153 resultados para Agricultural Credit Associations.
Resumo:
BACKGROUND: The relationship between cigarette smoking and cardiovascular disease is well established, yet the underlying mechanisms remain unclear. Although smokers have a more atherogenic lipid profile, this may be mediated by other lifestyle-related factors. Analysis of lipoprotein subclasses by the use of nuclear magnetic resonance spectroscopy (NMR) may improve characterisation of lipoprotein abnormalities. OBJECTIVE: We used NMR spectroscopy to investigate the relationships between smoking status, lifestyle-related risk factors, and lipoproteins in a contemporary cohort. METHODS: A total of 612 participants (360 women) aged 40–69 years at baseline (199021994) enrolled in the Melbourne Collaborative Cohort Study had plasma lipoproteins measured with NMR. Data were analysed separately by sex. RESULTS: After adjusting for lifestyle-related risk factors, including alcohol and dietary intake, physical activity, and weight, mean total low-density lipoprotein (LDL) particle concentration was greater for female smokers than nonsmokers. Both medium- and small-LDL particle concentrations contributed to this difference. Total high-density lipoprotein (HDL) and large-HDL particle concentrations were lower for female smokers than nonsmokers. The proportion with low HDL particle number was greater for female smokers than nonsmokers. For men, there were few smoking-related differences in lipoprotein measures. CONCLUSION: Female smokers have a more atherogenic lipoprotein profile than nonsmokers. This difference is independent of other lifestyle-related risk factors. Lipoprotein profiles did not differ greatly between male smokers and nonsmokers.
Resumo:
This study explored youth caregiving for a parent with multiple sclerosis (MS) from multiple perspectives, and examined associations between caregiving and child negative (behavioural emotional difficulties, somatisation) and positive (life satisfaction, positive affect, prosocial behaviour) adjustment outcomes overtime. A total of 88 families participated; 85 parents with MS, 55 partners and 130 children completed questionnaires at Time 1. Child caregiving was assessed by the Youth Activities of Caregiving Scale (YACS). Child and parent questionnaire data were collected at Time 1 and child data were collected 12 months later (Time 2). Factor analysis of the child and parent YACS data replicated the four factors (instrumental, social-emotional, personal-intimate, domestic-household care), all of which were psychometrically sound. The YACS factors were related to parental illness and caregiving context variables that reflected increased caregiving demands. The Time 1 instrumental and social-emotional care domains were associated with poorer Time 2 adjustment, whereas personal-intimate was related to better adjustment and domestic-household care was unrelated to adjustment. Children and their parents exhibited highest agreement on personal-intimate, instrumental and total caregiving, and least on domestic-household and social-emotional care. Findings delineate the key dimensions of young caregiving in MS and the differential links between caregiving activities and youth adjustment.
Resumo:
Micro-finance, which includes micro-credit as one of its core services, has become an important component of a range of business models – from those that operate on a strictly economic basis to those that come from a philanthropic base, through Non Government Organisations (NGOs). Its success is often measured by the number of loans issued, their size, and the repayment rates. This paper has a dual purpose: to identify whether the models currently used to deliver micro-credit services to the poor are socially responsible and to suggest a new model of delivery that addresses some of the social responsibility issues, while supporting community development. The proposed model is currently being implemented in Beira, the second largest city in Mozambique. Mozambique exhibits many of the characteristics found in other African countries so the model, if successful, may have implications for other poor African nations as well as other developing economies.
Resumo:
Background: Initiatives to promote utility cycling in countries like Australia and the US, which have low rates of utility cycling, may be more effective if they first target recreational cyclists. This study aimed to describe patterns of utility cycling and examine its correlates, among cyclists in Queensland, Australia. Methods: An online survey was administered to adult members of a state-based cycling community and advocacy group (n=1813). The survey asked about demographic characteristics and cycling behavior, motivators and constraints. Utility cycling patterns were described, and logistic regression modeling was used to examine associations between utility cycling and other variables. Results: Forty-seven percent of respondents reported utility cycling: most did so to commute (86%). Most journeys (83%) were >5 km. Being male, younger, employed full-time, or university-educated increased the likelihood of utility cycling (p<0.05). Perceiving cycling to be a cheap or a convenient form of transport were associated with utility cycling (p<0.05). Conclusions: The moderate rate of utility cycling among recreational cyclists highlights a potential to promote utility cycling among this group. To increase utility cycling, strategies should target female and older recreational cyclists and focus on making cycling a cheap and convenient mode of transport.
Resumo:
Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design
Resumo:
This paper uses an aggregate quantity space to decompose the temporal changes in nitrogen use efficiency and cumulative exergy use efficiency into changes of Moorsteen–Bjurek (MB) Total Factor Productivity (TFP) changes and changes in the aggregate nitrogen and cumulative exergy contents. Changes in productivity can be broken into technical change and changes in various efficiency measures such as technical efficiency, scale efficiency and residual mix efficiency. Changes in the aggregate nitrogen and cumulative exergy contents can be driven by changes in the quality of inputs and outputs and changes in the mixes of inputs and outputs. Also with cumulative exergy content analysis, changes in the efficiency in input production can increase or decrease the cumulative exergy transformity of agricultural production. The empirical study in 30 member countries of the Organisation for Economic Co-operation Development from 1990 to 2003 yielded some important findings. The production technology progressed but there were reductions in technical efficiency, scale efficiency and residual mix efficiency levels. This result suggests that the production frontier had shifted up but there existed lags in the responses of member countries to the technological change. Given TFP growth, improvements in nutrient use efficiency and cumulative exergy use efficiency were counteracted by reductions in the changes of the aggregate nitrogen contents ratio and aggregate cumulative exergy contents ratio. The empirical results also confirmed that different combinations of inputs and outputs as well as the quality of inputs and outputs could have more influence on the growth of nutrient and cumulative exergy use efficiency than factors that had driven productivity change. Keywords: Nutrient use efficiency; Cumulative exergy use efficiency; Thermodynamic efficiency change; Productivity growth; OECD agriculture; Sustainability
Resumo:
Despite many incidents about fake online consumer reviews have been reported, very few studies have been conducted to date to examine the trustworthiness of online consumer reviews. One of the reasons is the lack of an effective computational method to separate the untruthful reviews (i.e., spam) from the legitimate ones (i.e., ham) given the fact that prominent spam features are often missing in online reviews. The main contribution of our research work is the development of a novel review spam detection method which is underpinned by an unsupervised inferential language modeling framework. Another contribution of this work is the development of a high-order concept association mining method which provides the essential term association knowledge to bootstrap the performance for untruthful review detection. Our experimental results confirm that the proposed inferential language model equipped with high-order concept association knowledge is effective in untruthful review detection when compared with other baseline methods.