5,512 research outputs found

    A Multi-level Analysis on Implementation of Low-Cost IVF in Sub-Saharan Africa: A Case Study of Uganda.

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    Introduction: Globally, infertility is a major reproductive disease that affects an estimated 186 million people worldwide. In Sub-Saharan Africa, the burden of infertility is considerably high, affecting one in every four couples of reproductive age. Furthermore, infertility in this context has severe psychosocial, emotional, economic and health consequences. Absence of affordable fertility services in Sub-Saharan Africa has been justified by overpopulation and limited resources, resulting in inequitable access to infertility treatment compared to developed countries. Therefore, low-cost IVF (LCIVF) initiatives have been developed to simplify IVF-related treatment, reduce costs, and improve access to treatment for individuals in low-resource contexts. However, there is a gap between the development of LCIVF initiatives and their implementation in Sub-Saharan Africa. Uganda is the first country in East and Central Africa to undergo implementation of LCIVF initiatives within its public health system at Mulago Women’s Hospital. Methods: This was an exploratory, qualitative, single, case study conducted at Mulago Women’s Hospital in Kampala, Uganda. The objective of this study was to explore how LCIVF initiatives have been implemented within the public health system of Uganda at the macro-, meso- and micro-level. Primary qualitative data was collected using semi-structured interviews, hospital observations informal conversations, and document review. Using purposive and snowball sampling, a total of twenty-three key informants were interviewed including government officials, clinicians (doctors, nurses, technicians), hospital management, implementers, patient advocacy representatives, private sector practitioners, international organizational representatives, educational institution, and professional medical associations. Sources of secondary data included government and non-government reports, hospital records, organizational briefs, and press outputs. Using a multi-level data analysis approach, this study undertook a hybrid inductive/deductive thematic analysis, with the deductive analysis guided by the Consolidated Framework for Implementation Research (CFIR). Findings: Factors facilitating implementation included international recognition of infertility as a reproductive disease, strong political advocacy and oversight, patient needs & advocacy, government funding, inter-organizational collaboration, tension to change, competition in the private sector, intervention adaptability & trialability, relative priority, motivation &advocacy of fertility providers and specialist training. While barriers included scarcity of embryologists, intervention complexity, insufficient knowledge, evidence strength & quality of intervention, inadequate leadership engagement & hospital autonomy, poor public knowledge, limited engagement with traditional, cultural, and religious leaders, lack of salary incentives and concerns of revenue loss associated with low-cost options. Research contributions: This study contributes to knowledge of factors salient to implementation of LCIVF initiatives in a Sub-Saharan context. Effective implementation of these initiatives requires (1) sustained political support and favourable policy & legislation, (2) public sensitization and engagement of traditional, cultural, and religious leaders (3) strengthening local innovation and capacity building of fertility health workers, in particular embryologists (4) sustained implementor leadership engagement and inter-organizational collaboration and (5) proven clinical evidence and utilization of LCIVF initiatives in innovator countries. It also adds to the literature on the applicability of the CFIR framework in explaining factors that influence successful implementation in developing countries and offer opportunities for comparisons across studies

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Machine learning and mixed reality for smart aviation: applications and challenges

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    The aviation industry is a dynamic and ever-evolving sector. As technology advances and becomes more sophisticated, the aviation industry must keep up with the changing trends. While some airlines have made investments in machine learning and mixed reality technologies, the vast majority of regional airlines continue to rely on inefficient strategies and lack digital applications. This paper investigates the state-of-the-art applications that integrate machine learning and mixed reality into the aviation industry. Smart aerospace engineering design, manufacturing, testing, and services are being explored to increase operator productivity. Autonomous systems, self-service systems, and data visualization systems are being researched to enhance passenger experience. This paper investigate safety, environmental, technological, cost, security, capacity, and regulatory challenges of smart aviation, as well as potential solutions to ensure future quality, reliability, and efficiency

    Financial and Economic Review 22.

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    Resilience and food security in a food systems context

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    This open access book compiles a series of chapters written by internationally recognized experts known for their in-depth but critical views on questions of resilience and food security. The book assesses rigorously and critically the contribution of the concept of resilience in advancing our understanding and ability to design and implement development interventions in relation to food security and humanitarian crises. For this, the book departs from the narrow beaten tracks of agriculture and trade, which have influenced the mainstream debate on food security for nearly 60 years, and adopts instead a wider, more holistic perspective, framed around food systems. The foundation for this new approach is the recognition that in the current post-globalization era, the food and nutritional security of the world’s population no longer depends just on the performance of agriculture and policies on trade, but rather on the capacity of the entire (food) system to produce, process, transport and distribute safe, affordable and nutritious food for all, in ways that remain environmentally sustainable. In that context, adopting a food system perspective provides a more appropriate frame as it incites to broaden the conventional thinking and to acknowledge the systemic nature of the different processes and actors involved. This book is written for a large audience, from academics to policymakers, students to practitioners

    Income support and social protection in Latin America and the Caribbean: debates on policy options

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    In the area of social protection systems, the Latin American and Caribbean region is characterized by structural gaps in coverage and sufficiency, owed especially to widespread labour informality. To offset these deficits, the region has accumulated vast experience in social protection through the introduction of cash and in-kind transfers as non-contributory social protection. In addition, in light of the profound impacts of the coronavirus disease (COVID-19) pandemic and an unfavourable economic and labour context, the discussion on mechanisms for ensuring adequate income levels in the region has become central. This paper seeks to address the income protection dimension of social protection systems, exploring various instruments and policy options discussed in recent years from a comparative and regional perspective, focusing on their non-contributory component. By exploring their possible costs, it also analyses the feasibility of advancing progressively in various income protection modalities.Introduction / Raquel Santos Garcia, Claudia Robles .-- I. Basic income: conceptual elements and discussion / Jurgen De Wispelaere, Consuelo FarĂ­as .-- II. Guaranteed minimum income, universal transfers for children and older adults, and other income protection options / Consuelo FarĂ­as, Raquel Santos Garcia, Jurgen De Wispelaere .-- III. Moving towards income protection in Latin America and the Caribbean / Consuelo FarĂ­as, Raquel Santos Garcia .-- IV. Estimating the cost of cash transfers associated with the implementation of options to protect income levels in Latin America / Ernesto EspĂ­ndola .-- V. Final recommendations / Claudia Robles, Raquel Santos Garcia

    Addressing the burden of snakebite: analysing policy prioritisation, evaluating health systems, and fostering research on treatments

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    Introduction The World Health Organization (WHO) estimates 5.4 million snakebites annually. In 2019, WHO released a strategy to halve the burden of snakebite by 2030. This doctoral research aimed to generate practice and policy relevant evidence at three levels: globally, by understanding the prioritisation process in the WHO; nationally, in India, by evaluating the primary health care (PHC) system; and regionally, in South Asia, by fostering research on treatments. Methods To understand the global prioritisation of snakebite, I conducted a policy analysis, using interviews and documents as data sources. To evaluate health systems in India, I analysed secondary data for the first nationwide assessment of structural capacity and continuum of snakebite care. To understand health systems resilience, I used quantitative (analysis of facility-level data) and qualitative (interviews) approaches to understand the effects of COVID-19 and conducted an evidence synthesis on the effect of climate change. Through an overview of systematic reviews of treatments, I identified the need for a core outcome set (COS) on snakebite. I developed a COS for snakebite research in South Asia, by conducting a systematic review of outcomes and a Delphi survey. Results The policy analysis identified factors which enabled prioritisation of snakebite, and identified unaddressed challenges of sustaining legitimacy, and acceptance within the neglected tropical disease community. I identified structural limitations of the PHC system and gaps in referral pathways, in India. Relevant to the context, I report, how COVID-19 accentuated existing barriers, and identified that the choice of provider is a complex process with multiple factors interplaying. Evidence synthesis indicates the need to prepare health systems for possible geographic shifts in snakebite burden due to climate change. The overview of systematic reviews identified gaps in the evidence ecosystem. By developing a COS for future intervention research on snakebite treatments, I addressed the gap of non-standardised measurement of outcomes. Conclusion The findings of the thesis, provides contextually relevant evidence aligned with pillars of the WHO strategy, to practice and policy at global, national, sub-national, and program level. The policy analysis and COS work provides broader methodological insights, beyond snakebite

    Strategies to Reduce the Impact of Disruptions in Manufacturing Transportation Supply Chains

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    Abstract Supply chain managers in the manufacturing transportation industry grapple with reducing the impact of disruptions in transportation supply chains since 50% of U.S. companies have experienced between six to 20 disruptions per year. Ineffective transportation disruption strategies negatively impact the performance and profitability of manufacturing organizations resulting in losses and business failure. Grounded in Goldratt’s philosophy and thinking process of the Theory of Constraints (TOC), the purpose of this qualitative multiple case study was to explore successful strategies supply chain managers in the manufacturing transportation industry used to reduce the impact of disruptions in transportation supply chains. The participants were three supply chain managers from three different manufacturing industries doing business in the Commonwealth of Massachusetts, who successfully implemented strategies that reduced the impact of disruptions in manufacturing transportation in their organizations. Data were collected through face-to-face semistructured interviews, archival records, and social media websites. Through thematic analysis, three themes emerged: (a) technology and innovative solutions, (b) supply chain collaborative efforts, and (d) logistics and transportation innovative strategies. A key recommendation is for supply chain managers to create multi-vendor transportation ecosystems to work together rather than working by themselves. The implication for positive social change includes the potential to create employment and increase local communities’ tax revenues that could be used to provide the most needed social services

    Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeX

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    This study examines the efficacy of various neural network (NN) models in interpreting mental constructs via electroencephalogram (EEG) signals. Through the assessment of 16 prevalent NN models and their variants across four brain-computer interface (BCI) paradigms, we gauged their information representation capability. Rooted in comprehensive literature review findings, we proposed EEGNeX, a novel, purely ConvNet-based architecture. We pitted it against both existing cutting-edge strategies and the Mother of All BCI Benchmarks (MOABB) involving 11 distinct EEG motor imagination (MI) classification tasks and revealed that EEGNeX surpasses other state-of-the-art methods. Notably, it shows up to 2.1%-8.5% improvement in the classification accuracy in different scenarios with statistical significance (p < 0.05) compared to its competitors. This study not only provides deeper insights into designing efficient NN models for EEG data but also lays groundwork for future explorations into the relationship between bioelectric brain signals and NN architectures. For the benefit of broader scientific collaboration, we have made all benchmark models, including EEGNeX, publicly available at (https://github.com/chenxiachan/EEGNeX).Comment: 19 pages, 6 figure
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