Modelling of some biological materials using continuum mechanics

Continuum mechanics provides a mathematical framework for modelling the physical stresses experienced by a material. Recent studies show that physical stresses play an important role in a wide variety of biological processes, including dermal wound healing, soft tissue growth and morphogenesis. Thus, continuum mechanics is a useful mathematical tool for modelling a range of biological phenomena. Unfortunately, classical continuum mechanics is of limited use in biomechanical problems. As cells refashion the �bres that make up a soft tissue, they sometimes alter the tissue's fundamental mechanical structure. Advanced mathematical techniques are needed in order to accurately describe this sort of biological `plasticity'. A number of such techniques have been proposed by previous researchers. However, models that incorporate biological plasticity tend to be very complicated. Furthermore, these models are often di�cult to apply and/or interpret, making them of limited practical use. One alternative approach is to ignore biological plasticity and use classical continuum mechanics. For example, most mechanochemical models of dermal wound healing assume that the skin behaves as a linear viscoelastic solid. Our analysis indicates that this assumption leads to physically unrealistic results. In this thesis we present a novel and practical approach to modelling biological plasticity. Our principal aim is to combine the simplicity of classical linear models with the sophistication of plasticity theory. To achieve this, we perform a careful mathematical analysis of the concept of a `zero stress state'. This leads us to a formal de�nition of strain that is appropriate for materials that undergo internal remodelling. Next, we consider the evolution of the zero stress state over time. We develop a novel theory of `morphoelasticity' that can be used to describe how the zero stress state changes in response to growth and remodelling. Importantly, our work yields an intuitive and internally consistent way of modelling anisotropic growth. Furthermore, we are able to use our theory of morphoelasticity to develop evolution equations for elastic strain. We also present some applications of our theory. For example, we show that morphoelasticity can be used to obtain a constitutive law for a Maxwell viscoelastic uid that is valid at large deformation gradients. Similarly, we analyse a morphoelastic model of the stress-dependent growth of a tumour spheroid. This work leads to the prediction that a tumour spheroid will always be in a state of radial compression and circumferential tension. Finally, we conclude by presenting a novel mechanochemical model of dermal wound healing that takes into account the plasticity of the healing skin.

Economic growth, inequality and technology adoption in transitional economies

The stylized facts that motivate this thesis include the diversity in growth patterns that are observed across countries during the process of economic development, and the divergence over time in income distributions both within and across countries. This thesis constructs a dynamic general equilibrium model in which technology adoption is costly and agents are heterogeneous in their initial holdings of resources. Given the households‟ resource level, this study examines how adoption costs influence the evolution of household income over time and the timing of transition to more productive technologies. The analytical results of the model constructed here characterize three growth outcomes associated with the technology adoption process depending on productivity differences between the technologies. These are appropriately labeled as „poverty trap‟, „dual economy‟ and „balanced growth‟. The model is then capable of explaining the observed diversity in growth patterns across countries, as well as divergence of incomes over time. Numerical simulations of the model furthermore illustrate features of this transition. They suggest that that differences in adoption costs account for the timing of households‟ decision to switch technology which leads to a disparity in incomes across households in the technology adoption process. Since this determines the timing of complete adoption of the technology within a country, the implications for cross-country income differences are obvious. Moreover, the timing of technology adoption appears to be impacts on patterns of growth of households, which are different across various income groups. The findings also show that, in the presence of costs associated with the adoption of more productive technologies, inequalities of income and wealth may increase over time tending to delay the convergence in income levels. Initial levels of inequalities in the resources also have an impact on the date of complete adoption of more productive technologies. The issue of increasing income inequality in the process of technology adoption opens up another direction for research. Specifically increasing inequality implies that distributive conflicts may emerge during the transitional process with political- economy consequences. The model is therefore extended to include such issues. Without any political considerations, taxes would leads to a reduction in inequality and convergence of incomes across agents. However this process is delayed if politico-economic influences are taken into account. Moreover, the political outcome is sub optimal. This is essentially due to the fact that there is a resistance associated with the complete adoption of the advanced technology.

Towards controlled growth of carbon nanotubes from germanium on nanoindented silicon substrates

In this paper, we report on a metal-catalyst-free synthesis of carbon nanotubes (CNTs) on a pre-patterned Si(001) surface. Arrays of triangular-shaped holes were created by nanoindentation in specific sites of the sample. After germanium deposition and chemical vapor deposition (CVD) of acetylene, a few CNTs nucleated and grew from germanium nanoparticles. These results illustrate that it is possible to control the growth of CNTs without the use of any metal catalyst. By leading the assembly of Ge nanoparticles with a patterning technique, a precise control over the growth order is also attainable.

In vivo knockdown of the androgen receptor results in growth inhibition and regression of well-established, castration-resistant prostate tumours

Purpose: Progression to the castration-resistant state is the incurable and lethal end stage of prostate cancer, and there is strong evidence that androgen receptor (AR) still plays a central role in this process. We hypothesize that knocking down AR will have a major effect on inhibiting growth of castration-resistant tumors. Experimental Design: Castration-resistant C4-2 human prostate cancer cells stably expressing a tetracycline-inducible AR-targeted short hairpin RNA (shRNA) were generated to directly test the effects of AR knockdown in C4-2 human prostate cancer cells and tumors. Results:In vitro expression of AR shRNA resulted in decreased levels of AR mRNA and protein, decreased expression of prostate-specific antigen (PSA), reduced activation of the PSA-luciferase reporter, and growth inhibition of C4-2 cells. Gene microarray analyses revealed that AR knockdown under hormone-deprived conditions resulted in activation of genes involved in apoptosis, cell cycle regulation, protein synthesis, and tumorigenesis. To ensure that tumors were truly castration-resistant in vivo, inducible AR shRNA expressing C4-2 tumors were grown in castrated mice to an average volume of 450 mm3. In all of the animals, serum PSA decreased, and in 50% of them, there was complete tumor regression and disappearance of serum PSA. Conclusions: Whereas castration is ineffective in castration-resistant prostate tumors, knockdown of AR can decrease serum PSA, inhibit tumor growth, and frequently cause tumor regression. This study is the first direct evidence that knockdown of AR is a viable therapeutic strategy for treatment of prostate tumors that have already progressed to the castration-resistant state.

Validation of FHWA crash models for rural intersections - Lessons learned

A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.

Patterns of substrate utilization during long-term incubations at different temperatures

Microorganisms play key roles in biogeochemical cycling by facilitating the release of nutrients from organic compounds. In doing so, microbial communities use different organic substrates that yield different amounts of energy for maintenance and growth of the community. Carbon utilization efficiency (CUE) is a measure of the efficiency with which substrate carbon is metabolized versus mineralized by the microbial biomass. In the face of global change, we wanted to know how temperature affected the efficiency by which the soil microbial community utilized an added labile substrate, and to determine the effect of labile soil carbon depletion (through increasing duration of incubation) on the community's ability to respond to an added substrate. Cellobiose was added to soil samples as a model compound at several times over the course of a long-term incubation experiment to measure the amount of carbon assimilated or lost as CO2 respiration. Results indicated that in all cases, the time required for the microbial community to take up the added substrate increased as incubation time prior to substrate addition increased. However, the CUE was not affected by incubation time. Increased temperature generally decreased CUE, thus the microbial community was more efficient at 15 degrees C than at 25 degrees C. These results indicate that at warmer temperatures microbial communities may release more CO2 per unit of assimilated carbon. Current climate-carbon models have a fixed CUE to predict how much CO2 will be released as soil organic matter is decomposed. Based on our findings, this assumption may be incorrect due to variation of CUE with changing temperature. (c) 2008 Elsevier Ltd. All rights reserved.

Shoot growth dynamics and photosynthetic response to increased nitrogen availability in the alpine willow salix-glauca

Plants subjected to increases in the supply of resource(s) limiting growth may allocate more of those resources to existing leaves, increasing photosynthetic capacity, and/or to production of more leaves, increasing whole-plant photosynthesis. The responses of three populations of the alpine willow, Salix glauca, growing along an alpine topographic sequence representing a gradient in soil moisture and organic matter, and thus potential N supply, to N amendments, were measured over two growing seasons, to elucidate patterns of leaf versus shoot photosynthetic responses. Leaf-(foliar N, photosynthesis rates, photosynthetic N-use efficiency) and shoot-(leaf area per shoot, number of leaves per shoot, stem weight, N resorption efficiency) level measurements were made to examine the spatial and temporal variation in these potential responses to increased N availability. The predominant response of the willows to N fertilization was at the shoot-level, by production of greater leaf area per shoot. Greater leaf area occurred due to production of larger leaves in both years of the experiment and to production of more leaves during the second year of fertilization treatment. Significant leaf-level photosynthetic response occurred only during the first year of treatment, and only in the dry meadow population. Variation in photosynthesis rates was related more to variation in stomatal conductance than to foliar N concentration. Stomatal conductance in turn was significantly related to N fertilization. Differences among the populations in photosynthesis, foliar N, leaf production, and responses to N fertilization indicate N availability may be lowest in the dry meadow population, and highest in the ridge population. This result is contrary to the hypothesis that a gradient of plant available N corresponds with a snowpack/topographic gradient.

An alginate-based hybrid system for growth factor delivery in the functional repair of large bone defects

The treatment of challenging fractures and large osseous defects presents a formidable problem for orthopaedic surgeons. Tissue engineering/regenerative medicine approaches seek to solve this problem by delivering osteogenic signals within scaffolding biomaterials. In this study, we introduce a hybrid growth factor delivery system that consists of an electrospun nanofiber mesh tube for guiding bone regeneration combined with peptide-modified alginate hydrogel injected inside the tube for sustained growth factor release. We tested the ability of this system to deliver recombinant bone morphogenetic protein-2 (rhBMP-2) for the repair of critically-sized segmental bone defects in a rat model. Longitudinal [mu]-CT analysis and torsional testing provided quantitative assessment of bone regeneration. Our results indicate that the hybrid delivery system resulted in consistent bony bridging of the challenging bone defects. However, in the absence of rhBMP-2, the use of nanofiber mesh tube and alginate did not result in substantial bone formation. Perforations in the nanofiber mesh accelerated the rhBMP-2 mediated bone repair, and resulted in functional restoration of the regenerated bone. [mu]-CT based angiography indicated that perforations did not significantly affect the revascularization of defects, suggesting that some other interaction with the tissue surrounding the defect such as improved infiltration of osteoprogenitor cells contributed to the observed differences in repair. Overall, our results indicate that the hybrid alginate/nanofiber mesh system is a promising growth factor delivery strategy for the repair of challenging bone injuries.

Urban growth monitoring techniques for sustainable development

This paper discusses the role of advance techniques for monitoring urban growth and change for sustainable development of urban environment. It also presents results of a case study involving satellite data for land use/land cover classification of Lucknow city using IRS-1C multi-spectral features. Two classification algorithms have been used in the study. Experiments were conducted to see the level of improvement in digital classification of urban environment using Artificial Neural Network (ANN) technique.

Towards airport passenger experience models

This paper reports on the study of passenger experiences and how passengers interact with services, technology and processes at an airport. As part of our research, we have followed people through the airport from check-in to security and from security to boarding. Data was collected by approaching passengers in the departures concourse of the airport and asking for their consent to be videotaped. Data was collected and coded and the analysis focused on both discretionary and process related passenger activities. Our findings show the interdependence between activities and passenger experiences. Within all activities, passengers interact with processes, domain dependent technology, services, personnel and artifacts. These levels of interaction impact on passenger experiences and are interdependent. The emerging taxonomy of activities consists of (i) ownership related activities, (ii) group activities, (iii) individual activities (such as activities at the domain interfaces) and (iv) concurrent activities. This classification is contributing to the development of descriptive models of passenger experiences and how these activities affect the facilitation and design of future airports.

Important omitted spatial variables in safety models: Understanding contributing crash causes at intersections

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causation—rests upon the pursuit of numerous lines of inquiry. The research community has focused on analytical methods development (negative binomial specifications, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might think of different lines of inquiry in terms of ‘low lying fruit’—areas of inquiry that might provide significant improvements in understanding crash causation. It is the contention of this research that omitted variable bias caused by the exclusion of important variables is an important line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant ability to better understand contributing factors to crashes. This study—believed to represent a unique contribution to the safety literature—develops and examines the role of a sizeable set of spatial variables in intersection crash occurrence. In addition to commonly considered traffic and geometric variables, examined spatial factors include local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools. The results indicate that inclusion of these factors results in significant improvement in model explanatory power, and the results also generally agree with expectation. The research illuminates the importance of spatial variables in safety research and also the negative consequences of their omissions.