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Likelihood-free inference methods typically make use of a distance between simulated and real data. A common example is the maximum mean discrepancy (MMD), which has previously been used for approximate Bayesian computation, minimum distance estimation, generalised Bayesian inference, and within the nonparametric learning framework. The MMD is commonly estimated at a root-m rate, where m is the number of simulated samples. This can lead to significant computational challenges since a large m is required to obtain an accurate estimate, which is crucial for parameter estimation. In this paper, we propose a novel estimator for the MMD with significantly improved sample complexity. The estimator is particularly well suited for computationally expensive smooth simulators with low- to mid-dimensional inputs. This claim is supported through both theoretical results and an extensive simulation study on benchmark simulators.
A commercially pure Cu and a Cu-8 wt.%Sn alloy were subjected to high pressure torsion (HPT) to study the effect of Sn as solute element and deformation rate on the grain refinement mechanism and the defect accumulation in Cu. The microstructure and hardness of produced ultrafine grained (UFG) states of both materials were carefully characterized. We show that addition of Sn in Cu leads to significant decrease in grain size, accumulation of higher stored energy and increase in hardness accompanied with the delay of hardness saturation with shear strain. Increasing HPT deformation rate induces significant heat dissipation in the processed materials markedly pronounced in CuSn8 as compared to Cu. Surprisingly, deformation rate has the opposite effect on the microhardness of UFG Cu and CuSn8, which decreases with the deformation rate for the case of Cu, while exhibits faster saturation to higher values for CuSn8. We also show that despite higher self-heating at higher deformation rates, higher HPT rotation speedprovides reduction in grain size and increase in the defect density for CuSn8 alloy. This effect is assumed to be related to strong interactions between Sn solute atoms and strain-induced defects so that mechanically driven effects prevail over dynamic annihilation of dislocations. Finally, we present a qualitative model based on the phenomena of production and annihilation of dislocations. This model was able to reproduce the evolution of grain size, concentrations defects and hardness with different deformation parameters and after the addition of solute element in material.
The Super Separator Spectrometer-Low Energy Branch (S3--LEB) is a low-energy radioactive ion beam experiment under commissioning as part of the GANIL-SPIRAL2 facility. It will be used for the production and study of exotic nuclei by in-gas laser ionization and spectroscopy (IGLIS), decay spectroscopy, and mass spectrometry. We report recent results from the off-line commissioning of S3-LEB, including first laser spectroscopy measurements in both the gas cell and the supersonic gas jet, the determination of the transport efficiency of laser ions from the gas cell through the RFQ chain, and time-of-flight measurements with the multi-reflection time-of-flight mass spectrometer PILGRIM. The measurements were performed using erbium, introduced by evaporation from a heated filament in the gas environment. The reported laser spectroscopy results include a characterization of the pressure broadening in the gas cell, proof-of-principle isotope shift measurements, and hyperfine-structure measurements.
We present the first results obtained from the S3 Low-Energy Branch, the gas cell setup at SPIRAL2-GANIL, which will be installed behind the S3 spectrometer for atomic and nuclear spectroscopy studies of exotic nuclei. The installation is currently being commissioned offline, with the aim to establish optimum conditions for the operation of the radio frequency quadrupole ion guides, mass separation and ion bunching, providing high-efficiency and low-energy spatial spread for the isotopes of interest. Transmission and mass-resolving power measurements are presented for the different components of the S3-LEB setup. In addition, a single-longitudinal-mode, injection-locked, pumped pulsed-titanium–sapphire laser system has been recently implemented and is used for the first proof-of-principle measurements in an offline laser laboratory. Laser spectroscopy measurements of erbium, which is the commissioning case of the S3 spectrometer, are presented using the 4f126s23H6→4f12(3H)6s6p optical transition.
Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in 1/4one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA-Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h 2 =0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.
Abstract Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10−8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.