Research on Charging Process Strategy of Airborne Compressor

An air tank can be inflated with compressed air at anytime if the aircraft is equipped with an airbone compressor. . The different inlet altitude conditions and residual tank pressures both make it difficult to plan strategy about air tank filling. This paper studied the charging performance of the filling process in these complex working conditions, and proposed an inflating strategy of airborne compressor. A dynamic model is constructed to simulate the filling process of a multi-stage compressor with finite interstage volume. It takes 6 minutes to fill a tank with 2.0L volume from 0.101 MPa to 35 MPa, and startup process merely lasts 6 seconds. The experiment on the compressor was developed on the ground. The results validated with simulation values and shared similar evolution regularity of the pressure. The filling process at high altitude has been simulated. When residual bottle pressure is atmospheric pressure, with the altitude increasing from 0 km to 20km, the charging time increases from 6 minutes to more than 2 hours. Besides, the charging time is proportional to the residual pressure with a negative slope at a certain altitude. The mean torque in startup process declines with altitude rise, which proves filling at high altitude does not heavy the compressor’s load, as well as the electric machine control difficulty. Based on simulation results, a feasible working area satisfying ejection demand is proposed, which can be used to determine the charging time under any filling condition. In order to inflate the tank in thirty minutes, this airborne compressor must work under 19.7 km

A closer look at interacting dark energy with statefinder hierarchy and growth rate of structure

We investigate the interacting dark energy models by using the diagnostics of statefinder hierarchy and growth rate of structure. We wish to explore the deviations from $\Lambda$CDM and to differentiate possible degeneracies in the interacting dark energy models with the geometrical and structure growth diagnostics. We consider two interacting forms for the models, i.e., $Q_1=\beta H\rho_c$ and $Q_2=\beta H\rho_{de}$, with $\beta$ being the dimensionless coupling parameter. Our focus is the I$\Lambda$CDM model that is a one-parameter extension to $\Lambda$CDM by considering a direct coupling between the vacuum energy ($\Lambda$) and cold dark matter (CDM), with the only additional parameter $\beta$. But we begin with a more general case by considering the I$w$CDM model in which dark energy has a constant $w$ (equation-of-state parameter). For calculating the growth rate of structure, we employ the "parametrized post-Friedmann" theoretical framework for interacting dark energy to numerically obtain the $\epsilon(z)$ values for the models. We show that in both geometrical and structural diagnostics the impact of $w$ is much stronger than that of $\beta$ in the I$w$CDM model. We thus wish to have a closer look at the I$\Lambda$CDM model by combining the geometrical and structural diagnostics. We find that the evolutionary trajectories in the $S^{(1)}_3$--$\epsilon$ plane exhibit distinctive features and the departures from $\Lambda$CDM could be well evaluated, theoretically, indicating that the composite null diagnostic $\{S^{(1)}_3, \epsilon\}$ is a promising tool for investigating the interacting dark energy models.Comment: 17 pages, 4 figures; accepted for publication in JCA

Controlling Delivery Of Capsaicin From Layered-Flat Noodles Using Gastro-Resistant Dough Layers

This thesis describes the development of a novel capsaicin controlled-release/delivery using redesigned yellow alkaline noodles (i.e. layered noodles, LN) as the delivery system. The proposed LN was prepared by sandwiching the capsaicin-enriched dough (CED) in between two gastro-resistant layers. In the preliminary study, the formulation of CED was designed and the feasibility of using LN as a capsaicin-carrier was explored. In comparison with conventional noodles (CN) with equal amount of capsaicin, LN was proven to have significantly lower (P < 0.05) capsaicin losses during cooking and shorter lingering period of spiciness in the mouth after consuming the noodles. To withstand the gastro-intestinal conditions, application of gastro-resistant layers to produce LN was examined. The gastro-resistant layers were made from (a) wheat flour (LN-C), (b) wheat flour mixed with resistant starch flour (Fibersym®) (LN-F) and (c) wheat flour mixed with soy protein isolate (SPI) and microbial transglutaminase (MTG) (LN-MTG), respectively. Physicochemical properties, texture properties, capsaicin retentions and predicted glycemic index (pGI) of the developed LN were examined. LN-MTG showed the highest (P < 0.05) tensile strength and elasticity, as well as the highest (P < 0.05) capsaicin retention in stimulated mouth and intestinal conditions. In stimulated gastric conditions, the capsaicin retention of all noodles was similar. The pGI of LN-MTG and LN-F were similar (P > 0.05) and were significantly lower (P < 0.05) than LN-C

Blow up solutions to a viscoelastic fluid system and a coupled Navier-Stokes/Phase-Field system in R^2

We find explicit solutions to both the Oldroyd-B model with infinite Weissenberg number and the coupled Navier-Stokes/Phase-Field system. The solutions blow up in finite time.Comment: 5 page

Exponential Stability of the Inhomogeneous Navier-Stokes-Vlasov System in Vacuum

The main purpose of the present paper is to study the influence of the vacuum on the asymptotic behaviors of solutions to the inhomogeneous Navier-Stokes-Vlasov system in $\mathbb{R}^3\times\mathbb{R}^3$. To this end, we establish the uniform bound of the macroscopic density associated with the distribution function and prove the global existence and uniqueness of strong solutions to the Cauchy problem with vacuum for either small initial energy or large viscosity coefficient. The uniform boundedness and the presence of vacuum enable us to show that as the time evolves, the fluid velocity decays, while the distribution function concentrates towards a Dirac measure in velocity centred at $0$, with an exponential rate

FIRM CELEBRITY, REPUTATION AND PERFORMANCE: A SOCIAL MEDIA PERSPECTIVE

Firm celebrity and reputation are considered as valuable intangible resources leading to competitive advantages. Past research usually uses indirect measures, such as Fortune ratings or questionnaire surveys to examine the relationship between celebrity and reputation with firm financial performance. The follow-ship on microblogging services, such as Twitter, provides us an opportunity to measure the two assets directly. Constructing firm celebrity as the number of followers a firm has and firm eputation as the PageRank score of the firm, we discovered that both reputation and celebrity derived from social media have shown negative effects on firms\u27 return on assets, but have positive relationships with market capitalization. This is to say, despite of their relative inabilities to generate profits, the management of firms with high reputation and level of celebrity achieved higher market values, which is one of the most important goals for all companies. Furthermore, we also compared the different effects between reputation and celebrity on firm financial performance. The results showed that the level of celebrity has a stronger positive relation with market capitalization than firm reputation. On the other hand, firm reputation has a stronger impact on cost of goods sold than celebrity

Fucoxanthin Enhances Cisplatin-Induced Cytotoxicity via NFκB-Mediated Pathway and Downregulates DNA Repair Gene Expression in Human Hepatoma HepG2 Cells

Cisplain, a platinum-containing anticancer drug, has been shown to enhance DNA repair and to inhibit cell apoptosis, leading to drug resistance. Thus, the combination of anticancer drugs with nutritional factors is a potential strategy for improving the efficacy of cisplatin chemotherapy. In this study, we investigated the anti-proliferative effects of a combination of fucoxanthin, the major non-provitamin A carotenoid found in Undaria Pinnatifida, and cisplatin in human hepatoma HepG2 cells. We found that fucoxanthin (1–10 μΜ) pretreatment for 24 h followed by cisplatin (10 μΜ) for 24 h significantly decreased cell proliferation, as compared with cisplatin treatment alone. Mechanistically, we showed that fucoxanthin attenuated cisplatin-induced NFκB expression and enhanced the NFκB-regulated Bax/Bcl-2 mRNA ratio. Cisplatin alone induced mRNA expression of excision repair cross complementation 1 (ERCC1) and thymidine phosphorylase (TP) through phosphorylation of ERK, p38 and PI3K/AKT pathways. However, fucoxanthin pretreatment significantly attenuated cisplatin-induced ERCC1 and TP mRNA expression, leading to improvement of chemotherapeutic efficacy of cisplatin. The results suggest that a combined treatment with fucoxanthin and cisplatin could lead to a potentially important new therapeutic strategy against human hepatoma cells

A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions

The development of remote sensing has enabled the acquisition of information on land-cover change at different spatial scales. However, a trade-off between spatial and temporal resolutions normally exists. Fine-spatial-resolution images have low temporal resolutions, whereas coarse spatial resolution images have high temporal repetition rates. A novel super-resolution change detection method (SRCD)is proposed to detect land-cover changes at both fine spatial and temporal resolutions with the use of a coarse-resolution image and a fine-resolution land-cover map acquired at different times. SRCD is an iterative method that involves endmember estimation, spectral unmixing, land-cover fraction change detection, and super-resolution land-cover mapping. Both the land-cover change/no-change map and from–to change map at fine spatial resolution can be generated by SRCD. In this study, SRCD was applied to synthetic multispectral image, Moderate-Resolution Imaging Spectroradiometer (MODIS) multispectral image and Landsat-8 Operational Land Imager (OLI) multispectral image. The land-cover from–to change maps are found to have the highest overall accuracy (higher than 85%) in all the three experiments. Most of the changed land-cover patches, which were larger than the coarse-resolution pixel, were correctly detected

Improving super-resolution mapping through combining multiple super-resolution land-cover maps

Super-resolution mapping (SRM) is an ill-posed problem, and different SRM algorithms may generate non-identical fine spatial resolution land-cover maps (sub-pixel maps) from the same input coarse spatial resolution image. The output sub-pixels maps may each have differing strengths and weaknesses. A multiple SRM (M-SRM) method that combines the sub-pixel maps obtained from a set of SRM analyses, obtained from a single or multiple set of algorithms, is proposed in this study. Plurality voting, which selects the class with the most votes, is used to label each sub-pixel. In this study, three popular SRM algorithms, namely, the pixel swapping algorithm (PSA), the Hopfield neural network (HNN) algorithm, and Markov random field (MRF) based algorithm, were used. The proposed M-SRM algorithm was validated using two data sets: a simulated multi-spectral image and an airborne visible/infrared imaging spectrometer (AVIRIS) hyperspectral image. Results show that the highest overall accuracies were obtained by M-SRM in all experiments. For example, in the AVIRIS image experiment, the highest overall accuracies of PSA, HNN and MRF were 88.89%, 93.81% and 82.70% respectively, and increased to 95.06%, 95.37% and 85.56% respectively for M-SRM obtained from the multiple PSA, HNN and MRF analyses