Ion-sensing properties of 1D vanadium pentoxide nanostructures

The application of one-dimensional (1D) V2O5 center dot nH(2)O nanostructures as pH sensing material was evaluated. 1D V2O5 center dot nH(2)O nanostructures were obtained by a hydrothermal method with systematic control of morphology forming different nanostructures: nanoribbons, nanowires and nanorods. Deposited onto Au-covered substrates, 1D V2O5 center dot nH(2)O nanostructures were employed as gate material in pH sensors based on separative extended gate FET as an alternative to provide FET isolation from the chemical environment. 1D V2O5 center dot nH(2)O nanostructures showed pH sensitivity around the expected theoretical value. Due to high pH sensing properties, flexibility and low cost, further applications of 1D V2O5 center dot nH(2)O nanostructures comprise enzyme FET-based biosensors using immobilized enzymes.

Evaluating the performance of polypyrrole nanowires on the electrochemical sensing of ammonia in solution

This work encompasses the direct electrodeposition of polypyrrole nanowires onto Au substrates using different electrochemical techniques: normal pulse voltammetry (NPV) and constant potential method with the aim in applying these films for the first time in ammonia sensing in solution. The performance of these nanowire-based sensors are compared and evaluated in terms of: film morphology (analyzed with scanning electron microscopy); their sensitivity towards ammonia; electrochemical and contact angle measurements. For nanowires prepared by NPV, the sensitivity towards ammonia increases with increasing amount of electrodeposited polypyrrole, as expected due to the role of polypyrrole as electrochemical transducer for ammonia oxidation. On the other hand, nanowires prepared potentiostatically displayed an unexpected opposite behavior, attributed to the lower conductivity of longer polypyrrole nanowires obtained through this technique. These results evidenced that the analytical and physico-chemical features of nanostructured sensors can differ greatly from those of their conventional bulky analogous. (C) 2012 Elsevier B.V. All rights reserved.

Toward the Optimization of an e-Tongue System Using Information Visualization: A Case Study with Perylene Tetracarboxylic Derivative Films in the Sensing Units

The wide variety of molecular architectures used in sensors and biosensors and the large amount of data generated with some principles of detection have motivated the use of computational methods, such as information visualization techniques, not only to handle the data but also to optimize sensing performance. In this study, we combine projection techniques with micro-Raman scattering and atomic force microscopy (AFM) to address critical issues related to practical applications of electronic tongues (e-tongues) based on impedance spectroscopy. Experimentally, we used sensing units made with thin films of a perylene derivative (AzoPTCD acronym), coating Pt interdigitated electrodes, to detect CuCl(2) (Cu(2+)), methylene blue (MB), and saccharose in aqueous solutions, which were selected due to their distinct molecular sizes and ionic character in solution. The AzoPTCD films were deposited from monolayers to 120 nm via Langmuir-Blodgett (LB) and physical vapor deposition (PVD) techniques. Because the main aspects investigated were how the interdigitated electrodes are coated by thin films (architecture on e-tongue) and the film thickness, we decided to employ the same material for all sensing units. The capacitance data were projected into a 2D plot using the force scheme method, from which we could infer that at low analyte concentrations the electrical response of the units was determined by the film thickness. Concentrations at 10 mu M or higher could be distinguished with thinner films tens of nanometers at most-which could withstand the impedance measurements, and without causing significant changes in the Raman signal for the AzoPTCD film-forming molecules. The sensitivity to the analytes appears to be related to adsorption on the film surface, as inferred from Raman spectroscopy data using MB as analyte and from the multidimensional projections. The analysis of the results presented may serve as a new route to select materials and molecular architectures for novel sensors and biosensors, in addition to suggesting ways to unravel the mechanisms behind the high sensitivity obtained in various sensors.

Carbon nanotubes modified with antimony nanoparticles: A novel material for electrochemical sensing

In this study, a novel material for the electrochemical determination of bisphenol A using a nanocomposite based on multi-walled carbon nanotubes modified with antimony nanoparticles has been investigated. The morphology, structure, and electrochemical performance of the nanocomposite electrodes were characterised by field emission gun scanning electron microscopy, energy-dispersive X-ray spectroscopy, and cyclic voltammetry. A scan rate study and electrochemical impedance spectroscopy showed that the bisphenol A oxidation product is adsorbed on nanocomposite electrode surface. Differential pulse voltammetry in phosphate buffer solution at pH 6, allowed the development of a method to determine bisphenol A levels in the range of 0.5-5.0 mu mol L-1, with a detection limit of 5.24 nmol L-1 (1.19 mu g L-1). (C) 2012 Elsevier Ltd. All rights reserved.

Tailoring Molecular Architectures with Cobalt Tetrasulfonated Phthalocyanine: Immobilization in Layer-by-Layer Films and Sensing Applications

In the field of organic thin films, manipulation at the nanoscale can be obtained by immobilization of different materials on platforms designed to enhance a specific property via the layer-by-layer technique. In this paper we describe the fabrication of nanostructured films containing cobalt tetrasulfonated phthalocyanine (CoTsPc) obtained through the layer-by-layer architecture and assembled with linear poly(allylamine hydrochloride) (PAH) and poly(amidoamine) dendrimer (PAMAM) polyelectrolytes. Film growth was monitored by UV-vis spectroscopy following the Q band of CoTsPc and revealed a linear growth for both systems. Fourier transform infrared (FTIR) spectroscopy showed that the driving force keeping the structure of the films was achieved upon interactions of CoTsPc sulfonic groups with protonated amine groups present in the positive polyelectrolyte. A comprehensive SPR investigation on film growth reproduced the deposition process dynamically and provided an estimation of the thicknesses of the layers. Both FTIR and SPR techniques suggested a preferential orientation of the Pc ring parallel to the substrate. The electrical conductivity of the PAH films deposited on interdigitated electrodes was found to be very sensitive to water vapor. These results point to the development of a phthalocyanine-based humidity sensor obtained from a simple thin film deposition technique, whose ability to tailor molecular organization was crucial to achieve high sensitivity.

Temperature Sensing Using Colloidal-Core Photonic Crystal Fiber

We report on a temperature sensor based on the monitoring of the luminescence spectrum of CdSe/ZnS nanocrystals, dispersed in mineral oil and inserted into the core of a photonic crystal fiber. The high overlap between the pump light and the nanocrystals as well as the luminescence guiding provided by the fiber geometry resulted in relatively high luminescence powers and improved optical signal-to-noise ratio (OSNR). Also, both core end interfaces were sealed so as to generate a more stable and robust waveguide structure. Temperature sensitivity experiments indicated a 70 pm/degrees C spectral shift over the 5 degrees C to 90 degrees C range.

Sensing the "LUV" with HST+COS in Cycle 20 and beyond

New Cosmic Origins Spectrograph (COS) observing modes have extended the Hubble Space Telescope's spectral range to wavelengths between 900-1150 Å. However, the G140L/1280 and the Cycle 19 available G130M central wavelengths (1055 and 1096) that sample below 1150 Å were only available at focus positions which provided low-resolution (R<3,000). For HST Cycle 20, we introduced a new G130M/1222 central wavelength that covers 1065-1365 Å with R>10,000 everywhere, but optimized for 15000 from 1080-1200 Å. This mode places geo-coronal Lyα between the COS FUV detector segments to minimize detector gain sag. Also for Cycle 20, the resolution of the G130M/1055 and 1096 modes will be increased by a factor of 3-4 by optimizing the focus positions for these modes. This will give HST approximately the effective area of FUSE over the FUSE bandpass at 10,000. Here we present the current calibration status of the COS G130M/1055, 1096, and 1222 central wavelength settings at the original and second FUV lifetime positions with an emphasis on observing over the "Lyman UV", or "LUV", 912-1216 Å.

Bias and learning in temporal binding: intervals between actions and outcomes are compressed by prior bias

It has consistently been shown that agents judge the intervals between their actions and outcomes as compressed in time, an effect named intentional binding. In the present work, we investigated whether this effect is result of prior bias volunteers have about the timing of the consequences of their actions, or if it is due to learning that occurs during the experimental session. Volunteers made temporal estimates of the interval between their action and target onset (Action conditions), or between two events (No-Action conditions). Our results show that temporal estimates become shorter throughout each experimental block in both conditions. Moreover, we found that observers judged intervals between action and outcomes as shorter even in very early trials of each block. To quantify the decrease of temporal judgments in experimental blocks, exponential functions were fitted to participants’ temporal judgments. The fitted parameters suggest that observers had different prior biases as to intervals between events in which action was involved. These findings suggest that prior bias might play a more important role in this effect than calibration-type learning processes.

Layer-by-Layer assembled cobalt ferrite nanoparticles for chemical sensing

Ultra-thin (thicknesses of 50-90 nm) nanocomposite films of cobalt ferrite nanoparticles (np-CoFe2O4, 18 nm in diameter) and polyelectrolytes (doped polyaniline-PANI, poly-3,4-ethylenedioxy thiophene: polystyrene sulfonic acid-PEDOT:PSS, and sulfonated lignin-SL) are assembled layer-by-layer onto interdigitated microelectrodes aiming at to create novel nanostructured sensoactive materials for liquid media chemical sensors. The nanocomposites display a distinctive globular morphology with nanoparticles densely-packed while surrounded by polyelectrolytes. Due to the presence of np-CoFe2O4 the nanocomposites display low electrical conductivity according to impedance data. On the other hand, this apparent shortcoming turns such nanocomposites much more sensitive to the presence of ions in solution than films made exclusively of conducting polyelectrolytes. For example, the electrical resistance of np-CoFe2O4/PEDOT:PSS and PANI/SL/np-CoFe2O4/SL architectures has a 10-fold decrease when they are immersed in 20 mmol. L-1 NaCl solution. Impedance spectra fitted with the response of an equivalent circuit model suggest that the interface created between nanoparticles and polyelectrolytes plays a major role on the nanocomposites electrical/dielectrical behavior. Since charge transport is sensitive to nanoparticle-polyelectrolyte interfaces as well as to the physicochemical conditions of the environment, the np-CoFe2O4-based nanocomposites can be used as sensing elements in chemical sensors operated under ac regime and room temperature.

In situ and remote sensing signature of meddies east of the mid-Atlantic ridge

[EN] Mediterranean Water eddies (meddies) are thought to play an important climatic role. Nevertheless, their dynamics are not sufficiently known because of difficulties encountered in their observation. Though propagating below the main thermocline, a number of pieces of evidence of sea surface manifestation of meddies are collected. The present work is based on joint in situ and altimetry data analyses to prove that the meddies can be followed with remote sensing data for long periods of time. The in situ observations are based on data from an oceanographic cruise, which crossed three meddies, and reanalysis of historical data sets, including RAFOS floats paths. Suggested methodology permitted us to obtain uninterrupted tracks for several meddies for a period from several months to more than 2 years. It was found that the dynamically calm region to the north of the Azores current presents favorable conditions for meddy tracking. The meddy surface signal may become shattered and difficult to follow during interaction with a strong dynamic structures (the Azores current/surface vortexes) or peaking topography. Theoretical considerations support the observations and lead to the conclusion that the dynamic signature of meddies at the sea surface is an intrinsic property of meddy dynamics

Remote Sensing of the El Hierro submarine volcanic eruption plume

[EN] Between October 2011 and March 2012 submarine volcanic eruptions took place at El Hierro (Canary Islands). The event produced plumes of discolored waters due to the discharge of volcanic matter, gases and fluids. Field samples of Chl-a and sulphur reduced species were collected by some oceanographic cruises (Instituto Español de Oceanografía, IEO).

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.