AGN Environments in the Sloan Digital Sky Survey I: Dependence on Type, Redshift, and Luminosity

We explore how the local environment is related to the redshift, type, and luminosity of active galactic nuclei (AGN). Recent simulations and observations are converging on the view that the extreme luminosity of quasars is fueled in major mergers of gas-rich galaxies. In such a picture, quasars are expected to be located in regions with a higher density of galaxies on small scales where mergers are more likely to take place. However, in this picture, the activity observed in low-luminosity AGN is due to secular processes that are less dependent on the local galaxy density. To test this hypothesis, we compare the local photometric galaxy density on kiloparsec scales around spectroscopic Type I and Type II quasars to the local density around lower luminosity spectroscopic Type I and Type II AGN. To minimize projection effects and evolution in the photometric galaxy sample we use to characterize AGN environments, we place our random control sample at the same redshift as our AGN and impose a narrow redshift window around both the AGN and control targets. We find that higher luminosity AGN have more overdense environments compared to lower luminosity AGN on all scales out to our 2\Mpchseventy limit. Additionally, in the range $0.3\leqslant z\leqslant 0.6$, Type II quasars have similarly overdense environments to those of bright Type I quasars on all scales out to our 2\Mpchseventy limit, while the environment of dimmer Type I quasars appears to be less overdense than the environment of Type II quasars. We see increased overdensity for Type II AGN compared to Type I AGN on scales out to our limit of 2\Mpchseventy in overlapping redshift ranges. We also detect marginal evidence for evolution in the number of galaxies within 2\Mpchseventy of a quasar with redshift.Comment: 30 pages, 9 figures. Major revisions made for current version. Some content in previous version has been removed to refocus content on redshift and type effects. This content will be deferred to later work

Robust Machine Learning Applied to Astronomical Datasets III: Probabilistic Photometric Redshifts for Galaxies and Quasars in the SDSS and GALEX

We apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS DR5). We use a conceptually simple but novel application of NN to generate the PDFs - perturbing the object colors by their measurement error - and using the resulting instances of nearest neighbor distributions to generate numerous individual redshifts. When the redshifts are compared to existing SDSS spectroscopic data, we find that the mean value of each PDF has a dispersion between the photometric and spectroscopic redshift consistent with other machine learning techniques, being sigma = 0.0207 +/- 0.0001 for main sample galaxies to r < 17.77 mag, sigma = 0.0243 +/- 0.0002 for luminous red galaxies to r < ~19.2 mag, and sigma = 0.343 +/- 0.005 for quasars to i < 20.3 mag. The PDFs allow the selection of subsets with improved statistics. For quasars, the improvement is dramatic: for those with a single peak in their probability distribution, the dispersion is reduced from 0.343 to sigma = 0.117 +/- 0.010, and the photometric redshift is within 0.3 of the spectroscopic redshift for 99.3 +/- 0.1% of the objects. Thus, for this optical quasar sample, we can virtually eliminate 'catastrophic' photometric redshift estimates. In addition to the SDSS sample, we incorporate ultraviolet photometry from the Third Data Release of the Galaxy Evolution Explorer All-Sky Imaging Survey (GALEX AIS GR3) to create PDFs for objects seen in both surveys. For quasars, the increased coverage of the observed frame UV of the SED results in significant improvement over the full SDSS sample, with sigma = 0.234 +/- 0.010. We demonstrate that this improvement is genuine. [Abridged]Comment: Accepted to ApJ, 10 pages, 12 figures, uses emulateapj.cl

Conceptual problem solving in high school physics

Problem solving is a critical element of learning physics. However, traditional instruction often emphasizes the quantitative aspects of problem solving such as equations and mathematical procedures rather than qualitative analysis for selecting appropriate concepts and principles. This study describes the development and evaluation of an instructional approach called Conceptual Problem Solving (CPS) which guides students to identify principles, justify their use, and plan their solution in writing before solving a problem. The CPS approach was implemented by high school physics teachers at three schools for major theorems and conservation laws in mechanics and CPS-taught classes were compared to control classes taught using traditional problem solving methods. Information about the teachers’ implementation of the approach was gathered from classroom observations and interviews, and the effectiveness of the approach was evaluated from a series of written assessments. Results indicated that teachers found CPS easy to integrate into their curricula, students engaged in classroom discussions and produced problem solutions of a higher quality than before, and students scored higher on conceptual and problem solving measures

Do experts and novices direct attention differently in examining physics diagrams? A study of change detection using the flicker technique

It is known that experts identify or perceive meaningful patterns in visual stimuli related to their domain of expertise. This study explores the speed with which experts and novices detect changes in physics diagrams. Since change detection depends on where individuals direct their attention, differences in the speed with which experts and novices detect changes to diagrams would suggest differences in attention allocation between experts and novices. We present data from an experiment using the “flicker technique,” in which both physics experts and physics novices viewed nearly identical pairs of diagrams that are representative of typical introductory physics situations. The two diagrams in each pair contain a subtle difference that either does or does not change the underlying physics depicted in the diagram. Findings indicate that experts are faster at detecting physics-relevant changes than physics-irrelevant changes; however, there is no difference in response time for novices, suggesting that expertise guides attention for experts when inspecting physics diagrams. We discuss the cognitive implications of our findings

Best Practices from the American Society of Pain and Neuroscience (ASPN) for Clinical Research During a Pandemic or Emergency

The COVID-19 pandemic caught many areas of medicine in a state of unpreparedness for conducting research and completing ongoing projects during a global crisis, including the field of pain medicine. Waves of infection led to a disjointed ability to provide care and conduct clinical research. The American Society of Pain and Neuroscience (ASPN) Research Group has created guidance for pragmatic and ethical considerations for research during future emergency or disaster situations. This analysis uses governmental guidance, scientific best practices, and expert opinion to address procedure-based or device-based clinical trials during such times. Current literature offers limited recommendations on this important issue, and the findings of this group fill a void for protocols to improve patient safety and efficacy, especially as we anticipate the impact of future disasters and spreading global infectious diseases. We recommend local adaptations to best practices and innovations to enable continued research while respecting the stressors to the research subjects, investigator teams, health-care systems, and to local infrastructure

Best Practices from the American Society of Pain and Neuroscience (ASPN) for Clinical Research During a Pandemic or Emergency

The COVID-19 pandemic caught many areas of medicine in a state of unpreparedness for conducting research and completing ongoing projects during a global crisis, including the field of pain medicine. Waves of infection led to a disjointed ability to provide care and conduct clinical research. The American Society of Pain and Neuroscience (ASPN) Research Group has created guidance for pragmatic and ethical considerations for research during future emergency or disaster situations. This analysis uses governmental guidance, scientific best practices, and expert opinion to address procedure-based or device-based clinical trials during such times. Current literature offers limited recommendations on this important issue, and the findings of this group fill a void for protocols to improve patient safety and efficacy, especially as we anticipate the impact of future disasters and spreading global infectious diseases. We recommend local adaptations to best practices and innovations to enable continued research while respecting the stressors to the research subjects, investigator teams, health-care systems, and to local infrastructure

Medical Cannabis: A Review from the American Society of Pain and Neuroscience

Cannabinoids have recently gained a renewed interest due to their potential applicability to various medical conditions, specifically the management of chronic pain conditions. Unlike many other medications, medical cannabis is not associated with serious adverse events, and no overdose deaths have been reported. However, both safety and efficacy data for medical cannabis treatment of chronic, nonmalignant pain conditions are lacking. Therefore, representatives from the American Society of Pain and Neuroscience summarize the evidence, according to level and grade, for medical cannabis treatment of several different pain conditions. Treatment of cancer-related pain has prospective evidentiary support for the use of medical cannabis. Although 3 large and well-designed randomized controlled trials investigated cannabis treatment of cancer-related pain, the evidence yielded only a grade D recommendation. Neuropathic pain has been investigated in prospective studies, but a lack of high-quality evidence renders cannabis treatment for this indication a grade C recommendation. Both safety and efficacy data are lacking for use of medical cannabis to treat chronic nonmalignant pain conditions