Implementing family involvement in the treatment of patients with psychosis: a systematic review of facilitating and hindering factors

This paper presents independent research and was partially funded by the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (NIHR CLAHRC) North Thames at Bart's Health NHS Trust

Une espèce peu connue de la forêt méditerranéenne : Liquidambar orientalis

Présente les principales caractéristiques écologiques de l'espèce, arbre feuillu endémique (et relique) de la Turquie

An Investigation of the Relationship between Academic Achievement, Socio-economic Status, Cognitive Abilities, and Self-perceived Mathematical Abilities in High School Students.

We investigated mathematical skills in students from schools with different levels of socio-economic status. The purpose of the study was to identify the cognitive and subjective measures, which may be related to results in General Certificate of Secondary Education Mathematics Exam and mathematical self-assessment. The results of the multiple regression analyses and of group comparisons partially supported the hypotheses of the study and formed the basis for the formulation of new research question

Conditional Adversarial Camera Model Anonymization

The model of camera that was used to capture a particular photographic image (model attribution) is typically inferred from high-frequency model-specific artifacts present within the image. Model anonymization is the process of transforming these artifacts such that the apparent capture model is changed. We propose a conditional adversarial approach for learning such transformations. In contrast to previous works, we cast model anonymization as the process of transforming both high and low spatial frequency information. We augment the objective with the loss from a pre-trained dual-stream model attribution classifier, which constrains the generative network to transform the full range of artifacts. Quantitative comparisons demonstrate the efficacy of our framework in a restrictive non-interactive black-box setting.Comment: ECCV 2020 - Advances in Image Manipulation workshop (AIM 2020

Why involve families in acute mental healthcare? A collaborative conceptual review

This article presents independent research funded by the National Institute for Health Research (NIHR), the East London NHS Foundation Trust and the Centre for Public Engagement (CPE) at Queen Mary University of London (QMUL). AD is funded by the NIHR Doctoral Research Fellowship (DRF-2015-08-071). DG was supported by the NIHR Collaboration for Leadership in Applied Health Research and Care (CLAHRC) North Thames at Barts Health NHS Trust. KB, GB and SC were supported by the Centre for Public Engagement at QMUL

Online identification of cascading events in power systems with renewable generation using measurement data and machine learning

This paper introduces a framework for online identification of cascading events in power systems with renewable generation, based on supervised machine learning techniques and measurement data. Cascading events are low-probability, high-impact events, the propagation of which can lead even to large-scale blackouts, with severe consequences to society. The proposed methodology is based on Long-short term memory networks, considering uncertainties associated with renewable generation, system loading and initial contingencies. By utilizing time-series measurement data, the proposed method can predict the appearance of cascading events, as defined by the discrete action of protection devices which can capture voltage, frequency or transient instability related dynamic phenomena. The proposed framework is applied on a modified version of the IEEE-39 bus model incorporating detailed dynamic renewable generation and protection devices implementations. Results highlight that the suggested method can successfully identify cases with cascading events with up to 95.6% accuracy and with an average inference time of 0.042s, taking into account practical considerations related to phasor measurement units, such as availability and noise in measurement data

Personality, posttraumatic stress and trauma type: factors contributing to posttraumatic growth and its domains in a Turkish community sample

Background: Posttraumatic growth (PTG) is conceptualized as a positive transformation resulting from coping with and processing traumatic life events. This study examined the contributory roles of personality traits, posttraumatic stress (PTS) severity and their interactions on PTG and its domains, as assessed with the Posttraumatic Growth Inventory Turkish form (PTGI-T). The study also examined the differences in PTG domains between survivors of accidents, natural disasters and unexpected loss of a loved one. Methods: The Basic Personality Traits Inventory, Posttraumatic Diagnostic Scale, and PTGI-T were administered to a large stratified cluster community sample of 969 Turkish adults in their home settings. Results: The results showed that conscientiousness, agreeableness, and openness to experience significantly related to the total PTG and most of the domains. The effects of extraversion, neuroticism and openness to experience were moderated by the PTS severity for some domains. PTG in relating to others and appreciation of life domains was lower for the bereaved group. Conclusion: Further research should examine the mediating role of coping between personality and PTG using a longitudinal design

Education of artificial ant colony algorithm and usage in analysis of substance corner

In this study, information was given about flock intelligence, any colony and artificial nervous network, by using ant colony algorithm image edge that suitable result was found. Each pixel of the used image will represent the way that ant will follow for finding edge Pheromone collected between two pixels will help ant to find the point which are near each other. Performance of the found result was compared with Tion J. method

Une espèce peu connue de la forêt méditerranéenne : Liquidambar orientalis

International audiencePrésente les principales caractéristiques écologiques de l'espèce, arbre feuillu endémique (et relique) de la Turquie

Carbamazepine and valproic acid: Effects on the serum lipids and liver functions in children

We aimed to determine the effects of carbamazepine, which induces liver microsomal enzymes, and valproic acid on the serum lipids and liver function test results in epileptic children. Thirty-eight epileptic children (18 males, 20 females, mean age 8.6 +/- 3.9 years) were evaluated for serum lipids and liver function test results at the onset and the second and sixth months of antiepileptic therapy. The results of the children receiving carbamazepine (n = 31) and valproic acid (n = 7) were compared. In addition, the values obtained at different periods of treatment were compared within each group. The differences in the serum lipid levels and liver function test results of the children in the carbamazepine group and the valproic acid group were not statistically significant throughout the study. However, the total cholesterol, low-density lipoprotein, total cholesterol/high-density lipoprotein, and gamma glutamyl transferase levels were significantly increased in the carbamazepine group during treatment (P < 0.05) but not in the valproic acid group. Carbamazepine treatment alters the serum lipid profile of the children in such a way that it facilitates the development of atherosclerosis, Valproic acid does not alter the levels of the serum lipids. (C) 2000 by Elsevier Science Inc. All rights reserved