Bayesian additive regression trees (BART) has become increasingly popular as a flexible and scalable non-parametric model useful in many modern applied statistics regression problems. It brings many advantages to the practitioner dealing with large and complex non-linear response surfaces, such as a matrix-free formulation and the lack of a requirement to specify a regression basis a priori. Ho...

The regulation of mRNA stability plays an important role in the control of gene expression during cell motility and invasion. We previously reported that GTPase-activating protein [Src homology 3 (SH3) domain] binding protein (G3BP), a marker of cytoplasmic stress granules that are formed in stressed cells and regulate mRNA stability, binds and degrades the mRNA of binder of Arl two (BART) that...

Despite evidence supporting a relationship between impulsivity and naturalistic risk-taking, the relationship of impulsivity with laboratory-based measures of risky decision-making remains unclear. One factor contributing to this gap in our understanding is the degree to which different risky decision-making tasks vary in their details. We conducted an fMRI investigation of the Angling Risk Tas...

BACKGROUND Arm nonuse, defined as the difference between what the individual can do when constrained to use the paretic arm and what the individual does when given a free choice to use either arm, has not yet been quantified in individuals poststroke. OBJECTIVES (1) To quantify nonuse poststroke and (2) to develop and test a novel, simple, objective, reliable, and valid instrument, the Bilate...

Depression is associated with altered sensitivity to reward and punishment, which can influence complex decision-making. We examined punishment sensitivity in the performance of participants with major depressive disorder (MDD) with that of a comparison group on the automatic Balloon Analogue Risk Task (BART), which is a direct measure of risk taking. The present study examined the BART perform...

The emergence of attention-based architectures has led to significant improvements in the performance neural sequence-to-sequence models for text summarization. Although these have proved be effective summarizing English-written documents, their portability other languages is limited thus leaving plenty room improvement. In this paper, we present BART-IT, a model, based on BART architecture tha...