Parkinson's disease age at onset genome-wide association study : Defining heritability, genetic loci, and α-synuclein mechanisms

Background Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown. Objectives To identify the genetic determinants of PD age at onset. Methods Using genetic data of 28,568 PD cases, we performed a genome-wide association study based on PD age at onset. Results We estimated that the heritability of PD age at onset attributed to common genetic variation was similar to 0.11, lower than the overall heritability of risk for PD (similar to 0.27), likely, in part, because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni-corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in alpha-synuclein aggregation pathways. Remarkably, other well-established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD. Conclusions Overall, we have performed the largest age at onset of PD genome-wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease-linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. (c) 2019 International Parkinson and Movement Disorder SocietyPeer reviewe

A Tailor-made MR Damper for Bridge Cable Vibration Control: Experiment and Modelling

Magnetorheological (MR) dampers have emerged as one of the most promising devices to suppress cable vibration in cable-stayed bridges, owing to their attractive features of minute power requirement, controllability, fail-safe operation, rapid response and low environmental sensitivity. While possessing controllable damping capability, the MR dampers are unable to monitor cable vibrations for implementing semi-active closed-loop controls, and are used merely as adjustable passive dampers in an open-loop mode in the current practices. Hence, a novel self-sensing MR damper system with an embedded PZT sensor has been tailor-made for real-time cable vibration control. Its laboratorial fabrication and characterization are to report

Modelling of a Self-sensing Magnetorheological Damper Using Bayesian Regularized NARX Neural Network

The magnetorheological (MR) damper has been demonstrated to be one of the most promising semiactive control devices to suppress structural vibration. Recently, a novel self-sensing MR damper has been fabricated by integrating an actuation-only MR damper with a piezoelectric force sensor. Possessing the sensing-while-damping function, the damper offers a cost-effective innovation for real-time semiactive structural vibration control. However, due to its intrinsic nonlinear characteristics, modelling of the damper to adequately describe its hysteresis dynamics has been one of the prerequisite and challenging tasks for fully exploring its capabilities in real-time control implementation. In this paper, forward and inverse dynamic models of the self-sensing MR damper are developed based on the combined NARX (nonlinear autoregressive model with exogenous inputs) and neural network techniques. Experiments are performed to collect training and validation data for the NARX neural networks. The Bayesian regularization is adopted in the training phase to prevent over-fitting. Validation results indicate that the trained NARX neural network models accurately represent the forward and inverse dynamics of the damper, exhibit good generalization capability, and are adequate for control design and analysis

Smart Magnetorheological Dampers with Embedded Sensors for Vibration Control Applications

Smart magnetorheological (MR) dampers with embedded piezoelectric transducers have been developed to provide a closed-loop vibration control of bridge cables. The smart MR damper consists of a lead zirconate titanate (PZT) piezoelectric sensor integrated with a conventional MR damping device. The piezoelectric sensor is used to sense the external excitation forces exerted on the smart damper. The sensing-while-damping function of the smart damper offers great potential for real-time cable vibration control. To optimize the performance of the smart damper, the force sensors have been fabricated using different preloading conditions. The optimal condition has been determined from the calibration of the force sensors which was performed using force-controlled tests on a Material Test System (MTS). The performance tests of the smart MR damper have been conducted by mounting the smart MR damper on a MTS operating in a displacement-controlled excitation of sine waves with different driving conditions to the smart damper. The relationship between the applied current to the smart damper and the force sensed by the piezoelectric sensor is significant to provide the closed-loop vibration control. The experimental results proved that the smart MR damper has potential in the applications of real-time, closed-loop vibration control of civil and mechanical structures

Effect of electrode pattern on the outputs of piezosensors for wire bonding process control

A polyvinylidene fluoride (PVDF) piezosensor was installed as an integral part of an ultrasonic wire-bonding transducer for measuring bonding parameters, such as impact force, ultrasonic amplitude, and bond time. Four different types of electrode patterns were used to optimize the sensor outputs. When the ring-shaped electrode of the sensor was subdivided into four different sections, namely the top, bottom, left, and right sections, different output signals were observed during the wire-bonding process. The top section of the sensor was more sensitive to the impact force while the left and right sections could track the changes in the ultrasonic amplitude proficiently. This sensor has good potential to be used in an in situ automatic wire-bonding process-control system