Economic Strength Research Articles

Research on the Evaluation of Urban Quality in Yunnan Province Based on Principal Component Analysis Approach

Urban quality represents the spiritual taste and development quality of a city, and is the unity of the two. The level of urban quality reflects the level of the whole process of a city's planning, construction and management, and also directly affects the convenience and comfort of citizens' life, as well as relates to the agglomeration and attraction of various resource elements such as talents and industries. In other words, it is a comprehensive reflection of a city's strength, directly reflecting a city's economic development strength, urban social and cultural conditions, the beauty of the ecological environment, the level of public services and the living conditions of residents. China's economic development has entered a new period, has shifted from the stage of high-speed growth to the stage of high-quality development, and a clear understanding of the quality of the city is of great significance to high-quality development. This paper uses principal component analysis to conduct a comprehensive evaluation study of urban quality in 16 cities and towns in Yunnan Province from five dimensions: quality of urban economic development, social and cultural quality, quality of ecological environment, quality of public services, and quality of life of residents, using empirical data for the period of 2017-2021 as a sample of 16 cities and towns in Yunnan Province. The study found that although the comprehensive index of urban quality of each state and city in Yunnan Province has been steadily increasing year by year, the gap between the states and cities has not been significantly reduced. The development level of city sub-quality in each state and city in Yunnan Province is not balanced, and there are geographical differences, with a few cities, such as Kunming, having higher quality, while the quality of the majority of cities needs to be improved. The comprehensive scores of these city qualities are affected by indicators of economic development, social progress and environmental protection, and also show their own characteristics and advantages. In order to improve the quality of cities in Yunnan Province, it is recommended that policy guidance be strengthened, coordinated development among cities be promoted, investment in environmental protection be increased, and the development of social programs be advanced.

Location and Tracking Mode of Sports Rehabilitation Training With Self-Powered Sensors Based on Particle Swarm Optimization Algorithm

With the growth of the country’s economic strength, people’s living standards have steadily improved. Sports have become the main means to change physical fitness and maintain the per capita health index. The state also puts forward higher requirements for the security work of athletes, elderly groups and rehabilitation patients. Traditional rehabilitation training mainly relies on various sensor devices, such as acceleration sensing, pressure sensing and so on. These devices need a lot of energy to supply power for the equipment in the process of use, which is no longer suitable for today’s modern development environment. Based on the concept of self-powered sensors, this paper proposes a sports rehabilitation training model updated by particle swarm optimization algorithm. First of all, the performance and indicators of self-powered sensor devices are analyzed, and the self-powered electrical components are optimized using friction nano new energy technology. Starting from the basic characteristics of wearable models, we can ensure the consistency of posture in sports rehabilitation. During training, the wearing process will stretch 10% of the length in advance to ensure comfort and sensitivity. According to the results of the test record, the pulse index is clear and obvious, consistent with the actual number of minutes per minute. Finally, the sensor array model and function model are improved under the particle swarm optimization algorithm to realize the positioning and tracking function in sports rehabilitation training. The results show that the wearable training equipment optimized by particle swarm optimization can better locate and track the movement track than the traditional sports rehabilitation equipment. It can adjust the movement posture and protect the safety of trainers. At the same time, it is more prominent in performance and power supply duration.

Chinese Foreign Real Estate Investment and Local Voting in US Presidential Elections

Abstract Despite the increasing globalization of housing markets, little is known about its political implications. This study investigates whether rising Chinese investments in US homes influenced local voting in recent US presidential elections. Building on pocketbook/sociotropic voting and nativism theories, I develop hypotheses on the electoral consequences of foreign real estate investment through greater home demand and equity, improved local economies, and changing neighborhoods. Using difference-in-differences designs that combine a unique shock to Chinese capital outflows in 2013 with county-level measures of local attractiveness to Chinese investments, I find that greater exposure reduced Democratic vote shares in both the 2016 and 2020 presidential elections. Furthermore, an initially larger white population strengthened this effect, while a larger college-educated population weakened it. In contrast, local equity gains, housing competition, or economic strength did not systematically influence the effect. Together, the results appear more consistent with the pro-conservative effects of nativism.

Impact of CSR on Organizational Resilience across Chinese Listed Firms: Combination of Process-oriented and Outcome-oriented Perspectives

The firms are confronted with increasingly uncertain environment. Their ability to endure, recover and bounce back from a major disturbance is essential for firms’ survival and development. Therefore, how to cultivate organizational resilience has become an important issue. The paper operationalizes organizational resilience into two parts. One is the process of forming organizational resilience in pre-adversity period, another is the manifestation of organizational resilience in post-adversity period. Using the panel data from 2010 to 2019 and cross-sectional data in 2020 of listed firms in Chinese stock market, the paper employs fixed effect and OLS estimations to study the influence of corporate social responsibility (CSR) on organizational resilience by combining process-oriented and outcome-oriented perspectives. The results show that in context of China, CSR performance has mixed effects on organizational resilience. Specifically, CSR practice impacts organizational resilience through reducing financial volatility, instead of through improving economic strength in the process of formation. Furthermore, CSR practice shows no significant impact on the manifestation of organizational resilience when an adversity happens. The findings support the insurance-like effect of CSR practice. The study is the first attempt to interpret organizational resilience as a compound capability which is developed at tranquil period and manifested at adversity period. It is also one of the few empirical studies concerning the influence of CSR on organizational resilience with the background of a recently happened crisis. It contributes to the body of literatures on determinants of organizational resilience and suggests that CSR practice is a practical way to build up organizational resilience and maintain business sustainability.

The Competition of Regional Powers and its Impact on the Stability of the Middle East Region: (Iran - Israel as a Model)

The Middle East has become an area of regional and international competition as a result of differences between countries, which have taken on political and economic dimensions to achieve their interests and status on the regional and international arenas. This competition stems mainly from the strategic, geopolitical, and economic importance of the region, which prompted these regional powers or actors to formulate their policies and projects in a way that guarantees them the greatest expansion in the region at the expense of other countries.
 Some of the active regional powers in the Middle East are multinational states such as Iran, while others need to expand and eliminate or weaken Arab states that stand against them, such as Israel. Accordingly, its presence in the Middle East region is directly linked to defining the strategic concept of the great powers, led by the United States of America, by preserving its interests and the interests of its allies in the region in addition to containing the Arab countries that oppose it.
 These regional actors (Iran and Israel) have become influential actors in the Arab region as a result of several factors and variables, including soft power policy, economic strength, and high military capabilities. This competition and competition over the Middle East region is certainly supported by international actors. Israel was and is still supported by the United States of America. As for Iran, although its relationship with Russia most often reaches conflict, especially in terms of reducing its presence in Syria, it is a relationship based on cooperation. Regional competition is one of The most important challenges facing the Middle East region and still are, especially those that exist between regional actors in order to achieve their goals and strategies, and this competition has directly affected the stability of the region politically, economically, socially, culturally and security.

Study on macro performance and micro-analysis of high strength grouting material

Wind turbine duct put forward higher requirements for the performance of grouting materials. In order to obtain more economical high strength grouting materials (HSG), three kinds of low price main components, cement, quartz sand (QS) and fly ash microspheres (MS) were utilized and developed. Macro performance and micro-analysis of the HSG were conducted. The macro performance tests revealed that the mix proportion of HSG is determined as, cement: QS: MS: superplasticizer: swelling agent = 80:10:10:0.3:0.12, water binder ratio is determined as 0.26. Compressive and flexural strength of the HSG exceeding 120 MPa and 20 MPa respectively. The HSG also showed good fluidity and homogeneity. The micro-analysis showed that a complete and continuous micro-structure was formed and interface transition zone could not be observed. XRD and TG-DSC results meant that the amount of AFt increased. On the contrary, the amount of Ca(OH)2 decreased. pore diameter of the HSG was mostly 10 nm. The addition of swelling agent and MS did not changed the types of hydration products of HSG, but the pore structure was optimized. Due to the cheap components, HSG contributed higher profits with the lower price, and which perform good economic benefits and market competitiveness.

US-China Economic Statecraft: Turning Cold War into Negotiation

Abstract The trajectory of US economic strength relative to China has driven a reassessment of the US’ rules of engagement on trade and investment. China is turning more authoritarian, more focused on self-sufficiency, challenging US dominance in international institutions, global markets, and critical technologies. It selectively honors the market-based rules of the international trade order. Structural features of the Chinese economy and its management blunt the effectiveness of international rules-based trade policy tools. The US, in response, is becoming more aggressive, with protective trade measures and proactive industrial policy. A new cold war is emerging, confounding the broad foundation of collaborative interdependence that vastly accelerating world economic growth for the past 35 years. This paper examines the nature of these shifts and the need for and scope of more constructive economic statecraft by both the US and China in order to build a workable, new rules-based framework for managing international competition and trade that is acceptable to both countries. It contributes a path toward more constructive long-term negotiation as an alternative to an economic cold war.

Application of human–computer interaction virtual reality technology in urban cultural creative design

As the in-depth expansion and integrated application of information technology, smart city is one of the important directions for nurturing breakthroughs in the new generation of information technology, and an important part of the development of global strategic emerging industries. In the context of world peace, the world economy is developing rapidly and the process of urbanization is accelerating. The construction of a city not only reflects the economic strength of the city, but also is closely related to the life of the citizens. Therefore, this paper aimed to explore a new way of urban cultural creative design. This paper focused on the application of human–computer interaction virtual reality (VR) technology in urban cultural creative design. For this reason, this paper designed an interactive and immersive urban design simulation platform based on VR technology. In order to choose the viewing angle freely and control the design module freely, this paper proposed improved gesture recognition algorithm and anti-collision algorithm. The algorithm designed in this paper can enable designers to have better presentation effects when working on the platform, making architectural design more intuitive. Experiments show that the average accuracy rate of the gesture recognition algorithm designed in this paper reaches 97.3%, which is 4.1% higher than that of the traditional algorithm; and when the anti-collision algorithm in this paper is set to the optimal parameters, the accuracy rate is as high as 95%. These results fully demonstrate that the human–computer interaction VR technology design platform proposed in this paper has good design performance and can be applied to urban cultural creative design.

Research on Information Poverty in Ethnic Border Regions

The information revolution has ushered in a new era of information and economy, with information resources becoming a key resource for regional economic strength and core competitiveness. In the process of informatization in China, there is a significant gap between the central and western regions and the eastern regions in terms of information infrastructure, information resource transmission and acquisition capabilities, information resource utilization and development potential, and information industry development. Therefore, information differentiation and the digital divide have also become important factors leading to the wealth gap in the information age. Against the backdrop of promoting the development of poverty-stricken areas and rural revitalization strategies, the issue of information poverty among the vast rural population in the western region, especially in ethnic border areas, cannot be ignored. To solve the problem of information poverty in ethnic border areas, it is necessary to strengthen the construction of rural information environment, improve farmers’ information literacy, strengthen the construction of information service talent team, and improve the effectiveness of information services.

Empowering Careers through the Fusion of Vocational and Soft Skills

This article investigates into the intricate interplay between vocational skills and soft skills as pivotal determinants of career advancement and the successful realization of Omanisation goals. Focused on specialization students from vocational college in Ibri, Oman, the article addresses the pressing need to equip them with a well-rounded skill set in the face of an increasing influx of foreign workers, primarily from Asian nations. The symbiotic relationship between vocational skills and soft skills is highlighted, emphasizing how vocational proficiency must be complemented by attributes such as effective communication, adaptability, teamwork, critical thinking, and cultural awareness. Navigating through an array of literature and authoritative reports, including those from the Ministry of Labour and Ministry of Higher Education, the article emphasizes the urgency to empower Omani graduates to stand out amidst stiff competition. It showcases the significance of embedding soft skills within vocational training, making graduates not only vocationally adept but also adept at navigating diverse work environments. The findings of this research advocate for curriculum innovation, hands-on learning, and the inclusion of courses aligned with Oman's economic strengths. In conclusion, it emphasizes the collaborative efforts of educational institutions, government bodies, and the private sector to foster an ecosystem where graduates are not only well-prepared for employment but also integral to Oman's sustainable economic growth and Omanisation aspirations.

Strategi Pengembangan Usaha PT Godongijo Asri, di Depok Jawa Barat

Micro, small, and medium enterprises (MSMEs) are often referred to as one of the pillars of a region's economic strength. This is because MSMEs have the flexibility and ability to adapt to rapidly changing market conditions compared to large-scale companies. Depok City is one of the most strategic areas in West Java Province. Its location and position as a buffer for the capital city and its strong influence on economic growth in the surrounding area are an opportunity as well as a challenge so that Depok is be able to align its economic opportunities with the potential and direction of governance that have been structured. Godongijo, as one of the ecotourism MSMEs in Sawangan, has experienced a decrease in income in the last few months. Some of the causes are influenced by the nature of the tourism industry with different market needs due to developing trends, economic fluctuations, competition between tourist resort entrepreneurs, and the COVID-19 pandemic. Therefore, Godongijo needs to develop a competitive advantage that can provide high profits and the stability that determines the sustainability of its business. Primary data collection was obtained through direct observation and interviews with Godongijo Management. In addition, questionnaires were distributed to MSME players in the Godongijo area. Secondary or library data collection is obtained from national and international journals as well as research documents related to the development of local entrepreneurship. The strategy formulation method is based on internal and external factor analysis IE matrix, Strength, Weakness, Oppourtunities & Threats matrix (SWOT), and Quantitative Strategic Planning Matrix (QSPM). For the future, there are several development strategies from the results of the analysis that can be used according to the needs and business conditions of UMKM in Godongijo, such as making a characteristic gate or Godongijo icon so that it is quickly recognized by tourists in the city or outside the city, making the parking area wider, and establishing a Mini Zoo for children's educational tours.

Research on Spatial–Temporal Characteristics and Driving Factors of Urban Development Intensity for Pearl River Delta Region Based on Geodetector

The Pearl River Delta (PRD) is one of the most dynamic economic regions in the Asia-Pacific region. At present, it still faces many problems, such as the over-exploitation of urban land and unbalanced development. Through the study of the spatial–temporal characteristics of the development intensity of the PRD region and its driving factors, the key points and difficulties of urban development can be intuitively found. In previous studies, geodetector was widely used to determine the impact of driving factors. This paper uses several different research methods, including the Moran index, the semi-variability index, hot and cold spots, etc., based on the land use data of the PRD region in 1990, 2000, 2010, and 2020 to analyze the spatial–temporal characteristics of the development intensity. Combined with the socio-economic data of the statistical yearbook, factor detection and interaction detection of the 10 driving factors of development intensity are carried out based on geodetector, and reasonable optimization suggestions are put forward for the current situation of the region. The main conclusions are as follows: (1) The overall development intensity of the PRD region shows an upward trend, showing a “core periphery” spatial pattern of high center and low periphery centered around the Pearl River estuary. (2) The spatial distribution of cold and hot spots shows agglomeration, mainly in the form of high aggregation and low aggregation. (3) The driving factors for the development intensity for the PRD region in the past 30 years mainly include population agglomeration level, industrial structure level, economic strength level, terrain slope, etc. Among them, any two factors have a stronger interaction than a single factor, and all are enhanced by two factors. The dominant factors of interaction in different periods are different.

A Novel Political Optimizer-Based Feature Selection with an Optimal Machine Learning Model for Financial Crisis Prediction

In today’s digital environment, business intelligence advances make it difficult to stay competitive and up to date on business trends. Decision-making in the financial industry is increasingly being powered by big data and machine learning. A decision-making process may be thought of as any sequence of processes that an individual goes through in order to select the option or course of action that is most suitable to meet their needs and necessities. The ability to anticipate the onset of a financial crisis is a significant economic phenomenon. A nation’s economic development and strength can be gauged by its capacity to provide an accurate assessment of the number of failed firms and the frequency with which they fail. The economics of the globe have been ravaged by recent global crises like as the COVID-19 pandemic and other recent environmental, financial, and economic disasters, which have marginalized efforts to construct a maintainable economy and civilization. The health and growth of a nation’s economy can be determined by precisely estimating the number of enterprises that will fail and the number that will succeed. Historically, there have been numerous strategies for constructing a successful financial crisis prediction (FPC) method. Effectively predicting business failures is a gauge of a country’s economic health. Several strategies are available for effective FCP. Classification performance, forecast accuracy, and legality are insufficient for practical use. Several of the suggested methods work for some issues. The specific dataset is not expandable. To improve classification, design a good prediction model adaptable to several datasets. An effective financial crisis prediction method (FPC) requires the right qualities. ML models can also be used to classify a company’s financial health. This research presents political optimizer-based feature selection (POFS) with optimal cascaded deep forest (OCDF) for FCP in big data environments. Hadoop Map Reduce handles huge datasets. POFS reduces computing complexity by handling feature selection. POFS is an original FCP algorithm categorization using OCDF. SFO is used to optimize CDF model parameters. A thorough simulation study was performed to evaluate POFS performance on benchmark datasets OCDFs. The results confirmed the POFS-OCDF method’s superiority over state-of-the-art approaches. With an outstanding sensitivity of 0.912, specificity of 0.953, accuracy of 0.944, F-score of 0.930, and Matthews correlation coefficient (MCC) of 0.912, the proposed POFS-OCDF technique has shown optimum results. The experimental results demonstrated that the POFS-OCDF technique outperformed other recently developed strategies on a variety of criteria. As previously stated, Sunflower optimization (SFO) is also used to tune the Cascaded Deep Forest (CDF) parameters. A detailed simulation analysis is performed based on the benchmark dataset to evaluate the higher classification efficiency of the POFS-OCDF technique. The invention of the POFS algorithm for FCP exemplifies the work’s originality.

Heatwaves: does global research reflect the growing threat in the light of climate change?

BackgroundWith the increasing impacts of climate change, heatwaves are placing an enormous burden on health and social systems and threatening ecological diversity around the world. Heatwaves are increasing not only in frequency but also in severity and magnitude. They are causing the deaths of thousands of people. Research is needed on a multidisciplinary, supra-regional, and regional level.MethodsA detailed evaluation of the research conducted is not yet available. Therefore, this study provides a detailed insight into the publication landscape to identify key players, incentives, and requirements for future scientific efforts that are useful not only for scientists but also to stakeholders and project funders.ResultsThe number of publications on heatwaves is increasing, outpacing the trend of research indexed by the Science Citation Index Expanded. However, funding is lagging behind comparatively. Looking at absolute numbers, the USA, Australia, China, and some European countries have been identified as major players in heatwave research. If socio-economic numbers are included, Switzerland and Portugal lead the way. Australia and the UK dominate if the change in heatwave-exposed people is included. Nevertheless, exposure and economic strength of publishing countries were identified as the main drivers of national research interests. Previous heatwaves, in particular, have driven research efforts primarily at the national level.ConclusionFor an efficient monitoring or early detection system that also includes the economically weak regions, internationally networked efforts are necessary to enable preventive measures and damage limitation against heatwaves. Regardless of previous regional extreme heat events, research approaches should be focused to the global level.

Study on the influencing factors of the development of art education in colleges and universities based on the deep learning model

Abstract The development of art education in colleges and universities is a direct reflection of the soft power of culture. In this paper, based on two models, BP neural network and long and short-term memory neural network in deep learning model, we study the factors affecting the development of college art education. Firstly, the article introduces the basic models of the BP neural network and LSTM neural network and selects the indicators under three dimensions of college art education scale, college art education input, and output to visually analyze the development status of college art education and find the possible problems. Secondly, five dimensions, namely, population scale, policy support, economic strength, industrial structure, and faculty level, were selected as the influential indicators to study the level of art education in colleges and universities. The population size passed the 1% significance test, GDP per capita and faculty strength passed the 5% significance test, the influence coefficient of art education expenses was 0.349, and only the industrial structure failed the test. According to the analysis, we conclude that the factors affecting the development of art education in colleges and universities are mainly four aspects: population size, policy support, economic strength, and faculty level.

Biases in parasite biodiversity research: why some helminth species attract more research than others.

As the number of known and described parasite species grows every year, one might ask: how much do we actually know about these species beyond the fact they exist? For free-living taxa, research effort is biased toward a small subset of species based on their properties or human-centric factors. Here, using a large data set on over 2500 helminth parasite species described in the past two decades, we test the importance of several predictors on two measures of research effort: the number of times a species description is cited following its publication, and the number of times a species' name is mentioned in the scientific literature. Our analysis highlights some taxonomic biases: for instance, descriptions of acanthocephalans and nematodes tend to receive more citations than those of other helminths, and species of cestodes are less frequently mentioned in the literature than other helminths. We also found that helminths infecting host species of conservation concern receive less research attention, perhaps because of the constraints associated with research on threatened animals, while those infecting host species of human use receive greater research effort. Intriguingly, we found that species originally described by many co-authors subsequently attract more research effort than those described by one or few authors, and that research effort correlates negatively with the human population size of the country where a species was discovered, but not with its economic strength, measured by its gross domestic product. Overall, our findings reveal that we have conducted very little research, or none at all, on the majority of helminth parasite species following their discovery. The biases in study effort we identify have serious implications for future research into parasite biodiversity and conservation.

Analisis Kinerja Keuangan KSU Sri Nadi Bersama Sebelum dan Selama Masa Pandemi Covid 19 di Kota Denpasar, Bali

Analysis of Financial Performance of KSU Sri Nadi Bersama Before and During the Covid 19 Pandemic
 The concept of creating shared value is a business sustainability practice that has the nature to provide strengthening and independence of the surrounding environment. This consensus has been implemented by cooperatives in accordance with its function that gathers weak economic strength to become the lifeblood of the economy and strengthen the economic life of the nation. However, the Covid 19 pandemic has proven to have a bad effect on the micro to maceoeconomics. Therefore, this study aims to analyze the financial performance of KSU Sri Nadi Bersama Denpasar before and during the Covid 19 pandemic. The study used primary data in the form of monthly financial statements and primary data through interviews. The data analysis techniques used are descriptive analysis and paired t test on financial performance liquidity ratio, solvency ratio, profitability ratio and activity ratio. The results showed that there was a significant difference in liquidity ratio and solvency ratio in the pre-Covid 19 pandemic when compared to during the Covid 19 outbreak. Profitability ratios and activity ratios that showed no significant difference in financial performance in the period before and during the Covid 19 outbreak.

Research on Higher Education Level in Different Regions of China--Based on factors and clustering

This paper uses factor analysis and cluster analysis to evaluate and classify the development level and status of higher education in various regions of China. It is found that the level of educational development is greatly related to the economic strength and urban development level of various regions, and there is an imbalance between the development of the east and the west in the level of higher education, especially the development level of ethnic minority areas and the weak development level of the western region.In order to promote the comprehensive, coordinated and sustainable development of China's higher education, regional governments should make improvements, such as promoting the construction of new methods of higher education such as MOOC.

Assessing Regional Variation in Support for the Radical Right-Wing Party ‘Alternative for Germany’ (AfD)—A Novel Application of Institutional Anomie Theory across German Districts

The paper at hand aims to address a research gap by examining the spatial impact of economic and non-economic institutions on regional variation in the support for the German populist far-right party ‘Alternative for Germany (AfD)’. Adopting an interdisciplinary approach and drawing on institutional anomie theory, the study explores the relationship between economic dominance—economic inequality and economic strength—and regional AfD vote share, as well as the role of non-economic institutions in shaping support for the party. Using various regional indicators, the study assesses the strength of different institutions and their impact on the AfD’s electoral results in the year 2021 across 401 German districts (NUTS 3-level). The results point to significant differences between eastern and western Germany in the analysis of regional populist voting patterns. Economic dominance emerges as a stronger predictor of the AfD’s vote share in eastern regions. However, the findings on the protective effect of strong non-economic institutions against AfD voting are ambiguous and partly contrary to theoretical expectations. Overall, the study’s findings show that the newly introduced indicators deduced from institutional anomie theory contribute to the existing literature to help better understand regional variances in AfD support. Furthermore, the study contributes to the existing literature on the rise of contemporary radical right movements by employing Karl Polanyi’s framework of ‘disembedded’ markets. In doing so, it sheds light on the complex interplay between social change, anomic tendencies, and the growth of radical right movements in capitalist societies.

CHALLENGES OF REFORMING THE ACCUMULATED PENSION SYSTEM IN GEORGIA

Implementation of well-timed and successful reforms is an important cornerstone of economic strength in Georgia. An important element of economic development and long-term economic growth is the reform of the compulsory cumulative pension system, which began in Georgia in 2019 and is being successfully implemented to this day. But, the problem is that the implementation of any long-term and large-scale reform faces certain challenges that require a deep analysis of the reform and the development of effective mechanisms for sustainable development. Due to the low investment culture of the society, the reform of the cumulative mandatory pension system has great social importance and is characterized by high public interest.