Is there an interaction between socioeconomic status and FRAX 10-year fracture probability determined with and without bone density measures? Data from the Geelong Osteoporosis Study of female cohort.

FRAX(©) evaluates 10-year fracture probabilities and can be calculated with and without bone mineral density (BMD). Low socioeconomic status (SES) may affect BMD, and is associated with increased fracture risk. Clinical risk factors differ by SES; however, it is unknown whether aninteraction exists between SES and FRAX determined with and without the BMD. From the Geelong Osteoporosis Study, we drew 819 females aged ≥50 years. Clinical data were collected during 1993-1997. SES was determined by cross-referencing residential addresses with Australian Bureau of Statistics census data and categorized in quintiles. BMD was measured by dual energy X-ray absorptiometry at the same time as other clinical data were collected. Ten-year fracture probabilities were calculated using FRAX (Australia). Using multivariable regression analyses, we examined whether interactions existed between SES and 10-year probability for hip and any major osteoporotic fracture (MOF) defined by use of FRAX with and without BMD. We observed a trend for a SES * FRAX(no-BMD) interaction term for 10-year hip fracture probability (p = 0.09); however, not for MOF (p = 0.42). In women without prior fracture (n = 518), we observed a significant SES * FRAX(no-BMD) interaction term for hip fracture (p = 0.03) and MOF (p = 0.04). SES does not appear to have an interaction with 10-year fracture probabilities determined by FRAX with and without BMD in women with previous fracture; however, it does appear to exist for those without previous fracture.

Default probability for the Jordanian companies: A test of cash flow theory

Abstract
This paper aims to investigate the effect of cash flow and free cash flow on corporate failure in the emerging market in particular Jordan using two samples; matched sample and a cross sectional time-series (panel data) sample representative of 167 Jordanian companies in 1989-2003. LOGIT models are used to outline the relationship between firms’ financial health and the probability of default. Our results show that there is firm’s free cash flow increases corporate failure. The result also shows that the firm’s cash flow decreases corporate failure. Firms’ capital structures are fund a mental in predicting default. Capital structure is seen as the main factor affecting the probability of default as it affects a firm’s ability to access external sources of funds. Jordanian firms depend on short-term debt for both short and long term financing.

Climatic, vegetation and edaphic influences on the probability of fire across mediterranean woodlands of south-eastern Australia

 Aim: We investigated how the probability of burning is influenced by the time since fire (TSF) and gradients of climate, soil and vegetation in the fire-prone mediterranean-climate mallee woodlands of south-eastern Australia. This provided insight into the processes controlling contemporary fuel dynamics and fire regimes across biogeographical boundaries, and the consequent effects of climate change on potential shifts in boundaries between fuel systems and fire regimes, at a subcontinental scale. Location: South-eastern Australia. Methods: A desktop-based GIS was used to generate random sampling points across the study region to collect data on intersecting fire interval, rainfall, vegetation and soil type. We used a Bayesian framework to examine the effects of combinations of rainfall, vegetation and soil type on the hazard-of-burning and survival parameters of the Weibull distribution. These analyses identify the nature of environmental controls on the length of fire intervals and the age-dependence of the hazard of burning. Results: Higher rainfall was consistently associated with shorter fire intervals. Within a single level of rainfall, however, the interaction between soil and vegetation type influenced the length of fire intervals. Higher-fertility sands were associated with shorter fire intervals in grass-dominated communities, whereas lower-fertility sands were associated with shorter fire intervals in shrub-dominated communities. The hazard of burning remained largely independent of TSF across the region, only markedly increasing with TSF in shrub-dominated communities at high rainfall. Main conclusions: Rainfall had a dominant influence on fire frequency in the mediterranean-climate mallee woodlands of south-eastern Australia. Predicted changes in the spatial distribution and amount of rainfall therefore have the potential to drive changes in fire regimes, although the effects of soil fertility and rainfall on fire regimes do not align on a simple productivity gradient. Reduced soil fertility may favour plant traits that increase the rate of woody litter fuel accumulation and flammability, which may alter the overriding influence of rainfall gradients on fire regimes.

Detecting stepping stones by abnormal causality probability

Locating the real source of the Internet attacks has long been an important but difficult problem to be addressed. In the real world, attackers can easily hide their identities and evade punishment by relaying their attacks through a series of compromised systems or devices called stepping stones. Currently, researchers mainly use similar features from the network traffic, such as packet timestamps and frequencies, to detect stepping stones. However, these features can be easily destroyed by attackers using evasive techniques. In addition, it is also difficult to implement an appropriate threshold of similarity that can help justify the stepping stones. In order to counter these problems, in this paper, we introduce the consistent causality probability to detect the stepping stones. We formulate the ranges of abnormal causality probabilities according to the different network conditions, and on the basis of it, we further implement to self-adaptive methods to capture stepping stones. To evaluate our proposed detection methods, we adopt theoretic analysis and empirical studies, which demonstrate accuracy of the abnormal causality probability. Moreover, we compare our proposed methods with previous works. The result shows that our methods in this paper significantly outperform previous works in the accuracy of detection malicious stepping stones, even when evasive techniques are adopted by attackers.