903 resultados para Principle component


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Symmetry is a fundamental property found in both the physical and natural worlds. Bilateral symmetry is also present in the organization of the brain, however the degree to which symmetry is also an organizing principal between and within the key constituent elements of the nervous system, neurons, is not known. We compared and contrasted the structural organization of principal neurons (PN) in the three subnuclei of the lateral amygdala (LA) of the rat and for comparison also from the infralimbic cortex (IL)...

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The maximum principle for the space and time–space fractional partial differential equations is still an open problem. In this paper, we consider a multi-term time–space Riesz–Caputo fractional differential equations over an open bounded domain. A maximum principle for the equation is proved. The uniqueness and continuous dependence of the solution are derived. Using a fractional predictor–corrector method combining the L1 and L2 discrete schemes, we present a numerical method for the specified equation. Two examples are given to illustrate the obtained results.

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Two studies documented the “David and Goliath” rule—the tendency for people to perceive criticism of “David” groups (groups with low power and status) as less normatively permissible than criticism of “Goliath” groups (groups with high power and status). The authors confirmed the existence of the David and Goliath rule across Western and Chinese cultures (Study 1). However, the rule was endorsed more strongly in Western than in Chinese cultures, an effect mediated by cultural differences in power distance. Study 2 identified the psychological underpinnings of this rule in an Australian sample. Lower social dominance orientation (SDO) was associated with greater endorsement of the rule, an effect mediated through the differential attribution of stereotypes. Specifically, those low in SDO were more likely to attribute traits of warmth and incompetence to David versus Goliath groups, a pattern of stereotypes that was related to the protection of David groups from criticism.

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Nanotubes and nanosheets are low-dimensional nanomaterials with unique properties that can be exploited for numerous applications. This book offers a complete overview of their structure, properties, development, modeling approaches, and practical use. It focuses attention on boron nitride (BN) nanotubes, which have had major interest given their special high-temperature properties, as well as graphene nanosheets, BN nanosheets, and metal oxide nanosheets. Key topics include surface functionalization of nanotubes for composite applications, wetting property changes for biocompatible environments, and graphene for energy storage applications

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People’s beliefs about where society has come from and where it is going have personal and political consequences. Here, we conduct a detailed investigation of these beliefs through re-analyzing Kashima et al.’s (Study 2, n = 320) data from China, Australia, and Japan. Kashima et al. identified a “folk theory of social change” (FTSC) belief that people in society become more competent over time, but less warm and moral. Using three-mode principal components analysis, an under-utilized analytical method in psychology, we identified two additional narratives: Utopianism/Dystopianism (people becoming generally better or worse over time) and Expansion/Contraction (an increase/decrease in both positive and negative aspects of character over time). Countries differed in endorsement of these three narratives of societal change. Chinese endorsed the FTSC and Utopian narratives more than other countries, Japanese held Dystopian and Contraction beliefs more than other countries, and Australians’ narratives of societal change fell between Chinese and Japanese. Those who believed in greater economic/technological development held stronger FTSC and Expansion/Contraction narratives, but not Utopianism/Dystopianism. By identifying multiple cultural narratives about societal change, this research provides insights into how people across cultures perceive their social world and their visions of the future.

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This thesis considers whether the Australian Privacy Commissioner's use of its powers supports compliance with the requirement to 'take reasonable steps' to protect personal information in National Privacy Principle 4 of the Privacy Act 1988 (Cth). Two unique lenses were used. First, the Commissioner's use of powers was assessed against the principles of transparency, balance and vigorousness and secondly against alignment with an industry practice approach to securing information. Following a comprehensive review of publicly available materials, interviews and investigation file records, this thesis found that the Commissioner's use of his powers has not been transparent, balanced or vigorous, nor has it been supportive of an industry practice approach to securing data. Accordingly, it concludes that the Privacy Commissioner's use of its regulatory powers is unlikely to result in any significant improvement to the security of personal information held by organisations in Australia.

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This discussion paper is intended to provide background material for the workshop organised by Queensland University Technology (QUT) on 17 October 2014. The overall purpose of the workshop is to better understand the relationship between the precautionary principle and endangered species management in Australia. In particular, we are looking for real life examples (or hypotheticals) of where the principle is (or is not) being applied in relation to Australia’s endangered species. A wide variety of participants have been invited to the workshop including scientists, representatives of NGOs, lawyers and academics. Whilst some very general information is outlined below, we encourage all participants to bring their own thoughts on how the precautionary principle should operate and to reflect on examples of where you have seen it work (or not work) in Australia. The sharing of your own case studies is thus encouraged.

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As a new research method supplementing the existing qualitative and quantitative approaches, agent-based modelling and simulation (ABMS) may fit well within the entrepreneurship field because the core concepts and basic premises of entrepreneurship coincide with the characteristics of ABMS (McKelvey, 2004; Yang & Chandra, 2013). Agent-based simulation is a simulation method based on agent-based models. The agentbased models are composed of heterogeneous agents and their behavioural rules. By repeatedly carrying out agent-based simulations on a computer, the simulations reproduce each agent’s behaviour, their interactive process, and the emerging macroscopic phenomenon according to the flow of time. Using agent-based simulations, researchers may investigate temporal or dynamic effects of each agent’s behaviours.

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Bidirectional (anterograde and retrograde) motor-based intraflagellar transport (IFT) governs cargo transport and delivery processes that are essential for primary cilia growth and maintenance and for hedgehog signaling functions. The IFT dynein-2 motor complex that regulates ciliary retrograde protein transport contains a heavy chain dynein ATPase/motor subunit, DYNC2H1, along with other less well functionally defined subunits. Deficiency of IFT proteins, including DYNC2H1, underlies a spectrum of skeletal ciliopathies. Here, by using exome sequencing and a targeted next-generation sequencing panel, we identified a total of 11 mutations in WDR34 in 9 families with the clinical diagnosis of Jeune syndrome (asphyxiating thoracic dystrophy). WDR34 encodes a WD40 repeat-containing protein orthologous to Chlamydomonas FAP133, a dynein intermediate chain associated with the retrograde intraflagellar transport motor. Three-dimensional protein modeling suggests that the identified mutations all affect residues critical for WDR34 protein-protein interactions. We find that WDR34 concentrates around the centrioles and basal bodies in mammalian cells, also showing axonemal staining. WDR34 coimmunoprecipitates with the dynein-1 light chain DYNLL1 in vitro, and mining of proteomics data suggests that WDR34 could represent a previously unrecognized link between the cytoplasmic dynein-1 and IFT dynein-2 motors. Together, these data show that WDR34 is critical for ciliary functions essential to normal development and survival, most probably as a previously unrecognized component of the mammalian dynein-IFT machinery.

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Background Pollens of the Panicoideae subfamily of grasses including Bahia (Paspalum notatum) are important allergen sources in subtropical regions of the world. An assay for specific IgE to the major molecular allergenic component, Pas n 1, of Bahia grass pollen (BaGP) would have immunodiagnostic utility for patients with pollen allergy in these regions. Methods Biotinylated Pas n 1 purified from BaGP was coated onto streptavidin ImmunoCAPs. Subjects were assessed by clinical history of allergic rhinitis and skin prick test (SPT) to aeroallergens. Serum total, BaGP-specific and Pas n 1-specific IgE were measured. Results: Pas n 1 IgE concentrations were highly correlated with BaGP SPT (r = 0.795, p < 0.0001) and BaGP IgE (r = 0.915, p < 0.0001). At 0.23 kU/l Pas n 1 IgE, the diagnostic sensitivity (92.4%) and specificity (93.1%) for the detection of BaGP allergy was high (area under receiver operator curve 0.960, p < 0.0001). The median concentrations of Pas n 1 IgE in non-Atopic subjects (0.01 kU/l, n = 67) and those with other allergies (0.02 kU/l, n = 59) showed no inter-group difference, whilst grass pollen-Allergic patients with allergic rhinitis showed elevated Pas n 1 IgE (6.71 kU/l, n = 182, p < 0.0001). The inter-Assay coefficient of variation for the BaGP-Allergic serum pool was 6.92%. Conclusions Pas n 1 IgE appears to account for most of the BaGP-specific IgE. This molecular component immunoassay for Pas n 1 IgE has potential utility to improve the sensitivity and accuracy of diagnosis of BaGP allergy for patients in subtropical regions.

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The causes of autoimmune diseases have yet to be fully elucidated. Autoantibodies, autoreactive T cell responses, the presence of a predisposing major histocompatibility complex (MHC) haplotype and responsiveness to corticosteroids are features, and some are possibly contributory causes of autoimmune disease. The most challenging question is how autoimmune diseases are triggered. Molecular mimicry of host cell determinants by epitopes of infectious agents with ensuing cross-reactivity is one of the most popular yet still controversial theories for the initiation of autoimmune diseases [1]. Throughout the 1990s, hundreds of research articles focusing to various extents on epitope mimicry, as it is more accurately described in an immunological context, were published annually. Many of these articles presented data that were consistent with the hypothesis of mimicry but that did not actually prove the theory. Other equally convincing reports indicated that epitope mimicry was not the cause of the autoimmune disease despite sequence similarity between molecules of infectious agents and the host. Some 20 years ago, Rothman [2] proposed a model for disease causation and I have used this as a framework to examine the role of epitope mimicry in the development of autoimmune disease. The thesis of Rothman’s model is that an effect, in this instance autoimmune disease, arises as a result of a cause. In most cases, multiple-component causes contribute synergistically to yield the effect, and each of these components alone is insufficient as a cause. Logically, some component causes, such as the presence of a particular autoimmune response, are also necessary causes.

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Some statistical procedures already available in literature are employed in developing the water quality index, WQI. The nature of complexity and interdependency that occur in physical and chemical processes of water could be easier explained if statistical approaches were applied to water quality indexing. The most popular statistical method used in developing WQI is the principal component analysis (PCA). In literature, the WQI development based on the classical PCA mostly used water quality data that have been transformed and normalized. Outliers may be considered in or eliminated from the analysis. However, the classical mean and sample covariance matrix used in classical PCA methodology is not reliable if the outliers exist in the data. Since the presence of outliers may affect the computation of the principal component, robust principal component analysis, RPCA should be used. Focusing in Langat River, the RPCA-WQI was introduced for the first time in this study to re-calculate the DOE-WQI. Results show that the RPCA-WQI is capable to capture similar distribution in the existing DOE-WQI.

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Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

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Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve.

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We propose a robust method for mosaicing of document images using features derived from connected components. Each connected component is described using the Angular Radial Tran. form (ART). To ensure geometric consistency during feature matching, the ART coefficients of a connected component are augmented with those of its two nearest neighbors. The proposed method addresses two critical issues often encountered in correspondence matching: (i) The stability of features and (ii) Robustness against false matches due to the multiple instances of characters in a document image. The use of connected components guarantees a stable localization across images. The augmented features ensure a successful correspondence matching even in the presence of multiple similar regions within the page. We illustrate the effectiveness of the proposed method on camera captured document images exhibiting large variations in viewpoint, illumination and scale.