Comparative analysis of mast cell count in normal oral mucosa and oral pyogenic granuloma

Introduction: Mast cells are large granular cells that arise from a multipotent CD 34+ precursor in the bone marrow normally distributed throughout connective tissues. The most common method to study role of mast cells in any altered condition involves their identification and quantification in that condition and compare the values with that of the normal average count or number of mast cells. The present study was thus, undertaken to identify as well as quantify mast cells in oral pyogenic granuloma and compare it with the average count of mast cells in normal oral mucosa, thus aiming to assess the changes in count of mast cells in oral pyogenic granuloma. Materials and Methods: Ten cases of normal oral mucosa and thirty cases of oral pyogenic granuloma were studied for mast cell number using 1% toluidine blue. Results: An increase in mast cell number was observed in oral pyogenic granuloma. The mast cell count/high power field in pyogenic granuloma and normal oral mucosa was 10.27 and 4.58 respectively. There is a statistically significant increase in the mean of average mast cell count per high power field in oral pyogenic granuloma in comparison to normal oral mucosa. These facts may morphologically indicate a possibility of a role of mast cells in angiogenesis and recruitment of inflammatory cells which are characteristic features of oral pyogenic granulom

Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop

We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and words) in a language without orthography. We study the replacement of orthographic transcriptions by images and/or translated text in a well-resourced language to help unsupervised discovery from raw speech.Comment: Accepted to ICASSP 201

Empirical techniques and algorithms to develop a resilient non-supervised touch-based authentication system

Touch dynamics (or touch based authentication) refers to a behavioral biometric for touchscreen devices wherein a user is authenticated based on his/her executed touch gestures. This work addresses two research topics. We first present a series of empirical techniques to detect habituation in the user’s touch profile, its detrimental effect on authentication accuracy and strategies to overcome these effects. Habituation here refers to changes in the user’s profile and/or noise within it due to the user’s familiarization with the device and software application. With respect to habituation, we show that habituation causes the user’s touch profile to evolve significantly and irrevocably over time even after the user is familiar with the device and software application. This phenomenon considerably degrades classifier accuracy. We demonstrate techniques that lower the error rate to 3.68% and sets the benchmark in this field for a realistic test setup. Finally, we quantify the benefits of vote-based reclassification of predicted class labels and show that this technique is vital for achieving high accuracy in realistic touch-based authentication systems. In the second half, we implement the first ever non-supervised classification algorithm in touch based continual authentication. This scheme incorporates clustering into the traditional supervised algorithm. We reduce the mis-classification rate by fusing supervised random forest algorithm and non-supervised clustering (either Bayesian learning or simple rule of combinations). Fusing with Bayesian clustering reduced the mis-classification rate by 50% while fusing with simple rule of combination reduced the mis-classification rate by as much as 59.5% averaged over all the users.Master of ScienceComputer Science & Information SystemsUniversity of Michigan-Flinthttp://deepblue.lib.umich.edu/bitstream/2027.42/134750/1/Palaskar2016.pdfDescription of Palaskar2016.pdf : Main articl

Hinge axis - location, clinical use and controversies

The hinge axis is an imaginary line around which the condyles can rotate without translation. Terminal hinge position is the most retruded hinge position and it is significant because it is a learnable, repeatable and recordable position that coincides with the position of centric relation. There are many schools of thought regarding hinge axis. The proponents of Gnathology say that there is one transverse hinge axis common to both condyles which can be accurately located. The proponents of transographics claim that each condyle has a different transverse hinge axis and that a transograph is the only instrument that can duplicate this. Still others claim that an exact duplication of jaw movement is not possible on any machine. The aim of this article is to throw light on location, clinical use and controversies of hinge axis