139 research outputs found
A Bayesian Approach to Block Structure Inference in AV1-based Multi-rate Video Encoding
Due to differences in frame structure, existing multi-rate video encoding
algorithms cannot be directly adapted to encoders utilizing special reference
frames such as AV1 without introducing substantial rate-distortion loss. To
tackle this problem, we propose a novel bayesian block structure inference
model inspired by a modification to an HEVC-based algorithm. It estimates the
posterior probabilistic distributions of block partitioning, and adapts early
terminations in the RDO procedure accordingly. Experimental results show that
the proposed method provides flexibility for controlling the tradeoff between
speed and coding efficiency, and can achieve an average time saving of 36.1%
(up to 50.6%) with negligible bitrate cost.Comment: published in IEEE Data Compression Conference, 201
Electromagnetic Source Imaging via a Data-Synthesis-Based Convolutional Encoder-Decoder Network
Electromagnetic source imaging (ESI) requires solving a highly ill-posed
inverse problem. To seek a unique solution, traditional ESI methods impose
various forms of priors that may not accurately reflect the actual source
properties, which may hinder their broad applications. To overcome this
limitation, in this paper a novel data-synthesized spatio-temporally
convolutional encoder-decoder network method termed DST-CedNet is proposed for
ESI. DST-CedNet recasts ESI as a machine learning problem, where discriminative
learning and latent-space representations are integrated in a convolutional
encoder-decoder network (CedNet) to learn a robust mapping from the measured
electroencephalography/magnetoencephalography (E/MEG) signals to the brain
activity. In particular, by incorporating prior knowledge regarding dynamical
brain activities, a novel data synthesis strategy is devised to generate
large-scale samples for effectively training CedNet. This stands in contrast to
traditional ESI methods where the prior information is often enforced via
constraints primarily aimed for mathematical convenience. Extensive numerical
experiments as well as analysis of a real MEG and Epilepsy EEG dataset
demonstrate that DST-CedNet outperforms several state-of-the-art ESI methods in
robustly estimating source signals under a variety of source configurations.Comment: 15 pages, 14 figures, and journa
Global Infectious Diseases in August 2023: A Monthly Analysis
Infectious diseases frequently affect children and adults worldwide. Owing to their specific biology and mode of transmission, the presence of infected individuals or carriers in a region often leads to outbreaks of the disease in that region, and in severe cases, to the death of the infected individual. Infectious diseases have been one of the main causes of mass disability or death in humans for centuries. Surveillance of infectious diseases on a continental scale is therefore important for assessing, recognizing, and preventing the risks that these diseases may pose to animal and human health on a global scale. This report focuses on global infectious disease outbreaks and systematically summarises the timing and location of outbreaks in infected populations between 24 July and 23 August 2023 based on the Global Outbreak Information Surveillance System (GOSIS) of Shusi Technologies
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 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
The Ninth Visual Object Tracking VOT2021 Challenge Results
acceptedVersionPeer reviewe
Nursing students’ experiences of caring for dying patients during their internship : A descriptive literature review
Background: Clinical practice is an inseparable part of nursing education. Research showed that nursing students were under great pressure to care for dying patients and their families during clinical practice. Therefore, it is of great importance to provide professional hospice nursing support and guidance for nursing students.Aim: To describe nursing students’ experiences of caring for dying patients during their internship.Methods: Our research question was “How did nursing students describe their experiences of caring for dying patients during the internship?” We included qualitative research on nursing students’ experiences of caring for terminally ill patients in clinical practice. Databases PubMed and CINAHAL were used to retrieve 10 articles from 8 countries, as well, the qualitative data coding and qualitative content analysis were used to analyze the data.Results: Based on the results of the survey of “nursing students’ experiences in nursing terminal patients in clinical practice”, we divided them into five categories in a chronological order. The first part was the influence of previous relevant nursing experiences that was brought to the nursing students, the second was the emotions and feelings from nursing students in the process of nursing, the third was the relevant nursing measures mentioned by nursing students, the fourth was the way they coped with difficulties and the support they received by the nursing students, and finally the things they had learned and been inspired through these experiences.Conclusion: In clinical practice, it could be extremely stressful for nursing students to care for dying patients. Pre-practice schools should provide complete and full-fledged end-of-life education training to assist nursing students better adapt themselves to the role of nurses in clinical practice.Keywords: nursing students;dying patients;nursing experiences;clinical practice
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