Functional MR Imaging of visuo-spatial network in Autism Spectrum Disorder

Individuals with Autism Spectrum Disorder (ASD) are generally thought to have impaired attentional and executive function upon which all their cognitive and behaviour functions are based. Mental Rotation is a recognized visuo-spatial task, involving spatial working memory, known to involve activation in the fronto-parietal networks. To elucidate the functioning of fronto-parietal networks in ASD, the aim of this study was to use fMRI techniques with a mental rotation task, to characterize the underlying functional neural system. Sixteen male participants (seven highfunctioning autism or Asperger's syndrome; nine ageand performance IQ-matched controls) underwent fMRI. Participants were presented with 18 baseline and 18 rotation trials, with stimuli rotated 3- dimensionaUy (45°-180°). Data were acquired on a 3- Tesla scanner. The most widely accepted area reported to be involved in processing of visuo-spatial information. Posterior Parietal Cortex, was found to be activated in both groups, however, the ASD group showed decreased activation in cortical and subcortical frontal structures that are highly interconnected, including lateral and medial Brodmann area 6, frontal eye fields, caudate, dorsolateral prefrontal cortex and anterior cingulate. The suggested connectivity between these regions indicates that one or more circuits are impaired as a result of the disorder. In future it is hoped that we are able to identify the possible point of origin of this dysfunction, or indeed if the entire network is dysfunctional.

Pressure-Frequency Sensing Subxiphoid Access System for Use in Percutaneous Cardiac Electrophysiology: Prototype Design and Pilot Study Results

We have designed, built, and tested an early prototype of a novel subxiphoid access system intended to facilitate epicardial electrophysiology, but with possible applications elsewhere in the body. The present version of the system consists of a commercially available insertion needle, a miniature pressure sensor and interconnect tubing, read-out electronics to monitor the pressures measured during the access procedure, and a host computer with user-interface software. The nominal resolution of the system is <0.1 mmHg, and it has deviations from linearity of <1%. During a pilot series of human clinical studies with this system, as well as in an auxiliary study done with an independent method, we observed that the pericardial space contained pressure-frequency components related to both the heart rate and respiratory rate, while the thorax contained components related only to the respiratory rate, a previously unobserved finding that could facilitate access to the pericardial space. We present and discuss the design principles, details of construction, and performance characteristics of this system.

Diagnostic performance of Antineutrophil Cytoplasmic Antibody tests for Idiopathic Vasculitides: Metaanalysis with a focus on antimyeloperoxidase antibodies

Objective. The diagnostic value of tests for antimyeloperoxidase antibodies (anti-MPO) for systemic vasculitis is less established than that for cytoplasmic antineutrophil cytoplasmic antibody (cANCA)/antiproteinase 3 antibodies (anti-PR3). Controversy exists regarding the optimal utilization of indirect immunofluorescence (IIF) ANCA testing versus antigen-specific ANCA testing. To summarize the pertinent data, we conducted a metaanalysis examining the diagnostic value of ANCA testing systems that include assays for anti-MPO. Methods. We performed a structured Medline search and reference list review. Target articles in the search strategy were those reporting the diagnostic value of immunoassays for anti-MPO for the spectrum of systemic necrotizing vasculitides that includes Wegener's granulomatosis, microscopic polyangiitis, the Churg-Strauss syndrome, and isolated pauci-immune necrotizing or crescentic glomerulonephritis, regardless of other types of ANCA tests. Inclusion criteria required specification of a consecutive or random patient selection method and the use of acceptable criteria for the diagnosis of vasculitis exclusive of ANCA test results. Weighted pooled summary estimates of sensitivity and specificity were calculated for anti-MPO alone, anti-MPO + perinuclear ANCA (pANCA), and anti-MPO/pANCA + anti-PR3/cANCA. Results. Of 457 articles reviewed, only 7 met the selection criteria. Summary estimates of sensitivity and specificity (against disease controls only) of assays for anti-MPO for the diagnosis of systemic necrotizing vasculitides were 37.1% (confidence interval 26.6% to 47.6%) and 96.3% (CI 94.1% to 98.5%), respectively. When the pANCA pattern by IIF was combined with anti-MPO testing, the specificity improved to 99.4%, with a lower sensitivity, 31.5%. The combined ANCA testing system (anti-PR3/cANCA + anti-MPO/pANCA) increased the sensitivity to 85.5% with a specificity of 98.6%. Conclusion. These results suggest that while anti-MPO is relatively specific for the diagnosis of systemic vasculitis, the combination system of immunoassays for anti-MPO and IIF for pANCA is highly specific and both tests should be used together given the high diagnostic precision required for these conditions. Because patients with ANCA associated vasculitis have either anti-MPO with pANCA or anti-PR3 with cANCA, and rarely both, a combined ANCA testing system including anti-PR3/cANCA and anti-MPO/pANCA is recommended to optimize the diagnostic performance of ANCA testing. (J Rheumatol 2001;28:1584-90)

Cognitive style factors affecting database query performance

As end-user computing becomes more pervasive, an organization's success increasingly depends on the ability of end-users, usually in managerial positions, to extract appropriate data from both internal and external sources. Many of these data sources include or are derived from the organization's accounting information systems. Managerial end-users with different personal characteristics and approaches are likely to compose queries of differing levels of accuracy when searching the data contained within these accounting information systems. This research investigates how cognitive style elements of personality influence managerial end-user performance in database querying tasks. A laboratory experiment was conducted in which participants generated queries to retrieve information from an accounting information system to satisfy typical information requirements. The experiment investigated the influence of personality on the accuracy of queries of varying degrees of complexity. Relying on the Myers–Briggs personality instrument, results show that perceiving individuals (as opposed to judging individuals) who rely on intuition (as opposed to sensing) composed queries more accurately. As expected, query complexity and academic performance also explain the success of data extraction tasks.

Laser scanned photodiodes (LSPs) for image sensing

An optimized ZnO:Al/a-pin SixC1-x:H/Al configuration for the laser scanned photodiode (LSP) imaging detector is proposed and the read-out parameters improved. The effect of the sensing element structure, cell configuration and light source flux are investigated and correlated with the sensor output characteristics. Data reveals that for sensors with wide band gap doped layers an increase on the image signal optimized to the blue is achieved with a dynamic range of two orders of magnitude, a responsivity of 6 mA W-1 and a sensitivity of 17 muW cm(-2) at 530 nm. The main output characteristics such as image responsivity, resolution, linearity and dynamic range were analyzed under reverse, forward and short circuit modes. The results show that the sensor performance can be optimized in short circuit mode. A trade-off between the scan time and the required resolution is needed since the spot size limits the resolution due to the cross-talk between dark and illuminated regions leading to blurring effects.

Novel structure for large area image sensing

This work presents preliminary results in the study of a novel structure for a laser scanned photodiode (LSP) type of image sensor. In order to increase the signal output, a stacked p-i-n-p-i-n structure with an intermediate light-blocking layer is used. The image and the scanning beam are incident through opposite sides of the sensor and their absorption is kept in separate junctions by an intermediate light-blocking layer. As in the usual LSP structure the scanning beam-induced photocurrent is dependent on the local illumination conditions of the image. The main difference between the two structures arises from the fact that in this new structure the image and the scanner have different optical paths leading to an increase in the photocurrent when the scanning beam is incident on a region illuminated on the image side of the sensor, while a decreasing in the photocurrent was observed in the single junction LSP. The results show that the structure can be successfully used as an image sensor even though some optimization is needed to enhance the performance of the device.

Use of a-SiC:H Semiconductor-Based Transducer for Glucose Sensing through FRET Analysis

Glucose sensing is an issue with great interest in medical and biological applications. One possible approach to glucose detection takes advantage of measuring changes in fluorescence resonance energy transfer (FRET) between a fluorescent donor and an acceptor within a protein which undergoes glucose-induced changes in conformation. This demands the detection of fluorescent signals in the visible spectrum. In this paper we analyzed the emission spectrum obtained from fluorescent labels attached to a protein which changes its conformation in the presence of glucose using a commercial spectrofluorometer. Different glucose nanosensors were used to measure the output spectra with fluorescent signals located at the cyan and yellow bands of the spectrum. A new device is presented based on multilayered a-SiC:H heterostructures to detect identical transient visible signals. The transducer consists of a p-i'(a-SiC:H)-n/p-i(a-Si:H)-n heterostructure optimized for the detection of the fluorescence resonance energy transfer between fluorophores with excitation in the violet (400 nm) and emissions in the cyan (470 nm) and yellow (588 nm) range of the spectrum. Results show that the device photocurrent signal measured under reverse bias and using appropriate steady state optical bias, allows the separate detection of the cyan and yellow fluorescence signals presented.

Sensing Cloud Optimization to Solve ED of Units with Valve-Point Effects and Multi-fuels

In this paper a solution to an highly constrained and non-convex economical dispatch (ED) problem with a meta-heuristic technique named Sensing Cloud Optimization (SCO) is presented. The proposed meta-heuristic is based on a cloud of particles whose central point represents the objective function value and the remaining particles act as sensors "to fill" the search space and "guide" the central particle so it moves into the best direction. To demonstrate its performance, a case study with multi-fuel units and valve- point effects is presented.

Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

GPU implementation of a hyperspectral coded aperture algorithm for compressive sensing

This paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA) algorithm for compressive sensing on graphics processing units (GPUs). HYCA method combines the ideas of spectral unmixing and compressive sensing exploiting the high spatial correlation that can be observed in the data and the generally low number of endmembers needed in order to explain the data. The proposed implementation exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs using shared memory and coalesced accesses to memory. The proposed algorithm is evaluated not only in terms of reconstruction error but also in terms of computational performance using two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN. Experimental results using real data reveals signficant speedups up with regards to serial implementation.

Parallel hyperspectral coded aperture for compressive sensing on GPUs

The application of compressive sensing (CS) to hyperspectral images is an active area of research over the past few years, both in terms of the hardware and the signal processing algorithms. However, CS algorithms can be computationally very expensive due to the extremely large volumes of data collected by imaging spectrometers, a fact that compromises their use in applications under real-time constraints. This paper proposes four efficient implementations of hyperspectral coded aperture (HYCA) for CS, two of them termed P-HYCA and P-HYCA-FAST and two additional implementations for its constrained version (CHYCA), termed P-CHYCA and P-CHYCA-FAST on commodity graphics processing units (GPUs). HYCA algorithm exploits the high correlation existing among the spectral bands of the hyperspectral data sets and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. The proposed P-HYCA and P-CHYCA implementations have been developed using the compute unified device architecture (CUDA) and the cuFFT library. Moreover, this library has been replaced by a fast iterative method in the P-HYCA-FAST and P-CHYCA-FAST implementations that leads to very significant speedup factors in order to achieve real-time requirements. The proposed algorithms are evaluated not only in terms of reconstruction error for different compressions ratios but also in terms of computational performance using two different GPU architectures by NVIDIA: 1) GeForce GTX 590; and 2) GeForce GTX TITAN. Experiments are conducted using both simulated and real data revealing considerable acceleration factors and obtaining good results in the task of compressing remotely sensed hyperspectral data sets.

Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid Network

IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.

Distributed processing of large remote sensing images using MapReduce - A case of Edge Detection

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Gain-of-Function Mutations in IFIH1 Cause a Spectrum of Human Disease Phenotypes Associated with Upregulated Type I Interferon Signaling

The type I interferon system is integral to human antiviral immunity. However, inappropriate stimulation or defective negative regulation of this system can lead to inflammatory disease. We sought to determine the molecular basis of genetically uncharacterized cases of the type I interferonopathy Aicardi-Goutières syndrome, and of other patients with undefined neurological and immunological phenotypes also demonstrating an upregulated type I interferon response. We found that heterozygous mutations in the cytosolic double-stranded RNA receptor gene IFIH1 (MDA5) cause a spectrum of neuro-immunological features consistently associated with an enhanced interferon state. Cellular and biochemical assays indicate that these mutations confer a gain-of-function - so that mutant IFIH1 binds RNA more avidly, leading to increased baseline and ligand-induced interferon signaling. Our results demonstrate that aberrant sensing of nucleic acids can cause immune upregulation.

Ensemble classifiers in remote sensing: a comparative analysis

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.