Ensemble Learning Independent Component Analysis of Normal Galaxy Spectra

In this paper, we employe a new statistical analysis technique, Ensemble Learning for Independent Component Analysis (EL-ICA), on the synthetic galaxy spectra from a newly released high resolution evolutionary model by Bruzual & Charlot. We find that EL-ICA can sufficiently compress the synthetic galaxy spectral library to 6 non-negative Independent Components (ICs), which are good templates to model huge amount of normal galaxy spectra, such as the galaxy spectra in the Sloan Digital Sky Survey (SDSS). Important spectral parameters, such as starlight reddening, stellar velocity dispersion, stellar mass and star formation histories, can be given simultaneously by the fit. Extensive tests show that the fit and the derived parameters are reliable for galaxy spectra with the typical quality of the SDSS.Comment: 41 pages, 23 figures, to be published in A

Fungsi Sosial Cerita Rakyat Batu Bujang Lengong Di Nagari Alahan Panjang Kecamatan Lembah Gumanti Kabupaten Solok

The purpose for describe function social strori people stone bachelor lengong di Nagari Alahan Panjang Kecamatan Lembah Gumanti Kabupaten Solok hasil researeh in is function social ditemukan faef function social yaitu (1),Studi theory which be usea in research, (2) nature folklore nature, (3) function social strory people. Type researeh is researeh qualilative data dianalisis with step measuresDescribe result recording in language writler translate result interesting conclusior and write report.of destination in is function social strory people bachelor lengong foun Nagari Alahan Panjang Kecamatan Lembah Gumanti Kabupaten Solok, (1) Function social entertain, (2) Function social educate, (3) Function social begueath, (4) Function social tradition, (5) Function social identity

Decadal soil carbon accumulation across Tibetan permafrost regions

Acknowledgements We thank the members of Peking University Sampling Teams (2001–2004) and IBCAS Sampling Teams (2013–2014) for assistance in field data collection. We also thank the Forestry Bureau of Qinghai Province and the Forestry Bureau of Tibet Autonomous Region for their permission and assistance during the sampling process. This study was financially supported by the National Natural Science Foundation of China (31670482 and 31322011), National Basic Research Program of China on Global Change (2014CB954001 and 2015CB954201), Chinese Academy of Sciences-Peking University Pioneer Cooperation Team, and the Thousand Young Talents Program.Peer reviewedPostprintPostprin

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

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Construction of Strategic Early-Warning System in Cyberspace

Cyberspace strategic early-warning is a monitoring and warning system that is established by a country or group for early detection, tracking, identification, and notification of incoming major cyber attacks or the spreading destruction of powerful viruses. It’s an important component of a national security defense system. The implementation of the national cyber development strategy in China requires high attentions to the construction of a cyberspace strategic early-warning system. This study analyzes the major characteristics and basic requirements of strategic early-warning in cyberspace, and studies four major warning styles: security vulnerabilities, security threats, intrusion attacks, and abnormal behaviors warning. It also emphasizes four key projects, namely cyberspace surveying and mapping system, vulnerability collection and early-warning platform, threat intelligence perception and push system, as well as security monitoring and comprehensive early-warning system, after summarizing the construction of strategic early-warning and monitoring systems in cyberspace in China and abroad. Furthermore, we propose several countermeasures and suggestions, including strengthening high-level coordination, focusing on multi-source data integration, establishing professional earlywarning agencies, conducting regular security assessments, and implementing threat and early-warning grading mechanisms