Systems-based accident analysis in the led outdoor activity domain : application and evaluation of a risk management framework

Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussen's risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management framework's predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain.

Contribution of transmembrane domain V amino acids to β1l-adrenoceptor activity and affinity

There are two binding sites on the β1-adrenoceptor (AR), β1H and β1L corresponding to high and low affinity binding sites respectively, which can be activated to cause cardiostimulation (reviewed Kaumann and Molenaar, 2008). Some β-blockers that block β1AR and β2ARs can activate β1LARs at higher concentrations than those required to cause blockade. The β2AR does not form a corresponding low affinity binding site (Baker et al 2002) and therefore we postulated that heterologous amino acids are responsible for the formation of β1LAR. Our aim was to investigate whether heterologous amino acids of transmembrane domain V (TMDV) of β1AR and β2ARs contribute to β1LAR. β1ARs, β2ARs and mutant β1ARs containing all (β1(β2TMDV)AR) or single amino acids of TMDV of the β2AR were prepared and stably expressed in Chinese Hamster Ovary cells. Concentration-effect curves for cyclicAMP accumulation were carried out for (-)-CGP12177 or (-)-isoprenaline in the absence or presence of (-)-bupranolol. _______________________________________________________________________ (-)-CGP 12177 (-)-Bupranolol affinity (pKB) pEC50 vs (-)-CGP 12177 vs (-)-isoprenaline _______________________________________________________________________ β1AR 8.00 ± 0.11 (11) 7.23 ± 0.23 (5) 9.52 ± 0.28 (5) β2AR (high density) 9.24 ± 0.14 (5) 9.82 ± 0.52 (8) xPaulxxxxxxx β2AR (low density) no effect β1(β2TMV)AR 8.86 ± 0.10 (15) 8.06 ± 0.17 (8) 9.08 ± 0.22 (6) β1(V230I)AR 9.07 ± 0.07 (10) 7.64 ± 0.12 (8) 9.36 ± 0.28 (9) β1(R222Q)AR 8.09 ± 0.29 (6) 7.33 ± 0.23 (5) 9.36 ± 0.08 (6) β1(V230A)AR 7.59 ± 0.09 (6) 7.32 ± 0.24 (4) 8.62 ± 0.18 (5) _______________________________________________________________________ The potency of (-)-CGP12177 was higher at β2AR than at β1AR consistent with activation through a low affinity site at the β1AR (β1LAR) but not β2AR. The presence of V230 in β1AR accounted for the lower potency of (-)-CGP 12177. The affinity of (-)-bupranolol at β1AR and mutants was higher when determined with (-)-isoprenaline than with (-)-CGP 12177. The affinity of (-)-bupranolol determined against (-)-CGP 12177 was lower at β1AR compared to β2AR. The presence of V230 in β1AR accounted in part for the lower affinity. In conclusion V230 of the β1AR contributes in part to the low affinity binding site of β1AR. Baker JG, Hall IP, Hill SJ (2002). Pharmacological characterization of CGP12177 at the human β2-adrenoceptor. Br J Pharmacol 137, 400−408 Kaumann AJ, Molenaar P (2008) The low-affinity site of the β1-adrenoceptor and its relevance to cardiovascular pharmacology. Pharmacol Ther 118, 303-336

A measurement instrument for process modeling research : development, test and procedural model

Process modeling is an emergent area of Information Systems research that is characterized through an abundance of conceptual work with little empirical research. To fill this gap, this paper reports on the development and validation of an instrument to measure user acceptance of process modeling grammars. We advance an extended model for a multi-stage measurement instrument development procedure, which incorporates feedback from both expert and user panels. We identify two main contributions: First, we provide a validated measurement instrument for the study of user acceptance of process modeling grammars, which can be used to assist in further empirical studies that investigate phenomena associated with the business process modeling domain. Second, in doing so, we describe in detail a procedural model for developing measurement instruments that ensures high levels of reliability and validity, which may assist fellow scholars in executing their empirical research.

Noise robust voice activity detection using normal probability testing and time-domain histogram analysis

This paper presents a method of voice activity detection (VAD) suitable for high noise scenarios, based on the fusion of two complementary systems. The first system uses a proposed non-Gaussianity score (NGS) feature based on normal probability testing. The second system employs a histogram distance score (HDS) feature that detects changes in the signal through conducting a template-based similarity measure between adjacent frames. The decision outputs by the two systems are then merged using an open-by-reconstruction fusion stage. Accuracy of the proposed method was compared to several baseline VAD methods on a database created using real recordings of a variety of high-noise environments.

Noise robust voice activity detection using features extracted from the time-domain autocorrelation function

This paper presents a method of voice activity detection (VAD) for high noise scenarios, using a noise robust voiced speech detection feature. The developed method is based on the fusion of two systems. The first system utilises the maximum peak of the normalised time-domain autocorrelation function (MaxPeak). The second zone system uses a novel combination of cross-correlation and zero-crossing rate of the normalised autocorrelation to approximate a measure of signal pitch and periodicity (CrossCorr) that is hypothesised to be noise robust. The score outputs by the two systems are then merged using weighted sum fusion to create the proposed autocorrelation zero-crossing rate (AZR) VAD. Accuracy of AZR was compared to state of the art and standardised VAD methods and was shown to outperform the best performing system with an average relative improvement of 24.8% in half-total error rate (HTER) on the QUT-NOISE-TIMIT database created using real recordings from high-noise environments.

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.

Functional role of cell surface CUB domain-containing protein 1 in tumour cell dissemination

The function of CUB domain-containing protein 1 (CDCP1), a recently described transmembrane protein expressed on the surface of hematopoietic stem cells and normal and malignant cells of different tissue origin, is not well defined. The contribution of CDCP1 to tumor metastasis was analyzed by using HeLa carcinoma cells overexpressing CDCP1 (HeLa-CDCP1) and a high-disseminating variant of prostate carcinoma PC-3 naturally expressing high levels of CDCP1 (PC3-hi/diss). CDCP1 expression rendered HeLa cells more aggressive in experimental metastasis in immunodeficient mice. Metastatic colonization by HeLa-CDCP1 was effectively inhibited with subtractive immunization-generated, CDCP1-specific monoclonal antibody (mAb) 41-2, suggesting that CDCP1 facilitates relatively late stages of the metastatic cascade. In the chick embryo model, time- and dose-dependent inhibition of HeLa-CDCP1 colonization by mAb 41-2 was analyzed quantitatively to determine when and where CDCP1 functions during metastasis. Quantitative PCR and immunohistochemical analyses indicated that CDCP1 facilitated tumor cell survival soon after vascular arrest. Live cell imaging showed that the function-blocking mechanism of mAb 41-2 involved enhancement of tumor cell apoptosis, confirmed by attenuation of mAb 41-2–mediated effects with the caspase inhibitor z-VAD-fmk. Under proapoptotic conditions in vitro, CDCP1 expression conferred HeLa-CDCP1 cells with resistance to doxorubicin-induced apoptosis, whereas ligation of CDCP1 with mAb 41-2 caused additional enhancement of the apoptotic response. The functional role of naturally expressed CDCP1 was shown by mAb 41-2–mediated inhibition of both experimental and spontaneous metastasis of PC3-hi/diss. These findings confirm that CDCP1 functions as an antiapoptotic molecule and indicate that during metastasis CDCP1 facilitates tumor cell survival likely during or soon after extravasation.

Teachers' personal epistemologies and teacher education : emergent themes and future research

This chapter summarizes the responses to four questions in each of the chapters in this volume. The questions addressed the use of a conceptual framework that guides the chapter, issues of domain-generality, how personal epistemology relates to teaching, and how personal epistemologies change. We concluded that all of the chapters discussed the distinction between constructivist and transmission teaching practices, while suggesting that there are many inconsistencies in understanding the relationship between the nature of beliefs and teachers’ practices regardless of the relative sophistication of teachers’ personal epistemologies. We also summarized a multi-component instructional model for calibrating teaching practices based on suggestions in each of the chapters, and made four suggestions for future research, including the need for an integrated theory that accounts for the development and manifestations of personal pistemology in the classroom, the generalizability of fi ndings across different measurements, a set of guidelines to promote teacher epistemological change, and an explicit instructional model that explains the development and calibration of beliefs and practices. The goal of this volume was to examine the relationship between teachers’ personal epistemologies and teacher education. Sixteen different chapters addressed one or more aspects of this issue. Although each of the chapters addressed different aspects of teachers’ personal epistemologies, a number of common themes are apparent across the chapters. We believe it is useful to articulate these themes in greater detail to provide a better retrospective understanding of this volume, as well as a better prospective framework for future research and changes to teacher training programs. We divide this chapter into two main sections. The fi rst section addresses four key questions about the nature of teachers’ personal epistemologies that were discussed in the introductory chapter as part of a larger set of questions. These questions focus on how to conceptualize these beliefs as explicit models; whether beliefs are domain-specifi c or domain-general; how beliefs are related to teaching; and how beliefs change over time. We provide a summary of each chapter in terms of these four questions. The second section proposes four general suggestions for future research based on the studies reported within this volume.

Leveraging Web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons

Since manually constructing domain-specific sentiment lexicons is extremely time consuming and it may not even be feasible for domains where linguistic expertise is not available. Research on the automatic construction of domain-specific sentiment lexicons has become a hot topic in recent years. The main contribution of this paper is the illustration of a novel semi-supervised learning method which exploits both term-to-term and document-to-term relations hidden in a corpus for the construction of domain specific sentiment lexicons. More specifically, the proposed two-pass pseudo labeling method combines shallow linguistic parsing and corpusbase statistical learning to make domain-specific sentiment extraction scalable with respect to the sheer volume of opinionated documents archived on the Internet these days. Another novelty of the proposed method is that it can utilize the readily available user-contributed labels of opinionated documents (e.g., the user ratings of product reviews) to bootstrap the performance of sentiment lexicon construction. Our experiments show that the proposed method can generate high quality domain-specific sentiment lexicons as directly assessed by human experts. Moreover, the system generated domain-specific sentiment lexicons can improve polarity prediction tasks at the document level by 2:18% when compared to other well-known baseline methods. Our research opens the door to the development of practical and scalable methods for domain-specific sentiment analysis.

Objectifying early-number : a visual nomenclature to express mathematical domain knowledge

To address issues of divisive ideologies in the Mathematics Education community and to subsequently advance educational practice, an alternative theoretical framework and operational model is proposed which represents a consilience of constructivist learning theories whilst acknowledging the objective but improvable nature of domain knowledge. Based upon Popper’s three-world model of knowledge, the proposed theory supports the differentiation and explicit modelling of both shared domain knowledge and idiosyncratic personal understanding using a visual nomenclature. The visual nomenclature embodies Piaget’s notion of reflective abstraction and so may support an individual’s experience-based transformation of personal understanding with regards to shared domain knowledge. Using the operational model and visual nomenclature, seminal literature regarding early-number counting and addition was analysed and described. Exemplars of the resultant visual artefacts demonstrate the proposed theory’s viability as a tool with which to characterise the reflective abstraction-based organisation of a domain’s shared knowledge. Utilising such a description of knowledge, future research needs to consider the refinement of the operational model and visual nomenclature to include the analysis, description and scaffolded transformation of personal understanding. A detailed model of knowledge and understanding may then underpin the future development of educational software tools such as computer-mediated teaching and learning environments.

Towards participatory action design research : adapting action research and design science research methods for urban informatics

This paper proposes a new research method, Participatory Action Design Research (PADR), for studies in the Urban Informatics domain. PADR supports Urban Informatics research in developing new technological means (e.g. using mobile and ubiquitous computing) to resolve contemporary issues or support everyday life in urban environments. The paper discusses the nature, aims and inherent methodological needs of Urban Informatics research, and proposes PADR as a method to address these needs. Situated in a socio-technical context, Urban Informatics requires a close dialogue between social and design-oriented fields of research as well as their methods. PADR combines Action Research and Design Science Research, both of which are used in Information Systems, another field with a strong socio-technical emphasis, and further adapts them to the cross-disciplinary needs and research context of Urban Informatics.

Action research as foresight methodology

To the action researcher, who laboriously spends his or her hours working within the local contexts of communities or organisations to co-generate meaningful research, and who’s theories are hardened on the anvil of creating meaningful social change; futures studies might seem the discipline the most peripheral to its interests, and the most ill equipped to deal with the local and intimate domain of community existence. To the futurist, who laboriously spends his or her hours understanding the nuances of history and social change, who through persistent work, begins to make sense of the weak signals and the subtle shifts, action research would seem as simply an auxiliary field, inappropriate for understanding the greater scheme. I invite the reader, however, whether they belong to one camp or the other, to let go of their respective disciplinary perspectives, and see both belonging to each other. [Introduction] .

Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web