Fuzzified Single Phase Automatic Sequential Reactive Power Compensation with Minimized Switches

The current rapid growth in IoT technology facilitates the effortless implementation of bidirectional remote monitoring and control system implementation in homes and buildings. We have modeled an actual non-intrusive PnP sequential SVC prototype hardware and wireless FLC automation software design on a real single phase home appliances system as load modeling. In addition, we have also designed a novel Unidirectional MOSFET Switched Capasitor model (UniMosSC) which enables us to reduce the hardware cost and increase the life span of SVC due it uses minimum switching devices. The system we have designed is able to correct the power factor at the root of the problem at each appliance. Due to complexity of appliance clustering and overlapping clusters, we implemented fuzziness in the system for more reliability in computations. The system could be used in homes or buildings resulting in electricity bill reduction, saving dollars and cents

Pharmaceutical drug promotion: perception and attitude of medical interns towards drug company interactions in a tertiary care teaching hospital

Background: Interactions of pharmaceutical industry with the physicians which are usually mediated through pharmaceutical representatives have a significant impact on physician decision-making. This interaction can start as early as medical school during their training and this is said to influence their prescribing behavior when they become physicians. Aims and objectives of the study was to evaluate the attitude of interns towards pharmaceutical companies interactions including accepting gifts, ethical issues and influence on clinical decisions and also to study perception of medical interns towards the accuracy of information provided by the medical representatives.Methods: This was a cross sectional questionnaire based study that was conducted among the medical interns of the teaching hospital attached to Mandya Institute of Medical Sciences, Mandya. The study was carried out between July and August 2016. A preformed structured questionnaire was distributed to the interns consenting to participate in the study. Completed questionnaires were collected, compiled and data was analyzed.Results: A total of 93 questionnaires were distributed and 90 interns responded (response rate 96.7%). About 44.4% respondents felt that accepting gifts from Drug Company would influence their own decision making. Only 26.6% of them were of the opinion that it is ethical to accept pharmaceutical company gifts. Majority of them felt that Medical Representatives exaggerate the benefits of medicines and downplay the risks and contraindications of medicine. About 32.2% of them were of the opinion that they would prefer to prescribe the drug from the companies offering them with gifts over those without. Majority of the respondents felt that the doctors should be offered with gifts by drug companies whenever their drugs are prescribed.Conclusions: Attitude of Medical Interns towards Drug Company interactions as observed suggests for training the budding doctors on appropriate drug company interactions to prevent the risks associated with promotional efforts of pharmaceutical companies.

Study of analgesics usage in third trimester of pregnancy and its ill effects on pregnancy course and outcome

Background: Pregnancy is a special physiological state. Pregnancy care is one of the greatest challenges in medicine as it demands a special care in the use of drugs because of altered physiology. At least 10 percent of birth defects are thought to result from maternal drug exposures. NSAIDS are one of the most commonly used medications during pregnancy (17%) to treat painful events during pregnancy.Methods: A prospective observational study was conducted after taking approval from the Institutional ethical committee and study was conducted for a period of one year. Antenatal clinics and inpatients wards of department of obstetrics and Gynaecology were visited and all the pregnant women with exposure to analgesics during third trimester and at the time of labour were included in the study. Information regarding the analgesics exposure either prescribed by the physician or self-medicated was collected.Results: Total 1520 pregnant women were included in the study over a period of one year. Analgesic exposure was seen in 77.1% of pregnant women during labour. Most common analgesic used to relieve labour pain was tramadol. 22.9% pregnant women were exposed to analgesics during third trimester, among them exposure to paracetamol was observed in 14% of pregnant women and to tramadol in 8.9%. Indications for usage of these analgesics during pregnancy were fever with myalgia (45.8%), false labour pain (37%), and headache (11.4%).Conclusions: Study showed that there is a positive association between analgesics exposure during third trimester of pregnancy particularly to paracetamol exposure and preterm delivery. Association between paracetamol exposure and low birth weight was also observed in this study but this finding could be due to more number of preterm deliveries which could not be ruled out in this study. Further studies have to be conducted to confirm the association since there are only limited numbers of studies done till now

ANTIBACTERIAL AND ANTIOXIDANT ACTIVITIES OF STEM BARK ESSENTIAL OIL CONSTITUENTS OF LITSEA GLUTINOSA C. B. ROB.

Objective: To evaluate the chemical composition, antibacterial and antioxidant properties of stem bark essential oil of Litsea glutinosa C. B. Rob.Methods: The essential oil isolated from stem bark of L. glutinosa and their chemical composition was analyzed by gas chromatography coupled with mass spectrometry detector. The in vitro antibacterial activity of the stem bark essential oil was investigated against eight human pathogenic bacterial clinical isolates using agar disc diffusion method and MIC value was determined by modified resazurin microtitre-plate assay. The antioxidant activity of essential oil was measured by 2, 2-diphenyl-1-picrylhydrazyl radical (DPPH), 2, 2-azinobis-3-ethylbenzothiazoline-6-sulphonate radical cation (ABTS) and β-carotene bleaching assay.Results: GC-MS analysis of stem bark essential oil resulted in the identification of 37 compounds, off which 9,12-octadecadienoic acid (62.57%), hexadecanoic acid (12.68%), stigmast-5-en-3-ol (6.87%) and vitamin E (2.51%) were the main constituents representing 84.63% of the oil. The determination of in vitro antibacterial activity of stem bark essential oil resulted in significant inhibition zone (15.00±0.57 mm) and MIC value (0.15±0.15×10-2 mg/ml) against the pathogenic bacteria Vibrio cholera followed by Pseudomonas aeruginosa and Salmonella typhi. The results of DPPH radical scavenging (IC50:4.540±0.06 µg/ml), ABTS (IC50:256.02±0.06 µg/ml) and β-carotene bleaching assay (%I: 78.51±0.42 %) showed significant in vitro antioxidant property.Conclusion: L. glutinosa stem bark essential oil showed potential antibacterial activity against the Vibrio cholera. The results of this investigation supported the ethnomedical claim of essential oil as a demulcent, antidiarrheal and antioxidant drug

Analysis of medication errors in medicine ward of medical college teaching hospital, Mandya

Background: Medication errors are one of the most common types of medical error that is seen in hospitalised patients. Since medication error is one of the growing concerns of healthcare issue and have implications on patient safety, the purpose of this study was to identify medication error and in turn would help to create awareness among healthcare professionals and provide safety to the patients.Methods: Study was initiated after obtaining approval from the Institutional Ethics Committee. The study was done for a period of 1 year between June 2016 and May 2017. Clinical data and data regarding the medication that was prescribed, transcribed, dispensed, administered was collected and was analysed for various types of medication errors during the different stages of medication use process.Results: A total of 351 subjects were recruited in the study for assessing medication error. About 2,283 drugs were prescribed among 351 patients. Maximum number of drugs was administered through parenteral route (50.3%). Medication error was most common during the prescribing stage (51.4%) followed by transcribing stage (39.1%), administration stage (6.9%), and dispensing stage (2.6%). On an average 6 drugs were prescribed per patient. Total of about 5411 errors have occurred out of which 98.8% of errors were preventable, 1.2% of errors were non-preventable. Cardiovascular system (21.9%) and endocrine and renal system (21.9%) was commonly affected due to the medication errors.Conclusions: Medication errors are one of the commonest problems of the healthcare system should be identified and documented and their causes should be studied in order to develop systems that minimize the recurrence

Obstructive Sleep Apnea – Current Perpectives

Obstructive sleep apnea is a common sleep related breathing disorder. The demand for sleep medicine services has increased exponentially since the recognition of sleep apnea as a disease in the 1960s. The involvement of dentists in the treatment of sleep apnea has increased. It is important that dentists are aware of the problem of sleep disorders and the potential they have to help in their management

Analysis of Distribution Transformer Physiological and Electrical Fault Detection - A Smart Grid Application

  Power grids transport electricity from the point of generation to the market. Power conversion from HV to LV and vice versa occurs in grids, also known as substations. These substations or power grids can be accessible or situated in remote locations. Transformers are used to convert power; they are an essential part of transmission and distribution networks. The method of grid monitoring and maintenance is essentially a very monotonous one. Monitoring the health of the transformers to maintain an uninterrupted power supply to the customers is difficult in such circumstances. Overvoltage, load currents, oil temperature, transformer oil level, and other parameters are monitored. The condition of the distribution transformer’s is evaluated in this article using real-time data from the transformer and specific sensors connected to Raspberry pi and artificial neural networks, are used to analyse the situation and make decisions regarding the health of the transformer. A model has been proposed for continuous monitoring consistent vigilance and swift actions against any faulty situations