Smart Speech Segmentation using Acousto-Linguistic Features with look-ahead

Segmentation for continuous Automatic Speech Recognition (ASR) has traditionally used silence timeouts or voice activity detectors (VADs), which are both limited to acoustic features. This segmentation is often overly aggressive, given that people naturally pause to think as they speak. Consequently, segmentation happens mid-sentence, hindering both punctuation and downstream tasks like machine translation for which high-quality segmentation is critical. Model-based segmentation methods that leverage acoustic features are powerful, but without an understanding of the language itself, these approaches are limited. We present a hybrid approach that leverages both acoustic and language information to improve segmentation. Furthermore, we show that including one word as a look-ahead boosts segmentation quality. On average, our models improve segmentation-F0.5 score by 9.8% over baseline. We show that this approach works for multiple languages. For the downstream task of machine translation, it improves the translation BLEU score by an average of 1.05 points

Nano-sulforaphane attenuates PhIP-induced early abnormal embryonic neuro-development

Background: 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyrimidine (PhIP), one of the most abundant heterocyclic aromatic amines (HAA) formed by cooking meat at high temperatures, may modify humans and rodents through the metabolic process prior to affecting nervous system development. in humans and rodents may be modified by metabolic processes and then affecting nervous system development. Methods: In this paper, PhIP was used to prepare a chicken embryo model with abnormal embryonic nervous system defects. Sulforaphane (SFN) is a derivative of a glucosinolate, which is abundant in cruciferous vegetables, and can pass through the placental barrier. Moreover, SFN has antioxidant and anti-apoptotic functions and is considered as a bioactive antioxidant with significant neuroprotective effects. Nano-sulforaphane (Nano-SFN, Sulforaphane nanoparticles) was prepared by self-assembly using biocompatible, biodegradable methoxy polyethylene glycol 5000-b-polyglutamic acid 10000 (mPEG5K-PGA10K) as the substrate, to explore the new application of Nano-SFN and its modified compounds as leading compounds in protecting against the abnormal development of the embryonic nervous system. Results: The results show that Nano-SFN could protect against PhIP-induced central nervous system (CNS, derived from neural tube) and peripheral nervous system (PNS, derived from neural crest cells, NCCs) defects and neural tube defects (NTDs), and increase the embryo survival rate. Conclusions: This study indicates that Nano-SFN can effectively alleviate the developmental defects of embryonic nervous system induced by PhIP in the microenvironment and has a protective effect on embryonic development. It not only helps with expanding the application of SFN and improving its medicinal value, but also provides a possibility of SFN being developed as a novel drug for neuroprotection

Identification of the Transcriptional Regulator NcrB in the Nickel Resistance Determinant of Leptospirillum ferriphilum UBK03

The nickel resistance determinant ncrABCY was identified in Leptospirillum ferriphilum UBK03. Within this operon, ncrA and ncrC encode two membrane proteins that form an efflux system, and ncrB encodes NcrB, which belongs to an uncharacterized family (DUF156) of proteins. How this determinant is regulated remains unknown. Our data indicate that expression of the nickel resistance determinant is induced by nickel. The promoter of ncrA, designated pncrA, was cloned into the promoter probe vector pPR9TT, and co-transformed with either a wild-type or mutant nickel resistance determinant. The results revealed that ncrB encoded a transcriptional regulator that could regulate the expression of ncrA, ncrB, and ncrC. A GC-rich inverted repeat sequence was identified in the promoter pncrA. Electrophoretic mobility shift assays (EMSAs) and footprinting assays showed that purified NcrB could specifically bind to the inverted repeat sequence of pncrA in vitro; this was confirmed by bacterial one-hybrid analysis. Moreover, this binding was inhibited in the presence of nickel ions. Thus, we classified NcrB as a transcriptional regulator that recognizes the inverted repeat sequence binding motif to regulate the expression of the key nickel resistance gene, ncrA

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Exploring Psycholinguistic Differences Between Song and Ming Emperors Bases on Literary Edicts

Imperial edicts in ancient China were with strong political preference and practicality. It is very meaningful to interpret the psychological meaning of the emperors and necessary to analyze the sociality and individuality of emperors based on their imperial edicts. This paper analyzed the differences of psycholinguistic features in imperial edicts of Song and Ming dynasties via Classic Chinese LIWC (CC-LIWC) to obtain word frequency results for each word category in the edicts and used statistical tests to compare the differences of functional words-personal pronouns, emotional process words, cognitive insight words, physiological process words and motivational level words - in the edicts of Song and Ming dynasties. The result indicates the differences in CC-LIWC lexical frequencies between Ming and Song dynasties had an impact on the intensity of the emperors&rsquo;work and their mentality in dealing with state issues.</p