Technology-Supported Storytelling (TSST) Strategy in Virtual World for Multicultural Education

Learning culture through stories is an effective way for multicultural education, since stories are one of the most powerful and personal ways that we learn about the world. Storytelling, the process of telling stories, is a form of communication and a universal expression of culture. With the development of technology, storytelling emerges out of diverse ways. This study explores the storytelling in virtual worlds for multicultural education, and devises a Technology-Supported storytelling (TSST) strategy by examining and considering the characteristics of virtual worlds which could be incorporated into the storytelling, and then uses this strategy to teach Korean culture to students with different culture background. With this innovative TSST strategy in virtual world, this study expects to provide a guide to practice for teaching multicultural in digital era

The Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory is a second generation water Cherenkov detector designed to determine whether the currently observed solar neutrino deficit is a result of neutrino oscillations. The detector is unique in its use of D2O as a detection medium, permitting it to make a solar model-independent test of the neutrino oscillation hypothesis by comparison of the charged- and neutral-current interaction rates. In this paper the physical properties, construction, and preliminary operation of the Sudbury Neutrino Observatory are described. Data and predicted operating parameters are provided whenever possible.Comment: 58 pages, 12 figures, submitted to Nucl. Inst. Meth. Uses elsart and epsf style files. For additional information about SNO see http://www.sno.phy.queensu.ca . This version has some new reference

Measurement of the νe and total 8B solar neutrino fluxes with the Sudbury Neutrino Observatory phase-III data set

This paper details the solar neutrino analysis of the 385.17-day phase-III data set acquired by the Sudbury Neutrino Observatory (SNO). An array of 3He proportional counters was installed in the heavy-water target to measure precisely the rate of neutrino-deuteron neutral-current interactions. This technique to determine the total active 8B solar neutrino flux was largely independent of the methods employed in previous phases. The total flux of active neutrinos was measured to be 5.54-0.31+0.33(stat.)-0.34+0.36(syst.)×106 cm-2 s-1, consistent with previous measurements and standard solar models. A global analysis of solar and reactor neutrino mixing parameters yielded the best-fit values of Δm2=7.59-0.21+0.19×10 -5eV2 and θ=34.4-1.2+1.3degrees

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

The activity of Arabidopsis glycosyltranferases towards salicylic acid, 4-hydroxybenzoic acid, and other benzoates

Benzoates are a class of natural products containing compounds of industrial and strategic importance. In plants, the compounds exist in free form and as conjugates to a wide range of other metabolites such as glucose, which can be attached to the carboxyl group or to specific hydroxyl groups on the benzene ring. These glucosylation reactions have been studied for many years, but to date only one gene encoding a benzoate glucosyltransferase has been cloned. A phylogenetic analysis of sequences in the Arabidopsis genome revealed a large multigene family of putative glycosyltransferases containing a consensus sequence typically found in enzymes transferring glucose to small molecular weight compounds such as secondary metabolites. Ninety of these sequences have now been expressed as recombinant proteins in Escherichia coli, and their in vitro catalytic activities toward benzoates have been analyzed. The data show that only 14 proteins display activity toward 2-hydroxybenzoic acid, 4-hydroxybenzoic acid, and 3,4-dihydroxybenzoic acid. Of these, only two enzymes are active toward 2-hydroxybenzoic acid, suggesting they are the Arabidopsis salicylic acid glucosyltransferases. All of the enzymes forming glucose esters with the metabolites were located in Group L of the phylogenetic tree, whereas those forming O-glucosides were dispersed among five different groups. Catalytic activities were observed toward glucosylation of the 2-, 3-, or 4-hydroxyl group on the ring. To further explore their regioselectivity, the 14 enzymes were analyzed against benzoic acid, 3-hydroxybenzoic acid, 2,3-, 2,4-, 2,5-, and 2,6-dihydroxybenzoic acid. The data showed that glycosylation of specific sites could be positively or negatively influenced by the presence of additional hydroxyl groups on the ring. This study provides new tools for biotransformation reactions in vitro and a basis for engineering benzoate metabolism in plants

Comparison of Documents Classification Techniques to Classify Medical Reports

This paper addresses a real world problem: the classification of text documents in the medical domain. There are a number of approaches to classifying text documents. Here, we use a partially supervised classification approach and argue that it is effective and computationally efficient for real-world problems. The approach uses a two-step strategy to cut down on the effort required to label each document for classification. Only a small set of positive documents are labeled initially, with others being labeled automatically as a result of the first step. The second step builds the actual text classifier. There are a number of methods that have been proposed for each step. A comprehensive evaluation of various combinations of methods is conducted to compare their performances using real world medical documents. The results show that using EM based methods to build the classifier yields better results than SVM. We also experimentally show that careful selection of a subset of features to represent the documents can improve the performance of the classifiers