Zinc oxide nanoparticles (ZnO NPs) are frequently used in industrial products such as paint, surface coating, and cosmetics, recently, they have been explored biologic biomedical applications. Therefore, this study was undertaken to investigate the effect of ZnO NPs on cytotoxicity, apoptosis, autophagy human ovarian cancer cells (SKOV3).ZnO with a crystalline size 20 nm were characterized various analytical techniques, including ultraviolet-visible spectroscopy, X-ray diffraction,...

The development of electrical measurement technology has brought high latitude residential electricity consumption data to power companies, which contains the characteristics users' behavior and provides support for classification. In order improve efficiency feature extraction accuracy identification, a classification model based on sparse denoising autoencoder dimensionality reduction spectral clustering is proposed in this paper. Firstly, (SDAE) manually defining characteristic indicators...

Motor learning transfer, the ability to apply skills acquired in one task enhance performance a related task, is driven by changes neural ensemble activities. However, long-term evolution of population dynamics during motor transfer remains unclear. Specifically, how do patterns reorganize and stabilize over an extended period new task? To investigate mechanisms cortex that enable such we employed Brain-Machine Interface (BMI) paradigm rats. In experiment, rats first mastered lever-pressing...

Abstract Objectives . Coadaptive brain–machine interfaces (BMIs) allow subjects and external devices to adapt each other during the closed-loop control, which provides a promising solution for paralyzed individuals. Previous studies have focused on either improving sensory feedback facilitate subject learning or developing adaptive algorithms maintain stable decoder performance. In this work, we aim design an efficient coadaptive BMI framework not only facilitates of new tasks with designed...

Autonomous brain machine interfaces (BMIs) aim to enable paralyzed people self-evaluate their movement intention control external devices. Previous reinforcement learning (RL)-based decoders interpret the mapping between neural activity and movements using reward for well-trained subjects, have not investigated task procedure. The has developed a mechanism identify correct actions that lead rewards in new task. This internal guidance can be utilized replace reference advance BMIs as an...

Various media information in life can have an important impact on our understanding of music. In this paper, we present a demo, Mind Band, which is Cross-Media artificial intelligent composing platform using elements such as emoji, image and humming. practice, base system the valence-arousal model. We use emotion analysis to map them music pieces, are generated by Variational Autoencoder - Generative Adversarial Networks provide users with immersive experience uploading emoji/image/humming...

Reinforcement-learning (RL)-based brain-machine interfaces (BMIs) interpret dynamic neural activity into movement intention without patients' real limb movements, which is promising for clinical applications.A task generally requires the subjects to reach target within one step and rewards instantaneously.However, a BMI scenario involves tasks that require multiple steps, during sensory feedback provided indicate status of prosthesis, reward only given at end trial.Actually, internally...

Objectives. Brain-machine interfaces (BMIs) aim to help people with motor disabilities by interpreting brain signals into intentions using advanced signal processing methods. Currently, BMI users require intensive training perform a pre-defined task, not mention learning new task. Thus, it is essential understand neural information pathways among the cortical areas in task provide principles for designing BMIs abilities. We propose investigate relationship between medial prefrontal cortex...

An NoC (network on chip) constructed with silicon photonic microrings can be implemented CMOS technology and integrated processor cores the same die. Each microring in has two switching states, one consuming significantly less power than other. Different routing schemes lead to different numbers of high-power consumption state, result consumptions for NoC. In an earlier work, a looping-based algorithm was proposed which exploits characteristics states so as minimize Benes-type NoC; but this...

Brain-machine interfaces (BMIs) translate the neural activity into digital command to control external devices in accomplishing movement task, which could involve multiple stages of behaviors sequence. Previous work generally discriminates stage labels using a classifier and uses combination sub-decoders designed respectively for each stage. Without considering time dynamics activity, often introduces noisy estimation prediction. Brain-controlling neuro-prosthesis requires decoder...

Computer-Aided Alignment (CAA) is an effective method for improving image quality of optical system. This paper studies some key techniques CAA space telescope, including the mathematical model CAA, acquirement and processing aberration data, establishment sensitivity matrix solution misalignment. A numerical simulation a telescope has been performed to verify ability accuracy method.

Brain-machine interfaces (BMIs) help the disabled restore body functions by translating neural activity into digital commands to control external devices. Neural adaptation, where brain signals change in response stimuli or movements, plays an important role BMIs. When subjects purely use brain-control a prosthesis, some neurons will actively explore new tuning property accomplish movement task. The prediction of this can adapt more efficiently and maintain good decoding performance....

As terrorists are losing against counter-terrorism efforts, they turn to manipulating cryptocurrency prices through online social communities gain illicit profit fund their operations. Modeling temporal networks (OSNs) of these can possibly help provide useful intelligence about malicious activities. However, existing techniques do not learn sufficiently from diverse features enable prediction and simulation behavior. Research on simulating OSN behavior is widely available. This research...

Abstract Objective. Brain-machine interfaces (BMIs) translate neural activity into motor commands to restore functions for people with paralysis. Local field potentials (LFPs) are promising long-term BMIs, since the quality of recording lasts longer than single neuronal spikes. Inferring spike from population activities such as LFPs is challenging, because stem synaptic currents flowing in tissue produced by various ensembles and reflect synchronization. Existing studies that combine spikes...

It is quite challenging to predict dynamic stimulation patterns on downstream cortical regions from upstream neural activities. Spike prediction models used in traditional methods are trained by activity as the reference signal a supervised manner. However, unavailable when neurological disorders exist. This study proposes reinforcement learning-based point process framework generatively spike trains through behavior-level rewards, solving difficulty. The evaluated reconstruct transregional...

The lock-in amplifier can perform high-precision measurement in both time and amplitude dimensions, so that it becomes a key component of instrumental system for precision control. This article overviews the concept, technology, application phase-locked amplifiers as guide. It first explains development evolution analog, digital, virtual amplifiers, demonstrating their relationship differences. Then, classifies from mathematical perspective based on order type loops. Subsequently, testing...

In recent years, the spreading of malicious social media messages about financial stocks has threatened security market. Market Anomaly Attacks is an illegal practice in stock or commodities markets that induces investors to make purchase sale decisions based on false information. Identifying these threats from noisy datasets remains challenging because long time sequence postings, ambiguous textual context and difficulties for traditional deep learning approaches handle both temporal text...

Reinforcement learning (RL) algorithm interprets the movement intentions in Brain-machine interfaces (BMIs) with a reward signal. This can be an external (food or water) internal representation which links correct reward. Medial prefrontal cortex (mPFC) has been demonstrated to closely related reward-guided learning. In this paper, we propose model mPFC activities as of associated different actions RL framework. Support vector machine (SVM) is adopted analyze distinguish rewarded and...

Computer-aided alignment (CAA) is a significant technique to correct errors which are caused by the misalignment of each element in an optical system. It especially important such areas as space remote sensing systems, since manual adjustment impossible when it operates orbit. In this paper, three-mirror system adopted example perform CAA. Principle introduced. And based on CAA algorithm, method for segmented mirror expatiated detail. A numerical simulation has been performed verify ability...

Abstract Motor brain machine interfaces (BMIs) interpret neural activities from motor-related cortical areas in the into movement commands to control a prosthesis. As subject adapts prosthesis, medial prefrontal cortex (mPFC), upstream of primary motor (M1), is heavily involved reward-guided learning. Thus, considering mPFC and M1 functionality within hierarchical structure could potentially improve effectiveness BMI decoding while subjects are The commonly used Kalman method with only one...

Brain-machine interfaces (BMIs) translate neural signals into digital commands to control external devices. During the use of BMI, neurons may change their activity corresponding same stimuli or movement. The changes are represented by tuning parameters which gradually and abruptly. Adaptive algorithms were proposed estimate time-varying in order keep decoding performance stable. existing methods only searched new locally failed detect abrupt changes. Global search helps but requires known...