A unique distant submillimeter galaxy with an X-ray-obscured radio-luminous active galactic nucleus

We present a multiwavelength study of an atypical submillimeter galaxy in the GOODS-North field, with the aim to understand its physical properties of stellar and dust emission, as well as the central AGN activity. Although it is shown that the source is likely an extremely dusty galaxy at high redshift, its exact position of submillimeter emission is unknown. With the new NOEMA interferometric imaging, we confirm that the source is a unique dusty galaxy. It has no obvious counterpart in the optical and even NIR images observed with HST at lambda~<1.4um. Photometric-redshift analyses from both stellar and dust SED suggest it to likely be at z~>4, though a lower redshift at z~>3.1 cannot be fully ruled out (at 90% confidence interval). Explaining its unusual optical-to-NIR properties requires an old stellar population (~0.67 Gyr), coexisting with a very dusty ongoing starburst component. The latter is contributing to the FIR emission, with its rest-frame UV and optical light being largely obscured along our line of sight. If the observed fluxes at the rest-frame optical/NIR wavelengths were mainly contributed by old stars, a total stellar mass of ~3.5x10^11Msun would be obtained. An X-ray spectral analysis suggests that this galaxy harbors a heavily obscured AGN with N_H=3.3x10^23 cm^-2 and an intrinsic 2-10 keV luminosity of L_X~2.6x10^44 erg/s, which places this object among distant type 2 quasars. The radio emission of the source is extremely bright, which is an order of magnitude higher than the star-formation-powered emission, making it one of the most distant radio-luminous dusty galaxies. The combined characteristics of the galaxy suggest that the source appears to have been caught in a rare but critical transition stage in the evolution of submillimeter galaxies, where we are witnessing the birth of a young AGN and possibly the earliest stage of its jet formation and feedback.Comment: 13 pages in printer format, 10 figures, 1 table, accepted for publication in the A&

The Integrated Sachs-Wolfe Effect in Time Varying Vacuum Model

The integrated Sachs-Wolfe (ISW) effect is an important implication for dark energy. In this paper, we have calculated the power spectrum of the ISW effect in the time varying vacuum cosmological model, where the model parameter $\beta=4.407$ is obtained by the observational constraint of the growth rate. It's found that the source of the ISW effect is not only affected by the different evolutions of the Hubble function $H(a)$ and the dimensionless matter density $\Omega_m(a)$, but also by the different growth function $D_+(a)$, all of which are changed due to the presence of matter production term in the time varying vacuum model. However, the difference of the ISW effect in $\Lambda(t)\textmd{CDM}$ model and $\Lambda \textmd{CDM}$ model is lessened to a certain extent due to the integration from the time of last scattering to the present. It's implied that the observations of the galaxies with high redshift are required to distinguish the two models

Fermions on Thick Branes in the Background of Sine-Gordon Kinks

A class of thick branes in the background of sine-Gordon kinks with a scalar potential $V(\phi)=p(1+\cos\frac{2\phi}{q})$ was constructed by R. Koley and S. Kar [Classical Quantum Gravity \textbf{22}, 753 (2005)]. In this paper, in the background of the warped geometry, we investigate the issue of localization of spin half fermions on these branes in the presence of two types of scalar-fermion couplings: $\eta\bar{\Psi}\phi\Psi$ and $\eta\bar{\Psi}\sin\phi \Psi$. By presenting the mass-independent potentials in the corresponding Schr\"{o}dinger equations, we obtain the lowest Kaluza--Klein (KK) modes and a continuous gapless spectrum of KK states with $m^2>0$ for both types of couplings. For the Yukawa coupling $\eta\bar{\Psi}\phi\Psi$, the effective potential of the right chiral fermions for positive $q$ and $\eta$ is always positive, hence only the effective potential of the left chiral fermions could trap the corresponding zero mode. This is a well-known conclusion which had been discussed extensively in the literature. However, for the coupling $\eta\bar{\Psi}\sin\phi \Psi$, the effective potential of the right chiral fermions for positive $q$ and $\eta$ is no longer always positive. Although the value of the potential at the location of the brane is still positive, it has a series of wells and barriers on each side, which ensures that the right chiral fermion zero mode could be trapped. Thus we may draw the remarkable conclusion: for positive $\eta$ and $q$, the potentials of both the left and right chiral fermions could trap the corresponding zero modes under certain restrictions.Comment: 22 pages, 21 figures, published version to appear in Phys. Rev.

Preparation and Characteristic of Dextran-BSA Antibody and Establishment of it’s Elisa Immunoassay

The enzyme linked immunosorbent assay (ELISA) is a potential tool for the determination of dextran. In this study, dextran–BSA antigens were prepared by Reductive amination method, and were confirmed by SDS-PAGE and free amino detection. The effects of coupled reaction conditions such as different oxidation degree of dextran, the reaction time were investigated and the immunity of the resulting dextran- BSA neoglycoprotein antigens were evaluated through the interaction with standard dextran antibody. The immunogen was immunized with white rabbits to obtained polyclonal antibody respectively. A general and broad class-specific Elisa detection method was developed according to Elisa theory. The method was put to use for quantitative analysis of dextran in practical saccharose samples

Holographic Bosonic Technicolor

We consider a technicolor model in which the expectation value of an additional, possibly composite, scalar field is responsible for the generation of fermion masses. We define the dynamics of the strongly coupled sector by constructing its holographic dual. Using the AdS/CFT correspondence, we study the S parameter and the phenomenology of the light technihadrons. We find that the S parameter is small over a significant region of the model's parameter space. The particle spectrum is distinctive and includes a nonstandard Higgs boson as well as heavier hadronic resonances. Technihadron masses and decay rates are calculated holographically, as a function of the model's parameters.Comment: 20 Pages, 4 eps figures, REVTex. Minor corrections and comments adde

Genetic algorithms with self-organizing behaviour in dynamic environments

Copyright @ 2007 Springer-VerlagIn recent years, researchers from the genetic algorithm (GA) community have developed several approaches to enhance the performance of traditional GAs for dynamic optimization problems (DOPs). Among these approaches, one technique is to maintain the diversity of the population by inserting random immigrants into the population. This chapter investigates a self-organizing random immigrants scheme for GAs to address DOPs, where the worst individual and its next neighbours are replaced by random immigrants. In order to protect the newly introduced immigrants from being replaced by fitter individuals, they are placed in a subpopulation. In this way, individuals start to interact between themselves and, when the fitness of the individuals are close, one single replacement of an individual can affect a large number of individuals of the population in a chain reaction. The individuals in a subpopulation are not allowed to be replaced by individuals of the main population during the current chain reaction. The number of individuals in the subpopulation is given by the number of individuals created in the current chain reaction. It is important to observe that this simple approach can take the system to a self-organization behaviour, which can be useful for GAs in dynamic environments.Financial support was obtained from FAPESP (Proc. 04/04289-6)

Electric Field Effects on Graphene Materials

Understanding the effect of electric fields on the physical and chemical properties of two-dimensional (2D) nanostructures is instrumental in the design of novel electronic and optoelectronic devices. Several of those properties are characterized in terms of the dielectric constant which play an important role on capacitance, conductivity, screening, dielectric losses and refractive index. Here we review our recent theoretical studies using density functional calculations including van der Waals interactions on two types of layered materials of similar two-dimensional molecular geometry but remarkably different electronic structures, that is, graphene and molybdenum disulphide (MoS$_2$). We focus on such two-dimensional crystals because of they complementary physical and chemical properties, and the appealing interest to incorporate them in the next generation of electronic and optoelectronic devices. We predict that the effective dielectric constant ($\varepsilon$) of few-layer graphene and MoS$_2$ is tunable by external electric fields ($E_{\rm ext}$). We show that at low fields ($E_{\rm ext}^{}<0.01$ V/\AA) $\varepsilon$ assumes a nearly constant value $\sim$4 for both materials, but increases at higher fields to values that depend on the layer thickness. The thicker the structure the stronger is the modulation of $\varepsilon$ with the electric field. Increasing of the external field perpendicular to the layer surface above a critical value can drive the systems to an unstable state where the layers are weakly coupled and can be easily separated. The observed dependence of $\varepsilon$ on the external field is due to charge polarization driven by the bias, which show several similar characteristics despite of the layer considered.Comment: Invited book chapter on Exotic Properties of Carbon Nanomatter: Advances in Physics and Chemistry, Springer Series on Carbon Materials. Editors: Mihai V. Putz and Ottorino Ori (11 pages, 4 figures, 30 references

Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2&nbsp;+&nbsp;H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape

Research Status of the Orphan G Protein Coupled Receptor 158 and Future Perspectives

G-protein-coupled receptors (GPCRs) remain one of the most successful targets for therapeutic drugs approved by the US Food and Drug Administration (FDA). Many novel orphan GPCRs have been identified by human genome sequencing and considered as putative targets for refractory diseases. Of note, a series of studies have been carried out involving GPCR 158 (or GPR158) since its identification in 2005, predominantly focusing on the characterization of its roles in the progression of cancer and mental illness. However, advances towards an in-depth understanding of the biological mechanism(s) involved for clinical application of GPR158 are lacking. In this paper, we clarify the origin of the GPR158 evolution in different species and summarize the relationship between GPR158 and different diseases towards potential drug target identification, through an analysis of the sequences and substructures of GPR158. Further, we discuss how recent studies set about unraveling the fundamental features and principles, followed by future perspectives and thoughts, which may lead to prospective therapies involving GPR158

Heterogeneous network embedding enabling accurate disease association predictions.

BackgroundIt is significant to identificate complex biological mechanisms of various diseases in biomedical research. Recently, the growing generation of tremendous amount of data in genomics, epigenomics, metagenomics, proteomics, metabolomics, nutriomics, etc., has resulted in the rise of systematic biological means of exploring complex diseases. However, the disparity between the production of the multiple data and our capability of analyzing data has been broaden gradually. Furthermore, we observe that networks can represent many of the above-mentioned data, and founded on the vector representations learned by network embedding methods, entities which are in close proximity but at present do not actually possess direct links are very likely to be related, therefore they are promising candidate subjects for biological investigation.ResultsWe incorporate six public biological databases to construct a heterogeneous biological network containing three categories of entities (i.e., genes, diseases, miRNAs) and multiple types of edges (i.e., the known relationships). To tackle the inherent heterogeneity, we develop a heterogeneous network embedding model for mapping the network into a low dimensional vector space in which the relationships between entities are preserved well. And in order to assess the effectiveness of our method, we conduct gene-disease as well as miRNA-disease associations predictions, results of which show the superiority of our novel method over several state-of-the-arts. Furthermore, many associations predicted by our method are verified in the latest real-world dataset.ConclusionsWe propose a novel heterogeneous network embedding method which can adequately take advantage of the abundant contextual information and structures of heterogeneous network. Moreover, we illustrate the performance of the proposed method on directing studies in biology, which can assist in identifying new hypotheses in biological investigation