4,644 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

    Ideology and the Impact of Development Agency Activity. A Study of Agricultural Extension and Community Development in Botswana.

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    Community Development and Agricultural Extension programmes in Botswana are founded upon related theoretical approaches to the development task which provide the agencies with an operating ideology. The ideology in both cases emphasises the need to provide information, change values, and persuade people to participate in development. When the 'Pupil Farmer' scheme and the 'self help' projects of these government agencies are framed within this perspective other important dimensions of change and development like investment stimulation or institutional innovation tend to he neglected both in policy and in analysis of their clients’ needs. Extension workers try to persuade farmers to adopt 'modern’ techniques but their advice is ignored by much of the population because the innovations, being both time-consuming and expensive, are beyond their means. Extension staff however interpret the response as evidence of their clients’ deep-seated attachment to traditional ways for which the only cure is more persuasion. Community Development assists government to establish village development committees through which development projects can be organised. Villagers are expected to take development initiatives but the declining power of the chieftainship is not replaced by alternative authority so that these initiatives are difficult to sustain. Conflict and stalemate is put down to lack of education or backwardness for which the solution is more community development. Thus frustrated development activity tends to confirm existing "beliefs" but this alone is not an adequate explanation of the persistence of a limited ideology. In organisations with widely dispersed personnel where formal controls do not work conformity with organisational ideology "becomes an essential element in social control. The study concludes with a brief exploration of the organisational implications of these findings

    Securing IoT Applications through Decentralised and Distributed IoT-Blockchain Architectures

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    The integration of blockchain into IoT can provide reliable control of the IoT network's ability to distribute computation over a large number of devices. It also allows the AI system to use trusted data for analysis and forecasts while utilising the available IoT hardware to coordinate the execution of tasks in parallel, using a fully distributed approach. This thesis's  rst contribution is a practical implementation of a real world IoT- blockchain application, ood detection use case, is demonstrated using Ethereum proof of authority (PoA). This includes performance measurements of the transaction con-  rmation time, the system end-to-end latency, and the average power consumption. The study showed that blockchain can be integrated into IoT applications, and that Ethereum PoA can be used within IoT for permissioned implementation. This can be achieved while the average energy consumption of running the ood detection system including the Ethereum Geth client is small (around 0.3J). The second contribution is a novel IoT-centric consensus protocol called honesty- based distributed proof of authority (HDPoA) via scalable work. HDPoA was analysed and then deployed and tested. Performance measurements and evaluation along with the security analyses of HDPoA were conducted using a total of 30 di erent IoT de- vices comprising Raspberry Pis, ESP32, and ESP8266 devices. These measurements included energy consumption, the devices' hash power, and the transaction con rma- tion time. The measured values of hash per joule (h/J) for mining were 13.8Kh/J, 54Kh/J, and 22.4Kh/J when using the Raspberry Pi, the ESP32 devices, and the ESP8266 devices, respectively, this achieved while there is limited impact on each de- vice's power. In HDPoA the transaction con rmation time was reduced to only one block compared to up to six blocks in bitcoin. The third contribution is a novel, secure, distributed and decentralised architecture for supporting the implementation of distributed arti cial intelligence (DAI) using hardware platforms provided by IoT. A trained DAI system was implemented over the IoT, where each IoT device hosts one or more neurons within the DAI layers. This is accomplished through the utilisation of blockchain technology that allows trusted interaction and information exchange between distributed neurons. Three di erent datasets were tested and the system achieved a similar accuracy as when testing on a standalone system; both achieved accuracies of 92%-98%. The system accomplished that while ensuring an overall latency of as low as two minutes. This showed the secure architecture capabilities of facilitating the implementation of DAI within IoT while ensuring the accuracy of the system is preserved. The fourth contribution is a novel and secure architecture that integrates the ad- vantages o ered by edge computing, arti cial intelligence (AI), IoT end-devices, and blockchain. This new architecture has the ability to monitor the environment, collect data, analyse it, process it using an AI-expert engine, provide predictions and action- able outcomes, and  nally share it on a public blockchain platform. The pandemic caused by the wide and rapid spread of the novel coronavirus COVID-19 was used as a use-case implementation to test and evaluate the proposed system. While providing the AI-engine trusted data, the system achieved an accuracy of 95%,. This is achieved while the AI-engine only requires a 7% increase in power consumption. This demon- strate the system's ability to protect the data and support the AI system, and improves the IoT overall security with limited impact on the IoT devices. The  fth and  nal contribution is enhancing the security of the HDPoA through the integration of a hardware secure module (HSM) and a hardware wallet (HW). A performance evaluation regarding the energy consumption of nodes that are equipped with HSM and HW and a security analysis were conducted. In addition to enhancing the nodes' security, the HSM can be used to sign more than 120 bytes/joule and encrypt up to 100 bytes/joule, while the HW can be used to sign up to 90 bytes/joule and encrypt up to 80 bytes/joule. The result and analyses demonstrated that the HSM and HW enhance the security of HDPoA, and also can be utilised within IoT-blockchain applications while providing much needed security in terms of con dentiality, trust in devices, and attack deterrence. The above contributions showed that blockchain can be integrated into IoT systems. It showed that blockchain can successfully support the integration of other technolo- gies such as AI, IoT end devices, and edge computing into one system thus allowing organisations and users to bene t greatly from a resilient, distributed, decentralised, self-managed, robust, and secure systems

    Advanced Nanomaterials for Electrochemical Energy Conversion and Storage

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    This book focuses on advanced nanomaterials for energy conversion and storage, covering their design, synthesis, properties and applications in various fields. Developing advanced nanomaterials for high-performance and low-cost energy conversion and storage devices and technologies is of great significance in order to solve the issues of energy crisis and environmental pollution. In this book, various advanced nanomaterials for batteries, capacitors, electrocatalysis, nanogenerators, and magnetic nanomaterials are presente

    Home, Belonging and Multiculturalism in Twenty-First-Century British South Asian Fiction

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    This thesis contributes to the literary and cultural debates surrounding multiculturalism and questions of home and identity in contemporary Britain, using the British South Asian novel as a case study. Through close readings of six novels, including Maps For Lost Lovers (2004) by Nadeem Aslam, Londonstani (2006) by Gautam Malkani, The Year of Runaways (2015) by Sunjeev Sahota, Home Fire (2017) by Kamila Shamsie, Exit West (2017) by Mohsin Hamid, and In Our Mad and Furious City (2018) by Guy Gunaratne, the thesis brings theories of multiculturalism, class, and race into conversation with contemporary British South Asian fiction. It re-examines multiculturalism, as represented in the fiction, in light of recent key events that have catalysed its reconfigurations (e.g. 9/11, 7/7, the 2011 England riots and Brexit) alongside conceptual developments of notions of race, class, home and identity. Stuart Hall (1990) suggests that identity is constructed “within, not outside of, representation”, which indicates that literature plays a potentially important role in the public perception of identity (222). The thesis seeks to demonstrate that terms like diaspora, migrancy, hybridity and liminality do not fully capture the experience of multiculturalism as depicted in the selected novels. Whilst the thesis does not fully dismiss these terms, it redirects attention to critical, non-celebratory conceptions of multiculturalism. In so doing, it makes interventions into debates on multiculturalism. It shows how the UK government has tended to present multiculturalism as “a management exercise” (Mishra 2007, 133) through a “series of hesitant moves and recommendations”, which, as Peter Morey argues, it would be “hard to call […] a multicultural policy” (Morey 2018a, 5). It argues that theories of multiculturalism might become more 3 coherent if approached from specific theories of race, ethnicity, and class. Such mapping, as Vijay Mishra (2007) advocates, allows us to think more precisely about these theories, so that we can view multiculturalism as “a critical concept” rather than “a management exercise” (133). The thesis first sets out a theoretical framework by which to explore its central concerns with the modalities of representation of British South Asians in fiction and their engagement with ideas of home and identity that are always already inflected by the complexities of race, class, religion and multiculturalism. It then turns to the historical and socio-political contexts of diverse British South Asian experiences as they are depicted in the fiction. The research employs a mixed-method approach synthesising theories of multiculturalism, race, ethnicity, and class, with close readings of British South Asian fiction written between 2000 and 2020. In the process, this enables a critical re-evaluation of these theories (Gilroy 2004, Mishra 2007, Ahmed 2015). Finally, the thesis offers new ways of reading the various permutations of British South Asian identity as culturally diverse in contemporary literature produced by British South Asian authors

    “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

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    Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT's capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT's use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

    Post-Growth Geographies: Spatial Relations of Diverse and Alternative Economies

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    Post-Growth Geographies examines the spatial relations of diverse and alternative economies between growth-oriented institutions and multiple socio-ecological crises. The book brings together conceptual and empirical contributions from geography and its neighbouring disciplines and offers different perspectives on the possibilities, demands and critiques of post-growth transformation. Through case studies and interviews, the contributions combine voices from activism, civil society, planning and politics with current theoretical debates on socio-ecological transformation

    LASSO – an observatorium for the dynamic selection, analysis and comparison of software

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    Mining software repositories at the scale of 'big code' (i.e., big data) is a challenging activity. As well as finding a suitable software corpus and making it programmatically accessible through an index or database, researchers and practitioners have to establish an efficient analysis infrastructure and precisely define the metrics and data extraction approaches to be applied. Moreover, for analysis results to be generalisable, these tasks have to be applied at a large enough scale to have statistical significance, and if they are to be repeatable, the artefacts need to be carefully maintained and curated over time. Today, however, a lot of this work is still performed by human beings on a case-by-case basis, with the level of effort involved often having a significant negative impact on the generalisability and repeatability of studies, and thus on their overall scientific value. The general purpose, 'code mining' repositories and infrastructures that have emerged in recent years represent a significant step forward because they automate many software mining tasks at an ultra-large scale and allow researchers and practitioners to focus on defining the questions they would like to explore at an abstract level. However, they are currently limited to static analysis and data extraction techniques, and thus cannot support (i.e., help automate) any studies which involve the execution of software systems. This includes experimental validations of techniques and tools that hypothesise about the behaviour (i.e., semantics) of software, or data analysis and extraction techniques that aim to measure dynamic properties of software. In this thesis a platform called LASSO (Large-Scale Software Observatorium) is introduced that overcomes this limitation by automating the collection of dynamic (i.e., execution-based) information about software alongside static information. It features a single, ultra-large scale corpus of executable software systems created by amalgamating existing Open Source software repositories and a dedicated DSL for defining abstract selection and analysis pipelines. Its key innovations are integrated capabilities for searching for selecting software systems based on their exhibited behaviour and an 'arena' that allows their responses to software tests to be compared in a purely data-driven way. We call the platform a 'software observatorium' since it is a place where the behaviour of large numbers of software systems can be observed, analysed and compared
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