The ranking based constrained document clustering method and its application to social event detection

With the growing size and variety of social media files on the web, it’s becoming critical to efficiently organize them into clusters for further processing. This paper presents a novel scalable constrained document clustering method that harnesses the power of search engines capable of dealing with large text data. Instead of calculating distance between the documents and all of the clusters’ centroids, a neighborhood of best cluster candidates is chosen using a document ranking scheme. To make the method faster and less memory dependable, the in-memory and in-database processing are combined in a semi-incremental manner. This method has been extensively tested in the social event detection application. Empirical analysis shows that the proposed method is efficient both in computation and memory usage while producing notable accuracy.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

Supernatants of acquired immunodeficiency syndrome-related Kaposi's sarcoma cells induce endothelial cell chemotaxis and invasiveness

Kaposi's sarcoma (KS) in general, and acquired immunodeficiency syndrome-related KS (AIDS-KS) in particular, is a highly invasive and intensely angiogenic neoplasm of unknown cellular origin. We have recently established AIDS-KS cells in long term culture and reported the development of KS-like lesions in nude mice inoculated with these cells. Here, we have examined the in vitro invasiveness of basement membrane by AIDS-KS cells, as well as the effect(s) of their supernatants on the migration and invasiveness of human vascular endothelial cells. AIDS-KS cells were highly invasive in the Boyden chamber invasion assay and formed invasive, branching colonies in a 3-dimensional gel (Matrigel). Normal endothelial cells form tube-like structures on Matrigel. AIDS-KS cell-conditioned media induced endothelial cells to form invasive clusters in addition to tubes. KS-cell-conditioned media, when placed in the lower compartment of the Boyden chamber, stimulated the migration of human and bovine vascular endothelial cells across filters coated with either small amounts of collagen IV (chemotaxis) or a Matrigel barrier (invasion). Basic fibroblast growth factor could also induce endothelial cell chemotaxis and invasion in these assays. However, when antibodies to basic fibroblast growth factor were used the invasive activity induced by the AIDS-KS-cell-conditioned media was only marginally inhibited, suggesting that the large quantities of basic fibroblast growth factor-like material released by the AIDS-KS cells are not the main mediators of this effect. Specific inhibitors of laminin and collagenase IV action, which represent critical determinants of basement membrane invasion, blocked the invasiveness of the AIDS-KS cell-activated endothelial cells in these assays. These data indicate that KS cells appear to be of smooth muscle origin but secrete a potent inducer of endothelial cell chemotaxis and invasiveness which could be responsible for angiogenesis and the resulting highly vascularized lesions. These assays appear to be a model to study the invasive spread and angiogenic capacity of human AIDS-related KS and should prove useful in the identification of molecular mediators and potential inhibitors of neoplastic neovascularization.

Geographic co-distribution of influenza virus subtypes H7N9 and H5N1 in humans, China

Human infection with a novel low pathogenicity influenza A(H7N9) virus in eastern China has recently raised global public health concerns (1). The geographic sources of infection have yet to be fully clarified, and confirmed human cases from 1 province have not been linked to those from other provinces. While some studies have identified epidemiologic characteristics of subtype H7N9 cases and clinical differences between these cases and cases of highly pathogenic influenza A(H5N1), another avian influenza affecting parts of China (2–4), the spatial epidemiology of human infection with influenza subtypes H7N9 and H5N1 in China has yet to be elucidated. To test the hypothesis of co-distribution of high-risk clusters of both types of infection, we used all available data on human cases in mainland China and investigated the geospatial epidemiologic features...

Characterising the spatial dynamics of sympatric Aedes aegypti and Aedes albopictus populations in the Philippines

Entomological surveillance and control are essential to the management of dengue fever (DF). Hence, understanding the spatial and temporal patterns of DF vectors, Aedes (Stegomyia) aegypti (L.) and Ae. (Stegomyia) albopictus (Skuse), is paramount. In the Philippines, resources are limited and entomological surveillance and control are generally commenced during epidemics, when transmission is difficult to control. Recent improvements in spatial epidemiological tools and methods offer opportunities to explore more efficient DF surveillance and control solutions: however, there are few examples in the literature from resource-poor settings. The objectives of this study were to: (i) explore spatial patterns of Aedes populations and (ii) predict areas of high and low vector density to inform DF control in San Jose village, Muntinlupa city, Philippines. Fortnightly, adult female Aedes mosquitoes were collected from 50 double-sticky ovitraps (SOs) located in San Jose village for the period June-November 2011. Spatial clustering analysis was performed to identify high and low density clusters of Ae. aegypti and Ae. albopictus mosquitoes. Spatial autocorrelation was assessed by examination of semivariograms, and ordinary kriging was undertaken to create a smoothed surface of predicted vector density in the study area. Our results show that both Ae. aegypti and Ae. albopictus were present in San Jose village during the study period. However, one Aedes species was dominant in a given geographic area at a time, suggesting differing habitat preferences and interspecies competition between vectors. Density maps provide information to direct entomological control activities and advocate the development of geographically enhanced surveillance and control systems to improve DF management in the Philippines.

Frizzled-7 receptor ectodomain expression in a colon cancer cell line induces morphological change and attenuates tumor growth

Frizzled (FZD) receptors have a conserved N-terminal extracellular cysteine-rich domain that interacts with Wnts and co-expression of the receptor ectodomain can antagonize FZD-mediated signalling. Using the ectodomain as an antagonist we have modulated endogenous FZD7 signalling in the moderately differentiated colon adenocarcinoma cell line, SK-CO-1. Unlike the parental cell line, which grows as tightly associated adherent cell clusters, the FZD7 ectodomain expressing cells display a spread out morphology and grow as a monolayer in tissue culture. This transition in morphology was associated with decreased levels of plasma membrane-associated E-cadherin and β-catenin, localized increased levels of vimentin and redistribution of α6 integrin to cellular processes in the FZD7 ectodomain expressing cells. The morphological and phenotype changes induced by FZD7 ectodomain expression in SK-CO-1 cells is thus consistent with the cells undergoing an epithelial-to-mesenchymal-like transition. Furthermore, initiation of tumor formation in a xenograft tumor growth assay was attenuated in the FZD7 ectodomain expressing cells. Our results indicate a pivotal role for endogenous FZD7 in morphology transitions that are associated with colon tumor initiation and progression.

Conceptualising, evaluating and reporting social resilience in vulnerable regional and remote communities facing climate change in tropical Queensland : marine and tropical sciences research facility transition project final report

Regional and remote communities in tropical Queensland are among Australia’s most vulnerable in the face of climate change. At the same time, these socially and economically vulnerable regions house some of Australia’s most significant biodiversity values. Past approaches to terrestrial biodiversity management have focused on tackling biophysical interventions through the use of biophysical knowledge. An equally important focus should be placed on building regional-scale community resilience if some of the worst biodiversity impacts of climate change are to be avoided or mitigated. Despite its critical need, more systemic or holistic approaches to natural resource management have been rarely trialed and tested in a structured way. Currently, most strategic interventions in improving regional community resilience are ad hoc, not theory-based and short term. Past planning approaches have not been durable, nor have they been well informed by clear indicators. Research into indicators for community resilience has been poorly integrated within adaptive planning and management cycles. This project has aimed to resolve this problem by: * Reviewing the community and social resilience and adaptive planning literature to reconceptualise an improved framework for applying community resilience concepts; * Harvesting and extending work undertaken in MTSRF Phase 1 to identifying the learnings emerging from past MTSRF research; * Distilling these findings to identify new theoretical and practical approaches to the application of community resilience in natural resource use and management; * Reconsidering the potential interplay between a region’s biophysical and social planning processes, with a focus on exploring spatial tools to communicate climate change risk and its consequent environmental, economic and social impacts, and; * Trialling new approaches to indicator development and adaptive planning to improve community resilience, using a sub-regional pilot in the Wet Tropics. In doing so, we also looked at ways to improve the use and application of relevant spatial information. Our theoretical review drew upon the community development, psychology and emergency management literature to better frame the concept of community resilience relative to aligned concepts of social resilience, vulnerability and adaptive capacity. Firstly, we consider community resilience as a concept that can be considered at a range of scales (e.g. regional, locality, communities of interest, etc.). We also consider that overall resilience at higher scales will be influenced by resilience levels at lesser scales (inclusive of the resilience of constituent institutions, families and individuals). We illustrate that, at any scale, resilience and vulnerability are not necessarily polar opposites, and that some understanding of vulnerability is important in determining resilience. We position social resilience (a concept focused on the social characteristics of communities and individuals) as an important attribute of community resilience, but one that needs to be considered alongside economic, natural resource, capacity-based and governance attributes. The findings from the review of theory and MTSRF Phase 1 projects were synthesized and refined by the wider project team. Five predominant themes were distilled from this literature, research review and an expert analysis. They include the findings that: 1. Indicators have most value within an integrated and adaptive planning context, requiring an active co-research relationship between community resilience planners, managers and researchers if real change is to be secured; 2. Indicators of community resilience form the basis for planning for social assets and the resilience of social assets is directly related the longer term resilience of natural assets. This encourages and indeed requires the explicit development and integration of social planning within a broader natural resource planning and management framework; 3. Past indicator research and application has not provided a broad picture of the key attributes of community resilience and there have been many attempts to elicit lists of “perfect” indicators that may never be useful within the time and resource limitations of real world regional planning and management. We consider that modeling resilience for proactive planning and prediction purposes requires the consideration of simple but integrated clusters of attributes; 4. Depending on time and resources available for planning and management, the combined use of well suited indicators and/or other lesser “lines of evidence” is more flexible than the pursuit of perfect indicators, and that; 5. Index-based, collaborative and participatory approaches need to be applied to the development, refinement and reporting of indicators over longer time frames. We trialed the practical application of these concepts via the establishment of a collaborative regional alliance of planners and managers involved in the development of climate change adaptation strategies across tropical Queensland (the Gulf, Wet Tropics, Cape York and Torres Strait sub-regions). A focus on the Wet Tropics as a pilot sub-region enabled other Far North Queensland sub-region’s to participate and explore the potential extension of this approach. The pilot activities included: * Further exploring ways to innovatively communicate the region’s likely climate change scenarios and possible environmental, economic and social impacts. We particularly looked at using spatial tools to overlay climate change risks to geographic communities and social vulnerabilities within those communities; * Developing a cohesive first pass of a State of the Region-style approach to reporting community resilience, inclusive of regional economic viability, community vitality, capacitybased and governance attributes. This framework integrated a literature review, expert (academic and community) and alliance-based contributions; and * Early consideration of critical strategies that need to be included in unfolding regional planning activities with Far North Queensland. The pilot assessment finds that rural, indigenous and some urban populations in the Wet Tropics are highly vulnerable and sensitive to climate change and may require substantial support to adapt and become more resilient. This assessment finds that under current conditions (i.e. if significant adaptation actions are not taken) the Wet Tropics as a whole may be seriously impacted by the most significant features of climate change and extreme climatic events. Without early and substantive action, this could result in declining social and economic wellbeing and natural resource health. Of the four attributes we consider important to understanding community resilience, the Wet Tropics region is particularly vulnerable in two areas; specifically its economic vitality and knowledge, aspirations and capacity. The third and fourth attributes, community vitality and institutional governance are relatively resilient but are vulnerable in some key respects. In regard to all four of these attributes, however, there is some emerging capacity to manage the possible shocks that may be associated with the impacts of climate change and extreme climatic events. This capacity needs to be carefully fostered and further developed to achieve broader community resilience outcomes. There is an immediate need to build individual, household, community and sectoral resilience across all four attribute groups to enable populations and communities in the Wet Tropics region to adapt in the face of climate change. Preliminary strategies of importance to improve regional community resilience have been identified. These emerging strategies also have been integrated into the emerging Regional Development Australia Roadmap, and this will ensure that effective implementation will be progressed and coordinated. They will also inform emerging strategy development to secure implementation of the FNQ 2031 Regional Plan. Of most significance in our view, this project has taken a co-research approach from the outset with explicit and direct importance and influence within the region’s formal planning and management arrangements. As such, the research: * Now forms the foundations of the first attempt at “Social Asset” planning within the Wet Tropics Regional NRM Plan review; * Is assisting Local government at regional scale to consider aspects of climate change adaptation in emerging planning scheme/community planning processes; * Has partnered the State government (via the Department of Infrastructure and Planning and Regional Managers Coordination Network Chair) in progressing the Climate Change adaptation agenda set down within the FNQ 2031 Regional Plan; * Is informing new approaches to report on community resilience within the GBRMPA Outlook reporting framework; and * Now forms the foundation for the region’s wider climate change adaptation priorities in the Regional Roadmap developed by Regional Development Australia. Through the auspices of Regional Development Australia, the outcomes of the research will now inform emerging negotiations concerning a wider package of climate change adaptation priorities with State and Federal governments. Next stage research priorities are also being developed to enable an ongoing alliance between researchers and the region’s climate change response.

Universal codes from switching strategies

We discuss algorithms for combining sequential prediction strategies, a task which can be viewed as a natural generalisation of the concept of universal coding. We describe a graphical language based on Hidden Markov Models for defining prediction strategies, and we provide both existing and new models as examples. The models include efficient, parameterless models for switching between the input strategies over time, including a model for the case where switches tend to occur in clusters, and finally a new model for the scenario where the prediction strategies have a known relationship, and where jumps are typically between strongly related ones. This last model is relevant for coding time series data where parameter drift is expected. As theoretical contributions we introduce an interpolation construction that is useful in the development and analysis of new algorithms, and we establish a new sophisticated lemma for analysing the individual sequence regret of parameterised models.

Enhanced electron field emission from plasma-nitrogenated carbon nanotips

Nitrogenated carbon nanotips (NCNTPs) are synthesized by plasma-enhanced hot filament chemical vapor deposition from the hydrogen, methane, and nitrogen gas mixtures with different flow rate ratios of hydrogen to nitrogen. The morphological, structural, compositional, and electron field emission (EFE) properties of the NCNTPs were investigated by field emissionscanning electron microscopy, Raman spectroscopy, x ray photoelectron spectroscopy, and EFE high-vacuum system. It is shown that the NCNTPs deposited at an intermediate flow rate ratio of hydrogen to nitrogen feature the best size/shape and pattern uniformity, the highest nanotip density, the highest nitrogen concentration, as well as the best electron field emission performance. Several factors that come into play along with the nitrogen incorporation, such as the combined effect of the plasma sputtering and etching, the transition of sp 3carbon clusters to sp 2carbon clusters, the increase of the size of the sp 2 clusters, as well as the reduction of the work function, have been examined to interpret these experimental findings. Our results are highly relevant to the development of the next generation electron field emitters, flat panel displays, atomic force microscope probes, and several other advanced applications.

Do spoken nonword and sentence repetition tasks discriminate language impairment in children with an ASD?

The primary aim of this paper was to investigate heterogeneity in language abilities of children with a confirmed diagnosis of an ASD (N = 20) and children with typical development (TD; N = 15). Group comparisons revealed no differences between ASD and TD participants on standard clinical assessments of language ability, reading ability or nonverbal intelligence. However, a hierarchical cluster analysis based on spoken nonword repetition and sentence repetition identified two clusters within the combined group of ASD and TD participants. The first cluster (N = 6) presented with significantly poorer performances than the second cluster (N = 29) on both of the clustering variables in addition to single word and nonword reading. The significant differences between the two clusters occur within a context of Cluster 1 having language impairment and a tendency towards more severe autistic symptomatology. Differences between the oral language abilities of the first and second clusters are considered in light of diagnosis, attention and verbal short term memory skills and reading impairment.

Ge/Si quantum dot formation from non-uniform cluster fluxes

The controlled growth of ultra-small Ge/Si quantum dot (QD) nuclei (≈1 nm) suitable for the synthesis of uniform nanopatterns with high surface coverage, is simulated using atom-only and size non-uniform cluster fluxes. It is found that seed nuclei of more uniform sizes are formed when clusters of non-uniform size are deposited. This counter-intuitive result is explained via adatom-nanocluster interactions on Si(100) surfaces. Our results are supported by experimental data on the geometric characteristics of QD patterns synthesized by nanocluster deposition. This is followed by a description of the role of plasmas as non-uniform cluster sources and the impact on surface dynamics. The technique challenges conventional growth modes and is promising for deterministic synthesis of nanodot arrays.

Catalytic reduction of SO2 by CO over Pt l Au m (CO) n: a first-principles investigation

The catalytic activities, to the reduction of SO2 by CO, of clusters PtlAum (l + m = 2) with or without preadsorbing CO molecules are investigated using first-principles density functional theory. We find that the PtAu(CO)n (n = 1–3) clusters show more excellent catalytic properties than either pure metallic catalysts. Preadsorption of CO to the catalysts could effectively avoid platinum-based catalyst sulfur poisoning; as more CO molecules preadsorbed to the catalysts, the energy barriers for the carbonyl sulfide (COS) molecule’s desorption from the catalyst are remarkably decreased. We propose an ideal catalytic cycle to simultaneously get rid of SO2 and CO over the catalysts PtAu(CO)3.

Dynamic self-organization phenomena in complex ionized gas systems : new paradigms and technological aspects

An overview of dynamic self-organization phenomena in complex ionized gas systems, associated physical phenomena, and industrial applications is presented. The most recent experimental, theoretical, and modeling efforts to understand the growth mechanisms and dynamics of nano- and micron-sized particles, as well as the unique properties of the plasma-particle systems (colloidal, or complex plasmas) and the associated physical phenomena are reviewed and the major technological applications of micro- and nanoparticles are discussed. Until recently, such particles were considered mostly as a potential hazard for the microelectronic manufacturing and significant efforts were applied to remove them from the processing volume or suppress the gas-phase coagulation. Nowadays, fine clusters and particulates find numerous challenging applications in fundamental science as well as in nanotechnology and other leading high-tech industries.

Document clustering algorithms, representations and evaluation for information retrieval

This thesis presents new methods for classification and thematic grouping of billions of web pages, at scales previously not achievable. This process is also known as document clustering, where similar documents are automatically associated with clusters that represent various distinct topic. These automatically discovered topics are in turn used to improve search engine performance by only searching the topics that are deemed relevant to particular user queries.