Looking yonder : a model of arts engagement with teacher artists and professional artists in Queensland Schools

Since 2007 Kite Arts Education Program (KITE), based at Queensland Performing Arts Centre (QPAC), has been engaged in delivering a series of theatre-based experiences for children in low socio-economic primary schools in Queensland. KITE @ QPAC is an early childhood arts initiative of The Queensland Department of Education that is supported by and located at the Queensland Performing Arts Centre. KITE delivers relevant contemporary arts education experiences for Prep to Year 3 students and their teachers across Queensland. The theatre-based experiences form part of a three year artist-in-residency project titled Yonder that includes performances developed by the children with the support and leadership of Teacher Artists from KITE for their community and parents/carers in a peak community cultural institution. This paper provides an overview of the Yonder model and unpacks some challenges in activating the model for schools and cultural organisations.

Overview of INEX 2013

INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2013 evaluation campaign, which consisted of four activities addressing three themes: searching professional and user generated data (Social Book Search track); searching structured or semantic data (Linked Data track); and focused retrieval (Snippet Retrieval and Tweet Contextualization tracks). INEX 2013 was an exciting year for INEX in which we consolidated the collaboration with (other activities in) CLEF and for the second time ran our workshop as part of the CLEF labs in order to facilitate knowledge transfer between the evaluation forums. This paper gives an overview of all the INEX 2013 tracks, their aims and task, the built test-collections, and gives an initial analysis of the results

A web-based approach to data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques.

ATF3 suppresses metastasis of bladder cancer by regulating gelsolin-mediated remodeling of the actin cytoskeleton

Bladder cancer is associated with high recurrence and mortality rates due to metastasis. The elucidation of metastasis suppressors may offer therapeutic opportunities if their mechanisms of action can be elucidated and tractably exploited. In this study, we investigated the clinical and functional significance of the transcription factor activating transcription factor 3 (ATF3) in bladder cancer metastasis. Gene expression analysis revealed that decreased ATF3 was associated with bladder cancer progression and reduced survival of patients with bladder cancer. Correspondingly, ATF3 overexpression in highly metastatic bladder cancer cells decreased migration in vitro and experimental metastasis in vivo. Conversely, ATF3 silencing increased the migration of bladder cancer cells with limited metastatic capability in the absence of any effect on proliferation. In keeping with their increased motility, metastatic bladder cancer cells had increased numbers of actin filaments. Moreover, ATF3 expression correlated with expression of the actin filament severing protein gelsolin (GSN). Mechanistic studies revealed that ATF3 upregulated GSN, whereas ATF3 silencing reduced GSN levels, concomitant with alterations in the actin cytoskeleton. We identified six ATF3 regulatory elements in the first intron of the GSN gene confirmed by chromatin immunoprecipitation analysis. Critically, GSN expression reversed the metastatic capacity of bladder cancer cells with diminished levels of ATF3. Taken together, our results indicate that ATF3 suppresses metastasis of bladder cancer cells, at least in part through the upregulation of GSN-mediated actin remodeling. These findings suggest ATF3 coupled with GSN as prognostic markers for bladder cancer metastasis.

Photocatalysis on supported gold and silver nanoparticles under ultraviolet and visible light irradiation

Studies of the optical properties and catalytic capabilities of noble metal nanoparticles (NPs), such as gold (Au) and silver (Ag), have formed the basis for the very recent fast expansion of the field of green photocatalysis: photocatalysis utilizing visible and ultraviolet light, a major part of the solar spectrum. The reason for this growth is the recognition that the localised surface plasmon resonance (LSPR) effect of Au NPs and Ag NPs can couple the light flux to the conduction electrons of metal NPs, and the excited electrons and enhanced electric fields in close proximity to the NPs can contribute to converting the solar energy to chemical energy by photon-driven photocatalytic reactions. Previously the LSPR effect of noble metal NPs was utilized almost exclusively to improve the performance of semiconductor photocatalysts (for example, TiO2 and Ag halides), but recently, a conceptual breakthrough was made: studies on light driven reactions catalysed by NPs of Au or Ag on photocatalytically inactive supports (insulating solids with a very wide band gap) have demonstrated that these materials are a class of efficient photocatalysts working by mechanisms distinct from those of semiconducting photocatalysts. There are several reasons for the significant photocatalytic activity of Au and Ag NPs. (1) The conduction electrons of the particles gain the irradiation energy, resulting in high energy electrons at the NP surface which is desirable for activating molecules on the particles for chemical reactions. (2) In such a photocatalysis system, both light harvesting and the catalysing reaction take place on the nanoparticle, and so charge transfer between the NPs and support is not a prerequisite. (3) The density of the conduction electrons at the NP surface is much higher than that at the surface of any semiconductor, and these electrons can drive the reactions on the catalysts. (4) The metal NPs have much better affinity than semiconductors to many reactants, especially organic molecules. Recent progress in photocatalysis using Au and Ag NPs on insulator supports is reviewed. We focus on the mechanism differences between insulator and semiconductor-supported Au and Ag NPs when applied in photocatalytic processes, and the influence of important factors, light intensity and wavelength, in particular estimations of light irradiation contribution, by calculating the apparent activation energies of photo reactions and thermal reactions.

Targeted therapies in non-small cell lung cancer

The majority of non-small cell lung cancer (NSCLC) patients present with advanced disease and with a 5 year survival rate of <15% for these patients, treatment outcomes are considered extremely disappointing. Standard chemotherapy regimens provide some improvement to ~40% of patients. However, intrinsic and acquired chemoresistance are a significant problem and hinder sustained long term benefits of such treatments. Advances in proteomic and genomic profiling have increased our understanding of the aberrant molecular mechanisms that are driving an individual's tumour. The increased sensitivity of these technologies has enabled molecular profiling at the stage of initial biopsy thus paving the way for a more personalised approach to the treatment of cancer patients. Improvements in diagnostics together with a wave of new targeted small molecule inhibitors and monoclonal antibodies have revolutionised the treatment of cancer. To date there are essentially three targeted agents approved for clinical use in NSCLC. The tyrosine kinase inhibitor (TKI) erlotinib, which targets the epidermal growth factor receptor (EGFR) TK domain, has proven to be an effective treatment strategy in patients who harbour activating mutations in the EGFR TK domain. Bevacizumab a monoclonal antibody targeting the vascular endothelial growth factor (VEGF) can improve survival, response rates, and progression-free survival when used in combination with chemotherapy. Crizotinib, a small-molecule drug, inhibits the tyrosine kinase activity of the echinoderm microtubule-associated protein-like 4 anaplastic lymphoma kinase (EML4-ALK) fusion protein, resulting in decreased tumour cell growth, migration, and invasiveness in patients with locally advanced or metastatic NSCLC. The clinical relevance of several other targeted agents are under investigation in distinct molecular subsets of patients with key "driver" mutations including: KRAS, HER2, BRAF, MET, PIK3CA, AKT1,MAP2K1, ROS1 and RET. Often several pathways are activated simultaneously and crosstalk between pathways allows tumour cells to escape the inhibition of a single targeted agent. This chapter will explore the clinical development of currently available targeted therapies for NSCLC as well as those in clinical trials and will examine the synergy between cytotoxic therapies.

Knowledge unlatched : encouraging innovation in academic publishing through collective action and Open Access licensing

This case study examines the way in which Knowledge Unlatched is combining collective action and open access licenses to encourage innovation in markets for specialist academic books. Knowledge Unlatched is a not for profit organisation that has been established to help a global community of libraries coordinate their book purchasing activities more effectively and, in so doing, to ensure that books librarians select for their own collections become available for free for anyone in the world to read. The Knowledge Unlatched model is an attempt to re-coordinate a market in order to facilitate a transition to digitally appropriate publishing models that include open access. It offers librarians an opportunity to facilitate the open access publication of books that their own readers would value access to. It provides publishers with a stable income stream on titles selected by libraries, as well as an ability to continue selling books to a wider market on their own terms. Knowledge Unlatched provides a rich case study for researchers and practitioners interested in understanding how innovations in procurement practices can be used to stimulate more effective, equitable markets for socially valuable products.

Optimization of an integrated model for automatic reduction and expansion of long queries

A long query provides more useful hints for searching relevant documents, but it is likely to introduce noise which affects retrieval performance. In order to smooth such adverse effect, it is important to reduce noisy terms, introduce and boost additional relevant terms. This paper presents a comprehensive framework, called Aspect Hidden Markov Model (AHMM), which integrates query reduction and expansion, for retrieval with long queries. It optimizes the probability distribution of query terms by utilizing intra-query term dependencies as well as the relationships between query terms and words observed in relevance feedback documents. Empirical evaluation on three large-scale TREC collections demonstrates that our approach, which is automatic, achieves salient improvements over various strong baselines, and also reaches a comparable performance to a state of the art method based on user’s interactive query term reduction and expansion.

Estimating interference in the QPRP for subtopic retrieval

The Quantum Probability Ranking Principle (QPRP) has been recently proposed, and accounts for interdependent document relevance when ranking. However, to be instantiated, the QPRP requires a method to approximate the interference" between two documents. In this poster, we empirically evaluate a number of different methods of approximation on two TREC test collections for subtopic retrieval. It is shown that these approximations can lead to significantly better retrieval performance over the state of the art.

Revisiting logical imaging for information retrieval

Retrieval with Logical Imaging is derived from belief revision and provides a novel mechanism for estimating the relevance of a document through logical implication (i.e. P(q -> d)). In this poster, we perform the first comprehensive evaluation of Logical Imaging (LI) in Information Retrieval (IR) across several TREC test Collections. When compared against standard baseline models, we show that LI fails to improve performance. This failure can be attributed to a nuance within the model that means non-relevant documents are promoted in the ranking, while relevant documents are demoted. This is an important contribution because it not only contextualizes the effectiveness of LI, but crucially ex- plains why it fails. By addressing this nuance, future LI models could be significantly improved.

Indexing without spam

The presence of spam in a document ranking is a major issue for Web search engines. Common approaches that cope with spam remove from the document rankings those pages that are likely to contain spam. These approaches are implemented as post-retrieval processes, that filter out spam pages only after documents have been retrieved with respect to a user’s query. In this paper we suggest to remove spam pages at indexing time, therefore obtaining a pruned index that is virtually “spam-free”. We investigate the benefits of this approach from three points of view: indexing time, index size, and retrieval performances. Not surprisingly, we found that the strategy decreases both the time required by the indexing process and the space required for storing the index. Surprisingly instead, we found that by considering a spam-pruned version of a collection’s index, no difference in retrieval performance is found when compared to that obtained by traditional post-retrieval spam filtering approaches.

Teaching Teachers for the Future (TTF) Project TPACK Survey : summary of the key findings

This paper presents a summary of the key findings of the TTF TPACK Survey developed and administered for the Teaching the Teachers for the Future (TTF) Project implemented in 2011. The TTF Project, funded by an Australian Government ICT Innovation Fund grant, involved all 39 Australian Higher Education Institutions which provide initial teacher education. TTF data collections were undertaken at the end of Semester 1 (T1) and at the end of Semester 2 (T2) in 2011. A total of 12881 participants completed the first survey (T1) and 5809 participants completed the second survey (T2). Groups of like-named items from the T1 survey were subject to a battery of complementary data analysis techniques. The psychometric properties of the four scales: Confidence - teacher items; Usefulness - teacher items; Confidence - student items; Usefulness- student items, were confirmed both at T1 and T2. Among the key findings summarised, at the national level, the scale: Confidence to use ICT as a teacher showed measurable growth across the whole scale from T1 to T2, and the scale: Confidence to facilitate student use of ICT also showed measurable growth across the whole scale from T1 to T2. Additional key TTF TPACK Survey findings are summarised.

Ghrelin receptor (GHS-R1A) antagonism suppresses both operant alcohol self-administration and high alcohol consumption in rats

The mechanisms involved in alcohol use disorders are complex. It has been shown that ghrelin is an important signal for the control of body weight homeostasis, preferably by interacting with hypothalamic circuits, as well as for drug reward by activating the mesolimbic dopamine system. The ghrelin receptor (GHS-R1A) has been shown to be required for alcohol-induced reward. Additionally, ghrelin increases and GHR-R1A antagonists reduce moderate alcohol consumption in mice, and a single nucleotide polymorphism in the GHS-R1A gene has been associated with high alcohol consumption in humans. However, the role of central ghrelin signaling in high alcohol consumption is not known. Therefore, the role of GHS-R1A in operant self-administration of alcohol in rats as well as for high alcohol consumption in Long-Evans rats and in alcohol preferring [Alko alcohol (AA)] rats was studied here. In the present study, the GHS-R1A antagonist, JMV2959, was found to reduce the operant self-administration of alcohol in rats and to decrease high alcohol intake in Long-Evans rats as well as in AA rats. These results suggest that the ghrelin receptor signaling system, specifically GHS-R1A, is required for operant self-administration of alcohol and for high alcohol intake in rats. Therefore, the GHS-R1A may be a therapeutic target for treatment of addictive behaviors, such as alcohol dependence.

Crypto topics and applications II

In this chapter we continue the exposition of crypto topics that was begun in the previous chapter. This chapter covers secret sharing, threshold cryptography, signature schemes, and finally quantum key distribution and quantum cryptography. As in the previous chapter, we have focused only on the essentials of each topic. We have selected in the bibliography a list of representative items, which can be consulted for further details. First we give a synopsis of the topics that are discussed in this chapter. Secret sharing is concerned with the problem of how to distribute a secret among a group of participating individuals, or entities, so that only predesignated collections of individuals are able to recreate the secret by collectively combining the parts of the secret that were allocated to them. There are numerous applications of secret-sharing schemes in practice. One example of secret sharing occurs in banking. For instance, the combination to a vault may be distributed in such a way that only specified collections of employees can open the vault by pooling their portions of the combination. In this way the authority to initiate an action, e.g., the opening of a bank vault, is divided for the purposes of providing security and for added functionality, such as auditing, if required. Threshold cryptography is a relatively recently studied area of cryptography. It deals with situations where the authority to initiate or perform cryptographic operations is distributed among a group of individuals. Many of the standard operations of single-user cryptography have counterparts in threshold cryptography. Signature schemes deal with the problem of generating and verifying electronic) signatures for documents.Asubclass of signature schemes is concerned with the shared-generation and the sharedverification of signatures, where a collaborating group of individuals are required to perform these actions. A new paradigm of security has recently been introduced into cryptography with the emergence of the ideas of quantum key distribution and quantum cryptography. While classical cryptography employs various mathematical techniques to restrict eavesdroppers from learning the contents of encrypted messages, in quantum cryptography the information is protected by the laws of physics.

Causal behavioural profiles : efficient computation, applications, and evaluation

Analysis of behavioural consistency is an important aspect of software engineering. In process and service management, consistency verification of behavioural models has manifold applications. For instance, a business process model used as system specification and a corresponding workflow model used as implementation have to be consistent. Another example would be the analysis to what degree a process log of executed business operations is consistent with the corresponding normative process model. Typically, existing notions of behaviour equivalence, such as bisimulation and trace equivalence, are applied as consistency notions. Still, these notions are exponential in computation and yield a Boolean result. In many cases, however, a quantification of behavioural deviation is needed along with concepts to isolate the source of deviation. In this article, we propose causal behavioural profiles as the basis for a consistency notion. These profiles capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities of a process model. Consistency based on these profiles is weaker than trace equivalence, but can be computed efficiently for a broad class of models. In this article, we introduce techniques for the computation of causal behavioural profiles using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets. We also elaborate on the findings of applying our technique to three industry model collections.