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  • Articles  (1,290)
  • Springer  (1,290)
  • American Physical Society (APS)
  • Blackwell Publishing Ltd
  • 2015-2019  (1,290)
  • Stochastic Environmental Research and Risk Assessment  (547)
  • 4914
  • Architecture, Civil Engineering, Surveying  (1,290)
  • 1
    Publication Date: 2015-08-04
    Description: Thyroid cancer (TC) incidence in China has increased rapidly in recent years. Hangzhou is one of the areas with the highest TC incidence in China. However, the composite space–time variation and risk factors of TC are rarely investigated. We acquired 7147 TC cases from 2008 to 2012 in Hangzhou. Descriptive statistics were employed to compare the incidence disparities in different sub-populations. Geographical information systems were used to create spatial distribution maps. Hotspot analysis was applied to detect high/low incidence clusters, and the GeogDetector model was implemented to investigate the relationship between TC incidence and environmental factors. TC incidence in Hangzhou increased dramatically from 2008 to 2012: a noticeable 244.9 % increase, from 10.04 to 34.63 per 100,000 individuals, with a female to male ratio of 3.0, an urban to rural ratio of 3.2 and iodine sufficient to iodine deficient ratio of 3.5. Significantly high TC cluster was detected in the northeast area of Hangzhou. Elevation was found to be the most powerful determinant of TC distribution, followed by soil parent materials and slope. TC incidence decreased as elevation and slope increased. Concerning soil parent materials, deposited materials were generally linked to higher TC incidence than were eluvium ones. The spatial/temporal pattern of TC incidence is affected by geomorphology and soil property variations. Excessive iodine exposure may be a TC risk factor. Health research and management should pay sufficient attention to the improved understanding and prediction of the composite space–time distribution of the quickly increasing TC incidence described in this study.
    Print ISSN: 1436-3240
    Electronic ISSN: 1436-3259
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 2
    Publication Date: 2015-07-29
    Description: Accurate and precise estimation of return levels is often a key goal of any extreme value analysis. For example, in the UK the British Standards Institution (BSI) incorporate estimates of ‘once-in-50-year wind gust speeds’—or 50- year return levels —into their design codes for new structures; similarly, the Dutch Delta Commission use estimates of the 10,000- year return level for sea-surge to aid the construction of flood defence systems. In this paper, we briefly highlight the shortcomings of standard methods for estimating return levels, including the commonly-adopted block maxima and peaks over thresholds approach, before presenting an estimation framework which we show can substantially increase the precision of return level estimates. Our work allows explicit quantification of seasonal effects, as well as exploiting recent developments in the estimation of the extremal index for handling extremal clustering. From frequentist ideas, we turn to the Bayesian paradigm as a natural approach for building complex hierarchical or spatial models for extremes. Through simulations we show that the return level posterior mean does not have an exceedance probability in line with the intended encounter risk; we also argue that the Bayesian posterior predictive value gives the most satisfactory representation of a return level for use in practice, accounting for uncertainty in parameter estimation and future observations. Thus, where feasible, we propose a Bayesian estimation strategy for optimal return level inference.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 3
    Publication Date: 2015-07-29
    Description: In this study, a stochastic programming with imprecise probabilities (SP-IP) model is proposed for planning water resources systems. The SP-IP model is capable of addressing multiple uncertainties in the forms of intervals with random boundaries and imprecise probability distributions. The stochastic optimization model can be transformed into a deterministic equivalence in a straightforward manner. A case study of regional water resources allocation is used to demonstrate the applicability of the proposed model. Results indicate that the total net benefits would be decreased with increased probabilities of occurrence, reflecting a potential trade-off between economic benefits and associated risks. The SP-IP model is also capable of providing a variety of decision alternatives under different scenarios of water policies, which is useful for water managers to formulate an appropriate water management policy in an uncertain environment.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 4
    Publication Date: 2015-08-06
    Description: In order to evaluate the exposure risk of lead and cadmium in seafood for coastal residents in the coastline of the South China, representative seafood such as sea fish, crustaceans and molluscs were collected and used as research samples in many sampling points. By determining lead and cadmium content in sample using graphite furnace atomic absorption spectrometry, we carried out a safety evaluation of lead and cadmium contamination of seafood by single factor pollution index method. By calculating lead, cadmium intake of the coastal residents eating seafood, their exposure risk of lead, cadmium was assessed. It was found that, firstly, the content of lead and cadmium in mollusks was both higher than sea fish and crustaceans in the same waters. Secondly, the lead and cadmium pollution in seafood near the mouth of Pearl River was the most serious. Thirdly, lead and cadmium intakes of the coastal population eating seafood were at a basic level of security, but there were certain risks on the males less than 17 years old eating molluscs in Shenzhen Bay.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 5
    Publication Date: 2015-08-09
    Description: The surface water quality monitoring is an important concern of public organizations due to its relevance to the public health. Statistical methods are taken as consistent and essential tools in the monitoring procedures in order to prevent and identify environmental problems. This work presents the study case of the hydrological basin of the river Vouga, in Portugal. The main goal is discriminate the water monitoring sites using the monthly dissolved oxygen concentration dataset between January 2002 and May 2013. This is achieved through the extraction of trend and seasonal components in a linear mixed-effect state space model. The parameters estimation is performed with both maximum likelihood method and distribution-free estimators in a two-step procedure. The application of the Kalman smoother algorithm allows to obtain predictions of the structural components as trend and seasonality. The water monitoring sites are discriminated through the structural components by a hierarchical agglomerative clustering procedure. This procedure identified different homogenous groups relatively to the trend and seasonality components and some characteristics of the hydrological basin are presented in order to support the results.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 6
    Publication Date: 2015-08-25
    Description: Due to rapid growth of population and development of economy, water resources allocation problems have aroused wide concern. Therefore, optimization of water resources systems is complex and uncertain, which is a severe challenge faced by water managers. In this paper, a factorial multi-stage stochastic programming with chance constraints approach is developed to deal with the issues of water-resources allocation under uncertainty and risk as well as their interactions. It can deal with uncertainties described as both interval numbers and probability distributions, and can also support the risk assessment within a multistage context. The solutions associated with different risk levels of constraint violation can be obtained, which can help characterize the relationship between the economic objective and the system risk. The inherent interactions between factors at different levels and their effects on total net benefits can be revealed through the analysis of multi-parameter interactions.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 7
    Publication Date: 2015-08-08
    Description: The joint occurrence of extreme hydroclimatic events, such as simultaneous precipitation deficit and high temperature, results in the so-called compound events, and has a serious impact on risk assessment and mitigation strategies. Multivariate frequency analysis (MFA) allows a probabilistic quantitative assessment of this risk under uncertainty. Analyzing precipitation and temperature records in the contiguous United States (CONUS), and focusing on the assessment of the degree of rarity of the 2014 California drought, we highlight some critical aspects of MFA that are often overlooked and should be carefully taken into account for a correct interpretation of the results. In particular, we show that an informative exploratory data analysis (EDA) devised to check the basic hypotheses of MFA, a suitable assessment of the sampling uncertainty, and a better understanding of probabilistic concepts can help to avoid misinterpretation of univariate and multivariate return periods, and incoherent conclusions concerning the risk of compound extreme hydroclimatic events. Empirical results show that the dependence between precipitation deficit and temperature across the CONUS can be positive, negative or not significant and does not exhibit significant changes in the last three decades. Focusing on the 2014 California drought as a compound event and based on the data used, the probability of occurrence strongly depends on the selected variables and how they are combined, and is affected by large uncertainty, thus preventing definite conclusions about the actual degree of rarity of this event.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 8
    Publication Date: 2015-08-11
    Description: This paper is purposed to detect the spatial laws of gastric cancer in the rapid urbanization area and analyze relationships between gastric cancer and urbanization. Gastric cancer incidence data in Xiamen between 2006 and 2009 was collected from Xiamen CDC (Centre of Disease Control and Prevention). Urbanization age of Xiamen Island was calculated from remote images and terrain maps. Analysis results showed that 995 gastric cancer cases, accounting for 61.64 % was in Xiamen island, compared with 619 cases, accounting for 38.36 % outside. The average gastric cancer incidence was 32.98/1000,000 in Xiamen Island, compared to 16.13/1000,000 outside. The top ten sub-districts of gastric cancer all located in Xiamen Island, and urban areas have as more than twice gastric cancer incidence as rural area, with 28.62/100,000. The most likely spatial cluster of gastric cancer was Xiamen Island. Correlation analysis results indicated the urbanization age and spatial cluster degree had a significantly positive correlation relationship. Rapid urbanization in Xiamen changed the environment, namely acquired factors including land use change, air–water–soil pollution, less activity, electromagnetic radiation and contaminated sea foods. These are risk factors of gastric cancer. This research indicated that Xiamen Island was prevalent of gastric cancer with a positive correlation with urbanization age.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 9
    Publication Date: 2015-08-11
    Description: Acquiring the structures of porous media is very important when predicting flow properties in porous media. However, direct measurements of 3D microstructures of porous media with the resolution of microns or even nanometers are difficult to achieve due to the expensive cost of high-precision equipment. Therefore, as a typical stochastic simulation method, multiple-point statistics (MPS) was used to perform reconstruction based on real 3D volume data of porous media scanned by micro-CT. Because the ensemble of patterns extracted from a training image (TI) cannot be embedded into a linear space, the traditional MPS methods using linear dimensionality reduction, including filter-based simulation and distance-based pattern simulation, are not suitable to deal with the nonlinear situation. A new MPS method using isometric mapping, which is a method of nonlinear dimensionality reduction, to achieve nonlinear dimensionality reduction is proposed to decrease redundant data of TIs so that the subsequent simulation can be faster and more accurate for the reconstruction of porous media. Entropy theory is introduced to select a proper size of data template to balance the CPU cost and reconstructed quality. The comparisons between the reconstructed images and the target image show that the structural characteristics of reconstructed porous media using our method are similar to those of real volume data. This method also has shown advantages in reconstruction quality over typical methods using linear dimensionality reduction.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 10
    Publication Date: 2015-08-16
    Description: Long-term shoreline evolution due to longshore sediment transport is one of the key processes that need to be addressed in coastal engineering design and management. To adequately represent the inherent stochastic nature of the evolution processes, a probability density evolution model based on a Liouville-type equation is proposed for predicting the shoreline changes. In this model, the standard one-line beach evolution model that is widely used in coastal engineering design is reformulated in terms of the probability density function of shoreline responses. A computational algorithm involving a total variation diminishing scheme is employed to solve the resulting equation. To check the accuracy and robustness of the model, the predictions of the model are evaluated by comparing them with those from Monte Carlo simulations for two idealised shoreline configurations involving a single long jetty perpendicular to a straight shoreline and a rectangular beach nourishment case. The pertinent features of the predicted probabilistic shoreline responses are identified and discussed. The influence of the density distributions of the input parameters on the computed results is investigated.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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