Antibody Based Diagnostic for Detection Of Vibrios and their Biological Control using Antagonistic Bacteria in Macrobrachium Rosenbergii Larval Rearing Systems

The main objective of the work undertaken here was to develop an appropriate microbial technology to protect the larvae of M.rosenbergii in hatchery from vibriosis. This technology precisely is consisted of a rapid detection system of vibrios and effective antagonistic probiotics for the management of vibrios. The present work was undertaken with the realizations that to stabilize the production process of commercial hatcheries an appropriate, comprehensive and fool proof technology is required primarily for the rapid detection of Vibrio and subsequently for its management. Nine species of Vibrio have been found to be associated with larvae of M. rosenbergii in hatchery. Haemolytic assay of the Vibrio and Aeromonas on prawn blood agar showed that all isolates of V. alginolyticus and Aeromonas sp., from moribund, necrotized larve were haemolytic and the isolates of V.cholerae, V.splendidus II, V.proteolyticus and V.fluvialis from the larvae obtained from apparently healthy larval rearing systems were non-haemolytic. Hydrolytic enzymes such as lipase, chitinase and gelatinase were widespread amongst the Vibrio and Aeromonas isolates. Dominance of V.alginolyticus among the isolates from necrotic larvae and the failure in isolating them from rearing water strongly suggest that they infect larvae and multiply in the larval body and cause mortality in the hatchery. The observation suggested that the isolate V. alginolyticus was a pathogen to the larvae of M.rosenbergii. To sum up, through this work, nine species of Vibrio and genus Aeromonas associated with M.rosenbergii larval rearing systems could be isolated and segregated based on the haemolytic activity and the antibodies (PA bs) for use in diagnosis or epidemiological studies could be produced, based on a virulent culture of V.alginolyticus. This could possibly replace the conventional biochemical tests for identification. As prophylaxis to vibriosis, four isolates of Micrococcus spp. and an isolate of Pseudomonas sp. could be obtained which could possibly be used as antagonistic probiotics in the larval rearing system of M.rosenbergii.

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.

Process profiling using frequencies of system calls

In this paper we discuss our research in developing general and systematic method for anomaly detection. The key ideas are to represent normal program behaviour using system call frequencies and to incorporate probabilistic techniques for classification to detect anomalies and intrusions. Using experiments on the sendmail system call data, we demonstrate that we can construct concise and accurate classifiers to detect anomalies. We provide an overview of the approach that we have implemented

Feature Selection for Face Detection

We present a new method to select features for a face detection system using Support Vector Machines (SVMs). In the first step we reduce the dimensionality of the input space by projecting the data into a subset of eigenvectors. The dimension of the subset is determined by a classification criterion based on minimizing a bound on the expected error probability of an SVM. In the second step we select features from the SVM feature space by removing those that have low contributions to the decision function of the SVM.

Object Detection in Images by Components

In this paper we present a component based person detection system that is capable of detecting frontal, rear and near side views of people, and partially occluded persons in cluttered scenes. The framework that is described here for people is easily applied to other objects as well. The motivation for developing a component based approach is two fold: first, to enhance the performance of person detection systems on frontal and rear views of people and second, to develop a framework that directly addresses the problem of detecting people who are partially occluded or whose body parts blend in with the background. The data classification is handled by several support vector machine classifiers arranged in two layers. This architecture is known as Adaptive Combination of Classifiers (ACC). The system performs very well and is capable of detecting people even when all components of a person are not found. The performance of the system is significantly better than a full body person detector designed along similar lines. This suggests that the improved performance is due to the components based approach and the ACC data classification structure.

Instantaneous threat detection based on a semantic representation of activities, zones and trajectories

Threat detection is a challenging problem, because threats appear in many variations and differences to normal behaviour can be very subtle. In this paper, we consider threats on a parking lot, where theft of a truck’s cargo occurs. The threats range from explicit, e.g. a person attacking the truck driver, to implicit, e.g. somebody loitering and then fiddling with the exterior of the truck in order to open it. Our goal is a system that is able to recognize a threat instantaneously as they develop. Typical observables of the threats are a person’s activity, presence in a particular zone and the trajectory. The novelty of this paper is an encoding of these threat observables in a semantic, intermediate-level representation, based on low-level visual features that have no intrinsic semantic meaning themselves. The aim of this representation was to bridge the semantic gap between the low-level tracks and motion and the higher-level notion of threats. In our experiments, we demonstrate that our semantic representation is more descriptive for threat detection than directly using low-level features. We find that a person’s activities are the most important elements of this semantic representation, followed by the person’s trajectory. The proposed threat detection system is very accurate: 96.6 % of the tracks are correctly interpreted, when considering the temporal context.

An Optimum-Path Forest framework for intrusion detection in computer networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Pyroelectric composite film for X-ray intensity detection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A novel in situ Polymerase chain reaction hybridisation assay for the direct detection of bovine herpesvirus type 5 in formalin-fixed, paraffin-embedded tissues

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An attack signature model to computer security intrusion detection

Internal and external computer network attacks or security threats occur according to standards and follow a set of subsequent steps, allowing to establish profiles or patterns. This well-known behavior is the basis of signature analysis intrusion detection systems. This work presents a new attack signature model to be applied on network-based intrusion detection systems engines. The AISF (ACME! Intrusion Signature Format) model is built upon XML technology and works on intrusion signatures handling and analysis, from storage to manipulation. Using this new model, the process of storing and analyzing information about intrusion signatures for further use by an IDS become a less difficult and standardized process.

Effects of Protein A in Detection of Canine Distemper Virus through immunosensor construction

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Space-based optical observation system suitable for micro satellite

The PhD research activity has taken place in the space debris field. In detail, it is focused on the possibility of detecting space debris from the space based platform. The research is focused at the same time on the software and the hardware of this detection system. For the software, a program has been developed for being able to detect an object in space and locate it in the sky solving the star field. For the hardware, the possibility of adapting a ground telescope for space activity has been considered and it has been tested on a possible electronic board.

Immuno-detection of anthrose containing tetrasaccharide in the exosporium of Bacillus anthracis and Bacillus cereus strains

AIMS: Bacillus anthracis strains of various origins were analysed with the view to describe intrinsic and persistent structural components of the Bacillus collagen-like protein of anthracis glycoprotein associated anthrose containing tetrasaccharide in the exosporium. METHODS AND RESULTS: The tetrasaccharide consists of three rhamnose residues and an unique monosaccharide--anthrose. As anthrose was not found in spores of related strains of bacteria, we envisioned the detection of B. anthracis spores based on antibodies against anthrose-containing polysaccharides. Carbohydrate-protein conjugates containing the synthetic tetrasaccharide, an anthrose-rhamnose disaccharide or anthrose alone were employed to immunize mice. All three formulations were immunogenic and elicited IgG responses with different fine specificities. All sera and monoclonal antibodies derived from tetrasaccharide immunized mice cross-reacted not only with spore lysates of a panel of virulent B. anthracis strains, but also with some of the B. cereus strains tested. CONCLUSIONS: Our results demonstrate that antibodies to synthetic carbohydrates are useful tools for epitope analyses of complex carbohydrate antigens and for the detection of particular target structures in biological specimens. SIGNIFICANCE AND IMPACT OF THE STUDY: Although not strictly specific for B. anthracis spores, antibodies against the tetrasaccharide may have potential as immuno-capturing components for a highly sensitive spore detection system.

Comparison of Various Methods of Estrus Detection in Synchronized Virgin Beef Heifers

Methods of heat detection were compared in the Mid- Crest Area Cattle Evaluation Program (MACEP) heifer development program in the 1998-breeding season. A total of 189 heifers from thirteen consignors entered the program on November 10, 1997. These heifers were condition scored, hip height measured, weighed, disposition scored, booster vaccinated, and treated for parasites at the time of arrival. Determination of the heifer’s mature weight was made and a target of 65% of their mature weight at breeding was established. The ration was designed to meet this goal. The heifers were kept in a dry lot until all heifers were AI bred once. The heifers were periodically weighed and condition scored to monitor their gains and the ration was adjusted as needed. The estrus synchronization program consisted of an oral progesterone analog for 14 days; 17 days after completion of the progesterone analog treatment a single injection of prostaglandin was given and the heifers were then estrus detected. Two concurrent methods of estrus detection were utilized: 1) Ovatec â electronic breeding probe (probe), 2) HeatWatchâ estrus detection system (HW), and 3) a combination of probe and HW. Probe readings were obtained each 12 hours and the heifers were continuously monitored for estrus activity using the HW system. The probe was used as the primary estrus detection method and the HW system was used as a back-up system. Those heifers that did not demonstrate any estrus signs prior to 96 hours post prostaglandin treatment were mass inseminated at 96 hours. Post AI breeding, 151 of the heifers were placed on pasture and ran with clean-up bulls for 60 days. The remaining heifers left the program after the AI breeding was completed. Pregnancy to the AI breeding was determined by ultrasound on June 29, 1998. Results from using both probe and HW were 60% pregnant by AI, probe alone was 32% pregnant by AI, and HW alone was 27% pregnant by AI. The result of mass insemination was 20% pregnant by AI.

The role of AKT-mediated phosphorylation in suppression of MAD1 and the development of new approach in protein complex detection

MAX dimerization protein 1 (MAD1) is a basic-helix-loop-helix transcription factors that recruits transcription repressor such as HDAC to suppress target genes transcription. It antagonizes to MYC because the promoter binding sites for MYC are usually also serve as the binding sites for MAD1 so they compete for it. However, the mechanism of the switch between MYC and MAD1 in turning on and off of genes' transcription is obscure. In this study, we demonstrated that AKT-mediated MAD1 phosphorylation inhibits MAD1 transcription repression function. The association between MAD1 and its target genes' promoter is reduced after been phosphorylated by AKT; therefore, consequently, allows MYC to occupy the binding site and activates transcription. Mutation of such phosphorylation site abrogates the inhibition from AKT. In addition, functional assays demonstrated that AKT suppressed MAD1-mediated transcription repression of its target genes hTERT and ODC. Cell cycle and cell growth were also been released from inhibition by MAD1 in the presents of AKT. Taken together, our study suggests that MAD1 is a novel substrate of AKT and AKT-mediated MAD1 phosphorylation inhibits MAD1function; therefore, activates MAD1 target genes expression. ^ Furthermore, analysis of protein-protein interaction is indispensable for current molecular biology research, but multiplex protein dynamics in cells is too complicated to be analyzed by using existing biochemical methods. To overcome the disadvantage, we have developed a single molecule level detection system with nanofluidic chip. Single molecule was analyzed based on their fluorescent profile and their profiles were plotted into 2 dimensional time co-incident photon burst diagram (2DTP). From this 2DTP, protein complexes were characterized. These results demonstrate that the nanochannel protein detection system is a promising tool for future molecular biology. ^