1. Modello Fattura
2. Dichiarazione Dei Redditi Modello Unico
3. Modello Unico 2008

When decoding emotional and social signals in everyday life, we are usually provided with emotional cues from more than one sensory modality, mainly vision and hearing. Although the auditory information is relevant in communicating emotional and social meanings, vision seems to be the most important sensory modality for the extraction of socio-emotional stimulus qualities. Indeed, most information about others’ emotions - ranging from the most basic (i.e., inference of intentions from eye gaze direction) to the most advanced (i.e., understanding others’ personality traits, such as trustworthiness, or mental states through their eyes) - is extracted by looking at their face and body. In light of the above, one would expect early blindness to affect the capacity to make inferences about others’ emotional states and personality traits, given that these inferences have to be based on non-visual information.

Most research on this issue comes from qualitative observations within social and educational psychology though, whereas experimental evidence is more scarce.The present project will merge multidisciplinary, integrated tasks and highly innovative methodological approaches to shed light on the impact of blindness on social cognition capacities at both the functional and neural level. In particular, we will combine solid behavioral paradigms, functional magnetic resonance (fMRI) and transcranial magnetic stimulation (TMS), with which the three principal investigators have a specific and longstanding experience. Many decisions in modern societies have a very complex scientific basis. Clinicians have to choose between different drugs for treating a patient.

Central bankers have to forecast the evolution of financial markets, and to control the amount of money that circulates in a society. Physicists have to evaluate the impact of continued CO2 emissions for life on the planet. All these decisions are based on the forecasts of scientific models, and sometimes, their predictions reach a great degree of exactness (e.g., in identifying high-risk hospital patients and allocating resources efficiently).In short, how does science based on uncertain models contribute to good decisions?Our project investigates the interface between modeling and decision-making. We develop an understanding of how scientific models function, how they advance our knowledge despite their intrinsic uncertainty, and how they are interpreted in a decision context. More specifically, we focus on the following three questions, which correspond to our main targets:1. How can highly idealized and intrinsically uncertain scientific models be successful in prediction?2. Why can we trust and accept scientific models in spite of their intrinsic uncertainty and how should we factor in this uncertainty?3.

How should we synthesize actuarial, model-based judgment with human expertise in making practical decisions?In answering these three questions, our projects integrates foundational philosophical analysis (e.g., rational criteria for theory acceptance), formal and conceptual analysis, and case studies about construction and use of models in a number of relevant scientific disciplines like financial economics and evidence-based medicine. This project brings together a variety of competences and methods to address an issue that has recently gained attention by scholars working at the intersection of different disciplines: economics, psychology, sociology, cognitive sciences. The issue under debate concerns the interaction between cognitive modes and prosocial behavior, i.e., the extent to which individual behavior is beneficial to the society as a whole. The basic question is: which cognitive mode is more likely to foster prosocial behavior?

Up to now, such a debate is lively and far from being set. Our society is increasingly data-driven. Smartphones, computers, and smart sensors acquire, store, and transmit myriads of data, more and more easily. A major challenge for scientists is how to best use the information contained in the data.

In particular, control theorists need to better understand how to design algorithms that take automatic decisions on the basis of data, both recorded offline and acquired in real-time from sensors. The aim of this project is to provide fundamental scientific advances on how to design control systems directly from data. Both deforestation and pollution are key factors in global climate change. This is because forests are natural pollution sinks able to capture carbon dioxide emissions from the atmosphere and convert them into oxygen, which both humans and animals can breathe safely.

Unless proper countermeasures are taken, deforestation represents a big problem for climate: by cutting down forests without replacing the trees that are removed, the absorption efficiency of such carbon sinks is reduced, with possible catastrophic consequences. To counteract these effects, suitable policies are needed, such as reductions in the emission levels, and reforestation.This project complements the few available attempts in the literature to unify deforestation and pollution issues. In several fields of engineering and technology there is a growing demand of fast and accurate numerical simulations. New industrial and bio-medical products need to be efficiently designed, tested, and certified at different scales. New bio-inspired and engineered materials, conceived to reduce costs or to improve performance, must be evaluated in different working scenarios.

The tragic consequences of natural hazards should be reduced by means of accurate predictions of possible interactions with structures and infrastructures. In all these circumstances (just to name a few), numerical simulations are expected to play a fundamental role, despite the complexity of these problems and the limitations of modern computer architectures.The present project aims at fostering new advancements in the development of modern computational tools to bridge the gap between real-life problems and state-of-the-art engineering approaches. These systems are, and will be more and more, pervasive and ubiquitous, also in safety-critical situations. Examples range from robots and drones delivering goods to self-driving vehicles and smart buildings. These systems must satisfy safety requirements, and meet performance goals. It is fundamental to keep all such requirements into account from the design phase, to reduce the cost of development and avoid dangerous situations coming from unexpected requirement violation.Model-based engineering (MBE) of CPS is challenging due to some specific features of these systems: they act in an open physical space environment, which is subject to unpredictable changes.

Hence, approaches to MBE of CPS have to explicitly take into account the uncertainty and the spatial structure of the environment in which they act. In this project, we will propose a framework in this direction, dealing with spatially distributed CPS in an uncertain environment. The framework will allow engineers to describe the system and the requirements with a high-level, UML like specification language, which will be automatically converted in a domain specific language from which a formal executable model of the system and a formalization of requirements will be extracted.

Smart systems are large-scale, physically-distributed services where different kinds of data-collection sensors are used to supply information employed to efficiently manage assets and resources, and provide efficient operations. These systems are increasingly pervasive and interact extensively with their environment. It is thus crucial that unexpected and possibly dangerous situations be avoided. Hence, there is a strong need of techniques to guarantee that systems are trustworthy.

Here trustworthiness is a holistic property, encompassing different characteristics (safety, security, integrity, availability, correctness, reliability, resilience) that are not addressed in isolation but as a whole at system level.The goal of the project is the development and the experimentation of a novel methodology for the specification, implementation and validation of trustworthy smart systems based on formal methods. The BRIGHT -“Brilliant Researchers Impact on Growth Health and Trust in research“ project aims at enhancing the visibility and perception of researchers among the general population in Tuscany, simultaneously with all the European Researchers’ Night (ERN) initiatives.BRIGHT will bring the researchers in the squares and streets of the historical centres of the many cities invloved in the project, and will open the doors of the laboratories to the citizens.

They will have a chance to talk to the researchers, appreciate their preparation and passion, and listen from their own words about the positive impact of the results of their research on the quality of our lives. “Researchers make your life better!” is the guiding principle stemming from the passion, the enthusiasm and hard intellectual work of researchers’ daily work and how this contributes to the wellbeing of the general population.BRIGHT focuses on creating awareness on the important role played by researchers in addressing the great challenges ahead, such as health and wellbeing, new technologies, sustainable development, the physical and biological world, cultural heritage.

Sight has always been regarded as the most important sense for humans to interact with the surrounding world and acquire knowledge Nonetheless, individuals who are visually-deprived since birth show perceptual, cognitive and social skills that are to a great extent comparable to those found in sighted individuals. While historically research has focused mostly on the brain plastic reorganization that occurs in blind individuals, only more recently scientists from distinct labs across the world, including our own, have developed innovative strategies to understand how much vision is a mandatory prerequisite for the brain fine morphological architecture to develop and function. As a whole, the studies conducted to date in sighted and congenitally blind individuals have provided solid and novel evidence that most of the association 'visual' cortical areas develop independently from any visual experience and are able to process non-visual information as well, a property that we named supramodality.Two of the most important questions rising on the functional features of a supramodal functional organization are:1. Does a supramodal recruitment subserve similar mental strategies in sighted and blind?2. How is unisensory information integrated into a supramodal, more ‘conceptual’ representation?

This project will merge two multidisciplinary, integrated tasks with state-of-the-art methodological approaches to characterize the neural substrates that subtend the supramodal cortical organization and answer to these still-open questions. The capacity to have an aesthetic experience is a characteristic human trait and it is the result of a complex interplay between sensation, emotions and cognition.

Although the concept of “beauty” has been the object of centuries of philosophical and psychological debate, only in recent decades has it been the object of an organized cognitive neuroscience research program. Although recent developments are very promising, more work is needed to uncover the functional and neural mechanisms mediating the aesthetic experience.Our project aims to use neuroimaging (IMT Unit) and brain stimulation (Milano-Bicocca Unit) techniques to shed light on the neural network underpinning aesthetic experience for different categories of visual stimuli. Furthermore, consistent research points to the existence of several multisensory brain regions that process information regardless the sensory modality in which the input is acquired. Focusing here on touch, whether aesthetic appreciation of the same artworks in the visual and haptic modality lead to similar neural activations is not known.

We will investigate this aspect, also considering a related fascinating question, i.e., whether the mechanisms mediating aesthetic experience in the blind brain are the same as in case of a normally sighted brain. What is “beauty” for a blind person’s brain? (Milano-Bicocca and Pisa Unit have a long experience in studying blindness).Moreover, experience of and sensitivity to aesthetics has received little attention in the clinical setting. We know that aesthetical appreciation of paintings is spared in dementia and schizophrenia affects art perception, but very little is known for instance about major depression disorder, of which a core symptom is anhedonia. Can exposure to beautiful artistic images reduce non-physical pain? This hypothesis is grounded in neuroimaging and brain stimulation evidence showing that aesthetic viewing increases activity in the left dorsolateral prefrontal cortex that is usually hypo-activated in depressed patients.Finally, although a certain simplification is inherent to experimental neuroscience (that necessarily tend to look at “average” experiences), an interdisciplinary approach in which knowledge from art history and experimental methods converge is needed (against reductionism).

The project strongly aims to open a constructive dialogue between disciplines, such as art history and neuroscience, that have been often considered as having far (or even incompatible) approaches. The IMT-Lucca unit will have a fundamental role in assisting the other units in the selection of stimuli and paradigms and in critically contextualizing the findings about neural correlates of aesthetic appreciation in a broader perspective in which art history and philosophy are considered.Research Unit:. SoftPro project will study and design soft synergy-based robotics technologies to develop new prostheses, exoskeletons, and assistive devices for upper limb rehabilitation, which will greatly enhance the efficacy and accessibility to a greater number of users.

Building on solid methodological bases, SoftPro will produce a significant social impact, promoting advanced robot prosthetic and assistive technology “from bench to bedside”; but it will also introduce disruptively new, admittedly risky but potentially high-impact ideas and paradigms. Long-living software systems are typically available in a rich set of variants to deal with differing customer requirements and application contexts. Furthermore, users are often given the possibility to change to a different configuration online to dynamically adapt to varying environmental conditions. In addition to satisfying functional requirements, such changes are to preserve existing service-level agreements. The focus of this project is to define a methodology for expressing system variability and its impact on performance.

One of the most pressing and fascinating challenges scientists face today, is understanding the complexity of our globally interconnected society. The big data arising from the digital breadcrumbs of human activities promise to let us scrutinize the ground truth of individual and collective behaviour at an unprecedented detail and scale. There is an urgent need to harness these opportunities for scientific advancement and for the social good. The main obstacle to this accomplishment, besides the scarcity of data scientists, is the lack of a large-scale open infrastructure, where big data and social mining research canbe carried out.

To this end, SoBigData proposes to create the Social Mining & Big Data Ecosystem: a research infrastructure (RI) providing an integrated ecosystem for ethic-sensitive scientific discoveries and advanced applications of social data mining on the various dimensions of social life, as recorded by “big data”. Building on several established national infrastructures, SoBigData will open up new research avenues in multiple research fields, including mathematics, ICT, and human, social and economic sciences, by enabling easy comparison, re-use and integration of state-of-the-art big social data, methods, and services, into new research. It will not only strengthen the existing clusters of excellence in social data mining research, but also create a pan-European, inter-disciplinary community of social data scientists, fostered by extensive training, networking, and innovation activities.

In addition, as an open research infrastucture, SoBigData will promote repeatable and open science. Although SoBigData is primarily aimed at serving the needs of researchers, the openly available datasets and open source methods and services provided by the new research infrastructure will also impact industrial and other stakeholders (e.g. Government bodies, non-profit organisations, funders, policy makers). The BRIGHT project aims at enhancing the visibility and perception of researchers among the general population in the Tuscany Region, simultaneously with all the European Researchers’ Night (ERN) initiatives. BRIGHT acronym means “Brilliant Researchers Impact on Growth Health and Trust in research”, wishing to underline the positive aspect of the research activity in order to convey a positive message to the general public. BRIGHT focuses on creating awareness on the important role played by researchers in addressing the great challenges ahead, such as health and wellbeing, new technologies, sustainable development, physical and biological challenges, cultural heritage.

BRIGHT will be successful if it will be able to convince the population of the IMPACT of the researchers and the research's products for the development of the society, and to make people TRUST the researchers instead of being driven away by hoaxes with no scientific basis. The OpenMaker project aims to create a transformational and collaborative ecosystem that fosters collective innovations within the European manufacturing sector and drives it towards more sustainable business models, production processes, products, and governance systems.Building on the paradigm of Open Manufacturing, the project will achieve this goal by bringing together traditional manufacturers and digital-savvy makers and engaging in the process also universities, local authorities, civil society organisations and policy-makers.

Increased global competition and an urgent need to address sustainability and resource-efficiency of operations force European industries and large-scale infrastructure operators to look for efficient real-time decision-making systems that allow them to react rapidly, consistently and effectively to a continually changing economical and environmental landscape. Advances in optimization tools and the emergence of new highly pervasive, cheap, and reconfigurable wireless sensing technologies now motivate the research for novel distributed layers of plant management that are highly coordinated through the plant-wide circulation of information. The WIDE project aims at developing a rigorous framework for advanced control and real-time optimization of truly large-scale and spatially distributed processes, based on the integrated use of distributed model predictive control and wireless sensor feedback.While the technologies and methodologies investigated in WIDE are general enough for many contexts, the project employs its unique access to an operational European city water distribution network to prove the effectiveness of the new concept in real practice. The research unit will develop three lines of research related to political institutions, social conflicts and economic policies. At a general level, the aim of this unit is to analyze the endogenous formation of political institutions and beliefs. We want to build dynamic general equilibrium models where institutions and different kind of beliefs affect each other and change endogenously over time in order to better understand the formation of institutions and beliefs in the society.

Modello Fattura

The three directions of our research are the following. A first line focus on the study of the co-evolution of political institutions (such as democracies and dictatorships) and political ideology in terms of democratic culture. A second direction concerns the analysis of the interactions between religion and technology adoption with special attention on their effects on economic growth and fiscal policy outcomes. A third direction of this research focus on the effects of different political ideologies on the behavior of politicians, with special attention on their choices about reforms affecting their constituencies.

Si intende dotare la Biblioteca del materiale bibliografico necessario al potenziamento della ricerca e della didattica in tutti gli ambiti disciplinari della Scuola, mettere a disposizione dei cittadini e degli studenti lucchesi servizi e materiale non posseduti da altre biblioteche lucchesi (banche dati e riviste elettroniche specializzate), potenziando in tal modo il ruolo di punto di riferimento culturale per Lucca. Si prevede inoltre di rafforzare i rapporti di interscambio culturale con gli altri enti che operano nel campo della cultura e dell’educazione presenti sul territorio locale. ICT developments both enable and also enforce large-scale, highly-connected systems in society and industry. Knowledge to cope with these emerging systems is lacking. HYCON2 will stimulate and establish the long-term integration of the European research community, leading institutions and industry in the strategic field of control of complex, large-scale, and networked dynamical systems. It will interconnect scattered groups to create critical mass and complementarity, and will provide the necessary visibility and communication with the European industries.

HYCON2 will assess and coordinate basic and applied research, from fundamental analytical properties of complex systems to control design methodologies with networking, self-organizing and system-wide coordination. HYCON2 has identified several applications domains to motivate, integrate, and evaluate research in networked control.

These domains are ground and aerospace transportation, electrical power networks, process industries, and biological and medical systems. FOC is a Scientific Project Financed by FET OPEN Scheme in the field of Information and Communication Technology by the European Commission. The research topic is to understand and possibly forecast systemic risk and global financial instabilities We want to provide a novel integrated and network-oriented approach to the issue. On one hand, we will offer a theoretical framework to measure systemic risk in global financial market and financial networks. On the other hand, we will deliver an ICT collaborative platform for monitoring systemic fragility and the propagation of financial distress across institutions and markets around the world. Experts will be able to evaluate algorithms and models to forecast financial crises as well as visualise interactively possible future scenarios. The EU electric power system experiences a fundamental change in the quasi-monopolistic, top-down oriented, stable, and reasonable predictable arrangements of the past.

It now spans continents, has hundreds of millions consumers and hundreds of thousand producers, from nuclear power plants to privately-owned and operated badly predictable renewables such as solar cells, wind and microturbines and operates in an increasingly liberalized market. These developments pose huge challenges for its reliable and economic operation. This proposal focuses on the real-time power imbalance in the power net, which arises as a consequence of errors in the prediction of both production and demand. As this power imbalance will increase both in size and in frequency, presents arrangements to cope with this imbalance are no longer valid. They are neither reliable nor economic anymore. This project proposes an advanced ICT and control framework for ancillary services (reserve capacity) which allows a more intelligent solution by giving consumers and producers clear, real-time financial incentives to adapt their consumption/production according to the actual needs of the power system. This design is based on a distributed control structure, enabled by a fast ICT infrastructure and advanced control theory to reliably and economically deal with the necessary ancillary services.

Decisions by consumers, producers, power exchanges and TSOs can be taken locally, based on local or national preferences and regulation. Still, the embedded incentives of the proposed framework can guarantee that all these local decisions together contribute to the global objectives of the EE power net: a reliable electric energy supply at the lowest costs. Instead of investing in additional expensive and environment-unfriendly reserve production or storage facilities with a low utilization rate, the reliability and e4conomy are enforced by intelligent ICT and control. Future software-intensive systems, such as sensor networks, power grids, satellite and robot swarms, will generally exhibit a number of characteristic features: - Massive numbers of nodes, nodes with complex behavior, or complex interactions between nodes. Operation in open and non-deterministic environments with variable network topology. Need for adaptation, e.g., to changing environments and requirements.We call this future generation of software-intensive systems ensembles.

Dichiarazione Dei Redditi Modello Unico

The potentially huge impact – both positive and negative - of ensembles means that we need to understand ways to reliably and predictably model, design, and program them. Although there is a lot of research in this area, so far no theoretically well-founded technique for building ensembles exists. The goal of the ASCENS project is to develop such a method and to demonstrate its feasibility in three important application domains: robot swarms, cloud computing and e-mobility. There is a limited understanding of how virtual water trade affects food security. The benefits of such indirect trade of water, for instance, could be negatively affected by the lack of a single system of shared rules defining the economic value of water resources and preventing the consequent over-exploitation of these resources in fragile socio-economical and environmental contexts.The ViWaN project addresses these issues with an innovative and interdisciplinary approach aimed at studying the main drivers and consequences of international virtual water flows. The main objectives are two: a better understanding of the global dynamics in virtual water flows and the evaluation of the impact of such flows on food safety. We will investigate the complex relationships between climatic, agronomic and socio-economic factors that shape the evolution of the worldwide trade of virtual water.

The project will deliver quantitative modeling tools that enable an explicit representation of the relationships between virtual water flows and a set of explanatory variables; these models will be applied to a comprehensive database specifically built for the purpose. In addition, to improve the future management of the virtual water trade, the project will provide with a series of operational guidelines and proposals which are based on quantitative data. This project proceeds from the vision that fundamental advances of policy modelling in finance and climate finance can only stem from a genuinely interdisciplinary approach where network science, big data and ICT’s meet economics and financial regulation. Accordingly, on the one hand we will develop new methods to assess the systemic importance of market players in (climate) financial networks and we will evaluate the effect of regulations in close collaborations with representatives of various regulatory bodies. The results will contribute to the discussion on how financial innovations could ignite a transition towards a greener economy and a more sustainable financial system.

On the other hand, we will leverage on open data initiatives and semantic web to empower citizens with a more active role in relation to EU policies, by crowd-sourcing the mapping of the networks of influence involved in the policy making process. The problem: The design of collective adaptive systems (CAS) must be supported by a powerful well-founded framework for modelling and analysis. CAS consist of a large number of heterogeneous entities with decentralised control and varying degrees of complex autonomous behaviour. These entities may be competing for shared resources even when collaborating to reach common goals.

The pervasive but transparent nature of CAS, together with the importance of the societal goals they address, mean that it is imperative that thorough a priori analysis and verification of their design is carried out to investigate all aspects of their behaviour before they are put into operation. Future advancements in ICT domain are closely linked to the understanding about how multi-level complex systems function. Indeed, multi-level dependencies may amplify cascade failures or make more sudden the collapse of the entire system. Recent large-scale blackouts resulting from cascades in the power-grid coupled to the control communication system witness this point very clearly. A better understanding of multi-level systems is essential for future ICT’s and for improving life quality and security in an increasingly interconnected and interdependent world.

In this respect, complex networks science is particularly suitable for the many challenges that we face today, from critical infrastructures and communication systems, to techno-social and socio-economic networks. MULTIPLEX proposes a substantial paradigm shift for the development of a mathematical, computational and algorithmic framework for multi-level complex networks. Firstly, this will lead to a significant progress in the understanding and the prediction of complex multi-level systems.

Secondly, it will enable a better control, and optimization of their dynamics. By combining mathematical analyses, modelling approaches and the use of massive heterogeneous data sets, we shall address several prominent aspects of multi-level complex networks, i.e. Their topology, dynamical organization and evolution. Sviluppo su Lucca di una piattaforma di competenze e di tecnologie in tre ambiti ad alta rilevanza per la crescita del territorio: a) risparmio energetico e urbano b) sviluppo di tecnologie per la valorizzazione del patrimonio culturale locale c) sviluppo di un polo di competenze per analisi e servizi ad alto valore aggiunto per il sistema delle imprese; concorrendo a sviluppare Lucca come polo di rilevanza nazionale a tre linee di ricerca ad alta rilevanza applicativa per lo sviluppo del territorio, contribuendo a qualificare Lucca come filiera della Ricerca e dell’Innovazione.

Theoretically, the utilization of short-term contracts could help increase labor force participation, employment, efficiency and labour market opportunities. However, if not regulated in integration with the specific institutional framework, short-term contracts might generate undesired effects. By promoting adverse selection, driving the better workers away from the mother country as the less productive workers take up short-term contracts, short-term contracts might actually increase the brain drain. The purpose of EXODUS is to investigate the validity of these concerns and to analyze the way short-term contracts affect the brain drain phenomenon. In particular, EXODUS will focus on investigating the employment condition and behavioral choices of a specific category of workers: young individuals with a high level of education. The project addresses three main management problems in urban water system: optimal operational control, real-time monitoring and demand forecasting/management. Real-time optimal control deals with operating the main flow and pressure actuators to meet demands using the most sustainable sources and minimizing electricity costs and is tackled using stochastic model predictive control techniques.

Real-time monitoring of water quantity and quality refers to the continuous detection and location of leakage and or water quality problems. It uses fault detection and diagnosis techniques. Demand forecasting and management is based on smart metering techniques and includes detailed modelling of consumption patterns as well as a service of communication to consumers. The project will provide an integrated software platform and two real-life pilot demonstrations in Barcelona (Spain) and Lemesos (Cyprus), respectively.

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The DOLFINS project addresses the global challenge of making the financial system better serve society by placing scientific evidence and citizens participation at the centre of the policy process in finance. The project strives to give scientific evidence and citizens participation central roles in the policy process concerning finance. DOLFINS will focus on two crucial and interconnected policy areas that will shape the public debate in the coming 5 years: How to achieve financial stability and how to facilitate the long-term investments required by the transition to a more sustainable, more innovative, less unequal and greener EU economy. The expected impact is to achieve crucial advances in reshaping the policy process to overcome the financial and political crisis faced by the EU. We will deliver quantitative tools to evaluate policies aiming to tame systemic risk and to foster sustainable investing. The tools will be based on fundamental research combining network models and algorithmic game theory with broader economic insights. The DISIRE project has been inspired by the real existing needs of multiple industrial sectors, including the world leading industrial partners in the non-ferrous, ferrous, chemical and steel industries that are highly connected and already affiliated with the SPIRE PPP and its objectives.

Modello Unico 2008

The overall clear and measurable objective of the DISIRE project is to evolve the existing industrial processes by advancing theSustainable Process Industry through an overall Resource and Energy efficiency by the technological breakthroughs and concepts of the DISIRE technological platform in the field of Industrial Process Control (IPC). Specific DISIRE Process Analyzer Technology (PAT) will be able to define quality and performance requirements, that for the first time in the process industry will be able to be directly applied on the physical properties of the developed products and thus enabling the overall online and product specific reconfiguration of the control system. Crisis Lab, is a novel strategic research project financed by Italian Government (Progetti di Interesse CNR). The aim is of creating an Observatory of risks in domains ranging from finance, energy, markets, transport and urban systems, with interdisciplinary methodology based on the new science of Complex Networks.

The focus of the Crisis lab is to develop models using empirical data to describe the vulnerabilities of diverse socio-technical systems which have a complex underlying dependency structure. The globalization of our planet requires state-of-the-art methodologies for better understanding the dependency structure of multi-level systems which can be vulnerable to catastrophic failure. The Crisis Lab project is an international movement for the development of a new economic thinking, which has the strategic aim to develop new ideas, which lead our economic future and the recovery of the financial sector of its supporting role to society and to the real economy.

(PV) based on Silicon (Si) semiconductors is one the most growing technology in the World for renewable, sustainable, non-polluting, widely available clean energy sources. Theoretical and applied research aims at increasing the conversion efficiency of PV modules and their lifetime. The Si crystalline microstructure has an important role on both issues. Grain boundaries introduce additional resistance and reduce the conversion efficiency. Moreover, they are prone to micro-cracking, thus influencing the lifetime. At present, the existing standard qualification tests are not sufficient to provide a quantitative definition of lifetime, since all the possible failure mechanisms are not accounted for.

In this project, an innovative computational approach to design and durability assessment of PV modules is put forward. The aim is to complement real tests by virtual (numerical) simulations. To achieve a predictive stage, a challenging multi-field (multi-physics) computational approach is proposed, coupling the nonlinear elastic field, the thermal field and the electric field. To model real PV modules, an adaptive multi-scale and multi-field strategy will be proposed by introducing error indicators based on the gradients of the involved fields. This numerical approach will be applied to determine the upper bound to the probability of failure of the system.

This statistical assessment will involve an optimization analysis that will be efficiently handled by a Mathematica-based hybrid symbolic-numerical framework. Standard and non-standard experimental testing on Si cells and PV modules will also be performed to complement and validate the numerical approach. The new methodology based on the challenging integration of advanced physical and mathematical modelling, innovative computational methods and non-standard experimental techniques is expected to have a significant impact on the design, qualification and lifetime assessment of complex PV systems. Global Systems Science – GSS – is an emerging research field focused on the risks and opportunities involved in global coordination problems. Examples of global systems include the internet, financial markets, intellectual property rights, global energy use and others. Developing evidence and understanding in view of such systems and of related policies is rapidly becoming a vital challenge for modern societies. It requires capabilities for transdisciplinary work that cannot be mastered without massive use of ICT.

By the nature of the problem, the relevant datasets are mostly very big, including data streams from social media. To make things more complicated, the relevant algorithms do require the power of high-performance computing. High Performance Data Analysis (HPDA) is the key to success for GSS! A key contribution of the Center of Excellence for Global Systems Science – COEGSS – will be the development of an HPC-based framework to generate customized synthetic populations for GSS applications. By blending GSS and HPC, we will be able to provide decision makers and civil society with real-time assessments of global risks and opportunities as well as with essential background knowledge about them.

This will enable the HPC industry to supply hard- and software for applications well beyond the issues to which HPC has been dedicated so far.