Bio-inspired enhancement of reputation systems for intelligent environments

Providing security to the emerging field of ambient intelligence will be difficult if we rely only on existing techniques, given their dynamic and heterogeneous nature. Moreover, security demands of these systems are expected to grow, as many applications will require accurate context modeling. In this work we propose an enhancement to the reputation systems traditionally deployed for securing these systems. Different anomaly detectors are combined using the immunological paradigm to optimize reputation system performance in response to evolving security requirements. As an example, the experiments show how a combination of detectors based on unsupervised techniques (self-organizing maps and genetic algorithms) can help to significantly reduce the global response time of the reputation system. The proposed solution offers many benefits: scalability, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. For these reasons, we believe that our solution is capable of coping with the dynamism of ambient intelligence systems and the growing requirements of security demands.

Simulating Metabolic Processes Using an Architecture Based on Networks of Bio-inspired Processors.

In this work, we propose the Networks of Evolutionary Processors (NEP) [2] as a computational model to solve problems related with biological phenomena. In our first approximation, we simulate biological processes related with cellular signaling and their implications in the metabolism, by using an architecture based on NEP (NEP architecture) and their specializations: Networks of Polarized Evolutionary Processors (NPEP) [1] and NEP Transducers (NEPT) [3]. In particular, we use this architecture to simulate the interplay between cellular processes related with the metabolism as the Krebs cycle and the malate-aspartate shuttle pathway (MAS) both being altered by signaling by calcium.

An Architecture forRepresenting Biological Processes based on Networks of Bio-inspired Processors

n this paper we propose the use of Networks of Bio-inspired Processors (NBP) to model some biological phenomena within a computational framework. In particular, we propose the use of an extension of NBP named Network Evolutionary Processors Transducers to simulate chemical transformations of substances. Within a biological process, chemical transformations of substances are basic operations in the change of the state of the cell. Previously, it has been proved that NBP are computationally complete, that is, they are able to solve NP complete problems in linear time, using massively parallel computations. In addition, we propose a multilayer architecture that will allow us to design models of biological processes related to cellular communication as well as their implications in the metabolic pathways. Subsequently, these models can be applied not only to biological-cellular instances but, possibly, also to configure instances of interactive processes in many other fields like population interactions, ecological trophic networks, in dustrial ecosystems, etc.

Incertidumbre en bio-sensores ópticos asociada al desplazamiento espectral de los modos de interferencia de la señal de transducción

El análisis del comportamiento de los modos de interferencia tiene una aplicación cada vez mas amplia, especialmente en el campo de los biosensores opticos. En este tipo de sensores se observa el desplazamiento Δν de los modos de interferencia de la señal de transducción al reconocer un determinado agente biologico. Para medir ese desplazamiento se debe detectar la posición de un máximo o minimo de la senal antes y después de dicho desplazamiento. En este tipo de biosensores un parámetro de gran importancia es el periodo Pν de la senal el cual es inversamente proporcional al espesor óptico h0 del sensor en ausencia de agente biologico. El aumento de dicho periodo mejora la sensibilidad del sensor pero parece dificultar la detección del minimo o maximo. Por tanto, su efecto sobre la incetidumbre del resultado de la medida presentados efectos contrapuestos: la mejora de la sensibilidad frente a la dificultad creciente en la detección del minimo o maximo. En este trabajo, los autores analizan la propagación de incertidumbres en estos sensores utilizando herramientas de ajuste por MM.CC. para la detección de los minimos o máximos de la senal y técnicas de propagación de incertidumbres descritas en los suplementos 2 de la Guia ISO-GUM. El resultado del análisis permite dar una respuesta, justificada desde el punto de vista metrologico, de en que condiciones es conveniente o no aumentar el periodo Pν de la senal.

Marco computacional para la definición de un modelo bio-inspirado en la señalización celular

Las Redes de Procesadores Evolutivos-NEP propuestas en [Mitrana et al., 2001], son un modelo computacional bio-inspirado a partir de la evolución de poblaciones de células, definiendo a nivel sintáctico algunas propiedades biológicas. En este modelo, las células están representadas por medio de palabras que describen secuencias de ADN. Informalmente, en algún instante de tiempo, el sistema evolutivo está representado por una colección de palabras cada una de las cuales representa una célula. El espacio genotipo de las especies, es un conjunto que recoge aquellas palabras que son aceptadas como sobrevivientes (es decir, como \correctas"). Desde el punto de vista de la evolución, las células pertenecen a especies y su comunidad evoluciona de acuerdo a procesos biológicos como la mutación y la división celular. éstos procesos representan el proceso natural de evolución y ponen de manifiesto una característica intrínseca de la naturaleza: el paralelismo. En este modelo, estos procesos son vistos como operaciones sobre palabras. Formalmente, el modelo de las NEP constituyen una arquitectura paralela y distribuida de procesamiento simbólico inspirada en la Máquina de conexión [Hillis, 1981], en el Paradigma de Flujo Lógico [Errico and Jesshope, 1994] y en las Redes de Procesadores Paralelos de Lenguajes (RPPL) [Csuhaj-Varju and Salomaa, 1997]. Al modelo NEP se han ido agregando nuevas y novedosas extensiones hasta el punto que actualmente podemos hablar de una familia de Redes de Procesadores Bio-inspirados (NBP) [Mitrana et al., 2012b]. Un considerable número de trabajos a lo largo de los últimos años han demostrado la potencia computacional de la familia NBP. En general, éstos modelos son computacionalmente completos, universales y eficientes [Manea et al., 2007], [Manea et al., 2010b], [Mitrana and Martín-Vide, 2005]. De acuerdo a lo anterior, se puede afirmar que el modelo NEP ha adquirido hasta el momento un nivel de madurez considerable. Sin embargo, aunque el modelo es de inspiración biológica, sus metas siguen estando motivadas en la Teoría de Lenguajes Formales y las Ciencias de la Computación. En este sentido, los aspectos biológicos han sido abordados desde una perspectiva cualitativa y el acercamiento a la realidad biológica es de forma meramente sintáctica. Para considerar estos aspectos y lograr dicho acercamiento es necesario que el modelo NEP tenga una perspectiva más amplia que incorpore la interacción de aspectos tanto cualitativos como cuantitativos. La contribución de esta Tesis puede considerarse como un paso hacia adelante en una nueva etapa de los NEPs, donde el carácter cuantitativo del modelo es de primordial interés y donde existen posibilidades de un cambio visible en el enfoque de interés del dominio de los problemas a considerar: de las ciencias de la computación hacia la simulación/modelado biológico y viceversa, entre otros. El marco computacional que proponemos en esta Tesis extiende el modelo de las Redes de Procesadores Evolutivos (NEP) y define arquitectura inspirada en la definición de bloques funcionales del proceso de señalización celular para la solución de problemas computacionales complejos y el modelado de fenómenos celulares desde una perspectiva discreta. En particular, se proponen dos extensiones: (1) los Transductores basados en Redes de Procesadores Evolutivos (NEPT), y (2) las Redes Parametrizadas de Procesadores Evolutivos Polarizados (PNPEP). La conservación de las propiedades y el poder computacional tanto de NEPT como de PNPEP se demuestra formalmente. Varias simulaciones de procesos relacionados con la señalización celular son abordadas sintáctica y computacionalmente, con el _n de mostrar la aplicabilidad e idoneidad de estas dos extensiones. ABSTRACT Network of Evolutionary Processors -NEP was proposed in [Mitrana et al., 2001], as a computational model inspired by the evolution of cell populations, which might model some properties of evolving cell communities at the syntactical level. In this model, cells are represented by words which encode their DNA sequences. Informally, at any moment of time, the evolutionary system is described by a collection of words, where each word represents one cell. Cells belong to species and their community evolves according to mutations and division which are defined by operations on words. Only those cells accepted as survivors (correct) are represented by a word in a given set of words, called the genotype space of the species. This feature is analogous with the natural process of evolution. Formally, NEP is based on an architecture for parallel and distributed processing inspired from the Connection Machine [Hillis, 1981], the Flow Logic Paradigm [Errico and Jesshope, 1994] and the Networks of Parallel Language Processors (RPPL) [Csuhaj-Varju and Salomaa, 1997]. Since the date when NEP was proposed, several extensions and variants have appeared engendering a new set of models named Networks of Bio-inspired Processors (NBP) [Mitrana et al., 2012b]. During this time, several works have proved the computational power of NBP. Specifically, their efficiency, universality, and computational completeness have been thoroughly investigated [Manea et al., 2007, Manea et al., 2010b, Mitrana and Martín-Vide, 2005]. Therefore, we can say that the NEP model has reached its maturity. Nevertheless, although the NEP model is biologically inspired, this model is mainly motivated by mathematical and computer science goals. In this context, the biological aspects are only considered from a qualitative and syntactical perspective. In view of this lack, it is important to try to keep the NEP theory as close as possible to the biological reality, extending their perspective incorporating the interplay of qualitative and quantitative aspects. The contribution of this Thesis, can be considered as a starting point in a new era of the NEP model. Then, the quantitative character of the NEP model is mandatory and it can address completely new different types of problems with respect to the classical computational domain (e.g. from the computer science to system biology). Therefore, the computational framework that we propose extends the NEP model and defines an architecture inspired by the functional blocks from cellular signaling in order to solve complex computational problems and cellular phenomena modeled from a discrete perspective. Particularly, we propose two extensions, namely: (1) Transducers based on Network of Evolutionary Processors (NEPT), and (2) Parametrized Network of Polarized Evolutionary Processors (PNPEP). Additionally, we have formally proved that the properties and computational power of NEP is kept in both extensions. Several simulations about processes related with cellular signaling both syntactical and computationally have been considered to show the model suitability.

An eco-friendly way to fire retardant flexible polyurethane foam: layer-by-layer assembly of fully bio-based substances

The objective of the present study is to develop fully renewable and environmentally benign techniques for improving the fire safety of flexible polyurethane foams (PUFs). A multilayered coating made from cationic chitosan (CS) and anionic alginate (AL) was deposited on PUFs through layer-by-layer assembly. This coating system exhibits a slight influence on the thermal stability of PUF, but significantly improves the char formation during combustion. Cone calorimetry reveals that 10 CS-AL bilayers (only 5.7% of the foams weight) lead to a 66% and 11% reduction in peak heat release rate and total heat release, respectively, compared with those of the uncoated control. The notable decreased fire hazards of PUF are attributed to the CS-AL coatings being beneficial to form an insulating protective layer on the surface of burning materials that inhibits the oxygen and heat permeation and slows down the flammable gases in the vapor phase, and thereby improves the flame resistance. This water-based, environmentally benign natural coating will stimulate further efforts in improving fire safety for a variety of polymer substrates.

Perspectivas del cultivo de sorgo azucarero para bio-etanol en España en base a resultados varietales en ensayos multilocales

La especie Sorghum bicolor (L.) Moench., perteneciente a la familia de las gramíneas (Poaceae), es una planta de origen tropical, sensible al fotoperiodo y a la temperatura, que muestra una alta eficiencia fotosintética en condiciones adecuadas de cultivo.

Uncertainty in optical bio-sensors due to the spectral displacement of the interference modes of the transduction signal. Incertidumbre en bio-sensores ópticos asociada al desplazamiento espectral de los modos de interferencia de la señal de transducción

The analysis of the interference modes has an increasing application, especially in the field of optical biosensors. In this type of sensors, the displacement Δν of the interference modes of the transduction signal is observed when a particular biological agent is placed over the biosensor. In order to measure this displacement, the position of a maximum (or a minimum) of the signal must be detected before and after placing the agent over the sensor. A parameter of great importance for this kind of sensors is the period Pν of the signal, which is inversely proportional to the optical thickness h0 of the sensor in the absence of the biological agent. The increase of this period improves the sensitivity of the sensor but it worsens the detection of the maximum. In this paper, authors analyze the propagation of uncertainties in these sensors when using least squares techniques for the detection of the maxima (or minima) of the signal. Techniques described in supplement 2 of the ISO-GUM Guide are used. The result of the analysis allows a metrological educated answer to the question of which is the optimal period Pν of the signal. El análisis del comportamiento de los modos de interferencia tiene una aplicación cada vez más amplia, especialmente en el campo de los biosensores ópticos. En este tipo de sensores se observa el desplazamiento Δν de los modos de interferencia de la señal de transducción al reconocer un de-terminado agente biológico. Para medir ese desplazamiento se debe detectar la posición de un máximo o mínimo de la señal antes y después de dicho desplazamiento. En este tipo de biosensores un parámetro de gran importancia es el periodo Pν de la señal el cual es inversamente proporcional al espesor óptico h0 del sensor en ausencia de agente biológico. El aumento de dicho periodo mejora la sensibilidad del sensor pero parece dificultar la detección del mínimo o máximo. Por tanto, su efecto sobre la incertidumbre del resultado de la medida presenta dos efectos contrapuestos: la mejora de la sensibilidad frente a la dificultad creciente en la detección del mínimo ó máximo. En este trabajo, los autores analizan la propagación de incertidumbres en estos sensores utilizando herramientas de ajuste por MM.CC. para la detección de los mínimos o máximos de la señal y técnicas de propagación de incertidumbres descritas en el suplemento 2 de la Guía ISO-GUM. El resultado del análisis permite dar una respuesta, justificada desde el punto de vista metrológico, de en que condiciones es conveniente o no aumentar el periodo Pν de la señal.

Bio-climatic Design Handbook: designing public space to reach urban sustainability.

The "Bio-climatic Design Handbook: guidelines for the development of planning regulations" is a tool for urban planning and design professionals planning for the construction of public space taking into account bioclimatic and environmental standards. Based on environmental conditions assessment, urban design guidelines are given. These take into account various scales; from the territory to the microclimatic reality. From these general keys for the design of public space the handbook performs recommendations on specific case studies. The application of bioclimatic techniques in urban design promotes comfort in the public space and the respect for the existing environment, while it influences the energy consumption of buildings that conform this open space. The tool was developed in the context of BIOURB project, where Spain and Portugal cooperate writing this bilingual handbook. The case studies are located in this cross-border region.

A simulation environment for bio-inspired heterogeneous chained modular robots

This paper presents a new simulation environment aimed at heterogeneous chained modular robots. This simulator allows testing the feasibility of the design, checking how modules are going to perform in the field and verifying hardware, electronics and communication designs before the prototype is built, saving time and resources. The paper shows how the simulator is built and how it can be set up to adapt to new designs. It also gives some examples of its use showing different heterogeneous modular robots running in different environments.

Economic impacts of climate change on agrifood markets: A bio-economic approach with a focus on the EU

Projections for world food production and prices play a crucial role to evaluate and tackle future food security challenges. Understanding how these projections will be affected by climate change is the main objective of this study. By means of a bio-economic approach we assess the economic impacts of climate change on agrifood markets, providing both a global analysis and a regionalised evaluation within the EU. To account for uncertainty, we analyse the IPCC emission scenario A1B for the 2030 horizon under several simulation scenarios that differ in (1) the climate projection, from HadleyCM3 (warm) or ECHAM5 (mild) global circulation models; and (2) the influence of CO2 effects. Results of this study indicate that agrifood market projections to 2030 are very sensitive to climate change uncertainties and, in particular to the magnitude of the carbon fertilization effect.

Bio-based polymer nanocomposites based on nylon 11 and WS2 inorganic nanotubes

Tungsten disulphide nanotubes (INT-WS2) have been successfully dispersed in a bio-based polyamide matrix (nylon 11) by conventional melt processing. The effect of INT-WS2 content on the morphology, thermal stability, crystallization behaviour and dynamic mechanical properties is investigated. The results indicate that these inorganic nanotubes can be efficiently incorporated into the bio-based polymer matrix without the need for modifiers or surfactants. Additionally, it is found that the non-isothermal crystallization behaviour of nylon 11/INT-WS2 depends on both the cooling rate and INT-WS2 concentration. In particular, crystallization kinetics results demonstrate that the nucleating activity of INTs plays a dominant role in accelerating the crystallization of nylon 11. This fact leads to the appearance of the more-disordered phase at higher temperature. More significantly, it was shown that these INT-WS2 nanocomposites can facilitate a good processability and cost efficiency, and will be of interest for many eco-friendly and medical applications.

Cellular responses to psychomotor stimulant and neuroleptic drugs are abnormal in mice lacking the D1 dopamine receptor

Stimulation of dopamine D1 receptors has profound effects on addictive behavior, movement control, and working memory. Many of these functions depend on dopaminergic systems in the striatum and D1–D2 dopamine receptor synergies have been implicated as well. We show here that deletion of the D1 dopamine receptor produces a neural phenotype in which amphetamine and cocaine, two addictive psychomotor stimulants, can no longer stimulate neurons in the striatum to express cFos or JunB or to regulate dynorphin. By contrast, haloperidol, a typical neuroleptic that acts preferentially at D2-class receptors, remains effective in inducing catalepsy and striatal Fos/Jun expression in the D1 mutants, and these behavioral and neural effects can be blocked by D2 dopamine receptor agonists. These findings demonstrate that D2 dopamine receptors can function without the enabling role of D1 receptors but that D1 dopamine receptors are essential for the control of gene expression and motor behavior by psychomotor stimulants.

Glucocorticoids have state-dependent stimulant effects on the mesencephalic dopaminergic transmission.

An increase in the activity of mesencephalic dopaminergic neurons has been implicated in the appearance of pathological behaviors such as psychosis and drug abuse. Several observations suggest that glucocorticoids might contribute to such an increase in dopaminergic activity. The present experiments therefore analyzed the effects of corticosterone, the major glucocorticoid in the rat, both on dopamine release in the nucleus accumbens of freely moving animals by means of microdialysis, and on locomotor activity, a behavior dependent on accumbens dopamine. Given that glucocorticoids have certain state-dependent neuronal effects, their action on dopamine was studied in situations differing in dopaminergic tonus, including during the light and dark phases of the circadian cycle, during eating, and in groups of animals differing in their locomotor reactivity to novelty. Dopaminergic activity is increased in the dark period, further increased during food-intake, and is higher in rats defined as high responders to novelty than in low responders. Corticosterone, peripherally administered in a dose that approximates stress-induced plasma concentrations, increased extracellular concentrations of dopamine, and this increase was augmented in the dark phase, during eating, and in high responder rats. Corticosterone had little or no effects in the light phase and in low responder rats. Corticosterone also stimulated locomotor activity, an effect that paralleled the release of dopamine and was abolished by neurochemical (6-hydroxydopamine) depletion of accumbens dopamine. In conclusion, glucocorticoids have state-dependent stimulant effects on mesencephalic dopaminergic transmission, and an interaction between these two factors might be involved in the appearance of behavioral disturbances.