Time-lapse geophysical investigations over known archaeological features using electrical resistivity imaging and earth resistance

Electrical methods of geophysical survey are known to produce results that are hard to predict at different times of the year, and under differing weather conditions. This is a problem which can lead to misinterpretation of archaeological features under investigation. The dynamic relationship between a ‘natural’ soil matrix and an archaeological feature is a complex one, which greatly affects the success of the feature’s detection when using active electrical methods of geophysical survey. This study has monitored the gradual variation of measured resistivity over a selection of study areas. By targeting difficult to find, and often ‘missing’ electrical anomalies of known archaeological features, this study has increased the understanding of both the detection and interpretation capabilities of such geophysical surveys. A 16 month time-lapse study over 4 archaeological features has taken place to investigate the aforementioned detection problem across different soils and environments. In addition to the commonly used Twin-Probe earth resistance survey, electrical resistivity imaging (ERI) and quadrature electro-magnetic induction (EMI) were also utilised to explore the problem. Statistical analyses have provided a novel interpretation, which has yielded new insights into how the detection of archaeological features is influenced by the relationship between the target feature and the surrounding ‘natural’ soils. The study has highlighted both the complexity and previous misconceptions around the predictability of the electrical methods. The analysis has confirmed that each site provides an individual and nuanced situation, the variation clearly relating to the composition of the soils (particularly pore size) and the local weather history. The wide range of reasons behind survey success at each specific study site has been revealed. The outcomes have shown that a simplistic model of seasonality is not universally applicable to the electrical detection of archaeological features. This has led to the development of a method for quantifying survey success, enabling a deeper understanding of the unique way in which each site is affected by the interaction of local environmental and geological conditions.

Catechol biosensing using a nanostructured layer-by-layer film containing Cl-catechol 1,2-dioxygenase

dThe detection of aromatic compounds from pesticides and industrial wastewater has become of great interest, since these compounds withstand chemical oxidation and biological degradation, accumulating in the environment. In this work, a highly sensitive biosensor for detecting catechol was obtained with the immobilization of Cl-catechol 1,2-dioxygenase (CCD) in nanostructured films. CCD layers were alternated with poly(amidoamine) generation 4 (PAMAM G4) dendrimer using the electrostatic layer-by-layer (LbL) technique. Circular dichroism (CD) measurements indicated that the immobilized CCD preserved the same conformation as in solution. The thickness of the very first CCD layers in the LbL films was estimated at ca. 3.6 nm, as revealed by surface plasmon resonance (SPR). PAMAM/CCD 10-bilayer films were employed in detecting diluted catechol solutions using either an optical or electrical approach. Due to the mild immobilization conditions employed, especially regarding the pH and ionic strength of the dipping solutions, CCD remained active in the films for periods longer than 3 weeks. The optical detection comprised absorption experiments in which the formation of cis-cis muconic acid, resulting from the reaction between CCD and catechol, was monitored by measuring the absorbance at 260 nm after film immersion in catechol solutions. The electrical detection was carried out using LbL films deposited onto gold-interdigitated electrodes immersed in aqueous solutions at different catechol concentrations. Using impedance spectroscopy in a broad frequency range (1Hz-1kHz), we could detect catechol in solutions at concentrations as low as 10(-10) M. (c) 2005 Elsevier B.V. All rights reserved.

Imunossensores à base de filmes nanoestruturados de fibroína da seda - peptídeo antigênico NS5A-1-vanadato de ítrio: európio para detecção de Hepatite C

Pós-graduação em Química - IQ

Real-time detection of pneumothorax using electrical impedance tomogyaphy

Objectives: Pneumothorax is a frequent complication during mechanical ventilation. Electrical impedance tomography (EIT) is a noninvasive tool that allows real-time imaging of regional ventilation. The purpose of this study was to 1) identify characteristic changes in the EIT signals associated with pneumothoraces; 2) develop and fine-tune an algorithm for their automatic detection; and 3) prospectively evaluate this algorithm for its sensitivity and specificity in detecting pneumothoraces in real time. Design: Prospective controlled laboratory animal investigation. Setting: Experimental Pulmonology Laboratory of the University of Sao Paulo. Subjects: Thirty-nine anesthetized mechanically ventilated supine pigs (31.0 +/- 3.2 kg, mean +/- SD). Interventions. In a first group of 18 animals monitored by EIT, we either injected progressive amounts of air (from 20 to 500 mL) through chest tubes or applied large positive end-expiratory pressure (PEEP) increments to simulate extreme lung overdistension. This first data set was used to calibrate an EIT-based pneumothorax detection algorithm. Subsequently, we evaluated the real-time performance of the detection algorithm in 21 additional animals (with normal or preinjured lungs), submitted to multiple ventilatory interventions or traumatic punctures of the lung. Measurements and Main Results: Primary EIT relative images were acquired online (50 images/sec) and processed according to a few imaging-analysis routines running automatically and in parallel. Pneumothoraces as small as 20 mL could be detected with a sensitivity of 100% and specificity 95% and could be easily distinguished from parenchymal overdistension induced by PEEP or recruiting maneuvers, Their location was correctly identified in all cases, with a total delay of only three respiratory cycles. Conclusions. We created an EIT-based algorithm capable of detecting early signs of pneumothoraces in high-risk situations, which also identifies its location. It requires that the pneumothorax occurs or enlarges at least minimally during the monitoring period. Such detection was operator-free and in quasi real-time, opening opportunities for improving patient safety during mechanical ventilation.

Dendrimer-assisted immobilization of alcohol dehydrogenase in nanostructured films for biosensing: Ethanol detection using electrical capacitance measurements

The selective determination of alcohol molecules either in aqueous solutions or in vapor phase is of great importance for several technological areas. In the last years, a number of researchers have reported the fabrication of highly sensitive sensors for ethanol detection, based upon specific enzymatic reactions occurring at the surface of enzyme-containing electrodes. In this study, the enzyme alcohol dehydrogenase (ADH) was immobilized in a layer-by-layer fashion onto Au-interdigitated electrodes (IDEs), in conjunction with layers of PAMAM dendrimers. The immobilization process was followed in Teal time using quartz crystal microbalance (QCM), indicating that an average mass of 52.1 ng of ADH was adsorbed at each deposition step. Detection was carried out using a novel strategy entirely based upon electrical capacitance measurements, through which ethanol could be detected at concentrations of 1 part per million by volume (ppmv). (C) 2007 Elsevier B.V. All rights reserved.

Disturbance detection for optimal database storage in electrical distribution systems using artificial immune systems with negative selection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Partial discharge in power distribution electrical systems: pulse propagation models and detection optimization

Investigation on impulsive signals, originated from Partial Discharge (PD) phenomena, represents an effective tool for preventing electric failures in High Voltage (HV) and Medium Voltage (MV) systems. The determination of both sensors and instruments bandwidths is the key to achieve meaningful measurements, that is to say, obtaining the maximum Signal-To-Noise Ratio (SNR). The optimum bandwidth depends on the characteristics of the system under test, which can be often represented as a transmission line characterized by signal attenuation and dispersion phenomena. It is therefore necessary to develop both models and techniques which can characterize accurately the PD propagation mechanisms in each system and work out the frequency characteristics of the PD pulses at detection point, in order to design proper sensors able to carry out PD measurement on-line with maximum SNR. Analytical models will be devised in order to predict PD propagation in MV apparatuses. Furthermore, simulation tools will be used where complex geometries make analytical models to be unfeasible. In particular, PD propagation in MV cables, transformers and switchgears will be investigated, taking into account both irradiated and conducted signals associated to PD events, in order to design proper sensors.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Neuronal coincidence detection by voltage-sensitive electrical synapses

Coincidence detection is important for functions as diverse as Hebbian learning, binaural localization, and visual attention. We show here that extremely precise coincidence detection is a natural consequence of the normal function of rectifying electrical synapses. Such synapses open to bidirectional current flow when presynaptic cells depolarize relative to their postsynaptic targets and remain open until well after completion of presynaptic spikes. When multiple input neurons fire simultaneously, the synaptic currents sum effectively and produce a large excitatory postsynaptic potential. However, when some inputs are delayed relative to the rest, their contributions are reduced because the early excitatory postsynaptic potential retards the opening of additional voltage-sensitive synapses, and the late synaptic currents are shunted by already opened junctions. These mechanisms account for the ability of the lateral giant neurons of crayfish to sum synchronous inputs, but not inputs separated by only 100 μsec. This coincidence detection enables crayfish to produce reflex escape responses only to very abrupt mechanical stimuli. In light of recent evidence that electrical synapses are common in the mammalian central nervous system, the mechanisms of coincidence detection described here may be widely used in many systems.

Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

Fault Detection in Power Distribution Systems Using Automated Integration of Computational Intelligence Tools

The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Is Nitric Oxide a Mediator of the Effects of Low-Intensity Electrical Stimulation on Bone in Ovariectomized Rats?

Low-intensity electrical stimulation (LIES) may counteract the effects of ovariectomy (OVX) on nitric oxide synthase (NOS) expression, osteocyte viability, bone structure, and microarchitecture in rats (Lirani-Galvo et al., Calcif Tissue Int 84:502-509, 2009). The aim of the present study was to investigate if these effects of LIES could be mediated by NO. We analyzed the effects of NO blockage (by l-NAME) in the response to LIES on osteocyte viability, bone structure, and microarchitecture in OVX rats. Sixty rats (200-220 g) were divided into six groups: sham, sham-l-NAME (6 mg/kg/day), OVX, OVX-l-NAME, OVX-LIES, and OVX-LIES-l-NAME. After 12 weeks, rats were killed and tibiae collected for histomorphometric analysis and immunohistochemical detection of endothelial NOS (eNOS), inducible NOS (iNOS), and osteocyte apoptosis (caspase-3 and TUNEL). In the presence of l-NAME, LIES did not counteract the OVX-induced effects on bone volume and trabecular number (as on OVX-LIES). l-NAME blocked the stimulatory effects of LIES on iNOS and eNOS expression of OVX rats. Both l-NAME and LIES decreased osteocyte apoptosis. Our results showed that in OVX rats l-NAME partially blocks the effects of LIES on bone structure, turnover, and expression of iNOS and eNOS, suggesting that NO may be a mediator of some positive effects of LIES on bone.

Low-Intensity Electrical Stimulation Counteracts the Effects of Ovariectomy on Bone Tissue of Rats: Effects on Bone Microarchitecture, Viability of Osteocytes, and Nitric Oxide Expression

Low Intensity Electrical Stimulation (LIES) has been used for bone repair, but little is known about its effects on bone after menopause. Osteocytes probably play a role in mediating this physical stimulus and they could act as transducers through the release of biochemical signals, such as nitric oxide (NO). The aim of the present study was to investigate the effects of LIES on bone structure and remodeling, NOS expression and osteocyte viability in ovariectomized (OVX) rats. Thirty rats (200-220 g) were divided into 3 groups: SHAM, OVX, and OVX subjected to LIES (OVX + LIES) for 12 weeks. Following the protocol, rats were sacrificed and tibias were collected for histomorphometric analysis and immunohistochemical detection of endothelial NO synthase (eNOS), inducible NOS (iNOS), and osteocyte apoptosis (caspase-3 and TUNEL). OVX rats showed significant (p < 0.05 vs. SHAM) decreased bone volume (10% vs. 25%) and trabecular number (1.7 vs. 3.9), and increased eroded surfaces (4.7% vs. 3.2%) and mineralization surfaces (15.9% vs. 7.7%). In contrast, after LIES, all these parameters were significantly different from OVX but not different from SHAM. eNOS and iNOS were similarly expressed in subperiosteal regions of tibiae cortices of SHAM, not expressed in OVX, and similarly expressed in OVX + LIES when compared to SHAM. In OVX, the percentage of apoptotic osteocytes (24%) was significantly increased when compared to SHAM (11%) and OVX + LIES (8%). Our results suggest that LIES counteracts some effects of OVX on bone tissue preserving bone structure and microarchitecture, iNOS and eNOS expression, and osteocyte viability.

An Alternative Optical Method for Acoustic Resonance Detection in HID Lamps

Acoustic resonances are observed in high-pressure discharge lamps operated with ac input modulated power frequencies in the kilohertz range. This paper describes an optical resonance detection method for high-intensity discharge lamps using computer-controlled cameras and image processing software. Experimental results showing acoustic resonances in high-pressure sodium lamps are presented.