Genetic diversity in rosewood saplings (Aniba rosaeodora ducke, Lauraceae): an ecological approach

This article takes an ecological approach to the genetic diversity of Rosewood (Aniba rosaeodora Ducke) in a central Amazonian terra firme forest north of Manaus. Planted Rosewood setting, under partial shaded canopy, were assessed in terms of fruiting production, frugivory, and seed dispersal. Using RAPD molecular analysis procedures, the influence of the spatial distribution of adult trees on the genetic diversity (polymorphism) of saplings was assessed with genetic samples from 34 reproductive trees and 60 saplings. The density and distribution patterns the reproductive trees did not modify the sapling"s diversity (1.86%, AMOVA). Two types of adult tree dispersion were identified; i) clumped and ii) more widely dispersed. Polymorphism (77.5%) and gene flow were high between these. Although more sapling genetic variability in areas with a higher density of mature plants was not as high as expected, density did not affect the genetic diversity of samplings, indicating a high incidence of gene flow amongst trees. In planted Rosewood population (surrounded by low disturbed forest), fruiting trees experienced a high level of removal of seeds by toucans (Rhamphastidae), about of 50%. The high gene flow found among native trees suggested that toucans, promoting seed rain at short and long distances from maternal trees, actively contribute to the maintenance of genetic diversity within wild rosewood populations.

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

An evaluation of parchments' degradation a hybrid approach

Parchment stands for a multifaceted material made from animal skin, which has been used for centuries as a writing support or as bookbinding. Due to the historic value of objects made of parchment, understanding their degradation and their condition is of utmost importance to archives, libraries and museums, i.e., the assessment of parchment degradation is mandatory, although it is hard to do with traditional methodologies and tools for problem solving. Hence, in this work we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate Parchment Degradation and the respective Degree-of-Confidence that one has on such a happening.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

A high order model for piezoelectric rods: an asymptotic approach

Preprint submitted to International Journal of Solids and Structures. ISSN 0020-7683

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Electronic transport across linear defects in graphene

We investigate the low-energy electronic transport across grain boundaries in graphene ribbons and infinite flakes. Using the recursive Green’s function method, we calculate the electronic transmission across different types of grain boundaries in graphene ribbons. We show results for the charge density distribution and the current flow along the ribbon. We study linear defects at various angles with the ribbon direction, as well as overlaps of two monolayer ribbon domains forming a bilayer region. For a class of extended defect lines with periodicity 3, an analytic approach is developed to study transport in infinite flakes. This class of extended grain boundaries is particularly interesting, since the K and K0 Dirac points are superposed.

Towards human-like bimanual movements in anthropomorphic robots: a nonlinear optimization approach

Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

A novel and efficient approach to new N3-substituted-6,8-diaminopurines

[Excerpt] Purine nucleobases are fundamental biochemicals in living organisms. They have been a valuable inspiration for drug design once they play several key roles in the cell.1 To the best of our knowledge, reported routes to 8-aminopurines are still scarce due to the difficulty in introducing amino groups in this position of the purine ring. Here we report a novel, inexpensive and facile synthetic method to generate N3,N6-disubstituted-6,8-diaminopurines. In our research group, a number of substituted purines have been obtained from a common imidazole precursor, the 5-amino-4-cyanoformimidoyl imidazole 1. Recently, a comprehensive study on the reactivity of imidazoles 1 with nucleophiles under acidic conditions led us to develop experimental methods to incorporate primary amines into the cyanoformimidoyl group.2 (...)

To be or not to be a pseudogene: a molecular epidemiological approach to the mclx genes and its impact in tuberculosis

Tuberculosis presents a myriad of symptoms, progression routes and propagation patterns not yet fully understood. Whereas for a long time research has focused solely on the patient immunity and overall susceptibility, it is nowadays widely accepted that the genetic diversity of its causative agent, Mycobacterium tuberculosis, plays a key role in this dynamic. This study focuses on a particular family of genes, the mclxs (Mycobacterium cyclase/LuxR-like genes), which codify for a particular and nearly mycobacterial-exclusive combination of protein domains. mclxs genes were found to be pseudogenized by frameshift-causing insertion(s)/deletion(s) in a considerable number of M. tuberculosis complex strains and clinical isolates. To discern the functional implications of the pseudogenization, we have analysed the pattern of frameshift-causing mutations in a group of M. tuberculosis isolates while taking into account their microbial-, patient- and disease-related traits. Our logistic regression-based analyses have revealed disparate effects associated with the transcriptional inactivation of two mclx genes. In fact, mclx2 (Rv1358) pseudogenization appears to be primarily driven by the microbial phylogenetic background, being mainly related to the Euro-American (EAm) lineage; on the other hand, mclx3 (Rv2488c) presents a higher tendency for pseudogenization among isolates from patients born on the Western Pacific area, and from isolates causing extra-pulmonary infections. These results contribute to the overall knowledge on the biology of M. tuberculosis infection, whereas at the same time launch the necessary basis for the functional assessment of these so far overlooked genes.

Single-function approach to calibrating whatman n.º 42 filter paper based on suction versus water content relationships

Several suction–water-content (s-w) calibrations for the filter paper method (FPM) used for soil-suction measurement have been published. Most of the calibrations involve a bilinear function (i.e., two different equations) with an inflection point occurring at 60 kPaapproach for defining a continuous calibration function with a smooth transition between the high and low suctions based on a regression analysis of various previously published calibrations obtained for filter paper Whatman No. 42 (W42) is presented and discussed. The approach is applied herein to data obtained from three establish bilinear calibrations (six equations) for W42 filter paper to determine the two fitting parameters of the continuous function. An experimental evaluation of the new calibration show that the suctions estimated by the contact FPM test using the proposed function compare well with suctions measured by other laboratory techniques for two different soils for the suction range of 50 kPa