scholarly journals Excessive Worrying as a Central Feature of Anxiety during the First COVID-19 Lockdown-Phase in Belgium: Insights from a Network Approach

2021 ◽  
Vol 61 (1) ◽  
pp. 401
Author(s):  
Alexandre Heeren ◽  
Bernard Hanseeuw ◽  
Louise-Amélie Cougnon ◽  
Grégoire Lits
2019 ◽  
Vol 3 (1) ◽  
pp. 97-105
Author(s):  
Mary Zuccato ◽  
Dustin Shilling ◽  
David C. Fajgenbaum

Abstract There are ∼7000 rare diseases affecting 30 000 000 individuals in the U.S.A. 95% of these rare diseases do not have a single Food and Drug Administration-approved therapy. Relatively, limited progress has been made to develop new or repurpose existing therapies for these disorders, in part because traditional funding models are not as effective when applied to rare diseases. Due to the suboptimal research infrastructure and treatment options for Castleman disease, the Castleman Disease Collaborative Network (CDCN), founded in 2012, spearheaded a novel strategy for advancing biomedical research, the ‘Collaborative Network Approach’. At its heart, the Collaborative Network Approach leverages and integrates the entire community of stakeholders — patients, physicians and researchers — to identify and prioritize high-impact research questions. It then recruits the most qualified researchers to conduct these studies. In parallel, patients are empowered to fight back by supporting research through fundraising and providing their biospecimens and clinical data. This approach democratizes research, allowing the entire community to identify the most clinically relevant and pressing questions; any idea can be translated into a study rather than limiting research to the ideas proposed by researchers in grant applications. Preliminary results from the CDCN and other organizations that have followed its Collaborative Network Approach suggest that this model is generalizable across rare diseases.


2013 ◽  
Vol 44 (5) ◽  
pp. 303-310 ◽  
Author(s):  
Simon M. Laham ◽  
Yoshihisa Kashima

Goals are a central feature of narratives, and, thus, narratives may be particularly potent means of goal priming. Two studies examined two features of goal priming (postdelay behavioral assimilation and postfulfillment accessibility) that have been theorized to distinguish goal from semantic construct priming. Across the studies, participants were primed with high achievement, either in a narrative or nonnarrative context and then completed either a behavioral task, followed by a measure of construct accessibility, or a behavioral task after a delay. Indicative of goal priming, narrative-primed participants showed greater postdelay behavioral assimilation and less postfulfillment accessibility than those exposed to the nonnarrative prime. The implications of goal priming from narratives are discussed in relation to both theoretical and methodological issues.


2018 ◽  
Vol 125 (4) ◽  
pp. 606-615 ◽  
Author(s):  
Laura F. Bringmann ◽  
Markus I. Eronen
Keyword(s):  

2018 ◽  
Vol 106 (6) ◽  
pp. 603 ◽  
Author(s):  
Bendaoud Mebarek ◽  
Mourad Keddam

In this paper, we develop a boronizing process simulation model based on fuzzy neural network (FNN) approach for estimating the thickness of the FeB and Fe2B layers. The model represents a synthesis of two artificial intelligence techniques; the fuzzy logic and the neural network. Characteristics of the fuzzy neural network approach for the modelling of boronizing process are presented in this study. In order to validate the results of our calculation model, we have used the learning base of experimental data of the powder-pack boronizing of Fe-15Cr alloy in the temperature range from 800 to 1050 °C and for a treatment time ranging from 0.5 to 12 h. The obtained results show that it is possible to estimate the influence of different process parameters. Comparing the results obtained by the artificial neural network to experimental data, the average error generated from the fuzzy neural network was 3% for the FeB layer and 3.5% for the Fe2B layer. The results obtained from the fuzzy neural network approach are in agreement with the experimental data. Finally, the utilization of fuzzy neural network approach is well adapted for the boronizing kinetics of Fe-15Cr alloy.


2014 ◽  
Vol 4 (2) ◽  
pp. 122-138
Author(s):  
Keith Clavin

This essay examines Fagin from Oliver Twist as a villain whose construction joins Victorian anxieties about counterfeiting and economic deceptiveness with separate yet related concerns about the author's role in representing criminal life. Dickens triangulates Fagin's identity through cultural fears about Jewish participation within secondary markets, increased distance between purchaser and seller in an expanding credit economy, and moral ambiguities in respect to fiction-making. Read against non-literary Victorian writing about counterfeiters and crime, Fagin can be understood as a forger of identities and narratives. His ability to exploit interpersonal belief and economic value is a central feature of his villainy and one with precedent in other aspects of Victorian financial life. Dickens critiques capitalist culture by associating it with the imitative, fictional, and Jewish culture. In contrast, he aligns sincerity and truth with the middle-class, normative characters. Throughout, he marks the distinction between these two groups with comic incidence. The marginalised figures are fodder for humour and irony, while the conventional heroes are earnest.


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