An Efficient Feature Extraction Scheme for Mobile Anti-Shake in Augmented Reality

In recent years, augmented reality on mobile devices has become popular. Mobile shakes are the most typical type of interference in mobile augmented reality. To negate such interference, anti-shake is an urgent requirement. To enhance anti-shake efficiency, we propose an efficient feature extraction scheme for mobile anti-shake in augmented reality. The scheme directly detects corners to avoid the non-extreme constraint such that the efficiency of feature extraction is improved. Meanwhile, the scheme only updates the added corners during mobile shakes, which improves the accuracy of feature extraction. In the experiments, the memory consumption of existing methods is almost double compared to that in our scheme. Further, the runtime of our scheme is only half of the runtime of the existing methods. The experimental results demonstrate that our scheme performs better than the existing classic methods on mobile anti-shake in terms of memory consumption, efficiency, and accuracy

Local GABAergic signaling within sensory ganglia controls peripheral nociceptive transmission

The integration of somatosensory information is generally assumed to be a function of the central nervous system (CNS). Here we describe fully functional GABAergic communication within rodent peripheral sensory ganglia and show that it can modulate transmission of pain-related signals from the peripheral sensory nerves to the CNS. We found that sensory neurons express major proteins necessary for GABA synthesis and release and that sensory neurons released GABA in response to depolarization. In vivo focal infusion of GABA or GABA reuptake inhibitor to sensory ganglia dramatically reduced acute peripherally induced nociception and alleviated neuropathic and inflammatory pain. In addition, focal application of GABA receptor antagonists to sensory ganglia triggered or exacerbated peripherally induced nociception. We also demonstrated that chemogenetic or optogenetic depolarization of GABAergic dorsal root ganglion neurons in vivo reduced acute and chronic peripherally induced nociception. Mechanistically, GABA depolarized the majority of sensory neuron somata, yet produced a net inhibitory effect on the nociceptive transmission due to the filtering effect at nociceptive fiber T-junctions. Our findings indicate that peripheral somatosensory ganglia represent a hitherto underappreciated site of somatosensory signal integration and offer a potential target for therapeutic intervention

Neuropathic Injury-Induced Plasticity of GABAergic System in Peripheral Sensory Ganglia

GABA is a major inhibitory neurotransmitter in the mammalian central nervous system (CNS). Inhibitory GABAA channel circuits in the dorsal spinal cord are the gatekeepers of the nociceptive input from the periphery to the CNS. Weakening of these spinal inhibitory mechanisms is a hallmark of chronic pain. Yet, recent studies have suggested the existence of an earlier GABAergic “gate” within the peripheral sensory ganglia. In this study, we performed systematic investigation of plastic changes of the GABA-related proteins in the dorsal root ganglion (DRG) in the process of neuropathic pain development. We found that chronic constriction injury (CCI) induced general downregulation of most GABAA channel subunits and the GABA-producing enzyme, glutamate decarboxylase, consistent with the weakening of the GABAergic inhibition at the periphery. Strikingly, the α5 GABAA subunit was consistently upregulated. Knock-down of the α5 subunit in vivo moderately alleviated neuropathic hyperalgesia. Our findings suggest that while the development of neuropathic pain is generally accompanied by weakening of the peripheral GABAergic system, the α5 GABAA subunit may have a unique pro-algesic role and, hence, might represent a new therapeutic target

The transmembrane channel-like 6 (TMC6) in primary sensory neurons involving thermal sensation via modulating M channels

Introduction: The transmembrane channel-like (TMC) protein family contains eight members, TMC1–TMC8. Among these members, only TMC1 and TMC2 have been intensively studied. They are expressed in cochlear hair cells and are crucial for auditory sensations. TMC6 and TMC8 contribute to epidermodysplasia verruciformis, and predispose individuals to human papilloma virus. However, the impact of TMC on peripheral sensation pain has not been previously investigated.Methods: RNAscope was employed to detect the distribution of TMC6 mRNA in DRG neurons. Electrophysiological recordings were conducted to investigate the effects of TMC6 on neuronal characteristics and M channel activity. Zn2+ indicators were utilized to detect the zinc concentration in DRG tissues and dissociated neurons. A series of behavioural tests were performed to assess thermal and mechanical sensation in mice under both physiological and pathological conditions.Results and Discussion: We demonstrated that TMC6 is mainly expressed in small and medium dorsal root ganglion (DRG) neurons and is involved in peripheral heat nociception. Deletion of TMC6 in DRG neurons hyperpolarizes the resting membrane potential and inhibits neuronal excitability. Additionally, the function of the M channel is enhanced in TMC6 deletion DRG neurons owing to the increased quantity of free zinc in neurons. Indeed, heat and mechanical hyperalgesia in chronic pain are alleviated in TMC6 knockout mice, particularly in the case of heat hyperalgesia. This suggests that TMC6 in the small and medium DRG neurons may be a potential target for chronic pain treatment

Lattice-based provable data possession in the standard model for cloud-based smart grid data management systems

The smart grid is considered to be the next-generation electric power network. In a smart grid, there are massive data to be processed, so cloud computing is introduced into it to form a cloud-based smart grid data management system. However, with data no longer being stored locally, how to ensure the integrity of data stored in the cloud in the smart grid has become an urgent problem awaiting solution. Provable data possession has been proposed to solve this problem. With the development of quantum computer technology, quantum attacks-resistant cryptographic schemes are gradually entering people’s horizons. Lattice cryptography can resist quantum attacks. In this article, a lattice-based provable data possession scheme is proposed for cloud-based smart grid data management systems. The scheme is proved unforgeable under the small integer solution hard assumption in the standard model. Compared with other two efficient lattice-based provable data possession schemes in the standard model, our scheme also shows efficiency

Lattice-based provable data possession in the standard model for cloud-based smart grid data management systems

The smart grid is considered to be the next-generation electric power network. In a smart grid, there are massive data to be processed, so cloud computing is introduced into it to form a cloud-based smart grid data management system. However, with data no longer being stored locally, how to ensure the integrity of data stored in the cloud in the smart grid has become an urgent problem awaiting solution. Provable data possession has been proposed to solve this problem. With the development of quantum computer technology, quantum attacks-resistant cryptographic schemes are gradually entering people’s horizons. Lattice cryptography can resist quantum attacks. In this article, a lattice-based provable data possession scheme is proposed for cloud-based smart grid data management systems. The scheme is proved unforgeable under the small integer solution hard assumption in the standard model. Compared with other two efficient lattice-based provable data possession schemes in the standard model, our scheme also shows efficiency. </jats:p

The first application of modified neutron source multiplication method in subcriticality monitoring based on Monte Carlo

The control rod drive mechanism needs to be debugged after reactor fresh fuel loading. It is of great importance to monitor the subcriticality of this process accurately. A modified method was applied to the subcriticality monitoring process, in which only a single control rod cluster was fully withdrawn from the core. In order to correct the error in the results obtained by Neutron Source Multiplication Method, which is based on one point reactor model, Monte Carlo neutron transport code was employed to calculate the fission neutron distribution, the iterated fission probability and the neutron flux in the neutron detector. This article analyzed the effect of a coarse mesh and a fine mesh to tally fission neutron distributions, the iterated fission probability distributions and to calculate correction factors. The subcriticality before and after modification is compared with the subcriticality calculated by MCNP code. The modified results turn out to be closer to calculation. It's feasible to implement the modified NSM method in large local reactivity addition process using Monte Carlo code based on 3D model. Keywords: Subcriticality monitoring, Modified neutron source multiplication method, MCN

Design of Prediction-Based Controller for Networked Control Systems with Packet Dropouts and Time-Delay

A novel prediction-based controller design is proposed for networked control systems (NCSs) with stochastic packet dropouts and time-delay in their control channel. The sequence of packet dropouts, which are modelled as a Bernoulli process, is compensated by a zero-order holder (ZOH)-based module, whereas a state predictor is utilized for obtaining the predicted states at the time delayed. In view of dropout compensator and state predictor, a novel modified model predictive controller (MPC) is designed and proposed in the following procedures. Compared to cost function of a general model predictive controller, variables of states are substituted by the predicted ones as obtained from state predictor preliminarily. Then, a logical programming approach is applied to include all the possible circumstances in the prediction horizon. Consequently, the cost function is reformed as simultaneous minimax linear matrix inequalities (LMI) with constraints. As a result, toolbox YALMIP is employed in order to solve such minimax programming problem eventually. Simulation results are presented to show the feasibility and performance of proposed method.</jats:p