Sustainable approaches for stormwater quality improvements with experimental geothermal paving systems

This article has been made available through the Brunel Open Access Publishing Fund.This research assesses the next generation of permeable pavement systems (PPS) incorporating ground source heat pumps (geothermal paving systems). Twelve experimental pilot-scaled pavement systems were assessed for its stormwater treatability in Edinburgh, UK. The relatively high variability of temperatures during the heating and cooling cycle of a ground source heat pump system embedded into the pavement structure did not allow the ecological risk of pathogenic microbial expansion and survival. Carbon dioxide monitoring indicated relatively high microbial activity on a geotextile layer and within the pavement structure. Anaerobic degradation processes were concentrated around the geotextile zone, where carbon dioxide concentrations reached up to 2000 ppm. The overall water treatment potential was high with up to 99% biochemical oxygen demand removal. The pervious pavement systems reduced the ecological risk of stormwater discharges and provided a low risk of pathogen growth

Atmospheric freeze drying assisted by power ultrasound

[EN] Atmospheric freeze drying (AFD) is considered an alternative to vacuum freeze drying to keep the quality of fresh product. AFD allows continuous drying reducing fix and operating costs, but presents, as main disadvantage, a long drying time required. The application of power ultrasound (US) can accelerate AFD process. The main objective of the present study was to evaluate the application of power ultrasound to improve atmospheric freeze drying of carrot. For that purpose, AFD experiments were carried out with carrot cubes (10 mm side) at constant air velocity (2 ms-1), temperature (-10ºC) and relative humidity (10%) with (20.5 kWm-3, USAFD) and without (AFD) ultrasonic application. A diffusion model was used in order to quantify the influence of US in drying kinetics. To evaluate the quality of dry products, rehydration capacity and textural properties were determined. The US application during AFD of carrot involved the increase of drying rate. The effective moisture diffusivity identified in USAFD was 73% higher than in AFD experiments. On the other hand, the rehydration capacity was higher in USAFD than in AFD and the hardness of dried samples did not show significant (p<0.05) differences. Therefore, US application during AFD significantly (p<0.05) sped-up the drying process preserving the quality properties of the dry product.Santacatalina Bonet, JV.; Carcel Carrión, JA.; Simal, S.; García Pérez, JV.; Mulet Pons, A. (2012). Atmospheric freeze drying assisted by power ultrasound. IOP Conference Series: Materials Science and Engineering. 42:5-8. doi:10.1088/1757-899X/42/1/012021S5842Stawczyk, J., Li, S., Witrowa-Rajchert, D., & Fabisiak, A. (2006). Kinetics of Atmospheric Freeze-drying of Apple. Transport in Porous Media, 66(1-2), 159-172. doi:10.1007/s11242-006-9012-4Wolff, E., & Gibert, H. (1990). ATMOSPHERIC FREEZE-DRYING PART 1 : DESIGN, EXPERIMENTAL INVESTIGATION AND ENERGY-SAVING ADVANTAGES. Drying Technology, 8(2), 385-404. doi:10.1080/07373939008959890García-Pérez, J. V., Cárcel, J. A., Benedito, J., & Mulet, A. (2007). Power Ultrasound Mass Transfer Enhancement in Food Drying. Food and Bioproducts Processing, 85(3), 247-254. doi:10.1205/fbp07010Gallego-Juárez, J. A., Riera, E., de la Fuente Blanco, S., Rodríguez-Corral, G., Acosta-Aparicio, V. M., & Blanco, A. (2007). Application of High-Power Ultrasound for Dehydration of Vegetables: Processes and Devices. Drying Technology, 25(11), 1893-1901. doi:10.1080/07373930701677371Hassini, L., Azzouz, S., Peczalski, R., & Belghith, A. (2007). Estimation of potato moisture diffusivity from convective drying kinetics with correction for shrinkage. Journal of Food Engineering, 79(1), 47-56. doi:10.1016/j.jfoodeng.2006.01.02

Recent developments of control charts and identification of big data sources and future trends of current research

Control charts are one of the principal tools to monitor dynamic processes with the aim of rapid identification of changes in the behaviour of these processes. Such changes are usually associated with a move from an in-control condition to an out-of-control condition. The paper briefly reviews the historical origins and includes examples of recent developments, focussing on their use in fields different from the industrial applications in which they were initially derived and often employed. It also focusses on cases which depart from the commonly used Gaussian assumption and then considers potential effects of the big data revolution on future uses. A bibliometric analysis is also presented to identify distinct groups of research themes, including emerging and underdeveloped areas, which are hence potential topics for future research

Predictors of serum dioxin levels among adolescent boys in Chapaevsk, Russia: A cross-sectional pilot study

BACKGROUND: Toxicological studies and limited human studies have demonstrated associations between exposure to polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and polychlorinated biphenyls (PCBs) and adverse developmental and reproductive health effects. Given that children may be particularly susceptible to reproductive and developmental effects of organochlorines, and the paucity of information available regarding childhood exposures to dioxins in particular, we undertook a pilot study to describe the distribution of, and identify potential predictors of exposure to, dioxin-like compounds and dioxins among adolescent boys in Chapaevsk, Russia. The pilot study was also designed to guide the development of a large prospective cohort study on the relationship of exposure to PCDDs, PCDFs, and PCBs with growth and pubertal development in peri-pubertal Chapaevsk boys. METHODS: 221 boys age 14 to 17 participated in the pilot study. Each of the boys, with his mother, was asked to complete a nurse-administered detailed questionnaire on medical history, diet, and lifestyle. The diet questions were used to measure the current and lifetime consumption of locally grown or raised foods. Blood samples from 30 of these boys were sent to the Centers for Disease Control and Prevention (CDC) for analysis of dioxins, furans and PCBs. RESULTS: The median (25(th), 75(th )percentile) concentrations for total PCDDs, PCDFs and coplanar PCBs were 95.8 pg/g lipids (40.9, 144), 33.9 pg/g lipids (20.4, 61.8), and 120 pg/g lipids (77.6, 157), respectively. For WHO-TEQs, the median (25(th), 75(th )percentile) for total PCDDs, PCDFs, and coplanar PCBs were 0.29 (0.1, 9.14), 7.98 (5.27, 12.3), and 7.39 (4.51, 11.9), respectively. Although TCDD was largely non-detectable, two boys had high TCDD levels (17.9 and 21.7 pg/g lipid). Higher serum levels of sum of dioxin-like compounds and sum of dioxin TEQs were positively associated with increased age, consumption of fish, local meats other than chicken, PCB 118, and inversely with weeks of gestation. CONCLUSION: The total TEQs among Chapaevsk adolescents were higher than most values previously reported in non-occupationally exposed populations of comparable or even older ages. Dietary consumption of local foods, as well as age and weeks of gestation, predicted dioxin exposure in this population

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

for the ANZICS Centre for Outcome and Resource Evaluation (CORE) of the Australian and New Zealand Intensive Care Society (ANZICS)BACKGROUND Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. METHODS Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. RESULTS The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag ₄₀ and 35% had autocorrelation through to lag ₄₀; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. CONCLUSIONS The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.John L Moran, Patricia J Solomo

Time Series Models for Forecasting Wastewater Treatment Plant Performance

This paper describes a time series modeling procedure that can be useful for calculating predictions, with confidence intervals, of effluent quality one to five days ahead, and it explains how these predictions can serve as an early warning of process upsets that will sometimes enable an operator to take preventive action. The time series model has the form of an exponentially weighted moving average (EWMA). The interpretation of the model is that the response of the system can be predicted by deviations from the EWMA smoothed values of the predictor variables