An optimal sensor placement method for SHM based on Bayesian experimental design and polynomial chaos expansion

We present an optimal sensor placement methodology for structural health monitoring (SHM) purposes, relying on a Bayesian experimental design approach. The unknown structural properties, e.g. the residual strength and stiffness, are inferred from data collected through a network of sensors, whose architecture, i.e., type and position may largely affect the accuracy of the monitoring system. In tackling this issue, an optimal network configuration is herein sought by maximizing the expected information gain between prior and posterior probability distributions of the parameters to be estimated. Since the objective function linked to the network topology cannot be analytically computed, a numerical approximation is provided by means of a Monte Carlo analysis, wherein each realization is obtained via finite element modeling. Since the computational burden linked to this procedure often grows infeasible, a Polynomial Chaos Expansion (PCE) approach is adopted for accelerating the computation of the forward problem. The analysis expands over joint samples covering both structural state and design variables, i.e., sensor locations. Via increase of the number of deployed sensors in the network, the optimization procedure soon turns computationally costly due to the curse of dimensionality. To this end, a stochastic optimization method is adopted for accelerating the convergence of the optimization process and thereby the damage detection capability of the SHM system. The proposed method is applied to thin flexible structures, and the resulting optimal sensor configuration is shown. The effects of the number of training samples, the polynomial degree of the approximation expansion and the optimization settings are also discussed

Reactivity to AQP4 epitopes in relapsing–remitting multiple sclerosis

Autoantibodies against the water channel AQP4, expressed predominately in central nervous system astrocytes, are markers and pathogenic factors in Devic's disease. In this study we examined whether Multiple Sclerosis (MS) patients recognize antigenic epitopes on AQP4 that may define distinct disease subsets. We screened sera from 45 patients with relapsing–remitting MS (RRMS) and 13 patients with primary progressive MS (PMS). 23 Neuromyelitis Optica (NMO) patients previously characterized were used as assay positive/negative controls. Sera from 23 patients with Systemic Lupus Erythematosus, 23 with primary Sjogren syndrome without neurological involvement and from 28 healthy individuals were also used as controls. NMO-positive sera exhibited reactivity against the intracellular epitope AQPaa252-275, confirming previous observations. All RRMS sera tested negative for anti-AQP4 antibodies using a cell-based assay, but surprisingly, 13% of them reacted with the epitope AQPaa252-275. PMS, healthy and disease controls showed no specific reactivity. Whether these antibodies define distinct MS subsets and have a pathogenic potential pointing to convergent pathogenetic mechanism with NMO, or are simply markers of astrocytic damage, remains to be determined

An application of generative adversarial networks in structural health monitoring

In the current work, the use of generative adversarial networks (GANs) in a simulated structural health monitoring (SHM) application is studied. A specific type of GAN is considered, aiming at a disentangled representation of underlying features and clusters of data through some latent variables. This idea could prove useful in SHM, since explanation of how damage mechanisms or environmental conditions affect a structure may be exploited in order to monitor structures more effectively. In a simulated mass-spring example, different damage cases are introduced by reducing the stiffness of specific springs and different damage levels by applying different extents of stiffness reduction. The GAN implementation proves able to capture different damage cases through its categorical latent variables, as well as the damage extent within its continuous latent variables. The results demonstrate that the latent variables are indeed capturing the effect of damage in the structure and can be exploited for the purpose of condition assessment

Leptin, acylcarnitine metabolites and development of adiposity in the Rhea mother-child cohort in Crete, Greece.

OBJECTIVE: This study aims to investigate relations of serum leptin at age 4 with development of adiposity and linear growth during 3 years of follow-up among 75 Greek children and to identify serum metabolites associated with leptin at age 4 and to characterize their associations with adiposity gain and linear growth. METHODS: Linear regression models that accounted for maternal age, education and gestational weight gain and child's age and sex were used to examine associations of leptin and leptin-associated metabolites measured at age 4 with indicators of adiposity and linear growth at age 7. RESULTS: Each 1-unit increment in natural log-(ln)-transformed leptin corresponded with 0.33 (95% CI: 0.10, 0.55) units greater body mass index-for-age z-score gain during follow-up. Likewise, higher levels of the leptin-associated metabolites methylmalonyl-carnitine and glutaconyl-carnitine corresponded with 0.14 (95% CI: 0.01, 0.27) and 0.07 (95% CI: -0.01, 0.16) units higher body mass index-for-age z-score gain, respectively. These relationships did not differ by sex or baseline weight status and were independent of linear growth. CONCLUSIONS: These findings suggest that leptin, methylmalonyl-carnitine and possibly glutaconyl-carnitine are associated with weight gain during early childhood. Future studies are warranted to confirm these findings in other populations

A nexus of intrinsic dynamics underlies translocase priming

The cytoplasmic ATPase SecA and the membrane-embedded SecYEG channel assemble to form the Sec translocase. How this interaction primes and catalytically activates the translocase remains unclear. We show that priming exploits a nexus of intrinsic dynamics in SecA. Using atomistic simulations, smFRET, and HDX-MS, we reveal multiple dynamic islands that cross-talk with domain and quaternary motions. These dynamic elements are functionally important and conserved. Central to the nexus is a slender stem through which rotation of the preprotein clamp of SecA is biased by ATPase domain motions between open and closed clamping states. An H-bonded framework covering most of SecA enables multi-tier dynamics and conformational alterations with minimal energy input. As a result, cognate ligands select preexisting conformations and alter local dynamics to regulate catalytic activity and clamp motions. These events prime the translocase for high-affinity reception of non-folded preprotein clients. Dynamics nexuses are likely universal and essential in multi-liganded proteins.</p

Preproteins couple the intrinsic dynamics of SecA to its ATPase cycle to translocate via a catch and release mechanism

Protein machines undergo conformational motions to interact with and manipulate polymeric substrates. The Sec translocase promiscuously recognizes, becomes activated, and secretes >500 non-folded preprotein clients across bacterial cytoplasmic membranes. Here, we reveal that the intrinsic dynamics of the translocase ATPase, SecA, and of preproteins combine to achieve translocation. SecA possesses an intrinsically dynamic preprotein clamp attached to an equally dynamic ATPase motor. Alternating motor conformations are finely controlled by the γ-phosphate of ATP, while ADP causes motor stalling, independently of clamp motions. Functional preproteins physically bridge these independent dynamics. Their signal peptides promote clamp closing; their mature domain overcomes the rate-limiting ADP release. While repeated ATP cycles shift the motor between unique states, multiple conformationally frustrated prongs in the clamp repeatedly “catch and release” trapped preprotein segments until translocation completion. This universal mechanism allows any preprotein to promiscuously recognize the translocase, usurp its intrinsic dynamics, and become secreted

Preprotein mature domains contain translocase targeting signals that are essential for secretion

Secretory proteins are only temporary cytoplasmic residents. They are typically synthesized as preproteins, carrying signal peptides N-terminally fused to their mature domains. In bacteria secretion largely occurs posttranslationally through the membrane-embedded SecA-SecYEG translocase. Upon crossing the plasma membrane, signal peptides are cleaved off and mature domains reach their destinations and fold. Targeting to the translocase is mediated by signal peptides. The role of mature domains in targeting and secretion is unclear. We now reveal that mature domains harbor their own independent targeting signals (mature domain targeting signals [MTSs]). These are multiple, degenerate, interchangeable, linear or 3D hydrophobic stretches that become available because of the unstructured states of targeting-competent preproteins. Their receptor site on the cytoplasmic face of the SecYEG-bound SecA is also of hydrophobic nature and is located adjacent to the signal peptide cleft. Both the preprotein MTSs and their receptor site on SecA are essential for protein secretion. Evidently, mature domains have their own previously unsuspected distinct roles in preprotein targeting and secretion

Measuring sub-mm structural displacements using QDaedalus: a digital clip-on measuring system developed for total stations

The monitoring of rigid structures of modal frequencies greater than 5 Hz and sub-mm displacement is mainly based so far on relative quantities from accelerometers, strain gauges etc. Additionally geodetic techniques such as GPS and Robotic Total Stations (RTS) are constrained by their low accuracy (few mm) and their low sampling rates. In this study the application of QDaedalus is presented, which constitutes a measuring system developed at the Geodesy and Geodynamics Lab, ETH Zurich and consists of a small CCD camera and Total Station, for the monitoring of the oscillations of a rigid structure. In collaboration with the Institute of Structural Engineering of ETH Zurich and EMPA, the QDaedalus system was used for monitoring of the sub-mm displacement of a rigid prototype beam and the estimation of its modal frequencies up to 30 Hz. The results of the QDaedalus data analysis were compared to those of accelerometers and proved to hold sufficient accuracy and suitably supplementing the existing monitoring techniques

A hysteretic multiscale formulation for nonlinear dynamic analysis of composite materials

This article has been made available through the Brunel Open Access Publishing Fund.A new multiscale finite element formulation is presented for nonlinear dynamic analysis of heterogeneous structures. The proposed multiscale approach utilizes the hysteretic finite element method to model the microstructure. Using the proposed computational scheme, the micro-basis functions, that are used to map the microdisplacement components to the coarse mesh, are only evaluated once and remain constant throughout the analysis procedure. This is accomplished by treating inelasticity at the micro-elemental level through properly defined hysteretic evolution equations. Two types of imposed boundary conditions are considered for the derivation of the multiscale basis functions, namely the linear and periodic boundary conditions. The validity of the proposed formulation as well as its computational efficiency are verified through illustrative numerical experiments