bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Comparison Between Traditional Internal Combustion Engines and Hybrid Powertrains
Authors: Lu Jiacheng
Published: November 2024

This paper explores the performance differences between traditional internal combustion engines (ICEs) and hybrid engines. Traditional ICEs have been the cornerstone of automotive technology for over a century, operating by converting chemical energy from burning fuel into mechanical energy. Despite their widespread use, traditional ICEs are significant contributors to air pollution and global warming. In contrast, hybrid engines combine one or more electric motors with a traditional ICE, utilizing battery packs and regenerative braking to enhance fuel efficiency and reduce emissions. As society increasingly adopts hybrid vehicles due to their environmental benefits, understanding the advantages and disadvantages of both engine types is crucial. This study evaluates the energy efficiency, emissions, and power output of traditional and hybrid engines. By analyzing common driving scenarios, this paper provides a comprehensive comparison to inform consumer choices, manufacturing trends, and policies aimed at reducing the automotive industry's carbon footprint and improving economic factors related to fuel consumption. Ultimately, this research aims to contribute to the ongoing dialogue on sustainable transportation and the future of automotive engineering.
Innovation Model of Grassroots Staff Performance Appraisal in Big Data Environment
Authors: Yang Keling
Published: November 2024

With the rapid development of big data technology, new requirements and challenges have emerged for the performance evaluation methods of grassroots employees. This study focuses on the application of big data in performance assessment, providing a detailed analysis of the current methods for evaluating grassroots employee performance and the issues that exist within these methods. It reveals the major challenges that performance evaluation faces in a big data environment.  Based on this analysis, the paper proposes an innovative performance evaluation model designed to fully leverage the advantages of big data technology to enhance the fairness and accuracy of assessments. Additionally, it outlines an implementation plan and assessment methods for the new model and presents a feasibility analysis. Ultimately, this research aims to provide a more scientific and reasonable solution for the performance evaluation of grassroots employees, adapting to the developmental needs of the digital age.
Convergence Rate of Greedy SR1 With Trust Region Method
Authors: Xia Yu , Wu Hao
Published: November 2024

Recently, Greedy Quasi-Newton methods have attracted wide interests of some researchers for their explicit superlinear convergence rate. These algorithms which achieve rapid local convergence construct a matrix sequence to approximate the Hessian matrix of the objective function iteratively. This paper proposes an algorithm, GR-SR1-TR, which incorporate Greedy SR1 method with Trust Region framework and employs a new correction technique. We prove that the approximation matrix sequence has a linear descent property under the Frobenius-norm metric. Further, both the global convergence and an explicit superlinear rate are established. The effectiveness of GR-SR1-TR has been verified by preliminary numerical experiments.
Theoretical Evidence and Rules of the Application of the Injunction for Personality Rights in Cyber Violence Cases
Authors: Shi Ao
Published: November 2024

Cyber violence in the digital age features mass, concealment and diversity, which not only causes serious infringement on the personal and property safety of victims, but also brings new challenges to the existing network management order. The existing cyber violence governance mainly relies on the governance paths of individualism, organizationalism and nationalism. However, it is difficult to fully resolve the multiple risks triggered by cyber violence. The core function of the injunction system for personality rights established in the Civil Code is to provide a convenient and efficient protection mechanism for personality rights, and to build a protection mechanism for cyber violence governance that closely combines prevention in advance with timely infringement suppression, which to some extent makes up for the shortcomings of the traditional governance model with post-event relief as its essence. In terms of specific application, it is necessary to clarify the specific conditions and applicable procedures for embedding the injunction for personality rights into cyber violence governance. Meanwhile, it is of significance to distinguish between the application of injunction for personality rights and the safe harbor privacy principle, and improve the specific rules of blockchain electronic certificate deposit technology and platform responsibility, so as to provide technical support and platform connection for the embedding of injunction for personality rights into cyber violence governance.
Mathematical Modeling and Analysis of Atmospheric CO₂ Concentration and Global Temperature Change: A Multi-Model Approach
Authors: Liang Hangyu , Zhou Xinnuo
Published: November 2024

This research works on the trend of atmospheric CO2 levels and global temperature change by deployment multiple forecasting models. Historical data from 1959 to 2021 is used for analysis by fitting polynomials, exponential function, and autoregressive models in the forecasting of CO2 concentration. ARIMA and hybrid ARMA-polynomial models are used in forecasting temperatures. The results showed that atmospheric CO2 can achieve 512-513 ppm by 2050 and 688-835 ppm by 2100. Global land-ocean temperature will increase to 1.25°C, 1.50°C, and 2°C in the years 2030, 2038, and 2051, respectively. We have proven high correlation between CO2 concentration and temperature change based on our model's having good reliability over approximately a seventy-year period. This research bears valuable information regarding future climate trends and underscores pressing needs for continued surveillance as well as mitigation efforts.
Transcending Disciplinary Boundaries: The Advantages, Challenges, and Future Directions of STEM Education
Authors: Yang Shuai , Oh Eunjoo
Published: November 2024

STEM education (Science, Technology, Engineering, and Mathematics), as a key model in 21st-century global educational reform, has become a central focus due to its advantages in cultivating interdisciplinary skills, critical thinking, collaboration, communication abilities, and in stimulating students’ interest in learning. By integrating interdisciplinary knowledge, STEM education not only equips students to address complex real-world problems but also significantly enhances their practical skills. However, the implementation of STEM education faces challenges such as the complexity of curriculum integration, insufficient teacher training, and the limitations of assessment tools, all of which hinder its broad adoption and effective implementation. This study aims to comprehensively analyze the advantages of STEM education, explore its key challenges, and propose future development directions. By offering theoretical support to education policymakers, school administrators, and frontline teachers, the study seeks to promote the sustainable development and innovation of STEM education.
Path Planning Algorithms for Mobile Robots Based on Deep Reinforcement Learning
Authors: Zhang Zihan
Published: November 2024

This paper gives an introduction of path planning algorithms for mobile robots based on deep reinforcement learning (DRL). Firstly, the traditional path planning algorithms are compared with the deep reinforcement learning path planning algorithms. One key advantage of DRL-based algorithms is their ability to meet real-time interactions due to lower calculation requirements. Then, some basic path planning algorithms based on deep learning used in unknown and dynamic environment are introduced. After that, the efforts on the improvement of the basic DRL-based path planning algorithms are discussed. Their training results are compared with the traditional path planning algorithms and the DRL-based path planning algorithms without improvements. Finally, the advantages and disadvantages of DRL-based path planning algorithms are analyzed. Although these algorithms have already a relative fast convergence speed and high success rate, they still do not meet the accuracy requirement for sophisticated work. Besides, the train period is also expected to be shorten further. The potential improvements in the future are also pointed.
Thermodynamic modeling and simulation of working process of high efficiency two-stroke engine
Authors: Liu Zeyuan
Published: November 2024

In this paper, the thermodynamic modeling and simulation of high-efficiency two-stroke engine are studied. Based on the assumptions of uniform distribution of working fluid, adiabatic process and complete combustion, key parameters such as initial volume and compression ratio are set, and the model is established according to the ideal gas law. The model includes energy and mass conservation equations and state equations, and is used to describe the thermodynamic behavior of the engine. Using MATLAB/Simulink platform, the influence on performance was evaluated by adjusting the parameters such as fuel injection time and quantity, inlet size and combustion chamber shape. The results show that optimizing fuel injection strategy can balance power output and fuel economy, increasing inlet size can improve charging efficiency, and improving combustion chamber shape is beneficial to enhance flame propagation and combustion stability. The performance of the engine under different working conditions is analyzed, and the design optimization suggestions are put forward accordingly, aiming at improving the engine performance in an all-round way and providing theoretical and practical guidance for the design of high-efficiency and environment-friendly two-stroke engine.
Research on Weather Index-Based Insurance Method Based on EMW-AHP Algorithm
Authors: Xu Zhiyuan , Ji Yiyan , Zheng Qiaoyi
Published: November 2024

Extreme-weather events are becoming a crisis for property owners and insurers. The world has endured “more than $1 trillion in damages from more than 1,000 extreme-weather events in recent years.” However, by classifying the risk caused by extreme weather with weather index, weather index-based insurance method can be interesting for both property owners and insurers. This paper investigates the construction of the weather index-based insurance method following the example of two cities that experience extreme weather. This investigation is based on weather situation data form 40 different cities. Furthermore, In this paper, EWM-AHP algorithm is used to process the data, so as to construct the weather index-based insurance method. The results show that the regional weather risk can be divided into four levels according to the weather index calculated by equation given in the insurance method.
Optimization of Thermodynamic Cycles, Control System Innovation, and Reliability Enhancement in Variable Cycle Engines
Authors: Chen Yanjun
Published: November 2024

This paper examines the design and optimization of Variable Cycle Engines (VCEs) to achieve high efficiency across various flight conditions. By adjusting the bypass ratio, VCEs can optimize performance in both low-speed and high-speed flights, enhancing fuel economy and flight performance. Key areas include optimizing thermodynamic cycles through flexible bypass ratio adjustments and developing advanced multi-parameter control systems for precise and efficient operation. Despite increased complexity and weight, VCEs offer significant performance gains. Future research should focus on lightweight materials, robust control algorithms, and system integration to further improve VCE performance and reliability. These advancements will ensure VCEs play a crucial role in the future aviation sector, driving improvements in fuel efficiency, performance, and safety.
The Impact of Anxiety on Interpersonal Trust Among Individuals Undergoing Drug Rehabilitation in Compulsory Isolation Centers and Community Settings
Authors: Cao Xinyu , Zhu Meihong
Published: November 2024

Drug abusers often seek escapism and self-satisfaction by re-using drugs when facing anxiety and interpersonal conflicts. Enhancing their ability to build and maintain interpersonal trust is crucial for improving social interactions and external support. This study aims to analyze the impact of anxiety on interpersonal trust among individuals undergoing drug rehabilitation in compulsory isolation centers and community settings.
Application of Xgboost Model to Predict Bank Loan
Authors: Fang Yihan
Published: November 2024

Nowadays the bank loan has been a high-frequent behavior in the field of finance. Predicting the deposits paid by the lenders can effectively reduce the risk of credit fraud and avoid the loss of bank. Traditional methods like classification regressons and support vector machines  are difficult to deal with large sets of data and with relatively low accuracy. In this paper, a novel and robust method called XGBoost is applied in the bank loan and achieves a high accuracy. Also, proving the accessibility of XGBoost model in the business analysis field. The data set used in this study comes from a real bank customer database, which contains 16 variables. Regarding the categorical variables, this paper used one-hot encoding to make these variables can be identified by the model. Following by two steps feature selection, firstly used LVQ to filter variables with low importance, then used RFE to further select 11 variables. After that, this paper used these variables to build a XGBoost model to predict the bank loan deposit. Through hyperparameters optimization, this paper achieved a final accuracy of 80.62%, which shows an excellent model performance. In the future, this model can be used in the bank loan decision systems to determine the deposits that paid by lenders.
Research on Pricing Model of New Energy Vehicle Aftermarket Parts Based on Computer Simulation Technology
Authors: Yang Tengjian , Zhi Yunsheng , Hao Qi , Dong Qingyi , Zhang Fan
Published: November 2024

The paper presents a research method in the field of pricing for new energy vehicle parts. Firstly, a multidimensional approach is employed to comprehensively determine the fundamental factors affecting the pricing of new energy vehicle parts. Secondly, the method of index contribution is utilized to identify effective indicators of influencing factors. Subsequently, using these effective indicators, pricing models for new energy vehicle parts are separately constructed for the same region and different regions. Finally, computer dynamic simulation methods are applied to simulate and fit two pricing models. The results indicate that the proposed method of "Research on Pricing Model of New Energy Vehicle Aftermarket Parts Based on Computer Simulation Technology" can to some extent meet the requirements within the new energy vehicle industry.
A High-Dimensional Data Regression Model Based on Stacking-Gaussian Process Algorithm
Authors: Feng Yizhe , An Yongqi
Published: November 2024

In order to mine valuable information and potential rules from a large amount of data, processing high-dimensional data and establishing regression prediction models has become a hot research topic in the field of machine learning. High-dimensional input and nonlinear relationship fitting are two common problems in establishing regression models. Based on this, this paper proposes a high-dimensional data regression model based on a stacking framework and Gaussian process algorithm. Specifically, on the one hand, the stacking framework is used to alleviate the curse of dimensionality problem caused by high input dimensions. On the other hand, based on different kernel functions, the Gaussian process regression model can fit linear or nonlinear connection functions of different complexity. Simulation experiments and real data analysis show that the proposed method has smaller prediction errors, better prediction accuracy, and good generalization performance compared to some contrastive methods such as Random Forests, Lasso Regression, and Back Propagation Neural Network, demonstrating the superiority of the proposed model.
Advances and Prospects on Additive Manufacturing Used for Medical Implants
Authors: Fan Yaocong
Published: November 2024

Additive manufacturing (AM) is commonly used in the automotive, medical, and aerospace industries. With people concentrating more on healthcare, AM technology provides a more complex and free product structure, a growth spike in the application of AM can be seen in this field. Therefore, this paper focuses on a specific field of the medical industry, implants. This paper focuses on the latest improvements in AM used for implant production. Based on the relevant research reported on the Web of Science and Elsevier over the past five years, this article introduces the principles of the most widely used 3d printing technology for implant fabrication. It discusses the reasons for their successful use in this field. The existing typical technical routes and their advantages and limitations are summarized. This research also shows the latest advancements in those technologies. Based on their current characteristics and situations, this study gives some suggestions about potential further improvements and development prospects. This study provides an in-depth analysis of AM in the field of implants in the industry and points out the development direction of AM in the medical field in the future.
Comparisons Between Fuel Cells and Electric Engines and the Improvements in Engine Technology
Authors: Cheng Yihan
Published: November 2024

In addressing the pressing problem of carbon emissions and their part in the greenhouse effect, this paper emphasizes how important sustainable development is. The emphasis is on the transportation industry, which is responsible for a large portion of carbon footprints because of emissions from conventional combustion engines, which produce large amounts of greenhouse gases, including carbon dioxide, carbon monoxide, sulfur dioxide, and nitrogen oxides. The study presents electric batteries and fuel cells as practical countermeasures. It provides a thorough analysis by diving into the workings, common models, and procedures of these two engine kinds. After that, the study performs a comparison analysis of the benefits and downsides of fuel cells and electric batteries, taking into account several varieties within each category. This report, which offers a comprehensive overview of the current state and possible developments in fuel cell and electric engine technology, is based on experimental data and designs from previous research. Future advancements aimed at producing more eco-friendly and efficient transportation systems will be guided by the insights obtained.
Research on Vegetable Sales and Pricing Based on ARIMA Model and Regression Analysis
Authors: An Wenshuo , Wang Shuqi , Li Junhuan , Liu Yingchu
Published: November 2024

Vegetable products are perishable, so the supermarket's decision to replenish and price vegetables daily and sell defective products at a discount has a great impact on the profitability of the supermarket. This study is based on vegetable sales data. The aim is to analyze the relationship between total sales volume and cost markup pricing, study the seasonal changes in daily replenishment volume and its relationship with sales volume, determine the daily replenishment volume and pricing strategy for the next week, and explore the relationship between summer sales volume and average profit margin. Firstly, the sales data are classified by season and discounted or not, and the relationship between total sales and pricing is analyzed by replacing cost-plus pricing with average profit margin. Secondly, the daily replenishment of vegetables was correlated with the total sales, and the ARIMA time series model was used to predict the total daily replenishment in the coming week. Secondly, the daily replenishment volume of vegetables was correlated with the total sales volume, and the ARIMA time series model was used to predict the daily replenishment volume for the next week. Finally, a relationship model between sales volume and average profit margin was obtained through regression analysis, providing decision-makers with specific predictions on the total amount of daily vegetable restocking and pricing strategies for the next week, as well as a deeper understanding of the relationship between sales volume and average profit margin. Through the data analysis and modeling of this study, specific predictions on the daily replenishment volume and pricing strategy of vegetables for the next week have been provided to decision-makers, as well as a deep understanding of the relationship between sales volume and average profit margin. Through the data analysis and modeling of this study, the specific decision-making methods and promotion strategies of replenishment pricing were obtained, which provided a useful reference and guidance for the decision-making of vegetable supply and marketing.
Research on the Influence Mechanism of College Students' Entrepreneurial Tendency Based on Structural Equation Modeling
Authors: Gao Xindi
Published: November 2024

With the continuous fluctuations in the global economic landscape, college student entrepreneurship has emerged as a vital driver of economic progress. Through a systematic comparison of correlation analysis and structural equation modeling, examining aspects such as functional structure, primary graphs, second-order factors, mediating effects, and their applicable conditions in the SPSS and AMOS environments, this paper develops a structural model incorporating factors like personal characteristics, family circumstances, social support, and entrepreneurial education, while also proposing several research hypotheses. By analyzing the collected sample data, the model is validated, revealing that these elements significantly influence college students' entrepreneurial tendencies, with intricate interconnections shaping the pathways of influence. Focusing on the entrepreneurial situation of students attending undergraduate institutions in Jilin Province, the study delves into existing issues and their root causes, offering targeted strategies and recommendations. Consequently, this research enhances entrepreneurship education and training for college students, raising the success rates of their entrepreneurial ventures; ensures institutional backing for student entrepreneurship while balancing academic pursuits; and encourages involvement from diverse external entities in students' entrepreneurial activities, aiming to elevate the overall entrepreneurial capability of college students.
Study on Lamprey Population Growth and Sex Differentiation Models Using Bayesian Methods
Authors: Chen Anhang , Chen Guangyu
Published: November 2024

This study developed a predictive model to assess the ecological impacts of changing sex ratios in various lamprey populations, categorizing them into parasitic, non-parasitic, anadromous, and potamodromous types. Critical data on temperature tolerance and growth durations for four representative species were collected to analyze the interactions under different sex ratios, focusing on both competitive and mutualistic dynamics within communities. The model explored sex differentiation mechanisms through various adjustment modes, linking lamprey growth rates to environmental factors like temperature and resource availability. Bayesian methods were utilized to integrate prior knowledge and address uncertainties, predicting larvae's sex-based outcomes. Additionally, a Bayesian biomass dynamic model evaluated population dynamics considering birth and death rates. Markov Chain Monte Carlo (MCMC) simulations within this Bayesian framework facilitated robust parameter estimation, significantly enhancing the understanding of how sex ratio changes impact species-specific and regional biodiversity and population dynamics.
Exploration and Practice of Cross School Credit System Teaching Reform in Engineering Project Financing Course
Authors: Han Yudong , Liu Xiaowei
Published: November 2024

With the rapid development of economic globalization and technology, higher education is facing new challenges and opportunities. The traditional education model can no longer fully meet the needs of modern engineering and technical talents, especially in the complex and ever-changing field of engineering project financing. In order to adapt to this change, this article explores the possibility and implementation strategies of introducing a cross-school credit system for engineering project financing courses in civil engineering majors. The reform aims to broaden students' knowledge horizons, enhance their ability to solve practical problems, and promote communication and cooperation among universities by sharing high-quality educational resources. This article first analyzes the main problems in the current teaching of engineering project financing courses, such as the disconnect between theory and practice, and uneven distribution of teaching resources. Subsequently, through the study of successful cases both domestically and internationally, a specific plan for implementing the cross-school credit system was proposed. This plan not only covers the unification of curriculum standards and the design of evaluation systems, but also pays special attention to how to use modern information technology means, such as online learning platforms and virtual laboratories, to achieve cross regional teaching interaction and resource sharing. Meanwhile, based on the successful experience of pilot projects, this article proposes suggestions for further promoting this model and looks forward to the future development trend of engineering project financing course teaching. We believe that with the advancement of information technology and changes in social demands, the cross-school credit system will become one of the important ways to cultivate composite engineering and technical talents that meet the requirements of the new era.
Output Performance of PEMWE under Fluctuating Working Conditions
Authors: Kang Dugang , Qiu Yongjun , Kang Ligui , Huang Yanyun , Ma Lin , Huang Song
Published: November 2024

The fluctuation current introduced by renewable power sources often fluctuates in a wide power range due to their own fluctuation, greatly affecting the performance and safety of the electrolysis cell. Therefore, the input power of PEM water electrolysis process is variable, and it needs to be adjusted in combination with its dynamic characteristics during operation to ensure its performance and safety. In the transient model, research has found that under the condition of step voltage, the current density rapidly decreases, then rapidly increases, rises to the highest point, and slowly decreases before finally stabilizing. On the contrary, under the condition of step flow rate, the current density response is slow and takes about 8 seconds to stabilize.
An Innovation Proposal Employing Lead Screw Mechanism for Office Chair Height Adjustment
Authors: Yan Xiaotian
Published: November 2024

Currently, existing office chairs contain reclining and height adjustment capabilities but often require intensive manual adjustment or lack full customization. The motivation behind this concept was to create an office chair that maintains its utility while integrating more advanced mechanical designs to increase adjustability. The motorized seat height adjustment that implements a lead screw mechanism eliminates the need to manually crank a lever or apply pressure to the chair seat, which is common in chairs using a pneumatic cylinder. In this paper, a feasible innovation employing a lead screw mechanism for an office chair height change system is proposed. Firstly, the general background of current office chair height adjustment designs and drawbacks are discussed. Secondly, an overview of the modeling of the overall chair assembly and functions of the height change system’s parts is presented. Finally, analytical calculations are analyzed, and finite element analysis is conducted using SolidWorks to assess the nominal shear, nominal stresses, and static displacement of the lead screw. The result of this paper proves the feasibility of the implementation of the lead screw mechanism in office chairs.
VR/AR-based Wind Turbine Gearbox Maintenance Training System
Authors: Tang Qiancheng , Tang Yang
Published: November 2024

In view of the remote geographical location of wind farms, complex environmental conditions, especially the complex structure of gearboxes in wind turbines, which leads to the difficulty of equipment maintenance and troubleshooting, combined with the rapidly developing virtual reality technology (VR) and augmented reality technology (AR), a VR/AR wind power gearbox maintenance training system is designed to solve the above problems. The system includes a maintenance training system for gearbox maintenance, disassembly and assembly learning, exercises, working principle display, detailed data query of parts and AR model auxiliary inspection, to help maintenance personnel better complete the maintenance work of gearbox.
Finding Factors Influencing Tennis Match Trends Based on AHP-TOPSIS and LightGBM
Authors: Fu Qiang
Published: November 2024

The paper conducts a comprehensive analysis of the 2023 Wimbledon men's singles tournament in an attempt to quantify momentum to look at swings in play and runs of success, and to make predictions about flows of momentum. The paper introduces an innovative approach to analyzing tennis match dynamics by integrating the Analytic Hierarchy Process-Technique for Order Preference by Similarity to Ideal Solution (AHP-TOPSIS) with the LightGBM algorithm. The AHP-TOPSIS model quantifies player momentum, identifying key factors such as serving ability, strength, mentality, and in-game state that influence match outcomes. A novel aspect of this study is the application of the CUSUM algorithm to detect significant turning points within matches, providing a granular insight into the flow of play. Subsequently, the LightGBM model, known for its efficiency and accuracy, is employed to predict these turning points, offering a comprehensive predictive framework that enhances the understanding of match dynamics. The paper's findings underscore the predictive power of the serving factor and the state factor in determining match swings. This research contributes to the field by offering a more nuanced and data-driven perspective on tennis match analysis, with practical implications for both players and coaches in strategizing for competitive advantage.
The Application of Diesel Engine: From 21st Century to Modern Life
Authors: Wang Shujian
Published: November 2024

In this article, the author investigates the evolution and development of diesel engines, examining various types and their diverse applications. The analysis covers the advantages and drawbacks of these engines from the 20th century to the present, highlighting how efficiency and environmental concerns have become central to diesel engine innovation. Despite significant advancements, many challenges persist. The progress in engine technology has led to the creation of robust and time-tested engines, yet addressing the residual issues remains critical. As technology evolves, it is crucial to manage these developments effectively, ensuring that emerging problems are not overlooked. The future of diesel engines hinges on the continuous improvement and adoption of more advanced technologies to meet the growing demands of efficiency and sustainability. To achieve this, ongoing research and development are essential to overcome existing challenges and pave the way for innovative solutions that align with environmental and efficiency goals. This comprehensive analysis underscores the importance of balancing technological advancement with responsible management of new and existing issues.
The Impact of China: U.S Trade Frictions on Chinese Enterprise Innovation
Authors: Huang Ruoxi , Li Jiajing , Yu Jiatong
Published: November 2024

The trade frictions between the United States and China has brought great uncertainty and risk to the global economic development environment. Using the panel data of Chinese listed firms from 2009 to 2023, the Difference in Difference (DID) panel model and mediation effect model are employed to study the impact of the US-China trade frictions on firms' innovation. The empirical results show that the US-China trade friction has a negative impact on R&D innovation of Chinese firms. Further research finds that US-China trade friction has a stronger negative effect on R&D innovation of non-state-owned firms and the central and western regions. Finally, this paper finds that US-China trade friction will reduce corporate technology innovation by exacerbating corporate financing constraints.
A Survey on Hair Modeling
Authors: Yang Jingrong
Published: November 2024

Hair modeling is a vital research area in computer graphics, aiming to create realistic, controllable, and interactive hair models. Recent advancements in computer vision, deep learning, and physical simulations have significantly propelled the field of hair modeling. This paper provides a comprehensive overview of current hair modeling techniques, including generative models, physics-based approaches, interactive editing methods, deep learning-driven methods, and 3D modeling and reconstruction techniques. The fundamental principles, advantages, limitations, and potential applications of these methods are discussed.
Preface: 6th International Conference on Mechanics, Simulation and Control (ICMSC 2024)
Authors: Thackeray Cynthia , Li Hang
Published: November 2024

The 2024 6th International Conference on Mechanics, Simulation and Control (ICMSC 2024) was held during September 21-22, 2024, in San Jose, USA. This conference aims to bring together academic scientists, leading engineers, industry researchers and scholar students to exchange and share their experiences and research results, and will discuss the practical challenges encountered and the solutions adopted. The conference provided delegates with the opportunity to meet face-to-face with new ideas and application experiences, build business or research relationships, and find global partners for future collaboration.
ICMSC 2024 has been deliberated to showcase research accomplishments and to enrich the educational experience in about all aspects of mechanical engineering, applied mechanics, computer simulation, mathematical modeling, intelligent computing, automation and control engineering. The conference organizing committee has invited three keynote speakers. The two-day conference with nearly 24 oral presentations created the heart of the conference and provided ample opportunity for discussion during the conference.
We have many people to thank and would like to put the appreciation of their contribution on record. In this regard, the largest burden fell upon the experienced shoulders of keynote speakers, session chairs, and our technical reviewers along with substantial assistance received from active student volunteers.
The ICMSC Conference Committee
San Jose, USA
Temperature Forecasts in New York City Exploiting ARIMA Model
Authors: Du Shaofan
Published: November 2024

Efforts to estimate air temperatures play an important role in predicting climate impact on ecological, industrial, and agricultural fields. Accurate temperature prediction benefits the government, industry, and the public for planning activities. Moreover, the temperature forecasts provide people with safeguard life and property. This paper conducts an exploratory data analysis of the temperature time series data, taking New York City as a representative. The time series data contains the daily temperature in New York City from 1995 to May 2020. The considerable time scope is so comprehensive that it makes a forecast based on the periodic performance similar in approximately 20 years. In this work, the autoregressive integrated moving average (ARIMA) model is leveraged to forecast future values based on past periods. Its hyperparameters are determined by autoregressive correlation function, partial autoregressive correlation function, and Bayesian Information Criterion. The ARIMA model assumes that the future performance will resemble the past, and the temperature in different time stamps is similar, which makes it a suitable model in this case.
The Research on Temperature Variation Characteristic of Wood during High-intensity Microwave Pretreatment
Authors: He Xia , Yang Guanmin , Yan Xueming
Published: November 2024

High-intensity microwave pretreatment (HIMP) is a kind of wood modification technology with great potential. In this study, a microwave (MW) treatment of plantation poplar (populous deltoids) wood was investigated by applying MW treatments with varying conditions, such as radiation power, irradiation time, and initial moisture content of the wood. The effect of microwave pretreatment conditions on internal temperature of wood was studied systematically. Results show that the temperature of wood increased with the microwave radiation intensity and the irradiation time. Excessive moisture content would make the wood heated up slowly. The temperature of wood changed in three stages: rapid heating stage, constant temperature section and slow heating section.
Analysis of the Dynamic Response of A Liquid Rocket Under Seismic Waves
Authors: Chen Shiji , Wang Xueren , Chen Jiazhao , Zhang Xuan , Weng Jiexin
Published: November 2024

By adopting time history method in software ANSYS, dynamic response of a liquid rocket was analyzed when it was suffered from earthquake wave TAFT and EI, and the displacement and stress of the rocket were calculated. The result showed that the liquid rocket swung along the acting direction of the earthquake wave. The higher the position of rocket, the larger the swing, and the maximum displacement located on the top of the rocket, and the maximum stress located at the support places on the rear part. The higher the earthquake magnitude, the larger the swing, and the larger the maximum equivalent stress. The rocket has the possibility to fall down and damage in structure under a strong earthquake over 7 grade.
stupefacenti nel XXI secolo
Authors: Nencini Paolo
Published: November 2024

Finalizzato a proteggere la salute pubblica, il divieto dell’uso non terapeutico di numerose sostanze psicoattive è norma universalmente applicata nella cornice di un sistema internazionale di controllo. Tuttavia, le strategie di riduzione dell’offerta non sono riuscite a ridurre il consumo di un numero sempre più vasto di sostanze; inoltre, l’inabissamento del mercato nell’illegalità ha generato un inaccettabile incremento della violenza. Liberalizzazione, legalizzazione e decriminalizzazione sono le strategie proposte per governare un fenomeno che appare impossibile eradicare. Dopo avere esaminato tali strategie, l’articolo mostra quali siano le resistenze a tali propositi riformatori e quali siano per contro i progressi su tale via, soffermandosi infine sulla necessità di riconsiderare lo stato legale dei farmaci psicotropi secondo criteri scientifici più solidi che non un generico senso di cautela.
VOLATILE COMPOSITION AND ANTIBACTERIAL ACTIVITY OF CEIBA INSIGNIS FLOWERS
Authors: AMJAD M , INTISAR A , SATTAR T , HUSSAIN T , BATOOL N , AHMAD S , MUTAHIR Z , CHATTHA MB
Published: November 2024

This study reports the volatile oil composition and antibacterial activity of the flower of Ceiba insignis.  Oil extraction was carried out by microwave-assisted distillation where a yield of 0.11% was obtained. A total of 17 compounds were successfully identified by gas chromatography mass spectrometry out of which the most abundant constituents were furfural (20.18%), heptadecan-2-one (13.81%), pentacosane (10.82%), methyl-5-furfural (8.27%), heptacosane (6.09%) and phytol (5.88%). The antibacterial potential of this oil was evaluated by using the agar disc diffusion technique against 4 different strains. The oil exhibited the highest activity against K. pneumoniae (12.7mm), followed by S. aureus (12mm), E. coli. (11mm) and P. aeruginosa (10.7mm).
IMPACT OF EARLY SUCCESSFUL PPCI ON LEFT VENTRICULAR EJECTION FRACTION AMONG STEMI CASES
Authors: KAMAL S , KHAN AS , EMMAN UE , KHAN SA , ADEEL . , QAZI K
Published: November 2024

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide, making holistic health management essential for patients. Psychological well-being, particularly stress, depression, and anxiety management, is critical for effective CVD rehabilitation. Interventions focused on stress management hold promise for reducing these negative psychological impacts, thereby enhancing patient health and recovery Objective: T o determine the early impact of successful primary percutaneous coronary intervention (PPCI) on left ventricular ejection fraction (LVEF) and clinical outcomes in patients with ST-segment elevation myocardial infarction (STEMI). Methods: This study included 60 STEMI patients who underwent PPCI from July 2023 to July 2024. Patients were included if presented within 6 hours of onset of symptom. LVEF was assessed at presentation and six months post-PPCI. The post-procedural TIMI flow grade was recorded. Data on patient demographics, comorbidities, and procedural outcomes were collected. Results: The mean age was 59.57 ± 10.46 years, with 71.7% male. LVEF at presentation was 36.70 ± 4.76%, which significantly improved to 54.88 ± 2.73% at six months (p = 0.0001). Post-PPCI, 66.7% of patients achieved TIMI grade 3 flow, and 33.3% had TIMI grade 2 flow. In-hospital mortality was 3.3%, and major adverse cardiac events (MACE) occurred in 5% of patients. Conclusion: Early successful PPCI in STEMI patients results in significant improvement in LVEF and favorable clinical outcomes.
EFFECT OF STRESS MANAGEMENT ON LEVEL OF DEPRESSION, ANXIETY AND STRESS IN CARDIOVASCULAR DISEASE PATIENTS
Authors: KHAN MA , GUL R , IRSHAD E
Published: November 2024

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide, making holistic health management essential for patients. Psychological well-being, particularly stress, depression, and anxiety management, is critical for effective CVD rehabilitation. Interventions focused on stress management hold promise for reducing these negative psychological impacts, thereby enhancing patient health and recovery. Objective: This study aimed to evaluate the effect of a structured stress management intervention on reducing stress, depression, and anxiety levels in patients with cardiovascular disease. Methods: A pretest-posttest design with a control group was employed to assess the impact of stress management on mental health outcomes in CVD patients. Sixty patients with CVD were recruited from a private and a government hospital in Rawalpindi, Pakistan, in 2023. Patients were randomly assigned to either a control group (n=30) or an intervention group (n=30). The intervention group participated in eight weekly 90-minute sessions focused on stress, thought-feeling connections, relaxation techniques, cognitive distortion detection, management of anxiety and depression, social relations enhancement, and effective coping strategies. Data were collected at baseline (pretest), 1.5 months, and 3 months post-intervention using validated scales to measure anxiety, stress, and depression levels. The control group received standard care without any psychological intervention. Statistical analysis was performed using SPSS version 25, and repeated measures ANOVA was applied to evaluate changes in stress, depression, and anxiety levels over time. Results: The results revealed a significant reduction in stress, depression, and anxiety levels in the intervention group compared to the control group (p<0.05). Participants who underwent the stress management intervention showed substantial improvement in psychological well-being at both the 1.5-month and 3-month follow-ups. Conclusion: The stress management intervention demonstrated a significant positive impact on reducing anxiety, stress, and depression in CVD patients. These findings highlight the value of incorporating structured psychological support as a part of comprehensive care for cardiovascular patients, providing essential guidance for healthcare practitioners to enhance patient outcomes through holistic care.
Effect of Anthropometric Parameters on Quadriceps Femoris (Q) Angle: An Analytical Cross-Sectional Study from Iraq
Authors: Assi Mohammed Hussein , Al-Rubai Abdal-Jabbar Falih , Alwaeli Ali Mohsin
Published: November 2024

Background: One important clinical indicator that shows how the muscle affects the patellofemoral joint is the quadriceps angle. This angle is formed between the quadriceps femoris and the patellar ligament. It is also thought to be a key factor in maintaining good posture and patellar movement. The angle is often used as a clinical sign to check on people who have problems with their knee joints. Objective: The study is planned to measure the mean Q angle in Iraqi adult individuals with the goal of referring data to help improve the clinical diagnosis and evaluation of patients with knee joint malalignments. Methods: The right and left Q angles of 200 participants were measured using a universal goniometer. The relationship between Q angles and different anthropometric parameters was tested using appropriate statistical tests. Results: The mean right Q angles for males’ measure 15.63° and for the females 17.58°. The mean left Q angles for males measured 14.18° and for the females were 16.14°. Both Q angles (right and left) were greater in females. The study revealed a strong negative correlation between height and QA, a moderate negative correlation between weight and QA, and a slight negative correlation between BMI and QA. Conclusions: The study improves understanding of the usual range of the Q angle in a study group of seemingly healthy adults and attempts to establish a reference value for orthopedic surgeons, biomedical engineers, forensic specialists, and anthropologists.
Evaluating the administration of electronic university exams from the point of view of the teachers
Authors: Ahmed May Faisal
Published: November 2024

دراسة ميدانية استهدفت تقويم إدارة الامتحانات الجامعية الإلكترونية من وجهة نظر المعلِّمين، واعتمدت هذه الدراسة المنهج الوصفي التحليلي. تكوَّن مجتمع البحث من (1020) معلِّمًا، واختيرت عينة البحث بالطريقة الطبقية العشوائية بنسبة (20%) من مجتمع البحث، إذ بلغ عدد أفراد العينة (205) من مدرسي الثانوية. وصُمِّمت استبانة تضمنت (40) فقرة موزعة بين خمسة مجالات دراسية، وتأكدت الباحثة من صدقها وثباتها. حُلِّلت بيانات البحث باستعمال برنامج (SPSS)، وقامت الباحثة بتطبيق الاستبانة في العام الدراسي 2021-2022، وتوصلت إلى نتائج أهمها: إن مستوى تقويم إدارة الامتحانات الإلكترونية الجامعية كان جيِّدًا جدًّا ويعبِّر عن مهارة الهيأة التدريسية ومقدرتها، والتزامها بتدوين المعلومات في سجل خاص للامتحان. وفي نهاية البحث عدد من التوصيات في ضوء النتائج المتحققة.
المواقع الأثرية خارج أسوار بطوليمايس
Authors: عبد ربه مفتاح عثمان
Published: November 2024

أسست مدينة بطوليمايس حسب ما يتوفر من مصادر أكلاسيكية كميناء لمدينة برقة، لم يرد إلينا أي اسم لهذه المستوطنة قبل القرن الرابع ق.م حيث كانت تعرف باسم ميناء مدينة برقة وهو الاسم الذي ذكره لنا الكاتب الكلاسيكي سكولاكس  في أواخر القرن الربع قبل الميلاد، وربما يكون عدد من المستوطنين الإغريق الذين أسسوا مدينة برقة قد توجه والى هذا الموقع الذي يعد الأنسب ملاحيا والأقرب جغرافيا في المنطقة الساحلية الواقعة ما بين توكره والعقلة، ومن خلال بقايا الأواني الفخارية التي عثر عليها في هذه المدينة والتي تعود إلى فترة مبكرة جدا من الاستيطان الإغريقي قورينائية وهو ما بين 620 و600 ق.م. أن المعطيات المتوفرة حتى الآن تدعم الرأي القائل بان الاسم القديم لبطوليمايس هو برقة وأن هناك ارتباط وثيق جدا ما بين المدينتين إلى درجة لا يمكن معها التفريق بين المدنيتين. وأصبحت بطوليمايس في عهد الإمبراطور ديوقليسيان (293-305 ) عاصمة جديدة لإقليم ليبيا العليا وصارت مقرا للأساقفة المسيحيين والذين كان من أشهرهم القسيس سينسيوس وظلت حتى منتصف القرن الخامس الميلادي عاصمة لهذا الإقليم. المهم في بحثنا هذا نحاول تسليط الضوء على أهم المواقع الأثرية التي تقع خارج أسوار مدينة بطوليمايس وعلاقتها بهذه المدينة.