Damage detection in beams by using artificial neural networks and dynamical parameters

In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

Fast detection of the magnetic easy axis on steel sheet using the continuous rotational Barkhausen method

The magnetic behaviour of most commercial ferromagnetic steels is usually anisotropic presenting a magnetic easy axis. Changes in the direction of this axis can be related to mechanical changes and anomalies that occur in the fabrication process. The present work describes a method that uses a device with permanent magnets to create a precise rotational magnetic field. The device measures continuous Magnetic Barkhausen Noise signals related to the angle of magnetization, in order to determine the direction of the macroscopic magnetic easy axis. It also offers the possibility of obtaining real time parameters that quantify the magnetic anisotropy of the sample. (C) 2011 Elsevier Ltd. All rights reserved.

EX-SITU BIOREMEDIATION OF BRAZILIAN SOIL CONTAMINATED WITH PLASTICIZERS PROCESS WASTES

The aim of this research was to evaluate the bioremediation of a soil contaminated with wastes from a plasticizers industry, located in Sao Paulo, Brazil. A 100-kg soil sample containing alcohols, adipates and phthalates was treated in an aerobic slurry-phase reactor using indigenous and acclimated microorganisms from the sludge of a wastewater treatment plant of the plasticizers industry (11gVSS kg(-1) dry soil), during 120 days. The soil pH and temperature were not corrected during bioremediation; soil humidity was corrected weekly to maintain 40%. The biodegradation of the pollutants followed first-order kinetics; the removal efficiencies were above 61% and, among the analyzed plasticizers, adipate was removed to below the detection limit. Biological molecular analysis during bioremediation revealed a significant change in the dominant populations initially present in the reactor.

CHEMICAL DEGRADATION OF ESFENVALERATE AND HPLC-UV-PAD DETECTION OF INTERMEDIATES AND BY-PRODUCTS

The impact of pyretroids, their by-products and degradation products on humans and the environment is recognized as a serious problem. Despite several studies regarding esfenvalerate toxicity and its detection in water and sediments, there is still a lack of information about its degradation intermediates and by-products in water. In this work, an HPLC method was developed to follow up the degradation of esfenvalerate and to detect the intermediates and by-products formed during the chemical degradation process. The chemical degradation was performed using an esfenvalerate suspension and different concentrations of hydrogen peroxide, temperatures, and pH. The reaction was monitored for 24 hr, and during the kinetic experiments, samples were collected at several reaction times and analyzed by HPLC-UV-PAD. In the degradation process, eleven different compounds (intermediate and by-products) were detected, among them the metabolites 3-phenoxybenzoic acid and 3-phenoxybenzaldehyde. HPLC-UV-PAD proved to be a valuable analytical technique for the rapid and reliable separation and determination of esfenvalerate, its degradation intermediates, and by-products.

Platinum nanoparticles incorporated in silsesquioxane for use in LbL films for the simultaneous detection of dopamine and ascorbic acid

We describe the preparation of platinum nanoparticles (PtNPs) using the 3-n-propylpyridinium silsesquioxane chloride (SiPy+Cl-) as a nanoreactor and stabilizer. The formation of PtNPs was monitored by UV-Vis spectroscopy by measuring the decrease in the intensity of the band at 375 nm, which is attributed to the electronic absorption of PtCl62- ions. TEM images of Pt-SiPy+Cl- nanohybrid indicated an average size of 3-40 nm for PtNPs. The Pt-SiPy+Cl- was used as a polycation in the preparation of layer-by-layer films (LbL) on a glass substrate coated with fluorine-doped tin oxide (FTO) alternating with the polyanion poly(vinyl sulfonic acid) (PVS). The films were electrochemically tested in sulfuric acid to confirm the deposition of Pt-SiPy+Cl- onto the LbL films, observing the adsorption and desorption of hydrogen (E-pa = 0.1 V) and by the redox process of formation for PtO with E-pa = 1.3 V and E-pc = 0.65 V. FTIR and Raman spectra confirmed the presence of the PVS and Pt-SiPy+Cl- in the LbL films. A linear increase in the absorbance in the UV-Vis spectra of the Pt-SiPy+Cl- at 258 nm (pi -> pi* transition of the pyridine groups) with a number of Pt-SiPy+Cl-/PVS or PVS/SiPy+Cl- bilayers (R = 0.992) was observed. These LbL films were tested for the determination of dopamine (DA) in the presence of ascorbic acid (AA) with a detection limit (DL) on the order of 2.6 x 10(-6) mol L-1 and a quantification limit (QL) of 8.6 x 10(-6) mol L-1. The films exhibited a good repeatability and reproducibility, providing a potential difference of 550 mV for the oxidation of DA with AA interferent.

Development of enzymic time-temperature integrators with rapid detection for evaluation of continuous HTST pasteurization processes

The assessment of the thermal process impact in terms of food safety and quality is of great importance for process evaluation and design. This can be accomplished from the analysis of the residence time and temperature distributions coupled with the kinetics of thermal change, or from the use of a proper time-temperature integrator (TTI) as indicator of safety and quality. The objective of this work was to develop and test enzymic TTIs with rapid detection for the evaluation of continuous HTST pasteurization processes (70-85 degrees C, 10-60 s) of low-viscosity liquid foods, such as milk and juices. Enzymes peroxidase, lactoperoxidase and alkaline phosphatase in phosphate buffer were tested and activity was determined with commercial reflectometric strips. Discontinuous thermal treatments at various time-temperature combinations were performed in order to adjust a first order kinetic model of a two-component system. The measured time-temperature history was considered instead of assuming isothermal conditions. Experiments with slow heating and cooling were used to validate the adjusted model. Only the alkaline phosphatase TTI showed potential to be used for the evaluation of pasteurization processes. The choice was based on the obtained z-values of the thermostable and thermolabile fractions, on the cost and on the validation tests. (C) 2012 Elsevier Ltd. All rights reserved.

Ex-situ bioremediation of Brazilian soil contaminated with plasticizers process wastes

The aim of this research was to evaluate the bioremediation of a soil contaminated with wastes from a plasticizers industry, located in São Paulo, Brazil. A 100-kg soil sample containing alcohols, adipates and phthalates was treated in an aerobic slurry-phase reactor using indigenous and acclimated microorganisms from the sludge of a wastewater treatment plant of the plasticizers industry (11gVSS kg-1 dry soil), during 120 days. The soil pH and temperature were not corrected during bioremediation; soil humidity was corrected weekly to maintain 40%. The biodegradation of the pollutants followed first-order kinetics; the removal efficiencies were above 61% and, among the analyzed plasticizers, adipate was removed to below the detection limit. Biological molecular analysis during bioremediation revealed a significant change in the dominant populations initially present in the reactor.

Automatic (data-based) learning of expressive indicators for machine failure detection : a proposal

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Stimulus-induced gamma activity in the electrocorticogram of freely moving telemetric implanted rats: the neuronal signature of novelty detection

During this thesis a new telemetric recording system has been developed allowing ECoG/EEG recordings in freely behaving rodents (Lapray et al., 2008; Lapray et al., in press). This unit has been shown to not generate any discomfort in the implanted animals and to allow recordings in a wide range of environments. In the second part of this work the developed technique has been used to investigate what cortical activity was related to the process of novelty detection in rats’ barrel cortex. We showed that the detection of a novel object is accompanied in the barrel cortex by a transient burst of activity in the γ frequency range (40-47 Hz) around 200 ms after the whiskers contact with the object (Lapray et al., accepted). This activity was associated to a decrease in the lower range of γ frequencies (30-37 Hz). This network activity may represent the optimal oscillatory pattern for the propagation and storage of new information in memory related structures. The frequency as well as the timing of appearance correspond well with other studies concerning novelty detection related burst of activity in other sensory systems (Barcelo et al., 2006; Haenschel et al., 2000; Ranganath & Rainer, 2003). Here, the burst of activity is well suited to induce plastic and long-lasting modifications in neuronal circuits (Harris et al., 2003). The debate is still open whether synchronised activity in the brain is a part of information processing or an epiphenomenon (Shadlen & Movshon, 1999; Singer, 1999). The present work provides further evidence that neuronal network activity in the γ frequency range plays an important role in the neocortical processing of sensory stimuli and in higher cognitive functions.

An inter-comparison between a VIS/IR and a MW satellite-based methods for cloud detection and classification

This thesis is aimed to assess similarities and mismatches between the outputs from two independent methods for the cloud cover quantification and classification based on quite different physical basis. One of them is the SAFNWC software package designed to process radiance data acquired by the SEVIRI sensor in the VIS/IR. The other is the MWCC algorithm, which uses the brightness temperatures acquired by the AMSU-B and MHS sensors in their channels centered in the MW water vapour absorption band. At a first stage their cloud detection capability has been tested, by comparing the Cloud Masks they produced. These showed a good agreement between two methods, although some critical situations stand out. The MWCC, in effect, fails to reveal clouds which according to SAFNWC are fractional, cirrus, very low and high opaque clouds. In the second stage of the inter-comparison the pixels classified as cloudy according to both softwares have been. The overall observed tendency of the MWCC method, is an overestimation of the lower cloud classes. Viceversa, the more the cloud top height grows up, the more the MWCC not reveal a certain cloud portion, rather detected by means of the SAFNWC tool. This is what also emerges from a series of tests carried out by using the cloud top height information in order to evaluate the height ranges in which each MWCC category is defined. Therefore, although the involved methods intend to provide the same kind of information, in reality they return quite different details on the same atmospheric column. The SAFNWC retrieval being very sensitive to the top temperature of a cloud, brings the actual level reached by this. The MWCC, by exploiting the capability of the microwaves, is able to give an information about the levels that are located more deeply within the atmospheric column.

Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.

High-resolution computer simulation of the dynamics of isoelectric focusing using carrier ampholytes: focusing with concurrent electrophoretic mobilization is an isotachophoretic process

Focusing of four hemoglobins with concurrent electrophoretic mobilization was studied by computer simulation. A dynamic electrophoresis simulator was first used to provide a detailed description of focusing in a 100-carrier component, pH 6-8 gradient using phosphoric acid as anolyte and NaOH as catholyte. These results are compared to an identical simulation except that the catholyte contained both NaOH and NaCl. A stationary, steady-state distribution of carrier components and hemoglobins is produced in the first configuration. In the second, the chloride ion migrates into and through the separation space. It is shown that even under these conditions of chloride ion flux a pH gradient forms. All amphoteric species acquire a slight positive charge upon focusing and the whole pattern is mobilized towards the cathode. The cathodic gradient end is stable whereas the anodic end is gradually degrading due to the continuous accumulation of chloride. The data illustrate that the mobilization is a cationic isotachophoretic process with the sodium ion being the leading cation. The peak height of the hemoglobin zones decreases somewhat upon mobilization, but the zones retain a relatively sharp profile, thus facilitating detection. The electropherograms that would be produced by whole column imaging and by a single detector placed at different locations along the focusing column are presented and show that focusing can be commenced with NaCl present in the catholyte at the beginning of the experiment. However, this may require detector placement on the cathodic side of the catholyte/sample mixture interface.

Point Process Methodology for On-line Spatio-temporal Disease Surveillance

The AEGISS (Ascertainment and Enhancement of Gastrointestinal Infection Surveillance and Statistics) project aims to use spatio-temporal statistical methods to identify anomalies in the space-time distribution of non-specific, gastrointestinal infections in the UK, using the Southampton area in southern England as a test-case. In this paper, we use the AEGISS project to illustrate how spatio-temporal point process methodology can be used in the development of a rapid-response, spatial surveillance system. Current surveillance of gastroenteric disease in the UK relies on general practitioners reporting cases of suspected food-poisoning through a statutory notification scheme, voluntary laboratory reports of the isolation of gastrointestinal pathogens and standard reports of general outbreaks of infectious intestinal disease by public health and environmental health authorities. However, most statutory notifications are made only after a laboratory reports the isolation of a gastrointestinal pathogen. As a result, detection is delayed and the ability to react to an emerging outbreak is reduced. For more detailed discussion, see Diggle et al. (2003). A new and potentially valuable source of data on the incidence of non-specific gastro-enteric infections in the UK is NHS Direct, a 24-hour phone-in clinical advice service. NHS Direct data are less likely than reports by general practitioners to suffer from spatially and temporally localized inconsistencies in reporting rates. Also, reporting delays by patients are likely to be reduced, as no appointments are needed. Against this, NHS Direct data sacrifice specificity. Each call to NHS Direct is classified only according to the general pattern of reported symptoms (Cooper et al, 2003). The current paper focuses on the use of spatio-temporal statistical analysis for early detection of unexplained variation in the spatio-temporal incidence of non-specific gastroenteric symptoms, as reported to NHS Direct. Section 2 describes our statistical formulation of this problem, the nature of the available data and our approach to predictive inference. Section 3 describes the stochastic model. Section 4 gives the results of fitting the model to NHS Direct data. Section 5 shows how the model is used for spatio-temporal prediction. The paper concludes with a short discussion.

Detection of apoptosis in vivo using antibodies against caspase-induced neo-epitopes

Cell death induction by apoptosis is an important process in the maintenance of tissue homeostasis as well as tissue destruction during various pathological processes. Consequently, detection of apoptotic cells in situ represents an important technique to assess the extent and impact of cell death in the respective tissue. While scoring of apoptosis by histological assessment of apoptotic cells is still a widely used method, it is likely biased by sensitivity problems and observed-based variations. The availability of caspase-mediated neo-epitope-specific antibodies offers new tools for the detection of apoptosis in situ. Here, we discuss the use of immunohistochemical detection of cleaved caspase 3 and lamin A for the assessment of apoptotic cells in paraffin-embedded liver tissue. Furthermore, we evaluate the effect of tissue pretreatment and antigen retrieval on the sensitivity of apoptosis detection, background staining and maintenance of tissue morphology.

Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.