Finite-time prescribed performance tracking control of seeker stabilized platform in the discrete-time domain.

Current prescribed performance control (PPC) focuses on continuous-time systems, while this article proposes a novel discrete-time version of PPC for finite-time tracking of seeker stabilized platform in the discrete-time domain. Firstly, the newly developed performance functions are employed to impose finite-time prescribed performance on tracking errors. After that, a type of stabilization functions with respect to transformed errors are constructed for back-stepping controllers designing. On this basis, transformed errors are indirectly stabilized, and thus the pursued prescribed transient and steady-state behaviors are ensured for tracking errors via Lyapunov synthesis. Different from existing sliding-mode-control based discrete-time PPC, the addressed approach eliminates the sliding-mode structure and hence avoids high frequency chattering caused by such framework. Finally, compared simulations validate the superiority over existing methods.

Cognitive dysfunction in diabetes: abnormal glucose metabolic regulation in the brain.

Cognitive dysfunction is increasingly recognized as a complication and comorbidity of diabetes, supported by evidence of abnormal brain structure and function. Although few mechanistic metabolic studies have shown clear pathophysiological links between diabetes and cognitive dysfunction, there are several plausible ways in which this connection may occur. Since, brain functions require a constant supply of glucose as an energy source, the brain may be more susceptible to abnormalities in glucose metabolism. Glucose metabolic abnormalities under diabetic conditions may play an important role in cognitive dysfunction by affecting glucose transport and reducing glucose metabolism. These changes, along with oxidative stress, inflammation, mitochondrial dysfunction, and other factors, can affect synaptic transmission, neural plasticity, and ultimately lead to impaired neuronal and cognitive function. Insulin signal triggers intracellular signal transduction that regulates glucose transport and metabolism. Insulin resistance, one hallmark of diabetes, has also been linked with impaired cerebral glucose metabolism in the brain. In this review, we conclude that glucose metabolic abnormalities play a critical role in the pathophysiological alterations underlying diabetic cognitive dysfunction (DCD), which is associated with multiple pathogenic factors such as oxidative stress, mitochondrial dysfunction, inflammation, and others. Brain insulin resistance is highly emphasized and characterized as an important pathogenic mechanism in the DCD.

Fuzzy Neural Pseudo Control With Prescribed Performance for Waverider Vehicles: A Fragility-Avoidance Approach.

A fuzzy-neural-approximation-based pseudo nonaffine control protocol is proposed for waverider vehicles (WVs), which is capable of guaranteeing tracking errors with desired prescribed performance and rejecting the obstacle of fragility inherent to the traditional prescribed performance control (PPC). The pseudo control is defined to approximate the nonaffine dynamics of WVs, while there is no need of model affinization. Furthermore, fuzzy neural approximators are combined with the adaptive compensation strategy to resist both system uncertainties and external disturbances. Especially, a new type of nonfragile prescribed performance, being able to self-adjust its prescribed funnel, is proposed to remedy the fragility defect associated with the existing PPC. Finally, the realizability of the spurred prescribed performance is proved via stability proof, and the superiority of the addressed design is tested by compared simulations.

Qinling liquid ameliorates renal immune inflammatory damage via activating autophagy through AMPK/Stat3 pathway in uric acid nephropathy.

BACKGROUND: Excessive deposition of uric acid (UA) is one of the risk factors for kidney damage. Qinling liquid (QL) has a certain therapeutic effect on uric acid nephropathy (UAN), but its regulation mechanism is still unclear. METHODS: UAN rat models and UA induced rat renal tubular epithelial cells (NRK-52E) were constructed to evaluate the functional roles of QL. We firstly evaluated the kidney function and the degree of kidney damage in rats after QL treatment. Then, effects of QL on autophagy and NLRP3 inflammasome activation were assessed. Moreover, the regulation of QL in AMPK and Stat3 phosphorylation levels and the relationship among autophagy, AMPK/Stat3 pathway and NLRP3 inflammasomes were determined. RESULTS: QL could alleviate the inflammatory damage in UAN rats and promote the activation of autophagy. In addition, QL suppressed UA-induced activation of NLRP3 inflammasomes in rat renal tubular epithelial cells, which was partially reversed by autophagy inhibitor. Further, AMPK/Stat3 axis-mediated autophagy participated in the regulation of UA-induced NLRP3 inflammasome activation in NRK-52E cells. Finally, we confirmed that inhibiting AMPK/Stat3 pathway partly deteriorated the ameliorating effect of QL on renal immune inflammatory injury in UAN rats. CONCLUSION: Through in vivo and in vitro experiments, we found that QL promotes autophagy by activating the AMPK/Stat3 pathway, thereby improving renal immune inflammatory injury in UAN.

Hypersonic tracking control under actuator saturations via readjusting prescribed performance functions.

Prescribed performance control (PPC) has been shown to be an effective tool in pursuing prescribed transient and steady-state specifications. Unfortunately, the existing PPC is incapable of handling the peaking of errors caused by actuator saturations, which is due to the short of the ability of readjusting the prescribed performance functions. In this article, we propose a novel PPC scheme, namely the readjusting-performance-function-based approach, for hypersonic flight vehicles subject to actuator saturations. A new sort of performance functions containing readjusting terms are developed to impose prescribed constraints on the velocity tracking error and the altitude tracking error. More specially, the prescribed performance functions can be adaptively readjusted to guarantee that tracking errors are always within them. This eliminates the singular problem that is usually encountered by traditional PPC. To deal with the actuator saturation problem, a novel compensated system (CS) is exploited for the velocity dynamics. Then, the CS is further extended to the altitude subsystem by reforming it as a high-order formulation. Besides the aforementioned baseline controllers, optimal control protocols are also addressed based on adaptive dynamic programming. Finally, comparison simulation results are given to verify the advantages.

Extraction of Intangible Cultural Heritage Visual Elements by Deep Learning and Its Application in Grassland Tourism of the Silk Road Culture.

Inner Mongolia is rich in grassland tourism resources, and the development of grassland tourism is of great significance to Inner Mongolia tourism and promotion of grassland protection. To better promote the grassland tourism of the Silk Road culture, the Conditional Global Area Network (CGAN) and Morphology Connected Component Chan-Vase (MCC-CV) algorithm are used to enhance and segment the traditional embroidery patterns in Inner Mongolia. Firstly, the generative adversarial network (GAN) is optimized, and a new GAN is proposed with the feature vector extracted from the convolutional neural network (CNN) as the constraint condition. Secondly, the automatic segmentation algorithm of embroidery based on the MCC-CV model is proposed, and finally, the proposed algorithm is tested. The test results demonstrate that after 8000 iterations of the proposed image-enhancement algorithm, its personalized features are enhanced, and the segmentation accuracy of the proposed image segmentation algorithm is 60%. The proposed algorithm provides some ideas for the application of deep learning (DL) technology in the grassland tourism of the Silk Road culture and also helps operators to accurately grasp the market and make tourists more comfortable and pleasant.

Effects of Polygonum cuspidatum on AMPK-FOXO3α Signaling Pathway in Rat Model of Uric Acid-Induced Renal Damage.

BACKGROUND: To observe the effects of Chinese medicine (CM) Polygonum cuspidatum (PC) on adenosine 5'-monophosphate-activated protein kinase (AMPK), forkhead box O3α (FOXO3α), Toll-like receptor-4 (TLR4), NACHT, LRR and PYD domains-containing protein 3 (NLRP3), and monocyte chemoattractant protein-1 (MCP-1) expression in a rat model of uric acid-induced renal damage and to determine the molecular mechanism. METHODS: A rat model of uric acid-induced renal damage was established, and rats were randomly divided into a model group, a positive drug group, and high-, medium-, and low-dose PC groups (n=12 per group). A normal group (n=6) was used as the control. Rats in the normal and model groups were administered distilled water (10 mL•kg-1) by intragastric infusion. Rats in the positive drug group and the high-, medium-, and low-dose PC groups were administered allopurinol (23.33 mg•kg-1), and 7.46, 3.73, or 1.87 g•kg-1•d-1 PC by intragastric infusion, respectively for 6 to 8 weeks. After the intervention, reverse transcription polymerase chain reaction, Western blot, enzyme linked immunosorbent assay, and immunohistochemistry were used to detect AMPK, FOXO3α, TLR4, NLRP3, and MCP-1 mRNA and protein levels in renal tissue or serum. RESULTS: Compared with the normal group, the mRNA transcription levels of AMPK and FOXO3α in the model group were significantly down-regulated, and protein levels of AMPKα1, pAMPKα1 and FOXO3α were significantly down-regulated at the 6th and 8th weeks (P<0.01 or P<0.05). The mRNA transcription and protein levels of TLR4, NLRP3 and MCP-1 were significantly up-regulated (P<0.01 or P<0.05). Compared with the model group, at the 6th week, the mRNA transcription levels of AMPK in the high- and medium-dose groups, and protein expression levels of AMPKα1, pAMPKα1 and FOXO3α in the high-dose PC group, AMPKα1 and pAMPKα1 in the mediumdose PC group, and pAMPKα1 in the low-dose PC group were significantly up-regulated (P<0.01 or P<0.05); the mRNA transcription and protein levels of TLR4 and NLRP3 in the 3 CM groups, and protein expression levels of MCP-1 in the medium- and low-dose PC groups were down-regulated (P<0.01 or P<0.05). At the 8th week, the mRNA transcription levels of AMPK in the high-dose PC group and FOXO3α in the medium-dose PC group, and protein levels of AMPKα1, pAMPKα1 and FOXO3α in the 3 CM groups were significantly up-regulated (P<0.01 or P<0.05); the mRNA transcription levels of TLR4 in the medium- and low-dose PC groups, NLRP3 in the high- and low-dose PC groups and MCP-1 in the medium- and low-dose PC groups, and protein expression levels of TLR4, NLRP3 and MCP-1 in the 3 CM groups were down-regulated (P<0.01 or P<0.05). CONCLUSION: PC up-regulated the expression of AMPK and its downstream molecule FOXO3α and inhibited the biological activity of TLR4, NLRP3, and MCP-1, key signal molecules in the immunoinflammatory network pathway, which may be the molecular mechanism of PC to improve hyperuricemia-mediated immunoinflflammatory metabolic renal damage.

Backstepping Sliding Mode Control for Radar Seeker Servo System Considering Guidance and Control System.

This paper investigates the design of a missile seeker servo system combined with a guidance and control system. Firstly, a complete model containing a missile seeker servo system, missile guidance system, and missile control system (SGCS) was creatively proposed. Secondly, a designed high-order tracking differentiator (HTD) was used to estimate states of systems in real time, which guarantees the feasibility of the designed algorithm. To guarantee tracking precision and robustness, backstepping sliding-mode control was adopted. Aiming at the main problem of projectile motion disturbance, an adaptive radial basis function neural network (RBFNN) was proposed to compensate for disturbance. Adaptive RBFNN especially achieves online adjustment of residual error, which promotes estimation precision and eliminates the "chattering phenomenon". The boundedness of all signals, including estimation error of high-order tracking differentiator, was especially proved via the Lyapunov stability theory, which is more rigorous. Finally, in considered scenarios, line of sight angle (LOSA)-tracking simulations were carried out to verify the tracking performance, and a Monte Carlo miss-distance simulation is presented to validate the effectiveness of the proposed method.

Tracking control of air-breathing hypersonic vehicles with non-affine dynamics via improved neural back-stepping design.

This study considers the design of a new back-stepping control approach for air-breathing hypersonic vehicle (AHV) non-affine models via neural approximation. The AHV's non-affine dynamics is decomposed into velocity subsystem and altitude subsystem to be controlled separately, and robust adaptive tracking control laws are developed using improved back-stepping designs. Neural networks are applied to estimate the unknown non-affine dynamics, which guarantees the addressed controllers with satisfactory robustness against uncertainties. In comparison with the existing control methodologies, the special contributions are that the non-affine issue is handled by constructing two low-pass filters based on model transformations, and virtual controllers are treated as intermediate variables such that they aren't needed for back-stepping designs any more. Lyapunov techniques are employed to show the uniformly ultimately boundedness of all closed-loop signals. Finally, simulation results are presented to verify the tracking performance and superiorities of the investigated control strategy.

[Effects of Tengmei Decoction on the PPAR-y/NF-KB Signaling Pathway in Synovium of Collagen-in- duced Arthritis Rats].

Objective To observe the effects of Tengmei Decoction (TMD) on the expressions of peroxisome proliferator activated receptor gamma (PPARγ) , nuclear factor kappa B (NF-κB) , and IL- 17 in synovium of collagen-induced arthritis (CIA) rats, and to study its molecular mechanismpf. inhibi- ting synovial immune inflammatory injuries. Methods CIA model was established in Sprague-Dawley rats. Successfully modeled rats were randomly divided into the model group, the positive drug ,oup, high and low dose TMD groups, 6 in each group. Besides, a normal group was set up (n =6). Deionized water (10 mL . kg⁻¹ . d⁻¹) was administrated to rats in the normal group and the model group by gastro- gavage. Leflunomide (1. 87 mg . kg ⁻¹ . d ⁻¹) was administrated to rats in the positive drug group by gastro- gavage. TMD (31. 8 g crude drugs . kg ⁻¹ . d ⁻¹ and 15. 9 g crude drugs . kg ⁻¹ . d ⁻¹) was administrated to rats in high and low dose TMD groups respectively by gastrogavage. The intervention lasted for 12 suc- cessive weeks. Protein and mRNA levels of PPARy, P65, and IL-17 were detected at the end of intervention. Results Compared with the normal group, mRNA and protein expression levels of PPARγ, P65, and IL-17 were up-regulated in the model group (P <0. 01). Compared with the model group, PPARγ pro- tein expression level was up-regulated, mRNA and protein expression levels of P65 and IL-17 were down-regulated in high dose TMD group (P <0. 01). mRNA and protein expression levels of PPARγ were up-regulated, mRNA and protein expression levels of P65 and IL-17 were down-regulated in the positive drug group and low dose TMD group (P <0. 01). Conclusions TMD could ameliorate pathological damage of joint synovium , and inhibit expressions of immune inflammatory factors.

Novel prescribed performance neural control of a flexible air-breathing hypersonic vehicle with unknown initial errors.

A novel prescribed performance neural controller with unknown initial errors is addressed for the longitudinal dynamic model of a flexible air-breathing hypersonic vehicle (FAHV) subject to parametric uncertainties. Different from traditional prescribed performance control (PPC) requiring that the initial errors have to be known accurately, this paper investigates the tracking control without accurate initial errors via exploiting a new performance function. A combined neural back-stepping and minimal learning parameter (MLP) technology is employed for exploring a prescribed performance controller that provides robust tracking of velocity and altitude reference trajectories. The highlight is that the transient performance of velocity and altitude tracking errors is satisfactory and the computational load of neural approximation is low. Finally, numerical simulation results from a nonlinear FAHV model demonstrate the efficacy of the proposed strategy.

High-order tracking differentiator based adaptive neural control of a flexible air-breathing hypersonic vehicle subject to actuators constraints.

In this paper, an adaptive neural controller is exploited for a constrained flexible air-breathing hypersonic vehicle (FAHV) based on high-order tracking differentiator (HTD). By utilizing functional decomposition methodology, the dynamic model is reasonably decomposed into the respective velocity subsystem and altitude subsystem. For the velocity subsystem, a dynamic inversion based neural controller is constructed. By introducing the HTD to adaptively estimate the newly defined states generated in the process of model transformation, a novel neural based altitude controller that is quite simpler than the ones derived from back-stepping is addressed based on the normal output-feedback form instead of the strict-feedback formulation. Based on minimal-learning parameter scheme, only two neural networks with two adaptive parameters are needed for neural approximation. Especially, a novel auxiliary system is explored to deal with the problem of control inputs constraints. Finally, simulation results are presented to test the effectiveness of the proposed control strategy in the presence of system uncertainties and actuators constraints.

Self-driven one-step oil removal from oil spill on water via selective-wettability steel mesh.

Marine oil spills seriously endanger sea ecosystems and coastal environments, resulting in a loss of energy resources. Environmental and economic demands emphasize the need for new methods of effectively separating oil-water mixtures, while collecting oil content at the same time. A new surface-tension-driven, gravity-assisted, one-step, oil-water separation method is presented for sustained filtration and collection of oil from a floating spill. A benchtop prototype oil collection device uses selective-wettability (superhydrophobic and superoleophilic) stainless steel mesh that attracts the floating oil, simultaneously separating it from water and collecting it in a container, requiring no preseparation pumping or pouring. The collection efficiencies for oils with wide ranging kinematic viscosities (0.32-70.4 cSt at 40 °C) are above 94%, including motor oil and heavy mineral oil. The prototype device showed high stability and functionality over repeated use, and can be easily scaled for efficient cleanup of large oil spills on seawater. In addition, a brief consolidation of separation requirements for oil-water mixtures of various oil densities is presented to demonstrate the versatility of the material system developed herein.