Peginterferon plus ribavirin and sustained virological response rate in HCV-related advanced fibrosis: a real life study

Background: Tolerance and response to antiviral HCV treatment is poor in advanced fibrosis. The aim of this study was to assess SVR rate and its predictive factors in HCV advanced fibrosis patients treated in real life with full dose PEG-IFN plus RBV and to evaluate the adverse events related to treatment. Methods: A multicentric, retrospective study was conducted at six university hospitals. METAVIR F3 and F4 HCV monoinfected patients who were treated with PEG-IFN and RBV had their data analyzed. A stepwise logistic regression analysis was performed to identify the variables independently related to SVR. Adverse events were recorded during treatment. Results: 308 patients were included, 75% genotype 1 and 23% genotype 3. METAVIR F3 was present in 39% and F4 in 61% of patients. The median Child Pugh score for F4 patients was 5 (5–9). The global SVR rate was 34%, 11% were relapsers and 55% were nonresponders. SVR rates were similar between patients treated with PEG-IFN alfa 2a or alfa 2b (p = 0.24). SVR rates according to Child–Pugh score were 26% (Child A) and 18% (Child B). The independent factors related to SVR in F4 patients were genotype 3, RVR and fewer Child Pugh score points. Treatment interruption occurred in 31% patients and death occurred in 1.9%, all with liver cirrhosis. Conclusion: Treatment of HCV in patients with advanced fibrosis should not be postponed. However, a very careful evaluation of cirrhotic patients must be performed before treatment is indicated and careful monitoring is required during treatment.

Exercise domain profile through pulmonary gas exchange response during kendo practice by men

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power

Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.

Long-range, high bit-rate secure key distribution link utilizing Raman Ultra-long fiber laser (UFL)

The distribution of the secret key is the weakest link of many data encryption systems. Quantum key distribution (QKD) schemes provide attractive solutions [1], however their implementation remains challenging and their range and bit-rate are limited. Moreover, practical QKD systems, employ real-life components and are, therefore, vulnerable to diverse attack schemes [2]. Ultra-Long fiber lasers (UFLs) have been drawing much attention recently because of their fundamentally different properties compared to conventional lasers as well as their unique applications [3]. Here, we demonstrate a 100Bps, practically secure key distribution, over a 500km link, employing Raman gain UFL. Fig. 1(a) depicts a schematic of the UFL system. Each user has an identical set of two wavelength selective mirrors centered at l0 and l 1. In order to exchange a key-bit, each user independently choose one of these mirrors and introduces it as a laser reflector at their end. If both users choose identical mirrors, a clear signal develops and the bits in these cases are discarded. However if they choose complementary mirrors, (1, 0 or 0, 1 states), the UFL remains below lasing threshold and no signal evolves. In these cases, an eavesdropper can only detect noise and is unable to determine the mirror choice of the users, where the choice of mirrors represent a single key bit (e.g. Alice's choice of mirror is the key-bit). These bits are kept and added to the key. The absence of signal in the secure states faxilitates fast measurements to distinguish between the non-secure and the secure states and to determine the key-bit in the later case, Sequentially reapeating the single bit exchange protocol generate the entire keys of any desirable length. © 2013 IEEE.

Real effective exchange rates for 178 countries: A new database

We use data on exchange rates and consumer price indices and the weighting matrix derived by Bayoumi, Lee and Jaewoo (2006) to calculate consumer price index-based REER. The main novelties of our database are that (1) it includes data for 178 countries –many more than in any other publicly available database– plus an external REER for the euro area, using a consistent methodology; (2) it includes up-to-date REER values, such as data for January 2012; and (3) it is relatively easy to calculate REER against any arbitrary group of countries. The annual database is complete for 172 countries and the euro area for 1992-2011 and data is available for six other countries for a shorter period. For several countries annual data is available for earlier years as well, eg data is available for 67 countries from 1960. The monthly database is complete for 138 countries for January 1995-January 2012, and data is also available for 15 other countries for a shorter period. The indicators calculated by us are freely downloadable and will be irregularly updated.

Competitiveness factors : a study of the real estate market in China

The execution of 'macro-adjustment' policies by the central government to cool down the overheated real estate market in the past few years has created an unfavourable operating environment for real estate developers in Mainland China. Developers need to rethink their business model and create a new form of competitive advantage in order to survive. Despite this, research into the factors that influence the competitiveness of the real estate market in China has been limited. Therefore, a survey of 58 real estate actitioners, experts and academics in China was conducted to probe opinion on the factors that influence competitiveness in real estate firms in China. Survey results suggest that the developer's financial competency, market coverage and management competencies are vital to its competitiveness. Findings also highlight the importance of industry ecognition/award, share in different types of property sales/development projects, profit after tax, growth rate of their securities price, and diversification of R&D in reflecting the competitiveness of real estate developers in China. The findings provide an insight into the factors that influence competitiveness in China's real estate market and also assist practitioners to formulate competitiveness improvement strategies.

Scene invariant crowd counting for real-time surveillance

Automated crowd counting allows excessive crowding to be detected immediately, without the need for constant human surveillance. Current crowd counting systems are location specific, and for these systems to function properly they must be trained on a large amount of data specific to the target location. As such, configuring multiple systems to use is a tedious and time consuming exercise. We propose a scene invariant crowd counting system which can easily be deployed at a different location to where it was trained. This is achieved using a global scaling factor to relate crowd sizes from one scene to another. We demonstrate that a crowd counting system trained at one viewpoint can achieve a correct classification rate of 90% at a different viewpoint.

Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species.

Real-time performance modelling of a sustained attention to response task

Vigilance declines when exposed to highly predictable and uneventful tasks. Monotonous tasks provide little cognitive and motor stimulation and contribute to human errors. This paper aims to model and detect vigilance decline in real time through participant’s reaction times during a monotonous task. A lab-based experiment adapting the Sustained Attention to Response Task (SART) is conducted to quantify the effect of monotony on overall performance. Then relevant parameters are used to build a model detecting hypovigilance throughout the experiment. The accuracy of different mathematical models are compared to detect in real-time – minute by minute - the lapses in vigilance during the task. We show that monotonous tasks can lead to an average decline in performance of 45%. Furthermore, vigilance modelling enables to detect vigilance decline through reaction times with an accuracy of 72% and a 29% false alarm rate. Bayesian models are identified as a better model to detect lapses in vigilance as compared to Neural Networks and Generalised Linear Mixed Models. This modelling could be used as a framework to detect vigilance decline of any human performing monotonous tasks.

Uncertainties that matter : risk, response-ability, ethics and the moment of exchange in Live Art

This article examines the moment of exchange between artist, audience and culture in Live Art. Drawing on historical and contemporary examples, including examples from the Exist in 08 Live Art Event in Brisbane, Australia, in October 2008, it argues that Live Art - be it body art, activist art, site-specific performance, or other sorts of performative intervention in the public sphere - is characterised by a common set of claims about activating audiences, asking them to reflect on cultural norms challenged in the work. Live Art presents risky actions, in a context that blurs the boundaries between art and reality, to position audients as ‘witnesses’ who are personally implicated in, and responsible for, the actions unfolding before them. This article problematises assumptions about the way the uncertainties embedded in the Live Art encounter contribute to its deconstructive agenda. It uses the ethical theory of Emmanuel Levinas, Hans-Thies Lehmann and Dwight Conquergood to examine the mechanics of reductive, culturally-recuperative readings that can limit the efficacy of the Live Art encounter. It argues that, though ‘witnessing’ in Live Art depends on a relation to the real - real people, taking real risks, in real places - if it fails to foreground theatrical frame it is difficult for audients to develop the dual consciousness of the content, and their complicity in that content, that is the starting point for reflexivity, and response-ability, in the ethical encounter.

Network protocols and predictive control strategies for distributed real-time control applications

A trend in design and implementation of modern industrial automation systems is to integrate computing, communication and control into a unified framework at different levels of machine/factory operations and information processing. These distributed control systems are referred to as networked control systems (NCSs). They are composed of sensors, actuators, and controllers interconnected over communication networks. As most of communication networks are not designed for NCS applications, the communication requirements of NCSs may be not satisfied. For example, traditional control systems require the data to be accurate, timely and lossless. However, because of random transmission delays and packet losses, the control performance of a control system may be badly deteriorated, and the control system rendered unstable. The main challenge of NCS design is to both maintain and improve stable control performance of an NCS. To achieve this, communication and control methodologies have to be designed. In recent decades, Ethernet and 802.11 networks have been introduced in control networks and have even replaced traditional fieldbus productions in some real-time control applications, because of their high bandwidth and good interoperability. As Ethernet and 802.11 networks are not designed for distributed control applications, two aspects of NCS research need to be addressed to make these communication networks suitable for control systems in industrial environments. From the perspective of networking, communication protocols need to be designed to satisfy communication requirements for NCSs such as real-time communication and high-precision clock consistency requirements. From the perspective of control, methods to compensate for network-induced delays and packet losses are important for NCS design. To make Ethernet-based and 802.11 networks suitable for distributed control applications, this thesis develops a high-precision relative clock synchronisation protocol and an analytical model for analysing the real-time performance of 802.11 networks, and designs a new predictive compensation method. Firstly, a hybrid NCS simulation environment based on the NS-2 simulator is designed and implemented. Secondly, a high-precision relative clock synchronization protocol is designed and implemented. Thirdly, transmission delays in 802.11 networks for soft-real-time control applications are modeled by use of a Markov chain model in which real-time Quality-of- Service parameters are analysed under a periodic traffic pattern. By using a Markov chain model, we can accurately model the tradeoff between real-time performance and throughput performance. Furthermore, a cross-layer optimisation scheme, featuring application-layer flow rate adaptation, is designed to achieve the tradeoff between certain real-time and throughput performance characteristics in a typical NCS scenario with wireless local area network. Fourthly, as a co-design approach for both a network and a controller, a new predictive compensation method for variable delay and packet loss in NCSs is designed, where simultaneous end-to-end delays and packet losses during packet transmissions from sensors to actuators is tackled. The effectiveness of the proposed predictive compensation approach is demonstrated using our hybrid NCS simulation environment.

Real-time evaluation of driver’s alertness on highways

Suburbanisation has been internationally a major phenomenon in the last decades. Suburb-to-suburb routes are nowadays the most widespread road journeys; and this resulted in an increment of distances travelled, particularly on faster suburban highways. The design of highways tends to over-simplify the driving task and this can result in decreased alertness. Driving behaviour is consequently impaired and drivers are then more likely to be involved in road crashes. This is particularly dangerous on highways where the speed limit is high. While effective countermeasures to this decrement in alertness do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behaviour in real-time. The aim of this study is to evaluate in real-time the level of alertness of the driver through surrogate measures that can be collected from in-vehicle sensors. Slow EEG activity is used as a reference to evaluate driver's alertness. Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). Four different types of highways (driving scenario of 40 minutes each) are implemented through the variation of the road design (amount of curves and hills) and the roadside environment (amount of buildings and traffic). We show with Neural Networks that reduced alertness can be detected in real-time with an accuracy of 92% using lane positioning, steering wheel movement, head rotation, blink frequency, heart rate variability and skin conductance level. Such results show that it is possible to assess driver's alertness with surrogate measures. Such methodology could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring in real-time drivers' behaviour on highways, and therefore it could result in improved road safety.

Facilitating learning in a real time strategy computer game

The aim of this project was to implement a just-in-time hints help system into a real time strategy (RTS) computer game that would deliver information to the user at the time that it would be of the most benefit. The goal of this help system is to improve the user’s learning in terms of their rate of learning, retention and avoidance of stagnation. The first stage of this project was implementing a computer game to incorporate four different types of skill that the user must acquire, namely motor, perceptual, declarative knowledge and strategic. Subsequently, the just-in-time hints help system was incorporated into the game to assess the user’s knowledge and deliver hints accordingly. The final stage of the project was to test the effectiveness of this help system by conducting two phases of testing. The goal of this testing was to demonstrate an increase in the user’s assessment of the helpfulness of the system from phase one to phase two. The results of this testing showed that there was no significant difference in the user’s responses in the two phases. However, when the results were analysed with respect to several categories of hints that were identified, it became apparent that patterns in the data were beginning to emerge. The conclusions of the project were that further testing with a larger sample size would be required to provide more reliable results and that factors such as the user’s skill level and different types of goals should be taken into account.