Comparing Simple Quasar Demographics Models

This paper explores several simple model variations for the connections among quasars, galaxies, and dark matter halos for redshifts 1 < z < 6. A key component of these models is that we enforce a self-consistent black hole (BH) history by tracking both BH mass and BH growth rate at all redshifts. We connect objects across redshift with a simple constant-number-density procedure, and choose a fiducial model with a relationship between BH and galaxy growth rates that is linear and evolves in a simple way with redshift. Within this fiducial model, we find the quasar luminosity function (QLF) by calculating an "intrinsic" luminosity based on either the BH mass or BH growth rate, and then choosing a model of quasar variability with either a lognormal or truncated power-law distribution of instantaneous luminosities. This gives four model variations, which we fit to the observed QLF at each redshift. With the best-fit models in hand, we undertake a detailed comparison of the four fiducial models, and explore changes to our fiducial model of the BH-galaxy relationship. Each model variation can successfully fit the observed QLF, the shape of which is generally set by the "intrinsic" luminosity at the faint end and by the scatter due to variability at the bright end. We focus on accounting for the reasons that physically different models can make such similar predictions, and on identifying what observational data or physical arguments are most essential in breaking the degeneracies among models.Comment: 14 pages, 8 figures, 1 tabl

Irs2 and Irs4 synergize in non-LepRb neurons to control energy balance and glucose homeostasis★

Insulin receptor substrates (Irs1, 2, 3 and Irs4) mediate the actions of insulin/IGF1 signaling. They have similar structure, but distinctly regulate development, growth, and metabolic homeostasis. Irs2 contributes to central metabolic sensing, partially by acting in leptin receptor (LepRb)-expressing neurons. Although Irs4 is largely restricted to the hypothalamus, its contribution to metabolic regulation is unclear because Irs4-null mice barely distinguishable from controls. We postulated that Irs2 and Irs4 synergize and complement each other in the brain. To examine this possibility, we investigated the metabolism of whole body Irs4−/y mice that lacked Irs2 in the CNS (bIrs2−/−·Irs4−/y) or only in LepRb-neurons (Lepr∆Irs2·Irs4−/y). bIrs2−/−·Irs4−/y mice developed severe obesity and decreased energy expenditure, along with hyperglycemia and insulin resistance. Unexpectedly, the body weight and fed blood glucose levels of Lepr∆Irs2·Irs4−/y mice were not different from Lepr∆Irs2 mice, suggesting that the functions of Irs2 and Irs4 converge upon neurons that are distinct from those expressing LepRb

Enhanced thermoelectricity in Bi-sprayed bismuth sulphide particles

Bismuth sulphide (Bi2S3), an n-type semiconductor that critically demonstrates the Seebeck effect with Seebeck coefficients of about 300 μVK−1. However, its poor electrical conductivity makes it unsuitable for thermoelectric applications. In this study, we present a facile preparation method for fabricating Bi-sprayed Bi2S3 particles that alters their thermoelectric properties. Samples were created with differing Bi concentrations into the Bi2S3 compound to test for enhanced thermoelectric properties of the resulting Bi/Bi2S3 composites. The incorporation of excess Bi into Bi2S3 significantly improves the compound's electrical conductivity and optimises overall thermoelectric performance. The electrical conductivity of the Bi/Bi2S3 composites improved from 6.5 Scm−1 (for pristine Bi2S3) to 154 Scm−1 (for highest Bi added Bi2S3). Although the Seebeck coefficient of samples decreased with Bi incorporation, a high power factor (∼390 μWm−1K−2) has been achieved for an optimised composition of the composite. Incorporation of metallic Bi has led to an increase in the thermal conductivity of the samples, but the increase is not significant for the optimised composition of the composites where a high thermoelectric performance has been observed. Therefore, enhanced power factor and moderate thermal conductivity have resulted in a peak ZT value of 0.11 at room temperature. The strategy proposed here improves the thermoelectricity in Bi2S3 and shows excellent potential for developing better-performing thermoelectric compounds with excess elemental contents

Evaluation of the angiotensin II receptor blocker azilsartan medoxomil in African-American patients with hypertension

The efficacy and safety of azilsartan medoxomil (AZL-M) were evaluated in African-American patients with hypertension in a 6-week, double-blind, randomized, placebo-controlled trial, for which the primary end point was change from baseline in 24-hour mean systolic blood pressure (BP). There were 413 patients, with a mean age of 52years, 57% women, and baseline 24-hour BP of 146/91mmHg. Treatment differences in 24-hour systolic BP between AZL-M 40mg and placebo (-5.0mmHg; 95% confidence interval, -8.0 to -2.0) and AZL-M 80mg and placebo (-7.8mmHg; 95% confidence interval, -10.7 to -4.9) were significant (P.001 vs placebo for both comparisons). Changes in the clinic BPs were similar to the ambulatory BP results. Incidence rates of adverse events were comparable among the treatment groups, including those of a serious nature. In African-American patients with hypertension, AZL-M significantly reduced ambulatory and clinic BPs in a dose-dependent manner and was well tolerated

Modeling Luminosity-Dependent Galaxy Clustering Through Cosmic Time

We employ high-resolution dissipationless simulations of the concordance LCDM cosmology to model the observed luminosity dependence and evolution of galaxy clustering through most of the age of the universe, from z~5 to z~0. We use a simple, non-parametric model which monotonically relates galaxy luminosities to the maximum circular velocity of dark matter halos (V_max) by preserving the observed galaxy luminosity function in order to match the halos in simulations with observed galaxies. The novel feature of the model is the use of the maximum circular velocity at the time of accretion, V_max,acc, for subhalos, the halos located within virial regions of larger halos. We argue that for subhalos in dissipationless simulations, V_max,acc reflects the luminosity and stellar mass of the associated galaxies better than the circular velocity at the epoch of observation, V_max,now. The simulations and our model L-V_max relation predict the shape, amplitude, and luminosity dependence of the two-point correlation function in excellent agreement with the observed galaxy clustering in the SDSS data at z~0 and in the DEEP2 samples at z~1 over the entire probed range of projected separations, 0.1<r_p/(Mpc/h)<10.0. In particular, the small-scale upturn of the correlation function from the power-law form in the SDSS and DEEP2 luminosity-selected samples is reproduced very well. At z~3-5, our predictions also match the observed shape and amplitude of the angular two-point correlation function of Lyman-break galaxies (LBGs) on both large and small scales, including the small-scale upturn.Comment: 16 pages 11 figures, ApJ in pres

LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models

Large language models (LLMs) provide excellent text-generation capabilities, but standard prompting and generation methods generally do not lead to intentional or goal-directed agents and might necessitate considerable prompt tuning. This becomes particularly apparent in multi-turn conversations: even the best current LLMs rarely ask clarifying questions, engage in explicit information gathering, or take actions now that lead to better decisions after multiple turns. Reinforcement learning has the potential to leverage the powerful modeling capabilities of LLMs, as well as their internal representation of textual interactions, to create capable goal-directed language agents. This can enable intentional and temporally extended interactions, such as with humans, through coordinated persuasion and carefully crafted questions, or in goal-directed play through text games to bring about desired final outcomes. However, enabling this requires the community to develop stable and reliable reinforcement learning algorithms that can effectively train LLMs. Developing such algorithms requires tasks that can gauge progress on algorithm design, provide accessible and reproducible evaluations for multi-turn interactions, and cover a range of task properties and challenges in improving reinforcement learning algorithms. Our paper introduces the LMRL-Gym benchmark for evaluating multi-turn RL for LLMs, together with an open-source research framework containing a basic toolkit for getting started on multi-turn RL with offline value-based and policy-based RL methods. Our benchmark consists of 8 different language tasks, which require multiple rounds of language interaction and cover a range of tasks in open-ended dialogue and text games

E-Data Quality: How Publishers and Libraries are Working Together to Improve Data Quality

High quality data is essential for discovery and access of e-resources, but in many cases low quality, inaccurate information leads to low usage and a poor return on library investment dollars. In this article, publishers, aggregators, librarians, and knowledge base providers talk about how they are working together to improve access to e-resources

Aquilegia, Vol. 40 No. 1 - Winter 2015-2016, Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1188/thumbnail.jp

A Simple Model for Quasar Demographics

We present a simple model for the relationship between quasars, galaxies, and dark matter halos from 0.5<z<6. In the model, black hole (BH) mass is linearly related to galaxy mass, and galaxies are connected to dark matter halos via empirically constrained relations. A simple "scattered" light bulb model for quasars is adopted, wherein BHs shine at a fixed fraction of the Eddington luminosity during accretion episodes, and Eddington ratios are drawn from a lognormal distribution that is redshift-independent. This model has two free, physically meaningful parameters at each redshift: the normalization of the Mbh-Mgal relation and the quasar duty cycle; these parameters are fit to the observed quasar luminosity function (LF) over the interval 0.5<z<6. This simple model provides an excellent fit to the LF at all epochs, and also successfully predicts the observed projected two-point correlation of quasars from 0.5<z<2.5. It is significant that a single quasar duty cycle at each redshift is capable of reproducing the extant observations. The data are therefore consistent with a scenario wherein quasars are equally likely to exist in galaxies, and therefore dark matter halos, over a wide range in masses. The knee in the quasar LF is a reflection of the knee in the stellar mass-halo mass relation. Future constraints on the quasar LF and quasar clustering at high redshift will provide strong constraints on the model. In the model, the autocorrelation function of quasars becomes a strong function of luminosity only at the very highest luminosities, and will be difficult to observe because such quasars are so rare. Cross-correlation techniques may provide useful constraints on the bias of such rare objects.Comment: 12 pages, 12 figures, ApJ accepte