Thrombopoietin receptor agonist therapy in primary immune thrombocytopenia is associated with bone marrow hypercellularity and mild reticulin fibrosis but not other stromal abnormalities

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Generating nested quadrature rules with positive weights based on arbitrary sample sets

For the purpose of uncertainty propagation a new quadrature rule technique is proposed that has positive weights, has high degree, and is constructed using onl

Bayesian model calibration with interpolating polynomials based on adaptively weighted Leja nodes

An efficient algorithm is proposed for Bayesian model calibration, which is commonly used to estimate the model parameters of non-linear, computationally expens

Bayesian model calibration with interpolating polynomials based on adaptively weighted Leja nodes

An efficient algorithm is proposed for Bayesian model calibration, which is commonly used to estimate the model parameters of non-linear, computationally expensive models using measurement data. The approach is based on Bayesian statistics: using a prior distribution and a likelihood, the posterior distribution is obtained through application of Bayes' law. Our novel algorithm to accurately determine this posterior requires significantly fewer discrete model evaluations than traditional Monte Carlo methods. The key idea is to replace the expensive model by an interpolating surrogate model and to construct the interpolating nodal set maximizing the accuracy of the posterior. To determine such a nodal set an extension to weighted Leja nodes is introduced, based on a new weighting function. We prove that the convergence of the posterior has the same rate as the convergence of the model. If the convergence of the posterior is measured in the Kullback-Leibler divergence, the rate doubles. The algorithm and its theoretical properties are verified in three different test cases: analytical cases that confirm the correctness of the theoretical findings, Burgers' equation to show its applicability in implicit problems, and finally the calibration of the closure parameters of a turbulence model to show the effectiveness for computationally expensive problems

Adult Attachment and Personal Recovery in Clients With a Psychotic Disorder

Background: Personal recovery has become a key objective in the treatment of clients with a psychotic disorder. So far it has been established that the two attachment dimensions, ie, anxious and avoidant, are negatively associated with subjective well-being, self-esteem and hope. This study is the first to explore whether attachment styles are related to personal recovery in this population. Aims: To study the effects of anxious and avoidant attachment on personal recovery in a population with a psychotic disorder. Method: This cross-sectional study is part of the UP's multicenter cohort study on recovery from psychotic disorders, in which 265 participants are currently included. Attachment was assessed using the Psychosis Attachment Measure, including the anxious and avoidant attachment dimensions. Personal recovery was measured using the Recovering Quality of Life-10 (ReQOL-10) and the Individual Recovery Outcomes Counter (I.ROC). Regression analysis was used to investigate the effect of attachment on personal recovery. Results: We found negative effects of the anxious attachment style on the total scores of the ReQoL-10 (b = -4.54, SE = 0.69, β = β0.37) and the I.ROC (b = -5.21, SE = 0.89, β = -0.32). Although there were also negative effects of the avoidant attachment style on the total scores of the ReQoL-10 (b = -3.08, SE = 0.93, β = -0.18) and the I.ROC (b = -4.24, SE = 1.24, β = -0.19), these were less pronounced. Conclusion: Results show that both forms of insecure attachment (anxious and avoidant) are related to poorer personal recovery in clients with a psychotic disorder.</p