Bioremediation of Zinc Using Bacillus sp. Isolated from Metal- Contaminated Industrial Zone

The production of heavy metals has increased quickly since the industrial revolution. Heavy metals frequently form compounds that can be toxic, carcinogenic, or mutagenic, even in very small concentrations. The usual techniques of removing metals from wastewaters are in general expensive and have many restrictions. Alternative methods of metal removal and recovery based on biological materials have been measured. Among various agents, the use of microbes for the removal of metals from industrial and municipal wastewater has been proposed as a promising alternative to conventional heavy metal management strategies in past decades. Thus, the present study aims to isolate and characterize bacteria from soil, sediment, and waters of metal-contaminated industrial area to study the zinc resistance patterns and the zinc bioaccumulation potential of the selected microorganism. Zinc analysis of the samples revealed that concentrations varying from 39.832 m g/L to 310.24 m g/L in water, 12.81 m g/g to 407.53 m g/g in soil, and 81.06 m g/g to 829.54 m g/g in sediment are present. Bacterial zinc resistance study showed that tolerance to Zn was relatively low (<500 m g/ml). Ten bacterial genera were represented in soil and 11 from water, while only 5 bacterial genera were recorded from sediment samples. Bacillus, Pseudomonas , and Enterobacter were found in soil, sediment, and water samples. Highly zincresistant Bacillus sp. was selected for zinc removal experiment. Zinc removal studies revealed that at pH 5 about 40% reduction occurs; at pH 7, 25% occurs; and at pH 9, 50% occurs. Relatively an increased removal of Zinc was observed in the fi rst day of the experiment by Bacillus sp. The metal bioaccumulative potential of the selected isolates may have possible applications in the removal and recovery of zinc from industrial ef fluents.

Low k thin films based on rf plasma-polymerized aniline

Thermally stable materials with low dielectric constant (k < 3.9) are being hotly pursued. They are essential as interlayer dielectrics/intermetal dielectrics in integrated circuit technology, which reduces parasitic capacitance and decreases the RC time constant. Most of the currently employed materials are based on silicon. Low k films based on organic polymers are supposed to be a viable alternative as they are easily processable and can be synthesized with simpler techniques. It is known that the employment of ac/rf plasma polymerization yields good quality organic thin films, which are homogenous, pinhole free and thermally stable. These polymer thin films are potential candidates for fabricating Schottky devices, storage batteries, LEDs, sensors, super capacitors and for EMI shielding. Recently, great efforts have been made in finding alternative methods to prepare low dielectric constant thin films in place of silicon-based materials. Polyaniline thin films were prepared by employing an rf plasma polymerization technique. Capacitance, dielectric loss, dielectric constant and ac conductivity were evaluated in the frequency range 100 Hz– 1 MHz. Capacitance and dielectric loss decrease with increase of frequency and increase with increase of temperature. This type of behaviour was found to be in good agreement with an existing model. The ac conductivity was calculated from the observed dielectric constant and is explained based on the Austin–Mott model for hopping conduction. These films exhibit low dielectric constant values, which are stable over a wide range of frequencies and are probable candidates for low k applications.

An Alternative Approach To Computer System Security Monitoring And Enhancement Through System Call Sequence Analysis

Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.