Portrait of Nikolaus Braun 1932 Portraits Men

LBI

Corporate Social Responsibility (CSR) in junior and mid-tier Australian resources companies operating in developing nations - beyond the public relations offensive

NIt is now widely accepted that corporations have a responsibility to benefit society, as well as generate profit. This study used institutional theory to explore how the complex and contested notion of corporate social responsibility is understood and practiced by junior and mid-tier Australian resources companies operating in the world's most impoverished countries. The study found that CSR meaning and practice in this large but little researched group of companies was shaped by complex pressures at the global, industry, organisational and individual levels. Importantly, the study also revealed striking contradictions and ambiguities between participants' CSR aspirations and their actions and accountability.

Identification of a class of non-linear systems

This paper considers the on-line identification of a non-linear system in terms of a Hammerstein model, with a zero-memory non-linear gain followed by a linear system. The linear part is represented by a Laguerre expansion of its impulse response and the non-linear part by a polynomial. The identification procedure involves determination of the coefficients of the Laguerre expansion of correlation functions and an iterative adjustment of the parameters of the non-linear gain by gradient methods. The method is applicable to situations involving a wide class of input signals. Even in the presence of additive correlated noise, satisfactory performance is achieved with the variance of the error converging to a value close to the variance of the noise. Digital computer simulation establishes the practicability of the scheme in different situations.

Nine year changes in sitting time in young and mid-aged Australian women: Findings from the Australian longitudinal study for women's health

- Objective To examine changes in sitting time (ST) in women over nine years and to identify associations between life events and these changes. - Methods Young (born 1973–78, n = 5215) and mid-aged (born 1946–51, n = 6973) women reported life events and ST in four surveys of the Australian Longitudinal Study on Women's Health between 2000 and 2010. Associations between life events and changes in ST between surveys (decreasers ≥ 2 h/day less, increasers ≥ 2 h/day more) were estimated using generalized estimating equations. - Results Against a background of complex changes there was an overall decrease in ST in young women (median change − 0.48 h/day, interquartile range [IQR] = − 2.54, 1.50) and an increase in ST in mid-aged women (median change 0.43 h/day; IQR = − 1.29, 2.0) over nine years. In young women, returning to study and job loss were associated with increased ST, while having a baby, beginning work and decreased income were associated with decreased ST. In mid-aged women, changes at work were associated with increased ST, while retiring and decreased income were associated with decreased ST. - Conclusions ST changed over nine years in young and mid-aged Australian women. The life events they experienced, particularly events related to work and family, were associated with these changes.

Jer. (Jerusalem) - Worker's Eve. Class

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Jer. (Jerusalem) - Women's Sewing Class

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Mikveh Israel - Eve. Class

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Physical activity in mid-age and older women: Lessons from the Australian longitudinal study on women’s health

The Australian Longitudinal Study on Women’s Health (ALSWH) commenced in Australia in 1996 when researchers recruited approximately 40,000 women in three birth cohorts: 1973–1978, 1946–1951, and 1921–1926. Since then participants have completed surveys on a wide range of health issues, at approximately three-year intervals. This overview describes changes in physical activity (PA) over time in the mid-age and older ALSWH cohorts, and summarizes the findings of studies published to date on the determinants of PA, and its associated health outcomes in Australian women. The ALSWH data show a significant increase in PA during mid-age, and a rapid decline in activity levels when women are in their 80s. The study has demonstrated the importance of life stages and key life events as determinants of activity, the additional benefits of vigorous activity for mid-age women, and the health benefits of ‘only walking’ for older women. ALSWH researchers have also drawn attention to the benefits of activity in terms of a wide range of physical and mental health outcomes, as well as overall vitality and well-being. The data indicate that maintaining a high level of PA throughout mid and older age will not only reduce the risk of premature death, but also significantly extend the number of years of healthy life.

Prospective relationships between physical activity and optimism in young and mid-aged women

BACKGROUND: There is growing evidence that regular physical activity (PA) reduces the risk of poor mental health. Less research has focused on the relationship between PA and positive wellbeing. The study aims were to assess the prospective associations between PA and optimism, in both young and mid-aged women. METHODS: 9688 young women (born 1973-1978) completed self-report surveys in 2000 (age 22 to 27), 2003, 2006, and 2009; and 11,226 mid-aged women (born 1946-1951) completed surveys in 2001 (age 50-55) 2004, 2007, and 2010, as part of the Australian Longitudinal Study on Women's Health. Generalized estimating equation models (with 3-year time lag) were used to examine the relationship between PA and optimism in both cohorts. RESULTS: In both cohorts, women reporting higher levels of PA had greater odds of reporting higher optimism over the 9-year period, (young, OR = 5.04, 95% CI: 3.85-6.59; mid-age, OR = 5.77, 95% CI: 4.76-7.00) than women who reported no PA. Odds were attenuated in adjusted models, with depression accounting for a large amount of this attenuation (young, OR = 2.00, 95% CI: 1.57-2.55; mid-age, OR = 1.64 95% CI: 1.38-1.94). CONCLUSIONS: Physical activity can promote optimism in young and mid-aged women over time, even after accounting for the negative effects of other psychosocial indicators such as depression.

Dissipativeness and Stability of a Class of Distributed Parameter Systems

Input-output stability of linear-distributed parameter systems of arbitrary order and type in the presence of a distributed controller is analyzed by extending the concept of dissipativeness, with certain modifications, to such systems. The approach is applicable to systems with homogeneous or homogenizable boundary conditions. It also helps in generating a Liapunov functional to assess asymptotic stability of the system.

Emotional climate of a pre-service science teacher education class in Bhutan

This study explored pre-service secondary science teachers’ perceptions of classroom emotional climate in the context of the Bhutanese macro-social policy of Gross National Happiness. Drawing upon sociological perspectives of human emotions and using Interaction Ritual Theory this study investigated how pre-service science teachers may be supported in their professional development. It was a multi-method study involving video and audio recordings of teaching episodes supported by interviews and the researcher’s diary. Students also registered their perceptions of the emotional climate of their classroom at 3-minute intervals using audience response technology. In this way, emotional events were identified for video analysis. The findings of this study highlighted that the activities pre-service teachers engaged in matter to them. Positive emotional climate was identified in activities involving students’ presentations using video clips and models, coteaching, and interactive whole class discussions. Decreases in emotional climate were identified during formal lectures and when unprepared presenters led presentations. Emotions such as frustration and disappointment characterized classes with negative emotional climate. The enabling conditions to sustain a positive emotional climate are identified. Implications for sustaining macro-social policy about Gross National Happiness are considered in light of the climate that develops in science teacher education classes.

Classifying patients by their characteristics and clinical presentations; the use of latent class analysis

In this article, we introduce the general statistical analysis approach known as latent class analysis and discuss some of the issues associated with this type of analysis in practice. Two recent examples from the respiratory health literature are used to highlight the types of research questions that have been addressed using this approach.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.