995 resultados para Frobisher, Martin, Sir, approximately 1535-1594.


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Calleija, a small to medium sized (SME) Australian and internationally recognised fine jeweller has secured a significant strategic global partnership with one of the world’s best-known luxury automobile brands, Aston Martin. Forging this international relationship to produce an elegant fine jewellery collection has given rise to a new network between the Australian jewellery industry and the European automobile industry. Calleija’s exclusive association with Aston Martin consolidates a shared passion for the finest quality and craftsmanship which was inspired by Aston Martin’s Supercar, the One-77. This inspiration lead to John Calleija being chosen by Aston Martin to design this latest high-luxury offering in which each design is limited to only 77 pieces utilising 30 unique designs (Calleija, 2012). The story behind Calleija’s internationalisation to the United Kingdom (UK) and their subsequent business-to-business strategic partnership with Aston Martin is no doubt a good sign for the Australian jewellery industry.

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Working memory-related brain activation has been widely studied, and impaired activation patterns have been reported for several psychiatric disorders. We investigated whether variation in N-back working memory brain activation is genetically influenced in 60 pairs of twins, (29 monozygotic (MZ), 31 dizygotic (DZ); mean age 24.4 ± 1.7S.D.). Task-related brain response (BOLD percent signal difference of 2 minus 0-back) was measured in three regions of interest. Although statistical power was low due to the small sample size, for middle frontal gyrus, angular gyrus, and supramarginal gyrus, the MZ correlations were, in general, approximately twice those of the DZ pairs, with non-significant heritability estimates (14-30%) in the low-moderate range. Task performance was strongly influenced by genes (57-73%) and highly correlated with cognitive ability (0.44-0.55). This study, which will be expanded over the next 3 years, provides the first support that individual variation in working memory-related brain activation is to some extent influenced by genes.

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A major challenge in neuroscience is finding which genes affect brain integrity, connectivity, and intellectual function. Discovering influential genes holds vast promise for neuroscience, but typical genome-wide searches assess approximately one million genetic variants one-by-one, leading to intractable false positive rates, even with vast samples of subjects. Even more intractable is the question of which genes interact and how they work together to affect brain connectivity. Here, we report a novel approach that discovers which genes contribute to brain wiring and fiber integrity at all pairs of points in a brain scan. We studied genetic correlations between thousands of points in human brain images from 472 twins and their nontwin siblings (mean age: 23.7 2.1 SD years; 193 male/279 female).Wecombined clustering with genome-wide scanning to find brain systems withcommongenetic determination.Wethen filtered the image in a new way to boost power to find causal genes. Using network analysis, we found a network of genes that affect brain wiring in healthy young adults. Our new strategy makes it computationally more tractable to discover genes that affect brain integrity. The gene network showed small-world and scale-free topologies, suggesting efficiency in genetic interactions and resilience to network disruption. Genetic variants at hubs of the network influence intellectual performance by modulating associations between performance intelligence quotient and the integrity of major white matter tracts, such as the callosal genu and splenium, cingulum, optic radiations, and the superior longitudinal fasciculus.

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The human connectome has recently become a popular research topic in neuroscience, and many new algorithms have been applied to analyze brain networks. In particular, network topology measures from graph theory have been adapted to analyze network efficiency and 'small-world' properties. While there has been a surge in the number of papers examining connectivity through graph theory, questions remain about its test-retest reliability (TRT). In particular, the reproducibility of structural connectivity measures has not been assessed. We examined the TRT of global connectivity measures generated from graph theory analyses of 17 young adults who underwent two high-angular resolution diffusion (HARDI) scans approximately 3 months apart. Of the measures assessed, modularity had the highest TRT, and it was stable across a range of sparsities (a thresholding parameter used to define which network edges are retained). These reliability measures underline the need to develop network descriptors that are robust to acquisition parameters.

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The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

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The SNP-SNP interactome has rarely been explored in the context of neuroimaging genetics mainly due to the complexity of conducting approximately 10(11) pairwise statistical tests. However, recent advances in machine learning, specifically the iterative sure independence screening (SIS) method, have enabled the analysis of datasets where the number of predictors is much larger than the number of observations. Using an implementation of the SIS algorithm (called EPISIS), we used exhaustive search of the genome-wide, SNP-SNP interactome to identify and prioritize SNPs for interaction analysis. We identified a significant SNP pair, rs1345203 and rs1213205, associated with temporal lobe volume. We further examined the full-brain, voxelwise effects of the interaction in the ADNI dataset and separately in an independent dataset of healthy twins (QTIM). We found that each additional loading in the epistatic effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both the ADNI and QTIM samples.

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Background The Australian National Hand Hygiene Initiative (NHHI) is a major patient safety programme co-ordinated by Hand Hygiene Australia (HHA) and funded by the Australian Commission for Safety and Quality in Health Care. The annual costs of running this programme need to be understood to know the cost-effectiveness of a decision to sustain it as part of health services. Aim To estimate the annual health services cost of running the NHHI; the set-up costs are excluded. Methods A health services perspective was adopted for the costing and collected data from the 50 largest public hospitals in Australia that implemented the initiative, covering all states and territories. The costs of HHA, the costs to the state-level infection-prevention groups, the costs incurred by each acute hospital, and the costs for additional alcohol-based hand rub are all included. Findings The programme cost AU$5.56 million each year (US$5.76, £3.63 million). Most of the cost is incurred at the hospital level (65%) and arose from the extra time taken for auditing hand hygiene compliance and doing education and training. On average, each infection control practitioner spent 5 h per week on the NHHI, and the running cost per annum to their hospital was approximately AU$120,000 in 2012 (US$124,000, £78,000). Conclusion Good estimates of the total costs of this programme are fundamental to understanding the cost-effectiveness of implementing the NHHI. This paper reports transparent costing methods, and the results include their uncertainty.

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IMPORTANCE Patients with chest pain represent a high health care burden, but it may be possible to identify a patient group with a low short-term risk of adverse cardiac events who are suitable for early discharge. OBJECTIVE To compare the effectiveness of a rapid diagnostic pathway with a standard-care diagnostic pathway for the assessment of patients with possible cardiac chest pain in a usual clinical practice setting. DESIGN, SETTING, AND PARTICIPANTS A single-center, randomized parallel-group trial with blinded outcome assessments was conducted in an academic general and tertiary hospital. Participants included adults with acute chest pain consistent with acute coronary syndrome for whom the attending physician planned further observation and troponin testing. Patient recruitment occurred from October 11, 2010, to July 4, 2012, with a 30-day follow-up. INTERVENTIONS An experimental pathway using an accelerated diagnostic protocol (Thrombolysis in Myocardial Infarction score, 0; electrocardiography; and 0- and 2-hour troponin tests) or a standard-care pathway (troponin test on arrival at hospital, prolonged observation, and a second troponin test 6-12 hours after onset of pain) serving as the control. MAIN OUTCOMES AND MEASURES Discharge from the hospital within 6 hours without a major adverse cardiac event occurring within 30 days. RESULTS Fifty-two of 270 patients in the experimental group were successfully discharged within 6 hours compared with 30 of 272 patients in the control group (19.3% vs 11.0%; odds ratio, 1.92; 95% CI, 1.18-3.13; P = .008). It required 20 hours to discharge the same proportion of patients from the control group as achieved in the experimental group within 6 hours. In the experimental group, 35 additional patients (12.9%) were classified as low risk but admitted to an inpatient ward for cardiac investigation. None of the 35 patients received a diagnosis of acute coronary syndrome after inpatient evaluation. CONCLUSIONS AND RELEVANCE Using the accelerated diagnostic protocol in the experimental pathway almost doubled the proportion of patients with chest pain discharged early. Clinicians could discharge approximately 1 of 5 patients with chest pain to outpatient follow-up monitoring in less than 6 hours. This diagnostic strategy could be easily replicated in other centers because no extra resources are required.

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Objective Risk scores and accelerated diagnostic protocols can identify chest pain patients with low risk of major adverse cardiac event who could be discharged early from the ED, saving time and costs. We aimed to derive and validate a chest pain score and accelerated diagnostic protocol (ADP) that could safely increase the proportion of patients suitable for early discharge. Methods Logistic regression identified statistical predictors for major adverse cardiac events in a derivation cohort. Statistical coefficients were converted to whole numbers to create a score. Clinician feedback was used to improve the clinical plausibility and the usability of the final score (Emergency Department Assessment of Chest pain Score [EDACS]). EDACS was combined with electrocardiogram results and troponin results at 0 and 2 h to develop an ADP (EDACS-ADP). The score and EDACS-ADP were validated and tested for reproducibility in separate cohorts of patients. Results In the derivation (n = 1974) and validation (n = 608) cohorts, the EDACS-ADP classified 42.2% (sensitivity 99.0%, specificity 49.9%) and 51.3% (sensitivity 100.0%, specificity 59.0%) as low risk of major adverse cardiac events, respectively. The intra-class correlation coefficient for categorisation of patients as low risk was 0.87. Conclusion The EDACS-ADP identified approximately half of the patients presenting to the ED with possible cardiac chest pain as having low risk of short-term major adverse cardiac events, with high sensitivity. This is a significant improvement on similar, previously reported protocols. The EDACS-ADP is reproducible and has the potential to make considerable cost reductions to health systems.

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In uplink orthogonal frequency division multiple access (OFDMA), large timing offsets (TO) and/or carrier frequency offsets (CFO) of other users with respect to a desired user can cause significant multiuser interference (MUI). In this letter, we analytically characterize the degradation in the average output signal-to-interference ratio (SIR) due to the combined effect of both TOs as well as CFOs in uplink OFDMA. Specifically, we derive closed-form expressions for the average SIR at the DFT output in the presence of large CFOs and TOs. The analyticalexpressions derived for the signal and various interference terms at the DFT output are used to devise an interference cancelling receiver to mitigate the effect of CFO/TO-induced interferences.

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Table beet production in the Lockyer Valley of south-eastern Queensland is known to be adversely affected by soilborne root disease from infection by Pythium spp. However, little is known regarding the species or genotypes that are the causal agents of both pre- and post-emergence damping off. Based on RFLP analysis with HhaI, HinfI and MboI of the PCR amplified ITS region DNA from soil and diseased plant samples, the majority of 130 Pythium isolates could be grouped into three genotypes, designated LVP A, LVP B and LVP C. These groups comprised 43, 41 and 7% of all isolates, respectively. Deoxyribonucleic acid sequence analysis of the ITS region indicated that LVP A was a strain of Pythium aphanidermatum, with greater than 99% similarity to the corresponding P. aphanidermatum sequences from the publicly accessible databases. The DNA sequences from LVP B and LVP C were most closely related to P. ultimum and P. dissotocum, respectively. Lower frequencies of other distinct isolates with unique RFLP patterns were also obtained with high levels of similarity (>97%) to P. heterothallicum, P. periplocum and genotypes of P. ultimum other than LVP B. Inoculation trials of 1- and 4-week-old beet seedlings indicated that compared with isolates of the LVP B genotype, a higher frequency of LVP A isolates caused disease. Isolates with the LVP A, LVP B and LVP C genotypes were highly sensitive to the fungicide Ridomil MZ, which suppressed radial growth on V8 agar between approximately four and thirty fold at 5 μg/mL metalaxyl and 40 μg/mL mancozeb, a concentration far lower than the recommended field application rate.

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Handwritten dedication: Robert Weltsch in herzlicher Gesinnung MB

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Spontaneous mutation: discovered in February 2001 as a superior plant growing among “Common” buffalo grass growing on the breeder’s property at Saltash in the Hunter Valley (NSW). The selected material has smaller (finer) leaves and showed better growth and colour than the parent variety with minimal inputs (water, fertiliser) under stressful climatic conditions. Subsequently, it also showed better leaf colour retention than the parent variety during winter. A vegetative plug taken from the original plant has now undergone four subsequent vegetative divisions to expand the original material for performance trials in NSW and Queensland without showing any discernible off types. Main selection criteria: winter colour retention, small leaves, low fertiliser requirement. Propagation: vegetative. Breeder: Brent Redman, Maitland North, NSW. PBR Certificate Number 2715, Application Number 2002/283, granted 18 March 2005.