Image analysis by moment invariants using a set of step-like basis functions

Moment invariants have been thoroughly studied and repeatedly proposed as one of the most powerful tools for 2D shape identification. In this paper a set of such descriptors is proposed, being the basis functions discontinuous in a finite number of points. The goal of using discontinuous functions is to avoid the Gibbs phenomenon, and therefore to yield a better approximation capability for discontinuous signals, as images. Moreover, the proposed set of moments allows the definition of rotation invariants, being this the other main design concern. Translation and scale invariance are achieved by means of standard image normalization. Tests are conducted to evaluate the behavior of these descriptors in noisy environments, where images are corrupted with Gaussian noise up to different SNR values. Results are compared to those obtained using Zernike moments, showing that the proposed descriptor has the same performance in image retrieval tasks in noisy environments, but demanding much less computational power for every stage in the query chain.

Set agreement and the loneliness failure detector in crash-recovery systems

The set agreement problem states that from n proposed values at most n-1 can be decided. Traditionally, this problem is solved using a failure detector in asynchronous systems where processes may crash but not recover, where processes have different identities, and where all processes initially know the membership. In this paper we study the set agreement problem and the weakest failure detector L used to solve it in asynchronous message passing systems where processes may crash and recover, with homonyms (i.e., processes may have equal identities) and without a complete initial knowledge of the membership.

HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

A Semi-Lagrangian Particle Level Set Finite Element Method for Interface Problems

We present a quasi-monotone semi-Lagrangian particle level set (QMSL-PLS) method for moving interfaces. The QMSL method is a blend of first order monotone and second order semi-Lagrangian methods. The QMSL-PLS method is easy to implement, efficient, and well adapted for unstructured, either simplicial or hexahedral, meshes. We prove that it is unconditionally stable in the maximum discrete norm, � · �h,∞, and the error analysis shows that when the level set solution u(t) is in the Sobolev space Wr+1,∞(D), r ≥ 0, the convergence in the maximum norm is of the form (KT/Δt)min(1,Δt � v �h,∞ /h)((1 − α)hp + hq), p = min(2, r + 1), and q = min(3, r + 1),where v is a velocity. This means that at high CFL numbers, that is, when Δt > h, the error is O( (1−α)hp+hq) Δt ), whereas at CFL numbers less than 1, the error is O((1 − α)hp−1 + hq−1)). We have tested our method with satisfactory results in benchmark problems such as the Zalesak’s slotted disk, the single vortex flow, and the rising bubble.

A new set of integrals of motion to propagate the perturbed two-body problem

A formulation of the perturbed two-body problem that relies on a new set of orbital elements is presented. The proposed method represents a generalization of the special perturbation method published by Peláez et al. (Celest Mech Dyn Astron 97(2):131?150,2007) for the case of a perturbing force that is partially or totally derivable from a potential. We accomplish this result by employing a generalized Sundman time transformation in the framework of the projective decomposition, which is a known approach for transforming the two-body problem into a set of linear and regular differential equations of motion. Numerical tests, carried out with examples extensively used in the literature, show the remarkable improvement of the performance of the new method for different kinds of perturbations and eccentricities. In particular, one notable result is that the quadratic dependence of the position error on the time-like argument exhibited by Peláez?s method for near-circular motion under the J2 perturbation is transformed into linear.Moreover, themethod reveals to be competitive with two very popular elementmethods derived from theKustaanheimo-Stiefel and Sperling-Burdet regularizations.

Molecular tools to improve chestnut management: El Bierzo as a case study

The European chestnut (Castanea sativa Mill.) is a multipurpose species that has been widely cultivated around the Mediterranean basin since ancient times. New varieties were brought to the Iberian Peninsula during the Roman Empire, which coexist since then with native populations that survived the last glaciation. The relevance of chestnut cultivation has being steadily growing since the Middle Ages, until the rural decline of the past century put a stop to this trend. Forest fires and diseases were also major factors. Chestnut cultivation is gaining momentum again due to its economic (wood, fruits) and ecologic relevance, and represents currently an important asset in many rural areas of Europe. In this Thesis we apply different molecular tools to help improve current management strategies. For this study we have chosen El Bierzo (Castile and Leon, NW Spain), which has a centenary tradition of chestnut cultivation and management, and also presents several unique features from a genetic perspective (next paragraph). Moreover, its nuts are widely appreciated in Spain and abroad for their organoleptic properties. We have focused our experimental work on two major problems faced by breeders and the industry: the lack of a fine-grained genetic characterization and the need for new strategies to control blight disease. To characterize with sufficient detail the genetic diversity and structure of El Bierzo orchards, we analyzed DNA from 169 trees grafted for nut production covering the entire region. We also analyzed 62 nuts from all traditional varieties. El Bierzo constitutes an outstanding scenario to study chestnut genetics and the influence of human management because: (i) it is located at one extreme of the distribution area; (ii) it is a major glacial refuge for the native species; (iii) it has a long tradition of human management (since Roman times, at least); and (iv) its geographical setting ensures an unusual degree of genetic isolation. Thirteen microsatellite markers provided enough informativeness and discrimination power to genotype at the individual level. Together with an unexpected level of genetic variability, we found evidence of genetic structure, with three major gene pools giving rise to the current population. High levels of genetic differentiation between groups supported this organization. Interestingly, genetic structure does not match with spatial boundaries, suggesting that the exchange of material and cultivation practices have strongly influenced natural gene flow. The microsatellite markers selected for this study were also used to classify a set of 62 samples belonging to all traditional varieties. We identified several cases of synonymies and homonymies, evidencing the need to substitute traditional classification systems with new tools for genetic profiling. Management and conservation strategies should also benefit from these tools. The avenue of high-throughput sequencing technologies, combined with the development of bioinformatics tools, have paved the way to study transcriptomes without the need for a reference genome. We took advantage of RNA sequencing and de novo assembly tools to determine the transcriptional landscape of chestnut in response to blight disease. In addition, we have selected a set of candidate genes with high potential for developing resistant varieties via genetic engineering. Our results evidenced a deep transcriptional reprogramming upon fungal infection. The plant hormones ET and JA appear to orchestrate the defensive response. Interestingly, our results also suggest a role for auxins in modulating such response. Many transcription factors were identified in this work that interact with promoters of genes involved in disease resistance. Among these genes, we have conducted a functional characterization of a two major thaumatin-like proteins (TLP) that belongs to the PR5 family. Two genes encoding chestnut cotyledon TLPs have been previously characterized, termed CsTL1 and CsTL2. We substantiate here their protective role against blight disease for the first time, including in silico, in vitro and in vivo evidence. The synergy between TLPs and other antifungal proteins, particularly endo-p-1,3-glucanases, bolsters their interest for future control strategies based on biotechnological approaches.

Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices

The diversity of bibliometric indices today poses the challenge of exploiting the relationships among them. Our research uncovers the best core set of relevant indices for predicting other bibliometric indices. An added difficulty is to select the role of each variable, that is, which bibliometric indices are predictive variables and which are response variables. This results in a novel multioutput regression problem where the role of each variable (predictor or response) is unknown beforehand. We use Gaussian Bayesian networks to solve the this problem and discover multivariate relationships among bibliometric indices. These networks are learnt by a genetic algorithm that looks for the optimal models that best predict bibliometric data. Results show that the optimal induced Gaussian Bayesian networks corroborate previous relationships between several indices, but also suggest new, previously unreported interactions. An extended analysis of the best model illustrates that a set of 12 bibliometric indices can be accurately predicted using only a smaller predictive core subset composed of citations, g-index, q2-index, and hr-index. This research is performed using bibliometric data on Spanish full professors associated with the computer science area.

A level set approach for the analysis of flow and compaction during resin infusion in composite materials

Fluid flow and fabric compaction during vacuum assisted resin infusion (VARI) of composite materials was simulated using a level set-based approach. Fluid infusion through the fiber preform was modeled using Darcy’s equations for the fluid flow through a porous media. The stress partition between the fluid and the fiber bed was included by means of Terzaghi’s effective stress theory. Tracking the fluid front during infusion was introduced by means of the level set method. The resulting partial differential equations for the fluid infusion and the evolution of flow front were discretized and solved approximately using the finite differences method with a uniform grid discretization of the spatial domain. The model results were validated against uniaxial VARI experiments through an [0]8 E-glass plain woven preform. The physical parameters of the model were also independently measured. The model results (in terms of the fabric thickness, pressure and fluid front evolution during filling) were in good agreement with the numerical simulations, showing the potential of the level set method to simulate resin infusion

State of the Art and Future Trends in Grid Codes Applicable to Isolated Electrical Systems

Electrical power systems are changing their traditional structure, which was based on a little number of large generating power plants placed at great distances from loads by new models that tend to split the big production nodes in many smaller ones. The set of small groups which are located close to consumers and provide safe and quality energy is called distributed generation (DG). The proximity of the sources to the loads reduces losses associated with transportation and increases overall system efficiency. DG also favors the inclusion of renewable energy sources in isolated electrical systems or remote microgrids, because they can be installed where the natural resource is located. In both cases, as weak grids unable to get help from other nearby networks, it is essential to ensure appropriate behavior of DG sources to guarantee power system safety and stability. The grid codes sets out the technical requirements to be fulfilled for the sources connected in these electrical networks. In technical literature it is rather easy to find and compare grid codes for interconnected electrical systems. However, the existing literature is incomplete and sparse regarding isolated electrical systems and this happens due to the difficulties inherent in the pursuit of codes. Some countries have developed their own legislation only for their island territory (as Spain or France), others apply the same set of rules as in mainland, another group of island countries have elaborated a complete grid code for all generating sources and some others lack specific regulation. This paper aims to make a complete review of the state of the art in grid codes applicable to isolated systems, setting the comparison between them and defining the guidelines predictably followed by the upcoming regulations in these particular systems.