Wang, Rui; Guo, Xuehui; Pan, Da; Kelly, James; Bash, Jesse; Sun, Kang; Paulot, Fabien; Clarisse, Lieven; Van Damme, Martin; Whitburn, Simon; Coheur, Pierre-François; Clerbaux, Cathy; Zondlo, Mark
Monthly, high resolution (~2 km) ammonia (NH3) column maps from the Infrared Atmospheric Sounding Interferometer (IASI) were developed across the contiguous United States and adjacent areas. Ammonia hotspots (95th percentile of the column distribution) were highly localized with a characteristic length scale of 12 km and median area of 152 km2. Five seasonality classes were identified with k-means++ clustering. The Midwest and eastern United States had a broad, spring maximum of NH3 (67% of hotspots in this cluster). The western United States, in contrast, showed a narrower mid-summer peak (32% of hotspots). IASI spatiotemporal clustering was consistent with those from the Ammonia Monitoring Network. CMAQ and GFDL-AM3 modeled NH3 columns have some success replicating the seasonal patterns but did not capture the regional differences. The high spatial-resolution monthly NH3 maps serve as a constraint for model simulations and as a guide for the placement of future, ground-based network sites.
Current sheet and open field lines with footpoints near the edge of the polar cap. The magnetic axis is inclined relative to the rotation axis by 60 degrees. Red
field lines originate on the north polar cap and green field lines in the right panel originate on the south polar cap. Purple and grey colors indicate positive and negative net
local charge density in the current sheet, which is shown between 1.2-2 light cylinder radii.
Current sheet and open field lines with footpoints near the edge of the polar cap. The magnetic axis is inclined relative to the rotation axis by 90 degrees. Red field lines originate on the north polar cap and green field lines in the right panel originate on the south polar cap. Purple and grey colors indicate positive and negative net local charge density in the current sheet, which is shown between 1.2-2 light cylinder radii.
Kinetic modification of ideal stability theory from stabilizing resonances of mode-particle interaction has had success in explaining resistive wall mode (RWM) stability limits in tokamaks. With the goal of real-time stability forecasting, a reduced kinetic stability model has been implemented in the new Disruption Event Characterization and Forecasting (DECAF) code, which has been written to analyze disruptions in tokamaks. The reduced model incorporates parameterized models for ideal limits on beta, a ratio of plasma pressure to magnetic pressure, which are shown to be in good agreement with DCON code calculations. Increased beta between these ideal limits causes a shift in the unstable region of delta W_K space, where delta W_K is the change in potential energy due to kinetic effects that is solved for by the reduced model, such that it is possible for plasmas to be unstable at intermediate beta but stable at higher beta. Gaussian functions for delta W_K are defined as functions of E cross B frequency and collisionality, with parameters reflecting the experience of the National Spherical Torus Experiment (NSTX). The reduced model was tested on a database of discharges from NSTX and experimentally stable and unstable discharges were separated noticeably on a stability map in E cross B frequency, collisionality space. The reduced model only failed to predict an unstable RWM in 15.6% of cases with an experimentally unstable RWM and performed well on predicting stability for experimentally stable discharges as well.
To effectuate near real-time feedback control of ideal MHD instabilities in a tokamak geometry, a rapid solution for stability analysis is a prerequisite. Toward this end, we reformulate the δW stability method with a Hamilton-Jacobi theory, elucidating analytical and numerical features of the generic tokamak ideal MHD stability problem. The plasma response matrix is demonstrated to be the solution of an ideal MHD matrix Riccati differential equation (MRDE). Since Riccati equations are prevalent in the control theory literature, such a shift in perspective brings to bear a range of numerical methods that are well-suited to the robust, fast solution of control problems. We discuss the usefulness of Riccati techniques in solving the stiff ODEs often encountered in ideal MHD stability analyses-—for example, in tokamak edge and stellarator physics. We then demonstrate the applicability of such methods to an existing 2D ideal MHD stability code—DCON—enabling its parallel operation in near real-time. Output is shown to match with high accuracy, and with wall-clock time ≪ 1s. Such speed may help enable active feedback ideal MHD stability control, especially in tokamak plasmas whose ideal MHD equilibria evolve with inductive timescale τ > 1s-—as in ITER.
Martin, James K; Sheehan, Joseph P; Bratton, Benjamin P; Moore, Gabriel M; Mateus, André; Li, Sophia Hsin-Jung; Kim, Hahn; Rabinowitz, Joshua D; Typas, Athanasios; Savitski, Mikhail M; Wilson, Maxwell Z; Gitai, Zemer
The rise of antibiotic resistance and declining discovery of new antibiotics have created a global health crisis. Of particular concern, no new antibiotic classes have been approved for treating Gram-negative pathogens in decades. Here, we characterize a compound, SCH-79797, that kills both Gram-negative and Gram-positive bacteria through a unique dual-targeting mechanism of action (MoA) with undetectably-low resistance frequencies. To characterize its MoA, we combined quantitative imaging, proteomic, genetic, metabolomic, and cell-based assays. This pipeline demonstrates that SCH-79797 has two independent cellular targets, folate metabolism and bacterial membrane integrity, and outperforms combination treatments in killing MRSA persisters. Building on the molecular core of SCH-79797, we developed a derivative, Irresistin-16, with increased potency and showed its efficacy against Neisseria gonorrheae in a mouse vaginal infection model. This promising antibiotic lead suggests that combining multiple MoAs onto a single chemical scaffold may be an underappreciated approach to targeting challenging bacterial pathogens.