1,705 research outputs found

    Air quality assessment of carbon monoxide, nitrogen dioxide and sulfur dioxide levels in Blantyre, Malawi: a statistical approach to a stationary environmental monitoring station

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    Air quality in urban areas is a cause of concern because of increased industrial activities that contribute to large quantities of emissions. The study assess levels and variations of carbon monoxide (CO), nitrogen dioxide (NO2) and sulfur dioxide (SO2) in Blantyre, Malawi using a stationary environmental monitoring station (EMS). Results show that CO level (2.47 ± 1.23 mg m-3) were below the Malawian limit value (10.31 mg m-3). Although, NO2 (4.02 ± 2.47 mg m-3) and SO2 (8.58 ± 2.88 mg m-3) were significantly higher than allowable Malawian Standards (0.52 and 0.23 mg m-3, respectively). Discernible variations in hourly, diurnal, monthly and seasonal CO, SO2 and NO2 were apparent. Independent t-test confirmed that day time values were higher than those at night (p < 0.05). Thus, variations in local weather affect the disparity in hourly and diurnal values. Analysis of variance (ANOVA) confirmed significant variations in monthly observations. Moreover, independent t-test showed that wet season CO (2.32 mg m-3), SO2 (5.10 mg m-3) and NO2 (9.41 mg m-3) levels were higher than dry season values (CO = 2.32 mg m-3; SO2 = 3.42 mg m-3; NO2 = 8.13 mg m-3). A hierarchical cluster analysis (HCA) divided the 10 months into three groups based on distribution of CO, SO2 and NO2, air temperature, wind speed and wind direction. Furthermore, factor analysis (FA) showed that air temperature had significant contribution to variations in mean values of CO, SO2 and NO2 for the entire study period. The study shows a need for constant urban air quality monitoring in Blantyre and all urban areas in Malawi. It is recommended that the experimental site widen the scope of the study by utilizing the flexibility of the EMS. Key words: Air pollutants, principal component analysis, developing countries, environmental monitoringstation, Kaiser normalization

    Internal podalic version of second twin: Improving feet identification using a simulation model.

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    Podalic version and breech extraction require high obstetrical expertise. Identifying fetal extremities is the first crucial step for trainees. When this skill is not polished enough, it increases the inter-twin delivery interval and can even jeopardize the whole manoeuver. We present a model for simulating and training this specific skill, with obstetrical mannequin, and 3D printed hands and feet. Five feet and five hands (five rights and five lefts of each one) were printed in 3D after initial ultrasound acquisition of a near term fetus. Each foot and hand, was individually set in a condom filled with 100 cc of water and closed with a knot. A Sophie's Mum Birth Simulator Version 4.0 de MODEL-med was placed on the edge of the table. Each hand and foot was inserted into the pelvic mannequin. An evaluation of the students' skills using this model was performed. A significant reduction of the global mean to extract the first foot and all the feet was noticed at three month of interval. This model is an option to train and assess a crucial skill for version and breech extraction

    P3 amplitude reductions are associated with shared variance between internalizing and externalizing psychopathology

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    P3 amplitude reductions, commonly elicited in oddball paradigms, have been associated with both internalizing (e.g., depression and anxiety) and externalizing problems (e.g., substance use, aggression, and impulsivity). Recent factor analytic models have focused on the shared variance between internalizing and externalizing problems as a potentially important separable psychopathology construct (a general psychopathology factor, or p‐factor). To assess neurophysiological markers of this shared variance, we examined P3 amplitude to target and novel stimuli in an undergraduate sample with a range of internalizing and externalizing problems. Participants (N = 125) completed a rotated heads visual oddball paradigm, with IAPS pictures serving as infrequent novel stimuli. Results replicated P3 amplitude reduction relative to both target and novel stimuli separately for internalizing and externalizing problems, and found that the shared variance across internalizing and externalizing was significantly related to lower P3 amplitude to novels, targets, and a factor score of target and novel P3 measures. The present results are consistent with the interpretation that a general or shared problem behavior factor accounts for much of the associations between reduced P3 amplitude and internalizing and externalizing problems.There is a need for biological measures that can index emerging models of the shared variance between internalizing and externalizing problems (cf. general psychopathology factor, or p‐factor), to provide approaches for assessing the biological systems underlying these models. The current study found support for the idea that a general or shared problem behavior factor contributes to P3 amplitude reductions observed separately for internalizing and externalizing behaviors. This supports an inference that some biological systems are sensitive to processes associated with a shared problem behavior factor.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155993/1/psyp13618_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155993/2/psyp13618.pd

    Trait Sensitivity, Anxiety and Personality are predictive of Central Sensitisation Symptoms in Patients with Chronic Low Back Pain.

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    BACKGROUND:Sensitivity-related trait characteristics involving physical and emotional sensitivities and high trait anxiety personality types have been observed in individuals with non-specific chronic low back pain (NSCLBP). High trait sensitivity to sensory stimulation combined with interpretation biases based on personality type may contribute to the development of central sensitisation (CS) symptoms. To date there is limited research that has considered both sensitivity levels and personality type in NSCLBP with CS. The purpose of this study was to investigate 1) relationships between trait sensory profiles, trait anxiety and CS symptoms, and 2) the predictive capacity of sensory profiles, trait anxiety and personality types on CS symptoms, in people with NSCLBP. METHODS:This was a cross-sectional observational study using four self-report measures on adults (N = 165, mean age = 45 +-12 SD) from physiotherapy clinics in England, Ireland and New Zealand. Inclusion: NSCLBP > 6 months, aged 18-64, predominant CS pain presentation, no other pathology. Parametric and non-parametric correlation statistics and regression analyses were used. RESULTS:Positive correlations were found between central sensitisation inventory (CSI) scores and sensory hyper-sensitivity profiles and trait anxiety. CSI score increases could be predicted by: Sensory Sensitive, Low Registration profiles, trait anxiety scores and extreme defensive high anxious personality type. CONCLUSIONS:Trait sensory hyper- and/or hypo-sensitivity and high trait-anxiety related personality type characteristics predicts the extent of CS symptoms in people with NSCLBP. Further investigation is required to establish causality between these characteristics and CS symptoms. This article is protected by copyright. All rights reserved

    Can the triarchic model of psychopathy predict youth offender recidivism?

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    The triarchic model of psychopathy is one of the most influential models of psychopathy developed in recent years. The current aim is to investigate the utility of a self-report measure of the triarchic model of psychopathy in predicting criminal recidivism among a sample of incarcerated juvenile offenders. Male youth participants (N=228, M=16.38 years, SD=1.26 years) from the Detention Centers managed nation-wide by the Ministry of Justice of Portugal were followed during a two-year period and categorized as recidivists or non-recidivists. The Area Under the Curve (AUC) results showed that only the Disinhibition dimension of the triarchic model of psychopathy was able to significantly predict general recidivism. The binary logistic regression models controlling for relevant variables (e.g. age of first detention, past frequency of crimes, conduct disorder symptoms) found that the boldness, meanness, and disinhibition dimensions failed to predict general or violent recidivism. The overall findings suggest that the triarchic model of psychopathy demonstrates limited utility in terms of predicting recidivism among juvenile offenders.This work was partially supported by Portuguese Foundation for Science and Technology [grant number UID/PSI/01662/201

    Implementing Monte Carlo tests with P-value buckets

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    Software packages usually report the results of statistical tests using p-values. Users often interpret these by comparing them to standard thresholds, e.g. 0.1%, 1% and 5%, which is sometimes reinforced by a star rating (***, **, *). We consider an arbitrary statistical test whose p-value p is not available explicitly, but can be approximated by Monte Carlo samples, e.g. by bootstrap or permutation tests. The standard implementation of such tests usually draws a fixed number of samples to approximate p. However, the probability that the exact and the approximated p-value lie on different sides of a threshold (the resampling risk) can be high, particularly for p-values close to a threshold. We present a method to overcome this. We consider a finite set of user-specified intervals which cover [0,1] and which can be overlapping. We call these p-value buckets. We present algorithms that, with arbitrarily high probability, return a p-value bucket containing p. We prove that for both a bounded resampling risk and a finite runtime, overlapping buckets need to be employed, and that our methods both bound the resampling risk and guarantee a finite runtime for such overlapping buckets. To interpret decisions with overlapping buckets, we propose an extension of the star rating system. We demonstrate that our methods are suitable for use in standard software, including for low p-value thresholds occurring in multiple testing settings, and that they can be computationally more efficient than standard implementations

    Development of postural adjustments during reaching in typically developing infants from 4 to 18 months

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    Knowledge on the development of postural adjustments during infancy, in particular on the development of postural muscle coordination, is limited. This study aimed at the evaluation of the development of postural control during reaching in a supported sitting condition. Eleven typically developing infants participated in the study and were assessed at the ages of 4, 6, 10 and 18 months. We elicited reaching movements by presenting small toys at an arm’s length distance, whilst activity of multiple arm, neck and trunk muscles was recorded using surface EMG. A model-based computer algorithm was used to detect the onset of phasic muscle activity. The results indicated that postural muscle activity during reaching whilst sitting supported is highly variable. Direction-specific postural activity was inconsistently present from early age onwards and increased between 10 and 18 months without reaching a 100 % consistency. The dominant pattern of activation at all ages was the ‘complete pattern’, in which all direction-specific muscles were recruited. At 4 months, a slight preference for top-down recruitment existed, which was gradually replaced by a preference for bottom-up recruitment. We conclude that postural control during the ecological task of reaching during supported sitting between 4 and 18 months of age is primarily characterized by variation. Already from 4 months onwards, infants are—within the variation—sometimes able to select muscle recruitment strategies that are optimal to the task at hand

    Optimizing the Performance of Streaming Numerical Kernels on the IBM Blue Gene/P PowerPC 450 Processor

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    Several emerging petascale architectures use energy-efficient processors with vectorized computational units and in-order thread processing. On these architectures the sustained performance of streaming numerical kernels, ubiquitous in the solution of partial differential equations, represents a challenge despite the regularity of memory access. Sophisticated optimization techniques are required to fully utilize the Central Processing Unit (CPU). We propose a new method for constructing streaming numerical kernels using a high-level assembly synthesis and optimization framework. We describe an implementation of this method in Python targeting the IBM Blue Gene/P supercomputer's PowerPC 450 core. This paper details the high-level design, construction, simulation, verification, and analysis of these kernels utilizing a subset of the CPU's instruction set. We demonstrate the effectiveness of our approach by implementing several three-dimensional stencil kernels over a variety of cached memory scenarios and analyzing the mechanically scheduled variants, including a 27-point stencil achieving a 1.7x speedup over the best previously published results
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