Is the clinical Queensland High Risk Foot Form valid or reliable for research?

Background High-risk foot complications such as neuropathy, ischaemia, deformity, infections, ulcers and amputations consume considerable health care resources and typically result from chronic diseases. This study aimed to develop and test the validity and reliability of a Queensland High Risk Foot Form (QHRFF) tool. Methods Phase one involved developing a QHRFF using an existing diabetes high-risk foot tool, literature search, expert panel and several state-wide stakeholder groups. Phase two tested the criterion-related validity along with inter- and intra-rater reliability of the final QHRFF. Three cohorts of patients (n = 94) and four clinicians, representing different levels of expertise, were recruited. Validity was determined by calculating sensitivity, specificity and positive predictive values (PPV). Kappa and intra-class correlation (ICC) statistics were used to establish reliability. Results A QHRFF tool containing 46-items across seven domains was developed and endorsed. The majority of QHRFF items achieved moderate-to-perfect validity (PPV = 0.71 – 1) and reliability (Kappa/ICC = 0.41 – 1). Items with weak validity and/or reliability included those identifying health professionals previously attending the patient, other (non-listed) co-morbidity, previous foot ulcer, foot deformity, optimum offloading and optimum footwear. Conclusions The QHRFF had moderate-to-perfect validity and reliability across the majority of items, particularly identifying individual co-morbidities and foot complications. Items with weak validity or reliability need to be re-defined or removed. Overall, the QHRFF appears to be a valid and reliable tool to assess, collect and measure clinical data pertaining to high-risk foot complications for clinical or research purposes.

The politics of open-access publishing : M/C Journal, Public Intellectualism, and Academic Discourses of Legitimacy

This article investigates the discourses of academic legitimacy that surround the production, consumption, and accreditation of online scholarship. Using the web-based media and cultural studies journal (http://journal.media-culture.org.au) as a case study, it examines how online scholarly journals often position themselves as occupying a space between the academic and the popular and as having a functional advantage over print-based media in promoting a spirit of public intellectualism. The current research agenda of both government and academe prioritises academic research that is efficient, self-promoting, and relevant to the public. Yet, although the cost-effectiveness and public-intellectual focus of online scholarship speak to these research priorities, online journals such as M/C Journal have occupied, and continue to occupy, an unstable position in relation to the perceived academic legitimacy of their content. Although some online scholarly journals have achieved a limited form of recognition within a system of accreditation that still privileges print-based scholarship, I argue that this, nevertheless, points to the fact that traditional textual notions of legitimate academic work continue to pervade the research agenda of an academe that increasingly promotes flexible delivery of teaching and online research initiatives.

Unsupervised Domain Adaptation by Domain Invariant Projection

Domain-invariant representations are key to addressing the domain shift problem where the training and test exam- ples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typically compare these distributions in the original feature space. This space, however, may not be di- rectly suitable for such a comparison, since some of the fea- tures may have been distorted by the domain shift, or may be domain specific. In this paper, we introduce a Domain Invariant Projection approach: An unsupervised domain adaptation method that overcomes this issue by extracting the information that is invariant across the source and tar- get domains. More specifically, we learn a projection of the data to a low-dimensional latent space where the distance between the empirical distributions of the source and target examples is minimized. We demonstrate the effectiveness of our approach on the task of visual object recognition and show that it outperforms state-of-the-art methods on a stan- dard domain adaptation benchmark dataset

Repeatable Condition-Invariant Visual Odometry for Sequence-Based Place Recognition

This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.

Efficient microwave hydrothermal preparation of nanocrystalline anatase TiO2 colloids

Titanium dioxide nanocrystals are an important commercial product used primarily in white pigments and abrasives, however, more recently the anatase form of TiO2 has become a major component in electrochemical and photoelectrochemical devices. An important property of titanium dioxide nanocrystals for electrical applications is the degree of crystallinity. Numerous preparation methods exist for the production of highly crystalline TiO2 particles. The majority of these processes require long reaction times, high pressures and temperatures (450–1400 °C). Recently, hydrothermal treatment of colloidal TiO2 suspensions has been shown to produce quality crystalline products at low temperatures (<250 °C). In this paper we extend this idea utilising a direct microwave heating source. A comparison between convection and microwave hydrothermal treatment of colloidal TiO2 is presented. The resulting highly crystalline TiO2 colloids were characterised using Raman spectroscopy, XRD, TEM, and electron diffraction. The results show that the microwave treatment of colloidal TiO2 gives comparable increases in crystallinity with respect to normal hydrothermal treatments while requiring significantly less time and energy than the hydrothermal convection treatment.

Improving the Flexibility of Active Grids through Web Services

Active Grids are a form of grid infrastructure where the grid network is active and programmable. These grids directly support applications with value added services such as data migration, compression, adaptation and monitoring. Services such as these are particularly important for eResearch applications which by their very nature are performance critical and data intensive. We propose an architecture for improving the flexibility of Active Grids through web services. These enable Active Grid services to be easily and flexibly configured, monitored and deployed from practically any platform or application. The architecture is called WeSPNI ('Web Services based on Programmable Networks Infrastructure'). We present the architecture together with some early experimental results on using web services to monitor data movement in an active grid.

Tangible interfaces to explain Gaudi's use of ruled-surface geometries

This paper summarises the development of a machine-readable model series for explaining Gaudi's use of ruled surface geometry in the Sagrada Familia in Barcelona, Spain. The first part discusses the modeling methods underlying the columns of the cathedral and the techniques required to translate them into built structures. The second part discusses the design and development of a tangible machine-readable model to explain column-modeling methods interactively in educational contexts such as art exhibitions. It is designed to explain the principles underlying the column design by means of physical interaction without using mathematical terms or language.