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Development interventions increasingly include women's empowerment and gender equality among their objectives, but evaluating their impact has been stymied by the lack of measures that are comparable across interventions. This paper synthesizes the findings of 11 mixed-methods impact evaluations of agricultural development projects from South Asia and sub-Saharan Africa that were part of the Gender, Agriculture, and Assets Project, Phase 2 (GAAP2). As part of GAAP2, qualitative and quantitative data were used to develop and validate the multidimensional project-level Women's Empowerment in Agriculture Index (pro-WEAI), which was used to assess the impact of GAAP2 projects on women's empowerment. This paper assesses the extent to which: (1) a two- to three-year agricultural development project can contribute to women's empowerment; and (2) a suite of methods comprising a standardized quantitative measure of women's empowerment and a set of qualitative protocols, can evaluate such impacts. Our synthesis finds that the most common positive significant impacts were on the instrumental and collective agency indicators that comprise pro-WEAI, owing to the group-based approaches used. We found few projects significantly improved intrinsic agency, even among those with explicitly stated objectives to change gender norms. Unsurprisingly, we find mixed, and mostly null impacts on aggregate pro-WEAI, with positive impacts more likely in the South Asian, rather than African, cases. Our results highlight the need for projects to design their strategies specifically for empowerment, rather than assume that projects aiming to reach and benefit women automatically empower them. Our study also shows the value of a suite of methods containing a common metric to compare empowerment impacts and qualitative protocols to understand and contextualize these impacts. • We use pro-WEAI to assess 11 projects' impacts on women's agency and empowerment. • Pro-WEAI comprises quantitative and qualitative protocols co-developed by projects. • Significant positive impacts observed on instrumental and collective agency. • More limited or null impacts detected on intrinsic agency. • Intentionality is important in projects' strategies to empower women. [ABSTRACT FROM AUTHOR]

This paper attempts to empirically analyze the compatibility of national trade liberalization policies with regards to promoting widespread use of renewable energy resources across 71 low, lower-middle and upper-middle income countries from South Asia, East Asia, Pacific, Central Asia, Latin America, Caribbean islands and Sub-Saharan Africa. Annual time series data from 2000 to 2017 is employed to perform panel data cointegration and regression analyses. The results from the cointegration analyses show long-run associations between trade liberalization policies and the renewable energy consumption indicators. The Instrumental Variable Two-Stage Least Squares panel data estimator is employed to control for the endogeneity in the dataset. The overall results broadly point towards the effectiveness of greater trade openness in facilitating renewable energy transition only in the low-income economies while prolonging the transition periods in the lower and upper-middle income countries. The marginal impact of a rise in the trade openness index is estimated to enhance the renewable energy share in total energy consumption within low-income countries by 0.24% as opposed to lowering this share by 0.19% within lower-middle income economies. However, trade liberalization is found to attribute to greater efficiency of renewable energy use across all the three income groups. Thus, these findings have critically important policy implications for the respective governments. • Trade liberalization exerts heterogeneous impacts on renewable energy transition. • Trade openness increases renewable energy consumption only across the LIC. • Liberal trade policies enhance renewable energy shares only within LIC and UMIC. • Efficiency of renewable energy-use is amplified via trade liberalization. • Higher trade openness accounts for greater access to clean cooking fuels in LMIC. [ABSTRACT FROM AUTHOR]

This paper critically examines the literature on the grid-offgrid debate and discusses the role of and the relationship between different electricity access options through a synthesis and critical reflection. This paper finds that models using greater resolution and capturing low voltage distribution infrastructure appear to recommend decentralised electricity solutions, whereas central grid extension emerges as the preferred outcome of more aggregated analysis, concentrated population clusters and for higher demand scenarios. However, model results are seriously influenced by assumptions, data limitations, technology choice options, and model flexibility. Exclusion of cost of generation for grid systems, lack of village level information, inherent bias towards scale and type of technology, and absence of social equity considerations in the analysis remain major weaknesses of the existing models. Universal electrification requires a strong leadership and an enabling environment. An appropriate organizational set-up, a robust regulatory framework with reporting and evaluation oversight and a more inclusive approach to promote alternative options are vital ingredients. Power sector decarbonization pathways may affect electrification choices but our understanding is limited or lacking. Further work is required to develop a programmatic approach to delivery and more affordable and fairer outcome for all. • The paper presents the up-to-date review of the debate on grid and off-grid electrification. • We find a strong leadership and an enabling environment is essential for universal electrification by the year 2030. • Appropriate organizational set-up, robust regulatory framework and shift from grid-centric focus to a more inclusive approach to promote alternative options is equally important. • Important to develop a programmatic approach to delivery and more affordable and fairer outcome. [ABSTRACT FROM AUTHOR]

• Deep learning-based pneumonia detection in x-ray images is done in this work. • Different models of deep learning and transfer learning are analysed in this work for the image classification application. • An extensive analysis is carried out in this work with several experimental results. A large number of children die due to pneumonia every year worldwide. An estimated 1.2 million episodes of pneumonia were reported in children up to 5 years of age, of which 880,000 died in 2016. Hence, pneumonia is a major cause of death amongst children, with high prevalence rate in South Asia and Sub-Saharan Africa. Even in a developed country like the United States, pneumonia is among the top 10 causes of deaths. Early detection and treatment of pneumonia can reduce mortality rates among children significantly in countries having a high prevalence. Hence, this paper presents Convolutional Neural Network models to detect pneumonia using x-ray images. Several Convolutional Neural Networks were trained to classify x-ray images into two classes viz., pneumonia and non-pneumonia, by changing various parameters, hyperparameters and number of convolutional layers. Six models have been mentioned in the paper. First and second models consist of two and three convolutional layers, respectively. The other four models are pre-trained models, which are VGG16, VGG19, ResNet50, and Inception-v3. The first and second models achieve a validation accuracy of 85.26% and 92.31% respectively. The accuracy of VGG16, VGG19, ResNet50 and Inception-v3 are 87.28%, 88.46%, 77.56% and 70.99% respectively. [ABSTRACT FROM AUTHOR]

Crop residues (CR) have become a limited resource in mixed crop-livestock farms. As a result of the increasing demand and low availability of alternative resources, CR became an essential resource for household activities, especially for livestock keeping; a major livelihood element of smallholder farmers in the developing world. Farmers’ decisions on CR use are determined by farmers’ preferences, total crop production, availability of alternative resources and demand for CR. Interaction of these determinants can result in pressures and trade-offs of CR use. Determinants, pressures and trade-offs are shaped by the specific socio-economic and agro-ecological context of these mixed farms. The objective of this paper is to provide a comparative analysis of the determinants of CR use and to examine some options to cope with pressures and trade-offs in 12 study sites across Sub-Saharan Africa and South Asia. Drawing on socio-economic data at household and village level, we describe how cereal intensification and livestock feed demand influence use, pressures and trade-offs of CR use across study sites, specifically cereal residue. Our results show that in low cereal production and livestock feed demand sites, despite a low demand for CR and availability of alternative biomass, pressures and trade-offs of CR use are common particularly in the dry season. In sites with moderate cereal production, and low–moderate and moderate livestock feed demand, alternative biomass resources are scarce and most residues are fed to livestock or used to cover household needs. Subsequently, pressures and potential trade-offs are stronger. In sites with low cereal production and high livestock feed demand, pressures and trade-offs depend on the availability of better feed resources. Finally, sites with high cereal production and high livestock feed demand have been able to fulfil most of the demand for CR, limiting pressures and trade-offs. These patterns show that agricultural intensification, better management of communal resources and off-farm activities are plausible development pathways to overcome pressures and trade-offs of CR use. Although technologies can largely improve these trends, research and development should revisit past initiatives so as to develop innovative approaches to tackle the well-known problem of low agricultural production in many smallholder mixed systems, creating more sustainable futures. [ABSTRACT FROM AUTHOR]

Visas are an important means for countries to regulate the potential access of non-nationals to their territory. Past datasets and quantitative research on visas have focused on visa waivers, ignoring the fact that visas, where demanded, can vary greatly by cost. This paper presents a novel dataset based on a manual collection of visa costs for travel between a global set of country pairs in seven different categories (tourist, work, student, family reunification, business, transit, and other). Our analyses reveal a strong global visa cost divide that exposes the injustice in the right to travel for people located in different areas of the world. Whereas Europeans usually hardly have to work at all for travel permits, visa costs often amount to several weeks of mean income in Sub-Saharan Africa and South Asia. The result is a fundamentally paradoxical situation: The richer a country, the less its citizens pay for visas to go abroad (both in absolute terms and relative to their income). Poisson pseudo-maximum likelihood regression analyses reveal that a variety of factors influence the costs of visas between countries: reciprocal treatment, processing costs, historical-cultural ties, geographic proximity and regional, religious, economic, and political discrimination. This confirms the important role of visa costs as a tool for states to control population movements and simultaneously position themselves in international relations. [ABSTRACT FROM AUTHOR]