Jane Austen's lifelong health problems and final illness: New evidence points to a fatal Hodgkin's disease and excludes the widely accepted Addison's

Jane Austen is typically described as having excellent health until the age of 40 and the onset of a mysterious and fatal illness, initially identified by Sir Zachary Cope in 1964 as Addison's disease. Her biographers, deceived both by Cassandra Austen's destruction of letters containing medical detail, and the cheerful high spirits of the existing letters, have seriously underestimated the extent to which illness affected Austen's life. A medical history reveals that she was particularly susceptible to infection, and suffered unusually severe infective illnesses, as well as a chronic conjunctivitis that impeded her ability to write. There is evidence that Austen was already suffering from an immune deficiency and fatal lymphoma in January 1813, when her second and most popular novel, Pride and Prejudice, was published. Four more novels would follow, written or revised in the shadow of her increasing illness and debility. Whilst it is impossible now to conclusively establish the cause of her death, the existing medical evidence tends to exclude Addison's disease, and suggests there is a high possibility that Jane Austen's fatal illness was Hodgkin's disease, a form of lymphoma.

Prevalence and comorbidity of behavioral problems of children aged three to six: Results of the Braunschweiger Kindergartenstudie

Prevalence and comorbidity of behavioral problems of children aged three to six: Results of the Braunschweiger Kindergartenstudie Objectives: To analyze the frequency of behavioral and emotional problems and comorbidity of kindergarten children in Braunschweig as rated by their parents. Method: The analysis is part of the Braunschweiger Kindergartenstudie. In a sample of N = 809 children aged three to six the parents rated their children using a modified version of the Child Behavior Checklist/CBCL 4-18. Results: The prevalence rates range from 0.5% to 5.0%. The most frequent behavioral problems in kindergarten children were aggressive behavior and attention problems, followed by social problems. The study also provides bidirectional comorbidity rates. Conclusion: Finally the prevalence rates and the implications of the findings for prevention of behavioral problems in children are discussed.

Attitudes and management of alcohol problems in general practice: Descriptive analysis based on findings of a world health organization international collaborative survey

Aims: To determine if general practitioners' (GPs) experience of education on alcohol, support in their working environment for intervening with alcohol problems, and their attitudes have an impact on the number of patients they manage with alcohol problems. Methods: 1300 GPs from nine countries were surveyed with a postal questionnaire as part of a World Health Organization (WHO) collaborative study. Results: GPs who received more education on alcohol (OR = 1.5; 95% CI, 1.3-1.7), who perceived that they were working in a supportive environment (OR = 1.6; 95% CI, 1.4-1.9), who expressed higher role security in working with alcohol problems (OR = 2.0; 95% CI, 1.5-2.5) and who reported greater therapeutic commitment to working with alcohol problems (OR = 1.4: 95% CI, 1.1-1.7) were more likely to manage patients with alcohol-related harm. Conclusion: Both education and support in the working environment need to be provided to enhance the involvement of GPs in the management of alcohol problems.

Using distributions as statistical evidence in well-structured and ill-structured problems

Research has suggested that understanding in well-structured settings often does not transfer to the everyday, less-structured problems encountered outside of school. Little is known, beyond anecdotal evidence, about how teachers' consideration of distributions as evidence in well-structured settings compares with their use in ill-structured problem contexts. A qualitative study of preservice secondary teachers examined their use of distributions as evidence in four tasks of varying complexity and ill-structuredness. Results suggest that teachers' incorporation of distributions in well-structured settings does not imply that they will be incorporated in less structured problems (and vice-versa). Implications for research and teaching are discussed.

Trades and Graphs

The trade spectrum of a simple graph G is defined to be the set of all t for which it is possible to assemble together t copies of G into a simple graph H, and then disassemble H into t entirely different copies of G. Trade spectra of graphs have applications to intersection problems, and defining sets, of G-designs. In this investigation, we give several constructions, both for specific families of graphs, and for graphs in general.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Recreational fishing and fishing policies in the Netherlands and Australia: A comparative review

This article compares fisheries management, environmental problems and policies of the Netherlands and Australia. From this comparison lessons can be learned for countries that experience economic growth and on increase of leisure activity. In both countries, conflicts between the user groups, e.g. commercial and recreational fishers, are identified and the ways in which policymakers deal with these problems are outlined. Often suggested tools to address these problems are decision-making procedures based on a holistic framework in which economic, sociocultural, political/institutional, ecological aspects are included in the decision framework. Recreational fishing is today often the dominant factor in the resolution of these matters because of the relative economic, social and political power of recreational fishers as a group.