Optical fiber sensor for Hg(II) based on carbon dots

An optical fiber sensor for Hg(II) in aqueous solution based on sol–gel immobilized carbon dots nanoparticles functionalized with PEG200 and N-acetyl-l-cysteine is described. This sol–gel method generated a thin (about 750 nm), homogenous and smooth (roughness of 2.7±0.7 a˚ ) filmthat immobilizes the carbon dots and allows reversible sensing of Hg(II) in aqueous solution. A fast (less than 10 s), reversible and stable (the fluorescence intensity measurements oscillate less than 1% after several calibration cycles) sensor system was obtained. The sensor allow the detection of submicron molar concentrations of Hg(II) in aqueous solution. The fluorescence intensity of the immobilized carbon dots is quenched by the presence of Hg(II) with a Stern-Volmer constant (pH = 6.8) of 5.3×105M−1.

Optical processor based on a-SiC technology for spectral data error control

The SiC optical processor for error detection and correction is realized by using double pin/pin a-SiC:H photodetector with front and back biased optical gating elements. Data shows that the background act as selector that pick one or more states by splitting portions of the input multi optical signals across the front and back photodiodes. Boolean operations such as exclusive OR (EXOR) and three bit addition are demonstrated optically with a combination of such switching devices, showing that when one or all of the inputs are present the output will be amplified, the system will behave as an XOR gate representing the SUM. When two or three inputs are on, the system acts as AND gate indicating the present of the CARRY bit. Additional parity logic operations are performed by use of the four incoming pulsed communication channels that are transmitted and checked for errors together. As a simple example of this approach, we describe an all optical processor for error detection and correction and then, provide an experimental demonstration of this fault tolerant reversible system, in emerging nanotechnology.

PINPIN a-Si: H based structures for X-ray image detection using the laser scanning technique

Conventional film based X-ray imaging systems are being replaced by their digital equivalents. Different approaches are being followed by considering direct or indirect conversion, with the later technique dominating. The typical, indirect conversion, X-ray panel detector uses a phosphor for X-ray conversion coupled to a large area array of amorphous silicon based optical sensors and a couple of switching thin film transistors (TFT). The pixel information can then be readout by switching the correspondent line and column transistors, routing the signal to an external amplifier. In this work we follow an alternative approach, where the electrical switching performed by the TFT is replaced by optical scanning using a low power laser beam and a sensing/switching PINPIN structure, thus resulting in a simpler device. The optically active device is a PINPIN array, sharing both front and back electrical contacts, deposited over a glass substrate. During X-ray exposure, each sensing side photodiode collects photons generated by the scintillator screen (560 nm), charging its internal capacitance. Subsequently a laser beam (445 nm) scans the switching diodes (back side) retrieving the stored charge in a sequential way, reconstructing the image. In this paper we present recent work on the optoelectronic characterization of the PINPIN structure to be incorporated in the X-ray image sensor. The results from the optoelectronic characterization of the device and the dependence on scanning beam parameters are presented and discussed. Preliminary results of line scans are also presented. (C) 2014 Elsevier B.V. All rights reserved.

Detection of a Giardia lamblia coproantigen by using a commercially available immunoenzymatic assay, in Belo Horizonte, Brazil

It is known that fecal examination to detect Giardia lamblia cysts or trophozoites produces a high percentage of false-negative results. A commercially available immunoenzymatic assay (ProSpecT Giardia Microplate Assay, Alexon, Inc., BIOBRÁS) to detect G. lamblia specific coproantigen was evaluated for the first time in Brazil. A total of 90 specimens were tested. Each specimen was first tested as unpreserved stool, and then it was preserved in 10% Formalin to be tested 2 months later. The assay was able to identify all the 30 positive patients (sensitivity = 100.0%) by visual or spectrophotometric examination in the unpreserved specimens and was negative in 57 of the 60 patients without G. lamblia (specificity = 95.0%). The assay identified 27 of the 30 positive patients (sensitivity = 90.0%) and was negative in 59 of the 60 negatives (specificity = 98.3%) in the preserved stools according to both readings. A marked difference was observed in the optical densities in both groups, preserved and unpreserved stools, when the G. lamblia-positive specimens were compared to the negative or positive for other intestinal parasites than G. lamblia. The assay seems a good alternative for giardiasis diagnosis, especially when the fecal examination was repeatedly negative and the patient presents giardiasislike symptoms.

Disposable solid state probe for optical screening of chlorpromazine

We are presenting a simple, low-cost and rapid solid-state optical probe for screening chlorpromazine (CPZ) in aquacultures. The method exploits the colourimetric reaction between CPZ and Fe(III) ion that occurs at a solid/liquid interface, the solid layer consisting of ferric iron entrapped in a layer of plasticized PVC. If solutions containing CPZ are dropped onto such a layer, a colour change occurs from light yellow to dark pink or even light blue, depending on the concentration of CPZ. Visual inspection enables the concentration of CPZ to be estimated. The resulting colouration was also monitored by digital image collection for a more accurate quantification. The three coordinates of the hue, saturation and lightness system were obtained by standard image processing along with mathematical data treatment. The parameters affecting colour were assessed and optimized. Studies were conducted by visible spectrophotometry and digital image acquisition, respectively. The response of the optimized probe towards the concentration of CPZ was tested for several mathematical transformations of the colour coordinates, and a linear relation was found for the sum of hue and luminosity. The limit of detection is 50 μM (corresponding to about 16 μg per mL). The probe enables quick screening for CPZ in real water samples with prior sample treatment.

Use of elisa employing homologous and heterologous antigens for the detection of IgG and subclasses (IgG1 and IgG2) in the diagnosis of Canine visceral leishmaniasis

Indirect immunofluorescence is the method recommended for the diagnosis of visceral leishmanisis in dogs, however, the accuracy of this technique is low and its use on a large scale is limited. Since ELISA does not present these limitations, this technique might be an option for the detection of IgG or specific IgG1 and IgG2 subclasses. Canine ehrlichiosis is an important differential diagnosis of American Visceral Leishmaniasis (AVL). The present study compared ELISA using Leishmania chagasi and Leishmania braziliensis antigen for the detection of anti-Leishmania IgG and subclasses in serum samples from 37 dogs naturally infected with L. chagasi (AVL) and in samples from four dogs co-infected with L. braziliensis and L. chagasi (CI). The occurrence of cross-reactivity was investigated in control serum samples of 17 healthy dogs (HC) and 35 infected with Ehrlichia canis (EC). The mean optical density obtained for the detection of IgG was significantly higher when L. chagasi antigen was used, and was also higher in subgroup VLs (symptomatic) compared to subgroup Vla (asymptomatic). The correlation between IgG and IgG1 was low. The present results suggest that IgG ELISA using homologous antigen yields the best results, permitting the diagnosis of asymptomatic L. chagasi infection and the discrimination between cases of AVL and ehrlichiosis in dogs.

Amorphous silicon e 3D sensors applied to object detection

Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

Detection of purkinje images for automatic positioning of fixation target and interferometric measurements of anterior eye chamber

In cataract surgery, the eye’s natural lens is removed because it has gone opaque and doesn’t allow clear vision any longer. To maintain the eye’s optical power, a new artificial lens must be inserted. Called Intraocular Lens (IOL), it needs to be modelled in order to have the correct refractive power to substitute the natural lens. Calculating the refractive power of this substitution lens requires precise anterior eye chamber measurements. An interferometry equipment, the AC Master from Zeiss Meditec, AG, was in use for half a year to perform these measurements. A Low Coherence Interferometry (LCI) measurement beam is aligned with the eye’s optical axis, for precise measurements of anterior eye chamber distances. The eye follows a fixation target in order to make the visual axis align with the optical axis. Performance problems occurred, however, at this step. Therefore, there was a necessity to develop a new procedure that ensures better alignment between the eye’s visual and optical axes, allowing a more user friendly and versatile procedure, and eventually automatizing the whole process. With this instrument, the alignment between the eye’s optical and visual axes is detected when Purkinje reflections I and III are overlapped, as the eye follows a fixation target. In this project, image analysis is used to detect these Purkinje reflections’ positions, eventually automatically detecting when they overlap. Automatic detection of the third Purkinje reflection of an eye following a fixation target is possible with some restrictions. Each pair of detected third Purkinje reflections is used in automatically calculating an acceptable starting position for the fixation target, required for precise measurements of anterior eye chamber distances.

Instrumentation and software for the VERITAS Project and the detection of TeV Gamma-Ray Emission from the BL Lacertae Object 1ES1959+650

Transmission of Cherenkov light through the atmosphere is strongly influenced by the optical clarity of the atmosphere and the prevailing weather conditions. The performance of telescopes measuring this light is therefore dependent on atmospheric effects. This thesis presents software and hardware developed to implement a prototype sky monitoring system for use on the proposed next-generation gamma-ray telescope array, VERITAS. The system, consisting of a CCD camera and a far-infrared pyrometer, was successfully installed and tested on the ten metre atmospheric Cherenkov imaging telescope operated by the VERITAS Collaboration at the F.L. Whipple Observatory in Arizona. The thesis also presents the results of observations of the BL Lacertae object, 1ES1959+650, made with the Whipple ten metre telescope. The observations provide evidence for TeV gamma-ray emission from the BL Lacertae object, 1ES1959+650, at a level of more than 15 standard deviations above background. This represents the first unequivocal detection of this object at TeV energies, making it only the third extragalactic source seen at such levels of significance in this energy range. The flux variability of the source on a number of timescales is also investigated.

Detection of replication-defective hepatitis A virus based on the correlation between real-time polymerase chain reaction and ELISA in situ results

ELISA in situ can be used to titrate hepatitis A virus (HAV) particles and real-time polymerase chain reaction (RT-PCR) has been shown to be a fast method to quantify the HAV genome. Precise quantification of viral concentration is necessary to distinguish between infectious and non-infectious particles. The purpose of this study was to compare cell culture and RT-PCR quantification results and determine whether HAV genome quantification can be correlated with infectivity. For this purpose, three stocks of undiluted, five-fold diluted and 10-fold diluted HAV were prepared to inoculate cells in a 96-well plate. Monolayers were then incubated for seven, 10 and 14 days and the correlation between the ELISA in situ and RT-PCR results was evaluated. At 10 days post-incubation, the highest viral load was observed in all stocks of HAV via RT-PCR (10(5) copies/mL) (p = 0.0002), while ELISA revealed the highest quantity of particles after 14 days (optical density = 0.24, p < 0.001). At seven days post-infection, there was a significant statistical correlation between the results of the two methods, indicating equivalents titres of particles and HAV genome during this period of infection. The results reported here indicate that the duration of growth of HAV in cell culture must be taken into account to correlate genome quantification with infectivity.

Mass detection on mammograms: influence of signal shape uncertainty on human and model observers.

We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

Optical spectroscopy of the bladder washout fluid to optimize fluorescence cystoscopy with Hexvix®.

Fluorescence cystoscopy enhances detection of early bladder cancer. Water used to inflate the bladder during the procedure rapidly contains urine, which may contain fluorochromes. This frequently degradesfluorescence images. Samples of bladder washout fluid (BWF) or urine were collected (15 subjects). We studiedtheir fluorescence properties and assessed changes induced by pH (4 to 9) and temperature (15°C to 41°C).A typical fluorescence spectrum of BWF features a main peak (excitation/emission: 320∕420 nm, FWHM =50∕100 nm) and a weaker (5% to 20% of main peak intensity), secondary peak (excitation/emission: 455∕525 nm, FWHM = 80∕50 nm). Interpatient fluctuations of fluorescence intensity are observed. Fluorescence intensity decreases when temperature increases (max 30%) or pH values vary (max 25%). Neither approach is compatible with clinical settings. Fluorescence lifetime measurements suggest that 4-pyridoxic acid/riboflavin is the most likely molecule responsible for urine's main/secondary fluorescence peak. Our measurements give an insight into the spectroscopy of the detrimental background fluorescence. This should be included in the optical design of fluorescence cystoscopes. We estimate that restricting the excitation range from 370-430 nm to 395-415 nm would reduce the BWF background by a factor 2.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.

Risk Evaluation for Spoofing against a Sensor Supplied with Liveness Detection

The aim of this paper is to evaluate the risks associated with the use of fake fingerprints on a livescan supplied with a method of liveness detection. The method is based on optical properties of the skin. The sensor uses several polarizations and illuminations to capture the information of the different layers of the human skin. These experiments also allow for the determination under which conditions the system is deceived and if there is an influence respectively of the nature of the fake, the mould used for the production or the individuals involved in the attack. These experiments showed that current multispectral sensors can be deceived by the use of fake fingerprints created with or without the cooperation of the subject. Fakes created from direct casts perform better than those produced by fakes created from indirect casts. The results showed that the success of the attack is influenced by two main factors. The first is the quality of the fakes, and by extension the quality of the original fingerprint. The second is the combination of the general patterns involved in the attacks since an appropriate combination can strongly increase the rates of successful attacks.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.