Techniques for prediction of disruptions on TOKAMAKS

Introduction ------------ The physicist Andreevich Artsimovich in the 1970 wrote that "thermonuclear [fusion] energy will be ready when mankind needs it". Considering the actual world energy situation and the effect on the environment due to the present harnessing of the different sources of energy, the hope is that time for fusion is finally arrived. Background and Motivation ------------------------- The activities carried out in the framework of this thesis regarded the devel- opment, implementation and application of algorithms for classification and prediction of disruptions in Tokamaks. The balance of plasmas in a magnetic field can be described by the theory of magneto-hydro-dynamic (MHD). MHD instabilities are among the most serious factors that limit fusion devices operation in magnetic confinement configurations. When they occur on a large scale can degrade the perfor- mance of the plasma and lead to loss of confinement and control. A disruption is a sudden loss of stability or confinement of tokamak plasma; it is a critical event in which the plasma energy is lost within a time span of few milliseconds exposing the plasma facing components to se- vere thermo-mechanical stresses and conductors surrounding the vessel to huge electromagnetic forces. Therefore, it becomes of primary importance to avoid or mitigate disruptions in order to preserve the integrity of the ma- chine. This aspect and the understanding of disruptive phenomena play a key role in design and running of new experimental devices as ITER, cur- rently under construction in Cadarache (France), which will have the task of demonstrating the feasibility of fusion energy production from a technical and engineering point of view. These considerations motivate a strong interest in developing methods and techniques aimed to minimize both number and severity of disruptions. Furthermore when a disruption occurs it would be particularly important to be able to distinguish among its difierent types in order to improve avoidance and mitigation strategies. Since physical models able to reliably recognize and predict the occurrence of disruptions are currently not available, the re- search carried out fits in the broad framework of machine learning techniques that have been exploited as an alternative approach to disruption prediction and automatic classification. Promising approaches to prediction and classification are represented by the so-called "data-based" methods: to this purpose, existing systems have been applied and further developed and new approaches have been investi- gated. The mentioned activity has been carried out in collaboration with the University of Cagliari and European Research Centers for nuclear fusion, taking as case study some of the most important experimental machines such as JET and ASDEX Upgrade (AUG), with several months of research spent at the Culham Science Centre. Outline of the Thesis --------------------- In chapter 1 the perspectives of fusion in the world energy context as an almost unlimited source of energy for the future are discussed, with particu- lar reference to the role of magnetic confinement. Furthermore, the bases of fusion reactions have been introduced. In chapter 2 the main aspects of plasma stability in tokamaks configu- rations are described with the aim to provide an adequate reference for all the discussions of the following chapters. In particular, the main parameters related to plasma stability, which have been used for the construction of the databases, have been introduced. The chapter 3 is focused on the description of the operational limits with reference to the main quantities which should be maximized to im- prove plasma performance. Everything, also in the previous chapters, has been framed to introduce the key problems which this thesis has addressed: analysis, prediction and classification of disruptions. After the main consid- erations about the operational limits, the main phases, the causes and the consequences of disruptions have been discussed, trying to integrate the sta- bility concepts introduced in the previous chapter. The chapter 4 is finalized to provide an insight of the Machine Learn- ing methods which represent the starting point of all the analysis and algo- rithms implemented for disruption prediction and classification. Today the large amount of data available from fusion experiments and their character of high-dimensionality make particularly difficult handling, processing, un- derstanding and extracting properly what is really important among all the available information. Machine Learning allows to deal with the problem in efficient way. Therefore, a framework of all the techniques exploited for the analysis has been provided, with particular reference to the Manifold Learn- ing algorithms as Self Organizing Maps (SOMs) and Generative Topographic Mappings (GTMs). Also reference methods such as k-Nearest Neighbor (k- NN) or more recent methods such as Conformal Predictors, exploited for validation and reliability assessment purposes, have been described. In chapter 5 the state of the art of machine learning techniques ap- plied to disruption prediction and classification is presented, describing in particular the main applications with the widely employed Neural Networks, such Multi Layer Perceptrons (MLPs), Support Vector Machines (SVMs) and Self Organizing Maps (SOMs), and statistical methods such as Discrim- inant Analysis or Multiple Threshold technique. Strengths and weaknesses have also been discussed with reference to a possible solution to overcome the drawbacks of these methods: the multi-machine approach. Chapter 6 is dedicated to the description of the databases used for all the analysis presented in the following chapters. In particular, the statistical analysis and the data-reduction algorithms that have been needed to build a reliable and statistically representative database have been discussed in detail. The last three chapters contain all the analysis and all the algorithms im- plemented for the mapping of the operational space, disruption classification and prediction. In chapter 7 the mapping of the JET operational space is presented. The first sections deal with projections and data-visualization with linear projection methods such as Grand Tour (GT) and Principal Com- ponent Analysis (PCA). In the central part, the same aspects have been taken into account by exploiting nonlinear Manifold Learning techniques, SOM and GTM, on the base of which a detailed analysis of the operational space has been performed. Such analysis, showing the potentiality of the methods, has been performed, regarding GTM model, through the implementation of a dedicated tool. Finally, an outliers' analysis and performance indexes appo- sitely proposed have been considered for evaluating the overall performance of the mapping. In the chapter 8 the developed automatic disruption classification for JET has been described. The chapter is divided in two parts: the first one describes the classification of disruptions belonging to the Carbon Wall (CW) campaigns, whereas in the second part the classification of disruptions with the ITER-like Wall (ILW) is framed in the assessment of the suitability of the automatic classifier for real time applications, in conjunction with prediction systems working online at JET. The reliability of the results has been vali- dated by comparison with a k-NN based reference classifier and through the recent conformal predictors, with which is possible to provide, in addition to the prediction/classification, the related level of confidence. Chapter 9 is dedicated to the disruption prediction at ASDEX Upgrade. The first part is related to the description of the database and the data- reduction technique used to select a representative and balanced dataset. Self-Organizing Map and the Generative Topographic Mapping have been exploited to map ASDEX Upgrade operational space and to build a disrup- tion predictor, introducing at the same time their potentiality for disruptions classification. Furthermore, the use of this two methods combined with a Lo- gistic model has been proposed to realize a predictive system able to exploit the complementary behaviors of the two approaches, improving the overall performance in prediction

A machine-learning-based tool for last closed magnetic flux surface reconstruction on tokamak

Nuclear fusion power created by tokamak devices holds one of the most promising ways as a sustainable source of clean energy. One main challenge research field of tokamak is to predict the last closed magnetic flux surface (LCFS) determined by the interaction of the actuator coils and the internal tokamak plasma. This work requires high-dimensional, high-frequency, high-fidelity, real-time tools, further complicated by the wide range of actuator coils input interact with internal tokamak plasma states. In this work, we present a new machine learning model for reconstructing the LCFS from the Experimental Advanced Superconducting Tokamak (EAST) that learns automatically from the experimental data of EAST. This architecture can check the control strategy design and integrate it with the tokamak control system for real-time magnetic prediction. In the real-time modeling test, our approach achieves over 99% average similarity in LCFS reconstruction of the entire discharge process. In the offline magnetic reconstruction, our approach reaches over 93% average similarity

An Overview on the Current Status and Future Perspectives of Smart Cars

In recent years, the smart car sector has been increasing enormously in the Internet of Things (IoT) market. Furthermore, the number of smart cars seems set to increase over the next few years. This goal will be achieved because the application of recent IoT technologies to the automotive sector opens up innovative opportunities for the mobility of the future, in which connected cars will be more and more prominent in smart cities. This paper aims to provide an overview of the current status and future perspectives of smart cars, taking into account technological, transport, and social features. An analysis concerning the approaches to making smart a generic car, the possible evolutions that could occur in the coming decades, the characteristics of 5G, ADAS (advanced driver assistance systems), and the power sources is carried out in this paper. Document type: Articl

El perfil etario de las políticas de austeridad en la Gran Recesión: el caso de España

The austerity policies implemented in Spain during the years of the «great recession» (2008-2014) have had diverse effects on the socio-economic and vital conditions of children, young people and the elderly. In particular, the agenda of public policies and social spending applied during the crisis increased inequality between these social groups, privileging the interests of the adult population and the elderly, and calling into question7 the principle of inter-generational solidarity on which our familistic welfare system. In this article we describe this phenomenon and highlight the dominant narratives formulated by the main political actors when defining the rules of eligibility of the beneficiaries of public policies and attending to the specific needs of each age group. The statistical and documentary evidence collected points to the convenience of reflecting on the foundations of the inter-generational pact that organizes the redistribution of public resources in our country and that must ensure the sustainability of our social protection system.Las políticas de austeridad implementadas en España durante los años de la «gran recesión» (2008-2014) han tenido efectos diversos en las condiciones socio-económicas y vitales de niños, jóvenes y personas mayores. En particular, la agenda de políticas públicas y gasto social aplicada durante la crisis incrementó la desigualdad entre estos grupos sociales, privilegiando los intereses de la población adulta y de la tercera edad y poniendo en cuestión el principio de solidaridad inter-generacional sobre el cual se fundamenta nuestro sistema de bienestar de tradición marcadamente familista. En este artículo describimos dicho fenómeno y destacamos las narrativas dominantes formuladas por los actores políticos principales a la hora de definir las reglas de elegibilidad de los beneficiarios de políticas públicas y de atender las necesidades específicas de cada grupo etario. Las evidencias estadísticas y documentales recopiladas apuntan a la conveniencia de reflexionar sobre los fundamentos del pacto inter-generacional que organiza la redistribución de recursos públicos en nuestro país y que debe asegurar la sostenibilidad de nuestro sistema de protección social

American and european tomato history unveiled using haplotype and GBS analyses

Not many historical or archeological records remain from the tomato journey from Solanum pimpinellifolium (SP) to the vintage varieties, however, its domestication, migrations and diversification in Europe can be unveiled using genetic analyses. The study of 628 SP, Solanum lycopersicum var. cerasiforme (SLC), and Solanum lycopersicum var. lycopersicum (SLL) revealed: 1) SP evolved into SLC during a migration from Peru and Ecuador, 2) there is a wild SLC Mesoamerican population, 3) there are no wild SLC populations in Ecuador and Peru, 4) Peruvian and Ecuadorian SLC are an admixture of Mesoamerican SLC and SP, 5) SP introgressions in SLC harbor flowering control and light response genes, 6) at least some Mesoamerican SLL derives from domesticated Peruvian and Ecuadorian SLC. A GBS analysis of 1,254 accessions,Postprint (published version

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The modular network structure of the mutational landscape of Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is associated with the sequential accumulation of acquired genetic alterations. Although at diagnosis cytogenetic alterations are frequent in AML, roughly 50% of patients present an apparently normal karyotype (NK), leading to a highly heterogeneous prognosis. Due to this significant heterogeneity, it has been suggested that different molecular mechanisms may trigger the disease with diverse prognostic implications. We performed whole-exome sequencing (WES) of tumor-normal matched samples of de novo AML-NK patients lacking mutations in NPM1, CEBPA or FLT3-ITD to identify new gene mutations with potential prognostic and therapeutic relevance to patients with AML. Novel candidate-genes, together with others previously described, were targeted resequenced in an independent cohort of 100 de novo AML patients classified in the cytogenetic intermediate-risk (IR) category. A mean of 4.89 mutations per sample were detected in 73 genes, 35 of which were mutated in more than one patient. After a network enrichment analysis, we defined a single in silico model and established a set of seed-genes that may trigger leukemogenesis in patients with normal karyotype. The high heterogeneity of gene mutations observed in AML patients suggested that a specific alteration could not be as essential as the interaction of deregulated pathways

European traditional tomatoes galore: a result of farmers’ selection of a few diversity-rich loci

A comprehensive collection of 1254 tomato accessions, corresponding to European traditional and modern varieties, early domesticated varieties, and wild relatives, was analyzed by genotyping by sequencing. A continuous genetic gradient between the traditional and modern varieties was observed. European traditional tomatoes displayed very low genetic diversity, with only 298 polymorphic loci (95% threshold) out of 64 943 total variants. European traditional tomatoes could be classified into several genetic groups. Two main clusters consisting of Spanish and Italian accessions showed higher genetic diversity than the remaining varieties, suggesting that these regions might be independent secondary centers of diversity with a different history. Other varieties seem to be the result of a more recent complex pattern of migrations and hybridizations among the European regions. Several polymorphic loci were associated in a genome-wide association study with fruit morphological traits in the European traditional collection. The corresponding alleles were found to contribute to the distinctive phenotypic characteristic of the genetic varietal groups. The few highly polymorphic loci associated with morphological traits in an otherwise a low-diversity population suggests a history of balancing selection, in which tomato farmers likely maintained the morphological variation by inadvertently applying a high selective pressure within different varietal types.This work was supported by the European Commission H2020 research and innovation program through TRADITOM grant agreement no. 634561, G2P-SOL, grant agreement no. 677379, and HARNESSTOM grant agreement no. 101000716. MP is grateful to the Spanish Ministerio de Ciencia e Innovación for a postdoctoral grant (IJC2019-039091-I/AEI/10.13039/501100011033).Postprint (published version

New Electrocardiographic Algorithm for the Diagnosis of Acute Myocardial Infarction in Patients With Left Bundle Branch Block

Background Current electrocardiographic algorithms lack sensitivity to diagnose acute myocardial infarction (AMI) in the presence of left bundle branch block. Methods and Results A multicenter retrospective cohort study including consecutive patients with suspected AMI and left bundle branch block, referred for primary percutaneous coronary intervention between 2009 and 2018. Pre-2015 patients formed the derivation cohort (n=163, 61 with AMI); patients between 2015 and 2018 formed the validation cohort (n=107, 40 with AMI). A control group of patients without suspected AMI was also studied (n=214). Different electrocardiographic criteria were tested. A total of 484 patients were studied. A new electrocardiographic algorithm (BARCELONA algorithm) was derived and validated. The algorithm is positive in the presence of ST deviation ≥1 mm (0.1 mV) concordant with QRS polarity, in any lead, or ST deviation ≥1 mm (0.1 mV) discordant with the QRS, in leads with max (R|S) voltage (the voltage of the largest deflection of the QRS, ie, R or S wave) ≤6 mm (0.6 mV). In both the derivation and the validation cohort, the BARCELONA algorithm achieved the highest sensitivity (93%-95%), negative predictive value (96%-97%), efficiency (91%-94%) and area under the receiver operating characteristic curve (0.92-0.93), significantly higher than previous electrocardiographic rules (P<0.01); the specificity was good in both groups (89%-94%) as well as the control group (90%). Conclusions In patients with left bundle branch block referred for primary percutaneous coronary intervention, the BARCELONA algorithm was specific and highly sensitive for the diagnosis of AMI, leading to a diagnostic accuracy comparable to that obtained by ECG in patients without left bundle branch block

Band 3 Erythrocyte Membrane Protein Acts as Redox Stress Sensor Leading to Its Phosphorylation by p 72

In erythrocytes, the regulation of the redox sensitive Tyr phosphorylation of band 3 and its functions are still partially defined. A role of band 3 oxidation in regulating its own phosphorylation has been previously suggested. The current study provides evidences to support this hypothesis: (i) in intact erythrocytes, at 2 mM concentration of GSH, band 3 oxidation, and phosphorylation, Syk translocation to the membrane and Syk phosphorylation responded to the same micromolar concentrations of oxidants showing identical temporal variations; (ii) the Cys residues located in the band 3 cytoplasmic domain are 20-fold more reactive than GSH; (iii) disulfide linked band 3 cytoplasmic domain docks Syk kinase; (iv) protein Tyr phosphatases are poorly inhibited at oxidant concentrations leading to massive band 3 oxidation and phosphorylation. We also observed that hemichromes binding to band 3 determined its irreversible oxidation and phosphorylation, progressive hemolysis, and serine hyperphosphorylation of different cytoskeleton proteins. Syk inhibitor suppressed the phosphorylation of band 3 also preventing serine phosphorylation changes and hemolysis. Our data suggest that band 3 acts as redox sensor regulating its own phosphorylation and that hemichromes leading to the protracted phosphorylation of band 3 may trigger a cascade of events finally leading to hemolysis