MR of the spine with a fast T1-weighted fluid-attenuated inversion recovery sequence

Much is unclear about the pathophysiological mechanisms underlying painful temporomandibular disorders. In addition to various other theories, masticatory muscle dysfunction and pain have also been attributed to primary central nervous system hyperactivity. We assessed this possibility in a study using recent neurophysiological techniques. From among outpatients whose diagnosis of temporomandibular disorders had been obtained in stomatognathic facilities, we studied 10 patients with bilateral pain and 15 patients with unilateral pain, in whom electromyographic examination of the trigeminal reflexes disclosed normal findings except for absence or amplitude asymmetry of the jaw jerk. Transcranial magnetic stimulation yielded masseter motor evoked potentials of normal latency and amplitude, but five patients had to exert a near-maximum contraction to obtain their responses. The masseter silent periods elicited by the double-shock technique recovered normally. Because these tests measure the excitability of the masticatory system (including motor cortex, corticobulbar and corticoreticular connections, reticular interneurones and lower motoneurones), the lack of facilitation in these patients' responses excluded central hyperactivity as the primary cause of their masticatory dysfunction and pain.     

Gaussian profile estimation in one dimension

We present several new results on the classic problem of estimating Gaussian profile parameters from a set of noisy data, showing that an exact solution of the maximum likelihood equations exists for additive Gaussian-distributed noise. Using the exact solution makes it possible to obtain analytic formulas for the variances of the estimated parameters. Finally, we show that the classic formulation of the problem is actually biased, but that the bias can be eliminated by a straightforward algorithm.     

Surface-enhanced Raman scattering (SERS) and surface-enhanced resonance Raman scattering (SERRS): a review of applications

Surface-enhanced Raman scattering (SERS) and surface-enhanced resonance Raman scattering (SERRS) can provide positive identification of an analyte or an analyte mixture with high sensitivity and selectivity. Better understanding of the theory and advances in the understanding of the practice have led to the development of practical applications in which the unique advantages of SERS/SERRS have been used to provide effective solutions to difficult analytical problems. This review presents a basic theory and illustrates the way in which SERS/SERRS has been developed for practical use.     

Compact and miniature snapshot imaging polarimeter

We present and demonstrate a compact and miniature snapshot imaging polarimeter camera; it is anticipated that such a camera can be scaled down to less than 1.5 cm. Two Savart plates are used at the pupil plane to generate multiple fringes to encode the full Stokes vector in a single image. A geometric ray model is developed to explain the system. The numerical simulation based on this model is presented. Finally, the validity of the device is demonstrated by showing experimental results.     

Effects of processing parameters on electrospun fiber morphology

This study describes the application of a hybrid neuro-fuzzy inference system to control electrospinning process and how to use this approach for developing an electrospun fiber quality prediction system. An adaptive neuro-fuzzy inference system model has been applied to the use of electrospinning process parameters to study the relationship between electrospinning processing parameters and electrospun fiber morphology. Fiber morphology has been predicted and the impact of each processing parameter has been investigated. It was found that four electrospinning process parameters including: polymer solution concentration, spinning distance, applied voltage, and volume flow rate are the most influential factors to the electrospun fiber morphology. It was observed that the relationship existing between electrospinning processing parameters and nanofiber morphology is nonlinear.