Acoustic Kappa-Density Fluctuation Waves in Suprathermal Kappa Function Fluids

We describe a new wave mode similar to the acoustic wave in which both density and velocity fluctuate. Unlike the acoustic wave in which the underlying distribution is Maxwellian, this new wave mode occurs when the underlying distribution is a suprathermal kappa function and involves fluctuations in the power law index, kappa. This wave mode always propagates faster than the acoustic wave with an equivalent effective temperature and becomes the acoustic wave in the Maxwellian limit as kappa goes to infinity.Comment: 11 pages, 2 figures, in press AS

What's unusual in online disease outbreak news?

Background: Accurate and timely detection of public health events of international concern is necessary to help support risk assessment and response and save lives. Novel event-based methods that use the World Wide Web as a signal source offer potential to extend health surveillance into areas where traditional indicator networks are lacking. In this paper we address the issue of systematically evaluating online health news to support automatic alerting using daily disease-country counts text mined from real world data using BioCaster. For 18 data sets produced by BioCaster, we compare 5 aberration detection algorithms (EARS C2, C3, W2, F-statistic and EWMA) for performance against expert moderated ProMED-mail postings. Results: We report sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), mean alerts/100 days and F1, at 95% confidence interval (CI) for 287 ProMED-mail postings on 18 outbreaks across 14 countries over a 366 day period. Results indicate that W2 had the best F1 with a slight benefit for day of week effect over C2. In drill down analysis we indicate issues arising from the granular choice of country-level modeling, sudden drops in reporting due to day of week effects and reporting bias. Automatic alerting has been implemented in BioCaster available from http://born.nii.ac.jp. Conclusions: Online health news alerts have the potential to enhance manual analytical methods by increasing throughput, timeliness and detection rates. Systematic evaluation of health news aberrations is necessary to push forward our understanding of the complex relationship between news report volumes and case numbers and to select the best performing features and algorithms

Schizophrenia in older adults

Although the number of persons over the age of 55 with schizophrenia is expected to double over the next 20 years, the research data on older people with schizophrenia is limited. This appears to be because until the middle of the 20th century, it was assumed that mental illness in older people was a part of the aging process and older people are often excluded from research investigations. There is a need for nursing research to explore how people with schizophrenia, as they age, learn to manage their problems, as well as how those who are first diagnosed with schizophrenia in later life adapt to their illness. Mental health nurses need to be cautious in assigning premature labels to older adults with mental illness that may lead to unsubstantiated assumptions about levels of disability. Instead, they should realize individual potential regarding undiscovered strengths and should attempt to create interventions that recognize and foster personal development for older adults with schizophrenia

Towards cross-lingual alerting for bursty epidemic events

Background: Online news reports are increasingly becoming a source for event based early warning systems that detect natural disasters. Harnessing the massive volume of information available from multilingual newswire presents as many challenges as opportunities due to the patterns of reporting complex spatiotemporal events. Results: In this article we study the problem of utilising correlated event reports across languages. We track the evolution of 16 disease outbreaks using 5 temporal aberration detection algorithms on text-mined events classified according to disease and outbreak country. Using ProMED reports as a silver standard, comparative analysis of news data for 13 languages over a 129 day trial period showed improved sensitivity, F1 and timeliness across most models using cross-lingual events. We report a detailed case study analysis for Cholera in Angola 2010 which highlights the challenges faced in correlating news events with the silver standard. Conclusions: The results show that automated health surveillance using multilingual text mining has the potential to turn low value news into high value alerts if informed choices are used to govern the selection of models and data sources. An implementation of the C2 alerting algorithm using multilingual news is available at the BioCaster portal http://born.nii.ac.jp/?page=globalroundup

Storage of Natural Language Sentences in a Hopfield Network

This paper look at how the Hopfield neural network can be used to store and recall patterns constructed from natural language sentences. As a pattern recognition and storage tool, the Hopfield neural network has received much attention. This attention however has been mainly in the field of statistical physics due to the model's simple abstraction of spin glass systems. A discussion is made of the differences, shown as bias and correlation, between natural language sentence patterns and the randomly generated ones used in previous experiments. Results are given for numerical simulations which show the auto-associative competence of the network when trained with natural language patterns.Comment: latex, 10 pages with 2 tex figures and a .bib file, uses nemlap.sty, to appear in Proceedings of NeMLaP-

A New California Oil Boom? Drilling the Monterey Shale

The Monterey Shale is a vast oil-bearing geologic formation stretching from Southern California almost as far north as San Francisco. The formation has largely been untapped due to its complexity and the challenges presented by the shale's unusual geology