Studies on the effect of mercury on germination and biochemical changes of ground nut [Arachis hypogaea (L). var. VRI- 1] seedlings

The uptake and accumulation of mercury in various parts of the plants namely stem, root, leaf and seeds showed a gradual decrease with the steady increase in mercury treatment. It can be concluded that the VRI-1 variety of groundnut was proved to be tolerant to mercury. Hence it can it is recommended that the variety VRI – 1 can be cultivated in the soils contaminated with mercury and chloralkali  plants which use mercury as an electrode in cells for the manufacture of caustic soda and chlorine effluent. This will prevent considerably the extent of damage caused by mercuryon ground nut to a certain extent

Antidiabetic effect of Chloroxylon swietenia bark extracts on streptozotocin induced diabetic rats

Diabetes has been increasing at an alarming rate around the world, and experts have relied on remedies from the utilization of ancient drugs that are essentially derived from plants. The present study aimed to evaluate the antidiabetic potential of Chloroxylon swietenia bark extracts on streptozotocin induced diabetic rats. Diabetes was induced in male albino Wistar rats by single intraperitoneal injection of streptozotocin (STZ) (50 mg/kg b.w.). The diabetic rats were administered orally with C. swietenia bark (CSB) methanolic (CSBMEt) and aqueous (CSBAEt) (250 mg/kg b.w.) extracts and glibenclamide (600 µg/kg b.w.) by intragastric intubation for 45 days. The result showed a heavy loss in weight, increase in blood glucose and glycosylated hemoglobin level, and decline in plasma insulin and total hemoglobin content. Furthermore, glucose-6-phosphatase and fructose-1,6-bis phosphatase were found to be increased whereas hexokinase and glycogen contents were decreased in STZ induced diabetic rats. CSBAEt, CSBMEt and glibenclamide treated diabetic rats showed moderate reduction in blood glucose and glycosylated hemoglobin levels; in addition, plasma insulin and hemoglobin levels were elevated. The altered activities of carbohydrate metabolizing enzymes and liver glycogen were improved remarkably. CSBMEt results were comparable to the standard drug glibenclamide. The present findings support the usage of the plant extracts for the traditional treatment of diabetes

AUTHENTICATION SCHEME FOR SESSION PASSWORDS USING COLOR AND IMAGE

Graphical passwords are believed to be more secure than traditional textual passwords, but the authentications are usually complex and boring for users. Furthermore, most of the existing graphical password schemes are vulnerable to spyware and shoulder surfing. A novel graphical password scheme ColorLogin is proposed in this paper. ColorLogin is implemented in an interesting game way to weaken the boring feelings of the authentication. ColorLogin uses background color, a method not previously considered, to decrease login time greatly. Multiple colors are used to confuse the peepers, while not burdening the legitimate users. Meanwhile, the scheme is resistant to shoulder surfing and intersection attack to a certain extent. Experiments illustrate the effectiveness of ColorLogin

LEARNING TO RANK AND CLASSIFICATION OF BUG REPORTS USING SVM AND FEATURE EVALUATION

When a new bug report is received, developers usually need to reproduce the bug and perform code reviews to find the cause, a process that can be tedious and time consuming. A tool for ranking all the source files with respect to how likely they are to contain the cause of the bug would enable developers to narrow down their search and improve productivity. This project introduces an adaptive ranking approach that leverages project knowledge through functional decomposition of source code, API descriptions of library components, the bug-fixing history, the code change history, and the file dependency graph. Given a bug report, the ranking score of each source file is computed as a weighted combination of an array of features, where the weights are trained automatically on previously solved bug reports using a learning-to-rank technique. I applied SVM (Support Virtual Machine) to classify the bug reports to identify, which category the bug belongs to. It helps to fix the critical defects early. The ranking system evaluated on six large scale open source Java projects, using the before-fix version of the project for every bug report. The experimental results show that the learning-to-rank approach outperforms three recent state-of-the-art methods. In particular, proposed method makes correct recommendations within the top 10 ranked source files for over 70 percent of the bug reports in the Eclipse Platform and Tomcat projects