265 research outputs found

    Applying machine learning: a multi-role perspective

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    Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference

    Design and Evaluation of Parallel and Scalable Machine Learning Research in Biomedical Modelling Applications

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    The use of Machine Learning (ML) techniques in the medical field is not a new occurrence and several papers describing research in that direction have been published. This research has helped in analysing medical images, creating responsive cardiovascular models, and predicting outcomes for medical conditions among many other applications. This Ph.D. aims to apply such ML techniques for the analysis of Acute Respiratory Distress Syndrome (ARDS) which is a severe condition that affects around 1 in 10.000 patients worldwide every year with life-threatening consequences. We employ previously developed mechanistic modelling approaches such as the “Nottingham Physiological Simulator,” through which better understanding of ARDS progression can be gleaned, and take advantage of the growing volume of medical datasets available for research (i.e., “big data”) and the advances in ML to develop, train, and optimise the modelling approaches. Additionally, the onset of the COVID-19 pandemic while this Ph.D. research was ongoing provided a similar application field to ARDS, and made further ML research in medical diagnosis applications possible. Finally, we leverage the available Modular Supercomputing Architecture (MSA) developed as part of the Dynamical Exascale Entry Platform~- Extreme Scale Technologies (DEEP-EST) EU Project to scale up and speed up the modelling processes. This Ph.D. Project is one element of the Smart Medical Information Technology for Healthcare (SMITH) project wherein the thesis research can be validated by clinical and medical experts (e.g. Uniklinik RWTH Aachen).Notkun vélnámsaðferða (ML) í læknavísindum er ekki ný af nálinni og hafa nokkrar greinar verið birtar um rannsóknir á því sviði. Þessar rannsóknir hafa hjálpað til við að greina læknisfræðilegar myndir, búa til svörunarlíkön fyrir hjarta- og æðakerfi og spá fyrir um útkomu sjúkdóma meðal margra annarra notkunarmöguleika. Markmið þessarar doktorsrannsóknar er að beita slíkum ML aðferðum við greiningu á bráðu andnauðarheilkenni (ARDS), alvarlegan sjúkdóm sem hrjáir um 1 af hverjum 10.000 sjúklingum á heimsvísu á ári hverju með lífshættulegum afleiðingum. Til að framkvæma þessa greiningu notum við áður þróaðar aðferðir við líkanasmíði, s.s. „Nottingham Physiological Simulator“, sem nota má til að auka skilning á framvindu ARDS-sjúkdómsins. Við nýtum okkur vaxandi umfang læknisfræðilegra gagnasafna sem eru aðgengileg til rannsókna (þ.e. „stórgögn“), framfarir í vélnámi til að þróa, þjálfa og besta líkanaaðferðirnar. Þar að auki hófst COVID-19 faraldurinn þegar doktorsrannsóknin var í vinnslu, sem setti svipað svið fram og ARDS og gerði frekari rannsóknir á ML í læknisfræði mögulegar. Einnig nýtum við tiltæka einingaskipta högun ofurtölva, „Modular Supercomputing Architecture“ (MSA), sem er þróuð sem hluti af „Dynamical Exascale Entry Platform“ - Extreme Scale Technologies (DEEP-EST) verkefnisáætlun ESB til að kvarða og hraða líkanasmíðinni. Þetta doktorsverkefni er einn þáttur í SMITH-verkefninu (e. Smart Medical Information Technology for Healthcare) þar sem sérfræðingar í klíník og læknisfræði geta staðfest rannsóknina (t.d. Uniklinik RWTH Aachen)

    Current Insights on Lipid-Based Nanosystems

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    Lipid-based nanosystems, including solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs), cationic lipid nanoparticles, nanoemulsions, and liposomes, have been extensively studied to improve drug delivery through different administration routes. The main advantages of these systems are their ability to protect, transport, and control the release of lipophilic and hydrophilic molecules (either small-molecular-weight molecules or macromolecules); the use of generally recognized as safe (GRAS) excipients that minimize the toxicity of the formulations; and the possibility to modulate pharmacokinetics and enable the site-specific delivery of encapsulated payloads. In addition, the versatility of lipid-based nanosystems has further been demonstrated for the delivery of vaccines, the protection of active cosmetic ingredients, and the improvement of moisturizing properties of cosmetic formulations.Lipid-based nanosystems are well established and there are already different commercially approved formulations for various human disorders. This success has paved the way for the diversification of the pipeline of development, to address unmet medical needs for several indications, such as cancer, neurological disorders, and autoimmune, genetic, and infectious diseases.This Special Issue aims to update readers on the latest research on lipid-based nanosystems, both at the preclinical and clinical levels. A series of 15 articles (six reviews and nine studies) is presented, with authors from 12 different countries, showing the globality of the investigations that are being carried out in this area

    Novel Analytical Methods in Food Analysis

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    This reprint provides information on the novel analytical methods used to address challenges occurring at academic, regulatory, and commercial level. All topics covered include information on the basic principles, procedures, advantages, limitations, and applications. Integration of biological reagents, (nano)materials, technologies, and physical principles (spectroscopy and spectrometry) are discussed. This reprint is ideal for professionals of the food industry, regulatory bodies, as well as researchers

    Current Insights on Lipid-Based Nanosystems

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    Lipid-based nanosystems, including solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs), cationic lipid nanoparticles, nanoemulsions, and liposomes, have been extensively studied to improve drug delivery through different administration routes. The main advantages of these systems are their ability to protect, transport, and control the release of lipophilic and hydrophilic molecules (either small-molecular-weight molecules or macromolecules); the use of generally recognized as safe (GRAS) excipients that minimize the toxicity of the formulations; and the possibility to modulate pharmacokinetics and enable the site-specific delivery of encapsulated payloads. In addition, the versatility of lipid-based nanosystems has further been demonstrated for the delivery of vaccines, the protection of active cosmetic ingredients, and the improvement of moisturizing properties of cosmetic formulations.Lipid-based nanosystems are well established and there are already different commercially approved formulations for various human disorders. This success has paved the way for the diversification of the pipeline of development, to address unmet medical needs for several indications, such as cancer, neurological disorders, and autoimmune, genetic, and infectious diseases.This Special Issue aims to update readers on the latest research on lipid-based nanosystems, both at the preclinical and clinical levels. A series of 15 articles (six reviews and nine studies) is presented, with authors from 12 different countries, showing the globality of the investigations that are being carried out in this area

    A geo-informatics approach to sustainability assessments of floatovoltaic technology in South African agricultural applications

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    South African project engineers recently pioneered the first agricultural floating solar photovoltaic tech nology systems in the Western Cape wine region. This effort prepared our country for an imminent large scale diffusion of this exciting new climate solver technology. However, hydro-embedded photovoltaic sys tems interact with environmentally sensitive underlying aquatic ecosystems, causing multiple project as sessment uncertainties (energy, land, air, water) compared to ground-mounted photovoltaics. The dissimi lar behaviour of floatovoltaic technologies delivers a broader and more diversified range of technical advan tages, environmental offset benefits, and economic co-benefits, causing analytical modelling imperfections and tooling mismatches in conventional analytical project assessment techniques. As a universal interna tional real-world problem of significance, the literature review identified critical knowledge and methodology gaps as the primary causes of modelling deficiencies and assessment uncertainties. By following a design thinking methodology, the thesis views the sustainability assessment and modelling problem through a geo graphical information systems lens, thus seeing an academic research opportunity to fill critical knowledge gaps through new theory formulation and geographical knowledge creation. To this end, this philosophi cal investigation proposes a novel object-oriented systems-thinking and climate modelling methodology to study the real-world geospatial behaviour of functioning floatovoltaic systems from a dynamical system thinking perspective. As an empirical feedback-driven object-process methodology, it inspired the thesis to create new knowledge by postulating a new multi-disciplinary sustainability theory to holistically characterise agricultural floatovoltaic projects through ecosystems-based quantitative sustainability profiling criteria. The study breaks new ground at the frontiers of energy geo-informatics by conceptualising a holistic theoretical framework designed for the theoretical characterisation of floatovoltaic technology ecosystem operations in terms of the technical energy, environmental and economic (3E) domain responses. It campaigns for a fully coupled model in ensemble analysis that advances the state-of-the-art by appropriating the 3E theo retical framework as underpinning computer program logic blueprint to synthesise the posited theory in a digital twin simulation. Driven by real-world geo-sensor data, this geospatial digital twin can mimic the geo dynamical behaviour of floatovoltaics through discrete-time computer simulations in real-time and lifetime digital project enactment exercises. The results show that the theoretical 3E framing enables project due diligence and environmental impact assessment reporting as it uniquely incorporates balanced scorecard performance metrics, such as the water-energy-land-food resource impacts, environmental offset benefits and financial feasibility of floatovoltaics. Embedded in a geoinformatics decision-support platform, the 3E theory, framework and model enable numerical project decision-supporting through an analytical hierarchy process. The experimental results obtained with the digital twin model and decision support system show that the desktop-based parametric floatovoltaic synthesis toolset can uniquely characterise the broad and diverse spectrum of performance benefits of floatovoltaics in a 3E sustainability profile. The model uniquely predicts important impact aspects of the technology’s land, air and water preservation qualities, quantifying these impacts in terms of the water, energy, land and food nexus parameters. The proposed GIS model can quantitatively predict most FPV technology unknowns, thus solving a contemporary real-world prob lem that currently jeopardises floating PV project licensing and approvals. Overall, the posited theoretical framework, methodology model, and reported results provide an improved understanding of floating PV renewable energy systems and their real-world behaviour. Amidst a rapidly growing international interest in floatovoltaic solutions, the research advances fresh philosophical ideas with novel theoretical principles that may have far-reaching implications for developing electronic, photovoltaic performance models worldwide.GeographyPh. D. (Geography

    Sustainability in Viticulture - Agroforestry and Organic Wine Production in the Mosel Region, Germany

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    Since the mid-20th century, there has been an increasing industrialization and intensification of land use in the agricultural sector. This development is accompanied by increased productivity in thriving economies since World War II and the overall growth of the world population. In addition to providing widespread food supply, the industrialization of the agricultural sector has also led to high resource consumption and lasting environmental damage. As a result, particularly since the 1980s and 1990s, there has been a growing societal awareness of the negative impacts of agriculture on the environment and resources. In the wine-growing Mosel Region in Rhineland-Palatinate, which consists of vineyards along the Mosel, Saar, and Ruwer rivers, a few winemakers began to seek alternatives to conventional industrial cultivation methods and pesticides in the early 1980s. They adapted their agricultural practices in favor of sustainability and increasingly organized themselves in growing eco-associations. These few winemakers became part of a growing community of sustainable winegrowers in Germany. Nowadays, sustainably produced wines constitute a rapidly growing share of the German and international wine market. The ecologically managed vineyard area in Germany has also expanded since then, although machines and pesticides continue to be used due to the vulnerability of grapes to diseases and pests. This poses a fundamental dilemma for the operations of eco-winemakers who are striving to adapt their viticulture practices, in addition to the impacts of climate change. One of the practices playing a central role in the exploration of sustainability practices in this work is agroforestry. Agroforestry distinguishes between silvoarable and silvopastoral systems. Silvoarable systems combine trees or perennial plants and shrubs with crops. Silvopastoral systems combine trees and perennial plants and shrubs with animal husbandry. Agroforestry is a term coined in the 20th century, but its origins can be traced back to early forms of land use, beginning with Neolithic cultures about 10,000 years ago. Agroforestry practices such as grazing in orchards or planting hedges to protect crops have been maintained over centuries but have increasingly taken a back seat due to the intensification and mechanization of agriculture in the 20th century. The combination of trees with field crops or animals in agroforestry systems offers various synergistic effects, such as shading vineyards with trees planted in the rows of vines. This helps maintain soil moisture in dry spells and protects grapes from sunburn. Agroforestry systems also enable savings in labor and costs, as animal husbandry provides a continuous supply of dung and weed control through grazing. Given the changes in growing conditions due to climate change and societal demand for sustainable methods in food production, agroforestry is regaining importance and is being investigated as an innovative practice in this dissertation on sustainability development in viticulture. In addition to the application of agroforestry methods in viticulture, the use of fungus-resistant grape varieties (FRVs) is also addressed in this dissertation. The selection of grape varieties for viticulture has historically focused primarily on the quantity and quality of plant material. However, due to climate change as well as pests and diseases, the grapevine is facing increasing pressure. Therefore, beginning in the 19th century, grape varieties with resistance to diseases were deliberately bred. Nowadays, FRVs are gaining attractiveness for both winemakers and consumers, as they allow for a substantial reduction in pesticide use, thereby reducing costs and labor. At the same time, the avoidance of harmful chemicals opens up the possibility of a sustainable use of animals in the vineyard. Agroforestry systems in conjunction with Piwis thus offer opportunities to make wine production sustainable and future-oriented, while also diversifying the product range of winemakers through new grape varieties and animal products. This cumulative dissertation comprises three research articles based on qualitative interviews. Article 1 examined the use of agroforestry systems in viticulture and their potential to address the impacts of climate change on wine production and distribution. Planting rows of vines with trees led to more stable product quality during dry years, simultaneously resulting in reduced sunburn damage and soil erosion. However, based on their experiences, the interviewed winemakers favored a better-adapted agroforestry system that could also be part of value creation or combined with agro-photovoltaics. Article 2 investigated ecosystem services in silvopastorally managed vineyards, where animals grazed the vineyard, reducing weeds and significantly reducing labor. The silvopastoral vineyards increased biodiversity, wine quality, and enabled an expanded product portfolio. Article 3 dealt with alternative food networks and FRVs in sustainable viticulture. Alternative food networks aim to eliminate intermediaries in value chains and promote more direct interactions between producers and consumers. The article concludes that fungus-resistant grape varieties not only facilitate the management of vineyards but also the establishment of short value chains. The articles of this dissertation collectively demonstrate that agroforestry systems, FRVs, and alternative food networks offer opportunities for advancing sustainable viticulture
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