Artemisinin induced dormancy in Plasmodium falciparum : duration, recovery rates and implications in treatment failure

Background Despite the remarkable activity of artemisinin and its derivatives, monotherapy with these agents has been associated with high rates of recrudescence. The temporary arrest of the growth of ring-stage parasites (dormancy) after exposure to artemisinin drugs provides a plausible explanation for this phenomenon. Methods Ring-stage parasites of several Plasmodium falciparum lines were exposed to different doses of dihydroartemisinin (DHA) alone or in combination with mefloquine. For each regime, the proportion of recovering parasites was determined daily for 20 days. Results Parasite development was abruptly arrested after a single exposure to DHA, with some parasites being dormant for up to 20 days. Approximately 50% of dormant parasites recovered to resume growth within the first 9 days. The overall proportion of parasites recovering was dose dependent, with recovery rates ranging from 0.044% to 1.313%. Repeated treatment with DHA or with DHA in combination with mefloquine led to a delay in recovery and an ∼10-fold reduction in total recovery. Strains with different genetic backgrounds appeared to vary in their capacity to recover. Conclusions These results imply that artemisinin-induced arrest of growth occurs readily in laboratory-treated parasites and may be a key factor in P. falciparum malaria treatment failure.

Simultaneous localization and planning on multiple map hypotheses

This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

Integrating the impact of climate into event based failure models for water pipes

This paper presents an event-based failure model to predict the number of failures that occur in water distribution assets. Often, such models have been based on analysis of historical failure data combined with pipe characteristics and environmental conditions. In this paper weather data have been added to the model to take into account the commonly observed seasonal variation of the failure rate. The theoretical basis of existing logistic regression models is briefly described in this paper, along with the refinements made to the model for inclusion of seasonal variation of weather. The performance of these refinements is tested using data from two Australian water authorities.

Seasonal factors influencing the failure of buried water reticulation pipes

While the use of environmental factors in the analysis and prediction of failures of buried reticulation pipes in cold environments has been the focus of extensive work, the same cannot be said for failures occurring on pipes in other (non-freezing) environments. A novel analysis of pipe failures in such an environment is the subject of this paper. An exploratory statistical analysis was undertaken, identifying a peak in failure rates during mid to late summer. This peak was found to correspond to a peak in the rate of circumferential failures, whilst the rate of longitudinal failures remained constant. Investigation into the effect of climate on failure rates revealed that the peak in failure rates occurs due to differential soil movement as the result of shrinkage in expansive soils.

Understanding how the Australian climate can affect pipe failure

This paper details a statistical analysis of historical failure data, which focuses on determining the manner in which local climate affects pipe failure rates. It was found that seasonality exists in the data, indicating an affect of local climate on failure rate. Significant variation in failure rates was seen between the months of December and May, especially in February/March, whilst limited variations were seen in other months of the year. Further analysis found that failure rates were strongly correlated with minimum antecedent precipitation index and net evaporation and that climate affected failure rate by influencing soil moisture content. Interaction affects between static attributes of the pipe-environment system and local climate were also investigated.

Fracture load for short versus standard cemented hip stems : an experimental in vitro study

Introduction: In an attempt to reduce stress shielding in the proximal femur multiple new shorter stem design have become available. We investigated the load to fracture of a new polished tapered cemented short stem in comparison to the conventional polished tapered Exeter stem. Method: A total of forty-two stems, twenty-one short stems and twenty-one conventional stems both with three different offsets were cemented in a composite sawbone model and loaded to fracture. Results: study showed that femurs will break at a significantly lower load to failure with a shorter compared to conventional length Exeter stem. Conclusion: This Both standard and short stem design are safe to use as the torque to failure is 7–10 times as much as the torques seen in activities of daily living.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Effects of driver familiarity and prolonged or intermittent right-side failure on level crossing safety

This paper investigates the adverse effects of familiarity and human factors issues associated with the reliability of low-cost warning devices at level crossings. The driving simulator study featured a repetitive, low workload, monotonous driving task in which there were no failures of the level crossing (control) or prolonged or intermittent right-side failures (where the device reverts to a safe failure mode). The results of the experiment provided mixed support for the familiarity hypothesis. Four of the 23 participants collided with the train when it first appeared on trial 10 but safety margins increased from the first train to the next presentation of a train (trial 12). Contrary to expectations, the safety margins decreased with repeated right-side failure only for the intermittent condition. The limited head movement data showed that participants in the prolonged failure condition were more likely to turn their head to check for trains in the right-side failure trials than in earlier trials where there was no signal and no train. Few control participants turned their head to check for trains when no signal was presented. This research highlights the need to consider repetitive tasks and workload in experimental design and accident investigation at railway level crossings.

Data fusion and tracking with multiple UAVs

This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

The topography of multiple drug use among adolescent Australians : findings from the National Drug Strategy Household Survey

Introduction and aims: Despite evidence that many Australian adolescents have considerable experience with various drug types, little is known about the extent to which adolescents use multiple substances. The aim of this study was to examine the degree of clustering of drug types within individuals, and the extent to which demographic and psychosocial predictors are related to cluster membership. Design and method: A sample of 1402 adolescents aged 12-17. years were extracted from the Australian 2007 National Drug Strategy Household Survey. Extracted data included lifetime use of 10 substances, gender, psychological distress, physical health, perceived peer substance use, socioeconomic disadvantage, and regionality. Latent class analysis was used to determine clusters, and multinomial logistic regression employed to examine predictors of cluster membership. Result: There were 3 latent classes. The great majority (79.6%) of adolescents used alcohol only, 18.3% were limited range multidrug users (encompassing alcohol, tobacco, and marijuana), and 2% were extended range multidrug users. Perceived peer drug use and psychological distress predicted limited and extended multiple drug use. Psychological distress was a more significant predictor of extended multidrug use compared to limited multidrug use. Discussion and conclusion: In the Australian school-based prevention setting, a very strong focus on alcohol use and the linkages between alcohol, tobacco and marijuana are warranted. Psychological distress may be an important target for screening and early intervention for adolescents who use multiple drugs.

Multiple criteria-based real-time decision making by autonomous city vehicles

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.