Integration over song classification replicates: song variant analysis in the hihi

Human expert analyses are commonly used in bioacoustic studies and can potentially limit the reproducibility of these results. In this paper, a machine learning method is presented to statistically classify avian vocalizations. Automated approaches were applied to isolate bird songs from long field recordings, assess song similarities, and classify songs into distinct variants. Because no positive controls were available to assess the true classification of variants, multiple replicates of automatic classification of song variants were analyzed to investigate clustering uncertainty. The automatic classifications were more similar to the expert classifications than expected by chance. Application of these methods demonstrated the presence of discrete song variants in an island population of the New Zealand hihi (Notiomystis cincta). The geographic patterns of song variation were then revealed by integrating over classification replicates. Because this automated approach considers variation in song variant classification, it reduces potential human bias and facilitates the reproducibility of the results.

Perceived quality of e‐health services: A conceptual scale development of e‐health service quality based on the C‐OAR‐SE approach

Purpose Health service quality is an important determinant for health service satisfaction and behavioral intentions. The purpose of this paper is to investigate requirements of e‐health services and to develop a measurement model to analyze the construct of “perceived e‐health service quality.” Design/methodology/approach The paper adapts the C‐OAR‐SE procedure for scale development by Rossiter. The focal aspect is the “physician‐patient relationship” which forms the core dyad in the healthcare service provision. Several in‐depth interviews were conducted in Switzerland; first with six patients (as raters), followed by two experts of the healthcare system (as judges). Based on the results and an extensive literature research, the classification of object and attributes is developed for this model. Findings The construct e‐health service quality can be described as an abstract formative object and is operationalized with 13 items: accessibility, competence, information, usability/user friendliness, security, system integration, trust, individualization, empathy, ethical conduct, degree of performance, reliability, and ability to respond. Research limitations/implications Limitations include the number of interviews with patients and experts as well as critical issues associated with C‐OAR‐SE. More empirical research is needed to confirm the quality indicators of e‐health services. Practical implications Health care providers can utilize the results for the evaluation of their service quality. Practitioners can use the hierarchical structure to measure service quality at different levels. The model provides a diagnostic tool to identify poor and/or excellent performance with regard to the e‐service delivery. Originality/value The paper contributes to knowledge with regard to the measurement of e‐health quality and improves the understanding of how customers evaluate the quality of e‐health services.

Case-control study of ADARB1 and ADARB2 gene variants in migraine

Background: Migraine causes crippling attacks of severe head pain along with associated nausea, vomiting, photophobia and/or phonophobia. The aim of this study was to investigate single nucleotide polymorphisms (SNPs) in the adenosine deaminase, RNA-specific, B1 (ADARB1)and adenosine deaminase, RNA specific, B2 (ADARB2) genes in an Australian case-control Caucasian population for association with migraine. Both candidate genes are highly expressed in the central nervous system (CNS) and fit criteria for migraine neuropathology. SNPs in the ADARB2 gene were previously found to be positively associated with migraine in a pedigree-based GWAS using the genetic isolate of Norfolk Island, Australia. The ADARB1 gene was also chosen for investigation due to its important function in editing neurotransmitter receptor transcripts. Methods: Four SNPs in ADARB1 and nine in ADARB2 were selected by inspecting blocks of LD in Haploview for genotyping using either TaqMan or Sequenom assays. These SNPs were genotyped in two-hundred and ninety one patients who satisfied the International Classification of Headache Disorders, ICHD-II 2004 diagnostic criteria for migraine and three-hundred and fourteen controls and PLINK was used for association testing. Results: Chi-square (χ2) analysis found no significant association between any of the SNPs tested in the ADARB1 and ADARB2 genes in this study and the occurrence of migraine. Conclusions: In contrast to findings that SNPs in the ADARB2 gene were positively associated with migraine in the Norfolk Island population, we find no evidence to support the involvement of RNA editing genes in migraine susceptibility in an Australian Caucasian population.

Teaching children who have a diagnosis of Autism Spectrum Disorder

Best practice dictates that the Autism Spectrum Disorder (ASD) diagnostic process is informed by experienced professionals from at least two disciplines, for example psychology or speech pathology, with the diagnosis ultimately provided by a specialist medical practitioner e.g. child psychiatrist, neurologist or paediatrician. Irrespective of a child’s age, diagnosis relies upon information about their early development. Current information and observations on a child’s behaviour, communication and socialisation are considered by the specialist medical practitioner against the signs and symptoms detailed in one of several diagnostic systems. Two recently used classification systems in Australia have been the fourth edition of the Diagnostic Statistical Manual of Mental Disorders (DSM-IV) published by the American Psychiatric Association (1994) and the tenth edition of the International Classification of Disease (ICD-10), published by the World Health Organisation (2003).

Systematic literature review of incidence rates of low-speed vehicle run-over incidents in children

Aim: To systematically review the literature investigating the incidence of fatal and or nonfatal low-speed vehicle run-over (LSVRO) incidents in children aged 0–15 years. Methods: The following databases were searched using specific search terms, from their date of conception up to June 2011: Cochrane Library, Medline, CINAHL, Embase, AMI, Sociological Abstracts, ERIC, PsycArticles, PsycInfo, Urban Studies and Planning; Australian Criminology Database; Dissertations and Thesis; Academic Research Library; Social Services Abstracts; Family and Society; Scopus; and Web of Science. A total of 128 articles were identified in the databases (33 found by hand searching). The title and abstract of these were read, and 102 were removed because they were not primary research articles relating to LSVRO-type injuries. Twenty-six articles were assessed against the inclusion (reporting population level incidence rates) and exclusion criteria, 19 of which were excluded, leaving a total of five articles for inclusion in the review. Findings: Five studies were identified that met the inclusion criteria. The incidence rate in nonfatal LSVRO events varied in the range of 7.09 to 14.79 per 100,000 and from 0.63 to 3.2 per 100,000 in fatal events. Discussion: Using International Classification of Diseases codes for classifying fatal or nonfatal LSVRO incidents is problematic as there is no specific code for LSVRO. The current body of research is void of a comprehensive secular population data analysis. Only with an improved spectrum of incidence rates will appropriate evaluation of this problem be possible, and this will inform nursing prevention interventions. The effect of LSVRO incidents is clearly understudied. More research is required to address incidence rates in relation to culture, environment, risk factors, car design, and injury characteristics. Conclusions: Thevlack of nursing research or policy around this area of injury, most often to children, indicates a field of inquiry and policy development that needs attention.

Genetic, functional, and histopathological evaluation of two C-terminal BRCA1 missense variants

Background: The vast majority of BRCA1 missense sequence variants remain uncharacterised for their possible effect on protein expression and function, and therefore are unclassified in terms of their pathogenicity. BRCA1 plays diverse cellular roles and it is unlikely that any single functional assay will accurately reflect the total cellular implications of missense mutations in this gene. Objective: To elucidate the effect of two BRCA1 variants, 5236G>C (G1706A) and 5242C>A (A1708E) on BRCA1 function, and to survey the relative usefulness of several assays to direct the characterisation of other unclassified variants in BRCA genes. Methods and Results: Data from a range of bioinformatic, genetic, and histopathological analyses, and in vitro functional assays indicated that the 1708E variant was associated with the disruption of different cellular functions of BRCA1. In transient transfection experiments in T47D and 293T cells, the 1708E product was mislocalised to the cytoplasm and induced centrosome amplification in 293T cells. The 1708E variant also failed to transactivate transcription of reporter constructs in mammalian transcriptional transactivation assays. In contrast, the 1706A variant displayed a phenotype comparable to wildtype BRCA1 in these assays. Consistent with functional data, tumours from 1708E carriers showed typical BRCA1 pathology, while tumour material from 1706A carriers displayed few histopathological features associated with BRCA1 related tumours. Conclusions: A comprehensive range of genetic, bioinformatic, and functional analyses have been combined for the characterisation of BRCA1 unclassified sequence variants. Consistent with the functional analyses, the combined odds of causality calculated for the 1706A variant after multifactorial likelihood analysis (1:142) indicates a definitive classification of this variant as "benign". In contrast, functional assays of the 1708E variant indicate that it is pathogenic, possibly through subcellular mislocalisation. However, the combined odds of 262:1 in favour of causality of this variant does not meet the minimal ratio of 1000:1 for classification as pathogenic, and A1708E remains formally designated as unclassified. Our findings highlight the importance of comprehensive genetic information, together with detailed functional analysis for the definitive categorisation of unclassified sequence variants. This combination of analyses may have direct application to the characterisation of other unclassified variants in BRCA1 and BRCA2.

A critical evaluation of literature on robot path planning in dynamic environment

Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

Genetic burden associated with varying degrees of disease severity in endometriosis

Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities.

The validity of the GENEActiv wrist-worn accelerometer for measuring adult sedentary time in free living

OBJECTIVES Based on self-reported measures, sedentary time has been associated with chronic disease and mortality. This study examined the validity of the wrist-worn GENEactiv accelerometer for measuring sedentary time (i.e. sitting and lying) by posture classification, during waking hours in free living adults. DESIGN Fifty-seven participants (age=18-55 years 52% male) were recruited using convenience sampling from a large metropolitan Australian university. METHODS Participants wore a GENEActiv accelerometer on their non-dominant wrist and an activPAL device attached to their right thigh for 24-h (00:00 to 23:59:59). Pearson's Correlation Coefficient was used to examine the convergent validity of the GENEActiv and the activPAL for estimating total sedentary time during waking hours. Agreement was illustrated using Bland and Altman plots, and intra-individual agreement for posture was assessed with the Kappa statistic. RESULTS Estimates of average total sedentary time over 24-h were 623 (SD 103) min/day from the GENEActiv, and 626 (SD 123) min/day from the activPAL, with an Intraclass Correlation Coefficient of 0.80 (95% confidence intervals 0.68-0.88). Bland and Altman plots showed slight underestimation of mean total sedentary time for GENEActiv relative to activPAL (mean difference: -3.44min/day), with moderate limits of agreement (-144 to 137min/day). Mean Kappa for posture was 0.53 (SD 0.12), indicating moderate agreement for this sample at the individual level. CONCLUSIONS The estimation of sedentary time by posture classification of the wrist-worn GENEActiv accelerometer was comparable to the activPAL. The GENEActiv may provide an alternative, easy to wear device based measure for descriptive estimates of sedentary time in population samples

Combat sports analytics: Boxing punch classification using overhead depth imagery

In competitive combat sporting environments like boxing, the statistics on a boxer's performance, including the amount and type of punches thrown, provide a valuable source of data and feedback which is routinely used for coaching and performance improvement purposes. This paper presents a robust framework for the automatic classification of a boxer's punches. Overhead depth imagery is employed to alleviate challenges associated with occlusions, and robust body-part tracking is developed for the noisy time-of-flight sensors. Punch recognition is addressed through both a multi-class SVM and Random Forest classifiers. A coarse-to-fine hierarchical SVM classifier is presented based on prior knowledge of boxing punches. This framework has been applied to shadow boxing image sequences taken at the Australian Institute of Sport with 8 elite boxers. Results demonstrate the effectiveness of the proposed approach, with the hierarchical SVM classifier yielding a 96% accuracy, signifying its suitability for analysing athletes punches in boxing bouts.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Evaluating the specificity of community injury hospitalization data over time

This study identified the areas of poor specificity in national injury hospitalization data and the areas of improvement and deterioration in specificity over time. A descriptive analysis of ten years of national hospital discharge data for Australia from July 2002-June 2012 was performed. Proportions and percentage change of defined/undefined codes over time was examined. At the intent block level, accidents and assault were the most poorly defined with over 11% undefined in each block. The mechanism blocks for accidents showed a significant deterioration in specificity over time with up to 20% more undefined codes in some mechanisms. Place and activity were poorly defined at the broad block level (43% and 72% undefined respectively). Private hospitals and hospitals in very remote locations recorded the highest proportion of undefined codes. Those aged over 60 years and females had the higher proportion of undefined code usage. This study has identified significant, and worsening, deficiencies in the specificity of coded injury data in several areas. Focal attention is needed to improve the quality of injury data, especially on those identified in this study, to provide the evidence base needed to address the significant burden of injury in the Australian community.