A real-time epilepsy seizure detection approach based on EEG using short-time Fourier transform and Google-Net convolutional neural network.

Epilepsy is one of the most common brain disorders, and seizures of epilepsy have severe adverse effects on patients. Real-time epilepsy seizure detection using electroencephalography (EEG) signals is an important research area aimed at improving the diagnosis and treatment of epilepsy. This paper proposed a real-time approach based on EEG signal for detecting epilepsy seizures using the STFT and Google-net convolutional neural network (CNN).

Associations between plasma metal elements and risk of cognitive impairment among Chinese older adults.

Background: The relationship between plasma metal elements and cognitive function is unclear, especially in extremely older individuals. This present study aimed to explore the association between plasma metal concentrations and the risk of cognitive impairment (CI) in Chinese extremely older adults.

Methods: Individuals aged ≥90 years with plasm metal concentration data from the fifth wave of the 2008 Chinese Longitudinal Healthy Longevity Survey were included.

Downregulation of ITGA5 inhibits lymphangiogenesis and cell migration and invasion in male laryngeal squamous cell carcinoma.

ITGA5, a fibronectin receptor was highly expressed in laryngeal squamous cell carcinoma (LSCC) samples and was related to poor survival. However, the potential mechanism remains unclear. To elucidate the regulatory role of ITGA5 in LSCC progression, we investigated the effect of ITGA5 expression on lymphangiogenesis, migration, and invasion of LSCC cells in vitro and in vivo using immunohistochemistry, siRNA transfection, qRT-PCR, western blotting, enzyme-linked immunosorbent assay, flow cytometry, transwell co-culture, tube formation, cell migration, and invasion assays, and a subcutaneous graft tumor model.

Ganodermasides E-H, four new ergosterol derivatives from the endophytic fungus Epicoccum poae DJ-F associated with Euphorbia royleana.

Ganodermasides E-H (1-4), four new ergosterol derivatives and two known ones (5 and 6) were isolated from the fermentation of the endophytic fungus Epicoccum poae DJ-F in the stems of Euphorbia royleana Boiss. Their structures were elucidated by spectroscopic analysis, including extensive 1D NMR, 2D NMR, and HRESIMS techniques. All the isolated compounds were tested for their vitro antibacterial activity.

A digital twin framework for robust control of robotic-biological systems.

Medical device regulatory standards are increasingly incorporating computational modelling and simulation to accommodate advanced manufacturing and device personalization. We present a method for robust testing of engineered soft tissue products involving a digital twin paradigm in combination with robotic systems. We developed and validated a digital twin framework for calibrating and controlling robotic-biological systems.

A Hierarchical Data-Driven Predictive Control of Image-Based Visual Servoing Systems With Unknown Dynamics.

In this article, a hierarchical predictive control (PC) algorithm is designed for visual servoing mobile robot systems. At the kinematic level, the image-based visual servoing model of a wheeled mobile robot is established. By defining the corresponding performance index of the PC, an iterative linear quadratic regulator (iLQR) is used to obtain the velocity controller and to provide reference velocity for dynamics.

Advanced design and development of catalysts in propane dehydrogenation.

Propane dehydrogenation (PDH) is an industrial technology for direct propylene production, which has received extensive attention and realized large-scale application. At present, the commercial Pt/Cr-based catalysts suffer from fast deactivation and inferior stability resulting from active species sintering and coke depositing. To overcome the above problems, several strategies such as the modification of the support and the introduction of additives have been proposed to strengthen the catalytic performance and prolong the robust stability of Pt/Cr-based catalysts.

Set-Membership Global Estimation of Networked Systems.

This article is concerned with set-membership global estimation for a networked system under unknown-but-bounded process and measurement noises. First, a group of local set-membership estimators is deployed to obtain the local ellipsoidal estimate of the true system state. Each estimator is capable of communicating with its neighbors within its communication range.

Received Signal Strength Indicator-Based Indoor Localization Using Distributed Set-Membership Filtering.

Most of the existing localization schemes necessitate a priori statistical characteristic of measurement noise, which may be unrealistic in practical applications. This article addresses the problem of indoor localization by implementing distributed set-membership filtering based on a received signal strength indicator (RSSI) under unknown-but-bounded process and measurement noises. First, the transmit power and the path-loss exponent are estimated by a novel least-squares curve fitting (LSCF) method in RSSI-based localization.

Dissipativity Analysis for Neural Networks With Time-Varying Delays via a Delay-Product-Type Lyapunov Functional Approach.

This article is concerned with the problem of dissipativity and stability analysis for a class of neural networks (NNs) with time-varying delays. First, a new augmented Lyapunov-Krasovskii functional (LKF), including some delay-product-type terms, is proposed, in which the information on time-varying delay and system states is taken into full consideration. Second, by employing a generalized free-matrix-based inequality and its simplified version to estimate the derivative of the proposed LKF, some improved delay-dependent conditions are derived to ensure that the considered NNs are strictly ( Q , S , R )- γ -dissipative.

Elevated NO damages the photosynthetic apparatus by inducing the accumulation of superoxide anions and peroxynitrite in tobacco seedling leaves.

This study aimed to further understand the toxicity of high concentrations of nitrogen dioxide (NO) to plants, especially to plant photosynthesis. Tobacco plants in the six-leaf stage were exposed to 16.0 μL L NO to determine the activities of photosystem II (PSII) and photosystem I (PSI) reaction centers, the blocking site of PSII electron transport, the degree of membrane peroxidation and the relative expression of PsbA, PsbO and PsaA genes in the third fully expanded leaves by using gas exchange and chlorophyll fluorescence techniques, biochemical and RT-PCR analysis.

Resilient Tracking Control of Networked Control Systems Under Cyber Attacks.

This article is concerned with the resilient tracking control of a networked control system under cyber attacks. The attacker is an active adversary whose aim is to severely degrade the tracking performance of the system by launching deception attacks on the sensor-to-controller communication channels and denial-of-service attacks on the controller-to-plant channels, respectively. First, a concept of resilient set-membership tracking control is presented, through which the system's true state is guaranteed to reside in a bounding ellipsoidal set of the reference state regardless of the existence of attacks and unknown-but-bounded (UBB) noises.

Distributed Event-Triggered Estimation Over Sensor Networks: A Survey.

An event-triggered mechanism is of great efficiency in reducing unnecessary sensor samplings/transmissions and, thus, resource consumption such as sensor power and network bandwidth, which makes distributed event-triggered estimation a promising resource-aware solution for sensor network-based monitoring systems. This paper provides a survey of recent advances in distributed event-triggered estimation for dynamical systems operating over resource-constrained sensor networks. Local estimates of an unavailable state signal are calculated in a distributed and collaborative fashion based on only invoked sensor data.

Distributed H-Consensus Filtering for Attitude Tracking Using Ground-Based Radars.

This paper is concerned with the distributed H -consensus filtering problem on attitude tracking over a radar filter network subject to switching topology and random packet dropouts occurring in the data transmission from both the Sun sensor and the filters. Since ground-based radars cannot directly measure the satellite attitude, a Sun sensor is deployed at the satellite side and its measurements are transmitted to radar filters through different network communication channels while suffering from random packet dropouts with different probabilities. In the radar filter network, each radar filter receives data not only from the Sun sensor but also from its local neighboring radar filters in accordance with a switching network topology.

Active Full-Vehicle Suspension Control via Cloud-Aided Adaptive Backstepping Approach.

This paper is concerned with the adaptive backstepping control problem for a cloud-aided nonlinear active full-vehicle suspension system. A novel model for a nonlinear active suspension system is established, in which uncertain parameters, unknown friction forces, nonlinear springs and dampers, and performance requirements are considered simultaneously. In order to deal with the nonlinear characteristics, a backstepping control strategy is developed.

Low-Cost Graphite on Paper Pressure Sensor for a Robot Gripper with a Trivial Fabrication Process.

A flexible pressure sensor with a rudimentary, ultra-low cost, and solvent-free fabrication process is presented in this paper. The sensor has a graphite-on-paper stacked paper structure, which deforms and restores its shape when pressure is applied and released, showing an exceptionally fast response and relaxation time of ≈0.4 ms with a sensitivity of -5%/Pa.

Adaptive Event-Triggered Transmission Scheme and H Filtering Co-Design Over a Filtering Network With Switching Topology.

This paper addresses the distributed adaptive event-triggered H filtering problem for a class of sector-bounded nonlinear system over a filtering network with time-varying and switching topology. Both topology switching and adaptive event-triggered mechanisms (AETMs) between filters are simultaneously considered in the filtering network design. The communication topology evolves over time, which is assumed to be subject to a nonhomogeneous Markov chain.

A Novel Cyber Attack Detection Method in Networked Control Systems.

This paper is concerned with cyber attack detection in a networked control system. A novel cyber attack detection method, which consists of two steps: 1) a prediction step and 2) a measurement update step, is developed. An estimation ellipsoid set is calculated through updating the prediction ellipsoid set with the current sensor measurement data.

Distributed H State Estimation Over a Filtering Network With Time-Varying and Switching Topology and Partial Information Exchange.

This paper is concerned with the distributed H state estimation for a discrete-time target linear system over a filtering network with time-varying and switching topology and partial information exchange. Both filtering network topology switching and partial information exchange between filters are simultaneously considered in the filter design. The topology under consideration evolves not only over time but also by an event switch which is assumed to be subject to a nonhomogeneous Markov chain.

Event-Triggered Asynchronous Guaranteed Cost Control for Markov Jump Discrete-Time Neural Networks With Distributed Delay and Channel Fading.

This paper is concerned with the guaranteed cost control problem for a class of Markov jump discrete-time neural networks (NNs) with event-triggered mechanism, asynchronous jumping, and fading channels. The Markov jump NNs are introduced to be close to reality, where the modes of the NNs and guaranteed cost controller are determined by two mutually independent Markov chains. The asynchronous phenomenon is considered, which increases the difficulty of designing required mode-dependent controller.

Optimal Communication Network-Based H∞ Quantized Control With Packet Dropouts for a Class of Discrete-Time Neural Networks With Distributed Time Delay.

This paper is concerned with optimal communication network-based H∞ quantized control for a discrete-time neural network with distributed time delay. Control of the neural network (plant) is implemented via a communication network. Both quantization and communication network-induced data packet dropouts are considered simultaneously.

Set-membership fuzzy filtering for nonlinear discrete-time systems.

This paper is concerned with the set-membership filtering (SMF) problem for discrete-time nonlinear systems. We employ the Takagi-Sugeno (T-S) fuzzy model to approximate the nonlinear systems over the true value of state and to overcome the difficulty with the linearization over a state estimate set rather than a state estimate point in the set-membership framework. Based on the T-S fuzzy model, we develop a new nonlinear SMF estimation method by using the fuzzy modeling approach and the S-procedure technique to determine a state estimation ellipsoid that is a set of states compatible with the measurements, the unknown-but-bounded process and measurement noises, and the modeling approximation errors.

[Application of reversed pedicled submental island flap].

Objective: To explore the clinical applications of reversed pedicled submental island flap in the face and oropharynx.

Methods: The clinical data of ten cases of reconstruction of defect in the area of face or oropharynx following resection of tumors with reversed pedicled submental island flaps between January of 2004 to December of 2006 were retrospectively studied. The cases included six males and four females, aged from 24 to 76 (median 55 years).