A Study of Active Galactic Nuclei in Low Surface Brightness Galaxies with Sloan Digital Sky Survey Spectroscopy

Active galactic nuclei (AGN) in low surface brightness galaxies (LSBGs) have received little attention in previous studies. In this paper, we present detailed spectral analysis of 194 LSBGs from the Impey et al. (1996) APM LSBG sample which have been observed spectroscopically by the Sloan Digital Sky Survey Data Release 5 (SDSS DR5). Our elaborate spectral analysis enables us to carry out, for the first time, reliable spectral classification of nuclear activities in LSBGs based on the standard emission line diagnostic diagrams in a rigorous way. Star-forming galaxies are common, as found in about 52% LSBGs. We find, contrary to some of the previous claims, that the fraction of galaxies containing an AGN is significantly lower than that found in nearby normal galaxies of high surface brightness. This is qualitatively in line with the finding of Impey et al. (2001). This result holds true even within each morphological type from Sa to Sc. LSBGs having larger central stellar velocity dispersions, or larger physical sizes, tend to have a higher chance to harbor an AGN. For three AGNs with broad emission lines, the black hole masses estimated from the emission lines are broadly consistent with the well known M-$\sigma_\ast$ relation established for normal galaxies and AGNs.Comment: 5 tables and 14 figure

Axial plane optical microscopy.

We present axial plane optical microscopy (APOM) that can, in contrast to conventional microscopy, directly image a sample's cross-section parallel to the optical axis of an objective lens without scanning. APOM combined with conventional microscopy simultaneously provides two orthogonal images of a 3D sample. More importantly, APOM uses only a single lens near the sample to achieve selective-plane illumination microscopy, as we demonstrated by three-dimensional (3D) imaging of fluorescent pollens and brain slices. This technique allows fast, high-contrast, and convenient 3D imaging of structures that are hundreds of microns beneath the surfaces of large biological tissues

Swelling behaviour of compacted Maryland clay under different boundary conditions

This paper presents an experimental study on the swelling response of compacted Maryland clay specimens subjected to hydration under a range of boundary conditions. The research is multi-scale with swelling tests complemented by comprehensive mercury intrusion porosimetry analyses. The objective of the experimental programme is to establish the locus of final swollen states (in terms of void ratio and swelling pressure) and assess its robustness by testing a range of boundary conditions or combinations thereof. Five initial soil conditions were tested and swelling was generated by flooding or incremental suction reduction by way of the osmotic technique. The paper shows that, for a given soil condition, there is no influence of the stress–volume path on the final swollen state. This observation was corroborated at the microscopic level by the mercury intrusion porosimetry. It was concluded that the effect of different stiffness can actually be analysed in terms of the maximum stress applied to the specimen. In particular, a clear correlation was identified between the macroscopic strains and the confinement applied during the test, regardless of the boundary conditions. Also, the conceptual model relating the water ratio and micro void ratio proposed by E. Romero and co-workers in 2011 was found to prevail, regardless of the boundary conditions.Peer ReviewedPostprint (author's final draft

The characteristics of granites in the Gaofeng and Baocheng areas, Hainan Province, China: response to subduction of the Tethyan South China Sea

During the early Mesozoic Era there was intense magmatic activity near Hainan Island, South China. As a result, the granites of Hainan Island provide information on, and are suitable material to potentially improve understanding of the Cretaceous tectonic environment of the northern margin of the South China Sea. The Gaofeng and Baocheng intrusions are composed mainly of medium- to fine-grained biotite adamellite (Baocheng) and granodiorite (Gaofeng). The two intrusions yielded U–Pb LA-ICP-MS zircon ages of 107.7 ± 6.1 Ma (Gaofeng) and 105.8 ± 2.4 Ma (Baocheng). Regarding the major elements, the Gaofeng and Baocheng intrusions had medium Si and alkali contents and high Ca, Mg, and Al contents, with an aluminum saturation index of 0.95–1.03 and 1.05–1.30. The trace element and rare earth element (REE) characteristics showed that the two intrusions have intense heavy REE/light REE (HREE/LREE) fractionation, LREE enrichment, HREE depletion, and weak negative Eu anomalies. The intrusions were enriched in high field-strength elements and depleted in large ion lithophile elements. These geochemical characteristics indicate that the Hainan Province was in a tectonic subduction environment in the late Yanshanian period. Multiple geochemical characteristics demonstrate that the granites in the Hainan Province were formed by a different mechanism and in a different setting from those in Fujian and Zhejiang. The late Mesozoic granites of Fujian and Zhejiang were formed by the Western Pacific subduction. However, Hainan Island was under an arc environment formed by the northward subduction of the Tethyan-South China Sea during the Cretaceous leading to emplacement of the Gaofeng and Baocheng intrusions.</p

Resonant Column Test on the Frozen Silt Soil Modulus and Damping at Different Temperatures

The shear modulus and damping ratio of frozen soil are thebasic parameters of its dynamic properties and are often testedwith the dynamic triaxial apparatus. However, the resonantcolumn apparatus is more suitable for the testing at the microstrainlevel. A resonant column apparatus was here used toidentify the varying modes with negative temperature of theinitial shear modulus, modulus ratio, and damping ratio of frozensilt. Correction factor curves indicate that the temperaturehas a great effect on the shear modulus and damping ratio offrozen silt. The curves also show that, within the sensitive stage,the temperature significantly affects the modulus and damping.Within the insensitive stage, the modulus and dampingwere insensitive to the temperature. The experimental resultsand analysis given here provide support for improving seismicdesign codes and offer reasonable parameters for seismicresponse analysis in engineering construction in cold regions

Metal Recovery from Sludge through the Combination of Hydrothermal Sulfidation and Flotation

AbstractThe heavy metal in the waste can react with sulfur and be converted to metal sulfide through the hydrothermal sulfidation. For metal recovery, the synthetic metal sulfide can be enriched through subsequent flotation process. It is a novel way for the recovery of heavy metal from the sludge. In this study, the effects of liquid/solid ratio, mineralizer concentration, precursor concentration and dosage of sulfur on the sulfidation extent and floatation index were investigated. Result shows that with a precursor concentration of 15%, a Zn/S molar ratio of 1:1.2, a liquid/solid ratio of 3:1, the sulfidation extent of zinc in the sludge was greater than 92%, while the flotation recovery of zinc reached up to 45.34%. The toxicity characteristic leaching procedure (TCLP) revealed that stabilization and detoxification of heavy metals occurred during sulfidation

DeepTSP: Deep traffic state prediction model based on large-scale empirical data

Real-time traffic state (e.g., speed) prediction is an essential component for traffic control and management in an urban road network. How to build an effective large-scale traffic state prediction system is a challenging but highly valuable problem. This study focuses on the construction of an effective solution designed for spatio-temporal data to predict the traffic state of large-scale traffic systems. In this study, we first summarize the three challenges faced by large-scale traffic state prediction, i.e., scale, granularity, and sparsity. Based on the domain knowledge of traffic engineering, the propagation of traffic states along the road network is theoretically analyzed, which are elaborated in aspects of the temporal and spatial propagation of traffic state, traffic state experience replay, and multi-source data fusion. A deep learning architecture, termed as Deep Traffic State Prediction (DeepTSP), is therefore proposed to address the current challenges in traffic state prediction. Experiments demonstrate that the proposed DeepTSP model can effectively predict large-scale traffic states