CCL28 Induces Mucosal Homing of HIV-1-Specific IgA-Secreting Plasma Cells in Mice Immunized with HIV-1 Virus-Like Particles

Mucosae-associated epithelial chemokine (MEC or CCL28) binds to CCR3 and CCR10 and recruits IgA-secreting plasma cells (IgA-ASCs) in the mucosal lamina propria. The ability of this chemokine to enhance migration of IgA-ASCs to mucosal sites was assessed in a mouse immunization model using HIV-1IIIB Virus-like particles (VLPs). Mice receiving either HIV-1IIIB VLPs alone, CCL28 alone, or the irrelevant CCL19 chemokine were used as controls. Results showed a significantly increased CCR3 and CCR10 expression on CD19+ splenocytes of HIV-1IIIB VPL-CCL28-treated mice. HIV-1 Env-specific IFN-γ, IL-4 and IL-5 production, total IgA, anti-Env IgA as well as gastro-intestinal mucosal IgA-secreting plasma cells were also significantly augmented in these mice. Notably, sera and vaginal secretions from HIV-1IIIB VLP-CCL28-treated mice exhibited an enhanced neutralizing activity against both a HIV-1/B-subtype laboratory strain and a heterologous HIV-1/C-subtype primary isolate. These data suggest that CCL28 could be useful in enhancing the IgA immune response that will likely play a pivotal role in prophylactic HIV vaccines

Sensor Fault Tolerant Control for Aircraft Engines Using Sliding Mode Observer

This paper investigated the problem of fault estimation and fault-tolerant control (FTC) against sensor faults for aircraft engines. By applying a second order sliding mode observer (SOSMO) to the engine on-board model, estimations of the system states and sensor faults could be obtained simultaneously, and the result of state estimation was unaffected when using the reduced-order sliding mode system. This result gave rise to the idea to use the estimated states instead of physical sensor signal in the engine close-loop feedback control. Unlike those using passive FTC concepts, the tradeoff between control performance and robustness was inherently unnecessary. Meanwhile, compared to active FTC approaches, because any classical state/output feedback method can be directly applied to the proposed scheme without any controller reconfiguration, extra undesired dynamic responses caused by parameter reconfiguring were avoided. In this paper, the proposed FTC scheme was tested on the nonlinear model of a civil aircraft turbofan engine, and numerical simulation results showed satisfactory sensor FTC performance

Health Parameter Estimation with Second-Order Sliding Mode Observer for a Turbofan Engine

In this paper the problem of health parameter estimation in an aero-engine is investigated by using an unknown input observer-based methodology, implemented by a second-order sliding mode observer (SOSMO). Unlike the conventional state estimator-based schemes, such as Kalman filters (KF) and sliding mode observers (SMO), the proposed scheme uses a “reconstruction signal” to estimate health parameters modeled as artificial inputs, and is not only applicable to long-time health degradation, but reacts much quicker in handling abrupt fault cases. In view of the inevitable uncertainties in engine dynamics and modeling, a weighting matrix is created to minimize such effect on estimation by using the linear matrix inequalities (LMI). A big step toward uncertainty modeling is taken compared with our previous SMO-based work, in that uncertainties are considered in a more practical form. Moreover, to avoid chattering in sliding modes, the super-twisting algorithm (STA) is employed in observer design. Various simulations are carried out, based on the comparisons between the KF-based scheme, the SMO-based scheme in our earlier research, and the proposed method. The results consistently demonstrate the capabilities and advantages of the proposed approach in health parameter estimation

Robust Sensor Fault Reconstruction via a Bank of Second-Order Sliding Mode Observers for Aircraft Engines

This paper deals with sensor faults of aircraft engines under uncertainties using a bank of second-order sliding mode observers (SMOs). In view of the effect of inevitable uncertainties on the fault reconstruction, a method combining H ∞ concepts and linear matrix inequalities (LMIs) is proposed, in which a scaling matrix is designed to minimize the gain of the transfer function matrix from uncertainty to reconstruction. However, robust design generally requires that engine outputs outnumber faults. In the case where the above-mentioned requirement is not satisfied, a bank of sliding mode observers is proposed to ensure the degrees of freedom available in robust design. In specific, each observer corresponds to a certain sensor with the hypothesis that the corresponding sensor will not have faults, to create one degree of design freedom for each observer. After fault occurrence, a large estimation error is expected in the observers with wrong hypothesis, and then a logic module is designed to detect sensor faults and obtain the optimal robust sensor fault reconstruction at the same time. The proposed approach is applied to a nonlinear engine component-level-model (CLM) simulation platform, and a numerical study is performed to validate the effectiveness

Gas-Path Health Estimation for an Aircraft Engine Based on a Sliding Mode Observer

Aircraft engine gas-path health monitoring (GPHM) plays a critical role in engine health management (EHM). Among model-based approaches, the Kalman filter (KF) has been widely employed in GPHM. The main shortcoming of KF-based scheme lies in the lack of robustness against uncertainties. To enhance robustness, this paper describes a new GPHM architecture using a sliding mode observer (SMO). The convergence of the error system in uncertainty-existing circumstances is demonstrated, and the proposed method is developed to estimate components’ performance degradations regardless of modeling uncertainties. Simulations using a nonlinear model of a turbofan engine are presented, in which health monitoring problems are handled by the KF and the SMO, respectively. Results indicate the proposed approach possesses better diagnostic performance compared to the KF-based scheme, and the SMO shows its strong robustness and great potential to be applied to GPHM

Growth of hafnium dioxide thin films via metal-organic chemical vapor deposition

Metal-organic chemical vapour deposition (MOCVD) is a key technique for depositing thin solid film materials for use in important technological applications. To obtain thin films of the desired standard, it is essential to design volatile, reactive and thermally stable precursors. A metal-organic precursor consisting of Hf with excellent vaporization characteristics and low decomposition temperature has been reported. Hafnium dioxide thin films on a Mo substrate were obtained via thermal MOCVD using Hafnium(IV) acetylacetonate(Hf(acac) _4 ) in a horizontal cold-wall reactor. The Hf(acac) _4 precursor was synthesized from HfCl _4 and Hthd in methanol. Hf(acac) _4 was characterized using elemental analysis and infrared spectroscopy. The thermal decomposition properties were studied using thermogravimetric analysis under a nitrogen atmosphere. The results showed that Hf(acac) _4 was completely volatised at 245 °C. The thin films products were investigated using x-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). The results from these measurements revealed that the main crystalline phase was the monoclinic phase, the surface consists of hafnium and oxygen and the morphology was densely packed and composed of visible grains