No abstract

A sample size of 285 subjects (95 cases and 190 controls) was enrolled in the study. Anamnestic questionnaire was administered to the patients fulfilling the criteria. Based on the score attained, patients were grouped as TMD patients (case) or TMD free patients (control). A pre-designed performa was used to record the data. SPSS v.17.0 was used for descriptive and inferential analysis. RESULTS: The mean age of the participants was 33.3±11.2 years with male to female ratio of with 1.26:1. Maximum of the participants (72%) were of 41 years or less. Overall mean number of missing teeth in all participants was 3.41±3.08. Mean number of missing teeth in cases and controls was 4.46±3.65 and 2.89±2.60 respectively (p< 0.001). Tooth loss of <5 teeth & ≥5 teeth was observed in 53 & 42 cases as compared to 128 & 62 controls respectively (OR=0.61; 95% CI: 0.36 to 1.01; p-vale 0.056). The relationship for number of quadrants with number of missing teeth in cases and control groups was significant (p-value=<0.001). CONCLUSION: Present study indicates that there is significant correlation between the numbers of quadrants with tooth loss and TMD. Increasing the number of quadrants with tooth loss will increase the risk of TMD. However, the number of teeth lost itself has no association with TMD.

This paper deals with impulsive noise (IN) in multichannel (MC) Active Noise Control (ANC) Systems with Online Secondary Path Modelling (OSPM) employing adaptive algorithms for the first time. It compares performance of various existing techniques belonging to varied computational complexity range and proposes four new methods, namely: FxRLS-VSSLMS, VSSLMS-VSSLMS, FxLMAT-VSSLMS and NSS MFxLMAT-VSSLMS to deal with modest to very high impulsive noise (IN). Simulation results show that these proposed methods demonstrated improved performance in terms of fast convergence speed, lowest steady state error, robustness and stability under impulsive environment in addition to modelling accuracy for stationary as well as non-stationary environment besides reducing computational complexity many folds.