Robust guaranteed cost tracking control of quadrotor UAV with uncertainties

In this paper, a robust guaranteed cost controller (RGCC) is proposed for quadrotor UAV system with uncertainties to address set-point tracking problem. A sufficient condition of the existence for RGCC is derived by Lyapunov stability theorem. The designed RGCC not only guarantees the whole closed-loop system asymptotically stable but also makes the quadratic performance level built for the closed-loop system have an upper bound irrespective to all admissible parameter uncertainties. Then, an optimal robust guaranteed cost controller is developed to minimize the upper bound of performance level. Simulation results verify the presented control algorithms possess small overshoot and short setting time, with which the quadrotor has ability to perform set-point tracking task well.

An optimization technique for identifying robot manipulator parameters under uncertainty

Robot manipulators enable large-scale factory automation of simple and repeated tasks. Each manipulation is the result of the robot design and the command inputs provided by the operator. In this study, we focus on the accuracy improvement of practical robot manipulation under uncertainty, resulting in path-specific error values. Existing techniques for reducing the errors use high-precision sensors and measurements to obtain the values of a manipulator to provide feedback control. Instead of compensating errors in operation, this study designs a calibration table to obtain the error value for a designated path. This error is then used to adjust important parameters in the kinematic closed chain models of a manipulators via optimization. The proposed method reduces the cost and the dependence on the calibration process. Experimental results show that the overall accuracy of the manipulator is improved. The proposed method can also be extended to develop the optimal robotic manipulation planning and reliability assessment in the future.

Carcinogen Risk Assessment of Polycyclic Aromatic Hydrocarbons in Drinking Water, Using Probabilistic Approaches

BACKGROUND

This study was focused on the probability of carcinogen risk of low-level ingestion and dermal exposure with polycyclic aromatic hydrocarbons (PAHs) from drinking water in Tehran, capital of Iran.

METHODS

Concentrations of 16 PAHs were measured in the tap, bottled and heated tap water in four different seasons. Using a questionnaire-based survey, exposure with PAHs from drinking water was evaluated via direct ingestion, swimming, washing and showering. Finally, a comprehensive risk assessment was performed in four age groups. Rank correlation was used to represent variability in risk analysis and obtained coefficients were used for sensitivity analysis. In addition, Monte Carlo simulation was implemented to determine risk probability distributions and to calculate cumulative probability of the total risks in different age groups.

RESULTS

The lifetime average daily dose and the dermal absorbed dose were 0.69E-06 and 1.33E-05 mg/kg/day, respectively. The total estimated excess lifetime cancer risk (ELCR) of ingestion and dermal exposure were 1.57E-05 and 17.24E-05.

CONCLUSION

Sum of estimated ingestion and dermal ELCR was 18.81E-05, which was higher than the acceptable value recommended by WHO. It means a total of 1504 lifetime cancer cases in residents of Tehran. Monte Carlo simulation indicated that risk probability above the acceptable level was 96.2% in dermal exposure. Moreover, sensitivity analysis indicated that tap water consumption (P_spearman >0.92) and washing activities (P_spearman>0.95) had the greatest correlation on the cancer risk.

Climate change impact assessments on the water resources of India under extensive human interventions

Climate change is a major concern in the twenty-first century and its assessments are associated with multiple uncertainties, exacerbated and confounded in the regions where human interventions are prevalent. The present study explores the challenges for climate change impact assessment on the water resources of India, one of the world's largest human-modified systems. The extensive human interventions in the Energy-Land-Water-Climate (ELWC) nexus significantly impact the water resources of the country. The direct human interventions in the landscape may surpass/amplify/mask the impacts of climate change and in the process also affect climate change itself. Uncertainties in climate and resource assessments add to the challenge. Formulating coherent resource and climate change policies in India would therefore require an integrated approach that would assess the multiple interlinkages in the ELWC nexus and distinguish the impacts of global climate change from that of regional human interventions. Concerted research efforts are also needed to incorporate the prominent linkages in the ELWC nexus in climate/earth system modelling.

Investigating the dosimetric impact of seed location uncertainties in Collaborative Ocular Melanoma Study-based eye plaques

PURPOSE

To quantify the dosimetric effects of random and systematic seed position uncertainties in Collaborative Ocular Melanoma Study-based eye plaques.

METHODS AND MATERIALS

An eye plaque dose calculation routine was created using Task Group 43 formalism. A variety of clinical configurations were simulated, including two seed models: (125)I and (103)Pd, three eye plaque sizes, and eight plaque/eye orientations. Dose was calculated at four ocular anatomic sites and three central axis plaque depths. Random seed positional uncertainty was modeled by adding Gaussian random displacements, in one of three seed-motion degrees of freedom, to each seed's nominal coordinate. Distributions of dosimetric outcomes were obtained and fitted after 10(6) randomizations. Similar analysis was performed for deterministic, systematic shifts of the plaque along the eye surface and radially from the globe center.

RESULTS

Random seed placement uncertainties of 0.2-mm root mean square (RMS) (amplitude) produce dose changes that are typically <4% for each degree of freedom (95% confidence interval). Systematic seed placement uncertainties are generally greater than random uncertainty 95% confidence intervals (factor of 0.72-2.15), with the relative magnitudes depending on plaque size and location of interest. Eye plaque dosimetry is most sensitive to seed movement toward the center of the eye. Dosimetric uncertainty also increases with increasing dose gradients, which are typically greatest near the inner sclera, with smaller plaques, and with lower energy radionuclides (e.g., (103)Pd).

CONCLUSIONS

Dosimetric uncertainties due to the random seed positional displacements anticipated in the clinic are expected to be <4% for each degree of freedom in most circumstances.

Emerging contaminant uncertainties and policy: The chicken or the egg conundrum

Best practice in regulating contaminants of emerging concern (CEC) must involve the integration of science and policy, be defensible and accepted by diverse stakeholders. Key elements of CEC frameworks include identification and prioritisation of emerging contaminants, evaluation of health and environmental impacts from key matrices such as soil, groundwater, surface waters and sediment, assessments of available data, methods and technologies (and limitations), and mechanisms to take cognisance of diverse interests. This paper discusses one of the few frameworks designed for emerging contaminants, the Minnesota Department of Health (MDH) Drinking Water Contaminants of Emerging Concern (CEC) program. Further review of mechanisms for CECs in other jurisdictions reveals that there is only a small number of regulatory and guidance regimes globally. There is also merit in a formal mechanism for the global exchange of knowledge and outcomes associated with CECs of global interest.

Multi-thresholds for fault isolation in the presence of uncertainties

Monitoring of the faults is an important task in mechatronics. It involves the detection and isolation of faults which are performed by using the residuals. These residuals represent numerical values that define certain intervals called thresholds. In fact, the fault is detected if the residuals exceed the thresholds. In addition, each considered fault must activate a unique set of residuals to be isolated. However, in the presence of uncertainties, false decisions can occur due to the low sensitivity of certain residuals towards faults. In this paper, an efficient approach to make decision on fault isolation in the presence of uncertainties is proposed. Based on the bond graph tool, the approach is developed in order to generate systematically the relations between residuals and faults. The generated relations allow the estimation of the minimum detectable and isolable fault values. The latter is used to calculate the thresholds of isolation for each residual.

Perturbed dynamics of discrete-time switched nonlinear systems with delays and uncertainties

This paper addresses the dynamics of a class of discrete-time switched nonlinear systems with time-varying delays and uncertainties and subject to perturbations. It is assumed that the nominal switched nonlinear system is robustly uniformly exponentially stable. It is revealed that there exists a maximal Lipschitz constant, if perturbation satisfies a Lipschitz condition with any Lipschitz constant less than the maximum, then the perturbed system can preserve the stability property of the nominal system. In situations where the perturbations are known, it is proved that there exists an upper bound of coefficient such that the perturbed system remains exponentially stable provided that the perturbation is scaled by any coefficient bounded by the upper bound. A numerical example is provided to illustrate the proposed theoretical results.

Paraconsistent analysis network applied in the treatment of Raman spectroscopy data to support medical diagnosis of skin cancer

Paraconsistent logic (PL) is a type of non-classical logic that accepts contradiction as a fundamental concept and has produced valuable results in the analysis of uncertainties. In this work, algorithms based on a type of PL-paraconsistent annotated logic of two values (PAL2v)-are interconnected into a network of paraconsistent analysis (PANnet). PANnet was applied to a dataset comprising 146 Raman spectra of skin tissue biopsy fragments of which 30 spectra were determined to represent normal skin tissue (N), 96 were determined to represent tissue with basal cell carcinoma, and 19 were determined to be tissue with melanoma (MEL). In this database, paraconsistent analysis was able to correctly discriminate 136 out of a total of 145 fragments, obtaining a 93.793 % correct diagnostic accuracy. The application of PAL2v in the analysis of Raman spectroscopy signals produces better discrimination of cells than conventional statistical processes and presents a good graphical overview through its associated lattice structure. The technique of PAL2v-based data processing can be fundamental in the development of a computational tool dedicated to support the diagnosis of skin cancer using Raman spectroscopy.

On robust control of continuous-time systems with state-dependent uncertainties and its application to mechanical systems

This paper revisits the problems of robust stability analysis and control of continuous-time systems with state-dependent uncertainties. First, a more general polytopic model describing systems with state-dependent uncertain parameters is proposed, and such a system model is more applicable in practice. A low conservative stability condition is obtained for the system by introducing the Lagrange multiplier term and adding some weight matrix variables. Then, based on our proposed idea, the output-feedback controllers will be designed in two cases: (1) the system matrices share the same polytopic parameters; (2) the system matrices do not share the same polytopic parameters. The controllers are designed in a model-dependent manner, which can provide more flexibilities in control synthesis. Besides, a decay rate can be set in advance to achieve better system performances. Finally, a numerical example together with a classic mechanical system is used to demonstrate the effectiveness and applicability of our theoretical findings.

Getting water right: A case study in water yield modelling based on precipitation data

Water yield is a key ecosystem service in river basins and especially in dry regions around the World. In this study we carry out a modelling analysis of water yields in the Chubut River basin, located in one of the driest districts of Patagonia, Argentina. We focus on the uncertainty around precipitation data, a driver of paramount importance for water yield. The objectives of this study are to: i) explore the spatial and numeric differences among six widely used global precipitation datasets for this region, ii) test them against data from independent ground stations, and iii) explore the effects of precipitation data uncertainty on simulations of water yield. The simulations were performed using the ecosystem services model InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) with each of the six different precipitation datasets as input. Our results show marked differences among datasets for the Chubut watershed region, both in the magnitude of precipitations and their spatial arrangement. Five of the precipitation databases overestimate the precipitation over the basin by 50% or more, particularly over the more humid western range. Meanwhile, the remaining dataset (Tropical Rainfall Measuring Mission - TRMM), based on satellite measurements, adjusts well to the observed rainfall in different stations throughout the watershed and provides a better representation of the precipitation gradient characteristic of the rain shadow of the Andes. The observed differences among datasets in the representation of the rainfall gradient translate into large differences in water yield simulations. Errors in precipitation of +30% (-30%) amplify to water yield errors ranging from 50 to 150% (-45 to -60%) in some sub-basins. These results highlight the importance of assessing uncertainties in main input data when quantifying and mapping ecosystem services with biophysical models and cautions about the undisputed use of global environmental datasets.

Uncertainties in human health risk assessment of environmental contaminants: A review and perspective

Addressing uncertainties in human health risk assessment is a critical issue when evaluating the effects of contaminants on public health. A range of uncertainties exist through the source-to-outcome continuum, including exposure assessment, hazard and risk characterisation. While various strategies have been applied to characterising uncertainty, classical approaches largely rely on how to maximise the available resources. Expert judgement, defaults and tools for characterising quantitative uncertainty attempt to fill the gap between data and regulation requirements. The experiences of researching 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) illustrated uncertainty sources and how to maximise available information to determine uncertainties, and thereby provide an 'adequate' protection to contaminant exposure. As regulatory requirements and recurring issues increase, the assessment of complex scenarios involving a large number of chemicals requires more sophisticated tools. Recent advances in exposure and toxicology science provide a large data set for environmental contaminants and public health. In particular, biomonitoring information, in vitro data streams and computational toxicology are the crucial factors in the NexGen risk assessment, as well as uncertainties minimisation. Although in this review we cannot yet predict how the exposure science and modern toxicology will develop in the long-term, current techniques from emerging science can be integrated to improve decision-making.

Quantification of image distortions on the Utrecht interstitial CT/MR brachytherapy applicator at 3T MRI

PURPOSE

To quantify distortions on MR images of the Utrecht interstitial CT/MR applicator at a field strength of 3T using an MRI-only method.

MATERIALS AND METHODS

An MR-compatible phantom suspending the applicator in water was built and imaged on a Philips Ingenia 3T MRI scanner. A map of the magnetic field (B0) was calculated from multiecho images and used to quantify the field inhomogeneity. The expected displacements of the applicator could be quantified using the measured field inhomogeneity and sequence bandwidth. Additionally, two scans were acquired using opposing readout gradients. These scans were rigidly matched and their displacement was compared with the expected displacements from the B0 map. These same methods were applied in 4 patients. By rigid matching of the scans acquired with opposing readout direction the applicator displacement due to image distortion from B0 inhomogeneity as well as patient movement and organ deformation was determined.

RESULTS

According to the B0 map, the displacement on the intrauterine device of the plastic brachytherapy applicator was <0.4 mm for both the phantom and patients. Displacements obtained by the opposing readout method were ≤0.8 mm for each patient with a mean ± SD over the patients of 0.3 ± 0.1 mm.

CONCLUSION

The results of our study indicate that the B0 method agrees with the opposing readout method. Displacements caused by magnetic field inhomogeneity on 3T MRI were small compared with displacements due to patient movement and organ deformation.

Evaluating governance for sustainable development - Insights from experiences in the Dutch fen landscape

Prominent strands of discussion in the literature on governance for sustainable development debate how change can be induced to enhance sustainability, and how to evaluate the interventions aimed at prompting such change. Strikingly, there are few contributions about how prominent ideas of inducing change deal with multiple governance criteria for pursuing sustainable development. Moreover, the way ideas about inducing change relate to criteria of governance for sustainable development is not yet studied in an empirical context. This paper therefore comparatively analyses how three prominent modes of sustainable development governance - adaptive management, transition management and payments for environmental services - relate to a set of five prominent criteria reported in the literature, namely: equity, democracy, legitimacy, the handling of scale issues and the handling of uncertainty issues. It finds that the academic debates on these three modes address these criteria with varying attention and rather fragmented, while in the empirical setting of the Dutch fen landscape several aspects relating to the studied criteria were present and substantially influenced the functioning of the three modes of sustainable development. Together, the analysis of the literature debate and the empirical data are able to show that a narrow evaluation perspective may fail to diagnose and capture relevant struggles and complexities coming along with governance for sustainable development relevant issues. The study shows that in order to advance our understanding of governance for sustainable development, it is indeed important to include multiple criteria in studying these modes. Moreover, the study shows the importance of including empirical experiences which manifest when different modes for sustainable development are applied in real-world settings.

Decreasing Kd uncertainties through the application of thermodynamic sorption models

Radionuclide retardation processes during transport are expected to play an important role in the safety assessment of subsurface disposal facilities for radioactive waste. The linear distribution coefficient (Kd) is often used to represent radionuclide retention, because analytical solutions to the classic advection-diffusion-retardation equation under simple boundary conditions are readily obtainable, and because numerical implementation of this approach is relatively straightforward. For these reasons, the Kd approach lends itself to probabilistic calculations required by Performance Assessment (PA) calculations. However, it is widely recognised that Kd values derived from laboratory experiments generally have a narrow field of validity, and that the uncertainty of the Kd outside this field increases significantly. Mechanistic multicomponent geochemical simulators can be used to calculate Kd values under a wide range of conditions. This approach is powerful and flexible, but requires expert knowledge on the part of the user. The work presented in this paper aims to develop a simplified approach of estimating Kd values whose level of accuracy would be comparable with those obtained by fully-fledged geochemical simulators. The proposed approach consists of deriving simplified algebraic expressions by combining relevant mass action equations. This approach was applied to three distinct geochemical systems involving surface complexation and ion-exchange processes. Within bounds imposed by model simplifications, the presented approach allows radionuclide Kd values to be estimated as a function of key system-controlling parameters, such as the pH and mineralogy. This approach could be used by PA professionals to assess the impact of key geochemical parameters on the variability of radionuclide Kd values. Moreover, the presented approach could be relatively easily implemented in existing codes to represent the influence of temporal and spatial changes in geochemistry on Kd values.

Performance assessment of a commonly used "accumulation and wash-off" model from long-term continuous road runoff turbidity measurements

The suitability of a commonly used accumulation and wash-off model for continuous modelling of urban runoff contamination was evaluated based on 11-month turbidity and flow-rate records from an urban street. Calibration and uncertainty analysis were performed using a Markov Chain Monte-Carlo sampling method for both suspended solids loads (discharge rates) and concentration modelling. Selected models failed at replicating suspended solids concentration over the complete monitoring period. The studied dataset indeed suggests that the accumulation process is rather unpredictable and cannot be satisfactorily represented with usual accumulation models unless short periods are considered. Regarding suspended solid loads modelling, noticeably better performance was achieved, but similar results could as well be obtained with much simpler constant concentration models. Unless providing very accurate estimates of concentrations in runoff, accounting for their temporal variability during rain events may therefore not always be necessary for pollutant loads modelling, as loads are in fact mostly explained by runoff volumes.

An objective method for the production of isopach maps and implications for the estimation of tephra deposit volumes and their uncertainties

Characterization of explosive volcanic eruptive processes from interpretation of deposits is a key for assessing volcanic hazard and risk, particularly for infrequent large explosive eruptions and those whose deposits are transient in the geological record. While eruption size-determined by measurement and interpretation of tephra fall deposits-is of particular importance, uncertainties for such measurements and volume estimates are rarely presented. Here, tephra volume estimates are derived from isopach maps produced by modeling raw thickness data as cubic B-spline curves under tension. Isopachs are objectively determined in relation to original data and enable limitations in volume estimates from published maps to be investigated. The eruption volumes derived using spline isopachs differ from selected published estimates by 15-40 %, reflecting uncertainties in the volume estimation process. The formalized analysis enables identification of sources of uncertainty; eruptive volume uncertainties (>30 %) are much greater than thickness measurement uncertainties (~10 %). The number of measurements is a key factor in volume estimate uncertainty, regardless of method utilized for isopach production. Deposits processed using the cubic B-spline method are well described by 60 measurements distributed across each deposit; however, this figure is deposit and distribution dependent, increasing for geometrically complex deposits, such as those exhibiting bilobate dispersion.

Event-based quantification of emerging pollutant removal for an open stormwater retention basin - loads, efficiency and importance of uncertainties

Up to now, emerging contaminants have not been further-studied in in-situ stormwater best management practices and especially in detention basins. In this article, the efficiency of a dry stormwater detention basin was investigated regarding the removal of 7 alkylphenols and alkylphenol ethoxylates, 9 polybrominated diphenyl ethers, 45 pesticides and bisphenol A. Concentrations of contaminants were obtained by chemical analysis on dissolved and particulate phase distinctly. The removal efficiency was assessed on total, dissolved and particulate phase accounting for the global chain of uncertainty with a 95% confidence interval. Results showed that pesticides (rather hydrophilic) are not trapped in the detention basin but are released contrarily to B209 which is mostly in particulate phase. Alkylphenols and alkylphenol ethoxylates are present in both phases and the efficiency is storm event-dependent. Uncertainty consideration in efficiency determination revealed efficiency data, usually presented by raw values are not relevant to conclude on the performance of a detention basin. In this case study, efficiency data with a 95% confidence interval indicate that only 35%, 50% and 41% of campaigns showed an impact (in trapping or releasing) of the detention basin on alkylphenols and ethoxylates, polybrominated diphenyl ethers and pesticides respectively.

Tissue composition and density impact on the clinical parameters for (125)I prostate implants dosimetry

The MCNPX code was used to calculate the TG-43U1 recommended parameters in water and prostate tissue in order to quantify the dosimetric impact in 30 patients treated with (125)I prostate implants when replacing the TG-43U1 formalism parameters calculated in water by a prostate-like medium in the planning system (PS) and to evaluate the uncertainties associated with Monte Carlo (MC) calculations. The prostate density was obtained from the CT of 100 patients with prostate cancer. The deviations between our results for water and the TG-43U1 consensus dataset values were -2.6% for prostate V100, -13.0% for V150, and -5.8% for D90; -2.0% for rectum V100, and -5.1% for D0.1; -5.0% for urethra D10, and -5.1% for D30. The same differences between our water and prostate results were all under 0.3%. Uncertainties estimations were up to 2.9% for the gL(r) function, 13.4% for the F(r,θ) function and 7.0% for Λ, mainly due to seed geometry uncertainties. Uncertainties in extracting the TG-43U1 parameters in the MC simulations as well as in the literature comparison are of the same order of magnitude as the differences between dose distributions computed for water and prostate-like medium. The selection of the parameters for the PS should be done carefully, as it may considerably affect the dose distributions. The seeds internal geometry uncertainties are a major limiting factor in the MC parameters deduction.

Comparison of measured and predicted concentrations of selected pharmaceuticals in wastewater and surface water: a case study of a catchment area in the Po Valley (Italy)

The aim of this study is to compare measured and predicted concentrations of 11 antibiotics and the antiepileptic carbamazepine in wastewater and surface water and to discuss the accuracy and usefulness of applied predictive models in assessing their concentrations. The occurrence (exposure assessment) of the target compounds was monitored in the influent and effluent of a large municipal wastewater treatment plant, and in its receiving water body, situated in the Po Valley, Italy. Information on the consumption and sales of pharmaceuticals in Italy, along with data related to their excretion and removal during wastewater treatment, were used to predict the concentrations of the selected pharmaceuticals for the studied site. The measured and predicted concentrations were compared for all three sampling points, and according to a criterion available in literature and already adopted in similar studies, the prediction was considered "acceptable" when the ratio of predicted and measured concentrations was between 0.5 and 2. The results show that the concentrations were accurately predicted for ciprofloxacin in wastewaters, and for azithromycin, trimethoprim and carbamazepine in surface water. For all the other compounds and sampling points, the difference between the measured and the predicted concentrations was very high. Possible reasons for these discrepancies are discussed and the main potential factors that influence both measured and predicted concentrations are identified by means of an assessment of the uncertainties in the measured values and sensitivity of all the parameters required for predicting concentration ones. The potential factors are sampling mode for measured values and dilution factor, removal and excretion for predicted ones.

Review of clinical brachytherapy uncertainties: analysis guidelines of GEC-ESTRO and the AAPM

Background and purpose

A substantial reduction of uncertainties in clinical brachytherapy should result in improved outcome in terms of increased local control and reduced side effects. Types of uncertainties have to be identified, grouped, and quantified.

Methods

A detailed literature review was performed to identify uncertainty components and their relative importance to the combined overall uncertainty.

Results

Very few components (e.g., source strength and afterloader timer) are independent of clinical disease site and location of administered dose. While the influence of medium on dose calculation can be substantial for low energy sources or non-deeply seated implants, the influence of medium is of minor importance for high-energy sources in the pelvic region. The level of uncertainties due to target, organ, applicator, and/or source movement in relation to the geometry assumed for treatment planning is highly dependent on fractionation and the level of image guided adaptive treatment. Most studies to date report the results in a manner that allows no direct reproduction and further comparison with other studies. Often, no distinction is made between variations, uncertainties, and errors or mistakes. The literature review facilitated the drafting of recommendations for uniform uncertainty reporting in clinical BT, which are also provided. The recommended comprehensive uncertainty investigations are key to obtain a general impression of uncertainties, and may help to identify elements of the brachytherapy treatment process that need improvement in terms of diminishing their dosimetric uncertainties. It is recommended to present data on the analyzed parameters (distance shifts, volume changes, source or applicator position, etc.), and also their influence on absorbed dose for clinically-relevant dose parameters (e.g., target parameters such as D₉₀ or OAR doses). Publications on brachytherapy should include a statement of total dose uncertainty for the entire treatment course, taking into account the fractionation schedule and level of image guidance for adaptation.

Conclusions

This report on brachytherapy clinical uncertainties represents a working project developed by the Brachytherapy Physics Quality Assurances System (BRAPHYQS) subcommittee to the Physics Committee within GEC-ESTRO. Further, this report has been reviewed and approved by the American Association of Physicists in Medicine.

Establishing the level of safety concern for chemicals in food without the need for toxicity testing

There is demand for methodologies to establish levels of safety concern associated with dietary exposures to chemicals for which no toxicological data are available. In such situations, the application of in silico methods appears promising. To make safety statement requires quantitative predictions of toxicological reference points such as no observed adverse effect level and carcinogenic potency for DNA-reacting chemicals. A decision tree (DT) has been developed to aid integrating exposure information and predicted toxicological reference points obtained with quantitative structure activity relationship ((Q)SAR) software and read across techniques. The predicted toxicological values are compared with exposure to obtain margins of exposure (MoE). The size of the MoE defines the level of safety concern and should account for a number of uncertainties such as the classical interspecies and inter-individual variability as well as others determined on a case by case basis. An analysis of the uncertainties of in silico approaches together with results from case studies suggest that establishing safety concern based on application of the DT is unlikely to be significantly more uncertain than based on experimental data. The DT makes a full use of all data available, ensuring an adequate degree of conservatism. It can be used when fast decision making is required.

Mountain torrents: Quantifying vulnerability and assessing uncertainties

Vulnerability assessment for elements at risk is an important component in the framework of risk assessment. The vulnerability of buildings affected by torrent processes can be quantified by vulnerability functions that express a mathematical relationship between the degree of loss of individual elements at risk and the intensity of the impacting process. Based on data from the Austrian Alps, we extended a vulnerability curve for residential buildings affected by fluvial sediment transport processes to other torrent processes and other building types. With respect to this goal to merge different data based on different processes and building types, several statistical tests were conducted. The calculation of vulnerability functions was based on a nonlinear regression approach applying cumulative distribution functions. The results suggest that there is no need to distinguish between different sediment-laden torrent processes when assessing vulnerability of residential buildings towards torrent processes. The final vulnerability functions were further validated with data from the Italian Alps and different vulnerability functions presented in the literature. This comparison showed the wider applicability of the derived vulnerability functions. The uncertainty inherent to regression functions was quantified by the calculation of confidence bands. The derived vulnerability functions may be applied within the framework of risk management for mountain hazards within the European Alps. The method is transferable to other mountain regions if the input data needed are available.