Gambling revenues as a public administration issue : electronic gaming machines in Victoria

Gambling activities and the revenues derived have been seen as a way to increase economic development in deprived areas. There are also, however, concerns about the effects of gambling in general and electronic gaming machines (EGMs) in particular, on the resources available to the localities in which they are situated. This paper focuses on the factors that determine the extent and spending of community benefit-related EGM-generated resources within Victoria, Australia, focusing in particular on the relationships between EGM activity and socio-economic and social capital indicators, and how this relates to the community benefit resources generated by gaming.

Validation of the interRAI Cognitive Performance Scale against independent clinical diagnosis and the Mini-Mental State Examination in older hospitalized patients

Objective To compare the diagnostic accuracy of the interRAI Acute Care (AC) Cognitive Performance Scale (CPS2) and the Mini-Mental State Examination (MMSE), against independent clinical diagnosis for detecting dementia in older hospitalized patients. Design, Setting, and Participants The study was part of a prospective observational cohort study of patients aged ≥70 years admitted to four acute hospitals in Queensland, Australia, between 2008 and 2010. Recruitment was consecutive and patients expected to remain in hospital for ≥48 hours were eligible to participate. Data for 462 patients were available for this study. Measurements Trained research nurses completed comprehensive geriatric assessments and administered the interRAI AC and MMSE to patients. Two physicians independently reviewed patients’ medical records and assessments to establish the diagnosis of dementia. Indicators of diagnostic accuracy included sensitivity, specificity, predictive values, likelihood ratios and areas under receiver (AUC) operating characteristic curves. Results 85 patients (18.4%) were considered to have dementia according to independent clinical diagnosis. The sensitivity of the CPS2 [0.68 (95%CI: 0.58–0.77)] was not statistically different to the MMSE [0.75 (0.64–0.83)] in predicting physician diagnosed dementia. The AUCs for the 2 instruments were also not statistically different: CPS2 AUC = 0.83 (95%CI: 0.78–0.89) and MMSE AUC = 0.87 (95%CI: 0.83–0.91), while the CPS2 demonstrated higher specificity [0.92 95%CI: 0.89–0.95)] than the MMSE [0.82 (0.77–0.85)]. Agreement between the CPS2 and clinical diagnosis was substantial (87.4%; κ=0.61). Conclusion The CPS2 appears to be a reliable screening tool for assessing cognitive impairment in acutely unwell older hospitalized patients. These findings add to the growing body of evidence supporting the utility of the interRAI AC, within which the CPS2 is embedded. The interRAI AC offers the advantage of being able to accurately screen for both dementia and delirium without the need to use additional assessments, thus increasing assessment efficiency.

Cooperative education through a large scale industry-school partnership

In most of the advanced economies, students are losing interest in careers especially in en¬gineering and related industries. Hence, western economies are confronting a critical skilled labour shortage in areas of technology, science and engineering. Decisions about career pathways are made as early as the primary years of schooling and hence cooperation be¬tween industry and schools to attract students to the professions is crucial. The aim of this paper is to document how the organisational and institutional elements of one industry-school partnerships initiative — The Gateway Schools Program — contribute to productive knowledge sharing and networking. In particular this paper focuses on an initiative of an Australian State government in response to a perceived crisis around the skills shortage in an economy transitioning from a localised to a global knowledge production economy. The Gateway Schools initiative signals the first sustained attempt in Australia to incorporate schools into production networks through strategic partnerships linking them to partner organisations at the industry level. We provide case examples of how four schools opera¬tionalise the partnerships with the minerals and energy industries and how these partner¬ships as knowledge assets impact the delivery of curriculum and capacity building among teachers. Our ultimate goal is to define those characteristics of successful partnerships that do contribute to enhanced interest and engagement by students in those careers that are currently experiencing critical shortages.

Geologic map of the Valley Mountain 15’ quadrangle, San Bernardino and Riverside Counties, California: U.S. Geological Survey Geologic Quadrangle Map GQ–1767, scale 1:62,500

The Valley Mountain 15’ quadrangle straddles the Pinto Mountain Fault, which bounds the eastern Transverse Ranges in the south against the Mojave Desert province in the north. The Pinto Mountains, part of the eastern Transverse Ranges in the south part of the quadrangle expose a series of Paleoproterozoic gneisses and granite and the Proterozoic quartzite of Pinto Mountain. Early Triassic quartz monzonite intruded the gneisses and was ductiley deformed prior to voluminous Jurassic intrusion of diorite, granodiorite, quartz monzonite, and granite plutons. The Jurassic rocks include part of the Bullion Mountains Intrusive Suite, which crops out prominently at Valley Mountain and in the Bullion Mountains, as well as in the Pinto Mountains. Jurassic plutons in the southwest part of the quadrangle are deeply denuded from midcrustal emplacement levels in contrast to supracrustal Jurassic limestone and volcanic rocks exposed in the northeast. Dikes inferred to be part of the Jurassic Independence Dike Swarm intrude the Jurassic plutons and Proterozoic rocks. Late Cretaceous intrusion of the Cadiz Valley Batholith in the northeast caused contact metamorphism of adjacent Jurassic plutonic rocks...

National survey of viruses in pastures of subterranean clover. II. Statistical methodology for large scale quantitative ELISA

Statistical methodology was applied to a survey of time-course incidence of four viruses (alfalfa mosaic virus, clover yellow vein virus, subterranean clover mottle virus and subterranean clover red leaf virus) in improved pastures in southern regions of Australia. -from Authors

Local stress-strain distribution and load transfer across cartilage matrix at micro-scale using combined microscopy-based finite element method

Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.

Large-scale analysis of formations in soccer

Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

Dispute resolution across platforms : offshore gambling industry & EVE online

Contemporary online environments suffer from a regulatory gap; that is there are few options for participants between customer service departments and potentially expensive court cases in foreign jurisdictions. Whatever form of regulation ultimately fills that gap will be charged with determining whether specific behavior, within a specific environment, is fair or foul; whether it’s cheating or not. However, cheating is a term that, despite substantial academic study, remains problematic. Is anything the developer doesn’t want you to do cheating? Is it only if your actions breach the formal terms of service? What about the community norms, do they matter at all? All of these remain largely unresolved questions, due to the lack of public determination of cases in such environments, which have mostly been settled prior to legal action. In this paper, I propose a re-branding of participant activity in such environments into developer-sanctioned, advantage play, and cheating. Advantage play, ultimately, is activity within the environment in which the player is able to turn the mechanics of the environment to their advantage without breaching the rules of the environment. Such a definition, and the term itself, is based on the usage of the term within the gambling industry, in which advantage play is considered betting with the advantage in the players’ favor rather than that of the house. Through examples from both the gambling industry and the Massively Multiplayer Role-Playing Game Eve Online, I consider the problems in defining cheating, suggest how the term ‘advantage play’ may be useful in understanding participants behavior in contemporary environments, and ultimately consider the use of such terminology in dispute resolution models which may overcome this regulatory gap.

Slicing big data - Twitter, gambling and time sensitive information

Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

Asking the wrong questions about gambling

OVERSHADOWED by the debate about the government’s media legislation, the final report of the review of the Interactive Gambling Act 2001, published last week, received comparatively little attention. Like the government’s response to the report, the sparse media coverage focused on measures to prevent problem gambling – undoubtedly an important issue – but failed to discuss the fact that Australian gamblers, recreational or otherwise, continue to get a raw deal. The report seems likely to perpetuate a culture of high-margin, low-risk bookmaking, cutting Australians off from the global market under the guise of consumer protection. Also missing from the debate are two other questions: are Australian gamblers getting value for money, and where do the growing number of social games fit into the regulatory landscape?

A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters : theory and application to microfilaments

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.

Consumer perceptions of trade show effectiveness : scale development and validation within a B2C context

Purpose This paper develops and estimates a model to measure consumer perceptions of trade show effectiveness. Design/methodology/approach Data were collected at three separate B2C trade shows. Study 1 (n=47) involved field interviews with data subjected to qualitative item generation and content analysis. Study 2 data (n=147) were subjected to exploratory factor analysis and item-total correlation to identify a preliminary factor structure for the effectiveness construct and to test for reliability. In Study 3 (n=592), confirmatory factor analysis was undertaken to more rigorously test the factor structure and generalise across industries. Validity testing was also performed. Findings A three-dimensional factor structure for assessing consumer visitors’ perceptions of trade show effectiveness was produced incorporating research, operational, and entertainment components. Research limitations/implications Data were collected in Australia and results may not generalise across cultural boundaries. Practical implications The resulting measurement model may be used as a reliable post-hoc diagnostic tool to identify areas of trade show effectiveness where specific performance improvements are needed. Results indicate that exhibitors and organisers of B2C trade shows should consider effectiveness as a multidimensional phenomenon with entertainment, product / industry research, and the facilitation of purchase decision-making processes and problem resolution being key objectives for consumer attendees. These elements of effectiveness should each be addressed by exhibitors and organisers in planning their displays and events. Originality/value This is the first study to provide an empirically valid model for assessing trade show effectiveness from the consumer visitor’s perspective.

The evaluation of a clinical scar scale for porcine burn scars

This study describes the evaluation of a clinical scar scale for our porcine burn scars, which includes scar cosmetic outcome, colour, height and hair, supplemented with reference porcine scar photographs representing each scar outcome and scar colour scores. A total of 72 porcine burn scars at week 6 after burn were rated in vivo and/or on photographs. Good agreements were achieved for both intra-rater reliability (correlation is 0.86-0.98) and inter-rater reliability (ICC=80-85%). The results showed statistically significant correlations for each pair in this clinical scar scale (p<0.01), with the best correlation found between scar cosmetic outcome and scar colour. A multivariate principle components analysis revealed that this clinical scar assessment was highly correlated with scar histology, wound size, and re-epithelialisation data (p<0.001). More severe scars are clinically characterised by darker purple colouration, more elevation, no presence of hair, histologically by thicker scar tissue, thinner remaining normal dermis, are more likely to have worse contraction, and slower re-epithelialisation. This study demonstrates that our clinical scar scale is a reliable, independent and valuable tool for assessing porcine burn outcome and truthfully reflects scar appearance and function. To our knowledge, this is the first study demonstrating a high correlation between clinical scar assessment and scar histology, wound contraction and re-epithelialisation data on porcine burn scars. We believe that the successful use of porcine scar scales is invaluable for assessing potential human burn treatments.

French version of the Family Attitude Scale : psychometric properties and relation of attitudes to the respondent's psychiatric status

The Family Attitude Scale (FAS) is a self-report measure of critical or hostile attitudes and behaviors towards another family member, and demonstrates an ability to predict relapse in psychoses. Data are not currently available on a French version of the scale. The present study developed a French version of the FAS, using a large general population sample to test its internal structure, criterion validity and relationships with the respondents' symptoms and psychiatric diagnoses, and examined the reciprocity of FAS ratings by respondents and their partners. A total of 2072 adults from an urban population undertook a diagnostic interview and completed self-report measures, including an FAS about their partner. A subset of participants had partners who also completed the FAS. Confirmatory factor analyses revealed an excellent fit by a single-factor model, and the FAS demonstrated a strong association with dyadic adjustment. FAS scores of respondents were affected by their anxiety levels and mood, alcohol and anxiety diagnoses, and moderate reciprocity of attitudes and behaviors between the partners was seen. The French version of the FAS has similarly strong psychometric properties to the original English version. Future research should assess the ability of the French FAS to predict relapse of psychiatric disorders.

Developing an acculturation and resilience scale for use with culturally and linguistically diverse populations

Australian multicultural society consists of culturally and linguistically diverse (CALD) migrants, refugees and international students from different parts of the world. Despite hardships, these individuals show resilience and adapt successfully. However, there is a dearth of scales measuring these positive developments and personal strengths. The study describes the development and evaluation of a scale measuring resilience and acculturation of CALD people. Items were generated for the Acculturation and Resilience Scale (AARS).The AARS and other acculturation and psychological distress scales were administered to 225 CALD community members. Exploratory factor analyses resulted in a 27-item AARS with three subscales: Acculturation, Resilience, and Spirituality. The three-factor structure was subjected to a confirmatory factor analysis on a sample of 515 international students. The factor structure stability was upheld by the second sample. The psychometric properties were investigated using the two samples and demonstrated satisfactory internal consistency, test-retest reliability, and divergent validity. The scale addresses a major gap in the literature and can be used to measure the positive acculturation and resilience of the newly arrived and relocated individuals. Further research is warranted to examine the scale’s psychometric properties with migrants and refugees from a range of ethnic communities.