AGN anisotropic radiative feedback set by black hole spin

ABSTRACT We consider the impact of anisotropic radiation on the active galactic nucleus (AGN) radiative dusty feedback. The radiation pattern originating from the accretion disc is determined by the central black hole (BH) spin. Here we analyse how such BH spin-induced angular dependence affects the dynamics and energetics of the radiation pressure-driven outflows, as well as AGN obscuration and BH accretion. In addition, we explore the effect of a spatially varying dust-to-gas ratio on the outflow propagation. We obtain two distinct trends for high-spin and low-spin objects, providing a direct connection between anisotropic feedback and BH spin. In the case of maximum spin, powerful quasi-spherical outflows can propagate on large scales, at all inclination angles with fairly uniform energetics. In contrast, in the case of zero spin, only weaker bipolar outflows can be driven in the polar directions. As a result, high BH spins can efficiently clear out the obscuring gas from most directions, whereas low BH spins can only remove dusty gas from the polar regions, hence also determining the overall AGN obscuration geometry. Due to such anisotropic feedback, high BH spins can prevent accretion of gas from most directions (except in the equatorial plane), while low BH spins allow inflows to proceed from a wider range of directions. This may have important implications for the BH growth in the early Universe. Anisotropic radiative dusty feedback, ruled by the BH spin, may thus play a major role in shaping AGN evolution over cosmic time.

Measuring Peer Feedback on Writing Class: A Study on Third-Semester Pre-Service English Teachers

This research aimed to measure the contributions of students’ peer feedback set in the collaborative writing class. Of 144 population, 55 undergraduate English education students were involved as the participants in a quasi-experimental research design which was conducted through a non-randomized five experimental and five control groups. There were 25 experimental participants attended in the regular classes with the collaborative writing class syntax, namely; genres selection, problem-based learning, genres, and peer feedback practices, while other 30 control participants naturally attended in the same activity. Data were collected through the collaborative writing’s pre- and post-test, and peer feedback instruments within four weeks of the lectures. Data analysis used the Mann-Whitney U, and Wilcoxon signed rank tests. The findings show that the collaborative writing’s peer feedback positively contributes to students’ writing skills and learning awareness resulted in the post-tests. Peer feedback may correct students’ writing mistakes and contribute a significant difference between the experimental and control groups (Z=-2,471; p≤0,05). Peer feedback socially tightens students’ collaborative writing and promotes a mutual relationship among group members, and reduces lecturer’s feedback.

Kinetic Model of Translational Autoregulation

We investigate dynamics of a kinetic model of inhibitory autoregulation as exemplified when a protein inhibits its own production by interfering with its messenger RNA, known in molecular biology as translational autoregulation. We first show how linear models without feedback set the stage with a nonequilibrium steady state that constitutes the target of the regulation. However, regulation in the simple linear model is far from optimal. The negative feedback mechanism whereby the protein “jams” the mRNA greatly enhances the effectiveness of the control, with response to perturbation that is targeted, rapid, and metabolically efficient. Understanding the full dynamics of the system phase space is essential to understanding the autoregulation process.

Cutting Cycles of Conditional Preference Networks with Feedback Set Approach

As a tool of qualitative representation, conditional preference network (CP-net) has recently become a hot research topic in the field of artificial intelligence. The semantics of CP-nets does not restrict the generation of cycles, but the existence of the cycles would affect the property of CP-nets such as satisfaction and consistency. This paper attempts to use the feedback set problem theory including feedback vertex set (FVS) and feedback arc set (FAS) to cut cycles in CP-nets. Because of great time complexity of the problem in general, this paper defines a class of the parent vertices in a ring CP-nets firstly and then gives corresponding algorithm, respectively, based on FVS and FAS. Finally, the experiment shows that the running time and the expressive ability of the two methods are compared.

Material discrimination and mixture ratio estimation in nanocomposites via harmonic atomic force microscopy

Harmonic atomic force microscopy (AFM) was employed to discriminate between different materials and to estimate the mixture ratio of the constituent components in nanocomposites. The major influencing factors, namely amplitude feedback set-point, drive frequency and laser spot position along the cantilever beam, were systematically investigated. Employing different set-points induces alternation of tip–sample interaction forces and thus different harmonic responses. The numerical simulations of the cantilever dynamics were well-correlated with the experimental observations. Owing to the deviation of the drive frequency from the fundamental resonance, harmonic amplitude contrast reversal may occur. It was also found that the laser spot position affects the harmonic signal strengths as expected. Based on these investigations, harmonic AFM was employed to identify material components and estimate the mixture ratio in multicomponent materials. The composite samples are composed of different kinds of nanoparticles with almost the same shape and size. Higher harmonic imaging offers better information on the distribution and mixture of different nanoparticles as compared to other techniques, including topography and conventional tapping phase. Therefore, harmonic AFM has potential applications in various fields of nanoscience and nanotechnology.