956 resultados para Single pollen identification


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This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

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A new approach is proposed for obtaining a non-linear area-based equivalent model of power systems to express the inter-area oscillations using synchronised phasor measurements. The generators that remain coherent for inter-area disturbances over a wide range of operating conditions define the areas, and the reduced model is obtained by representing each area by an equivalent machine. The parameters of the reduced system are identified by processing the obtained measurements, and a non-linear Kalman estimator is then designed for the estimation of equivalent area angles and frequencies. The simulation of the approach on a two-area system shows substantial reduction of non-inter-area modes in the estimated angles. The proposed methods are also applied to a ten-machine system to illustrate the feasibility of the approach on larger and meshed networks.

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Police reported crash data are the primary source of crash information in most jurisdictions. However, the definition of serious injury within police-reported data is not consistent across jurisdictions and may not be accurate. With the Australian National Road Safety Strategy targeting the reduction of serious injuries, there is a greater need to assess the accuracy of the methods used to identify these injuries. A possible source of more accurate information relating to injury severity is hospital data. While other studies have compared police and hospital data to highlight the under-reporting in police-reported data, little attention has been given to the accuracy of the methods used by police to identify serious injuries. The current study aimed to assess how accurate the identification of serious injuries is in police-reported crash data, by comparing the profiles of transport-related injuries in the Queensland Road Crash Database with an aligned sample of data from the Queensland Hospital Admitted Patients Data Collection. Results showed that, while a similar number of traffic injuries were recorded in both data sets, the profile of these injuries was different based on gender, age, location, and road user. The results suggest that the ‘hospitalisation’ severity category used by police may not reflect true hospitalisations in all cases. Further, it highlights the wide variety of severity levels within hospitalised cases that are not captured by the current police-reported definitions. While a data linkage study is required to confirm these results, they highlight that a reliance on police-reported serious traffic injury data alone could result in inaccurate estimates of the impact and cost of crashes and lead to a misallocation of valuable resources.

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A new approach for recognizing the iris of the human eye is presented. Zero-crossings of the wavelet transform at various resolution levels are calculated over concentric circles on the iris, and the resulting one-dimensional (1-D) signals are compared with model features using different dissimilarity functions.

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The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research examining effects of uncertainties of generic WSN platform and verifying the capability of SHM-oriented WSNs, particularly on demanding SHM applications like modal analysis and damage identification of real civil structures. This article first reviews the major technical uncertainties of both generic and SHM-oriented WSN platforms and efforts of SHM research community to cope with them. Then, effects of the most inherent WSN uncertainty on the first level of a common Output-only Modal-based Damage Identification (OMDI) approach are intensively investigated. Experimental accelerations collected by a wired sensory system on a benchmark civil structure are initially used as clean data before being contaminated with different levels of data pollutants to simulate practical uncertainties in both WSN platforms. Statistical analyses are comprehensively employed in order to uncover the distribution pattern of the uncertainty influence on the OMDI approach. The result of this research shows that uncertainties of generic WSNs can cause serious impact for level 1 OMDI methods utilizing mode shapes. It also proves that SHM-WSN can substantially lessen the impact and obtain truly structural information without having used costly computation solutions.

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A security system based on the recognition of the iris of human eyes using the wavelet transform is presented. The zero-crossings of the wavelet transform are used to extract the unique features obtained from the grey-level profiles of the iris. The recognition process is performed in two stages. The first stage consists of building a one-dimensional representation of the grey-level profiles of the iris, followed by obtaining the wavelet transform zerocrossings of the resulting representation. The second stage is the matching procedure for iris recognition. The proposed approach uses only a few selected intermediate resolution levels for matching, thus making it computationally efficient as well as less sensitive to noise and quantisation errors. A normalisation process is implemented to compensate for size variations due to the possible changes in the camera-to-face distance. The technique has been tested on real images in both noise-free and noisy conditions. The technique is being investigated for real-time implementation, as a stand-alone system, for access control to high-security areas.

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Finite element frame analysis programs targeted for design office application necessitate algorithms which can deliver reliable numerical convergence in a practical timeframe with comparable degrees of accuracy, and a highly desirable attribute is the use of a single element per member to reduce computational storage, as well as data preparation and the interpretation of the results. To this end, a higher-order finite element method including geometric non-linearity is addressed in the paper for the analysis of elastic frames for which a single element is used to model each member. The geometric non-linearity in the structure is handled using an updated Lagrangian formulation, which takes the effects of the large translations and rotations that occur at the joints into consideration by accumulating their nodal coordinates. Rigid body movements are eliminated from the local member load-displacement relationship for which the total secant stiffness is formulated for evaluating the large member deformations of an element. The influences of the axial force on the member stiffness and the changes in the member chord length are taken into account using a modified bowing function which is formulated in the total secant stiffness relationship, for which the coupling of the axial strain and flexural bowing is included. The accuracy and efficiency of the technique is verified by comparisons with a number of plane and spatial structures, whose structural response has been reported in independent studies.

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AIMS: To investigate the evolutionary origins of Australian healthcare-associated (HCA) methicillin-resistant Staphylococcus aureus (MRSA) strains from a panel of historical isolates typed using current genotyping techniques. METHODS: Nineteen MRSA isolates from 1965 to 1981 were examined and antibiotic susceptibility profiles determined. Genetic characterisation included real-time (RT) polymerase chain reaction (PCR) assays to identify single nucleotide polymorhpism (SNP) clonal complexes (SNP CC) and sequence type (SNP ST), multi locus sequence typing (MLST) and staphylococcal chromosomal cassette mec typing. RESULTS: All SNP CC30 isolates belonged to a novel sequence type, ST2249. All SNP CC239 isolates were confirmed as ST239-MRSA-III, except for a new single locus variant of ST239, ST2275. A further new type, ST2276, was identified. CONCLUSIONS: The earliest MRSA examined from 1965 was confirmed as ST250-MRSA-I, consistent with archaic European types. Identification of ST1-MRSA-IV in 1981 is the earliest appearance of this clinically important lineage which manifested in Australia and the United States in the 1990s. A previously unknown multi-resistant clone, ST2249-MRSA-III, was identified from 1973. Gentamicin resistance first appeared in this novel strain from 1976 and not ST239 as previously suspected. Thus, ST2249 was present in the earliest phase of the HCA MRSA epidemic in eastern Australia and was perhaps related to the emergence of the globally epidemic strain ST239.

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The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.

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Objectives Current evidence to support non-medical prescribing is predominantly qualitative, with little evaluation of accuracy, safety and appropriateness. Our aim was to evaluate a new model of service for the Australia healthcare system, of inpatient medication prescribing by a pharmacist in an elective surgery preadmission clinic (PAC) against usual care, using an endorsed performance framework. Design Single centre, randomised controlled, two-arm trial. Setting Elective surgery PAC in a Brisbane-based tertiary hospital. Participants 400 adults scheduled for elective surgery were randomised to intervention or control. Intervention A pharmacist generated the inpatient medication chart to reflect the patient's regular medication, made a plan for medication perioperatively and prescribed venous thromboembolism (VTE) prophylaxis. In the control arm, the medication chart was generated by the Resident Medical Officers. Outcome measures Primary outcome was frequency of omissions and prescribing errors when compared against the medication history. The clinical significance of omissions was also analysed. Secondary outcome was appropriateness of VTE prophylaxis prescribing. Results There were significantly less unintended omissions of medications: 11 of 887 (1.2%) intervention orders compared with 383 of 1217 (31.5%) control (p<0.001). There were significantly less prescribing errors involving selection of drug, dose or frequency: 2 in 857 (0.2%) intervention orders compared with 51 in 807 (6.3%) control (p<0.001). Orders with at least one component of the prescription missing, incorrect or unclear occurred in 208 of 904 (23%) intervention orders and 445 of 1034 (43%) controls (p<0.001). VTE prophylaxis on admission to the ward was appropriate in 93% of intervention patients and 90% controls (p=0.29). Conclusions Medication charts in the intervention arm contained fewer clinically significant omissions, and prescribing errors, when compared with controls. There was no difference in appropriateness of VTE prophylaxis on admission between the two groups.

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Introduction The culture in many team sports involves consumption of large amounts of alcohol after training/competition. The effect of such a practice on recovery processes underlying protein turnover in human skeletal muscle are unknown. We determined the effect of alcohol intake on rates of myofibrillar protein synthesis (MPS) following strenuous exercise with carbohydrate (CHO) or protein ingestion. Methods In a randomized cross-over design, 8 physically active males completed three experimental trials comprising resistance exercise (8×5 reps leg extension, 80% 1 repetition maximum) followed by continuous (30 min, 63% peak power output (PPO)) and high intensity interval (10×30 s, 110% PPO) cycling. Immediately, and 4 h post-exercise, subjects consumed either 500 mL of whey protein (25 g; PRO), alcohol (1.5 g·kg body mass−1, 12±2 standard drinks) co-ingested with protein (ALC-PRO), or an energy-matched quantity of carbohydrate also with alcohol (25 g maltodextrin; ALC-CHO). Subjects also consumed a CHO meal (1.5 g CHO·kg body mass−1) 2 h post-exercise. Muscle biopsies were taken at rest, 2 and 8 h post-exercise. Results Blood alcohol concentration was elevated above baseline with ALC-CHO and ALC-PRO throughout recovery (P<0.05). Phosphorylation of mTORSer2448 2 h after exercise was higher with PRO compared to ALC-PRO and ALC-CHO (P<0.05), while p70S6K phosphorylation was higher 2 h post-exercise with ALC-PRO and PRO compared to ALC-CHO (P<0.05). Rates of MPS increased above rest for all conditions (~29–109%, P<0.05). However, compared to PRO, there was a hierarchical reduction in MPS with ALC-PRO (24%, P<0.05) and with ALC-CHO (37%, P<0.05). Conclusion We provide novel data demonstrating that alcohol consumption reduces rates of MPS following a bout of concurrent exercise, even when co-ingested with protein. We conclude that alcohol ingestion suppresses the anabolic response in skeletal muscle and may therefore impair recovery and adaptation to training and/or subsequent performance.

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Electrocatalytic processes will undoubtedly be at the heart of energising future transportation and technology with the added importance of being able to create the necessary fuels required to do so in an environmentally friendly and cost effective manner. For this to be successful two almost mutually exclusive surface properties need to be reconciled, namely producing highly active/reactive surface sites that exhibit long term stability. This article reviews the various approaches which have been undertaken to study the elusive nature of these active sites on metal surfaces which are considered as adatoms or clusters of adatoms with low coordination number. This includes the pioneering studies at extended well defined stepped single crystal surfaces using cyclic voltammetry up to the highly sophisticated in situ electrochemical imaging techniques used to study chemically synthesised nanomaterials. By combining the information attained from single crystal surfaces, individual nanoparticles of defined size and shape, density functional theory calculations and new concepts such as mesoporous multimetallic thin films and single atom electrocatalysts new insights into the design and fabrication of materials with highly active but stable active sites can be achieved. The area of electrocatalysis is therefore not only a fascinating and exciting field in terms of realistic technological and economical benefits but also from the fundamental understanding that can be acquired by studying such an array of interesting materials.

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The molecular mechanisms involved in non‑small cell lung cancer tumourigenesis are largely unknown; however, recent studies have suggested that long non-coding RNAs (lncRNAs) are likely to play a role. In this study, we used public databases to identify an mRNA-like, candidate long non-coding RNA, GHSROS (GHSR opposite strand), transcribed from the antisense strand of the ghrelin receptor gene, growth hormone secretagogue receptor (GHSR). Quantitative real-time RT-PCR revealed higher expression of GHSROS in lung cancer tissue compared to adjacent, non-tumour lung tissue. In common with many long non-coding RNAs, GHSROS is 5' capped and 3' polyadenylated (mRNA-like), lacks an extensive open reading frame and harbours a transposable element. Engineered overexpression of GHSROS stimulated cell migration in the A549 and NCI-H1299 non-small cell lung cancer cell lines, but suppressed cell migration in the Beas-2B normal lung-derived bronchoepithelial cell line. This suggests that GHSROS function may be dependent on the oncogenic context. The identification of GHSROS, which is expressed in lung cancer and stimulates cell migration in lung cancer cell lines, contributes to the growing number of non-coding RNAs that play a role in the regulation of tumourigenesis and metastatic cancer progression.

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The recently identified can didate gene, HLA-H, for haemochromatosis (HH) by Feder et al. generated considerable scientific interest coupled with a degree of uncertainty about the likely involvement of this gene in this common iron metabolism disorder, Feder et al. found a single point mutation resulting in an amino acid substitution (C282Y) that was homozygous in 148 (83%) of their patients, heterozygous in 9 patients (5%) but completely absent in 21 patients (12%). They proposed that the lack of a causative mutation in HLA-H in 12% of their patients was because these cases were not linked to chromosome 6p. A significant weakness in this argument is that all familial studies of the disorder so far have concluded that HH is due to a single major HLA-linked gene5-7. The ultimate test for a candidate gene is the clear segregation of a mutation with the disorder in all patients. Thus, some of the uncertainty surrounding the role of HLA-H in HH may be resolved by the identification of complete concordance of the C282Y mutation (or some other mutation) in HLA H with disease status in HH families. One potential problem in the design of such an experimental analysis is that a number of studies have shown the presence of a predominant ancestral haplotype in all HH populations examined: Australian, French, Italian, UK and US Thus in the analysis of a putative causative mutation, it is important to include families with...