Large scale participatory acoustic sensor data analysis : tools and reputation models to enhance effectiveness

Acoustic sensors play an important role in augmenting the traditional biodiversity monitoring activities carried out by ecologists and conservation biologists. With this ability however comes the burden of analysing large volumes of complex acoustic data. Given the complexity of acoustic sensor data, fully automated analysis for a wide range of species is still a significant challenge. This research investigates the use of citizen scientists to analyse large volumes of environmental acoustic data in order to identify bird species. Specifically, it investigates ways in which the efficiency of a user can be improved through the use of species identification tools and the use of reputation models to predict the accuracy of users with unidentified skill levels. Initial experimental results are reported.

Understanding the legal implications of data sharing, access and reuse in the Australian research landscape

Researchers are increasingly involved in data-intensive research projects that cut across geographic and disciplinary borders. Quality research now often involves virtual communities of researchers participating in large-scale web-based collaborations, opening their earlystage research to the research community in order to encourage broader participation and accelerate discoveries. The result of such large-scale collaborations has been the production of ever-increasing amounts of data. In short, we are in the midst of a data deluge. Accompanying these developments has been a growing recognition that if the benefits of enhanced access to research are to be realised, it will be necessary to develop the systems and services that enable data to be managed and secured. It has also become apparent that to achieve seamless access to data it is necessary not only to adopt appropriate technical standards, practices and architecture, but also to develop legal frameworks that facilitate access to and use of research data. This chapter provides an overview of the current research landscape in Australia as it relates to the collection, management and sharing of research data. The chapter then explains the Australian legal regimes relevant to data, including copyright, patent, privacy, confidentiality and contract law. Finally, this chapter proposes the infrastructure elements that are required for the proper management of legal interests, ownership rights and rights to access and use data collected or generated by research projects.

Corneal markers of diabetic neuropathy

Diabetic neuropathy is a significant clinical problem that currently has no effective therapy, and in advanced cases, leads to foot ulceration and lower limb amputation. The accurate detection, characterization and quantification of this condition are important in order to define at-risk patients, anticipate deterioration, monitor progression, and assess new therapies This review evaluates novel corneal methods of assessing diabetic neuropathy. Two new non-invasive corneal markers have emerged, and in cross-sectional studies have demonstrated their ability to stratify the severity of this disease. Corneal confocal microscopy allows quantification of corneal nerve parameters and non-contact corneal esthesiometry, the functional correlate of corneal structure, assesses the sensitivity of the cornea. Both these techniques are quick to perform, produce little or no discomfort for the patient, and are suitable for clinical settings. Each has advantages and disadvantages over traditional techniques for assessing diabetic neuropathy. Application of these new corneal markers for longitudinal evaluation of diabetic neuropathy has the potential to reduce dependence on more invasive, costly, and time-consuming assessments, such as skin biopsy.

Reliability of ultrasonographic measurement of the architecture of the vastus lateralis and gastrocnemius medialis muscles in older adults

Objective To determine the test-retest reliability of measurements of thickness, fascicle length (Lf) and pennation angle (θ) of the vastus lateralis (VL) and gastrocnemius medialis (GM) muscles in older adults. Participants Twenty-one healthy older adults (11 men and ten women; average age 68·1 ± 5·2 years) participated in this study. Methods Ultrasound images (probe frequency 10 MHz) of the VL at two sites (VL site 1 and 2) were obtained with participants seated with knee at 90º flexion. For GM measures, participants lay prone with ankle fixed at 15º dorsiflexion. Measures were taken on two separate occasions, 7 days apart (T1 and T2). Results The ICCs (95% CI) were: VL site 1 thickness = 0·96(0·90–0·98); VL site 2 thickness = 0·96(0·90–0·98), VL θ = 0·87(0·68–0·95), VL Lf = 0·80(0·50–0·92), GM thickness = 0·97(0·92–0·99), GM θ = 0·85(0·62–0·94) and GM Lf =0·90(0·75–0·96). The 95% ratio limits of agreement (LOAs) for all measures, calculated by multiplying the standard deviation of the ratio of the results between T1 and T2 by 1·96, ranged from 10·59 to 38·01%. Conclusion The ability of these tests to determine a real change in VL and GM muscle architecture is good on a group level but problematic on an individual level as the relatively large 95% ratio LOAs in the current study may encompass the changes in architecture observed in other training studies. Therefore, the current findings suggest that B-mode ultrasonography can be used with confidence by researchers when investigating changes in muscle architecture in groups of older adults, but its use is limited in showing changes in individuals over time.

The Biodex Isokinetic Dynamometer for knee strength assessment in children : advantages and limitations

Objective: To critically appraise the Biodex System 4 isokinetic dynamometer for strength assessment of children. Methods: Appraisal was based on experiences from two independent laboratories involving testing of 213 children. Issues were recorded and the manufacturer was consulted regarding appropriate solutions. Results: The dynamometer had insufficient height adjustment for alignment of the knee for some children, requiring the construction of padding to better fit the child within the dynamometer. Potential for entrapment of the non-testing leg was evident in the passive and eccentric modes and a leg bracket restraint was constructed. Automated gravity correction did not operate when protocols were linked or data was exported to an external device. Conclusions: Limitations were noted, some of which were applicable to knee strength testing in general and others which were specific to use with children. However, most of these obstacles could be overcome, making the Biodex System 4 suitable for assessment of knee strength in children.

Interactive processes link the multiple symptoms of fatigue in sport competition

Muscle physiologists often describe fatigue simply as a decline of muscle force and infer this causes an athlete to slow down. In contrast, exercise scientists describe fatigue during sport competition more holistically as an exercise-induced impairment of performance. The aim of this review is to reconcile the different views by evaluating the many performance symptoms/measures and mechanisms of fatigue. We describe how fatigue is assessed with muscle, exercise or competition performance measures. Muscle performance (single muscle test measures) declines due to peripheral fatigue (reduced muscle cell force) and/or central fatigue (reduced motor drive from the CNS). Peak muscle force seldom falls by >30% during sport but is often exacerbated during electrical stimulation and laboratory exercise tasks. Exercise performance (whole-body exercise test measures) reveals impaired physical/technical abilities and subjective fatigue sensations. Exercise intensity is initially sustained by recruitment of new motor units and help from synergistic muscles before it declines. Technique/motor skill execution deviates as exercise proceeds to maintain outcomes before they deteriorate, e.g. reduced accuracy or velocity. The sensation of fatigue incorporates an elevated rating of perceived exertion (RPE) during submaximal tasks, due to a combination of peripheral and higher CNS inputs. Competition performance (sport symptoms) is affected more by decision-making and psychological aspects, since there are opponents and a greater importance on the result. Laboratory based decision making is generally faster or unimpaired. Motivation, self-efficacy and anxiety can change during exercise to modify RPE and, hence, alter physical performance. Symptoms of fatigue during racing, team-game or racquet sports are largely anecdotal, but sometimes assessed with time-motion analysis. Fatigue during brief all-out racing is described biomechanically as a decline of peak velocity, along with altered kinematic components. Longer sport events involve pacing strategies, central and peripheral fatigue contributions and elevated RPE. During match play, the work rate can decline late in a match (or tournament) and/or transiently after intense exercise bursts. Repeated sprint ability, agility and leg strength become slightly impaired. Technique outcomes, such as velocity and accuracy for throwing, passing, hitting and kicking, can deteriorate. Physical and subjective changes are both less severe in real rather than simulated sport activities. Little objective evidence exists to support exercise-induced mental lapses during sport. A model depicting mind-body interactions during sport competition shows that the RPE centre-motor cortex-working muscle sequence drives overall performance levels and, hence, fatigue symptoms. The sporting outputs from this sequence can be modulated by interactions with muscle afferent and circulatory feedback, psychological and decision-making inputs. Importantly, compensatory processes exist at many levels to protect against performance decrements. Small changes of putative fatigue factors can also be protective. We show that individual fatigue factors including diminished carbohydrate availability, elevated serotonin, hypoxia, acidosis, hyperkalaemia, hyperthermia, dehydration and reactive oxygen species, each contribute to several fatigue symptoms. Thus, multiple symptoms of fatigue can occur simultaneously and the underlying mechanisms overlap and interact. Based on this understanding, we reinforce the proposal that fatigue is best described globally as an exercise-induced decline of performance as this is inclusive of all viewpoints.

Melanoma cell invasiveness is regulated by miR-211 suppression of the BRN2 transcription factor

To identify microRNAs potentially involved in melanomagenesis, we compared microRNA expression profiles between melanoma cell lines and cultured melanocytes. The most differentially expressed microRNA between the normal and tumor cell lines was miR-211. We focused on this pigment-cell-enriched miRNA as it is derived from the microphthalmia-associated transcription factor (MITF)-regulated gene, TRPM1 (melastatin). We find that miR-211 expression is greatly decreased in melanoma cells and melanoblasts compared to melanocytes. Bioinformatic analysis identified a large number of potential targets of miR-211, including POU3F2 (BRN2). Inhibition of miR-211 in normal melanocytes resulted in increased BRN2 protein, indicating that endogenous miR-211 represses BRN2 in differentiated cells. Over-expression of miR-211 in melanoma cell lines changed the invasive potential of the cells in vitro through directly targeting BRN2 translation. We propose a model for the apparent non-overlapping expression levels of BRN2 and MITF in melanoma, mediated by miR-211 expression.

Acoustic component detection for automatic species recognition in environmental monitoring

Automatic species recognition plays an important role in assisting ecologists to monitor the environment. One critical issue in this research area is that software developers need prior knowledge of specific targets people are interested in to build templates for these targets. This paper proposes a novel approach for automatic species recognition based on generic knowledge about acoustic events to detect species. Acoustic component detection is the most critical and fundamental part of this proposed approach. This paper gives clear definitions of acoustic components and presents three clustering algorithms for detecting four acoustic components in sound recordings; whistles, clicks, slurs, and blocks. The experiment result demonstrates that these acoustic component recognisers have achieved high precision and recall rate.

Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data

In this paper we present a sequential Monte Carlo algorithm for Bayesian sequential experimental design applied to generalised non-linear models for discrete data. The approach is computationally convenient in that the information of newly observed data can be incorporated through a simple re-weighting step. We also consider a flexible parametric model for the stimulus-response relationship together with a newly developed hybrid design utility that can produce more robust estimates of the target stimulus in the presence of substantial model and parameter uncertainty. The algorithm is applied to hypothetical clinical trial or bioassay scenarios. In the discussion, potential generalisations of the algorithm are suggested to possibly extend its applicability to a wide variety of scenarios

A Bayesian approach for estimating detection times in horses : exploring the pharmacokinetics of a urinary acepromazine metabolite

We describe the population pharmacokinetics of an acepromazine (ACP) metabolite (2-(1-hydroxyethyl)promazine) (HEPS) in horses for the estimation of likely detection times in plasma and urine. Acepromazine (30 mg) was administered to 12 horses, and blood and urine samples were taken at frequent intervals for chemical analysis. A Bayesian hierarchical model was fitted to describe concentration-time data and cumulative urine amounts for HEPS. The metabolite HEPS was modelled separately from the parent ACP as the half-life of the parent was considerably less than that of the metabolite. The clearance ($Cl/F_{PM}$) and volume of distribution ($V/F_{PM}$), scaled by the fraction of parent converted to metabolite, were estimated as 769 L/h and 6874 L, respectively. For a typical horse in the study, after receiving 30 mg of ACP, the upper limit of the detection time was 35 hours in plasma and 100 hours in urine, assuming an arbitrary limit of detection of 1 $\mu$g/L, and a small ($\approx 0.01$) probability of detection. The model derived allowed the probability of detection to be estimated at the population level. This analysis was conducted on data collected from only 12 horses, but we assume that this is representative of the wider population.

Rule-based approach for identifying assertions in clinical free-text data

A rule-based approach for classifying previously identified medical concepts in the clinical free text into an assertion category is presented. There are six different categories of assertions for the task: Present, Absent, Possible, Conditional, Hypothetical and Not associated with the patient. The assertion classification algorithms were largely based on extending the popular NegEx and Context algorithms. In addition, a health based clinical terminology called SNOMED CT and other publicly available dictionaries were used to classify assertions, which did not fit the NegEx/Context model. The data for this task includes discharge summaries from Partners HealthCare and from Beth Israel Deaconess Medical Centre, as well as discharge summaries and progress notes from University of Pittsburgh Medical Centre. The set consists of 349 discharge reports, each with pairs of ground truth concept and assertion files for system development, and 477 reports for evaluation. The system’s performance on the evaluation data set was 0.83, 0.83 and 0.83 for recall, precision and F1-measure, respectively. Although the rule-based system shows promise, further improvements can be made by incorporating machine learning approaches.

The influence of architecture on degradation and tissue ingrowth into three-dimensional poly(lactic-co-glycolic acid) scaffolds in vitro and in vivo

The in vitro and in vivo degradation properties of poly(lactic-co-glycolic acid) (PLGA) scaffolds produced by two different technologies - thermally induced phase separation (TIPS), and solvent casting and particulate leaching (SCPL) were compared. Over 6 weeks, in vitro degradation produced changes in SCPL scaffold dimension, mass, internal architecture and mechanical properties. TIPS scaffolds produced far less changes in these parameters providing significant advantages over SCPL. In vivo results were based on a microsurgically created arteriovenous (AV) loop sandwiched between two TIPS scaffolds placed in a polycarbonate chamber under rat groin skin. Histologically, a predominant foreign body giant cell response and reduced vascularity was evident in tissue ingrowth between 2 and 8 weeks in TIPS scaffolds. Tissue death occurred at 8 weeks in the smallest pores. Morphometric comparison of TIPS and SCPL scaffolds indicated slightly better tissue ingrowth but greater loss of scaffold structure in SCPL scaffolds. Although advantageous in vitro, large surface area:volume ratios and varying pore sizes in PLGA TIPS scaffolds mean that effective in vivo (AV loop) utilization will only be achieved if the foreign body response can be significantly reduced so as to allow successful vascularisation, and hence sustained tissue growth, in pores less than 300 μm. © 2005 Elsevier Ltd. All rights reserved.

A fragment of the LG3 peptide of endorepellin is present in the urine of physically active mining workers : a potential marker of physical activity

Biomarker analysis has been implemented in sports research in an attempt to monitor the effects of exertion and fatigue in athletes. This study proposed that while such biomarkers may be useful for monitoring injury risk in workers, proteomic approaches might also be utilised to identify novel exertion or injury markers. We found that urinary urea and cortisol levels were significantly elevated in mining workers following a 12 hour overnight shift. These levels failed to return to baseline over 24h in the more active maintenance crew compared to truck drivers (operators) suggesting a lack of recovery between shifts. Use of a SELDI-TOF MS approach to detect novel exertion or injury markers revealed a spectral feature which was associated with workers in both work categories who were engaged in higher levels of physical activity. This feature was identified as the LG3 peptide, a C-terminal fragment of the anti-angiogenic / anti-tumourigenic protein endorepellin. This finding suggests that urinary LG3 peptide may be a biomarker of physical activity. It is also possible that the activity mediated release of LG3 / endorepellin into the circulation may represent a biological mechanism for the known inverse association between physical activity and cancer risk / survival.

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.

A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design

Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.