Verifiable Visualization for Isosurface Extraction

Visual representations of isosurfaces are ubiquitous in the scientific and engineering literature. In this paper, we present techniques to assess the behavior of isosurface extraction codes. Where applicable, these techniques allow us to distinguish whether anomalies in isosurface features can be attributed to the underlying physical process or to artifacts from the extraction process. Such scientific scrutiny is at the heart of verifiable visualization - subjecting visualization algorithms to the same verification process that is used in other components of the scientific pipeline. More concretely, we derive formulas for the expected order of accuracy (or convergence rate) of several isosurface features, and compare them to experimentally observed results in the selected codes. This technique is practical: in two cases, it exposed actual problems in implementations. We provide the reader with the range of responses they can expect to encounter with isosurface techniques, both under ""normal operating conditions"" and also under adverse conditions. Armed with this information - the results of the verification process - practitioners can judiciously select the isosurface extraction technique appropriate for their problem of interest, and have confidence in its behavior.

A Parallel Hardware Architecture for Scale and Rotation Invariant Feature Detection

This paper proposes a parallel hardware architecture for image feature detection based on the Scale Invariant Feature Transform algorithm and applied to the Simultaneous Localization And Mapping problem. The work also proposes specific hardware optimizations considered fundamental to embed such a robotic control system on-a-chip. The proposed architecture is completely stand-alone; it reads the input data directly from a CMOS image sensor and provides the results via a field-programmable gate array coupled to an embedded processor. The results may either be used directly in an on-chip application or accessed through an Ethernet connection. The system is able to detect features up to 30 frames per second (320 x 240 pixels) and has accuracy similar to a PC-based implementation. The achieved system performance is at least one order of magnitude better than a PC-based solution, a result achieved by investigating the impact of several hardware-orientated optimizations oil performance, area and accuracy.

U-curve: A branch-and-bound optimization algorithm for U-shaped cost functions on Boolean lattices applied to the feature selection problem

This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.

Automatic contour extraction from 2D neuron images

This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

Antioxidant therapy attenuates oxidative stress in the blood of subjects exposed to occupational airborne contamination from coal mining extraction and incineration of hospital residues

Coal mining and incineration of solid residues of health services (SRHS) generate several contaminants that are delivered into the environment, such as heavy metals and dioxins. These xenobiotics can lead to oxidative stress overgeneration in organisms and cause different kinds of pathologies, including cancer. In the present study the concentrations of heavy metals such as lead, copper, iron, manganese and zinc in the urine, as well as several enzymatic and non-enzymatic biomarkers of oxidative stress in the blood (contents of lipoperoxidation = TBARS, protein carbonyls = PC, protein thiols = PT, alpha-tocopherol = AT, reduced glutathione = GSH, and the activities of glutathione S-transferase = GST, glutathione reductase = GR, glutathione peroxidase = GPx, catalase = CAT and superoxide dismutase = SOD), in the blood of six different groups (n = 20 each) of subjects exposed to airborne contamination related to coal mining as well as incineration of solid residues of health services (SRHS) after vitamin E (800 mg/day) and vitamin C (500 mg/day) supplementation during 6 months, which were compared to the situation before the antioxidant intervention (Avila et al., Ecotoxicology 18:1150-1157, 2009; Possamai et al., Ecotoxicology 18:1158-1164, 2009). Except for the decreased manganese contents, heavy metal concentrations were elevated in all groups exposed to both sources of airborne contamination when compared to controls. TBARS and PC concentrations, which were elevated before the antioxidant intervention decreased after the antioxidant supplementation. Similarly, the contents of PC, AT and GSH, which were decreased before the antioxidant intervention, reached values near those found in controls, GPx activity was reestablished in underground miners, and SOD, CAT and GST activities were reestablished in all groups. The results showed that the oxidative stress condition detected previously to the antioxidant supplementation in both directly and indirectly subjects exposed to the airborne contamination from coal dusts and SRHS incineration, was attenuated after the antioxidant intervention.

Extraction of cellulose whiskers from cassava bagasse and their applications as reinforcing agent in natural rubber

In this work cassava bagasse, a by-product of cassava starch industrialization was investigated as a new raw material to extract cellulose whiskers. This by-product is basically constituted of cellulose fibers (17.5 wt%) and residual starch (82 wt%). Therefore, this residue contains both natural fibers and a considerable quantity of starch and this composition suggests the possibility of using cassava bagasse to prepare both starch nanocrystals and cellulose whiskers. In this way, the preparation of cellulose whiskers was investigated employing conditions of sulfuric acid hydrolysis treatment found in the literature. The ensuing materials were characterized by transmission electron microscopy (TEM) and X-ray diffraction experiments. The results showed that high aspect ratio cellulose whiskers were successfully obtained. The reinforcing capability of cellulose whiskers extracted from cassava bagasse was investigated using natural rubber as matrix. High mechanical properties were observed from dynamic mechanical analysis. (C) 2010 Elsevier B.V. All rights reserved.

Development of a new stir bar sorptive extraction coating and its application for the determination of six pesticides in sugarcane juice

In this article, a novel polydimethylsiloxane/activated carbon (PDMS-ACB) material is proposed as a new polymeric phase for stir bar sorptive extraction (SBSE). The PDMS-ACB stir bar, assembled using a simple Teflon (R)/glass capillary mold, demonstrated remarkable stability and resistance to organic solvents for more than 150 extractions. The SBSE bar has a diameter of 2.36 mm and a length of 2.2 cm and is prepared to contain 92 mu L of polymer coating. This new PDMS-ACB bar was evaluated for its ability to determine the quantity of pesticides in sugarcane juice samples by performing liquid desorption (LD) in 200 mu L of ethyl acetate and analyzing the solvent through gas chromatography coupled with mass spectrometry (GC-MS). A fractional factorial design was used to evaluate the main parameters involved in the extraction procedure. Then, a central composite design with a star configuration was used to optimize the significant extraction parameters. The method used demonstrated a limit of quantification (LOQ) of 0.5-40 mu g/L, depending on the analyte detected; the amount of recovery varied from 0.18 to 49.50%, and the intraday precision ranged from 0.072 to 8.40%. The method was used in the analysis of real sugarcane juice samples commercially available in local markets.

Determination of fluoxetine in plasma by gas chromatography-mass spectrometry using stir bar sorptive extraction

This article presents a method employing stir bar sorptive extraction (SBSE) with in situ derivatization, in combination with either thermal or liquid desorption on-line coupled to gas chromatography-mass spectrometry for the analysis of fluoxetine in plasma samples. Ethyl chloroformate was employed as derivatizing agent producing symmetrical peaks. Parameters such as solvent polarity, time for analyte desorption, and extraction time, were evaluated. During the validation process, the developed method presented specificity, linearity (R-2 > 0.99), precision (R.S.D. < 15%), and limits of quantification (LOQ) of 30 and 1.37 pg mL(-1), when liquid and thermal desorption were employed, respectively. This simple and highly sensitive method showed to be adequate for the measurement-of fluoxetine in typical and trace concentration levels. (c) 2008 Elsevier B.V. All rights reserved.

Dynamic Solid Phase DNA Extraction and PCR Amplification in Polyester-Toner Based Microchip

A variety of substrates have been used for fabrication of microchips for DNA extraction, PCR amplification, and DNA fragment separation, including the more conventional glass and silicon as well as alternative polymer-based materials. Polyester represents one such polymer, and the laser-printing of toner onto polyester films has been shown to be effective for generating polyester-toner (PeT) microfluidic devices with channel depths on the order of tens of micrometers. Here, we describe a novel and simple process that allows for the production of multilayer, high aspect-ratio PeT microdevices with substantially larger channel depths. This innovative process utilizes a CO(2) laser to create the microchannel in polyester sheets containing a uniform layer of printed toner, and multilayer devices can easily be constructed by sandwiching the channel layer between uncoated cover sheets of polyester containing precut access holes. The process allows the fabrication of deep channels, with similar to 270 mu m, and we demonstrate the effectiveness of multilayer PeT microchips for dynamic solid phase extraction (dSPE) and PCR amplification. With the former, we found that (i) more than 65% of DNA from 0.6 mu L of blood was recovered, (ii) the resultant DNA was concentrated to greater than 3 ng/mu L., (which was better than other chip-based extraction methods), and (iii) the DNA recovered was compatible with downstream microchip-based PCR amplification. Illustrative of the compatibility of PeT microchips with the PCR process, the successful amplification of a 520 bp fragment of lambda-phage DNA in a conventional thermocycler is shown. The ability to handle the diverse chemistries associated with DNA purification and extraction is a testimony to the potential utility of PeT microchips beyond separations and presents a promising new disposable platform for genetic analysis that is low cost and easy to fabricate.

Polydimethylsiloxane/polypyrrole stir bar sorptive extraction and liquid chromatography (SBSE/LC-UV) analysis of antidepressants in plasma samples

A new polymeric coating consisting of a dual-phase, polydimethylsiloxane (PDMS) and polypyrrole (PPY) was developed for the stir bar sorptive extraction (SBSE) of antidepressants (mirtazapine, citalopram, paroxetine, duloxetine, fluoxetine and sertraline) from plasma samples, followed by liquid chromatography analysis (SBSE/LC-UV). The extractions were based on both adsorption (PPY) and sorption (PDMS) mechanisms. SBSE variables, such as extraction time, temperature, pH of the matrix, and desorption time were optimized, in order to achieve suitable analytical sensitivity in a short time period. The PDMS/PPY coated stir bar showed high extraction efficiency (sensitivity and selectivity) toward the target analytes. The quantification limits (LOQ) of the SBSE/LC-UV method ranged from 20 ng mL(-1) to 50 ng mL(-1), and the linear range was from LOQ to 500 ng mL(-1), with a determination coefficient higher than 0.99. The inter-day precision of the SBSE/LC-UV method presented a variation coefficient lower than 15%. The efficiency of the SBSE/LC-UV method was proved by analysis of plasma samples from elderly depressed patients. (C) 2008 Elsevier B.V. All rights reserved.

Characters Extraction for Traffic Sign Destination boards in video and still images

Traffic Control Signs or destination boards on roadways offer significant information for drivers. Regulation signs tell something like your speed, turns, etc; Warning signs warn drivers of conditions ahead to help them avoid accidents; Destination signs show distances and directions to various locations; Service signs display location of hospitals, gas and rest areas etc. Because the signs are so important and there is always a certain distance from them to drivers, to let the drivers get information clearly and easily even in bad weather or other situations. The idea is to develop software which can collect useful information from a special camera which is mounted in the front of a moving car to extract the important information and finally show it to the drivers. For example, when a frame contains on a destination drive sign board it will be text something like "Linkoping 50",so the software should extract every character of "Linkoping 50", compare them with the already known character data in the database. if there is extracted character match "k" in the database then output the destination name and show to the driver. In this project C++ will be used to write the code for this software.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Dichlorvos exposure impedes extraction and amplification of DNA from insects in museum collections

Background: The insecticides dichlorvos, paradichlorobenzene and naphthalene have been commonly used to eradicate pest insects from natural history collections. However, it is not known how these chemicals affect the DNA of the specimens in the collections. We thus tested the effect of dichlorvos, paradichlorobenzene and naphthalene on DNA of insects (Musca domestica) by extracting and amplifying DNA from specimens exposed to insecticides in two different concentrations over increasing time intervals. Results: The results clearly show that dichlorvos impedes both extraction and amplification of mitochondrial and nuclear DNA after relatively short time, whereas paradichlorobenzene and naphthalene do not. Conclusion: Collections treated with paradichlorobenzene and naphthalene, are better preserved concerning DNA, than those treated with dichlorvos. Non toxic pest control methods should, however, be preferred due to physical damage of specimens and putative health risks by chemicals.