Prospective association between physical activity and falls in community-dwelling older women

Abstract Objective: To explore associations between physical activity and risk of falls and broken or fractured bones in community-dwelling older women. Design, setting and participants: This was a prospective observational survey with 3- and 6-year follow-ups. The sample included 8562 healthy, community-dwelling women, aged 70-75 years in 1996, who completed surveys as participants in the Australian Longitudinal Study on Women’s Health. Outcomes were reports of a fall to the ground, injury from a fall, and broken or fractured bones in 1999 and 2002. The main predictor variable was physical activity level in 1996, categorized based on weekly frequency as none/very low, low, moderate, high, and very high. Covariates were demographic and health-related variables. Logistic regression models were computed separately for each outcome in 1999 and 2002. Main results: In multivariable models, very high physical activity was associated with decreased risk of a fall in 1999 (odds ratio 0.67, 95% CI 0.48 to 0.93) and in 2002 (odds ratio 0.62, 95% CI 0.42 to 0.92). High/very high physical activity was associated with decreased risk of broken or fractured bones in 2002 (odds ratio 0.64, 95% CI 0.42 to 0.96). No significant association was found between physical activity and injury from a fall. Conclusions: The results suggest that at least daily moderate to vigorous physical activity is required for the primary prevention of falls to the ground and broken or fractured bones in women aged 70-75 years.

Digit recognition using trispectral features

Features derived from the trispectra of DFT magnitude slices are used for multi-font digit recognition. These features are insensitive to translation, rotation, or scaling of the input. They are also robust to noise. Classification accuracy tests were conducted on a common data base of 256× 256 pixel bilevel images of digits in 9 fonts. Randomly rotated and translated noisy versions were used for training and testing. The results indicate that the trispectral features are better than moment invariants and affine moment invariants. They achieve a classification accuracy of 95% compared to about 81% for Hu's (1962) moment invariants and 39% for the Flusser and Suk (1994) affine moment invariants on the same data in the presence of 1% impulse noise using a 1-NN classifier. For comparison, a multilayer perceptron with no normalization for rotations and translations yields 34% accuracy on 16× 16 pixel low-pass filtered and decimated versions of the same data.

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.

Arterial traffic congestion analysis using Bluetooth duration data

The aim of this study is to assess the potential use of Bluetooth data for traffic monitoring of arterial road networks. Bluetooth data provides the direct measurement of travel time between pairs of scanners, and intensive research has been reported on this topic. Bluetooth data includes “Duration” data, which represents the time spent by Bluetooth devices to pass through the detection range of Bluetooth scanners. If the scanners are located at signalised intersections, this Duration can be related to intersection performance, and hence represents valuable information for traffic monitoring. However the use of Duration has been ignored in previous analyses. In this study, the Duration data as well as travel time data is analysed to capture the traffic condition of a main arterial route in Brisbane. The data consists of one week of Bluetooth data provided by Brisbane City Council. As well, micro simulation analysis is conducted to further investigate the properties of Duration. The results reveal characteristics of Duration, and address future research needs to utilise this valuable data source.

A node-based smoothed conforming point interpolation method (NS-CPIM) for elasticity problems

This paper formulates a node-based smoothed conforming point interpolation method (NS-CPIM) for solid mechanics. In the proposed NS-CPIM, the higher order conforming PIM shape functions (CPIM) have been constructed to produce a continuous and piecewise quadratic displacement field over the whole problem domain, whereby the smoothed strain field was obtained through smoothing operation over each smoothing domain associated with domain nodes. The smoothed Galerkin weak form was then developed to create the discretized system equations. Numerical studies have demonstrated the following good properties: NS-CPIM (1) can pass both standard and quadratic patch test; (2) provides an upper bound of strain energy; (3) avoid the volumetric locking; (4) provides the higher accuracy than those in the node-based smoothed schemes of the original PIMs.

Not-for-profits and risk accountability : insuring the third sector

Not for profit organisations face significant challenges in managing organisational risk. In this regard not-for-profits are not unique but they are distinguishable from their 'for-profit' counterparts in that they are less likely to have the resources to find sufficient risk management strategies and plans, are very vunerable to cyclical changes in the insurance market and are not usually in a position to pass on the costs of increased premiums to third parties such as consumers of their services. This article explores the nature and extent of risks faced by the not-for-profit sector; the appropriateness and scope of risk management to reduce and manage the likelihood and incidence of risk; and the types of insurance and options to cover risks that materialise. It concludes with a recommendation for a potential course of action.

Raising awareness of traffic pollution: the potential benefits and problems of using a warning smell

Exposure to traffic pollution is increasing worldwide as people move to cities, and as more vehicles join the roads, creating longer journeys and more traffic jams. Most traffic pollutants are odourless and invisible, which hides exposure from the public. If traffic pollution had a distinctive smell it would enable people to avoid exposure, and increase the political will for difficult policy changes. A smell may also instigate longer-term changes, such as switching to active transport for school pick-ups. A smell could be added using a fuel additive or a temporary device attached to vehicle exhausts.

Communications and learning structures that facilitate transfer of knowledge at innovation transition points

Innovation processes are rarely smooth and disruptions often occur at transition points were one knowledge domain passes the technology on to another domain. At these transition points communication is a key component in assisting the smooth hand over of technologies. However for smooth transitions to occur we argue that appropriate structures have to be in place and boundary spanning activities need to be facilitated. This paper presents three case studies of innovation processes and the findings support the view that structures and boundary spanning are essential for smooth transitions. We have explained the need to pass primary responsibility between agents to successfully bring an innovation to market. We have also shown the need to combine knowledge through effective communication so that absorptive capacity is built in process throughout the organisation rather than in one or two key individuals.

Some empirical results for neo-Piagetian reasoning in novice programmers and the relationship to code explanation questions

Recent research on novice programmers has suggested that they pass through neo-Piagetian stages: sensorimotor, preoperational, and concrete operational stages, before eventually reaching programming competence at the formal operational stage. This paper presents empirical results in support of this neo-Piagetian perspective. The major novel contributions of this paper are empirical results for some exam questions aimed at testing novices for the concrete operational abilities to reason with quantities that are conserved, processes that are reversible, and properties that hold under transitive inference. While the questions we used had been proposed earlier by Lister, he did not present any data for how students performed on these questions. Our empirical results demonstrate that many students struggle to answer these problems, despite the apparent simplicity of these problems. We then compare student performance on these questions with their performance on six explain in plain English questions.

Government initiative and start-up firms’ eco-innovation : A case study through the ecological modernisation lens

Government programs to finance small firms or start-ups have attracted a little empirical attention. From an economical perspective, the effect of government grants is evaluated by a measure of innovation or firm productivity. Yet, this paper takes a different approach from economical view aiming to address the research question “How do start ups firms view the relationship between government grants and their co-efficient innovation effort?” Semi-structured interviews with grant recipients (start-up business owners revealed that the grants assist firms to leverage their resource limitations but at the same time the grants also act as a major roadblock for their product development success.

Developing support for micro-entrepreneurs in a developing economy in Africa

The purpose of this paper is to explore the means of building the capacity of those who are running an organisation designed to support and resource start-ups and growing micro enterprises among some of the world’s poorest urban poor. The project is based in Beira, Mozambique, one of the poorest countries in the world. The result of this study is the development of a model for providing ongoing, inexpensive, effective, capacity building in developing economies. The model also provides a base for the further development of strategies to provide better support to micro entrepreneurs in poor developing economies.

Transit line passenger transmission and productiveness under high load conditions

Deterministic transit capacity analysis applies to planning, design and operational management of urban transit systems. The Transit Capacity and Quality of Service Manual (1) and Vuchic (2, 3) enable transit performance to be quantified and assessed using transit capacity and productive capacity. This paper further defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures the transit task performed over distance. Passenger transmission (p-km/h) captures the passenger task delivered by service at speed. Transit productiveness (p-km/h) captures transit work performed over time. These measures are useful to operators in understanding their services’ or systems’ capabilities and passenger quality of service. This paper accounts for variability in utilized demand by passengers along a line and high passenger load conditions where passenger pass-up delay occurs. A hypothetical case study of an individual bus service’s operation demonstrates the usefulness of passenger transmission in comparing existing and growth scenarios. A hypothetical case study of a bus line’s operation during a peak hour window demonstrates the theory’s usefulness in examining the contribution of individual services to line productive performance. Scenarios may be assessed using this theory to benchmark or compare lines and segments, conditions, or consider improvements.

Digital human modelling for vehicle design and manufacturing

Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

CAUSEE Dataset and documentation

The Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) is the largest study of new firm creation ever undertaken in Australia. The project provides an exciting opportunity to fundamentally improve our understanding of independent entrepreneurship in Australia by studying factors that initiate, hinder and facilitate the process of emergence of new economic activities and organisations. The longitudinal project has followed a large random sample of nascent firms (n=625) and young firms (n=559) over a six year period. NFs are on-going start-up efforts while YFs are already established but less than four years old. The study also includes a comparison group of non-founders and over-samples of over 100 high potential start-ups in each category. The CAUSEE dataset file contains hundreds of variables throughout 5 waves of data collection. Extensive documentation on the dataset is available in the related handbook. The CAUSEE project has received significant external funding from the Australian Research Council (DP0666616 and LP0776845); National Australia Bank; BDO Australia, and the Australian Government Department of Industry, Innovation and Science.

Introduction

In this volume we compile and comment on a collection of some of the most important works on nascent entrepreneurship that have appeared in the last two decades. We do not go further back than that because up until1992 hardly any systematic research on the pre-operational stage of business creation was undertaken. In that year, the terms 'nascent entrepreneur' and 'nascent venture' appear for the first time in the research literature (Reynolds and Miller, Chapter l, 1992; Reynolds and White, 1992). This signals the emergence of a new research paradigm designed to study• business creation processes empirically at very early stages, before an operational firm has come into existence. The most central feature of this type of research is that it identifies a statistically representative sample of nascent entrepreneurs (NEs)- people engaged in ongoing but not yet operational business start-ups- via screening interviews with a very large random sample of adults. The overarching research questions pursued in this emerging research tradition are the following: 1. What proportion of individuals (in various population subgroups) are trying to start a new business at any given time? 2. What led them to engage in the creation of a new business? 3. What characteristics and behaviors associated with the founder(s), the venture, the environment and the process are associated with persistence, progress and success in trying to start a new business?