Correction for ambiguous solutions in factor analysis using a penalized least squares objective

Factor analysis is a powerful tool used for the analysis of dynamic studies. One of the major drawbacks of factor analysis of dynamic structures (FADS) is that the solution is not mathematically unique when only nonnegativity constraints are used to determine factors and factor coefficients. In this paper, a method to correct for ambiguous FADS solutions has been developed. A nonambiguous solution (to within certain scaling factors) is obtained by constructing and minimizing a new objective function. The most common objective function consists of a least squares term that when minimized with nonnegativity constraints, forces agreement between the applied factor model and the measured data. In our method, this objective function is modified by adding a term that penalizes multiple components in the images of the factor coefficients. Due to nonuniqueness effects, these factor coefficients consist of more than one physiological component. The technique was tested on computer simulations, an experimental canine cardiac study using 99mTc-teboroxime, and a patient planar 99mTc-MAG3 renal study. The results show that the technique works well in comparison to the truth in computer simulations and to region of interest (ROI) measurements in the experimental studies.     

Factor graph methods for three-dimensional shape reconstruction as applied to LIDAR imaging

Two methods based on factor graphs for reconstructing the three-dimensional (3D) shape of an object from a series of two-dimensional images are presented. First, a factor graph model is developed for image segmentation to obtain silhouettes from raw images; the shape-from-silhouette technique is then applied to yield the 3D reconstruction of the object. The second method presented is a direct 3D reconstruction of the object using a factor graph model for the voxels of the reconstruction. While both methods should be applicable to a variety of input data types, they will be developed and demonstrated for a particular application involving the LIDAR imaging of a submerged target. Results from simulations and from real LIDAR data are shown that detail the performance of the methods.     

Optical Transceiver Chips Based on Co-Integration of Capacitively Coupled Proximity Interconnects and VCSELs

Combining the strengths of both proximity communication and optical communication, a new hybrid input-output (I/O) platform delivers on-chip bandwidth off-chip and over distance. We demonstrate, for the first time, a four-channel hybrid I/O interface by integrating proximity communication and vertical-cavity surface-emitting-laser-based parallel optical interconnects on the same commercial 90-nm complementary metal-oxide-semiconductor platform. The optical I/O can operate at 5 Gb/s per channel, and the complete hybrid I/O interface achieved 2.5 Gb/s per channel. We characterize the I/O link performance for various data rates and chip separations, and show 10-mum chip separation tolerance for proximity communication     

Detectability of dynamic photon emission in static Si CCD for signal path determination in integrated circuits

The detection of dynamic photon emission by static cameras is an inexpensive approach to track circuit signal paths, but successful application depends on the signal pattern and frequency the devices are operating at. For improvement of predictability, a model has been developed, built upon the composition of operating modes and targeted to calculate the static emission signal. On single transistor test structures, the model is verified and an operating frequency correlates to the detection limit. Ring oscillator results confirm that only a fraction of the inverter switching time is accompanied by photon emission. At a real circuit it is demonstrated that operating condition limits for signal path detection in static photon emission detectors can be defined.     

Low-frequency pulsed electromagnetic field exposure can alter neuroprocessing in humans

Extremely low-frequency magnetic fields (from DC to 300 Hz) have been shown to affect pain sensitivity in snails, rodents and humans. Here, a functional magnetic resonance imaging study demonstrates how the neuromodulation effect of these magnetic fields influences the processing of acute thermal pain in normal volunteers. Significant interactions were found between pre- and post-exposure activation between the sham and exposed groups for the ipsilateral (right) insula, anterior cingulate and bilateral hippocampus/caudate areas. These results show, for the first time, that the neuromodulation induced by exposure to low-intensity low-frequency magnetic fields can be observed in humans using functional brain imaging and that the detection mechanism for these effects may be different from those used by animals for orientation and navigation. Magnetoreception may be more common than presently thought.