Automatic real-time interpolation of radiation hazards: prototype and system architecture considerations

Detecting and monitoring the development of radioactive releases in the atmosphere is important. In many European countries monitoring networks have been established to perform this task. In the Netherlands the National Radioactivity Monitoring network (NRM) was installed. Currently, point maps are used to interpret the data from the NRM. Automatically generating maps in realtime would improve the interpretation of the data by giving the user a clear overview of the present radiological situation and provide an estimate of the radioactivity level at unmeasured locations. In this paper we present a prototype system that automatically generates real-time maps of radioactivity levels and presents results in an interoperable way through a Web Map Service. The system defines a first step towards a emergency management system and is suited primarily for data without large outliers. The automatic interpolation is done using universal kriging in combination with an automatic variogram fitting procedure. The focus is on mathematical and operational issues and on architectural considerations on how to improve the interoperability and portability of the prototype system

Complete synchronization of chaotic atmospheric models by connecting only a subset of state space

Connected chaotic systems can, under some circumstances, synchronize their states with an exchange of matter and energy between the systems. This is the case for toy models like the Lorenz 63, and more complex models. In this study we perform synchronization experiments with two connected quasi-geostrophic (QG) models of the atmosphere with 1449 degrees of freedom. The purpose is to determine whether connecting only a subset of the model state space can still lead to complete synchronization (CS). In addition, we evaluated whether empirical orthogonal functions (EOF) form efficient basis functions for synchronization in order to limit the number of connections. In this paper, we show that only the intermediate spectral wavenumbers (5-12) need to be connected in order to achieve CS. In addition, the minimum connection timescale needed for CS is 7.3 days. Both the connection subset and the connection timescale, or strength, are consistent with the time and spatial scales of the baroclinic instabilities in the model. This is in line with the fact that the baroclinic instabilities are the largest source of divergence between the two connected models. Using the Lorenz 63 model, we show that EOFs are nearly optimal basis functions for synchronization. The QG model results show that the minimum number of EOFs that need to be connected for CS is a factor of three smaller than when connecting the original state variables

Архівна Евристика: практичні аспекти

Для молодої генерації сучасних дослідників здійснення ефективного пошуку інформації для вирішення конкретних завдань набуває надзвичайної ваги та актуальності. Вміння грамотно і професійно шукати достовірну та актуальну інформацію, робити висновки та приймати правильні рішення спонукає фахівця-інтелектуала опановувати спеціальні евристичні методи

Ototopical drops containing a novel antibacterial synthetic peptide: safety and efficacy in adults with chronic suppurative otitis media

ObjectiveChronic suppurative otitis media (CSOM) is a chronic infectious disease with worldwide prevalence that causes hearing loss and decreased quality of life. As current (antibiotic) treatments often unsuccessful and antibiotic resistance is emerging, alternative agents and/or strategies are urgently needed. We considered the synthetic antimicrobial and anti-biofilm peptide P60.4Ac to be an interesting candidate because it also displays anti-inflammatory activities including lipopolysaccharide-neutralizing activity. The aim of the present study was to investigate the safety and efficacy of ototopical drops containing P60.4Ac in adults with CSOM without cholesteatoma.MethodsWe conducted a range-finding study in 16 subjects followed by a randomized, double blinded, placebo-controlled, multicentre phase IIa study in 34 subjects. P60.4Ac-containing ototopical drops or placebo drops were applied twice a day for 2 weeks and adverse events (AEs) and medication use were recorded. Laboratory tests, swabs from the middle ear and throat for bacterial cultures, and audiometry were performed at intervals up to 10 weeks after therapy. Response to treatment was assessed by blinded symptom scoring on otoscopy.ResultsApplication of P60.4Ac-containing ototopical drops (0.25-2.0 mg of peptide/ml) in the ear canal of patients suffering from CSOM was found to be safe and well-tolerated. The optimal dose (0.5 mg of peptide/ml) was selected for the subsequent phase IIa study. Safety evaluation revealed only a few AEs that were unlikely related to study treatment and all, except one, were of mild to moderate intensity. In addition to this excellent safety profile, P60.4Ac ototopical drops resulted in a treatment success in 47% of cases versus 6% in the placebo group.ConclusionThe efficacy/safety balance assessed in the present study provides a compelling justification for continued clinical development of P60.4Ac in therapy-resistant CSOM.Development and application of statistical models for medical scientific researc

Assessing biomass based on canopy height profiles using airborne laser scanning data in eucalypt plantations

This study aimed to map the stem biomass of an even-aged eucalyptus plantation in southeastern Brazil based on canopy height profile (CHPs) statistics using wall-to-wall discrete return airborne laser scanning (ALS), and compare the results with alternative maps generated by ordinary kriging interpolation from field-derived measurements. The assessment of stem biomass with ALS data was carried out using regression analysis methods. Initially, CHPs were determined to express the distribution of laser point heights in the ALS cloud for each sample plot. The probability density function (pdf) used was the Weibull distribution, with two parameters that in a secondary task, were used as explanatory variables to model stem biomass. ALS metrics such as height percentiles, dispersion of heights, and proportion of points were also investigated. A simple linear regression model of stem biomass as a function of the Weibull scale parameter showed high correlation (adj.R2 = 0.89). The alternative model considering the 30th percentile and the Weibull shape parameter slightly improved the quality of the estimation (adj.R2 = 0.93). Stem biomass maps based on the Weibull scale parameter doubled the accuracy of the ordinary kriging approach (relative root mean square error = 6 % and 13 %, respectively)

Ensemble modeling and statistical mapping of airborne radioactivity

Manufacturing and processing of chemicals and other substances takes place in densely populated areas world wide. Whilst this kind of industry is essential for society, the proximity to populated areas introduces great risks. Accidents such as Chernobyl underline the importance of minimizing the risk that such an accident occurs and when it occurs to take effective countermeasures. The main goal of this thesis was to explore two ways of combining the many sources of information that are available to decision makers in the event of an accident. Note that in this study we focused on accidents involving radioactive material. Our results showed we could effectively design an automatic interpolation system for background radiation levels. A second major contribution was the use of rainfall intensity maps derived from rainfall radar images to improve the interpolated maps of radiation level. Furthermore, this thesis illustrated the use of web-services to effectively distribute the results of the interpolation system through a Web Map Service and discussed the potential use of other web service standards such as a Web Processing Service. Modeling of a tracer dataset showed the great potential of ensemble modeling combined with data assimilation. However, the results also showed that there still was much to gain in modeling actual radiation level patterns. This could be attributed to the scale difference between the model and the observations used for data assimilation. Finally, we concluded that ensemble modeling was preferable to deterministic modeling. First, ensemble modeling quantifies the uncertainty associated with the model predictions, which is essential for decision making. Second, ensemble modeling provides a formal way through data assimilation to use observation to improve the physical model, i.e. data assimilation. The conclusion of thesis was that each of these methods has its own merits and is useful for decision makers. The main advantage of geostatistics is its speed of calculation. A disadvantage is the lack of being able to use interpolation for forecasting and the poor performance under emergency conditions. Physical modeling on the other hand performs well under emergency conditions and explicitly incorporates a lot of the underlying process which causes the spatial pattern in radiation level. However, run times are quite large compared to geostatistics. Both methods quantify the uncertainty associated with their prediction. This allowed us to construct prediction intervals and classify them relative to threshold values. These exceedance maps, which incorporate the uncertainty of the prediction, are of great benefit to decision makers. Although we focused on radioactivity in this thesis, we believe that the results are also useful for other environmental issues such as ground water pollution

Assimilation of observations of radiation level into an atmospheric transport model: A case study with the particle filter and the ETEX tracer dataset

Atmospheric transport models and observations from monitoring networks are commonly used aids for forecasting spatial distribution of contamination in case of a radiological incident. In this study, we assessed the particle filter data-assimilation technique as a tool for ensemble forecasting the spread of radioactivity. We used measurements from the ETEX-1 tracer experiment and model results from the NPK-Puff atmospheric dispersion model. We showed that assimilation of observations improves the ensemble forecast compared to runs without data assimilation. The improvement is most prominent for nowcasting: the mean squared error was reduced by a factor of 7. For forecasting, the improvement of the mean squared error resulting from assimilation of observations was found to dissipate within a few hours. We ranked absolute model values and observations and calculated the mean squared error of the ranked values. This measure of the correctness of the pattern of high and low values showed an improvement for forecasting up to 48 h. We conclude that the particle filter is an effective tool in better modeling the spread of radioactivity following a releas

Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network

Detection of radiological accidents and monitoring the spread of the contamination is of great importance. Following the Chernobyl accident many European countries have installed monitoring networks to perform this task. Real-time availability of automatically interpolated maps showing the spread of radioactivity during and after an accident would improve the capability of decision makers to accurately respond to a radiological accident. The objective of this paper is to present a real-time automatic interpolation system suited for natural background radioactivity. Interpolating natural background radiation allows us to better understand the natural variability, thus improving our ability to detect accidents. A real-time automatic interpolation system suited for natural background radioactivity presents a first step towards a system that can deal with radiological accidents. The interpolated maps are produced using a combination of universal kriging and an automatic variogram fitting procedure. The system provides a map of (1) the kriging prediction, (2) the kriging standard error and (3) the position of approximate prediction intervals relative to a threshold. The maps are presented through a Web Map Service (WMS) to ensure interoperability with existing Geographic Information Systems (GIS

Using rainfall radar data to improve interpolated maps of dose rate in the Netherlands

The radiation monitoring network in the Netherlands is designed to detect and track increased radiation levels, dose rate more specifically, in 10-minute intervals. The network consists of 153 monitoring stations. Washout of radon progeny by rainfall is the most important cause of natural variations in dose rate. The increase in dose rate at a given time is a function of the amount of progeny decaying, which in turn is a balance between deposition of progeny by rainfall and radioactive decay. The increase in progeny is closely related to average rainfall intensity over the last 2.5 h. We included decay of progeny by using weighted averaged rainfall intensity, where the weight decreases back in time. The decrease in weight is related to the half-life of radon progeny. In this paper we show for a rainstorm on the 20th of July 2007 that weighted averaged rainfall intensity estimated from rainfall radar images, collected every 5 min, performs much better as a predictor of increases in dose rate than using the non-averaged rainfall intensity. In addition, we show through cross-validation that including weighted averaged rainfall intensity in an interpolated map using universal kriging (UK) does not necessarily lead to a more accurate map. This might be attributed to the high density of monitoring stations in comparison to the spatial extent of a typical rain event. Reducing the network density improved the accuracy of the map when universal kriging was used instead of ordinary kriging (no trend). Consequently, in a less dense network the positive influence of including a trend is likely to increase. Furthermore, we suspect that UK better reproduces the sharp boundaries present in rainfall maps, but that the lack of short-distance monitoring station pairs prevents cross-validation from revealing this effect

Veilig leven met stralingsrisico’s

De kans op een ongeluk met radioactief materiaal in Nederland is niet groot, maar wel reëel. We hebben een nationaal netwerk om vrijgekomen straling te meten. Maar wanneer sla je alarm en ga je over tot een ingrijpende evacuatie? Naast modellen voor emissie, weersvoorspelling en atmosferische verspreiding van radioactieve stoffen helpt geografi sche kennis hierbij