelligent transportation system demonstrates the potential of the multi-intelligence reinforcement learning framework in vehicle collaboration and optimization of traffic flow, effectively alleviating traffic congestion. Experiments show that the system significantly improves decision-making efficiency and accuracy, verifying the effectiveness of reinforcement learning in decision-making in complex environments.
The Relationship between Education and the Market: Incorporating Enterprise Risk Management (ERM) and Marketing
Authors: Chen Jiayi
Published: December 2024

Education and the market are core components of society and reciprocate one another in intrinsic manners. This paper analyses the connection between education within the market and the structure of educational practices when it comes to the profession of marketing and Enterprise Risk Management (ERM). Nowadays, the interaction between education and the market has attracted increasing focus from scholars, however, there are still some deficiencies. Therefore, this paper focuses on examining how educational units influence marketing and ERM professional competence in the market. Thus, the study identifies that education is a significant driver in understanding consumer behavior, carrying out strategic interventions, and mitigating risks. More seriously, the results show that the improvement in education status increases the capacities of people to respond to market conditions and organizational vulnerability. Based on this, the paper proposes several suggestions for improving learning methods to better meet market demands: increasing the number of skills-based aspects such as internships and assignments, enhancing collaboration between academic institutions and businesses, and updating curricula frequently to the existing job market and innovations. These recommendations are intended to improve people's and organizations' performance and to support economic growth and development.
Research on the application intention of virtual photo technology in commemorative culture based on the theory of planned behavior
Authors: Qiao Jingwen
Published: December 2024

In recent years, artificial intelligence technology has developed rapidly, and its prospects have also attracted much attention. In the field of digital commemoration, artificial intelligence technology also plays a huge role. In this field, artificial intelligence technology is deeply integrated with emotional commemoration methods to provide participating individuals with videos of deceased loved ones, providing a highly immersive emotional connection and experience. This research plan is based on the theory of planned behavior and aims to analyze individual attitudes, subjective norms, and perceived behavioral control in individuals' use of virtual photo technology. And further, study how these factors influence individuals' behavioral intentions to use technology and their evaluation of interactivity during use. This study adopted a quantitative method and designed a questionnaire to measure relevant variables of individuals' behavior using virtual photo technology based on the guidance of the TPB Behavior Manual. This study will contribute to understanding how emotional value, social influence, and personal confidence influence individuals' participation intentions in virtual commemoration technologies. The research results can provide theoretical guidance for the future digital commemorative entity industry.
The Development and Popularity of Hip Hop Culture and Its Clothing: Supreme vs. Louis Vuitton
Authors: Yue Jiaying
Published: December 2024

In recent years, hip-hop culture spread more and more widely. That influence is also growing. Among them, there are obvious manifestations in its clothing. Hip-hop clothing is diverse and widely used in everyday wear, fashion design, and a range of cultural activities. The unique rebellious courage, sense of freedom and anti-traditional significance of hip hop culture have derived various kinds of clothing and peripheral products. At present, hip hop style clothing blending different cultures has become an important cultural expression and fashion trend. This paper first combs the historical development of hip-hop clothing, and then takes the joint name of Supreme and Louis Vuitton (LV) as an example to describe the extensive application of hip hop in the fashion industry. In addition, the paper further investigates the current hip hop clothing costume matching and fashion elements and draws a conclusion that hip hop clothing has become a mainstream fashion worldwide.
Fuel cell cars with hydrogen production, storage, costs, efficiency and production model in manufacturing
Authors: Fang Peijun
Published: December 2024

Given the increasing global concern about climate change and environmental pollution, the development and application of clean energy have become particularly urgent. Hydrogen energy, with its high energy density and clean combustion characteristics, is widely regarded as the core of the future sustainable energy system. Although the wide application of hydrogen energy is constrained by life cycle cost and fuel safety. The primary elements influencing hydrogen's life cycle cost are its production, supply, market price, demand, storage, distribution, and cost of investment. The current hydrogen production, storage, and transportation technologies are summarized, including steam methane reorganization (SMR), wind and solar power generation, alkaline hydrolysis (AWE), high-pressure gas cylinders, low-temperature liquid hydrogen storage, ammonia compound hydrogen storage, methane compound hydrogen storage and hydrogen transportation. The article aims to provide a comprehensive perspective on the current situation and future development trends of hydrogen production and storage technology and provide suggestions for the sustainable progress of green hydrogen production and utilization.
Parameter Optimization in DeBERTa for Text Classification Using PCA on Limited GPU Resources
Authors: Lin Yvheng
Published: December 2024

This study focuses on optimizing Decoding-enhanced Bidirectional Encoder Representations from Transformers with disentangled Attention (DeBERTa) for text classification tasks, particularly on smaller datasets with limited GPU resources, by using Principal Component Analysis (PCA) to adjust and explain parameter choices. The goal is to reduce the model's parameters without significantly compromising accuracy. Specifically, the research employs DeBERTav3 on the Internet Movie Database (IMDb) dataset, without pre-training, and uses PCA to analyse the embedding and attention components of the model. PCA is applied to identify and reduce parameters by observing the Number of smallest factors that has a given Neglected cumulative contributing Rate of principal components (NNR), iteratively refining the model until optimal efficiency is achieved. This study demonstrates that PCA can effectively guide parameter adjustments, allowing even a smaller model to maintain high accuracy. The IMDb dataset is used to validate the approach, showing that a reduced DeBERTa model can still achieve competitive performance, making it particularly useful for natural language processing tasks involving minority languages or constrained computational environments. The findings have broader implications for optimizing large language models, suggesting that future work could explore combining PCA with techniques like factorized embedding parameterization to further enhance efficiency.
Stroke Prediction Base on Logistic Regression Model
Authors: Li Le
Published: December 2024

The prediction of stroke using risk factors and basic demographic information can be valuable for primary prevention and community healthcare workers. Machine learning models are becoming more prevalent in clinical prediction due to their high accuracy. This study investigates stroke prediction using four machine learning models including logistic regression, random forest, Lasso Regression (Least Absolute Shrinkage and Selection Operator), and Extreme Gradient Boosting (XGBoost). Six key variables—age, gender, work type, heart disease history, marital status, residency type, smoking status, Body Mass Index (BMI), and average glucose level—are used for prediction. Among the dataset of 3,255 observations, 180 individuals experienced stroke, indicating an extremely imbalanced dataset. Therefore, balanced accuracy is the key metric used to compare model performance. The balanced accuracy for logistic regression, Lasso Regression, random forest, and XGBoost are 78.4%, 61.7%, 50%, and 67.7%, respectively. Logistic regression demonstrated the strongest performance, while also highlighting the significant role of age, particularly for individuals over 45.
Risk Factors and Management of Adolescent Tuberculosis
Authors: Lai Qingfeng
Published: December 2024

Tuberculosis (TB) is an acute or chronic pulmonary infectious disease caused by Mycobacterium tuberculosis and transmitted through the air, which is one of the major infectious diseases threatening human life and health. It is a communicable disease primarily spread via respiratory droplets. TB can affect individuals of any age, this study refers to TB occurring in individuals aged 10-19 (inclusive) as adolescent TB. Despite the overall good control of tuberculosis in China, the incidence rate among adolescents has been rising. Adolescent TB is influenced by both genetic and environmental factors, presents with atypical clinical symptoms, has a low recognition rate, and poor treatment adherence. This not only affects the physical health of adolescents but may also impact the psychological health and academic development. This paper reviews the related influencing factors of the adolescent TB and discusses diagnostic and treatment strategies to provide better approaches for managing and preventing adolescent TB.