The fundamental nature and extent of the coronal line region (CLR), which may serve as a vital tracer for Active Galactic Nucleus (AGN) activity, remain unresolved. Previous studies suggest that the CLR is produced by AGN-driven outflows and occupies a distinct region between the broad line region and the narrow line region, which places it tens to hundreds of parsecs from the galactic center. Here, we investigate 10 coronal line (CL; ionization potential $\ge$ 100 eV) emitting galaxies from the SDSS-IV MaNGA catalog with emission from one or more CLs detected at $\ge$ $5{\sigma}$ above the continuum in at least 10 spaxels - the largest such MaNGA catalog. We find that the CLR is far more extended, reaching out to 1.3 - 23 kpc from the galactic center. We cross-match our sample of 10 CL galaxies with the largest existing MaNGA AGN catalog and identify 7 in it; two of the remaining three are galaxy mergers and the final one is an AGN candidate. Further, we measure the average CLR electron temperatures to range between 12,331 K - 22,530 K, slightly above the typical threshold for pure AGN photoionization ($\sim$ 20,000 K) and indicative of shocks (e.g., merger-induced or from supernova remnants) in the CLR. We reason that ionizing photons emitted by the central continuum source (i.e. AGN photoionization) primarily generate the CLs, and that energetic shocks are an additional ionization mechanism that likely produce the most extended CLRs we measure.

We derive a quantum master equation to treat quantum systems interacting with multiple reservoirs. The formalism is used to investigate atomic transport across a variety of lattice configurations. We demonstrate how the behavior of an electronic diode, a field-effect transistor, and a bipolar junction transistor can be realized with neutral, ultracold atoms trapped in optical lattices. An analysis of the current fluctuations is provided for the case of the atomtronic diode. Finally, we show that it is possible to demonstrate AND logic gate behavior in an optical lattice.

To understand the complexity of global events, one must navigate a web of interwoven sub-events, identifying those most impactful elements within the larger, abstract macro-event framework at play. This concept can be extended to the field of natural language processing (NLP) through the creation of structured event schemas which can serve as representations of these abstract events. Central to our approach is the Schema Curation Interface 3.0 (SCI 3.0), a web application that facilitates real-time editing of event schema properties within a generated graph e.g., adding, removing, or editing sub-events, entities, and relations directly through an interface.

Discourse relation classification is an especially difficult task without explicit context markers (Prasad et al., 2008). Current approaches to implicit relation prediction solely rely on two neighboring sentences being targeted, ignoring the broader context of their surrounding environments (Atwell et al., 2021). In this research, we propose three new methods in which to incorporate context in the task of sentence relation prediction: (1) Direct Neighbors (DNs), (2) Expanded Window Neighbors (EWNs), and (3) Part-Smart Random Neighbors (PSRNs). Our findings indicate that the inclusion of context beyond one discourse unit is harmful in the task of discourse relation classification.