112 research outputs found
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
ECG signal classification in wearable devices based on compressed domain.
Wearable devices are often used to diagnose arrhythmia, but the electrocardiogram (ECG) monitoring process generates a large amount of data, which will affect the detection speed and accuracy. In order to solve this problem, many studies have applied deep compressed sensing (DCS) technology to ECG monitoring, which can under-sampling and reconstruct ECG signals, greatly optimizing the diagnosis process, but the reconstruction process is complex and expensive. In this paper, we propose an improved classification scheme for deep compressed sensing models. The framework is comprised of four modules: pre-processing; compression; and classification. Firstly, the normalized ECG signals are compressed adaptively in the three convolutional layers, and then the compressed data is directly put into the classification network to obtain the results of four kinds of ECG signals. We conducted our experiments on the MIT-BIH Arrhythmia Database and Ali Cloud Tianchi ECG signal Database to validate the robustness of our model, adopting Accuracy, Precision, Sensitivity and F1-score as the evaluation metrics. When the compression ratio (CR) is 0.2, our model has 98.16% accuracy, 98.28% average accuracy, 98.09% Sensitivity and 98.06% F1-score, all of which are better than other models
Numerical and Experimental Study of the Structural Color by Widening the Pore Size of Nanoporous Anodic Alumina
The structural color originated from the nanoporous anodic alumina (NAA) film is related to the structural characteristics. This paper aimed to obtain different structural colors which can cover the whole visible range by widening the pore size of metal-coated NAA. First, we used the Finite Difference Time Domain (FDTD) method to analyze the relationship between the physical structure and optical properties. Then, we fabricated different colors and expected color pattern by widening the pore diameter of NAA. Numerical and experimental study shows that the colors can cover the whole visible range by widening the pore diameter. This work can not only lead to better understanding of the mechanism of tuning color on NAA film, but also help us to fabricate expected color in the whole light range
A hybrid approach for measuring the vibrational trend of hydroelectric unit with enhanced multi-scale chaotic series analysis and optimized least squares support vector machine
Facile fabrication of functional PDMS surfaces with tunable wettablity and high adhesive force via femtosecond laser textured templating
Femtosecond laser processing is emerged as a promising tool to functionalize surfaces of various materials, including metals, semiconductors, and polymers. However, the productivity of this technique is limited by the low efficiency of laser raster scanning. Here we report a facile approach for efficiently producing large-area functional polymer surfaces, by which metal is firstly textured by a femtosecond laser, and the as-prepared hierarchical structures are subsequently transferred onto polydimethylsiloxane (PDMS) surfaces. Aluminum pieces covered by laser induced micro/nano-structures act as template masters and their performance of displaying diverse colors are investigated. Polymer replicas are endowed with tunable wetting properties, which are mainly attributed to the multi-scale surface structures. Furthermore, the surfaces are found to have extremely high adhesive force for water drops because of the high water penetration depth and the resultant high contact angle hysteresis. This characteristic facilitates many potential applications like loss-free tiny water droplets transportation. The reusability of metal master and easiness of soft lithography make it to be a very simple, fast and cost-efficient way for mass production of functional polymeric surfaces
Femtosecond laser direct writing of functional stimulus-responsive structures and applications
Diverse natural organisms possess stimulus-responsive structures to adapt to the surrounding environment. Inspired by nature, researchers have developed various smart stimulus-responsive structures with adjustable properties and functions to address the demands of ever-changing application environments that are becoming more intricate. Among many fabrication methods for stimulus-responsive structures, femtosecond laser direct writing (FsLDW) has received increasing attention because of its high precision, simplicity, true three-dimensional machining ability, and wide applicability to almost all materials. This paper systematically outlines state-of-the-art research on stimulus-responsive structures prepared by FsLDW. Based on the introduction of femtosecond laser-matter interaction and mainstream FsLDW-based manufacturing strategies, different stimulating factors that can trigger structural responses of prepared intelligent structures, such as magnetic field, light, temperature, pH, and humidity, are emphatically summarized. Various applications of functional structures with stimuli-responsive dynamic behaviors fabricated by FsLDW, as well as the present obstacles and forthcoming development opportunities, are discussed
Visualization 1: Two-stage optical recording: photoinduced birefringence and surface-mediated bits storage in bisazo-containing copolymers towards ultrahigh data memory
Readout of multi-level bits by changing the reading beam polarization. The bits intensities smoothly transit from one state (bright or dack) to the other (dack or bright). Originally published in Optics Express on 03 October 2016 (oe-24-20-23557
Exploring the mechanism of luteolin by regulating microglia polarization based on network pharmacology and in vitro experiments
Abstract Neuroinflammation manifests following injury to the central nervous system (CNS) and M1/M2 polarization of microglia is closely associated with the development of this neuroinflammation. In this study, multiple databases were used to collect targets regarding luteolin and microglia polarization. After obtaining a common target, a protein–protein interaction (PPI) network was created and further analysis was performed to obtain the core network. Molecular docking of the core network with luteolin after gene enrichment analysis. In vitro experiments were used to examine the polarization of microglia and the expression of related target proteins. A total of 77 common targets were obtained, and the core network obtained by further analysis contained 38 proteins. GO and KEGG analyses revealed that luteolin affects microglia polarization in regulation of inflammatory response as well as the interleukin (IL)-17 and tumor necrosis factor (TNF) signaling pathways. Through in vitro experiments, we confirmed that the use of luteolin reduced the expression of inducible nitric oxide synthase (iNOS), IL-6, TNF-α, p-NFκBIA (p-IκB-α), p-NFκB p65, and MMP9, while upregulating the expression of Arg-1 and IL-10. This study reveals various potential mechanisms by which luteolin induces M2 polarization in microglia to inhibit the neuroinflammatory response
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