Development of a new versatile computer controlled electrochemical/ESR data acquisition system

A new versatile computer controlled electrochemlcal/ESR data acquisition system has been developed for the Investigation of short-lived radicals with life-times of 20 milliseconds and greater, Different computer programs have been developed to monitor the decay of radicals; over hours or minutes, seconds or milliseconds. Signal averaging and Fourier smoothing is employed in order to improve the signal to noise ratio. Two microcomputers are used to control the system, one home-made computer containing the M6800 chip which controls the magnetic field, and an IBM PC XT which controls the electrochemistry and the data acquisition. The computer programs are written in Fortran and C, and call machine language subroutines, The system functions by having the radical generated by an electrochemical pulse: after or during the pulse the ESR data are collected. Decaying radicals which have half-lives of seconds or greater have their spectra collected in the magnetic field domain, which can be swept as fast as 200 Gauss per second. The decay of the radicals in the millisecond region is monitored by time-resolved ESR: a technique in which data is collected in both the time domain and in the magnetic field domain. Previously, time-resolved ESR has been used (without field modulation) to investigate ultra-short-lived species with life-times in the region of only a few microseconds. The application of the data acquisition system to chemical systems is illustrated. This is the first time a computer controlled system whereby the radical is generated by electrochemical means and subsequently the ESR data collected, has been developed.

An auto-switch for multisampling of a wire beam electrode corrosion monitoring system

An auto-switch device has been designed, constructed, and tested for multisensor corrosion measurements. The auto-switch is able to connect/disconnect the selected wire beam electrode and/or electrode pairs under computer control. A computer controlled analog switch-array consisting of 100 inputs has been used as an essential part of the switch bank. The switch-bank is an essential component of a corrosion-monitoring instrument that is expected to find wide application in industry. The performance of the switch-bank is discussed and its effect on the signals is illustrated.

Highly programmable surface

A highly programmable electro-mechanical surface is developed using an effective array of individual pins arranged in a gridform. Each pin can be independently raised or lowered to create a wide range of contoured surfaces. It was found that as the number of elements increased. high levels of accuracy could still be achieved. however the required processing power increased logarithmically. This finding was attributed to the large amounts of data being passed. and subsequently led to a second focus; various methods of data management and flow control techniques within large-scale multi elemental systems. Results indicated a large potential for highly programmable surfaces within industry to provide a computer controlled surface for rapid prototyping. The research also revealed the potential for such a device to be used as a HID within Haptic applications.

Computer reminders for chlamydia screening in general practice : a randomized controlled trial

Background: Chlamydia notifications are increasing in Australia, and the use of a computer alert prompting general practitioners to test young women is a potential way to increase opportunistic chlamydia testing. The aim of this trial was to determine the effectiveness of a computer alert in general practice on chlamydia testing in young women.

Methods: In 2006, clinics (n = 68) in Melbourne, Australia were cluster randomized into 2 groups: the intervention group received a computerized alert advising the general practitioner to discuss chlamydia testing with their patient which popped up when the medical record of a 16- to 24-year-old woman was opened; the control group received no alert. The outcome was whether or not that patient received a chlamydia test at the level of a single consultation with an eligible patient. A mixed effects logistic regression model adjusting for clustering was used to assess the impact of the alert on the proportion of women tested for chlamydia during the trial period.

Results: Testing increased from 8.3% (95% confidence interval (CI): 6.8, 9.8) to 12.2% (95% CI: 9.1, 15.3) (P < 0.01) in the intervention group, and from 8.8% (95% CI: 6.8, 10.7) to 10.6% (95% CI: 8.5, 12.7) (P < 0.01) in the control group. Overall, the intervention group had a 27% (OR = 1.3; 95% CI: 1.1, 1.4) greater increase in testing.

Conclusion: The results of this study suggest that alerts alone may not be sufficient to get chlamydia testing levels up sufficiently high enough to have an impact on the burden of chlamydia in the population but that they could be included as part of a more complex intervention.

Improving communication when seeking informed consent: a randomised controlled study of a computer-based method for providing information to prospective clinical trial participants

OBJECTIVE: To assess the efficacy, with respect to participant understanding of information, of a computer-based approach to communication about complex, technical issues that commonly arise when seeking informed consent for clinical research trials. DESIGN, SETTING AND PARTICIPANTS: An open, randomised controlled study of 60 patients with diabetes mellitus, aged 27-70 years, recruited between August 2006 and October 2007 from the Department of Diabetes and Endocrinology at the Alfred Hospital and Baker IDI Heart and Diabetes Institute, Melbourne. INTERVENTION: Participants were asked to read information about a mock study via a computer-based presentation (n = 30) or a conventional paper-based information statement (n = 30). The computer-based presentation contained visual aids, including diagrams, video, hyperlinks and quiz pages. MAIN OUTCOME MEASURES: Understanding of information as assessed by quantitative and qualitative means. RESULTS: Assessment scores used to measure level of understanding were significantly higher in the group that completed the computer-based task than the group that completed the paper-based task (82% v 73%; P = 0.005). More participants in the group that completed the computer-based task expressed interest in taking part in the mock study (23 v 17 participants; P = 0.01). Most participants from both groups preferred the idea of a computer-based presentation to the paper-based statement (21 in the computer-based task group, 18 in the paper-based task group). CONCLUSIONS: A computer-based method of providing information may help overcome existing deficiencies in communication about clinical research, and may reduce costs and improve efficiency in recruiting participants for clinical trials.

Blind source separation based on phase and frequency redundancy of cyclostationary signals

This paper presents a new method for blind source separation by exploiting phase and frequency redundancy of cyclostationary signals in a complementary way. It requires a weaker separation condition than those methods which only exploit the phase diversity or the frequency diversity of the source signals. The separation criterion is to diagonalize a polynomial matrix whose coefficient matrices consist of the correlation and cyclic correlation matrices, at time delay .TAU. = 0, of multiple measurements. An algorithm is proposed to perform the blind source separation. Computer simulation results illustrate the performance of the new algorithm in comparison with the existing ones.

Speed control and policing in a cellular mobile network: speedNet

In this paper, we describe SpeedNet, a GSM network variant which resembles an ad hoc wireless mobile network where base stations keep track of the velocities of mobile users (cars). SpeedNet is intended to track mobile users and their speed passively for both speed policing and control of traffic. The speed of the vehicle is controlled in a speed critical zone by means of an electro-mechanical control system, suitably referred to as VVLS (Vehicular Velocity Limiting System). VVLS is mounted on the vehicle and responds to the command signals generated by the base station. It also determines the next base station to handoff, in order to improve the connection reliability and bandwidth efficiency of the underlying network. Robust Extended Kalman Filter (REKF) is used as a passive velocity estimator of the mobile user with the widely used proportional and integral controller speed control. We demonstrate through simulation and analysis that our prediction algorithm can successfully estimate the mobile user’s velocity with low system complexity as it requires two closest mobile base station measurements and also it is robust against system uncertainties due to the inherent deterministic nature in the mobility model.

An exploratory cluster randomised controlled trial of knowledge translation strategies to support evidence-informed decision-making in local governments (The KT4LG study)

Background: Childhood overweight and obesity is the most prevalent and, arguably, politically complex child health problem internationally. Governments, communities and industry have important roles to play, and are increasingly expected to deliver an evidence-informed system-wide prevention program. However, efforts are impeded by a lack of organisational access to and use of research evidence. This study aims to identify feasible, acceptable and ideally, effective knowledge translation (KT) strategies to increase evidence-informed decision making in local governments, within the context of childhood obesity prevention as a national policy priority.
Methods/Design: This paper describes the methods for KT4LG, a cluster randomised controlled trial which is exploratory in nature, given the limited evidence base and methodological advances. KT4LG aims to examine a program of KT strategies to increase the use of research evidence in informing public health decisions in local governments. KT4LG will also assess the feasibility and acceptability of the intervention. The intervention program comprises a facilitated program of evidence awareness, access to tailored research evidence, critical appraisal skills development, networking and evidence summaries and will be compared to provision of evidence summaries alone in the control program. 28 local governments were randomised to intervention or control, using computer generated numbers, stratified by budget tertile (high, medium or low). Questionnaires will be used to measure impact, costs, and outcomes, and key informant interviews will be used to examine processes, feasibility, and experiences. Policy tracer studies will be included to examine impact of intervention on policies within relevant government policy documents.
Discussion: Knowledge translation intervention studies with a focus on public health and prevention are very few in number. Thus, this study will provide essential data on the experience of program implementation and evaluation of a system-integrated intervention program employed within the local government public health context. Standardised programs of system, organisational and individual KT strategies have not been described or rigorously evaluated. As such, the findings will make a significant contribution to understanding whether a facilitated program of KT strategies hold promise for facilitating evidence-informed public health decision making within complex multisectoral government organisations.

Human action segmentation via controlled use of missing data in HMMs

Segmentation of individual actions from a stream of human motion is an open problem in computer vision. This paper approaches the problem of segmenting higher-level activities into their component sub-actions using Hidden Markov Models modified to handle missing data in the observation vector. By controlling the use of missing data, action labels can be inferred from the observation vector during inferencing, thus performing segmentation and classification simultaneously. The approach is able to segment both prominent and subtle actions, even when subtle actions are grouped together. The advantage of this method over sliding windows and Viterbi state sequence interrogation is that segmentation is performed as a trainable task, and the temporal relationship between actions is encoded in the model and used as evidence for action labelling.

Randomised controlled trials and 'unexpected' adverse events associated with newly released drugs : improvements in pharmacovigilance systems are necessary for real-time identification of patient safety risks

Adverse drug events are one of the major causes of morbidity in developed countries, yet the drugs involved in these events have been trialled and approved on the basis of randomised controlled trials (RCTs), regarded as the study design that will produce the best evidence.

Though the focus on adverse drug events has been primarily on processes and outcomes associated with the use of these approved drugs, attention needs to be directed to the way in which the RCT study design is structured. The implementation of controls to achieve internal validity in RCTs may be the very controls that reduce external validity, and contribute to the levels of adverse drug events associated with the release of a new drug to the wider patient population.

An examination of these controls, and the effects they can have on patient safety, underscore the importance of knowing about how the clinical trials of a drug are undertaken, rather than relying only on the recorded outcomes.

As the majority of new drugs are likely to be prescribed to older patients who have one or more comorbidities in addition to that targeted by a new drug, and as the RCTs of those drugs typically under-represent the elderly and exclude patients with multiple comorbidities, timely assessment of drug safety signals is essential.

It is unlikely that regulatory jurisdictions will undertake a reassessment of safety issues for drugs that are already approved. Instead, reliance has been placed on adverse drug event reporting systems. Such systems have a very low reporting rate, and most adverse drug events remain unreported, to the eventual cost to patients and healthcare systems.

This makes it essential for near real-time systems that can pick up safety signals as they occur, so that modifications to the product information (or removal of the drug) can be implemented.

Authenticating the identity of computer users with typing biometrics and the fuzzy min-max neural network

In this paper, typing biometrics is applied as an additional security measure to the password-based or Personal Identification Number (PIN)-based systems to authenticate the identity of computer users. In particular, keystroke pressure and latency signals are analyzed using the Fuzzy Min-Max (FMM) neural network for authentication purposes. A special pressure-sensitive keyboard is designed to collect keystroke pressure signals, in addition to the latency signals, from computer users when they type their passwords. Based on the keystroke pressure and latency signals, the FMM network is employed to classify the computer users into two categories, i.e., genuine users or impostors. To assess the effectiveness of the proposed approach, two sets of experiments are conducted, and the results are compared with those from statistical methods and neural network models. The experimental outcomes positively demonstrate the potentials of using typing biometrics and the FMM network to provide an additional security layer for the current password-based or PIN-based methods in authenticating the identity of computer users.

Can social dancing prevent falls in older adults? a protocol of the Dance, Aging, Cognition,Economics (DAnCE) fall prevention randomised controlled trial

Background:  Falls are one of the most common health problems among older people and pose a major economic burden on health care systems. Exercise is an accepted stand-alone fall prevention strategy particularly if it is balance training or regular participation in Tai chi. Dance shares the ‘holistic’ approach of practices such as Tai chi. It is a complex sensorimotor rhythmic activity integrating multiple physical, cognitive and social elements. Small-scale randomised controlled trials have indicated that diverse dance styles can improve measures of balance and mobility in older people, but none of these studies has examined the effect of dance on falls or cognition. This study aims to determine whether participation in social dancing: i) reduces the number of falls; and ii) improves cognitive functions associated with fall risk in older people.

Methods/design: A single-blind, cluster randomised controlled trial of 12 months duration will be conducted. Approximately 450 participants will be recruited from 24 self-care retirement villages that house at least 60 residents each in Sydney, Australia. Village residents without cognitive impairment and obtain medical clearance will be eligible. After comprehensive baseline measurements including physiological and cognitive tests and self-completed questionnaires, villages will be randomised to intervention sites (ballroom or folk dance) or to a wait-listed control using a computer randomisation method that minimises imbalances between villages based on two baseline fall risk measures. Main outcome measures are falls, prospectively measured, and the Trail Making cognitive function test. Cost-effectiveness and cost-utility analyses will be performed.

Discussion: This study offers a novel approach to balance training for older people. As a community-based approach to fall prevention, dance offers older people an opportunity for greater social engagement, thereby making a major contribution to healthy ageing. Providing diversity in exercise programs targeting seniors recognises the heterogeneity of multicultural populations and may further increase the number of taking part in exercise.

Bayesian nonparametric extraction of hidden contexts from pervasive honest signals

Hidden patterns and contexts play an important part in intelligent pervasive systems. Most of the existing works have focused on simple forms of contexts derived directly from raw signals. High-level constructs and patterns have been largely neglected or remained under-explored in pervasive computing, mainly due to the growing complexity over time and the lack of efficient principal methods to extract them. Traditional parametric modeling approaches from machine learning find it difficult to discover new, unseen patterns and contexts arising from continuous growth of data streams due to its practice of training-then-prediction paradigm. In this work, we propose to apply Bayesian nonparametric models as a systematic and rigorous paradigm to continuously learn hidden patterns and contexts from raw social signals to provide basic building blocks for context-aware applications. Bayesian nonparametric models allow the model complexity to grow with data, fitting naturally to several problems encountered in pervasive computing. Under this framework, we use nonparametric prior distributions to model the data generative process, which helps towards learning the number of latent patterns automatically, adapting to changes in data and discovering never-seen-before patterns, contexts and activities. The proposed methods are agnostic to data types, however our work shall demonstrate to two types of signals: accelerometer activity data and Bluetooth proximal data. © 2014 IEEE.

Web-based alcohol intervention for Māori university students: double-blind, multi-site randomized controlled trial

AIMS: Like many indigenous peoples, New Zealand Māori bear a heavy burden of alcohol-related harm relative to their non-indigenous compatriots, and disparities are greatest among young adults. We tested the effectiveness of web-based alcohol screening and brief intervention (e-SBI) for reducing hazardous drinking among Māori university students. DESIGN: Parallel, double-blind, multi-site, randomized controlled trial. SETTING: Seven of New Zealand's eight universities. PARTICIPANTS: In April 2010, we sent e-mail invitations to all 6697 17-24-year-old Māori students to complete a brief web questionnaire including the Alcohol Use Disorders Identification Test (AUDIT)-C, a screening tool for hazardous and harmful drinking. Those screening positive were computer randomized to: <10 minutes of web-based alcohol assessment and personalized feedback (intervention) or screening alone (control). MEASUREMENTS: We conducted a fully automated 5-month follow-up assessment with observers and participants blinded to study hypotheses, design and intervention delivery. Pre-determined primary outcomes were: (i) frequency of drinking, (ii) amount consumed per typical drinking occasion, (iii) overall volume of alcohol consumed and (iv) academic problems. FINDINGS: Of the participants, 1789 were hazardous or harmful drinkers (AUDIT-C ≥ 4) and were randomized: 850 to control, 939 to intervention. Follow-up assessments were completed by 682 controls (80%) and 733 intervention group members (78%). Relative to controls, participants receiving intervention drank less often [RR = 0.89; 95% confidence interval (CI): 0.82-0.97], less per drinking occasion (RR = 0.92; 95% CI: 0.84-1.00), less overall (RR = 0.78; 95% CI: 0.69-0.89) and had fewer academic problems (RR = 0.81; 95% CI: 0.69-0.95). CONCLUSIONS: Web-based screening and brief intervention reduced hazardous and harmful drinking among non-help-seeking Māori students in a large-scale pragmatic trial. The study has wider implications for behavioural intervention in the important but neglected area of indigenous health.