Desarrollo de una guía para el abordaje de incidentes de ciberseguridad en infraestructuras críticas industriales

La producción masiva de bienes se automatiza mediante los sistemas de control industrial. Estos sistemas son muy robustos y son aptos para funcionamiento contínuo. Gracias a ello, estos sistemas automatizan también, plantas de potabilización de agua, producción y distribución de energía, siderúrgicas, y sistemas de semaforización, entre otros. Es decir, automatizan muchas infraestructuras críticas. Estos sistemas no se pensaron para ser seguros. Por ello, su seguridad se basó en el aislamiento físico. Nuevas necesidades de mayor eficiencia y productividad requieren de la integración de estos sistemas con los sistemas de administración, con nuevas tecnologías como ser: big data, internet de las cosas, inteligencia artificial, entre otras, e incluso con Internet, dejándolos expuestos a una gran cantidad de riesgos y amenazas para los que no están preparados. En este proyecto se estudian los riesgos de ciberseguridad a los que están expuestas las infraestructuras críticas industriales. Se plantea la elaboración de una guía para mitigarlos y remediar los efectos frente a estos incidentes.Eje: Seguridad informática.Red de Universidades con Carreras en Informátic

Animal Models of Parkinson’s Disease

Parkinson\u27s disease (PD) is a neurodegenerative disorder characterized by the degeneration of dopaminergic neurons in the substantia nigra pars compacta, the consequent dopamine deficit in the striatum and the accumulation of aggregated α‐synuclein (α‐syn) in specific brain regions. The underlying pathophysiology of PD remains poorly understood. Animal models are the best tools to study the pathogenesis of PD. Most studies in PD animal models have focused on the motor features associated with dopamine depletion but still the molecular basis of PD and the molecular pathways of cell death remain unknown. While cellular models have helped to identify specific events, in vivo animal models have simulated most, although not all, of the hallmarks of PD and are useful for testing new neuroprotective approaches. In this chapter, we provide a summary of the most used PD animal models, including their advantages and limitations. Classically, in vivo PD animal models can be divided into those using environmental or synthetic neurotoxins (toxin‐based models) or those utilizing the in vivo expression of PD‐related mutations (genetic models). These models include 6‐hydroxydopamine (6‐OHDA), 1‐methyl‐1,2,3,6‐tetrahydropyridine (MPTP), rotenone, and paraquat, as well as genetic models such as those related to α‐syn, PINK1, Parkin, DJ‐1, and LRRK2

155-day Periodicity in Solar Cycles 3 and 4

The near 155 days solar periodicity, so called Rieger periodicity, was first detected in solar flares data and later confirmed with other important solar indices. Unfortunately, a comprehensive analysis on the occurrence of this periodicity during previous centuries can be further complicated due to the poor quality of the sunspot number time-series. We try to detect the Rieger periodicity during the solar cycles 3 and 4 using information on aurorae observed at mid and low latitudes. We use two recently discovered aurora datasets, observed in the last quarter of the 18th century from UK and Spain. Besides simple histograms of time between consecutive events we analyse monthly series of number of aurorae observed using different spectral analysis (MTM and Wavelets). The histograms show the probable presence of Rieger periodicity during cycles 3 and 4. However different spectral analysis applied has only confirmed undoubtedly this hypothesis for solar cycle 3.Comment: 13 pages, 6 figures, to appear in New Astronom

Fast T2 gradient-spin-echo (T2-GraSE) mapping for myocardial edema quantification: first in vivo validation in a porcine model of ischemia/reperfusion

Background: Several T2-mapping sequences have been recently proposed to quantify myocardial edema by providing T2 relaxation time values. However, no T2-mapping sequence has ever been validated against actual myocardial water content for edema detection. In addition, these T2-mapping sequences are either time-consuming or require specialized software for data acquisition and/or post-processing, factors impeding their routine clinical use. Our objective was to obtain in vivo validation of a sequence for fast and accurate myocardial T2-mapping (T2 gradient-spin-echo [GraSE]) that can be easily integrated in routine protocols. Methods: The study population comprised 25 pigs. Closed-chest 40 min ischemia/reperfusion was performed in 20 pigs. Pigs were sacrificed at 120 min (n = 5), 24 h (n = 5), 4 days (n = 5) and 7 days (n = 5) after reperfusion, and heart tissue extracted for quantification of myocardial water content. For the evaluation of T2 relaxation time, cardiovascular magnetic resonance (CMR) scans, including T2 turbo-spin-echo (T2-TSE, reference standard) mapping and T2-GraSE mapping, were performed at baseline and at every follow-up until sacrifice. Five additional pigs were sacrificed after baseline CMR study and served as controls. Results: Acquisition of T2-GraSE mapping was significantly (3-fold) faster than conventional T2-TSE mapping. Myocardial T2 relaxation measurements performed by T2-TSE and T2-GraSE mapping demonstrated an almost perfect correlation (R-2 = 0.99) and agreement with no systematic error between techniques. The two T2-mapping sequences showed similarly good correlations with myocardial water content: R-2 = 0.75 and R-2 = 0.73 for T2-TSE and T2-GraSE mapping, respectively. Conclusions: We present the first in vivo validation of T2-mapping to assess myocardial edema. Given its shorter acquisition time and no requirement for specific software for data acquisition or post-processing, fast T2-GraSE mapping of the myocardium offers an attractive alternative to current CMR sequences for T2 quantification.This work was supported by a competitive grant from the Ministry of Economy and Competitiveness (MINECO) through the Carlos III Institute of Health -Fondo de Investigacion Sanitaria (PI13/01979)-, the Fondo Europeo de Desarrollo Regional (FEDER, RD: SAF2013-49663-EXP), and in part by the FP7-PEOPLE-2013-ITN Next generation training in cardiovascular research and innovation-Cardionext. Rodrigo Fernandez-Jimenez is recipient of a Rio Hortega fellowship from the Ministry of Economy and Competitiveness through the Instituto de Salud Carlos III, and a FICNIC fellowship from the Fundacio Jesus Serra, the Fundacion Interhospitalaria de Investigacion Cardiovascular (FIC) and the Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC). Javier Sanchez-Gonzalez is an employee of Philips Healthcare. Jaume Aguero is a FP7-PEOPLE-2013-ITN-Cardionext fellow. Carlos Galan-Arriola is recipient of a ``Contrato Predoctoral de Formacion en Investigacion en Salud (PFIS), FI14/00356´´. This study forms part of a Master Research Agreement (MRA) between CNIC and Philips Healthcare. Borja Ibanez is supported by the Red de Investigacion Cardiovascular (RIC) of the Spanish Ministry of Health (RD 12/0042/0054). The CNIC is supported by the Spanish Ministry of Economy and Competitiveness and the Pro-CNIC Foundation.S

Expression Cloning of lsc , a Novel Oncogene with Structural Similarities to the Dbl Family of Guanine Nucleotide Exchange Factors

In a screen for genes with oncogenic potential expressed by the murine B6SUtA1 myeloid progenitor cell line, we isolated a 2. 5-kilobase pair cDNA whose expression causes strong morphological transformation and deregulated proliferation of NIH 3T3 cells. The transforming cDNA encodes a truncated protein (designated Lsc) with a region of sequence similarity to the product of the lbc oncogene. This region includes the tandem Dbl homology and pleckstrin homology domains that are hallmarks of the Dbl-like proteins, a family of presumptive or demonstrated guanine nucleotide exchange factors that act on Rho family GTPases. Lsc requires intact Dbl homology and pleckstrin homology domains for its oncogenic activity. The transforming activity of Lsc in NIH 3T3 cells is reduced by cotransfection with p190 (a GTPase activating protein for Rho family GTPases) and the Rho family dominant-negative mutants RhoA(19N), CDC42(17N), and Rac1(17N). These results indicate a role for the Rho family of GTPases in mediating the transforming activity of Lsc and are consistent with the exchange specificities that have been attributed to Dbl family members. The lsc gene is expressed in a variety of tissues and is particularly abundant in hemopoietic tissues (thymus, spleen, and bone marrow). Lsc is a member of a growing family of proteins that may function as activators of Rho family GTPases in a developmental or tissue-specific manner

An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities

Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student's affective state, to move them out of negative states that inhibit learning, into positive states such as engagement. In spite of their obvious potential to provide the personalisation that would give extra support for learners with intellectual disabilities, little work on AIEd systems that utilise affect recognition currently addresses this group. Our system used multimodal sensor data and machine learning to first identify three affective states linked to learning (engagement, frustration, boredom) and second determine the presentation of learning content so that the learner is maintained in an optimal affective state and rate of learning is maximised. To evaluate this adaptive learning system, 67 participants aged between 6 and 18 years acting as their own control took part in a series of sessions using the system. Sessions alternated between using the system with both affect detection and learning achievement to drive the selection of learning content (intervention) and using learning achievement alone (control) to drive the selection of learning content. Lack of boredom was the state with the strongest link to achievement, with both frustration and engagement positively related to achievement. There was significantly more engagement and less boredom in intervention than control sessions, but no significant difference in achievement. These results suggest that engagement does increase when activities are tailored to the personal needs and emotional state of the learner and that the system was promoting affective states that in turn promote learning. However, longer exposure is necessary to determine the effect on learning

Mapping the Interacting Regions between Troponins T and C. Binding of TnT and TnI peptides to TnC and NMR mapping of the TnT-binding site on TnC

Muscular contraction is triggered by an increase in calcium concentration, which is transmitted to the contractile proteins by the troponin complex. The interactions among the components of the troponin complex (troponins T, C, and I) are essential to understanding the regulation of muscle contraction. While the structure of TnC is well known, and a model for the binary TnC·TnI complex has been recently published (Tung, C.-S., Wall, M. E., Gallagher, S. C., and Trewhella, J. (2000)Protein Sci. 9, 1312–1326), very little is known about TnT. Using non-denaturing gels and NMR spectroscopy, we have analyzed the interactions between TnC and five peptides from TnT as well as how three TnI peptides affect these interactions. Rabbit fast skeletal muscle peptide TnT-(160–193) binds to TnC with a dissociation constant of 30 ± 6 µm. This binding still occurs in the presence of TnI-(1–40) but is prevented by the presence of TnI-(56–115) or TnI-(96–139), both containing the primary inhibitory region of TnI. TnT-(228–260) also binds TnC. The binding site for TnT-(160–193) is located on the C-terminal domain of TnC and was mapped to the surface of TnC using NMR chemical shift mapping techniques. In the context of the model for the TnC·TnI complex, we discuss the interactions between TnT and the other troponin subunits

The role of the land-surface model for climate change projections over the Iberian Peninsula

The importance of land-surface processes within Regional Climate Models for accurately reproducing the present-day climate is well known. However, their role when projecting future climate is still poorly reported. Hence, this work assesses the influence of the land-surface processes, particularly the contribution of soil moisture, when projecting future changes for temperature, precipitation and wind over a complex area as the Iberian Peninsula, which, in addition, shows great sensitivity to climate change. The main signals are found for the summer season, when the results indicate a strengthening in the increases projected for both mean temperature and temperature variability as a consequence of the future intensification of the positive soil moisture-temperature feedback. The more severe warming over the inner dry Iberian Peninsula further implies an intensification of the Iberian thermal low and, thus, of the cyclonic circulation. Furthermore, the land-atmosphere coupling leads to the projection of a wider future daily temperature range, since maximum temperatures are more affected than minima, a feature absent in non-coupled simulations. Regarding variability, the areas where the land-atmosphere coupling introduces larger changes are those where the reduction in the soil moisture content is more dramatic in future simulations, i.e., the so-called transitional zones. As regards precipitation, weaker positive signals for convective precipitation and more intense negative signals for non-convective precipitation are obtained as a result of the soil moisture-atmosphere interactions. These results highlight the crucial contribution of soil moisture to climate change projections and suggest its plausible key role for future projections of extreme events