Extragalactic Foreground Contamination in Temperature-based CMB Lens Reconstruction

We discuss the effect of unresolved point source contamination on estimates of the CMB lensing potential, from components such as the thermal Sunyaev-Zel'dovich effect, radio point sources, and the Cosmic Infrared Background. We classify the possible trispectra associated with such source populations, and construct estimators for the amplitude and scale-dependence of several of the major trispectra. We show how to propagate analytical models for these source trispectra to biases for lensing. We also construct a "source-hardened" lensing estimator which experiences significantly smaller biases when exposed to unresolved point sources than the standard quadratic lensing estimator. We demonstrate these ideas in practice using the sky simulations of Sehgal et. al., for cosmic-variance limited experiments designed to mimic ACT, SPT, and Planck

Threshhold analysis of phase locked loops

Computer technique for predicting threshold in phased locked loops with and without frequency modulatio

Pure xenon hexafluoride prepared for thermal properties studies

Preparation of a xenon hexafluoride and sodium fluoride salt yields a sample of the highest possible purity for use in thermal measurements. The desired hexafluoride can easily be freed from the common contaminants, xenon tetra-fluoride, xenon difluoride, and xenon oxide tetrafluoride, because none of these compounds reacts with sodium fluoride

Fostering Students\u27 Identification with Mathematics and Science

Book Summary: Interest in Mathematics and Science Learning is the first volume to assemble findings on the role of interest in mathematics and science learning. As the contributors illuminate across the volume’s 22 chapters, interest provides a critical bridge between cognition and affect in learning and development. This volume will be useful to educators, researchers, and policy makers, especially those whose focus is mathematics, science, and technology education. Chapter Summary: The primary purpose of this chapter is to explore the process whereby students transition from a short-term, situational interest in mathematics or science to a more enduring individual interest in which they incorporate performance in mathematics or science into their self-definitions (e.g. I am a scientist ). We do so by examining the research related to domain identification, which is the extent to which students define themselves through a role or performance in a domain, such as mathematics or science. Understanding the process of domain identification is important because it can contribute to an understanding of how individual interest develops over time. The means through which students become highly domain identified involves many factors that are internal (e.g. goals and beliefs) and external (e.g. family environment and educational experiences) to them. Students who are more identified with an academic domain tend to demonstrate increased motivation, effort, perseverance (when faced with failure), and achievement. Importantly, students with lower domain identification tend to demonstrate less motivation, lower effort, and fewer desirable outcomes. Student outcomes in a domain can reciprocally influence domain identification by reinforcing or altering it. This feedback loop can help explain incremental changes in motivation, self-concept, individual interest, and, ultimately, important outcomes such as achievement, choice of college major, and career path. This dynamic model presents possible mechanisms for influencing student outcomes. Furthermore, assessing students\u27 domain identification can allow practitioners to intervene to prevent undesirable outcomes. Finally, we present research on how mathematics and science instructors could use the principles of the MUSIC Model of Academic Motivation to enhance students\u27 domain identification, by (a) empowering students, (b) demonstrating the usefulness of the domain, (c) supporting students\u27 success, (d) triggering students\u27 interests, and (e) fostering a sense of caring and belonging. We conclude that by using the MUSIC model, instructors can intentionally design educational experiences to help students progress from a situational interest to one that is more enduring and integrated into their identities

New Clarification About Observation Billing May Improve Care for Behavioral Health Patients

Emergency Physicians provide ongoing care to psychiatric patients beyond the confines of a standard emergency room visit.  Often, when we identify patients who need specialty psychiatric care, patients board in the emergency department awaiting acceptance and transfer to an outside facility.  Even in cases where it has taken multiple days to complete the transfer, it has been unclear how to properly obtain reimbursement for this care.  We discuss a new coding clarification that may provide a pathway to improve part of this situation

Distribution of Gaussian Process Arc Lengths

We present the first treatment of the arc length of the Gaussian Process (GP) with more than a single output dimension. GPs are commonly used for tasks such as trajectory modelling, where path length is a crucial quantity of interest. Previously, only paths in one dimension have been considered, with no theoretical consideration of higher dimensional problems. We fill the gap in the existing literature by deriving the moments of the arc length for a stationary GP with multiple output dimensions. A new method is used to derive the mean of a one-dimensional GP over a finite interval, by considering the distribution of the arc length integrand. This technique is used to derive an approximate distribution over the arc length of a vector valued GP in $\mathbb{R}^n$ by moment matching the distribution. Numerical simulations confirm our theoretical derivations.Comment: 10 pages, 4 figures, Accepted to The 20th International Conference on Artificial Intelligence and Statistics (AISTATS

Perspectives on subnational carbon and climate footprints: A case study of Southampton, UK

Sub-national governments are increasingly interested in local-level climate change management. Carbon- (CO2 and CH4) and climate-footprints—(Kyoto Basket GHGs) (effectively single impact category LCA metrics, for global warming potential) provide an opportunity to develop models to facilitate effective mitigation. Three approaches are available for the footprinting of sub-national communities. Territorial-based approaches, which focus on production emissions within the geo-political boundaries, are useful for highlighting local emission sources but do not reflect the transboundary nature of sub-national community infrastructures. Transboundary approaches, which extend territorial footprints through the inclusion of key cross boundary flows of materials and energy, are more representative of community structures and processes but there are concerns regarding comparability between studies. The third option, consumption-based, considers global GHG emissions that result from final consumption (households, governments, and investment). Using a case study of Southampton, UK, this chapter develops the data and methods required for a sub-national territorial, transboundary, and consumption-based carbon and climate footprints. The results and implication of each footprinting perspective are discussed in the context of emerging international standards. The study clearly shows that the carbon footprint (CO2 and CH4 only) offers a low-cost, low-data, universal metric of anthropogenic GHG emission and subsequent management

ASSESSING GRADUATE STUDENT NEEDS AND RESPONSIVE INSTITUTION ASSETS: APPLICATION OF AN ASSET AND CAPACITY BUILDING HYBRID FRAMEWORK

This study seeks to better understand the needs of graduate students at a large southeastern university through a qualitative needs assessment framed by Altschuld’s (2015) asset / capacity building needs assessment model. Through graduate student focus groups and faculty, staff and administrator interviews, this study investigates the needs, successes, and assets of and for post-baccalaureate students within the university setting and context. Qualitative analysis procedures inductive thematic content analysis, primarily following an interpretivist paradigm (Fereday & Muir-Cochraine, 2006; Saldana, 2016). Findings illustrate the existence of both specific graduate student needs as well as assets to supplement these needs. Study analysis yielded thirteen primary themes, which were then categorized into Altschuld’s (2015) asset / capacity building needs assessment framework of unmet needs, barriers, current assets, and future assets. Study findings evidence several key current assets currently supporting graduate student success, including graduate student support structures, research opportunities, and professional development opportunities. Unmet needs and barriers evidenced in the study included areas focused on communication, advising, mental health, and institutional structures. Future assets include building broader, deeper graduate student communities and emphasizing the importance of individual student identities. Recommendations to improve graduate student success evidenced from this study include the establishment of a centralized hub for graduate students, a review of institutional processes, and increased support and structures for advising and community development