Online Mental Health Information Behaviours of Emerging Adults: A Web Usability and User Experience Study

This study aims to employ usability study technologies to learn how emerging adults interact online with mental health information

Second year technical report on-board processing for future satellite communications systems

Advanced baseband and microwave switching techniques for large domestic communications satellites operating in the 30/20 GHz frequency bands are discussed. The nominal baseband processor throughput is one million packets per second (1.6 Gb/s) from one thousand T1 carrier rate customer premises terminals. A frequency reuse factor of sixteen is assumed by using 16 spot antenna beams with the same 100 MHz bandwidth per beam and a modulation with a one b/s per Hz bandwidth efficiency. Eight of the beams are fixed on major metropolitan areas and eight are scanning beams which periodically cover the remainder of the U.S. under dynamic control. User signals are regenerated (demodulated/remodulated) and message packages are reformatted on board. Frequency division multiple access and time division multiplex are employed on the uplinks and downlinks, respectively, for terminals within the coverage area and dwell interval of a scanning beam. Link establishment and packet routing protocols are defined. Also described is a detailed design of a separate 100 x 100 microwave switch capable of handling nonregenerated signals occupying the remaining 2.4 GHz bandwidth with 60 dB of isolation, at an estimated weight and power consumption of approximately 400 kg and 100 W, respectively

Herpetofaunal Inventory of Arkansas Post National Memorial, Arkansas County, Arkansas

The Arkansas Post National Memorial (ARPO) is a unique historical landmark with an interesting herpetofaunal community. We conducted an amphibian and reptile inventory of this national park from 2000-2002. We found eight amphibian and 21 reptilian species inhabiting the park. These included eight species not previously identified at ARPO. Overall species richness was highest at Alligator Slough, although the northern portion of ARPO was relatively rich. Aquatic trophic guilds included 7 (36.8%) piscivores, 7 (36.8%) omnivores, 4 (21.1%) insectivores, and one (5.3%) carnivore. The terrestrial trophic guilds included 13 (76.5%) insectivores, 2 (11.8%) carnivores, and 1 (5.9%) each of omnivores and generalized carnivores. We provide a species list, analysis of the distributions, diversity relationships and the trophic guilds present at ARPO, including management recommendations for the conservation of the herpetofauna community at ARPO

\u27Ideology\u27 or \u27Situation Sense\u27? An Experimental Investigation of Motivated Reasoning and Professional Judgment

This Article reports the results of a study on whether political predispositions influence judicial decisionmaking. The study was designed to overcome the two principal limitations on existing empirical studies that purport to find such an influence: the use of nonexperimental methods to assess the decisions of actual judges; and the failure to use actual judges in ideologically-biased-reasoninge xperiments. The study involved a sample of sitting judges (n = 253), who, like members of a general public sample (n = 8oo), were culturally polarized on climate change, marijuana legalization and other contested issues. When the study subjects were assigned to analyze statutory interpretationp roblems, however, only the responses of the general-public subjects and not those of the judges varied in patterns that reflected the subjects\u27 cultural values. The responses of a sample of lawyers (n = 217) were also uninfluenced by their cultural values; the responses of a sample of law students (n = 284), in contrast, displayed a level of cultural bias only modestly less pronounced than that observed in the general-public sample. Among the competing hypotheses tested in the study, the results most supported the position that professional judgment imparted by legal training and experience confers resistance to identityprotective cognition-a dynamic associated with politically biased information processing generally-but only for decisions that involve legal reasoning. The scholarly and practical implications of the findings are discussed

\u27 Ideology or Situation Sense ? An Experimental Investigation of Motivated Reasoning and Professional Judgment

This Article reports the results of a study on whether political predispositions influence judicial decisionmaking. The study was designed to overcome the two principal limitations on existing empirical studies that purport to find such an influence: the use of nonexperimental methods to assess the decisions of actual judges; and the failure to use actual judges in ideologically-biased-reasoning experiments. The study involved a sample of sitting judges (n = 253), who, like members of a general public sample (n = 800), were culturally polarized on climate change, marijuana legalization and other contested issues. When the study subjects were assigned to analyze statutory interpretation problems, however, only the responses of the general-public subjects and not those of the judges varied in patterns that reflected the subjects’ cultural values. The responses of a sample of lawyers (n = 217) were also uninfluenced by their cultural values; the responses of a sample of law students (n = 284), in contrast, displayed a level of cultural bias only modestly less pronounced than that observed in the general-public sample. Among the competing hypotheses tested in the study, the results most supported the position that professional judgment imparted by legal training and experience confers resistance to identity-protective cognition—a dynamic associated with politically biased information processing generally—but only for decisions that involve legal reasoning. The scholarly and practical implications of the findings are discussed

Fast Hamiltonian sampling for large scale structure inference

In this work we present a new and efficient Bayesian method for nonlinear three dimensional large scale structure inference. We employ a Hamiltonian Monte Carlo (HMC) sampler to obtain samples from a multivariate highly non-Gaussian lognormal Poissonian density posterior given a set of observations. The HMC allows us to take into account the nonlinear relations between the observations and the underlying density field which we seek to recover. As the HMC provides a sampled representation of the density posterior any desired statistical summary, such as the mean, mode or variance, can be calculated from the set of samples. Further, it permits us to seamlessly propagate non-Gaussian uncertainty information to any final quantity inferred from the set of samples. The developed method is extensively tested in a variety of test scenarios, taking into account a highly structured survey geometry and selection effects. Tests with a mock galaxy catalog based on the millennium run show that the method is able to recover the filamentary structure of the nonlinear density field. The results further demonstrate the feasibility of non-Gaussian sampling in high dimensional spaces, as required for precision nonlinear large scale structure inference. The HMC is a flexible and efficient method, which permits for simple extension and incorporation of additional observational constraints. Thus, the method presented here provides an efficient and flexible basis for future high precision large scale structure inference.Comment: 14 pages, 7 figure

Sampling constrained probability distributions using Spherical Augmentation

Statistical models with constrained probability distributions are abundant in machine learning. Some examples include regression models with norm constraints (e.g., Lasso), probit, many copula models, and latent Dirichlet allocation (LDA). Bayesian inference involving probability distributions confined to constrained domains could be quite challenging for commonly used sampling algorithms. In this paper, we propose a novel augmentation technique that handles a wide range of constraints by mapping the constrained domain to a sphere in the augmented space. By moving freely on the surface of this sphere, sampling algorithms handle constraints implicitly and generate proposals that remain within boundaries when mapped back to the original space. Our proposed method, called {Spherical Augmentation}, provides a mathematically natural and computationally efficient framework for sampling from constrained probability distributions. We show the advantages of our method over state-of-the-art sampling algorithms, such as exact Hamiltonian Monte Carlo, using several examples including truncated Gaussian distributions, Bayesian Lasso, Bayesian bridge regression, reconstruction of quantized stationary Gaussian process, and LDA for topic modeling.Comment: 41 pages, 13 figure