Response to “Comment on ‘Indications of energetic consequences of decoherence at short times for scattering from open quantum systems’” [AIP Advances 1, 049101 (2011)]

The Comment by Mayers and Reiter criticizes our work on two counts. Firstly, it is claimed that the quantum decoherence effects that we report in consequence of our experimental analysis of neutron Compton scattering from H in gaseous H2 are not, as we maintain, outside the framework of conventional neutron scatteringtheory. Secondly, it is claimed that we did not really observe such effects, owing to a faulty analysis of the experimental data, which are claimed to be in agreement with conventional theory. We focus in this response on the critical issue of the reliability of our experimental results and analysis. Using the same standard Vesuvio instrument programs used by Mayers et al., we show that, if the experimental results for H in gaseous H2 are in agreement with conventional theory, then those for D in gaseous D2 obtained in the same way cannot be, and vice-versa. We expose a flaw in the calibration methodology used by Mayers et al. that leads to the present disagreement over the behaviour of H, namely the ad hoc adjustment of the measured H peak positions in TOF during the calibration of Vesuvio so that agreement is obtained with the expectation of conventional theory. We briefly address the question of the necessity to apply the theory of open quantum systems.

Mindfulness-meditation on the move : implementation of an ACT-based mindfulness practice intervention and training within a University Dance program

As part of the introduction of a broader dance medicine and science related health and wellbeing program, a 9 week mindfulness-meditation ACT-based program was delivered to all students undertaking full-time University dance training (N = 106). The aim of the program was to assist students in the further development of performance psychology skills that could be applied in both performance and non-performance settings. Participant groups were comprised of both male (N = 12) and female (N = 94) students from across all three year levels of two undergraduate dance courses, divided into three groups by mixed year levels due to timetable scheduling requirements. Pre- and post-testing was undertaken utilising the Mindful Attention Awareness Scale (MAAS-15), a uni-dimensional measure of mindfulness, in addition to qualitative questions checking the current level of awareness and understanding of mindfulness practice and its application. Weekly sessions were conducted by qualified sport and exercise psychologists and covered key practices such as: Mindfulness of Body, Mindfulness of Breathing, Mindfulness of Sounds, ACT-based and general Imagery exercises, Developing Open Awareness, Mindfulness of Emotions, and Developing Inner Stillness. Students were required to maintain a reflective journal that was utilised at the end of each weekly session, in addition to completion of a mid-Semester reflective debrief. Teaching staff additionally attended the weekly sessions and linked the mindfulness practice learnings into the student’s practical dance and academic classes where appropriate. Anecdotal feedback indicates that participation in the mindfulness-meditation sessions and the development of these mental skills has resulted in positive performance and personal outcomes. Observations collated from staff and students, results from the data collection phases and recommendations regarding future applications within dance training settings will be discussed within the presentation.

Relevation! : an open source system for information retrieval relevance assessment

Relevation! is a system for performing relevance judgements for information retrieval evaluation. Relevation! is web-based, fully configurable and expandable; it allows researchers to effectively collect assessments and additional qualitative data. The system is easily deployed allowing assessors to smoothly perform their relevance judging tasks, even remotely. Relevation! is available as an open source project at: http://ielab.github.io/relevation.

STI-GMaS : an open-source environment for simulation of sexually-transmitted infections

Background Sexually-transmitted pathogens often have severe reproductive health implications if treatment is delayed or absent, especially in females. The complex processes of disease progression, namely replication and ascension of the infection through the genital tract, span both extracellular and intracellular physiological scales, and in females can vary over the distinct phases of the menstrual cycle. The complexity of these processes, coupled with the common impossibility of obtaining comprehensive and sequential clinical data from individual human patients, makes mathematical and computational modelling valuable tools in developing our understanding of the infection, with a view to identifying new interventions. While many within-host models of sexually-transmitted infections (STIs) are available in existing literature, these models are difficult to deploy in clinical/experimental settings since simulations often require complex computational approaches. Results We present STI-GMaS (Sexually-Transmitted Infections – Graphical Modelling and Simulation), an environment for simulation of STI models, with a view to stimulating the uptake of these models within the laboratory or clinic. The software currently focuses upon the representative case-study of Chlamydia trachomatis, the most common sexually-transmitted bacterial pathogen of humans. Here, we demonstrate the use of a hybrid PDE–cellular automata model for simulation of a hypothetical Chlamydia vaccination, demonstrating the effect of a vaccine-induced antibody in preventing the infection from ascending to above the cervix. This example illustrates the ease with which existing models can be adapted to describe new studies, and its careful parameterisation within STI-GMaS facilitates future tuning to experimental data as they arise. Conclusions STI-GMaS represents the first software designed explicitly for in-silico simulation of STI models by non-theoreticians, thus presenting a novel route to bridging the gap between computational and clinical/experimental disciplines. With the propensity for model reuse and extension, there is much scope within STI-GMaS to allow clinical and experimental studies to inform model inputs and drive future model development. Many of the modelling paradigms and software design principles deployed to date transfer readily to other STIs, both bacterial and viral; forthcoming releases of STI-GMaS will extend the software to incorporate a more diverse range of infections.

Keyword field-free conjunctive keyword searches on encrypted data and extension for dynamic groups

We consider the following problem: a user stores encrypted documents on an untrusted server, and wishes to retrieve all documents containing some keywords without any loss of data confidentiality. Conjunctive keyword searches on encrypted data have been studied by numerous researchers over the past few years, and all existing schemes use keyword fields as compulsory information. This however is impractical for many applications. In this paper, we propose a scheme of keyword field-free conjunctive keyword searches on encrypted data, which affirmatively answers an open problem asked by Golle et al. at ACNS 2004. Furthermore, the proposed scheme is extended to the dynamic group setting. Security analysis of our constructions is given in the paper.

Senataxin plays an essential role with DNA damage response proteins in meiotic recombination and gene silencing

Senataxin, mutated in the human genetic disorder ataxia with oculomotor apraxia type 2 (AOA2), plays an important role in maintaining genome integrity by coordination of transcription, DNA replication, and the DNA damage response. We demonstrate that senataxin is essential for spermatogenesis and that it functions at two stages in meiosis during crossing-over in homologous recombination and in meiotic sex chromosome inactivation (MSCI). Disruption of the Setx gene caused persistence of DNA double-strand breaks, a defect in disassembly of Rad51 filaments, accumulation of DNA:RNA hybrids (R-loops), and ultimately a failure of crossing-over. Senataxin localised to the XY body in a Brca1-dependent manner, and in its absence there was incomplete localisation of DNA damage response proteins to the XY chromosomes and ATR was retained on the axial elements of these chromosomes, failing to diffuse out into chromatin. Furthermore persistence of RNA polymerase II activity, altered ubH2A distribution, and abnormal XY-linked gene expression in Setx⁻/⁻ revealed an essential role for senataxin in MSCI. These data support key roles for senataxin in coordinating meiotic crossing-over with transcription and in gene silencing to protect the integrity of the genome.

Artemisinin resistance in Plasmodium falciparum : a process linked to dormancy?

Artemisinin (ART) based combination therapy (ACT) is used as the first line treatment of uncomplicated falciparum malaria in over 100 countries and is the cornerstone of malaria control and elimination programs in these areas. However, despite the high potency and rapid parasite killing action of ART derivatives there is a high rate of recrudescence associated with ART monotherapy and recrudescence is not uncommon even when ACT is used. Compounding this problem are reports that some parasites in Cambodia, a known foci of drug resistance, have decreased in vivo sensitivity to ART. This raises serious concerns for the development of ART resistance in the field even though no major phenotypic and genotypic changes have yet been identified in these parasites. In this article we review available data on the characteristics of ART, its effects on Plasmodium falciparum parasites and present a hypothesis to explain the high rate of recrudescence associated with this potent class of drugs and the current enigma surrounding ART resistance.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

miRPlant : an integrated tool for identification of plant miRNA from RNA sequencing data

Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.

Synthesizing form and data : developing practices for student engagement and learning

We explore the relationship between form and data as a design agenda and learning strategy for novice visual information designers. Our students are university seniors in digital, visual design but novices to information design, manipulation and interpretation. We describe design strategies developed to scaffold sophisticated aesthetic and conceptual engagement despite limited understanding of the domain of designing with information. These revolve around an open-ended design project where students created a physical design from data of their choosing and research. The accompanying learning strategies concern this relationship between data and form to investigate it materially, formally and through ideation. Exemplifying student works that cross media and design domains are described.

Meta-analysis of microarray data identifies GAS6 expression as an independent predictor of poor survival in ovarian cancer

Seeking new biomarkers for epithelial ovarian cancer, the fifth most common cause of death from all cancers in women and the leading cause of death from gynaecological malignancies, we performed a meta-analysis of three independent studies and compared the results in regard to clinicopathological parameters. This analysis revealed that GAS6 was highly expressed in ovarian cancer and therefore was selected as our candidate of choice. GAS6 encodes a secreted protein involved in physiological processes including cell proliferation, chemotaxis, and cell survival. We performed immunohistochemistry on various ovarian cancer tissues and found that GAS6 expression was elevated in tumour tissue samples compared to healthy control samples (P < 0.0001). In addition, GAS6 expression was also higher in tumours from patients with residual disease compared to those without. Our data propose GAS6 as an independent predictor of poor survival, suggesting GAS6, both on the mRNA and on the protein level, as a potential biomarker for ovarian cancer. In clinical practice, the staining of a tumour biopsy for GAS6 may be useful to assess cancer prognosis and/or to monitor disease progression.

A cost-effectiveness analysis of a telephone-linked care intervention for individuals with Type 2 diabetes

AIM: To assess the cost-effectiveness of an automated telephone-linked care intervention, Australian TLC Diabetes, delivered over 6 months to patients with established Type 2 diabetes mellitus and high glycated haemoglobin level, compared to usual care. METHODS: A Markov model was designed to synthesize data from a randomized controlled trial of TLC Diabetes (n=120) and other published evidence. The 5-year model consisted of three health states related to glycaemic control: 'sub-optimal' HbA1c ≥58mmol/mol (7.5%); 'average' ≥48-57mmol/mol (6.5-7.4%) and 'optimal' <48mmol/mol (6.5%) and a fourth state 'all-cause death'. Key outcomes of the model include discounted health system costs and quality-adjusted life years (QALYS) using SF-6D utility weights. Univariate and probabilistic sensitivity analyses were undertaken. RESULTS: Annual medication costs for the intervention group were lower than usual care [Intervention: £1076 (95%CI: £947, £1206) versus usual care £1271 (95%CI: £1115, £1428) p=0.052]. The estimated mean cost for intervention group participants over five years, including the intervention cost, was £17,152 versus £17,835 for the usual care group. The corresponding mean QALYs were 3.381 (SD 0.40) for the intervention group and 3.377 (SD 0.41) for the usual care group. Results were sensitive to the model duration, utility values and medication costs. CONCLUSION: The Australian TLC Diabetes intervention was a low-cost investment for individuals with established diabetes and may result in medication cost-savings to the health system. Although QALYs were similar between groups, other benefits arising from the intervention should also be considered when determining the overall value of this strategy.

Piecing the puzzle together : enhancing the quality of road trauma surveillance through linkage of police and health data

This program of research linked police and health data collections to investigate the potential benefits for road safety in terms of enhancing the quality of data. This research has important implications for road safety because, although police collected data has historically underpinned efforts in the area, it is known that many road crashes are not reported to police and that these data lack specific injury severity information. This research shows that data linkage provides a more accurate quantification of the severity and prevalence of road crash injuries which is essential for: prioritising funding; targeting interventions; and estimating the burden and cost of road trauma.

An open pit multistage mine production scheduling model for drilling, blasting and excavating operations

This paper proposes a new multi-resource multi-stage scheduling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.