Textile Fingerprinting for Dismount Analysis in the Visible, Near, and Shortwave Infrared Domain

The ability to accurately and quickly locate an individual, or a dismount, is useful in a variety of situations and environments. A dismount\u27s characteristics such as their gender, height, weight, build, and ethnicity could be used as discriminating factors. Hyperspectral imaging (HSI) is widely used in efforts to identify materials based on their spectral signatures. More specifically, HSI has been used for skin and clothing classification and detection. The ability to detect textiles (clothing) provides a discriminating factor that can aid in a more comprehensive detection of dismounts. This thesis demonstrates the application of several feature selection methods (i.e., support vector machines with recursive feature reduction, fast correlation based filter) in highly dimensional data collected from a spectroradiometer. The classification of the data is accomplished with the selected features and artificial neural networks. A model for uniquely identifying (fingerprinting) textiles are designed, where color and composition are determined in order to fingerprint a specific textile. An artificial neural network is created based on the knowledge of the textile\u27s color and composition, providing a uniquely identifying fingerprinting of a textile. Results show 100% accuracy for color and composition classification, and 98% accuracy for the overall textile fingerprinting process

Evaluating the effects of increasing physical activity to optimize rehabilitation outcomes in hospitalized older adults (MOVE Trial): Study protocol for a randomized controlled trial

Background: Older adults who have received inpatient rehabilitation often have significant mobility disability at discharge. Physical activity levels in rehabilitation are also low. It is hypothesized that providing increased physical activity to older people receiving hospital-based rehabilitation will lead to better mobility outcomes at discharge. Methods/Design: A single blind, parallel-group, multisite randomized controlled trial with blinded assessment of outcome and intention-to-treat analysis. The cost effectiveness of the intervention will also be examined. Older people (age >60 years) undergoing inpatient rehabilitation to improve mobility will be recruited from geriatric rehabilitation units at two Australian hospitals. A computer-generated blocked stratified randomization sequence will be used to assign 198 participants in a 1:1 ratio to either an 'enhanced physical activity' (intervention) group or a 'usual care plus' (control) group for the duration of their inpatient stay. Participants will receive usual care and either spend time each week performing additional physical activities such as standing or walking (intervention group) or performing an equal amount of social activities that have minimal impact on mobility such as card and board games (control group). Self-selected gait speed will be measured using a 6-meter walk test at discharge (primary outcome) and 6 months follow-up (secondary outcome). The study is powered to detect a 0.1 m/sec increase in self-selected gait speed in the intervention group at discharge. Additional measures of mobility (Timed Up and Go, De Morton Mobility Index), function (Functional Independence Measure) and quality of life will be obtained as secondary outcomes at discharge and tertiary outcomes at 6 months follow-up. The trial commenced recruitment on 28 January 2014. Discussion: This study will evaluate the efficacy and cost effectiveness of increasing physical activity in older people during inpatient rehabilitation. These results will assist in the development of evidenced-based rehabilitation programs for this population. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12613000884707(Date of registration 08 August 2013); ClinicalTrials.gov Identifier NCT01910740(Date of registration 22 July 2013)

Regulated Fluctuations in Nanog Expression Mediate Cell Fate Decisions in Embryonic Stem Cells

The notion that the differentiated state of a cell population is determined simply by expression of specific marker genes is changing. In this work, the authors reveal that a pluripotent cell population comprises cells with temporal fluctuations in the expression of Nanog