Solar pond ground heat loss to a moving water table

An analytical solution is presented that calculates the heat loss from the bottom of a solar pond (or any heated object) to a soil that contains a moving water table. The water table is treated as a fluid slab moving as a slug flow in one dimension. Edge effects and horizontal heat conduction are ignored. Both steady-state and time-dependent solutions are presented. Results are presented in terms of an effectiveness ratio—the actual heat flux divided by the steady-state heat flux resulting from a constant temperature heat sink at the depth of the water table. The only water-table parameter that strongly affects the effectiveness is the fluid capacity rate. Thus, for any potential solar pond site, a measurement of the mass flow rate of the water table combined with knowledge of the soil thermal properties will allow a good estimation of the ground heat loss expected over the lifetime of the pond.     

Evacuated-tube directional-radiating cooling system

A new type of radiative cooling system is described. The radiator makes use of nonimaging optics and evacuated-tube technology to radiate significant amounts of heat to the 3 K environment of outer space. The nonimaging optics are used to direct the radiation overhead, through the most transparent part of the 8–13 μm atmospheric window. The required optical concentration is small, and relatively simple mirror geometries are possible. The evacuated-tube technology is used to attain storage temperatures at or below the freezing point, even when dewpoint temperatures are well above the freezing point.     

Estimation of sampling error variance in the meta-analysis of correlations: Use of average correlation in the homogeneous case.

The estimate of the population correlation used in the formula for sampling error variance of a correlation is typically the observed correlation, but in meta-analysis the average of the observed correlations can be used. For the case in which there is no variation in the study population correlations or sample sizes and the number of studies is very large, the authors found that use of the average correlation estimator is more accurate than use of the traditional, individual correlation estimator, except in those rare cases in which the uncorrected population correlation is greater than .60. For typical sample sizes, when the uncorrected population correlation is between -.40 and .40, there is virtually no error in the meta-analysis credibility interval based on the average correlation estimator. On the other hand, the amount of the error in the individual correlation estimator is qualitatively important if the sample is 25 or less and the population correlation is less than .40. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Genetic determinants of sensitivity to ethanol in inbred mice.

Mice from 15 inbred strains (n?=?27–40 per strain) differed in sensitivity to ethanol-induced effects on open-field activity, hypothermia, rotarod ataxia, and anesthesia. Sensitivities to the different behavioral responses were generally uncorrelated. This suggests that the genetic determinants of behavioral sensitivity to one domain of ethanol effects are unrelated to those determining other responses. On the other hand, some variables were genetically related. For example, those strains sensitive to the loss of righting reflex induced by higher doses of ethanol showed reduced activity in the open field at lower doses and were more sensitive to ethanol-induced decreases in rearing. More generally, the pattern of results suggests that genetically influenced sensitivity to ethanol is not a monolithic phenomenon. Rather, it is specific to the particular response variable studied. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Parental caregiving and child externalizing behavior in nonclinical samples: A meta-analysis.

A meta-analysis of 47 studies was used to shed light on inconsistencies in the concurrent association between parental caregiving and child externalizing behavior. Parent–child associations were strongest when the measure of caregiving relied on observations or interviews, as opposed to questionnaires, and when the measure tapped combinations of parent behaviors (patterns), as opposed to single behaviors. Stronger parent–child associations were also found for older than for younger children, and for mothers than for fathers. Finally, externalizing was more strongly linked to parental caregiving for boys than for girls, especially among preadolescents and their mothers. The meta-analysis helps account for inconsistencies in findings across previous studies and supports theories emphasizing reciprocity of parent and child behavior. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Response of depressed adolescents to cognitive-behavioral treatment: Do differences in initial severity clarify the comparison of treatments?

Evaluated the impact of pretreatment depression severity and functional impairment on the response of 2 samples of older depressed adolescents (115 Ss total divided into low-severity groups and high-severity groups) to 2 group cognitive-behavioral treatments. Differences between the 2 active treatments and between active treatment and a waiting-list control condition were expected to be greater in the more severely depressed-impaired group. Improvement for the 2 active treatments in comparison to the control condition was greater in the more severely depressed group in one of the samples but not the other. The prediction that the relative effectiveness of the 2 treatments would be accentuated in the more severely depressed adolescents received no support in either sample. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analysis of clinical trial data: The problem of outcome overlap.

The immediate goal of any clinical trial is to determine to which of a specified set of treatments future patients are to be assigned, particularly when analyzing data from clinical trials. When the outcome distributions of Experimental (E) and Control (C) treatments overlap, differences between treatment group means are not conclusive and may not be very informative, so a display of the overlapped frequency distributions and a summary measure of the probability of a random patient in E doing better than a random patient in C are needed. When outcome distributions overlap, the question of statistical model becomes crucial even when there are very significant differences between group means and very large effect sizes. Determining what patient variables interact with treatments is the route to optimal assignment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)