Cross-sectional geometry of weight-bearing tibia in female athletes subjected to different exercise loadings

Summary The association of long-termsport-specific exercise loading with cross-sectional geometry of the weight-bearing tibia was evaluated among 204 female athletes representing five different exercise loadings and 50 referents. All exercises involving ground impacts (e.g., endurance running, ball games, jumping) were associated with thicker cortex at the distal and diaphyseal sites of the tibia and also with large diaphyseal cross-section, whereas the high-magnitude (powerlifting) and non-impact (swimming) exercises were not. Introduction Bones adapt to the specific loading to which they are habitually subjected. In this cross-sectional study, the association of long-term sport-specific exercise loading with the geometry of the weight-bearing tibia was evaluated among premenopausal female athletes representing 11 different sports.

Methods A total of 204 athletes were divided into five exercise loading groups, and the respective peripheral quantitative computed tomographic data were compared to data obtained from 50 physically active, non-athletic referents. Analysis of covariance was used to estimate the between-group differences.

Results At the distal tibia, the high-impact, odd-impact, and repetitive low-impact exercise loading groups had ~30% to 50% (p<0.05) greater cortical area (CoA) than the referents. At the tibial shaft, these three impact groups had ~15% to 20% (p<0.05) greater total area (ToA) and ~15% to 30% (p<0.05) greater CoA. By contrast, both the high-magnitude and repetitive non-impact groups had similar ToA and CoA values to the reference group at both tibial sites.

Conclusions High-impact, odd-impact, and repetitive lowimpact exercise loadings were associated with thicker cortex at the distal tibia. At the tibial shaft, impact loading was not only associated with thicker cortex, but also a larger cross-sectional area. High-magnitude exercise loading did not show such associations at either site but was comparable to repetitive non-impact loading and reference data. Collectively, the relevance of high strain rate together with moderate-to-high strain magnitude as major determinants of osteogenic loading of the weight-bearing tibia is implicated.

Mobile solutions for front-line health workers in developing countries

We introduce an architecture for low-cost mobile Health (mHealth) applications that run on health-workers’ existing devices. Moreover, we envision extending the phone’s capabilities with an external to attach “sensor” modules, such as pulse oximeter, ECG and phonocardiogram. Our design principles are frugality and simplicity. We propose a comprehensive solution to aid health-workers in their daily tasks, at a low-cost and high penetration rate.

CAFS : a novel lightweight cache-based scheme for large-scale intrusion alert fusion

In this paper, we present some practical experiences on implementing an alert fusion mechanism from our project. After investigation on most of the existing alert fusion systems, we found the current body of work alternatively weighed down in the mire of insecure design or rarely deployed because of their complexity. As confirmed by our experimental analysis, unsuitable mechanisms could easily be submerged by an abundance of useless alerts. Even with the use of methods that achieve a high fusion rate and low false positives, attack is also possible. To find the solution, we carried out analysis on a series of alerts generated by well-known datasets as well as realistic alerts from the Australian Honey-Pot. One important finding is that one alert has more than an 85% chance of being fused in the following five alerts. Of particular importance is our design of a novel lightweight Cache-based Alert Fusion Scheme, called CAFS. CAFS has the capacity to not only reduce the quantity of useless alerts generated by intrusion detection system, but also enhance the accuracy of alerts, therefore greatly reducing the cost of fusion processing. We also present reasonable and practical specifications for the target-oriented fusion policy that provides a quality guarantee on alert fusion, and as a result seamlessly satisfies the process of successive correlation. Our experiments compared CAFS with traditional centralized fusion. The results showed that the CAFS easily attained the desired level of simple, counter-escapable alert fusion design. Furthermore, as a lightweight scheme, CAFS can easily be deployed and excel in a large amount of alert fusions, which go towards improving the usability of system resources. To the best of our knowledge, our work is a practical exploration in addressing problems from the academic point of view. Copyright © 2011 John Wiley & Sons, Ltd.

Securing RFID systems from SQLIA

While SQL injection attacks have been plaguing web applications for years the threat they pose to RFID systems have only identified recently. Because the architecture of web systems and RFID systems differ considerably the prevention and detection techniques proposed for web applications are not suitable for RFID systems. In this paper we propose a system to secure RFID systems against tag based SQLIA. Our system is optimized for the architecture of RFID systems and consists of a query structure matching technique and tag data cleaning technique. The novelty of the proposed system is that it's specifically aimed at RFID systems and has the ability to detect and prevent second order injections which is a problem most current solutions haven't addressed. The preliminary evaluation of our query matching technique is very promising showing very high detection rate with minimal false positives.

Improving reliability of unbalanced text mining by reducing performance bias

Class imbalance in textual data is one important factor that affects the reliability of text mining. For imbalanced textual data, conventional classifiers tend to have a strong performance bias, which results in high accuracy rate on the majority class but very low rate on the minorities. An extreme strategy for unbalanced learning is to discard the majority instances and apply one-class classification to the minority class. However, this could easily cause another type of bias, which increases the accuracy rate on minorities by sacrificing the majorities. This chapter aims to investigate approaches that reduce these two types of performance bias and improve the reliability of discovered classification rules. Experimental results show that the inexact field learning method and parameter optimized one class classifiers achieve more balanced performance than the standard approaches.

Resource-aware speculative prefetching in wireless networks

Mobile users connected to wireless networks expect performance comparable to those on wired networks for interactive multimedia applications. Satisfying Quality of Service (QoS) requirements for such applications in wireless networks is a challenging problem due to limitations of low bandwidth, high error rate and frequent disconnections of wireless channels. In addition, wireless networks suffer from varying bandwidth. In this paper we investigate object prefetching during times of connectedness and bandwidth availability to enhance user perceived connectedness. This paper presents an access model that is suitable for multimedia access in wireless networks. Access modelling for the purpose of predicting future accesses in the context of speculative prefetching has received much attention in the literature. The model recognizes that a web page, instead of just a single file, is typically a compound of several files. When it comes to making prefetch decisions, most previous studies in speculative prefetching resort to simple heuristics, such as prefetching an item with access probabilities larger than a manually tuned threshold. This paper takes a different approach. Specifically, it models the performance of the prefetcher, taking into account access predictions and resource parameters, and develops a prefetch policy based on a theoretical analysis of the model. Since the analysis considers cache as one of the resource parameters, the resulting policy integrates prefetch and cache replacement decisions. The paper investigates the effect of prefetching on network load. In order to make effective use of available resources and maximize access improvement, it is beneficial to prefetch all items with access probabilities exceeding certain threshold.

Wireless haptic rendering for mobile platforms

Computer haptics has so far been performed on a personal computer (PC). Off the shelf haptic devices provide only PC interfaces and software drivers for control and communication. The new wave of high capable tablet PCs and high end smart phones introduced new platforms for haptic applications. The major problem was to communicate wirelessly to provide user convenience and support mobility which is an essential feature for these platforms. In this paper we provide a wireless layered communication protocol and a hardware setup that enables off the shelf haptic devices to communicate wirelessly with a mobile device. The layers in the protocol enable the change of any hardware components without affecting the data flow. However, the adoption of the wireless interface instead of the wired one comes with the price of speed. Haptic refresh loops require a relatively high refresh rate of 1000 Hz compared to graphics loop which require between 30 and 60 only. An interpolation algorithm was demonstrated to compensate the latency and secure a stable user experience. The introduced setup was tested against portable environments and the users could perform similar functionalities to what are available on a wired setup to a PC.

Compact stacked planar inverted-F antenna for passive deep brain stimulation implants

A compact meandered three-layer stacked circular planar inverted-F antenna is designed and simulated at the UHF band (902.75 – 927.25 MHz) for passive deep brain stimulation implants. The UHF band is used because it offers small antenna size, and high data rate. The top and middle radiating layers are meandered, and low cost substrate and superstrate materials are used to limit the radius and height of the antenna to 5 mm and 1.64 mm, respectively. A dielectric substrate of FR-4 of εr= 4.7 and δ= 0.018, and a biocompatible superstrate of silicone of er= 3.7 and d= 0.003 with thickness of 0.2 mm are used in the design. The resonance frequency of the proposed antenna is 918 MHz with a bandwidth of 24 MHz at return loss of −10 dB in free space. The antenna parameter such as 3D gain pattern of the designed antenna within a skin-tissue model is evaluated by using the finite element method. The compactness, wide bandwidth, round shape, and stable characteristics in skin make this antenna suitable for DBS. The feasibility of the wireless power transmission to the implant in the human head is also examined.

Multi-layer implantable antenna for closed loop deep brain stimulation system

A multi-layer circular planar inverted-F antenna is designed and simulated at the industrial, scientific, and medical (ISM) band of 915 MHz for closed loop deep brain stimulation implant. The ISM band is considered due to the capabilities of small antenna size, high data rate, and long transmission range. In the proposed four-layer antenna, the top three radiating layers are meandered, and a high permittivity substrate and superstrate materials are used to limit the radius and the height of the antenna to 3.5 mm and 2.2 mm, respectively. The bottom layer works as a ground plate. The Roger RO3210 of εr = 10.2 and δ = 0.003 is used as a dielectric substrate and superstrate. The resonance frequency of the proposed antenna is 915 MHz with a bandwidth of 12 MHz at the return loss of -10 dB in free space. The stacked layered structure reduces the antenna size, and the circular shape makes it easily implantable into the human head. The antenna parameters (e.g. 3D gain pattern), SAR value, and electric field distribution within a six layers spherical head model are evaluated by using the finite element method (FEM). The feasibility of the wireless transmission of power, control and command signal to the implant in the human head is also examined. © 2012 IEEE.

A cluster randomised trial of an internet-based intervention program for tinnitus distress in an industrial setting

The effectiveness of a therapist-supported Internet intervention program for tinnitus distress in an industrial setting was evaluated using a cluster randomised design. Fifty-six Australian employees of two industrial organisations were randomly assigned, based on their work site (18 work sites from BP Australia and five from BHP Billiton), to either a cognitive behavioural therapy (CBT) program or an information-only control program. Participants were assessed at pre- and postprogram, measuring tinnitus distress, depression, anxiety, stress, quality of life, and occupational health. The CBT program was not found to be superior to the information program for treating tinnitus distress. A high attrition rate and small sample size limit the generalisability of the findings, and further developments of the program and assessment process are needed to enhance engagement and compliance.

Surgical treatment of lateral clavicle fractures associated with complete coracoclavicular ligament disruption: clinico-radiological outcomes of acromioclavicular joint sparing and spanning implants

Distal clavicle fracture associated with complete coracoclavicular ligament disruption represents an unstable injury, and osteosynthesis is recommended. This study was performed (1) to retrospectively analyse the clinico-radiological outcomes of two internal fixation techniques, and (2) to identify and analyse radiographic fracture patterns of fracture that are associated with this injury. Conclusions: Internal fixation of this fracture pattern is associated with a high union rate and favorable clinical outcomes with both techniques. A combination of distal radius plate and ligament reconstruction device resulted in stable fixation and significantly lower reoperation rates, and should be used when fracture geometry permits (Types 1 and 2).

Urban growth in arid environments : developing water sustainability indicators for Abu Dhabi (UAE)

The United Arab Emirates (UAE) face a serious water problem. It has a very dry climate, high evaporation rate, combined with large water consumption from fast growing population, economic activities and uncontrolled uses of water for irrigation. Currently, UAE has one of the largest water footprints in the world. Groundwater is overexploited. Waste water is increasingly being treated to supply non-drinking water, but it still cover a small proportion of the demand. Desalination of sea water is the main source of potable water in UAE, but the high economic cost of desalination, its intensive energy demand and the adverse effects of its effluents on the marine life are a major concern. Other factors contributing to the problem are the focus of water management policies on keep supplying the growing demand for water, the increase of the per capita water consumption, and the free water charge for most of population. This research goal is to develop a water sustainability set of indicators for the challenging context of UAE. This paper presents the first stage of the research. Based on a review of the literature, the proposed framework involves 19 indicators, divided into four categories: water availability; water quality; water use efficiency; and policy and governance. Using an integrated cause-effect approach (DSR - Driving force, State, Response), the indicators were related in terms of their interdependencies, with a holistic view of the city water cycle. A preliminary test of the indicators to Abu Dhabi as a case study allowed an evaluation of the main 'Driving force' on the system, such as the scarcity of water due to natural constraints of the region, and increasing water consumption patterns of modern society; an assessment of the current 'state', which is under serious water stress. Also it indicated some potential 'responses', such as implementing policies for increasing efficient use.

A pose-wise linear illumination manifold model for face recognition using video

The objective of this work is to recognize faces using video sequences both for training and novel input, in a realistic, unconstrained setup in which lighting, pose and user motion pattern have a wide variability and face images are of low resolution. There are three major areas of novelty: (i) illumination generalization is achieved by combining coarse histogram correction with fine illumination manifold-based normalization; (ii) pose robustness is achieved by decomposing each appearance manifold into semantic Gaussian pose clusters, comparing the corresponding clusters and fusing the results using an RBF network; (iii) a fully automatic recognition system based on the proposed method is described and extensively evaluated on 600 head motion video sequences with extreme illumination, pose and motion pattern variation. On this challenging data set our system consistently demonstrated a very high recognition rate (95% on average), significantly outperforming state-of-the-art methods from the literature.

A data mining approach for detection of self-propagating worms

In this paper we demonstrate our signature based detector for self-propagating worms. We use a set of worm and benign traffic traces of several endpoints to build benign and worm profiles. These profiles were arranged into separate n-ary trees. We also demonstrate our anomaly detector that was used to deal with tied matches between worm and benign trees. We analyzed the performance of each detector and also with their integration. Results show that our signature based detector can detect very high true positive. Meanwhile, the anomaly detector did not achieve high true positive. Both detectors, when used independently, suffer high false positive. However, when both detectors were integrated they maintained a high detection rate of true positive and minimized the false positive

Feasibility, acceptability and potential effectiveness of a mobile health (mHealth) weight management programme for New Zealand adults

Background
Mobile health (mHealth) behaviour change programmes use mobile phones and the internet to deliver health information and behaviour change support to participants. Such programmes offer a potentially cost-effective way to reach many individuals who do not currently access weight loss services. We developed a mHealth weight management programme using proven face-to-face behaviour change techniques and incorporating target population input. Our aim was to evaluate the feasibility, acceptability and potential effectiveness of this programme for ethnically diverse adults with a view to informing a larger trial.

Results
Fifty three adults who had a BMI of ≥25 kg/m2 and wanted to lose weight (81% female, mean age 42 years, mean BMI 35.7 kg/m2, 26% Maori, 34% Pacific) received the eight-week mHealth weight loss programme. Anthropometric measures were taken at two face-to-face assessments at baseline and 12-weeks (i.e. four weeks after cessation of intervention).

Twelve-week follow-up measurements were available for 36/53 participants (68%). Non-completers were younger and more likely to be male and of Pacific ethnicity. Thirty five participants (66%) reported reading ‘all or most’ text messages sent and 96% responded to at least one text data collection question over the eight-week active intervention period. Eighty one per cent of participants logged in to the study website at least once during the eight-week study period. In the intention-to-treat analysis, mean weight change was -1.0 kg (SD 3.1) at 12 weeks (p = 0.024) and change in BMI was -0.34 kg/m2 (SD 1.1) (p = 0.026). In the completers only analysis (n = 36), mean weight change was -1.4 kg (SD 3.6) (p = 0.023) and change in BMI was -0.50 kg/m2 (SD 1.3) (p = 0.025).

Conclusions
A mHealth weight management programme is feasible to deliver to an ethnically diverse population. Changes in body weight and BMI at 12 weeks indicate that the programme could be effective in supporting people with weight loss. However, the high dropout rate indicates a need for further improvements to the programme.