Characteristics of culturally and linguistically diverse mental health clients

The present study examined Queensland Transcultural Mental Health Centre (QTMHC) client characteristics in order to provide a better understanding for development of future health service delivery models. Archived data that was collected for 1499 clients over two years period (2007-2009) was analysed using descriptive statistics and Chi squares. The results indicated that clients were referred from a range of sources and were generally adults. There were more women than men, who sought services. At least half of the clients had language barriers and relied on bilingual workers. Most frequently expressed mental health issues were mood disorder symptoms, followed by symptoms of schizophrenia and psychosis and anxiety. Acculturation strains and stressors were described as the most common psychosocial issues. Mental health and psychosocial issues differed for age, gender and world regions from which the CALD clients originated. The findings provided an understanding of clients who seek services at QTMHC. Various ways in which transcultural services and data bases can be further improved are discussed.

A lightweight biometric signature scheme for user authentication over networks

We introduce a lightweight biometric solution for user authentication over networks using online handwritten signatures. The algorithm proposed is based on a modified Hausdorff distance and has favorable characteristics such as low computational cost and minimal training requirements. Furthermore, we investigate an information theoretic model for capacity and performance analysis for biometric authentication which brings additional theoretical insights to the problem. A fully functional proof-of-concept prototype that relies on commonly available off-the-shelf hardware is developed as a client-server system that supports Web services. Initial experimental results show that the algorithm performs well despite its low computational requirements and is resilient against over-the-shoulder attacks.

Effect of family relatedness on characteristics of estimated IBD probabilities in relation to precision of QTL estimates

Background: A random QTL effects model uses a function of probabilities that two alleles in the same or in different animals at a particular genomic position are identical by descent (IBD). Estimates of such IBD probabilities and therefore, modeling and estimating QTL variances, depend on marker polymorphism, strength of linkage and linkage disequilibrium of markers and QTL, and the relatedness of animals in the pedigree. The effect of relatedness of animals in a pedigree on IBD probabilities and their characteristics was examined in a simulation study. Results: The study based on nine multi-generational family structures, similar to a pedigree structure of a real dairy population, distinguished by an increased level of inbreeding from zero to 28 % across the studied population. Highest inbreeding level in the pedigree, connected with highest relatedness, was accompanied by highest IBD probabilities of two alleles at the same locus, and by lower relative variation coefficients. Profiles of correlation coefficients of IBD probabilities along the marked chromosomal segment with those at the true QTL position were steepest when the inbreeding coefficient in the pedigree was highest. Precision of estimated QTL location increased with increasing inbreeding and pedigree relatedness. A method to assess the optimum level of inbreeding for QTL detection is proposed, depending on population parameters. Conclusions: An increased overall relationship in a QTL mapping design has positive effects on precision of QTL position estimates. But the relationship of inbreeding level and the capacity for QTL detection depending on the recombination rate of QTL and adjacent informative marker is not linear. © 2010 Freyer et al., licensee BioMed Central Ltd.

A high frequency current source converter with adjustable magnitude to drive high power piezoelectric transducers

A general electrical model of a piezoelectric transducer for ultrasound applications consists of a capacitor in parallel with RLC legs. A high power voltage source converter can however generate significant voltage stress across the transducer that creates high leakage currents. One solution is to reduce the voltage stress across the piezoelectric transducer by using an LC filter, however a main drawback is changing the piezoelectric resonant frequency and its characteristics. Thereby it reduces the efficiency of energy conversion through the transducer. This paper proposes that a high frequency current source converter is a suitable topology to drive high power piezoelectric transducers efficiently.

Ventilation distribution in rats : part 2 – a comparison of electrical impedance tomography and hyperpolarised helium magnetic resonance imaging

Background: Hyperpolarised helium MRI (He3 MRI) is a new technique that enables imaging of the air distribution within the lungs. This allows accurate determination of the ventilation distribution in vivo. The technique has the disadvantages of requiring an expensive helium isotope, complex apparatus and moving the patient to a compatible MRI scanner. Electrical impedance tomography (EIT) a non-invasive bedside technique that allows constant monitoring of lung impedance, which is dependent on changes in air space capacity in the lung. We have used He3MRI measurements of ventilation distribution as the gold standard for assessment of EIT. Methods: Seven rats were ventilated in supine, prone, left and right lateral position with 70% helium/30% oxygen for EIT measurements and pure helium for He3 MRI. The same ventilator and settings were used for both measurements. Image dimensions, geometric centre and global in homogeneity index were calculated. Results: EIT images were smaller and of lower resolution and contained less anatomical detail than those from He3 MRI. However, both methods could measure positional induced changes in lung ventilation, as assessed by the geometric centre. The global in homogeneity index were comparable between the techniques. Conclusion: EIT is a suitable technique for monitoring ventilation distribution and inhomgeneity as assessed by comparison with He3 MRI.

Saturated core high-temperature superconducting fault current limiters as an alternative to conventional series reactors in a distribution grid

Series reactors are used in distribution grids to reduce the short-circuit fault level. Some of the disadvantages of the application of these devices are the voltage drop produced across the reactor and the steep front rise of the transient recovery voltage (TRV), which generally exceeds the rating of the associated circuit breaker. Simulations were performed to compare the characteristics of a saturated core High-Temperature Superconducting Fault Current Limiter (HTS FCL) and a series reactor. The design of the HTS FCL was optimized using the evolutionary algorithm. The resulting Pareto frontier curve of optimum solution is presented in this paper. The results show that the steady-state impedance of an HTS FCL is significantly lower than that of a series reactor for the same level of fault current limiting. Tests performed on a prototype 11 kV HTS FCL confirm the theoretical results. The respective transient recovery voltages (TRV) of the HTS FCL and an air core reactor of comparable fault current limiting capability are also determined. The results show that the saturated core HTS FCL has a significantly lower effect on the rate of rise of the circuit breaker TRV as compared to the air core reactor. The simulations results are validated with shortcircuit test results.

Semantic labelling for document feature patterns using ontological subjects

Finding and labelling semantic features patterns of documents in a large, spatial corpus is a challenging problem. Text documents have characteristics that make semantic labelling difficult; the rapidly increasing volume of online documents makes a bottleneck in finding meaningful textual patterns. Aiming to deal with these issues, we propose an unsupervised documnent labelling approach based on semantic content and feature patterns. A world ontology with extensive topic coverage is exploited to supply controlled, structured subjects for labelling. An algorithm is also introduced to reduce dimensionality based on the study of ontological structure. The proposed approach was promisingly evaluated by compared with typical machine learning methods including SVMs, Rocchio, and kNN.

Visualization of thermal characteristics around the absorber tube of a standard parabolic trough thermal collector by 3D simulation

Three dimensional conjugate heat transfer simulation of a standard parabolic trough thermal collector receiver is performed numerically in order to visualize and analyze the surface thermal characteristics. The computational model is developed in Ansys Fluent environment based on some simplified assumptions. Three test conditions are selected from the existing literature to verify the numerical model directly, and reasonably good agreement between the model and the test results confirms the reliability of the simulation. Solar radiation flux profile around the tube is also approximated from the literature. An in house macro is written to read the input solar flux as a heat flux wall boundary condition for the tube wall. The numerical results show that there is an abrupt variation in the resultant heat flux along the circumference of the receiver. Consequently, the temperature varies throughout the tube surface. The lower half of the horizontal receiver enjoys the maximum solar flux, and therefore, experiences the maximum temperature rise compared to the upper part with almost leveled temperature. Reasonable attributions and suggestions are made on this particular type of conjugate thermal system. The knowledge that gained so far from this study will be used to further the analysis and to design an efficient concentrator photovoltaic collector in near future.

Integration of opinion into customer analysis model

As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.

Hot topic detection in news blogs from the perspective of W2T

News blog hot topics are important for the information recommendation service and marketing. However, information overload and personalized management make the information arrangement more difficult. Moreover, what influences the formation and development of blog hot topics is seldom paid attention to. In order to correctly detect news blog hot topics, the paper first analyzes the development of topics in a new perspective based on W2T (Wisdom Web of Things) methodology. Namely, the characteristics of blog users, context of topic propagation and information granularity are unified to analyze the related problems. Some factors such as the user behavior pattern, network opinion and opinion leader are subsequently identified to be important for the development of topics. Then the topic model based on the view of event reports is constructed. At last, hot topics are identified by the duration, topic novelty, degree of topic growth and degree of user attention. The experimental results show that the proposed method is feasible and effective.

Dynamic performance characteristics of an innovative Hybrid Composite Floor Plate System under human-induced loads

This study explored the dynamic performance of an innovative Hybrid Composite Floor Plate System (HCFPS), composed of Polyurethane (PU) core, outer layers of Glass–fibre Reinforced Cement (GRC) and steel laminates at tensile regions, using experimental testing and Finite Element (FE) modelling. Experimental testing included heel impact and walking tests for 3200 mm span HCFPS panels. FE models of the HCFPS were developed using the FE program ABAQUS and validated with experimental results. HCFPS is a light-weight high frequency floor system with excellent damping ratio of 5% (bare floor) due to the central PU core. Parametric studies were conducted using the validated FE models to investigate the dynamic response of the HCFPS and to identify characteristics that influence acceleration response under human induced vibration in service. This vibration performance was compared with recommended acceptable perceptibility limits. The findings of this study show that HCFPS can be used in residential and office buildings as a light-weight floor system, which does not exceed the perceptible thresholds due to human induced vibrations.

Physical characteristics of the indoor environment that affect health and wellbeing in healthcare facilities : a review

Understanding the physical characteristics of the indoor environment that affect human health and wellbeing is the key requirement underpinning the beneficial design of a healthcare facility (HCF). We reviewed and summarised physical factors of the indoor environment reported to affect human health and wellbeing in HCFs. Research materials included articles identified in a Pubmed search, guidelines, books, reports and monographs, as well as the bibliographies of review articles in the area studied. Of these, 209 publications were selected for this review. According to the literature, there is evidence that the following physical factors of the indoor environment affect the health and wellbeing of human beings in an HCF: safety, ventilation and HVAC systems, thermal environment, acoustic environment, interior layout and room type, windows (including daylight and views), nature and gardens, lighting, colour, floor covering, furniture and its placement, ergonomics, wayfinding, artworks and music. Some of these, in themselves, directly promote or hinder health and wellbeing, but the physical factors may also have numerous indirect impacts by influencing the behaviour, actions, and interactions of patients, their families and the staff members. The findings of this research enable a good understanding of the different physical factors of the indoor environment on health and wellbeing and provide a practical resource for those responsible for the design and operate the facilities as well as researchers investigating these factors. However, more studies are needed in order to inform the design of optimally beneficial indoor environments in HCFs for all user groups.

Engine performance characteristics for biodiesels of different degrees of saturation and carbon chain lengths

This experimental study examines the effect on performance and emission outputs of a compression ignition engine operating on biodiesels of varying carbon chain length and the degree of unsaturation. A well-instrumented, heavy-duty, multi-cylinder, common-rail, turbo-charged diesel engine was used to ensure that the results contribute in a realistic way to the ongoing debate about the impact of biofuels. Comparative measurements are reported for engine performance as well as the emissions of NOx, particle number and size distribution, and the concentration of the reactive oxygen species (which provide a measure of the toxicity of emitted particles). It is shown that the biodiesels used in this study produce lower mean effective pressure, somewhat proportionally with their lower calorific values; however, the molecular structure has been shown to have little impact on the performance of the engine. The peak in-cylinder pressure is lower for the biodiesels that produce a smaller number of emitted particles, compared to fossil diesel, but the concentration of the reactive oxygen species is significantly higher because of oxygen in the fuels. The differences in the physicochemical properties amongst the biofuels and the fossil diesel significantly affect the engine combustion and emission characteristics. Saturated short chain length fatty acid methyl esters are found to enhance combustion efficiency, reduce NOx and particle number concentration, but results in high levels of fuel consumption.

Regression and hypothesis tests for multivariate GNSS state time series

A satellite based observation system can continuously or repeatedly generate a user state vector time series that may contain useful information. One typical example is the collection of International GNSS Services (IGS) station daily and weekly combined solutions. Another example is the epoch-by-epoch kinematic position time series of a receiver derived by a GPS real time kinematic (RTK) technique. Although some multivariate analysis techniques have been adopted to assess the noise characteristics of multivariate state time series, statistic testings are limited to univariate time series. After review of frequently used hypotheses test statistics in univariate analysis of GNSS state time series, the paper presents a number of T-squared multivariate analysis statistics for use in the analysis of multivariate GNSS state time series. These T-squared test statistics have taken the correlation between coordinate components into account, which is neglected in univariate analysis. Numerical analysis was conducted with the multi-year time series of an IGS station to schematically demonstrate the results from the multivariate hypothesis testing in comparison with the univariate hypothesis testing results. The results have demonstrated that, in general, the testing for multivariate mean shifts and outliers tends to reject less data samples than the testing for univariate mean shifts and outliers under the same confidence level. It is noted that neither univariate nor multivariate data analysis methods are intended to replace physical analysis. Instead, these should be treated as complementary statistical methods for a prior or posteriori investigations. Physical analysis is necessary subsequently to refine and interpret the results.

Improving the hydrogen gas sensing performance of Pt/MoO3 nanoplatelets using a nano thick layer of La2O3

In this paper, we present how a thin RF sputtered layer of lanthanum oxide (La2O3) can alter electrical and improve hydrogen gas sensing characteristics of Pt/molybdenum oxide (MoO3) nanostructures Schottky diodes. We derived the barrier height, ideality factor and dielectric constant from the measured I–V characteristics at operating temperatures in the range of 25–300 ◦C. The dynamic response, response and recovery times were obtained upon exposure to hydrogen gas at different concentrations. Analysis of the results indicated a substantial improvement to the voltage shift sensitivity of the sensors incorporating the La2O3 layer. We associate this enhancement to the formation of numerous trap states due to the presence of the La2O3 thin film on the MoO3 nanoplatelets. These trap states increase the intensity of the dipolar charges at the metal–semiconductor interface, which induce greater bending of the energy bands. However, results also indicate that the presence of La2O3 trap states also increases response and recover times as electrons trapping and de-trapping processes occur before they can pass through this thin dielectric layer.