Prey selection and food habits of Burrowing Owls in Colorado

Food habits of Burrowing Owls ( Speotyto cunicularia ) were studied during the breeding seasons of 1990 and 1991 in central Colorado. Concurrent insect availability studies were conducted to determine selection for specific insect families. Analysis of 1445 castings indicated use of only one insect family, the carrion beetles (Silphidae), at a rate greater than expected based on availability in one year. Castings and prey remains showed different dietary components. Prey remains showed greater use of small mammals, moths, amphibians, and passerines, and castings indicated greater use of mice and beetles. Methodology in raptor food habits studies may therefore bias results.     

Temperature-related behavior of some migrant birds in the desert

Behavior of migrant birds in relation to temperature was studied and compared to that of resident species in the northern Mojave Desert. Migrants reduced foraging intensity above 30 C, but resident species showed no striking decrease in intensity of foraging at temperatures up to 35 C. Migrant species shifted activities to shaded microhabitats at temperatures between 20 and 30 C; the resident Verdin showed a similar shift at 35 C. Most migrants decreased the amount of time spent foraging at temperatures above 30; Verdins showed a similar but stronger response to temperatures about 30 C. Significant reductions in the use of hovering and hawking maneuvers were found among migrants at temperatures above 30 C. Migrants showed similar types of behavioral adjustments to temperatures as did resident desert species, but they responded earlier in the daily temperature cycle. Desert birds appear to correlate their daily activity strongly with temperature, but nondesert species may respond either to temperature or time of day.     

For whom the bell tolls? DING proteins in health and disease

DING proteins, identified mainly by their eponymous N-terminal sequences, are ubiquitous in living organisms. Amongst bacteria, they are common in pseudomonads, and have been characterised with respect to genetics and structure. They form part of a wider family of phosphate-binding proteins, with emerging roles in phosphate acquisition and pathogenicity. Many DING proteins have been isolated in eukaryotes, in which they have been associated with very diverse biological activities, often in the context of possible signalling roles. Disease states in which DING proteins have been implicated include rheumatoid arthritis, lithiasis, atherosclerosis, some tumours and tumour-associated cachexia, and bacterial and viral adherence. Complete genetic and structural characterisation of eukaryotic DING genes and proteins is still lacking, though the phosphate-binding site seems to be conserved. Whether as bacterial proteins related to bacterial pathogenicity, or as eukaryotic components of biochemical signalling systems, DING proteins require further study. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Identification of asymmetric prediction intervals through causal forces

When causal forces are specified, the expected direction of the trend can be compared with the trend based on extrapolation. Series in which the expected trend conflicts with the extrapolated trend are called contrary series. We hypothesized that contrary series would have asymmetric forecast errors, with larger errors in the direction of the expected trend. Using annual series that contained minimal information about causality, we examined 671 contrary forecasts. As expected, most (81%) of the errors were in the direction of the causal forces. Also as expected, the asymmetries were more likely for longer forecast horizons; for six‐year‐ahead forecasts, 89% of the forecasts were in the expected direction. The asymmetries were often substantial. Contrary series should be flagged and treated separately when prediction intervals are estimated, perhaps by shifting the interval in the direction of the causal forces. Copyright © 2001 John Wiley & Sons, Ltd.     

Gordon Pask's Conversation Theory: A Domain Independent Constructivist Model of Human Knowing

Although it is conceded (as argued by many)that distinct knowledge domains do presentparticular problems of coming to know, in thispaper it is argued that it is possible (anduseful) to construct a domain independent modelof the processes of coming to know, one inwhich observers share understandings and do soin agreed ways. The model in question is partof the conversation theory (CT) of Gordon Pask. CT, as a theory of theory construction andcommunication, has particular relevance forfoundational issues in science and scienceeducation. CT explicitly propounds a ``radicalconstructivist' (RC) epistemology. A briefaccount is given of the main tenets of RC andCT's place in that tradition and the traditionsof cybernetics. The paper presents a briefnon-technical account of the main concepts ofCT including elaborations by Laurillard andHarri-Augstein and Thomas. As part of CT, Pask also elaborated a methodology – knowledgeand task analysis – for analysing the structureof different knowledge domains; thismethodology is sketched in outline.     

TRPV3 is a calcium-permeable temperature-sensitive cation channel

Transient receptor potential (TRP) proteins are cation-selective channels that function in processes as diverse as sensation and vasoregulation. Mammalian TRP channels that are gated by heat and capsaicin (>43 degrees C; TRPV1 (ref. 1)), noxious heat (>52 degrees C; TRPV2 (ref. 2)), and cooling (< 22 degrees C; TRPM8 (refs 3, 4)) have been cloned; however, little is known about the molecular determinants of temperature sensing in the range between approximately 22 degrees C and 40 degrees C. Here we have identified a member of the vanilloid channel family, human TRPV3 (hTRPV3) that is expressed in skin, tongue, dorsal root ganglion, trigeminal ganglion, spinal cord and brain. Increasing temperature from 22 degrees C to 40 degrees C in mammalian cells transfected with hTRPV3 elevated intracellular calcium by activating a nonselective cationic conductance. As in published recordings from sensory neurons, the current was steeply dependent on temperature, sensitized with repeated heating, and displayed a marked hysteresis on heating and cooling. On the basis of these properties, we propose that hTRPV3 is thermosensitive in the physiological range of temperatures between TRPM8 and TRPV1.     

Correspondence on the selection of error measures for comparisons among forecasting methods

Clements and Hendry (1993) proposed the Generalized Forecast Error Second Moment (GFESM) as an improvement to the Mean Square Error in comparing forecasting performance across data series. They based their conclusion on the fact that rankings based on GFESM remain unaltered if the series are linearly transformed. In this paper, we argue that this evaluation ignores other important criteria. Also, their conclusions were illustrated by a simulation study whose relationship to real data was not obvious. Thirdly, prior empirical studies show that the mean square error is an inappropriate measure to serve as a basis for comparison. This undermines the claims made for the GFESM.     

Training Load Monitoring Algorithms on Highly Sub-Metered Home Electricity Consumption Data

The growing interest in energy-efficient buildings is driving changes in investment, design, and occupant behavior. To better focus cost and resource conservation efforts, electricity consumption feedback can be used to provide motivation, guidance, and verification. Disaggregating by end-use helps both consumers and producers to identify targets for conservation. While hardware-based sub-metering is costly and labor-intensive, non-intrusive load monitoring (NILM) is capable of gathering detailed energy-use data with minimal equipment cost and installation time. However, variations in measurements between metering devices complicate the process of compiling the necessary appliance profiles. Future work involves the devel-opment of NILM algorithms using sensor fusion and detailed appliance-level data gathered from a highly-sensed house currently being constructed near Pittsburgh, Pennsylvania.