Wealthy Nations Research Articles

Carbon Trading in Developing Economies: Challenges, Opportunities, and Best Practices

Globally, carbon trading, a market-driven approach to cut greenhouse gas emissions, has become increasingly popular. Developing economies are increasingly looking at carbon trading as a strategy to balance economic progress with environmental sustainability, even though wealthier nations have historically been the main players in carbon markets. This assessment looks at the main obstacles, chances, and recommended procedures related to carbon trading in developing nations. The obstacles encompass feeble regulatory structures, insufficient knowledge, unstable markets, and giving precedence to commercial expansion above ecological issues. On the other hand, carbon trading offers chances for technological transfer, international financial access, climate risk mitigation, and sustainable development. These regions' best practices for carbon markets place a premium on robust regulatory frameworks, capacity building, equitable pricing systems, and public-private partnerships. By addressing the challenges and embracing these best practices, developing economies can leverage carbon trading to meet their development goals while contributing to global climate action.

Evaluation of Energy Security Submits on Climate Change; Kyoto Protocol and Copenhagen Accord

The rise and incessant increase of Industrialization, modernization and advance technology have attributed to a greater challenge in contemporary international politics. It has brought about a shift in major discuss and study of international relations and politics from the anarchical nature of nation states to climate change. This research work focuses on the hypocrisy in United Nation, a case study of the Kyoto Protocol and Copenhagen submit. It highlights the various submit held to find solution to climate change, the discrepancy and hypocritical politics or decision in the United Nation, solutions agreed from various submit and as well the United nation contribution to climate change. It adopted a qualitative method of research with data’s from written literature and journals from different scholars and UN articles. Realism was adopted as theoretical frame work which shows that sates will go to any extents to defends her interest not minding the global disaster, which has influenced the decisions and as brought about rational and immoral decisions from some advance or rich nations. It concludes that, the hypocritical nature of some states has posed more threats to the issues at hand, due to the use of fossil fuels, every wealthy nation today became wealthy, the world's largest development agencies refuse to support the use of fossil fuels, which poor countries may employ to escape poverty at the insistence of wealthier nations not minding the fact that they contribute more to global emission than the poor nations. The study therefore recommends that, a legal frame work need to be set, nation states need to forget political and ideological differences and rather corporate to find solution to the gory situation. Lastly, advance countries who contributed more to global emission should be held accountable and should as well finance poor countries to implement the policies.

GAN-Augmented Naïve Bayes for identifying high-risk coronary artery disease patients using CT angiography data

Coronary artery disease (CAD) is one of the most common cardiovascular disorders affecting millions of individuals globally. It is the leading cause of mortality in both the wealthy and impoverished nations. CAD patients exhibit a wide range of symptoms, some of which are not evident until a major incident occurs. The development of techniques for early detection and precise diagnosis is heavily dependent on research. The proposed system introduces a novel approach, Generative Adversarial Networks Augmented Naïve Bayes (GAN-ANB), to classify high-risk CAD patients using Coronary Computed Tomography Angiography (CCTA) imaging data. The database included images from Coronary Computed Tomography Angiography (CCTA) records of 5,000 individuals. The developed GAN framework consists of a generator to generate synthetic patient profiles, and a discriminator to distinguish between genuine and synthetic profiles to improve the identification of high-risk CAD patients. Adding synthetic data to the training process allowed the discriminator to be utilized further to improve predictive modeling. The performance of the GAN-enhanced prediction model was assessed using accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic curve (ROC). The model exhibited an outstanding Dice Similarity Coefficient (0.91), Mean Intersection Over Union (0.90), recall (0.96), and precision (0.98) in differentiating between high-risk and low-risk individuals. The identification of high-risk patients with CAD is greatly enhanced by the integration of GANs with clinical and imaging data. ROC of 0.99 was achieved by the GAN-ANB model, which outperformed conventional machine learning models, was achieved using the GAN-ANB model. High cholesterol level, diabetes, and some CCTA-derived imaging characteristics, including plaque load and luminal stenosis, were among the major predictors. This method offers a powerful tool for early diagnosis and intervention, potentially leading to improved patient outcomes and lower healthcare expenditure.

Do the Energy-Related Uncertainties Stimulate Renewable Energy Demand in Developed Economies? Fresh Evidence from the Role of Environmental Policy Stringency and Global Economic Policy Uncertainty

Despite earlier research on green energy, there is still a significant gap in understanding how energy-related uncertainties affect renewable energy consumption (REN), especially in developed nations. Thus, this study explicitly looks into how the energy-related uncertainty index (EUI) can promote (or diminish) REN in sixteen wealthy nations between 2000 and 2020. Furthermore, we attempt to specify the factors of REN and explore whether environmental policy stringency (EPS) and global economic policy uncertainty (GEPU) could help moderate (or intensify) the EUI-REN nexus. To achieve this, we employ different panel data methods. The results underscore that the EUI significantly impacts REN, denoting that higher uncertainties related to energy markets lead to promoting REN. Additionally, the (EUI × EPS) underlines that EPS has a favorable role in increasing the positive effect of the EUI on REN in sample developed countries while (EUI × GEPU) has a detrimental effect. Remarkably, the findings underline that the effect of the EUI on REN is more positive in high EPS countries and that the positive effect of the EUI is more moderate when GEPU is high. The findings also underscore that the development of the financial market, FDI, personal remittances, and EPS positively stimulate REN whereas CO2, total natural resources rents, economic activity, and GEPU have a detrimental impact. The results are robust, and authorities and policymakers are advised to implement a wide range of policy proposals to accomplish sustainable development goals (SDGs) 7 and 13.

Study of Patients’ Satisfaction with different types of Telemedicine Services provided by the Ministry of Health in Saudi Arabia

One way to gauge the quality of healthcare is to look at how satisfied patients are with the system overall. Finding out how happy patients are with various telemedicine services offered by Saudi Arabia's Ministry of Health is the main goal of this research. The satisfaction of Saudi Arabian customers using telemedicine services was assessed in a cross-sectional survey. Customers of the 940 medical contact centre and the Sehha app, two telemedicine services, were surveyed using a rigorous random selection technique. Two hundred and fifty users of the 940 medical contact centre and the Sehha app were selected at random to fill out a pre-designed survey about their level of satisfaction with various aspects of the two health services. Out of 250 people who used telemedicine services, 83.14 percent were happy with the care they received overall, while 8.03 percent were unhappy. These days, telemedicine apps are employed by a lot of wealthy nations and even some underdeveloped ones to help provide healthcare to people faster for all sorts of medical issues. In Saudi Arabia, telemedicine services generally had good satisfaction ratings, with no discernible variation in ratings between the 940 medical contact centre and the Sehha app. Customers who used telemedicine services were generally pleased and were even willing to recommend them to others.

Lipoprotein, Cholesterol, Treatment Strategies, and its Impact on Cardiovascular Diseases

A main cause of death internationally, cardiovascular (CV) illness accounted for about 31.4% of fatalities worldwide in 2012. According to estimates, a 33% decline in coronary heart disease (CHD) mortality in the United States between 1980 and 2000 was caused by a decrease in total cholesterol levels. Similar declines in CHD fatalities (varying from 19% to 46%) in other wealthy nations have been linked to lower total cholesterol levels. Lipoproteins are complex particles with a central core containing cholesterol esters and triglycerides surrounded by free cholesterol, phospholipids, and apolipoproteins, which facilitate lipoprotein formation and function. However, numerous individuals do not achieve LDL-C goal values because of statin resistance or adherence to statin medication. If cholesterol targets are not achieved with statins alone, alternative medicines include ezetimibe, fibrates, and nicotinic acid. In addition, people with familial high cholesterol levels (FH). Lipoprotein may act as a proinflammatory mediator that augments the lesion formation in atherosclerotic plaques. HDL metabolism represents a major target for the development of therapies intended to reduce the risk of atherosclerotic cardiovascular disease. Individual cardiovascular preventative treatments should be targeted largely at individuals at higher risk who will benefit most, with the prevention and treatment of dyslipidemia being viewed as a crucial component of those interventions. Since statins have been demonstrated to lessen the risk of serious vascular events by lowering low-density lipoprotein cholesterol (LDL-C), they continue to be the first-choice medication.

The Management of Bronchial Asthma (Tamak Shwasa) through Panchakarma Procedure with Ishvaku (Lagenariasiceraria) Vamana: A Case Report

Background Bronchial asthma, a hypersensitivity illness, is rising quickly in the modern world, particularly in wealthy nations. However, according to clinical features, bronchial asthma and Ayurvedic Tamaka Shwasa are similar diseases. Asthma is incurable, according to traditional medical knowledge. Both patients and doctors are looking at complementary and alternative systems of medicine as options because current prescriptions do not offer adequate treatment for terminal and long-term cures. Ayurvedic medicine has the potential to be a viable and efficient treatment option for bronchial asthma. Vaman karma is helpful for treatment globally so that people worldwide can keep faith in it based on scientific evidence. The first line of treatment for Tamakshwasa’s Utkleshita vastha is Vamana. To determine Vamana Karma’s involvement in Tamak shwas, a season it connected to Tamak shwasa has been searched for and attempted to be established in this case study. Purpose This study aimed to assess the efficacy of Ayurvedic management, including specific Ishwaku vaman karma, in Tamaka Shwasa. Materials and Methods A single case study of a 21-year-old man diagnosed with bronchial asthma. He was presented with frequent allergy due to dust, had an onset of sneezing due to cold weather, had a complaint of cold and cough on and off since childhood, and had a history of pneumonia in childhood. Observation and Outcome A 9-day symptomatic patient assessment was completed. The patient’s overall quality of life was greatly enhanced, and the outcome was satisfactory. In conclusion, the above-mentioned regimen significantly improved the management of bronchial asthma.

Improving COVID‐19 Detection Through Cooperative Deep‐Learning Pipeline for Lung Semantic Segmentation in Medical Imaging

ABSTRACTThe global impact of COVID‐19 has resulted in millions of individuals being afflicted, with a staggering mortality toll of over 16 000 over a span of 2 years. The dearth of resources and diagnostic techniques has had an impact on both emerging and wealthy nations. In response to this, researchers from the domains of engineering and medicine are using deep learning methods to create automated algorithms for detecting COVID‐19. This work included the development and comparison of a collaborative deep‐learning model for the identification of COVID‐19 using CT scan images, in comparison to previous deep learning‐based methods. The model underwent an ablation study using publicly accessible COVID‐19 CT imaging datasets, with encouraging outcomes. The suggested model might aid doctors and academics in devising tools to expedite the process of determining the optimal therapeutic approach for health professionals, hence reducing the risk of potential problems.

COVID-19 Vaccination and Public Health: Addressing Global, Regional, and Within-Country Inequalities.

The COVID-19 pandemic, with over 775 million cases and 7 million deaths by May 2024, has drastically impacted global public health and exacerbated existing healthcare inequalities. The swift development and distribution of COVID-19 vaccines have been critical in combating the virus, yet disparities in access to and administration of the vaccine have highlighted deep-seated inequities at global, regional, and national levels. Wealthier nations have benefited from early access to vaccines, while low- and middle-income countries (LMICs) have faced persistent shortages. Initiatives such as COVAX aimed to address these disparities, but challenges persist. Socioeconomic factors, education, ethnic identity, and the healthcare infrastructure play crucial roles in vaccine equity. For example, lower-income individuals often face barriers such as poor access to healthcare, misinformation, and logistical challenges, particularly in rural areas. Addressing these inequities requires a multifaceted approach, integrating national policies with local strategies to enhance vaccines' accessibility, counter misinformation, and ensure equitable distribution. Collaborative efforts at all levels are essential to promote vaccine equity and effectively control the pandemic, ensuring that all populations have fair access to life-saving vaccines. This review explores these complex issues, offering insights into the barriers and facilitators of vaccine equity and providing recommendations to promote more equitable and effective vaccination programs. With a focus on the different levels at which vaccination policies are planned and implemented, the text provides guidelines to steer vaccination strategies, emphasizing the role of international cooperation and local policy frameworks as keys to achieving equitable vaccination coverage.

Unequal exchange of labour in the world economy

Researchers have argued that wealthy nations rely on a large net appropriation of labour and resources from the rest of the world through unequal exchange in international trade and global commodity chains. Here we assess this empirically by measuring flows of embodied labour in the world economy from 1995–2021, accounting for skill levels, sectors and wages. We find that, in 2021, the economies of the global North net-appropriated 826 billion hours of embodied labour from the global South, across all skill levels and sectors. The wage value of this net-appropriated labour was equivalent to €16.9 trillion in Northern prices, accounting for skill level. This appropriation roughly doubles the labour that is available for Northern consumption but drains the South of productive capacity that could be used instead for local human needs and development. Unequal exchange is understood to be driven in part by systematic wage inequalities. We find Southern wages are 87–95% lower than Northern wages for work of equal skill. While Southern workers contribute 90% of the labour that powers the world economy, they receive only 21% of global income.

Forecasting corporate social investment in Asian based organizational features of corporate social responsibility

Corporate Social Responsibility (CSR) activities, which target social and environmental challenges, are prompted by pressures from stakeholders. As a result, businesses use Corporate Social Investment (CSI) channels to finance CSR initiatives in the areas in which they conduct business. There is still a dearth of empirical studies in developing regions, especially in Asian countries, despite the large number of CSR studies carried out in wealthy nations. In order to determine the degree to which Firm Size and Organizational Sector predict Corporate Social Investment (CSI) in Asia, this quantitative study used frameworks for CSR and stakeholder engagement. To find out if these two organizational traits, used separately or together, have a substantial impact on CSI, three study questions were presented. Data from 54 Asian-based companies that submitted reports to the Global Reporting Initiative (GRI) between 2018 and 2022 were examined in this study. Multiple regression analysis (MRA) using archival data from GRI reports showed that Organizational Sector emerged as a significant predictor (b = 0.275, p = 0.005), indicating that manufacturing and fertilizing companies contributed more to CSI than other companies, while Firm Size did not significantly predict CSI spending (b = −0.089, p = 0.259). This emphasizes how critical it is to take the Organizational Sector into consideration as an important predictor of corporate social responsibility (CSR) and how important it is to take this into account when figuring out how firms might support social development in Asian communities.

Identifying biodiversity surrogates and management indicator species for tall, WET Forests: A case study of australian arboreal marsupials

Halting the loss of biodiversity is a major challenge for humanity given the number of species at risk, the limited resources dedicated to conservation relative to levels of investment that are needed, and the impossibility of monitoring all threatened species, even in wealthy nations. Some of these challenges might be possibly addressed, in part, if conservation shortcuts could be found. These include the use of surrogates, proxies, and indicators in which easy to measure entities can accurately reflect the remainder of, for example, a particular assemblage of species.In the work reported here, we explored the indicator potential of particular species of arboreal marsupials in the tall, wet forests of south-eastern Australia. We did this through an empirical exploration of co-occurrence patterns using an analysis of a long-term dataset on arboreal marsupials that we gathered between 1997 and 2022 at 178 permanent field sites.Our analyses contained evidence of positive co-occurrence relationships between some pairs of species, but negative ones between others. In addition, relatively high levels of overall species richness in the arboreal marsupial assemblage were associated with four of the six species we analysed. We then tested the idea that these co-occurrence patterns were context-dependent. Although context dependence is a familiar issue in ecology, its importance for recognizing and understanding the limitations of surrogates like indicator species is often not well recognised. Indeed, we present evidence that some co-occurrence patterns varied across time and in response to key aspects of forest condition including the availability of nest sites in hollow-bearing trees, forest type, and stand age. We discuss these findings in relation to how context dependence can help us understand the applicability and limitations of ecological indicators. Our findings, based on long-term data, suggest that focused management efforts for a particular species as a “management indicator species” will not necessarily ensure positive outcomes for other species across all contexts. Therefore, targeted conservation efforts may be required for individual species, particularly species of conservation concern.

A Mathematical Model Investigating the Impact of Campaign Program on the Pattern of Transmission of Anemia in Pregnant Women

Anemia, a pervasive global health issue, is on the rise across the globe, impacting both developing and wealthy nations. Anemia, a hematological condition, can manifest at any point in life and is prevalent among pregnant individuals. The worldwide incidence of anemia among women of reproductive age is around 29.4%, with over 40% of pregnant women being affected. Anemia is a widespread issue that significantly contributes to illness and death, particularly in regions where malaria is prevalent. Anemia during pregnancy has a substantial effect on both the health of the fetus and the mother. Anemia has been identified as the cause of 20% of maternal fatalities in Africa. Iron deficiency is the primary cause of anemia. This research presents a comprehensive model that describes the dynamics of anemia in pregnant women and their fetus. The population is categorized into three classes: susceptible, impacted, and treated. A control factor that varies or changes over time, namely a campaign program, is being investigated. The model exhibits an equilibrium point and the stability of such points is assessed. Furthermore, the sensitivity analysis of the equilibrium point is conducted to identify the crucial parameters. Numerical simulations are conducted to observe the dynamic behavior of the model. Evidence demonstrates that the marketing program is successful in reducing the advancement of diseases. The implementation of an early accelerated campaign program greatly reduces the number of pregnant patients, as well as the yearly miscarriages and fatalities. However, discontinuing the applied treatment may reverse this positive outcome and increase the burden. Findings also suggest that the implementation of control measures helps to minimize the prevalence of anemia but may not eliminate the condition.

Development and Promotion Countermeasures for Export Growth of Pakistan Textile Products

Pakistan's textile industry is vital to GDP, employment, and exports. Pakistan is strategically located in the global textiles and apparel market due to its large production and export capabilities. This sector struggles with inconsistent product quality, market barriers, high global standards, and protectionist trade policies in wealthy nations. Addressing these issues is essential for industry growth and global competitiveness. This study identifies these challenges and proposes strategic solutions to improve export performance and global competitiveness to boost Pakistan's textile sector's economic stability and growth. A thorough mixed-methods strategy integrating qualitative and quantitative research methodologies was employed in the study. By conducting surveys by websites and literature reviews related to the industry, we were able to gather primary data. We also used secondary sources such as government reports, trade journals, and trade organizations to compile our data. We used quantitative analyses in our study to determine how spending on R&D, technology upgrades, and quality control affected export performance. We looked at energy consumption, production, waste management, and export amounts in various industries of Pakistan. Improving export performance and meeting international standards requires investments in quality control, technology upgrades, and research and development, according to the study. It also lists the obstacles to entering certain markets and suggests ways to overcome them, such as through government assistance, sustainable practices, and vocational education and training. If Pakistan's textile industry follows these suggestions, it will become more competitive internationally.

Development of IoT based intelligent irrigation system using particle swarm optimization and XGBoost techniques

A crop needs regular watering throughout its life to grow well. Irrigation improves food growth. Machines irrigate plants. The dry Sahel, which gets a lot of rain during the summer season but is dry in winter, needs irrigation. When it doesn't rain enough, crops need watering. By constantly monitoring soil moisture, humidity, temperature, and pH, precision agriculture reduces water use and increases crop output. Precision gardening uses less water. In many wealthy nations, efficient farming requires the internet of things (IoT). Particle swarm optimization (PSO) and XGBoost are used in this IoT-based intelligent watering system. Humidity and moisture sensors gather soil data at grass roots. Sensors constantly gather this data. These data are useless for smart watering. PSOselects smart watering data. This reduces central cloud info storage. Then, machine learning methods are trained using soil humidity, moisture, crop, and weather data. These programs can calculate a crop's water requirements. IoT devices control irrigation system water flow and results in saving fresh water. XGBoost algorithm is saving water from 23% to 27% for different crops.

The right time: women, medicine and maternal age in 1980s Aotearoa New Zealand

In the late twentieth century, increasing numbers of women in wealthy nations waited until they were aged in their 30s to give birth and become parents. This article examines responses...

Trade Diversion effects of China`s Vat Export Rebates

AbstractThe utilization of value-added tax (VAT) export rebates serves as a key component of Chinese trade policy. While existing literature extensively demonstrates the positive impact of these rebates on Chinese exports, the potential negative repercussions for global trade, widely debated in the media, have remained relatively unexplored. This study assesses the trade diversion effects of China's VAT rebates within a "four-way" fixed effects Poisson Pseudo-Maximum Likelihood structural gravity framework spanning 75 countries over the period 2004–2018. The results indicate that, on average, a 1% increase in the rebate leads to a 2.62% reduction in third-country exports. The impact varies significantly at the country level. Wealthier nations with greater trade liberalization and diversified exports at the intensive margin are less susceptible to the effects of China’s export rebate policy. Additionally, there is evidence that countries exporting higher-quality goods experience more significant negative effects. Finally, the negative effects are driven by machinery and equipment sector and intensive margin.

Forecasting corporate social investment in Asian based organizational features of corporate social responsibility

Corporate Social Responsibility (CSR) activities, which target social and environmental challenges, are prompted by pressures from stakeholders. As a result, businesses use Corporate Social Investment (CSI) channels to finance CSR initiatives in the areas in which they conduct business. There is still a dearth of empirical study in developing regions, especially in Asian countries, despite the large number of CSR studies carried out in wealthy nations. In order to determine the degree to which Firm Size and Organizational Sector predict Corporate Social Investment (CSI) in Asia, this quantitative study used frameworks for CSR and stakeholder engagement. To find out if these two organizational traits, used separately or together, have a substantial impact on CSI, three study questions were presented. Data from 54 Asian based companies that submitted reports to the Global Reporting Initiative (GRI) between 2018 and 2022 were examined in this study. Multiple regression analysis (MRA) using archival data from GRI reports showed that Organizational Sector emerged as a significant predictor (b = 0.275, p = 0.005), indicating that manufacturing and fertilizing companies contributed more to CSI than other companies, while Firm Size did not significantly predict CSI spending (b = −0.089, p = 0.259). This emphasizes how critical it is to take organizational sector into consideration as an important predictor of corporate social responsibility (CSR), and how important it is to take this into account when figuring out how firms might support social development in Asian communities.

How the GATT agreement on agriculture shifted pollution from its richer to poorer members: Implications for sustainability mandates of trade agreements

This paper evaluates the impact of the General Agreement on Tariffs and Trade's Agreement on Agriculture (GATT AA) on outcomes outlined as its sustainability goals. They include adopting and sustaining agricultural practices to lower fertilizer pollution from nitrogen and phosphate, as well as to lower CO2 levels from vegetal and animal production. This study evaluates if these goals were met for those nations that joined the GATT AA. Applying an Environmental Kuznets Curve (EKC) framework, we examine the change in levels of the specific pollutants specified in the GATT AA's Application of Phytosanitary Measures (SPS) provision for 101 countries for the time frame pre- and post- joining the GATT AA. The results suggest that wealthy GATT AA member nations were able to lower their integrated agrarian toxicity relatively more and mainly through increasing the imports of foodstuffs. The implication is that trade liberalization may have allowed richer nations to lower their pollution levels by importing rather than producing certain crops associated with relatively more toxic fertilization. Further investigation can analyze such findings in the context of changing assumptions of EKC and Ecologically Unequal Exchange theories.

The Folly of Food Waste amidst Food Insecurity in the United States: A Literature Review

Food insecurity is an economic and social condition that involves individuals having limited or uncertain access to healthy food. Despite the well-intentioned efforts of both governmental and not-for-profit organizations in addressing food insecurity, well over one-in-ten households in the U.S., the wealthiest nation in the world, experience food insecurity every year. The objective of this literature review was to identify and explicate the methods and outcomes of food insecurity interventions that have been conducted among U.S. adults. This literature review identified 38 studies detailing several government programs and research interventions designed to address food insecurity. Results from the review highlight how the Supplemental Nutrition Assistance Program (SNAP), The Emergency Food Assistance Program (TEFAP), and not-for-profit food banks have demonstrated success in improving food insecurity. However, the prevalence of food insecurity among U.S. households has fluctuated without any sustained decreases that achieve a food insecurity rate that remains below 10 percent of the population. Food waste, which refers to food that is edible yet discarded at the retail or consumption phases, is rampant in the U.S., as approximately 30 percent (66.5 million tons) of edible food is wasted after leaving the farm every year. Food waste prevention efforts that involve rescuing edible, nutritious food and redistributing it to individuals who are food insecure can promote both environmental wellbeing and public health through simultaneous reductions in food waste and food insecurity.