KNOWLEDGE, ATTITUDE, AND PRACTICE OF GENERIC DRUGS AMONG DOCTORS IN A TERTIARY CARE HOSPITAL

Objectives: Generic medicines constitute an important aspect of affordable health care. “JAN AUSHADHI” campaign was started by the Government of India in 2008 to support generic prescriptions. Recently, medical council of India had requested all clinicians for generic prescriptions. With this background, this study was undertaken to evaluate the knowledge, attitude, and practice of generic medicines among doctors. Methods: It was a cross-sectional, prospective, questionnaire-based study. After obtaining institute permission, validated questionnaires were distributed to different clinical departments at Vydehi Institute of Medical Sciences and Research Centre, Bengaluru. With gentle reminders in between, filled forms were collected after 7 days. Results: Mean age of the participants was 29.05±17.81 years. Out of 250 questionnaires distributed, 156 were returned back without responding. The response rate was 62.4%. Out of 156, 35 (22.43%) were intern medical officers, 89 (57.05%) were post-graduates, and 32 (20.51%) were faculty members. Regarding knowledge, the mean score was 6.24±0.17. 52 (33.33%) participants had good knowledge, 73 (46.79%) had average knowledge, and 31 (19.87%) had poor knowledge about generic medicines. Generics were prescribed by 90 (57.69%) participants. Most of the clinicians (66.02%) felt that prescribing in generics is not a burden on them provided government ensured the quality control of drugs. 121 (77.56%) stated that the socioeconomic status of the patient is an important factor while prescribing generics. 136 (87.17%) felt that generics bring down the treatment costs. Conclusion: This study shows that participants were well aware about generic drugs. As opined by the clinicians, a national level online reference must be made available

Study on the Crystal Structure and Microstructure Evolution of Shock-processed Titanium Powder

Titanium powder was rapidly solidified by using shock-wave consolidation technique. The critical parameters were controlled by intrumented detonics and pin-oscillography. The compacted specimens were investigated for crystal structure and microstructural strengthening by using standard diagnostic techniques. The density of the final product was found to be greater than 96% of the theoretical value. X-ray diffraction pattern reveals intact crystalline structure without the presence of any undesired phases. The particle size reduction indicated by XRD was supported by laser diffraction based particle size analyzer. Results from energy dispersive spectroscopy ruled out the possibility of any segregation within the compacts. Scanning electron microscopy showed crack-free, voids-free, melt-free, fracture-less compacts of titanium with a unidirectional dendrite orientation without any grain-growth

Automation in colouration technology to predict dyeing parameters for desired shade and fastness

450-458In this study, dyeing parameters, such as dye conc., sodium sulphide conc., salt conc., and time, have been statistically framed through full-factorial design software to generate sets of experimental variables. Cotton has been dyed using all these sets of variables separately, and then evaluated for respective surface colour strength (K/S), and colour fastness properties, such as fastness to light, washing and rubbing. The outputs thus generated are then analyzed using ANN to generate a big data, by which dyer can predict any shade. This will help in eliminating the rigorous laboratory trials and forecasting colour strength & quality of dyeing well before the dyeing process is materialized. The whole data sets are then uploaded in cloud computing to enable to acquire the data. It is observed that by assigning diffent values of K/S on cloud, the dyeing parameters can be obtained to achieve desired output in further application

Automation in colouration technology to predict dyeing parameters for desired shade and fastness

In this study, dyeing parameters, such as dye conc., sodium sulphide conc., salt conc., and time, have been statisticallyframed through full-factorial design software to generate sets of experimental variables. Cotton has been dyed using all thesesets of variables separately, and then evaluated for respective surface colour strength (K/S), and colour fastness properties,such as fastness to light, washing and rubbing. The outputs thus generated are then analyzed using ANN to generate a bigdata, by which dyer can predict any shade. This will help in eliminating the rigorous laboratory trials and forecasting colourstrength & quality of dyeing well before the dyeing process is materialized. The whole data sets are then uploaded in cloudcomputing to enable to acquire the data. It is observed that by assigning diffent values of K/S on cloud, the dyeingparameters can be obtained to achieve desired output in further applicatio