How to reduce the number of rating scale items without predictability loss?

Rating scales are used to elicit data about qualitative entities (e.g., research collaboration). This study presents an innovative method for reducing the number of rating scale items without the predictability loss. The "area under the receiver operator curve method" (AUC ROC) is used. The presented method has reduced the number of rating scale items (variables) to 28.57\% (from 21 to 6) making over 70\% of collected data unnecessary. Results have been verified by two methods of analysis: Graded Response Model (GRM) and Confirmatory Factor Analysis (CFA). GRM revealed that the new method differentiates observations of high and middle scores. CFA proved that the reliability of the rating scale has not deteriorated by the scale item reduction. Both statistical analysis evidenced usefulness of the AUC ROC reduction method.Comment: 14 pages, 5 figure

The mTOR inhibitor rapamycin down-regulates the expression of the ubiquitin ligase subunit Skp2 in breast cancer cells

INTRODUCTION: Loss of the cyclin-dependent kinase inhibitor p27 is associated with poor prognosis in breast cancer. The decrease in p27 levels is mainly the result of enhanced proteasome-dependent degradation mediated by its specific ubiquitin ligase subunit S phase kinase protein 2 (Skp2). The mammalian target of rapamycin (mTOR) is a downstream mediator in the phosphoinositol 3' kinase (PI3K)/Akt pathway that down-regulates p27 levels in breast cancer. Rapamycin was found to stabilize p27 levels in breast cancer, but whether this effect is mediated through changes in Skp2 expression is unknown. METHODS: The expression of Skp2 mRNA and protein levels were examined in rapamycin-treated breast cancer cell lines. The effect of rapamycin on the degradation rate of Skp2 expression was examined in cycloheximide-treated cells and in relationship to the anaphase promoting complex/Cdh1 (APC\C) inhibitor Emi1. RESULTS: Rapamycin significantly decreased Skp2 mRNA and protein levels in a dose and time-dependent fashion, depending on the sensitivity of the cell line to rapamycin. The decrease in Skp2 levels in the different cell lines was followed by cell growth arrest at G1. In addition, rapamycin enhanced the degradation rate of Skp2 and down-regulated the expression of the APC\C inhibitor Emi1. CONCLUSION: These results suggest that Skp2, an important oncogene in the development and progression of breast cancer, may be a novel target for rapamycin treatment

Generating placated random shapes for an area estimation study

Random but visually nice shapes are often needed for cognitive experiments and processes. This study describes a heuristic for generating random but nice shapes. We call them placated shapes. These shapes are produced by applying the Gaussian blur to randomly generated polygons. Subsequently, the threshold is set to transform pixels to black and white from different shades of gray. This transformation produces placated shapes for easier estimation of areas. Randomly generated placated shapes are used for testing the accuracy of cognitive processes by pairwise comparisons. They can also be used in many other areas such as computer games or software testing. Such shapes could also be used for camouflaging heavy army equipment

Internet Contamination as a Global Harm and a Social Problem

Abstract. This position paper demonstrates that the global and cumulative cost of dealing with spam i

Improving the predictability of ICU illness severity scales

Abstract-This study demonstrates how to improve the predictability of one of the commonly used ICUs severity of illness scales, namely APACHE II, by using the consistency-driven pairwise comparisons (CDPC) method. From a conceptual view, there is little doubt that all items have exactly equal importance or contribution to predicting mortality risk of patients admitted to ICUs. Computing new weights for all individual items is a considerable step forward since it is based on reasonable to assume that not all individual items have equal contribution in predicting mortality risk. The received predictability improvement is 1.6% (from 70.9% to 72.5%) and the standard error decreased from 0.045 to 0.046. This must be taken as an indication of the right way to go