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\"This innovative atlas deconstructs the contemporary image of the North-South divide and advocates the need for the international community to redraw the global map, as the contemporary world map with the 1980 Brandt Line drawing a stark divide between developed and underdeveloped countries no longer serves its purpose in the twenty-first century. Throughout the book a range of colourful maps and charts graphically demonstrate the ways in which the world has changed over the last two thousand years. The atlas firstly analyses the genesis, nature and validity of the Brandt Line, before going on to discuss its validity through centuries, especially in 1980 and after, and finally demonstrating the many definitions and philosophies of development that exist or may exist, which make it difficult to define a single notion of a Global North and South. The book concludes by proposing a new schemes of division between developed and developing countries. This book will serve as a perfect textbook for students studying global divisions within geography, politics, economics, international relations, and development departments, as well as being a useful guide for researchers, and for those working in NGOs and government institutions\"-- Provided by publisher.

The safe, highly effective measles vaccine has been recommended globally since 1974, yet in 2017 there were more than 17 million cases of measles and 83,400 deaths in children under 5 years old, and more than 99% of both occurred in low- and middle-income countries (LMICs) 1 , 2 , 3 – 4 . Globally comparable, annual, local estimates of routine first-dose measles-containing vaccine (MCV1) coverage are critical for understanding geographically precise immunity patterns, progress towards the targets of the Global Vaccine Action Plan (GVAP), and high-risk areas amid disruptions to vaccination programmes caused by coronavirus disease 2019 (COVID-19) 5 , 6 , 7 – 8 . Here we generated annual estimates of routine childhood MCV1 coverage at 5 × 5-km 2 pixel and second administrative levels from 2000 to 2019 in 101 LMICs, quantified geographical inequality and assessed vaccination status by geographical remoteness. After widespread MCV1 gains from 2000 to 2010, coverage regressed in more than half of the districts between 2010 and 2019, leaving many LMICs far from the GVAP goal of 80% coverage in all districts by 2019. MCV1 coverage was lower in rural than in urban locations, although a larger proportion of unvaccinated children overall lived in urban locations; strategies to provide essential vaccination services should address both geographical contexts. These results provide a tool for decision-makers to strengthen routine MCV1 immunization programmes and provide equitable disease protection for all children. Although progress in the coverage of routine measles vaccination in children in low- and middle-income countries was made during 2000–2019, many countries remain far from the goal of 80% coverage in all districts by 2019.

We investigate a recent methodology we have proposed to extract valuable information on the competitiveness of countries and complexity of products from trade data. Standard economic theories predict a high level of specialization of countries in specific industrial sectors. However, a direct analysis of the official databases of exported products by all countries shows that the actual situation is very different. Countries commonly considered as developed ones are extremely diversified, exporting a large variety of products from very simple to very complex. At the same time countries generally considered as less developed export only the products also exported by the majority of countries. This situation calls for the introduction of a non-monetary and non-income-based measure for country economy complexity which uncovers the hidden potential for development and growth. The statistical approach we present here consists of coupled non-linear maps relating the competitiveness/fitness of countries to the complexity of their products. The fixed point of this transformation defines a metrics for the fitness of countries and the complexity of products. We argue that the key point to properly extract the economic information is the non-linearity of the map which is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We present a detailed comparison of the results of this approach directly with those of the Method of Reflections by Hidalgo and Hausmann, showing the better performance of our method and a more solid economic, scientific and consistent foundation.

An effective and efficient planning of an urban growth and land use changes and its impact on the environment requires information about growth trends and patterns amongst other important information. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries however, there exist a very few studies showing the application of these models and their performances. In this study two models such as cellular automata (CA) and the SLEUTH models are applied in a geographical information system (GIS) to simulate and predict the urban growth and land use change for the City of Sana’a (Yemen) for the period 2004–2020. GIS based maps were generated for the urban growth pattern of the city which was further analyzed using geo-statistical techniques. During the models calibration process, a total of 35 years of time series dataset such as historical topographical maps, aerial photographs and satellite imageries was used to identify the parameters that influenced the urban growth. The validation result showed an overall accuracy of 99.6 %; with the producer’s accuracy of 83.3 % and the user’s accuracy 83.6 %. The SLEUTH model used the best fit growth rule parameters during the calibration to forecasting future urban growth pattern and generated various probability maps in which the individual grid cells are urbanized assuming unique “urban growth signatures”. The models generated future urban growth pattern and land use changes from the period 2004–2020. Both models proved effective in forecasting growth pattern that will be useful in planning and decision making. In comparison, the CA model growth pattern showed high density development, in which growth edges were filled and clusters were merged together to form a compact built-up area wherein less agricultural lands were included. On the contrary, the SLEUTH model growth pattern showed more urban sprawl and low-density development that included substantial areas of agricultural lands.

We developed the DAMA (Distribution of Alien Mammals) database, a comprehensive source reporting the global distribution of the 230 species of mammals that have established self-sustaining and free-ranging populations outside their native range due to direct or indirect human action. Every alien range is accompanied by information on its invasion stage, pathway, method of introduction, and date of introduction. We collected information from 827 different sources (scientific literature, books, risk assessments, reports, online biodiversity databases and websites), and used it to draw alien range maps for these species following the IUCN mapping framework. DAMA comprises 2,726 range polygons, covering 199 countries, 2,190 level 1 administrative areas, and 11 zoogeographic realms for the period 21500 BC–AD 2017. The most represented orders among introduced mammal species are Rodentia (n = 58, 25.22%), Cetartiodactyla (n = 49 species, 21.30%), Carnivora (n = 30 species, 13.04%), Diprotodontia (n = 28, 12.17%), and Primates (n = 26, 11.30%). Mammal species have been frequently introduced for hunting (n = 100), pet trade (n = 57), conservation (n = 51), and fauna improvement (n = 42). The majority of range polygons are placed on islands (n = 2,196, 80.56%), encompass populations that have moved beyond establishment and into the invasion stage (n = 1,655, 60.71%), and originated from 1500 AD to the present (n = 1,496, 54.88%). Despite inheriting literature biases towards more studied regions (e.g., developed countries), DAMA is the most up-to-date picture of alien mammal global distribution and can be used to investigate their invasion ecology across different biogeographical regions. There are no copyright or proprietary restrictions; IUCN range maps were modified into a derivative work according to the IUCN’s terms of service.

In order to transcend the challenge of accelerating the establishment of cadastres and to efficiently maintain them once established, innovative, and automated cadastral mapping techniques are needed. The focus of the research is on the use of high-resolution optical sensors on unmanned aerial vehicle (UAV) platforms. More specifically, this study investigates the potential of UAV-based cadastral mapping, where the ENVI feature extraction (FX) module has been used for data processing. The paper describes the workflow, which encompasses image pre-processing, automatic extraction of visible boundaries on the UAV imagery, and data post-processing. It shows that this approach should be applied when the UAV orthoimage is resampled to a larger ground sample distance (GSD). In addition, the findings show that it is important to filter the extracted boundary maps to improve the results. The results of the accuracy assessment showed that almost 80% of the extracted visible boundaries were correct. Based on the automatic extraction method, the proposed workflow has the potential to accelerate and facilitate the creation of cadastral maps, especially for developing countries. In developed countries, the extracted visible boundaries might be used for the revision of existing cadastral maps. However, in both cases, the extracted visible boundaries must be validated by landowners and other beneficiaries.

This volume presents work from an international group of writers who explore conceptualizations of what defined \"East\" and \"West\" in Eastern Europe, imperial Russia, and the Soviet Union. The contributors analyze the effects of transnational interactions on ideology, politics, and cultural production. They reveal that the roots of an East/West cultural divide were present many years prior to the rise of socialism and the cold war. The chapters offer insights into the complex stages of adoption and rejection of Western ideals in areas such as architecture, travel writings, film, music, health care, consumer products, political propaganda, and human rights. They describe a process of mental mapping whereby individuals \"captured and possessed\" Western identity through cultural encounters and developed their own interpretations from these experiences. Despite these imaginaries, political and intellectual elites devised responses of resistance, defiance, and counterattack to defy Western impositions. Socialists believed that their cultural forms and collectivist strategies offered morally and materially better lives for the masses and the true path to a modern society. Their sentiments toward the West, however, fluctuated between superiority and inferiority. But in material terms, Western products, industry, and technology, became the ever-present yardstick by which progress was measured. The contributors conclude that the commodification of the necessities of modern life and the rise of consumerism in the twentieth century made it impossible for communist states to meet the demands of their citizens. The West eventually won the battle of supply and demand, and thus the battle for cultural influence.

Aim: To conduct a bibliometric analysis of the nurses’ job satisfaction from 2004 to 2023. Design: The bibliometric and visual analysis was performed in January 2024. Methods: Bibliometric approaches were applied to analyse 11,993 articles, utilising R and VOSviewer software. Results: Articles published by 24,155 authors from 1735 distinct sources between 2004 and 2023 were retrieved from the Web of Science and incorporated into the research’s purview. The most productive nation and institution correspondingly were the United States and the University of Toronto. The leading scholars in this sphere were Spence Laschinger, Heather K, Labrague, Leodoro J, and Rodwell, John according to Price’s Law, author co‐citation and bibliographic‐coupling network analysis. 14,152 keywords about nurses’ job satisfaction study were discovered in this research. The most common keywords encompassed “job satisfaction,” “nurses,” “burnout,” “turnover,” and “intention” It was also observed that while trend topics like “work engagement” “COVID‐19” and “grit” have gained popularity recently, the most commonly employed trend topics in earlier years included “empirical research report” “longitudinal study,” and “organizational characteristics.” Conclusion: Research on nurses’ job satisfaction remains relatively limited and requires more attention, especially in developing countries. Developed countries, especially the United Kingdom and the United States, are the main contributors to nurse job satisfaction research. In the early days, nurse job satisfaction research mainly focused on the current status and influencing factors of nurse job satisfaction in different medical organizations, nurse groups or departments, while more researchers have recently paid more attention to research on specific issues emerging in this field, such as the impact of COVID‐19 on nurse job satisfaction and turnover. In addition, scholars in the field of nurse job satisfaction focus on finding the real determinants of job satisfaction of adult practicing nurses, such as interpersonal value consistency, human resource management, and the impact of job satisfaction of adult nurses in different medical environments. Topics such as “perseverance,” “COVID‐19” and “work engagement” may be potential focuses for future research. Furthermore, transnational research should be given greater emphasis to investigate whether the major factors and effective interferences of nurses’ job satisfaction differ between cultures and more multicenter as well as big sample studies should be conducted to efficiently improve nurses’ job satisfaction. Impact: This study used bibliometric analysis to examine the most contributing nations, institutions, authors, trend topics, and research focus. Data on the present state of nurses’ job satisfaction research, including its knowledge maps, study emphasis, and thematic trends are few. The findings of this research can lay a strong basis for future research and offer direction. No Patient or Public Contribution: There were no humankind subjects in the bibliometric analysis of published papers.

Spatial–temporal analysis of land-use/land-cover (LULC) change as well as the monitoring and modeling of urban expansion are essential for the planning and management of urban environments. Such environments reflect the economic conditions and quality of life of the individual country. Urbanization is generally influenced by national laws, plans and policies and by power, politics and poor governance in many less-developed countries. Remote sensing tools play a vital role in monitoring LULC change and measuring the rate of urbanization at both the local and global levels. The current study evaluated the LULC changes and urban expansion of Jhapa district of Nepal. The spatial–temporal dynamics of LULC were identified using six time-series atmospherically-corrected surface reflectance Landsat images from 1989 to 2016. A hybrid cellular automata Markov chain (CA–Markov) model was used to simulate future urbanization by 2026 and 2036. The analysis shows that the urban area has increased markedly and is expected to continue to grow rapidly in the future, whereas the area for agriculture has decreased. Meanwhile, forest and shrub areas have remained almost constant. Seasonal rainfall and flooding routinely cause predictable transformation of sand, water bodies and cultivated land from one type to another. The results suggest that the use of Landsat time-series archive images and the CA–Markov model are the best options for long-term spatiotemporal analysis and achieving an acceptable level of prediction accuracy. Furthermore, understanding the relationship between the spatiotemporal dynamics of urbanization and LULC change and simulating future landscape change is essential, as they are closely interlinked. These scientific findings of past, present and future land-cover scenarios of the study area will assist planners/decision-makers to formulate sustainable urban development and environmental protection plans and will remain a scientific asset for future generations.

Purpose To analyze the AI research in the field of nursing, to explore the current situation, hot topics, and prospects of AI research in the field of nursing, and to provide a reference for researchers to carry out related studies. Methods We used the VOSviewer 1.6.17, SciMAT, and CiteSpace 5.8.R3 to generate visual cooperation network maps for the country, organizations, authors, citations, and keywords and perform burst detection, theme evolution, and so forth. Findings A total of 9318 articles were obtained from the Web of Science Core Collection database. Four hundred and thirty‐one AI research related to the field of nursing was published by 855 institutions from 54 countries. CIN‐Computers Informatics Nursing was the top productive journal. The United States was the dominant country. The transnational cooperation between authors from developed countries was closer than that between authors from developing countries. The main hot topics included nurse rostering, nursing diagnosis, nursing decision support, disease risk factor prediction, nursing big data management, expert system, support vector machine, decision tree, deep learning, natural language processing, and nursing education. Machine learning represented one of the cutting‐edge and most applicable branches of artificial intelligence in the field of nursing, and deep learning was the hottest technology among many machine learning methods in recent years. One of the most cited papers was published by Burke in 2004 and cited 500 times, which critically evaluated AI methods to deal with nurse scheduling problems. Conclusions Although AI has been paid more and more attention to the field of nursing, there is still a lack of high‐yielding authors who have been engaged in this field for a long time. Most of the high contribution authors and institutions came from developed countries; therefore, more transnational and multi‐disciplinary cooperation is needed to promote the development of AI in the nursing field. This bibliometric analysis not only provided a comprehensive overview to help researchers to understand the important articles, journals, potential collaborators, and institutions in this field but also analyzed the history, hot spots, and future trends of the research topic to provide inspiration for researchers to choose research directions.