The application of a novel, cell permeable activity-based probe for the detection of cysteine cathepsins.

Cysteine cathepsins, such as cathepsin S (CTSS), are implicated in the pathology of a wide range of diseases and are of potential utility as diagnostic and prognostic biomarkers. In previous work, we demonstrated the potency and efficiency of a biotinylated diazomethylketone (DMK)-based activity-based probe (ABP), biotin-PEG-LVG-DMK, for disclosure of recombinant CTSS and CTSS in cell lysates. However, the limited cell permeability of both the biotin and spacer groups restricted detection of CTSS to cell lysates. The synthesis and characterisation of a cell permeable ABP to report on intracellular CTSS activity is reported. The ABP, Z-PraVG-DMK, a modified peptidyl diazomethylketone, was based on the N-terminus of human cystatin motif (Leu-Val-Gly). The leucine residue was substituted for the alkyne-bearing proparcylglycine to facilitate conjugation of an azide-tagged reporter group using click chemistry, following irreversible inhibition of CTSS. When incubated with viable Human Embryonic Kidney 293 cells, Z-PraVG-DMK permitted disclosure of CTSS activity following cell lysis and rhodamine azide conjugation, by employing standard click chemistry protocols. Furthermore, the fluorescent tag facilitated direct detection of CTSS using in-gel fluorescent scanning, obviating the necessity for downstream biotin-streptavidin conjugation and detection procedures.

Respiratory electron transport activity in plankton: determinants and detection

Programa de doctorado en Oceanografía. La fecha de publicación es la fecha de lectura

Experimenting with an intrusion detection system for encrypted networks

Network-based Intrusion Detection Systems (NIDSs) analyse network traffic to detect instances of malicious activity. Typically, this is only possible when the network traffic is accessible for analysis. With the growing use of Virtual Private Networks (VPNs) that encrypt network traffic, the NIDS can no longer access this crucial audit data. In this paper, we present an implementation and evaluation of our approach proposed in Goh et al. (2009). It is based on Shamir's secret-sharing scheme and allows a NIDS to function normally in a VPN without any modifications and without compromising the confidentiality afforded by the VPN.

Facial feature detection for in-car environment

Acoustically, vehicles are extremely noisy environments and as a consequence audio-only in-car voice recognition systems perform very poorly. Seeing that the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem. However, implementing such an approach requires a system being able to accurately locate and track the driver’s face and facial features in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using this system, we present our results which show that using the Viola-Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose.

Transaction mining for fraud detection in ERP Systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Fraud detection in ERP systems using scenario matching

ERP systems generally implement controls to prevent certain common kinds of fraud. In addition however, there is an imperative need for detection of more sophisticated patterns of fraudulent activity as evidenced by the legal requirement for company audits and the common incidence of fraud. This paper describes the design and implementation of a framework for detecting patterns of fraudulent activity in ERP systems. We include the description of six fraud scenarios and the process of specifying and detecting the occurrence of those scenarios in ERP user log data using the prototype software which we have developed. The test results for detecting these scenarios in log data have been verified and confirm the success of our approach which can be generalized to ERP systems in general.

Lip detection for audio-visual speech recognition in-car environment

Acoustically, car cabins are extremely noisy and as a consequence audio-only, in-car voice recognition systems perform poorly. As the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem by using audio visual automatic speech recognition (AVASR). However, implementing AVASR requires a system being able to accurately locate and track the drivers face and lip area in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using the AVICAR [1] in-car database, we show that the Viola- Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose for audio-visual speech recognition system.

Analysis of detection performance in spectrum sensing optimisation for long sensing periods

Spectrum sensing optimisation techniques maximise the efficiency of spectrum sensing while satisfying a number of constraints. Many optimisation models consider the possibility of the primary user changing activity state during the secondary user's transmission period. However, most ignore the possibility of activity change during the sensing period. The observed primary user signal during sensing can exhibit a duty cycle which has been shown to severely degrade detection performance. This paper shows that (a) the probability of state change during sensing cannot be neglected and (b) the true detection performance obtained when incorporating the duty cycle of the primary user signal can deviate significantly from the results expected with the assumption of no such duty cycle.

Activity modelling in crowded environments : a soft decision approach

Probabilistic topic models have recently been used for activity analysis in video processing, due to their strong capacity to model both local activities and interactions in crowded scenes. In those applications, a video sequence is divided into a collection of uniform non-overlaping video clips, and the high dimensional continuous inputs are quantized into a bag of discrete visual words. The hard division of video clips, and hard assignment of visual words leads to problems when an activity is split over multiple clips, or the most appropriate visual word for quantization is unclear. In this paper, we propose a novel algorithm, which makes use of a soft histogram technique to compensate for the loss of information in the quantization process; and a soft cut technique in the temporal domain to overcome problems caused by separating an activity into two video clips. In the detection process, we also apply a soft decision strategy to detect unusual events.We show that the proposed soft decision approach outperforms its hard decision counterpart in both local and global activity modelling.

Approximate clone detection in repositories of business process models

Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.

The effect of exercise intensity on fat oxidation and non-exercise activity thermogenesis in overweight/obese men

It is frequently reported that the actual weight loss achieved through exercise interventions is less than theoretically expected. Amongst other compensatory adjustments that accompany exercise training (e.g., increases in resting metabolic rate and energy intake), a possible cause of the less than expected weight loss is a failure to produce a marked increase in total daily energy expenditure due to a compensatory reduction in non-exercise activity thermogenesis (NEAT). Therefore, there is a need to understand how behaviour is modified in response to exercise interventions. The proposed benefits of exercise training are numerous, including changes to fat oxidation. Given that a diminished capacity to oxidise fat could be a factor in the aetiology of obesity, an exercise training intensity that optimises fat oxidation in overweight/obese individuals would improve impaired fat oxidation, and potentially reduce health risks that are associated with obesity. To improve our understanding of the effectiveness of exercise for weight management, it is important to ensure exercise intensity is appropriately prescribed, and to identify and monitor potential compensatory behavioural changes consequent to exercise training. In line with the gaps in the literature, three studies were performed. The aim of Study 1 was to determine the effect of acute bouts of moderate- and high-intensity walking exercise on NEAT in overweight and obese men. Sixteen participants performed a single bout of either moderate-intensity walking exercise (MIE) or high-intensity walking exercise (HIE) on two separate occasions. The MIE consisted of walking for 60-min on a motorised treadmill at 6 km.h-1. The 60-min HIE session consisted of walking in 5-min intervals at 6 km.h-1 and 10% grade followed by 5-min at 0% grade. NEAT was assessed by accelerometer three days before, on the day of, and three days after the exercise sessions. There was no significant difference in NEAT vector magnitude (counts.min-1) between the pre-exercise period (days 1-3) and the exercise day (day 4) for either protocol. In addition, there was no change in NEAT during the three days following the MIE session, however NEAT increased by 16% on day 7 (post-exercise) compared with the exercise day (P = 0.32). During the post-exercise period following the HIE session, NEAT was increased by 25% on day 7 compared with the exercise day (P = 0.08), and by 30-33% compared with the pre-exercise period (day 1, day 2 and day 3); P = 0.03, 0.03, 0.02, respectively. To conclude, a single bout of either MIE or HIE did not alter NEAT on the exercise day or on the first two days following the exercise session. However, extending the monitoring of NEAT allowed the detection of a 48 hour delay in increased NEAT after performing HIE. A longer-term intervention is needed to determine the effect of accumulated exercise sessions over a week on NEAT. In Study 2, there were two primary aims. The first aim was to test the reliability of a discontinuous incremental exercise protocol (DISCON-FATmax) to identify the workload at which fat oxidation is maximised (FATmax). Ten overweight and obese sedentary male men (mean BMI of 29.5 ¡Ó 4.5 kg/m2 and mean age of 28.0 ¡Ó 5.3 y) participated in this study and performed two identical DISCON-FATmax tests one week apart. Each test consisted of alternate 4-min exercise and 2-min rest intervals on a cycle ergometer. The starting work load of 28 W was increased every 4-min using 14 W increments followed by 2-min rest intervals. When the respiratory exchange ratio was consistently >1.0, the workload was increased by 14 W every 2-min until volitional exhaustion. Fat oxidation was measured by indirect calorimetry. The mean FATmax, ƒtV O2peak, %ƒtV O2peak and %Wmax at which FATmax occurred during the two tests were 0.23 ¡Ó 0.09 and 0.18 ¡Ó 0.08 (g.min-1); 29.7 ¡Ó 7.8 and 28.3 ¡Ó 7.5 (ml.kg-1.min-1); 42.3 ¡Ó 7.2 and 42.6 ¡Ó 10.2 (%ƒtV O2max) and 36.4 ¡Ó 8.5 and 35.4 ¡Ó 10.9 (%), respectively. A paired-samples T-test revealed a significant difference in FATmax (g.min-1) between the tests (t = 2.65, P = 0.03). The mean difference in FATmax was 0.05 (g.min-1) with the 95% confidence interval ranging from 0.01 to 0.18. Paired-samples T-test, however, revealed no significant difference in the workloads (i.e. W) between the tests, t (9) = 0.70, P = 0.4. The intra-class correlation coefficient for FATmax (g.min-1) between the tests was 0.84 (95% confidence interval: 0.36-0.96, P < 0.01). However, Bland-Altman analysis revealed a large disagreement in FATmax (g.min-1) related to W between the two tests; 11 ¡Ó 14 (W) (4.1 ¡Ó 5.3 ƒtV O2peak (%)).These data demonstrate two important phenomena associated with exercise-induced substrate oxidation; firstly, that maximal fat oxidation derived from a discontinuous FATmax protocol differed statistically between repeated tests, and secondly, there was large variability in the workload corresponding with FATmax. The second aim of Study 2 was to test the validity of a DISCON-FATmax protocol by comparing maximal fat oxidation (g.min-1) determined by DISCON-FATmax with fat oxidation (g.min-1) during a continuous exercise protocol using a constant load (CONEX). Ten overweight and obese sedentary males (BMI = 29.5 ¡Ó 4.5 kg/m2; age = 28.0 ¡Ó 4.5 y) with a ƒtV O2max of 29.1 ¡Ó 7.5 ml.kg-1.min-1 performed a DISCON-FATmax test consisting of alternate 4-min exercise and 2-min rest intervals on a cycle ergometer. The 1-h CONEX protocol used the workload from the DISCON-FATmax to determine FATmax. The mean FATmax, ƒtV O2max, %ƒtV O2max and workload at which FATmax occurred during the DISCON-FATmax were 0.23 ¡Ó 0.09 (g.min-1); 29.1 ¡Ó 7.5 (ml.kg-1.min-1); 43.8 ¡Ó 7.3 (%ƒtV O2max) and 58.8 ¡Ó 19.6 (W), respectively. The mean fat oxidation during the 1-h CONEX protocol was 0.19 ¡Ó 0.07 (g.min-1). A paired-samples T-test revealed no significant difference in fat oxidation (g.min-1) between DISCON-FATmax and CONEX, t (9) = 1.85, P = 0.097 (two-tailed). There was also no significant correlation in fat oxidation between the DISCON-FATmax and CONEX (R=0.51, P = 0.14). Bland- Altman analysis revealed a large disagreement in fat oxidation between the DISCONFATmax and CONEX; the upper limit of agreement was 0.13 (g.min-1) and the lower limit of agreement was ¡V0.03 (g.min-1). These data suggest that the CONEX and DISCONFATmax protocols did not elicit different rates of fat oxidation (g.min-1). However, the individual variability in fat oxidation was large, particularly in the DISCON-FATmax test. Further research is needed to ascertain the validity of graded exercise tests for predicting fat oxidation during constant load exercise sessions. The aim of Study 3 was to compare the impact of two different intensities of four weeks of exercise training on fat oxidation, NEAT, and appetite in overweight and obese men. Using a cross-over design 11 participants (BMI = 29 ¡Ó 4 kg/m2; age = 27 ¡Ó 4 y) participated in a training study and were randomly assigned initially to: [1] a lowintensity (45%ƒtV O2max) exercise (LIT) or [2] a high-intensity interval (alternate 30 s at 90%ƒtV O2max followed by 30 s rest) exercise (HIIT) 40-min duration, three times a week. Participants completed four weeks of supervised training and between cross-over had a two week washout period. At baseline and the end of each exercise intervention,ƒtV O2max, fat oxidation, and NEAT were measured. Fat oxidation was determined during a standard 30-min continuous exercise bout at 45%ƒtV O2max. During the steady state exercise expired gases were measured intermittently for 5-min periods and HR was monitored continuously. In each training period, NEAT was measured for seven consecutive days using an accelerometer (RT3) the week before, at week 3 and the week after training. Subjective appetite sensations and food preferences were measured immediately before and after the first exercise session every week for four weeks during both LIT and HIIT. The mean fat oxidation rate during the standard continuous exercise bout at baseline for both LIT and HIIT was 0.14 ¡Ó 0.08 (g.min-1). After four weeks of exercise training, the mean fat oxidation was 0.178 ¡Ó 0.04 and 0.183 ¡Ó 0.04 g.min-1 for LIT and HIIT, respectively. The mean NEAT (counts.min-1) was 45 ¡Ó 18 at baseline, 55 ¡Ó 22 and 44 ¡Ó 16 during training, and 51 ¡Ó 14 and 50 ¡Ó 21 after training for LIT and HIIT, respectively. There was no significant difference in fat oxidation between LIT and HIIT. Moreover, although not statistically significant, there was some evidence to suggest that LIT and HIIT tend to increase fat oxidation during exercise at 45% ƒtV O2max (P = 0.14 and 0.08, respectively). The order of training treatment did not significantly influence changes in fat oxidation, NEAT, and appetite. NEAT (counts.min-1) was not significantly different in the week following training for either LIT or HIIT. Although not statistically significant (P = 0.08), NEAT was 20% lower during week 3 of exercise training in HIIT compared with LIT. Examination of appetite sensations revealed differences in the intensity of hunger, with higher ratings after LIT compared with HIIT. No differences were found in preferences for high-fat sweet foods between LIT and HIIT. In conclusion, the results of this thesis suggest that while fat oxidation during steady state exercise was not affected by the level of exercise intensity, there is strong evidence to suggest that intense exercise could have a debilitative effect on NEAT.

Practical physical activity measurement in youth : a review of contemporary approaches

Background: The accurate evaluation of physical activity levels amongst youth is critical for quantifying physical activity behaviors and evaluating the effect of physical activity interventions. The purpose of this review is to evaluate contemporary approaches to physical activity evaluation amongst youth. Data sources: The literature from a range of sources was reviewed and synthesized to provide an overview of contemporary approaches for measuring youth physical activity. Results: Five broad categories are described: self-report, instrumental movement detection, biological approaches, direct observation, and combined methods. Emerging technologies and priorities for future research are also identified. Conclusions: There will always be a trade-off between accuracy and available resources when choosing the best approach for measuring physical activity amongst youth. Unfortunately, cost and logistical challenges may prohibit the use of "gold standard" physical activity measurement approaches such as doubly labelled water. Other objective methods such as heart rate monitoring, accelerometry, pedometry, indirect calorimetry, or a combination of measures have the potential to better capture the duration and intensity of physical activity, while self-reported measures are useful for capturing the type and context of activity.

Activity analysis in complicated scenes using DFT coefficients of particle trajectories

Modelling activities in crowded scenes is very challenging as object tracking is not robust in complicated scenes and optical flow does not capture long range motion. We propose a novel approach to analyse activities in crowded scenes using a “bag of particle trajectories”. Particle trajectories are extracted from foreground regions within short video clips using particle video, which estimates long range motion in contrast to optical flow which is only concerned with inter-frame motion. Our applications include temporal video segmentation and anomaly detection, and we perform our evaluation on several real-world datasets containing complicated scenes. We show that our approaches achieve state-of-the-art performance for both tasks.

Spectrum sensing, detection and optimisation in cognitive radio for non-stationary primary user signals

Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

A longitudinal study of health-related quality of life, fatigue and physical activity in chronic kidney disease patients

This study assessed the health-related quality of life (HRQoL), fatigue and physical activity levels of 28 persons with chronic kidney disease (CKD) on initial administration of an erythropoietin stimulating agent, and at 3 months, 6 months and 12 months. The sample comprised of 15 females and 13 males whose ages ranged from 31 to 84 years. Physical activity was measured using the Human Activity Profile (HAP): Self-care, Personal/Household work, Entertainment/Social, Independent exercise. Quality of life was measured using the SF-36 which gives scores on physical health (physical functioning, role-physical, bodily pain and general health) and mental health (vitality, social functioning, role-emotional and emotional well-being). Fatigue was measured by the Fatigue Severity Scale (FSS). Across all time points the renal sample engaged in considerably less HAP personal/household work activities and entertainment/social activities compared to healthy adults. The normative sample engaged in three times more independent/exercise activities compared to renal patients. One-way Repeated measures ANOVAs indicated a significant change over time for SF-36 scales of role physical, vitality, emotional well-being and overall mental health. There was a significant difference in fatigue levels over time [F(3,11) = 3.78, p<.05]. Fatigue was highest at baseline and lowest at 6 months. The more breathlessness the CKD patient reported, the fewer activities undertaken and the greater the reported level of fatigue. There were no significant age differences over time for fatigue or physical activity. Age differences were only found for SF-36 mental health at 3 months (t=-2.41, df=14, p<.05). Those younger than 65 years had lower emotional well-being compared to those aged over 65. Males had poorer physical health compared to females at 12 months. There were no significant gender differences on mental health at any time point. In the management of chronic kidney disease, early detection of a person’s inability to engage in routine activities due to fatigue is necessary. Early detection would enable timely interventions to optimise HRQoL and independent exercise.