Role of Perceived Importance in Intergroup Contact.

Furthering G. W. Allport's (1954) contentions for optimal contact, the authors introduce a new construct: the perceived importance of contact. They propose that perceived importance is the best proximal predictor of contact's reduction of prejudice. If individuals have opportunities for contact at work or in the neighborhood, their chances to have intergroup acquaintances and friends increase. Intergroup contact among acquaintances and friends can be perceived as more or less important, which in turn determines intergroup evaluations. A 1st study shows that the new measure of perceived importance is indeed distinct from established quantity and quality indicators. The results are cross-validated in a 2nd study that also sheds light on the meaning of importance. In 3rd and 4th studies, structural equation analyses and a meta-analysis support the hypotheses. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Human stem cell assays in immune-deficient mice

Much of our understanding of the organization of the cells that comprise the hematopoietic system and the cellular and molecular mechanisms that regulate their development is derived from mouse models. However, knowledge of the human hematopoietic system and identification of human stem cells have, until recently, been hampered by the absence of in vivo assays that measure their repopulation capacity. The development of methods to transplant normal and leukemic human hematopoietic cells into immune-deficient SCID mice provides the foundation for human stem cell assays. This review will focus on recent evidence that normal and leukemic human stem cells can be assayed in these systems.     

Development of a recurrent Sigma-Pi neural network rainfall forecasting system in Hong Kong

At the moment, weather forecasting is still an art — the experience and intuition of forecasters play a significant role in determining the quality of forecasting. This paper describes the development of a new approach to rainfall forecasting using neural networks. It deals with the extraction of information from radar images and an evaluation of past rain gauge records to provide shortterm rainfall forecasting. All of the meteorological data were provided by the Royal Observatory of Hong Kong (ROHK). Preprocessing procedures were essential for this neural network rainfall forecasting. The forecast of the rainfall was performed every half an hour so that a storm warning signal can be delivered to the public in advance. The network architecture is based on a recurrent Sigma-Pi network. The results are very promising, and this neural-based rainfall forecasting system is capable of providing a rain storm warning signal to the Hong Kong public one hour ahead.     

CMV colitis masquerading as colon cancer--an unusual presentation of acquired immunodeficiency syndrome

To determine whether there is any correlation between sudden decrease in barometric pressure and onset of labor, a non-experimental, retrospective study at a 948-bed tertiary care hospital was done. Pregnant patients of 36 weeks gestation or more who presented with spontaneous onset of labor during the 48 hours surrounding the 12 occurrences of significant drop in barometric pressure in 1992 were included in the study. Significantly more occurrences of onset of labor were identified in the 24 hours after a drop in barometric pressure than were identified in the 24 hours prior to the drop in barometric pressure (P < 0.05). Therefore, the overall number of labor onsets increased in the 24 hours following a significant drop in barometric pressure.     

The validity of the Gammarus:Asellus ratio as an index of organic pollution: abiotic and biotic influences.

In freshwaters. Gammarus spp. are more sensitive to organic pollution than Asellus spp. and the relative abundance of the two taxa has been proposed as a pollution index. We tested the validity of this by examining the relationship between the Gammarus: Asellus (G : A) ratio and (1) a suite of physico-chemical variables. (2) established biotic (average score per taxon, ASPT) and richness (species richness (S) and Ephemeroptera, Plecoptera and Trichoptera families richness (EPT family richness)) indices generated from the macroinvertebrate community. In addition, we investigated a suspected biotic interaction, predation, between Gammarus and Asellus. Both univariate and multivariate analyses showed that the G: A ratio was sometimes responsive to changes in parameters linked to organic pollution, such as BOD5 and nitrate levels. However, the G : A ratio also appeared responsive to variables not directly linked to organic pollution, such as conductivity and distance from source. There were significant positive correlations among the G : A ratio and the ASPT, S and EPT, indicating that changes in the relative abundances of Gammarus and Asellus were reflected in changes in the pollution sensitivity and richness of the wider macroinvertebrate community. A laboratory experiment revealed significant predation of Asellus aquaticus juveniles by Gammarus duebeni celticus adults, but no reciprocal predation. We propose that the G: A ratio may be useful as a crude measure of organic pollution that could supplement more complex indices in a multimetric approach to pollution monitoring or be used for monitoring individual sites, where a simple technique is required for monitoring purposes over a period of time. Also, we urge recognition of the possible role of biotic interactions among taxa used in the generation of pollution indices.     

Intramolecular crosslinking of poly(vinyl alcohol)

Poly(vinyl alcohol) is crosslinked in dilute solution (c=0.1 wt%) with glutaraldehyde. The reaction product is characterized by viscometry and gel permeation chromatography (g.p.c.). The intrinsic viscosity decreases with increasing degree of crosslinking and does not depend on temperature. G.p.c. reveals that the reaction product is not homogeneous, but consists of a mixture of particles with different sizes, possibly both intra- and intermolecularly crosslinked molecules. The intramolecularly crosslinked molecules are smaller in size than the initial polymer molecules and their size depends on the degree of crosslinking. They possess a narrow particle size distribution even if the initial polymer sample had a broad molecular weight distribution.     

Coal liquefaction using a hydrogenated creosote oil solvent: H-atom transfer from hydrogen donor components in the solvent

The presence of hydroaromatic, hydrogen donor components in a coal-derived solvent is one of the more important factors in the successful operation of a non-catalytic coal liquefaction process. Various hydrogen donor species present in a hydrogenated creosote oil have been identified. Their rate of disappearance under conditions that are consistent with a short residence time coal liquefaction process has been used to rank the reactivities of the various hydrogen donors. 1,2,3,10b-Tetrahydrofluoranthene was found to be an exceptional donor while 4,5-dihydropyrene, the hexahydropyrenes and 9,10-dihydrophenanthrene were found to be quite active. Sym.-octahydrophenanthrene and 2a,3,4,5-tetrahydroacenaphthene exhibited moderate activity. Tetralin and the four methyltetralin isomers were found to be unreactive under the coal liquefaction conditions employed.     

Integration of prior knowledge of measurement noise in kernel density classification

Samples can be measured with different precisions and reliabilities in different experiments, or even within the same experiment. These varying levels of measurement noise may deteriorate the performance of a pattern recognition system, if not treated with care. Here we seek to investigate the benefit of incorporating prior knowledge about measurement noise into system construction. We propose a kernel density classifier which integrates such prior knowledge. Instead of using an identical kernel for each sample, we transform the prior knowledge into a distinct kernel for each sample. The integration procedure is straightforward and easy to interpret. In addition, we show how to estimate the diverse measurement noise levels in a real world dataset. Compared to the basic methods, the new kernel density classifier can give a significantly better classification performance. As expected, this improvement is more obvious for small sample size datasets and large number of features.     

Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification E-Algorithm

Power distribution systems have been significantly affected by many outage-causing events. Good fault cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real-world data sets often degrades the fault cause identification performance. In this paper, the E-algorithm, which is extended from the fuzzy classification algorithm by Ishibuchi to alleviate the effect of imbalanced data constitution, is applied to Duke Energy outage data for distribution fault cause identification. Three major outage causes (tree, animal, and lightning) are used as prototypes. The performance of E-algorithm on real-world imbalanced data is compared with artificial neural network. The results show that the E-algorithm can greatly improve the performance when the data are imbalanced