Heart disease has become the "number one killer" of human health, directly or indirectly endangering human health in the form of complications. Segmentation of the left ventricle can provide ...diagnostic value for evaluating cardiac health and identifying certain pathology. In this paper, we propose method called multi-constrained segmentation (MC-Seg) automatically calculates and measures the full segmentation results of left ventricle. We use U-Net convolution neural network architecture first to segment left ventricle as a benchmark. Taking into account the correlation between tasks, we add multitask learning to the segmentation results at the same time to improve the performance and improve the generalization of the network. Our method was validated and evaluated on the MICCAI 2018 ventricular dataset. After 50 rounds of training, by segmenting the cardiac MRI images from 145 patients, we reduced the training loss to 0.002 and the average dice overlap coefficients of the test set were 0.886. The results show that our method is innovative and can effectively improve the performance of left ventricular segmentation.
Different radio access technology vary with communication parameters, such as mobility, coverage and bandwidth etc. Joint Admission Control (JAC) technology therefore is put forward to make the ...different Radio Access Networks (RANs) work together. This paper proposes a distributed JAC scheme based on the ecology theory in heterogeneous wireless network. It establishes a mapping relationship of ecological competition and heterogeneous radio resources management, and adopts the Gause-Lotka-Volterra (GLV) model to predict the heterogeneous network traffic. Based on the mapping relationship and GLV model, the network parameters can be adjusted to achieve a balanced traffic state for different RANs. In the simulation, we evaluate the network traffic and blocking probability performances. Results show that the ecology-inspired JAC scheme can balance the traffic, reduces the networks competition effect, and moreover makes the profits by different operators jointly.
We explore the bound neutrons decay into invisible particles (e.g.,
$n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator
detector. The invisible decay includes two decay ...modes: $ n \rightarrow { inv}
$ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in
$^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some
de-excitation modes of the excited residual nuclei can produce a time- and
space-correlated triple coincidence signal in the JUNO detector. Based on a
full Monte Carlo simulation informed with the latest available data, we
estimate all backgrounds, including inverse beta decay events of the reactor
antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and
neutral current interactions of atmospheric neutrinos. Pulse shape
discrimination and multivariate analysis techniques are employed to further
suppress backgrounds. With two years of exposure, JUNO is expected to give an
order of magnitude improvement compared to the current best limits. After 10
years of data taking, the JUNO expected sensitivities at a 90% confidence level
are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and
$\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$.
\(^{134}\)Xe is a candidate isotope for neutrinoless double beta decay~(\(0\nu\beta\beta\)) search. In addition, the two-neutrino case (\(2\nu\beta\beta\)) allowed by the Standard Model of particle ...physics has not yet been observed. Utilizing the 10.4% of \(^{134}\)Xe in the natural xenon in the PandaX-4T detector and its first 94.9-day exposure, we have established the most stringent constraints on \(2\nu\beta\beta\) and \(0\nu\beta\beta\) of \(^{134}\)Xe half-lives, with limits of \(2.8\times10^{22}\) yr and \(3.0\times10^{23}\) yr at 90% confidence level, respectively. The \(2\nu\beta\beta\) (\(0\nu\beta\beta\)) limit surpasses the previously reported best result by a factor of 32 (2.7), highlighting the potential of large monolithic natural xenon detectors.
Neutrinos from core-collapse supernovae are essential for the understanding of neutrino physics and stellar evolution. The dual-phase xenon dark matter detectors can provide a way to track explosions ...of galactic supernovae by detecting neutrinos through coherent elastic neutrino-nucleus scatterings. In this study, a variation of progenitor masses as well as explosion models are assumed to predict the neutrino fluxes and spectra, which result in the number of expected neutrino events ranging from 6.6 to 13.7 at a distance of 10 kpc over a 10-second duration with negligible backgrounds at PandaX-4T. Two specialized triggering alarms for monitoring supernova burst neutrinos are built. The efficiency of detecting supernova explosions at various distances in the Milky Way is estimated. These alarms will be implemented in the real-time supernova monitoring system at PandaX-4T in the near future, providing the astronomical communities with supernova early warnings.
