65 resultados para Domain-specific analysis


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In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters improve convergence property of the standard LMS adaptive filters by applying the fixed data-independent orthogonal transforms and power normalization. However, the convergence performance of this class of adaptive filters can be quite different for various input processes, and it has not been fully explored. In this paper, we first discuss the mean-square stability and steady-state performance of this class of adaptive filters. We then analyze the effects of the transforms and power normalization performed in the various adaptive filters for both first-order and second-order AR processes. We derive the input asymptotic eigenvalue distributions and make comparisons on their convergence performance. Finally, computer simulations on AR process as well as moving-average (MA) process and autoregressive-moving-average (ARMA) process are demonstrated for the support of the analytical results.

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Linkage analysis is a successful procedure to associate diseases with specific genomic regions. These regions are often large, containing hundreds of genes, which make experimental methods employed to identify the disease gene arduous and expensive. We present two methods to prioritize candidates for further experimental study: Common Pathway Scanning (CPS) and Common Module Profiling (CMP). CPS is based on the assumption that common phenotypes are associated with dysfunction in proteins that participate in the same complex or pathway. CPS applies network data derived from protein–protein interaction (PPI) and pathway databases to identify relationships between genes. CMP identifies likely candidates using a domain-dependent sequence similarity approach, based on the hypothesis that disruption of genes of similar function will lead to the same phenotype. Both algorithms use two forms of input data: known disease genes or multiple disease loci. When using known disease genes as input, our combined methods have a sensitivity of 0.52 and a specificity of 0.97 and reduce the candidate list by 13-fold. Using multiple loci, our methods successfully identify disease genes for all benchmark diseases with a sensitivity of 0.84 and a specificity of 0.63. Our combined approach prioritizes good candidates and will accelerate the disease gene discovery process.

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EGF domains are extracellular protein modules cross-linked by three intradomain disulfides. Past studies suggest the existence of two types of EGF domain with three-disulfides, human EGF-like (hEGF) domains and complement C1r-like (cEGF) domains, but to date no functional information has been related to the two different types, and they are not differentiated in sequence or structure databases. We have developed new sequence patterns based on the different C-termini to search specifically for the two types of EGF domains in sequence databases. The exhibited sensitivity and specificity of the new pattern-based method represents a significant advancement over the currently available sequence detection techniques. We re-annotated EGF sequences in the latest release of Swiss-Prot looking for functional relationships that might correlate with EGF type. We show that important post-translational modifications of three-disulfide EGFs, including unusual forms of glycosylation and post-translational proteolytic processing, are dependent on EGF subtype. For example, EGF domains that are shed from the cell surface and mediate intercellular signaling are all hEGFs, as are all human EGF receptor family ligands. Additional experimental data suggest that functional specialization has accompanied subtype divergence. Based on our structural analysis of EGF domains with three-disulfide bonds and comparison to laminin and integrin-like EGF domains with an additional interdomain disulfide, we propose that these hEGF and cEGF domains may have arisen from a four-disulfide ancestor by selective loss of different cysteine residues.

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Peptide inhibitors of insulin-regulated aminopeptidase (IRAP) accelerate spatial learning and facilitate memory retention and retrieval by binding competitively to the catalytic site of the enzyme and inhibiting its catalytic activity. IRAP belongs to the M1 family of Zn2+-dependent aminopeptidases characterized by a catalytic domain that contains two conserved motifs, the HEXXH(X)18E Zn2+-binding motif and the GXMEN exopeptidase motif. To elucidate the role of GXMEN in binding peptide substrates and competitive inhibitors, site-directed mutagenesis was performed on the motif. Non-conserved mutations of residues G428, A429 and N432 resulted in mutant enzymes with altered catalytic activity, as well as divergent changes in kinetic properties towards the synthetic substrate leucine β-naphthalamide. The affinities of the IRAP inhibitors angiotensin IV, Nle1-angiotensin IV, and LVV-hemorphin-7 were selectively decreased. Substrate degradation studies using the in vitro substrates vasopressin and Leu-enkephalin showed that replacement of G428 by either D, E or Q selectively abolished the catalysis of Leu-enkephalin, while [A429G]IRAP and [N432A]IRAP mutants were incapable of cleaving both substrates. These mutational studies indicate that G428, A429 and N432 are important for binding of both peptide substrates and inhibitors, and confirm previous results demonstrating that peptide IRAP inhibitors competitively bind to its catalytic site.

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This paper addresses the area of video annotation, indexing and retrieval, and shows how a set of tools can be employed, along with domain knowledge, to detect narrative structure in broadcast news. The initial structure is detected using low-level audio visual processing in conjunction with domain knowledge. Higher level processing may then utilize the initial structure detected to direct processing to improve and extend the initial classification.

The structure detected breaks a news broadcast into segments, each of which contains a single topic of discussion. Further the segments are labeled as a) anchor person or reporter, b) footage with a voice over or c) sound bite. This labeling may be used to provide a summary, for example by presenting a thumbnail for each reporter present in a section of the video. The inclusion of domain knowledge in computation allows more directed application of high level processing, giving much greater efficiency of effort expended. This allows valid deductions to be made about structure and semantics of the contents of a news video stream, as demonstrated by our experiments on CNN news broadcasts.

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This paper presents a new time-frequency approach to the underdetermined blind source separation using the parallel factor decomposition of third-order tensors. Without any constraint on the number of active sources at an auto-term time-frequency point, this approach can directly separate the sources as long as the uniqueness condition of parallel factor decomposition is satisfied. Compared with the existing two-stage methods where the mixing matrix should be estimated at first and then used to recover the sources, our approach yields better source separation performance in the presence of noise. Moreover, the mixing matrix can be estimated at the same time of the source separation process. Numerical simulations are presented to show the superior performance of the proposed approach to some of the existing two-stage blind source separation methods that use the time-frequency representation as well.

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Urban Sustainability expresses the level of conservation of a city while living a town or consuming its urban resources, but the measurement of urban sustainability depends on what are considered important indicators of conservation besides the permitted levels of consumption in accordance with adopted criteria. This criterion should have common factors that are shared for all the members tested or cities to be evaluated as in this particular case for Abu Dhabi, but also have specific factors that are related to the geographic place, community and culture, that is the measures of urban sustainability specific to a middle east climate, community and culture where GIS Vector and Raster analysis have a role or add a value in urban sustainability measurements or grading are considered herein. Scenarios were tested using various GIS data types to replicate urban history (ten years period), current status and expected future of Abu Dhabi City setting factors to climate, community needs and culture. The useful Vector or Raster GIS data sets that are related to every scenario where selected and analysed in the sense of how and how much it can benefit the urban sustainability ranking in quantity and quality tests, this besides assessing the suitable data nature, type and format, the important topology rules to be considered, the useful attributes to be added, the relationships which should be maintained between data types of a geo- database, and specify its usage in a specific scenario test, then setting weights to each and every data type representing some elements of a phenomenon related to urban suitability factor. The results of assessing the role of GIS analysis provided data collection specifications such as the measures of accuracy reliable to a certain type of GIS functional analysis used in an urban sustainability ranking scenario tests. This paper reflects the prior results of the research that is conducted to test the multidiscipline evaluation of urban sustainability using different indicator metrics, that implement vector GIS Analysis and Raster GIS analysis as basic tools to assist the evaluation and increase of its reliability besides assessing and decomposing it, after which a hypothetical implementation of the chosen evaluation model represented by various scenarios was implemented on the planned urban sustainability factors for a certain period of time to appraise the expected future grade of urban sustainability and come out with advises associated with scenarios for assuring gap filling and relative high urban future sustainability. The results this paper is reflecting are concentrating on the elements of vector and raster GIS analysis that assists the proper urban sustainability grading within the chosen model, the reliability of spatial data collected; analysis selected and resulted spatial information. Starting from selecting some important indicators to comprise the model which include regional culture, climate and community needs an example of what was used is Energy Demand & Consumption (Cooling systems). Thus, this factor is related to the climate and it‟s regional specific as the temperature varies around 30-45 degrees centigrade in city areas, GIS 3D Polygons of building data used to analyse the volume of buildings, attributes „building heights‟, estimate the number of floors from the equation, following energy demand was calculated and consumption for the unit volume, and compared it in scenario with possible sustainable energy supply or using different environmental friendly cooling systems this is followed by calculating the cooling system effects on an area unit selected to be 1 sq. km, combined with the level of greenery area, and open space, as represented by parks polygons, trees polygons, empty areas, pedestrian polygons and road surface area polygons. (initial measures showed that cooling system consumption can be reduced by around 15 -20 % with a well-planned building distributions, proper spaces and with using environmental friendly products and building material, temperature levels were also combined in the scenario extracted from satellite images as interpreted from thermal bands 3 times during the period of assessment. Other examples of the assessment of GIS analysis to urban sustainability took place included Waste Productivity, some effects of greenhouse gases measured by the intensity of road polygons and closeness to dwelling areas, industry areas as defined from land use land cover thematic maps produced from classified satellite images then vectors were created to take part in defining their role within the scenarios. City Noise and light intensity assessment was also investigated, as the region experiences rapid development and noise is magnified due to construction activities, closeness of the airports, and highways. The assessment investigated the measures taken by urban planners to reduce degradation or properly manage it. Finally as a conclusion tables were presented to reflect the scenario results in combination with GIS data types, analysis types, and the level of GIS data reliability to measure the sustainability level of a city related to cultural and regional demands.

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This paper presents design and simulation of a circular meander dipole antenna at the industrial, scientific, and medical band of 915 MHz for energy scavenging in a passive head-mountable deep brain stimulation device. The interaction of the proposed antenna with a rat body is modeled and discussed. In the antenna, the radiating layer is meandered, and a FR-4 substrate is used to limit the radius and height of the antenna to 14 mm and 1.60 mm, respectively. The resonance frequency of the designed antenna is 915 MHz and the bandwidth of 15 MHz at a return loss of -10 dB in free space. To model the interaction of the antenna with a rat body, two aspects including functional and biological are considered. The functional aspect includes input impedance, resonance frequency, gain pattern, radiation efficiency of the antenna, and the biological aspect involves electric field distribution, and SAR value. A complete rat model is used in the finite difference time domain based EM simulation software XFdtd. The simulated results demonstrate that the specific absorption rate distributions occur within the skull in the rat model, and their values are higher than the standard regulated values for the antenna receiving power of 1W.

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Meta-analysis and meta-regression were used to evaluate whether evidence to date demonstrates deficits in procedural memory in individuals with specific language impairment (SLI), and to examine reasons for inconsistencies of findings across studies. The Procedural Deficit Hypothesis (PDH) proposes that SLI is largely explained by abnormal functioning of the frontal-basal ganglia circuits that support procedural memory. It has also been suggested that declarative memory can compensate for at least some of the problems observed in individuals with SLI. A number of studies have used Serial Reaction Time (SRT) tasks to investigate procedural learning in SLI. In this report, results from eight studies that collectively examined 186 participants with SLI and 203 typically-developing peers were submitted to a meta-analysis. The average mean effect size was .328 (CI95: .071, .584) and was significant. This suggests SLI is associated with impairments of procedural learning as measured by the SRT task. Differences among individual study effect sizes, examined with meta-regression, indicated that smaller effect sizes were found in studies with older participants, and in studies that had a larger number of trials on the SRT task. The contributions of age and SRT task characteristics to learning are discussed with respect to impaired and compensatory neural mechanisms in SLI.

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Background
According to previous reports, the risk of disability as a result of diabetes varies from none to double. Disability is an important measure of health and an estimate of the risk of disability as a result of diabetes is crucial in view of the global diabetes epidemic. We did a systematic review and meta-analysis to estimate this risk.

Methods
We searched Ovid, Medline, Embase, Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature up to Aug 8, 2012. We included studies of adults that compared the risk of disability—as measured by activities of daily living (ADL), instrumental activities of daily living (IADL), or mobility—in people with and without any type of diabetes. We excluded studies of subpopulations with specific illnesses or of people in nursing homes. From the studies, we recorded population characteristics, how diabetes was diagnosed (by doctor or self-reported), domain and definition of disability, and risk estimates for disability. We calculated pooled estimates by disability type and type of risk estimate (odds ratio [OR] or risk ratio [RR]).

Results
Our systematic review returned 3224 results, from which 26 studies were included in our meta-analyses. Diabetes increased the risk of mobility disability (15 studies; OR 1·71, 95% CI 1·53—1·91; RR 1·51, 95% CI 1·38—1·64), of IADL disability (ten studies; OR 1·65, 95% CI 1·55—1·74), and of ADL disability (16 studies; OR 1·82, 95% CI 1·63—2·04; RR 1·82, 95% CI 1·40—2·36).

Interpretation
Diabetes is associated with a strong increase in the risk of physical disability. Efforts to promote healthy ageing should account for this risk through prevention and management of diabetes.

Funding
Monash University, Baker IDI Bright Sparks Foundation, Australian Postgraduate Award, VicHealth, National Health and Medical Research Council, Australian Research Council, Victorian Government.

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The purpose of this study is to design a low-cost planar Archimedean dipole antenna for batteryless transcranial direct current stimulation devices. The antenna parameters including resonance frequency, radiation efficiency, radiation pattern, and gain are simulated using finite difference time domain based electromagnetic simulation software XFdtd. The proposed antenna is simulated with low-cost FR4 PCB substrate of thickness of 1.6 mm. The antenna is designed with half wavelength of resonant frequency and fed with a matching line. The target frequency band is the industrial, scientific and medical (ISM) band of 915 MHz which is in the simulated band width of 31 MHz (903-934MHz). Moreover, since the bio-effect of specific absorption rate by radio frequency electromagnetic wave for power harvesting is an important concern, we try to find out the safety limit. Thus a quantitative analysis of distributions of electric field and power absorption in anatomical human head model by the far field radio frequency energy received by our designed antenna has been presented.

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Recent studies using the mouse showed an inverse correlation between the Caveolin 1 gene expression and lactation, and this was regulated by prolactin. However, current study using mammary explants from pregnant mice showed that while insulin (I), cortisol (F) and prolactin (P) resulted in maximum induction of the β-casein gene, FP and IFP resulted in the downregulation of Caveolin 1. Additionally, IF, FP and IFP resulted in the downregulation of Caveolin 2. Immunohistochemistry confirmed localisation of Caveolin 1 specific to myoepithelial cells and adipocytes. Comparative studies with the tammar wallaby showed Caveolin 1 and 2 had 70-80% homology with the mouse proteins. However, in contrast to the mouse, Caveolin 1 and 2 genes showed a significantly increased level of expression in the mammary gland during lactation. The regulation of tammar Caveolin 1 and 2 gene expression was examined in mammary explants from pregnant tammars, and no significant difference was observed either in the absence or in the presence of IFP.