Cardiac Computed Tomography for Cardioembolic Stroke Evaluation in a Patient With a Mechanical Aortic Valve.

We present a case of cardioembolic stroke in a patient with a history of mechanical aortic valve who was compliant with anticoagulation medication. Cardiac computed tomography was used as an alternative, noninvasive means of evaluation for the cardioembolic source of stroke and identified subvalvular mobile pannus of the mechanical aortic valve.

Measures of wave intensity as a non-invasive surrogate for cardiac function predicts mortality in haemodialysis patients.

Background: Risk prediction in haemodialysis (HD) patients is challenging due to the impact of the dialysis regime on the patient's volume status and the complex interplay with cardiac function, comorbidities and hypertension. Cardiac function as a key predictor of cardiovascular (CV) mortality in HD patients is challenging to assess in daily routine. Thus the aim of this study was to investigate the association of a novel, non-invasive relative index of systolic function with mortality and to assess its interplay with volume removal.

Potential exposure of honey bees to neonicotinoid seed treatments in US rice.

Neonicotinoid insecticide seed treatments are commonly used in rice (Oryza sativa) production to control rice water weevil (Lisorhoptrus oryzophilus). With the use of neonicotinoid seed treatments, there is potential that honey bees (Apis mellifera) could be exposed to neonicotinoids through translocation to the pollen. Studies were conducted in 2015 and 2016 to determine the level of neonicotinoids present in flag leaves, pollen, and grain of rice.

Sampling bias corrections for accurate neural measures of redundant, unique, and synergistic information.

Shannon Information theory has long been a tool of choice to measure empirically how populations of neurons in the brain encode information about cognitive variables. Recently, Partial Information Decomposition (PID) has emerged as principled way to break down this information into components identifying not only the unique information carried by each neuron, but also whether relationships between neurons generate synergistic or redundant information. While it has been long recognized that Shannon information measures on neural activity suffer from a (mostly upward) limited sampling estimation bias, this issue has largely been ignored in the burgeoning field of PID analysis of neural activity.

Optimizing Epoxy Molding Compound Processing: A Multi-Sensor Approach to Enhance Material Characterization and Process Reliability.

The in-line control of curing during the molding process significantly improves product quality and ensures the reliability of packaging materials with the required thermo-mechanical and adhesion properties. The choice of the morphological and thermo-mechanical properties of the molded material, and the accuracy of their determination through carefully selected thermo-analytical methods, play a crucial role in the qualitative prediction of trends in packaging product properties as process parameters are varied. This work aimed to verify the quality of the models and their validation using a highly filled molding resin with an identical chemical composition but 10 wt% difference in silica particles (SPs).