Cryptographic coprocessors for embedded systems

In the field of embedded systems design, coprocessors play an important role as a component to increase performance. Many embedded systems are built around a small General Purpose Processor (GPP). If the GPP cannot meet the performance requirements for a certain operation, a coprocessor can be included in the design. The GPP can then offload the computationally intensive operation to the coprocessor; thus increasing the performance of the overall system. A common application of coprocessors is the acceleration of cryptographic algorithms. The work presented in this thesis discusses coprocessor architectures for various cryptographic algorithms that are found in many cryptographic protocols. Their performance is then analysed on a Field Programmable Gate Array (FPGA) platform. Firstly, the acceleration of Elliptic Curve Cryptography (ECC) algorithms is investigated through the use of instruction set extension of a GPP. The performance of these algorithms in a full hardware implementation is then investigated, and an architecture for the acceleration the ECC based digital signature algorithm is developed. Hash functions are also an important component of a cryptographic system. The FPGA implementation of recent hash function designs from the SHA-3 competition are discussed and a fair comparison methodology for hash functions presented. Many cryptographic protocols involve the generation of random data, for keys or nonces. This requires a True Random Number Generator (TRNG) to be present in the system. Various TRNG designs are discussed and a secure implementation, including post-processing and failure detection, is introduced. Finally, a coprocessor for the acceleration of operations at the protocol level will be discussed, where, a novel aspect of the design is the secure method in which private-key data is handled

Metacognition in monkeys during an oculomotor task.

This study investigated whether rhesus monkeys show evidence of metacognition in a reduced, visual oculomotor task that is particularly suitable for use in fMRI and electrophysiology. The 2-stage task involved punctate visual stimulation and saccadic eye movement responses. In each trial, monkeys made a decision and then made a bet. To earn maximum reward, they had to monitor their decision and use that information to bet advantageously. Two monkeys learned to base their bets on their decisions within a few weeks. We implemented an operational definition of metacognitive behavior that relied on trial-by-trial analyses and signal detection theory. Both monkeys exhibited metacognition according to these quantitative criteria. Neither external visual cues nor potential reaction time cues explained the betting behavior; the animals seemed to rely exclusively on internal traces of their decisions. We documented the learning process of one monkey. During a 10-session transition phase, betting switched from random to a decision-based strategy. The results reinforce previous findings of metacognitive ability in monkeys and may facilitate the neurophysiological investigation of metacognitive functions.

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Investigation of Blast Wave Propagation: Correlating External Pressures to Brain Injury Predictors

Blast-induced Traumatic Brain Injury (bTBI) is the signature injury of the Iraq and Afghanistan wars; however, current understanding of bTBI is insufficient. In this study, novel analysis methods were developed to investigate correlations between external pressures and brain injury predictors. Experiments and simulations were performed to analyze placement of helmet-mounted pressure sensors. A 2D Finite Element model of a helmeted head cross-section was loaded with a blast wave. Pressure time-histories for nodes on the inner and outer surfaces of the helmet were cross-correlated to those inside the brain. Parallel physical experiments were carried out with a helmeted headform, pressure sensors, and pressure chamber. These analysis methods can potentially lead to better helmet designs and earlier detection and treatment of bTBI.

HBHA-specific IFN-{gamma} Synthesis at the Site of Infection during Active Tuberculosis in Humans.

RATIONALE: Tuberculosis (TB) remains a major cause of mortality. A better understanding of the immune responses to mycobacterial antigens may be helpful to develop improved vaccines and diagnostics. OBJECTIVE: The mycobacterial antigen heparin-binding-hemagglutinin (HBHA) induces strong interferon-gamma (IFN-gamma) responses by circulating lymphocytes from Mycobacterium tuberculosis latently infected subjects, and low responses associated with CD4(+) regulatory T (Treg) cells in TB patients. Here, we investigated HBHA-specific IFN-gamma responses at the site of the TB disease. METHODS: Bronchoalveolar lavages, pleural fluids and blood were prospectively collected from 61 patients with a possible diagnosis of pulmonary and/or pleural TB. HBHA-specific IFN-gamma production was analyzed by flow cytometry and ELISA. The suppressive effect of pleural Treg cells was investigated by depletion experiments. MEASUREMENTS AND MAIN RESULTS: The percentages of HBHA-induced IFN-gamma(+) alveolar and pleural lymphocytes were higher for pulmonary (P<0.0001) and for pleural (P<0.01) TB than for non-TB controls. Local CD4(+) and CD8(+) T cells produced the HBHA-specific IFN-gamma. This local secretion was not suppressed by Treg lymphocytes, contrasting with previously reported data on circulating lymphocytes. CONCLUSION: TB patients display differential effector and regulatory T cell responses to HBHA in local and circulating lymphocytes with a predominant effector CD4(+) and CD8(+) response locally, compared to a predominant Treg response among circulating lymphocytes. These findings may be helpful for the design of new vaccines against TB, and the detection of HBHA-specific T cells at the site of the infection may be a promising tool for the rapid diagnosis of active TB.

Applications of DNP-NMR for the measurement of heteronuclear T1 relaxation times

Measurement of heteronuclear spin-lattice relaxation times is hampered by both low natural abundance and low detection sensitivity. Combined with typically long relaxation times, this results in extended acquisition times which often renders the experiment impractical. Recently a variant of dynamic nuclear polarisation has been demonstrated in which enhanced nuclear spin polarisation, generated in the cryo-solid state, is transferred to the liquid state for detection. Combining this approach with small flip angle pulse trains, similar to the FLASH-T(1) imaging sequence, allows the rapid determination of spin-lattice relaxation times. In this paper we explore this method and its application to the measurement of T(1) for both carbon-13 and nitrogen-15 at natural abundance. The effects of RF inhomogeneity and the influence of proton decoupling in the context of this experiment are also investigated.

Iron organic speciation determination in rainwater using cathodic stripping voltammetry

A sensitive method using Competitive Ligand Exchange-Adsorptive Cathodic Stripping Voltammetry (CLE-ACSV) has been developed to determine for the first time iron (Fe) organic speciation in rainwater over the typical natural range of pH. We have adapted techniques previously developed in other natural waters to rainwater samples, using the competing ligand 1-nitroso-2-naphthol (NN). The blank was equal to 0.17 ± 0.05 nM (n = 14) and the detection limit (DL) for labile Fe was 0.15 nM which is 10–70 times lower than that of previously published methods. The conditional stability constant for NN under rainwater conditions was calibrated over the pH range 5.52–6.20 through competition with ethylenediaminetetraacetic acid (EDTA). The calculated value of the logarithm of β′Fe3+3(NN)β′Fe3+(NN)3 increased linearly with increasing pH according to log β′Fe3+3(NN)=2.4±0.6×pH+11.9±3.5log β′Fe3+(NN)3=2.4±0.6×pH+11.9±3.5 (salinity = 2.9, T = 20 °C). The validation of the method was carried out using desferrioxamine mesylate B (DFOB) as a natural model ligand for Fe. Adequate detection windows were defined to detect this class of ligands in rainwater with 40 μM of NN from pH 5.52 to 6.20. The concentration of Fe-complexing natural ligands was determined for the first time in three unfiltered and one filtered rainwater samples. Organic Fe-complexing ligand concentrations varied from 104.2 ± 4.1 nM equivalent of Fe(III) to 336.2 ± 19.0 nM equivalent of Fe(III) and the logarithm of the conditional stability constants, with respect to Fe3+, varied from 21.1 ± 0.2 to 22.8 ± 0.3. This method will provide important data for improving our understanding of the role of wet deposition in the biogeochemical cycling of iron.

Assistive software tools for secondary-level students with literacy difficulties.

Study conducted to evaluate the effectiveness of four assistive technology (AT) tools on literacy: (1) speech synthesis, (2) spellchecker, (3) homophone tool, and (4) dictionary. All four of these programs are featured in TextHelp’s Read&Write Gold software package. A total of 93 secondary-level students with reading disabilities participated in the study. The participants completed a number of computer-based literacy tests after being assigned to a Read&Write group or a control group that utilized Microsoft Word. The results indicated that improvements in the following areas for the Read&Write group: (1) reading comprehension, (2) homophone error detection, (3) spelling error detection, and (4) word meanings. The Microsoft Word group also improved in the areas of word meanings and error detection, though performed worse on homophone error detection. The authors contend that these results indicate that speech synthesis, spell checkers, homophone tools, and dictionary programs have a positive effect on literacy among students with reading disabilities. This study was conducted by researchers at the Queen’s University in Belfast, Ireland.

A Fabry-Perot Refractometer for Chemical Vapor Sensing by Solid-Phase Microextraction

The contour lithography method [1] is used to improve the fabrication yield of previously demonstrated [2] microfluidic Fabry-Perot (FP) refractive index (RI) sensors. The sensors are then coated with polydimethylsiloxane (PDMS) based polymers to detect vapor analytes by solid-phase microextraction (SPME). Preliminary characterization of devices coated with two different polymers and exposed to xylenes vapors yields a maximum sensitivity of 0.015 nm/ppm and a detection limit below 120 ppm.

Probing warm dense lithium by inelastic X-ray scattering

One of the grand challenges of contemporary physics is understanding strongly interacting quantum systems comprising such diverse examples as ultracold atoms in traps, electrons in high-temperature superconductors and nuclear matter. Warm dense matter, defined by temperatures of a few electron volts and densities comparable with solids, is a complex state of such interacting matter. Moreover, the study of warm dense matter states has practical applications for controlled thermonuclear fusion, where it is encountered during the implosion phase, and it also represents laboratory analogues of astrophysical environments found in the core of planets and the crusts of old stars, Here we demonstrate how warm dense matter states can be diagnosed and structural properties can be obtained by inelastic X-ray scattering measurements on a compressed lithium sample. Combining experiments and ab initio simulations enables us to determine its microscopic state and to evaluate more approximate theoretical models for the ionic structure.

WASP-41b: A Transiting Hot Jupiter Planet Orbiting a Magnetically Active G8V Star

We report the discovery of a transiting planet with an orbital period of 3.05 days orbiting the star TYC 7247-587-1. The star, WASP-41, is a moderately bright G8 V star (V=11.6) with a metallicity close to solar ([Fe/H]=-0.08±0.09). The star shows evidence of moderate chromospheric activity, both from emission in the cores of the Ca ii H and K ines and photometric variability with a period of 18.4 days and an amplitude of about 1%. We use a new method to show quantitatively that this periodic signal has a low false-alarm probability. The rotation period of the star implies a gyrochronological age for WASP-41 of 1.8 Gyr with an error of about 15%. We have used a combined analysis of the available photometric and spectroscopic data to derive the mass and radius of the planet (0.92±0.06 M, 1.20±0.06 R). Further observations of WASP-41 can be used to explore the connections between the properties of hot Jupiter planets and the level of chromospheric activity in their host stars.

Determination of thyreostat residues from bovine matrices using high-performance liquid chromatography

High-performance liquid chromatography (HPLC) methodologies were evaluated for the detection and quantification of thyreostatic drug residues in cattle serum and thyroid tissue. The paper details a protocol, using a simple ethyl acetate extraction for the determination of thiouracil, tapazole, methyl thiouracil, propyl thiouracil and phenyl thiouracil in thyroid tissue. Using two sequential HPLC injections, and quantitative analysis, in two steps, all five thyreostats were detectable at concentrations greater than 2.45-4.52 ng/g. Modifications to a published method for detection of thyreostatic residues in serum involving the addition of mercaptoethanol and a freezing step are described. The modifications improved sensitivity and allowed detection of the five thyreostats at levels greater than 16.98-35.25 ng/ml. Young bulls were treated with thyreostats to demonstrate the validity of the methodologies described. Administered thyreostats were not absorbed equally by the test animals and the compounds were not all detected in the serum samples removed at 7 days following drug withdrawal. These experiments indicate the necessity to be able to detect thyreostat residues in a variety of matrices. (C) 1998 Elsevier Science B.V. All rights reserved.

Determination of diclofenac from paediatric urine samples by stir bar sorptive extraction (SBSE)-HPLC-UV technique

A novel stir bar sorptive extraction (SBSE) method coupled with high performance liquid chromatography (HPLC) and UV detection for the extraction of diclofenac (DIC) from paediatric urine samples has been developed and validated. Selectivity and sensitivity being the prime objectives of the bioanalytical method for clinical samples, an optimised SBSE protocol was developed that selectively extracted DIC from various concurrently administered drugs. The validated assay was found to be linear (r=0.9999) over a concentration range of 100-2000 ng mL(-1). SBSE showed consistent recoveries (similar to 70%) of DIC across the validated linearity range. Overall, the method exhibited excellent accuracy and precision across all QC concentrations, tested over three days. Calculated LOD and LOQ were found to be 12.03 ng mL(-1) and 36.37 ng mL(-1), respectively, however, for the experimental purposes, 100 ngmL(-1) was considered as the validated LOQ(accuracy and precision at this LQC was

Direct evidence for a bystander effect of ionizing radiation in primary human fibroblasts

Bystander responses underlie some of the current efforts to develop gene therapy approaches for cancer treatment. Similarly, they may have a role in strategies to treat tumours with targeted radioisotopes. In this study we show direct evidence for the production of a radiation-induced bystander response in primary human fibroblasts, We utilize a novel approach of using a charged-particle microbeam, which allows individual cells within a population to be selected and targeted with counted charged particles. Individual primary human fibroblasts within a population of 600-800 cells were targeted with between 1 and 15 helium ions (effectively, alpha -particles). The charged particles were delivered through the centre of the nucleus with an accuracy of +/- 2 mum and a detection and counting efficiency of greater than 99%. When scored 3 days later, even though only a single cell had been targeted, typically an additional 80-100 damaged cells were observed in the surviving population of about 5000 cells. The yield of damaged cells was independent of the number of charged particles delivered to the targeted cell, Similar results of a 2-3-fold increase in the background level of damage present in the population were observed whether 1 or 4 cells were targeted within the dish. Also, when 200 cells within one quadrant of the dish were exposed to radiation, there was a 2-3-fold increase in the damage level in an unexposed quadrant of the dish, This effect was independent of the presence of serum in the culture medium and was only observed when a cell was targeted, but not when only the medium was exposed, confirming that a cell-mediated response is involved. (C) 2001 Cancer Research Campaign.

The use of geoscience methods for terrestrial forensic searches

Geoscience methods are increasingly being utilised in criminal, environmental and humanitarian forensic investigations, and the use of such methods is supported by a growing body of experimental and theoretical research. Geoscience search techniques can complement traditional methodologies in the search for buried objects, including clandestine graves, weapons, explosives, drugs, illegal weapons, hazardous waste and vehicles. This paper details recent advances in search and detection methods, with case studies and reviews. Relevant examples are given, together with a generalised workflow for search and suggested detection technique(s) table. Forensic geoscience techniques are continuing to rapidly evolve to assist search investigators to detect hitherto difficult to locate forensic targets.