The contribution from blazar cascade emission to the extragalactic gamma-ray background: What a role does the extragalactic magnetic field play?

We estimate the contribution to the extragalactic gamma-ray background (EGRB) from both intrinsic and cascade emissions produced by blazars using a simple semi- analysis method for two models of the blazar gamma-ray luminosity function (GLF). For the cascade emission, we consider two possible contributions: one is due to that the flux of the cascade emission is lower than the Fermi LAT sensitivity (case I), which is independent on the extragalactic magnetic field (EGMF), another is due to the fact that the flux of the cascade emission is larger than the Fermi LAT sensitivity but the emission angle is larger than LAT point-spread-function (PSF) angle (case II), which depends on the EGMF. Our results indicate that (1) blazar contribution to the EGRB is dominant although it depends on the GLF model and the EGMF; (2) the EGMF plays an important role in estimating the contribution from the cascade emission produced by blazars, the contribution from the cascade emission will significantly alter the EGRB spectrum when the strength of the EGMF is large enough (say BEGMF > 10-12 G); and (3) since the cascade emission in case II reaches a saturation when the strength of the EGMF is ? 10-11 G, it is very possible that the contribution from the cascade emission produced by blazars can be considered as another method to probe the upper limit of the strength of the EGMF.Comment: 6 pages, 3 figures. Accepted for publication in MNRA

Therapeutic Effects of Coccomyxagloeobotrydiformis on the Metabolic Syndrome in Rats

Background/Aims: The metabolic syndrome (MS) is a cluster of metabolic changes that carry a high risk of cardiovascular disease (CVD). A newly discovered microalga, coccomyxagloeobotrydiformis (CGD), has been reported to improve ischemic stroke and metabolism-related indicators. We observed the therapeutic effects of CGD on MS and postulated the underlying mechanism. Methods: A diet-induced MS model in rats was used to observe the therapeutic effects of CGD on MS. Blood-glucose and lipid indices were measured using enzymatic colorimetric kits. A biologic data acquisition and analysis system (BL-420F) was used to evaluate cardiac function. Expression of mitochondrial respiratory chain (MRC) enzymes was measured by immunofluorescence staining. The proteins associated with oxidative stress, apoptosis and inflammation were detected by western blotting. Results: Body weight, abdominal circumference, fasting blood glucose , blood pressure as well as serum levels of total cholesterol, triglycerides and low-density lipoprotein-cholesterol were decreased whereas serum levels of high-density lipoprotein-cholesterol was increased in CGD-treated MS rats. CGD increased left-ventricular systolic pressure, left-ventricular end-diastolic pressure, left-ventricular systolic pressure maximum rate of increase and left-ventricular diastolic pressure maximum rate of decrease in MS rats with cardiovascular complications. CGD up-regulated expression of adenosine monophosphate-activated protein kinase and peroxisome proliferator activated receptor gamma coactivator 1-alpha in the heart, adipose tissue and skeletal muscle. Expression of the MRC subunits of ATPase 6, cytochrome b and succinate dehydrogenase complex, subunit-A was increased whereas that of uncoupling protein-2 decreased in different tissues. CGD showed anti-oxidation effects by increasing expression of superoxide dismutase and decreasing that of malondialdehyde. High expression of Bcl-2 and low expression of Bax and caspase-3 supported the anti-apoptotic effect of CGD on the cardiovascular complications of MS. Conclusion: CGD has a therapeutic effect on MS and associated cardiovascular complications by eliciting mitochondrial protection and having anti-oxidation and anti-apoptosis effects. CGD could be used for MS treatment

Data Driven Robust Energy and Reserve Dispatch Based on a Nonparametric Dirichlet Process Gaussian Mixture Model

Traditional robust optimization methods use box uncertainty sets or gamma uncertainty sets to describe wind power uncertainty. However, these uncertainty sets fail to utilize wind forecast error probability information and assume that the wind forecast error is symmetrical and independent. This assumption is not reasonable and makes the optimization results conservative. To avoid such conservative results from traditional robust optimization methods, in this paper a novel data driven optimization method based on the nonparametric Dirichlet process Gaussian mixture model (DPGMM) was proposed to solve energy and reserve dispatch problems. First, we combined the DPGMM and variation inference algorithm to extract the GMM parameter information embedded within historical data. Based on the parameter information, a data driven polyhedral uncertainty set was proposed. After constructing the uncertainty set, we solved the robust energy and reserve problem. Finally, a column and constraint generation method was employed to solve the proposed data driven optimization method. We used real historical wind power forecast error data to test the performance of the proposed uncertainty set. The simulation results indicated that the proposed uncertainty set had a smaller volume than other data driven uncertainty sets with the same predefined coverage rate. Furthermore, the simulation was carried on PJM 5-bus and IEEE-118 bus systems to test the data driven optimization method. The simulation results demonstrated that the proposed optimization method was less conservative than traditional data driven robust optimization methods and distributionally robust optimization methods

A New Three-Dimension Deceptive Scene Generation against Single-Pass Multibaseline InSAR Based on Multiple Transponders

The interferometry synthetic aperture radar (InSAR) deceptive jamming method utilizing two synergetic transponders can generate a false three-dimension (3D) scene in a single baseline InSAR image. However, such deceptive capability could be reduced by the multibaseline InSAR system. To obtain effective deception on multibaseline InSAR, a novel deceptive scene generation method jointly employing multiple transponders is proposed. It only demands that each transponder is modulated with a complex coefficient when generating a false point. The complex modulation coefficient can be offline calculated according to the deceptive point coordinate by solving a matrix. Besides, the complex modulation coefficient can be combined with the deceptive scene template, and thus a large 3D deceptive scene is able to be created quickly in the multibaseline InSAR image by using the fast two-dimension (2D) SAR deceptive scene generation algorithm. As long as the number of transponders is not less than the number of antennas of the multibaseline InSAR system, this proposed method is effective. The effectiveness of the proposed method is validated by computer simulations