Clinical and demographic features of Meige's syndrome

Fifty five patients with Meige's syndrome were examined for clinical and demographic features. The mean age of onset was 52.3 years. The peak age of onset was in the sixth decade with a male to female ratio of 1.11:1. The mean duration of illness was 3.7 years. Commonest initial symptom was increased blinking, seen in 30 cases (54.5%). Twenty five patients (45.4%) had complete syndrome of blepharospasm with oromandibular dystonia, whereas 24 patients (43.6%) had blepharospasm alone and the rest (6 patients, 10.9%) had oromandibular dystonia. The extension of spasm beyond cranial muscles was observed in 10 patients (18.1%). Eleven patients had family history of dystonia or other extrapyramidal disorders. Incidence of depression was high in these cases.     

In vivo demonstration of microcalcification in breast cancer using high resolution ultrasound

84 patients with 89 primary breast cancers underwent high resolution ultrasound, mammography and histological evaluation. Pathological specimens and hard copy images of both imaging modalities were reviewed in order to document the amount of microcalcification present in each tumour. A total of 44, 40 and 46 tumours had visible microcalcification using high resolution ultrasound, mammography and histology, respectively. Using mammography as the gold standard, ultrasound achieved a sensitivity of 95%, specificity of 87.8% and accuracy of 91% in the detection of microcalcification. Histology had a sensitivity of 80%, specificity of 71.4% and accuracy of 75.3%. We conclude that ultrasound is sensitive in the detection of microcalcification in breast cancer when they are within a mass lesion, and is a reliable diagnostic sign of carcinoma when present.     

Learning Recognition and Segmentation Using the Cresceptron

This paper presents a framework called Cresceptron for view-based learning, recognition and segmentation. Specifically, it recognizes and segments image patterns that are similar to those learned, using a stochastic distortion model and view-based interpolation, allowing other view points that are moderately different from those used in learning. The learning phase is interactive. The user trains the system using a collection of training images. For each training image, the user manually draws a polygon outlining the region of interest and types in the label of its class. Then, from the directional edges of each of the segmented regions, the Cresceptron uses a hierarchical self-organization scheme to grow a sparsely connected network automatically, adaptively and incrementally during the learning phase. At each level, the system detects new image structures that need to be learned and assigns a new neural plane for each new feature. The network grows by creating new nodes and connections which memorize the new image structures and their context as they are detected. Thus, the structure of the network is a function of the training exemplars. The Cresceptron incorporates both individual learning and class learning; with the former, each training example is treated as a different individual while with the latter, each example is a sample of a class. In the performance phase, segmentation and recognition are tightly coupled. No foreground extraction is necessary, which is achieved by backtracking the response of the network down the hierarchy to the image parts contributing to recognition. Several stochastic shape distortion models are analyzed to show why multilevel matching such as that in the Cresceptron can deal with more general stochastic distortions that a single-level matching scheme cannot. The system is demonstrated using images from broadcast television and other video segments to learn faces and other objects, and then later to locate and to recognize similar, but possibly distorted, views of the same objects.     

A model for primary and heterogeneous secondary reactions of wood pyrolysis

A chain growth model for heterogeneous secondary reactions is developed for the pyrolysis of large wood particles and the parameters determined by nonlinear optimization. The model takes both the volatile retention time and cracking and repolymerization reactions of the vapours with the decomposing solid as well as sutocatalysis into consideration. The extent of the secondary reactions is strongly influenced by the time and the ratio of the autocatalytic (propagation) reaction rate to noncatalytic (initiation) reaction rate. The wood which has a higher value of the autocatalytic/noncatalytic ratio also has a higher exothermic heat of reaction and yields a higher amount of final char residue. This fact confirms the heterogeneous secondary reactions lead to carbon enrichment of the final residue and are accompanied with an exothermic heat of reaction. The lower activation energies of the initiation and propagation reactions as compared to primary reactions (competitive reaction model consisting of weight loss and char forming reactions) confirm autocatalysis in large particles. The sealed reactor studies of small quantities of fine wood samples show that heterogeneous secondary reactions and not lower heating rates in large particles are the main source of char formed during the thermal decomposition of large wood particles. The model predictions are in agreement with the weight loss and temperature versus time curves over a wide range of particle size and furnace temperatures.     

Cluster formation of kaolin using the hindered settling technique

The settling of kaolin has been studied in various alcohol-benzene mixtures, under controlled moisture conditions. The influence of the parameters of the settling apparatus has been evaluated. From the log Q/?² vs. ? plots, the average particle size has been calculated, and the effect of absorbed moisture and the nature of the solvent mixture on cluster formation have been discussed. The constants of Oliver's equation for these systems have been obtained and their significance in the light of Landel's theory has been discussed.     

An analytical model for the interaction between an insoluble particle and an advancing solid/liquid interface

In this article, the behavior of particles in front of an advancing solidJliquid interface was analyzed. In the analytical model presented, the critical velocity for the transition from particle pushing to engulfment by the interface was calculated as a function of relevant material parameters and processing variables. In particular, the effect of the difference in the thermal properties of the particle and the matrix on the particle/interface interaction was examined. It was demonstrated that the presence of particles could destabilize the interface which, in turn, affected the behavior of particles at the interface. Based on the analysis, a particle behavior map was constructed to illustrate the complex particle behaviors in different material systems under various growth conditions. Theoretical predictions were compared against experimental results obtained in transparent organic materials as well as in metallic systems. The relevance of these observations to the melt processing of particulate-reinforced metal matrix composites (MMCs) was discussed. Formerly Assistant Research Engineer, The University of Alabama, is now Manufacturing Engineer     

Persistent internal polarization studies in poly(N-vinylcarbazole)trinitrofluorenone charge transfer complex

Studies on the persistent internal polarization in poly(N-vinylcarbazole) (PNVC)/trinitrofluorenone (TNF) charge transfer complex are reported. This complex is known to be photoconducting and in the present investigation, the photoelectret charge has been studied as a function of applied voltage, intensity of illumination and time of polarization. A saturation effect is observed in each case. Also the possibility of the use of PNVC/TNF complex in PIP electrophotography has been explored and a comparison of the results of this investigation is made with the results obtained for PNVC.