Exercise and lymphoedema : Is it good or bad?

Being physically active during and following treatment for breast cancer has been associated with a range of benefits including improved fitness and function, body composition and immune function and reductions in stress, depression and anxiety, as well as the number and severity of treatment-related side-effects such as nausea, fatigue and pain, all of which contribute to improvements in quality of life. There is also emerging evidence linking active lifestyles with improved survival. Therefore, there is little doubt that participating in regular exercise following breast cancer is ‘good’. Unfortunately, research investigating the role of exercise for women considered at high-risk of lymphoedema or who have developed lymphedema following breast cancer is lacking. For fear of initiating or exacerbating lymphoedema, these women have traditionally been cautioned rather than encouraged to be regularly active. However, recent preliminary findings suggest that being inactive may increase risk of developing lymphedema, and that for those with lymphoedema, participation in an exercise program does not exacerbate the condition. This presentation will address what we know about the role of exercise following a breast cancer diagnosis and will provide some practical recommendations about becoming and staying regularly active following breast cancer, for those with and without lymphoedema.

Molecular architecture of the human sinus node: insights into the function of the cardiac pacemaker.

BACKGROUND: Although we know much about the molecular makeup of the sinus node (SN) in small mammals, little is known about it in humans. The aims of the present study were to investigate the expression of ion channels in the human SN and to use the data to predict electrical activity. METHODS AND RESULTS: Quantitative polymerase chain reaction, in situ hybridization, and immunofluorescence were used to analyze 6 human tissue samples. Messenger RNA (mRNA) for 120 ion channels (and some related proteins) was measured in the SN, a novel paranodal area, and the right atrium (RA). The results showed, for example, that in the SN compared with the RA, there was a lower expression of Na(v)1.5, K(v)4.3, K(v)1.5, ERG, K(ir)2.1, K(ir)6.2, RyR2, SERCA2a, Cx40, and Cx43 mRNAs but a higher expression of Ca(v)1.3, Ca(v)3.1, HCN1, and HCN4 mRNAs. The expression pattern of many ion channels in the paranodal area was intermediate between that of the SN and RA; however, compared with the SN and RA, the paranodal area showed greater expression of K(v)4.2, K(ir)6.1, TASK1, SK2, and MiRP2. Expression of ion channel proteins was in agreement with expression of the corresponding mRNAs. The levels of mRNA in the SN, as a percentage of those in the RA, were used to estimate conductances of key ionic currents as a percentage of those in a mathematical model of human atrial action potential. The resulting SN model successfully produced pacemaking. CONCLUSIONS: Ion channels show a complex and heterogeneous pattern of expression in the SN, paranodal area, and RA in humans, and the expression pattern is appropriate to explain pacemaking.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Mathematical modelling of muscle recruitment and function in the lumbar spine

Low back pain is an increasing problem in industrialised countries and although it is a major socio-economic problem in terms of medical costs and lost productivity, relatively little is known about the processes underlying the development of the condition. This is in part due to the complex interactions between bone, muscle, nerves and other soft tissues of the spine, and the fact that direct observation and/or measurement of the human spine is not possible using non-invasive techniques. Biomechanical models have been used extensively to estimate the forces and moments experienced by the spine. These models provide a means of estimating the internal parameters which can not be measured directly. However, application of most of the models currently available is restricted to tasks resembling those for which the model was designed due to the simplified representation of the anatomy. The aim of this research was to develop a biomechanical model to investigate the changes in forces and moments which are induced by muscle injury. In order to accurately simulate muscle injuries a detailed quasi-static three dimensional model representing the anatomy of the lumbar spine was developed. This model includes the nine major force generating muscles of the region (erector spinae, comprising the longissimus thoracis and iliocostalis lumborum; multifidus; quadratus lumborum; latissimus dorsi; transverse abdominis; internal oblique and external oblique), as well as the thoracolumbar fascia through which the transverse abdominis and parts of the internal oblique and latissimus dorsi muscles attach to the spine. The muscles included in the model have been represented using 170 muscle fascicles each having their own force generating characteristics and lines of action. Particular attention has been paid to ensuring the muscle lines of action are anatomically realistic, particularly for muscles which have broad attachments (e.g. internal and external obliques), muscles which attach to the spine via the thoracolumbar fascia (e.g. transverse abdominis), and muscles whose paths are altered by bony constraints such as the rib cage (e.g. iliocostalis lumborum pars thoracis and parts of the longissimus thoracis pars thoracis). In this endeavour, a separate sub-model which accounts for the shape of the torso by modelling it as a series of ellipses has been developed to model the lines of action of the oblique muscles. Likewise, a separate sub-model of the thoracolumbar fascia has also been developed which accounts for the middle and posterior layers of the fascia, and ensures that the line of action of the posterior layer is related to the size and shape of the erector spinae muscle. Published muscle activation data are used to enable the model to predict the maximum forces and moments that may be generated by the muscles. These predictions are validated against published experimental studies reporting maximum isometric moments for a variety of exertions. The model performs well for fiexion, extension and lateral bend exertions, but underpredicts the axial twist moments that may be developed. This discrepancy is most likely the result of differences between the experimental methodology and the modelled task. The application of the model is illustrated using examples of muscle injuries created by surgical procedures. The three examples used represent a posterior surgical approach to the spine, an anterior approach to the spine and uni-lateral total hip replacement surgery. Although the three examples simulate different muscle injuries, all demonstrate the production of significant asymmetrical moments and/or reduced joint compression following surgical intervention. This result has implications for patient rehabilitation and the potential for further injury to the spine. The development and application of the model has highlighted a number of areas where current knowledge is deficient. These include muscle activation levels for tasks in postures other than upright standing, changes in spinal kinematics following surgical procedures such as spinal fusion or fixation, and a general lack of understanding of how the body adjusts to muscle injuries with respect to muscle activation patterns and levels, rate of recovery from temporary injuries and compensatory actions by other muscles. Thus the comprehensive and innovative anatomical model which has been developed not only provides a tool to predict the forces and moments experienced by the intervertebral joints of the spine, but also highlights areas where further clinical research is required.

A comparison of executive function in very preterm and term infants at 8 months corrected age

Executive function (EF) emerges in infancy and continues to develop throughout childhood. Executive dysfunction is believed to contribute to learning and attention problems in children at school age. Children born very preterm are more prone to these problems than their full-term peers.

Methods and preliminary results for a data linkage project to determine long-term survival after intensive care unit admission

Aims: To describe a local data linkage project to match hospital data with the Australian Institute of Health and Welfare (AIHW) National Death Index (NDI) to assess longterm outcomes of intensive care unit patients. Methods: Data were obtained from hospital intensive care and cardiac surgery databases on all patients aged 18 years and over admitted to either of two intensive care units at a tertiary-referral hospital between 1 January 1994 and 31 December 2005. Date of death was obtained from the AIHW NDI by probabilistic software matching, in addition to manual checking through hospital databases and other sources. Survival was calculated from time of ICU admission, with a censoring date of 14 February 2007. Data for patients with multiple hospital admissions requiring intensive care were analysed only from the first admission. Summary and descriptive statistics were used for preliminary data analysis. Kaplan-Meier survival analysis was used to analyse factors determining long-term survival. Results: During the study period, 21 415 unique patients had 22 552 hospital admissions that included an ICU admission; 19 058 surgical procedures were performed with a total of 20 092 ICU admissions. There were 4936 deaths. Median follow-up was 6.2 years, totalling 134 203 patient years. The casemix was predominantly cardiac surgery (80%), followed by cardiac medical (6%), and other medical (4%). The unadjusted survival at 1, 5 and 10 years was 97%, 84% and 70%, respectively. The 1-year survival ranged from 97% for cardiac surgery to 36% for cardiac arrest. An APACHE II score was available for 16 877 patients. In those discharged alive from hospital, the 1, 5 and 10-year survival varied with discharge location. Conclusions: ICU-based linkage projects are feasible to determine long-term outcomes of ICU patients

Micro-family-owned business : transitory survival mechanism or long term wealth creator?

Principal Topic: Entrepreneurship is key to employment, innovation and growth (Acs & Mueller, 2008), and as such, has been the subject of tremendous research in both the economic and management literatures since Solow (1957), Schumpeter (1934, 1943), and Penrose (1959). The presence of entrepreneurs in the economy is a key factor in the success or failure of countries to grow (Audretsch and Thurik, 2001; Dejardin, 2001). Further studies focus on the conditions of existence of entrepreneurship, influential factors invoked are historical, cultural, social, institutional, or purely economic (North, 1997; Thurik 1996 & 1999). Of particular interest, beyond the reasons behind the existence of entrepreneurship, are entrepreneurial survival and good ''performance'' factors. Using cross-country firm data analysis, La Porta & Schleifer (2008) confirm that informal micro-businesses provide on average half of all economic activity in developing countries. They find that these are utterly unproductive compared to formal firms, and conclude that the informal sector serves as a social security net ''keep[ing] millions of people alive, but disappearing over time'' (abstract). Robison (1986), Hill (1996, 1997) posit that the Indonesian government under Suharto always pointed to the lack of indigenous entrepreneurship , thereby motivating the nationalisation of all industries. Furthermore, the same literature also points to the fact that small businesses were mostly left out of development programmes because they were supposed less productive and having less productivity potential than larger ones. Vial (2008) challenges this view and shows that small firms represent about 70% of firms, 12% of total output, but contribute to 25% of total factor productivity growth on average over the period 1975-94 in the industrial sector (Table 10, p.316). ---------- Methodology/Key Propositions: A review of the empirical literature points at several under-researched questions. Firstly, we assess whether there is, evidence of small family-business entrepreneurship in Indonesia. Secondly, we examine and present the characteristics of these enterprises, along with the size of the sector, and its dynamics. Thirdly, we study whether these enterprises underperform compared to the larger scale industrial sector, as it is suggested in the literature. We reconsider performance measurements for micro-family owned businesses. We suggest that, beside productivity measures, performance could be appraised by both the survival probability of the firm, and by the amount of household assets formation. We compare micro-family-owned and larger industrial firms' survival probabilities after the 1997 crisis, their capital productivity, then compare household assets of families involved in business with those who do not. Finally, we examine human and social capital as moderators of enterprises' performance. In particular, we assess whether a higher level of education and community participation have an effect on the likelihood of running a family business, and whether it has an impact on households' assets level. We use the IFLS database compiled and published by RAND Corporation. The data is a rich community, households, and individuals panel dataset in four waves: 1993, 1997, 2000, 2007. We now focus on the waves 1997 and 2000 in order to investigate entrepreneurship behaviours in turbulent times, i.e. the 1997 Asian crisis. We use aggregate individual data, and focus on households data in order to study micro-family-owned businesses. IFLS data covers roughly 7,600 households in 1997 and over 10,000 households in 2000, with about 95% of 1997 households re-interviewed in 2000. Households were interviewed in 13 of the 27 provinces as defined before 2001. Those 13 provinces were targeted because accounting for 83% of the population. A full description of the data is provided in Frankenberg and Thomas (2000), and Strauss et alii (2004). We deflate all monetary values in Rupiah with the World Development Indicators Consumer Price Index base 100 in 2000. ---------- Results and Implications: We find that in Indonesia, entrepreneurship is widespread and two thirds of households hold one or several family businesses. In rural areas, in 2000, 75% of households run one or several businesses. The proportion of households holding both a farm and a non farm business is higher in rural areas, underlining the reliance of rural households on self-employment, especially after the crisis. Those businesses come in various sizes from very small to larger ones. The median business production value represents less than the annual national minimum wage. Figures show that at least 75% of farm businesses produce less than the annual minimum wage, with non farm businesses being more numerous to produce the minimum wage. However, this is only one part of the story, as production is not the only ''output'' or effect of the business. We show that the survival rate of those businesses ranks between 70 and 82% after the 1997 crisis, which contrasts with the 67% survival rate for the formal industrial sector (Ter Wengel & Rodriguez, 2006). Micro Family Owned Businesses might be relatively small in terms of production, they also provide stability in times of crisis. For those businesses that provide business assets figures, we show that capital productivity is fairly high, with rates that are ten times higher for non farm businesses. Results show that households running a business have larger family assets, and households are better off in urban areas. We run a panel logit model in order to test the effect of human and social capital on the existence of businesses among households. We find that non farm businesses are more likely to appear in households with higher human and social capital situated in urban areas. Farm businesses are more likely to appear in lower human capital and rural contexts, while still being supported by community participation. The estimation of our panel data model confirm that households are more likely to have higher family assets if situated in urban area, the higher the education level, the larger the assets, and running a business increase the likelihood of having larger assets. This is especially true for non farm businesses that have a clearly larger and more significant effect on assets than farm businesses. Finally, social capital in the form of community participation also has a positive effect on assets. Those results confirm the existence of a strong entrepreneurship culture among Indonesian households. Investigating survival rates also shows that those businesses are quite stable, even in the face of a violent crisis such as the 1997 one, and as a result, can provide a safety net. Finally, considering household assets - the returns of business to the household, rather than profit or productivity - the returns of business to itself, shows that households running a business are better off. While we demonstrate that uman and social capital are key to business existence, survival and performance, those results open avenues for further research regarding the factors that could hamper growth of those businesses in terms of output and employment.

Survival Power: An Empirical Analysis of Power in a Life and Death Situation

This paper seeks to identify what antecedents of power make it more or less likely for people to survive in a life-threatening situation.In particular, we look at the Titanic disaster as the life or death situation. Maritime disasters can be interpreted as quasi-natural experiments because every person is affected by the shock. True human nature becomes apparent in such a dangerous situation. Five antecedents of power are distinguished: physical strength, economic resources, nationality, social and moral factors. This empirical analysis supports the notion that power is a key determinant in extreme situations of life or death.

Planning for survival

When the global financial crisis has its own acronym (the “GFC”), you know its going to be around for a while. This article looks at some of the risk/opportunity assessments you should take into consideration if you are planning for your property development business to still be around when the GFC is a thing of the past.

Re-conceptualising IS function's support performance : a preliminary model

While IS function has gained widespread attention for over two decades, there is little consensus among information systems (IS) researchers and practitioners on how best to evaluate IS function's support performance. This paper reports on preliminary findings of a larger research effort proceeds from a central interest in the importance of evaluating IS function's support in organisations. This study is the first that attempts to re-conceptualise and conceive evaluate IS function's support as a multi- dimensional formative construct. We argue that a holistic measure for evaluating evaluate IS function's support should consist of dimensions that together assess the variety of the support functions and the quality of the support services provided to end-users. Thus, the proposed model consists of two halves, "Variety" and "Quality" within which resides seven dimensions. The Variety half includes five dimensions: Training; Documentation; Data- related Support, Software-related Support; and Hardware-related Support. The Quality half includes two dimensions: IS Support Staff and Support Services Performance. The proposed model is derived using a directed content analysis of 83 studies; from top IS outlets, employing the characteristics of the analytic theory and consistent with formative construct development procedures.