GPS Seismology for a moderate magnitude earthquake: Lessons learned from the analysis of the 31 October 2013 ML6.4 Ruisui (Taiwan) earthquake

The 31 October 2013 ML 6.4 Ruisui earthquake was well recorded by twelve 50-Hz, four 20-Hz and thirteen 1-Hz GPS receivers, and twenty-five strong motion stations located within the epicentral distance of 90 km in eastern Taiwan. Kinematic positioning solutions estimated by four GNSS software (TRACK, RTKLIB, GIPSY, VADASE) are used to derive the seismic waveforms and the co-seismic displacements for this event; strong motion accelerometers are used to verify the capability of high rate GPS to detect seismic waves generated by this earthquake. Results show that the coordinate repeatability of the GPS displacements time series are ~6 mm and ~20 mm standard deviation in the horizontal and vertical components respectively, after applying spatial filtering. The largest co-seismic displacement derived from high-rate GPS is nearly 15 centimeter at 5 km northeast of the epicenter. S waves and surface waves are successfully detected by motions of high-rate GPS and double-integrated accelerometers within the 15 km epicentral distance. For the first time twelve 50-Hz and four 20 Hz GPS observations for seismological study were used and analyzed in Taiwan; a clear benefit was evidenced with regard to the seismic waves features detection, with respect to the 1-Hz GPS data, so that ultra-high rate (> 1-Hz) observations can compensate the sparse coverage of seismic data, provided proper monuments for the GPS permanent stations are realized. Spectra analysis between co-located GPS and strong motion data further suggests that the optimal sampling rate for high-rate GPS Seismology study is 5 Hz. The 2013 Ruisui Taiwan earthquake recorded by the high-rate GPS permanent stations network in Taiwan demonstrates the benefits of GPS Seismology for a moderate size earthquake at a local scale

Contextual Label Projection for Cross-Lingual Structure Extraction

Translating training data into target languages has proven beneficial for cross-lingual transfer. However, for structure extraction tasks, translating data requires a label projection step, which translates input text and obtains translated labels in the translated text jointly. Previous research in label projection mostly compromises translation quality by either facilitating easy identification of translated labels from translated text or using word-level alignment between translation pairs to assemble translated phrase-level labels from the aligned words. In this paper, we introduce CLAP, which first translates text to the target language and performs contextual translation on the labels using the translated text as the context, ensuring better accuracy for the translated labels. We leverage instruction-tuned language models with multilingual capabilities as our contextual translator, imposing the constraint of the presence of translated labels in the translated text via instructions. We compare CLAP with other label projection techniques for creating pseudo-training data in target languages on event argument extraction, a representative structure extraction task. Results show that CLAP improves by 2-2.5 F1-score over other methods on the Chinese and Arabic ACE05 datasets.Comment: Work in Progres

MiniSUPERB: Lightweight Benchmark for Self-supervised Speech Models

Self-supervised learning (SSL) is a popular research topic in speech processing. Successful SSL speech models must generalize well. SUPERB was proposed to evaluate the ability of SSL speech models across many speech tasks. However, due to the diversity of tasks, the evaluation process requires huge computational costs. We present MiniSUPERB, a lightweight benchmark that efficiently evaluates SSL speech models with comparable results to SUPERB while greatly reducing the computational cost. We select representative tasks and sample datasets and extract model representation offline, achieving 0.954 and 0.982 Spearman's rank correlation with SUPERB Paper and SUPERB Challenge, respectively. In the meanwhile, the computational cost is reduced by 97% in regard to MACs (number of Multiply-ACcumulate operations) in the tasks we choose. To the best of our knowledge, this is the first study to examine not only the computational cost of a model itself but the cost of evaluating it on a benchmark

Perceptions, Behavioral Expectations, and Implementation Timing for Response Actions in a Hurricane Emergency

This study examined the perceived attributes, behavioral expectations, and expected implementation timing of 11 organizational emergency response actions for hurricane emergencies. The perceived attributes of the hurricane response actions were characterized by two hazard-related attributes (effectiveness for person protection and property protection) and five resource-related attributes (financial costs, required knowledge/skill, required equipment, required time/effort, and required cooperation). A total of 155 introductory psychology students responded to a hypothetical scenario involving an approaching Category 4 hurricane. The data collected in this study explain previous findings of untimely protective action decision making. Specifically, these data reveal distinctly different patterns for the expected implementation of preparatory actions and evacuation recommendations. Participants used the hazard-related and resource-related attributes to differentiate among the response actions and the expected timing of implementation. Moreover, participants’ behavioral expectations and expected implementation timing for the response actions were most strongly correlated with those actions’ effectiveness for person protection. Finally, participants reported evacuation implementation times that were consistent with a phased evacuation strategy in which risk areas are evacuated in order of their proximity to the coast. However, the late initiation of evacuation in risk areas closest to the coast could lead to very late evacuation of risk areas farther inland

The Anti-hepatitis B Virus Activity of Boehmeria nivea Extract in HBV-viremia SCID Mice

Boehmeria nivea extract (BNE) is widely used in southern Taiwan as a folk medicine for hepato-protection and hepatitis treatment. In previous studies, we demonstrated that BNE could reduce the supernatant hepatitis B virus (HBV) DNA in HBV-producing HepG2 2.2.15 cells. In the present study, we established an animal model of HBV viremia and used it to validate the efficacy of BNE in vivo. In this animal model, serum HBV DNA and HBsAg were elevated in accordance with tumor growth. To evaluate the anti-HBV activity of BNE, HBV-viremia mice were built up after one subcutaneous inoculation of HepG2 2.2.15 tumor cells in severe combined immunodeficiency mice over 13 days. The levels of serum HBV DNA were elevated around 105–106 copies per milliliter. Both oral and intraperitoneal administration of BNE were effective at inhibiting the production of HBsAg and HBV DNA, whereas tumor growth was not affected by all test articles. Intraperitoneal administration of BNE appeared to have greater potential to inhibit serum HBV DNA levels compared with oral administration under the same dosage. Notably, reduced natural killer cell activity was also observed after high dosage of BNE administration, and this correlated with reduced serum HBV DNA. In conclusion, BNE exhibited potential anti-HBV activity in an animal model of HBV viremia