Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Semiparametric modeling of the spatial distribution of occupational accident risk in the casual labor market, Piracicaba, southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.

Risk-based Modeling to Develop Zoning Criteria for Land-use Near Canadian Airports

Land development in the vicinity of airports often leads to land-use that can attract birds that are hazardous to aviation operations. For this reason, certain forms of land-use have traditionally been discouraged within prescribed distances of Canadian airports. However, this often leads to an unrealistic prohibition of land-use in the vicinity of airports located in urban settings. Furthermore, it is often unclear that the desired safety goals have been achieved. This paper describes a model that was created to assist in the development of zoning regulations for a future airport site in Canada. The framework links land-use to bird-related safety-risks and aircraft operations by categorizing the predictable relationships between: (i) different land uses found in urbanized and urbanizing settings near airports; (ii) bird species; and (iii) the different safety-risks to aircraft during various phases of flight. The latter is assessed relative to the runway approach and departure paths. Bird species are ranked to reflect the potential severity of an impact with an aircraft (using bird weight, flocking characteristics, and flight behaviours). These criteria are then employed to chart bird-related safety-risks relative to runway reference points. Each form of land-use is categorized to reflect the degree to which it attracts hazardous bird species. From this information, hazard and risk matrices have been developed and applied to the future airport setting, thereby providing risk-based guidance on appropriate land-uses that range from prohibited to acceptable. The framework has subsequently been applied to an existing Canadian airport, and is currently being adapted for national application. The framework provides a risk-based and science-based approach that offers municipalities and property owner’s flexibility in managing the risks to aviation related to their land use.

Modeling the influence of APOC3, APOE, and TNF polymorphisms on the risk of antiretroviral therapy-associated lipid disorders

BACKGROUND: Single-nucleotide polymorphisms in genes involved in lipoprotein and adipocyte metabolism may explain why dyslipidemia and lipoatrophy occur in some but not all antiretroviral therapy (ART)-treated individuals. METHODS: We evaluated the contribution of APOC3 -482C-->T, -455T-->C, and 3238C-->G; epsilon 2 and epsilon 4 alleles of APOE; and TNF -238G-->A to dyslipidemia and lipoatrophy by longitudinally modeling >2600 lipid determinations and 2328 lipoatrophy assessments in 329 ART-treated patients during a median follow-up period of 3.4 years. RESULTS: In human immunodeficiency virus (HIV)-infected individuals, the effects of variant alleles of APOE on plasma cholesterol and triglyceride levels and of APOC3 on plasma triglyceride levels were comparable to those reported in the general population. However, when treated with ritonavir, individuals with unfavorable genotypes of APOC3 and [corrected] APOE were at risk of extreme hypertriglyceridemia. They had median plasma triglyceride levels of 7.33 mmol/L, compared with 3.08 mmol/L in the absence of ART. The net effect of the APOE*APOC3*ritonavir interaction was an increase in plasma triglyceride levels of 2.23 mmol/L. No association between TNF -238G-->A and lipoatrophy was observed. CONCLUSIONS: Variant alleles of APOE and APOC3 contribute to an unfavorable lipid profile in patients with HIV. Interactions between genotypes and ART can lead to severe hyperlipidemia. Genetic analysis may identify patients at high risk for severe ritonavir-associated hypertriglyceridemia.

Modeling of dangerous phenomena and innovative techniques for hazard evaluation and risk mitigation

Society is frequently exposed to and threatened by dangerous phenomena in many parts of the world. Different types of such phenomena require specific actions for proper risk management, from the stages of hazard identification to those of mitigation (including monitoring and early-warning) and/or reduction. The understanding of both predisposing factors and triggering mechanisms of a given danger and the prediction of its evolution from the source to the overall affected zone are relevant issues that must be addressed to properly evaluate a given hazard.

On Modeling an Innovative Monitoring Network for Protecting and Managing Cultural Heritage from Risk Events

In this paper the model of an Innovative Monitoring Network involving properly connected nodes to develop an Information and Communication Technology (ICT) solution for preventive maintenance of historical centres from early warnings is proposed. It is well known that the protection of historical centres generally goes from a large-scale monitoring to a local one and it could be supported by a unique ICT solution. More in detail, the models of a virtually organized monitoring system could enable the implementation of automated analyses by presenting various alert levels. An adequate ICT solution tool would allow to define a monitoring network for a shared processing of data and results. Thus, a possible retrofit solution could be planned for pilot cases shared among the nodes of the network on the basis of a suitable procedure utilizing a retrofit catalogue. The final objective would consist in providing a model of an innovative tool to identify hazards, damages and possible retrofit solutions for historical centres, assuring an easy early warning support for stakeholders. The action could proactively target the needs and requirements of users, such as decision makers responsible for damage mitigation and safeguarding of cultural heritage assets.

Use of structural equation modeling to examine the association between breast cancer risk perception and repeat screening mammography among United States women

Breast cancer is the second leading cause of cancer death in United States women, estimated to be diagnosed in 1 out of 8 women in their lifetime. Screening mammography detects breast cancer in its pre-clinical stages when treatment strategies have the greatest chance of success, and is currently the only population-wide prevention method proven to reduce the morbidity and mortality associated with breast cancer. Research has shown that the majority of women are not screened annually, with estimates ranging front 6% - 30% of eligible women receiving all available annual mammograms over a 5-year or greater time frame. Health behavior theorists believe that perception of risk/susceptibility to a disease influences preventive health behavior, in this case, screening mammography The purpose of this dissertation is to examine the association between breast cancer risk perception and repeat screening mammography using a structural equation modeling (SEM) framework. A series of SEM multivariate regressions were conducted using self-reported, nationally representative data from the 2005 National Health Interview Survey. Interaction contrasts were tested to measure the potential moderating effects of variables which have been shown to be predictive of mammography use (physician recommendation, economic barriers, structural barriers, race/ethnicity) on the association between breast cancer risk perception and repeat mammography, while controlling for the covariates of age, income, region, nativity, and educational level. Of the variables tested for moderation, results of the SEM analyses identify physician recommendation as the only moderator of the relationship between risk perception and repeat mammography, thus the potentially most effective point of intervention to increase mammography screening, and decrease the morbidity and mortality associated with breast cancer. These findings expand the role of the physician from recommendation to one of attenuating the effect of risk perception and increasing repeat screening. The long range application of the research is the use of the SEM methodology to identify specific points of intervention most likely to increase preventive behavior in population-wide research, allowing for the most effective use of intervention funds.^

Risk Prediction In Cardiovascular Epidemiology: Considerations for Modeling Composite Endpoints

Thesis (Master's)--University of Washington, 2016-08

Multiphase flow in porous media: meta-modeling techniques for sensitivity analysis and risk assessment

One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Water regimes in the Brazilian Cerrados are sensitive to climatological disturbances and human intervention. The risk that critical water-table levels are exceeded over long periods of time can be estimated by applying stochastic methods in modeling the dynamic relationship between water levels and driving forces such as precipitation and evapotranspiration. In this study, a transfer function-noise model, the so called PIRFICT-model, is applied to estimate the dynamic relationship between water-table depth and precipitation surplus/deficit in a watershed with a groundwater monitoring scheme in the Brazilian Cerrados. Critical limits were defined for a period in the Cerrados agricultural calendar, the end of the rainy season, when extremely shallow levels (< 0.5-m depth) can pose a risk to plant health and machinery before harvesting. By simulating time-series models, the risk of exceeding critical thresholds during a continuous period of time (e.g. 10 days) is described by probability levels. These simulated probabilities were interpolated spatially using universal kriging, incorporating information related to the drainage basin from a digital elevation model. The resulting map reduced model uncertainty. Three areas were defined as presenting potential risk at the end of the rainy season. These areas deserve attention with respect to water-management and land-use planning.

Semiparametric modeling of the spatial distribution of occupational accident risk in the casual labor market, Piracicaba, southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.

Modeling Flood Stage-Duration-Frequency: A Risk Assessment of Critical Infrastructure in the Tidal Potomac

The service of a critical infrastructure, such as a municipal wastewater treatment plant (MWWTP), is taken for granted until a flood or another low frequency, high consequence crisis brings its fragility to attention. The unique aspects of the MWWTP call for a method to quantify the flood stage-duration-frequency relationship. By developing a bivariate joint distribution model of flood stage and duration, this study adds a second dimension, time, into flood risk studies. A new parameter, inter-event time, is developed to further illustrate the effect of event separation on the frequency assessment. The method is tested on riverine, estuary and tidal sites in the Mid-Atlantic region. Equipment damage functions are characterized by linear and step damage models. The Expected Annual Damage (EAD) of the underground equipment is further estimated by the parametric joint distribution model, which is a function of both flood stage and duration, demonstrating the application of the bivariate model in risk assessment. Flood likelihood may alter due to climate change. A sensitivity analysis method is developed to assess future flood risk by estimating flood frequency under conditions of higher sea level and stream flow response to increased precipitation intensity. Scenarios based on steady and unsteady flow analysis are generated for current climate, future climate within this century, and future climate beyond this century, consistent with the WWTP planning horizons. The spatial extent of flood risk is visualized by inundation mapping and GIS-Assisted Risk Register (GARR). This research will help the stakeholders of the critical infrastructure be aware of the flood risk, vulnerability, and the inherent uncertainty.

FLOOD RISK ASSESSMENT UNDER HISTORICAL AND PREDICTED LAND USE CHANGE USING CONTINUOUS HYDROLOGIC MODELING

Current procedures for flood risk estimation assume flood distributions are stationary over time, meaning annual maximum flood (AMF) series are not affected by climatic variation, land use/land cover (LULC) change, or management practices. Thus, changes in LULC and climate are generally not accounted for in policy and design related to flood risk/control, and historical flood events are deemed representative of future flood risk. These assumptions need to be re-evaluated, however, as climate change and anthropogenic activities have been observed to have large impacts on flood risk in many areas. In particular, understanding the effects of LULC change is essential to the study and understanding of global environmental change and the consequent hydrologic responses. The research presented herein provides possible causation for observed nonstationarity in AMF series with respect to changes in LULC, as well as a means to assess the degree to which future LULC change will impact flood risk. Four watersheds in the Midwest, Northeastern, and Central United States were studied to determine flood risk associated with historical and future projected LULC change. Historical single framed aerial images dating back to the mid-1950s were used along with Geographic Information Systems (GIS) and remote sensing models (SPRING and ERDAS) to create historical land use maps. The Forecasting Scenarios of Future Land Use Change (FORE-SCE) model was applied to generate future LULC maps annually from 2006 to 2100 for the conterminous U.S. based on the four IPCC-SRES future emission scenario conditions. These land use maps were input into previously calibrated Soil and Water Assessment Tool (SWAT) models for two case study watersheds. In order to isolate effects of LULC change, the only variable parameter was the Runoff Curve Number associated with the land use layer. All simulations were run with daily climate data from 1978-1999, consistent with the 'base' model which employed the 1992 NLCD to represent 'current' conditions. Output daily maximum flows were converted to instantaneous AMF series and were subsequently modeled using a Log-Pearson Type 3 (LP3) distribution to evaluate flood risk. Analysis of the progression of LULC change over the historic period and associated SWAT outputs revealed that AMF magnitudes tend to increase over time in response to increasing degrees of urbanization. This is consistent with positive trends in the AMF series identified in previous studies, although there are difficulties identifying correlations between LULC change and identified change points due to large time gaps in the generated historical LULC maps, mainly caused by unavailability of sufficient quality historic aerial imagery. Similarly, increases in the mean and median AMF magnitude were observed in response to future LULC change projections, with the tails of the distributions remaining reasonably constant. FORE-SCE scenario A2 was found to have the most dramatic impact on AMF series, consistent with more extreme projections of population growth, demands for growing energy sources, agricultural land, and urban expansion, while AMF outputs based on scenario B2 showed little changes for the future as the focus is on environmental conservation and regional solutions to environmental issues.

Modeling Alzheimer disease with iPSCs and mouse model for the identification of risk factors, new targets, and potential therapeutical strategies

Alzheimer's disease (AD) is the most common neurodegenerative disease in elderly. Donepezil is the first-line drug used for AD. In section one, the experimental activity was oriented to evaluate and characterize molecular and cellular mechanisms that contribute to neurodegeneration induced by the Aβ1-42 oligomers (Aβ1-42O) and potential neuroprotective effects of the hybrids feruloyl-donepezil compound called PQM130. The effects of PQM130 were compared to donepezil in a murine AD model, obtained by intracerebroventricular (i.c.v.) injection of Aβ1-42O. The intraperitoneal administration of PQM130 (0.5-1 mg/kg) after i.c.v. Aβ1-42O injection improved learning and memory, protecting mice against spatial cognition decline. Moreover, it reduced oxidative stress, neuroinflammation and neuronal apoptosis, induced cell survival and protein synthesis in mice hippocampus. PQM130 modulated different pathways than donepezil, and it is more effective in counteracting Aβ1-42O damage. The section two of the experimental activity was focused on studying a loss of function variants of ABCA7. GWA studies identified mutations in the ABCA7 gene as a risk factor for AD. The mechanism through which ABCA7 contributes to AD is not clear. ABCA7 regulates lipid metabolism and critically controls phagocytic function. To investigate ABCA7 functions, CRISPR/Cas9 technology was used to engineer human iPSCs and to carry the genetic variant Y622*, which results in a premature stop codon, causing ABCA7 loss-of-function. From iPSCs, astrocytes were generated. This study revealed the effects of ABCA7 loss in astrocytes. ABCA7 Y622* mutation induced dysfunctional endocytic trafficking, impairing Aβ clearance, lipid dysregulation and cell homeostasis disruption, alterations that could contribute to AD. Though further studies are needed to confirm the PQM130 neuroprotective role and ABCA7 function in AD, the provided results showed a better understanding of AD pathophysiology, a new therapeutic approach to treat AD, and illustrated an innovative methodology for studying the disease.