scholarly journals The effect of toxicity on COVID-19 news network formation in political subcommunities on Reddit: An affiliation network approach

2021 ◽  
Vol 61 ◽  
pp. 102397
Author(s):  
Wallace Chipidza
2013 ◽  
Vol 89 (Suppl 1) ◽  
pp. A295.2-A295
Author(s):  
A M Niekamp ◽  
C J P A Hoebe ◽  
L A G Mercken ◽  
N H T M Dukers-Muijrers

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.


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.


1986 ◽  
Vol 56 (01) ◽  
pp. 023-027 ◽  
Author(s):  
C J Jen ◽  
L V McIntire

SummaryWhether platelet microtubules are involved in clot retraction/ contraction has been controversial. To address this question we have simultaneously measured two clotting parameters, clot structural rigidity and isometric contractile force, using a rheological technique. For recalcified PRP clots these two parameters began rising together at about 15 min after CaCl2 addition. In the concentration range affecting microtubule organization in platelets, colchicine, vinca alkaloids and taxol demonstrated insignificant effects on both clotting parameters of a recalcified PRP clot. For PRP clots induced by adding small amounts of exogenous thrombin, the kinetic curves of clot rigidity were biphasic and without a lag time. The first phase corresponded to a platelet-independent network forming process, while the second phase corresponded to a platelet-dependent process. These PRP clots began generating contractile force at the onset of the second phase. For both rigidity and force parameters, only the second phase of clotting kinetics was retarded by microtubule affecting reagents. When PRP samples were clotted by adding a mixture of CaCl2 and thrombin, the second phase clotting was accelerated and became superimposed on the first phase. The inhibitory effects of micro tubule affecting reagents became less pronounced. Thrombin clotting of a two-component system (washed platelets/ purified fibrinogen) was also biphasic, with the second phase being microtubule-dependent. In conclusion, platelet microtubules are important in PRP clotted with low concentrations of thrombin, during which fibrin network formation precedes platelet-fibrin interactions. On the other hand they are unimportant if a PRP clot is induced by recalcification, during which the fibrin network is constructed in the presence of platelet-fibrin interactions. The latter is likely to be more analogous to physiological processes in vivo.


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