Statistical Study of Emerging Flux Regions and the Upper Atmosphere Response

We statistically study the property of emerging flux regions (EFRs) and the upper solar atmosphere response to the flux emergence by using data from the Helioseismic and Magnetic Imager (HMI) and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). Parameters including the total emerged flux, the flux growth rate, the maximum area, the duration of the emergence and the separation speed of the opposite polarities are adopted to delineate the property of the EFRs. The response of the upper atmosphere is addressed by the response of the atmosphere at different wavelengths (and thus at different temperatures). According to our results, the total emerged fluxes are in the range of (0.44 -- 11.2)$\times10^{19}$ Mx while the maximum area ranges from 17 to 182 arcsec$^2$. The durations of the emergence are between 1 and 12 hours, which are positively correlated to both the total emerged flux and the maximum area. The maximum distances between the opposite polarities are 7 -- 25 arcsec and are also correlated to the duration positively. The separation speeds are from 0.05 to 1.08 km s$^{-1}$, negatively correlated to the duration. The derived flux growth rates are (0.1 -- 1.3)$\times10^{19}$ Mx hr$^{-1}$, which are positively correlated to the total emerging flux. The upper atmosphere responds to the flux emergence in the 1600\AA\ chromospheric line first, and then tens and hundreds of seconds later, in coronal lines, such as the 171\AA\ (T=10$^{5.8}$ K) and 211\AA\ (T=10$^{6.3}$ K) lines almost simultaneously, suggesting the successively heating of atmosphere from the chromosphere to the corona

Platform-Based Online Services, Competitive Actions, And E-Marketplace Seller Performance

Platform-based services are online services provided by e-marketplace operators to online sellers for them to compete and enhance performance. This paper aims at examining two important questions in the context of e-marketplace: (1) what kind of platform-based services can be used by online retail sellers as competitive moves? and (2) to what extent does the usage of these platform-based services impact online seller’s performance? Drawing on competitive dynamics theory, we argue that sellers that undertake a larger number of, more complex and heterogeneous platform-based services achieve better performance in e-marketplace. Using data of 1046 sellers, who open online retail stores and sell cosmetics on Taobao, a Chinese e-marketplace, we found that while undertaking more complex platform-based services is important by itself, it is more important to be strategic by undertaking a large number of platform-based services and these services had better be different from its competitors and the industry. Implications for practice and research and suggestions for future research on improving sellers’ competitiveness are discussed. This research was supported in part by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (No. CityU 141809)

Dephasing of Transverse Spin Current in Ferrimagnetic Alloys

It has been predicted that transverse spin current can propagate coherently (without dephasing) over a long distance in antiferromagnetically ordered metals. Here, we estimate the dephasing length of transverse spin current in ferrimagnetic CoGd alloys by spin pumping measurements across the compensation point. A modified drift-diffusion model, which accounts for spin-current transmission through the ferrimagnet, reveals that the dephasing length is about 4-5 times longer in nearly compensated CoGd than in ferromagnetic metals. This finding suggests that antiferromagnetic order can mitigate spin dephasing -- in a manner analogous to spin echo rephasing for nuclear and qubit spin systems -- even in structurally disordered alloys at room temperature. We also find evidence that transverse spin current interacts more strongly with the Co sublattice than the Gd sublattice. Our results provide fundamental insights into the interplay between spin current and antiferromagnetic order, which are crucial for engineering spin torque effects in ferrimagnetic and antiferromagnetic metals

Nonlinear Time Series: Computations and Applications 2012

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Turning dead leaves into an active multifunctional material as evaporator, photocatalyst, and bioplastic

Large numbers of leaves fall on the earth each autumn. The current treatments of dead leaves mainly involve completely destroying the biocomponents, which causes considerable energy consumption and environmental issues. It remains a challenge to convert waste leaves into useful materials without breaking down their biocomponents. Here, we turn red maple dead leaves into an active three-component multifunctional material by exploiting the role of whewellite biomineral for binding lignin and cellulose. Owing to its intense optical absorption spanning the full solar spectrum and the heterogeneous architecture for effective charge separation, films of this material show high performance in solar water evaporation, photocatalytic hydrogen production, and photocatalytic degradation of antibiotics. Furthermore, it also acts as a bioplastic with high mechanical strength, high-temperature tolerance, and biodegradable features. These findings pave the way for the efficient utilization of waste biomass and innovations of advanced materials

Synthesis of titanate nanofibers co-sensitized with ZnS and Bi2S3 nanocrystallites and their application on pollutants removal

The synthesis of nanocomposite materials combining titanate nanofibers (TNF) with nanocrystalline ZnS and Bi2S3 semiconductors is described in this work. The TNF were produced via hydrothermal synthesis and sensitized with the semiconductor nanoparticles, through a single-source precursor decomposition method. ZnS and Bi2S3 nanoparticles were successfully grown onto the TNF's surface and Bi2S3-ZnS/TNF nanocomposite materials with different layouts were obtained using either a layer-by-layer or a co-sensitization approach. The samples' photocatalytic performance was first evaluated through the production of the hydroxyl radical using terephthalic acid as probe molecule. All the tested samples show photocatalytic ability for the production of this oxidizing species. Afterwards, the samples were investigated for the removal of methylene blue. The nanocomposite materials with best adsorption ability for the organic dye were the ZnS/TNF and Bi2S3ZnS/TNF. The removal of the methylene blue was systematically studied, and the most promising results were obtained considering a sequential combination of an adsorption-photocatalytic degradation process using the Bi2S3ZnS/TNF powder as a highly adsorbent and photocatalyst material.Comment: 26 pages, 10 figure

ProBDNF Collapses Neurite Outgrowth of Primary Neurons by Activating RhoA

BACKGROUND: Neurons extend their dendrites and axons to build functional neural circuits, which are regulated by both positive and negative signals during development. Brain-derived neurotrophic factor (BDNF) is a positive regulator for neurite outgrowth and neuronal survival but the functions of its precursor (proBDNF) are less characterized. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that proBDNF collapses neurite outgrowth in murine dorsal root ganglion (DRG) neurons and cortical neurons by activating RhoA via the p75 neurotrophin receptor (p75NTR). We demonstrated that the receptor proteins for proBDNF, p75NTR and sortilin, were highly expressed in cultured DRG or cortical neurons. ProBDNF caused a dramatic neurite collapse in a dose-dependent manner and this effect was about 500 fold more potent than myelin-associated glycoprotein. Neutralization of endogenous proBDNF by using antibodies enhanced neurite outgrowth in vitro and in vivo, but this effect was lost in p75NTR(-/-) mice. The neurite outgrowth of cortical neurons from p75NTR deficient (p75NTR(-/-)) mice was insensitive to proBDNF. There was a time-dependent reduction of length and number of filopodia in response to proBDNF which was accompanied with a polarized RhoA activation in growth cones. Moreover, proBDNF treatment of cortical neurons resulted in a time-dependent activation of RhoA but not Cdc42 and the effect was absent in p75NTR(-/-) neurons. Rho kinase (ROCK) and the collapsin response mediator protein-2 (CRMP-2) were also involved in the proBDNF action. CONCLUSIONS: proBDNF has an opposing role in neurite outgrowth to that of mature BDNF. Our observations suggest that proBDNF collapses neurites outgrowth and filopodial growth cones by activating RhoA through the p75NTR signaling pathway

Self-Consistent Asset Pricing Models

We discuss the foundations of factor or regression models in the light of the self-consistency condition that the market portfolio (and more generally the risk factors) is (are) constituted of the assets whose returns it is (they are) supposed to explain. As already reported in several articles, self-consistency implies correlations between the return disturbances. As a consequence, the alpha's and beta's of the factor model are unobservable. Self-consistency leads to renormalized beta's with zero effective alpha's, which are observable with standard OLS regressions. Analytical derivations and numerical simulations show that, for arbitrary choices of the proxy which are different from the true market portfolio, a modified linear regression holds with a non-zero value $\alpha_i$ at the origin between an asset $i$'s return and the proxy's return. Self-consistency also introduces ``orthogonality'' and ``normality'' conditions linking the beta's, alpha's (as well as the residuals) and the weights of the proxy portfolio. Two diagnostics based on these orthogonality and normality conditions are implemented on a basket of 323 assets which have been components of the S&P500 in the period from Jan. 1990 to Feb. 2005. These two diagnostics show interesting departures from dynamical self-consistency starting about 2 years before the end of the Internet bubble. Finally, the factor decomposition with the self-consistency condition derives a risk-factor decomposition in the multi-factor case which is identical to the principal components analysis (PCA), thus providing a direct link between model-driven and data-driven constructions of risk factors.Comment: 36 pages with 8 figures. large version with 6 appendices for the Proceedings of the 5th International Conference APFS (Applications of Physics in Financial Analysis), June 29-July 1, 2006, Torin

Dark Energy Perturbations Revisited

In this paper we study the evolution of cosmological perturbations in the presence of dynamical dark energy, and revisit the issue of dark energy perturbations. For a generally parameterized equation of state (EoS) such as w_D(z) = w_0+w_1\frac{z}{1+z}, (for a single fluid or a single scalar field ) the dark energy perturbation diverges when its EoS crosses the cosmological constant boundary w_D=-1. In this paper we present a method of treating the dark energy perturbations during the crossing of the $w_D=-1$ surface by imposing matching conditions which require the induced 3-metric on the hypersurface of w_D=-1 and its extrinsic curvature to be continuous. These matching conditions have been used widely in the literature to study perturbations in various models of early universe physics, such as Inflation, the Pre-Big-Bang and Ekpyrotic scenarios, and bouncing cosmologies. In all of these cases the EoS undergoes a sudden change. Through a detailed analysis of the matching conditions, we show that \delta_D and \theta_D are continuous on the matching hypersurface. This justifies the method used[1-4] in the numerical calculation and data fitting for the determination of cosmological parameters. We discuss the conditions under which our analysis is applicable.Comment: 10 pages and 1 figure