A Spatial Planning Support System for Managing Bangalore's Urban Sprawl

Urban sprawl is the outgrowth along the periphery of cities and along highways. Although an accurate definition of urban sprawl may be debated, a consensus is that urban sprawl is characterized by an unplanned and uneven pattern of growth, driven by multitude of processes and leading to inefficient resource utilization. Urbanization in India has never been as rapid as it is in recent times. As one of the fastest growing economies in the world, India faces stiff challenges in managing the urban sprawl, while ensuring effective delivery of basic services in urban areas. The urban areas contribute significantly to the national economy (more than 50% of GDP), while facing critical challenges in accessing basic services and necessary infrastructure, both social and economic. The overall rise in the population of the urban poor or the increase in travel times due to congestion along road networks are indicators of the effectiveness of planning and governance in assessing and catering for this demand. Agencies of governance at all levels: local bodies, state government and federal government, are facing the brunt of this rapid urban growth. It is imperative for planning and governance to facilitate, augment and service the requisite infrastructure over time systematically. Provision of infrastructure and assurance of the delivery of basic services cannot happen overnight and hence planning has to facilitate forecasting and service provision with appropriate financial mechanisms.

Spatial ecology of an oak-associated herbivore community : A metacommunity of herbivores

Habitat fragmentation is currently affecting many species throughout the world. As a consequence, an increasing number of species are structured as metapopulations, i.e. as local populations connected by dispersal. While excellent studies of metapopulations have accumulated over the past 20 years, the focus has recently shifted from single species to studies of multiple species. This has created the concept of metacommunities, where local communities are connected by the dispersal of one or several of their member species. To understand this higher level of organisation, we need to address not only the properties of single species, but also establish the importance of interspecific interactions. However, studies of metacommunities are so far heavily biased towards laboratory-based systems, and empirical data from natural systems are urgently needed. My thesis focuses on a metacommunity of insect herbivores on the pedunculate oak Quercus robur a tree species known for its high diversity of host-specific insects. Taking advantage of the amenability of this system to both observational and experimental studies, I quantify and compare the importance of local and regional factors in structuring herbivore communities. Most importantly, I contrast the impact of direct and indirect competition, host plant genotype and local adaptation (i.e. local factors) to that of regional processes (as reflected by the spatial context of the local community). As a key approach, I use general theory to generate testable hypotheses, controlled experiments to establish causal relations, and observational data to validate the role played by the pinpointed processes in nature. As the central outcome of my thesis, I am able to relegate local forces to a secondary role in structuring oak-based insect communities. While controlled experiments show that direct competition does occur among both conspecifics and heterospecifics, that indirect interactions can be mediated by both the host plant and the parasitoids, and that host plant genotype may affect local adaptation, the size of these effects is much smaller than that of spatial context. Hence, I conclude that dispersal between habitat patches plays a prime role in structuring the insect community, and that the distribution and abundance of the target species can only be understood in a spatial framework. By extension, I suggest that the majority of herbivore communities are dependent on the spatial structure of their landscape and urge fellow ecologists working on other herbivore systems to either support or refute my generalization.

Spatial correlation in grain misorientation distribution

Grain misorientation was studied in relation to the nearest neighbor's mutual distance using electron back-scattered diffraction measurements. The misorientation correlation function was defined as the probability density for the occurrence of a certain misorientation between pairs of grains separated by a certain distance. Scale-invariant spatial correlation between neighbor grains was manifested by a power law dependence of the preferred misorientation vs. inter-granular distance in various materials after diverse strain paths. The obtained negative scaling exponents were in the range of -2 +/- 0.3 for high-angle grain boundaries. The exponent decreased in the presence of low-angle grain boundaries or dynamic recrystallization, indicating faster decay of correlations. The correlations vanished in annealed materials. The results were interpreted in terms of lattice incompatibility and continuity conditions at the interface between neighboring grains. Grain-size effects on texture development, as well as the implications of such spatial correlations on texture modeling, were discussed.

Secondary metabolites in Gerbera hybrida

Plants produce a diversity of secondary metabolites, i.e., low-molecular-weight compounds that have primarily ecological functions in plants. The flavonoid pathway is one of the most studied biosynthetic pathways in plants. In order to understand biosynthetic pathways fully, it is necessary to isolate and purify the enzymes of the pathways to study individual steps and to study the regulatory genes of the pathways. Chalcone synthases are key enzymes in the formation of several groups of flavonoids, including anthocyanins. In this study, a new chalcone synthase enzyme (GCHS4), which may be one of the main contributors to flower colour, was characterised from the ornamental plant Gerbera hybrida. In addition, four chalcone synthase-like genes and enzymes (GCHS17, GCHS17b, GCHS26 and GCHS26b) were studied. Spatial expression of the polyketide synthase gene family in gerbera was also analysed with quantitative RT-PCR from 12 tissues, including several developmental stages and flower types. A previously identified MYB transcription factor from gerbera, GMYB10, which regulates the anthocyanin pathway, was transferred to gerbera and the phenotypes were analysed. Total anthocyanin content and anthocyanidin profiles of control and transgenic samples were compared spectrophotometrically and with HPLC. The overexpression of GMYB10 alone was able to change anthocyanin pigmentation: cyanidin pigmentation was induced and pelargonidin pigmentation was increased. The gerbera 9K cDNA microarray was used to compare the gene expression profiles of transgenic tissues against the corresponding control tissues to reveal putative target genes for GMYB10. GMYB10 overexpression affected the expression of both early and late biosynthetic genes in anthocyanin-accumulating transgenic tissues, including the newly isolated gene GCHS4. Two new MYB domain factors, named as GMYB11 and GMYB12, were also upregulated. Gene transfer is not only a powerful tool for basic research, but also for plant breeding. However, crop improvement by genetic modification (GM) remains controversial, at least in Europe. Many of the concerns relating to both human health and to ecological impacts relate to changes in the secondary metabolites of GM crops. In the second part of this study, qualitative and quantitative differences in cytotoxicity and metabolic fingerprints between 225 genetically modified Gerbera hybrida lines and 42 non-GM Gerbera varieties were compared. There was no evidence for any major qualitative and quantitative changes between the GM lines and non-GM varieties. The developed cell viability assays offer also a model scheme for cell-based cytotoxicity screening of a large variety of GM plants in standardized conditions.

Development and evaluation of a spatial decision support system for malaria elimination in Bhutan

Background: Bhutan has reduced its malaria incidence significantly in the last 5 years, and is aiming for malaria elimination by 2016. To assist with the management of the Bhutanese malaria elimination programme a spatial decision support system (SDSS) was developed. The current study aims to describe SDSS development and evaluate SDSS utility and acceptability through informant interviews. Methods: The SDSS was developed based on the open-source Quantum geographical information system (QGIS) and piloted to support the distribution of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) in the two sub-districts of Samdrup Jongkhar District. It was subsequently used to support reactive case detection (RACD) in the two sub-districts of Samdrup Jongkhar and two additional sub-districts in Sarpang District. Interviews were conducted to ascertain perceptions on utility and acceptability of 11 informants using the SDSS, including programme and district managers, and field workers. Results: A total of 1502 households with a population of 7165 were enumerated in the four sub-districts, and a total of 3491 LLINs were distributed with one LLIN per 1.7 persons. A total of 279 households representing 728 residents were involved with RACD. Informants considered that the SDSS was an improvement on previous methods for organizing LLIN distribution, IRS and RACD, and could be easily integrated into routine malaria and other vector-borne disease surveillance systems. Informants identified some challenges at the programme and field level, including the need for more skilled personnel to manage the SDSS, and more training to improve the effectiveness of SDSS implementation and use of hardware. Conclusions: The SDSS was well accepted and informants expected its use to be extended to other malaria reporting districts and other vector-borne diseases. Challenges associated with efficient SDSS use included adequate skills and knowledge, access to training and support, and availability of hardware including computers and global positioning system receivers.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Building teachers' pedagogy practices in reasoning, to improve students' dispositions towards mathematics

Drawing on participatory action research, this study identifies the pedagogies necessary to advance reasoning, which is one of the proficiencies from the Australian Curriculum Mathematics, and explores how reasoning leads to greater productive disposition. With the current emphasis on STEM in schools, this research is timely. This thesis makes an original and substantive contribution to the understanding of why and how teachers can most effectively advance student proficiency in reasoning through targeted instructional strategies and style of instruction. The study explores the ways in which teacher practices, when focused on reasoning, enhance the disposition of students towards greater mathematical proficiency.

Natural recovery from cannabis use in people with psychosis: A qualitative study

- Objective There is rapidly growing evidence of natural recovery from cannabis use in people with psychosis, but little is known about how it occurs. This qualitative study explores what factors influence the decision to cease cannabis use, maintain cessation, and prevent relapse. - Methods Ten people with early psychosis and lifetime cannabis misuse, who had been abstinent for at least a month, were recruited from public adult mental health services. These six men and four women participated in a semi-structured qualitative interview assessing reasons for addressing cannabis use, effective change strategies, lapse contexts, and methods used to regain control. Interpretative phenomenological analysis was used to identify themes in their responses. - Results Participants had a mean age of 23 years (SD = 3.7), started using cannabis at age 13.7 (SD = 1.6), began daily use at 17 (SD = 3.1), and had abstained from cannabis for 7.9 months (SD = 5.4). Awareness of the negative impact of substance use across multiple domains and the presence of social support for cannabis cessation were seen as vital to sustained success, as was utilization of a combination of coping strategies. The ability to address pressure from substance-using peers was commonly mentioned. - Conclusions Maximally effective treatment may need to focus on eliciting a range of benefits of cessation and control strategies and on maximizing both support for change and resistance to peer pressure. Further research might focus on comparing perceived effective strategies between individuals who obtain sustained cessation versus those who relapse.

Spatial and vertical heterogeneities in aerosol properties over oceanic regions around India: Implications for radiative forcing

The influence of atmospheric aerosols on Earth's radiation budget and hence climate, though well recognized and extensively investigated in recent years, remains largely uncertain mainly because of the large spatio-temporal heterogeneity and the lack of data with adequate resolution. To characterize this diversity, a major multi-platform field campaign ICARB (Integrated Campaign for Aerosols, gases and Radiation Budget) was carried out during the pre-monsoon period of 2006 over the Indian landmass and surrounding oceans, which was the biggest such campaign ever conducted over this region. Based on the extensive and concurrent measurements of the optical and physical properties of atmospheric aerosols during ICARB, the spatial distribution of aerosol radiative forcing was estimated over the entire Bay of Bengal (BoB), northern Indian Ocean and Arabian Sea (AS) as well as large spatial variations within these regions. Besides being considerably lower than the mean values reported earlier for this region, our studies have revealed large differences in the forcing components between the BoB and the AS. While the regionally averaged aerosol-induced atmospheric forcing efficiency was 31 +/- 6 W m(-2) tau(-1) for the BoB, it was only similar to 18 +/- 7 W m(-2) tau(-1) for the AS. Airborne measurements revealed the presence of strong, elevated aerosol layers even over the oceans, leading to vertical structures in the atmospheric forcing, resulting in significant warming in the lower troposphere. These observations suggest serious climate implications and raise issues ranging from the impact of aerosols on vertical thermal structure of the atmospheric and hence cloud formation processes to monsoon circulation.

Reasoning about discontinuance of information system use

While many studies have explored conditions and consequences of information systems adoption and use, few have focused on the final stages of the information system lifecycle. In this paper, I develop a theoretical and an initial empirical contribution to understanding individuals’ intentions to discontinue the use of an information system. This understanding is important because it yields implications about maintenance, retirement, and users’ switching decisions, which ultimately can affect work performance, system effectiveness, and return on technology investments. In this paper, I offer a new conceptualization of factors determining users’ intentions to discontinue the use of information systems. I then report on a preliminary empirical test of the model using data from a field study of information system users in a promotional planning routine in a large retail organization. Results from the empirical analysis provide first empirical support for the theoretical model. I discuss the work’s implications for theory on information systems continuance and dual-factor logic in information system use. I also provide suggestions for managers dealing with cessation of information systems and broader work routine change in organizations due to information system end-of-life decisions.

Influence of spatial variability of permeability property on steady state seepage flow and slope stability analysis

In recent years, spatial variability modeling of soil parameters using random field theory has gained distinct importance in geotechnical analysis. In the present Study, commercially available finite difference numerical code FLAC 5.0 is used for modeling the permeability parameter as spatially correlated log-normally distributed random variable and its influence on the steady state seepage flow and on the slope stability analysis are studied. Considering the case of a 5.0 m high cohesive-frictional soil slope of 30 degrees, a range of coefficients of variation (CoV%) from 60 to 90% in the permeability Values, and taking different values of correlation distance in the range of 0.5-15 m, parametric studies, using Monte Carlo simulations, are performed to study the following three aspects, i.e., (i) effect ostochastic soil permeability on the statistics of seepage flow in comparison to the analytic (Dupuit's) solution available for the uniformly constant permeability property; (ii) strain and deformation pattern, and (iii) stability of the given slope assessed in terms of factor of safety (FS). The results obtained in this study are useful to understand the role of permeability variations in slope stability analysis under different slope conditions and material properties. (C) 2009 Elsevier B.V. All rights reserved.

Kernel-based spatial-color modeling for fast moving object tracking

Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

Memory-efficient spatial prediction image compression scheme

In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates the predicted error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. In quantization phase, we used a modified SPIHT algorithm to achieve efficiency in memory requirements. The memory constraint plays a vital role in wireless and bandwidth-limited applications. A single reusable list is used instead of three continuously growing linked lists as in case of SPIHT. This method is error resilient. The performance is measured in terms of PSNR and memory requirements. The algorithm shows good compression performance and significant savings in memory. (C) 2006 Elsevier B.V. All rights reserved.