Browsing by Subject "Modeling"
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- ItemOpen AccessEstimating aerodynamic roughness over complex surface terrain(2013) Nield, Joanna M; King, James; Wiggs, Giles F S; Leyland, Julian; Bryant, Robert G; Chiverrell, Richard C; Darby, Stephen E; Eckardt, Frank D; Thomas, David S G; Vircavs, Larisa H; Washington, RichardSurface roughness plays a key role in determining aerodynamic roughness length (zo) and shear velocity, both of which are fundamental for determining wind erosion threshold and potential. While Zocan be quantified from wind measurements, large proportions of wind erosion prone surfaces remain too remote for this to be a viable approach. Alternative approaches therefore seek to relate Zoto morphological roughness metrics. However, dust-emitting landscapes typically consist of complex small-scale surface roughness patterns and few metrics exist for these surfaces which can be used to predict Zofor modeling wind erosion potential. In this study terrestrial laser scanning was used to characterize the roughness of typical dust-emitting surfaces (playa and sandar) where element protrusion heights ranged from 1 to 199 mm, over which vertical wind velocity profiles were collected to enable estimation of zo. Our data suggest that, although a reasonable relationship (R2> 0.79) is apparent between 3-D roughness density and Zo, the spacing of morphological elements is far less powerful in explaining variations in Zothan metrics based on surface roughness height (R2 > 0.92). This finding is in juxtaposition to wind erosion models that assume the spacing of larger-scale isolated roughness elements is most important in determining Zo. Rather, our data show that any metric based on element protrusion height has a higher likelihood of successfully predicting Zo. This finding has important implications for the development of wind erosion and dust emission models that seek to predict the efficiency of aeolian processes in remote terrestrial and planetary environments.
- ItemOpen AccessReporting and handling of missing data in predictive research for prevalent undiagnosed type 2 diabetes mellitus: a systematic review(BioMed Central Ltd, 2015) Masconi, Katya L; Matsha, Tandi; Echouffo-Tcheugui, Justin; Erasmus, Rajiv; Kengne, AndreMissing values are common in health research and omitting participants with missing data often leads to loss of statistical power, biased estimates and, consequently, inaccurate inferences. We critically reviewed the challenges posed by missing data in medical research and approaches to address them. To achieve this more efficiently, these issues were analyzed and illustrated through a systematic review on the reporting of missing data and imputation methods (prediction of missing values through relationships within and between variables) undertaken in risk prediction studies of undiagnosed diabetes. Prevalent diabetes risk models were selected based on a recent comprehensive systematic review, supplemented by an updated search of English-language studies published between 1997 and 2014. Reporting of missing data has been limited in studies of prevalent diabetes prediction. Of the 48 articles identified, 62.5% (n=30) did not report any information on missing data or handling techniques. In 21 (43.8%) studies, researchers opted out of imputation, completing case-wise deletion of participants missing any predictor values. Although imputation methods are encouraged to handle missing data and ensure the accuracy of inferences, this has seldom been the case in studies of diabetes risk prediction. Hence, we elaborated on the various types and patterns of missing data, the limitations of case-wise deletion and state-of the-art methods of imputations and their challenges. This review highlights the inexperience or disregard of investigators of the effect of missing data in risk prediction research. Formal guidelines may enhance the reporting and appropriate handling of missing data in scientific journals.
- ItemOpen AccessUndereporting of acute pesticide poisoning in Tanzania: modelling results from two cross-sectional studies(BioMed Central, 2016-11-29) Lekei, Elikana E; Ngowi, Aiwerasia V; London, LeslieBackground: Acute pesticide poisoning (APP) is known to cause serious injuries to end users globally but the magnitude of this problem in Tanzania is not well known. This study aimed to determine the extent and pattern of underreporting of APP in Tanzania to inform the development of a surveillance system and appropriate interventions. Methods: This study integrates findings from two recent Tanzanian studies. A household survey established the proportion of poisoned farmers in a typical rural area who reported to hospital for a pesticide poisoning. Only 5 of the 112 farmers who reported attending hospital due to poisonings could be traced in medical records at the facilities they claimed to have attended. The 95% confidence interval for this ratio (5/112) was used to generate a high and low boundary for the estimates. Three under-estimation factors were generated for sensitivity analysis to adjust for under-reporting. A review of health facilities in three regions of Tanzania collected prospective data on admissions for APP in 2006 to generate population-based APP incidence rates stratified by circumstances of poisoning (occupational, accidental, suicide, and unknown). Sensitivity analysis was conducted involving adjustment for high and low boundaries of the under-reporting of occupational APP and an adjustment for different scenario allocations of cases with ‘unknown’ circumstances to different combinations of known circumstances. Results: The study estimated the rate of occupational poisoning as ranging from 11.3–37.7 cases/million to 84.3–279.9 cases per million. The rate of all poisonings (occupational and non-occupational) ranged from 24.45–48.01 cases per million to 97.37–290.29 cases per million. Depending on the choice of scenario and under-reporting correction factor used, occupational APP could comprise from 52.2 to 96% of all APP cases. Conclusion: The study confirms that data on APP in Tanzanian hospitals are poorly reported and that occupational circumstances are particularly overlooked in routine facility-based surveillance. Occupational APP needs to be taken more seriously in addressing prevention measures. A comprehensive surveillance system for APP should consider multiple data sources including community self-reporting in order to achieve better coverage.
- ItemOpen AccessUnsteady contact melting of a rectangular cross-section material on a flat plate(2008) Myers, T G; Mitchell, S L; Muchatibaya, GThe work in this paper concerns a mathematical model of the contact melting process of a rectangular material in contact with a hot plate. The problem is described by a coupled system of heat equations in the solid and melt layer, fluid flow in the melt, a Stefan condition at the melt interface, and a force balance between the weight of the solid and the fluid pressure. Since the melt layer remains thin throughout the process, we use the lubrication approximation to the fluid equations and assume that the heat flow in the fluid is dominated by conduction across the thin film. In the solid we employ a heat balance integral method. Results show that the film height has initial and final rapid increases, whereas for intermediate times the height slowly increases. The quasisteady state of previous models is never attained: This is shown to be an effect of neglecting the change in mass and conduction in the solid. The previously observed initial infinite velocity of the melt is shown to be a result of the perfect thermal contact assumption. For a water-ice system the melting rate is shown to be approximately linear, this allows us to reduce the problem to solving a single first order differential equation for the liquid layer thickness. The main analysis is carried out in two dimensions, but we briefly highlight the extension to three dimensions. The method is verified by comparison with previously published experimental results on the melting of n -octadecane.