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.

Empowerment climate, supervisory support for creativity and work role performance in new product development settings: A team level investigation

This thesis is an examination of how organisational context variables affect the performance of new product development (NPD) teams. Specifically, the extent to how team empowerment climate and supervisory support for creativity impact NPD team performance. Moreover, this thesis is a step forward in the ongoing development of work role performance theory by examining Griffin et al.'s (2007) work role performance model in the context of NPD teams. This thesis addresses the lack of research exploring work role performance dimensions in NPD teams and the extent to which a team empowerment climate and supervisory support for creativity impact NPDs performance.

Ferrous iron oxidation by foam immobilized Acidithiobacillus ferrooxidans: Experiments and modeling

Ferrous iron bio-oxidation by Acidithiobacillus ferrooxidans immobilized on polyurethane foam was investigated. Cells were immobilized on foams by placing them in a growth environment and fully bacterially activated polyurethane foams (BAPUFs) were prepared by serial subculturing in batches with partially bacterially activated foam (pBAPUFs). The dependence of foam density on cell immobilization process, the effect of pH and BAPUF loading on ferrous oxidation were studied to choose operating parameters for continuous operations. With an objective to have high cell densities both in foam and the liquid phase, pretreated foams of density 50 kg/m3 as cell support and ferrous oxidation at pH 1.5 to moderate the ferric precipitation were preferred. A novel basket-type bioreactor for continuous ferrous iron oxidation, which features a multiple effect of stirred tank in combination with recirculation, was designed and operated. The results were compared with that of a free cell and a sheet-type foam immobilized reactors. A fivefold increase in ferric iron productivity at 33.02 g/h/L of free volume in foam was achieved using basket-type bioreactor when compared to a free cell continuous system. A mathematical model for ferrous iron oxidation by Acidithiobacillus ferrooxidans cells immobilized on polyurethane foam was developed with cell growth in foam accounted by an effectiveness factor. The basic parameters of simulation were estimated using the experimental data on free cell growth as well as from cell attachment to foam under nongrowing conditions. The model predicted the phase of both oxidation of ferrous in shake flasks by pBAPUFs as well as by fully activated BAPUFs for different cell loadings in foam. Model for stirred tank basket bioreactor predicted within 5% both transient and steady state of the experiments closely for the simulated dilution rates. Bio-oxidation at high Fe2+ concentrations were simulated with experiments when substrate and product inhibition coefficients were factored into cell growth kinetics.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

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.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

Surveillance of Surgical Site Infections following Major Hip and Knee Surgery in Finland

Background and aims. Since 1999, hospitals in the Finnish Hospital Infection Program (SIRO) have reported data on surgical site infections (SSI) following major hip and knee surgery. The purpose of this study was to obtain detailed information to support prevention efforts by analyzing SIRO data on SSIs, to evaluate possible factors affecting the surveillance results, and to assess the disease burden of postoperative prosthetic joint infections in Finland. Methods. Procedures under surveillance included total hip (THA) and total knee arthroplasties (TKA), and the open reduction and internal fixation (ORIF) of femur fractures. Hospitals prospectively collected data using common definitions and written protocol, and also performed postdischarge surveillance. In the validation study, a blinded retrospective chart review was performed and infection control nurses were interviewed. Patient charts of deep incisional and organ/space SSIs were reviewed, and data from three sources (SIRO, the Finnish Arthroplasty Register, and the Finnish Patient Insurance Centre) were linked for capture-recapture analyses. Results. During 1999-2002, the overall SSI rate was 3.3% after 11,812 orthopedic procedures (median length of stay, eight days). Of all SSIs, 56% were detected after discharge. The majority of deep incisional and organ/space SSIs (65/108, 60%) were detected on readmission. Positive and negative predictive values, sensitivity, and specificity for SIRO surveillance were 94% (95% CI, 89-99%), 99% (99-100%), 75% (56-93%), and 100% (97-100%), respectively. Of the 9,831 total joint replacements performed during 2001-2004, 7.2% (THA 5.2% and TKA 9.9%) of the implants were inserted in a simultaneous bilateral operation. Patients who underwent bilateral operations were younger, healthier, and more often males than those who underwent unilateral procedures. The rates of deep SSIs or mortality did not differ between bi- and uni-lateral THAs or TKAs. Four deep SSIs were reported following bilateral operations (antimicrobial prophylaxis administered 48-218 minutes before incision). In the three registers, altogether 129 prosthetic joint infections were identified after 13,482 THA and TKA during 1999-2004. After correction with the positive predictive value of SIRO (91%), a log-linear model provided an estimated overall prosthetic joint infection rate of 1.6% after THA and 1.3% after TKA. The sensitivity of the SIRO surveillance ranged from 36% to 57%. According to the estimation, nearly 200 prosthetic joint infections could occur in Finland each year (the average from 1999 to 2004) after THA and TKA. Conclusions. Postdischarge surveillance had a major impact on SSI rates after major hip and knee surgery. A minority of deep incisional and organ/space SSIs would be missed, however, if postdischarge surveillance by questionnaire was not performed. According to the validation study, most SSIs reported to SIRO were true infections. Some SSIs were missed, revealing some weakness in case finding. Variation in diagnostic practices may also affect SSI rates. No differences were found in deep SSI rates or mortality between bi- and unilateral THA and TKA. However, patient materials between these two groups differed. Bilateral operations require specific attention paid to their antimicrobial prophylaxis as well as to data management in the surveillance database. The true disease burden of prosthetic joint infections may be heavier than the rates from national nosocomial surveillance systems usually suggest.

Social and environmental reporting practices of organisations operating in, or sourcing products from, a developing country : evidence from Bangladesh

This research consists of a broad study in three parts of the social and environmental reporting practices of organisations operating in or sourcing products from a developing country, in this case Bangladesh. The first part of this study explores the social and environmental disclosure practices of the Bangladesh Garment Manufacturers and Exporters Association (BGMEA), the body responsible for organising the activities of 4,200 entities involved in the export of garments from Bangladesh. By way of interview, this part documents the opinions of numerous senior executives from the BGMEA with regard to any changes in the degree of social and environmental pressures since 1985. Utilising a complementary theoretical perspective that includes legitimacy theory, stakeholder theory and institutional theory this part then performs an analysis of the BGMEA's annual reports (1987-2005), t o explore the link between the perceived pressures and changes entailed therein and the social and environmental disclosure practices of the BGMEA across the period of analysis. The results show that the disclosure practices of BGMEA appear to be directly driven by the changing expectations of multinational buying companies- the group deemed to be the most powerful stakeholder group. This section is the first known study to interview managers from a large organisation in a developing country about shifting stakeholder expectations and then to link these changing expectations to annual report disclosures across an extended period of analysis. The findings then directly lead to the second major part of this thesis which investigates the social and environmental disclosure practices of two major multinational buying companies: Nike and H&M. Adopting a joint consideration of legitimacy theory and media agenda setting theory, this second part investigates the linkage between negative media attention and positive corporate social and environmental disclosures over a 19 year period. The results support the view that for those industry-related social and environmental issues that attract the greatest amount of negative media attention, these companies react by providing positive social and environmental disclosures. The results were particularly significant in relation to labour practices in developing countries-the issue that attracts the greatest amount of negative media attention for the companies in question. While the second part demonstrates that the media influences particular disclosure practices, the third part of the thesis shows what drives the media. Based on the speculation provided in the second part, the third part tests the proposition that the media is an important ally of NGOs in their quest to influence change in corporate accountabilities. Through the use of interviews, the results of this part of the study provide evidence to support previously untested perspectives about NGOs' utilisation of the m edia. The results reveal that NGOs use the media because the media is responsible for creating real changes in the operations and disclosure policies of organisations sourcing products from Bangladesh. The various pressures impacting the activities of organisations operating in or sourcing products from developing countries constitutes a fascinating area of investigation, and it is hoped that this study will motivate further research in this area.

Preparation of reticulated MAX-phase support with morphology-controllable nanostructured ceria coating for gas exhaust catalyst devices

Reticulated porous Ti3AlC2 ceramic, a member of the MAX-phase family (Mn+1AXn phases, where M is an early transition metal, A is an A-group element, and X is carbon and/or nitrogen), was prepared from the highly dispersed aqueous suspension by a replica template method. Through a cathodic electrogeneration method, nanocrystalline catalytic CeO2 coatings were deposited on the conductive porous Ti 3AlC2 supports. By adjusting the pH value and cathodic deposition current, coatings exhibiting nanocellar, nanosheets-like, or bubble-free morphologies can be obtained. This work expects to introduce a novel practically feasible material system and a catalytic coating preparation technique for gas exhaust catalyst devices.

Kallikrein-related peptidase 4 induces tumour microenvironment alterations that support tumour growth

Kallikrein-related peptidase 4 (KLK4) is a protease with elevated production in prostate cancer versus benign tissue. KLK4 expression is associated with prostate cancer risk, and its activity favours tumour progression through increasing cell motility and growth. Importantly, over-production of KLK4 in prostate glandular cells precedes tumour formation, positioning the enzyme to play a role in early remodelling of the tumour microenvironment, a process essential for tumour growth. We sought to identify the proteins and downstream signalling pathways targeted by KLK4 activity, to define its role in tumour microenvironment remodelling and evaluate the efficacy of KLK4 inhibition as a cancer therapy.

Conceptualising social media support for tacit knowledge sharing: physicians’ perspectives and experiences

Purpose – This paper aims to explore the potential contributions of social media in supporting tacit knowledge sharing, according to the physicians’ perspectives and experiences. Design/methodology/approach – Adopting a qualitative survey design, 24 physicians were interviewed. Purposive and snowball sampling were used to select the participants. Thematic analysis approach was used for data analysis. Findings – The study revealed five major themes and over 20 sub-themes as potential contributions of social media to tacit knowledge flow among physicians. The themes included socialising, practising, networking, storytelling and encountering. In addition, with the help of the literature and the supporting data, the study proposed a conceptual model that explains the potential contribution of social media to tacit knowledge sharing. Research limitations/implications – The study had both theoretical (the difficulty of distinguishing tacit and explicit knowledge in practice) and practical limitations (small sample size). The study findings have implications for the healthcare industry whose clinical teams are not always physically co-located but must exchange their critical experiential and tacit knowledge. Originality/value – The study has opened up a new discussion of this area by demonstrating and conceptualising how social media tools may facilitate tacit knowledge sharing.

Cluster based training for scaling non-linear support vector machines

Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.