Pulsed mononode dye laser developed for a geophysical application

Following the extension of the lidar technique in the study of the atmosphere, the necessity of having a high power pulsed laser beam with a narrowed bandwidth and the possibility of selecting a particular wavelength within a certain spectral region arises. With the collaboration of others, a laser cavity using the multiwave Fizeau wedge (MWFW) was developed. Using the classical method of beam amplification with the aid of different stages, a new pulsed dye laser device was designed. The originality resides in the use of reflecting properties of the MFWF. Locally a plan wave coming with a particular angular incidence is reflected with a greater than unity coefficient; this is the consequence of the wedge angle which doubles the participation of every ray in the interferometric process. This dye laser operation and advantages are discussed. The feasibility of different geophysical applications envisageable with this laser is discussed

Self-consistent modelling of hot plasmas within non-extensive Tsallis' thermostatistics

A study of the effects of non-extensivity on the modelling of atomic physics in hot dense plasmas is proposed within Tsallis' statistics. The electronic structure of the plasma is calculated through an average-atom model based on the minimization of the non-extensive free energy.Comment: submitted to "Eur. Phys. J. D

Stratified genome-wide association analysis of type 2 diabetes reveals subgroups with genetic and environmental heterogeneity

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analysing subgroups based on age-at-onset of diabetes and body mass index (BMI). In UK Biobank, 36 494 T2D cases were stratified into 3 subgroups and GWAS performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 SNPs significantly associated genome-wide with T2D in one or more subgroups also showed evidence of heterogeneity between the subgroups, (Cochrane's Q p < 0.01) with 2 remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, based on genetic profile, BMI and age, resulted in excellent diabetes prediction (AUC = 0.92). A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimising combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach

The present rate of Supernovae

We present and discuss the most recent determination of the rate of Supernovae in the local Universe. A comparison with other results shows a general agreement on the gross values but still significant differences on the values of the rates of various SN rates in different kinds of galaxies. The rate of SNe, used as a probe of Star Formation, confirms the young progenitor scenario for SNII+Ib/c. The increasing diversity of SNe reflects also in the SN yields which may affect the chemical evolution of the Galaxy but, because of the limited statistics, we cannot estimate the contributions of the new subtypes yet. It is also expected that in a few years observational determinations of the SN rates at various look-back times will be available.Comment: 9 pages, Latex, 1 figure, To appear in the proceedings of the conference "The Chemical Evolution of The Milky Way: Stars versus Clusters", eds. F. Matteucci and F. Giovannelli, Vulcano, Italy, September 20-24 199

Stratified genome-wide association analysis of Type 2 Diabetes reveals subgroups with genetic and environmental heterogeneity

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analysing subgroups based on age-at-onset of diabetes and body mass index (BMI). In UK Biobank, 36 494 T2D cases were stratified into 3 subgroups and GWAS performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 SNPs significantly associated genome-wide with T2D in one or more subgroups also showed evidence of heterogeneity between the subgroups, (Cochrane’s Q p < 0.01) with 2 remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, based on genetic profile, BMI and age, resulted in excellent diabetes prediction (AUC = 0.92). A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimising combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach