Enriching community engaged learning through interdisciplinary collaboration

Twenty first century society presents critical challenges for higher education (Brew 2013, 2). The challenges facing modern communities require graduates to have skills that respond to issues at the boundaries of, and intersections between, disciplines. Mounting evidence suggests that interdisciplinary curriculum and pedagogies help students to develop boundary-crossing skills and a deeper awareness of the student’s domain-specific knowledge (Spelt et al. 2009; Strober 2011). Spelt et al. (2009) describe boundary-crossing skills as the ability to engage with different discourses, take account of multiple perspectives, synthesise knowledge of different disciplines, and cope with complexity. In this chapter we investigate emerging conditions, practical processes, and pedagogical strategies that are enabling the Lab stakeholders, the community, the university, and students to participate in interdisciplinary community-engaged learning. Aspects of the Lab that are considered in this chapter include building trust, sharing values, establishing learning goals that are reflected in learning experiences and assessment, and employing strategies that define and attend to relationships and roles. The case study, “The Recognition of Aboriginal and Torres Strait Islander Peoples in the Australian Constitution”, a QUT collaborative project with the Social Justice Research Unit Anglicare Southern Queensland, describes the collaborators, processes, outcomes, and the lessons learned through one Lab project over three semesters. The issues illustrated in the case study are then further explored in a critical discussion of the strategies supporting interdisciplinarity in community-engaged learning across university/community collaboration, within and across the university, and for student participants

Localization and place recognition using an ultra-wide band (UWB) radar

This paper presents an approach to mobile robot localization, place recognition and loop closure using a monostatic ultra-wide band (UWB) radar system. The UWB radar is a time-of-flight based range measurement sensor that transmits short pulses and receives reflected waves from objects in the environment. The main idea of the poposed localization method is to treat the received waveform as a signature of place. The resulting echo waveform is very complex and highly depends on the position of the sensor with respect to surrounding objects. On the other hand, the sensor receives similar waveforms from the same positions.Moreover, the directional characteristics of dipole antenna is almost omnidirectional. Therefore, we can localize the sensor position to find similar waveform from waveform database. This paper proposes a place recognitionmethod based on waveform matching, presents a number of experiments that illustrate the high positon estimation accuracy of our UWB radar-based localization system, and shows the resulting loop detection performance in a typical indoor office environment and a forest.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

Multi-action recognition via stochastic modelling of optical flow and gradients

In this paper we propose a novel approach to multi-action recognition that performs joint segmentation and classification. This approach models each action using a Gaussian mixture using robust low-dimensional action features. Segmentation is achieved by performing classification on overlapping temporal windows, which are then merged to produce the final result. This approach is considerably less complicated than previous methods which use dynamic programming or computationally expensive hidden Markov models (HMMs). Initial experiments on a stitched version of the KTH dataset show that the proposed approach achieves an accuracy of 78.3%, outperforming a recent HMM-based approach which obtained 71.2%.

Computational analysis of epigenetic information in human DNA sequences

Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

A method for optimal fit of patient-specific fracture fixation plates

Anatomically pre-contoured fracture fixation plates are a treatment option for bone fractures. A well-fitting plate can be used as a tool for anatomical reduction of the fractured bone. However, recent studies showed that some plates fit poorly for many patients due to considerable shape variations between bones of the same anatomical site. Therefore, the plates have to be manually fitted and deformed by surgeons to fit each patient optimally. The process is time-intensive and labor-intensive, and could lead to adverse clinical implications such as wound infection or plate failure. This paper proposes a new iterative method to simulate the patient-specific deformation of an optimally fitting plate for pre-operative planning purposes. We further demonstrate the validation of the method through a case study. The proposed method involves the integration of four commercially available software tools, Matlab, Rapidform2006, SolidWorks, and ANSYS, each performing specific tasks to obtain a plate shape that fits optimally for an individual tibia and is mechanically safe. A typical challenge when crossing multiple platforms is to ensure correct data transfer. We present an example of the implementation of the proposed method to demonstrate successful data transfer between the four platforms and the feasibility of the method.

The contribution of ISO 14067 to the evolution of global greenhouse gas standards—A review

Due to the increasing recognition of global climate change, the building and construction industry is under pressure to reduce carbon emissions. A central issue in striving towards reduced carbon emissions is the need for a practicable and meaningful yardstick for assessing and communicating greenhouse gas (GHG) results. ISO 14067 was published by the International Organization for Standardization in May 2013. By providing specific requirements in the life cycle assessment (LCA) approach, the standard clarifies the GHG assessment in the aspects of choosing system boundaries and simulating use and end-of-life phases when quantifying carbon footprint of products (CFPs). More importantly, the standard, for the first time, provides step-to-step guidance and standardized template for communicating CFPs in the form of CFP external communication report, CFP performance tracking report, CFP declaration and CFP label. ISO 14067 therefore makes a valuable contribution to GHG quantification and transparent communication and comparison of CFPs. In addition, as cradle-to-grave should be used as the system boundary if use and end-of-life phases can be simulated, ISO 14067 will hopefully promote the development and implementation of simulation technologies, with Building Information Modelling (BIM) in particular, in the building and construction industry.

The O-specific polysaccharide structure and biosynthetic gene cluster of Yersinia pseudotuberculosis serotype O:11

In the Yersinia pseudotuberculosis serotyping scheme, 21 serotypes are present originating from about 30 different O-factors distributed within the species. With regard to the chemical structures of lipopolysaccharides (LPSs) and the genetic basis of their biosynthesis, a number, but not all, of Y. pseudotuberculosis strains representing different serotypes have been investigated. In order to present an overall picture of the relationship between genetics and structures, we have been working on the genetics and structures of various Y. pseudotuberculosis O-specific polysaccharides (OPSs). Here, we present a structural and genetic analysis of the Y. pseudotuberculosis serotype O:11 OPS. Our results showed that this OPS structure has the same backbone as that of Y. pseudotuberculosis O:1b, but with a 6d-l-Altf side-branch instead of Parf. The 3′ end of the gene cluster is the same as that for O:1b and has the genes for synthesis of the backbone and for processing the completed repeat unit. The 5′ end has genes for synthesis of 6d-l-Altf and its transfer to the repeating unit backbone. The pathway for the synthesis of the 6d-l-Altf appears to be different from that for 6d-l-Altp in Y. enterocolitica O:3. The chemical structure of the O:11 repeating unit is [Figure]

The genetics and structure of the O-specific polysaccharide of Yersinia pseudotuberculosis serotype O:10 and its relationship with Escherichia coli O111 and Salmonella enterica O35

The O-specific polysaccharide (OPS) is a variable constituent of the lipopolysaccharide of Gram-negative bacteria. The polymorphic nature of OPSs within a species is usually first defined serologically, and the current serotyping scheme for Yersinia pseudotuberculosis consists of 21 O serotypes of which 15 have been characterized genetically and structurally. Here, we present the structure and DNA sequence of Y. pseudotuberculosis O:10 OPS. The O unit consists of one residue each of d-galactopyranose, N-acetyl-d-galactosamine (2-amino-2-deoxy-d-galactopyranose) and d-glucopyranose in the backbone, with two colitose (3,6-dideoxy-l-xylo-hexopyranose) side-branch residues. This structure is very similar to that shared by Escherichia coli O111 and Salmonella enterica O35. The gene cluster sequences of these serotypes, however, have only low levels of similarity to that of Y. pseudotuberculosis O:10, although there is significant conservation of gene order. Within Y. pseudotuberculosis, the O10 structure is most closely related to the O:6 and O:7 structures.

Genetic characterisation and structural analysis of the O-specific polysaccharide of Yersinia pseudotuberculosis serotype O:1c

Many, but not all, of the current 21 serotypes of Yersinia pseudotuberculosis have been investigated with regard to the chemical structures of their O-specific polysaccharide (OPS) and the genetic basis of their biosynthesis. Completion of the genetics and structures of the remaining serotypes will enhance our understanding of the emerging relationship between genetics and structures within this species. Here, we present a structural and genetic analysis of the Y. pseudotuberculosis serotype O:1c OPS. Our results showed that this OPS has the same backbone as Y. pseudotuberculosis O:2b, but with a 3,6-dideoxy-D-ribo-hexofuranose (paratofuranose, Parf) side-branch instead of a 3,6-dideoxy-D-xylo-hexopyranose (abequopyranose, Abep). The 3'-end of the gene cluster is the same as for O:2b and has the genes for synthesis of the backbone and for processing the completed repeat unit. The 5'-end of the cluster consists of the same genes as O:1b for synthesis of Parf and a related gene for its transfer to the repeating unit backbone.

The O-specific polysaccharide structure and gene cluster of serotype O:12 of the Yersinia pseudotuberculosis complex, and the identification of a novel L-quinovose biosynthesis gene

A major virulence factor for Yersinia pseudotuberculosis is lipopolysaccharide, including O-polysaccharide (OPS). Currently, the OPS based serotyping scheme for Y. pseudotuberculosis includes 21 known O-serotypes, with genetic and structural data available for 17 of them. The completion of the OPS structures and genetics of this species will enable the visualization of relationships between O-serotypes and allow for analysis of the evolutionary processes within the species that give rise to new serotypes. Here we present the OPS structure and gene cluster of serotype O:12, thus adding one more to the set of completed serotypes, and show that this serotype is present in both Y. pseudotuberculosis and the newly identified Y. similis species. The O:12 structure is shown to include two rare sugars: 4-C[(R)-1-hydroxyethyl]-3,6-dideoxy-d-xylo-hexose (d-yersiniose) and 6-deoxy-l-glucopyranose (l-quinovose). We have identified a novel putative guanine diphosphate (GDP)-l-fucose 4-epimerase gene and propose a pathway for the synthesis of GDP-l-quinovose, which extends the known GDP-l-fucose pathway.

Afferent specific regulation of cortical and subcortical synaptic input to the lateral amygdala by norepinephrine

The lateral amygdala (LA) has been extensively implicated in the neurobiology of conditioned fear paradigms. Norepinepherine (NE), especially its beta receptors, has been implicated in consolidation, reconsolidation and extinction of fear memories, and has been proposed as a potential treatment for PTSD (Berlau and McGaugh, NLM, 2006; Debiec and LeDoux, N, 2005)...

From ImageNet to mining: Adapting visual object detection with minimal supervision

This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

Paralog-specific kinase inhibition of FGFR4: Adding to the arsenal of anti-FGFR agents

In this issue of Cancer Discovery, Hagel and colleagues report the design and the in vitro and in vivo activity of a novel, irreversible, paralog-specific kinase inhibitor of FGFR4, BLU9931. This compound binds covalently to a cysteine residue in the hinge region of FGFR4 but not in FGFR1-3. BLU9931 induces tumor shrinkage in hepatocellular carcinoma models that express a functioning ligand/receptor complex consisting of FGF19/FGFR4/KLB and adds to a growing list of anti-FGFR4 agents.

Automatic image scaling for place recognition in changing environments

Robustness to variations in environmental conditions and camera viewpoint is essential for long-term place recognition, navigation and SLAM. Existing systems typically solve either of these problems, but invariance to both remains a challenge. This paper presents a training-free approach to lateral viewpoint- and condition-invariant, vision-based place recognition. Our successive frame patch-tracking technique infers average scene depth along traverses and automatically rescales views of the same place at different depths to increase their similarity. We combine our system with the condition-invariant SMART algorithm and demonstrate place recognition between day and night, across entire 4-lane-plus-median-strip roads, where current algorithms fail.