Zipf and Type-Token rules for the English, Spanish, Irish and Latin languages

The Zipf curves of log of frequency against log of rank for a large English corpus of 500 million word tokens, 689,000 word types and for a large Spanish corpus of 16 million word tokens, 139,000 word types are shown to have the usual slope close to –1 for rank less than 5,000, but then for a higher rank they turn to give a slope close to –2. This is apparently mainly due to foreign words and place names. Other Zipf curves for highlyinflected Indo-European languages, Irish and ancient Latin, are also given. Because of the larger number of word types per lemma, they remain flatter than the English curve maintaining a slope of –1 until turning points of about ranks 30,000 for Irish and 10,000 for Latin. A formula which calculates the number of tokens given the number of types is derived in terms of the rank at the turning point, 5,000 for both English and Spanish, 30,000 for Irish and 10,000 for Latin.

Recent applications of Chemical Imaging to pharmaceutical process monitoring and quality control

Chemical Imaging (CI) is an emerging platform technology that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Vibrational spectroscopic methods, such as Near Infrared (NIR) and Raman spectroscopy, combined with imaging are particularly useful for analysis of biological/pharmaceutical forms. The rapid, non-destructive and non-invasive features of CI mark its potential suitability as a process analytical tool for the pharmaceutical industry, for both process monitoring and quality control in the many stages of drug production. This paper provides an overview of CI principles, instrumentation and analysis. Recent applications of Raman and NIR-CI to pharmaceutical quality and process control are presented; challenges facing Cl implementation and likely future developments in the technology are also discussed. (C) 2007 Elsevier B.V. All rights reserved.

Controls on the contemporary distribution of lake thecamoebians (testate amoebae) in the Greater Toronto Area and their potential as water quality indicators.

Thecamoebians were examined from 71 surface sediment samples collected from 21 lakes and ponds in the Greater Toronto Area to (1) elucidate the controls on faunal distribution in modern lake environments; and (2) to consider the utility of thecamoebians in quantitative studies of water quality change. This area was chosen because it includes a high density of kettle and other lakes which are threatened by urban development and where water quality has deteriorated locally as a result of contaminant inputs, particularly nutrients. Fifty-eight samples yielded statistically significant thecamoebian populations. The most diverse faunas (highest Shannon Diversity Index values) were recorded in lakes beyond the limits of urban development, although the faunas of all lakes showed signs of sub-optimal conditions. The assemblages were divided into five clusters using Q-mode cluster analysis, supported by Detrended Correspondence Analysis. Canonical Correspondence Analysis (CCA) was used to examine species-environment relationships and to explain the observed clusterings. Twenty-four measured environmental variables were considered, including water property attributes (e.g., pH, conductivity, dissolved oxygen), substrate characteristics, sediment-based phosphorus (Olsen P) and 11 environmentally available metals. The thecamoebian assemblages showed a strong association with phosphorus, reflecting the eutrophic status of many of the lakes, and locally to elevated conductivity measurements, which appear to reflect road salt inputs associated with winter de-icing operations. Substrate characteristics, total organic carbon and metal contaminants (particularly Cu and Mg) also influenced the faunas of some samples. A series of partial CCAs show that of the measured variables, sedimentary phosphorus has the largest influence on assemblage distribution, explaining 6.98% (P < 0.002) of the total variance. A transfer function was developed for sedimentary phosphorus (Olsen P) using 58 samples from 15 of the studied lakes. The best performing model was based on weighted averaging with inverse deshrinking (WA Inv, r jack 2= 0.33, RMSEP = 102.65 ppm). This model was applied to a small modern thecamoebian dataset from a eutrophic lake in northern Ontario to predict phosphorus and performed satisfactorily. This preliminary study confirms that thecamoebians have considerable potential as quantitative water quality indicators in urbanising regions, particularly in areas influenced by nutrient inputs and road salts.

Evaluation of the Q-method as a method of public participation in the selection of sustainable development indicators

The complexity of sustainable development means that it is often difficult to evaluate and communicate the concept effectively. One standard method to reduce complexity and improve Communication, while maintaining scientific objectivity, is to use selected indicators. The aim of this paper is to describe and evaluate a process Of public participation in the selection of sustainable development indicators that utilised the Q-method for discourse analysis. The Q-method was Utilised to combine public opinion with technical expertise to create a list of technically robust indicators that would be relevant to the public, The method comprises statement collection, statement analysis, Q-sorts and Q-sort analysis. The results of the Q-method generated a list of statements for which a preliminary list of indicators was then developed by a team of experts from the fields of environmental science, sustainable development and Psychology. Subsequently members of the public evaluated the preliminary list of indicators, to select a final list of indicators that were both technically sound and incorporated the views of the public. The Utilisation of the Q-method in this process was evaluated using previously published criteria. The application of the Q-method in this context needs to be considered not only by the quality of the indicators developed, but also from the perspective of the benefit of the process to the participants. it was concluded that the Q-method provided an effective framework for public participation in the selection of indicators as it allowed the public to discuss Sustainable development in familiar language and in the context of their daily lives. By combining this information with expert input, a list of technically robust indicators that resonate with the public was developed. The results demonstrated that many citizens are not aware Of Sustainable development, and if it is to be successfully communicated to them, then indicators and policy need to be couched in terms familiar and relevant to citizen and communities. (C) 2009 Elsevier Ltd. All rights reserved.

Energy monitoring and quality control of a single screw extruder

Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

The effect of multiple chronic conditions on self-rated health, disability and quality of life among the older populations of Northern Ireland and the Republic of Ireland: a comparison of two nationally representative cross-sectional surveys

Objectives: Multimorbidity is common in the older population, but the impact of combinations of chronic conditions on disability and quality of life (QoL) is not well known. This analysis explores the effect of specific combinations of chronic diseases on disability, QoL and self-rated health (SRH).

Design: We used data from two population representative cross-sectional studies, the Northern Ireland Health and Social Wellbeing Survey (NIHSWS) 2005 and the Survey of Lifestyle, Attitudes and Nutrition (SLAN) 2007 (conducted in the Republic of Ireland).

Setting: Randomly selected community-living participants were interviewed at home.

Participants: A total of 6159 participants aged 50 years and older were included in the analysis.

Outcome measures: Chronic conditions were classified as cardiovascular disease, chronic pain,diabetes or respiratory disease. Interaction terms estimated by logistic regression were used to examine the effects of multiple chronic conditions on disability, SRH and QoL.

Results: Each chronic condition group was correlated with each of the others after adjusting for sociodemographic factors. Those from Northern Ireland were more likely to report a limitation in daily activities (45%) compared to those from the Republic of Ireland (21%). Each condition had an independent effect on disability, SRH and QoL, and those with multiple chronic conditions reported the worst outcomes. However, there were no statistically significant positive interactions between chronic condition groups with respect to any outcome.

Conclusions: Chronic conditions affect individuals largely independent of each other with respect to their effect on disability, SRH and QoL. However, a significant proportion of the population aged 50 years and over across the island of Ireland lives with multimorbidity,and this group is at the highest risk of disability, poor SRH and poor QoL.