Global Development Research Articles

СИСТЕМНИЙ АНАЛІЗ МЕТАЛУРГІЙНОГО ВИРОБНИЦТВА ЯК ПІДҐРУНТТЯ ФОРМУВАННЯ СИСТЕМИ КОМПЛАЄНС

The purpose of the study is to determine modern approaches to the strategy of applying the compliance system at metallurgical enterprises. From the standpoint of the theory of hypercomplex dynamic systems, the components of the metallurgical enterprise are considered. Hypercomplexity is provided by the variety of sub-sectors included in the research object. The system properties of metallurgical production are highlighted, in particular, hypercomplexity (S1), dynamism (S2) and structurality (S3). It is shown that one of the latest global scientific developments regarding the procedure for compliance with obligations in the financial and industrial spheres is the theoretical concept of Compliance. It is advisable to provide advisory functions to the Compliance system at the enterprise, when the final decision on the implementation of its recommendations is taken by the management of the enterprise at the appropriate level. It is shown that common to all theories of Compliance is finding a balance between such categories as "compliance" with established requirements and "risks" from inappropriate fulfillment of obligations. The ratio of financial risks and the probability of compliance with these risks of business entities is given. It is shown that Compliance should acquire the status of not only a controlling body, but also take into account the elements of psychology in the implementation of its activities.

Sustainable Palm Oil Investment Climate in Indonesia: Foreign and Domestic Promotion by the Local Government

This paper focuses on foreign and domestic palm oil investment promotion strategies in Dumai, Indonesia, to assess the sustainable development investment climate. Exploratory qualitative research is conducted with a case study to examine the foreign and domestic oil palm investment climate. The researchers employed NVivo 12 Plus software and the Biblioshiny application to collect, analyse and visualise bibliometric data. The research indicates that the Dumai government has pursued a strategy to stabilise the foreign and domestic palm oil investment climate by conducting promotions abroad and domestically. The conclusions show that the oil palm investment climate has been unable to positively contribute to economic, social and environmental growth in sustainable development in Dumai. Positive impacts of oil palm investment include offering livelihoods, creating new jobs and increasing local revenue. This research aids the government of Dumai in improving the global palm oil sustainable development investment climate.

A Study on Employees Perception From Govche India Private Limited Towards Investing in Indian Stock Market

Stock market investments have become a typical occurrence for all people today. The development of the country's stock markets has a significant impact on the growth of the national economy. Global financial market developments have opened up a wide range of markets and investment opportunities for investors. Making investment decisions is a difficult undertaking that requires extensive analysis. Research has been conducted to identify the variables affecting investors' preferences and investment choices. Through the use of a structured questionnaire, primary data is acquired. The study included 107 respondents as its sample size. Data was analysed in this study using percentages, chi square, and Anova. It has been discovered that economic factors such as currency strength and legal considerations have an impact on investment choices.

Research on Global Exhibition Industry Management Models and Their Implications for China's Regional Exhibition Industry

The exhibition industry, as an integral part of the modern service sector, functions as a catalyst for regional economic development and is one of the key indicators of a region's openness and developmental potential. With over 170 years of growth, international exhibition industry management models have matured significantly. Developed countries such as Germany, the United Kingdom, France, and Canada have gradually established four predominant development models: government-led, market-led, association-led, and a hybrid of government and market. These models hold a dominant position in the global development of the exhibition industry. The pace and level of development of the exhibition industry largely depend on the chosen management model. An appropriate industry management model can foster rapid development of the exhibition industry, whereas an unsuitable one can hinder progress. Under the new circumstances, China insists on implementing more extensive, broader, and deeper opening-up policies, accelerating the internationalization of the exhibition industry and gradually forming five major regional clusters: the Yangtze River Delta, the Pearl River Delta, the Bohai Rim, the Northeast, and the Midwest. In this context, analyzing international exhibition industry management models is of significant importance for improving China's exhibition industry management and promoting high-quality development of regional exhibition industries in China.

Geographies of super-philanthropy: Disaggregating the global philanthropic complex

In recent decades the world has witnessed an unparalleled growth of philanthropic initiatives and institutions that has proven inextricable from the vast accumulation and concentration of wealth on a global scale. Echoing recent calls for geographers to study philanthropy, this paper seeks to advance a critical geographical understanding of globalising philanthropy. Inspired by geographical scholarship on relational thinking, the paper frames the varied manifestations of contemporary philanthropy as a ‘philanthropic complex’ in order to understand philanthropy through central themes of relationality, intermediation and stabilisation. Advancing theories of philanthropy by characterising the complex's geographical unevenness and political functions of depoliticisation, the paper closes by outlining avenues in which relational thinking about philanthropy can advance geographical theories of elites and global development.

Factors Associated with Inclusion of Japan in Phase I Multiregional Clinical Trials in Oncology.

Early inclusion of Japan in the global development program could be a key factor in reducing the drug lag, making participation in phase I multiregional clinical trials (Ph. I MRCTs) an important consideration for oncology drug development in Japan. We aimed to investigate the factors associated with the inclusion of Japan in Ph. I MRCTs in oncology. We compared the trial design, target population, type of primary tested drug, trial conduct profile, and sponsor profile for Ph. I MRCTs with or without Japan conducted by the top 20 companies in more than two countries and started between January 1, 2011, and December 31, 2020. One hundred and ninety-seven Ph. I MRCTs included Japan, and 697 did not. Detailed features of the Ph. I MRCTs in oncology were summarized, and several factors (trial design, target population, trial conduct profile, and sponsor profile) associated with inclusion of Japan in the Ph. I MRCTs were identified. It is important for Japanese subsidiaries within global pharmaceutical companies to closely communicate with the headquarters based on medical practice and unmet needs in Japan to join global development from an early stage. In addition, further efforts to attract emerging biopharmaceutical companies to Japan from the regulatory and/or political perspectives would be needed, thereby preventing drug lag in Japan.

Modeling and FDTD discretization of stochastic Maxwell's equations with Drude dispersion

We develop the stochastic Maxwell's equations with Drude model under both additive and multiplicative noises. The additive noises characterize the random fluctuations in the electric current and magnetic current densities in Maxwell's equations, while the multiplicative noise describes the external fluctuation of electric field in the Drude dispersion equation of motion. For the stochastic models with Drude dispersion, we derive the averaged global energy law considering both types of noises. The CN-FDTD and Yee-FDTD discretization schemes are developed for solving the stochastic system over staggered grids. We establish the discrete averaged global energy laws for the CN-FDTD and Yee-FDTD schemes. Numerical experiments show the discrete averaged global energy evolutions and the convergence rates of the schemes for the stochastic Maxwell's equations with Drude model. We numerically simulate and analyze the stochastic electromagnetic propagation within Drude materials under various sinusoidal sources, initial wave conditions and additive and multiplicative noises.

Life Cycle Assessment and Model Optimization for Sustainable Energy Cross-Border E-Commerce

INTRODUCTION: In an in-depth study of the application of sustainable energy in cross-border e-commerce, a comprehensive assessment and model optimization of its life cycle are conducted to promote the practical application of sustainable development in e-commerce. With the increasing global concern for renewable energy and environmental protection, e-commerce, as an international business model, has attracted much attention in terms of the environmental and social impacts of its sustainability.OBJECTIVES: The aim is to provide scientific assessment methods and effective model optimization strategies to promote the feasibility and sustainability of cross-border e-commerce for sustainable energy.METHODS: A comprehensive life cycle assessment (LCA) model was constructed using the system life cycle assessment (SLCA) methodology by collecting data from various aspects of sustainable energy cross-border e-commerce. The model considers the entire life cycle process from energy production, logistics, transportation, and product manufacturing to final consumption and integrates various factors such as resource utilization, environmental emissions, and social responsibility. Based on the assessment, a series of model optimization strategies are proposed, including suggestions for improving supply chain efficiency, promoting green energy applications, and strengthening social responsibility.RESULTS: This study achieved significant life cycle assessment and model optimization results. In terms of energy use, promoting the application of renewable energy significantly reduces carbon emissions; in terms of supply chain management, optimization leads to an overall efficiency improvement and a reduction in resource wastage; and in terms of social responsibility, the enterprise strengthens employee training and community involvement, which enhances its social image. These results show that sustainable energy cross-border e-commerce can better achieve sustainable development goals through systematic assessment and optimization.CONCLUSION: Life cycle assessment and model optimization provide scientific assessment methods and practical suggestions for sustainable energy cross-border e-commerce. In global sustainable development, the e-commerce industry should actively adopt sustainable energy and minimize its negative impacts on the environment and society by optimizing production and supply chain management. Future research can continue to expand the assessment model and deeply explore the potential of sustainable energy in e-commerce to provide more precise guidance for the industry's sustainable development.

What and why in teaching about sustainability

Education has responded to global Sustainable Development (SD) goals by drawing on a range of issue-related, context-based, and cross-curricular approaches to teaching SD. This paper aims to examine how teachers describe the content in SD and how they justify this content concerning their teaching practice. The Pedagogical Content Knowledge (PCK) framework, with its reflective tool Content Representation (CoRe), was used in combination with semi-structured interviews to capture 18 Swedish upper-secondary science teachers’ reflections. The results indicate four themes of content that the teachers emphasise: energy and global warming, ecosystem services and biodiversity, presence of harmful substances and materials in nature, and imbalance of natural substances in nature. The teachers justified these content themes in terms of the importance of students’ gaining different perspectives (local, global, ecological, social, and economic), belief in the future, action competence, and general scientific education. The paper contributes to sustainability education research, as it focuses on teaching sustainability in the light of the PCK framework. Also, it can support and inspire teachers when they decide what content to include when teaching SD.

Global oceans suffer extreme heatwaves intensifying since the early 21st century: A new comprehensive index

As a result of global warming, major ocean basins have witnessed an increase in the number of extreme warm events and a decrease in the number of extreme cold events, increasing the number of marine heatwave (MHW) events. Previous quantification of MHW events has been limited to simple single metrics, which can only recognize some characteristics from a particular aspect. Here, we propose a new marine Heat Wave Comprehensive Index (HWCI) by fusing multiple metrics to characterize the scalable cumulative intensity of MHWs, which exhibits excellent identification reliability and superiority to effectively monitor the evolutionary patterns of various levels of MHW events. We find that five levels of global MHW events have presented an obvious spatial expansion and temporal enhancement pattern since the early 21st century, with the obvious spatial contraction (32.98 %) of weak events followed by the expansion (19.82 %) of extreme events at the highest growth rate of 0.07, primarily in the mid–low-latitude oceans and the Arctic. The results demonstrate that extreme MHW events dominate global MHW evolution patterns and that the expansion and intensification of such episodes have major implications for the event distribution and level structure. The new indicator is promising for directly measuring and identifying MHWs, and contributes to a more comprehensive understanding of the evolution of MHWs in the context of global climate change.

Modernization Theory Revised: Testing the Relationship between Inward Foreign Direct Investment and Homicide

Purpose: Modernization theory suggests that economic development is temporarily disruptive to social life and can lead to crimes of violence such as homicide. However, few studies have considered how the modernization process works. Specifically, they neglected the role of globalization. Previous research has suggested that certain measures of globalization may be theoretically linked to homicide. This study examines how inward Foreign Direct Investment (FDI), a key component of globalization and economic development, is associated with cross-national homicide rates.
 Methods: Data from 101 countries were collected and analyzed to examine the relationship between inward FDI and homicide. Indirect effects of inward FDI on homicide through urbanization and economic growth were also examined.
 Results: The results show that inward foreign direct investment increases cross-national homicide rates, both directly and indirectly through increased urbanization.
 Conclusion: While economic development benefits society, the concomitant, deleterious effects should be considered by policymakers, especially those seeking inward foreign direct investment in their countries. Future researchers will want to consider examining other measures of globalization.

Does energy transition policy enhance urban green innovation capabilities?–a quasi-natural experiment based on China’s new energy demonstration city policy

As the importance of global climate change and sustainable development issues increases, the enhancement of urban green innovation capabilities is particularly crucial since cities are the main source of energy consumption and carbon emissions. This study focuses on China’s New Energy Demonstration City policy to explore how it influences urban green innovation capabilities. By employing a quasi-natural experimental method, combined with data from 282 Chinese cities from 2007 to 2021, this paper provides an in-depth analysis of the impact of the New Energy Demonstration City policy on urban green innovation capabilities. It was found that the policy significantly improves the cities’ green innovation capabilities, and this conclusion remains valid after robustness checks. The study also reveals that technological investment and public environmental awareness are two critical mechanisms through which the New Energy Demonstration City policy affects urban green innovation capabilities. Furthermore, this policy has been found to significantly enhance the green innovation capabilities of neighboring cities through spatial spillover effects. The study also examines the interaction between the national-level Big Data Comprehensive Experimental Zone policy and the New Energy Demonstration City policy, discovering that the pilot policy of the national-level Big Data Comprehensive Experimental Zone has to some extent promoted the effectiveness of the New Energy Demonstration City policy in driving urban green transformation. This research provides a new perspective for understanding the dynamics of urban green innovation and points the way for future research and policymaking.

A dual-population-based evolutionary algorithm for multi-objective optimization problems with irregular Pareto fronts

When solving multi-objective optimization problems (MOPs) with irregular Pareto fronts (e.g., disconnected, degenerated, inverted) via evolutionary algorithms, a critical issue is how to obtain a set of well-distributed Pareto optimal solutions. To remedy this issue, we propose a dual-population-based evolutionary algorithm with individual exploitation and weight vector adaptation, named DPEA-IEAW. Specifically, the two populations, termed globPop and locPop, individually evolve by decomposition-based and Pareto dominance-based methods, responsible for global evolution and local evolution, respectively. These two populations collaborate through substantial information exchange, thereby facilitating each other’s evolution. Firstly, the distribution of the two populations is analyzed and an individual exploitation operation is designed for locPop to exploit some promising areas that are undeveloped in globPop. Then, the guide-position is devised for globPop to indicate the optimal point for a subproblem on the Pareto front (PF). By using the guide-position, a strategy for generating uniform weight vectors is proposed to improve the population diversity. Finally, comprehensive experiments on 37 widely used test functions and 2 real-world problems demonstrate that the proposed DPEA-IEAW outperforms comparison algorithms in solving MOPs with various PFs.

Tracking annual changes of coastal aquaculture ponds in China during 1986–2021

The rapid expansion of coastal aquaculture ponds has made outstanding contributions to global food security and economic development in coastal areas, but this expansion inevitably has a significant impact on coastal ecosystems. Strengthening the spatiotemporal monitoring of aquaculture ponds is crucial for optimizing coastal land use and efficiently managing aquaculture ponds. However, aquaculture pond data on national scale and interannual variability are lacking. Here, we utilized Landsat times series images from 1986 to 2021 to generate annual maps of aquaculture ponds in China's coastal areas and investigated its spatiotemporal characteristics. We find that the overall accuracy of our aquaculture ponds classification was over 90% each year. Aquaculture ponds were concentrated in Bohai Bay, the Jiangsu Coastal Plain, and the Pearl River Delta in China's coastal areas. The time series of aquaculture ponds change could be divided into three stages: rapid growth (1986–2000), stable growth (2001–2016), and a slow decline (2017–2021). The spatial evolution of aquaculture ponds was characterized by (1) continuous seaward expansion, (2) continuous inland and seaward expansion, (3) continuous inland expansion, (4) continuous expansion and then shrinkage, and (5) rapid shrinkage. Moreover, the main aquaculture ponds classification errors were salt pans, reservoirs, abandoned ponds, port facilities, lakes, and pit ponds. Our study demonstrated a new method for applying satellite remote sensing for coastal ecosystem management, and our maps and findings can be used to optimize the development and sustainability of coastal aquaculture ponds.

Research on the development status, problems, and optimization path of green finance in commercial banks

With the green economy gradually becoming the trend of global economic development, green finance has also risen to China's national strategy and become a new blue ocean business for the future development of commercial banks. The development of green finance not only plays an obvious role in improving economic efficiency and realizing the transformation and upgrading of industrial structure, but also plays a great significance role in environmental protection, and realize the harmony and unity of man and nature, which is an important initiative to realize the progress and development of the country.The article firstly points out the problems in the process of green finance development, and analyzes the challenges faced in the process of green finance development. Finally, the article gives the optimized ways for commercial banks to develop green finance from four perspectives, such as learning international law governance experience, introducing the Equator Principles for project evaluation, improving policy support, strengthening government guidance, strengthening product research and development and innovation, and attaching importance to talent cultivation, so as to provide a reference for China to further promote green finance and achieve high-quality development.

A Comprehensive Survey of Deep Learning and Its Applications in Advancing Artificial Intelligence

: Deep learning, a subset of machine learning, stands at the forefront of artificial intelligence, striving to bridge the gap to its ultimate goal. This paper employs summary and induction methodologies to research into the area of deep learning. It begins by surveying the global development and current landscape of deep learning. Next, it elucidates the structural principles, characteristics, and key models, including stacked auto encoders, deep belief networks, deep Boltzmann machines, and convolutional neural networks. Furthermore, it examines the latest advancements and applications of deep learning across diverse domains such as speech processing, computer vision, natural language processing, and medical diagnostics. Finally, the paper outlines the challenges and future research directions within the realm of deep learning

From sub-Saharan Africa to China: Evolutionary history and adaptation of Drosophila melanogaster revealed by population genomics.

Drosophila melanogaster is a widely used model organism for studying environmental adaptation. However, the genetic diversity of populations in Asia is poorly understood, leaving a notable gap in our knowledge of the global evolution and adaptation of this species. We sequenced genomes of 292 D. melanogaster strains from various ecological settings in China and analyzed them along with previously published genome sequences. We have identified six global genetic ancestry groups, despite the presence of widespread genetic admixture. The strains from China represent a unique ancestry group, although detectable differentiation exists among populations within China. We deciphered the global migration and demography of D. melanogaster, and identified widespread signals of adaptation, including genetic changes in response to insecticides. We validated the effects of insecticide resistance variants using population cage trials and deep sequencing. This work highlights the importance of population genomics in understanding the genetic underpinnings of adaptation, an effort that is particularly relevant given the deterioration of ecosystems.

The Role and Challenges of Machine Learning in the Construction of a Community of Human Destiny

- The advent of machine learning (ML) has significantly transformed various fields, including the realm of social sciences and humanities. This paper explores the pivotal role and inherent challenges of machine learning in fostering the construction of a community of human destiny (CHD), a concept emphasizing shared global interests and collective human development. Machine learning, with its capacity to analyze vast datasets and uncover patterns, holds the potential to address complex issues such as poverty, inequality, and environmental sustainability, which are integral to the community of human destiny vision. However, the deployment of machine learning in this context is fraught with challenges, including ethical considerations, data privacy concerns, and the need for interdisciplinary collaboration. By examining theoretical frameworks, this paper aims to provide insights into how machine learning can be harnessed effectively to advance the goals of community of human destiny while also highlighting the importance of governance frameworks and ethical guidelines in ensuring that machine learning contributes positively to the common good. The paper argues that while machine learning presents significant opportunities for the community of human destiny, a cautious and responsible approach is essential to navigate the associated challenges and to ensure that technological advancements align with humanistic values and the overarching goal of a harmonious and sustainable global community.

World Controversy: Water Sustainability In An Environmental Accounting Perspective

Social and environmental concerns have emerged as globally compelling topics, necessitating attention from all stakeholders due to their significant impact on human life. Sustainable global economic development is intricately tied to the Triple Bottom Line concept, emphasizing Profit, People, and Planet. Among critical natural resources, water resources play a central role across various economic sectors, especially amidst escalating global water scarcity and degradation challenges. While research in this area has evolved significantly, many studies remain limited in scope, focusing on specific processes or regions and failing to provide comprehensive insights into water usage across different sectors. Building upon previous research, this study employs a Systematic Literature Review (SLR) method from 2019 to 2023 to understand trends and progress in water sustainability accounting research. Through the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) method, 23 relevant articles were identified and analyzed from various publishers such as Elsevier, Emerald, MDPI, and others. The findings reveal a diverse distribution of articles across publishers, with Elsevier being the most frequently utilized. This study contributes to the literature by offering insights into recent trends and areas of focus in water sustainability accounting research, informing future research directions and policy-making efforts to address social, environmental, and economic challenges effectively.

PRODIGE - envelope to disk with NOEMA III. The origin of complex organic molecule emission in SVS13A

Complex organic molecules (COMs) have been found toward low-mass protostars, but the origins of the COM emission are still unclear. It can be associated with, for example, hot corinos, outflows, and/or accretion shock and disk atmospheres. We aim to disentangle the origin of the COM emission toward the chemically rich protobinary system SVS13A using six O-bearing COMs. We conducted NOrthern Extended Millimeter Array (NOEMA) observations toward SVS13A as part of the PROtostars DIsks: Global Evolution (PRODIGE) program. Our previous DCN observations reveal a possible infalling streamer, which may affect the chemistry of the central protobinary by inducing accretion outbursts and/or shocked gas. We further analyzed six O-bearing COMs: CH3OH aGg'- (CH2OH)2 C2H5OH CH2(OH)CHO CH3CHO and CH3OCHO . Although the COM emission is not spatially resolved, we constrained the source sizes to $ arcsec (90$-$120 au) by conducting uv-domain Gaussian fitting. Interestingly, the high-spectral-resolution data reveal complex line profiles with multiple peaks; although the line emission is likely dominated by the secondary, VLA4A, at LSR =7.36$ km s$^ $, the numbers of peaks (sim $2-5$), the velocities, and the linewidths of these six O-bearing COMs are different. The local thermodynamic equilibrium (LTE) fitting unveils differences in excitation temperatures and emitting areas among these COMs. We further conducted multiple-velocity-component LTE fitting to decompose the line emission into different kinematic components. As a result, the emission of these COMs is decomposed into up to six velocity components from the LTE modeling. The physical conditions (temperature, column density, and source size) of these components from each COM are obtained, and Markov chain Monte Carlo sampling was performed to test the fitting results. We find a variety in excitation temperatures ($100-500$ K) and source sizes (D$ au) from these kinematic components from different COMs. The emission of each COM can trace several components, and different COMs most likely trace different regions. Given this complex structure, we suggest that the central region is inhomogeneous and unlikely to be heated by only protostellar radiation. We conclude that accretion shocks induced by the large-scale infalling streamer likely exist and contribute to the complexity of the COM emission. This underlines the importance of high-spectral-resolution data when analyzing COM emission in protostars and deriving relative COM abundances.