Study of Drug induced skin reactions in the patients attending outpatient Department of Dermatology

Adverse drug reaction is any noxious change which is suspected to be due to drug, occurs at doses normally used in humans for prophylaxis, diagnosis, therapy of disease or for modification of physiological function. Adverse drug reactions cause both morbidity and mortality. Drug induced skin reactions are the most common type of adverse drug reaction and clinical presentation varies. We investigated the profile of drug induced skin reactions in the patients attending outpatient department of Dermatology, Kilpauk Medical College and Hospital, from September 2011 to February 2013. Data were recorded in WHO Suspected adverse reaction report form and analyzed statistically by Chi-square test. Causality and severity of adverse drug reaction were done. In conclusion, analyzing 100 ADRs men were more affected than female. Drug rash was the most common drug induced skin reaction. The suspected drug causing more reactions was Antibacterial agent. Hence ADR data base studies conducted across multiple centres provide early warning signals in preventing adverse drug reactions

Evaluation of analgesic activity of levofloxacin in adult albino rats

Background: Levofloxacin is a fluorinated quinolone antimicrobial used in the treatment of various bacterial infections and was active against both gram positive and gram negative bacteria. Levofloxacin is an optically active isomer of ofloxacin. Apart from its antibacterial action, it also exhibit antinociceptive properties. This study was conducted with the aim to evaluate the analgesic activity of Levofloxacin in albino rat in comparison with aspirin.Methods: Thirty adult albino rats weighing 150-250 gm were obtained from central animal house. The animals were divided into five groups of six animals each. Group I served as control received normal feed and water. Group II served as standard received tablet aspirin 100 mg/kg (oral) and Group III, IV, V served as test T1, T2, T3 and received tablet levofloxacin 10 mg/kg, 20 mg/kg and 40 mg/kg (oral), respectively. The analgesic effect of levofloxacin was evaluated using Eddy’s hot plate and tail flick methods and compared with standard analgesic aspirin. The values obtained were expressed as mean±SD. Statistical analysis of difference between groups were carried out using one-way analysis of variance (ANOVA). Probability p<0.05 was taken as the level of statistical significance.Results: Levofloxacin at 40 mg/kg showed statistically (p<0.05) elevation in pain threshold and a higher antinociceptive activity in comparison to control and standard groups.Conclusions: In the present study, levofloxacin has showed promising results as an analgesic when compared to the control and standard groups. It may be a lead compound for identifying newer adjuvant analgesic agents

REMOTE TRACKING OF ANDROID SMARTPHONES

The Purpose of the paper is to trace out the status and progress of the employee mobile and the relevant information is transferred to the mobile of the project manager and updated in the web server. The employee’s problem related to the company can be monitored by the project manager and he can also track the employee’s current location through the GPS. In existing system, the CBI alone can trace the mobile phone of any person with the help of unique IMEI number in telephone exchange. So there is no possibility to trace any information regarding the employee’s mobile details by the project manager. So to overcome, this system was implemented

A Visual Computing Unified Application Using Deep Learning and Computer Vision Techniques

Vision Studio aims to utilize a diverse range of modern deep learning and computer vision principles and techniques to provide a broad array of functionalities in image and video processing. Deep learning is a distinct class of machine learning algorithms that utilize multiple layers to gradually extract more advanced features from raw input. This is beneficial when using a matrix as input for pixels in a photo or frames in a video. Computer vision is a field of artificial intelligence that teaches computers to interpret and comprehend the visual domain. The main functions implemented include deepfake creation, digital ageing (de-ageing), image animation, and deepfake detection. Deepfake creation allows users to utilize deep learning methods, particularly autoencoders, to overlay source images onto a target video. This creates a video of the source person imitating or saying things that the target person does. Digital aging utilizes generative adversarial networks (GANs) to digitally simulate the aging process of an individual. Image animation utilizes first-order motion models to create highly realistic animations from a source image and driving video. Deepfake detection is achieved by using advanced and highly efficient convolutional neural networks (CNNs), primarily employing the EfficientNet family of models