4,179 research outputs found

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Computational and experimental studies on the reaction mechanism of bio-oil components with additives for increased stability and fuel quality

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    As one of the world’s largest palm oil producers, Malaysia encountered a major disposal problem as vast amount of oil palm biomass wastes are produced. To overcome this problem, these biomass wastes can be liquefied into biofuel with fast pyrolysis technology. However, further upgradation of fast pyrolysis bio-oil via direct solvent addition was required to overcome it’s undesirable attributes. In addition, the high production cost of biofuels often hinders its commercialisation. Thus, the designed solvent-oil blend needs to achieve both fuel functionality and economic targets to be competitive with the conventional diesel fuel. In this thesis, a multi-stage computer-aided molecular design (CAMD) framework was employed for bio-oil solvent design. In the design problem, molecular signature descriptors were applied to accommodate different classes of property prediction models. However, the complexity of the CAMD problem increases as the height of signature increases due to the combinatorial nature of higher order signature. Thus, a consistency rule was developed reduce the size of the CAMD problem. The CAMD problem was then further extended to address the economic aspects via fuzzy multi-objective optimisation approach. Next, a rough-set based machine learning (RSML) model has been proposed to correlate the feedstock characterisation and pyrolysis condition with the pyrolysis bio-oil properties by generating decision rules. The generated decision rules were analysed from a scientific standpoint to identify the underlying patterns, while ensuring the rules were logical. The decision rules generated can be used to select optimal feedstock composition and pyrolysis condition to produce pyrolysis bio-oil of targeted fuel properties. Next, the results obtained from the computational approaches were verified through experimental study. The generated pyrolysis bio-oils were blended with the identified solvents at various mixing ratio. In addition, emulsification of the solvent-oil blend in diesel was also conducted with the help of surfactants. Lastly, potential extensions and prospective work for this study have been discuss in the later part of this thesis. To conclude, this thesis presented the combination of computational and experimental approaches in upgrading the fuel properties of pyrolysis bio-oil. As a result, high quality biofuel can be generated as a cleaner burning replacement for conventional diesel fuel

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    The demographic echo of war and social mobility in Russia

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    Defence date: 11 June 2019Examining Board: Prof. Fabrizio Bernardi, European University Institute (Supervisor); Prof. Juho Härkönen, European University Institute; Prof. Theodore P. Gerber, University of Wisconsin-Madison; Prof. Jan O. Jonsson, Nuffield College, University of Oxford / Swedish Institute for Social Research (SOFI), Stockholm UniversityRecurring variations in cohort size (also known as ‘baby booms’ and ‘baby busts’) are known to be a factor affecting the fortunes of people born to different cohorts. However, existing evidence in this regard comes overwhelmingly from Western countries, while little is known about the impact of similar processes in Russia despite the fact it is the country in which the Second World War has left, perhaps, the most sizeable and far-reaching demographic trace. Apart from immense casualties and devastating effects on the health of the surviving population, it had a major impact on the fertility of several generations that sent ripples through Russia’s population age structure for years to come – the phenomenon that Russian demographers metaphorically refer to as the ‘demographic echo of war’. In this study, I explore the effects of this peculiar demographic context on individual social mobility both during the Soviet and the post-Soviet period, using rich data from the Max Planck Education and Employment Survey and Russian Longitudinal Monitoring Survey. In general, I find that the demographic echo of war affected the individual mobility patterns of Russians in several intricate ways, although the magnitude of its impact does not warrant the conclusion that it had a decisive effect on people’s fortunes. The study also makes several theoretical contributions to existing scholarship on the relationship between changes in population age structure and the process of social stratification

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Valorización sostenible de lodos y residuos agroalimentarios para la producción de hidrógeno, metano y biofertilizante: transición a la economía circular

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    Los principales retos de la sociedad actual son la lucha contra la contaminación, el cambio climático y las emisiones de gases efecto invernadero asociadas, principalmente, a la creciente demanda energética mundial. La búsqueda de soluciones sostenibles ha supuesto un importante foco de investigación para la búsqueda de fuentes energéticas alternativas a los combustibles fósiles. Además, aún siguen sin resolverse los problemas ligados a la generación incontrolada de residuos orgánicos de diferentes procedencias. Así, por un lado, la creciente implementación de plantas de tratamiento de aguas residuales ha conllevado al aumento en la generación de lodos de depuradora difíciles y costosos de gestionar por dichas plantas. Por otro lado, en Andalucía y, concretamente, en la comarca de Jerez de la Frontera, el sector vitivinícola genera grandes cantidades de desechos procedentes de la producción del vino. Asimismo, otro sector generador de residuos en auge lo componen las granjas y explotaciones avícolas debido a la creciente demanda de exportación cárnica. Estas instalaciones generan grandes cantidades de estiércol avícola que requieren una adecuada gestión previa a su aplicación al suelo. La presente Tesis Doctoral propone un tratamiento conjunto de lodos de depuradora y residuos agroalimentarios (vinazas de vino y estiércol avícola). El proceso seleccionado para este fin ha sido la digestión anaerobia aplicada mediante diferentes tecnologías: procesos monoetapa y sistemas con separación simultánea de fases de temperatura y de microorganismos. Esta última tecnología requiere dos digestores conectados en serie: en el primer digestor se fomenta la hidrólisis/acidogénesis del sustrato para generar biohidrógeno, mientras que en segundo se opera en condiciones metanogénicas para la obtención de biometano y biofertilizante. Adicionalmente, se analizan diferentes temperaturas de operación, termofílica y mesofílica, de forma que se optimice tanto la generación de H2 y CH4 en el biogás como la producción de un digestato de características adecuadas para su uso como biofertilizante. El estudio y optimización de estas tecnologías anaerobias permitirá la gestión simultanea de tres desechos generados en el entorno cercano a la comarca del Jerez, solucionando el problema ambiental derivado de la generación de los mismos y generando, fruto del proceso, productos de gran valor añadido tales como biohidrógeno, biometano y biofertilizante. Con ello se consigue cerrar el ciclo productivo y enfocar el problema desde el prisma de la economía circular. La presente Tesis Doctoral se presenta como compendio de nueve publicaciones científicas en las cuales se recogen los resultados obtenidos en cada etapa experimental desarrollada. Se comienza con un análisis bibliométrico del estado del arte de la digestión anaerobia (recogido en la revista International Journal of Hydrogen Energy), seguido de la exposición y análisis de los resultados más relevantes obtenidos en el desarrollo de cada etapa de experimentación a escala de laboratorio (7 publicaciones científicas en revistas de alto impacto en el sector). Adicionalmente, se incluye una publicación en la que se analiza la viabilidad tecno-económica de la tecnología anaerobia para la co-digestión anaerobia de lodos y residuos agroalimentarios en tres diferentes escenarios. Los primeros ensayos experimentales abordados tienen como objetivo determinar la proporción óptima de estiércol avícola que habría que añadir al lodo de depuradora y a la vinaza para generar biogás, así como los rangos de temperatura de operación más apropiados en cuanto a producción de biohidrógeno y biometano. Las mezclas de sustratos analizadas consisten en proporciones de lodo y vinaza (50:50) y diferentes proporciones de estiércol avícola. Las mezclas en las proporciones seleccionadas, se someten a test normalizados de potencial de biodegradación para la obtención de biohidrógeno o biometano, según el caso, a diferentes temperaturas operativas. Concretamente, se estudia el potencial bioquímico de hidrógeno (BHP) de las mezclas en tres rangos de temperatura diferentes (mesófilico (35ºC), termofílico (55ºC) e hipertermofílico (70ºC). Adicionalmente se desarrollan estudios paralelos para identificar el potencial bioquímico de metano (BMP) en rango mesofílico. Los resultados obtenidos muestran que la proporción de lodo:vinaza:estiércol avícola óptima es 49.5:49.5:1, con el máximo rendimiento de hidrógeno (27,10 mLH2/gSV) en rango de temperatura termofílico. Para los otros rangos de temperatura estudiados, la producción de hidrógeno es prácticamente nula. Con los efluentes procedentes de los ensayos de fermentación ácida de la etapa anterior se configuran nuevos test para identificar el potencial bioquímico de metano de cada efluente ácido operando en rango mesofílico. Los resultados experimentales indican que el máximo rendimiento de metano se alcanza con el efluente procedente de los test BHP operando en rango hipertermofílico, llegando a alcanzar valores 117,00 y 113,00 mLCH4/gSV para las mezclas lodo:vinaza (50:50) y lodo:vinaza:estiércol avícola (49,5:49,5:1), respectivamente. En cambio, los tests BMP desarrollados con el efluente ácido de los tests BHP en rango termofílico presentan menores valores, con un máximo de 52,05 mLCH4/gSV para la mezcla con estiércol avícola en proporción 49,5:49,5:1 lodo:vinaza:estiércol avícola. El análisis cinético de los resultados experimentales pone de manifiesto que la producción de hidrógeno se ajusta al modelo de Cone mientras que los datos experimentales de producción de metano se ajustan al modelo de Gompertz modificado. Estos ensayos permitieron el desarrollo de tres artículos científicos, de los cuales dos se encuentran publicados en la revista científica Journal of Hydrogen Energy y otro bajo revisión en la revista Journal of Cleaner Production. Posteriormente, y en base a estos resultados, se diseñan nuevos experimentos en régimen de alimentación semicontinuo a escala de laboratorio utilizando reactores de tres litros. Estos ensayos permiten optimizar el funcionamiento del proceso de co-digestión de lodo y vinaza así como de la tri-digestión lodos+vinaza+estiércol avícola en rango mesofílico para diferentes tiempos hidráulicos de retención (THR). Asimismo, se llevan a cabo estudios paralelos para optimizar los procesos de digestión en fases separadas termofílico-acidogénico y mesofílico-metanogénico del proceso de tri-digestión de lodo, vinaza y estiércol avícola. Los rangos de temperatura seleccionados son consecuencia de los resultados previos, en los que la mayor producción de hidrógeno se registraba para temperaturas termofílicas. El estudio y análisis comparativo de los principales resultados del estudio abordado para los procesos monoetapa ha sido publicado en la revista internacional Fuel. Los resultados indican que la tecnología de tri-digestión anaerobia en rango mesofílico, operando con una mezcla de sustratos de lodo, vinaza y estiércol avícola en proporción 49.5:49.5:1 es la que obtiene la mayor eficiencia depurativa en base a demanda química de oxígeno total (DQOT) (51%), sólidos volátiles (SV) (57%) y rendimiento de metano (262,00 mLCH4/gSV). Además, un análisis de patógenos pone de manifiesto la ausencia de patógenos en el efluente digerido, por lo que las condiciones de operación ensayadas consiguen la higienización del efluente haciéndolo apto para su catalogación como biosólido clase A según la Agencia de Protección Ambiental de EEUU (US EPA). Las dos siguientes publicaciones recogen los resultados obtenidos en las etapas de optimización de las fases termofílica-acidogénica y mesofílica-metanogénica de forma individual. Para ello, se abordan ensayos a diferentes THR (10, 8, 6, 5, 4 y 3 días) hasta observar desestabilización de los sistemas, correspondientes a tasas de carga orgánica (OLR) aplicadas de 2,93; 3,48; 4,62; 6,18; 6,82 y 7,75 gSV/L/d. Para cada THR se evalúan los rendimientos de generación de biohidrógeno y biometano, las eficacias depurativas, actividad microbiana y concentración de patógenos. Los resultados obtenidos indican que el THR para una operación óptima de la fase acidogénica es de 5 días, mientras que para fase metanogénica es de 12 días. Así, la primera fase termofílica-acidogénica se alcanza un valor de rendimiento de hidrógeno máximo de 40,41 mLH2/gSV con una actividad microbiana 5,64e-11LH2/cells para el THR de 5 días. En la etapa mesofílica-metanogénica, la máxima eficiencia de depuración de SV (56%) y el máximo rendimiento de metano registrado (391,00 mLCH4/gSV) se obtiene a 12 días-THR con la mayor eliminación de patógenos en el efluente. Estas condiciones permiten obtener un efluente que cumple con las especificaciones para ser clasificado como biosólido clase A según la US EPA. Es interesante resaltar la correlación positiva que se establece entre el aumento de OLR aplicada al sistema y el aumento de la actividad microbiana en el mismo. Estos estudios han permitido la elaboración de dos artículos científicos de los cuales uno se encuentra bajo revisión en la revista científica Biomass and Bioenergy y el otro fue publicado en la revista Chemical Engineering Journal. Los siguientes estudios abordados en régimen semicontinuo de co-digestión de lodo, vinaza y estiércol avícola a escala de laboratorio van dirigidos a realizar un estudio comparativo del funcionamiento de las tecnologías seleccionadas: co-digestión anaerobia convencional en una sola etapa y dos diferentes rangos de temperatura (termofílica y mesofílica) y co-digestión anaerobia con separación de fases y de temperatura. Las condiciones que se analizan son las óptimas de operación para los procesos monoetapa (13 días-THR) y para el proceso con separación de fases (20 días-THR). Los resultados obtenidos mostraron que la separación de fases acidogénica-metanogénica y 20 días-THR presenta beneficios tales como una mayor eficiencia depurativa medida como DQOT (65%), siendo este valor un 26% y 17% superior a los datos obtenidos en condiciones el proceso monoetapa termofílico y mesofílico respectivamente. La eficacia de eliminación de SV alcanza el 90%, mientras que los reactores monoetapa arrojan valores de 41% y 43% de eliminación de SV, para las condiciones termofílica y mesofílica, respectivamente. Asimismo, se registra un mayor rendimiento de metano (320,00 mLCH4/gSV) al que hay que sumar la obtención de biohidrógeno en la primera fase del proceso. En conclusión, la tecnología con separación de fases de temperatura y microorganismos supone una mejora tecnológica a considerar por las estaciones depuradoras que pretendan mejorar su eficacia energética. Los resultados de este estudio fueron publicados en la revista científica Fuel. Finalmente, con el fin de comprobar la viabilidad de la implementación de esta tecnología, se lleva a cabo un estudio tecno-económico que abarca a las tres condiciones de co-digestión anaerobia estudiadas (co-digestión anaerobia mesofílica monoetapa, termofílica monoetapa, y co-digestión anaerobia con separación de fases de temperaturas y de microorganismos) aplicando herramientas de estudio de rentabilidad económica de cara a su implementación a escala industrial. El estudio confirma la viabilidad tecno-económica del proceso de separación de fases, mostrando los mejores datos de rentabilidad en su implementación a escala industrial frente a la co-digestión anaerobia en una sola etapa. Los resultados de este estudio se recogen en la novena publicación científica en la revista Internacional Journal of Environmental Management que forma parte de esta Memoria de Tesis Doctoral

    On the Utility of Representation Learning Algorithms for Myoelectric Interfacing

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    Electrical activity produced by muscles during voluntary movement is a reflection of the firing patterns of relevant motor neurons and, by extension, the latent motor intent driving the movement. Once transduced via electromyography (EMG) and converted into digital form, this activity can be processed to provide an estimate of the original motor intent and is as such a feasible basis for non-invasive efferent neural interfacing. EMG-based motor intent decoding has so far received the most attention in the field of upper-limb prosthetics, where alternative means of interfacing are scarce and the utility of better control apparent. Whereas myoelectric prostheses have been available since the 1960s, available EMG control interfaces still lag behind the mechanical capabilities of the artificial limbs they are intended to steer—a gap at least partially due to limitations in current methods for translating EMG into appropriate motion commands. As the relationship between EMG signals and concurrent effector kinematics is highly non-linear and apparently stochastic, finding ways to accurately extract and combine relevant information from across electrode sites is still an active area of inquiry.This dissertation comprises an introduction and eight papers that explore issues afflicting the status quo of myoelectric decoding and possible solutions, all related through their use of learning algorithms and deep Artificial Neural Network (ANN) models. Paper I presents a Convolutional Neural Network (CNN) for multi-label movement decoding of high-density surface EMG (HD-sEMG) signals. Inspired by the successful use of CNNs in Paper I and the work of others, Paper II presents a method for automatic design of CNN architectures for use in myocontrol. Paper III introduces an ANN architecture with an appertaining training framework from which simultaneous and proportional control emerges. Paper Iv introduce a dataset of HD-sEMG signals for use with learning algorithms. Paper v applies a Recurrent Neural Network (RNN) model to decode finger forces from intramuscular EMG. Paper vI introduces a Transformer model for myoelectric interfacing that do not need additional training data to function with previously unseen users. Paper vII compares the performance of a Long Short-Term Memory (LSTM) network to that of classical pattern recognition algorithms. Lastly, paper vIII describes a framework for synthesizing EMG from multi-articulate gestures intended to reduce training burden

    20th SC@RUG 2023 proceedings 2022-2023

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    Modelação e Negociação de Flexibilidade em Comunidades de Energia Renovável

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    The progressive replacement of traditional generation resources with intermittent resources has reduced the available supply-side flexibility and increased the need to unlock flexibility on the demand-side. At the same time, the rising electricity consumption in residential buildings requires an analysis of the potential flexibility of the loads within them to contribute to the operation needs of electrical grids. Lastly, regulations governing self consumption have allowed end consumers to form energy communities based on local electricity markets. This is an additional incentive to define strategies for trading available flexibility at local level, in separate but simultaneously integrated structures within wholesale electricity markets. The proposed dissertation work focuses on studying the flexibility of energy production and consumption by prosumers within a Renewable Energy Community (REC). The objective is to investigate how residential flexibility can be determined, modeled, and aggregated for trading in a local market created for this purpose. The work to be developed will present a two-stage model that determines residential technical flexibility and establishes a local market only for its transaction. In the first stage, the optimal scheduling of domestic devices (flexible units or FUs) for each prosumer is determined, serving as a baseline for comparison, along with the technical limits of flexibility (maximum and minimum possible consumption profiles) for each FU. In the second stage, a market model is established only for flexibility exchanges. The technical flexibility determined in the first stage is offered to the Community Manager (CM) as flexibility offer, with an associated price. This entity acts as an aggregator and simultaneously as the operator of the local market. At this level, the Distribution System Operator (DSO) submits its flexibility requirements for the next day to the CM, who is responsible for executing the clearing process. The pricing of the flexibility offered by prosumers in the market is based on the base energy tariff they are subject to, which corresponds to the cost of their optimal scheduling obtained in the first stage, without considering this flexibility. Therefore, offering flexibility becomes an incentive to reduce prosumers energy costs or increase their utility, complementing their mere participation in energy markets. A case study based on a renewable energy community with a strong penetration of emerging technologies is used to validate and demonstrate the relevance of the proposed approach in terms of determining and activating residential FU flexibility. The obtained results show that participation in the local flexibility market leads to a reduction in prosumers energy costs, around 4.5%, in average. It can be an incentive for prosumers to join RECs that would not only have local energy trading structures but also mechanisms for negotiating and sharing flexibility. In addition, it was evidenced that the impact of electric vehicle chargers and battery energy storage systems on the total flexibility offered and accepted in the market is much greater than that the impact of other small loads studied. This not only constitutes an incentive for the study of the operational flexibility of these resources but also for investments in these emerging technologies.A substituição progressiva dos recursos de geração tradicionais por recursos intermitentes tem reduzido a flexibilidade disponível do lado da oferta e aumentado a necessidade de desbloqueá-la do lado da procura. Ao mesmo tempo, o aumento do consumo de eletricidade nos edifícios residenciais obriga a que seja analisada a flexibilidade potencial das cargas que o constituem, de modo a contribuir para as necessidades de operação das redes elétricas. Por último, a regulamentação do autoconsumo, tem permitido aos consumidores finais constituir comunidades energéticas baseadas em mercados locais de eletricidade. Isto torna ainda mais importante a definição de estratégias para comercializar a flexibilidade disponível a esse nível, em estruturas de mercado local separadas, mas simultaneamente integradas nos mercados grossistas de eletricidade. O trabalho proposto para dissertação assenta no estudo da flexibilidade da produção e consumo de energia por parte dos prosumidores de uma Comunidade de Energia Renovável. O objetivo é estudar como a flexibilidade residencial pode ser determinada, modelada e agregada de modo a ser transacionada num mercado local criado para esse fim. Assim, o trabalho a ser desenvolvido apresentará um modelo de dois estágios que determina a flexibilidade técnica residencial e cria um mercado local exclusivo para transaciona-la. Numa primeira fase, determina-se o escalonamento óptimo dos dispositivos domésticos (unidades flexíveis ou UF) de cada prosumidor, o que constitui uma baseline de comparação, bem como os limites técnicos de flexibilidade (perfis de consumo máximos e mínimos possíveis) de cada UF. Num segundo estágio, é estabelecido um modelo de mercado apenas para trocas de flexibilidade. A flexibilidade técnica determinada no primeiro estágio é disponibilizada ao Gestor de Comunidade (CM), enquanto oferta de flexibilidade, com um preço associado. Esta entidade desempenha as funções de agregador e simultaneamente de operador do mercado local. A este nível, o Operador do Sistema de Distribuição (ORD) submete os seus requisitos de flexibilidade, para o dia seguinte, ao CM, que é responsável pelo executar o clearing. A precificação da flexibilidade oferecida pelos prosumidores em mercado é feita com base no valor da tarifa base de energia a que estão sujeitos, que corresponde ao custo do seu escalonamento ótimo, obtido no primeiro estágio, que não considera essa mesma flexibilidade. Portanto, oferecer flexibilidade torna-se um incentivo para reduzir os custos energéticos dos prosumidores ou aumentar a sua utilidade, o que complementa a sua mera participação nos mercados de energia. Um caso de estudo baseado numa comunidade de energia com forte penetração de tecnologias emergentes é utilizado e valida a metodologia desenvolvida. Para além disso é evidenciada a relevância da abordagem proposta em termos de determinação e ativação da flexibilidade de UFs residenciais os impactos das mesmas no fecho de mercado. Os resultados evidenciam que participação no mercado local de flexibilidade induz uma redução dos custos energéticos dos prosumidores, na casa 4.5%, em média. O impacto dos carregadores de veículos elétricos e dos sistemas de armazenamento de energia em baterias na flexibilidade total oferecida e aceite em mercado é muito superior ao de outras pequenas cargas estudadas. Tudo isto pode vir a resultar num incentivo ao investimento nos recursos referidos, bem como à associação de prosumidores em comunidades de energia renovável, onde para além de estruturas locais de comercialização de energia, existam outras que permitam a negociação e partilha de flexibilidade

    Computational Approaches to Drug Profiling and Drug-Protein Interactions

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    Despite substantial increases in R&D spending within the pharmaceutical industry, denovo drug design has become a time-consuming endeavour. High attrition rates led to a long period of stagnation in drug approvals. Due to the extreme costs associated with introducing a drug to the market, locating and understanding the reasons for clinical failure is key to future productivity. As part of this PhD, three main contributions were made in this respect. First, the web platform, LigNFam enables users to interactively explore similarity relationships between ‘drug like’ molecules and the proteins they bind. Secondly, two deep-learning-based binding site comparison tools were developed, competing with the state-of-the-art over benchmark datasets. The models have the ability to predict offtarget interactions and potential candidates for target-based drug repurposing. Finally, the open-source ScaffoldGraph software was presented for the analysis of hierarchical scaffold relationships and has already been used in multiple projects, including integration into a virtual screening pipeline to increase the tractability of ultra-large screening experiments. Together, and with existing tools, the contributions made will aid in the understanding of drug-protein relationships, particularly in the fields of off-target prediction and drug repurposing, helping to design better drugs faster
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