999 resultados para Biomimetic sensor


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Plants as well as other biological organisms achieve directed movements by fibres that constraint and direct the isotropic expansion of a matrix material. In order to mimic these actuators, complex arrangements of rigid fibres must be achieved, which is challenging, especially at small scales. In this paper, a new method to organize carbon nanotubes (CNTs) into complex shapes is employed to create a framework for hydrogel infiltration. These CNT frameworks can be realized as iris, needle and bridge architectures, and after hydrogel infiltration, they show directed actuation in response to water uptake. Finally, we show how the latter can be employed as a novel hygroscopic sensor. © 2011 IEEE.

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A novel reusable molecularly imprinted polymer (MIP) assembled on a polymeric layer of carboxylated poly(vinyl chloride) (PVCsingle bondCOOH) for myoglobin (Myo) detection was developed. This polymer was casted on the gold working area of a screen printed electrode (Au-SPE), creating a novel disposable device relying on plastic antibodies. Electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and Fourier transform infrared spectroscopy (FTIR) studies confirmed the surface modification. The MIP/Au-SPE devices displayed a linear behaviour in EIS from 0.852 to 4.26 μg mL−1, of positive slope 6.50 ± 1.48 (kΩ mL μg−1). The limit of detection was 2.25 μg mL−1. Square wave voltammetric (SWV) assays were made in parallel and showed linear responses between 1.1 and 2.98 μg mL−1. A current decrease was observed against Myo concentration, producing average slopes of −0.28 ± 0.038 μA mL μg−1. MIP/Au-SPE also showed good results in terms of selectivity. The error% found for each interfering species were 7% for troponin T (TnT), 11% for bovine serum albumin (BSA) and 2% for creatine kinase MB (CKMB), respectively. Overall, the technical modification over the Au-SPE was found a suitable approach for screening Myo in biological fluids.

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Myoglobin (Mb) is among the cardiac biomarkers playing a major role in urgent diagnosis of cardiovascular diseases. Its monitoring in point-of-care is therefore fundamental. Pursuing this goal, a novel biomimetic ionophore for the potentiometric transduction of Mb is presented. It was synthesized by surface molecular imprinting (SMI) with the purpose of developing highly efficient sensor layers for near-stereochemical recognition of Mb. The template (Mb) was imprinted on a silane surface that was covalently attached to silica beads by means of self-assembled monolayers. First the silica was modified with an external layer of aldehyde groups. Then, Mb was attached by reaction with its amine groups (on the external surface) and subsequent formation of imine bonds. The vacant places surrounding Mb were filled by polymerization of the silane monomers 3-aminopropyltrimethoxysilane (APTMS) and propyltrimethoxysilane (PTMS). Finally, the template was removed by imine cleavage after treatment with oxalic acid. The results materials were finely dispersed in plasticized PVC selective membranes and used as ionophores in potentiometric transduction. The best analytical features were found in HEPES buffer of pH 4. Under this condition, the limits of detection were of 1.3 × 10−6 mol/L for a linear response after 8.0 × 10−7 mol/L with an anionic slope of −65.9 mV/decade. The imprinting effect was tested by preparing non-imprinted (NI) particles and employing these materials as ionophores. The resulting membranes showed no ability to detect Mb. Good selectivity was observed towards creatinine, sacarose, fructose, galactose, sodium glutamate, and alanine. The analytical application was conducted successfully and showed accurate and precise results.

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A novel poly(p-xylylene), PPX, derivative bearing phenyl side groups was electrochemically synthesized in 85% yield. The polymer, poly(2-phenyl-p-xylylene) (PPPX), presented a major fraction (88%) soluble in common organic solvents. It showed to be thermally resistant up to 140 degrees C. UV-VIS analysis revealed an Egap of similar to 3.0 eV. Gas sensors made from thin films of CSA doped PPPX deposited on interdigitated electrodes exhibited significant changes in electrical conductance upon exposure to five carbonyl compounds: acetaldehyde, propionaldehyde. benzaldehyde, acetone and butanone. Three-dimensional plots of relative response vs. time of half-response vs. time of half-recovery showed good discrimination between the five carbonyl Compounds tested. (C) 2008 Elsevier B.V. All rights reserved.

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This thesis was driven by the ambition to create suitable model systems that mimic complex processes in nature, like intramolecular transitions, such as unfolding and refolding of proteins, or intermolecular interactions between different cell compo-nents. Novel biophysical approaches were adopted by employing atomic force mi-croscopy (AFM) as the main measurement technique due to its broad diversity. Thus, high-resolution imaging, adhesion measurements, and single-molecule force distance experiments were performed on the verge of the instrumental capabilities. As first objective, the interaction between plasma membrane and cytoskeleton, me-diated by the linker protein ezrin, was pursued. Therefore, the adsorption process and the lateral organization of ezrin on PIP2 containing solid-supported membranes were characterized and quantified as a fundament for the establishment of a biomimetic model system. As second component of the model system, actin filaments were coated on functionalized colloidal probes attached on cantilevers, serving as sensor elements. The zealous endeavor of creating this complex biomimetic system was rewarded by successful investigation of the activation process of ezrin. As a result, it can be stated that ezrin is activated by solely binding to PIP2 without any further stimulating agents. Additional cofactors may stabilize and prolong the active conformation but are not essentially required for triggering ezrin’s transformation into an active conformation. In the second project, single-molecule force distance experiments were performed on bis-loop tetra-urea calix[4]arene-catenanes with different loading rates (increase in force per second). These macromolecules were specifically designed to investigate the rupture and rejoining mechanism of hydrogen bonds under external load. The entangled loops of capsule-like molecules locked the unbound state of intramolecular hydrogen bonds mechanically, rendering a rebinding observable on the experimental time scale. In conjunction with Molecular Dynamics simulations, a three-well potential of the bond rupture process was established and all kinetically relevant parameters of the experiments were determined by means of Monte Carlo simulations and stochastic modeling. In summary, it can be stated that atomic force microscopy is an invaluable tool to scrutinize relevant processes in nature, such as investigating activation mechanisms in proteins, as shown by analysis of the interaction between F-actin and ezrin, as well as exploring fundamental properties of single hydrogen bonds that are of paramount interest for the complete understanding of complex supramolecular structures.

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Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. In this paper, a key management scheme is proposed to defeat node capture attack by offering both forward and backward secrecies. Our scheme overcomes the pitfalls which Nilsson et al.'s scheme suffers from, and is not more expensive than their scheme.

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The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.

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In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

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Articular cartilage damage is a persistent and increasing problem with the aging population, and treatments to achieve biological repair or restoration remain a challenge. Cartilage tissue engineering approaches have been investigated for over 20 years, but have yet to achieve the consistency and effectiveness for widespread clinical use. One of the potential reasons for this is that the engineered tissues do not have or establish the normal zonal organization of cells and extracellular matrix that appears critical for normal tissue function. A number of approaches are being taken currently to engineer tissue that more closely mimics the organization of native articular cartilage. This review focuses on the zonal organization of native articular cartilage, strategies being used to develop such organization, the reorganization that occurs after culture or implantation, and future prospects for the tissue engineering of articular cartilage with biomimetic zones.

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This thesis investigates the problem of robot navigation using only landmark bearings. The proposed system allows a robot to move to a ground target location specified by the sensor values observed at this ground target posi- tion. The control actions are computed based on the difference between the current landmark bearings and the target landmark bearings. No Cartesian coordinates with respect to the ground are computed by the control system. The robot navigates using solely information from the bearing sensor space. Most existing robot navigation systems require a ground frame (2D Cartesian coordinate system) in order to navigate from a ground point A to a ground point B. The commonly used sensors such as laser range scanner, sonar, infrared, and vision do not directly provide the 2D ground coordi- nates of the robot. The existing systems use the sensor measurements to localise the robot with respect to a map, a set of 2D coordinates of the objects of interest. It is more natural to navigate between the points in the sensor space corresponding to A and B without requiring the Cartesian map and the localisation process. Research on animals has revealed how insects are able to exploit very limited computational and memory resources to successfully navigate to a desired destination without computing Cartesian positions. For example, a honeybee balances the left and right optical flows to navigate in a nar- row corridor. Unlike many other ants, Cataglyphis bicolor does not secrete pheromone trails in order to find its way home but instead uses the sun as a compass to keep track of its home direction vector. The home vector can be inaccurate, so the ant also uses landmark recognition. More precisely, it takes snapshots and compass headings of some landmarks. To return home, the ant tries to line up the landmarks exactly as they were before it started wandering. This thesis introduces a navigation method based on reflex actions in sensor space. The sensor vector is made of the bearings of some landmarks, and the reflex action is a gradient descent with respect to the distance in sensor space between the current sensor vector and the target sensor vec- tor. Our theoretical analysis shows that except for some fully characterized pathological cases, any point is reachable from any other point by reflex action in the bearing sensor space provided the environment contains three landmarks and is free of obstacles. The trajectories of a robot using reflex navigation, like other image- based visual control strategies, do not correspond necessarily to the shortest paths on the ground, because the sensor error is minimized, not the moving distance on the ground. However, we show that the use of a sequence of waypoints in sensor space can address this problem. In order to identify relevant waypoints, we train a Self Organising Map (SOM) from a set of observations uniformly distributed with respect to the ground. This SOM provides a sense of location to the robot, and allows a form of path planning in sensor space. The navigation proposed system is analysed theoretically, and evaluated both in simulation and with experiments on a real robot.