Design of a performance-oriented workplace e-learning system using ontology

E-learning is emerging as a popular learning approach utilized by many organizations. Despite the ever increasing practices of e-learning in the workplace, most e-learning applications fail to meet learners’ needs or serve organization’s quests for success. Significant gaps exist between organizational interests and individual needs when they come to e-learning, which make e-learning applications less goal-effective. To solve this problem, a performance-oriented approach is presented in this study. Key performance indicators (KPIs) are set up to clarify organizational training needs, and help learners establish rational learning objectives. In addition, ontology is used for constructing formal and machine-understandable conceptualization of the performance-oriented learning environment. Using this approach, a KPI-oriented learning ontology and prototype system have been developed and evaluated to demonstrate the effectiveness of the approach.     

A comparison of Landsat TM and MODIS vegetation indices for estimating forage phenology in desert bighorn sheep (Ovis canadensis nelsoni) habitat in the Sonoran Desert,USA

Sonoran Desert bighorn sheep (Ovis canadensis mexicana) occupy rugged upland areas that experience irregular periods of vegetation growth associated with precipitation events. These episodic and often spatially limited events provide important forage and preformed water resources that may be important drivers of animal movement and habitat use. Habitat-use models that incorporate forage phenology would broaden our understanding of desert bighorn ecology and have considerable potential to inform conservation efforts for the species. Field-based methods are of limited utility to characterize vegetation phenology across large areas. Vegetation indices (VI) derived from satellite imagery are a viable alternative, but may be confounded by areas of high relief and shadow effects that can degrade VI values. The varying spatial and temporal resolutions of readily available satellite sensors, such as the Landsat thematic mapper (TM) and moderate-resolution imaging spectrometer (MODIS), present additional challenges. In this study, we sought to minimize degrading effects of terrain on TM- and MODIS-based estimates of vegetation phenology. We compared effects of high topographic relief on time series MODIS- and TM-based VI such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) using VI departures from average (DA) in shaded and unshaded areas. Sun elevation angle negatively impacted TM-derived NDVI and EVI values in areas of steep terrain. In contrast, MODIS-derived NDVI values were insensitive to sun elevation and terrain effects, whereas MODIS-derived EVI was degraded in areas of steep terrain. Time series MODIS NDVI and EVI DA values differed significantly during months of low sun elevation angle. Average MODIS EVI departure values were ≥20% lower than NDVI under these conditions, confounding time series estimates of plant phenology. Our best results were obtained from MODIS 16-day composited NDVI. These remote-sensing-based VI estimates of seasonal plant phenology and productivity can be used to inform models of habitat use and movements of desert bighorn over large areas.     

A computational model for tracking subsurface tissue deformation during stereotactic neurosurgery

Recent advances in the field of stereotactic neurosurgery have made it possible to coregister preoperative computed tomography (CT) and magnetic resonance (MR) images with instrument locations in the operating field. However, accounting for intraoperative movement of brain tissue remains a challenging problem. While intraoperative CT and MR scanners record concurrent tissue motion, there is motivation to develop methodologies which would be significantly lower in cost and more widely available. The approach we present is a computational model of brain tissue deformation that could be used in conjunction with a limited amount of concurrently obtained operative data to estimate subsurface tissue motion. Specifically, we report on the initial development of a finite element model of brain tissue adapted from consolidation theory. Validations of the computational mathematics in two and three dimensions are shown with errors of 1%-2% for the discretizations used. Experience with the computational strategy for estimating surgically induced brain tissue motion in vivo is also presented. While the predicted tissue displacements differ from measured values by about 15%, they suggest that exploiting a physics-based computational framework for updating preoperative imaging databases during the course of surgery has considerable merit. However, additional model and computational developments are needed before this approach can become a clinical reality.     

Three distinct D-amino acid substitutions confer potent antiangiogenic activity on an inactive peptide derived from a thrombospondin-1 type 1 repeat

Mal II, a 19-residue peptide derived from the second type 1 properdin-like repeat of the antiangiogenic protein thrombospondin-1 (TSP-1), was inactive in angiogenesis assays. Yet the substitution of any one of three L-amino acids by their D-enantiomers conferred on this peptide a potent antiangiogenic activity approaching that of the intact 450-kDa TSP-1. Substituted peptides inhibited the migration of capillary endothelial cells with an ED50 of 8.5 nM for the D-Ile-15 substitution, 10 nM for the D-Ser-4 substitution, and 0.75 nM for the D-Ser-5 substitution. A peptide with D-Ile at position 15 could be shortened to its last seven amino acids with little loss in activity. Like whole TSP-1, the Mal II D-Ile derivative inhibited a broad range of angiogenic inducers, was selective for endothelial cells, and required CD36 receptor binding for activity. A variety of end modifications further improved peptide potency. An ethylamide-capped heptapeptide was also active systemically in that when injected i.p. it rendered mice unable to mount a corneal angiogenic response, suggesting the potential usefulness of such peptides as antiangiogenic therapeutics.     

What's in a smile?

In positive social contexts, both adults and older infants show more Duchenne smiling (which involves high cheek raising) than non-Duchenne smiling (which does not). This study compared Duchenne and non-Duchenne smiles in early infancy for clues to their emotional significance. Infants (N?=?13) from 1 to 6 months of age were videotaped weekly for 5 min in 208 face-to-face interactions with their mothers. Levels of Duchenne and non-Duchenne smiling were correlated within interactive sessions, and the 2 smiles had similar developmental trajectories. Duchenne smiles were typically preceded by non-Duchenne smiles. The results suggest these frequently contrasted types of smiles occur in similar situations and are often different temporal phases of a continuous emotional process. In contrast to adults, infant Duchenne smiles had longer durations than non-Duchenne smiles, suggesting infant smiling does not fit adult models of emotional functioning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)