Notes

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Fourth, D3R agonist had no effect on γ power of either young or aged mice.

This study reveals DR subtype-mediated hippocampal γ oscillations is aging-related and DR4 activation restores the impaired γ oscillations in aged brain, and suggests that D4R is the potential target for the improvement of cognitive deficits related to the aging and aging-related diseases.
This study reveals DR subtype-mediated hippocampal γ oscillations is aging-related and DR4 activation restores the impaired γ oscillations in aged brain, and suggests that D4R is the potential target for the improvement of cognitive deficits related to the aging and aging-related diseases.
Recent evidence of genetics and metabonomics indicated a potential role of apolipoprotein M (ApoM) in the pathogenesis of Alzheimer's disease (AD). Here, we aimed to investigate the association between plasma ApoM with AD.

A multicenter, cross-sectional study recruited patients with AD (
= 67), age- and sex-matched cognitively normal (CN) controls (
= 73). After the data collection of demographic characteristics, lifestyle risk factors, and medical history, we examined and compared the plasma levels of ApoM, tau phosphorylated at threonine 217 (p-tau217) and neurofilament light (NfL). Multivariate logistic regression analysis was applied to determine the association of plasma ApoM with the presence of AD. The correlation analysis was used to explore the correlations between plasma ApoM with cognitive function [Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA)], activities of daily living (ADL), and the representative blood-based biomarkers (plasma p-tau217 and NfL). Receiveoup analyses, these associations remained in different
ϵ 4 status participants and sex subgroups. ApoM/TC ratio (ΔAUC = 0.056,
= 0.044) and ApoM/TG ratio (ΔAUC = 0.097,
= 0.011) had a statistically remarkably larger AUC than ApoM, respectively. The independent addition of ApoM and its derived indicators to the basic model [combining age, sex,
ϵ 4, and body mass index (BMI)] led to the significant improvement in diagnostic power, respectively (each
< 0.05).

All the findings preliminarily uncovered the association between plasma ApoM and AD and provided more evidence of the potential of ApoM as a candidate biomarker of AD.
All the findings preliminarily uncovered the association between plasma ApoM and AD and provided more evidence of the potential of ApoM as a candidate biomarker of AD.Assistive exoskeleton robots are being widely applied in neurorehabilitation to improve upper-limb motor and somatosensory functions. During robot-assisted exercises, the central nervous system appears to highly attend to external information-processing (IP) to efficiently interact with robotic assistance. However, the neural mechanisms underlying this process remain unclear. The rostromedial prefrontal cortex (rmPFC) may be the core of the executive resource allocation that generates biases in the allocation of processing resources toward an external IP according to current behavioral demands. Here, we used functional near-infrared spectroscopy to investigate the cortical activation associated with executive resource allocation during a robot-assisted motor task. During data acquisition, participants performed a right-arm motor task using elbow flexion-extension movements in three different loading conditions robotic assistive loading (ROB), resistive loading (RES), and non-loading (NON). Participants were asked to strive for kinematic consistency in their movements. A one-way repeated measures analysis of variance and general linear model-based methods were employed to examine task-related activity. We demonstrated that hemodynamic responses in the ventral and dorsal rmPFC were higher during ROB than during NON. Moreover, greater hemodynamic responses in the ventral rmPFC were observed during ROB than during RES. Increased activation in ventral and dorsal rmPFC subregions may be involved in the executive resource allocation that prioritizes external IP during human-robot interactions. In conclusion, these findings provide novel insights regarding the involvement of executive control during a robot-assisted motor task.This article aims to address problems in the current clustering process of low-energy adaptive clustering hierarchy (LEACH) in the wireless sensor networks, such as strong randomness and local optimum in the path optimization. This article proposes an optimal combined weighting (OCW) and improved ant colony optimization (IACO) algorithm for the LEACH protocol optimization. First, cluster head nodes are updated via a dynamic replacement mechanism of the whole network cluster head nodes to reduce the network energy consumption. In order to improve the quality of the selected cluster head nodes, this article proposes the OCW method to dynamically change the weight according to the importance of the cluster head node in different regions, in accordance with the three impact factors of the node residual energy, density, and distance between the node and the sink node in different regions. Second, the network is partitioned and the transmission path among the clusters can be optimized by the transfer probability in IACO with combined local and global pheromone update mechanism. The efficacy of the proposed LEACH protocol optimization method has been verified with MATLAB simulation experiments.Recently, the robotic arm control system based on a brain-computer interface (BCI) has been employed to help the disabilities to improve their interaction abilities without body movement. However, it's the main challenge to implement the desired task by a robotic arm in a three-dimensional (3D) space because of the instability of electroencephalogram (EEG) signals and the interference by the spontaneous EEG activities. Moreover, the free motion control of a manipulator in 3D space is a complicated operation that requires more output commands and higher accuracy for brain activity recognition. Based on the above, a steady-state visual evoked potential (SSVEP)-based synchronous BCI system with six stimulus targets was designed to realize the motion control function of the seven degrees of freedom (7-DOF) robotic arm. Meanwhile, a novel template-based method, which builds the optimized common templates (OCTs) from various subjects and learns spatial filters from the common templates and the multichannel EEG signal, was applied to enhance the SSVEP recognition accuracy, called OCT-based canonical correlation analysis (OCT-CCA). The comparison results of offline experimental based on a public benchmark dataset indicated that the proposed OCT-CCA method achieved significant improvement of detection accuracy in contrast to CCA and individual template-based CCA (IT-CCA), especially using a short data length. In the end, online experiments with five healthy subjects were implemented for achieving the manipulator real-time control system. AG 825 The results showed that all five subjects can accomplish the tasks of controlling the manipulator to reach the designated position in the 3D space independently.Electromagnetic actuation is a new technique for non-invasive manipulation, which provides wireless and controllable power source for magnetic micro-/nano-particles. This technique shows great potential in the field of precise mechanics, environment protection, and biomedical engineering. In this paper, a new quadrupole electromagnetic actuated system was constructed, which was composed of four electromagnetic coils, each coil being actuated by an independent DC power supplier. The magnetic field distribution in the workspace was obtained through finite element modeling and numerical simulation via COMSOL software, as well as the effect of the current flow through the coil in the field distribution. Moreover, parameters of the electromagnetic system were optimized through parametric modeling analysis. A magnetic field map was constructed for rapidly solving the desired driving current from the required magnetic flux density. Experiments were conducted to manipulate a micro-particle along the desired circular path. The proposed work provides theoretical references and numerical fundamentals for the control of magnetic particle in future.Aiming at the situation that the structural parameters of the general manipulators are uncertain, a time-varying impedance controller based on model reference adaptive control (MRAC) is proposed in this article. The proposed controller does not need to use acceleration-based feedback or to measure external loads and can tolerate considerable structure parameter errors. The global uniform asymptotic stability of the time-varying closed-loop system is analyzed, and a selection approach for control parameters is presented. It is demonstrated that, by using the proposed control parameter selection approach, the closed-loop system under the adaptive controller is equivalent to an existing result. The feasibility of the presented controller for the general manipulators is demonstrated by some numerical simulations.Transfemoral amputees are currently forced to utilize energetically passive prostheses that provide little to no propulsive work. Among the several joints and muscles required for healthy walking, the ones most vital for push-off assistance include the knee, ankle, and metatarsophalangeal (MTP) joints. There are only a handful of powered knee-ankle prostheses (also called powered transfemoral prostheses) in literature and few of them comprise a toe-joint. However, no one has researched the impact of toe-joint stiffness on walking with a power transfemoral prosthesis. This study is aimed at filling this gap in knowledge. We conducted a study with an amputee and a powered transfemoral prosthesis consisting of a spring loaded toe-joint. The prosthesis's toe-joint stiffness was varied between three values 0.83 Nm/deg, 1.25 Nm/deg, and infinite (rigid). This study found that 0.83 Nm/deg stiffness reduced push-off assistance and resulted in compensatory movements that could lead to issues over time. While the joint angles and moments did not considerably vary across 1.25 Nm/deg and rigid stiffness, the latter led to greater power generation on the prosthesis side. However, the 1.25 Nm/deg joint stiffness resulted in the least power production from the intact side. We, thus, concluded that the use of a stiff toe-joint with a powered transfemoral prosthesis can reduce the cost of transport of the intact limb.Due to the cumbersome and expensive data collection process, facial action unit (AU) datasets are generally much smaller in scale than those in other computer vision fields, resulting in overfitting AU detection models trained on insufficient AU images. Despite the recent progress in AU detection, deployment of these models has been impeded due to their limited generalization to unseen subjects and facial poses. In this paper, we propose to learn the discriminative facial AU representation in a self-supervised manner. Considering that facial AUs show temporal consistency and evolution in consecutive facial frames, we develop a self-supervised pseudo signal based on temporally predictive coding (TPC) to capture the temporal characteristics. To further learn the per-frame discriminativeness between the sibling facial frames, we incorporate the frame-wisely temporal contrastive learning into the self-supervised paradigm naturally. The proposed TPC can be trained without AU annotations, which facilitates us using a large number of unlabeled facial videos to learn the AU representations that are robust to undesired nuisances such as facial identities, poses.
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