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The global textile and apparel sector is critically important as an early phase in industrialization for many developing countries and as a provider of employment opportunities to thousands of low-income workers, many of them women. The goal of this book is to explore how the lifting of the Multi-fibre Arrangement/ Agreement on Textiles and Clothing (MFA/ATC) quotas has affected nine countries Bangladesh, Cambodia, Honduras, India, Mexico, Morocco, Pakistan, Sri Lanka, and Vietnam with the broader aim of better understanding the links between globalization and poverty in the developing world. Analyzing how employment, wage premiums, and the structure of the apparel industry have changed after the MFA/ATC can generate important lessons for policy makers for economic development and poverty reduction. This book uses in-depth country case studies as the broad methodological approach. In-depth country studies are important because countries are idiosyncratic: differences in regulatory context, history, location, trade relationships, and policies shape both the apparel sector and how the apparel sector changed after the end of the MFA. In-depth country studies place broader empirical work in context and strengthen the conclusions. The countries in this book were chosen because they represent the diversity of global apparel production, including differences across regions, income levels, trade relationships, and policies. The countries occupy different places in the global value chain that now characterizes apparel production. Not surprisingly, the countries studied in this book represent the diversity of post-MFA experiences. This book highlights four key findings: The first is that employment and export patterns after the MFA/ATC did not necessarily match predictions. This book shows that only about a third of the variation in cross-country changes in exports is explained by wage differences. While wage differences explain some of the production shifts, domestic policies targeting the apparel sector, ownership type, and functional upgrading of the industry also played an important role. Second, changes in exports are usually, but not always, good indicators of what happens to wages and employment. While rising apparel exports correlated with rising wages and employment in the large Asian countries, rising exports coincided with falling employment in Sri Lanka. Third, this book identifies the specific ways that changes in the global apparel market affected worker earnings, thus helping to explain impacts on poverty. Fourth, in terms of policies, the countries that had larger increases in apparel exports were those that promoted apparel sector upgrading; those that did not promote upgrading had smaller increases or even falling exports.

The objective of the Nepal Investment Climate Assessment (ICA) is to evaluate the investment climate in Nepal in all its dimensions and promote policies to strengthen the private sector. The investment climate is made up of many dimensions that shape the opportunities for investments, employment creation, and growth of private firms. Such dimensions include factor markets, product markets, infrastructure services, and the macroeconomic, legal, regulatory, and institutional framework. The report's key finding is that while there are some niche sectors growing and expanding employment in Nepal (including tourism and certain educational and other services), there are many constraints to the investment climate in Nepal that are hindering the development and growth of the private sector. In particular, political instability, poor infrastructure, poor labor relations, poor access to finance, and declining exports plague Nepal's private sector. To overcome many of these issues and move forward, many reforms are needed. Given the extent of the challenge, effective public-private dialogue is required so that the government and the private sector can work in partnership to address these constraints. The pervasiveness and impact of political instability in Nepal makes the investment climate in the country comparable more to Afghanistan than other countries in the region or the comparator countries used in the analysis. While this comparison is unflattering, it is true. Political instability has stifled growth and limited Nepal's ability to exploit its hydropower and tourism potential. Interestingly, many firms do not perceive access to land and finance as major obstacles. This could be a reflection of lack of dynamism: Nepalese firms are simply not planning to invest, expand, and grow in their unstable and unpredictable environment. The peace dividend is not difficult to measure. As the surveys show, ending civil unrest alone would give back to enterprises 44 working days a year. The effects on economic activity, investment, growth, and job creation could be potentially huge.

Studies on the spatiotemporal relationship between historical climate change and the patterns of population and war are rare. In this research, statistical methods (such as correlation test and Granger causality analysis) and visualization technique are applied to demonstrate how temperature, in terms of long-term trend and cyclic mode, fundamentally affects the temporal-spatial variations of population center and war center during imperial China (5–1911 CE). Results show that (1) the consistent southward migration of population center and war center overall accords with the macro-trend of temperature cooling over the last two millennia. (2) The extent of the outward expansion of the Chinese Empire is measured by the population center–war center distance that lengthens during warm periods but shortens in cold phases, which correspond to the north/west/northwestward advancement and south/east/eastward retreatment of war center, respectively, while population center moves within a small range. (3) The shift of population latitude precedes that of war latitude, indicating the change from ecological-demographic to social-political sphere in space. We suggest that similar to population center, the temperature-influenced ancient Hu Line, which symbolizes the disparity of population density in different regions of China, may shift by several hundred kilometers; latitudinal rather than longitudinal variations of population center and war center are more robust in history. We also find that precipitation controls war center and population center on the multicentennial scale, but not the scale focused upon in this study. These findings provide new insights and theoretical implications into the in-depth understanding of the nature–human nexus.

Although average incomes in China have risen dramatically since the 1980s, concerns are increasing that the rural elderly have not benefited from growth to the same extent as younger people and the urban elderly. Concerns about welfare of the rural elderly combine spatial and demographic issues. Large gaps exist between conditions in coastal and interior regions and between conditions in urban and rural areas of the country. In addition to differences in income by geography, considerable differences exist across demographic groups in the level of coverage by safety nets, in the benefits received through the social welfare system, and in the risks of falling into poverty. This book aims to do two things: first, it provides detailed empirical analysis of the welfare and living conditions of the rural elderly since the early 1990s in the context of large-scale rural-to-urban migration, and second, it explores the evolution of the rural pension system in China over the past two decades and raises a number of issues on its current implementation and future directions. Although the two sections of the book are distinct in analytical terms, they are closely linked in policy terms: the first section demonstrates in several ways a rationale for greater public intervention in the welfare of the rural elderly, and the second documents the response of policy to date and options to consider for deepening the coverage and effects of the rural pension system over the longer term.

Although dengue is typically considered an urban disease, rural communities are also at high risk. To clarify dynamics of dengue virus (DENV) transmission in settings with characteristics generally considered rural (e.g., lower population density, remoteness), we conducted a phylogenetic analysis in 6 communities in northwestern Ecuador. DENV RNA was detected by PCR in 121/488 serum samples collected from febrile case-patients during 2019-2021. Phylogenetic analysis of 27 samples from Ecuador and other countries in South America confirmed that DENV-1 circulated during May 2019-March 2020 and DENV-2 circulated during December 2020-July 2021. Combining locality and isolation dates, we found strong evidence that DENV entered Ecuador through the northern province of Esmeraldas. Phylogenetic patterns suggest that, within this province, communities with larger populations and commercial centers were more often the source of DENV but that smaller, remote communities also play a role in regional transmission dynamics.

Population registration has been proposed for normalizing a large group of images into a common space, which is important in many clinical and research studies, such as brain development, aging, and atlas construction. Different from pairwise registration problem that aligns the target image to the reference directly, determining the reference or the hidden common space with the least bias is important in population registration. In order to decrease this bias, a lot of work takes the arithmetic mean image as the reference. However, the arithmetic mean image is usually too smooth to guide the population registration. This work presents an efficient symmetric population registration strategy for brain template construction, which defines the symmetric population center guiding population registration. This is important because the population registration problem can be translated into a series of pairwise registration problem which is easier to optimize and implement. Another prominent merit of proposed population registration algorithm is reference-free, which eliminates the reference dependency–related bias in population registration. Based on this symmetric population registration, the brain template is constructed by approximating both the population’s intensity and gradient information. In addition, we also present a new measurement named with average bias for evaluating the unbiasedness of brain template. Experiments were first carried out on four synthetic images created with controllable transforms, which aim at comparing the difference between conventional method and proposed method. Further experiment is designed for reference-free validation. Finally, in real inter-subject brain data, twenty MRI T1 volumes with size 256 × 256 × 176 are used to construct a symmetric brain template with proposed population registration method. The constructed brain template has a small bias and clear brain details comparing with DARTEL.

What this research may achieve points towards the need to progressively improve the reasonableness in establishing Social Welfare Agencies (SWAs). The service capacity of SWAs is far below the population of the level III extremely disabled. This is a serious problem. This evaluation can assist social welfare and public health departments to determine what locations to approve for establishing SWAs in the short term and plan for new SWAs more precisely, as well as rein in budgetary priorities. As an illustration, in considering the distance between SWAs and the extremely disabled, the service quality of SWAs and fairness in the planning have to be taken into account. Introducing a Service Quantity Needed-Index for SWAs (SNIS) into the current measure of approving and planning new SWAs shall assist the departments in distributing social welfare resources to areas most in need of help. In addition, using the modified data to recalculate SNIS can examine needs regularly. Employing basic statistical areas for short-term applications in Taipei City SWA projects, considering the distance between SWAs and the extremely disabled, the agencies’ service quality and fairness in the planning of SWAs need to receive more attention. Previous research mostly employed straight-line distances rather than road distances. To a certain extent, this overlooked the actual capacity of roads as well as led to some degree of discrepancies in evaluations. This essay focuses on calculating SNIS, mainly towards guiding the establishment of facilities and concretely proposing how to optimize their locations. Future research can add in needs at that time in accordance with current evaluation results to propose plans to optimize the locations, or maybe integrate weights of disability to adjust multiple requirements of SWAs.

For well over a century, migration researchers have recognized the lack of adequate distance measures to be a key obstacle for advancing understanding of internal migration. The problem arises from the convention of spatially defining migration as the crossing of administrative borders. Because administrative regions vary in size, shape, and settlement patterns, it is difficult to tell how far movers go, raising doubts about the generalizability of research in the field. This article shows that satellite data on nighttime lights can be used to infer accurate measures of migration distance. We first use the intensity of nighttime lights to locate mean population centers that closely correspond to mean population centers calculated from actual population data. Until now, locating mean population centers accurately has been problematic, as it has required highly disaggregated population data, which are lacking in many countries. The nighttime lights data, which are freely available on a yearly basis, solve this challenge. We then show that this information can be used to accurately estimate migration distances.

Hazardous materials (HAZMAT) are important for daily production in cities, which usually have a high population. To avoid the threat to public safety and security, the routes for HAZMAT transportation should be planned legitimately by mitigating the maximum risk to population centers. For the objective of min-max local risk in urban areas, this study has newly proposed an optimization model where the service of a link for HAZMAT transportation was taken as the key decision variable. Correspondingly, the symmetric problem of min-max optimization takes significant meanings. Moreover, in consideration of the work load of solving the model under a lot of decision variables, a heuristic algorithm was developed to obtain an optimal solution. Thereafter, a case study was made to test the proposed model and algorithm, and the results were compared with those generated by deterministic solving approaches. In addition, this research is able to be an effective reference for authorities on the management of HAZMAT transportation in urban areas.

Research to eliminate health disparities in the United States is best approached from the perspective of population health. The objectives of this paper are to: a) describe how ongoing research at the eight national Centers for Population Health and Health Disparities (CPHHD) is using a population health perspective and a community-based approach to advance the field of health disparities research; and b) to discuss potential implications of such research for health policies that target some of the determinants of population health.