Aplicação de sensor de deslocamento angular em fibra óptica para medição de concentração de líquidos via ondas acústicas guiadas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Spectroradiometry of soil and comparison with orbital sensors

The aim of this study was to characterize and compare the spectral behavior of different soil classes obtained by orbital and terrestrial sensors. For this, an area of 184 ha in Rafard (SP) Brazil was staked on a regular grid of 100x100 m and soil samples were collected and georeferenced. After that, soil spectral curves were obtained with IRIS sensor and the sample points were overlaid at Landsat and ASTER images for spectral data collection. The soil samples were classified and mean soil curves for all sensors were generated by soil classes. The soil classes were differentiated by texture, organic matter and total iron for all sensors studied, the orbital sensors despite the lower spectral resolution, maintained the characteristics of the soil and the curves of reflectance intensity.

Development of an enzymeless electroanalytical method for the indirect detection of creatinine in urine samples

The aim of this study is to develop a new enzymeless electroanalytical method for the indirect quantification of creatinine from urine sample. This method is based on the electrochemical monitoring of picrate anion reduction at a glassy carbon electrode in an alkaline medium before and after it has reacted with creatinine (Jaffe's reaction). By using the differential pulse voltammetry technique under the optimum experimental conditions (step potential, amplitude potential, reaction time, and temperature), a linear analytical curve was obtained for concentrations of creatinine ranging from 1 to 80 mu mol L-1, with a detection limit of 380 nmol L-1. This proposed method was used to measure creatinine in human urine without the interference of most common organic species normally present in biological fluids (e.g., uric acid, ascorbic acid, glucose, and phosphocreatinine). The results obtained using urine samples were highly similar to the results obtained using the reference spectrophotometric method (at a 95% confidence level). (C) 2012 Elsevier B.V. All rights reserved.

Performance of an electronic tongue during monitoring 2-rnethylisoborneol and geosmin in water samples

2-Methylisoborneol (MIB) and geosmin (GSM) are sub products from algae decomposition and, depending on their concentration, can be toxic: otherwise, they give unpleasant taste and odor to water. For water treatment companies it is important to constantly monitor their presence in the distributed water and avoid further costumer complaints. Lower-cost and easy-to-read instrumentation would be very promising in this regard. In this study, we evaluate the potentiality of an electronic tongue (ET) system based on non-specific polymeric sensors and impedance measurements in monitoring MIB and GSM in water samples. Principal component analysis (PCA) applied to the generated data matrix indicated that this ET was capable to perform with remarkable reproducibility the discrimination of these two contaminants in either distilled or tap water, in concentrations as low as 25 ng L-1. Nonetheless, this analysis methodology was rather qualitative and laborious, and the outputs it provided were greatly subjective. Also, data analysis based on PCA severely restricts automation of the measuring system or its use by non-specialized operators. To circumvent these drawbacks, a fuzzy controller was designed to quantitatively perform sample classification while providing outputs in simpler data charts. For instance, the ET along with the referred fuzzy controller performed with a 100% hit rate the quantification of MIB and GSM samples in distilled and tap water. The hit rate could be read directly from the plot. The lower cost of these polymeric sensors allied to the especial features of the fuzzy controller (easiness on programming and numerical outputs) provided initial requirements for developing an automated ET system to monitor odorant species in water production and distribution. (C) 2012 Elsevier B.V. All rights reserved.

Dendrimers/TiO2 nanoparticles layer-by-layer films as extended gate FET for pH detection

The layer-by-layer (LbL) technique combined with field-effect transistor (FET) based sensors has enabled the production of pH-sensitive platforms with potential application in biosensors. A variation of the FET architecture, so called separative extended gate FET (SEGFET) devices, are promise as an alternative to conventional ion sensitive FET (ISFET). SEGFET configuration exhibits the advantage of combining the field-effect concept with organic and inorganic materials directly adsorbed on the extended gate, allowing the test of new pH-sensitive materials in a simple and low cost way. In this communication, poly(propylene imine) dendrimer (PPI) and TiO2 nanoparticles (TiO2-np) were assembled onto gold-covered substrates via layer-by-layer technique to produce a low cost SEGFET pH sensor. The sensor presented good pH sensitivity, ca. 57 mV pH(-1), showing that our strategy has potential advantages to fabricate low cost pH-sensing membranes. (C) 2012 Elsevier B.V. All rights reserved.

Optical chemical sensors using polythiophene derivatives as active layer for detection of volatile organic compounds

Several studies on polythiophene gas sensors, based mainly on electrochemical and gravimetric principles can be found in the literature. However, other principles of gas detection, such as optical and thermal, are still little studied. Optical sensing is suitable for remote detection and offers great versatility at low cost. Here,we report on the use of thin films of seven polythiophene derivatives as active layer in optical sensors for the detection of six volatile organic compounds (n-hexane, toluene, tetrahydrofuran, chloroform, dichloromethane and methanol) and water vapor, in concentration range of 500-30,000 ppm. The results showed that it is possible to use different polythiophene derivatives to differentiate VOCs by optical sensing. Differentiation can be performed based on the presence or not of response to an analyte and the sensitivity value of the sensors for the analytes. Another important feature is the lack of the effect of humidity on the response of most films, which could be a major drawback in the application of these sensors. (C) 2011 Elsevier B.V. All rights reserved.

Design of laminated piezocomposite shell transducers with arbitrary fiber orientation using topology optimization approach

Sensor and actuator based on laminated piezocomposite shells have shown increasing demand in the field of smart structures. The distribution of piezoelectric material within material layers affects the performance of these structures; therefore, its amount, shape, size, placement, and polarization should be simultaneously considered in an optimization problem. In addition, previous works suggest the concept of laminated piezocomposite structure that includes fiber-reinforced composite layer can increase the performance of these piezoelectric transducers; however, the design optimization of these devices has not been fully explored yet. Thus, this work aims the development of a methodology using topology optimization techniques for static design of laminated piezocomposite shell structures by considering the optimization of piezoelectric material and polarization distributions together with the optimization of the fiber angle of the composite orthotropic layers, which is free to assume different values along the same composite layer. The finite element model is based on the laminated piezoelectric shell theory, using the degenerate three-dimensional solid approach and first-order shell theory kinematics that accounts for the transverse shear deformation and rotary inertia effects. The topology optimization formulation is implemented by combining the piezoelectric material with penalization and polarization model and the discrete material optimization, where the design variables describe the amount of piezoelectric material and polarization sign at each finite element, with the fiber angles, respectively. Three different objective functions are formulated for the design of actuators, sensors, and energy harvesters. Results of laminated piezocomposite shell transducers are presented to illustrate the method. Copyright (C) 2012 John Wiley & Sons, Ltd.

Power consumption analysis for self-diagnosis of Wireless Sensor Nodes

Wireless sensor networks can transform our buildings in smart environments, improving comfort, energy efficiency and safety. Today however, wireless sensor networks are not considered reliable enough for being deployed on large scale. In this thesis, we study the main failure causes for wireless sensor networks, the existing solutions to improve reliability and investigate the possibility to implement self-diagnosis through power consumption measurements on the sensor nodes. Especially, we focus our interest on faults that generate in-range errors: those are wrong readings but belong to the range of the sensor and can therefore be missed by external observers. Using a wireless sensor network deployed in the R\&D building of NXP at the High Tech Campus of Eindhoven, we performed a power consumption characterization of the Wireless Autonomous Sensor (WAS), and studied through some experiments the effect that faults have in the power consumption of the sensor.

Analysis Methodology for Flow-level Evaluation of a Hybrid Mobile-Sensor Network

Our society uses a large diversity of co-existing wired and wireless networks in order to satisfy its communication needs. A cooper- ation between these networks can benefit performance, service availabil- ity and deployment ease, and leads to the emergence of hybrid networks. This position paper focuses on a hybrid mobile-sensor network identify- ing potential advantages and challenges of its use and defining feasible applications. The main value of the paper, however, is in the proposed analysis approach to evaluate the performance at the mobile network side given the mixed mobile-sensor traffic. The approach combines packet- level analysis with modelling of flow-level behaviour and can be applied for the study of various application scenarios. In this paper we consider two applications with distinct traffic models namely multimedia traffic and best-effort traffic.

Effects of cerebral perfusion pressure and increased fraction of inspired oxygen on brain tissue oxygen, lactate and glucose in patients with severe head injury

OBJECTIVE: The purpose of the study was to measure the effects of increased inspired oxygen on patients suffering severe head injury and consequent influences on the correlations between CPP and brain tissue oxygen (PtiO2) and the effects on brain microdialysate glucose and lactate. METHODS: In a prospective, observational study 20 patients suffering severe head injury (GCS< or =8) were studied between January 2000 and December 2001. Each patient received an intraparenchymal ICP device and an oxygen sensor and, in 17 patients brain microdialysis was performed at the cortical-subcortical junction. A 6 h 100% oxygen challenge (F IO2 1.0) ( Period A) was performed as early as possible in the first 24 hours after injury and compared with a similar 6 hour period following the challenge ( Period B). Statistics were performed using the linear correlation analysis, one sample t-test, as well as the Lorentzian peak correlation analysis. RESULTS: F IO2 was positively correlated with PtiO2 (p < 0.0001) over the whole study period. PtiO2 was significantly higher (p < 0.001) during Period A compared to Period B. CPP was positively correlated with PtiO2 (p < 0.001) during the whole study. PtiO2 peaked at a CPP value of 78 mmHg performing a Lorentzian peak correlation analysis of all patients over the whole study. During Period A the brain microdialysate lactate was significantly lower (p = 0.015) compared with Period B. However the brain microdialysate glucose remained unchanged. CONCLUSION: PtiO2 is significantly positively correlated with F IO2, meaning that PtiO2 can be improved by the simple manipulation of increasing F IO2 and ABGAO2. PtiO2 is positively correlated with CPP, peaking at a CPP value of 78 mmHg. Brain microdialysate lactate can be lowered by increasing PtiO2 values, as observed during the oxygen challenge, whereas microdialysate glucose is unchanged during this procedure. Extension of the oxygen challenge time and measurement of the intermediate energy metabolite pyruvate may clarify the metabolic effects of the intervention. Prospective comparative studies, including analysis of outcome on a larger multicenter basis, are necessary to assess the long term clinical benefits of this procedure.

Distributed sensor failure detection in sensor networks

We investigate the problem of distributed sensors' failure detection in networks with a small number of defective sensors, whose measurements differ significantly from the neighbor measurements. We build on the sparse nature of the binary sensor failure signals to propose a novel distributed detection algorithm based on gossip mechanisms and on Group Testing (GT), where the latter has been used so far in centralized detection problems. The new distributed GT algorithm estimates the set of scattered defective sensors with a low complexity distance decoder from a small number of linearly independent binary messages exchanged by the sensors. We first consider networks with one defective sensor and determine the minimal number of linearly independent messages needed for its detection with high probability. We then extend our study to the multiple defective sensors detection by modifying appropriately the message exchange protocol and the decoding procedure. We show that, for small and medium sized networks, the number of messages required for successful detection is actually smaller than the minimal number computed theoretically. Finally, simulations demonstrate that the proposed method outperforms methods based on random walks in terms of both detection performance and convergence rate.

ATM Signaling to TSC2: Mechanisms and Implications for Cancer Therapy

Ataxia telangiectasia mutated (ATM) is a critical component of the cellular response to DNA damage, where it acts as a damage sensor, and signals to a large network of proteins which execute the important tasks involved in responding to the damage, namely inducing cell cycle checkpoints, inducing DNA repair, modulating transcriptional responses, and regulating cell death pathways if the damage cannot be repaired faithfully. We have now discovered that an additional novel component of this ATM-dependent damage response involves induction of autophagy in response to oxidative stress. In contrast to DNA damage-induced ATM activation however, oxidative stress induced ATM, occurs in the cytoplasm, and does not require nuclear-to-cytoplasmic shuttling of ATM. Using several cell culture systems including MCF7 breast carcinoma cells, SKOV3 ovarian cancer cells, and various lineages of mouse embryonic fibroblasts, we showed that once activated by reactive oxygen species (ROS), ATM signals to mTORC1 to induce autophagy via the LKB1-AMPK-TSC2 pathway. Targeting dysregulation of mTORC1 in Atm-deficient mice, which succumb to lymphomagenesis within 3-4 months of age with daily administration of rapamycin, could significantly extend survival and cause regression of tumors, suggesting that pharmacologically targeting this pathway has therapeutic implications in cancer. We also identified a second contrasting pathway for DNA damage-induced mTORC1 repression which does not require AMPK activation, but does require ATM and TSC2. Several potential mechanisms including mTOR localization and p53-mediated pathways were ruled out however we identified that TSC2 may be an additional cytoplasmic direct ATM substrate that is engaged in response to DNA damage specifically. Lastly, a study was performed to examine whether autophagy induced by ovarian cancer therapeutics (focusing on cisplatin, since paclitaxel does not induce autophagy in the SKOV3 cell line model we used) plays a role in resistance to therapy since autophagy can play both pro-survival mechanisms or be a mechanism of cell death. Using a genetic approach to knock-down Atg5 expression with shRNA in SKOV3 ovarian carcinoma cells, we compared the cytotoxicity of cisplatin in vector or Atg5 knock-down cells, and demonstrated that autophagy does not play any significant role in the response to cisplatin in this cell line.

Surface patterned polymer micro-cantilever arrays for sensing

Microinjection molding was employed to fabricate low-cost polymer cantilever arrays for sensor applications. Cantilevers with micrometer dimensions and aspect ratios as large as 10 were successfully manufactured from polymers, including polypropylene and polyvinylidenfluoride. The cantilevers perform similar to the established silicon cantilevers, with Q-factors in the range of 10–20. Static deflection of gold coated polymer cantilevers was characterized with heat cycling and self-assembled monolayer formation of mercaptohexanols. A hybrid mold concept allows easy modification of the surface topography, enabling customized mechanical properties of individual cantilevers. Combined with functionalization and surface patterning, the cantilever arrays are qualified for biomedical applications

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

Low-energy energetic neutral atom imaging of Io plasma and neutral tori

Io's plasma and neutral tori play significant roles in the Jovian magnetosphere. We present feasibility studies of measuring low-energy energetic neutral atoms (LENAs) generated from the Io tori. We calculate the LENA flux between 10 eV and 3 keV. The energy range includes the corotational plasma flow energy. The expected differential flux at Ganymede distance is typically 10(3)-10(5) cm(-2) s(-1) sr(-1) eV(-1) near the energy of the corotation. It is above the detection level of the planned LENA sensor that is to be flown to the Jupiter system with integration times of 0.01-1 s. The flux has strong asymmetry with respective to the Io phase. The observations will exhibit periodicities, which can be attributed to the Jovian magnetosphere rotation and the rotation of Io around Jupiter. The energy spectra will exhibit dispersion signatures, because of the non-negligible flight time of the LENAs from Io to the satellite. In 2030, the Jupiter exploration mission JUICE will conduct a LENA measurement with a LENA instrument, the Jovian Neutrals Analyzer (JNA). From the LENA observations collected by JNA, we will be able to derive characteristic quantities, such as the density, velocity, velocity distribution function, and composition of plasma-torus particles. We also discuss the possible physics to be explored by JNA in addition to the constraints for operating the sensor and analyzing the obtained dataset. (C) 2015 Elsevier Ltd. All rights reserved.