As a consequence of a terrorist attack, people may experience posttraumatic stress disorder (PTSD) and lack of feeling secure in relationships. This longitudinal study aimed to examine the prevalence of PTSD symptoms over time, the relationship between adult attachment styles and PTSD, as well as their association with degree of exposure, and finally to consider the distribution and the trajectory of attachment styles. The sample consisted of 235 students (M=125, F=110) who were exposed to different levels of trauma intensity in response to a bombing attack. Participants were recruited and assessed approximately 1 month and 5 months after the attack using a battery of questionnaires. Findings revealed, as expected, that 79.5% of the participants met the criteria for current probable PTSD and 78.2% endorsed one of the three insecure attachment dimensions at baseline, which declined over time. Correlational analyses revealed a significant positive relationship between intensity of exposure and both PTSD symptoms and insecure attachment. The results confirm and extend previous findings on the association between direct exposure to life-threatening situation and the risk of behavioural and emotional problems among civilians, which may present as non-specific psychopathology.
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
... Show MoreReservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and
... Show MoreIn this review of literature, the light will be concentrated on the role of stem cells as an approach in periodontal regeneration.
DBNRAHA Hameed, IJRSSH PUBLICATION, 2018
Dylan Thomas (1914-1953) is a modern poet belongs to the apocalyptic movement of the 1940's.This movement is influenced by the doctrines and techniques of surrealism.
Poetry for him should not be primarily concerned with man in society, but with the celebration of spiritual truth. It should bring to light the hidden causes, hence his personal interest is to strip darkness and explore the inward motives. To do this he uses a cluster of images: a constant building up and breaking down of images. His poetry depends on the romantic spontaneity, suggestiveness of the Symbolists and the the surrealists' mysterious liberation of the unconsciousness and
... Show MoreDylan Thomas (1914-1953) is a modern poet belongs to the apocalyptic movement of the 1940's.This movement is influenced by the doctrines and techniques of surrealism. Poetry for him should not be primarily concerned with man in society, but with the celebration of spiritual truth. It should bring to light the hidden causes, hence his personal interest is to strip darkness and explore the inward motives. To do this he uses a cluster of images: a constant building up and breaking down of images. His poetry depends on the romantic spontaneity, suggestiveness of the Symbolists and the the surrealists' mysterious liberation of the unconsciousness and the emotional involvement in the dynamics of life. In "Light Breaks
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