Micron precision calibration methods for alignment sensors in particle accelerators

Large Hadron Collider (LHC) at CERN, the European Organization for Nuclear Research, has, on each side of its four experiments, a set of three magnets, called low-beta magnets. These magnets provide the final-focus for the beams that collide head on in the experiments. The magnets have to be permanently monitored with micron precision as they are crucial for collisions with high luminosity in the experiments. The systems used are hydrostatic levelling systems, wire position systems and invarradial systems. The sensors have to withstand a highly radioactive environment,strong magnetic fields and cannot be returned for check and calibration to the manufacturer once exposed to radiation. In order to validate the sensors before their installation in the tunnel, to check them within their measurement system and for check and calibration after use, a series of tests have been put in place

Continuous limits of residual neural networks in case of large input data

Residual deep neural networks (ResNets) are mathematically described as interacting particle systems. In the case of infinitely many layers the ResNet leads to a system of coupled system of ordinary differential equations known as neural differential equations. For large scale input data we derive a mean-field limit and show well-posedness of the resulting description. Further, we analyze the existence of solutions to the training process by using both a controllability and an optimal control point of view. Numerical investigations based on the solution of a formal optimality system illustrate the theoretical findings

A characteristic particle method for traffic flow simulations on highway networks

A characteristic particle method for the simulation of first order macroscopic traffic models on road networks is presented. The approach is based on the method "particleclaw", which solves scalar one dimensional hyperbolic conservations laws exactly, except for a small error right around shocks. The method is generalized to nonlinear network flows, where particle approximations on the edges are suitably coupled together at the network nodes. It is demonstrated in numerical examples that the resulting particle method can approximate traffic jams accurately, while only devoting a few degrees of freedom to each edge of the network.Comment: 15 pages, 5 figures. Accepted to the proceedings of the Sixth International Workshop Meshfree Methods for PDE 201

A rarefaction-tracking method for hyperbolic conservation laws

We present a numerical method for scalar conservation laws in one space dimension. The solution is approximated by local similarity solutions. While many commonly used approaches are based on shocks, the presented method uses rarefaction and compression waves. The solution is represented by particles that carry function values and move according to the method of characteristics. Between two neighboring particles, an interpolation is defined by an analytical similarity solution of the conservation law. An interaction of particles represents a collision of characteristics. The resulting shock is resolved by merging particles so that the total area under the function is conserved. The method is variation diminishing, nevertheless, it has no numerical dissipation away from shocks. Although shocks are not explicitly tracked, they can be located accurately. We present numerical examples, and outline specific applications and extensions of the approach.Comment: 21 pages, 7 figures. Similarity 2008 conference proceeding

Kinetic models for optimal control of wealth inequalities

We introduce and discuss optimal control strategies for kinetic models for wealth distribution in a simple market economy, acting to minimize the variance of the wealth density among the population. Our analysis is based on a finite time horizon approximation, or model predictive control, of the corresponding control problem for the microscopic agents' dynamic and results in an alternative theoretical approach to the taxation and redistribution policy at a global level. It is shown that in general the control is able to modify the Pareto index of the stationary solution of the corresponding Boltzmann kinetic equation, and that this modification can be exactly quantified. Connections between previous Fokker-Planck based models and taxation-redistribution policies and the present approach are also discussed

Integrative analysis identifies key molecular signatures underlying neurodevelopmental deficits in fragile X syndrome

BACKGROUND: Fragile X syndrome (FXS) is a neurodevelopmental disorder caused by epigenetic silencing of FMR1 and loss of FMRP expression. Efforts to understand the molecular underpinnings of the disease have been largely performed in rodent or nonisogenic settings. A detailed examination of the impact of FMRP loss on cellular processes and neuronal properties in the context of isogenic human neurons remains lacking. METHODS: Using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 to introduce indels in exon 3 of FMR1, we generated an isogenic human pluripotent stem cell model of FXS that shows complete loss of FMRP expression. We generated neuronal cultures and performed genome-wide transcriptome and proteome profiling followed by functional validation of key dysregulated processes. We further analyzed neurodevelopmental and neuronal properties, including neurite length and neuronal activity, using multielectrode arrays and patch clamp electrophysiology. RESULTS: We showed that the transcriptome and proteome profiles of isogenic FMRP-deficient neurons demonstrate perturbations in synaptic transmission, neuron differentiation, cell proliferation and ion transmembrane transporter activity pathways, and autism spectrum disorder-associated gene sets. We uncovered key deficits in FMRP-deficient cells demonstrating abnormal neural rosette formation and neural progenitor cell proliferation. We further showed that FMRP-deficient neurons exhibit a number of additional phenotypic abnormalities, including neurite outgrowth and branching deficits and impaired electrophysiological network activity. These FMRP-deficient related impairments have also been validated in additional FXS patient-derived human-induced pluripotent stem cell neural cells. CONCLUSIONS: Using isogenic human pluripotent stem cells as a model to investigate the pathophysiology of FXS in human neurons, we reveal key neural abnormalities arising from the loss of FMRP.Peer reviewe

Exome Sequencing and Rare Variant Analysis Reveals Multiple Filaggrin Mutations in Bangladeshi Families with Atopic Eczema and Additional Risk Genes

M.P was supported by a Fellowship from the German Research Foundation (DFG). This work received infrastructure support through the DFG Cluster of Excellence “Inflammation at Interfaces” (grants EXC306 and EXC306/2), and was supported by grants (WE2678/6-1, WE2678/6-2, WE2678/9) from the DFG and the e:Med sysINFLAME grant no. 01ZX1306A from the German Federal Ministry of Education and Research (BMBF). J.E.A.C. and X.F.C.C.W. are funded by A*STAR SPF funding for translational skin research and genetic orphan disease