Grid Global Behavior Prediction

Complexity has always been one of the most important issues in distributed computing. From the first clusters to grid and now cloud computing, dealing correctly and efficiently with system complexity is the key to taking technology a step further. In this sense, global behavior modeling is an innovative methodology aimed at understanding the grid behavior. The main objective of this methodology is to synthesize the grid's vast, heterogeneous nature into a simple but powerful behavior model, represented in the form of a single, abstract entity, with a global state. Global behavior modeling has proved to be very useful in effectively managing grid complexity but, in many cases, deeper knowledge is needed. It generates a descriptive model that could be greatly improved if extended not only to explain behavior, but also to predict it. In this paper we present a prediction methodology whose objective is to define the techniques needed to create global behavior prediction models for grid systems. This global behavior prediction can benefit grid management, specially in areas such as fault tolerance or job scheduling. The paper presents experimental results obtained in real scenarios in order to validate this approach

Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoring

High-throughput data analysis challenges in laboratory automation and lab-on-a-chip devices’ applications are continuously increasing. In cell culture monitoring, specifically, the electrical cell-substrate impedance sensing technique (ECIS), has been extensively used for a wide variety of applications. One of the main drawbacks of ECIS is the need for implementing complex electrical models to decode the electrical performance of the full system composed by the electrodes, medium, and cells. In this work we present a new approach for the analysis of data and the prediction of a specific biological parameter, the fill-factor of a cell culture, based on a polynomial regression, data-analytic model. The method was successfully applied to a specific ECIS circuit and two different cell cultures, N2A (a mouse neuroblastoma cell line) and myoblasts. The data-analytic modeling approach can be used in the decoding of electrical impedance measurements of different cell lines, provided a representative volume of data from the cell culture growth is available, sorting out the difficulties traditionally found in the implementation of electrical models. This can be of particular importance for the design of control algorithms for cell cultures in tissue engineering protocols, and labs-on-a-chip and wearable devices applicationsEspaña, Ministerio de Ciencia e Innovación y Universidades project RTI2018-093512-B-C2

Estudio de la especificidad de vías de insulina/IGF-1 en los patrones de arborización y señalización mediante el uso de virus asociados a adenovirus

Objetivo: Las vías de señalización de insulina y del factor de crecimiento insulínico tipo I(IGF-1) están involucradas en el control de la arborización dendrítica, señalización y crecimientocelular. Varios estudios han demostrado que déficits en estas vías están relacionadoscon trastornos cognitivos, tales como autismo, y con un elevado riesgo de sufrir demencia.Con tal de elucidar el papel exacto que tiene la señalización de insulina cerebral en las funcionesneuronales importantes para los procesos cognitivos, pretendemos silenciar la expresiónde los substratos del receptor de insulina; IRS-1 e IRS-2, los cuales son dos componentesclave en la vía de señalización de Insulina-IGF-1. Diseño experimental y Métodos: Contal de estudiar el papel de IRS-1 e IRS-2 en la arborización dendrítica y en la plasticidadneuronal, generaremos varios virus adeno asociados (AAV) que sean específicos de neurona.Además, estas partículas víricas contendrán específicos shRNA para poder silenciar laexpresión de IRS-1 y/o IRS-2, junto con un gen chivato para comprobar la eficiencia de lainfección del virus. La generación de estas partículas la hemos realizado siguiendo el métodode recombinación Gateway, utilizando un promotor específico de neurona y un shRNAcontra IRS-1/IRS-2 junto con EGFP como gen chivato. Resultados y conclusiones: Hemossido capaces de generar una partícula vírica que consta de un promotor genérico potente(CMV) junto con el gen chivato EGFP. Hemos testado la eficiencia y actividad de esta partículavírica in vivo en varias regiones del cerebro de rata.Objective: The Insulin and insulin-like growth factor 1 (IGF-1) pathway are involved in thenormal control of dendritic arborisation, cell signalling and development. Several studieshave shown that deficits in these pathways are related to cognitive disorders, such as autism,and an increased risk of dementia. To elucidate the specific role of brain insulin signallingin neuronal functions that are relevant for cognitive processes we want to silence thegene expression of the Insulin Receptor Substrate 1, and 2, (IRS-1, IRS-2) two key componentsof the Insulin-IGF-1 pathway. Research Design and Methods: To study the roleof IRS-1 and IRS-2 in dendritic arborisation and neural plasticity we want to generate severaladeno-associated viruses (AAV) that are neuron-specific. Besides these virus willcontain a specific shRNA to silence both IRS-1or IRS-2 and a reporter gene in order to tracktheir infection efficiency. To do so, we have followed the Gateway method for viral particlesgeneration, with a neuron-specific promoter and a shRNA against IRS-1/IRS-2 along withthe enhanced green fluorescent protein (EGFP) as a reporter gene. Results and conclusions:We have been able to generate a viral particle that contains a strong generic promoter(CMV) along with a reporter gene (EGFP). We have tested the efficiency and activityof this viral particle in vivo in several regions of the rat brain

Dynamics of a levitron under a periodic magnetic forcing

The Levitron is a toy that consists of a spinning top that levitates over a magnetic base for a few minutes, until air drag decreases the spin rate below a certain limit. Stable levitation, lasting hours or even days, has been achieved for Levitrons that were externally driven by either an air jet or an alternating magnetic field. We report measurements of stable levitation for the latter case. We show that the top precession couples with the frequency of the alternating field, so that the precession period equals the period of the field. In addition, the top rotates around itself with the same period. We present numerical simulations that reproduce the essential features of this dynamics. It is also shown that the magnetic torque that drives the top is due to a misalignment between the magnetic dipole moment and the mechanical axis of the to

Aplicación de la Escala Latinoamericana y del Caribe sobre Seguridad Alimentaria (ELCSA) y su asociación con la posesión de árboles frutales, siembra de hortalizas y posesión de cultivos en San Felipe Cuapexco, Puebla

Objetivo. Estimar la proporción de hogares de San Felipe Cuapexco en Inseguridad Alimentaria utilizando la Escala Latinoamericana y del Caribe sobre Seguridad Alimentaria (ELCSA), así como abordar y determinar la relación entre el grado de Inseguridad Alimentaria y la posesión de árboles frutales, hortalizas y cultivos. Material y Métodos. Se consideró la información de 105 hogares a quienes se aplicó la versión de la Escala Latinoamericana y del Caribe sobre Seguridad Alimentaria adoptada y aplicada en la Encuesta Nacional de Ingreso y Gasto en los Hogares (ENIGH) tanto en el 2010 como en el 2012. Esta escala fue acompañada de preguntas adicionales sobre variables con las que se determinaría la asociación de la Inseguridad Alimentaria. Se determinó la distribución de los grados de Inseguridad Alimentaria asociados a las variables determinadas. Resultados. A nivel general 61.9% de los hogares presentan Inseguridad Alimentaria Leve. 35.25% Moderada y 1.9% Inseguridad Severa. No se encontró una asociación clara manifiesta entre grados de Inseguridad Alimentaria y posesión de árboles frutales, sin embargo, se descubrió una asociación evidente entre posesión de siembra de hortalizas y menor grado de Inseguridad Alimentaria, esta asociación también es manifiesta entre número de cultivos por hogar y menor grado de Inseguridad Alimentaria. Conclusión. El incremento de la siembra de hortalizas en los hogares y la búsqueda y mantenimiento de las actividades agrícolas en las localidades rurales decrementan el grado de Inseguridad Alimentaria

Estudio, análisis y desarrollo de técnicas de “interactive machine learning” y su comparación con el “machine learning” tradicional.

[Resumen]: El Aprendizaje Máquina es usado por gran parte de la comunidad científica como una caja negra: datos de entrada, ajuste de hiperparámetros, entrenamiento del modelo y obtención de resultados. Los modelos que se desarrollen bajo este escenario corren el riesgo de no escalar bien, volverse estáticos o ser difíciles de evaluar. El Aprendizaje Máquina Interactivo son un conjunto de técnicas que intentan introducir activamente a los humanos en el bucle de aprendizaje de los modelos, funciona especialmente bien cuando el dominio es complejo, no hay suficientes datos o son muy costosos de anotar. El Aprendizaje Máquina Interactivo se divide dependiendo del papel que ocupa el humano dentro del ciclo de aprendizaje del modelo. En nuestro proyecto el Aprendizaje Activo es la aproximación desarrollada que consiste en que el modelo consulta al humano (oráculo) los casos que generan mayor incertidumbre en sus predicciones. En este proyecto aplicamos las técnicas de Aprendizaje Máquina Interactivo a un problema real con datos de pacientes oncológicos con cáncer de páncreas, donde los datos y el tiempo de etiquetado de los médicos son limitados. Para aplicar la solución fue necesario utilizar técnicas de aumento de datos generando casos sintéticos de cáncer de páncreas mediante una Red Generativa Antagónica. Los resultados muestran como la incorporación del humano al bucle de entrenamiento provoca que el modelo converja de manera más rápida y eficiente con un menor coste humano que las aproximaciones clásicas.[Abstract]: Machine Learning is used by most of the scientific community as a black box: input data, hyperparameters optimization, training the model and obtaining results. Models developed under this scenario run the risk of not scaling well, becoming static or difficult to evaluate. Interactive Machine Learning are a set of techniques that attempt to actively introduce humans into the learning loop of models, works especially well when the domain is complex, not enough data or is too costly to annotate. Interactive Machine Learning is divided depending on the role of the human within the model learning loop. In our project, Active Learning is the approach developed which consists of the model consulting the human (oracle) for the cases that generate greater uncertainty in its predictions. In this project we applied the Interactive Machine Learning techniques to a real problem with data from oncological patients with pancreatic cancer, where data and labeling time of physicians are limited. To apply the solution it was necessary to use data augmentation techniques generating synthetic cases of pancreatic cancer using an Generative Adversarial Network. The results show how the incorporation of the human into the training loop causes the model to converge faster and more efficiently with a lower human cost than classical approaches.Traballo fin de grao (UDC.FIC). Enxeñaría Informática. Curso 2021/202

Frontiers and political agregations in Celtiberia: data for a debate

Proyecto de investigación “Entre la paz y la guerra: alianzas, confederaciones y diplomacia en el Occidente mediterráneo (siglos III-I a.C.)” (Ref. HAR2011-27782), Plan Nacional I+D+I, Ministerio de Economía y Competitividad, Gobierno de España. Grupo de Investigación Occidens UIB-UAM (www.occidens.es).En el contexto de la II Guerra Púnica (218-206 a.C. para la península Ibérica) y el proceso de expansión romana en Celtiberia (ca. 195-133 a.C.), nuestro objetivo se centra en poner en valor la dimensión espacial, territorial, de las dinámicas históricas, delimitando su papel en la generación de identidades en el mundo celtibérico. Planteamos, en primer lugar, un análisis diacrónico y una contextualización geopolítica de las referencias a coaliciones militares en el interior peninsular, destacando las alianzas defensivas formadas en la década de los años 90 del siglo II a.C. para tratar de contener el avance romano en la línea del Tajo, así como otros ejemplos de coaliciones conocidas para las guerras celtibéricas de mediados de siglo. Estudiamos también, seguidamente, la estructura interna de las póleis celtibéricas, subrayando su composición mixta (oppidum-ager), y reconstruyendo algunos datos sobre la gestión local de los recintos defensivos y de los límites de los territorios. Finalmente, analizamos los tres niveles político-militares identificables en el mundo celtibérico y su correlato territorial. Partiendo del concepto básico de civitas (en terminología latina), se discute la naturaleza suprapolítica y/o étnica de los populi, para analizar finalmente los mecanismos de generación de grandes alianzas y coaliciones, cuya perpetuación en el tiempo habría propiciado también la aparición de elementos identitarios regionales.In the context of the Second Punic War (218-206 BC for the Iberian Peninsula) and the process of Roman expansion in Celtiberia (ca. 195-133 BC), we underline the importance of the territorial, spatial dimension of the historical dynamics, defining its role in the generation of identities in the Celtiberian world. We propose, firstly, a diachronic analysis and a geopolitical contextualization of references to military coalitions in the inner Iberian Peninsula, paying special attention to the defensive alliances formed in the early 90s of the 2nd century BC trying to contain the Roman advance on the line of the river Tagus. We consider also other examples of coalitions during the central decades of the 2nd century. Later on, we deal with the internal structure of the Celtiberian póleis, stressing its mixed composition (oppidum-ager), and reconstructing some data on the local management of the defensive structures and the limits of the territories. Finally, we analyze the three political-military layers that can be identified in the Celtiberian world and its territorial correlate. Starting from the basic concept of civitas (in Latin terminology), the suprapolitical and / or ethnic nature of the populi is discussed, to analyze, finally, the mechanisms of generation of large alliances and coalitions, whose perpetuation in time have also led to the emergence of elements of regional identity

Single-board device individual authentication based on hardware performance and autoencoder transformer models

The proliferation of the Internet of Things (IoT) has led to the emergence of crowdsensing applications, where a multitude of interconnected devices collaboratively collect and analyze data. Ensuring the authenticity and integrity of the data collected by these devices is crucial for reliable decision-making and maintaining trust in the system. Traditional authentication methods are often vulnerable to attacks or can be easily duplicated, posing challenges to securing crowdsensing applications. Besides, current solutions leveraging device behavior are mostly focused on device identification, which is a simpler task than authentication. To address these issues, an individual IoT device authentication framework based on hardware behavior fingerprinting and Transformer autoencoders is proposed in this work. To support the design, a threat model details the security problems faced when performing hardware-based authentication in IoT. This solution leverages the inherent imperfections and variations in IoT device hardware to differentiate between devices with identical specifications. By monitoring and analyzing the behavior of key hardware components, such as the CPU, GPU, RAM, and Storage on devices, unique fingerprints for each device are created. The performance samples are considered as time series data and used to train outlier detection transformer models, one per device and aiming to model its normal data distribution. Then, the framework is validated within a spectrum crowdsensing system leveraging Raspberry Pi devices. After a pool of experiments, the model from each device is able to individually authenticate it between the 45 devices employed for validation. An average True Positive Rate (TPR) of 0.74±0.13 and an average maximum False Positive Rate (FPR) of 0.06±0.09 demonstrate the effectiveness of this approach in enhancing authentication, security, and trust in crowdsensing applications

Procedure to use phosphogypsum industrial waste for mineral CO 2 sequestration

Industrial wet phosphoric acid production in Huelva (SW Spain) has led to the controversial stockpiling of waste phosphogypsum by-products, resulting in the release of significant quantities of toxic impurities in salt marshes in the Tinto river estuary. In the framework of the fight against global climate change and the effort to reduce carbon dioxide emissions, a simple and efficient procedure for CO 2 mineral sequestration is presented in this work, using phosphogypsum waste as a calcium source. Our results demonstrate the high efficiency of portlandite precipitation by phosphogypsum dissolution using an alkaline soda solution. Carbonation experiments performed at ambient pressure and temperature resulted in total conversion of the portlandite into carbonate. The fate of trace elements present in the phosphogypsum waste was also investigated, and trace impurities were found to be completely transferred to the final calcite. We believe that the procedure proposed here should be considered not only as a solution for reducing old stockpiles of phosphogypsum wastes, but also for future phosphoric acid and other gypsum-producing industrial processes, resulting in more sustainable production.Junta de Andalucía TEP115Ministerio de Ciencia e Innovación PIA42008-3