976 resultados para Identification numbers, Personal
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Pedestrian safety is a critical issue in Ethiopia. Reports show that 50 to 60% of traffic fatality victims in the country are pedestrians. The primary aim of this research was to examine the possible causes of and contributing factors to crashes with pedestrians in Ethiopia, and improve pedestrian safety by recommending possible countermeasures. The secondary aim was to develop appropriate pedestrian crash models for two-way two-lane rural roads and roundabouts in the capital city of Ethiopia. This research uses quantitative methods throughout the process of the investigation. The research has applied various statistical methods. The results of this research support the idea that geometric and operational features have significant influence on pedestrian safety and crashes. Accordingly, policies and strategies are needed to safeguard pedestrians in Ethiopia.
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Problems can occur in mentoring relationships if there is a “lack of mentoring skills on the part of the mentor” (Soutter, Kerr - Roubicek & Smith, 2000, p. 6), which includes the effectiveness of mentor’s personal attributes. There is little Australian research that analyses primary teachers’ personal attributes for mentoring; hence this study aims to examine preservice teachers’ perceptions of their mentors’ personal attributes. Specifically, this study focuses on mentors’ personal attributes in relation to their mentoring of primary science teaching....
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Perceptions of mentors' practices related to primary science teaching were obtained from final year preservice teachers after a 4-week practicum. Responses to a survey (n=59), constructed through literature-based practices and attributes of effective mentors, identified perceived strengths and weaknesses in the area of mentoring preservice teachers of primary science. Through exploratory factor analysis, this pilot study also tested the unidimensionality of mentoring practices and attributes assigned to categories (factors) that may characterise mentoring in primary science teaching. These suggested factors, namely, personal attributes, system requirements, pedagogical knowledge, modelling, and feedback had Cronbach alpha coefficients of internal consistency reliability of 0.93, 0.78, 0.94, 0.90, and 0.81 respectively. Survey responses indicated that mentors generally do not provide specific mentoring in primary science teaching. It is argued that science education reform requires the identification of factors and associated attributes and practices of mentoring primary science in order to effectively develop preservice teachers in primary science teaching.
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This project aimed to identify novel genetic risk variants associated with migraine in the Norfolk Island population. Statistical analysis and bioinformatics approaches such as polygenic modeling and gene clustering methods were carried out to explore genotypic and expression data from high-throughput techniques. This project had a particular focus on hormonal genes and other genetic variants and identified a modest effect size on the migraine phenotype.
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Testing the strategies of discourse and materiality, this practice-based and practice-led research experiments with how anonymous storytelling by vulnerable communities, like that of the sexual minorities and their allies in Malaysia, can better speak to their human rights issues without further subjecting them to personal attacks and targetted persecution. The research identifies the critical role of the voice in lending authenticity and credibility to first person narratives; and contextual credibility as a form of credibility which personal stories naturally aspire to achieve with audiences. Adopting a discursive view of persuasion and recognising too that the power of persuasion may in effect lie with those who receive these stories rather than with those who tell them, the insights and knowledge gained from the research informed the development of the field output, Persuasive Storytelling by Vulnerable Communities in Aggressive Contexts: A Human Rights Communication Framework.
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Introduction Canadian C spine rule and NEXUS criteria have identified risk factors for cervical spine injury in adults but not for children. PECARN has developed an 8 variable model for cervical spine injury in children. We sought to identify the mechanism, prevalence of PECARN risk factors, injury patterns, and management of severe Paediatric cervical spine injuries presenting to the major children’s hospitals in Brisbane, Australia. Methods This a retrospective study of the children with cervical spine injuries who presented directly or were referred to the major children’s hospitals in Brisbane over 5 years. Results There were 38 patients with 18 male and 20 female.The mean age was 8.6 years. They were divided into two groups according to their age, (Group 1 < =8 years had 18 (47%) patients, while group 2 (9-15 years) had 20 (53%) patients. Motor vehicle related injuries were the most common (61%) in Group 1 while it was sporting injuries (50%) in group 2. All patients in group 1 had upper cervical injury (C0-C2) while subaxial injuries were most common in group 2 (66.6%). 82% of the patients had 2 or more PECARN risk factors. 18 children (47%) had normal neurological assessment at presentation, 6 (16%) had radicular symptoms, 11 (29%) could not be assessed as they had already been intubated due to the severity of the injury, 3 (8%) had incomplete cord injury. 29 (69%) patients had normal neurological assessment at final follow up and 2 children died from their injuries. Conclusion Our study confirms that younger children sustain upper cervical injuries most commonly secondary to motor vehicle accidents, while the older sustain subaxial injuries from sporting activities. The significant prevalence of the PECARN risk factors among this cohort of patients have led to them being incorporated into a protocol at these hospitals used to assess patients with suspected cervical spinal injury.
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Any kind of imbalance in the operation of a wind turbine has adverse effect on the downstream torsional components as well as tower structure. It is crucial to detect imbalance at its very inception. The identification of the type of imbalance is also required so that appropriate measures of fault accommodation can be performed in the control system. In particular, it is important to distinguish between mass and aerodynamic imbalance. While the former is gradually caused by a structural anomaly (e.g. ice deposition, moisture accumulation inside blade), the latter is generally associated to a fault in the pitch control system. This paper proposes a technique for the detection and identification of imbalance fault in large scale wind turbines. Unlike most other existing method it requires only the rotor speed signal which is readily available in existing turbines. Signature frequencies have been proposed in this work to identify imbalance type based on their physical phenomenology. The performance of this technique has been evaluated by simulations using an existing benchmark model. The effectiveness of the proposed method has been confirmed by the simulation results.
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Objective. To identify genomic regions linked with determinants of age at symptom onset, disease activity, and functional impairment in ankylosing spondylitis (AS). Methods. A whole genome linkage scan was performed in 188 affected sibling pair families with 454 affected individuals. Traits assessed were age at symptom onset, disease activity assessed by the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and functional impairment assessed by the Bath Ankylosing Spondylitis Functional Index (BASFI). Parametric and nonparametric quantitative linkage analysis was performed using parameters defined in a previous segregation study. Results. Heritabilities of the traits studied in this data set were as follows: BASDAI 0.49 (P = 0.0001, 95% confidence interval [95% CI] 0.23-0.75), BASFI 0.76 (P = 10-7, 95% CI 0.49-1.0), and age at symptom onset 0.33 (P = 0.005, 95% CI 0.04-0.62). No linkage was observed between the major histocompatibility complex (MHC) and any of the traits studied (logarithm of odds [LOD] score <1.0). "Significant" linkage (LOD score 4.0) was observed between a region on chromosome 18p and the BASDAI. Age at symptom onset showed "suggestive" linkage to chromosome 11p (LOD score 3.3). Maximum linkage with the BASFI was seen at chromosome 2q (LOD score 2.9). Conclusion. In contrast to the genetic determinants of susceptibility to AS, clinical manifestations of the disease measured by the BASDAI, BASFI, and age at symptom onset are largely determined by a small number of genes not encoded within the MHC.
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Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify common disease-associated variants. Even quite large GWAS, however, have only at best identified moderate proportions of the genetic variants contributing to disease heritability. To provide cost-effective genotyping of common and rare variants to map the remaining heritability and to fine-map established loci, the Immunochip Consortium has developed a 200,000 SNP chip that has been produced in very large numbers for a fraction of the cost of GWAS chips. This chip provides a powerful tool for immunogenetics gene mapping.
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Change in temperature is often a major environmental factor in triggering waterborne disease outbreaks. Previous research has revealed temporal and spatial patterns of bacterial population in several aquatic ecosystems. To date, very little information is available on aquaculture environment. Here, we assessed environmental temperature effects on bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei (FASFL). Water samples were collected over a one-year period, and aquatic bacteria were characterized by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA pyrosequencing. Resulting DGGE fingerprints revealed a specific and dynamic bacterial population structure with considerable variation over the seasonal change, suggesting that environmental temperature was a key driver of bacterial population in the FASFL. Pyrosequencing data further demonstrated substantial difference in bacterial community composition between the water at higher (WHT) and at lower (WLT) temperatures in the FASFL. Actinobacteria, Proteobacteria and Bacteroidetes were the highest abundant phyla in the FASFL, however, a large number of unclassified bacteria contributed the most to the observed variation in phylogenetic diversity. The WHT harbored remarkably higher diversity and richness in bacterial composition at genus and species levels when compared to the WLT. Some potential pathogenenic species were identified in both WHT and WLT, providing data in support of aquatic animal health management in the aquaculture industry.
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The koala (Phascolarctos cinereus) is an Australian marsupial that continues to experience significant population declines. Infectious diseases caused by pathogens such as Chlamydia are proposed to have a major role. Very few species-specific immunological reagents are available, severely hindering our ability to respond to the threat of infectious diseases in the koala. In this study, we utilise data from the sequencing of the koala transcriptome to identify key immunological markers of the koala adaptive immune response and cytokines known to be important in the host response to chlamydial infection in other species. This report describes the identification and preliminary sequence analysis of (1) T lymphocyte glycoprotein markers (CD4, CD8); (2) IL-4, a marker for the Th2 response; (3) cytokines such as IL-6, IL-12 and IL-1β, that have been shown to have a role in chlamydial clearance and pathology in other hosts; and (4) the sequences for the koala immunoglobulins, IgA, IgG, IgE and IgM. These sequences will enable the development of a range of immunological reagents for understanding the koala’s innate and adaptive immune responses, while also providing a resource that will enable continued investigations into the origin and evolution of the marsupial immune system.
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Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time-consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user-friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two-stage algorithm. First, an alignment-free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment-based K2P distance nearest-neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment-free methods and (ii) higher scalability than alignment-based distance methods and character-based methods. These results suggest that this platform is able to deal with both large-scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/.
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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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Background Domestic violence against women is a major public health problem and violations of women’s human rights. Health professionals could play an important role in screening for the victims. From the evidence to date, it is unclear whether health professionals do play an active role in identification of the victims. Objectives To develop a reliable and valid instrument to measure health professionals’ attitude to identifying female victims of domestic violence. Methods A primary questionnaire was constructed in accordance with established guidelines using the Theory of Planned Behaviour Ajzen (1975) to develop an instrument to measure health professionals’ attitudes in identifying female victim of DV. An expert panel was used to establish content validity. Focus groups amongst a group of health professionals (N = 5) of the target population were performed to confirm face validity. A pilot study (N = 30 nurses and doctors) was undertaken to elicit the feasibility and reliability of the questionnaire. The questionnaire was also administered a second time after one week to check the stability of the tests. Results Feedbacks of the expert panel’s and group discussion confirmed that the questionnaire had the content and face validity. Cronbach’s alpha values for all the items were greater than 0.7. Strong correlations between the direct and indirect measures confirmed that the indirect measures were well constructed. High test-retest correlations confirmed that the measures were reliable in the sense of temporal stability. Significance This tool has the potential to be used by researchers in expanding the knowledge base in this important area.
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Ankylosing spondylitis is a common, highly heritable inflammatory arthritis affecting primarily the spine and pelvis. In addition to HLA-B*27 alleles, 12 loci have previously been identified that are associated with ankylosing spondylitis in populations of European ancestry, and 2 associated loci have been identified in Asians. In this study, we used the Illumina Immunochip microarray to perform a case-control association study involving 10,619 individuals with ankylosing spondylitis (cases) and 15,145 controls. We identified 13 new risk loci and 12 additional ankylosing spondylitis-associated haplotypes at 11 loci. Two ankylosing spondylitis-associated regions have now been identified encoding four aminopeptidases that are involved in peptide processing before major histocompatibility complex (MHC) class I presentation. Protective variants at two of these loci are associated both with reduced aminopeptidase function and with MHC class I cell surface expression.