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Abstract Background Environmental quality significantly affects various aspects of human existence. This study employs ecological footprint as a proxy to assess the impact of environmental quality on the TFR, measured as births per woman. This study investigates the extent to which ecological footprint indicators impact on the TFR in across 31 countries between from 1990 to 2017. Methods We gathered data on ecological footprints, specifically carbon, agricultural land, grazing land, forest products, and fisheries, from the Global Footprint Network. Information on the TFR, Human Development Index (HDI), and per capita Gross National Income (GNI) were sourced from the World Bank and the United Nations. We applied static panel and quantile regression models to scrutinize the connection between the ecological footprint and TFR, showing how the former influences the latter. Results The outcomes reveal that, in both fixed and random effects models, factors including HDI, carbon, and fishing grounds exert a negative influence on TFR, all at a significance level of p

Background: Environmental quality significantly affects various aspects of human existence. This study employs ecological footprint as a proxy to assess the impact of environmental quality on the TFR, measured as births per woman. This study investigates the extent to which ecological footprint indicators impact on the TFR in across 31 countries between from 1990 to 2017. Methods: We gathered data on ecological footprints, specifically carbon, agricultural land, grazing land, forest products, and fisheries, from the Global Footprint Network. Information on the TFR, Human Development Index (HDI), and per capita Gross National Income (GNI) were sourced from the World Bank and the United Nations. We applied static panel and quantile regression models to scrutinize the connection between the ecological footprint and TFR, showing how the former influences the latter. Results: The outcomes reveal that, in both fixed and random effects models, factors including HDI, carbon, and fishing grounds exert a negative influence on TFR, all at a significance level of p < 0.01. Conversely, cropland and forest product footprints exhibited a favorable impact on the TFR (p < 0.01). Furthermore, GNI per capita positively affected the TFR in both models, with a p-value of 0.01. Quantiles regression analysis demonstrated that HDI and carbon footprint had a negative impact on TFR across all quantiles. This statistical significance is maintained for all quantiles, although it is only significant for the carbon footprint up to the 60th quantile, at p < 0.01. Conclusions: This study establishes a negative correlation between specific ecological footprint indicators, such as carbon and fishing grounds, and TFR. Conversely, there was a positive correlation between the footprint of forest products and the TFR. The primary conclusion drawn is that there is heterogeneity in the results regarding the relationship between ecological footprint and TFR. Moreover, the ecological footprint indicators considered in this study did not uniformly influence TFR. Each ecological footprint indicator exhibited distinct effects on the TFR, displaying either positive or negative correlation coefficients. Future research endeavors may delve into how ecological footprints impact other population dynamics, such as mortality and migration. [ABSTRACT FROM AUTHOR]

Tourism is based on the physical movement of people, and it is therefore of fundamental importance to have a transport system that is functional and that can facilitate travel to tourist destinations. However, transport is also important in itself because it ensures the freedom of movement for people and reduces social distances, in turn promoting growth and economic development. For this reason, it is necessary to design a transport and infrastructure system that is functional and promotes the accessibility of tourist destinations. Nodal analysis, applied to tourism flows in Italy, highlights the contradiction of a transport system which has enforced the policy of large hubs, in a country where there are many tourist destinations. Nevertheless, the nodal analysis methodology applied to the tourist flows show the need to strengthen the connection between the Adriatic and Tyrrhenian coasts, as well as the connection with some regions of the south, such as the Basilicata region. Moreover, it would be appropriate to enhance the railway line on the Adriatic dorsal in order to reach some tourist regions with greater ease. In the same way, the geographical configuration of Italy makes an enhancement of the ports highly desirable, creating an intermodal system. [ABSTRACT FROM AUTHOR]

This paper aims to identify factors that influence the successful implementation of ODA rural development projects for developing countries. To this end, it has analysed the implementation process of a project, ‘The Integrated Rural Development Project in Kyrgyz Republic’, currently being carried out in Kyrgyzstan via Good Neighbors International (GNI) with support from KOICA (Korean International Cooperation Agency). The analysis method employed in this study is decision tree analysis. By means of a review of previous studies on the implementation of ODA projects, variables that are believed to have an impact on the successful implementation of ODA rural development projects were derived. The values of each variable for thirty villages in Kyrgyzstan were derived and used as independent variables, and decision tree analysis was performed using the overall execution performance score for each village as the dependent variable. As a result, it was found that co-operation between field managers active at the project site and village residents was the most important determining factor of success.

The primary goal of common wheat (T. aestivum) breeding is increasing yield without negatively impacting the agronomic traits or product quality. Genetic approaches to improve the yield increasingly target genes that impact the grain weight and number. An energetic trade-off exists between the grain weight and grain number, the result of which is that most genes that increase the grain weight also decrease the grain number. QTL associated with grain weight and number have been identified throughout the hexaploid wheat genome, leading to the discovery of numerous genes that impact these traits. Genes that have been shown to impact these traits will be discussed in this review, including TaGNI, TaGW2, TaCKX6, TaGS5, TaDA1, WAPO1, and TaRht1. As more genes impacting the grain weight and number are characterized, the opportunity is increasingly available to improve common wheat agronomic yield by stacking the beneficial alleles. This review provides a synopsis of the genes that impact grain weight and number, and the most beneficial alleles of those genes with respect to increasing the yield in dryland and irrigated conditions. It also provides insight into some of the genetic mechanisms underpinning the trade-off between grain weight and number and their relationship to the source-to-sink pathway. These mechanisms include the plant size, the water soluble carbohydrate levels in plant tissue, the size and number of pericarp cells, the cytokinin and expansin levels in developing reproductive tissue, floral architecture and floral fertility. [ABSTRACT FROM AUTHOR]

Starting from the fact that the index of human development is a mirror reflecting the integrated standard of living, education level and health of the population of a country, the paper presents and analyzes the evolution of the human development index in 46 European states during 1990-2017, as well and grouping and ranking them according to the values of their four components. The analyzes revealed that there are significant differences regarding the rank of some countries in the hierarchy of HDI values compared to its rank according to the individual values of the indicators that enter the HDI structure.

The primary goal of common wheat (T. aestivum) breeding is increasing yield without negatively impacting the agronomic traits or product quality. Genetic approaches to improve the yield increasingly target genes that impact the grain weight and number. An energetic trade-off exists between the grain weight and grain number, the result of which is that most genes that increase the grain weight also decrease the grain number. QTL associated with grain weight and number have been identified throughout the hexaploid wheat genome, leading to the discovery of numerous genes that impact these traits. Genes that have been shown to impact these traits will be discussed in this review, including TaGNI, TaGW2, TaCKX6, TaGS5, TaDA1, WAPO1, and TaRht1. As more genes impacting the grain weight and number are characterized, the opportunity is increasingly available to improve common wheat agronomic yield by stacking the beneficial alleles. This review provides a synopsis of the genes that impact grain weight and number, and the most beneficial alleles of those genes with respect to increasing the yield in dryland and irrigated conditions. It also provides insight into some of the genetic mechanisms underpinning the trade-off between grain weight and number and their relationship to the source-to-sink pathway. These mechanisms include the plant size, the water soluble carbohydrate levels in plant tissue, the size and number of pericarp cells, the cytokinin and expansin levels in developing reproductive tissue, floral architecture and floral fertility.

Developing countries account to more than 80% of the world population. In the last two decades, the term 'developing countries' is used to group the countries that have not yet reached level of sophisticated industrialization like Western Europe and North America. In developing countries, acute postoperative pain management has special considerations. Barriers to implementing adequate acute postoperative pain management refer to health service organization, drug availability, inadequate education of pain management providers, as well as inadequate education of patients themselves and prejudices they may have regarding their postoperative pain and consequences if is inadequately treated. Health care workers in developing world are making effort to improve postoperative pain management. Serbia has been included in PAIN OUT European network initiative, with the aim to construct the bundle of simply applied measures and the effects of their implementation on postoperative pain treatment. So far, most of these measures refer to health service improvement, increasing availability of opioid analgetics, local anaesthetics and non-steroid anti-inflammatory drugs as well as education of the medical staff, patients and families.

The article deals with the system of EU own resources which is currently formed by traditional own resources, VAT-based resource and GNI-based resource. The system and its potential reform have been subject of scientific and political debates for many years. On 21 July 2020, the European Council agreed on the multiannual financial framework 2021-2027 and a specific recovery instrument Next Generation EU. The European Council conclusions also confirmed the need to reform the existing system and to introduce new own resources (e.g. resource based on nonrecycled plastic waste). Therefore, this article aims to elaborate on the EU own resources and their future post-2020. The methods of description, analysis, comparison, and synthesis were used for writing this contribution. First, the current system of EU budget revenue is analysed. Second, reform efforts since the establishment of the High Level Group on Own Resources are described. Third, the European Commission's original proposal from 2018 is compared to the European Council conclusions. [ABSTRACT FROM AUTHOR]

This study aims to provide an accurate and realistic prediction model for electricity demand using population, imports, exports, per capita Gross Domestic Product (GDP) and per capita Gross National Income (GNI) data for India. Four different models were used for different combinations of the above five input variables and the effect of input variables on the estimation of electricity demand has been demonstrated. In order to train the network 29 years data and to test the network 9 years data have been used. The future electricity demand for a period of 8 years from 2013 to 2020 has been predicted. The performance of the ANFIS technique is proved to be better than Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN).

Urban air pollution with benzene, toluene, ethyl benzene and xylenes (BTEX) is a common phenomenon in major cities where the pollution mainly originates from traffic as well as from residential heating. An attempt to rank cities according to their BTEX air pollution is not necessarily straight forward as we are faced with several individual pollutants simultaneously. A typical procedure is based on aggregation of data for the single compounds, a process that not only hides important information but is also subject to compensation effects. The present study applies a series of partial ordering tools to circumvent the aggregation. Based on partial ordering, most important indicators are disclosed, and an average ranking of the cities included in the study is derived. Since air pollution measurements are often subject to significant uncertainties, special attention has been given to the possible effect of uncertainty and/or data noise. Finally, the effect of introducing weight regimes is studied. In a concluding section the gross national income per person (GNI) is brought into play, demonstrating a positive correlation between BTEX air pollution and GNI. The results are discussed in terms of the ability/willingness to combat air pollution in the cities studied. The present study focuses on Almaty, the largest city in Kazakhstan and compares the data from Almaty to another 19 major cities around the world. It is found that the benzene for Almaty appears peculiar high. Overall Almaty appears ranked as the 8th most BTEX polluted city among the 20 cities included in the study. [ABSTRACT FROM AUTHOR]

The objectives of this article are to clarify definitions and to produce estimates of the eight aggregate measures of income and product (gross domestic product, gross domestic income, gross national product, gross national income, net domestic product, net domestic income, net national product and net national income) for Canada and the United States over the 1980-2008 period. The article also discusses the implications of the eight measures for productivity and living standards analysis. It concludes that GDP and NDP are the most appropriate measures of output for productivity analysis, while NNI is the most appropriate measure of income for the analysis of living standards because it captures the impact on real income of terms of trade changes, net income received from abroad, and the sustainability of the capital stock.

Middle East countries are clustered between the years 1980-2013 according to the their exports, imports, inflation, gross domestic product deflator (GDP def. annual %), gross domestic product (GDP), gross national income (GNI), gross saving, the net income of the foreign exchange rate, population growth (annual %) and the total population. We identify three different periods, respectively 1980:01-2003:12, 2003:01-2010:12, 2010:01-2013:12, examined the economic situation of countries. Including countries for clustering are Bahrain, Iraq, Iranian, Israel, Kuwait, Libyan, Lebanon, Egypt, Syria, Saudi Arabia, Turkey, Omman, Jordan, and Yemen. The result of analysis indicates that the countries vary for the first two periods are not so many than the third period. [ABSTRACT FROM AUTHOR]

Purpose: To estimate the annual loss of productivity from blindness and moderate to severe visual impairment (MSVI) using simple models (analogous to how a rapid assessment model relates to a comprehensive model) based on minimum wage (MW) and gross national income (GNI) per capita (US$, 2011). Methods: Cost of blindness (COB) was calculated for the age group ≥50 years in nine sample countries by assuming the loss of current MW and loss of GNI per capita. It was assumed that all individuals work until 65 years old and that half of visual impairment prevalent in the ≥50 years age group is prevalent in the 50–64 years age group. For cost of MSVI (COMSVI), individual wage and GNI loss of 30% was assumed. Results were compared with the values of the uncorrected refractive error (URE) model of productivity loss. Results: COB (MW method) ranged from $0.1 billion in Honduras to $2.5 billion in the United States, and COMSVI ranged from $0.1 billion in Honduras to $5.3 billion in the US. COB (GNI method) ranged from $0.1 million in Honduras to $7.8 billion in the US, and COMSVI ranged from $0.1 billion in Honduras to $16.5 billion in the US. Most GNI method values were near equivalent to those of the URE model. Conclusion: Although most people with blindness and MSVI live in developing countries, the highest productivity losses are in high income countries. The global economy could improve if eye care were made more accessible and more affordable to all. [ABSTRACT FROM AUTHOR]

This study aims to provide an accurate and realistic prediction model for electricity demand using population, imports, exports, per capita Gross Domestic Product (GDP) and per capita Gross National Income (GNI) data for India. Four different models were used for different combinations of the above five input variables and the effect of input variables on the estimation of electricity demand has been demonstrated. In order to train the network 29 years data and to test the network 9 years data have been used. The future electricity demand for a period of 8 years from 2013 to 2020 has been predicted. The performance of the ANFIS technique is proved to be better than Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN). [ABSTRACT FROM AUTHOR]

Background: To reach the Millennium Development Goals for health, influential international bodies advocate for more resources to be directed to the health sector, in particular medical treatment. Yet, health has many determinants beyond the health sector that are less evident than proximate predictors. Aim: To assess the relative importance of major socioeconomic determinants of population health, measured as infant mortality rate (IMR), at country level. Methods: National-level data from 152 countries based on World Development Indicators 2003 were used for multivariate linear regression analyses of five socioeconomic predictors of IMR: public spending on health, GNI/capita, poverty rate, income equality (Gini index), and young female illiteracy rate. Analyses were performed on a global level and stratified for low-, middle-, and high-income countries. Results: In order of importance, GNl/capita, young female illiteracy, and income equality predicted 92% of the variation in national IMR whereas public spending on health and poverty rate were non-significant determinants when adjusted for confounding. In low-income countries, female illiteracy was more important than GNI/capita. Income equality (Gini index) was an independent predictor of IMR in middle-income countries only. In high-income countries none of these predictors was significant. Conclusions: The relative importance of major health determinants varies between income levels, thus extrapolating health policies from high- to low-income countries is problematic. Since the size, per se, of public health spending does not independently predict health outcomes, functioning health systems are necessary to make health investments efficient. Potential health gains from improved female education and economic growth should be considered in low- and middle-income countries. [ABSTRACT FROM AUTHOR]

The research's fundamental investigation elaborates on interactions between tertiary educational factors and Namibia's sustainable economic development. Sequential mixed-research-method guides the investigation towards its results: A quantitative statistical data analysis enables the selection of interrelated educational and economic factors and monitors its development within Namibia's last three decades. Subsequent qualitative interviews accumulate respondents' subjective assessments that enable answering the fundamental interaction. Globally evident connections between a nation's tertiary education system and its economic development are partially confirmed within Namibia. The domestic government recognizes the importance of education that represents a driving force for its sustainable economic development. Along with governmental NDP's (National Development Program) and its long-term Vision 2030, Namibia is on the right track in transforming itself into a Knowledge-Based and Sustainable Economy. This transformation process increases human capital, growing GDP, and enhances domestic's living standards. Namibia's multiculturalism and its unequal resource distribution provoke difficulties for certain ethnicities accessing educational institutions. Namibia's tertiary education system's other challenges are missing infrastructures, lacking curricula' quality, and absent international expertise. The authors' findings suggest that, due to Namibia's late independence, there is a substantial need to catch up in creating a Namibian identity. Socioeconomic actions would enhance domestic's self-esteem and would enable the development of sustainable economic sectors. Raising the Namibian tertiary education system's educational quality and enhancing its access could lead to diversification of economic sectors, accelerating its internationalization process. Besides that, Namibia has to face numerous challenges, including corruption, unemployment, and multidimensional poverty, that interact with its tertiary education system. [ABSTRACT FROM AUTHOR]