987 resultados para Gagliardi, Paolo, 1675-1742.


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In this work we used a 3D quantitative CT ultrasound imaging system to characterise polymer gel dosimeters. The system comprised of two identical 5 MHz 128 element phased-array ultrasound transducers co-axially aligned and submerged in water as a coupling agent. Rotational and translational movement of the gel dosimeter sample between the transducers were performed using a robotic arm. Ultrasound signals were generated and received using an Olympus Omniscan unit. Dose sensitivity of attenuation and time of flight ultrasonic parameters were assessed using this system.

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Ultrasound has been examined previously as an alternative readout method for irradiated polymer gel dosimeters, with authors reporting varying dose response to ultrasound transmission measurements. In this current work we extend previous work to measure the broadband ultrasound attenuation (BUA) response of irradiated PAGAT gel dosimeters, using a novel ultrasound computed tomography system.

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In this study x-ray CT has been used to produce a 3D image of an irradiated PAGAT gel sample, with noise-reduction achieved using the ‘zero-scan’ method. The gel was repeatedly CT scanned and a linear fit to the varying Hounsfield unit of each pixel in the 3D volume was evaluated across the repeated scans, allowing a zero-scan extrapolation of the image to be obtained. To minimise heating of the CT scanner’s x-ray tube, this study used a large slice thickness (1 cm), to provide image slices across the irradiated region of the gel, and a relatively small number of CT scans (63), to extrapolate the zero-scan image. The resulting set of transverse images shows reduced noise compared to images from the initial CT scan of the gel, without being degraded by the additional radiation dose delivered to the gel during the repeated scanning. The full, 3D image of the gel has a low spatial resolution in the longitudinal direction, due to the selected scan parameters. Nonetheless, important features of the dose distribution are apparent in the 3D x-ray CT scan of the gel. The results of this study demonstrate that the zero-scan extrapolation method can be applied to the reconstruction of multiple x-ray CT slices, to provide useful 2D and 3D images of irradiated dosimetry gels.

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Ab initio Density Functional Theory (DFT) calculations are performed to study the diffusion of atomic hydrogen on a Mg(0001) surface and their migration into the subsurface layers. A carbon atom located initially on a Mg(0001) surface can migrate into the sub-surface layer and occupy a fcc site, with charge transfer to the C atom from neighboring Mg atoms. The cluster of postively charged Mg atoms surrounding a sub-surface C is then shown to facilitate the dissociative chemisorption of molecular hydrogen on the Mg(0001) surface, and the surface migration and subsequent diffusion into the subsurface of atomic hydrogen. This helps rationalize the experimentally-observed improvement in absorption kinetics of H2 when graphite or single walled carbon nanotubes (SWCNT) are introduced into the Mg powder during ball milling.

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BACKGROUND: Public hospital EDs in Australia have become increasingly congested because of increasing demand and access block. Six per cent of ED patients attend private hospital EDs whereas 45% of the population hold private health insurance. OBJECTIVES: This study describes the patients attending a small selection of four private hospital EDs in Queensland and Victoria, and tests the feasibility of a private ED database. METHODS: De-identified routinely collected patient data were provided by the four participating private hospital and amalgamated into a single data set. RESULT: The mean age of private ED patients was 52 years. Males outnumbered females in all age groups except > 80 years. Attendance was higher on weekends and Mondays, and between 08.00 and 20.00 h. There were 6.6% of the patients triaged as categories 1 and 2, and 60% were categories 4 or 5. There were 36.4% that required hospital admission. Also, 96% of the patients had some kind of insurance. Furthermore, 72% were self-referred and 12% were referred by private medical practitioners. Approximately 25% arrived by ambulance. There were 69% that completed their ED treatment within 4 h. CONCLUSION: This study is the first public description of patients attending private EDs in Australia. Private EDs have a significant role to play in acute medical care and in providing access to private hospitals which could alleviate pressure on public EDs. This study demonstrates the need for consolidated data based on a consistent data set and data dictionary to enable system-wide analysis, benchmarking and evaluation

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While forensic psychology is commonly associated with the criminal and family law domains, its ambit to offer skills and knowledge at the legal interface also makes it particularly suited to the civil law domain. At this time, civil law is arguably the least represented legislative area in terms of psychological research and professional commentary. However, it is also a broad area, with its very breadth providing scope for research consideration, as urged by Greene. The purposes of this article are (1) to review the broad role of the psychologist in the conduct of civil litigation matters in Australia, (2) to assist the novice to the area by indicating a non-exhaustive list of potentially ambiguous terms and concepts common to the conduct of professional practice, and; (3) to highlight, as an example, one area of practice not only where legal direction demands professional pragmatism but also where opportunity arises for psychological research to vitally address a major social issue.

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Objective Describe the characteristics of patients presenting to Emergency Departments (EDs) within Queensland, Australia with injuries due to assault with a glass implement (‘glassing’) and to set this within the broader context of presentations due to alcohol-related violence. Methods Analysis of prospectively collected ED injury surveillance data collated by the Queensland Injury Surveillance Unit (QISU) between 1999 and 2011. Cases of injury due to alcohol-related violence were identified and analysed using coded fields supplemented with qualitative data contained within the injury description text. Descriptive statistics were used to assess the characteristics of injury presentations due to alcohol-related violence. Violence included interpersonal violence and aggression (verbal aggression and object violence). Results A total of 4629 cases were studied. The study population was predominantly male (72%) and aged 18 to 24 (36%), with males in this age group comprising more than a quarter of the study population (28%). Nine percent of alcohol-related assault injuries were a consequence of ‘glassing’. The home was the most common location for alcohol-related violence (31%) and alcohol-related ‘glassings’ (33%). Overall, the most common glass object involved was a bottle (75%), however, within licensed venues an even mix of a drinking glass (44%) and glass bottle (45%) were identified. Conclusions Contrary to public perception generated by media, ‘glassing’ incidents, particularly at licensed venues, constitute a relatively small proportion of all alcohol-related violence. The current study highlights the predominance of young men injured following alcohol-related violence, demonstrating a key focus area within the population for aiming prevention strategies.

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Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.

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Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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This paper introduces a parallel implementation of an agent-based model applied to electricity distribution grids. A fine-grained shared memory parallel implementation is presented, detailing the way the agents are grouped and executed on a multi-threaded machine, as well as the way the model is built (in a composable manner) which is an aid to the parallelisation. Current results show a medium level speedup of 2.6, but improvements are expected by incor-porating newer distributed or parallel ABM schedulers into this implementa-tion. While domain-specific, this parallel algorithm can be applied to similarly structured ABMs (directed acyclic graphs).

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Many factors are identified as contributing to the high demand for emergency department (ED) care. Similarly, there have been many initiatives taken to minimise the impact that is placed on EDs. Many of these, however, do not consider the patient's opinions and motivations. The aim of this cross-sectional study was to understand patients’ perspectives and reasons behind their decision to present to EDs. 911 surveys were collected from patients presenting to eight QLD EDs in 2011. Based on the Principal Component Analysis technique, a six-item scale entitled "Best services at emergency departments" was extracted (α = 0.729) measuring patients' opinions and perspectives. Further, the independent t-tests were conducted between various groups of ED users. The results suggest that multiple users more likely viewed EDs as the best place for their conditions than the first-time users (Median 10.73 v 11.56, p<0.001). Moreover, patients who made the decision to present by themselves had a more favourable perception of the ED services than those for whom the decision was made or others were involved (Median 11.38 v 10.80, p=0.003). Method of arrival did not affect the respondents’ perception of ED (11.13 v 11.00, p=0.65). The results of this research indicate that patients’ perception of ED as the best and most appropriate place for attention to their medical conditions plays an important role in their decision to present and keep returning to ED. Understanding patients’ reasons and decisions enhances the success of planning and implementing alternative services to manage the demand for ED services.

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Chemical vapor deposition (CVD) is widely utilized to synthesize graphene with controlled properties for many applications, especially when continuous films over large areas are required. Although hydrocarbons such as methane are quite efficient precursors for CVD at high temperature (∼1000 °C), finding less explosive and safer carbon sources is considered beneficial for the transition to large-scale production. In this work, we investigated the CVD growth of graphene using ethanol, which is a harmless and readily processable carbon feedstock that is expected to provide favorable kinetics. We tested a wide range of synthesis conditions (i.e., temperature, time, gas ratios), and on the basis of systematic analysis by Raman spectroscopy, we identified the optimal parameters for producing highly crystalline graphene with different numbers of layers. Our results demonstrate the importance of high temperature (1070 °C) for ethanol CVD and emphasize the significant effects that hydrogen and water vapor, coming from the thermal decomposition of ethanol, have on the crystal quality of the synthesized graphene.

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The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

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The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

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In the field of rolling element bearing diagnostics, envelope analysis has gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of this technique has been extended to cases in which small speed fluctuations occur, maintaining high effectiveness and efficiency. In order to make this algorithm suitable to all industrial applications, the constraint on speed has to be removed completely. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This chapter presents a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.