bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Simpson’s Paradox and Its Applications
Authors: Lei Zhihao
Published: June 2024

As a matter of fact, the enigmatic nature and far-reaching consequences of Simpson's Paradox have captivated both scholars and professionals. On this basis, this investigation seeks to offer an exhaustive review of the paradox, examining its historical background, mathematical formulations, and its utilization in diverse sectors. To be specific, the study probes into how the paradox influences the efficacy of healthcare treatments, its contribution to sustaining gender inequality in educational settings like UC Berkeley, and the challenges it presents in analyzing data with multiple dimensions. The research also points out existing gaps in the literature, specifically the absence of methodical solutions for addressing the paradox in intricate, multi-faceted scenarios. Overall, the significance of this study lies in its multi-faceted exploration of Simpson's Paradox. It serves as a foundational text that aims to improve statistical literacy and promote a nuanced understanding of data interpretation, thereby contributing to better decision-making across multiple disciplines.
ARIMA-Xgboost Based Pricing and Replenishment Strategy for Perishable Goods
Authors: Mei Yifan , Yang Yiqing , Chen Huirong , Shi Weihan , Su Xinhua
Published: June 2024

Based on the enterprise sales data, the study analyzes the correlation between sales of commodities, taking vegetable products as an example, and takes into account the impact of replenishment, pricing, and sales of perishable products, and considers the joint decision-making problem of pricing and dynamic replenishment of perishable products, and designs the ARIMA-XGBoost joint decision-making model. The results show that there is a sales correlation between different commodities, and through sales, big data can be a more accurate prediction of the replenishment amount in the future period, so based on the pricing and the maximization of the revenue model set up by the study can achieve more accurate replenishment and pricing decisions.
Analysis of Guided Filters in Image Processing Evidence from Feathered Mask
Authors: Jiang Shengting
Published: June 2024

As a matter of fact, with the development of the electronic computers, the technique of fast Fourier transform is used in the realm of image processing. In reality, when dealing with different situations, a variety of filters and kernels will be applied and the guided filter is one of these. With this in mind, in this study, the specific task of feathered mask of image processing will be analyzed. According to the analysis, the filters improve the details at the edge of the image mask. It shows that the guided filters perform well on edge preservation and image enhancement. Moreover, the limitations and improvement will also be raised in the article at the same time. This paper aims to raise the interest of the guided filters in the realm of image processing and give some future outlooks of this method. Overall, these results shed light on guiding further exploration of Feathered musk.
Research of Influence Factors on House Price through Worldwide especially in the Factor of Human
Authors: Lyu Zhe
Published: June 2024

Since the monetization and commercialization of housing in China in 1998, the housing price has continued to rise, and the high housing price has caused no small trouble to the life of ordinary people. At the same time, with the development of China's economy, a large number of people flow from rural to urban, from the central and western to the east. This paper makes an empirical analysis on the data of more than ten cities from 2000 to 2009. Then the relevant data was used. Finally, this paper estimates the impact of real estate price on population migration from 2000 to 2009. The results show that during 2000-2009, the real estate price has a significant impact on population migration, and the real estate price has become an important factor in each region. Generally, areas with high housing prices also have high per capita income, which attracts more population inflows. According to the research, the following suggestions are put forward: strengthen the interactive research of real estate price and population migration: strengthen regional exchanges and cooperation to grasp the overall population flow trend; strengthen the construction of low-income housing; improve the transportation network; adjust the structure of land supply and stabilize real estate prices.
Monte-Carlo Simulations and Applications in Machine Learning, Option Pricing, and Quantum Processes
Authors: Liu Renning
Published: June 2024

As a matter of fact, Monte Carlo simulations have evolved as a powerful computational tool with applications spanning various domains in recent years, thanks to the rapid development of computation ability. With this in mind, this research paper explores the application of Monte Carlo simulations in machine learning, optical pricing, and physical quantum processes. To be specific, this study will discuss the methodology of Monte Carlo simulations, present simulation results, and highlight the significance of employing these simulations in diverse fields. Additionally, this study will summary the historical development of Monte Carlo simulations, provide a literature review of main application scenarios, as well as outline the motivation behind this research. At the same time, it will address the current limitations of Monte Carlo simulations in these applications and offer insights into future prospects for usage. Overall, these results shed light on guiding further exploration of implementation in the state-of-art fields.
Study on Correlative Factors of Seawater Temperature Based on Regression Analysis
Authors: Chen Yingting , Zhao Runyi
Published: June 2024

The seawater temperature is important that affects marine ecosystems and marine life. This paper aimed to analyze the main factors that affect seawater temperature using Bottle Database collected at California Cooperative Oceanic Fisheries Investigations stations. The dataset contained seawater samples collected using bottles. Linear regression was performed using temperature as the dependent variable and depth, salinity, oxygen, and potential density as independent variables. Stepwise methods were used to select variables for regression models. To determine the most influential factor affecting temperature, the random forest was used to rank four independent variables. The plot generated by this analysis showed that potential density strongly influenced seawater temperature, followed by salinity, oxygen, and depth. Then four models were built, including Ordinary Multilinear regression, Linear regression considering the interaction, Linear regression with variable transformation, and Linear regression combining interactions and transformation. The 4th Model, had the highest adjusted R-squared and the lowest prediction sum of squares, making it the most useful model. This model indicated that 4 predictor factors all have significant effects on temperature, and their interactions also play a crucial role. Finally, model 4 can be used to predict water temperature based on depth, salinity, oxygen, and potential density, showing that seawater temperature could be predicted efficiently using these relevant variables. This study provides valuable insights into the main factors affecting seawater temperature and demonstrates the usefulness of linear regression and random forest approaches.
Analysis of the impact caused by sea level rise on tidal energy development and coastal areas
Authors: Chen Yinuo
Published: June 2024

Global warming has long been an important issue. Melting glaciers are one of its hazards, along with rising sea levels. Besides, tidal energy as an increasingly significant renewable energy has grasped people’s attention more than before. However, global warming has a remarkable effect on the power production from the tide. There are also some other effects which the rising sea level will have on the nearby coastal areas. It may interfere the tidal amplitude, tidal line, tidal cycle and the tidal surge, and each element will affect the efficiency of the tidal power plant. In this paper, the effects of rising sea level on tidal power are analyzed and some adaptation strategies to help the local communities are proposed.
Combustion Process and Performance of HCCI Engines under Different Fuels
Authors: Yan Minghao
Published: June 2024

In the wake of industrial advancement, environmental protection has garnered significant attention, particularly concerning engine-generated pollution. The Homogeneous Charge Compression Ignition (HCCI) engine emerges as a promising solution, offering enhanced combustion efficiency with diverse fuels. This research delves into the combustion characteristics of HCCI engines, employing various fuels under assorted conditions. For natural gas HCCI engines, an elevation in the hydrogen ratio bolsters the combustion reaction and augments thermal efficiency. A heightened compression ratio diminishes CO and HC emissions, albeit with a surge in NOx emissions. The n-butanol HCCI engine, utilizing a gasoline and n-butanol fuel mixture, reveals enhanced reactivity and thermal efficiency with an increased mixture ratio. Optimal power is achieved at an excess air coefficient (α) of 0.88, diverging from conventional aviation engines. The coal-based naphtha HCCI engine exhibits amplified thermal efficiency with escalating mixture ratios and temperatures. This comprehensive study underscores the pivotal role of fuel type and operational conditions in optimizing HCCI engine performance, contributing to the reduction of environmental impact while ensuring efficient energy utilization.
Analysis of Different Statistical Indicators for Machine Learning
Authors: Zhu Tiexuan
Published: June 2024

As a matter of fact, machine learning has been widely adopted in various fields on account of rapid development of computing ability in recent years. In reality, with advances in computer hardware and the explosion of data, machine learning has become an ideal choice for processing this data. With this in mind, processing such large amounts of data requires a lot of computing power and algorithms, and also offers a wide range of applications for machine learning. On this basis, this article mainly considers the formulation and application of statistical measures from his three aspects: classifier, regression, and clustering. To be specific, different metrics are presented and real examples are discussed in the various situation in detail. In addition, current application scenarios and limitations of machine learning are presented. At the same time, the prospects for further study are proposed. Overall, these results shed light on guiding further exploration of machine learning.
Research on the Construction of First-Class Courses in Applied Undergraduate Colleges Based on the OBE Concept: Take the "Film and Television Image Creation" Course as an Example
Authors: Xu Gang , Xing Lu
Published: June 2024

The construction of first-class courses in higher education is not only crucial for the quality of education but also forms the cornerstone of students' career development. This paper aims to explore the construction methods of the "Film and Television Image Creation" course in applied undergraduate colleges and universities to enhance teaching quality and optimize students' comprehensive qualities. By employing the Outcome-Based Education (OBE) theory, which is centered on learning outcomes, the paper emphasizes the importance of designing course objectives, teaching activities, and assessing students' learning achievements. The research method combines theory with practice, and through specific case analysis and course piloting, it elaborates in detail how to implement the OBE concept within the "Film and Television Image Creation" course. The study suggests that the implementation of the OBE concept helps to clarify teaching objectives, optimize the teaching process, and significantly improve students' creativity and practical skills. This reform not only enhances the teaching effectiveness of the course but also provides a solid foundation for the comprehensive development of students and their future careers. The systematic course design and outcome-oriented teaching methods hold significant theoretical and practical importance for the cultivation of applied talents.
Research On the Classification Patterns of High-Potassium Glass and Lead-Barium Glass Based On K-Means Clustering Analysis
Authors: Guo Shirong
Published: June 2024

This study employs the K-means clustering analysis algorithm to conduct a comprehensive investigation into the classification patterns of high-potassium glass and lead-barium glass. Initially, by selecting two cluster centers for analysis, significant differences in composition between high-potassium and lead-barium glass are revealed through the merging and simple processing of data samples from forms one and two. Subsequently, extensive analysis and statistics with multiple cluster centers reveal a suitable cluster ratio of 1:3, leading to the determination of four cluster centers for further analysis, resulting in the identification of four subcategories. Detailed analysis indicates one as a high-potassium type and three as lead-barium types. Through algorithmic computations and validation using the silhouette coefficient model, we summarize the composition characteristics of each category, demonstrating the rationality of the classification. Furthermore, fitting classification is applied to eight cultural relic samples, and the validity and sensitivity of the classification results are further verified through the silhouette coefficient model, ensuring the reliability of the classification.
Analysis of Planet Searching and Detection: Radial Velocity, Gravitation Microlensing and Transiting
Authors: Li Yuanjing
Published: June 2024

As a matter of fact, planet searching plays a critical role in astrophysics and cosmology. This paper focuses on three main methods of planetary search and detection: radial velocity, gravitational microlensing, and transit. First, this study introduces the background and significance of planetary search and detection, pointing out the importance of planetary detection for understanding the origin of the universe and the existence of life. Then, the article describes seven exoplanet detection methods and what they can detect. It explains the principles, instrumentation, and technical details of radial velocity method, transit method, and gravitational microlensing method, and cite some successful cases. Finally, this study looks forward to future directions of planetary search and detection, including the utilization of new observational equipment and techniques to improve detection efficiency and accuracy, and the search for more Earth-like planets and possible life existence. These results offer guideline for advancing the development of planetary detection.
Research on the Current Situation and Future Development Trends of Direct Air Capture Technology
Authors: You Truman
Published: June 2024

Global warming is getting worse over time, and it seems like world governments are still fairly reluctant to fully commit to a carbon neutrality plan. Vast amounts of research have been published demonstrating that CO2 emissions into the atmosphere greatly contributes to global warming, so much attention has been given toward ideas promising to reduce CO2 in the atmosphere. One idea that has been proposed to help achieve carbon neutrality is Direct Air Capture technology (DAC). DAC has existed as a concept since 1999 and is currently still in development. This report examines the current state of DAC technology as well as the opportunities that the future could hold. It is found that current DAC technology is very inefficient and it is believed that further improvements are too slow to create a big difference in the near future. Energy input is expected to drop in the coming decades., but not by a significant number. Future DAC technology seems to hold potential, with costs seeming to point to a better direction than modern technology. It is evident that the proper way to move forward in the future is to look toward other avenues of research while continuing to develop DAC technology.
Investigating Factors Affecting House Prices - Chicago as an Example
Authors: Qian Chengrui
Published: June 2024

House is a very important necessity in human society and its price is also highly concerned. With the rapid development of the society, the house price is also rising rapidly, how to find some favourable ways to buy a house is very important for people. This paper will firstly analyse the relationship between house price and some factors by grouping them with box-and-line diagrams, then further calculate the correlation coefficients between the factors and house price, and further correlate the factors with house price. After that, this paper will use multiple linear regression to analyse the relationship using house price as y and other eight variables as x. After that, this paper will conclude that Space, Garage, Bathroom, Lot will have a substantial positive impact on the price. The price will have a significant negative effect due to the bedroom. But Room, Condition, Tax will not have any effect on Price. Finally, this paper will summaries the results of the analysis and provide some preferred methods for people to buy houses.
On the Continuity of Functions and Their Application in Polynomial Approximation
Authors: Tang Bowei
Published: June 2024

Researchers continue to explore the topological properties of continuity, including the use of open sets, neighborhoods, and limit points to define and characterize continuous functions. For other aspects, scholars have made achievements in both linear operators and functionals in the context of functional analysis, including applications to integral and differential equations. The development would also see achievements in studies with partial derivatives, directional derivatives, and differentiability. This study primarily discusses how to understand the continuity of one-variable and multivariable functions and introduces some methods for determining continuity. It then explores the application of function continuity in polynomial approximation, specifically focusing on approximating continuous functions in different scenarios using polynomials.
Stock Price Prediction Model Analysis Based on Neural Network
Authors: Yin Mingzhe
Published: June 2024

As a matter of fact, stock price prediction is always crucial for investors and scholars to gain extra return from the stock market. Thanks to the rapid development of the machine learning techniques as well as computation ability (e.g., GPU), various deep leaning models based on the concepts of neural networks are proposed and applied in stock price prediction. On this basis, this paper will investigate the feasibility of stock price prediction based on various neural network deep learning scenarios. With this in mind, the BP neural network, principal component-based BP neural network (PCA-BP neural network) as well as GA-BP neural network are implemented to realize stock price prediction. In order to compare the effectiveness, the ARIMA model is also adopted as a benchmark. According to the analysis, neural network is suitable for stock price prediction. Overall, these results shed light on guiding further exploration of stock price prediction based on the state-o-art machine learning approaches.
Different cathode materials for lithium-ion batteries
Authors: Deng Yilong , Wang Haoze , Zhang Yiguo
Published: June 2024

Due to the increasing need for electronic products like smartphones and electric vehicles, lithium-ion battery research has long been a prominent field of study. Lithium-ion batteries are a growing battery technology that is widely used in industries such as power, electronic equipment, communication, civil aviation, and the military as an efficient, dependable, and long-lasting energy storage system. Lithium-ion batteries' cathode materials are an essential component, and how well they function has a significant impact on how well and how long the battery will survive. Based on their structural characteristics, layered rock salt, spinel, and olivine are the three major types of materials used to create cathodes. Each structure has a unique arrangement that gives the matching materials a varied performance. To serve as a guide for choosing cathode materials for the next lithium-ion batteries, this article discusses the research progress of cathode materials with various architectures based on these three structures and analyzes their benefits and drawbacks.
Assessing the Prospects and Challenges of Hydroelectric Power Generation in Malaysia: A Multidimensional Analysis
Authors: Tu Sitian
Published: June 2024

Environmental problems have been growing over the past few decades, prompting many developing countries to explore green alternatives for energy generation and consumption, such as hydro power. This study wants to investigate the status of hydroelectricity in Malaysia across various dimensions and assess the policies and challenges associated with the hydro power industry. To begin with, a comprehensive literature review will be conducted, encompassing research papers and reports that delve into the current state of hydro power in Malaysia. Furthermore, this study will analyze the hydroelectricity sector in Malaysia from political, economic, social, and technological perspectives by employing a PEST analysis framework. This multi-faceted approach will provide a more holistic understanding of the potential impact that hydro power could have on the country. The study will also focus on the SCORE program, aiming to discern its environmental effects in terms of CO2 emissions. It can be tentatively concluded that hydro power appears to offer a promising path for power generation. However, the SCORE program does exhibit initial negative impacts. This situation may evolve positively in the future if challenges related to technology and politics are successfully addressed.
Dynamic Relationship Analysis and Decision Optimization of Key System Factors Based on LSTM Model
Authors: Zhu Shixian
Published: June 2024

Within the setting of a vegetable laboratory,the short shelf life of vegetable samples poses a challenge as their quality tends to deteriorate rapidly. This study delves into the relationship between the usage of various vegetable categories and individual samples with time, as well as the interdependence among different projects, using descriptive statistical analysis and correlation coefficient matrix calculations. To more accurately predict the overall usage of vegetable samples in various categories for the upcoming seven days, an advanced Long Short-Term Memory (LSTM) model is introduced. This deep learning algorithm successfully captures the dynamic trends in sample usage through the learning of time-series data, providing a robust predictive tool for laboratory management.Considering laboratory requirements, the total number of different vegetable categories, and the usage of samples in each category, the focus of the study shifts from vegetable categories to individual items. In order to determine the precise replenishment quantity of experimental materials for July 1st, a genetic algorithm model is employed. This unique model design, achieved through the continuous evolution of populations, identifies the optimal solution that best fits the experimental conditions. Such a distinctive modeling approach enables laboratory managers to plan laboratory resources more effectively, ensuring optimal experimental outcomes throughout the process.
Analysis of the Principle and Phenomena of Butterfly Effects
Authors: Ban Xuxi
Published: June 2024

As a matter of fact, the butterfly effect refers to the phenomenon that small initial conditions can lead to greatly different output results in chaotic systems, which plays an important role in nonlinear dynamics. In recent years, various fields have faced the issues of the butterfly effects, the numerical way to analyze the chaos is crucial to investigate. The purpose of this study is to reveal the internal law of the butterfly effect and its significant influence on the stability of the system through the in-depth analysis of the principle and phenomenon of the butterfly effect. First of all, this paper will introduce the origin of the butterfly effect and related theoretical explanations, and on this basis, put forward a specific case. The significance of this study is to remind people of the importance of small factors in influencing the whole system, and to provide theoretical support for future model building and decision-making.
Microgrid Development Model and Control Strategy for Dual Carbon Target
Authors: Xia Chuyang
Published: June 2024

In recent years, in the face of China's increasingly serious environmental pollution and energy structure problems, the country has proposed the double carbon target of "peak carbon" by 2030 and "carbon neutral" by 2060, and microgrids, as a kind of small-scale power generation and distribution system with economy and environmental protection, can better absorb distributed energy. In the context of the dual carbon target, it is important to study the development mode and control strategy of microgrids energy. This paper firstly elaborates the advantages of combining microgrid and distributed energy, divides microgrid into grid-connected microgrid and stand-alone microgrid according to the operation mode, and gives the mathematical model of distributed energy. Based on the above, this paper studies grid-connected and stand-alone microgrids. Additionally, single-objective and multi-objective models under different strategies have been presented. The single-objective model aims to minimize operating costs, while the multi-objective model aims to minimize operating costs and carbon emissions simultaneously. Genetic algorithms have been employed to solve this problem, and MATLAB simulations have been used to analyze the models. The results of the simulations demonstrate that this strategy can significantly reduce carbon emissions with only a marginal increase in costs, thus validating the correctness and effectiveness of this approach.
Research on the Unemployment Rate in Texas based on ARIMA Model
Authors: ShangGuan Xiuyuan
Published: June 2024

Since the outbreak of the COVID-19 pandemic in 2020, the issue of unemployment has garnered widespread attention from the government, the public, employers and various other stakeholders. In this context, accurate prediction of the unemployment rate has become particularly crucial. This study builds upon previous research and focuses on the unemployment rate data in Texas from January 1976 to September 2023. Firstly, the data undergoes first-order differencing to transform it into a stable time series. Subsequently, the author constructs ARIMA models with different parameters and select appropriate evaluation metrics to obtain more accurate forecasting results. Finally, in conjunction with the realities of the COVID-19 pandemic, a comprehensive analysis is conducted on both the predictive outcomes and the original data. Analysis of the raw data shows that the impact of the COVID-19 pandemic on the unemployment rate is undeniable. The forecasting results indicate an upward trend in the unemployment rate for the state of Texas. Based on these analyses, this paper presents some policy recommendations to the government in addressing the unemployment issue.
Regional Building Value Assessment under Extreme Weather Based on HEN Assessment Model
Authors: Liu Chengzhi
Published: June 2024

The frequent occurrence of extreme weather events has caused significant losses around the world, which has drawn attention to property sustainability. In order to better evaluate the value of regional buildings under the influence of extreme weather, this paper proposes a HEN evaluation model. First of all, this paper selects three first-level indicators: humanity, economy and nature, and extends this to 10 second-level indicators. Secondly, this paper proposes different data normalization methods for different types of indicators, and uses three methods to determine the weight from a combination of subjective and objective perspectives. Finally, this paper proposes the building value index (BVI) and applies the model to 50 states in the United States. In addition, this paper divides BVI into five value levels, and proposes different levels of protection measures according to the value levels.
Unravelling Three Differential Mean Value Theorems in Calculus
Authors: Fan Zhaosheng , Fu Yiran , Xu Haoling
Published: June 2024

The theoretical foundation of differential aspect in real analysis is the differential mean value theorem, which connects to both the local and total properties of the copula function. The link between the copula function's local and overall properties is differential calculus. The maximum value, minimum value, extreme value, monotonicity, and other difficulties may all be resolved with the help of these differential mean value theorems. Additionally, they aid in the computation of limits, the demonstration of inequality, and the identification of the curve's inflection point and concave-convex interval. They are also capable of mapping the function and locating the equation's root. To tackle these issues, one can apply a number of significant findings from the differential mean value theorem. This study gives the formulae for solving three distinct mean value theorems. The Cauchy, Lagrange, and Roller theorems are examples of these mean value theorems. Understanding the connections between the three mean value theorems is made easier by these studies, which also provide an explanation of the theory underlying the theorems and provide examples and visuals of their practical application.
Development Dilemma and Improvement Measures of IP Film and Television Plays
Authors: Bai Yifan
Published: June 2024

In recent years, the film and television industry has paid more and more attention to IP development, and many popular online novels or games have been adapted into film and television works. The rapid development of IP film and television drama benefits from the rise of popular culture and the excavation of high-quality resources on the Internet, which makes the creative inspiration of IP film and television drama endless and has achieved good market response. However, due to the blind pursuit of commercialization by some practitioners, the development of IP film and television drama is in trouble. Based on IP film and television drama, this paper explores the reasons for the rise and development dilemma of IP film and television drama creation in China in the new era, so as to provide reasonable improvement measures for its development path.
Research on Underwriting Risk Based on EWM-TOPSIS and SARIMA Models
Authors: Zhang Minyu , Liu Jiashan
Published: June 2024

Recent climate change-induced extreme weather events have heightened property insurance claims, prompting the development of an insurance model utilizing advanced mathematical models. Utilizing the EWM-TOPSIS model, a comprehensive framework for underwriting risk assessment was developed and applied to determine the 20-year Insurance Claim Risk Index (ICRI) for both Beijing and Guizhou Province. Predictive modeling using the SARIMA model produced ICRI values for Beijing (0.134, 0.154, 0.149) and for Guizhou Province (0.265, 0.304, 0.169). Assuming the ICRI follows a normal distribution, a statistical analysis was conducted on 40 ICRI data points. Based on this, the ICRI was categorized into three levels, providing a foundation for the insurance company's decision-making. In Beijing, it is suggested to insure for the next three years, while in Guizhou, it is advised not to insure for the first two years or to start the business in the third year.
Stock Market Efficiency and International Market Integration -- Empirical Analysis with the Chinese CSI 1000 Index
Authors: Zhang Panfei
Published: June 2024

Based on daily stock returns from 2016 to 2023, the study digs into the return pattern of the Chinese A share stock index. The study first adopts the ARMA framework for the analysis of serial correlation of daily stock return. The univariate analysis shows the positive autocorrelation of stock return, which indicates the momentum feature of the stock market in the short run and rejects the efficient market hypothesis. Then the study extends the autoregression model to ARDL regression with information from American and Japanese stock markets to test for the information spillover effect. The multivariate analysis shows evidence of stock market integration, as the Chinese stock market responds to the condition of regional and global markets. Moreover, the subsample analysis shows an improvement in Chinese stock market efficiency with reduced serial correlation. Meanwhile, the responsiveness of the Chinese stock market to international markets has been lower with COVID-19 as well.
Effectiveness of cartoons for children's procedural pain: a systematic review with meta-analysis.
Authors: Re Luca Giuseppe , D'Elia Massimiliano , Aloia Vincenza , Rippa Stefania Celeste , Tommasi Valentina
Published: June 2024

BACKGROUND: Cartoons are widely used distraction techniques for nonpharmacological management of procedural pain in pediatric settings. There are a few studies in the literature evaluate the effect of intervention on procedural pain, but a systematic review aimed at providing a summary of the overall effect is lacking.
AIM: To summarize the available evidence on effectiveness of cartoons for children’s procedural pain.
METHODS: Searching for parallel-group controlled trials was carried out on thirteen biomedical databases, five trial registries, web resources and gray literature sources from each database or resource setup date to 22 January 2023. Primary outcome was procedural pain, secondary outcome was anxiety. RoB 2 and ROBINS-I were used to assess risk of bias of included studies.
RESULTS: 24 trials were selected for this review, which included a total of 3046 pediatric subjects. Children who watch cartoons during medical procedures experience less pain (SMD= -1.29; 95% CI: -1.75, -0.83; N=2239) and anxiety (UMD= -1.75; 95% CI: -2.94, -0.56; N=552) compared to children provided standard of care; for both outcomes, results are statistically significant. GRADE method shows moderate certainty/quality of evidence.
CONCLUSIONS: Cartoons are more effective than standard of care in reducing procedural pain and anxiety in children. Pending future studies confirming the results, we recommend their implementation in daily clinical practice even in care settings with limited resources.
Application of Stochastic Processes in Financial Market Models
Authors: Zou Shufang , Dong Xuejiao , Yan Bangzu
Published: June 2024

This paper explores the significant role of stochastic processes in financial modeling, tracing the evolution from basic Brownian motion to sophisticated stochastic differential equations used in modern financial markets. Beginning with the historical development of Brownian motion, identified by Robert Brown and later mathematically modeled by Louis Bachelier for stock price fluctuations, the paper outlines its foundational influence on the Efficient Market Hypothesis and the random walk theory. The extension of these concepts in the Black-Scholes model for option pricing highlights the practical applications of these theories in predicting financial outcomes. The discussion progresses to geometric Brownian motion (GBM) and its crucial role in stock price modeling, emphasizing its use in Monte Carlo simulations for option pricing. The limitations of the Black-Scholes model and GBM in dealing with real market conditions such as stochastic volatility and jump-diffusion processes are addressed, showcasing the evolution of more complex models like the Heston model and GARCH. Interest rate models like the Vasicek and Cox-Ingersoll-Ross models are evaluated for their real-world applicability, particularly in scenarios of low and negative interest rates. This comprehensive review not only underscores the theoretical advancements in financial modeling but also its practical implications in contemporary financial markets.
Public-Private Partnerships and Sustainable Development – Designing Relational Business Models
Authors: Ricart Joan E.
Published: June 2024

There are tremendous challenges in meeting the 17 sustainable development goals (SDGs) of Agenda 2030. A collaborative search for solutions is needed to tackle the complex and novel problems at the crux of these challenges. This requires local governments and companies to join forces with other stakeholders. This collaboration usually takes the form of new Public-Private partnerships (PPPs) in emerging innovation ecosystems focused on the SDGs. These ecosystems are integrated through relational business models – multisided platforms with heterogeneous stakeholders and multidimensional utilities. Using the newly developed stakeholder resource-based view (SRBV), we have identified some characteristics of these business models and their complex relational governance. We recognize that a lot of work is still needed to define the right governance for PPPs.
Experimenting with the design, pedagogy and practice of business design at one b-school
Authors: Beausoleil Angèle M.
Published: June 2024

This paper examines the posturing, positioning and practice of Business Design (BD) at Rotman School of Management, University of Toronto, exploring its evolution since the late 1990s to today. It outlines BD’s introduction as a design thinking-lite approach to strategy innovation and its evolution to an experimental design-driven innovation pedagogy for MBA students. A triangulated theoretical foundation combines design principles, innovation theory and management education with the aim to teach and study BD as an innovation management learning construct. The resulting Business Design Method is examined with early findings of its impact, however offers more of a provocation rather than proof of a successful design curriculum for b-schools.
A Case Report on SARS-CoV-2 Positive Neonate with Complex Heart Disease
Authors: Das Jagadish , Khan Mohammad , Ferdous Jannatul , Shaheen Mohammed , Hasan Syeda , Das Adrita , Akther Arifa , Bhuiyan Kamrunnahar
Published: June 2024

In pediatric patients, Coronavirus disease-19 (COVID-19) presents usually without symptoms or with mild to moderate COVID-19. However, infants may present with more severe diseases, leading to even respiratory failure. COVID-19 may adversely affect the course of congenital heart disease (CHD) and vice versa in neonates and small infants. There is limited data about confirmed COVID-19 cases with CHD in neonates and early infancy. A newborn infant with confirmed COVID-19 was admitted to the Department of Neonatology of Chittagong Medical College Hospital. The case presented with C-Transposition of great arteries, superior-inferior ventricles, large upper muscular VSD with reverse shunt, large ASD with a left to right shunt, moderate right AV valve regurgitation (MR), and severe pulmonary hypertension. The newborn infant was isolated and was treated with antibiotics and cardiac drugs, along with supportive care. Ultimately, the infant deteriorated and expired. A newborn infant might be infected with COVID-19 even if a history of such infection in parents and caregivers is not found. Early identification of COVID-19 in neonates with CHD is essential for planning treatment, including limiting its transmission in the community.
Fundación y Dotación del Hospital del Corpus Christi de Toledo por Doña Leonor de Mendoza, y su donación a los Hermanos del Hábito de Juan de Dios. 1596.
Authors: Gómez Jara Jesús
Published: June 2024

Resumen: Doña Leonor de Mendoza fundó en 1567 la Capilla del Corpus Christi en Toledo, dotándola con ocho capellanías y cuantiosos bienes y rentas. Desde 1571-1573 pasó a ser Iglesia y Colegio, siempre bajo el mismo patronazgo y advocación. En 1596 la fundadora decide cambiar el destino y otorga nueva escritura por la que anula y revoca dicha fundación, e instituye el Hospital-Convento del Corpus Christi para convalecientes pobres, dotándole con todos los bienes y rentas que tenía asignados a la anterior Capilla, más algunas nuevas adquisiciones, donándoselo para su gestión a los Hermanos del hábito de Juan de Dios, fallecido en 1550, actualmente Orden Hospitalaria de San Juan de Dios. En este trabajo tratamos del proceso fundacional, su dotación y la aceptación y toma de posesión por los Hermanos de Juan de Dios. Habrá una segunda parte en que se abordará la Composición y Descripción del Complejo Conventual-Hospitalario y su desarrollo durante los seis primeros años (1696-1602), basándonos principalmente en documentos notariales y conventuales originales de la época.
Un poco más acerca de los llamados ángeles arcabuceros.
Authors: Gentile Lafaille Margarita Elvira
Published: June 2024

A partir del inventario de bienes del primer marqués del Valle de Toxo (1718) se trata el tema de los personajes alados quienes, elegantemente vestidos a la moda de la época y exhibiendo armas de fuego portátiles, se ven en lienzos ubicados en lo alto de las paredes de algunas iglesias andinas. Se resumen y explican el uso y función de tales imágenes, y la dinámica de su invención, ocaso y traslado al mercado de arte en el noroeste argentino.
Respect begets respect: Perception of the students on the importance of respecting teachers
Authors: Samano Ivy M , V Bersola Nicole Allanes , Mosot Benjoy A , Lusdo Arlan P , E Caño Crevin Rabaii , C Luyahan Mc Ivan , Lopez Apol , Marie Lecaba Ernellia , Lamanilao Randy P
Published: June 2024

Using a quantitative descriptive research design, this study examined students' perceptions of the importance of respecting teachers at Balite National High School, a public secondary school in the Philippines. Survey data were collected from Grade 7 to 12 students. The findings revealed that while there is consistency in students' expectations of respectful behavior across different grade levels and ages, significant differences exist based on sex. Male and female students have varying perspectives on what constitutes respectful behavior, possibly influenced by societal norms and gender roles. Additionally, differences in perception based on grade level but not age suggest that academic maturity and educational experiences may shape students' views on conduct. The study highlights the significance of gender dynamics, indicating differing perceptions of conduct between male and female students. Understanding these factors is crucial for educators to promote respect and effectively create an inclusive learning environment. Further research and targeted interventions are needed to address these complexities and foster a more respectful school environment.
The Impact of Electronic Government Policy on Transparency and Accountability in Public Services
Authors: Wijaya Sandita , Alfitri  , Thamrin M. Husni , Salya Dida H.
Published: June 2024

Implementing the Electronic Government policy has become the main focus in efforts to increase transparency and accountability in public services. This policy is intended to change the way of interaction between government and society, expand access to information, and increase service efficiency. However, there are still various challenges that need to be overcome, including data security issues and gaps in technology access across various demographics. This research aims to evaluate the impact of Electronic Government policies on transparency and accountability in public services. This research uses a qualitative approach, collecting data from various relevant studies and sources for analysis. The data is processed to identify emerging themes and patterns, ensuring the validity and reliability of the conclusions produced. The research conclusion shows that e-government is significant in increasing transparency and accountability, by speeding up service processes and increasing public participation. However, challenges such as data security and uneven access are still major obstacles. Continuous evaluation and adaptation to feedback from the community are needed to improve and sharpen the implementation of this policy. Further development in e-government technology is also essential to overcome current weaknesses. An inclusive and sustainable development strategy will be key in making e-government a more effective tool for transparent and accountable government.
Potential and application of abortive transcripts as a novel molecular marker of cancers
Authors: Zhang Tian-Miao , Zhu Xiao-Nian , Qin Shao-Wei , Guo Xue-Feng , Xing Xue-Kun , Zhao Li-Feng , Tan Sheng-Kui
Published: June 2024

Abortive transcript (AT) is a 2-19 nt long non-coding RNA that is produced in the abortive initiation stage. Abortive initiation was found to be closely related to RNA polymerase through in vitro experiments. Therefore, the distribution of AT length and the scale of abortive initiation are correlated to the promoter, discriminator, and transcription initiation sequence, and can be affected by transcription elongation factors. AT plays an important role in the occurrence and development of various diseases. Here we summarize the discovery of AT, the factors responsible for AT formation, the detection methods and biological functions of AT, to provide new clues for finding potential targets in the early diagnosis and treatment of cancers.
Analisis Dampak Fasilitas Likuiditas Pembiayaan Perumahan (FLPP) Terhadap Kesejahteraan Masyarakat Berpenghasilan Rendah (MBR)
Authors: Izza Sevilla Ruhul , Franssisca Maria Lasma , Nurcahya Wirawan Firman
Published: June 2024

Terdapat backlog perumahan sebanyak 9.9 juta unit pada tahun 2023 yang menunjukkan bahwa masih adanya kesenjangan yang signifikan antara kebutuhan perumahan dan pasokan yang tersedia. Sesuai dengan pasal 28H ayat 1 UUD 1945 mengamanatkan bahwa setiap orang berhak atas hunian yang layak dan sehat, sehingga dibuatlah sebuah program yang memberikan kemudahan akses perumahan bagi mereka yang terkendala dalam finansial terkhususnya Masyarakat Berpenghasilan Rendah (MBR) yaitu Fasilitas Likuiditas Pembiayaan Perumahan (FLPP). Penelitian ini bertujuan untuk melihat dampak dari Fasilitas Likuiditas Pembiayaan Perumahan (FLPP) terhadap kesejahteraan Masyarakat Berpenghasilan Rendah (MBR). Metode yang digunakan adalah deskriptif kualitatif dengan data sekunder yang diperoleh dari studi literatur melalui buku, artikel dalam jurnal, bahan makalah, sumber daring dan cetak relevan lainnya. Hasil dari penelitian ini menjelaskan bahwa adanya Fasilitas Likuiditas Pembiayaan Perumahan (FLPP) dapat memberikan kesejahteraan kepada Masyarakat Berpenghasilan Rendah karena telah memenuhi 3 syarat yang menjadi acuan kesejahteraan yaitu pemenuhan kesejahteraan materi, kesejahteraan masyarakat, dan keamanan.