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Climate change is affecting and will increasingly influence human health and wellbeing. Children are particularly vulnerable to the impact of climate change. An extensive literature review regarding the impact of climate change on children’s health was conducted in April 2012 by searching electronic databases PubMed, Scopus, ProQuest, ScienceDirect, and Web of Science, as well as relevant websites, such as IPCC and WHO. Climate change affects children’s health through increased air pollution, more weather-related disasters, more frequent and intense heat waves, decreased water quality and quantity, food shortage and greater exposure to toxicants. As a result, children experience greater risk of mental disorders, malnutrition, infectious diseases, allergic diseases and respiratory diseases. Mitigation measures like reducing carbon pollution emissions, and adaptation measures such as early warning systems and post-disaster counseling are strongly needed. Future health research directions should focus on: (1) identifying whether climate change impacts on children will be modified by gender, age and socioeconomic status; (2) refining outcome measures of children’s vulnerability to climate change; (3) projecting children’s disease burden under climate change scenarios; (4) exploring children’s disease burden related to climate change in low-income countries, and ; (5) identifying the most cost-effective mitigation and adaptation actions from a children’s health perspective.

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This paper examines the use of crowdfunding platforms to fund academic research. Looking specifically at the use of a Pozible campaign to raise funds for a small pilot research study into home education in Australia, the paper reports on the success and problems of using the platform. It also examines the crowdsourcing of literature searching as part of the package. The paper looks at the realities of using this type of platform to gain start–up funding for a project and argues that families and friends are likely to be the biggest supporters. The finding that family and friends are likely to be the highest supporters supports similar work in the arts communities that are traditionally served by crowdfunding platforms. The paper argues that, with exceptions, these platforms can be a source of income in times where academics are finding it increasingly difficult to source government funding for projects.

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In the field of information retrieval (IR), researchers and practitioners are often faced with a demand for valid approaches to evaluate the performance of retrieval systems. The Cranfield experiment paradigm has been dominant for the in-vitro evaluation of IR systems. Alternative to this paradigm, laboratory-based user studies have been widely used to evaluate interactive information retrieval (IIR) systems, and at the same time investigate users’ information searching behaviours. Major drawbacks of laboratory-based user studies for evaluating IIR systems include the high monetary and temporal costs involved in setting up and running those experiments, the lack of heterogeneity amongst the user population and the limited scale of the experiments, which usually involve a relatively restricted set of users. In this paper, we propose an alternative experimental methodology to laboratory-based user studies. Our novel experimental methodology uses a crowdsourcing platform as a means of engaging study participants. Through crowdsourcing, our experimental methodology can capture user interactions and searching behaviours at a lower cost, with more data, and within a shorter period than traditional laboratory-based user studies, and therefore can be used to assess the performances of IIR systems. In this article, we show the characteristic differences of our approach with respect to traditional IIR experimental and evaluation procedures. We also perform a use case study comparing crowdsourcing-based evaluation with laboratory-based evaluation of IIR systems, which can serve as a tutorial for setting up crowdsourcing-based IIR evaluations.

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Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.

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The binding kinetics of NF-kappaB p50 to the Ig-kappaB site and to a DNA duplex with no specific binding site were determined under varying conditions of potassium chloride concentration using a surface plasmonresonance biosensor. Association and dissociation rate constants were measured enabling calculation of the dissociation constants. Under previously established high affinity buffer conditions, the k a for both sequences was in the order of 10(7) M-1s-1whilst the k d values varied 600-fold in a sequence-dependent manner between 10(-1) and 10(-4 )s-1, suggesting that the selectivity of p50 for different sequences is mediated primarily through sequence-dependent dissociation rates. The calculated K D value for the Ig-kappaB sequence was 16 pM, whilst the K D for the non-specific sequence was 9.9 nM. As the ionic strength increased to levels which are closer to that of the cellular environment, the binding of p50 to the non-specific sequence was abolished whilst the specific affinity dropped to nanomolar levels. From these results, a mechanism is proposed in which p50 binds specific sequences with high affinity whilst binding non-specific sequences weakly enough to allow efficient searching of the DNA.

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This thesis developed new search engine models that elicit the meaning behind the words found in documents and queries, rather than simply matching keywords. These new models were applied to searching medical records: an area where search is particularly challenging yet can have significant benefits to our society.

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We present a study to understand the effect that negated terms (e.g., "no fever") and family history (e.g., "family history of diabetes") have on searching clinical records. Our analysis is aimed at devising the most effective means of handling negation and family history. In doing so, we explicitly represent a clinical record according to its different content types: negated, family history and normal content; the retrieval model weights each of these separately. Empirical evaluation shows that overall the presence of negation harms retrieval effectiveness while family history has little effect. We show negation is best handled by weighting negated content (rather than the common practise of removing or replacing it). However, we also show that many queries benefit from the inclusion of negated content and that negation is optimally handled on a per-query basis. Additional evaluation shows that adaptive handing of negated and family history content can have significant benefits.

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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.

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In today’s world of information-driven society, many studies are exploring usefulness and ease of use of the technology. The research into personalizing next-generation user interface is also ever increasing. A better understanding of factors that influence users’ perception of web search engine performance would contribute in achieving this. This study measures and examines how users’ perceived level of prior knowledge and experience influence their perceived level of satisfaction of using the web search engines, and how their perceived level of satisfaction affects their perceived intention to reuse the system. 50 participants from an Australian university participated in the current study, where they performed three search tasks and completed survey questionnaires. A research model was constructed to test the proposed hypotheses. Correlation and regression analyses results indicated a significant correlation between (1) users’ prior level of experience and their perceived level of satisfaction in using the web search engines, and (2) their perceived level of satisfaction in using the systems and their perceived intention to reuse the systems. A theoretical model is proposed to illustrate the causal relationships. The implications and limitations of the study are also discussed.

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Background & Research Focus Managing knowledge for innovation and organisational benefit has been extensively investigated in studies of large firms (Smith, Collins & Clark, 2005; Zucker, et al., 2007) and to a large extent there is limited research into studies of small- and medium- sized enterprises (SMEs). There are some investigations in knowledge management research on SMEs, but what remains to be seen in particular is the question of where are the potential challenges for managing knowledge more effectively within these firms? Effective knowledge management (KM) processes and systems lead to improved performance in pursuing distinct capabilities that contribute to firm-level innovation (Nassim 2009; Zucker et al. 2007; Verona and Ravasi 2003). Managing internal and external knowledge in a way that links it closely to the innovation process can assist the creation and implementation of new products and services. KM is particularly important in knowledge intensive firms where the knowledge requirements are highly specialized, diverse and often emergent. However, to a large extent the KM processes of small firms that are often the source of new knowledge and an important element of the value networks of larger companies have not been closely studied. To address this gap which is of increasing importance with the growing number of small firms, we need to further investigate knowledge management processes and the ways that firms find, capture, apply and integrate knowledge from multiple sources for their innovation process. This study builds on the previous literature and applies existing frameworks and takes the process and activity view of knowledge management as a starting point of departure (see among others Kraaijenbrink, Wijnhoven & Groen, 2007; Enberg, Lindkvist, & Tell, 2006; Lu, Wang & Mao, 2007). In this paper, it is attempted to develop a better understanding of the challenges of knowledge management within the innovation process in small knowledge-oriented firms. The paper aims to explore knowledge management processes and practices in firms that are engaged in the new product/service development programs. Consistent with the exploratory character of the study, the research question is: How is knowledge integrated, sourced and recombined from internal and external sources for innovation and new product development? Research Method The research took an exploratory case study approach and developed a theoretical framework to investigate the knowledge situation of knowledge-intensive firms. Equipped with the conceptual foundation, the research adopted a multiple case study method investigating four diverse Australian knowledge-intensive firms from IT, biotechnology, nanotechnology and biochemistry industries. The multiple case study method allowed us to document in some depth the knowledge management experience of the theses firms. Case study data were collected through a review of company published data and semi-structured interviews with managers using an interview guide to ensure uniform coverage of the research themes. This interview guide was developed following development of the framework and a review of the methodologies and issues covered by similar studies in other countries and used some questions common to these studies. It was framed to gather data around knowledge management activity within the business, focusing on the identification, acquisition and utilisation of knowledge, but collecting a range of information about subject as well. The focus of the case studies was on the use of external and internal knowledge to support their knowledge intensive products and services. Key Findings Firstly a conceptual and strategic knowledge management framework has been developed. The knowledge determinants are related to the nature of knowledge, organisational context, and mechanism of the linkages between internal and external knowledge. Overall, a number of key observations derived from this study, which demonstrated the challenges of managing knowledge and how important KM is as a management tool for innovation process in knowledge-oriented firms. To summarise, findings suggest that knowledge management process in these firms is very much project focused and not embedded within the overall organisational routines and mainly based on ad hoc and informal processes. Our findings highlighted lack of formal knowledge management process within our sampled firms. This point to the need for more specialised capabilities in knowledge management for these firms. We observed a need for an effective knowledge transfer support system which is required to facilitate knowledge sharing and particularly capturing and transferring tacit knowledge from one team members to another. In sum, our findings indicate that building effective and adaptive IT systems to manage and share knowledge in the firm is one of the biggest challenges for these small firms. Also, there is little explicit strategy in small knowledge-intensive firms that is targeted at systematic KM either at the strategic or operational level. Therefore, a strategic approach to managing knowledge for innovation as well as leadership and management are essential to achieving effective KM. In particular, research findings demonstrate that gathering tacit knowledge, internal and external to the organization, and applying processes to ensure the availability of knowledge for innovation teams, drives down the risks and cost of innovation. KM activities and tools, such as KM systems, environmental scanning, benchmarking, intranets, firm-wide databases and communities of practice to acquire knowledge and to make it accessible, were elements of KM. Practical Implications The case study method that used in this study provides practical insight into the knowledge management process within Australian knowledge-intensive firms. It also provides useful lessons which can be used by other firms in managing the knowledge more effectively in the innovation process. The findings would be helpful for small firms that may be searching for a practical method for managing and integrating their specialised knowledge. Using the results of this exploratory study and to address the challenges of knowledge management, this study proposes five practices that are discussed in the paper for managing knowledge more efficiently to improve innovation: (1) Knowledge-based firms must be strategic in knowledge management processes for innovation, (2) Leadership and management should encourage various practices for knowledge management, (3) Capturing and sharing tacit knowledge is critical and should be managed, (4)Team knowledge integration practices should be developed, (5) Knowledge management and integration through communication networks, and technology systems should be encouraged and strengthen. In sum, the main managerial contribution of the paper is the recognition of knowledge determinants and processes, and their effects on the effective knowledge management within firm. This may serve as a useful benchmark in the strategic planning of the firm as it utilises new and specialised knowledge.

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Expert searchers engage with information in a variety of professional settings, as information brokers, reference librarians, information architects and faculty who teach advanced searching. As my recent research shows, the expert searcher’s information experience is defined by profound discernment of critical concepts about information, and a fluid ability to apply this knowledge to their engagement with the information environment. The information experience of the expert searcher means active and intentional participation with the processes and players that created that information environment. Expert searchers become an integral and seamless part of their information environment and also play a role in facilitating the information experiences of others. In this chapter, after discussing my understanding of the concept of information experience, I outline how I used threshold concept theory to explore the information experience of expert searchers. Through the findings, I identify four threshold concepts in the acquisition of search expertise that provide new perspectives on the information experience of the expert searcher. These new perspectives have implications for search engine design and how advanced search skills are taught. Finally, I consider how the fresh insights about the expert searcher’s experiences contribute to wider understanding about information experience.

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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.

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The development of vocalizations during postnatal growth in the flat-headed bats, Tylonycteris pachypus and T. robustula in South China is described. Females of both species gave birth to twins at the end of May, and the infants flew in the last ten days of June. Vocalizations served as precursors to echolocation calls and as isolation calls (i-calls) used to attract mothers. As the infants grew, the frequency of i-calls and precursor calls increased. The duration of i-calls increased little before 6-day old and then decreased. At the same time, the duration of echolocation precursor calls decreased. The directive calls that the mother or the infant emitted when searching for each other are also described. Female directive calls are lower in frequency and longer in duration than their echolocation calls, and the duration of infant directive calls is longer than those of the i-calls and precursor calls.

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Female greater wax moths Galleria mellonella display by wing fanning in response to bursts of ultrasonic calls produced by males. The temporal and spectral characteristics of these calls show some similarities with the echolocation calls of bats that emit frequency-modulated (FM) signals. Female G. mellonella therefore need to distinguish between the attractive signals of male conspecifics, which may lead to mating opportunities, and similar sounds made by predatory bats. We therefore predicted that (1) females would display in response to playbacks of male calls; (2) females would not display in response to playbacks of the calls of echolocating bats (we used the calls of Daubenton's bat Myotis daubentonii as representative of a typical FM echolocating bat); and (3) when presented with male calls and bat calls during the same time block, females would display more when perceived predation risk was lower. We manipulated predation risk in two ways. First, we varied the intensity of bat calls to represent a nearby (high risk) or distant (low risk) bat. Second, we played back calls of bats searching for prey (low risk) and attacking prey (high risk). All predictions were supported, suggesting that female G. mellonella are able to distinguish conspecific male mating calls from bat calls, and that they modify display rate in relation to predation risk. The mechanism (s) by which the moths separate the calls of bat and moth must involve temporal cues. Bat and moth signals differ considerably in duration, and differences in duration could be encoded by the moth's nervous system and used in discrimination.

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In our large library of annotated environmental recordings of animal vocalizations, searching annotations by label can return thousands of results. We propose a heat map of aggregated annotation time and frequency bounds, maintaining the shape of the annotations as they appear on the spectrogram. This compactly displays the distribution of annotation bounds for the user's query, and allows them to easily identify unusual annotations. Key to this is allowing zero values on the map to be differentiated from areas where there are single annotations.