Characterisation of the efficacy of endodontic medications using a three-dimensional fluorescent tooth model: An ex vivo study

The purpose of this study was to establish a three-dimensional fluorescent tooth model to investigate bacterial viability against intra-canal medicaments across the thickness and surface of root dentine. Dental microbial biofilms (Enterococcus faecalis and Streptococcus mutans) were established on the external root surface and bacterial kill was monitored over time against intra-canal medicament (Ca(OH)2 ) using fluorescent microscopy in conjunction with BacLight SYTO9 and propidium iodide stains. An Olympus digital camera fitted to SZX16 fluorescent microscope captured images of bacterial cells in biofilms on the external root surface. Viability of biofilm was measured by calculating the total pixel area of green (viable bacteria) and red (non-viable bacteria) for each image using ImageJ® software. All data generated were assessed for normality and then analysed using a Mann-Whitney t-test. The viability of S. mutans biofilm following Ca(OH)2 treatment showed a significant decline compared with the untreated group (P = 0.0418). No significant difference was seen for E. faecalis biofilm between the Ca(OH)2 and untreated groups indicating Ca(OH)2 medicament is ineffective against E. faecalis biofilm. This novel three-dimensional fluorescent biofilm model provides a new clinically relevant tool for testing of medicaments against dental biofilms.

Growth and Characterization of GaSb-Based Type-II InAs/GaSb Superlattice Photodiodes for Mid-Infrared Detection

InAs/GaSb superlattice (SL) midwave infrared photovoltaic detectors are grown by molecular beam epitaxy on GaSb(001) residual p-type substrates. A thick GaSb layer is grown under the optimized growth condition as a buffer layer. The detectors containing a 320-period 8ML/8ML InAs/GaSb SL active layer are fabricated with a series pixel area using anode sulfide passivation. Corresponding to 50% cutoff wavelengths of 5.0 mu m at 77 K, the peak directivity of the detectors is 1.6 x 10(10) cm.Hz(1/2) W-1 at 77 K.

GaAs Based InAs/GaSb Superlattice Short Wavelength Infrared Detectors Grown by Molecular Beam Epitaxy

InAs/GaSb superlattice (SL) short wavelength infrared photoconduction detectors are grown by molecular beam epitaxy on GaAs(001) semi-insulating substrates. An interfacial misfit mode AlSb quantum dot layer and a thick GaSb layer are grown as buffer layers. The detectors containing a 200-period 2ML/8ML InAs/GaSb SL active layer are fabricated with a pixel area of 800 x 800 mu m(2) without using passivation or antireflection coatings. Corresponding to the 50% cutoff wavelengths of 2.05 mu m at 77K and 2.25 mu m at 300 K, the peak detectivities of the detectors are 4 x 10(9) cm.Hz(1/2)/W at 77K and 2 x 10(8) cm.Hz(1/2)/W at 300 K, respectively.

Cytometric quantification of singlet oxygen in the human malaria parasite Plasmodium falciparum

The malaria parasite Plasmodium falciparum proliferates within human erythrocytes and is thereby exposed to a variety of reactive oxygen species (ROS) such as hydrogen peroxide, hydroxyl radical, superoxide anion, and highly reactive singlet oxygen (1O2). While most ROS are already well studied in the malaria parasite, singlet oxygen has been neglected to date. In this study we visualized the generation of 1O2 by live cell fluorescence microscopy using 3-(p-aminophenyl) fluorescein as an indicator dye. While 1O2 is found restrictively in the parasite, its amount varies during erythrocytic schizogony. Since the photosensitizer cercosporin generates defined amounts of 1O2 we have established a new cytometric method that allows the stage specific quantification of 1O2. Therefore, the parasites were first classified into three main stages according to their respective pixel-area of 200600 pixels for rings, 7001,200 pixels for trophozoites and 1,4002,500 pixels for schizonts. Interestingly the highest mean concentration of endogenous 1O2 of 0.34 nM is found in the trophozoites stage, followed by 0.20 nM (ring stage) and 0.10 nM (schizont stage) suggesting that 1O2 derives predominantly from the digestion of hemoglobin. (c) 2012 International Society for Advancement of Cytometry

Defining the light emitting area for displays in the unipolar regime of highly efficient light emitting transistors

Light-emitting field effect transistors (LEFETs) are an emerging class of multifunctional optoelectronic devices. It combines the light emitting function of an OLED with the switching function of a transistor in a single device architecture the dual functionality of LEFETs has the potential applications in active matrix displays. However, the key problem of existing LEFETs thus far has been their low EQEs at high brightness, poor ON/OFF and poorly defined light emitting area-a thin emissive zone at the edge of the electrodes. Here we report heterostructure LEFETs based on solution processed unipolar charge transport and an emissive polymer that have an EQE of up to 1% at a brightness of 1350a €...cd/m 2, ON/OFF ratio > 10 4 and a well-defined light emitting zone suitable for display pixel design. We show that a non-planar hole-injecting electrode combined with a semi-transparent electron-injecting electrode enables to achieve high EQE at high brightness and high ON/OFF ratio. Furthermore, we demonstrate that heterostructure LEFETs have a better frequency response (f cut-off = 2.6a €...kHz) compared to single layer LEFETs the results presented here therefore are a major step along the pathway towards the realization of LEFETs for display applications.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Estimating winter crop area across seasons and regions using time-sequential MODIS imagery.

The wheat grain industry is Australia's second largest agricultural export commodity. There is an increasing demand for accurate, objective and near real-time crop production information by industry. The advent of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform has augmented the capability of satellite-based applications to capture reflectance over large areas at acceptable pixel scale, cost and accuracy. The use of multi-temporal MODIS-enhanced vegetation index (EVI) imagery to determine crop area was investigated in this article. Here the rigour of the harmonic analysis of time-series (HANTS) and early-season metric approaches was assessed when extrapolating over the entire Queensland (QLD) cropping region for the 2005 and 2006 seasons. Early-season crop area estimates, at least 4 months before harvest, produced high accuracy at pixel and regional scales with percent errors of -8.6% and -26% for the 2005 and 2006 seasons, respectively. In discriminating among crops at pixel and regional scale, the HANTS approach showed high accuracy. The errors for specific area estimates for wheat, barley and chickpea were 9.9%, -5.2% and 10.9% (for 2005) and -2.8%, -78% and 64% (for 2006), respectively. Area estimates of total winter crop, wheat, barley and chickpea resulted in coefficient of determination (R(2)) values of 0.92, 0.89, 0.82 and 0.52, when contrasted against the actual shire-scale data. A significantly high coefficient of determination (0.87) was achieved for total winter crop area estimates in August across all shires for the 2006 season. Furthermore, the HANTS approach showed high accuracy in discriminating cropping area from non-cropping area and highlighted the need for accurate and up-to-date land use maps. The extrapolability of these approaches to determine total and specific winter crop area estimates, well before flowering, showed good utility across larger areas and seasons. Hence, it is envisaged that this technology might be transferable to different regions across Australia.

A 1,000 Frames/s Programmable Vision Chip with Variable Resolution and Row-Pixel-Mixed Parallel Image Processors

A programmable vision chip with variable resolution and row-pixel-mixed parallel image processors is presented. The chip consists of a CMOS sensor array, with row-parallel 6-bit Algorithmic ADCs, row-parallel gray-scale image processors, pixel-parallel SIMD Processing Element (PE) array, and instruction controller. The resolution of the image in the chip is variable: high resolution for a focused area and low resolution for general view. It implements gray-scale and binary mathematical morphology algorithms in series to carry out low-level and mid-level image processing and sends out features of the image for various applications. It can perform image processing at over 1,000 frames/s (fps). A prototype chip with 64 x 64 pixels resolution and 6-bit gray-scale image is fabricated in 0.18 mu m Standard CMOS process. The area size of chip is 1.5 mm x 3.5 mm. Each pixel size is 9.5 mu m x 9.5 mu m and each processing element size is 23 mu m x 29 mu m. The experiment results demonstrate that the chip can perform low-level and mid-level image processing and it can be applied in the real-time vision applications, such as high speed target tracking.

Fabrication of an integrated pixel with an organic light-emitting diode driven by copper phthalocyanine organic thin film transistors

An organic integrated pixel with organic light-emitting diodes (OLEDs) driven by organic thin film transistors (OTFTs) is fabricated by a greatly simplified processing. The OTFTs are based on copper phthalocyanine as the active medium and fabricated on indium-tin-oxide (ITO) glass with top-gate structure, thus an organic integrated pixel is easily made by integrating OLED with OTFT. The OTFTs show field-effect mobility of 0.4 cm(2) /Vs and on/off ratio of 10(3) order. The OLED is driven well and emits the brightness as large as 2100cd/m(2) at a current density of 14.6 mu A/cm(2) at -19.7 V gate voltage. This simple device structure is promising in the future large-area flexible OLED displays.

Multi-standard sub-pixel interpolation architecture for video motion estimation

A new domain-specific reconfigurable sub-pixel interpolation architecture for multi-standard video Motion Estimation (ME) is presented. The mixed use of parallel and serial-input FIR filters achieves high throughput rate and efficient silicon utilisation. Flexibility has been achieved by using a multiplexed reconfigurable data-path controlled by a selection signal. Silicon design studies show that this can be implemented using 34.8K gates with area and performance that compares very favourably with existing fixed solutions based solely on the H.264 standard. ©2008 IEEE.

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

Influência dos simuladores de tecidos moles na densidade óssea e dentária por meio de duas análises radiográficas: subtração digital e intensidade de pixel

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Grapevine Yield and Leaf Area Estimation Using Supervised Classification Methodology on RGB Images Taken under Field Conditions

The aim of this research was to implement a methodology through the generation of a supervised classifier based on the Mahalanobis distance to characterize the grapevine canopy and assess leaf area and yield using RGB images. The method automatically processes sets of images, and calculates the areas (number of pixels) corresponding to seven different classes (Grapes, Wood, Background, and four classes of Leaf, of increasing leaf age). Each one is initialized by the user, who selects a set of representative pixels for every class in order to induce the clustering around them. The proposed methodology was evaluated with 70 grapevine (V. vinifera L. cv. Tempranillo) images, acquired in a commercial vineyard located in La Rioja (Spain), after several defoliation and de-fruiting events on 10 vines, with a conventional RGB camera and no artificial illumination. The segmentation results showed a performance of 92% for leaves and 98% for clusters, and allowed to assess the grapevine’s leaf area and yield with R2 values of 0.81 (p < 0.001) and 0.73 (p = 0.002), respectively. This methodology, which operates with a simple image acquisition setup and guarantees the right number and kind of pixel classes, has shown to be suitable and robust enough to provide valuable information for vineyard management.

Effects of pixel noise and stimulus structure on visual detection performance

This thesis consisted of two major parts, one determining the masking characteristics of pixel noise and the other investigating the properties of the detection filter employed by the visual system. The theoretical cut-off frequency of white pixel noise can be defined from the size of the noise pixel. The empirical cut-off frequency, i.e. the largest size of noise pixels that mimics the effect of white noise in detection, was determined by measuring contrast energy thresholds for grating stimuli in the presence of spatial noise consisting of noise pixels of various sizes and shapes. The critical i.e. minimum number of noise pixels per grating cycle needed to mimic the effect of white noise in detection was found to decrease with the bandwidth of the stimulus. The shape of the noise pixels did not have any effect on the whiteness of pixel noise as long as there was at least the minimum number of noise pixels in all spatial dimensions. Furthermore, the masking power of white pixel noise is best described when the spectral density is calculated by taking into account all the dimensions of noise pixels, i.e. width, height, and duration, even when there is random luminance only in one of these dimensions. The properties of the detection mechanism employed by the visual system were studied by measuring contrast energy thresholds for complex spatial patterns as a function of area in the presence of white pixel noise. Human detection efficiency was obtained by comparing human performance with an ideal detector. The stimuli consisted of band-pass filtered symbols, uniform and patched gratings, and point stimuli with randomised phase spectra. In agreement with the existing literature, the detection performance was found to decline with the increasing amount of detail and contour in the stimulus. A measure of image complexity was developed and successfully applied to the data. The accuracy of the detection mechanism seems to depend on the spatial structure of the stimulus and the spatial spread of contrast energy.

Spatial and temporal measurements using polyoxometalate, enzymatic and biofilm layers on a CMOS 0.35 μm 64 X 64-pixel I.S.F.E.T. array sensor

This thesis presents the achievements and scientific work conducted using a previously designed and fabricated 64 x 64-pixel ion camera with the use of a 0.35 μm CMOS technology. We used an array of Ion Sensitive Field Effect Transistors (ISFETs) to monitor and measure chemical and biochemical reactions in real time. The area of our observation was a 4.2 x 4.3 mm silicon chip while the actual ISFET array covered an area of 715.8 x 715.8 μm consisting of 4096 ISFET pixels in total with a 1 μm separation space among them. The ion sensitive layer, the locus where all reactions took place was a silicon nitride layer, the final top layer of the austriamicrosystems 0.35 μm CMOS technology used. Our final measurements presented an average sensitivity of 30 mV/pH. With the addition of extra layers we were able to monitor a 65 mV voltage difference during our experiments with glucose and hexokinase, whereas a difference of 85 mV was detected for a similar glucose reaction mentioned in literature, and a 55 mV voltage difference while performing photosynthesis experiments with a biofilm made from cyanobacteria, whereas a voltage difference of 33.7 mV was detected as presented in literature for a similar cyanobacterial species using voltamemtric methods for detection. To monitor our experiments PXIe-6358 measurement cards were used and measurements were controlled by LabVIEW software. The chip was packaged and encapsulated using a PGA-100 chip carrier and a two-component commercial epoxy. Printed circuit board (PCB) has also been previously designed to provide interface between the chip and the measurement cards.