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Developing techniques for assessing various risks and calculating probabilities of ruin and survival are exciting topics for mathematically-inclined academics. For practicing actuaries and financial engineers, the resulting insights have provided enormous opportunities but also created serious challenges to overcome, thus facilitating closer cooperation between industries and academic institutions. In this book, several renown researchers with extensive interdisciplinary research experiences share their thoughts that, in one way or another, contribute to the betterment of practice and theory of decision making under uncertainty. Behavioral, cultural, mathematical, and statistical aspects of risk assessment and modelling have been explored, and have been often illustrated using real and simulated data. Topics range from financial and insurance risks to security-type risks, from one-dimensional to multi- and even infinite-dimensional risks.

aggregate discounted claims --- Markovian arrival process --- partial integro-differential equation --- covariance --- multivariate gamma distribution --- multiplicative background risk model --- aggregate risk --- individual risk model --- collective risk model --- risk measure --- cumulative Parisian ruin --- stochastic orders --- surplus process --- renewal process --- discounted aggregate claims --- copulas --- archimedean copulas --- background risk --- systematic risk --- transfer function --- information processing --- order statistic --- concomitant --- ruin probability --- dual risk model --- constant interest rate --- integral equation --- Laplace transform --- numerical approximation --- maximal tail dependence --- clustering --- financial time series --- weighted cuts --- copula --- national culture --- survival analysis --- hazard model --- rating migrations --- advanced measurement approach --- confidence interval --- Monte Carlo --- operational risk --- value-at-risk --- central limit theorem --- insurance --- max-stable random fields --- rate of spatial diversification --- reinsurance --- risk management --- risk theory --- spatial dependence --- spatial risk measures and corresponding axiomatic approach --- n/a

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Landscapes have long been viewed as ‘multifunctional’, integrating ecological, economic, sociocultural, historical, and aesthetic dimensions. Landscape science and public awareness in Europe have been progressing in leaps and bounds. The challenges involved in landscape-related issues and fields, however, are multiple and refer to landscape stewardship and protection, as well as to the development of comprehensive theoretical and methodological approaches, in tandem with public sensitization and participatory governance and in coordination with appropriate top-down planning and policy instruments. Landscape-scale approaches are fundamental to the understanding of past and present cultural evolution, and are now considered to be an appropriate spatial framework for the analysis of sustainability. Methods and tools of landscape analysis and intervention have also gone a long way since their early development in Europe and the United States. Although significant progress has been made, there remain many issues which are understudied or not investigated at all—at least in a Mediterranean context. This Special Issue addresses the application of landscape theory and practice in the Eastern Mediterranean and mainly, but not exclusively, reports on the outcomes of an international conference held in Jordan, in December 2015, with the title “Landscapes of Eastern Mediterranean: Challenges, Opportunities, Prospects and Accomplishments”. The focus of this Special Issue, landscapes of the Eastern Mediterranean region, thus constitutes a timely area of research interest, not only because these landscapes have so far been understudied, but also as a rich site of strikingly variegated, long-standing multicultural human–environmental interactions. These interactions, resting on and taking shape through millennia of continuity in tradition, have been striving to adapt to technological advances, while currently juggling with manifold and multilayered socioeconomic and climate–environmental crises.

Cyprus --- landscape archaeology --- sacred space --- political power --- economy --- religion --- ideology --- ancient sanctuaries --- churches --- comparative study --- landforms --- Landscape Character Assessment (LCA) --- Land Description Unit (LDU) --- spatial distributions --- topography --- geographical information system --- historical maps --- landscape changes --- rural land --- classification --- GIS --- LCA --- Land Description Units --- mapping --- planning --- typology --- Landscape Risk Assessment Model --- Landscape Decision Support System --- East Med landscape --- landscape --- stakeholders’ analysis --- Eastern Mediterranean --- Greek-speaking --- Arabic-speaking --- Arabic landscape and garden art --- Byzantine landscape and garden art --- cultural sustainability --- political sustainability --- Twain-born Border Lord --- landscape character assessment --- multi-functional landscapes --- planning --- UK --- Cyprus --- participatory --- governance --- landscape --- public realm --- urban environment --- local authority --- Lebanon --- Mediterranean --- n/a

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The sustainable governance of water resources relies on processes of multi-stakeholder collaborations and interactions that facilitate knowledge co-creation and social learning. Governance systems are often fragmented, forming a barrier to adequately addressing the myriad of challenges affecting water resources, including climate change, increased urbanized populations, and pollution. Transitions towards sustainable water governance will likely require innovative learning partnerships between public, private, and civil society stakeholders. It is essential that such partnerships involve vertical and horizontal communication of ideas and knowledge, and an enabling and democratic environment characterized by informal and open discourse. There is increasing interest in learning-based transitions. Thus far, much scholarly thinking and, to a lesser degree, empirical research has gone into understanding the potential impact of social learning on multi-stakeholder settings. The question of whether such learning can be supported by forms of serious gaming has hardly been asked. This Special Issue critically explores the potential of serious games to support multi-stakeholder social learning and collaborations in the context of water governance. Serious games may involve simulations of real-world events and processes and are challenge players to solve contemporary societal problems; they, therefore, have a purpose beyond entertainment. They offer a largely untapped potential to support social learning and collaboration by facilitating access to and the exchange of knowledge and information, enhancing stakeholder interactions, empowering a wider audience to participate in decision making, and providing opportunities to test and analyze the outcomes of policies and management solutions. Little is known about how game-based approaches can be used in the context of collaborative water governance to maximize their potential for social learning. While several studies have reported examples of serious games, there is comparably less research about how to assess the impacts of serious games on social learning and transformative change.

simulations --- serious games --- Q-method --- integrated water resources management --- policy analysis --- nexus --- participatory modelling --- serious game --- system dynamics --- water-food-land-energy-climate --- active learning --- drinking water --- role-play --- stakeholder collaboration --- Water Safety Plan --- water supply --- serious games --- social simulation --- social learning --- relational practices --- river basin management --- water governance --- multi-party collaboration --- stakeholders --- experimental social research --- Maritime Spatial Planning (MSP) --- stakeholder participation --- serious game --- Blue Growth --- Good Environmental Status --- serious games (SGs) --- water management --- value change --- transcendental values --- social equity --- sustainability --- Schwartz’s Value Survey (SVS) --- Integrated Water Resource Management (IWRM) --- psychosocial perspectives --- decision-making processes --- assessment --- educational videogames --- online games --- water --- ecology education --- drinking water management --- peri-urban --- institutions --- gaming-simulation --- groundwater --- capacity building --- serious games --- planning support systems --- knowledge co-creation --- sustainability --- maritime spatial planning --- serious gaming --- flood --- urban --- rural --- infrastructure --- decision making --- serious games --- role-playing games --- learning-based intervention --- transformative change --- social learning --- aquaculture --- Mekong Delta --- mangrove --- gamification --- serious games --- water governance --- stakeholder participation --- sustainability --- game-based learning --- integrated water resource management (IWRM) --- natural resource management --- simulation --- serious game --- social learning --- stakeholder collaboration --- sustainability --- water governance

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Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.

memristor --- artificial synapse --- neuromorphic computing --- memristor-CMOS hybrid circuit --- temporal pooling --- sensory and hippocampal responses --- cortical neurons --- hierarchical temporal memory --- neocortex --- memristor-CMOS hybrid circuit --- defect-tolerant spatial pooling --- boost-factor adjustment --- memristor crossbar --- neuromorphic hardware --- memristor --- compact model --- emulator --- neuromorphic --- synapse --- STDP --- pavlov --- neuromorphic systems --- spiking neural networks --- memristors --- spike-timing-dependent plasticity --- RRAM --- vertical RRAM --- neuromorphics --- neural network hardware --- reinforcement learning --- AI --- neuromorphic computing --- multiscale modeling --- memristor --- optimization --- RRAM --- simulation --- memristors --- neuromorphic engineering --- OxRAM --- self-organization maps --- synaptic device --- memristor --- neuromorphic computing --- artificial intelligence --- hardware-based deep learning ICs --- circuit design --- memristor --- RRAM --- variability --- time series modeling --- autocovariance --- graphene oxide --- laser --- memristor --- crossbar array --- neuromorphic computing --- wire resistance --- synaptic weight --- character recognition --- neuromorphic computing --- Flash memories --- memristive devices --- resistive switching --- synaptic plasticity --- artificial neural network --- spiking neural network --- pattern recognition --- strongly correlated oxides --- resistive switching --- neuromorphic computing --- transistor-like devices --- artificial intelligence --- neural networks --- resistive switching --- memristive devices --- deep learning networks --- spiking neural networks --- electronic synapses --- crossbar array --- pattern recognition

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This special volume offers a snapshot of the latest developments in mineral exploration, in particular, geophysical, geochemical, and computational methods. It reflects the cutting-edge applications of geophysics and geochemistry, as well as novel technologies, such as in artificial intelligence and hyperspectral exploration, methods that have profoundly changed how exploration is conducted. This special volume is a representation of these cutting-edge and pioneering methods to consider and conduct exploration, and should serve both as a valuable compendium of the most innovative exploration methodologies available and as a foreshadowing of the form of future exploration. As such, this volume is of significant importance and would be useful to any exploration geologist and company

one-class support vector machine --- bat algorithm --- mineral prospectivity mapping --- receiver operating characteristic --- area under the curve --- Youden index --- MT --- gravity --- elastic-net regularization --- cross-gradients constraints --- joint inversion --- LCT --- pegmatite --- lithium --- exploration --- targeting --- gravity gradiometry --- magnetotelluric --- model-space --- data-space --- joint inversion --- mineral resource classification --- JORC code --- limestone deposit --- project pursuit multivariate transform --- (co)-simulation --- laser-induced breakdown spectroscopy --- LIBS --- geochemical exploration --- geochemical fingerprinting --- micro-imaging --- grain size analysis --- mineral texture --- CSAMT --- dual-frequency IP --- mineral exploration --- Vosges --- Variscan orogeny --- Natzwiller --- Kagenfels --- granite --- lithium --- tungsten --- niobium --- exploration targeting --- stream sediments --- QEMSCAN® --- Jinchuan Cu–Ni sulfide deposit --- deep mineral exploration --- CSAMT --- inversion --- 3D mineral prospectivity modeling --- spatial analysis --- GA-SVR --- epithermal gold deposits --- Axi deposit