The diagnostic accuracy of telegeriatrics for the diagnosis of dementia via video conferencing

Introduction The suitability of video conferencing (VC) technology for clinical purposes relevant to geriatric medicine is still being established. This project aimed to determine the validity of the diagnosis of dementia via VC. Methods This was a multisite, noninferiority, prospective cohort study. Patients, aged 50 years and older, referred by their primary care physician for cognitive assessment, were assessed at 4 memory disorder clinics. All patients were assessed independently by 2 specialist physicians. They were allocated one face-to-face (FTF) assessment (Reference standard – usual clinical practice) and an additional assessment (either usual FTF assessment or a VC assessment) on the same day. Each specialist physician had access to the patient chart and the results of a battery of standardized cognitive assessments administered FTF by the clinic nurse. Percentage agreement (P0) and the weighted kappa statistic with linear weight (Kw) were used to assess inter-rater reliability across the 2 study groups on the diagnosis of dementia (cognition normal, impaired, or demented). Results The 205 patients were allocated to group: Videoconference (n = 100) or Standard practice (n = 105); 106 were men. The average age was 76 (SD 9, 51–95) and the average Standardized Mini-Mental State Examination Score was 23.9 (SD 4.7, 9–30). Agreement for the Videoconference group (P0= 0.71; Kw = 0.52; P < .0001) and agreement for the Standard Practice group (P0= 0.70; Kw = 0.50; P < .0001) were both statistically significant (P < .05). The summary kappa statistic of 0.51 (P = .84) indicated that VC was not inferior to FTF assessment. Conclusions Previous studies have shown that preliminary standardized assessment tools can be reliably administered and scored via VC. This study focused on the geriatric assessment component of the interview (interpretation of standardized assessments, taking a history and formulating a diagnosis by medical specialist) and identified high levels of agreement for diagnosing dementia. A model of service incorporating either local or remote administered standardized assessments, and remote specialist assessment, is a reliable process for enabling the diagnosis of dementia for isolated older adults.

Controlled growth of carbon nanotubes for electronic and photovoltaic applications

Carbon nanotubes (CNTs), experimentally observed for the first time twenty years ago, have triggered an unprecedented research effort, on the account of their astonishing structural, mechanical and electronic properties. Unfortunately, the current inability in predicting the CNTs’ properties and the difficulty in controlling their position on a substrate are often limiting factors for the application of this material in actual devices. This research aims at the creation of specific methodologies for controlled synthesis of CNTs, leading to effectively employ them in various fields of electronics, e.g. photovoltaics. Focused Ion Beam (FIB) patterning of Si surfaces is here proposed as a means for ordering the assembly of vertical-aligned CNTs. With this technique, substrates with specific nano-structured morphologies have been prepared, enabling a high degree of control over CNTs’ position and size. On these nano-structured substrates, the growth of CNTs has been realized by chemical vapor deposition (CVD), i.e. thermal decomposition of hydrocarbon gases over a heated catalyst. The most common materials used as catalysts in CVD are transition metals like Fe and Ni; however, their presence in the CNT products often results in shortcomings for electronic applications, especially for those based on silicon, being the metallic impurities incompatible with very-large-scale integration (VLSI) technology. In the present work the role of Ge dots as an alternative catalysts for CNTs synthesis on Si substrates has been thoroughly assessed, finding a close connection between the catalytic activity of such material and the CVD conditions, which can affect both size and morphology of the dots. Successful CNT growths from Ge dots have been obtained by CVD at temperatures ranging from 750 to 1000°C, with mixtures of acetylene and hydrogen in an argon carrier gas. The morphology of the Si surface is observed to play a crucial role for the outcome of the CNT synthesis: natural (i.e. chemical etching) and artificial (i.e. FIB patterning, nanoindentation) means of altering this morphology in a controlled way have been then explored to optimize the CNTs yield. All the knowledge acquired in this study has been finally applied to synthesize CNTs on transparent conductive electrodes (indium-tin oxide, ITO, coated glasses), for the creation of a new class of anodes for organic photovoltaics. An accurate procedure has been established which guarantees a controlled inclusion of CNTs on ITO films, preserving their optical and electrical properties. By using this set of conditions, a CNTenhanced electrode has been built, contributing to improve the power conversion efficiency of polymeric solar cells.

Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.

Low temperature synthesis of carbon nanotubes on indium tin oxide electrodes for organic solar cells

The electrical performance of indium tin oxide (ITO) coated glass was improved by including a controlled layer of carbon nanotubes directly on top of the ITO film. Multi-wall carbon nanotubes (MWCNTs) were synthesized by chemical vapor deposition, using ultra-thin Fe layers as catalyst. The process parameters (temperature, gas flow and duration) were carefully refined to obtain the appropriate size and density of MWCNTs with a minimum decrease of the light harvesting in the cell. When used as anodes for organic solar cells based on poly(3-hexylthiophene) (P3HT) and phenyl-C61-butyric acid methyl ester (PCBM), the MWCNT-enhanced electrodes are found to improve the charge carrier extraction from the photoactive blend, thanks to the additional percolation paths provided by the CNTs. The work function of as-modified ITO surfaces was measured by the Kelvin probe method to be 4.95 eV, resulting in an improved matching to the highest occupied molecular orbital level of the P3HT. This is in turn expected to increase the hole transport and collection at the anode, contributing to the significant increase of current density and open circuit voltage observed in test cells created with such MWCNT-enhanced electrodes.

Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.

Development of a gas nanosensor node powered by solar cells

This work focuses on the development of a stand-alone gas nanosensor node, powered by solar energy to track concentration of polluted gases such as NO2, N2O, and NH3. Gas sensor networks have been widely developed over recent years, but the rise of nanotechnology is allowing the creation of a new range of gas sensors [1] with higher performance, smaller size and an inexpensive manufacturing process. This work has created a gas nanosensor node prototype to evaluate future field performance of this new generation of sensors. The sensor node has four main parts: (i) solar cells; (ii) control electronics; (iii) gas sensor and sensor board interface [2-4]; and (iv) data transmission. The station is remotely monitored through wired (ethernet cable) or wireless connection (radio transmitter) [5, 6] in order to evaluate, in real time, the performance of the solar cells and sensor node under different weather conditions. The energy source of the node is a module of polycrystalline silicon solar cells with 410cm2 of active surface. The prototype is equipped with a Resistance-To-Period circuit [2-4] to measure the wide range of resistances (KΩ to GΩ) from the sensor in a simple and accurate way. The system shows high performance on (i) managing the energy from the solar panel, (ii) powering the system load and (iii) recharging the battery. The results show that the prototype is suitable to work with any kind of resistive gas nanosensor and provide useful data for future nanosensor networks.

In the pursuit of effective affective computing : the relationship between features and registration

For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.

Coordinated tuning of DFIG-based wind turbines and batteries using bacteria foraging technique for maintaining constant grid power output

This paper proposes the use of battery energy storage (BES) system for the grid-connected doubly fed induction generator (DFIG). The BES would help in storing/releasing additional power in case of higher/lower wind speed to maintain constant grid power. The DC link capacitor is replaced with the BES system in a DFIG-based wind turbine to achieve the above-mentioned goal. The control scheme is modified and the co-ordinated tuning of the associated controllers to enhance the damping of the oscillatory modes is presented using bacterial foraging technique. The results from eigenvalue analysis and the time domain simulation studies are presented to elucidate the effectiveness of the BES systems in maintaining the grid stability under normal operation.

A portable approach for the surveillance of dengue virus-infected mosquitoes

Dengue virus is the most significant human viral pathogen spread by the bite of an infected mosquito. With no vaccine or antiviral therapy currently available, disease prevention relies largely on surveillance and mosquito control. Preventing the onset of dengue outbreaks and effective vector management would be considerably enhanced through surveillance of dengue virus prevalence in natural mosquito populations. However, current approaches to the identification of virus in field-caught mosquitoes require relatively slow and labor intensive techniques such as virus isolation or RT-PCR involving specialized facilities and personnel. A rapid and portable method for detecting dengue virus-infected mosquitoes is described. Using a hand held battery operated homogenizer and a dengue diagnostic rapid strip the viral protein NS1 was detected as a marker of dengue virus infection. This method could be performed in less than 30 min in the field, requiring no downstream processing, and is able to detect a single infected mosquito in a pool of at least 50 uninfected mosquitoes. The method described in this study allows rapid, real-time monitoring of dengue virus presence in mosquito populations and could be a useful addition to effective monitoring and vector control responses.

Pedigree-free animal models : the relatedness matrix reloaded

Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.

Teaching Teachers for the Future (TTF) project TPACK Survey : summary of the key findings

This paper presents a summary of the key findings of the TTF TPACK Survey developed and administered for the Teaching the Teachers for the Future (TTF) Project implemented in 2011. The TTF Project, funded by an Australian Government ICT Innovation Fund grant, involved all 39 Australian Higher Education Institutions which provide initial teacher education. TTF data collections were undertaken at the end of Semester 1 (T1) and at the end of Semester 2 (T2) in 2011. A total of 12881 participants completed the first survey (T1) and 5809 participants completed the second survey (T2). Groups of like-named items from the T1 survey were subject to a battery of complementary data analysis techniques. The psychometric properties of the four scales: Confidence - teacher items; Usefulness - teacher items; Confidence - student items; Usefulness- student items, were confirmed both at T1 and T2. Among the key findings summarised, at the national level, the scale: Confidence to use ICT as a teacher showed measurable growth across the whole scale from T1 to T2, and the scale: Confidence to facilitate student use of ICT also showed measurable growth across the whole scale from T1 to T2. Additional key TTF TPACK Survey findings are summarised.

Visual motion perception predicts driving hazard perception ability

PURPOSE: To examine the basis of previous findings of an association between indices of driving safety and visual motion sensitivity and to examine whether this association could be explained by low-level changes in visual function. METHODS: 36 visually normal participants (aged 19 – 80 years), completed a battery of standard vision tests including visual acuity, contrast sensitivity and automated visual fields. and two tests of motion perception including sensitivity for movement of a drifting Gabor stimulus, and sensitivity for displacement in a random-dot kinematogram (Dmin). Participants also completed a hazard perception test (HPT) which measured participants’ response times to hazards embedded in video recordings of real world driving which has been shown to be linked to crash risk. RESULTS: Dmin for the random-dot stimulus ranged from -0.88 to -0.12 log minutes of arc, and the minimum drift rate for the Gabor stimulus ranged from 0.01 to 0.35 cycles per second. Both measures of motion sensitivity significantly predicted response times on the HPT. In addition, while the relationship involving the HPT and motion sensitivity for the random-dot kinematogram was partially explained by the other visual function measures, the relationship with sensitivity for detection of the drifting Gabor stimulus remained significant even after controlling for these variables. CONCLUSION: These findings suggest that motion perception plays an important role in the visual perception of driving-relevant hazards independent of other areas of visual function and should be further explored as a predictive test of driving safety. Future research should explore the causes of reduced motion perception in order to develop better interventions to improve road safety.

Evaluation of screening tests for predicting older driver performance and safety assessed by an on-road test

A number of tests and test batteries are available for the prediction of older driver safety, but many of these have not been validated against standardized driving outcome measures. The aim of this study was to evaluate a series of previously described screening tests in terms of their ability to predict the potential for safe and unsafe driving. Participants included 79 community-dwelling older drivers (M=72.16 years, SD=5.46; range 65-88 years; 57 males and 22 females) who completed a previously validated multi-disciplinary driving assessment, a hazard perception test, a hazard change detection test and a battery of vision and cognitive tests. Participants also completed a standardized on-road driving assessment. The multi-disciplinary test battery had the highest predictive ability with a sensitivity of 80% and a specificity of 73%, followed by the hazard perception test which demonstrated a sensitivity of 75% and a specificity of 61%. These findings suggest that a relatively simple and practical battery of tests from a range of domains has the capacity to predict safe and unsafe driving in older adults.

The Multidimensional Loss Scale : validating a cross cultural instrument for measuring loss in Burmese refugees

The Multidimensional Loss Scale: Initial Development and Psychometric Evaluation The Multidimensional Loss Scale (MLS) represents the first instrument designed specifically to measure loss in refugee populations. Researchers developed initial items of the Multidimensional Loss Scale to assess Experience of Loss Events and Loss Distress in a culturally sensitive manner across multiple domains (social, material, intra-personal and cultural). A sample of 70 recently settled Burmese adult refugees completed a battery of questionnaires, including new scale items. Analyses explored the scale’s factor structure, internal consistency, convergent validity and divergent validity. Principal Axis Factoring supported a five-factor model: Loss of Symbolic Self, Loss of Interdependence, Loss of Home, Interpersonal Loss, and Loss of Intrapersonal Integrity. Chronbach’s Alphas indicated satisfactory internal consistency for Experience of Loss Events (.85) and Loss Distress (.92). Convergent and divergent validity of Loss Distress were supported by moderate correlations with interpersonal grief and trauma symptoms and weak correlations with depression and anxiety. The new scale was well received by people from refugee backgrounds and shows promise for application in future research and practice

Utility of the Mild Brain Injury Atypical Symptoms Scale to detect symptom exaggeration : an analogue simulation study

Brief self-report symptom checklists are often used to screen for postconcussional disorder (PCD) and posttraumatic stress disorder (PTSD) and are highly susceptible to symptom exaggeration. This study examined the utility of the five-item Mild Brain Injury Atypical Symptoms Scale (mBIAS) designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist–Civilian (PCL–C). Participants were 85 Australian undergraduate students who completed a battery of self-report measures under one of three experimental conditions: control (i.e., honest responding, n = 24), feign PCD (n = 29), and feign PTSD (n = 32). Measures were the mBIAS, NSI, PCL–C, Minnesota Multiphasic Personality Inventory–2, Restructured Form (MMPI–2–RF), and the Structured Inventory of Malingered Symptomatology (SIMS). Participants instructed to feign PTSD and PCD had significantly higher scores on the mBIAS, NSI, PCL–C, and MMPI–2–RF than did controls. Few differences were found between the feign PCD and feign PTSD groups, with the exception of scores on the NSI (feign PCD > feign PTSD) and PCL–C (feign PTSD > feign PCD). Optimal cutoff scores on the mBIAS of ≥8 and ≥6 were found to reflect “probable exaggeration” (sensitivity = .34; specificity = 1.0; positive predictive power, PPP = 1.0; negative predictive power, NPP = .74) and “possible exaggeration” (sensitivity = .72; specificity = .88; PPP = .76; NPP = .85), respectively. Findings provide preliminary support for the use of the mBIAS as a tool to detect symptom exaggeration when administering the NSI and PCL–C.