Irvine Valley College

The purpose of the present study was to examine the relationships among self-esteem, self-discipline, and academic success. Three hypotheses were posed. First, it was expected that there would be a positive correlation between self-esteem and self-discipline. Second, it was expected that there would be a positive correlation between self-esteem and academic success. Third, it was expected that there would be a positive correlation between self-discipline and academic success. Eighteen college students from a Southern California community college volunteered to participate for extra credit. Participants completed an online survey, which took approximately 20 minutes to complete. Results calculated utilizing JASP through Pearson’s correlations showed full support for the first hypothesis, partial support for the second, and partial support for the third. These results suggest that students who are higher in self-discipline tend to have higher self-esteem and positive perceptions about their academic success.

In the field of power systems, the concept of infinity plays a crucial theoretical role, enabling the depiction of extreme limits as quantities approach very large values. This theoretical model simplifies complex issues and encourages innovative problem-solving strategies for engineers. This article delves into the diverse role of infinity as a theoretical construct within power systems, illustrating how this abstraction aligns with the practical application of engineering principles. The discussion covers topics, such as ground potential and infinite bus as reference points, the importance of infinity in power line analysis, the practical effects of short-circuits and open-circuits in power systems, and the continuity of state variables. By connecting theoretical and practical aspects, this article enhances the understanding of how infinity is utilized as a tool in electrical engineering, highlighting its importance in simplifying complex problems and advancing the design and analysis of power systems.

The Markov Chain Monte Carlo (MCMC) methods have become indispensable tools in modern statistical computation, enabling researchers to approximate complex probability distributions that are otherwise intractable. This paper focus on MCMC in Statistics and Probability area which is used to draw samples from a probability distribution. In order to introduce this algorithm in a relatively light and straightforward way, this paper breaks the content into two parts: Markov Chain and MCMC, and brings in stochastic process, Markov property, Ordinary Monte Carlo, and Monte Carlo Integration in succession. On this foundation, this paper formally introduces two algorithms of MCMC that are Metropolis-Hasting Algorithm and Gibbs Sampling, the most famous and significant algorithms of MCMC. With this approach, this paper concludes both the advantages and disadvantages of these two algorithms, laying the foundation of the further study and the deeper utilizations of MCMC and, hopefully, contributing to providing a certain degree of assistance for scholars.

The subprime mortgage crisis has a huge impact on American society, it makes a lot of countries get into financial crisis too. A lot of countries economy goes downturn. It is due to the lack of supervision of the U.S. financial industry, and with the need for rapid economic recovery, led to the financial crisis in the later years, and the U.S. economy fell into negative growth. Subsequently, the U.S. strengthened the supervision of the financial market in order to restore the U.S. economy. The significance of this article is to analyze the economic impact of subprime mortgages on the United States and to study some wrong policies behind the prosperous U.S. economy. The policy which commended by this article are that the national economic development should not focus on the short-term, but on longterm development. Loans should be given to small and medium-sized enterprises to promote the progress of social and economic development.

BackgroundUnderstanding evolution is an important part of undergraduate biology education. Despite its importance, however, students often struggle to understand evolution, often holding preconceived notions of what evolution is. Here, we investigate how students in both majors and non-majors introductory biology define and conceive of evolution at the start of the semester for a two-year college and a four-year university near each other. We analyze open-ended responses to an in-class activity on the first day of the semester that asked students to define evolution, generating insight into how students are thinking of evolution prior to any formal instruction on evolution in college.ResultsOur analysis of over 300 student responses reveals that students hold diverse conceptions about evolution, with some students perceiving evolution in the context of evolutionary processes while other students define evolution by referring to perceived evolutionary consequences. In addition, we identify multiple non-normative conceptions about evolution, including students viewing evolution and natural selection as synonymous and not recognizing other evolutionary forces, and find that very few students likely have developed mental models linking evolution and genetics. In addition, we find few differences between how students at the two- and four-year institutions perceive evolution, and similarly few differences between students in a majors and non-majors introductory biology, suggesting that these conceptions of evolution are widespread at the beginning of introductory biology, regardless of major or institution.ConclusionsWe situate our results in the existing literature examining student conceptions of evolution, with our results extending past work that has primarily relied on more closed-ended questions or focused on specific evolutionary concepts (e.g., natural selection). Our results largely align with past work on student thinking of evolution but provide a broader, more holistic perspective at the ideas and framework that students are drawing upon when introductory biology instructors first introduce the term ‘evolution’. We conclude our paper by discussing implications for the biology education research community as well as instructors.

Abstract As a green industry, forestry plays a pivotal role in economic and ecological development. Green Total Factor Productivity (GTFP) is a crucial indicator of forestry progress. This paper employs the Non‐Radial Distance Function (NDDF) model to measure forestry GTFP in forestry comprehensively. Additionally, it utilizes fuzzy set qualitative comparative analysis (fsQCA) to explore pathways for enhancing forestry GTFP across technological, organizational, and environmental (TOE) dimensions. The study reveals the following outcomes: Government financial support and six additional antecedent conditions offer three distinct avenues to boost forestry GTFP in forestry. Regional disparities emerge, with technology‐driven pathways predominantly found in eastern provinces, dual‐driven routes centered on average forest land size and forestry carbon sinks (FCS) taking precedence in central provinces, and dual‐driven paths driven by government support and FCS coming to the forefront in western provinces. Under specific circumstances, government financial support and foreign investment exhibit potential interchangeability, facilitating the attainment of elevated forestry GTFP in forestry. However, a constraint arises from operating entities' low average forest land size. Ultimately, this study equips policymakers with a nuanced understanding of the factors shaping forestry GTFP in forestry, enabling them to craft compelling, regionally tailored policies that foster adaptability and contribute to the sustainable development of the forestry sector, recognizing that a one‐size‐fits‐all approach may not be suitable for all regions.

The modules of photovoltaic systems (PV), whether land-mounted or installed on building roofs, are secured by racks and mounting structures. These components are usually constructed from metal, prompting the question of whether electrical bonding for equipotential reasons is necessary. Solar trackers may be employed in photovoltaic systems, equipped with servo motors that orient the payload toward the sun to maximize energy production. The servo may fail and energize the mounting structures. This paper advocates for bonding decisions to be based on the specific characteristics of the PV system and to be made on a case-by-case basis. The paper discusses the distinctions between Class I and Class II PV equipment, highlighting the implications for grounding and bonding based on the type of insulation employed. Through a detailed exploration of the underlying principles, design considerations, and industry standards, this paper endeavors to equip readers with the knowledge and tools necessary to make informed grounding decisions for their specific PV installations. It aims to contribute to the ongoing efforts toward safer, more efficient, and sustainable energy generation by addressing these critical aspects of PV systems design.

In the realm of power systems, infinity serves as a pivotal theoretical construct, facilitating the representation of extreme limits of quantities as they approach exceedingly large values. This theoretical framework simplifies complex problems and fosters creative problem-solving approaches for engineers. This paper explores the multifaceted role of infinity as a theoretical construct in power systems scenarios, showcasing how this abstraction harmonizes with the practical application of engineering principles. The discussion spans concepts such as the ground-potential and infinite bus as reference points, the significance of infinity in power lines analysis, the practical implications of short-circuits and open-circuits in power systems, and the continuity of state variables. By bridging the theoretical and practical aspects, this paper contributes to a comprehensive understanding of how infinity is harnessed as a tool in the field of electrical engineering, demonstrating its significance in simplifying intricate problems and advancing power systems design and analysis.

Based on panel data from 16 prefecture-level cities in Shandong Province from 2011 to 2020, the paper utilizes the super-efficiency SBM model with undesirable outputs to measure the green economic efficiency of each city.Spatial autocorrelation analysis and the natural breaks method are applied to analyze the spatial-temporal evolution of green economic efficiency.Lastly, a panel Tobit model is used to analyze the factors affecting green economic efficiency.The study's outcomes are as outlined below: (1) The green economy efficiency of the 16 cities in Shandong Province showed an overall increasing trend from 2011 to 2020.However, there is a noticeable disparity in green economic efficiency among cities, with developed cities exhibiting relatively higher levels of efficiency.(2) The proportion of cities with high green economic efficiency steadily increases, and these highefficiency regions gradually cluster around the provincial capital and the eastern coastal areas.While there is heterogeneous clustering of green economic efficiency, the degree of this heterogeneity decreases over time.(3) Social security, economic development, and technological advancement significantly enhance green economic efficiency, whereas the industrial structure noticeably impedes efficiency.Environmental regulations and urbanization levels have a less pronounced impact on efficiency.Drawing from these findings, this chapter presents targeted policy recommendations.

With the development of digital and green economies, enterprise digital transformation inventively promotes green technological innovation. Using data from listed companies in Shanghai and Shenzhen from 2008 to 2021 with text analysis, we construct a multidimensional fixed-effect model to study the impact of enterprise digital transformation on green technology innovation. We find that enterprise digital transformation promotes green technology innovation, holding after a series of robustness tests and endogeneity treatments, by reducing financing constraints and easing enterprise risks. Further analysis shows that among the two sub-dimensions of enterprise green technology innovation, the promotion effect on independent innovation of green technology is more prominent. There is also a time lag effect in the promotion effect on both green technology innovation and its sub-dimensions, showing a tendency to enhance and then weaken. Moreover, the positive effect of enterprise digital transformation is more significant in heavy pollution industries, alongside non-state-owned and small-scale enterprises, with different performances in sub-dimension.