Factors that Lead to the Immunotherapy Gap in Multiple Sclerosis Testing

Multiple sclerosis is a disease that affects the central nervous system. Most doctors and scientists believe that it is an autoimmune disease. Simply put, the immune system attacks the nerves in a person’s body, thereby causing myelin damage, inflammation, and neurodegeneration. The plaque that then builds up on the nerves is scar tissue created when the wounds made by the immune system heal. It is this plaque that inhibits communication between the axons in the body and causes the symptoms of MS, which includes problems with movement, pain, vision problems, trouble swallowing, fatigue, and heat sensitivity (Baker et al., 2011, p. 647)

Chemo-radiotherapy induced oral mucositis during IMRT for head and neck cancer: an assessment

Background: This study is conducted mainly to evaluate the changes in quality and quantity of oral epithelial cells during the course of IMRT. Material and Methods: 30 Patients undergoing chemo-radiotherapy were followed through course of treatment. They were compared with a group of age- and sex-matched healthy individuals. The procedure involved WHO clinical scoring, collection of oral washings and preparation of buccal smears from both study group and control group. The changes occurred were recorded as a way of assessing the severity of oral mucositis. Results: revealed a significant occurrence of oral mucositis in almost all patients during weekly follow up. There was a significant increase in percentage of viable buccal epithelial cells in study group when compared to normal controls ( P <0.005) during and at the end of chemo-radiotherapy. Conclusion s : quantification of oral mucositis can be done at cellular level by determining the oral mucosal cell viability and their maturation during IMRT

Mothering and Othering: Surrogacy and the Saga of Yashoda

Framed as a science fiction thriller, Hari and Harish’s Telugu 2022 film Yashoda focuses on surrogacy, the capitalist agenda of the cosmetics industry, and body politics. Frequently, the film shifts to a melodramatic strain and offers problematic and regressive representations of motherhood, but there are still significant merits to the film in terms of its subject matter

A STUDY ON GRIEVANCE HANDLING IN RAMCO CEMENTS LIMITED GOVINHAPURAM WORKS AT ARIYALUR

Grievance refers to any dissatisfaction or sense of injustice which is felt by an employee in reference to his/her pay, working conditions, leave, recoveries of dues or other aspects of employment.Grievances handling is important a part of any company. It helps to unravel the matter of an employee who is trouble and needs some kind help.The sample respondents are used for collecting the information is merely 125 employees within the total population of the organization.The majority of the respondents said redressal of employee’s grievances makes job satisfaction. Keywords: Grievance, Job satisfaction, Employment, Redressal, Recovery

Development of LTO LPCVD Process for 6 Wafers at RIT

Low Temperature Oxide (LTO) thin films were prepared using a Low Pressure Chemical Vapor Deposition process. By employing statistically designed experiments, the number of experimental runs required was minimized. The full-factorial experimental design was set up to examine effects temperature, gas flow and pressure had on deposition rate, wafer to wafer uniformity, within the wafer uniformity and within run uniformity. The average deposition rate found to be 112A per minute. The LTO baseline process conditions optimized based on the results of this project are: Temperature of 410C, pressure of 33OmTorr and gas flow ratio of 0.55

Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data

We propose an efficient family of algorithms to learn the parameters of a Bayesian network from incomplete data. In contrast to textbook approaches such as EM and the gradient method, our approach is non-iterative, yields closed form parameter estimates, and eliminates the need for inference in a Bayesian network. Our approach provides consistent parameter estimates for missing data problems that are MCAR, MAR, and in some cases, MNAR. Empirically, our approach is orders of magnitude faster than EM (as our approach requires no inference). Given sufficient data, we learn parameters that can be orders of magnitude more accurate