Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
For the past decade, temporal annotation has been sparse: only a small portion of event pairs in a text was annotated. We present NarrativeTime, the first timeline-based annotation framework that achieves full coverage of all possible TLINKs. To compare with the previous SOTA in dense temporal annotation, we perform full re-annotation of the classic TimeBankDense corpus (American English), which shows comparable agreement with a signigicant increase in density. We contribute TimeBankNT corpus (with each text fully annotated by two expert annotators), extensive annotation guidelines, open-source tools for annotation and conversion to TimeML format, and baseline results.more » « less
-
The recent explosion in question answering research produced a wealth of both factoid reading comprehension (RC) and commonsense reasoning datasets. Combining them presents a different kind of task: deciding not simply whether information is present in the text, but also whether a confident guess could be made for the missing information. We present QuAIL, the first RC dataset to combine text-based, world knowledge and unanswerable questions, and to provide question type annotation that would enable diagnostics of the reasoning strategies by a given QA system. QuAIL contains 15K multi-choice questions for 800 texts in 4 domains. Crucially, it offers both general and text-specific questions, unlikely to be found in pretraining data. We show that QuAIL poses substantial challenges to the current state-of-the-art systems, with a 30% drop in accuracy compared to the most similar existing dataset.more » « less
-
Liu, W.; Wang, Y.; Guo, B.; Tang, X.; Zeng, S. (Ed.)Sensitivity studies have shown that the 15 O(α, γ) 19 Ne reaction is the most important reaction rate uncertainty affecting the shape of light curves from Type I X-ray bursts. This reaction is dominated by the 4.03 MeV resonance in 19 Ne. Previous measurements by our group have shown that this state is populated in the decay sequence of 20 Mg. A single 20 Mg(βp α) 15 O event through the key 15 O(α, γ) 19 Ne resonance yields a characteristic signature: the emission of a proton and alpha particle. To achieve the granularity necessary for the identification of this signature, we have upgraded the Proton Detector of the Gaseous Detector with Germanium Tagging (GADGET) into a time projection chamber to form the GADGET II detection system. GADGET II has been fully constructed, and is entering the testing phase.more » « less
-
Liu, W.; Wang, Y.; Guo, B.; Tang, X.; Zeng, S. (Ed.)15 O( α , γ ) 19 Ne is regarded as one of the most important thermonuclear reactions in type I X-ray bursts. For studying the properties of the key resonance in this reaction using β decay, the existing Proton Detector component of the Gaseous Detector with Germanium Tagging (GADGET) assembly is being upgraded to operate as a time projection chamber (TPC) at FRIB. This upgrade includes the associated hardware as well as software and this paper mainly focusses on the software upgrade. The full detector set up is simulated using the ATTPCROOTv 2 data analysis framework for 20 Mg and 241 Am.more » « less
-
Abstract Reconnection in the magnetotail occurs along so‐called X‐lines, where magnetic field lines tear and detach from plasma on microscopic spatial scales (comparable to particle gyroradii). In 2017–2020, the Magnetospheric MultiScale (MMS) mission detected X‐lines in the magnetotail enabling their investigation on local scales. However, the global structure and evolution of these X‐lines, critical for understanding their formation and total energy conversion mechanisms, remained virtually unknown because of the intrinsically local nature of observations and the extreme sparsity of concurrent data. Here, we show that mining a multi‐mission archive of space magnetometer data collected over the last 26 yr and then fitting a magnetic field representation modeled using flexible basis‐functions faithfully reconstructs the global pattern of X‐lines; 24 of the 26 modeled X‐lines match (Bz = 0 isocontours are within ∼2 Earth radii orRE) or nearly match (Bz = 2 nT isocontours are within ∼2RE) the locations of the MMS encountered reconnection sites. The obtained global reconnection picture is considered in the context of substorm activity, including conventional substorms and more complex events.more » « less
An official website of the United States government

Full Text Available