Unsupervised extraction of recurring words from infant-directed speech

To date, most computational models of infant word segmentation have worked from phonemic or phonetic input, or have used toy datasets. In this paper, we present an algorithm for word extraction that works directly from naturalistic acoustic input: infant-directed speech from the CHILDES corpus. The algorithm identifies recurring acoustic patterns that are candidates for identification as words or phrases, and then clusters together the most similar patterns. The recurring patterns are found in a single pass through the corpus using an incremental method, where only a small number of utterances are considered at once. Despite this limitation, we show that the algorithm is able to extract a number of recurring words, including some that infants learn earliest, such as Mommy and the child’s name. We also introduce a novel information-theoretic evaluation measure

Psychosocial risk and protective factors associated with perpetration of gender-based violence in a community sample of men in rural KwaZulu-Natal, South Africa

Background. Rates of gender-based violence (GBV) in South Africa (SA) are among the highest in the world. In societies where social ideals of masculinity encourage male dominance and control over women, gender power imbalances contribute to male perpetration and women’s vulnerability. The drivers that cause men to perpetrate GBV and those that lead to HIV overlap and interact in multiple and complex ways. Multiple risk and protective factors for GBV perpetration by males operate interdependently at a number of levels; at the individual level, these include chronic anxiety and depression, which have been shown to lead to risky sexual behaviours.Objectives. (i) To examine psychosocial risk factors (symptoms of anxiety and depression) as well as protective factors (social support and self-esteem) as self-reported by a cohort of males in rural KwaZulu-Natal (KZN) Province, SA; and (ii) to determine whether there are differences in anxiety, depression, social support and self-esteem between perpetrators and non-perpetrators.Methods. A cross-sectional study using quasi-probability cluster sampling of 13 of 28 wards in Harry Gwala District, KZN. Participants were then randomly chosen from each ward proportionate to size.Results. The participants were relatively young (median age 22 years); over half were schoolgoers, and 91.3% had never married. Over 43% of the sample reported clinical levels of anxiety and depressive symptoms on the Brief Symptom Inventory. Rates of GBV perpetration were 60.9%, 23.6% and 10.0% for psychological abuse, non-sexual physical violence and sexual violence, respectively. GBV perpetration was associated with higher depression, higher anxiety, lower self-esteem and lower social support.Conclusions. Interventions to address GBV need to take modifiable individual-level factors into account

Prolactinoma presenting as chronic anaemia with osteoporosis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Unexplained anaemia is a rare mode of presentation for prolactinoma. We describe a case of a man, with chronic anaemia ascribed to old age. Six years later, he was evaluated and diagnosed with a prolactinoma and resultant osteoporosis. Prolactinoma in old people may present insidiously with chronic anaemia and osteoporosis with or without sexual dysfunction.</p> <p>Case presentation</p> <p>We describe the case of a 70-year-old Caucasian man who presented with mild anaemia and tiredness. His anaemia was investigated and ascribed to senescence. Endocrine causes were not considered or tested for. Six years later, he was again referred. Reassessment and direct questioning revealed long-standing sexual dysfunction. It was also discovered that our patient had fractured his radius twice, with minor trauma, during the preceding year. His serum prolactin was massively increased and a magnetic resonance imaging (MRI) scan of the head demonstrated a pituitary mass consistent with a prolactinoma. Dual X-ray absorptiometry revealed osteoporosis. Treatment of the prolactinoma led to a reduction in his serum prolactin with a rise in his haemoglobin to normal levels. This suggested that the prolactinoma was present during the initial presentation and was the cause of his anaemia.</p> <p>Conclusion</p> <p>This case highlights the importance of fully evaluating and investigating unexplained anaemia in older people and that endocrine causes should be considered. Osteoporosis also requires evaluation with secondary causes considered.</p

Motion Deblurring in the Wild

The task of image deblurring is a very ill-posed problem as both the image and the blur are unknown. Moreover, when pictures are taken in the wild, this task becomes even more challenging due to the blur varying spatially and the occlusions between the object. Due to the complexity of the general image model we propose a novel convolutional network architecture which directly generates the sharp image.This network is built in three stages, and exploits the benefits of pyramid schemes often used in blind deconvolution. One of the main difficulties in training such a network is to design a suitable dataset. While useful data can be obtained by synthetically blurring a collection of images, more realistic data must be collected in the wild. To obtain such data we use a high frame rate video camera and keep one frame as the sharp image and frame average as the corresponding blurred image. We show that this realistic dataset is key in achieving state-of-the-art performance and dealing with occlusions

FAST: A multi-processed environment for visualization of computational fluid dynamics

Three-dimensional, unsteady, multi-zoned fluid dynamics simulations over full scale aircraft are typical of the problems being investigated at NASA Ames' Numerical Aerodynamic Simulation (NAS) facility on CRAY2 and CRAY-YMP supercomputers. With multiple processor workstations available in the 10-30 Mflop range, we feel that these new developments in scientific computing warrant a new approach to the design and implementation of analysis tools. These larger, more complex problems create a need for new visualization techniques not possible with the existing software or systems available as of this writing. The visualization techniques will change as the supercomputing environment, and hence the scientific methods employed, evolves even further. The Flow Analysis Software Toolkit (FAST), an implementation of a software system for fluid mechanics analysis, is discussed

Targeting the Microbiota to Address Diet-Induced Obesity: A Time Dependent Challenge

peer-reviewedLinks between the gut microbiota and host metabolism have provided new perspectives on obesity. We previously showed that the link between the microbiota and fat deposition is age- and time-dependent subject to microbial adaptation to diet over time. We also demonstrated reduced weight gain in diet-induced obese (DIO) mice through manipulation of the gut microbiota with vancomycin or with the bacteriocin-producing probiotic Lactobacillus salivarius UCC118 (Bac+), with metabolic improvement achieved in DIO mice in receipt of vancomycin. However, two phases of weight gain were observed with effects most marked early in the intervention phase. Here, we compare the gut microbial populations at the early relative to the late stages of intervention using a high throughput sequencing-based analysis to understand the temporal relationship between the gut microbiota and obesity. This reveals several differences in microbiota composition over the intervening period. Vancomycin dramatically altered the gut microbiota composition, relative to controls, at the early stages of intervention after which time some recovery was evident. It was also revealed that Bac+ treatment initially resulted in the presence of significantly higher proportions of Peptococcaceae and significantly lower proportions of Rikenellaceae and Porphyromonadaceae relative to the gut microbiota of L. salivarius UCC118 bacteriocin negative (Bac-) administered controls. These differences were no longer evident at the later time. The results highlight the resilience of the gut microbiota and suggest that interventions may need to be monitored and continually adjusted to ensure sustained modification of the gut microbiota.The authors are supported in part by Teagasc, Science Foundation Ireland (in the form of a research centre grant to the Alimentary Pharmabiotic Centre and PI awards to PWOT and PC) and by Alimentary Health Ltd

Fast and easy blind deblurring using an inverse filter and PROBE

PROBE (Progressive Removal of Blur Residual) is a recursive framework for blind deblurring. Using the elementary modified inverse filter at its core, PROBE's experimental performance meets or exceeds the state of the art, both visually and quantitatively. Remarkably, PROBE lends itself to analysis that reveals its convergence properties. PROBE is motivated by recent ideas on progressive blind deblurring, but breaks away from previous research by its simplicity, speed, performance and potential for analysis. PROBE is neither a functional minimization approach, nor an open-loop sequential method (blur kernel estimation followed by non-blind deblurring). PROBE is a feedback scheme, deriving its unique strength from the closed-loop architecture rather than from the accuracy of its algorithmic components

Human methanogen diversity and incidence in healthy and diseased colonic groups using mcrA gene analysis

<p>Abstract</p> <p>Background</p> <p>The incidence and diversity of human methanogens are insufficiently characterised in the gastrointestinal tract of both health and disease. A PCR and clone library methodology targeting the <it>mcrA </it>gene was adopted to facilitate the two-fold aim of surveying the relative incidence of methanogens in health and disease groups and also to provide an overview of methanogen diversity in the human gastrointestinal tract.</p> <p>Results</p> <p>DNA faecal extracts (207 in total) from a group of healthy controls and five gastrointestinal disease groups were investigated. Colorectal cancer, polypectomised, irritable bowel syndrome and the control group had largely equivalent numbers of individuals positive for methanogens (range 45–50%). Methanogen incidence in the inflammatory bowel disease groups was reduced, 24% for ulcerative colitis and 30% for Crohn's disease. Four unique <it>mcrA </it>gene restriction fragment length polymorphism profiles were identified and bioinformatic analyses revealed that the majority of all sequences (94%) retrieved from libraries were 100% identical to <it>Methanobrevibacter smithii mcrA </it>gene. In addition, <it>mcrA </it>gene sequences most closely related to <it>Methanobrevibacter oralis </it>and members of the order <it>Methanosarcinales </it>were also recovered.</p> <p>Conclusion</p> <p>The <it>mcrA </it>gene serves as a useful biomarker for methanogen detection in the human gut and the varying trends of methanogen incidence in the human gut could serve as important indicators of intestinal function. Although <it>Methanobrevibacter smithii </it>is the dominant methanogen in both the distal colon of individuals in health and disease, the diversity of methanogens is greater than previously reported. In conclusion, the low incidence of methanogens in Inflammatory Bowel Disease, the functionality of the methanogens and impact of methane production in addition to competitive interactions between methanogens and other microbial groups in the human gastrointestinal tract warrants further investigation.</p

Learning object categories from Google's image search

Current approaches to object category recognition require datasets of training images to be manually prepared, with varying degrees of supervision. We present an approach that can learn an object category from just its name, by utilizing the raw output of image search engines available on the Internet. We develop a new model, TSI-pLSA, which extends pLSA (as applied to visual words) to include spatial information in a translation and scale invariant manner. Our approach can handle the high intra-class variability and large proportion of unrelated images returned by search engines. We evaluate the models on standard test sets, showing performance competitive with existing methods trained on hand prepared datasets

FAST: A multi-processed environment for visualization of computational fluid

Three dimensional, unsteady, multizoned fluid dynamics simulations over full scale aircraft is typical of problems being computed at NASA-Ames on CRAY2 and CRAY-YMP supercomputers. With multiple processor workstations available in the 10 to 30 Mflop range, it is felt that these new developments in scientific computing warrant a new approach to the design and implementation of analysis tools. These large, more complex problems create a need for new visualization techniques not possible with the existing software or systems available as of this time. These visualization techniques will change as the supercomputing environment, and hence the scientific methods used, evolve ever further. Visualization of computational aerodynamics require flexible, extensible, and adaptable software tools for performing analysis tasks. FAST (Flow Analysis Software Toolkit), an implementation of a software system for fluid mechanics analysis that is based on this approach is discussed