Bridges to the Baccalaureate Program at J. Sargeant Reynolds Community College and Virginia Commonwealth University

This paper describes a research apprenticeship to encourage and to inspire minority students to major in disciplines that lead to careers in biomedical research

Community College Perspectives on Teacher Preparation in Virginia

The need for future teachers who are well versed in mathematics and science will not be provided by Virginia’s four-year institutions alone. A large portion of those students who complete their K-8 teacher preparation programs at Virginia’s four-year institutions have studied a significant portion, if not all, of their mathematics and science at community colleges. Therefore, if future teachers are to have completed appropriate mathematics and science courses these must be provided by the community colleges. In addition, community colleges can play a critical role in attracting people with a high potential for becoming excellent teachers. Two-year colleges are located in urban and rural areas, enroll a large portion of Virginia’s minority students, and welcome returning adults. We need to attract students from this source if we are to produce sufficient numbers of well prepared teachers in Virginia. A recent National Science Foundation workshop developed detailed recommendations conceming the role of two-year colleges. This paper will focus on these recommendations

Experiencing Science, An Introduction to Real Methods of Science for the Preservice Teacher

The scientific method presented in the middle school classroom introduces the experimental approach of science in a way that may actually bear little resemblance to the processes actually used by working scientists. Teachers equipped with an insight into the motivations, philosophy, tools, and culture of science will better convey an accurate and positive picture of science as a critically important human endeavor. The Experiencing Science course was designed to answer the challenge of giving the pre-service teacher and decision-maker better insight into actual processes used by scientists, in the context of each of the major disciplines

A tutorial task and tertiary courseware model for collaborative learning communities

RAED provides a computerised infrastructure to support the development and administration of Vicarious Learning in collaborative learning communities spread across multiple universities and workplaces. The system is based on the OASIS middleware for Role-based Access Control. This paper describes the origins of the model and the approach to implementation and outlines some of its benefits to collaborative teachers and learners

A New Record of Deepwater Sculpin, Myoxocephalus thompsonii, in Northeastern Alberta

We present the first documented records of Deepwater Sculpin, Myoxocephalus thompsonii, from northern Alberta, and the second record for the province. Three specimens of Deepwater Sculpin were taken in gill nets set at 17 to 20 m depth in Colin Lake, Alberta, on 15 September 2001. Colin Lake, located in the Canadian Shield region of northeastern Alberta about 125 km northeast of Fort Chipewyan, drains into Lake Athabasca via the Colin River. The only other known Alberta population of Deepwater Sculpin inhabits Upper Waterton Lake in the southwestern corner of the province. This record is approximately 300 km SSE of the nearest verified record in the Northwest Territories and 400 km NW of the nearest verified record in Saskatchewan

PATENTS, R&D AND LAG EFFECTS: EVIDENCE FROM FLEXIBLE METHODS FOR COUNT PANEL DATA ON MANUFACTURING FIRMS

Hausman, Hall and Griliches (1984) and Hall, Griliches and Hausman (1986) investigated whether there was a lag in the patent-R&D relationship for the U.S. manufacturing sector using 1970¿s data. They found that there was little evidence of anything but contemporaneous movement of patents and R&D. We reexamine this important issue employing new longitudinal patent data at the firm level for the U.S. manufacturing sector from 1982 to 1992. To address unique features of the data, we estimate various distributed lag and dynamic multiplicative panel count data models. The paper also develops a new class of count panel data models based on series expansion of the distribution of individual effects. The empirical analyses show that, although results are somewhat sensitive to different estimation methods, the contemporaneous relationship between patenting and R&D expenditures continues to be rather strong, accounting for over 60% of the total R&D elasticity. Regarding the lag structure of the patents-R&D relationship, we do find a significant lag in all empirical specifications. Moreover, the estimated lag effects are higher than have previously been found, suggesting that the contribution of R&D history to current patenting has increased from the 1970¿s to the 1980¿s.Innovative activity, Patents and R&D, Individual effects, count panel data methods.

The role of growth in long term investment returns

Stocks with a high valuation compared to fundamental values imply a high growth rate, yet these stocks have typically under-performed in subsequent years supporting Lakonishok, Shleifer and Vishney's (1994) contrarian investment strategies. The precise definition of growth and subtle differences of measuring growth are explored in assessing the role of growth in long-term investment decisions and stock valuation. Results from a later period and with additional tests than employed by LSV indicate that growth is a primary valuation factor, and valuation measures such as E/P and B/M, are imperfect proxies for expected growth. Growth appears mean reverting, but investors do not seem able to discern changes in growth rates and this miss-specification of expected growth may help explain the superiority of value versus growth strategies. In addition, investors' naïve extrapolations of past growth provide explanatory power in future holding period returns

The Disdrometer Verification Network (DiVeN): a UK network of laser precipitation instruments

Starting in February 2017, a network of 14 Thies laser precipitation monitors (LPMs) were installed at various locations around the United Kingdom to create the Disdrometer Verification Network (DiVeN). The instruments were installed for verification of radar hydrometeor classification algorithms but are valuable for much wider use in the scientific and operational meteorological community. Every Thies LPM is able to designate each observed hydrometeor into one of 20 diameter bins from ≥0.125 to >8 mm and one of 22 speed bins from >0.0 to >20.0 m s−1. Using empirically derived relationships, the instrument classifies precipitation into one of 11 possible hydrometeor classes in the form of a present weather code, with an associated indicator of uncertainty. To provide immediate feedback to data users, the observations are plotted in near-real time (NRT) and made publicly available on a website within 7 min. Here we describe the Disdrometer Verification Network and present specific cases from the first year of observations. Cases shown here suggest that the Thies LPM performs well at identifying transitions between rain and snow, but struggles with detection of graupel and pristine ice crystals (which occur infrequently in the United Kingdom) inherently, due to internal processing. The present weather code quality index is shown to have some skill without the supplementary sensors recommended by the manufacturer. Overall the Thies LPM is a useful tool for detecting hydrometeor type at the surface and DiVeN provides a novel dataset not previously observed for the United Kingdom

Improved cloud-phase determination of low-level liquid and mixed-phase clouds by enhanced polarimetric lidar

The unambiguous retrieval of cloud phase from polarimetric lidar observations is dependent on the assumption that only cloud scattering processes affect polarization measurements. A systematic bias of the traditional lidar depolarization ratio can occur due to a lidar system's inability to accurately measure the entire backscattered signal dynamic range, and these biases are not always identifiable in traditional polarimetric lidar systems. This results in a misidentification of liquid water in clouds as ice, which has broad implications on evaluating surface energy budgets. The Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland employs multiple planes of linear polarization, and photon counting and analog detection schemes, to self evaluate, correct, and optimize signal combinations to improve cloud classification. Using novel measurements of diattenuation that are sensitive to both horizontally oriented ice crystals and counting system nonlinear effects, unambiguous measurements are possible by over constraining polarization measurements. This overdetermined capability for cloud-phase determination allows for system errors to be identified and quantified in terms of their impact on cloud properties. It is shown that lidar system dynamic range effects can cause errors in cloud-phase fractional occurrence estimates on the order of 30 % causing errors in attribution of cloud radiative effects on the order of 10–30 %. This paper presents a method to identify and remove lidar system effects from atmospheric polarization measurements and uses co-located sensors at Summit to evaluate this method. Enhanced measurements are achieved in this work with non-orthogonal polarization retrievals as well as analog and photon counting detection facilitating a more complete attribution of radiative effects linked to cloud properties