Quantifying the performance of a top-down natural ventilation Windcatcher™

Estimating the performance of a natural ventilation system is very important if one is to correctly size the system for a particular application. Estimating the performance of a Windcatcher™ is complicated by the complex flow patterns that occur during the top-down ventilation process. Methods for predicting Windcatcher™ performance can currently be separated into simplistic analytic methods such as the envelope flow model and the use of complex and time consuming numerical methods such as CFD. This article presents an alternative semi-empirical approach in which a detailed analytic model makes use of experimental data in the literature in order to provide a fast but accurate estimate of Windcatcher™ performance. Included in the model are buoyancy effects, the effect of changes in wind speed and direction, as well as the treatment of sealed and unsealed rooms. The semi-empirical predictions obtained are shown to compare well with measured data and air buoyancy is shown only to be significant at relatively low flow velocities. In addition, a very simple algorithm is proposed for quantifying the air flow rates from a room induced by a Windcatcher™ in the absence of buoyancy effects

Changes in cytokine production during pregnancy in patients with Graves' disease

In order to investigate the role of type 1 and type 2 cytokines in the remission of Graves' disease (GD) during pregnancy, spontaneous and mitogen-stimulated production of interleukin (IL)-4, IL-6, IL-10, IL-12, interferon-γ (IFN-γ), and tumour necrosis factor-α (TNF-α) were measured by enzyme-linked immunospot assay of peripheral blood mononuclear cells from 10 pregnant women with GD, 8 healthy pregnant women, and 10 healthy nonpregnant women. Tests were performed in the first, second, and third trimesters of pregnancy and 10-17 weeks after delivery. IL-4 production was not affected greatly by normal or GD pregnancy, whereas IFN-γ production was suppressed throughout pregnancy but returned to normal levels after delivery in both controls and patients. IL-6 and TNF-α tended to be higher in GD pregnancy than normal pregnancy, especially in the second and third trimesters. Controls had raised IL-10 in the first trimester with a return to normal levels by the third trimester, whereas patients had raised levels throughout pregnancy. IL-12 levels were suppressed to a greater extent in control than Graves' pregnancy, especially during the second and third trimesters. Ratios of IL10:IL12 in phytohemaglutinin (PHA)-stimulated cultures were much lower in GD than normal pregnancy and cross-regulation of IL-10 and IL-12 may be deficient in GD.published_or_final_versio

Changes in cytokine production in healthy subjects practicing Guolin Qigong : a pilot study

BACKGROUND: Guolin Qigong is a combination of meditation, controlled breathing and physical movement designed to control the vital energy (qi) of the body and consequently to improve spiritual, physical and mental health. Practice of Qigong has been reported to alter immunological function, but there have been few studies of its effects on cytokines, the key regulators of immunity. METHODS: Numbers of peripheral blood cytokine-secreting cells were determined by ELISPOT in 19 healthy volunteers aged 27 – 55, before they were taught the practice of Qigong and after 3, 7 and 14 weeks of daily practice. The effect of Qigong on blood cortisol was also examined. RESULTS: Numbers of IL4 and IL12-secreting cells remained stable. IL6 increased at 7 weeks and TNFα increased in unstimulated cultures at 3 and 7 weeks but decreased at these times in LPS and SAC-stimulated cultures. Of particular interest, IFNγ-secreting cells increased and IL10-secreting cells decreased in PHA-stimulated cultures, resulting in significant increases in the IFNγ:IL10 ratio. Cortisol, a known inhibitor of type 1 cytokine production, was reduced by practicing Qigong. CONCLUSION: These preliminary studies in healthy subjects, although not necessarily representative of a randomized healthy population and not including a separate control group, have indicated that blood levels of the stress-related hormone cortisol may be lowered by short-term practice of Qigong and that there are concomitant changes in numbers of cytokine-secreting cells. Further studies of the effect of Qigong in patients with clinical diseases known to be associated with type 2 cytokine predominance are merited

Indoor air quality in U.K. school classrooms ventilated by natural ventilation windcatchers

The provision of good IAQ in schools is important both for the health of students and in maximising educational achievement. It is, however, common for school classrooms to be significantly under-ventilated and this can lead to high levels of CO2 and other pollutants. Natural ventilation offers the potential to improve IAQ within schools whilst, at the same time reducing running and maintenance costs. Accordingly, this article examines a natural ventilation strategy based on the use of a roof mounted split-duct Windcatcher ventilator. Here, 16 U.K. classrooms are studied and CO2, temperature, relative humidity and ventilation rates are measured for the summer and winter seasons. Results show that, during the summer months, the ventilator is capable of significantly improving ventilation rates as well as reducing CO2 levels, especially when used in combination with open windows. However, in the winter months, the ventilator is seen not to open for a sufficient length of time and so CO2 levels rise above those required in the standards. Thus, the ventilator is shown to have the potential to improve IAQ within school classrooms, but the operation of the ventilator should be carefully controlled in order to realise these benefits. It is common for ventilation rates in school classrooms to fall below the levels required by relevant standards. The data presented here demonstrates that by using a top-down natural ventilation Windcatcher as part of a well designed natural ventilation strategy, ventilation rates in school classrooms can be significantly improved

Mineralogical sources of groundwater fluoride in Archaen bedrock/regolith aquifers: Mass balances from southern India and north-central Sri Lanka

STUDY REGION: The Maheshwaram and Waipally catchments of Andhra Pradesh, India, and the Plonnaruwa catchment of north-central Sri Lanka. STUDY FOCUS: The distribution of F across eight crystalline phases and between the bedrock and the regolith at eleven sites in three catchments is documented. Mineral contributions to F release during weathering and regolith development are quantified. NEW HYDROLOGICAL INSIGHTS FOR THE REGION: An estimate of weathering duration for the in situ regolith in Andhra Pradesh, 250-380 Ka, is close to a previous estimate for southern India. Partial or total destruction of the primary F-bearing bedrock minerals and consistent depletion of F in the remnant minerals result in a much reduced total F content in the regolith. Leaching experiments and field relationships, however, indicate a greater potential for F mobilisation to groundwater from the regolith than the bedrock. Schemes for managed aquifer recharge should beware the risk of mobilising additional F to groundwater

Advances in reproductive biology and seed production systems of Eucalyptus: The case of Eucalyptus globulus

Eucalyptus globulus is the main eucalypt species grown in Australian plantations. The focus on seedling deployment systems, coupled with exploitation of large, open-pollinated base populations for breeding purposes over the last two decades, has required a detailed understanding of the reproductive biology of this species. We review our research on the reproductive biology of E. globulus, with a focus on it’s breeding system and advances made in seed production systems. While most improved seed is still obtained from open-pollinated seedling or grafted seed orchards, the development of the one-stop/single-visit pollination procedure has revolutionised the breeding and deployment of this species. The reduced costs of controlled pollination has meant full pedigree-control can now be maintained in large advanced generation breeding populations and E. globulus is one of the few eucalypt species where large-scale production of manually pollinated seed for family forestry is being undertaken

Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults

This is the final version. Available from the publisher via the DOI in this record.The data that support the findings of this study are available from University of Exeter Medical School/Oxford University but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of University of Exeter Medical School/Oxford University. R code is made available in supplementary file (see Additional file 2).Background: There is much interest in the use of prognostic and diagnostic prediction models in all areas of clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been increasing at the expense of classic statistical models. Previous studies have compared performance between these two approaches but their findings are inconsistent and many have limitations. We aimed to compare the discrimination and calibration of seven models built using logistic regression and optimised machine learning algorithms in a clinical setting, where the number of potential predictors is often limited, and externally validate the models. Methods: We trained models using logistic regression and six commonly used machine learning algorithms to predict if a patient diagnosed with diabetes has type 1 diabetes (versus type 2 diabetes). We used seven predictor variables (age, BMI, GADA islet-autoantibodies, sex, total cholesterol, HDL cholesterol and triglyceride) using a UK cohort of adult participants (aged 18–50 years) with clinically diagnosed diabetes recruited from primary and secondary care (n = 960, 14% with type 1 diabetes). Discrimination performance (ROC AUC), calibration and decision curve analysis of each approach was compared in a separate external validation dataset (n = 504, 21% with type 1 diabetes). Results: Average performance obtained in internal validation was similar in all models (ROC AUC ≥ 0.94). In external validation, there were very modest reductions in discrimination with AUC ROC remaining ≥ 0.93 for all methods. Logistic regression had the numerically highest value in external validation (ROC AUC 0.95). Logistic regression had good performance in terms of calibration and decision curve analysis. Neural network and gradient boosting machine had the best calibration performance. Both logistic regression and support vector machine had good decision curve analysis for clinical useful threshold probabilities. Conclusion: Logistic regression performed as well as optimised machine algorithms to classify patients with type 1 and type 2 diabetes. This study highlights the utility of comparing traditional regression modelling to machine learning, particularly when using a small number of well understood, strong predictor variables.National Institute for Health Research (NIHR