Fixing human factor IX (fIX): correction of a cryptic RNA splice enables the production of biologically active fIX in the mammary gland of transgenic mice.

Transgenic mice and sheep secrete only low levels of human factor IX in their milk because of an aberrant splicing of the transgene RNA in the mammary gland. Removal of the cryptic 3' splice site prevents this splicing and leads to the production of relatively high levels of factor IX. The purified protein is fully active showing that the mammary gland is capable of the efficient post-translational modification of this protein and that transgenic animals are a suitable means of its production.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Statistical analysis of the goodness of classical factor analysis regression (CFAR) /

Cover title.

Human factors analysis of automotive adaptive equipment for disabled drivers. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

An investigation of the goodness of fit of the maximum likelihood estimation procedure in factor analysis /

Thesis--Illinois.

The structure of labor market segmentation of occupations : some evidence from factor analysis /

Includes bibliographies (p. 31).

The human factor in innovation and productivity [microform] : hearings (including the record of a seminar sponsored by the American Association for the Advancement of Science on July 28, 1981) before the Subcommittee on Science, Research, and Technology of the Committee on Science and Technology, U.S. House of Representatives, Ninety-seventh Congress, first session, September 9, 10, 11, 15, 16, 17, 1981.

"No. 51."

Measurement of the human factor in industry, To be presented at the national conference of the Western Efficiency Society, May 22-25, 1917.

Mode of access: Internet.

An application of factor analysis to water quality data /

Cover title.

The human factor in mining reclamation /

Mode of access: Internet.

Gray's model of personality and aggregate level factor analysis

Previous research shows that correlations tend to increase in magnitude when individuals are aggregated across groups. This suggests that uncorrelated constellations of personality variables (such as the primary scales of Extraversion and Neuroticism) may display much higher correlations in aggregate factor analysis. We hypothesize and report that individual level factor analysis can be explained in terms of Giant Three (or Big Five) descriptions of personality, whereas aggregate level factor analysis can be explained in terms of Gray's physiological based model. Although alternative interpretations exist, aggregate level factor analysis may correctly identify the basis of an individual's personality as a result of better reliability of measures due to aggregation. We discuss the implications of this form of analysis in terms of construct validity, personality theory, and its applicability in general. Copyright (C) 2003 John Wiley Sons, Ltd.