An approach to valuing ponds within farming systems for aquaculture

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Building reflective practices in a pre-service math and science teacher education course that focuses on qualitative video analysis

The use of video for in-service and pre-service teacher development has been gaining acceptance, and yet video remains a challenging and understudied tool. Many projects have used video to help pre-service and in-service teachers reflect on their own teaching processes, examine teacher–student interactions, and develop their professional vision. But rarely has video been used in ways more akin to qualitative education research that is focused on student learning. Even more rarely has this focus occurred at the earliest stages of pre-service teaching when students have not yet decided to pursue teaching careers. Yet here we argue that there are benefits to our approach. We examine a course for prospective pre-service math and science teachers at the University of California, Berkeley, that engages participants in qualitative video analysis to foster their reflective practice. This course is unique in that the prospective pre-service teachers engage in qualitative video analysis at a level characteristic of professional educational research, in that their analysis focuses on student learning of math and science content. We describe classroom activities that provide opportunities for the preservice teacher participants to better observe, notice, and interpret their students’ sociocognitive activity. The course culmination project involves participants developing and teaching lessons in a high school classroom. The participants then videotape the lessons and conduct qualitative video analysis. Results include detailed examples of two selected prospective pre-service teachers demonstrating coherent and effective approaches to conceptualizing the learning and teaching of mathematical and science content along with some potential design principles for building reflective practices through qualitative video projects. © 2018 Association for Science Teacher Education

Block-Conditional Missing at Random Models for Missing Data

Two major ideas in the analysis of missing data are (a) the EM algorithm [Dempster, Laird and Rubin, J. Roy. Statist. Soc. Ser. B 39 (1977) 1--38] for maximum likelihood (ML) estimation, and (b) the formulation of models for the joint distribution of the data ${Z}$ and missing data indicators ${M}$, and associated "missing at random"; (MAR) condition under which a model for ${M}$ is unnecessary [Rubin, Biometrika 63 (1976) 581--592]. Most previous work has treated ${Z}$ and ${M}$ as single blocks, yielding selection or pattern-mixture models depending on how their joint distribution is factorized. This paper explores "block-sequential"; models that interleave subsets of the variables and their missing data indicators, and then make parameter restrictions based on assumptions in each block. These include models that are not MAR. We examine a subclass of block-sequential models we call block-conditional MAR (BCMAR) models, and an associated block-monotone reduced likelihood strategy that typically yields consistent estimates by selectively discarding some data. Alternatively, full ML estimation can often be achieved via the EM algorithm. We examine in some detail BCMAR models for the case of two multinomially distributed categorical variables, and a two block structure where the first block is categorical and the second block arises from a (possibly multivariate) exponential family distribution.Comment: Published in at http://dx.doi.org/10.1214/10-STS344 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Comparing the Profitability of Beef Production Enterprises in North Dakota

Agricultural Finance, Production Economics,

Two-Method Planned Missing Designs for Longitudinal Research

We examine longitudinal extensions of the two-method measurement design, which uses planned missingness to optimize cost-efficiency and validity of hard-to-measure constructs. These designs use a combination of two measures: a “gold standard” that is highly valid but expensive to administer, and an inexpensive (e.g., survey-based) measure that contains systematic measurement bias (e.g., response bias). Using simulated data on four measurement occasions, we compared the cost-efficiency and validity of longitudinal designs where the gold standard is measured at one or more measurement occasions. We manipulated the nature of the response bias over time (constant, increasing, fluctuating), the factorial structure of the response bias over time, and the constraints placed on the latent variable model. Our results showed that parameter bias is lowest when the gold standard is measured on at least two occasions. When a multifactorial structure was used to model response bias over time, it is necessary to have the “gold standard” measures included at every time point, in which case most of the parameters showed low bias. Almost all parameters in all conditions displayed high relative efficiency, suggesting that the 2-method design is an effective way to reduce costs and improve both power and accuracy in longitudinal research

Dynamic FOV visible light communications receiver for dense optical networks

This study explores how the field-of-view (FOV) of a visible light communications (VLCs) receiver can be manipulated to realise the best signal-to-noise ratio (SNR) while supporting device mobility and optimal access point (AP) selection. The authors propose a dynamic FOV receiver that changes its aperture according to receiver velocity, location, and device orientation. The D-FOV technique is evaluated through modelling, analysis, and experimentation in an indoor environment comprised of 15 VLC APs. The proposed approach is also realised as an algorithm that is studied through analysis and simulation. The results of the study indicate the efficacy of the approach including a 3X increase in predicted SNR over static FOV approaches based on measured received signal strength in the testbed. Additionally, the collected data reveal that D-FOV increases effectiveness in the presence of noise. Finally, the study describes the tradeoffs among the number of VLC sources, FOV, user device velocity, and SNR as a performance metric.Accepted manuscrip

The shapes of the circumstellar silicate features

Around oxygen-rich stars the spectra of most long-period variables (LPV) show an excess infrared emission which is attributed to circumstellar silicate dust grains. It is known that the spectral energy distribution of the 10 micron emissions shows variations from star to star. With the availability of many Infrared Astronomy Satellite (IRAS) Low Resolution Spectra (LRS) in the 8 to 22 micron region, the 10 micron feature can be studied to determine its uniformity (or lack thereof). The excess silicate emissions (10 micron emission), divided into three groups characterized by similar spectral shapes, are discussed

Tensile film clamps and mounting block for the rheovibron and autovibron viscoelastometer

A set of film clamps and a mounting block for use in the determination of tensile modulus and damping properties of films in a manually operated or automated Rheovibron is diagrammed. These clamps and mounting block provide uniformity of sample gripping and alignment in the instrument. Operator dependence and data variability are greatly reduced