The mineralogy of newly formed dust in active galactic nuclei

The tori around active galactic nuclei (AGN) are potential formation sites for large amounts of dust, and they may help resolve the so-called dust budget crisis at high redshift. We investigate the dust composition in 53 of the 87 Palomar Green (PG) quasars showing the 9.7 micron silicate feature in emission. By simultaneously fitting the mid-infrared spectroscopic features and the underlying continuum, we estimate the mass fraction in various amorphous and crystalline dust species. We find that the dust consists predominantly of alumina and amorphous silicates, with a small fraction in crystalline form. The mean crystallinity is 8 +/- 6%, with more than half of the crystallinities greater than 5%, well above the upper limit determined for the Galaxy. Higher values of crystallinity are found for higher oxide fractions and for more luminous sources.Comment: 24 pages, 9 figures, accepted for publication in Planetary and Space Scienc

Towards Interpretable Natural Language Understanding with Explanations as Latent Variables

Recently generating natural language explanations has shown very promising results in not only offering interpretable explanations but also providing additional information and supervision for prediction. However, existing approaches usually require a large set of human annotated explanations for training while collecting a large set of explanations is not only time consuming but also expensive. In this paper, we develop a general framework for interpretable natural language understanding that requires only a small set of human annotated explanations for training. Our framework treats natural language explanations as latent variables that model the underlying reasoning process of a neural model. We develop a variational EM framework for optimization where an explanation generation module and an explanation-augmented prediction module are alternatively optimized and mutually enhance each other. Moreover, we further propose an explanation-based self-training method under this framework for semi-supervised learning. It alternates between assigning pseudo-labels to unlabeled data and generating new explanations to iteratively improve each other. Experiments on two natural language understanding tasks demonstrate that our framework can not only make effective predictions in both supervised and semi-supervised settings, but also generate good natural language explanation

Hydrogen-enriched compressed natural gas network simulation for consuming green hydrogen considering the hydrogen diffusion process

Transporting green hydrogen by existing natural gas networks has become a practical means to accommodate curtailed wind and solar power. Restricted by pipe materials and pressure levels, there is an upper limit on the hydrogen blending ratio of hydrogen-enriched compressed natural gas (HCNG) that can be transported by natural gas pipelines, which affects whether the natural gas network can supply energy safely and reliably. To this end, this paper investigates the effects of the intermittent and fluctuating green hydrogen produced by different types of renewable energy on the dynamic distribution of hydrogen concentration after it is blended into natural gas pipelines. Based on the isothermal steady-state simulation results of the natural gas network, two convection–diffusion models for the dynamic simulation of hydrogen injections are proposed. Finally, the dynamic changes of hydrogen concentration in the pipelines under scenarios of multiple green hydrogen types and multiple injection nodes are simulated on a seven-node natural gas network. The simulation results indicate that, compared with the solar-power-dominated hydrogen production-blending scenario, the hydrogen concentrations in the natural gas pipelines are more uniformly distributed in the wind-power-dominated scenario and the solar–wind power balance scenario. To be specific, in the solar-power-dominated scenario, the hydrogen concentration exceeds the limit for more time whilst the overall hydrogen production is low, and the local hydrogen concentration in the natural gas network exceeds the limit for nearly 50% of the time in a day. By comparison, in the wind-power-dominated scenario, all pipelines can work under safe conditions. The hydrogen concentration overrun time in the solar–wind power balance scenario is also improved compared with the solar-power-dominated scenario, and the limit-exceeding time of the hydrogen concentration in Pipe 5 and Pipe 6 is reduced to 91.24% and 91.99% of the solar-power-dominated scenario. This work can help verify the day-ahead scheduling strategy of the electricity-HCNG integrated energy system (IES) and provide a reference for the design of local hydrogen production-blending systems

Experiments of Water Flooded Longitudinal State on Offshore Thick Reservoir

Reservoir sedimentary rhythmic is an important geological factors influencing the dynamic characteristics of the reservoir development and residual oil distribution. Bohai LD oil field is a typical thick reservoir, large well spacing multilayer commingled production in offshore oil field conditions, the gravity effect is more apparent, the remaining oil in the middle and high water period is comparatively complicated. For further study the remaining oil distribution of reservoir after water flooding, the research of indoor core displacement experiment was carried out. Combine the reservoir properties, design parameters according to similar principle, in this paper, the distribution of remaining oil and the production dynamics characteristics under different rhythm is researched. The research results indicate that: Due to gravitational differentiation, the reservoir is submerged at the bottom under homogeneous rhythm. The higher the core permeability, the stronger the gravity differentiation act, the smaller water flooded vertical thickness is, and remaining oil concentrate at the top. Gravity makes positive rhythm formation longitudinal contradictions become more prominent, after water flooding breakthrough, water cut rise fast, core recovery is low, the remaining oil is concentrated in the upper part of the low permeable formation; Gravitational differentiation can play a role in reverse rhythm, water drive is relatively uniform, core recovery is high. Under composite rhythm, the displacement situation of water drive is similar to the single rhythm

Motor Sequence Learning Is Associated With Hippocampal Subfield Volume in Humans With Medial Temporal Lobe Epilepsy

Objectives: Medial temporal lobe epilepsy (mTLE) is characterized by decreased hippocampal volume, which results in motor memory consolidation impairments. However, the extent to which motor memory acquisition are affected in humans with mTLE remains poorly understood. We therefore examined the extent to which learning of a motor tapping sequence task is affected by mTLE.Methods: MRI volumetric analysis was performed using a T1-weighted three-dimensional gradient echo sequence in 15 patients with right mTLE and 15 control subjects. Subjects trained on a motor sequence tapping task with the left hand in right mTLE and non-dominant hand in neurologically-intact controls.Results: The number of correct sequences performed by the mTLE patient group increased after training, albeit to a lesser extent than the control group. Although hippocampal subfield volume was reduced in mTLE relative to controls, no differences were observed in the volumes of other brain areas including thalamus, caudate, putamen and amygdala. Correlations between hippocampal subfield volumes and the change in pre- to post-training performance indicated that the volume of hippocampal subfield CA2–3 was associated with motor sequence learning in patients with mTLE.Significance: These results provide evidence that individuals with mTLE exhibit learning on a motor sequence task. Learning is linked to the volume of hippocampal subfield CA2–3, supporting a role of the hippocampus in motor memory acquisition.Highlights-Humans with mTLE exhibit learning on a motor tapping sequence task but not to the same extent as neurologically-intact controls.-Hippocampal subfield volumes are significantly reduced after mTLE. Surrounding brain area volumes do not show abnormalities.-Hippocampal subfield CA2–3 volume is associated with motor sequence learning in humans with mTLE

Experimental study of thermal fracturing of Hot Dry Rock irradiated by moving laser beam: Temperature, efficiency and porosity

A new laser irradiation fracturing method is employed to crack the Hot Dry Rock (HDR) and variations of rock temperature, specific energy (SE) and modified specific energy (MSE), thermal damages and open porosity of granite samples caused by moving laser beams with various irradiating conditions including laser power, diameter and moving speed of laser beam were investigated. Results indicate that rock temperature and the corresponding temperature gradients near the laser beam spots are strongly dependent on the laser power, beam diameter and irradiation time. The high temperature generated by the laser irradiation melts and cracks the HDR samples. The removed mass, cracked mass and size of grooving kerf induced by laser irradiation are also related to various irradiation conditions. SE and MSE are found nonlinearly reduced with the increased laser power density. Laser irradiation has a greater enhancement to thermal fracturing of granite than it does to thermal drilling. The open porosity (OP) of irradiated HDR samples increases with increasing laser power, decreasing diameter and moving speed of laser beam. The results can provide some guidance to those seeking a new economical and reasonable fracturing method for the HDR geothermal exploitation

Fe controls the reproduction of zoogloea and sludge bulking in oil-in-iron wastewater

Following the final biological treatment, the oil wastewater is intended for reuse in factory floor cleaning. However, the presence of varying concentrations of oil-in-iron characteristic wastewater has led to a sudden surge in sludge SV to 90%, adversely affecting water treatment efficiency. In this study, we conducted an analysis of microbial community structure and selected pepA and 16S rRNA primers to assess the proportions of zoogloea and total bacteria in sludge bulking. Iron concentration plays a pivotal role, and it should be maintained at or 0.6 mgL−1. By selective discharging of sludge to maintain 1,700 mgL−1, we minimized iron enrichment, thereby enhancing the sludge settling performance. Maintaining dissolved oxygen (DO) at 3.5 mgL−1 supports the aerobic sludge's ability to replenish iron in its system, while the oil content should be controlled at 145.33 mgL−1 to reduce the release of iron into the water. The order of significance is as follows: sludge concentration > Fe amount > DO > oil content. Implementing this approach was applied in the field for 1 week and effectively reduced the SV from 90% to approximately 43%. The interaction between quorum sensing molecules related to sludge bulking and iron, leading to the formation of complexes, underscores the significance of controlling iron levels. This study offers a valuable case for practical application of quorum quenching technology in oil wastewater, presenting a rapid, efficient, and cost-effective solution to address the issue of sludge bulking