Bayesian Approach to Linear Bayesian Networks

This study proposes the first Bayesian approach for learning high-dimensional linear Bayesian networks. The proposed approach iteratively estimates each element of the topological ordering from backward and its parent using the inverse of a partial covariance matrix. The proposed method successfully recovers the underlying structure when Bayesian regularization for the inverse covariance matrix with unequal shrinkage is applied. Specifically, it shows that the number of samples $n = \Omega( d_M^2 \log p)$ and $n = \Omega(d_M^2 p^{2/m})$ are sufficient for the proposed algorithm to learn linear Bayesian networks with sub-Gaussian and 4m-th bounded-moment error distributions, respectively, where $p$ is the number of nodes and $d_M$ is the maximum degree of the moralized graph. The theoretical findings are supported by extensive simulation studies including real data analysis. Furthermore the proposed method is demonstrated to outperform state-of-the-art frequentist approaches, such as the BHLSM, LISTEN, and TD algorithms in synthetic data

Representative levels of blood lead, mercury, and urinary cadmium in youth: Korean Environmental Health Survey in Children and Adolescents (KorEHS-C), 2012–2014

AbstractBackgroundThis study examined levels of blood lead and mercury, and urinary cadmium, and associated sociodemographic factors in 3–18 year-old Korean children and adolescents.Materials and methodsWe used the nationally representative Korean Environmental Health Survey in Children and Adolescents data for 2012–2014 and identified 2388 children and adolescents aged 3–18 years. The median and 95th percentile exposure biomarker levels with 95% confidence intervals (CIs) were calculated. Multivariate regression analyses were performed on log transformed exposure biomarker levels adjusted for age, sex, area, household income, and father’s education level. The median exposure biomarker levels were compared with data from Germany, the US, and Canada, as well as the levels of Korean children measured at different times.ResultsThe median levels of blood lead and mercury, as well as urinary cadmium were 1.23μg/dL, 1.80μg/L, and 0.40μg/L (95% CIs, 1.21–1.25, 1.77–1.83, and 0.39–0.41, respectively). The blood lead levels were significantly higher in boys and younger children (p<0.0001) and children with less educated fathers (p=0.004) after adjusting for covariates. Urinary cadmium level increased with age (p<0.0001). The median levels of blood mercury and urinary cadmium were much higher in Korean children and adolescents than those in their peers in Germany, the US, and Canada. Blood lead levels tended to decrease with increasing age and divergence between the sexes, particularly in the early teen years. Median levels of blood lead and urinary cadmium decreased since 2010.ConclusionSociodemographic factors, including age, sex, and father’s education level were associated with environmental exposure to heavy metals in Korean children and adolescents. These biomonitoring data are valuable for ongoing surveillance of environmental exposure in this vulnerable population

Enhanced Diamagnetic Repulsion of Blood Cells Enables Versatile Plasma Separation for Biomarker Analysis in Blood

A hemolysis-free and highly efficient plasma separation platform enabled by enhanced diamagnetic repulsion of blood cells in undiluted whole blood is reported. Complete removal of blood cells from blood plasma is achieved by supplementing blood with superparamagnetic iron oxide nanoparticles (SPIONs), which turns the blood plasma into a paramagnetic condition, and thus, all blood cells are repelled by magnets. The blood plasma is successfully collected from 4 mL of blood at flow rates up to 100 mu L min(-1) without losing plasma proteins, platelets, or exosomes with 83.3 +/- 1.64% of plasma volume recovery, which is superior over the conventional microfluidic methods. The theoretical model elucidates the diamagnetic repulsion of blood cells considering hematocrit-dependent viscosity, which allows to determine a range of optimal flow rates to harvest platelet-rich plasma and platelet-free plasma. For clinical validations, it is demonstrated that the method enables the greater recovery of bacterial DNA from the infected blood than centrifugation and the immunoassay in whole blood without prior plasma separation

Advection Flows-Enhanced Magnetic Separation for High-Throughput Bacteria Separation from Undiluted Whole Blood

A major challenge to scale up a microfluidic magnetic separator for extracorporeal blood cleansing applications is to overcome low magnetic drag velocity caused by viscous blood components interfering with magnetophoresis. Therefore, there is an unmet need to develop an effective method to position magnetic particles to the area of augmented magnetic flux density gradients while retaining clinically applicable throughput. Here, a magnetophoretic cell separation device, integrated with slanted ridge-arrays in a microfluidic channel, is reported. The slanted ridges patterned in the microfluidic channels generate spiral flows along the microfluidic channel. The cells bound with magnetic particles follow trajectories of the spiral streamlines and are repeatedly transferred in a transverse direction toward the area adjacent to a ferromagnetic nickel structure, where they are exposed to a highly augmented magnetic force of 7.68 mu N that is much greater than the force (0.35 pN) at the side of the channel furthest from the nickel structure. With this approach, 91.68% +/- 2.18% of Escherichia coli (E. coli) bound with magnetic nanoparticles are successfully separated from undiluted whole blood at a flow rate of 0.6 mL h(-1) in a single microfluidic channel, whereas only 23.98% +/- 6.59% of E. coli are depleted in the conventional microfluidic device

Artificial van der Waals hybrid synapse and its application to acoustic pattern recognition

Designing high-performance and energy efficient neural network hardware remains a challenge. Here, the authors develop a van der Waals hybrid synaptic device that features linear and symmetric conductance-update characteristics and demonstrate the feasibility for hardware neural network performing acoustic pattern recognition

IMIS-Beiträge

The percolation model, taking into account the percolative nature of current transport due to anisotropy, is a powerful tool for predicting the field and temperature dependences of critical current in MgB superconducting wires. The critical current behaviour measured from MgB wires can be obviously explained by only four fitting parameters, the anisotropy parameter, the pinning force maximum, the upper critical field along the ab-plane, and the percolation threshold. Moreover, the temperature dependence of the upper critical field is further explained by the dirty-limit two-gap theory