A new sabellid that infests the shells of molluscs and its implications for abalone mariculture

Bibliography: leaves 76-87.Infestations of sabellid polychaetes were found in South African farmed abalone in 1994. Growth experiments confirmed that infested abalone had reduced growth rates. Surveys of both the intertidal and subtidal region at various locations around the South African coastline revealed that the sabellid was endemic to the region. It occurred in a range of mollusc species, but some species were more susceptible than others. The fact that some molluscan species became infested with worms only when exposed to them in the laboratory suggests that environmental factors may play a role in controlling natural levels of infestation. Different host selection on the East Coast of South Africa suggests that there may be more than one species of worm. Larvae disperse by crawling and settle at the growing edge of the shell underneath the mantle. Although the larvae are benthic, there is limited transfer of larvae through the water column, which can result in export of larvae from infested tanks. The risks of dispersal are discussed in a farm management context. Abalone kept in more hygienic laboratory conditions tended to grow faster than in farm tanks and had lower levels of infestation by sabellid larvae. This was attributed to the sabellids being less fecund under these conditions. This was probably caused by lack of food as evidenced in a separate starvation experiment. Based on experimental observations and farm experience it was possible to make management recommendations to limit the effect of the sabellid Quantitative measurement taols to assess the impact and productivity of sabellid infestations were developed Management of infestations on a farm requires a combination of inhibiting transfer and productivity of the worm and also promoting growth of the abalone. However, the constant risk of exposure to natural populations of sabellids necessitates the development oJ a treatment to eradicate sabellid infestations. The use of microcapsules as a drug delivery mechanism was explored and holds promise. Gelatin microcapsules, oil immulsions and liposomes were experimented with. All formulations were successfully produced in the desired size range of 2-30 μm. In all cases the sabellid'l readily ingested the capsules. Various toxins were successfully added to the formulations, but none of the treatments were able to harm the sabellids. The problem appeared to be the short passage time within the guts and the inability of the sabellids to digest the outer encapsulating layers to expose the toxins. More research is required to find the correct combination of toxin and delivery mechanism

MFIRE-2: A Multi Agent System for Flow-based Intrusion Detection Using Stochastic Search

Detecting attacks targeted against military and commercial computer networks is a crucial element in the domain of cyberwarfare. The traditional method of signature-based intrusion detection is a primary mechanism to alert administrators to malicious activity. However, signature-based methods are not capable of detecting new or novel attacks. This research continues the development of a novel simulated, multiagent, flow-based intrusion detection system called MFIRE. Agents in the network are trained to recognize common attacks, and they share data with other agents to improve the overall effectiveness of the system. A Support Vector Machine (SVM) is the primary classifier with which agents determine an attack is occurring. Agents are prompted to move to different locations within the network to find better vantage points, and two methods for achieving this are developed. One uses a centralized reputation-based model, and the other uses a decentralized model optimized with stochastic search. The latter is tested for basic functionality. The reputation model is extensively tested in two configurations and results show that it is significantly superior to a system with non-moving agents. The resulting system, MFIRE-2, demonstrates exciting new network defense capabilities, and should be considered for implementation in future cyberwarfare applications

Tinospora cordifolia (GILOY): A MAGICAL SHRUB

Medicinal plants have been used as natural medicines, since prehistoric times because of the presence of natural chemical constituents. Among them Tinospora cordifolia has a wide array of bioactive principles as well as it has been proven medicinally important plant, have not received considerable scientific attention. The plant is commonly used as traditional ayurvedic medicine and has several therapeutic properties such as jaundice, rheumatism, urinary disorder, skin diseases, diabetes, anemia, inflammation, allergic condition, anti-periodic, radio protective properties, etc. A special focus has been made on its health benefits in treating endocrine and metabolic disorders and its potential as an immune booster. The stem of this plant is generally used to cure diabetes by regulating level of blood glucose. T. cordifolia is well known for its immunomodulatory        response. This property has been well documented by scientists. A large variety of compounds which are responsible for immunomodulatory and cytotoxic effects are 11-hydroxymuskatone, N-methyle-2-pyrrolidone, Nformylannonain, cordifolioside A, magnoflorine, tinocordioside and syringin. Root extract of this plant has been shown a decrease in the regular resistance against HIV. The active principles from T. cordifolia enhance host immune system by increasing immunoglobulin and blood leukocyte levels and by the stimulation of stem cell proliferation. Tinospora cordifolia has been used in indigenous systems of medicine, as indicated in various classical texts of Ayurvedic System of Medicine, viz. Charak, Sushrut and Ashtang Hridaya and other ancient treaties

A Multi Agent System for Flow-Based Intrusion Detection

The detection and elimination of threats to cyber security is essential for system functionality, protection of valuable information, and preventing costly destruction of assets. This thesis presents a Mobile Multi-Agent Flow-Based IDS called MFIREv3 that provides network anomaly detection of intrusions and automated defense. This version of the MFIRE system includes the development and testing of a Multi-Objective Evolutionary Algorithm (MOEA) for feature selection that provides agents with the optimal set of features for classifying the state of the network. Feature selection provides separable data points for the selected attacks: Worm, Distributed Denial of Service, Man-in-the-Middle, Scan, and Trojan. This investigation develops three techniques of self-organization for multiple distributed agents in an intrusion detection system: Reputation, Stochastic, and Maximum Cover. These three movement models are tested for effectiveness in locating good agent vantage points within the network to classify the state of the network. MFIREv3 also introduces the design of defensive measures to limit the effects of network attacks. Defensive measures included in this research are rate-limiting and elimination of infected nodes. The results of this research provide an optimistic outlook for flow-based multi-agent systems for cyber security. The impact of this research illustrates how feature selection in cooperation with movement models for multi agent systems provides excellent attack detection and classification

A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

The rising sophistication of cyber threats as well as the improvement of physical computer network properties present increasing challenges to contemporary Intrusion Detection (ID) techniques. To respond to these challenges, a multi agent system (MAS) coupled with flow-based ID techniques may effectively complement traditional ID systems. This paper develops: 1) a scalable software architecture for a new, self-organized, multi agent, flow-based ID system; and 2) a network simulation environment suitable for evaluating implementations of this MAS architecture and for other research purposes. Self-organization is achieved via 1) a reputation system that influences agent mobility in the search for effective vantage points in the network; and 2) multi objective evolutionary algorithms that seek effective operational parameter values. This paper illustrates, through quantitative and qualitative evaluation, 1) the conditions for which the reputation system provides a significant benefit; and 2) essential functionality of a complex network simulation environment supporting a broad range of malicious activity scenarios. These results establish an optimistic outlook for further research in flow-based multi agent systems for ID in computer networks

Identifying the locations, movement and habitat of the European fire ant, Myrmica rubra : an invasive species in the urban/suburban environment of Halifax, Nova Scotia

v, 119 leaves : ill. (chiefly col.), col. maps ; 29 cm.Includes abstract.Includes bibliographical references (leaves 98-105).Myrmica rubra , also known as the European Fire Ant, is a pestiferous, invasive species in North America. It administers a painful sting and causes many residents to be unable to use their outdoor property. In this study, nest preferences in the urban/suburban environment were investigated. Habitat characteristics such as vegetation, substrate and edaphic factors were compared to nest densities. The species showed high adaptability to all nest features. However, the majority of nests were found in ground flora roots or against a hard substrate in a slightly acidic soil. This differs from nest sites in rural invaded areas where most nests are found in leaf litter or wood. A secondary study measured densities of ants using sucrose bait stations. The results were mapped using GIS and showed a correlation between locations of nests and densities in vials. An exponential increase of residents encountering this species indicates an irruption is occurring

A framework for the application of network telescope sensors in a global IP network

The use of Network Telescope systems has become increasingly popular amongst security researchers in recent years. This study provides a framework for the utilisation of this data. The research is based on a primary dataset of 40 million events spanning 50 months collected using a small (/24) passive network telescope located in African IP space. This research presents a number of differing ways in which the data can be analysed ranging from low level protocol based analysis to higher level analysis at the geopolitical and network topology level. Anomalous traffic and illustrative anecdotes are explored in detail and highlighted. A discussion relating to bogon traffic observed is also presented. Two novel visualisation tools are presented, which were developed to aid in the analysis of large network telescope datasets. The first is a three-dimensional visualisation tool which allows for live, near-realtime analysis, and the second is a two-dimensional fractal based plotting scheme which allows for plots of the entire IPv4 address space to be produced, and manipulated. Using the techniques and tools developed for the analysis of this dataset, a detailed analysis of traffic recorded as destined for port 445/tcp is presented. This includes the evaluation of traffic surrounding the outbreak of the Conficker worm in November 2008. A number of metrics relating to the description and quantification of network telescope configuration and the resultant traffic captures are described, the use of which it is hoped will facilitate greater and easier collaboration among researchers utilising this network security technology. The research concludes with suggestions relating to other applications of the data and intelligence that can be extracted from network telescopes, and their use as part of an organisation’s integrated network security system