Organotypic culture of normal, dysplastic and squamous cell carcinoma-derived oral cell lines reveals loss of spatial regulation of CD44 and p75(NTR) in malignancy

Oral squamous cell carcinomas (OSCC) often arise from dysplastic lesions. The role of cancer stem cells in tumour initiation is widely accepted, yet the potential existence of pre-cancerous stem cells in dysplastic tissue has received little attention. Cell lines from oral diseases ranging in severity from dysplasia to malignancy provide opportunity to investigate the involvement of stem cells in malignant progression from dysplasia. Stem cells are functionally defined by their ability to generate hierarchical tissue structures in consortium with spatial regulation. Organotypic cultures readily display tissue hierarchy in vitro; hence, in this study, we compared hierarchical expression of stem cell-associated markers in dermis-based organotypic cultures of oral epithelial cells from normal tissue (OKF6-TERT2), mild dysplasia (DOK), severe dysplasia (POE-9n) and OSCC (PE/CA P J15). Expression of CD44, p75NTR, CD24 and ALDH was studied in monolayers by flow cytometry and in organotypic cultures by immunohistochemistry. Spatial regulation of CD44 and p75NTR was evident for organotypic cultures of normal (OKF6-TERT2) and dysplasia (DOK and POE-9n) but was lacking for OSCC (PE/CA PJ15)-derived cells. Spatial regulation of CD24 was not evident. All monolayer cultures exhibited CD44, p75NTR, CD24 antigens and ALDH activity (ALDEFLUOR® assay), with a trend towards loss of population heterogeneity that mirrored disease severity. In monolayer, increased FOXA1 and decreased FOXA2 expression correlated with disease severity, but OCT3/4, Sox2 and NANOG did not. We conclude that dermis-based organotypic cultures give opportunity to investigate the mechanisms that underlie loss of spatial regulation of stem cell markers seen with OSCC-derived cells.

Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

‘The health-location connection’: using GIS and social media on smartphones to track engagement with the Local urban environment for work, recreation, and physical activity

A technologically innovative study was undertaken across two suburbs in Brisbane, Australia, to assess socioeconomic differences in women's use of the local environment for work, recreation, and physical activity. Mothers from high and low socioeconomic suburbs were instructed to continue with usual daily routines, and to use mobile phone applications (Facebook Places, Twitter, and Foursquare) on their mobile phones to ‘check-in’ at each location and destination they reached during a one-week period. These smartphone applications are able to track travel logistics via built-in geographical information systems (GIS), which record participants’ points of latitude and longitude at each destination they reach. Location data were downloaded to Google Earth and excel for analysis. Women provided additional qualitative data via text regarding the reasons and social contexts of their travel. We analysed 2183 ‘check-ins’ for 54 women in this pilot study to gain quantitative, qualitative, and spatial data on human-environment interactions. Data was gathered on distances travelled, mode of transport, reason for travel, social context of travel, and categorised in terms of physical activity type – walking, running, sports, gym, cycling, or playing in the park. We found that the women in both suburbs had similar daily routines with the exception of physical activity. We identified 15% of ‘check-ins’ in the lower socioeconomic group as qualifying for the physical activity category, compared with 23% in the higher socioeconomic group. This was explained by more daily walking for transport (1.7kms to 0.2kms) and less car travel each week (28.km to 48.4kms) in the higher socioeconomic suburb. We ascertained insights regarding the socio-cultural influences on these differences via additional qualitative data. We discuss the benefits and limitations of using new technologies and Google Earth with implications for informing future physical and social aspects of urban design, and health promotion in socioeconomically diverse cities.

The need for and appropriate application of spatial data for disaster management and strengthening community resilience

It is only in recent years that the critical role that spatial data can play in disaster management and strengthening community resilience has been recognised. The recognition of this importance is singularly evident from the fact that in Australia spatial data is considered as soft infrastructure. In the aftermath of every disaster this importance is being increasingly strengthened with state agencies paying greater attention to ensuring the availability of accurate spatial data based on the lessons learnt. For example, the major flooding in Queensland during the summer of 2011 resulted in a comprehensive review of responsibilities and accountability for the provision of spatial information during such natural disasters. A high level commission of enquiry completed a comprehensive investigation of the 2011 Brisbane flood inundation event and made specific recommendations concerning the collection of and accessibility to spatial information for disaster management and for strengthening community resilience during and after a natural disaster. The lessons learnt and processes implemented were subsequently tested by natural disasters during subsequent years. This paper provides an overview of the practical implementation of the recommendations of the commission of enquiry. It focuses particularly on the measures adopted by the state agencies with the primary role for managing spatial data and the evolution of this role in Queensland State, Australia. The paper concludes with a review of the development of the role and the increasing importance of spatial data as an infrastructure for disaster planning and management which promotes the strengthening of community resilience.

Capturing opportunities for business and innovation in knowledge intensive services

Research on opportunity has been extensively studied in contexts of new firm or new venture creation (Choi & Shepherd, 2004; Mullins & Forlani, 2005; Ozgen & Baron, 2007) where start-ups and new ventures use both opportunity discovery and opportunity creation (Alvarez & Barney 2005, 2007). Less research is found on examining the relationship between opportunity and innovation in existing firms (with Drucker (1985) an exception). In large firms, opportunity recognition has been analysed in terms of antecedent conditions, elements and outcomes (Ireland, Covin & Kuratko, 2009), but to date less attention has been given to how small and medium enterprises capture and use opportunities to remain competitive. Little research has been carried out regarding how smaller firms use opportunities to create new business with existing customers or use technological advances with new customers to create new economic activity, growth and competitive advantage. This study presents findings from a comparative case analysis of 20 diverse firms in the spatial information industry and identifies constructs associated with identifying opportunities that lead to better business performance and firm level innovation.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

GIS and qualitative data on young mothers’ use of urban neighbourhoods for physical activity

Public health research consistently demonstrates the salience of neighbourhood as a determinant of both health-related behaviours and outcomes across the human life course. This paper will report on the findings from a mixed-methods Brisbane-based study that explores how mothers with primary school children from both high and low socioeconomic suburbs use the local urban environment for the purpose of physical activity. Firstly, we demonstrate findings from an innovative methodology using the geographic information systems (GIS) embedded in social media platforms on mobile phones to track locations, resource-use, distances travelled, and modes of transport of the families in real-time; and secondly, we report on qualitative data that provides insight into reasons for differential use of the environment by both groups. Spatial/mapping and statistical data showed that while the mothers from both groups demonstrated similar daily routines, the mothers from the high SEP suburb engaged in increased levels of physical activity, travelled less frequently and less distance by car, and walked more for transport. The qualitative data revealed differences in the psychosocial processes and characteristics of the households and neighbourhoods of the respective groups, with mothers in the lower SEP suburb reporting more stress, higher conflict, and lower quality relationships with neighbours.

Mawson the astrobiologist rover : towards automatic recognition of stromatolites

This work aims at developing a planetary rover capable of acting as an assistant astrobiologist: making a preliminary analysis of the collected visual images that will help to make better use of the scientists time by pointing out the most interesting pieces of data. This paper focuses on the problem of detecting and recognising particular types of stromatolites. Inspired by the processes actual astrobiologists go through in the field when identifying stromatolites, the processes we investigate focus on recognising characteristics associated with biogenicity. The extraction of these characteristics is based on the analysis of geometrical structure enhanced by passing the images of stromatolites into an edge-detection filter and its Fourier Transform, revealing typical spatial frequency patterns. The proposed analysis is performed on both simulated images of stromatolite structures and images of real stromatolites taken in the field by astrobiologists.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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Personal media and wireless cities : towards an urban spatial analysis

For the past decade, at least, varieties of small, hand held networked instruments have appeared on the global scene, selling in record numbers, and being utilized by all manner of persons from the old to the young; children, women, men, the wealthy and the poor and in all countries. Their presences bespeak a radical shift in telecommunications infrastructure and the future of communications. They are particularly visible in urban areas where mobile transmission network infrastructure (3G, 4G, cellular and Wi-Fi) is more established and substantial, options more plentiful, and density of populations more dramatic. These end user products—I phones, cell phones, Blackberries, DSi, DS, IPads, Zooms, and others – of the mobile communications industry are the latest, hottest globalized commodities. At the same time, wirelessness, or the state of being wireless, and therefore capable of taking along one's networks, communicating from unlikely spaces, and navigating with GPS, is a complex social, political and economic communications phenomenon of early 21st century life. This thesis examines the specter of being wireless in cities. It lends the entire idea an experimentally envisioned, historical and planned context wherein personalization of media tools is seen both as a design development of corporate, artistic, and military imagination, as well as a profound social phenomenon enabling new forms of sharing, belonging, and urban community. In doing that it asserts the parameters of a new mobile space which, aside from clear benefits to humankind by way of mobility, has reinscribed numerous categories including gender. Moreover, it posits the recognition of other, more nuanced theoretical spaces for complex readings of gender and gendered use, including some instantiation of the notion of 'network' itself as a cyborgian and gendered social form. Additionally, cities are studied as places where technology is not only quickly popularized, but is connected to larger political interests, such as the reading of data, tracking of information, and the new security culture. In so doing the work has been undertaken as an urban spatial analysis and experimental ethnography, utilizing architectural, feminist, techno-utopian, industrial and theoretical literatures as discursive underpinnings from whence understandings and interpretations of mobile space, the mobile office, networked mobility, and personal media have come, linking the space of cities to specific, pioneering urban public art projects in which voice, texting and MMS have been utilized in expressions of ubiquitous networks and urban history. Through numerous examples of techno art, the thesis discusses the 'wireless city' as an emerging cultural, socially constructed economic and spatial entity, both conceived and formed through historic processes of urbanization.

Artificial neural networks to predict activity type and energy expenditure in youth

Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

Multi-scale bio-inspired place recognition

This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.

Spatial-temporal epidemiological analyses of two sympatric, co-endemic alphaviral diseases in Queensland, Australia

Background: The two most reported mosquito-borne diseases in Queensland, a northern state of Australia, are Ross River virus (RRV) disease and Barmah Forest virus (BFV) disease. Both diseases are endemic in Queensland and have similar clinical symptoms and comparable transmission cycles involving a complex inter-relationship between human hosts, various mosquito vectors, and a range of nonhuman vertebrate hosts, including marsupial mammals that are unique to the Australasian region. Although these viruses are thought to share similar vectors and vertebrate hosts, RRV is four times more prevalent than BFV in Queensland. Methods: We performed a retrospective analysis of BFV and RRV human disease notification data collected from 1995 to 2007 in Queensland to ascertain whether there were differences in the incidence patterns of RRV and BFV disease. In particular, we compared the temporal incidence and spatial distribution of both diseases and considered the relationship between their disease dynamics. We also investigated whether a peak in BFV incidence during spring was indicative of the following RRV and BFV transmission season incidence levels. Results: Although there were large differences in the notification rates of the two diseases, they had similar annual temporal patterns, but there were regional variations between the length and magnitude of the transmission seasons. During periods of increased disease activity, however, there was no association between the dynamics of the two diseases. Conclusions: The results from this study suggest that while RRV and BFV share similar mosquito vectors, there are significant differences in the ecology of these viruses that result in different epidemic patterns of disease incidence. Further investigation is required into the ecology of each virus to determine which factors are important in promoting RRV and BFV disease outbreaks.

Emotion and architectural environments : a case for Functional Near Infrared Spectroscopy (fNIRS) in assessing emotional responses to spatial environments

Collaboration between neuroscience and architecture is emerging as a key field of research as demonstrated in recent times by development of the Academy of Neuroscience for Architecture (ANFA) and other societies. Neurological enquiry of affect and spatial experience from a design perspective remains in many instances unchartered. Research using portable near infrared spectroscopy (fNIRs) - an emerging non-invasive neuro-imaging device, is proving convincing in its ability to detect emotional responses to visual, spatio-auditory and task based stimuli. This innovation provides a firm basis to potentially track cortical activity in the appraisal of architectural environments. Additionally, recent neurological studies have sought to explore the manifold sensory abilities of the visually impaired to better understand spatial perception in general. Key studies reveal that early blind participants perform as well as sighted due to higher auditory and somato-sensory spatial acuity. Studies also report pleasant and unpleasant emotional responses within certain interior environments revealing a deeper perceptual sensitivity than would be expected. Comparative fNIRS studies between the sighted and blind concerning spatial experience has the potential to provide greater understanding of emotional responses to architectural environments. Supported by contemporary theories of architectural aesthetics, this paper presents a case for the use of portable fNIRS imaging in the assessment of emotional responses to spatial environments experienced by both blind and sighted. The aim of the paper is to outline the implications of fNIRS upon spatial research and practice within the field of architecture and points to a potential taxonomy of particular formations of space and affect.