8,204 research outputs found

    A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms

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    Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data. A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability. To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity. A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case. The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change. The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence

    Educating Sub-Saharan Africa:Assessing Mobile Application Use in a Higher Learning Engineering Programme

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    In the institution where I teach, insufficient laboratory equipment for engineering education pushed students to learn via mobile phones or devices. Using mobile technologies to learn and practice is not the issue, but the more important question lies in finding out where and how they use mobile tools for learning. Through the lens of Kearney et al.’s (2012) pedagogical model, using authenticity, personalisation, and collaboration as constructs, this case study adopts a mixed-method approach to investigate the mobile learning activities of students and find out their experiences of what works and what does not work. Four questions are borne out of the over-arching research question, ‘How do students studying at a University in Nigeria perceive mobile learning in electrical and electronic engineering education?’ The first three questions are answered from qualitative, interview data analysed using thematic analysis. The fourth question investigates their collaborations on two mobile social networks using social network and message analysis. The study found how students’ mobile learning relates to the real-world practice of engineering and explained ways of adapting and overcoming the mobile tools’ limitations, and the nature of the collaborations that the students adopted, naturally, when they learn in mobile social networks. It found that mobile engineering learning can be possibly located in an offline mobile zone. It also demonstrates that investigating the effectiveness of mobile learning in the mobile social environment is possible by examining users’ interactions. The study shows how mobile learning personalisation that leads to impactful engineering learning can be achieved. The study shows how to manage most interface and technical challenges associated with mobile engineering learning and provides a new guide for educators on where and how mobile learning can be harnessed. And it revealed how engineering education can be successfully implemented through mobile tools

    Antibody Targeting of HIV-1 Env: A Structural Perspective

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    A key component of contemporary efforts toward a human immunodeficiency virus 1 (HIV-1) vaccine is the use of structural biology to understand the structural characteristics of antibodies elicited both from human patients and animals immunized with engineered 'immunogens,' or early vaccine candidates. This thesis will report on projects characterizing both types of antibodies against HIV-1. Chapter 1 will introduce relevant topics, including the reasons HIV-1 is particularly capable of evading the immune system in natural infection and after vaccination, the 20+ year history of unsuccessful HIV-1 vaccine large-scale efficacy trials, an introduction to broadly neutralizing antibodies (bNAbs), and a review of common strategies utilized in HIV-1 immunogen design today. Chapter 2 describes the isolation, high-resolution structural characterization, and in vitro resistance profile of a new bNAb, 1-18, that is both very broad and potent, as well as able to restrict HIV-1 escape in vivo. Chapter 3 reports the results of an epitope-focusing immunogen design and immunization experiment carried out in wild type mice, rabbits, and non-human primates where it was shown that B cells targeting the desired epitope were expanded after a single prime immunization with immunogen RC1 or a variant, RC1-4fill. Chapter 4 describes Ab1245, an off-target non-neutralizing monoclonal antibody isolated in a macaque that had been immunized with a series of sequential immunogens after the prime immunization reported in Chapter 3. The antibody structure describes a specific type of distracting response as it binds in a way that causes a large structural change in Env, resulting in the destruction of the neutralizing fusion peptide epitope. Chapter 5 is adapted from a review about how antibodies differentially recognize the viruses HIV-1, SARS-CoV-2, and Zika virus. This review serves as an introduction to the virus SARS-CoV-2, which is the topic of the final chapter, Chapter 6. In this chapter, structures of many neutralizing antibodies isolated from SARS-CoV-2 patients were used to define potentially therapeutic classes of neutralizing receptor-binding domain (RBD) antibodies based on their epitopes and binding profiles

    Graphical scaffolding for the learning of data wrangling APIs

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    In order for students across the sciences to avail themselves of modern data streams, they must first know how to wrangle data: how to reshape ill-organised, tabular data into another format, and how to do this programmatically, in languages such as Python and R. Despite the cross-departmental demand and the ubiquity of data wrangling in analytical workflows, the research on how to optimise the instruction of it has been minimal. Although data wrangling as a programming domain presents distinctive challenges - characterised by on-the-fly syntax lookup and code example integration - it also presents opportunities. One such opportunity is how tabular data structures are easily visualised. To leverage the inherent visualisability of data wrangling, this dissertation evaluates three types of graphics that could be employed as scaffolding for novices: subgoal graphics, thumbnail graphics, and parameter graphics. Using a specially built e-learning platform, this dissertation documents a multi-institutional, randomised, and controlled experiment that investigates the pedagogical effects of these. Our results indicate that the graphics are well-received, that subgoal graphics boost the completion rate, and that thumbnail graphics improve navigability within a command menu. We also obtained several non-significant results, and indications that parameter graphics are counter-productive. We will discuss these findings in the context of general scaffolding dilemmas, and how they fit into a wider research programme on data wrangling instruction

    Industry 4.0: product digital twins for remanufacturing decision-making

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    Currently there is a desire to reduce natural resource consumption and expand circular business principles whilst Industry 4.0 (I4.0) is regarded as the evolutionary and potentially disruptive movement of technology, automation, digitalisation, and data manipulation into the industrial sector. The remanufacturing industry is recognised as being vital to the circular economy (CE) as it extends the in-use life of products, but its synergy with I4.0 has had little attention thus far. This thesis documents the first investigating into I4.0 in remanufacturing for a CE contributing a design and demonstration of a model that optimises remanufacturing planning using data from different instances in a product’s life cycle. The initial aim of this work was to identify the I4.0 technology that would enhance the stability in remanufacturing with a view to reducing resource consumption. As the project progressed it narrowed to focus on the development of a product digital twin (DT) model to support data-driven decision making for operations planning. The model’s architecture was derived using a bottom-up approach where requirements were extracted from the identified complications in production planning and control that differentiate remanufacturing from manufacturing. Simultaneously, the benefits of enabling visibility of an asset’s through-life health were obtained using a DT as the modus operandi. A product simulator and DT prototype was designed to use Internet of Things (IoT) components, a neural network for remaining life estimations and a search algorithm for operational planning optimisation. The DT was iteratively developed using case studies to validate and examine the real opportunities that exist in deploying a business model that harnesses, and commodifies, early life product data for end-of-life processing optimisation. Findings suggest that using intelligent programming networks and algorithms, a DT can enhance decision-making if it has visibility of the product and access to reliable remanufacturing process information, whilst existing IoT components provide rudimentary “smart” capabilities, but their integration is complex, and the durability of the systems over extended product life cycles needs to be further explored

    Managing global virtual teams in the London FinTech industry

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    Today, the number of organisations that are adopting virtual working arrangements has exploded, and the London FinTech industry is no exception. During recent years, FinTech companies have increasingly developed virtual teams as a means of connecting and engaging geographically dispersed workers, lowering costs, and enabling greater speed and adaptability. As the first study in the United Kingdom regarding global virtual team management in the FinTech industry, this DBA research seeks answers to the question, “What makes for the successful management of a global virtual team in the London FinTech industry?”. Straussian grounded-theory method was chosen as this qualitative approach lets participants have their own voice and offers some flexibility. It also allows the researcher to have preconceived ideas about the research undertaking. The research work makes the case for appreciating the voice of people with lived experiences. Ten London-based FinTech Managers with considerable experience running virtual teams agreed to take part in this study. These Managers had spent time working at large, household-name firms with significant global reach, and one had recently become founder and CEO of his own firm, taking on clients and hiring contract staff from around the world. At least eight of the other participants were senior ‘Heads’ of various technology teams and one was a Managing Director working at a ‘Big Four’ consultancy. They had all (and many still did) spent years running geographically distributed teams with members as far away as Pacific Asia and they were all keen to discuss that breadth of experience and the challenges they faced. Results from these in-depth interviews suggested that there are myriad reasons for a global virtual team, from providing 24 hour, follow-the-sun service to locating the most cost-effective resources with the highest skills. It also confirmed that there are unique challenges to virtual management and new techniques are required to help navigate virtual managers through them. Managing a global virtual team requires much more than the traditional management competencies. Based on discussion with the respondents, a set of practical recommendations for global virtual team management was developed and covered a wide range of issues related to recruitment and selection, team building, developing standard operating procedures, communication, motivation, performance management, and building trust

    Investigative Methods: An NCRM Innovation Collection

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    This Innovation Collection on investigative methods brings together investigators working in different domains, sectors, and on different topics of interest to help capture the breadth, scope and relevance of investigative practices over 10 substantive chapters. Each of the papers presents a different investigative method or set of methods and, through case studies, attempts to demonstrate their value. All the contributions, in different ways and for different purposes, seek to reconstruct acts, events, practices, biographies and/or milieux, to which the researchers in question lack direct access, but which they want to reconstruct via the traces those phenomena leave behind, traces themselves often produced as part of the phenomena under investigation. These include reports of methods used in investigations on: - The use of force by state actors, including into police violence, military decisions to attack civilians, the provenance of munitions used to attack civilians, and the use and abuse of tear gas; - Networks of far-right discourse, and its links to criminal attacks and state-leveraged misinformation campaigns; - Archives to establish the penal biographies of convicts and the historical practices of democratic petitioning; - Corporate structures and processes that enable tax avoidance and an avoidance of legal responsibilities to workers and the environment. A working principle of the collection is that investigative methods may be considered, alongside creative, qualitative, quantitative, digital, participatory and mixed methods, a distinct yet complementary style of research
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