In the present work, a back propagation neural network model has been developed for the prediction of flank wear in turning operations. Large numbers of experiments have been performed on mild steel work-piece material using high speed steel (HSS) as the cutting tool. Process parametric conditions including cutting speed, feed-rate, depth of cut, and the measured parameters such as cutting force, chip thickness and vibration signals are used as inputs to the neural network model. Flank wear of the cutting tool corresponding to these conditions is the output of the neural network. The inclusion of chip width in addition to the existing inputs to the neural network model has been considered. The convergence of mean square error both in training and testing came out very well. The performance of the trained neural network has been tested with the experimental data, and is found to be in good agreement.

Background: Mycobacterium Tuberculosis (MTB) is one of the most ancient diseases of mankind. Pulmonary tuberculosis (PTB) is the most common, despite the diagnosis and treatment of TB. Many studies reported, a collaboration between PTB susceptibility. In our research study, we report meantime findings after enrolling 732 of a planned 212 participants. Study Design: A descriptive cross-sectional study. Methods: The study conducted on patients with TB in west India was conducted in the Department of Microbiology, Index Medical College; Indore Madhya Pradesh. Patients suspected of PTB were qualified for screening if their age varied from 25 to 60 years and with both gender, signs and symptoms associated with PTB such as cough for more than 2 weeks, fever, weight loss, chest pain, and abnormal chest X-ray findings in results and cartridge-based nucleic acid amplification test (CBNAAT) positive. All Patients were monitored monthly while they visited in TB and chest clinic for TB treatment. Results: A total of 937 patients were selected for the study. Out of which only 732 patients were enrolled. About 212 patents were positive for CBNAAT and 520 were found negative. The confirmed positive CBNAAT patients do not have a history of tuberculosis. In this study about 21.72% were ZN stain positive, 33.46% were culture positive and 28.96% were CBNAAT positive. Conclusion: The current scenario of traditionally AFB-negative PTB is not sensitive enough to establish the diagnosis of active tuberculosis without CBNAAT. They underdiagnose PTB and over-treat people without PTB.

Background: Many studies reported association between TB susceptibility and diabetes mellitus (DM). Some studies were retrospective, did not assess other co morbidities related with tuberculosis. The effects of diabetes on tuberculosis severity (EDOTS) can be hypothesizing that burden of cases India is leading in TB and runner-up in diabetic. We report interim findings after enrolling 732 of a planned 212 subjects.Methods: This study conducted on patients with TB in west India with DM and normoglycemia defined by glucose tolerance test (GTT) and glucose fasting. Glycocylated hemoglobin (HbA1c), lipids profile and 25-hydroxyvitamin D were measured at the time of enrollment of patients. All patients were monitored monthly while they visited in TB and chest clinic for TB treatment.Results: Of 212 eligible patients, 117 (55.18%) were classified as diabetic, 49 (23.11%) with pre diabetic history (PDM), and 46 (21.70%) as normoglycemic (NG). DM patients were more likely to have a family history of diabetes in comparison to NG patients. Low density lipoprotein (LDH)) was higher in KDM as compared with NDM and NG patients. More patients (32) found diabetic through OGTT as compared with HbA1c (29).Conclusions: Early EDOTS, glycemic control and improve lifestyle can reduce the heterogeneity and implications for the TB-DM. Early diagnosis of TB and DM plays an important role in the management and treatment of TBDM.

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