Mineral implications in health issues of captive rhinos have received much attention lately. This study was undertaken to establish reference values for the mineral status of rhinos. Serum/plasma samples of free-ranging black (Diceros bicornis) and white (Ceratotherium simum) rhinos and of captive black, white, Indian (Rhinoceros unicornis), and Sumatran (Dicerorhinus sumatrensis) rhinos, as well as liver tissue samples of captive black, white, and Indian rhinos were analyzed for mineral content. Circulating mineral levels of free-ranging animals were subject to variation according to region. In free-ranging animals, high molybdenum (Mo) values compared to horse normals were striking. Captive animals displayed even higher circulating Mo concentrations. The significance of iron (Fe) overload in captive specimens of the browsing rhinos (black and Sumatran) was confirmed. Hepatic Fe levels increased in blacks with age. Although this Fe overload is suspected to be linked with diets, the data indicate that this is not due solely to an excessive dietary Fe supply. Whereas the grazing species (white and Indian) had high liver copper (Cu) levels, the browsing species had low to marginal liver Cu concentrations. Liver concentrations of K, Mg, Co, and Mo increased with age in captive black rhinos. Additional findings include high circulating Se levels in all rhino species.

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Some may argue that the proliferation of personal computers together with the widespread use of the Internet has brought many benefits to society.  The popularity of the internet and its associated online services continues to grow at an exponential rate and consequently, so does the number of avenues for potential exploitation.  Prior research has already established that sexual predators and social engineers use the Internet as a means to target and exploit individuals.  Indeed, previous studies highlight the significant threats faced by users of instant messaging and social networking facilities.  Online role-playing games and virtual environments provide yet another platform for users to interact with one another.   Evidence suggests that subscribers of such services often become so immersed in a fantasy world that their ability to differentiate between the virtual and real world is reduced.  This monograph investigates the level of threat faced by users of  virtual environments and online role-playing games.  The study made use of an online survey to assess the current level of awareness and understanding amongst individuals who spend excessive amounts of time engaging in such environments.

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The creation of new knowledge from manipulating and analysing existing knowledge is one of the primary objectives of any cognitive system. Most of the effort on Big Data research has been focussed upon Volume and Velocity, while Variety, “the ugly duckling” of Big Data, is often neglected and difficult to solve. A principal challenge with Variety is being able to understand and comprehend the data. This paper proposes and evaluates an automated approach for metadata identification and enrichment in describing Big Data. The paper focuses on the use of self-learning systems that will enable automatic compliance of data against regulatory requirements along with the capability of generating valuable and readily usable metadata towards data classification. Two experiments towards data confidentiality and data identification were conducted in evaluating the feasibility of the approach. The focus of the experiments was to confirm that repetitive manual tasks can be automated, thus reducing the focus of a Data Scientist on data identification and thereby providing more focus towards the extraction and analysis of the data itself. The origin of the datasets used were Private/Business and Public/Governmental and exhibited diverse characteristics in relation to the number of files and size of the files. The experimental work confirmed that: (a) the use of algorithmic techniques attributed to the substantial decrease in false positives regarding the identification of confidential information; (b) evidence that the use of a fraction of a data set along with statistical analysis and supervised learning is sufficient in identifying the structure of information within it. With this approach, the issues of understanding the nature of data can be mitigated, enabling a greater focus on meaningful interpretation of the heterogeneous data.