Comparison of the HSPF and HBV-INCA models: Crossing the Atlantic divide

Observation shows that the watershed-scale models in common use in the United States (US) differ from those used in the European Union (EU). The question arises whether the difference in model use is due to familiarity or necessity. Do conditions in each continent require the use of unique watershed-scale models, or are models sufficiently customizable that independent development of models that serve the same purpose (e.g., continuous/event- based, lumped/distributed, field-Awatershed-scale) is unnecessary? This paper explores this question through the application of two continuous, semi-distributed, watershed-scale models (HSPF and HBV-INCA) to a rural catchment in southern England. The Hydrological Simulation Program-Fortran (HSPF) model is in wide use in the United States. The Integrated Catchments (INCA) model has been used extensively in Europe, and particularly in England. The results of simulation from both models are presented herein. Both models performed adequately according to the criteria set for them. This suggests that there was not a necessity to have alternative, yet similar, models. This partially supports a general conclusion that resources should be devoted towards training in the use of existing models rather than development of new models that serve a similar purpose to existing models. A further comparison of water quality predictions from both models may alter this conclusion.

Suitable sites for sustainable aquaculture development in Mymensingh, Bangladesh: A GIS methodological perspective

A GIS study was carried out to find out the sites suitable for aquaculture in Mymensingh region. A number of criteria were selected for GIS modeling followed by the approach of Kapetsky (1994). The criteria were developed from a range of existing data sources such as, surface and underground water level, availability of feed ingredients and animal wastes, sources of fish fry, market facilities, extension support and communication facilities for aquaculture development. The data were located, collected and compiled from different GOs and NGOs located in the region along with primary data from the field survey wherever necessary and then prepared for computer analyses. Using the database, a series of GIS models were developed in order to ascertain and prioritize the most suitable areas for aquaculture development in the region. Out of total 407,528 ha available lands in the region, the study identified 99,415 ha very suitable and 302,754 ha moderately suitable for aquaculture promotion. Result of the study is indicative to the modeling power of GIS for aquaculture application and could be used to refine the models in future, particularly if it is supported with further detail field data. To get a more concrete and complete model, detailed study should be made available on the availability of mustard oil cake, rice bran, wheat bran, and usable animal and urban wastes that could be used as low-cost feed for sustainable aquaculture.

Identification of major histocompatibility complex class I alleles in Chinese rhesus macaques

Major histocompatibility complex (MHC) class I information is vital for understanding variance of immune responses in HIV vaccination and biomedical models. In this study, 9 Mamu-A and 13 Mamu-B alleles were identified from the cDNA products of 10 Chinese

Evaluating the impacts of iteration on PD processes by transforming task network models into System Dynamics models

Iteration is unavoidable in the design process and should be incorporated when planning and managing projects in order to minimize surprises and reduce schedule distortions. However, planning and managing iteration is challenging because the relationships between its causes and effects are complex. Most approaches which use mathematical models to analyze the impact of iteration on the design process focus on a relatively small number of its causes and effects. Therefore, insights derived from these analytical models may not be robust under a broader consideration of potential influencing factors. In this article, we synthesize an explanatory framework which describes the network of causes and effects of iteration identified from the literature, and introduce an analytic approach which combines a task network modeling approach with System Dynamics simulation. Our approach models the network of causes and effects of iteration alongside the process architecture which is required to analyze the impact of iteration on design process performance. We show how this allows managers to assess the impact of changes to process architecture and to management levers which influence iterative behavior, accounting for the fact that these changes can occur simultaneously and can accumulate in non-linear ways. We also discuss how the insights resulting from this analysis can be visualized for easier consumption by project participants not familiar with simulation methods. Copyright © 2010 by ASME.

Differences between FRP bond behavior in cracked and uncracked regions

Based on an analysis of the experimental results of a proposed bond test method, significant differences are shown to exist between the local FRP bond stress-slip relationships in the uncracked anchorage regions and in the regions between cracks. The proposed method simulates the bond behavior between the flexural cracks and anchorage regions of a flexurally FRP-strengthened RC beam. The boundary conditions, including the presence of cracks and steel, are shown to have significant effects on the local bond stress-slip models. The results showed that, at the same force, the bond stresses in the regions between cracks were lower than in regions outside the cracks, so the debonding formed in the anchorage regions. The local bond stress-slip models in the anchorage regions can be obtained from the conventional bond test methods but these do not mimic the conditions between the cracks.

Construction of nonparametric Bayesian models from parametric Bayes equations

We consider the general problem of constructing nonparametric Bayesian models on infinite-dimensional random objects, such as functions, infinite graphs or infinite permutations. The problem has generated much interest in machine learning, where it is treated heuristically, but has not been studied in full generality in non-parametric Bayesian statistics, which tends to focus on models over probability distributions. Our approach applies a standard tool of stochastic process theory, the construction of stochastic processes from their finite-dimensional marginal distributions. The main contribution of the paper is a generalization of the classic Kolmogorov extension theorem to conditional probabilities. This extension allows a rigorous construction of nonparametric Bayesian models from systems of finite-dimensional, parametric Bayes equations. Using this approach, we show (i) how existence of a conjugate posterior for the nonparametric model can be guaranteed by choosing conjugate finite-dimensional models in the construction, (ii) how the mapping to the posterior parameters of the nonparametric model can be explicitly determined, and (iii) that the construction of conjugate models in essence requires the finite-dimensional models to be in the exponential family. As an application of our constructive framework, we derive a model on infinite permutations, the nonparametric Bayesian analogue of a model recently proposed for the analysis of rank data.

An examination of strain space versus stress space for the formulation of elastoplastic constitutive models

Several elastoplastic soil models have been proposed over the years that are formulated in strain space rather than stress space due to certain analytical and computational advantages. One such model, BRICK (Simpson 1992), has been continuously utilized and developed for industrial applications within Arup Geotechnics for more than two decades. This paper aims to describe the advantages and difficulties associated with strain space modeling. In addition, it will show how recent advances in modeling the effects of stress history, stiffness anisotropy, strength anisotropy and time-dependence in conventional stress space models can be transferred to the BRICK model. © 2010 Taylor & Francis Group, London.