Robust Fault Tolerant Control for Discrete-Time Dynamic Systems With Applications to Aero Engineering Systems

Unexpected faults in actuators and sensors may degrade the reliability and safety of aero engineering systems. Therefore, there is motivation to develop integrated fault tolerant control techniques with applications to aero engineering systems. In this paper, discrete-time dynamic systems, in the presence of simultaneous actuator/sensor faults, partially decoupled unknown input disturbances, and sensor noises, are investigated. A jointly state/fault estimator is formulated by integrating an unknown input observer, augmented system approach, and optimization algorithm. Unknown input disturbances can be either decoupled by an unknown input observer, or attenuated by a linear matrix inequality optimization, enabling the estimation error to be input-to-state stable. Estimator-based signal compensation is then implemented to mitigate adverse effects from the unanticipated actuator and sensor faults. A pre-designed controller, which maintains normal system behaviors under a fault-free scenario, is allowed to work along with the presented fault tolerant mechanism of the signal compensations. The fault-tolerant closed-loop system can be ensured to mitigate the effects from the faults, guarantee the input-to-state stability, and satisfy the required robustness performance. The proposed fault estimation and fault tolerant control methods are developed for both discrete-time linear and discrete-time Lipschitz nonlinear systems. Finally, the proposed techniques are applied to a jet engine system and a flight control system for simulation validation

Inhibition of APE1/Ref-1 Redox Activity with APX3330 Blocks Retinal Angiogenesis in vitro and in vivo

This study examines the role of APE1/Ref-1 in the retina and its potential as a therapeutic target for inhibiting retinal angiogenesis. APE1/Ref-1 expression was quantified by Western blot. The role of APE1/Ref-1 redox function in endothelial cell in vitro angiogenesis was examined by treating retinal vascular endothelial cells (RVECs) with APX3330, a small molecule inhibitor of APE1/Ref-1 redox activity. In vitro methods included a proliferation assay, a transwell migration assay, a Matrigel tube formation assay, and a Real-Time Cell Analysis (RTCA) using the xCELLigence System. In vivo functional studies of APE1/Ref-1 were carried out by treating very low density lipoprotein (VLDL) receptor knockout mice (Vldlr−/−) with intravitreal injection of APX3330, and subsequent measurement of retinal angiomatous proliferation (RAP)-like neovascularization for one week. APE1/Ref-1 was highly expressed in the retina and in RVECs and pericytes in mice. APX3330 (1–10 μM) inhibited proliferation, migration and tube formation of RVECs in vitro in a dose-dependent manner. Vldlr−/− RVECs were more sensitive to APX3330 than wild-type RVECs. In Vldlr−/− mice, a single intravitreal injection of APX3330 at the onset of RAP-like neovascularization significantly reduced RAP-like neovascularization development. APE1/Ref-1 is expressed in retinal vascular cells. APX3330 inhibits RVEC angiogenesis in vitro and significantly reduces RAP-like neovascularization in Vldlr−/− mice. These data support the conclusion that APE1/Ref-1 redox function is required for retinal angiogenesis. Thus, APE1/Ref-1 may have potential as a therapeutic target for treating neovascular age-related macular degeneration and other neovascular diseases

IRF2BP2 attenuates gestational diabetes mellitus by activating AMPK signaling

Purpose: To investigate the role of interferon regulatory factor 2 binding protein 2 (IRF2BP2) in gestational diabetes mellitus (GDM). Methods: Mice were injected intraperitoneally with streptozotocin to establish a model of GDM and then subjected to intraperitoneal glucose tolerance test (IPGTT) and intraperitoneal insulin tolerance test (IPITT) to determine glucose and insulin tolerances. Lipid metabolism was evaluated by enzyme-linked immunosorbent assay (ELISA). The histomorphology of pancreatic islets was assessed by hematoxylin and eosin staining. Results: IRF2BP2 was downregulated in pancreatic tissues of mice with GDM (p < 0.001). Mice in GDM group showed higher blood glucose levels than those in normal pregnancy group. However, overexpression of IRF2BP2 reduced glucose and insulin levels in mice with GDM. Overexpression of IRF2BP2 increased the level of high-density lipoprotein (HDL) and reduced triglyceride (TG), total cholesterol (TC), and low-density lipoprotein (LDL) levels in mice with GDM (p < 0.001). The histopathological changes in the islets of mice with GDM were also ameliorated by overexpression of IRF2BP2. Overexpression of IRF2BP2 reduced IL-6, IL-1β, and TNF-α levels and increased protein expression of p-AMPK in mice with GDM. Conclusion: IRF2BP2 ameliorates the outcomes of GDM and suppressed inflammation in mice with GDM through activation of AMPK signaling. Thus, IRF2BP2 is a potential therapeutic strategy for the management of GDM. Keywords: IRF2BP2; inflammation; gestational diabetes mellitus; AMPK; mice; insulin toleranc

Actuator and Sensor Fault Classification for Wind Turbine Systems Based on Fast Fourier Transform and Uncorrelated Multi-Linear Principal Component Analysis Techniques

In response to the high demand of the operation reliability and predictive maintenance, health monitoring and fault diagnosis and classification have been paramount for complex industrial systems (e.g., wind turbine energy systems). In this study, data-driven fault diagnosis and fault classification strategies are addressed for wind turbine energy systems under various faulty scenarios. A novel algorithm is addressed by integrating fast Fourier transform and uncorrelated multi-linear principal component analysis techniques in order to achieve effective three-dimensional space visualization for fault diagnosis and classification under a variety of actuator and sensor faulty scenarios in 4.8 MW wind turbine benchmark systems. Moreover, comparison studies are implemented by using multi-linear principal component analysis with and without fast Fourier transform, and uncorrelated multi-linear principal component analysis with and without fast Fourier transformation data pre-processing, respectively. The effectiveness of the proposed algorithm is demonstrated and validated via the wind turbine benchmark

Effects of Methotrexate on Plasma Cytokines and Cardiac Remodeling and Function in Postmyocarditis Rats

Excessive immune activation and inflammatory mediators may play a critical role in the pathogenesis of chronic heart failure. Methotrexate is a commonly used anti-inflammatory and immunosuppressive drug. In this study, we used a rat model of cardiac myosin-induced experimental autoimmune myocarditis to investigate the effects of low-dose methotrexate (0.1 mg/kg/d for 30 d) on the plasma level of cytokines and cardiac remodeling and function. Our study showed that levels of tumor necrosis factor-(TNF-)alpha and interleukin-6 (IL-6) are significantly increased in postmyocarditis rats, compared with the control rats. Methotrexate treatment reduced the plasma levels of TNF-alpha and IL-6 and increased IL-10 level, compared to saline treatment. In addition, postmyocarditis rats showed significant cardiac fibrosis characterized by increased myocardial collagen volume fraction, perivascular collagen area, and the ratio of collagen type I to type III, compared with the control rats. However, MTX treatment not only markedly attenuated cardiac fibrosis, diminished the left ventricular end-diastolic dimension, but also increased the left ventricular ejection fraction and fractional shortening. Collectively, these results suggest that low-dose methotrexate has ability to regulate inflammatory responses and improves cardiac function and hence contributes to prevent the development of postmyocarditis dilated cardiomyopathy

Study on the law of residual deformation in mining subsidence area and its influence on the safety of ground buildings

After the mining subsidence area reaches the stable state of surface movement, due to the continuous existence of the mutual extrusion and activation state between rock strata, the movement of particles, rock creep, and soil compression will affect the surface movement in the long-term stability, thereby threatening the safety and stability of the above ground buildings. In order to study the deformation law of rock strata movement and surface displacement after the mining subsidence area is stabilized, establish a ground deformation model caused by mining, explore the characteristics of ground movement and deformation under the action of building loads, design a similar material simulation experiment, record the ground movement changes within 378 days after the mining is completed, after the settlement is stabilized, apply equivalent loads of 10–30 floors to the model at different locations, and study various surface deformation data, Analyze the change rule. In order to quantitatively analyze the impact of residual deformation of goaf on buildings under building load, the D5 gate area of Tangshan World Horticultural Exposition in mining subsidence area is taken as an example to calculate the ground settlement value and other deformation data using probability analysis method, and the Kelvin model in rock mechanics is introduced in terms of the duration of residual deformation. The calculation results are close to the actual measured values, and the impact of residual deformation on the proposed building is analyzed

A novel folate-modified self-microemulsifying drug delivery system of curcumin for colon targeting

Lin Zhang1*, Weiwei Zhu2*, Chunfen Yang1, Hongxia Guo1, Aihua Yu1, Jianbo Ji3, Yan Gao1, Min Sun1, Guangxi Zhai11Department of Pharmaceutical Engineering, College of Pharmacy, Shandong University, Jinan; 2Department of Pharmacy, Yantai Yuhuangding Hospital, Yantai; 3Department of Pharmacology, College of Pharmacy, Shandong University, Jinan, China*These authors contributed equally to the workBackground: The objective of this study was to prepare, characterize, and evaluate a folate-modified self-microemulsifying drug delivery system (FSMEDDS) with the aim to improve the solubility of curcumin and its delivery to the colon, facilitating endocytosis of FSMEDDS mediated by folate receptors on colon cancer cells.Methods: Ternary phase diagrams were constructed in order to obtain the most efficient self-emulsification region, and the formulation of curcumin-loaded SMEDDS was optimized by a simplex lattice experiment design. Then, three lipophilic folate derivatives (folate-polyethylene glycol-distearoylphosphatidylethanolamine, folate-polyethylene glycol-cholesteryl hemisuccinate, and folate-polyethylene glycol-cholesterol) used as a surfactant were added to curcumin-loaded SMEDDS formulations. An in situ colon perfusion method in rats was used to optimize the formulation of FSMEDDS. Curcumin-loaded FSMEDDS was then filled into colon-targeted capsules and the in vitro release was investigated. Cytotoxicity studies and cellular uptake studies was used in this research.Results: The optimal formulation of FSMEDDS obtained with the established in situ colon perfusion method in rats was comprised of 57.5% Cremophor® EL, 32.5% Transcutol® HP, 10% Capryol™ 90, and a small amount of folate-polyethylene glycol-cholesteryl hemisuccinate (the weight ratio of folate materials to Cremophor EL was 1:100). The in vitro release results indicated that the obtained formulation of curcumin could reach the colon efficiently and release the drug immediately. Cellular uptake studies analyzed with fluorescence microscopy and flow cytometry indicated that the FSMEDDS formulation could efficiently bind with the folate receptors on the surface of positive folate receptors cell lines. In addition, FSMEDDS showed greater cytotoxicity than SMEDDS in the above two cells.Conclusion: FSMEDDS-filled colon-targeted capsules are a potential carrier for colon delivery of curcumin.Keywords: curcumin, SMEDDS, folate receptor, colon targetin

Data-Driven Fault Classification for Non-Inverting Buck–Boost DC–DC Power Converters Based on Expectation Maximisation Principal Component Analysis and Support Vector Machine Approaches

Data-driven fault classification for power converter systems has been taking more into considerations in power electronics, machine drives, and electric vehicles. It is challenging to classify the different topologies of faults in the real time monitoring control systems. In this paper, a data-driven and supervised machine learning-based fault classification technique is adopted by combining and consolidating with Expectation Maximisation Principal Component Analysis (EMPCA) and Support Vector Machine (SVM) to substantiate the availability of fault classification. The proposed methodology is applied to the non-inverting Buck–Boost DC–DC power converter systems subjected to the incipient fault and serious fault, respectively. Finally, the feasibility of the approach is validated by intensive simulations and comparison studies