•We provide a life cycle cost analysis for a degrading system.•We consider a multi-dimensional degradation process.•We consider the influence of degradation dependence and environmental variations.
...This paper presents a life cycle cost model for systems subject to multiple dependent degradation processes and environmental influence. Different from most existing studies that assume an infinite time horizon for cost analysis, we evaluate the life cycle cost within a finite horizon. The system is subject to multiple degradation processes, among which the dependence is described via copula. In addition to the stochastic dependence of the degradation processes, the health condition of the system is influenced by the operating environment. The environmental influence on the system condition lies in two aspects: It accelerates or decelerates the degradation processes and meanwhile leads to a random failure threshold. System reliability considering multiple dependent degradation processes and environmental influence is assessed as the first step, followed by the life cycle cost analysis. A numerical example is presented to illustrate the proposed model.
In existing neural network (NN) learning control methods, the trajectory of NN inputs must be recurrent to satisfy a stringent condition termed persistent excitation (PE) so that NN parameter ...convergence is obtainable. This paper focuses on command-filtered backstepping adaptive control for a class of strict-feedback nonlinear systems with functional uncertainties, where an NN composite learning technique is proposed to guarantee convergence of NN weights to their ideal values without the PE condition. In the NN composite learning, spatially localized NN approximation is employed to handle functional uncertainties, online historical data together with instantaneous data are exploited to generate prediction errors, and both tracking errors and prediction errors are employed to update NN weights. The influence of NN approximation errors on the control performance is also clearly shown. The distinctive feature of the proposed NN composite learning is that NN parameter convergence is guaranteed without the requirement of the trajectory of NN inputs being recurrent. Illustrative results have verified effectiveness and superiority of the proposed method compared with existing NN learning control methods.
An analytical three-phase induction machine model is proposed, derived, and validated in this paper. This model is capable for arbitrary qd0-frame analysis and core loss estimation at both line-fed ...and inverter-fed situations. Detailed model-based machine copper and core loss estimations are presented. A simulation verification of the model consistency is given under a changing load profile in MATLAB/Simulink. Then, the model is verified comprehensively using three induction machines (1.5 HP, 3 HP, and 10 HP), where the model is proved to be scalable, and to provide excellent machine loss estimation in line-fed situation and inverter-fed situation with machine input line filters, as well as in the flux-weakening region. Finally, a series of sensitivity tests of the model parameters are performed and the effects of the parameters on the machine losses are discussed. It is believed that the proposed model will be beneficial for various qd0-frame model-based research works of three-phase induction machines.
Ischemic stroke (IS) is a major cause of disability and death in adults, and the immune response plays an indispensable role in its pathological process. After the onset of IS, an inflammatory storm, ...with the infiltration and mobilization of the mononuclear phagocyte system (MPS), is triggered in the brain. Microglia are rapidly activated in situ, followed by waves of circulating monocytes into the ischemic area. Activated microglia and monocytes/macrophages are mainly distributed in the peri‐infarct area. These cells have similar morphology and functions, such as secreting cytokines and phagocytosis. Previously, the presence of the MPS was considered a marker of an exacerbated inflammatory response that contributes to brain damage. However, recent studies have suggested a rather complicated role of the MPS in IS. Here, we reviewed articles focusing on various functions of the MPS among different phases of IS, including recruitment, polarization, phagocytosis, angiogenesis, and interaction with other types of cells. Moreover, due to the characteristics of the MPS, we also noted clinical research addressing alterations in the MPS as potential biomarkers for IS patients for the purposes of predicting prognosis and developing novel therapeutic strategies.
Pathophysiological effects of mononuclear phagocyte system MPS in ischemic stroke.
The activation of the immune system and the onset of pro- and anti-inflammatory responses play crucial roles in the pathophysiological processes of ischaemic stroke (IS). CD4
regulatory T (Treg) ...cells is the main immunosuppressive cell population that is studied in the context of peripheral tolerance, autoimmunity, and the development of chronic inflammatory diseases. In recent years, more studies have focused on immune modulation after IS, and Treg cells have been demonstrated to be essential in the remission of inflammation, nerve regeneration, and behavioural recovery. However, the exact effects of Treg cells in the context of IS remain controversial, with some studies suggesting a negative correlation with stroke outcomes. In this review, we aim to provide a comprehensive overview of the current understanding of Treg cell involvement in post-stroke homeostasis. We summarized the literature focusing on the temporal changes in Treg cell populations after IS, the mechanisms of Treg cell-mediated immunomodulation in the brain, and the potential of Treg cell-based therapies for treatment. The purposes of the current article are to address the importance of Treg cells and inspire more studies to help physicians, as well as scientists, understand the whole map of immune responses during IS.
The proper monitoring of quality-related but hard-to-measure variables is currently one of the bottlenecks limiting the safe and efficient operations of industrial processes. This paper proposes a ...novel ensemble learning algorithm by coordinating global and local Gaussian process regression (GPR) models, and this algorithm is able to capture global and local process behaviours for accurate prediction and timely process monitoring. To further address the deterioration in predictions when using the off-line training and online testing strategy, this paper proposes an adaptive ranking strategy to perform ensemble learning for the sub-GPR models. In this adaptive strategy, we use the moving-window technique to rank and select several of the best sub-model predictions and then average them together to make the final predictions. Last but not least, the least absolute shrinkage and selection operator (Lasso) works together with factor analysis (FA) in a two-step variable selection method to remove under-correlated model input variables in the first stage and to compress over-correlated model input variables in the second stage. The proposed prediction model is validated in two real wastewater treatment plants (WWTPs) with stationary and nonstationary behaviours. The results show that the proposed methodology achieves better performance than other standard methods in the context of their predictions of quality-related variables.
•Global and local GPR models are implemented for ensemble learning.•Bootstrap is used to stimulate the training datasets and model hyper-parameters.•Moving-window technique is used to rank and to select several best sub-model predictions.•A two-stage variable selection strategy, termed as Lasso-FA, is proposed.•Methodologies were validated through simulated and real data sets.
Improving efficacy of oncolytic virotherapy remains challenging due to difficulty increasing specificity and immune responses against cancer and limited understanding of its population dynamics. ...Here, we construct programmable and modular synthetic gene circuits to control adenoviral replication and release of immune effectors selectively in hepatocellular carcinoma cells in response to multiple promoter and microRNA inputs. By performing mouse model experiments and computational simulations, we find that replicable adenovirus has a superior tumor-killing efficacy than non-replicable adenovirus. We observe a synergistic effect on promoting local lymphocyte cytotoxicity and systematic vaccination in immunocompetent mouse models by combining tumor lysis and secretion of immunomodulators. Furthermore, our computational simulations show that oncolytic virus which encodes immunomodulators can exert a more robust therapeutic efficacy than combinatorial treatment with oncolytic virus and immune effector. Our results provide an effective strategy to engineer oncolytic adenovirus, which may lead to innovative immunotherapies for a variety of cancers.
The DNA methyltransferase Dnmt3a has high expression in terminally differentiated macrophages; however, its role in innate immunity remains unknown. Here we report that deficiency in Dnmt3a ...selectively impaired the production of type I interferons triggered by pattern-recognition receptors (PRRs), but not that of the proinflammatory cytokines TNF and IL-6. Dnmt3a-deficient mice exhibited enhanced susceptibility to viral challenge. Dnmt3a did not directly regulate the transcription of genes encoding type I interferons; instead, it increased the production of type I interferons through an epigenetic mechanism by maintaining high expression of the histone deacetylase HDAC9. In turn, HDAC9 directly maintained the deacetylation status of the key PRR signaling molecule TBK1 and enhanced its kinase activity. Our data add mechanistic insight into the crosstalk between epigenetic modifications and post-translational modifications in the regulation of PRR signaling and activation of antiviral innate immune responses.
This paper presents the analysis and control of a multilevel modular converter (MMC)-based HVDC transmission system under three possible single-line-to-ground fault conditions, with special focus on ...the investigation of their different fault characteristics. Considering positive-, negative-, and zero-sequence components in both arm voltages and currents, the generalized instantaneous power of a phase unit is derived theoretically according to the equivalent circuit model of the MMC under unbalanced conditions. Based on this model, a novel double-line frequency dc-voltage ripple suppression control is proposed. This controller, together with the negative- and zero-sequence current control, could enhance the overall fault-tolerant capability of the HVDC system without additional cost. To further improve the fault-tolerant capability, the operation performance of the HVDC system with and without single-phase switching is discussed and compared in detail. Simulation results from a three-phase MMC-HVDC system generated with MATLAB/Simulink are provided to support the theoretical analysis and proposed control schemes.
Abstract
This paper proposes a comprehensive control strategy for a battery energy storage system (BESS) participating in primary frequency modulation (FM) while considering the state of charge (SOC) ...recovery. On the one hand, when the frequency fluctuations are outside the dead zone of the FM, variable coefficient virtual sag control and variable coefficient virtual inertia control are coordinated for more accurate primary FM. Also, an assisted FM strategy is proposed, where the temporal alignment of assisted FM is determined by the regional segmentation of the frequency deviation and SOC, and it enables the BESS to recover SOC concurrently during its involvement in primary FM. On the other hand, when the frequency fluctuations are inside the dead zone of the FM, typical S‐type functions are deployed to dynamically establish the mutual constraints relationships of SOC recovery demand coefficient and frequency deviation. Subsequently, the recovery control coefficients are derived, and accordingly, a SOC recovery strategy is proposed. Finally, simulation results verify the efficacy of the proposed control strategy in the grid primary FM system and demonstrate that the strategy expedites the SOC recovery and concurrently diminishes the conventional unit output.
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