Resilience of water supply systems in meeting the challenges posed by climate change and population growth

This research project provides a scientifically robust approach for assessing the resilience of water supply systems, which are critical infrastructure, to impacts of climate change and population growth. An approach for the identification of trigger points that allows timely and appropriate management actions to be taken to avoid catastrophic system failure is an important outcome of this project. In the current absence of a formal method to evaluate the resilience of a water supply system, the approach developed in this study was based on the characterisation of resilience of a water supply system to a range of surrogate measures. Accordingly, a set of indicators are proposed to evaluate system behaviour and logistic regression analysis was used to assess system behaviour under predicted rainfall, storage and demand conditions.

Investigating the impact of project definition clarity on project performance: Structural equation modeling study

Having a clear project definition is crucial for successful construction projects. It affects design quality, project communication between stakeholders and final project performance in terms of cost, schedule and quality. This study examines the relationship between project definition and final project performance through a structural equation model comprising 4 latent constructs and 6 path hypotheses using data from a questionnaire survey of 120 general contractors in the Malaysian construction industry. The results show that in the study population, all three items impact the project performance, but the link between design quality and project performance is indirect. Instead, the clarity of project definition affects project performance indirectly through design quality and project communication and design quality affects project performance indirectly through project communication. The primary contribution is to provide quantitative confirmation of the more general statements made in the literature from around the world and therefore adds to and consolidates existing knowledge. Practical implications derived from the finding are also proposed for various project stakeholders. Furthermore, as lack of the clarity of project definition is a very common occurrence in construction projects globally, these findings have important ramifications for all construction projects in expanding and clarifying existing knowledge on what is needed for the successful delivery of construction projects.

Modeling meat yield based on measurements of body traits in genetically improved giant freshwater prawn (GFP) Macrobrachium rosenbergii

A single-generation dataset consisting of 1,730 records from a selection program for high growth rate in giant freshwater prawn (GFP, Macrobrachium rosenbergii) was used to derive prediction equations for meat weight and meat yield. Models were based on body traits [body weight, total length and abdominal width (AW)] and carcass measurements (tail weight and exoskeleton-off weight). Lengths and width were adjusted for the systematic effects of selection line, male morphotypes and female reproductive status, and for the covariables of age at slaughter within sex and body weight. Body and meat weights adjusted for the same effects (except body weight) were used to calculate meat yield (expressed as percentage of tail weight/body weight and exoskeleton-off weight/body weight). The edible meat weight and yield in this GFP population ranged from 12 to 15 g and 37 to 45 %, respectively. The simple (Pearson) correlation coefficients between body traits (body weight, total length and AW) and meat weight were moderate to very high and positive (0.75–0.94), but the correlations between body traits and meat yield were negative (−0.47 to −0.74). There were strong linear positive relationships between measurements of body traits and meat weight, whereas relationships of body traits with meat yield were moderate and negative. Step-wise multiple regression analysis showed that the best model to predict meat weight included all body traits, with a coefficient of determination (R 2) of 0.99 and a correlation between observed and predicted values of meat weight of 0.99. The corresponding figures for meat yield were 0.91 and 0.95, respectively. Body weight or length was the best predictor of meat weight, explaining 91–94 % of observed variance when it was fitted alone in the model. By contrast, tail width explained a lower proportion (69–82 %) of total variance in the single trait models. It is concluded that in practical breeding programs, improvement of meat weight can be easily made through indirect selection for body trait combinations. The improvement of meat yield, albeit being more difficult, is possible by genetic means, with 91 % of the variation in the trait explained by the body and carcass traits examined in this study.

Cardiovascular diseases and vulnerable plaques: data, modeling, predictions and clinical applications PREFACE

Introduction Two symposia on “cardiovascular diseases and vulnerable plaques” Cardiovascular disease (CVD) is the leading cause of death worldwide. Huge effort has been made in many disciplines including medical imaging, computational modeling, bio- mechanics, bioengineering, medical devices, animal and clinical studies, population studies as well as genomic, molecular, cellular and organ-level studies seeking improved methods for early detection, diagnosis, prevention and treatment of these diseases [1-14]. However, the mechanisms governing the initiation, progression and the occurrence of final acute clinical CVD events are still poorly understood. A large number of victims of these dis- eases who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs [8,9]. Most cardiovascular diseases are associated with vulnerable plaques. A grand challenge here is to develop new imaging techniques, predictive methods and patient screening tools to identify vulnerable plaques and patients who are more vulnerable to plaque rupture and associated clinical events such as stroke and heart attack, and recommend proper treatment plans to prevent those clinical events from happening. Articles in this special issue came from two symposia held recently focusing on “Cardio-vascular Diseases and Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications.” One was held at Worcester Polytechnic Institute (WPI), Worcester, MA, USA, July 13-14, 2014, right after the 7th World Congress of Biomechanics. This symposium was endorsed by the World Council of Biomechanics, and partially supported by a grant from NIH-National Institute of Biomedical Image and Bioengineering. The other was held at Southeast University (SEU), Nanjing, China, April 18-20, 2014.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Modeling ecological and evolutionary processes in spatially structured populations

Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

Modeling transport through an environment crowded by a mixture of obstacles of different shapes and sizes

Many biological environments are crowded by macromolecules, organelles and cells which can impede the transport of other cells and molecules. Previous studies have sought to describe these effects using either random walk models or fractional order diffusion equations. Here we examine the transport of both a single agent and a population of agents through an environment containing obstacles of varying size and shape, whose relative densities are drawn from a specified distribution. Our simulation results for a single agent indicate that smaller obstacles are more effective at retarding transport than larger obstacles; these findings are consistent with our simulations of the collective motion of populations of agents. In an attempt to explore whether these kinds of stochastic random walk simulations can be described using a fractional order diffusion equation framework, we calibrate the solution of such a differential equation to our averaged agent density information. Our approach suggests that these kinds of commonly used differential equation models ought to be used with care since we are unable to match the solution of a fractional order diffusion equation to our data in a consistent fashion over a finite time period.

Cyclosporine population pharmacokinetics in pediatric renal transplant recipients

Cyclosporine is an immunosuppressant drug with a narrow therapeutic index and large variability in pharmacokinetics. To improve cyclosporine dose individualization in children, we used population pharmacokinetic modeling to study the effects of developmental, clinical, and genetic factors on cyclosporine pharmacokinetics in altogether 176 subjects (age range: 0.36–20.2 years) before and up to 16 years after renal transplantation. Pre-transplantation test doses of cyclosporine were given intravenously (3 mg/kg) and orally (10 mg/kg), on separate occasions, followed by blood sampling for 24 hours (n=175). After transplantation, in a total of 137 patients, cyclosporine concentration was quantified at trough, two hours post-dose, or with dose-interval curves. One-hundred-four of the studied patients were genotyped for 17 putatively functionally significant sequence variations in the ABCB1, SLCO1B1, ABCC2, CYP3A4, CYP3A5, and NR1I2 genes. Pharmacokinetic modeling was performed with the nonlinear mixed effects modeling computer program, NONMEM. A 3-compartment population pharmacokinetic model with first order absorption without lag-time was used to describe the data. The most important covariate affecting systemic clearance and distribution volume was allometrically scaled body weight i.e. body weight**3/4 for clearance and absolute body weight for volume of distribution. The clearance adjusted by absolute body weight declined with age and pre-pubertal children (< 8 years) had an approximately 25% higher clearance/body weight (L/h/kg) than did older children. Adjustment of clearance for allometric body weight removed its relationship to age after the first year of life. This finding is consistent with a gradual reduction in relative liver size towards adult values, and a relatively constant CYP3A content in the liver from about 6–12 months of age to adulthood. The other significant covariates affecting cyclosporine clearance and volume of distribution were hematocrit, plasma cholesterol, and serum creatinine, explaining up to 20%–30% of inter-individual differences before transplantation. After transplantation, their predictive role was smaller, as the variations in hematocrit, plasma cholesterol, and serum creatinine were also smaller. Before transplantation, no clinical or demographic covariates were found to affect oral bioavailability, and no systematic age-related changes in oral bioavailability were observed. After transplantation, older children receiving cyclosporine twice daily as the gelatine capsule microemulsion formulation had an about 1.25–1.3 times higher bioavailability than did the younger children receiving the liquid microemulsion formulation thrice daily. Moreover, cyclosporine oral bioavailability increased over 1.5-fold in the first month after transplantation, returning thereafter gradually to its initial value in 1–1.5 years. The largest cyclosporine doses were administered in the first 3–6 months after transplantation, and thereafter the single doses of cyclosporine were often smaller than 3 mg/kg. Thus, the results suggest that cyclosporine displays dose-dependent, saturable pre-systemic metabolism even at low single doses, whereas complete saturation of CYP3A4 and MDR1 (P-glycoprotein) renders cyclosporine pharmacokinetics dose-linear at higher doses. No significant associations were found between genetic polymorphisms and cyclosporine pharmacokinetics before transplantation in the whole population for which genetic data was available (n=104). However, in children older than eight years (n=22), heterozygous and homozygous carriers of the ABCB1 c.2677T or c.1236T alleles had an about 1.3 times or 1.6 times higher oral bioavailability, respectively, than did non-carriers. After transplantation, none of the ABCB1 SNPs or any other SNPs were found to be associated with cyclosporine clearance or oral bioavailability in the whole population, in the patients older than eight years, or in the patients younger than eight years. In the whole population, in those patients carrying the NR1I2 g.-25385C–g.-24381A–g.-205_-200GAGAAG–g.7635G–g.8055C haplotype, however, the bioavailability of cyclosporine was about one tenth lower, per allele, than in non-carriers. This effect was significant also in a subgroup of patients older than eight years. Furthermore, in patients carrying the NR1I2 g.-25385C–g.-24381A–g.-205_-200GAGAAG–g.7635G–g.8055T haplotype, the bioavailability was almost one fifth higher, per allele, than in non-carriers. It may be possible to improve individualization of cyclosporine dosing in children by accounting for the effects of developmental factors (body weight, liver size), time after transplantation, and cyclosporine dosing frequency/formulation. Further studies are required on the predictive value of genotyping for individualization of cyclosporine dosing in children.

Modeling of formation of gold nanoparticles by citrate method

Properties of nanoparticles are size dependent, and a model to predict particle size is of importance. Gold nanoparticles are commonly synthesized by reducing tetrachloroauric acid with trisodium citrate, a method pioneered by Turkevich et al (Discuss. Faraday Soc. 1951, 11, 55). Data from several investigators that used this method show that when the ratio of initial concentrations of citrate to gold is varied from 0.4 to similar to 2, the final mean size of the particles formed varies by a factor of 7, while subsequent increases in the ratio hardly have any effect on the size. In this paper, a model is developed to explain this widely varying dependence. The steps that lead to the formation of particles are as follows: reduction of Au3+ in solution, disproportionation of Au+ to gold atoms and their nucleation, growth by disproportionation on particle surface, and coagulation. Oxidation of citrate results in the formation of dicarboxy acetone, which aids nucleation but also decomposes into side products. A detailed kinetic model is developed on the basis of these steps and is combined with population balance to predict particle-size distribution. The model shows that, unlike the usual balance between nucleation and growth that determines the particle size, it is the balance between rate of nucleation and degradation of dicarboxy acetone that determines the particle size in the citrate process. It is this feature that is able to explain the unusual dependence of the mean particle size on the ratio of citrate to gold salt concentration. It is also found that coagulation plays an important role in determining the particle size at high concentrations of citrate.

Modeling of precipitation in reverse micellar systems

A model of the precipitation process in reverse micelles has been developed to calculate the size of fine particles obtained therein. While the method shares several features of particle nucleation and growth common to precipitation in large systems, complexities arise in describing the processes of nucleation, due to the extremely small size of a micelle and of particle growth caused by fusion among the micelles. Occupancy of micelles by solubilized molecules is governed by Poisson statistics, implying most of them are empty and cannot nucleate of its own. The model therefore specifies the minimum number of solubilized molecules required to form a nucleus which is used to calculate the homogeneous nucleation rate. Simultaneously, interaction between micelles is assumed to occur by Brownian collision and instantaneous fusion. Analysis of time scales of various events shows growth of particles to be very fast compared to other phenomena occurring. This implies that nonempty micelles either are supersaturated or contain a single precipitated particle and allows application of deterministic population balance equations to describe the evolution of the system with time. The model successfully predicts the experimental measurements of Kandori ct al.(3) on the size of precipitated CaCO3 particles, obtained by carbonation of reverse micelles containing aqueous Ca(OH)(2) solution.

A vision modeling framework for DHM using geometrically estimated FoV

Digital human modeling (DHM) involves modeling of structure, form and functional capabilities of human users for ergonomics simulation. This paper presents application of geometric procedures for investigating the characteristics of human visual capabilities which are particularly important in the context mentioned above. Using the cone of unrestricted directions through the pupil on a tessellated head model as the geometric interpretation of the clinical field-of-view (FoV), the results obtained are experimentally validated. Estimating the pupil movement for a given gaze direction using Listing's Law, FoVs are re-computed. Significant variation of the FoV is observed with the variation in gaze direction. A novel cube-grid representation, which integrated the unit-cube representation of directions and the enhanced slice representation has been introduced for fast and exact point classification for point visibility analysis for a given FoV. Computation of containment frequency of every grid-cell for a given set of FoVs enabled determination of percentile-based FoV contours for estimating the visual performance of a given population. This is a new concept which makes visibility analysis more meaningful from ergonomics point-of-view. The algorithms are fast enough to support interactive analysis of reasonably complex scenes on a typical desktop computer. (C) 2011 Elsevier Ltd. All rights reserved.

A finite population model of mlecular evolution: theory and computation

This article is concerned with the evolution of haploid organisms that reproduce asexually. In a seminal piece of work, Eigen and coauthors proposed the quasispecies model in an attempt to understand such an evolutionary process. Their work has impacted antiviral treatment and vaccine design strategies. Yet, predictions of the quasispecies model are at best viewed as a guideline, primarily because it assumes an infinite population size, whereas realistic population sizes can be quite small. In this paper we consider a population genetics-based model aimed at understanding the evolution of such organisms with finite population sizes and present a rigorous study of the convergence and computational issues that arise therein. Our first result is structural and shows that, at any time during the evolution, as the population size tends to infinity, the distribution of genomes predicted by our model converges to that predicted by the quasispecies model. This justifies the continued use of the quasispecies model to derive guidelines for intervention. While the stationary state in the quasispecies model is readily obtained, due to the explosion of the state space in our model, exact computations are prohibitive. Our second set of results are computational in nature and address this issue. We derive conditions on the parameters of evolution under which our stochastic model mixes rapidly. Further, for a class of widely used fitness landscapes we give a fast deterministic algorithm which computes the stationary distribution of our model. These computational tools are expected to serve as a framework for the modeling of strategies for the deployment of mutagenic drugs.

Modeling of agglomeration inside a droplet with nanosuspensions in an acoustic field

This short communication reports results of particle agglomeration details of an acoustically levitated nanosilica droplet. The droplet undergoes thermo-physical and morphological changes under external heating load (convective or radiative) forming different solid structures due to particle agglomeration. We report an agglomeration model based on population balance approach coupled with species and energy conservation equations in the liquid phase and compare it with the experimentally observed structure formations using high speed photography. The analysis is able to predict similar spherical bowl shaped morphologies as observed experimentally using scanning electron microscopy and laser induced fluorescence. (C) 2012 Elsevier Ltd. All rights reserved.

Modeling harvest rates and numbers from age and sex ratios: A demonstration for elephant populations

Illegal harvest rates of wildlife populations are often unknown or difficult to estimate from field data due to under-reporting or incomplete detection of carcasses. This is especially true for elephants that are killed for ivory or in conflicts with people. We describe a method to infer harvest rates from coarse field data of three population parameters, namely, adult female to male ratio, male old-adult to young-adult ratio, and proportion of adult males in the population using Jensen's (2000) 2-sex, density-dependent Leslie matrix model. The specific combination of male and female harvest rates and numbers can be determined from the history of harvest and estimate of population size. We applied this technique to two populations of elephants for which data on age structure and records of mortality were available-a forest-dwelling population of the Asian elephant (at Nagarahole, India) and an African savannah elephant population (at Samburu, Kenya) that had experienced male-biased harvest regimes over 2-3 decades. For the Nagarahole population, the recorded numbers of male and female elephants killed illegally during 1981-2000 were 64% and 88% of the values predicted by the model, respectively, implying some non-detection or incomplete reporting while for the Samburu population the recorded and modeled numbers of harvest during 1990-1999 closely matched. This technique, applicable to any animal population following logistic growth model, can be especially useful for inferring illegal harvest numbers of forest elephants in Africa and Asia.

Modeling harvest rates and numbers from age and sex ratios: A demonstration for elephant populations

Illegal harvest rates of wildlife populations are often unknown or difficult to estimate from field data due to under-reporting or incomplete detection of carcasses. This is especially true for elephants that are killed for ivory or in conflicts with people. We describe a method to infer harvest rates from coarse field data of three population parameters, namely, adult female to male ratio, male old-adult to young-adult ratio, and proportion of adult males in the population using Jensen's (2000) 2-sex, density-dependent Leslie matrix model. The specific combination of male and female harvest rates and numbers can be determined from the history of harvest and estimate of population size. We applied this technique to two populations of elephants for which data on age structure and records of mortality were available-a forest-dwelling population of the Asian elephant (at Nagarahole, India) and an African savannah elephant population (at Samburu, Kenya) that had experienced male-biased harvest regimes over 2-3 decades. For the Nagarahole population, the recorded numbers of male and female elephants killed illegally during 1981-2000 were 64% and 88% of the values predicted by the model, respectively, implying some non-detection or incomplete reporting while for the Samburu population the recorded and modeled numbers of harvest during 1990-1999 closely matched. This technique, applicable to any animal population following logistic growth model, can be especially useful for inferring illegal harvest numbers of forest elephants in Africa and Asia. (C) 2013 Elsevier Ltd. All rights reserved.