8,825 research outputs found

    Bildung in der digitalen Transformation

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    Die Coronapandemie und der durch sie erzwungene zeitweise Übergang von Präsenz- zu Distanzlehre haben die Digitalisierung des Bildungswesens enorm vorangetrieben. Noch deutlicher als vorher traten dabei positive wie negative Aspekte dieser Entwicklung zum Vorschein. Während den Hochschulen der Wechsel mit vergleichsweise geringen Reibungsverlusten gelang, offenbarten sich diese an Schulen weitaus deutlicher. Trotz aller Widrigkeiten erscheint eines klar: Die zeitweisen Veränderungen werden Nachwirkungen zeigen. Eine völlige Rückkehr zum Status quo ante ist kaum noch vorstellbar. Zwei Fragen bestimmen vor diesem Hintergrund die Doppelgesichtigkeit des Themas der 29. Jahrestagung der Gesellschaft für Medien in der Wissenschaft (GMW). Erstens: Wie ‚funktioniert‘ Bildung in der sich derzeit ereignenden digitalen Transformation und welche Herausforderungen gibt es? Und zweitens: Befindet sich möglicherweise Bildung selbst in der Transformation? Beiträge zu diesen und weiteren Fragen vereint der vorliegende Tagungsband

    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

    Characterising the role of the Amyloid Precursor Protein and Glucagon-like peptide-1 analogues in Age-Related Macular Degeneration

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    Age-related macular degeneration (AMD) is a progressive retinal neurodegenerative disorder characterised, in some forms of the disease, by the loss of photoreceptors and the underlying retinal pigment epithelium (RPE) in the macula due to the accumulation of extracellular deposits known as “drusen”. A major component of drusen deposits is the Alzheimer’s disease (AD)-related amyloid beta (Aβ)-peptide, a 4kDa peptide derived from the larger amyloid precursor protein (APP) through sequential cleavage by enzymes known as β- and γ-secretases. Alternatively, in the ‘non-amyloidogenic’ pathway, APP can be processed by a third enzyme, α-secretase, which cleaves within the Aβ region of the protein thereby preventing the production of toxic peptides as well as producing a larger soluble fragment, sAPPα, known for its neuroprotective and neurotrophic properties. The current project aims to characterise the role played by APP and its proteolytic fragments in AMD using human retinal pigment epithelial cells (ARPE-19) and UV-A light (a known AMD risk factor) as the stressor. In addition, a group of diabetes drugs known as Glucagon Like Peptide-1 (GLP-1) analogues that have previously been purported to reduce neuronal death in AD and Parkinson’s Disease (PD) have been tested for their ability to protect ARPE-19 cells against stress-inducing reagents relative to AMD (UV-A light, hydrogen peroxide and Aβ-peptides). The results of the current study demonstrate that endogenous cell-associated full-length APP expression was depleted in ARPE-19 cells following UV-A irradiation. Furthermore, β-secretase but not α-secretase processing of the protein was reduced. Small interfering RNA-mediated depletion of endogenous APP or γ-secretase (but not α- or β-secretase) inhibition ablated the detrimental effect of UV-A on cell viability. In contrast, α-secretase and, possibly, γ-secretase but not β-secretase activity appeared to promote the longer-term proliferation of ARPE-19 cells in the absence of UV-A irradiation. Furthermore, two of the GLP-1 analogues tested, liraglutide and lixisenatide, were able to restore cell viability after UV-A exposure. Collectively, these data indicate clear links between the expression/proteolysis of APP and the proliferation and resistance of ARPE-19 cells to UV-A irradiation. Whilst these effects are clearly differential, the data warrant further investigation of the role played by APP in AMD. Furthermore, the protective effects against UV-A shown by liraglutide and lixisenatide warrant further investigation of the molecular mechanisms involved with a view to identifying new drug targets for the prevention or treatment of retinal neurodegenerative diseases such as AMD

    Modern Folk Devils

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    The devilish has long been integral to myths, legends, and folklore, firmly located in the relationships between good and evil, and selves and others. But how are ideas of evil constructed in current times and framed by contemporary social discourses? Modern Folk Devils builds on and works with Stanley Cohen’s theory on folk devils and moral panics to discuss the constructions of evil. The authors present an array of case-studies that illustrate how the notion of folk devils nowadays comes into play and animates ideas of otherness and evil throughout the world. Examining current fears and perceived threats, this volume investigates and analyzes how and why these devils are constructed. The chapters discuss how the devilish may take on many different forms: sometimes they exist only as a potential threat, other times they are a single individual or phenomenon or a visible group, such as refugees, technocrats, Roma, hipsters, LGBT groups, and rightwing politicians. Folk devils themselves are also given a voice to offer an essential complementary perspective on how panics become exaggerated, facts distorted, and problems acutely angled.;Bringing together researchers from anthropology, sociology, political studies, ethnology, and criminology, the contributions examine cases from across the world spanning from Europe to Asia and Oceania

    Technologies and Applications for Big Data Value

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    This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

    Experimental models of focal neuroinflammation - Efficacy assessment of pharmaceuticals of multiple sclerosis using PET imaging

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    Neuroinflammation (NI) is a key player in neurodegenerative diseases, such as multiple sclerosis (MS). Magnetic resonance imaging is the gold standard imaging method for diagnosis of MS, however, better diagnostic tools are needed for the follow-up of disease progression, earlier diagnosis, and assessment of patients’ response to therapy. Positron emission tomography (PET) is a sensitive and selective functional imaging method for investigating mechanisms of diseases at a molecular level. NI can be visualised in PET by targeting the 18 kDa translocator protein (TSPO), which is upregulated during NI on the mitochondria of glial cells. This study aimed to evaluate the properties of [18F]GE-180, a 2nd generation TSPO PET radiotracer, in a unilateral model of acute NI and evaluate the efficacy of immunomodulatory drugs, anti-VLA-4 and dimethyl fumarate (DMF), in two different focal rat models of experimental autoimmune encephalomyelitis (EAE), the fDTH-EAE and fMOG-EAE models. The applied methods were in vivo PET imaging, digital autoradiography, and immunohistochemical (IHC) staining. Study I indicated improved binding potential of [18F]GE-180 over the 1st generation tracer [11C]PK11195 and showed that the unilateral model of acute NI is suitable for the evaluation of novel PET tracers of NI. Study II indicated that anti- VLA-4 had no short-term treatment effects in the fDHT-EAE-rat model. However, discontinuation of the treatment caused a rebound that could be detected with [18F]GE-180. Study III showed, that short-term, but not long-term, DMF treatment decreases uptake of [18F]GE-180 in the fDTH-EAE rat model, and no rebound effect was detected after halting the treatment for 10 weeks. Nevertheless, the efficacy of DMF was detected using IHC for CD4+ and CD8+ cells. No DMF treatment effect was observed in the fMOG-EAE model. In conclusion, focal animal models of NI are applicable for evaluating novel PET tracers. Furthermore, efficacy assessment of immunomodulatory drugs can be evaluated using TSPO PET when the tracer is binding to the same biomarker that the drug is affectingPesäkkeisen aivotulehduksen kokeelliset mallit – multippeliskleroosin lääkkeiden vaikuttavuuden arviointi käyttäen PETkuvantamista Keskushermoston tulehdus on tila, joka ilmenee useissa hermorappeumasairauksissa, kuten pesäkekovettumataudissa (MS-tauti). MS-taudin kuvantamisdiagnostiikan ensisijainen menetelmä on magneettikuvaus, mutta uusia diagnostisia menetelmiä tarvitaan taudin mahdollisimman varhaiseksi toteamiseksi, etenemisen seuraamiseksi, ja uusien lääkehoitojen tehon arvioimiseksi. Positroniemissiotomografia (PET) on kajoamaton kuvantamismenetelmä, jonka avulla on mahdollista seurata aivojen tulehdusreaktiota hyödyntämällä tulehduksen aikana yliilmentyvään translokaatioproteiiniin (TSPO) sitoutuvia PET-merkkiaineita. Tämän tutkimuksen tavoitteena oli verrata TSPO-molekyyliin sitoutuvan toisen sukupolven PET-merkkiaineen ([18F]GE-180) sekä jo käytössä olevan merkkiaineen ([11C]PK11195) ominaisuuksia akuutin tulehduksen rottamallissa. Lisäksi tavoitteena oli arvioida immuunivastetta muokkaavien lääkkeiden, anti-VLA-4:n ja dimetyylifumaraatin, tehokkuutta lyhyt- ja pitkäaikaishoidossa fDTH-EAE- ja fMOG-EAE-malleissa, joissa rotille aiheutetaan pesäkkeinen autoimmuunienkefalomyeliitti. Tulehdusreaktiossa tapahtuvia muutoksia seurattiin hyödyntäen in vivo [18F]GE-180-PET-kuvantamista, autoradiografiaa, sekä kudosvärjäyksiä. Ensimmäisessä osatyössä [18F]GE-180-merkkiaineen havaittiin soveltuvan [11C]PK11195-merkkiainetta paremmin aivotulehduksen kuvantamiseen eläinmalleissa: aivojen tulehdusalue oli merkittävästi suurempi ja merkkiaineen sitoutumiskyky ja spesifisyys parempi. Toisessa osatyössä anti-VLA-4-lääkehoidon vaikutusta ei ollut mahdollista seurata [18F]GE-180-PET-kuvantamisella fDTHEAE-mallin kroonisen tulehduksen vaiheessa. Hoidon lopettamisen jälkeen ilmenevä voimakas tulehduksen uudelleenaktivoituminen oli kuitenkin mahdollista havaita PET-kuvauksella. Kolmannessa osatyössä dimetyylifumaraatin havaittiin hillitsevän tulehdusta fDTH-EAE-mallissa lyhytaikaishoidossa yhden viikon hoidon jälkeen, mutta ei enää myöhemmissä aikapisteissä, eikä fMOG-EAE-mallissa. Tämä väitöskirjatutkimus osoitti, että pesäkkeisen tulehduksen rottamalleja voidaan hyödyntää uusien tulehdusta kuvantavien PET-merkkiaineiden, sekä immuunivastetta muokkaavien lääkkeiden tehokkuuden arvioinnissa

    New Research and Trends in Higher Education

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    This book aims to discuss new research and trends on all dimensions of Higher Education, as there is a growing interest in the field of Higher Education, regarding new methodologies, contexts, and technologies. It includes investigations of diverse issues that affect the learning processes in Higher Education: innovations in learning, new pedagogical methods, and new learning contexts.In this sense, original research contributions of research papers, case studies and demonstrations that present original scientific results, methodological aspects, concepts and educational technologies, on the following topics:a) Technological Developments in Higher Education: mobile technology, virtual environments, augmented reality, automation and robotics, and other tools for universal learning, focusing on issues that are not addressed by existing research;b) Digital Higher Education: mobile learning, eLearning, Game-based Learning, social media in education, new learning models and technologies and wearable technologies for education;c) Case Studies in Higher Education: empirical studies in higher education regarding digital technologies, new methodologies, new evaluation techniques and tools, perceptions of learning processes efficiency and digital learning best practice
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