Urban growth in the Kathmandu Valley: The transformation of public space

Traditional towns of the Kathmandu Valley boast a fine provision of public spaces in their neighbourhoods. Historically, a hierarchy of public space has been distributed over the entire town with each neighbourhood centered around more or less spacious public squares. However, rapid growth of these towns over the past decades has resulted in haphazard development of new urban areas with little provision of public space. Recent studies indicate that the loss of public space is a major consequence of the uncontrolled urban growth of the Kathmandu Valley and its new neighbourhoods. This paper reviews the current urban growth of the Kathmandu Valley and its impact on the development of public space in new neighbourhoods. The preliminary analysis of the case study of three new neighbourhoods shows that the formation and utilization of neighbourhood public space exhibit fundamental differences from those found in the traditional city cores. The following key issues are identified in this paper: a) Governance and regulations have been a challenge to regulate rapid urban growth; b) The current pattern of neighbourhood formation is found to be different from that of traditional neighbourhoods due to the changes with rapid urban development; c) Public spaces have been compromised in both planned and unplanned new neighbourhoods in terms of their quantity and quality; d) The changing provision of public space has contributed to its changing use and meaning; and e) The changing demographic composition, changing society and life style have had direct impact on the declining use of public space. Moreover, the management of public spaces remains a big challenge due to their changing nature and the changing governance. The current transformation public space does not appear to be conducive, and has led to adversely changing social environment of the new neighbourhoods.

Regulation of P-fimbrial phase variation frequencies in Escherichia coli CFT073

Adherence of uropathogenic Escherichia coli to host tissue is required for infection and is mediated by fimbriae, such as pyelonephritis-associated pili (Pap). Expression of P fimbriae is regulated by phase variation, and to date, phase transition frequencies have been measured only for pap regulatory region constructs integrated into the E. coli K-12 chromosome. The aim of this work was to measure P phase transition frequencies in clinical isolates for the first time, including frequencies for the sequenced strain E. coli CFT073. P fimbriation and associated phase transition frequencies were measured for two E. coli clinical isolates and compared with levels for homologous pap constructs in E. coli K-12. Fimbriation and off-to-on transition frequencies were always higher in the clinical isolate. It was concluded that the regulatory inputs controlling papI expression are likely to be different in E. coli CFT073 and E. coli K-12 as (i) phase variation could be stimulated in E. coli K-12 by induction of papI and (ii) the level of expression of a papI::gfp+ fusion was higher in E. coli CFT073 than in E. coli K-12. Furthermore, phase transition frequencies for the two E. coli CFT073 pap clusters were shown to be different depending on the culture conditions, indicating that there is a hierarchy of expression depending on signal inputs.

Stem-like cells with luminal progenitor phenotype survive castration in human prostate cancer

Castration is the standard therapy for advanced prostate cancer (PC). Although this treatment is initially effective, tumors invariably relapse as incurable, castration-resistant PC (CRPC). Adaptation of androgen-dependent PC cells to an androgen-depleted environment or selection of pre-existing,CRPC cells have been proposed as mechanisms of CRPC development. Stem cell (SC)-like PC cells have been implicated not only as tumor initiating/maintaining in PC but also as tumor-reinitiating cells in CRPC. Recently, castration-resistant cells expressing the NK3 homeobox 1 (Nkx3-1) (CARNs), the other luminal markers cytokeratin 18 (CK18) and androgen receptor (AR), and possessing SC properties, have been found in castrated mouse prostate and proposed as the cell-of-origin of CRPC. However, the human counterpart of CARNs has not been identified yet. Here, we demonstrate that in the human PC xenograft BM18, preexisting SC-like and neuroendocrine (NE) PC cells are selected by castration and survive as totally quiescent. SClike BM18 cells, displaying the SC markers aldehyde dehydrogenase 1A1 or NANOG, coexpress the luminal markers NKX3-1, CK18, and a low level of AR (ARlow) but not basal or NE markers. These CR luminal SC-like cells, but not NE cells, reinitiate BM18 tumor growth after androgen replacement. The ARlow seems to mediate directly both castration survival and tumor reinitiation. This study identifies for the first time in human PC SC-/CARN-like cells that may represent the cell-of-origin of tumor reinitiation as CRPC. This finding will be fundamental for refining the hierarchy among human PC cancer cells and may have important clinical implications.

Setting the agenda, influencing public opinion, and advocating for social change

This study seeks to contribute to the systematic explanation of journalists’ professional role orientations. Focusing on three aspects of journalistic interventionism – the importance of setting the political agenda, influencing public opinion and advocating for social change – multilevel analyses found substantive variation in interventionism at the individual level of the journalist, the level of the media organizations, and the societal level. Based on interviews with 2100 journalists from 21 countries, findings affirm theories regarding a hierarchy of influences in news work. We found journalists to be more willing to intervene in society when they work in public media organizations and in countries with restricted political freedom. An important conclusion of our analysis is that journalists’ professional role orientations are also rooted within perceptions of cultural and social values. Journalists were more likely to embrace an interventionist role when they were more strongly motivated by the value types of power, achievement and tradition.

Co-movements in commodity prices : a note based on network analysis

This article analyses co-movements in a wide group of commodity prices during the time period 1992–2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co-movement of the commodity prices in our time sample, however from mid-2008 to the end of 2009 co-movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains, and oilseeds) and which have increased their degree of co-movement during the sampled period.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

AITSL pilot projects [Queensland University of Technology : The existing school-based practices and processes for the use of NAPLAN data] Final report

This pilot project investigated the existing practices and processes of Proficient, Highly Accomplished and Lead teachers in the interpretation, analysis and implementation of National Assessment Program – Literacy and Numeracy (NAPLAN) data. A qualitative case study approach was the chosen methodology, with nine teachers across a variety of school sectors interviewed. Themes and sub-themes were identified from the participants’ interview responses revealing the ways in which Queensland teachers work with NAPLAN data. The data illuminated that generally individual schools and teachers adopted their own ways of working with data, with approaches ranging from individual/ad hoc, to hierarchical or a whole school approach. Findings also revealed that data are the responsibility of various persons from within the school hierarchy; some working with the data electronically whilst others rely on manual manipulation. Manipulation of data is used for various purposes including tracking performance, value adding and targeting programmes for specific groups of students, for example the gifted and talented. Whilst all participants had knowledge of intervention programmes and how practice could be modified, there were large inconsistencies in knowledge and skills across schools. Some see the use of data as a mechanism for accountability, whilst others mention data with regards to changing the school culture and identifying best practice. Overall, the findings showed inconsistencies in approach to focus area 5.4. Recommendations therefore include a more national approach to the use of educational data.

Destination Brand Performance Measurement Over Time

With increasing investments being made in brand development by destination marketing organisations (DMO) since the 1990s, including rebranding and repositioning, more research is necessary to enhance understanding of how to effectively monitor destination brand performance over time. This chapter summarises key findings from a study of brand performance of a competitive set of destinations, in their most important market, between 2003 and 2012. Brand performance was measured from the perspective of consumer perceptions, based on the concept of consumer-based brand equity (CBBE). The results indicated almost no change in perceptions of the five destinations over the 10-year period. Due to the commonality of challenges faced by DMOs worldwide, it is suggested the CBBE hierarchy provides destination marketers with a practical tool for evaluating brand performance over time; in terms of measures of effectiveness of past marketing communications, as well as indicators of future performance.

A continental-scale tool for acoustic identification of European bats

Summary 1. Acoustic methods are used increasingly to survey and monitor bat populations. However, the use of acoustic methods at continental scales can be hampered by the lack of standardized and objective methods to identify all species recorded. This makes comparable continent-wide monitoring difficult, impeding progress towards developing biodiversity indicators, transboundary conservation programmes and monitoring species distribution changes. 2. Here we developed a continental-scale classifier for acoustic identification of bats, which can be used throughout Europe to ensure objective, consistent and comparable species identifications. We selected 1350 full-spectrum reference calls from a set of 15 858 calls of 34 European species, from EchoBank, a global echolocation call library. We assessed 24 call parameters to evaluate how well they distinguish between species and used the 12 most useful to train a hierarchy of ensembles of artificial neural networks to distinguish the echolocation calls of these bat species. 3. Calls are first classified to one of five call-type groups, with a median accuracy of 97·6%. The median species-level classification accuracy is 83·7%, providing robust classification for most European species, and an estimate of classification error for each species. 4. These classifiers were packaged into an online tool, iBatsID, which is freely available, enabling anyone to classify European calls in an objective and consistent way, allowing standardized acoustic identification across the continent. 5. Synthesis and applications. iBatsID is the first freely available and easily accessible continental- scale bat call classifier, providing the basis for standardized, continental acoustic bat monitoring in Europe. This method can provide key information to managers and conservation planners on distribution changes and changes in bat species activity through time.

Synthetic rating system for railway bridge management

This thesis developed a condition assessment and rating method to identify those bridges in a network which are in most need of repair for an effective life cycle management. The method estimates the contribution of critical factors towards bridge deterioration and uses structural analysis to overcome the subjectivity of traditional current condition assessment methods. This research was a part of the CRC project titled 'Life Cycle Management of Railway Bridges'. Efficient usage of resources and enhancing the safety and serviceability of railway bridges are the significant outcomes of using the proposed method.

An architecture for trustworthy open data services

This paper addresses the development of trust in the use of Open Data through incorporation of appropriate authentication and integrity parameters for use by end user Open Data application developers in an architecture for trustworthy Open Data Services. The advantages of this architecture scheme is that it is far more scalable, not another certificate-based hierarchy that has problems with certificate revocation management. With the use of a Public File, if the key is compromised: it is a simple matter of the single responsible entity replacing the key pair with a new one and re-performing the data file signing process. Under this proposed architecture, the the Open Data environment does not interfere with the internal security schemes that might be employed by the entity. However, this architecture incorporates, when needed, parameters from the entity, e.g. person who authorized publishing as Open Data, at the time that datasets are created/added.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Evaluation of Interconnect Fabrics for an Embedded MPSoC in 28 nm FD-SOI

Embedded many-core architectures contain dozens to hundreds of CPU cores that are connected via a highly scalable NoC interconnect. Our Multiprocessor-System-on-Chip CoreVAMPSoC combines the advantages of tightly coupled bus-based communication with the scalability of NoC approaches by adding a CPU cluster as an additional level of hierarchy. In this work, we analyze different cluster interconnect implementations with 8 to 32 CPUs and compare them in terms of resource requirements and performance to hierarchical NoCs approaches. Using 28nm FD-SOI technology the area requirement for 32 CPUs and AXI crossbar is 5.59mm2 including 23.61% for the interconnect at a clock frequency of 830 MHz. In comparison, a hierarchical MPSoC with 4 CPU cluster and 8 CPUs in each cluster requires only 4.83mm2 including 11.61% for the interconnect. To evaluate the performance, we use a compiler for streaming applications to map programs to the different MPSoC configurations. We use this approach for a design-space exploration to find the most efficient architecture and partitioning for an application.

Integration of Opinion Mining into customer analysis model

This research proposes a multi-dimensional model for Opinion Mining, which integrates customers' characteristics and their opinions about products (or services). Customer opinions are valuable for companies to deliver right products or services to their customers. This research presents a comprehensive framework to evaluate opinions' orientation based on products' hierarchy attributes. It also provides an alternative way to obtain opinion summaries for different groups of customers and different categories of produces.

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship

Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.