Fault detection and isolation in robotic manipulators via neural networks: A comparison among three architectures for residual analysis

In this article we discuss artificial neural networks‐based fault detection and isolation (FDI) applications for robotic manipulators. The artificial neural networks (ANNs) are used for both residual generation and residual analysis. A multilayer perceptron (MLP) is employed to reproduce the dynamics of the robotic manipulator. Its outputs are compared with actual position and velocity measurements, generating the so‐called residual vector. The residuals, when properly analyzed, provides an indication of the status of the robot (normal or faulty operation). Three ANNs architectures are employed in the residual analysis. The first is a radial basis function network (RBFN) which uses the residuals of position and velocity to perform fault identification. The second is again an RBFN, except that it uses only the velocity residuals. The third is an MLP which also performs fault identification utilizing only the velocity residuals. The MLP is trained with the classical back‐propagation algorithm and the RBFN is trained with a Kohonen self‐organizing map (KSOM). We validate the concepts discussed in a thorough simulation study of a Puma 560 and with experimental results with a 3‐joint planar manipulator. © 2001 John Wiley & Sons, Inc.     

Urinary proteomic analysis of chronic allograft nephropathy

The pathogenesis of progressive renal allograft injury, which is termed chronic allograft nephropathy (CAN), remains obscure and is currently defined by histology. Prospective protocol-biopsy trials have demonstrated that clinical and standard laboratory tests are insufficiently sensitive indicators of the development and progression of CAN. The study aim was to determine if CAN could be characterized by urinary proteomic data and identify the proteins associated with disease. The urinary proteome of 75 renal transplant recipients and 20 healthy volunteers was analyzed using surface enhanced laser desorption and ionization MS. Patients could be classified into subgroups with normal histology and Banff CAN grades 2-3 with a sensitivity of 86% and a specificity of 92% by applying the classification algorithm Adaboost to urinary proteomic data. Several urinary proteins associated with advanced CAN were identified including α1-microglobulin, β2-microglobulin, prealbumin, and endorepellin, the antiangiogenic C-terminal fragment of perlecan. Increased urinary endorepellin was confirmed by ELISA and increased tissue expression of the endorepellin/perlecan ratio by immunofluoresence analysis of renal biopsies. In conclusion, analysis of urinary proteomic data has further characterized the more severe CAN grades and identified urinary endorepellin, as a potential biomarker of advanced CAN.     

Studies on SiC, DLC and TiO2 thin films as piezoresistive sensor materials for high temperature application

The use of thin films as sensing elements for microsensor applications has been shown very attractive due to their low-cost fabrication, potential for integration with standard CMOS technologies and possibility of deposition on different substrate types. In particular, piezoresistive sensors based on thin films have been commonly developed because can be easily implemented using microfabrication processes and present the best relation between sensitivity and system complexity, which showing great advantages in term of device integration. In our previous works (Fraga et al. 2010, 2011a), we studied undoped and nitrogen-doped PECVD a-SiC thin films as alternative materials to replace the silicon piezoresistors in strain and pressure sensors for harsh environments. Here, we focused our attention on the piezoresistive properties of sputtered silicon carbide (SiC), diamond-like carbon (DLC) and titanium dioxide (TiO₂) thin films. These materials were evaluated in terms of sensitivity or gauge factor and of the influence of the temperature on this sensitivity, allowing a preliminary analysis of the applicability of these thin films in high temperature piezoresistive sensors.     

DISCRETE WAVELET TRANSFORM FOR DENOISING RAMAN SPECTRA OF HUMAN SKIN TISSUES USED IN A DISCRIMINANT DIAGNOSTIC ALGORITHM

In this work, we applied the discrete wavelet transform (DWT) method as a denoising tool for dispersive Raman spectra of skin samples, and we compared the results obtained with the low-order polynomial fitting in a discriminating model based on principal components analysis (PCA). We used a set of 50 Raman spectra of skin tissue fragments diagnosed as normal (N) (25 spectra) and basocellular cell carcinoma (BCC) (25 spectra). A denoising procedure using DWT and its inverse was employed, and the resulting spectra were compared to denoising using low-order polynomial fitting and adjacent averaging smoothing. The tissue spectral profile showed changes in the intensity of bands below 1400 cm^?1 for DWT compared to the denoising by polynomial and smoothing. By applying PCA and Mahalanobis distance in both groups processed, we verified that the filtering method does not alter significantly the discrimination of N and BCC tissues. However, the DWT denoising presented an interesting result, which showed the main components after decomposition of the Raman signal used in the reconstruction.     

Petri net based process scheduling: A model of the control system of flexible manufacturing systems

In this paper, we propose a class of algorithms for the sub-optimal solution of a particular class of problems of process scheduling, particularly focusing on a case study in the area of flexible manufacturing systems (FMSs). The general class of problems we face in our approach is characterized as follows: there is a set of concurrent processes, each formed by a number of temporally related tasks (segments). Tasks are executable by alternate resource sets, different both in performance and costs. Processes and tasks are characterized by release times, due dates, and deadlines. Time constraints are also present in the availability of each resource in resource sets. It has been proven that such a problem does not admit an algorithm for an optimal solution in polynomial time. Our proposed algorithm finds a sub-optimal schedule according to a set of optimization criteria, based on task and process times (earliness, tardiness), and/or time independent costs of resources. Our approach to process scheduling is based on Timed Coloured Petri Nets. We describe the structure of the coordination and scheduling algorithms, concentrating on (i) the general-purpose component, and (ii) the application-dependent component. In particular, the paper focuses on the following issues: (i) theautomatic synthesis of Petri net models of the coordination subsystem, starting from the problem knowledge base; (ii) the dynamic behavior of the coordination subsystem, whose kernel is a High Level Petri net executor, a coordination process based on an original, general purpose algorithm; (iii) the structure of the real-time scheduling subsystem, based on particular heuristic sub-optimal multi-criteria algorithms. Furthermore, the paper defines the interaction mechanisms between the coordination and scheduling subsystems. Our approach clearly distinguishes the mechanism of the net execution from the decision support system. Two conceptually distinct levels, which correspond to two different, interacting implementation modules in the prototype CASE tool, have been defined: theexecutor and thescheduler levels. One of the outstanding differences between these levels is that the executor is conceived as a fast, efficient coordination process, without special-purpose problem-solving capabilities in case of conflicts. The scheduler, on the other hand, is the adaptive, distributed component, whose behavior may heavily depend on the problem class. If the scheduler fails, the executor is, in any case, able to proceed with a general-purpose conflict resolution strategy. Experimental results on the real-time performance of the kernel of the implemented system are finally shown in the paper. The approach described in this paper is at the basis of a joint project with industrial partners for the development of a CASE tool for the simulation of blast furnaces.     

Relative Contribution of Blood Pressure and Renal Sympathetic Nerve Activity to Proximal Tubular Sodium Reabsorption via NHE3 Activity

We examined the effects of an acute increase in blood pressure (BP) and renal sympathetic nerve activity (rSNA) induced by bicuculline (Bic) injection in the paraventricular nucleus of hypothalamus (PVN) or the effects of a selective increase in rSNA induced by renal nerve stimulation (RNS) on the renal excretion of sodium and water and its effect on sodium-hydrogen exchanger 3 (NHE3) activity. Uninephrectomized anesthetized male Wistar rats were divided into three groups: (1) Sham; (2) Bic PVN: (3) RNS + Bic injection into the PVN. BP and rSNA were recorded, and urine was collected prior and after the interventions in all groups. RNS decreased sodium (58%) and water excretion (53%) independently of BP changes (p < 0.05). However, after Bic injection in the PVN during RNS stimulation, the BP and rSNA increased by 30% and 60% (p < 0.05), respectively, diuresis (5-fold) and natriuresis (2.3-fold) were increased (p < 0.05), and NHE3 activity was significantly reduced, independently of glomerular filtration rate changes. Thus, an acute increase in the BP overcomes RNS, leading to diuresis, natriuresis, and NHE3 activity inhibition.     

Comparison of bioactive phytochemical content and release of isothiocyanates in selected brassica sprouts

The consumption of brassica sprouts as raw vegetables provides a fair amount of glucosinolates (GLs) and active plant myrosinase, which enables the breakdown of GLs into health-promoting isothiocyanates (ITCs). This study reports the determination of the main constituents related to human health found in edible sprouts of two Brassica oleracea varieties, broccoli and Tuscan black kale, and two Raphanus sativus varieties, Daikon and Sango. Radish sprouts exhibited the highest ability to produce ITCs, with Daikon showing the greatest level of conversion of GLs into bioactive ITCs (96.5%), followed by Sango (90.0%). Tuscan black kale gave a value of 68.5%, whereas broccoli displayed the lowest with 18.7%. ITCs were not the exclusive GL breakdown products in the two B. oleracea varieties, since nitriles were also produced, thus accounting for the lower conversion observed. Measuring the release of plant ITCs is a valuable tool in predicting the potential level of exposure to these bioactive compounds after the consumption of raw brassica sprouts.     

Superior Cerebellar Atrophy: An Imaging Clue to Diagnose ITPR1-Related Disorders

The inositol 1,4,5-triphosphate receptor type 1 (ITPR1) gene encodes an InsP₃-gated calcium channel that modulates intracellular Ca²⁺ release and is particularly expressed in cerebellar Purkinje cells. Pathogenic variants in the ITPR1 gene are associated with different types of autosomal dominant spinocerebellar ataxia: SCA15 (adult onset), SCA29 (early-onset), and Gillespie syndrome. Cerebellar atrophy/hypoplasia is invariably detected, but a recognizable neuroradiological pattern has not been identified yet. With the aim of describing ITPR1-related neuroimaging findings, the brain MRI of 14 patients with ITPR1 variants (11 SCA29, 1 SCA15, and 2 Gillespie) were reviewed by expert neuroradiologists. To further evaluate the role of superior vermian and hemispheric cerebellar atrophy as a clue for the diagnosis of ITPR1-related conditions, the ITPR1 gene was sequenced in 5 patients with similar MRI pattern, detecting pathogenic variants in 4 of them. Considering the whole cohort, a distinctive neuroradiological pattern consisting in superior vermian and hemispheric cerebellar atrophy was identified in 83% patients with causative ITPR1 variants, suggesting this MRI finding could represent a hallmark for ITPR1-related disorders.     

Development of oxidised and heat-moisture treated potato starch film

This study investigated the effects of sodium hypochlorite oxidation and a heat-moisture treatment of potato starch on the physicochemical, pasting and textural properties of potato starches in addition to the water vapour permeability (WVP) and mechanical properties of potato starch films produced from these starches. The carbonyl contents, carboxyl contents, swelling power, solubility, pasting properties and gel texture of the native, oxidised and heat-moisture treated (HMT) starches were evaluated. The films made of native, oxidised and HMT starches were characterised by thickness, water solubility, colour, opacity, mechanical properties and WVP. The oxidised and HMT starches had lower viscosity and swelling power compared to the native starch. The films produced from oxidised potato starch had decreased solubility, elongation and WVP values in addition to increased tensile strength compared to the native starch films. The HMT starch increased the tensile strength and WVP of the starch films compared to the native starch.     

Zinc Oxide Nanoparticles: Synthesis,Antimicrobial Activity and Food Packaging Applications

Zinc oxide (ZnO) is an inorganic compound widely used in everyday applications. ZnO is currently listed as a generally recognized as safe (GRAS) material by the Food and Drug Administration and is used as food additive. The advent of nanotechnology has led the development of materials with new properties for use as antimicrobial agents. Thus, ZnO in nanoscale has shown antimicrobial properties and potential applications in food preservation. ZnO nanoparticles have been incorporated in polymeric matrices in order to provide antimicrobial activity to the packaging material and improve packaging properties. This review presents the main synthesis methods of ZnO nanoparticles, principal characteristics and mechanisms of antimicrobial action as well as the effect of their incorporation in polymeric matrices. Safety issues such as exposure routes and migration studies are also discussed.