Showing papers by "Technical University of Madrid published in 2009"

The architecture of mutualistic networks minimizes competition and increases biodiversity

Abstract: The main theories of biodiversity either neglect species interactions or assume that species interact randomly with each other. However, recent empirical work has revealed that ecological networks are highly structured, and the lack of a theory that takes into account the structure of interactions precludes further assessment of the implications of such network patterns for biodiversity. Here we use a combination of analytical and empirical approaches to quantify the influence of network architecture on the number of coexisting species. As a case study we consider mutualistic networks between plants and their animal pollinators or seed dispersers. These networks have been found to be highly nested, with the more specialist species interacting only with proper subsets of the species that interact with the more generalist. We show that nestedness reduces effective interspecific competition and enhances the number of coexisting species. Furthermore, we show that a nested network will naturally emerge if new species are more likely to enter the community where they have minimal competitive load. Nested networks seem to occur in many biological and social contexts, suggesting that our results are relevant in a wide range of fields.

A glucosinolate metabolism pathway in living plant cells mediates broad-spectrum antifungal defense.

Abstract: Selection pressure exerted by insects and microorganisms shapes the diversity of plant secondary metabolites. We identified a metabolic pathway for glucosinolates, known insect deterrents, that differs from the pathway activated by chewing insects. This pathway is active in living plant cells, may contribute to glucosinolate turnover, and has been recruited for broad-spectrum antifungal defense responses. The Arabidopsis CYP81F2 gene encodes a P450 monooxygenase that is essential for the pathogen-induced accumulation of 4-methoxyindol-3-ylmethylglucosinolate, which in turn is activated by the atypical PEN2 myrosinase (a type of beta-thioglucoside glucohydrolase) for antifungal defense. We propose that reiterated enzymatic cycles, controlling the generation of toxic molecules and their detoxification, enable the recruitment of glucosinolates in defense responses.

A Review of Wireless Sensor Technologies and Applications in Agriculture and Food Industry: State of the Art and Current Trends

Abstract: The aim of the present paper is to review the technical and scientific state of the art of wireless sensor technologies and standards for wireless communications in the Agri-Food sector. These technologies are very promising in several fields such as environmental monitoring, precision agriculture, cold chain control or traceability. The paper focuses on WSN (Wireless Sensor Networks) and RFID (Radio Frequency Identification), presenting the different systems available, recent developments and examples of applications, including ZigBee based WSN and passive, semi-passive and active RFID. Future trends of wireless communications in agriculture and food industry are also discussed.

Horizontal visibility graphs: Exact results for random time series

Abstract: networks. This procedure allows us to apply methods of complex network theory for characterizing time series. In this work we present the horizontal visibility algorithm, a geometrically simpler and analytically solvable version of our former algorithm, focusing on the mapping of random series series of independent identically distributed random variables. After presenting some properties of the algorithm, we present exact results on the topological properties of graphs associated with random series, namely, the degree distribution, the clustering coefficient, and the mean path length. We show that the horizontal visibility algorithm stands as a simple method to discriminate randomness in time series since any random series maps to a graph with an exponential degree distribution of the shape Pk=1 /32 /3 k2 , independent of the probability distribution from which the series was generated. Accordingly, visibility graphs with other Pk are related to nonrandom series. Numerical simulations confirm the accuracy of the theorems for finite series. In a second part, we show that the method is able to distinguish chaotic series from independent and identically distributed i.i.d. theory, studying the following situations: i noise-free low-dimensional chaotic series, ii low-dimensional noisy chaotic series, even in the presence of large amounts of noise, and iii high-dimensional chaotic series coupled map lattice, without needs for additional techniques such as surrogate data or noise reduction methods. Finally, heuristic arguments are given to explain the topological properties of chaotic series, and several sequences that are conjectured to be random are analyzed.

The role of new technologies in the learning process: Moodle as a teaching tool in Physics

Abstract: In this work we present an overview of the undergraduate online Physics course that we have implemented in the Moodle platform. This course has been developed as an enhancement of the face-to-face courses. The aim of this course is to create an online learning community which helps both teachers and students to have a virtual space where we can share knowledge through different kinds of supervised activities, chats and forums. As we will show in this paper, the students' response to this initiative has been very good: the online Physics course helps them to reinforce their abilities and knowledge.

Estimation of turbulent convection velocities and corrections to Taylor's approximation

Abstract: A new method is introduced for estimating the convection velocity of individual modes in turbulent shear flows that, in contrast to most previous ones, only requires spectral information in the temporal or spatial direction over which a modal decomposition is desired, while only using local derivatives in other directions. If no spectral information is desired, the method provides a natural definition for the average convection velocity, as well as a way to estimate the accuracy of the frozen-turbulence approximation. Existing data from numerical turbulent channels at friction Reynolds numbers Reτ 1900 are used to validate the new method against classical ones, and to characterize the dependence of the convection velocity on the eddy wavelength and wall distance. The results indicate that the small scales in turbulent channels travel at the local mean velocity, while large ‘global’ modes travel at a more uniform speed proportional to the bulk velocity. To estimate the systematic deviations introduced in experimental spectra by the use of Taylor’s approximation with a wavelengthindependent convection velocity, a semi-empirical fit to the computed convection velocities is provided. It represents well the data throughout the Reynolds number range of the simulations. It is shown that Taylor’s approximation not only displaces the large scales near the wall to shorter apparent wavelengths but also modifies the shape of the spectrum, giving rise to spurious peaks similar to those observed in some experiments. To a lesser extent the opposite is true above the logarithmic layer. The effect increases with the Reynolds number, suggesting that some of the recent challenges to the k −1 x energy spectrum may have to be reconsidered.

Application of a LES technique to characterize the wake deflection of a wind turbine in yaw

Abstract: When a wind turbine works in yaw, the wake intensity and the power production of the turbine become slightly smaller and a deflection of the wake is induced. Therefore, a good understanding of this effect would allow an active control of the yaw angle of upstream turbines to steer the wake away from downstream machines, reducing its effect on them. In wind farms where interaction between turbines is significant, it is of interest to maximize the power output from the wind farm as a whole and to reduce fatigue loads on downstream turbines due to the increase of turbulence intensity in wakes. A large eddy simulation model with particular wind boundary conditions has been used recently to simulate and characterize the turbulence generated by the presence of a wind turbine and its evolution downstream the machine. The simplified turbine is placed within an environment in which relevant flow properties like wind speed profile, turbulence intensity and the anisotropy of turbulence are found to be similar to the ones of the neutral atmosphere. In this work, the model is used to characterize the wake deflection for a range of yaw angles and thrust coefficients of the turbine. The results are compared with experimental data obtained by other authors with a particle image velocimetry technique from wind tunnel experiments. Also, a comparison with simple analytical correlations is carried out. Copyright © 2009 John Wiley & Sons, Ltd.

The visibility graph: A new method for estimating the Hurst exponent of fractional Brownian motion

Abstract: Fractional Brownian motion (fBm) has been used as a theoretical framework to study real-time series appearing in diverse scientific fields. Because of its intrinsic nonstationarity and long-range dependence, its characterization via the Hurst parameter, H, requires sophisticated techniques that often yield ambiguous results. In this work we show that fBm series map into a scale-free visibility graph whose degree distribution is a function of H. Concretely, it is shown that the exponent of the power law degree distribution depends linearly on H. This also applies to fractional Gaussian noises (fGn) and generic f−β noises. Taking advantage of these facts, we propose a brand new methodology to quantify long-range dependence in these series. Its reliability is confirmed with extensive numerical simulations and analytical developments. Finally, we illustrate this method quantifying the persistent behavior of human gait dynamics.

Nanoparticle penetration and transport in living pumpkin plants: in situ subcellular identification

Abstract: In recent years, the application of nanotechnology in several fields of bioscience and biomedicine has been studied. The use of nanoparticles for the targeted delivery of substances has been given special attention and is of particular interest in the treatment of plant diseases. In this work both the penetration and the movement of iron-carbon nanoparticles in plant cells have been analyzed in living plants of Cucurbita pepo. The nanoparticles were applied in planta using two different application methods, injection and spraying, and magnets were used to retain the particles in movement in specific areas of the plant. The main experimental approach, using correlative light and electron microscopy provided evidence of intracellular localization of nanoparticles and their displacement from the application point. Long range movement of the particles through the plant body was also detected, particles having been found near the magnets used to immobilize and concentrate them. Furthermore, cell response to the nanoparticle presence was detected. Nanoparticles were capable of penetrating living plant tissues and migrating to different regions of the plant, although movements over short distances seemed to be favoured. These findings show that the use of carbon coated magnetic particles for directed delivery of substances into plant cells is a feasible application.

Collaborative filtering adapted to recommender systems of e-learning

Abstract: In the context of e-learning recommender systems, we propose that the users with greater knowledge (for example, those who have obtained better results in various tests) have greater weight in the calculation of the recommendations than the users with less knowledge. To achieve this objective, we have designed some new equations in the nucleus of the memory-based collaborative filtering, in such a way that the existent equations are extended to collect and process the information relative to the scores obtained by each user in a variable number of level tests.

Topological analysis of polymeric melts: chain-length effects and fast-converging estimators for entanglement length.

Abstract: Primitive path analyses of entanglements are performed over a wide range of chain lengths for both bead spring and atomistic polyethylene polymer melts. Estimators for the entanglement length N_{e} which operate on results for a single chain length N are shown to produce systematic O(1/N) errors. The mathematical roots of these errors are identified as (a) treating chain ends as entanglements and (b) neglecting non-Gaussian corrections to chain and primitive path dimensions. The prefactors for the O(1/N) errors may be large; in general their magnitude depends both on the polymer model and the method used to obtain primitive paths. We propose, derive, and test new estimators which eliminate these systematic errors using information obtainable from the variation in entanglement characteristics with chain length. The new estimators produce accurate results for N_{e} from marginally entangled systems. Formulas based on direct enumeration of entanglements appear to converge faster and are simpler to apply.

How do personality, team processes and task characteristics relate to job satisfaction and software quality?

Abstract: This article analyses the relationships between personality, team processes, task characteristics, product quality and satisfaction in software development teams. The data analysed here were gathered from a sample of 35 teams of students (105 participants). These teams applied an adaptation of an agile methodology, eXtreme Programming (XP), to develop a software product. We found that the teams with the highest job satisfaction are precisely the ones whose members score highest for the personality factors agreeableness and conscientiousness. The satisfaction levels are also higher when the members can decide how to develop and organize their work. On the other hand, the level of satisfaction and cohesion drops the more conflict there is between the team members. Finally, the teams exhibit a significant positive correlation between the personality factor extraversion and software product quality.

A pivotal role of the basic leucine zipper transcription factor bZIP53 in the regulation of Arabidopsis seed maturation gene expression based on heterodimerization and protein complex formation.

Abstract: Transcription of Arabidopsis thaliana seed maturation (MAT) genes is controlled by members of several transcription factor families, such as basic leucine zippers (bZIPs), B3s, MYBs, and DOFs. In this work, we identify Arabidopsis bZIP53 as a novel transcriptional regulator of MAT genes. bZIP53 expression in developing seeds precedes and overlaps that of its target genes. Gain- and loss-of-function approaches indicate a correlation between the amount of bZIP53 protein and MAT gene expression. Specific in vivo and in vitro binding of bZIP53 protein to a G-box element in the albumin 2S2 promoter is demonstrated. Importantly, heterodimerization with bZIP10 or bZIP25, previously described bZIP regulators of MAT gene expression, significantly enhances DNA binding activity and produces a synergistic increase in target gene activation. Full-level target gene activation is strongly correlated with the ratio of the correspondent bZIP heterodimerization partners. Whereas bZIP53 does not interact with ABI3, a crucial transcriptional regulator in Arabidopsis seeds, ternary complex formation between the bZIP heterodimers and ABI3 increases the expression of MAT genes in planta. We therefore propose that heterodimers containing bZIP53 participate in enhanceosome formation to produce a dramatic increase in MAT gene transcription.

The NADPH-oxidase AtrbohB plays a role in Arabidopsis seed after-ripening.

Abstract: Summary • Seeds can enter a state of dormancy, in which they do not germinate under optimal environmental conditions. Dormancy can be broken during seed after-ripening in the low-hydrated state. • By screening enhancer trap lines of Arabidopsis, we identified a role for the NADPH-oxidase AtrbohB in after-ripening. Semiquantitative PCR was used to investigate AtrbohB transcripts in seeds. These methods were complemented with a pharmacological approach using the inhibitor diphenylene iodonium chloride (DPI) and biomechanical measurements in the Brassicaceae seed model system cress (Lepidium sativum) as well as protein carbonylation assays. • atrbohB mutants fail to after-ripen and show reduced protein oxidation. AtrbohB pre-mRNA is alternatively spliced in seeds in a hormonally and developmentally regulated manner. AtrbohB is a major producer of superoxide in germinating Arabidopsis seeds, and inhibition of superoxide production by diphenylene iodonium (DPI) leads to a delay in Arabidopsis and cress seed germination and cress endosperm weakening. • Reactive oxygen species produced by AtrbohB during after-ripening could act via abscisic acid (ABA) signalling or post-translational protein modifications. Alternative splicing could be a general mechanism in after-ripening: by altered processing of stored pre-mRNAs seeds could react quickly to environmental changes.

Latent Force Models

Abstract: Purely data driven approaches for machine learning present diculties when data is scarce relative to the complexity of the model or when the model is forced to extrapolate On the other hand, purely mechanistic approaches need to identify and specify all the interactions in the problem at hand (which may not be feasible) and still leave the issue of how to parameterize the system In this paper, we present a hybrid approach using Gaussian processes and dierential equations to combine data driven modelling with a physical model of the system We show how dierent, physically-inspired, kernel functions can be developed through sensible, simple, mechanistic assumptions about the underlying system The versatility of our approach is illustrated with three case studies from computational biology, motion capture and geostatistics

Health‐related fitness in adolescents: underweight, and not only overweight, as an influencing factor. The AVENA study

Abstract: This study investigated differences in health-related fitness (20-m shuttle run, handgrip, bent arm hang, standing long jump, shuttle run 4 x 10 m and sit and reach tests) in 2474 Spanish adolescents (1196 boys and 1278 girls; age 13-18.5 years) classed as underweight, normal weight, overweight or obese according to body mass index. Body fat and fat-free mass were derived from skinfold thickness. The prevalence of underweight was higher than obesity in girls (4.8% vs 3.0%, respectively; P<0.05) and the opposite in boys (3.9% vs 5.8%, respectively; P<0.05). Underweight was associated with a higher performance in the bent arm hang test in girls (P<0.05) and a lower performance in handgrip in both genders (P<0.01) compared with normal weight. Overweight and obese adolescents presented a lower performance in 20-m shuttle run, bent arm hang, standing long jump and shuttle run 4 x 10 m tests (P<0.001), but a higher performance in handgrip strength (P<0.001) compared with normal weight. In weight-bearing tests, the association became non-significant after adjusting for fat mass. In conclusion, not only overweight and obesity but also underweight seem to be determinants of health-related fitness in adolescents. The associations could be related to differences in body composition.

Counting Synapses Using FIB/SEM Microscopy: A True Revolution for Ultrastructural Volume Reconstruction.

Abstract: The advent of transmission electron microscopy (TEM) in the 1950’s represented a fundamental step in the study of neuronal circuits. The application of this technique soon led to the realization that the number of synapses changes during the course of normal life, as well as under certain pathological or experimental circumstances. Since then, one of the main goals in neurosciences has been to define simple and accurate methods to estimate the magnitude of these changes. Contrary to analysing single sections, TEM reconstructions are extremely time-consuming and difficult. Therefore, most quantitative studies use stereological methods to define the three-dimensional characteristics of synaptic junctions that are studied in two dimensions. Here, to count the exact number of synapses per unit of volume we have applied a new three-dimensional reconstruction method that involves the combination of focused ion beam milling and scanning electron microscopy (FIB/SEM). We show that the images obtained with FIB/SEM are similar to those obtained with TEM, but with the advantage that FIB/SEM permits serial reconstructions of large volumes of tissue to be generated rapidly and automatically. Furthermore, we compared the estimates of the number of synapses obtained with stereological methods with the values obtained by FIB/SEM reconstructions. We concluded that FIB/SEM not only provides the actual number of synapses per volume but it is also much easier and faster to use than other currently available TEM methods. More importantly, it also avoids most of the errors introduced by stereological methods and overcomes the difficulties associated with these techniques.

Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process

Abstract: Machine tool automation is an important aspect for manufacturing companies facing the growing demand of profitability and high quality products as a key for competitiveness. The purpose of supervising machining processes is to detect interferences that would have a negative effect on the process but mainly on the product quality and production time. In a manufacturing environment, the prediction of surface roughness is of significant importance to achieve this objective. This paper shows the efficacy of two different machine learning classification methods, Bayesian networks and artificial neural networks, for predicting surface roughness in high-speed machining. Experimental tests are conducted using the same data set collected in our own milling process for each classifier. Various measures of merit of the models and statistical tests demonstrate the superiority of Bayesian networks in this field. Bayesian networks are also easier to interpret that artificial neural networks.

Optical Slot-Waveguide Based Biochemical Sensors

Abstract: Slot-waveguides allow light to be guided and strongly confined inside a nanometer-scale region of low refractive index. Thus stronger light-analyte interaction can be obtained as compared to that achievable by a conventional waveguide, in which the propagating beam is confined to the high-refractive-index core of the waveguide. In addition, slot-waveguides can be fabricated by employing CMOS compatible materials and technology, enabling miniaturization, integration with electronic, photonic and fluidic components in a chip, and mass production. These advantages have made the use of slot-waveguides for highly sensitive biochemical optical integrated sensors an emerging field. In this paper, recent achievements in slot-waveguide based biochemical sensing will be reviewed. These include slot-waveguide ring resonator based refractometric label-free biosensors, label-based optical sensing, and nano-opto-mechanical sensors.

Developing search strategies for detecting relevant experiments

Abstract: Our goal is to analyze the optimality of search strategies for use in systematic reviews of software engineering experiments. Studies retrieval is an important problem in any evidence-based discipline. This question has not been examined for evidence-based software engineering as yet. We have run several searches exercising different terms denoting experiments to evaluate their recall and precision. Based on our evaluation, we propose using a high recall strategy when there are plenty of resources or the results need to be exhaustive. For any other case, we propose optimal, or even acceptable, search strategies. As a secondary goal, we have analysed trends and weaknesses in terminology used in articles reporting software engineering experiments. We have found that it is impossible for a search strategy to retrieve 100% of the experiments of interest (as happens in other experimental disciplines), because of the shortage of reporting standards in the community.