ifying the risk associated with the occurrence of wildfires and the magnitude of water quality impacts has important implications for managing water supplies. At present, no suitable integrative model exists that considers the probabilistic nature of system inputs as well as the range of processes and scales involved in this problem. We present FIRESTORM, a new model currently in development that aims to determine the range of sediment and associated contaminant loads that may be delivered to water supply reservoirs from the combination of wildfire and subsequent rainfall events. This Monte Carlo model incorporates the probabilistic nature of fire ignition, fire weather and rainfall, and includes deterministic models for fire behaviour and locally dominant erosion processes. FIRESTORM calculates the magnitude and associated annual risk of catchment-scale sediment loads associated with the occurrence of wildfire and rainfall generated by two rain event types. The two event types are localised, high intensity, short-duration convective storms, and widespread, longer duration synoptic-scale rainfall events. Initial application and testing of the model will focus on the two main reservoirs supplying water to Melbourne, Australia, both of which are situated in forest catchments vulnerable to wildfire. Probabilistic fire ignition and weather scenarios have been combined using 40 years of fire records and weather observations. These are used to select from a dataset of over 80
Application of Physiologically Based Pharmacokinetic Models in Chemical Risk Assessment
Mumtaz, Moiz; Fisher, Jeffrey; Blount, Benjamin; Ruiz, Patricia
2012-01-01. PMID:22523493
Racial Differences in the Performance of Existing Risk Prediction Models for Incident Type 2 Diabetes: The CARDIA Study.; Wu, Wen-Chih
2016-01-01. PMID:26628420
Modeling the Risk of Secondary Malignancies after Radiotherapy
Schneider, Uwe
2011-01-01
In developed countries, more than half of all cancer patients receive radiotherapy at some stage in the management of their disease. However, a radiation-induced secondary malignancy can be the price of success if the primary cancer is cured or at least controlled. Therefore, there is increasing concern regarding radiation-related second cancer risks in long-term radiotherapy survivors and a corresponding need to be able to predict cancer risks at high radiation doses. Of particular interest are second cancer risk estimates for new radiation treatment modalities such as intensity modulated radiotherapy, intensity modulated arc-therapy, proton and heavy ion radiotherapy. The long term risks from such modern radiotherapy treatment techniques have not yet been determined and are unlikely to become apparent for many years, due to the long latency time for solid tumor induction. Most information on the dose-response of radiation-induced cancer is derived from data on the A-bomb survivors who were exposed to γ-rays and neutrons. Since, for radiation protection purposes, the dose span of main interest is between zero and one Gy, the analysis of the A-bomb survivors is usually focused on this range. With increasing cure rates, estimates of cancer risk for doses larger than one Gy are becoming more important for radiotherapy patients. Therefore in this review, emphasis was placed on doses relevant for radiotherapy with respect to radiation induced solid cancer. Simple radiation protection models should be used only with extreme care for risk estimates in radiotherapy, since they are developed exclusively for low dose. When applied to scatter radiation, such models can predict only a fraction of observed second malignancies. Better semi-empirical models include the effect of dose fractionation and represent the dose-response relationships more accurately. The involved uncertainties are still huge for most of the organs and tissues. A major reason for this is that the
Risk factors correlated with risk of insulin resistance using homeostasis model assessment in adolescents in Taiwan.
Lin, Shiyng-Yu; Su, Chien-Tien; Hsieh, Yi-Chen; Li, Yu-Ling; Chen, Yih-Ru; Cheng, Shu-Yun; Hu, Chien-Ming; Chen, Yi-Hua; Hsieh, Fang-I; Chiou, Hung-Yi
2015-03-01.
Quantitative Risk Modeling of Fire on the International Space Station
NASA Technical Reports Server (NTRS)..
Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation
NASA Technical Reports Server (NTRS)
2012-01-01.
Modeling the operational risk in Iranian commercial banks: case study of a private bank
NASA Astrophysics Data System (ADS)
Momen, Omid; Kimiagari, Alimohammad; Noorbakhsh, Eaman
2012-08-01
The Basel Committee on Banking Supervision from the Bank for International Settlement classifies banking risks into three main categories including credit risk, market risk, and operational risk. The focus of this study is on the operational risk measurement in Iranian banks. Therefore, issues arising when trying to implement operational risk models in Iran are discussed, and then, some solutions are recommended. Moreover, all steps of operational risk measurement based on Loss Distribution Approach with Iran's specific modifications are presented. We employed the approach of this study to model the operational risk of an Iranian private bank. The results are quite reasonable, comparing the scale of bank and other risk categories.
Transmission of risk from parents with chronic pain to offspring: an integrative conceptual model.
Stone, Amanda L; Wilson, Anna C
2016-12-01
Offspring of parents with chronic pain are at increased risk for pain and adverse mental and physical health outcomes (Higgins et al, 2015). Although the association between chronic pain in parents and offspring has been established, few studies have addressed why or how this relation occurs. Identifying mechanisms for the transmission of risk that leads to the development of chronic pain in offspring is important for developing preventive interventions targeted to decrease risk for chronic pain and related outcomes (eg, disability and internalizing symptoms). This review presents a conceptual model for the intergenerational transmission of chronic pain from parents to offspring with the goal of setting an agenda for future research and the development of preventive interventions. Our proposed model highlights 5 potential mechanisms for the relation between parental chronic pain and pediatric chronic pain and related adverse outcomes: (1) genetics, (2) alterations in early neurobiological development, (3) pain-specific social learning, (4), general parenting and family health, and (5) exposure to stressful environment. In addition, the model presents 3 potential moderators for the relation between parent and child chronic pain: (1) the presence of chronic pain in a second parent, (2) timing, course, and location of parental chronic pain, and (3) offspring's characteristics (ie, sex, developmental stage, race or ethnicity, and temperament). Such a framework highlights chronic pain as inherently familial and intergenerational, opening up avenues for new models of intervention and prevention that can be family centered and include at-risk children.-01-01
Abstract-03-01 adults over 55
Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments
Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.; Hu, Qinhong
2015-09-28
This study statistically analyzed a grain-size based additivity model that has been proposed to scale reaction rates and parameters from laboratory to field. The additivity model assumed that reaction properties in a sediment including surface area, reactive site concentration, reaction rate, and extent can be predicted from field-scale grain size distribution by linearly adding reaction properties for individual grain size fractions. This study focused on the statistical analysis of the additivity model with respect to reaction rate constants using multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment as an example. Experimental data of rate-limited U(VI) desorption in a stirred flow-cell reactor were used to estimate the statistical properties of multi-rate parameters for individual grain size fractions. The statistical properties of the rate constants for the individual grain size fractions were then used to analyze the statistical properties of the additivity model to predict rate-limited U(VI) desorption in the composite sediment, and to evaluate the relative importance of individual grain size fractions to the overall U(VI) desorption. The result indicated that the additivity model provided a good prediction of the U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model, and U(VI) desorption in individual grain size fractions have to be simulated in order to apply the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel size fraction (2-8mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.
A Spatio-temporal Model of African Animal Trypanosomosis Risk
2015-01-01Tech Samsung Galaxy A04s 5G Price in India Tipped Ahead Of Launch By Nick Osei Danso On Jul 20, 2022 Share The Samsung Galaxy A04s 5G smartphone’s price in India has been tipped. The 5G-ready phone will reportedly carry an affordable price tag. The word on the street is that a new budget Samsung phone is headed to India soon. The Samsung Galaxy A04s 5G India launch is on the cards. Notably, it will be one of the most affordable phones with 5G support in India. However, details about the handset’s launch date in the country are still scarce. To recap, we got a glimpse into a few official-looking Samsung Galaxy A04s design renders in April, courtesy of tipster OnLeaks. Now, the Samsung