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Many studies have shown effects of plants species on fungal communities, but these are often confounded with soil effects. Thus, the specific role of plant species in structuring rhizospheric and soil fungal communities is poorly described. Our study used microcosms in which plants were grown under artificial conditions to bridge this gap. Two perennial grasses dominating subalpine grasslands, Festuca paniculata and Dactylis glomerata, were grown at two levels of fertilization on standard soil. Fungal communities were determined by 454 pyrosequencing of the internal transcribed spacer 1 region. Among the fungal communities characterized by the primers used, original communities were associated to each plant species and also diverged between rhizosphere and bulk soils within each plant species, though there were no significant fertilization effects. Differences regarded global composition of the fungal communities and abundant molecular operational taxonomic units (MOTUs). Both plant species and location effects were reflected more in the abundance than in the composition of MOTUs. The observed differences in fungal communities coincide with differing strategies of plant root growth, with D. glomerata having greater root mass, length, and area than F. paniculata. Our study, by dissociating soil effects from plant effects, demonstrated that plant species exert a key control on soil fungi. We suggest that such effects may be linked to inter-specific differences in root traits and their consequences on nitrogen uptake.

One of the main challenges in model-driven software engineering is to automate the resolution of design model inconsistencies. We propose to use the artificial intelligence technique of automated planning for the purpose of resolving such inconsistencies through the generation of one or more resolution plans. We implemented Badger, a regression planner in Prolog that generates such plans. We assess its scalability on the resolution of different types of structural inconsistencies in UML models using both generated models and reverse-engineered models of varying sizes, the largest ones containing more than 10,000 model elements. We illustrate the metamodel-independence of our approach by applying it to the resolution of code smells in a Java program. We discuss how the user can adapt the order in which resolution plans are presented by modifying the cost function of the planner algorithm.

A historical prospective cohort study of 6630 drivers from the Canton of Geneva was carried out to evaluate mortality and incidence of cancer in this occupation. The study population was all men (of all vocations) who held in 1949 a special licence for driving lorries, taxis, buses, or coaches and all new licence holders in the period 1949-61. Men born before 1900 and those with only an ordinary driving licence were excluded. According to the occupation registered on their licence, the 6630 drivers were distributed into three groups: (1) professional drivers (n = 1726), (2) non-professional drivers \"more exposed\" to exhaust gas and fumes (this group included occupations such as vehicle mechanic, policeman, road sweeper; n = 712), and (3) non-professional drivers \"less exposed,\" composed of all other occupations (n = 4192). The cohort was followed up from 1949 to December 1986 and the trace of 197 men (3%) was lost. Compared with the general population of the Canton of Geneva, professional drivers experienced significant excess risks, taking into account 15 years of latency, for all causes of death (standardised mortality ratio (SMR) 115, 90% confidence interval (90% CI) 107-123) and for all malignant neoplasms (SMR 125, 90% CI 112-140; standardised incidence ratio (SIR) 128, 90% CI 115-142). Cause specific analysis showed significant excesses for lung cancer (SMR 150, 90% CI 123-181; SIR 161, 90% CI 129-198), oesophageal cancer (SMR 183, 90% CI 108-291), stomach cancer (SMR 179, 90% CI 117-263; SIR233, 90% CI 156-336), rectal cancer (SMR 258, 90% CIU 162-392; SIR 200, 90% CI 127-300), and cirrhosis of the liver (SMR 145, 90% CI 104-198). Risk of lung cancer increased significantly with time from first exposure. Among non-professional drivers no significant excess risk was found except for lung cancer mortality among the \"less exposed\" group (SMR 121, 90% CI 103-140), and for incidence of lung cancer among the \"more exposed\" group (SIR 161, 90% CI 111-227). The possible casual relation between exposure to engine exhaust emissions and the increased risk for lung cancer and for cancer of the gastrointestinal tract found among professional drivers is discussed.