Numerical simulation study on suppression effect of water mist on PMMA combustion under external radiant heat flux

Numerical model was built with fire dynamic simulator and theocratical simulation was carried out to investigate the suppression effect of water mist on ignition and combustion process of typical solid material polymethyl methacrylate under external radiant heat flux. Characteristic parameters such as ignition time, surface temperature, heat release rate and temperature distribution of flame central plane during ignition and combustion process under different thermal radiant fluxes were obtained and compared with experimental results. The suppression effect of spray droplets on ignition and combustion process was analyzed and discussed. The results show the theoretical calculations of combustion characteristic parameters are in good agreement with experimental measurements. Water mist droplets can effectively delay the ignition time. Quantitative data proves that the water mist flow rate at 0.9 L/(min·m2) can delay the ignition time of samples by about 1,100 s while the radiant heat flux is 50 kW/m2. The simulation results can provide theoretical support and data reference for typical solid material fire prevention and fire extinguishment in practice

Role of Scrib and Dlg in anterior-posterior patterning of the follicular epithelium during Drosophila oogenesis

<p>Abstract</p> <p>Background</p> <p>Proper patterning of the follicle cell epithelium over the egg chamber is essential for the <it>Drosophila </it>egg development. Differentiation of the epithelium into several distinct cell types along the anterior-posterior axis requires coordinated activities of multiple signaling pathways. Previously, we reported that <it>lethal(2)giant larvae </it>(<it>lgl</it>), a <it>Drosophila </it>tumor suppressor gene, is required in the follicle cells for the posterior follicle cell (PFC) fate induction at mid-oogenesis. Here we explore the role of another two tumor suppressor genes, <it>scribble </it>(<it>scrib</it>) and <it>discs large </it>(<it>dlg</it>), in the epithelial patterning.</p> <p>Results</p> <p>We found that removal of <it>scrib </it>or <it>dlg </it>function from the follicle cells at posterior terminal of the egg chamber causes a complete loss of the PFC fate. Aberrant specification and differentiation of the PFCs in the mosaic clones can be ascribed to defects in coordinated activation of the EGFR, JAK and Notch signaling pathways in the multilayered cells. Meanwhile, the clonal analysis revealed that loss-of-function mutations in <it>scrib/dlg </it>at the anterior domains result in a partially penetrant phenotype of defective induction of the stretched and centripetal cell fate, whereas specification of the border cell fate can still occur in the most anterior region of the mutant clones. Further, we showed that <it>scrib </it>genetically interacts with <it>dlg </it>in regulating posterior patterning of the epithelium.</p> <p>Conclusion</p> <p>In this study we provide evidence that <it>scrib </it>and <it>dlg </it>function differentially in anterior and posterior patterning of the follicular epithelium at oogenesis. Further genetic analysis indicates that <it>scrib </it>and <it>dlg </it>act in a common pathway to regulate PFC fate induction. This study may open another window for elucidating role of <it>scrib/dlg </it>in controlling epithelial polarity and cell proliferation during development.</p

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

Online Learning Based Performance Optimization in Wireless Networks with Context Information

Adapting to unreliable links is a key challenge to meet the high demands for next-generation wireless communication and networking. For instance, channel variations caused by multi-path fading, shadowing, and mobility, can lead to packet losses and decrease network throughput \cite{hashemi2018efficient}. This issue is especially important in a 5G/B5G system because of the adoption of millimeter-wave (mmWave) communications. MmWave signals bear much higher propagation loss than lower frequencies due to atmospheric absorption and low penetration, which is exacerbated by blocking and mobility. These challenges were mainly addressed by various physical/link/network layer mechanisms, such as transmission power, rate control, channel coding, opportunistic routing, etc. However, they all come at the expense of higher resource consumption/overhead and are limited by the intrinsic characteristics of the wireless channel. Reconfigurable antennas (RAs) emerged as a promising technology that can deal with channel variations and enhance the capacity and reliability of the wireless channel. RAs is possible to directly enhance the link performance by altering the physical channel itself. To fully exploit the advantage of RAs, optimal antenna modes/beams need to be selected in an online manner. The main challenges are two-fold: uncertainty of channel over time, and a large number of candidate antenna modes/beams. Multi-armed bandit-based online learning algorithms were proposed to address this challenge, but the main drawback of existing approaches are that their regret scales linearly with the number of antenna modes/beams, which converges slowly when the latter is large. In this dissertation, we focus on alleviating the aforementioned challenges by exploiting channel related context information. We propose several optimal online antenna mode/beam selection frameworks for SISO/MIMO single-hop wireless links and extend to joint antenna mode/beam and route selection for multi-hop wireless networks, based on the Multi-Armed Bandit (MAB) framework. First, we present two novel antenna mode pruning strategies and integrate them with Thompson sampling (TS), which exploit the relationship between antenna radiation pattern and channel state. These two algorithms pre-process the action set (reduce the number of arms in the action set) to achieve a higher convergence rate. However, it does not fully utilize channel information as context information. To fully exploit channel information, we present a Hierarchical Thompson Sampling (HTS) algorithm. The high level idea of HTS is to divide the arms into multiple clusters, first uses TS to sample a cluster and then samples an individual arm inside that cluster. Furthermore, we present two algorithms that exploit channel modeling to predict the channel conditions of unexplored antenna modes at each time step, by relating the correlation between different channel states to the underlying antenna modes. In addition, we present an efficient MAB algorithm for joint routing and beam selection in multi-hop networks: combinatorial lower confidence bound (LCB) based joint route and beam selection with channel prediction (CLCB-JRBS-CP). This algorithm also exploits channel modeling to predict the channel conditions of unexplored beams. Finally, we propose a Hierarchical Unimodal Upper Confidence Bound (HUUCB) algorithm to further improve the convergence of the HTS algorithm, with the assumption that each cluster's arms' expected rewards satisfy the Unimodal property. The HUUCB algorithm can be applied to a variety of problems in communications, such as optimal beam selection in mmWave links with multiple frequencies, and applications beyond communications, such as joint vehicle speed and route optimization in road navigation

Research and Simulation on Division Attack Airspace

Division attack is the basic tactical action of air strike operation carried out by the Air Force. The aircraft tactical action model is analyzed and established according to the Division attack pattern. Track points are determined on the basis of parameters of the weapons, and the ideal trajectory is determined under the constraint of the flights’ ideal parameters and the type of target. The upper winds and pilot’ operating error are taken into account on the ideal track, and the total deviation is calculated. We put forward a method of establishing airspace based on the probability deviation of the attack track, and adopt the relevant flight data to carry on the simulation verification. The final results show that the effectiveness and practicability of this method, and it is helpful for the rapid generation of relevant airspace

Performance analysis and optimization of multi-stage combined thermoelectric generators

A numerical model of multi-stage combined thermoelectric generators is established based on non-equilibrium thermodynamics. Taking a 5-stage thermoelectric generator for example, the output characteristics are analyzed. With the power and efficiency as the goal, the thermoelectric elements configuration and electrical current are optimized synchronously. The results show that when the temperature difference and the Seebeck coefficient are small, same number of thermoelectric elements in each stage results in the maximal power output; when the temperature difference or the Seebeck coefficient is large, the optimal configuration is that the numbers of thermoelectric elements increase with the same difference from the high temperature stage to the low temperature stage.Papers presented at the 13th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Portoroz, Slovenia on 17-19 July 2017 .International centre for heat and mass transfer.American society of thermal and fluids engineers

Geographical distribution of coral reefs and their responses to environmental factors in the South China Sea

Coral reefs represent distinctive yet vulnerable marine ecosystems. Recently, these ecosystems have faced threats and degradation from multiple factors. A comprehensive understanding of coral distribution and niche information forms the theoretical foundation for addressing the ongoing coral crisis. This study employed the MaxEnt model to predict coral distribution in the central and southern regions of the South China Sea (SCS), while also obtaining ecological niche information. Utilizing CMIP6 data, the future exposure risk of corals was evaluated under two forcing scenarios (SSP245 and SSP585). The findings revealed that the highly suitable areas for corals in the SCS were approximately 31,360 km2, mainly distributed in the middle and east of Xisha, Zhongsha Atoll, Huangyan Island, and the north of the Nansha Islands. The probability of coral presence in the north and west of Xisha and the south of Nansha was low. The key environmental factors exerting significant influences on coral occurrence included seawater temperature, photosynthetically active radiation, current velocity, and dissolved oxygen. Among them, seawater velocity and nitrate emerged as the primary factors discerning differences in coral fitness across the study regions, which also verified the results of principal component analysis. Under extreme scenarios predicted by the end of this century (SSP585-2090s), over 43 % of coral distribution areas would face the highest exposure risk, mainly concentrated in southern Nansha. The primary drivers of this increased risk were the substantial changes occurring in temperature, dissolved oxygen, and nitrate. This research serves as a reference for coral conservation under climate change in the future