What you should know about Zika virus testing : for pregnant women who may have been exposed to Zika 2-12 weeks ago

If you or your sex partner live in or recently traveled to an area with Zika, you may have been exposed to Zika. You may havequestions about Zika and how to find out if you\ue2\u20ac\u2122ve been infected. Learn more about Zika virus testing for pregnant womenand what you might expect if you have Zika virus during pregnancy.CS272943Date printed on piece: December 20, 2016.Date from document properties: modified 1/4/2017igm.pd

Analysis of the excited argon atoms in the GEC RF reference cell by means of one-dimensional PIC simulations

We examine the question of whether the excited states in argon contribute significantly to ionization in a capacitively coupled plasma through metastable pooling and step-ionization processes. We look at this issue by means of a one-dimensional particle-in-cell (PIC) code, with collisions treated by a Monte Carlo collision package. In the range explored, 50–1000 mTorr, the main source of ionization, in the absence of secondary emission, is direct ionization from the ground state with a contribution from excited states that is negligible at lower pressures, but increases in importance at higher pressures. When secondary electrons are included, their interaction with ground state neutrals dominates the ionization. At higher pressures the metastable profiles can reveal useful information on the non-uniform mean electron energy across the discharge, even though these states do not necessarily play a significant role in ionization

Atomic data for core and edge modeling needs

Future magnetic fusion energy devices, will have both very high Z (tungsten) and low Z (beryllium) plasma facing components, are setting the agenda for current atomic data needs. Data for the light species are in good shape but the heavy species present some challenges. We outline an approach for systematic heavy element data production for fusion applications in addition to techniques for handling the large amount of data in modeling codes efficiently