Two level fatigue loading (H-L) of MG alloys: micromechanic modeling VS. experiments

A statistical micromechanic fatigue model shows some of the main features of macro fatigue behavior like S-N power law, endurance limit, Goodman diagram, etc. The model correlates micro statistical damage parameters to the macro behavior. The recursive evolution equation has been recently transformed to a nonlinear differential form, which enables a simple analytic solution. Using these results, a two level (H-L) fatigue loading case is modeled analytically, leading to a failure design formula which is based solely on the one level S-N data. Specifically, the model predicts a generalized “Miner type” behavior, which is controlled on the micro-level by the very basic strength dispersion factor of the microelements, and on the macro-level by the S-N power (slope). The proposed H-L predictions were tested by fatigue experiments on two Magnesium alloys (AZ31 and AM50). Results showed good correlation, in spite of the natural large scatter

Quantifying HIV transmission flow between high-prevalence hotspots and surrounding communities: a population-based study in Rakai, Uganda

Background International and global organisations advocate targeting interventions to areas of high HIV prevalence (ie, hotspots). To better understand the potential benefits of geo-targeted control, we assessed the extent to which HIV hotspots along Lake Victoria sustain transmission in neighbouring populations in south-central Uganda. Methods We did a population-based survey in Rakai, Uganda, using data from the Rakai Community Cohort Study. The study surveyed all individuals aged 15–49 years in four high-prevalence Lake Victoria fishing communities and 36 neighbouring inland communities. Viral RNA was deep sequenced from participants infected with HIV who were antiretroviral therapy-naive during the observation period. Phylogenetic analysis was used to infer partial HIV transmission networks, including direction of transmission. Reconstructed networks were interpreted through data for current residence and migration history. HIV transmission flows within and between high-prevalence and low-prevalence areas were quantified adjusting for incomplete sampling of the population. Findings Between Aug 10, 2011, and Jan 30, 2015, data were collected for the Rakai Community Cohort Study. 25 882 individuals participated, including an estimated 75·7% of the lakeside population and 16·2% of the inland population in the Rakai region of Uganda. 5142 participants were HIV-positive (2703 [13·7%] in inland and 2439 [40·1%] in fishing communities). 3878 (75·4%) people who were HIV-positive did not report antiretroviral therapy use, of whom 2652 (68·4%) had virus deep-sequenced at sufficient quality for phylogenetic analysis. 446 transmission networks were reconstructed, including 293 linked pairs with inferred direction of transmission. Adjusting for incomplete sampling, an estimated 5·7% (95% credibility interval 4·4–7·3) of transmissions occurred within lakeside areas, 89·2% (86·0–91·8) within inland areas, 1·3% (0·6–2·6) from lakeside to inland areas, and 3·7% (2·3–5·8) from inland to lakeside areas