Information in the Tails of the Distribution of Analysts\u27 Quarterly Earnings Forecasts

Investors generally measure earnings announcement news on the basis of the difference between actual earnings and two salient benchmarks: earnings in the same quarter the previous year and a consensus drawn from a distribution of forecasts by financial analysts. We evaluate the implications of a third salient benchmark: the most optimistic forecast when actual earnings exceed the consensus and the most pessimistic forecast when the consensus exceeds actual earnings. We find that considering the information in these tails of the distribution of analysts\u27 earnings forecasts enhances the profitability of post earnings announcement drift strategies

Correction of Optical Aberrations in Elliptic Neutron Guides

Modern, nonlinear ballistic neutron guides are an attractive concept in neutron beam delivery and instrumentation, because they offer increased performance over straight or linearly tapered guides. However, like other ballistic geometries they have the potential to create significantly non-trivial instrumental resolution functions. We address the source of the most prominent optical aberration, namely coma, and we show that for extended sources the off-axis rays have a different focal length from on-axis rays, leading to multiple reflections in the guide system. We illustrate how the interplay between coma, sources of finite size, and mirrors with non-perfect reflectivity can therefore conspire to produce uneven distributions in the neutron beam divergence, the source of complicated resolution functions. To solve these problems, we propose a hybrid elliptic-parabolic guide geometry. Using this new kind of neutron guide shape, it is possible to condition the neutron beam and remove almost all of the aberrations, whilst providing the same performance in beam current as a standard elliptic neutron guide. We highlight the positive implications for a number of neutron scattering instrument types that this new shape can bring.Comment: Presented at NOP2010 Conference in Alpe d'Huez, France, in March 201

Scientometrics as an Important Tool for the Growth of the Field of Learning Analytics

This article introduces the special issue from SoLAR’s Learning Analytics and Knowledge conference. Learning analytics is an emerging field incorporating theory and practice from numerous disciplines to investigate how learner interactions in digital environments can provide actionable data about the learning process. As the field continues to expand there is a timely opportunity to evaluate its ongoing maturation. This evaluation could be in part informed by regular scientometric analyses from both the Journal and Conference publications. These analyses can collectively provide insight into the development of learning analytics more broadly and assist with the allocation of resources to under-represented areas for example.</jats:p

Learning analytics – a growing field and community engagement

This editorial discusses events that marked the period since the publication of the previous issue – the 5th International Conference on Learning Analytics and Knowledge (LAK 2015), Learning Analytics Summer Institutes (LASIs 2015), and Learning Analytics Policy Briefing in the European Parliament. This period saw releases of two important publications for system-wide implementation of learning analytics in higher education published by Jisc and the Australian Government’s Office for Learning and Teaching. An important recognition of the maturation of the field of learning analytics is the recent publication of the 2015 Google Scholar Metrics identifying the LAK proceedings as the only conference proceedings among the 20 most cited publication venues in educational technology. Building bridges for enhancing impact is another important activity for the field maturation through developing linkages of learning analytics with educational data mining, user modeling, the learning sciences, technology enhanced learning, cyber-learning, and learning at scale. This editorial also introduces a special section published in this issue dedicated to the exploration of connections between self-regulated learning and learning analytics, introduces two regular research papers featured in this issue and describes several special sections that will be published in future issues of the journal.</jats:p

Innovations in Active Education Techniques: Team Based Learning, Flipping the Classroom, and Think-Pair-Share

Team-based learning, flipped classroom, and think-pair-share are active learning pedagogies used commonly in undergraduate medical education today. They are based on constructivist learning theory and are effective to use to actively teach foundational knowledge to medical students. They also help students work on team dynamics, critical thinking, and clinical knowledge application. These techniques can be employed without expensive technology or special training. Medical education was grossly affected by the COVID-19 pandemic and the inability to assemble in person. These educational techniques all allow for enhanced and active remote learning. With the amplification of remote education delivery during the pandemic, it is easy to see how we can use these techniques to spread foundational medical education more equitably across the globe

Soil quality assessment of an agroforestry system following long-term management in the Ozark Highlands

The Soil Management Assessment Framework (SMAF) is a quantitative soil quality (SQ) evaluation tool that is widely applied to assess soil response to specific agricultural management practices over time. Considering the reported SQ benefits of agroforestry (AF) systems and the potential usefulness of SMAF, the objective of this study was to evaluate the effects of tree species (pecan [Carya illinoinensis (Wangenh.) K. Koch] and northern red oak [Quercus rubra L.]), soil fertility source (poultry litter [PL] and inorganic N fertilizer [control]), and soil depth (0–15 and 15–30 cm) on SMAF-derived SQ indices after 17 yr of management at an AF site in northwest Arkansas. Averaged across soil depth, soil organic C scores under red oak with PL application had a lower score (0.48) than red oak fertilized with inorganic N (0.60) and pecan receiving long-term PL applications (0.60), which did not differ from pecan with inorganic N fertilizer application (0.51). Averaged across soil depth, the soil quality index (SQI) for pecan receiving PL applications was 1.1 times greater than that under red oak receiving PL and soils under pecan receiving inorganic N fertilizer. Soil quality assessments use in AF are novel, as SMAF has not been used to identify soil health in these systems, although specific tree crop codes need to be developed in SMAF. Results of this study demonstrate that soils planted under various tree species respond dissimilarly to fertilizer sources and that management may improve overall SQ

Optical Propagation and Communication

Contains an introduction and reports on five research projects.Maryland Procurement Office Contract MDA 904-90-C-5070National Science Foundation Grant ECS 87-18970National Institute of Standards and Technology Grant 60-NANBOD-1052U.S. Army Research Office Grant DAAL03-90-G-0128U.S. Army Research Office Contract DAAL03-87-K-0117U.S. Navy - Office of Naval Research Grant N00014-89-J-1163U.S. Air Force - Office of Scientific Research Contract F49620-90-C-003

Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science During the LAPSE-RATE Campaign

Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 °C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS

Convocation

Program listing performers and works performe