Alzheimer’s disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline and neurodegenerative disorder. Abnormal aggregations of intracellular neurofibrillary tangles (NFTs) and unusual accumulations of extracellular amyloid-β (Aβ) peptides are two important pathological features in AD brains. However, in spite of large-scale clinical studies and computational simulations, the molecular mechanisms of AD development and progression are still unclear. In this study, we divided all of the samples into two groups: early stage (Braak score I-–III) and later stage (Braak score IV–VI). By big database mining, the candidate genetic and epigenetic networks (GEN) have been constructed. In order to find out the real GENs for two stages of AD, we performed systems identification and system order detection scheme to prune false positives with the help of corresponding microarray data. Applying the principal network projection (PNP) method, core GENs were extracted from real GENs based on the projection values. By the annotation of KEGG pathway, we could obtain core pathways from core GENs and investigate pathogenetic mechanisms for the early and later stage of AD, respectively. Consequently, according to pathogenetic mechanisms, several potential biomarkers are identified as drug targets for multiple-molecule drug design in the treatment of AD.
This study proposes a dual-stage lens actuator used for optical disc drives, which includes a piezoceramic parallel-beam as a fine actuator and a voice coil motor (VCM) as the coarse one. The positioning algorithm of the objective lens is comprised of robust H ? fine/coarse controllers designed based on l synthesis and a repetitive controller to further reduce effects of disturbance. To these ends, the dynamic model of the piezoceramic parallelbeam and VCM are first established and then identified by experiments. Based on these identified models, the system dynamics is represented as a standard form, which is ready for l synthesis to design robust controller. Performing optimization, the desired robust H ? controller used for conducting fine/coarse positioning is obtained. In addition to H ? control design, the repetitive controller is further forged to reduce the effect of disturbance based on the periodic nature of the disturbance. Simulations and experiments are conducted to validate the performance expected by previously designed controllers. The experiment shows that the fine piezo-actuator bears the responsibilities of compensating in-precision positioning of the coarse VCM actuator and external small level periodic disturbance.
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