4,017 research outputs found

    g-Factors and the Interplay of Collective and Single-Particle Degrees of Freedom in Superdeformed Mass-190 Nuclei

    Get PDF
    Interplay of collective and single-particle degrees of freedom is a common phenomenon in strongly correlated many-body systems. Despite many successful efforts in the study of superdeformed nuclei, there is still unexplored physics that can be best understood only through the nuclear magnetic properties. We point out that study of the gyromagnetic factor (g-factor) may open a unique opportunity for understanding superdeformed structure. Our calculations suggest that investigation of the g-factor dependence on spin and particle number can provide important information on single-particle structure and its interplay with collective motion in the superdeformed mass-190 nuclei. Modern experimental techniques combined with the new generation of sensitive detectors should be capable of testing our predictions.Comment: 4 pages, 2 eps figures, accepted by Phys. Rev.

    Computational Job Market Analysis:with Natural Language Processing

    Get PDF
    Recent technological advances underscore the dynamic nature of the labormarket. These transformative shifts yield significant consequences foremployment prospects, resulting in the increase of job vacancy data acrossplatforms and languages. The aggregation of such data holds the potentialto gain valuable insights into labor market demands, the emergence ofnew skills, and the overall facilitation of job matching. These benefitsextend to various parties, including job platforms, recruitment agencies,applicants, and other stakeholders within the ecosystem. However, despitethe prevalence of such insights in the private sector, we lack transparentlanguage technology systems and data for this domain.The primary objective of this thesis is to investigate the use of NaturalLanguage Processing (NLP) technology for the extraction of relevantinformation from job descriptions. We identify several general challengeswithin this domain. These encompass a scarcity of available training andevaluation data, a lack of standardized guidelines to annotate data, and ashortage of effective methods for extracting information from job ads.Therefore, we embark on a comprehensive study of the entire process:First, framing the problem and getting annotated data for training NLPmodels. Here, our contributions encompass job description datasets, includinga de-identification dataset, and a novel active learning algorithmdesigned for efficient model training. Second, we introduce several extractionmethodologies to tackle the task of information extraction from jobadvertisement data: A skill extraction approach using weak supervision,a taxonomy-aware pre-training methodology adapting a multilingual languagemodel to the job market domain, and a retrieval-augmented modelleveraging multiple skill extraction datasets to enhance overall extractionperformance. Lastly, given the extracted information, we delve into thegrounding of this data within a designated taxonomy

    Temporal Profiles and Spectral Lags of XRF 060218

    Get PDF
    The spectral and temporal properties of the non-thermal emission ofthe nearby XRF 060218 in 0.3-150 keV band are studied. We show that both the spectral energy distribution and the light curve properties suggest the same origin of the non-thermal emission detected by {\em Swift} BAT and XRT. This event has the longest pulse duration and spectral lag observed to date among the known GRBs. The pulse structure and its energy dependence are analogous to typical GRBs. By extrapolating the observed spectral lag to the {\em CGRO/BATSE} bands we find that the hypothesis that this event complies with the same luminosity-lag relation with bright GRBs cannot be ruled out at 2σ2\sigma significance level. These intriguing facts, along with its compliance with the Amati-relation, indicate that XRF 060218 shares the similar radiation physics as typical GRBs.Comment: 9 pages in emulateapj format, including 4 figures and 1 table, accepted for publication in ApJ Letter

    VAMP721 conformations unmask an extended motif for K+ channel binding and gating control

    Get PDF
    Soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins play a major role in membrane fusion and contribute to cell expansion, signaling, and polar growth in plants. The SNARE SYP121 of Arabidopsis thaliana that facilitates vesicle fusion at the plasma membrane also binds with, and regulates, K+ channels already present at the plasma membrane to affect K+ uptake and K+-dependent growth. Here, we report that its cognate partner VAMP721, which assembles with SYP121 to drive membrane fusion, binds to the KAT1 K+ channel via two sites on the protein, only one of which contributes to channel-gating control. Binding to the VAMP721 SNARE domain suppressed channel gating. By contrast, interaction with the amino-terminal longin domain conferred specificity on VAMP721 binding without influencing gating. Channel binding was defined by a linear motif within the longin domain. The SNARE domain is thought to wrap around this structure when not assembled with SYP121 in the SNARE complex. Fluorescence lifetime analysis showed that mutations within this motif, which suppressed channel binding and its effects on gating, also altered the conformational displacement between the VAMP721 SNARE and longin domains. The presence of these two channel-binding sites on VAMP721, one also required for SNARE complex assembly, implies a well-defined sequence of events coordinating K+ uptake and the final stages of vesicle traffic. It suggests that binding begins with VAMP721, and subsequently with SYP121, thereby coordinating K+ channel gating during SNARE assembly and vesicle fusion. Thus, our findings also are consistent with the idea that the K+ channels are nucleation points for SNARE complex assembly
    corecore