2,767 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

    Climate Change and Critical Agrarian Studies

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    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    Air Quality Research Using Remote Sensing

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    Air pollution is a worldwide environmental hazard that poses serious consequences not only for human health and the climate but also for agriculture, ecosystems, and cultural heritage, among other factors. According to the WHO, there are 8 million premature deaths every year as a result of exposure to ambient air pollution. In addition, more than 90% of the world’s population live in areas where the air quality is poor, exceeding the recommended limits. On the other hand, air pollution and the climate co-influence one another through complex physicochemical interactions in the atmosphere that alter the Earth’s energy balance and have implications for climate change and the air quality. It is important to measure specific atmospheric parameters and pollutant compound concentrations, monitor their variations, and analyze different scenarios with the aim of assessing the air pollution levels and developing early warning and forecast systems as a means of improving the air quality and safeguarding public health. Such measures can also form part of efforts to achieve a reduction in the number of air pollution casualties and mitigate climate change phenomena. This book contains contributions focusing on remote sensing techniques for evaluating air quality, including the use of in situ data, modeling approaches, and the synthesis of different instrumentations and techniques. The papers published in this book highlight the importance and relevance of air quality studies and the potential of remote sensing, particularly that conducted from Earth observation platforms, to shed light on this topic

    Radiation-directed production of chemical reagents and petroleum additives from waste organic feedstocks

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    Nuclear cogeneration is the collation of co-processes that aims to improve the sustainability, overall efficiency, and profitability of nuclear power by producing alternative products alongside electricity. A range of existing cogeneration processes explores the use of waste stream process heat for a variety of processes including district heating and desalination. However, the direct application of under-utilized ionization energy has yet to be fully realized. This thesis is a study on the potential application of ionizing radiation from nuclear facilities towards the radiolytic production of organic chemicals derived from waste renewable feedstocks. Here we show that glycerol, a notable waste feedstock from biodiesel production can be converted into acetol (hydroxyacetone) or solketal which are textile and biofuel additives, respectively using ionizing radiation from a 250-kW research fission reactor. The radical-initiated chain reaction for hydroxyl acetone (acetol) production is optimised to produce the highest G value (2.7 ± 0.4 µmol J−1) and mass productivity (~1 %) to be reported in the available radiolysis literature. A previously unreported radiolytic product, solketal, which is a valuable biofuel additive is produced radiolytically using ternary glycerol, acetone, and water mixtures with G-values of 1.5 ± 0.2 µmol J−1 at 50 kGy. Empirical data showed a preference for low LET, low dose rate, γ-ray emissions such as those from spent fuel was found to be favourable for acetol and solketal production. Simulating three production scenarios with MCNP models for preferential solketal production found that a spent fuel facility consisting of ~1710 elements showed the largest production capacity at 57.4 ± 5.6 t year−1 due to the high volume available to be irradiated. Extrapolating to a theoretical European production network involving ~180 equivalent SFP facilities based on relative reactor power, a total of (1.3 ± 0.1) × 104 t year−1 of solketal could be produced, contributing to (2.5 ± 0.2) × 108 litres year−1 to a (95% petroleum, 5% solketal) fuel blend. While this represents only ~0.3 % of total transport fuels consumed within the EU, it presents a pioneering process that could be feasible if G-values and mass productivities were improved upon

    A First Course in Causal Inference

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    I developed the lecture notes based on my ``Causal Inference'' course at the University of California Berkeley over the past seven years. Since half of the students were undergraduates, my lecture notes only require basic knowledge of probability theory, statistical inference, and linear and logistic regressions

    Subgroup discovery for structured target concepts

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    The main object of study in this thesis is subgroup discovery, a theoretical framework for finding subgroups in data—i.e., named sub-populations— whose behaviour with respect to a specified target concept is exceptional when compared to the rest of the dataset. This is a powerful tool that conveys crucial information to a human audience, but despite past advances has been limited to simple target concepts. In this work we propose algorithms that bring this framework to novel application domains. We introduce the concept of representative subgroups, which we use not only to ensure the fairness of a sub-population with regard to a sensitive trait, such as race or gender, but also to go beyond known trends in the data. For entities with additional relational information that can be encoded as a graph, we introduce a novel measure of robust connectedness which improves on established alternative measures of density; we then provide a method that uses this measure to discover which named sub-populations are more well-connected. Our contributions within subgroup discovery crescent with the introduction of kernelised subgroup discovery: a novel framework that enables the discovery of subgroups on i.i.d. target concepts with virtually any kind of structure. Importantly, our framework additionally provides a concrete and efficient tool that works out-of-the-box without any modification, apart from specifying the Gramian of a positive definite kernel. To use within kernelised subgroup discovery, but also on any other kind of kernel method, we additionally introduce a novel random walk graph kernel. Our kernel allows the fine tuning of the alignment between the vertices of the two compared graphs, during the count of the random walks, while we also propose meaningful structure-aware vertex labels to utilise this new capability. With these contributions we thoroughly extend the applicability of subgroup discovery and ultimately re-define it as a kernel method.Der Hauptgegenstand dieser Arbeit ist die Subgruppenentdeckung (Subgroup Discovery), ein theoretischer Rahmen für das Auffinden von Subgruppen in Daten—d. h. benannte Teilpopulationen—deren Verhalten in Bezug auf ein bestimmtes Targetkonzept im Vergleich zum Rest des Datensatzes außergewöhnlich ist. Es handelt sich hierbei um ein leistungsfähiges Instrument, das einem menschlichen Publikum wichtige Informationen vermittelt. Allerdings ist es trotz bisherigen Fortschritte auf einfache Targetkonzepte beschränkt. In dieser Arbeit schlagen wir Algorithmen vor, die diesen Rahmen auf neuartige Anwendungsbereiche übertragen. Wir führen das Konzept der repräsentativen Untergruppen ein, mit dem wir nicht nur die Fairness einer Teilpopulation in Bezug auf ein sensibles Merkmal wie Rasse oder Geschlecht sicherstellen, sondern auch über bekannte Trends in den Daten hinausgehen können. Für Entitäten mit zusätzlicher relationalen Information, die als Graph kodiert werden kann, führen wir ein neuartiges Maß für robuste Verbundenheit ein, das die etablierten alternativen Dichtemaße verbessert; anschließend stellen wir eine Methode bereit, die dieses Maß verwendet, um herauszufinden, welche benannte Teilpopulationen besser verbunden sind. Unsere Beiträge in diesem Rahmen gipfeln in der Einführung der kernelisierten Subgruppenentdeckung: ein neuartiger Rahmen, der die Entdeckung von Subgruppen für u.i.v. Targetkonzepten mit praktisch jeder Art von Struktur ermöglicht. Wichtigerweise, unser Rahmen bereitstellt zusätzlich ein konkretes und effizientes Werkzeug, das ohne jegliche Modifikation funktioniert, abgesehen von der Angabe des Gramian eines positiv definitiven Kernels. Für den Einsatz innerhalb der kernelisierten Subgruppentdeckung, aber auch für jede andere Art von Kernel-Methode, führen wir zusätzlich einen neuartigen Random-Walk-Graph-Kernel ein. Unser Kernel ermöglicht die Feinabstimmung der Ausrichtung zwischen den Eckpunkten der beiden unter-Vergleich-gestelltenen Graphen während der Zählung der Random Walks, während wir auch sinnvolle strukturbewusste Vertex-Labels vorschlagen, um diese neue Fähigkeit zu nutzen. Mit diesen Beiträgen erweitern wir die Anwendbarkeit der Subgruppentdeckung gründlich und definieren wir sie im Endeffekt als Kernel-Methode neu

    Researches regarding the evolution, magnitude and complexity of the impact generated by the economic activities on the East Jiu River

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    Ongoing development of modern society, based on consumption of goods and services, leads to the increase of compulsoriness of economic agents to face market requirements by increasing the degree of local and regional industrialization. Establishment of new economic activities generates negative pressures on the environment and surface waters, generating increased pollution, manifested by vulnerability of aquatic ecosystems to stressors. Preliminary studies carried out within the doctoral thesis entitled 'Research on the evolution, magnitude and complexity of the impact of economic activities on the East Jiu' include information on characteristic elements of the East Jiu River basin, in accordance with the Water Framework Directive 2000/60/CE. The objectives of the field research aimed to identify economic activities in the eastern Jiu Valley generating an impact on the environment (especially the mining industry, but also timber exploitation and processing, local agriculture, animal husbandry and waste storage), establishing a quarterly monitoring program of the river basin, identification of flora and fauna species and identification of areas vulnerable to potential pollution. Based on observations made in situ and on information obtained from the evolution process of the monitoring program, the appropriate methodologies for assessing physical-chemical and ecological quality of the water were selected. Study of the evolution of the impact generated by economic activities on the East Jiu was carried out by mathematical modelling, with finite volumes, of the East Jiu River basin and plotting of pollutant dispersion maps. The magnitude and complexity of impact generated by economic activities was studied by using a complex system based on fuzzy logic, designed based on interactions between natural and artificial systems, between physical-chemical indicators of water and ecosystem. The research carried out substantiates in development of necessary technical measures to reduce the impact generated by economic activities located in eastern Jiu Valley, without significantly changing the hydrodynamics of the river basin. Following research, during different research stages, methods, techniques and tools were designed and accomplished with the help of which, water and aquatic ecosystems’ quality can be assessed, as well as the impact generated by human activity on the Jiu River, at a given moment and/or continuously.:CONTENT ACKNOWLEDGEMENTS SUMMARY LIST OF FIGURES LIST OF TABLES ABBREVIATIONS INTRODUCTION PURPOSE OF THE THESIS AND RESEARCH METHODOLOGY CHAPTER 1 THE EAST JIUL RIVER HYDROGRAPHIC BASIN 1.1. Soil and subsoil of the Eastern part of Jiu Valley 1.2. Climate description of the Eastern part of Jiu Valley 1.3. Geology particularities of the Eastern part of Jiu Valley 1.4. Groundwater features of the Eastern part of Jiu Valley 1.5. Flora and fauna of the Eastern part of Jiu Valley CHAPTER 2 SOURCES OF IMPACT ON THE QUALITY OF WATER, RIPARIAN, TERRESTRIAL AND AQUATIC ECOSYSTEMS 2.1. Mining industry 2.2. Wood processing industry in the Eastern part of Jiu Valley 2.3. Urban agriculture and local animal husbandry 2.4. Inappropriate urban household waste storage CHAPTER 3 MONITORING PROGRAM AND METHODS OF EVALUATION OF THE QUALITY OF THE EAST JIUL RIVER 3.1. Establishment of monitoring (control) sections 3.2. Monitoring program of the East Jiu River basin 3.3. Sampling, transport and analysis of water samples 3.4. Methodology used to establish the water quality CHAPTER 4 QUALITY ASSESSMENT OF WATER IN THE EASTERN JIU HYDROGRAPHIC BASIN 4.1. Section 1 - Jieț River - upstream of household settlements (blank assay) 4.2. Section 2 - East Jiu River - in the area of Tirici village 4.3. Section 3 - Răscoala brook - before the confluence with East Jiu River 4.4. Section 4 - East Jiu River - after the confluence with the Răscoala brook 4.5. Section 5 - Taia River - upstream of the confluence with East Jiu River 4.6. Section 6 - East Jiu River - before the confluence with the Taia River 4.7. Section 7 - East Jiu River - after the confluence with the Taia River 4.8. Section 8 - Jiet River downstream of household settlements 4.9. Section 9 - East Jiu River - after the confluence with the Jieț River 4.10. Section 10 - East Jiu River - before the confluence with Banița River 4.11. Section 11 - Roşia River - upstream of household settlements 4.12. Section 12 - Bănița River - after the confluence with the Roșia River 4.13. Section 13 - East Jiu River - after the confluence with the Banița River 4.14. Section 14 - Maleia River - before the confluence with East Jiu River 4.15. Section 15 - Slătioara River - before the confluence with East Jiu River 4.16. Section 16 – East Jiu River - before the confluence with West Jiu River CHAPTER 5 INFLUENCES OF PHYSICAL-CHEMICAL FACTORS ON AQUATIC ICHTHYOFAUNA IN THE EAST JIU RIVER BASIN 5.1. Total suspended solids and aquatic ecosystems 5.2. Acidity or basicity reaction of surface watercourses 5.3. Aquatic ecosystem requirements for gas oversaturation 5.4. Nitrogenous compounds in watercourse 5.5. Phenols, aquatic ecosystems and water quality CHAPTER 6 ANALYSIS OF THE IMPACT GENERATED BY ECONOMIC ACTIVITIES IN THE EASTERN PART OF JIU VALLEY 6.1. Impact analysis of mining industry in the Eastern Part of Jiu Valley 6.2. The general impact of Eastern Jiu Valley dumps to water quality 6.3. Research on effective infiltration in the Eastern part of Jiu Valley 6.4. Research on groundwater quality in the Eastern part of Jiu Valley 6.5. Analysis of the impact generated by local micro-agriculture 6.6. Analysis of the impact generated by deforestation and wood processing 6.7. Analysis of the impact generated by non-compliant landfilling of waste CHAPTER 7 EVOLUTION OF THE IMPACT GENERATED BY ECONOMIC ACTIVITIES IN THE EASTERN JIU VALLEY 7.1. Analysis of the dynamic elements of the watercourse - RMA2 mode 7.2. Analysis of pollutants concentration evolution in the water course - RMA4 module 7.3. Computational field and composition of the energy model of the East Jiu River 7.4. Extension and evolution of the impact generated by economic activities on the East Jiu River 7.5. Extension and evolution of the impact caused by organic pollution of the East Jiu River CHAPTER 8 MAGNITUDE AND COMPLEXITY OF THE IMPACT GENERATED BY ECONOMIC ACTIVITIES IN THE EASTERN JIU VALLEY 8.1. Definition of input linguistic variables 8.2. Linguistic outputs of the fuzzy interference system 8.3. Defining the Black Box set of rules 8.4. Proficiency testing of complex systems based on fuzzy logic 8.5. While it is all about the wheel do not forget about the cube CONCLUSIONS AND PERSONAL CONTRIBUTIONS REFERENCE

    The Forward Physics Facility at the High-Luminosity LHC

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    High energy collisions at the High-Luminosity Large Hadron Collider (LHC) produce a large number of particles along the beam collision axis, outside of the acceptance of existing LHC experiments. The proposed Forward Physics Facility (FPF), to be located several hundred meters from the ATLAS interaction point and shielded by concrete and rock, will host a suite of experiments to probe standard model (SM) processes and search for physics beyond the standard model (BSM). In this report, we review the status of the civil engineering plans and the experiments to explore the diverse physics signals that can be uniquely probed in the forward region. FPF experiments will be sensitive to a broad range of BSM physics through searches for new particle scattering or decay signatures and deviations from SM expectations in high statistics analyses with TeV neutrinos in this low-background environment. High statistics neutrino detection will also provide valuable data for fundamental topics in perturbative and non-perturbative QCD and in weak interactions. Experiments at the FPF will enable synergies between forward particle production at the LHC and astroparticle physics to be exploited. We report here on these physics topics, on infrastructure, detector, and simulation studies, and on future directions to realize the FPF's physics potential

    The Forward Physics Facility at the High-Luminosity LHC

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