Independent distractor frequency and age-of-acquisition dffects in picture-word interference: FMRI evidence for post-lexical and lexical accounts according to distractor type

In two fMRI experiments, participants named pictures with superimposed distractors that were high or low in frequency or varied in terms of age of acquisition. Pictures superimposed with low-frequency words were named more slowly than those superimposed with high-frequency words, and late-acquired words interfered with picture naming to a greater extent than early-acquired words. The distractor frequency effect (Experiment 1) was associated with increased activity in left premotor and posterior superior temporal cortices, consistent with the operation of an articulatory response buffer and verbal selfmonitoring system. Conversely, the distractor age-of-acquisition effect (Experiment 2) was associated with increased activity in the left middle and posterior middle temporal cortex, consistent with the operation of lexical level processes such as lemma and phonological word form retrieval. The spatially dissociated patterns of activity across the two experiments indicate that distractor effects in picture-word interference may occur at lexical or postlexical levels of processing in speech production.

Development of a switch mode assisted linear amplifier for use as a high fidelity voltage source

Frequency Domain Spectroscopy (FDS) is one of the major techniques used for determining the condition of the cellulose based paper and pressboard components in large oil/paper insulated power transformers. This technique typically makes use of a sinusoidal voltage source swept from 0.1 mHz to 1 kHz. The excitation test voltage source used must meet certain characteristics, such as high output voltage, high fidelity, low noise and low harmonic content. The amplifier used; in the test voltage source; must be able to drive highly capacitive loads. This paper proposes that a switch-mode assisted linear amplifier (SMALA) can be used in the test voltage source to meet these criteria. A three level SMALA prototype amplifier was built to experimentally demonstrate the effectiveness of this proposal. The developed SMALA prototype shows no discernable harmonic distortion in the output voltage waveform, or the need for output filters, and is therefore seen as a preferable option to pulse width modulated digital amplifiers. The lack of harmonic distortion and high frequency switching noise in the output voltage of this SMALA prototype demonstrates its feasibility for applications in FDS, particularly on highly capacitive test objects such as transformer insulation systems.

Development of non-intrusive monitoring for reactive switching of high voltage circuit breaker

High-voltage circuit breakers are among the most important equipments for ensuring the efficient and safe operation of an electric power system. On occasion, circuit breaker operators may wish to check whether equipment is performing satisfactorily and whether controlled switching systems are producing reliable and repeatable stress control. Monitoring of voltage and current waveforms during switching using established methods will provide information about the magnitude and frequency of voltage transients as a result of re-ignitions and restrikes. However, high frequency waveform measurement requires shutdown of circuit breaker and use of specialized equipment. Two utilities, Hydro-Québec in Canada and Powerlink Queensland in Australia, have been working on the development and application of a non-intrusive, cost-effective and flexible diagnostic system for monitoring high-voltage circuit breakers for reactive switching. The proposed diagnostic approach relies on the non-intrusive assessment of key parameters such as operating times, prestrike characteristics, re-ignition and restrike detection. Transient electromagnetic emissions have been identified as a promising means to evaluate the abovementioned parameters non-intrusively. This paper describes two complimentary methods developed concurrently by Powerlink and Hydro-Québec. Also, return of experiences on the application to capacitor bank and shunt reactor switching is presented.

General practitioner utilisation amongst urban Aboriginal and Torres Strait Islander children aged less than 5 years

Aim There are limited studies documenting the frequency and reason for attendance to primary health care services in Australian children, particularly for urban Aboriginal and Torres Strait Islander children. This study describes health service utilisation in this population in an urban setting. Methods An ongoing prospective cohort study of Aboriginal and Torres Strait Islander children aged <5 years registered with an urban Aboriginal and Torres Strait Islander primary health care centre in Brisbane, Australia. Detailed demographic, clinical, health service utilisation and risk factor data are collected by Aboriginal researchers at enrolment and monthly for a period of 12 months on each child. The incidence of health service utilisation was calculated according to the Poisson distribution. Results Between 14 February 2013 and 31 October 2014, 118 children were recruited, providing data for 535 child-months of observation. Ninety-one percent of children were Aboriginal, 4% Torres Strait Islander and 5% were both Aboriginal and Torres Strait Islander. The incidence of presentations to see a doctor for any reason was 43.9 episodes/100 child months (95%CI 38.4 – 49.9) The most common reasons for presentation were for immunisations (23%), respiratory illnesses (19%) and for Australian Government funded Indigenous child health check (16%). The primary health services used, for majority of these visits were Aboriginal and Torres Strait Islander specific medical services (61%). Conclusions Within a cultural-specific service for an urban Aboriginal and Torres Strait Islander people, there is a high frequency of childhood attendance at for primary health care services. Well-health checks and respiratory illnesses were the most common reasons. The high proportion of visits for well child services suggests a potential for opportunistic health promotion, education and early interventions across a range of child health issues.

No evidence for genetic association with the let-7 microRNA-binding site or other common KRAS variants in risk of endometriosis

STUDY QUESTION Is there a contribution of the minor allele at the KRAS single nucleotide polymorphism (SNP) rs61764370 in the let-7 microRNA-binding site to endometriosis risk? SUMMARY ANSWER We found no evidence for association between endometriosis risk and rs61764370 or any other SNPs in KRAS. WHAT IS KNOWN ALREADY The rs61764370 SNP in the 3' untranslated region of the KRAS gene is predicted to disrupt a complementary binding site (LCS6) for the let-7 microRNA, and was recently reported to be at a high frequency (31%) in 132 women of varying ancestry with endometriosis compared with frequencies in a database of population controls (up to 7.6% depending on ancestry), suggesting a strong effect of this KRAS SNP in the aetiology of endometriosis. STUDY DESIGN, SIZE AND DURATION This was a case-control study with a total of 11 206 subjects. The study was performed between February 2012 and July 2012. PARTICIPANTS/MATERIALS, SETTINGAND METHODS We first investigated a possible association between common markers in KRAS and endometriosis risk from our genome-wide association (GWA) data in 3194 surgically confirmed endometriosis cases and 7060 controls of European ancestry. Although rs61764370 was not genotyped on the GWA arrays, five SNPs typed in the study were highly correlated with this variant. The rs61764370 and two SNPs highly correlated with rs61764370 were then genotyped in 933 endometriosis cases and 952 controls using the Sequenom MassARRAY platform. MAIN RESULTS AND THE ROLE OF CHANCE There was no evidence for an association between rs61764370 and endometriosis risk P = 0.411 and odds ratio = 1.10 (95% confidence intervals: 0.88-1.36). We also found no evidence for an association between the highly correlated SNP rs17387019 and endometriosis. Their minor allele frequencies in cases and controls were of 0.087-0.091 similar to the population frequency reported previously for this variant in controls. Analyses of endometriosis cases with revised American Fertility Society stage III/IV disease also showed no evidence for an association between these SNPs and endometriosis risk. LIMITATIONS AND REASONS FOR CAUTION The GWA and genotyped data sets were not independent since individuals and cases from some families overlap. Controls in our GWA study were not screened for endometriosis. WIDER IMPLICATIONS OF THE FINDINGS The key SNP, rs61764370, was genotyped in a subset of samples. Our results do not support the suggestion that carrying the minor allele at rs61764370 contributes to a significant number of endometriosis cases and rs61764370 is, therefore, unlikely to be a useful marker of endometriosis risk. STUDY FUNDING/COMPETING INTEREST(S) The research was funded by grants from the Australian National Health and Medical Research Council and Wellcome Trust. None of the authors has competing interests for the study.

Early and late electrophysiological effects of distractor frequency in picture naming: Reconciling input and output accounts

The “distractor-frequency effect” refers to the finding that high-frequency (HF) distractor words slow picture naming less than low-frequency distractors in the picture–word interference paradigm. Rival input and output accounts of this effect have been proposed. The former attributes the effect to attentional selection mechanisms operating during distractor recognition, whereas the latter attributes it to monitoring/decision mechanisms operating on distractor and target responses in an articulatory buffer. Using high-density (128-channel) EEG, we tested hypotheses from these rival accounts. In addition to conducting stimulus- and response-locked whole-brain corrected analyses, we investigated the correct-related negativity, an ERP observed on correct trials at fronto-central electrodes proposed to reflect the involvement of domain general monitoring. The wholebrain ERP analysis revealed a significant effect of distractor frequency at inferior right frontal and temporal sites between 100 and 300-msec post-stimulus onset, during which lexical access is thought to occur. Response-locked, region of interest (ROI) analyses of fronto-central electrodes revealed a correct-related negativity starting 121 msec before and peaking 125 msec after vocal onset on the grand averages. Slope analysis of this component revealed a significant difference between HF and lowfrequency distractor words, with the former associated with a steeper slope on the time windowspanning from100 msec before to 100 msec after vocal onset. The finding of ERP effects in time windows and components corresponding to both lexical processing and monitoring suggests the distractor frequency effect is most likely associated with more than one physiological mechanism.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.