Control of a robotic arm for transporting objects based on neuro-fuzzy learning visual information

[Abstract] New applications related to robotic manipulation or transportation tasks, with or without physical grasping are being developed. To perform these activities di erent kind of perceptions are need. One of the key perceptions in robotics is vision. However, camera-based systems have inherent errors which a ect the quality of the information obtained. Image distortion slows down information processing and defers data availability to last processing stages, decreasing performance. In this paper, a new approach to correct diverse sources of visual distortions on images in early stages of the data processing is proposed. The goal of the proposed system/algorithm is the computation of the tilt angle of an object transported by a robot. After capturing the image, the computing system extracts the angle using a Fuzzy Filter that corrects all distortions at only one processing step. This filter has been developed by means of Neuro-Fuzzy learning techniques, using data obtained from real experiments. In this way, computing time can be decreased and the performance of the robotic application can be increased. The resulting algorithm has been tried out experimentally in robot transportation tasks in the humanoid robot TEO (Task Environment Operator).Ministerio de Economía y Competitividad; DPI2013-47944-C4-1-RComunidad de Madrid; S2013/MIT-274

Comparison of parasite loads in serum and blood samples from patients in acute and chronic phases of Chagas disease

Molecular methods have been developed for the detection and quantification of Trypanosoma cruzi DNA in blood samples from patients with Chagas disease. However, aspects of sample processing necessary for quantitative real-time PCR (qPCR), such as the addition of guanidine hydrochloride to whole blood samples, may limit timely access to molecular diagnosis. We analysed 169 samples from serum and guanidine-EDTA blood (GEB) obtained from patients in acute and chronic phases of Chagas disease. We applied qPCR targeted to the satellite DNA region. Finally, we compared the parasite loads and cycle of threshold values of the qPCR. The results confirmed the usefulness of serum samples for the detection and quantification of parasite DNA in patients with Chagas disease, especially in the acute phase. However, the parasite loads detected in serum samples from patients in the chronic phase were lower than those detected in GEB samples. The epidemiological implications of the findings are herein discussed. © Cambridge University Press 2018

Approaches for Removal of PAHs in Soils: Bioaugmentation, Biostimulation and Bioattenuation

Polycyclic aromatic hydrocarbons (PAHs)‐contaminated soils have been a concern during last decades; consequently, physicochemical and biological technologies have emerged and evolved with the aim of remediating them. Particularly, biological technologies are considered promising since they are low cost, safe and environmentally friendly. However, their results so far have been diverse and scattered. This chapter includes a review of the current status on bioaugmentation, biostimulation and bioattenuation techniques, which have been applied in PAHs‐contaminated agricultural soils during the last decades. Successes and failures in PAHs remediation applied at microcosm and field levels are exhibited. Furthermore, the effects of microbial inoculum, the soil organic matter and the particle size of the aggregates on the PAHs’ availability and on the subsequent microbial biodegradation are reviewed. Finally, agricultural management systems are considered in the prediction of the behaviour and the end‐point of some contaminants, as well as in the success of applying a biological technique

On the numerical modeling of granular material flows via the Particle Finite Element Method (PFEM)

The aim of this work is to describe a numerical framework for reliably and robustly simulating the different kinematic conditions exhibited by granular materials while spreading ---from a stagnant condition, when the material is at rest, to a transition to granular flow, and back to a deposit profile. The gist of the employed modeling approach was already presented by the authors in a recent work (Cante et al., 2014), but no proper description of the underlying numerical techniques was provided therein. The present paper focuses precisely on the detailed discussion of such numerical techniques, as well as on its rigorous validation with the experimental results obtained by Lajeunesse, et al. in Ref. ( Lajeunesse et al., 2004). The constitutive model is based on the concepts of large strains plasticity. The yield surface is defined in terms of the Drucker Prager yield function, endowed with a deviatoric plastic flow and the elastic part by a hypoelastic model. The plastic flow condition is assumed nearly incompressible, so a u - p mixed formulation, with a stabilization of the pressure term via the Polynomial Pressure Projection (PPP), is employed. The numerical scheme takes as starting point the Particle Finite Element Method (PFEM) in which the spatial domain is continuously redefined by a different nodal reconnection, generated by a Delaunay triangulation. In contrast to classical PFEM approximations ( Idelsohn et al., 2004), in which the free boundary is obtained by a geometrical technique (a-shape method), in this work the boundary is treated as a material surface, and the boundary nodes are removed or inserted by means of an error function. One of the novelties of this work is the use of the so-called Impl-Ex hybrid integration technique to enhance the spectral properties of the algorithmic tangent moduli and thus reduce the number of iterations and robustness of the accompanying Newton-Raphson solution algorithm (compared with fully implicit schemes respectively). The new set of numerical tools implemented in the PFEM algorithm – including new discretization techniques, the use of a projection of the variables between meshes, and the constraint of the free-surface instead using classic a-shape – allows us to eliminate the negative Jacobians present during large deformation problems, which is one of the drawbacks in the simulation of granular flows. Finally, numerical results are compared with the experiments developed in Ref. (Lajeunesse et al., 2004), where a granular mass, initially confined in a cylindrical container, is suddenly allowed to spread by the sudden removal of the container. The study is carried out using different geometries with varying initial aspect ratios. The excellent agreement between computed and experimental results convincingly demonstrates the reliability of the model to reproduce different kinematic conditions in transient and stationary regimes

Skin prick test wheal detection in 3D images via convolutional neural networks

The skin prick test (SPT) is performed to diagnose different types of allergies. This medical procedure requires measuring the size of the skin wheals that appear when the test is performed. However, the manual measurement method is cumbersome and suffers from intraand inter-observer errors. Thus, multiple approaches have been developed to improve the reproducibility of the test. This work aims to improve part of the automated reading of the SPT to improve the reliability of the wheal detection procedure through the use of convolutional neural networks (CNN). Our proposal starts from the 3D images of the SPT from the arm of patients. They are processed for global surface removal, and then a CNN is trained to produce an output mask that detects the wheals. Finally, the contour of each wheal and its largest diameter is obtained. Encouraging results with mean difference 0.966 mm and mean coefficient of variation 7.29% show that the proposed method provides reliable automated skin wheal detection

Investigation of the long effective conjugation length in defect-free insulated molecular wires

Due to the “insulation” of the π-conjugated backbones, insulated molecular wires (IMWs) are expected to be applied to various optoelectronic applications and nanotechnology.[1] Recently, Kazunori et al have succeeded in the synthesis of a self-threading polythiophene with a polyrotaxane-like 3D architecture (PSTB, see Figure 1), for which an intrawire hole mobility of 0.9 cm2 V−1 s−1 has been measured.[2] Here, we aim to evaluate the extent of π-conjugation along polythiophene backbones sheathed within defect-free “insulating” layers. A comparison between the experimental Raman spectra of the self-threading oligomers (i.e. 2STB-5STB) and the corresponding PSTB polymer indicates that: (i) the ratio of relative intensities of the two most intense Raman bands (I1375/1445) increases with the elongation of the size chain but does not saturate up to the pentamer, and (ii) π-conjugation spreads over 17–18 thiophene units in the polymer. Whether the effective conjugation length of the polymer is better described by using the long oligomer extrapolation approach[3] or periodic DFT calculations of the polymer is discussed in detailed by exploiting the very recent potentialities of state-of-the-art quantum chemical simulations of vibrational properties for crystalline solids.[Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech