Connecting the dots: Understanding the interrelated impacts of type,quality and children's awareness of design features and the mathematics content learning goals in digital math games and related learning outcomes

This study focused on an examination of how type, quality and children's awareness of design features in digital math games, along with an awareness of the mathematics goals of the game, were related to learning outcomes. We conducted a parallel conversion mixed methods study with 45 students in Grades 3 and 4 (ages 9–10). Students participated in clinical interviews using three digital math games. The results suggest a moderated mediation relationship in which the quality of the design features moderated the mediating impact of children's awareness of the game's design features, specifically when the child was aware of the mathematics content learning goal (MCLG) of the game. These findings show how important it is that design features are of high quality in a digital math game, and how this is intertwined with children's awareness of the features and the MCLG. When these variables intertwined in just the right way, the interactions between the children and the digital math game afforded mathematical learning growth.     

Detection of tuberculosis using MEMS

Microsystem Technologies - Tuberculosis is a contagious disease caused by the bacteria, Mycobacterium Tuberculosis. Early detection of TB is vital to increase the chances of cure. In this paper, a...     

A differential transformer-based force sensor utilizing a magnetic fluid core

Microsystem Technologies - A force sensor utilizing a transformer concept with a ferrofluid core was developed. A ferrofluid reservoir was machined out of Teflon and the open top of the reservoir...     

Poly(oxyphosphazenes): A unifying look at structure and morphology

Variations in thermotropic behavior have been investigated for many crystalline polyphosphazenes. Experimental results obtained from DSC, solid-state MAS NMR, dilatometry, mechanical property (creep and dynamic) measurements, birefringence, X-ray (wide and small-angle), and electron diffraction have been made as a function of temperature in an attempt to elucidate the structure-morphology behavior in these polymers. Initially all polyphosphazenes described in this study crystallize from dilute or moderately concentrated solutions in the monoclinic form with relatively low crystallinity (50%). When heated, these specimens expand atT(1) and adopt a chain-extended 2D mesophase morphology in order to relieve congestion. Above this first-orderT(1) temperature a chain-extended –P=N– chain backbone morphology transforms into an isotropic phase at the melting temperatureT _m. When cooled, samples transform into the mesostate. However, crystallization from the mesophase belowT(1) takes place into a 3D orthorhombic state. These two modes of ordering/disordering are in accordance with (i) a hexatic chain packing [betweenT(1) andT _m] with variously mobile side groups that also exhibits smectic features when mesogenic side groups are present and (ii) a 3D orthorhombic structure of high crystallinity belowT(1). The initial monoclinic phase is accessible only via a solution crystallization route. Solid-state MAS NMR, crystallization kinetic measurements, and optical microscopy studies obtained from oriented and unoriented polymers have been especially germane in providing a unifying picture for mesophase formation and ordering in polyoxyphosphazenes. X-ray and electron diffraction evidence is complicated by critical overlapping peaks that are found under these same conditions. They demonstrate that (a) positional disorder exists along the chain direction and (b) the side chain above, as well as below, theT(1) transition is governed by the mobility, size, and type of side group in circumstances where phase transformations occur.     

A new algorithm to compute the discrete inverse radon transform

The aim of this paper is to compute the discrete inverse Radon transform over ⁿ . The Radon transform is a function with domainS ^n–1×. It is shown that under different measure this function can be defined with domain ⁿ . In this case one can compute the discrete inverse Radon transform in the Cartesian coordinate system without interpolating from polar to Cartesian coordinates or using the backprojection operator.     

Steric stabilization of Stöber silica dispersions using organosilanes

Organosilanes of the general formula R _x Si(OR)_4–x (where R is an alkyl group and R = CH₃ or CH₂CH₃) were used to sterically stabilize hexane dispersions of submicrometre silica spheres. The dispersions were characterized according to sediment volume results. For 0.5m silica particles, the sediment density increased by more than a factor of three up to 50 to 55% of theoretical in the presence of organosilanes with 12 or more carbons in the R group. Solid-state¹³C nuclear magnetic resonance was used to characterize the powder-dispersant interaction; this technique can distinguish between carbons in the R group of the organosilane and residual organic groups in the silica. Scanning electron micrographs of filter compacts were used to further characterize the dispersions and indicated the presence of primary particles as well as small agglomerates.     

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to reduce gene/non-coding RNA features. Dorsolateral prefrontal cortex (dlpfc) RNA-seq data from 254 individuals was obtained from the CommonMind consortium. The average predictive accuracy for SCZ patients was 67% based on coding genes, and 96% based on long non-coding RNAs (lncRNAs). Machine learning is a powerful algorithm to reduce functional biomarkers in SCZ patients. The lncRNAs capture the characteristics of SCZ tissue more accurately than mRNA as the former regulate every level of gene expression, not limited to mRNA levels.     

Investigation of the Anti-Methicillin-Resistant Staphylococcus aureus Activity of (+)-Tanikolide- and (+)-Malyngolide-Based Analogues Prepared by Asymmetric Synthesis

Herein, we report antibacterial and antifungal evaluation of a series of previously prepared (+)-tanikolide analogues. One analogue, (4S,6S)-4-methyltanikolide, displayed promising anti-methicillin-resistant Staphylococcus aureus activity with a MIC of 12.5 µg/mL. Based on the antimicrobial properties of the structurally related (−)-malyngolide, two further analogues (4S,6S)-4-methylmalyngolide and (4R,6S)-4-methylmalyngolide bearing a shortened n-nonyl alkyl side chain were prepared in the present study using a ZrCl₄-catalysed deprotection/cyclisation as the key step in their asymmetric synthesis. When these were tested for activity against anti-methicillin-resistant Staphylococcus aureus, the MIC increased to 50 µg/mL.     

Recent Advances in Boron Nitride Based Hybrid Polymer Nanocomposites

Boron nitride (BN) is an eminent inorganic compound having many interesting characteristics such as improved oxidation resistance, mechanical strength, good thermal conductivity (TC), higher bandgap, high chemical stability, thermal stability, high hydrophobicity, and electrical insulation. The use of BN as a filler in polymers is a well-established strategy to tailor the properties of polymer composites. Recent studies depict an interesting urge to reap the synergistic effect of various nanofillers with BN in the form of hybrids. Hence the consolidation of the works on BN based hybrid fillers would definitely attract researchers so that these new filler systems could be transformed into useful polymer nanocomposites in future. This review article focuses on the synthesis and characterization of various boron nitride based hybrids in detail. Moreover, the review also throws light on different BN hybrid reinforced polymer nanocomposites (PNCs) and their thermal, electrical, electronic as well as biomedical applications in a detailed manner. Thus the review anticipates serving as a tool toward understanding the recent trends in the field of boron nitride hybrid based ternary polymer composites.     

Effect of dietary n−3 and n−6 polyunsaturated fatty acids on lipid-metabolizing enzymes in obese rat liver

This study was designed to examine whether n−3 and n−6 polyunsaturated fatty acids at a very low dietary level (about 0.2%) would alter liver activities in respect to fatty acid oxidation. Obese Zucker rats were used because of their low level of fatty acid oxidation, which would make increases easier to detect. Zucker rats were fed diets containing different oil mixtures (5%, w/w) with the same ratio of n−6/n−3 fatty acids supplied either as fish oil or arachidonic acid concentrate. Decreased hepatic triacylglycerol levels were observed only with the diet containing fish oil. In mitochondrial outer membranes, which support carnitine palmitoyltransferase I activity, cholesterol content was similar for all diets, while the percentage of 22∶6n−3 and 20∶4n−6 in phospholipids was enhanced about by 6 and 3% with the diets containing fish oil and arachidonic acid, respectively. With the fish oil diet, the only difference found in activities related to fatty acid oxidation was the lower sensitivity of carnitine palmitoyltransferase I to malonyl-CoA inhibition. With the diet containing arachidonic acid, peroxisomal fatty acid oxidation and carnitine palmitoyltransferase I activity were markedly depressed. Compared with the control diet, the diets enriched in fish oil and in arachidonic acid gave rise to a higher specific activity of aryl-ester hydrolase in microsomal fractions. We suggest that slight changes in composition of n−3 or n−6 polyunsaturated fatty acids in mitochondrial outer membranes may alter carnitine palmitoyltransferase I activity.