Magnetic nanodoping: Atomic control of spin states in cobalt doped silver clusters

The interaction of magnetic dopants with delocalized electron states can result in interesting many-body physics. Here, the magnetic properties of neutral and charged finite silver metal host clusters with a magnetic cobalt atom impurity were investigated experimentally by exploiting the complementary methods of Stern- Gerlach molecular beam deflection and x-ray magnetic circular dichroism spectroscopy and are accompanied by density functional theory calculations and charge transfer multiplet simulations. The influence of the number of valence electrons and the consequences of impurity encapsulation were addressed in free size-selected, singly cobalt-doped silver clusters CoAg0,n+ (n = 2–15). Encapsulation of the dopant facilitates the formation of delocalized electronic shells with complete hybridization of the impurity 3d- and the host 5s-derived orbitals, which results in impurity valence electron delocalization, effective spin relaxation, and a low-spin ground state. In the exohedral size regime, spin pairing in the free electron gas formed by the silver 5s electrons is the dominating driving force determining the local 3d occupation of the impurity and therefore, adjusting the spin magnetic moment accordingly

BioScore: A tool to assess the impacts of European Community policies on Europe's biodiversity

BioScore offers a European biodiversity impact assessment tool. The tool contains indicator values on the ecological preferences of more than 1000 species of birds, mammals, amphibians, reptiles, fish, butterflies, dragonflies, aquatic macro-invertebrates and vascular plants. These values are linked to policy-related pressures and environmental variables

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Choosing the Right Patterns : An Experimental Comparison between Different Tree Inclusion Relations

In recent years a variety of mining algorithms has been developed, to derive all frequent subtrees from a database of labeled ordered rooted trees. These algorithms share properties such as enumeration strategies and pruning techniques. They differ however in the tree inclusion relation used and how attribute values are dealt with. In this work we investigate the different approaches with respect to ‘usefulness’ of the derived patterns, in particular, the performance of classifiers that use the derived patterns as features. In order to find a good tradeoff between expressiveness and runtime performance of the different approaches, we also take the complexity of the different classifiers into account, as well as the run time and memory usage of the different approaches. The experiments are performed on two real datasets. The results show that significant improvement in both predictive performance and computational efficiency can be gained by choosing the right tree mining approach

FAT-CAT : frequent attributes tree based classification

The natural representation of XML data is to use the underlying tree structure of the data. When analyzing these trees we are ensured that no structural information is lost. These tree structures can be efficiently analyzed due to the existence of frequent pattern mining algorithms that works directly on tree structured data. In this work we describe a classification method for XML data based on frequent attribute trees. From these frequent patterns we select so called emerging patterns, and use these as binary features in a decision tree algorithm. The experimental results show that combining emerging attribute tree patterns with standard classification methods, is a promising combination to tackle the classification of XML documents