10,792 research outputs found

    Search for heavy Majorana or Dirac neutrinos and right-handed WW gauge bosons in final states with charged leptons and jets in pppp collisions at s=13\sqrt{s}=13 TeV with the ATLAS detector

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    A search for heavy right-handed Majorana or Dirac neutrinos NRN_{\mathrm{R}} and heavy right-handed gauge bosons WRW_{\mathrm{R}} is performed in events with energetic electrons or muons, with the same or opposite electric charge, and energetic jets. The search is carried out separately for topologies of clearly separated final-state products (``resolved'' channel) and topologies with boosted final states with hadronic products partially overlapping and reconstructed as a large-radius jet (``boosted'' channel). The events are selected from pppp collision data at the LHC with an integrated luminosity of 139 fb1^{-1} collected by the ATLAS detector at s\sqrt{s} = 13 TeV. No significant deviations from the Standard Model predictions are observed. The results are interpreted within the theoretical framework of a left-right symmetric model, and lower limits are set on masses in the heavy right-handed WRW_{\mathrm{R}} boson and NRN_{\mathrm{R}} plane. The excluded region extends to about m(WR)=6.4m(W_{\mathrm{R}}) = 6.4 TeV for both Majorana and Dirac NRN_{\mathrm{R}} neutrinos at m(NR)<1m(N_{\mathrm{R}})<1 TeV. NRN_{\mathrm{R}} with masses of less than 3.5 (3.6) TeV are excluded in the electron (muon) channel at m(WR)=4.8m(W_{\mathrm{R}})=4.8 TeV for the Majorana neutrinos, and limits of m(NR)m(N_{\mathrm{R}}) up to 3.6 TeV for m(WR)=5.2m(W_{\mathrm{R}}) = 5.2 (5.05.0) TeV in the electron (muon) channel are set for the Dirac neutrinos.Comment: 48 pages in total, author list starting page 31, 9 figures, 5 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/EXOT-2019-39

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice

    Corporate Social Responsibility: the institutionalization of ESG

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    Understanding the impact of Corporate Social Responsibility (CSR) on firm performance as it relates to industries reliant on technological innovation is a complex and perpetually evolving challenge. To thoroughly investigate this topic, this dissertation will adopt an economics-based structure to address three primary hypotheses. This structure allows for each hypothesis to essentially be a standalone empirical paper, unified by an overall analysis of the nature of impact that ESG has on firm performance. The first hypothesis explores the evolution of CSR to the modern quantified iteration of ESG has led to the institutionalization and standardization of the CSR concept. The second hypothesis fills gaps in existing literature testing the relationship between firm performance and ESG by finding that the relationship is significantly positive in long-term, strategic metrics (ROA and ROIC) and that there is no correlation in short-term metrics (ROE and ROS). Finally, the third hypothesis states that if a firm has a long-term strategic ESG plan, as proxied by the publication of CSR reports, then it is more resilience to damage from controversies. This is supported by the finding that pro-ESG firms consistently fared better than their counterparts in both financial and ESG performance, even in the event of a controversy. However, firms with consistent reporting are also held to a higher standard than their nonreporting peers, suggesting a higher risk and higher reward dynamic. These findings support the theory of good management, in that long-term strategic planning is both immediately economically beneficial and serves as a means of risk management and social impact mitigation. Overall, this contributes to the literature by fillings gaps in the nature of impact that ESG has on firm performance, particularly from a management perspective

    Anuário científico da Escola Superior de Tecnologia da Saúde de Lisboa - 2021

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    É com grande prazer que apresentamos a mais recente edição (a 11.ª) do Anuário Científico da Escola Superior de Tecnologia da Saúde de Lisboa. Como instituição de ensino superior, temos o compromisso de promover e incentivar a pesquisa científica em todas as áreas do conhecimento que contemplam a nossa missão. Esta publicação tem como objetivo divulgar toda a produção científica desenvolvida pelos Professores, Investigadores, Estudantes e Pessoal não Docente da ESTeSL durante 2021. Este Anuário é, assim, o reflexo do trabalho árduo e dedicado da nossa comunidade, que se empenhou na produção de conteúdo científico de elevada qualidade e partilhada com a Sociedade na forma de livros, capítulos de livros, artigos publicados em revistas nacionais e internacionais, resumos de comunicações orais e pósteres, bem como resultado dos trabalhos de 1º e 2º ciclo. Com isto, o conteúdo desta publicação abrange uma ampla variedade de tópicos, desde temas mais fundamentais até estudos de aplicação prática em contextos específicos de Saúde, refletindo desta forma a pluralidade e diversidade de áreas que definem, e tornam única, a ESTeSL. Acreditamos que a investigação e pesquisa científica é um eixo fundamental para o desenvolvimento da sociedade e é por isso que incentivamos os nossos estudantes a envolverem-se em atividades de pesquisa e prática baseada na evidência desde o início dos seus estudos na ESTeSL. Esta publicação é um exemplo do sucesso desses esforços, sendo a maior de sempre, o que faz com que estejamos muito orgulhosos em partilhar os resultados e descobertas dos nossos investigadores com a comunidade científica e o público em geral. Esperamos que este Anuário inspire e motive outros estudantes, profissionais de saúde, professores e outros colaboradores a continuarem a explorar novas ideias e contribuir para o avanço da ciência e da tecnologia no corpo de conhecimento próprio das áreas que compõe a ESTeSL. Agradecemos a todos os envolvidos na produção deste anuário e desejamos uma leitura inspiradora e agradável.info:eu-repo/semantics/publishedVersio

    Redefining Community in the Age of the Internet: Will the Internet of Things (IoT) generate sustainable and equitable community development?

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    There is a problem so immense in our built world that it is often not fully realized. This problem is the disconnection between humanity and the physical world. In an era of limitless data and information at our fingertips, buildings, public spaces, and landscapes are divided from us due to their physical nature. Compared with the intense flow of information from our online world driven by the beating engine of the internet, our physical world is silent. This lack of connection not only has consequences for sustainability but also for how we perceive and communicate with our built environment in the modern age. A possible solution to bridge the gap between our physical and online worlds is a technology known as the Internet of Things (IoT). What is IoT? How does it work? Will IoT change the concept of the built environment for a participant within it, and in doing so enhance the dynamic link between humans and place? And what are the implications of IoT for privacy, security, and data for the public good? Lastly, we will identify the most pressing issues existing in the built environment by conducting and analyzing case studies from Pomona College and California State University, Northridge. By analyzing IoT in the context of case studies we can assess its viability and value as a tool for sustainability and equality in communities across the world

    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

    Supernatural crossing in Republican Chinese fiction, 1920s–1940s

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    This dissertation studies supernatural narratives in Chinese fiction from the mid-1920s to the 1940s. The literary works present phenomena or elements that are or appear to be supernatural, many of which remain marginal or overlooked in Sinophone and Anglophone academia. These sources are situated in the May Fourth/New Culture ideological context, where supernatural narratives had to make way for the progressive intellectuals’ literary realism and their allegorical application of supernatural motifs. In the face of realism, supernatural narratives paled, dismissed as impractical fantasies that distract one from facing and tackling real life. Nevertheless, I argue that the supernatural narratives do not probe into another mystical dimension that might co-exist alongside the empirical world. Rather, they imagine various cases of the characters’ crossing to voice their discontent with contemporary society or to reflect on the notion of reality. “Crossing” relates to characters’ acts or processes of trespassing the boundary that separates the supernatural from the conventional natural world, thus entailing encounters and interaction between the natural and the supernatural. The dissertation examines how crossing, as a narrative device, disturbs accustomed and mundane situations, releases hidden tensions, and discloses repressed truths in Republican fiction. There are five types of crossing in the supernatural narratives. Type 1 is the crossing into “haunted” houses. This includes (intangible) human agency crossing into domestic spaces and revealing secrets and truths concealed by the scary, feigned ‘haunting’, thus exposing the hidden evil and the other house occupiers’ silenced, suffocated state. Type 2 is men crossing into female ghosts’ apparitional residences. The female ghosts allude to heart-breaking, traumatic experiences in socio-historical reality, evoking sympathetic concern for suffering individuals who are caught in social upheavals. Type 3 is the crossing from reality into the characters’ delusional/hallucinatory realities. While they physically remain in the empirical world, the characters’ abnormal perceptions lead them to exclusive, delirious, and quasi-supernatural experiences of reality. Their crossings blur the concrete boundaries between the real and the unreal on the mental level: their abnormal perceptions construct a significant, meaningful reality for them, which may be as real as the commonly regarded objective reality. Type 4 is the crossing into the netherworld modelled on the real world in the authors’ observation and bears a spectrum of satirised objects of the Republican society. The last type is immortal visitors crossing into the human world. This type satirises humanity’s vices and destructive potential. The primary sources demonstrate their writers’ witty passion to play with super--natural notions and imagery (such as ghosts, demons, and immortals) and stitch them into vivid, engaging scenes using techniques such as the gothic, the grotesque, and the satirical, in order to evoke sentiments such as terror, horror, disgust, dis--orientation, or awe, all in service of their insights into realist issues. The works also creatively tailor traditional Chinese modes and motifs, which exemplifies the revival of Republican interest in traditional cultural heritage. The supernatural narratives may amaze or disturb the reader at first, but what is more shocking, unpleasantly nudging, or thought-provoking is the problematic society and people’s lives that the supernatural (misunderstandings) eventually reveals. They present a more compre--hensive treatment of reality than Republican literature with its revolutionary consciousness surrounding class struggle. The critical perspectives of the supernatural narratives include domestic space, unacknowledged history and marginal individuals, abnormal mentality, and pervasive weaknesses in humanity. The crossing and supernatural narratives function as a means of better understanding the lived reality. This study gathers diverse primary sources written by Republican writers from various educational and political backgrounds and interprets them from a rare perspective, thus filling a research gap. It promotes a fuller view of supernatural narratives in twentieth-century Chinese literature. In terms of reflecting the social and personal reality of the Republican era, the supernatural narratives supplement the realist fiction of the time

    Increased lifetime of Organic Photovoltaics (OPVs) and the impact of degradation, efficiency and costs in the LCOE of Emerging PVs

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    Emerging photovoltaic (PV) technologies such as organic photovoltaics (OPVs) and perovskites (PVKs) have the potential to disrupt the PV market due to their ease of fabrication (compatible with cheap roll-to-roll processing) and installation, as well as their significant efficiency improvements in recent years. However, rapid degradation is still an issue present in many emerging PVs, which must be addressed to enable their commercialisation. This thesis shows an OPV lifetime enhancing technique by adding the insulating polymer PMMA to the active layer, and a novel model for quantifying the impact of degradation (alongside efficiency and cost) upon levelized cost of energy (LCOE) in real world emerging PV installations. The effect of PMMA morphology on the success of a ternary strategy was investigated, leading to device design guidelines. It was found that either increasing the weight percent (wt%) or molecular weight (MW) of PMMA resulted in an increase in the volume of PMMA-rich islands, which provided the OPV protection against water and oxygen ingress. It was also found that adding PMMA can be effective in enhancing the lifetime of different active material combinations, although not to the same extent, and that processing additives can have a negative impact in the devices lifetime. A novel model was developed taking into account realistic degradation profile sourced from a literature review of state-of-the-art OPV and PVK devices. It was found that optimal strategies to improve LCOE depend on the present characteristics of a device, and that panels with a good balance of efficiency and degradation were better than panels with higher efficiency but higher degradation as well. Further, it was found that low-cost locations were more favoured from reductions in the degradation rate and module cost, whilst high-cost locations were more benefited from improvements in initial efficiency, lower discount rates and reductions in install costs

    Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process

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    Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine). In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model. AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development. Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models. In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri
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