Black Hole Feeding and Feedback in a Compact Galaxy

We perform high-resolution hydrodynamical simulations using the framework of {\it MACER} to investigate supermassive black hole (SMBH) feeding and feedback in a massive compact galaxy, which has a small effective radius but a large stellar mass, with a simulation duration of 10 Gyr. We compare the results with a reference galaxy with a similar stellar mass but a less concentrated stellar density distribution, as typically found in local elliptical galaxies. We find that about 10% of the time, the compact galaxy develops multi-phase gas within a few kpc, but the accretion flow through the inner boundary below the Bondi radius is always a single phase. The inflow rate in the compact galaxy is several times larger than in the reference galaxy, mainly due to the higher gas density caused by the more compact stellar distribution. Such a higher inflow rate results in stronger SMBH feeding and feedback and a larger fountain-like inflow-outflow structure. Compared to the reference galaxy, the star formation rate in the compact galaxy is roughly two orders of magnitude higher but is still low enough to be considered quiescent. Over the whole evolution period, the black hole mass grows by $\sim$50% in the compact galaxy, much larger than the value of $\sim$ 3% in the reference galaxy.Comment: 7 pages, 6 figure

Observational Evidence for Hot Wind Impact on pc-scale in Low-luminosity Active Galactic Nucleus

Supermassive black holes in galaxies spend majority of their lifetime in the low-luminosity regime, powered by hot accretion flow. Strong winds launched from the hot accretion flow have the potential to play an important role in active galactic nuclei (AGN) feedback. Direct observational evidence for these hot winds with temperature around 10 keV, has been obtained through the detection of highly ionized iron emission lines with Doppler shifts in two prototypical low-luminosity AGNs, namely M81* and NGC 7213. In this work, we further identify blueshifted H-like O/Ne emission lines in the soft X-ray spectra of these two sources. These lines are interpreted to be associated with additional outflowing components possessing velocity around several $10^3$ km/s and lower temperature (~0.2-0.4 keV). Blue-shifted velocity and the X-ray intensity of these additional outflowing components are hard to be explained by previously detected hot wind freely propagating to larger radii. Through detailed numerical simulations, we find the newly detected blue-shifted emission lines would come from circumnuclear gas shock-heated by the hot wind instead. Hot wind can provide larger ram pressure force on the clumpy circumnuclear gas than the gravitational force from central black hole, effectively impeding the black hole accretion of gas. Our results provide strong evidences for the energy and momentum feedback by the hot AGN wind.Comment: 19 pages, 9 figures, submitted to Ap

Chip-based photonic radar for high-resolution imaging

Radar is the only sensor that can realize target imaging at all time and all weather, which would be a key technical enabler for future intelligent society. Poor resolution and large size are two critical issues for radars to gain ground in civil applications. Conventional electronic radars are difficult to address both issues especially in the relatively low-frequency band. In this work, we propose and experimentally demonstrate, for the first time to the best of our knowledge, a chip-based photonic radar based on silicon photonic platform, which can implement high resolution imaging with very small footprint. Both the wideband signal generator and the de-chirp receiver are integrated on the chip. A broadband photonic imaging radar occupying the full Ku band is experimentally established. A high precision range measurement with a resolution of 2.7 cm and an error of less than 2.75 mm is obtained. Inverse synthetic aperture (ISAR) imaging of multiple targets with complex profiles are also implemented.Comment: 4 pages, 6figure

Effects of congestion charging and subsidy policy on vehicle flow and revenue with user heterogeneity

Traffic congestion is a major issue in urban traffic networks. Both congestion charging and subsidy policy can solve traffic congestion to some extent, but which one is better? Based on this, this paper constructs a typical transit network consisting of three travel tools in four common travel modes. Travelers' values of time affect their choice of transportation in the congestion network, thus a stochastic user equilibrium model is established by considering travelers' heterogenous values of time to evaluate the effects of different combinations of congestion charging and subsidy policies on vehicle flow and revenue. Numerical results indicate that the effectiveness of congestion charging and subsidy policy in alleviating traffic congestion depends on the object of charging or subsidizing. Congestion charging for private cars can reduce traffic flow and alleviate traffic congestion, but charging for ridesharing cars does not reduce traffic flow and may even cause traffic congestion. Subsidizing public buses does not reduce traffic flow, but it can ease congestion by coordinating traffic flow on both edges of the dual-modal transport. The combination of no subsidy for public buses and charging for both private cars and ridesharing cars can obtain the greatest revenue, but it does not alleviate traffic congestion. Although the combination of charging for private cars and subsidizing public buses does not bring the most benefits, it can reduce traffic flow, and its revenue is also considerable. This study can provide quantitative decision support for the government to ease traffic congestion and improve government revenue

CRAI Biblioteca del Campus de Mundet. Memòria d'activitats 2016

Memòria que recull les activitats realitzades al CRAI Biblioteca del Campus de Mundet durant l'any 2016

Immunological effects of the PE/PPE family proteins of Mycobacterium tuberculosis and related vaccines

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb), and its incidence and mortality are increasing. The BCG vaccine was developed in the early 20th century. As the most widely administered vaccine in the world, approximately 100 million newborns are vaccinated with BCG every year, which has saved tens of millions of lives. However, due to differences in region and race, the average protective rate of BCG in preventing tuberculosis in children is still not high in some areas. Moreover, because the immune memory induced by BCG will weaken with the increase of age, it is slightly inferior in preventing adult tuberculosis, and BCG revaccination cannot reduce the incidence of tuberculosis again. Research on the mechanism of Mtb and the development of new vaccines against TB are the main strategies for preventing and treating TB. In recent years, Pro-Glu motif-containing (PE) and Pro-Pro-Glu motif-containing (PPE) family proteins have been found to have an increasingly important role in the pathogenesis and chronic protracted infection observed in TB. The development and clinical trials of vaccines based on Mtb antigens are in progress. Herein, we review the immunological effects of PE/PPE proteins and the development of common PE/PPE vaccines

Joint optimization of depth and ego-motion for intelligent autonomous vehicles

The three-dimensional (3D) perception of autonomous vehicles is crucial for localization and analysis of the driving environment, while it involves massive computing resources for deep learning, which can't be provided by vehicle-mounted devices. This requires the use of seamless, reliable, and efficient massive connections provided by the 6G network for computing in the cloud. In this paper, we propose a novel deep learning framework with 6G enabled transport system for joint optimization of depth and ego-motion estimation, which is an important task in 3D perception for autonomous driving. A novel loss based on feature map and quadtree is proposed, which uses feature value loss with quadtree coding instead of photometric loss to merge the feature information at the texture-less region. Besides, we also propose a novel multi-level V-shaped residual network to estimate the depths of the image, which combines the advantages of V-shaped network and residual network, and solves the problem of poor feature extraction results that may be caused by the simple fusion of low-level and high-level features. Lastly, to alleviate the influence of image noise on pose estimation, we propose a number of parallel sub-networks that use RGB image and its feature map as the input of the network. Experimental results show that our method significantly improves the quality of the depth map and the localization accuracy and achieves the state-of-the-art performance