One-Shot Parameter Identification of the Thevenin's Model for Batteries: Methods and Validation

Parameter estimation is of foundational importance for various model-based battery management tasks, including charging control, state-of-charge estimation and aging assessment. However, it remains a challenging issue as the existing methods generally depend on cumbersome and time-consuming procedures to extract battery parameters from data. Departing from the literature, this paper sets the unique aim of identifying all the parameters offline in a one-shot procedure, including the resistance and capacitance parameters and the parameters in the parameterized function mapping from the state-of-charge to the open-circuit voltage. Considering the well-known Thevenin's battery model, the study begins with the parameter identifiability analysis, showing that all the parameters are locally identifiable. Then, it formulates the parameter identification problem in a prediction-error-minimization framework. As the non-convexity intrinsic to the problem may lead to physically meaningless estimates, two methods are developed to overcome this issue. The first one is to constrain the parameter search within a reasonable space by setting parameter bounds, and the other adopts regularization of the cost function using prior parameter guess. The proposed identifiability analysis and identification methods are extensively validated through simulations and experiments

Distributed topology identification algorithm of distribution network based on neighboring interaction

Intelligent distributed control and protection is a promising route towards flexible and safety operation of distribution network with widespread access of distributed energy resources A fundamental premise of the distributed decision-making is that each smart terminal can identify the topological structure of the feeder and track its changes. This paper proposes a distributed topology identification algorithm with high fault tolerance based on peer-to-peer communication. The smart terminal units (STU) installed on the nodes can dynamiclly track and identify the network topology through local measurement and information exchange with neighboring STUs. The proposed algorithm combines local measurement mutual check with contralateral connectivity predictive correction, and significantly improves the tolerance of measurement errors in topology identification. Test examples are presented to verify the effectiveness of the method

A Semiparametrically Efficient Estimator of the Time‐Varying Effects for Survival Data with Time‐Dependent Treatment

The timing of a time‐dependent treatment—for example, when to perform a kidney transplantation—is an important factor for evaluating treatment efficacy. A naïve comparison between the treated and untreated groups, while ignoring the timing of treatment, typically yields biased results that might favour the treated group because only patients who survive long enough will get treated. On the other hand, studying the effect of a time‐dependent treatment is often complex, as it involves modelling treatment history and accounting for the possible time‐varying nature of the treatment effect. We propose a varying‐coefficient Cox model that investigates the efficacy of a time‐dependent treatment by utilizing a global partial likelihood, which renders appealing statistical properties, including consistency, asymptotic normality and semiparametric efficiency. Extensive simulations verify the finite sample performance, and we apply the proposed method to study the efficacy of kidney transplantation for end‐stage renal disease patients in the US Scientific Registry of Transplant Recipients.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134221/1/sjos12196_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134221/2/sjos12196.pd

Effect of Multifrequency Ultrasonic-Assisted Vacuum Cooking on the Muscle Fiber Structure and Water-Holding Capacity of Stewed Marinated Beef

The effect of multifrequency ultrasonic-assisted vacuum cooking on the muscle fiber structure and water-holding capacity of stewed marinated beef was studied. Changes in the muscle fiber structure, texture properties and moisture content of stewed marinated beef prepared from beef shank under different ultrasonic frequencies (40/52/68, 40/52, 40/68, 52/68, 40, 52, 68 and 0 kHz) were measured. The results showed that with increasing the number of ultrasound frequencies, myofibrillar fragmentation index (MFI), the contents of β-turn and random coil increased, and the texture attribute of elasticity tended to increase, while the contents of α-helix and β-sheet decreased, and so did the hardness, chewiness, and cohesiveness of stewed marinated beef. Meanwhile, the solubility of connective tissue on the surface of muscle fibers increased, the separation and fracture of muscle fibers became more apparent. Low field-nuclear magnetic resonance (LF-NMR) results showed that ultrasound treatment caused a leftward shift of the transverse relaxation time (T2) and shortened it, thus changing the water distribution. As the number of ultrasonic frequencies increased, the shifting range of transverse relaxation time to the left increased, and the contents of bound water and free water also increased, while the content of quasi-bound water correspondingly decreased. Cooking loss was significantly lower in the triple-frequency group than in the dual-frequency and single-frequency groups, while the product yield showed an opposite trend, the highest value being found in the triple-frequency group. In summary, ultrasound treatment destroyed the muscle fiber structure and improved the water-holding capacity of stewed beef; the more the number of ultrasonic frequencies, the more pronounced the effect

Chimeric Antigen Receptor (CAR) Treg: A Promising Approach to Inducing Immunological Tolerance

Cellular therapies with polyclonal regulatory T-cells (Tregs) in transplantation and autoimmune diseases have been carried out in both animal models and clinical trials. However, The use of large numbers of polyclonal Tregs with unknown antigen specificities has led to unwanted effects, such as systemic immunosuppression, which can be avoided via utilization of antigen-specific Tregs. Antigen-specific Tregs are also more potent in suppression than polyclonal ones. Although antigen-specific Tregs can be induced in vitro, these iTregs are usually contaminated with effector T cells during in vitro expansion. Fortunately, Tregs can be efficiently engineered with a predetermined antigen-specificity via transfection of viral vectors encoding specific T cell receptors (TCRs) or chimeric antigen receptors (CARs). Compared to Tregs engineered with TCRs (TCR-Tregs), CAR-modified Tregs (CAR-Tregs) engineered in a non-MHC restricted manner have the advantage of widespread applications, especially in transplantation and autoimmunity. CAR-Tregs also are less dependent on IL-2 than are TCR-Tregs. CAR-Tregs are promising given that they maintain stable phenotypes and functions, preferentially migrate to target sites, and exert more potent and specific immunosuppression than do polyclonal Tregs. However, there are some major hurdles that must be overcome before CAR-Tregs can be used in clinic. It is known that treatments with anti-tumor CAR-T cells cause side effects due to cytokine “storm” and neuronal cytotoxicity. It is unclear whether CAR-Tregs would also induce these adverse reactions. Moreover, antibodies specific for self- or allo-antigens must be characterized to construct antigen-specific CAR-Tregs. Selection of antigens targeted by CARs and development of specific antibodies are difficult in some disease models. Finally, CAR-Treg exhaustion may limit their efficacy in immunosuppression. Recently, innovative CAR-Treg therapies in animal models of transplantation and autoimmune diseases have been reported. In this mini-review, we have summarized recent progress of CAR-Tregs and discussed their potential applications for induction of immunological tolerance

Interactions between CNS and immune cells in tuberculous meningitis

The central nervous system (CNS) harbors its own special immune system composed of microglia in the parenchyma, CNS-associated macrophages (CAMs), dendritic cells, monocytes, and the barrier systems within the brain. Recently, advances in the immune cells in the CNS provided new insights to understand the development of tuberculous meningitis (TBM), which is the predominant form of Mycobacterium tuberculosis (M.tb) infection in the CNS and accompanied with high mortality and disability. The development of the CNS requires the protection of immune cells, including macrophages and microglia, during embryogenesis to ensure the accurate development of the CNS and immune response following pathogenic invasion. In this review, we summarize the current understanding on the CNS immune cells during the initiation and development of the TBM. We also explore the interactions of immune cells with the CNS in TBM. In the future, the combination of modern techniques should be applied to explore the role of immune cells of CNS in TBM

Fast Neighbor Search By Using Revised K-D Tree

We present two new neighbor query algorithms, including range query (RNN) and nearest neighbor (NN) query, based on revised k-d tree by using two techniques. The first technique is proposed for decreasing unnecessary distance computations by checking whether the cell of a node is inside or outside the specified neighborhood of query point, and the other is used to reduce redundant visiting nodes by saving the indices of descendant points. We also implement the proposed algorithms in Matlab and C. The Matlab version is to improve original RNN and NN which are based on k-d tree, C version is to improve k-Nearest neighbor query (kNN) which is based on buffer k-d tree. Theoretical and experimental analysis have shown that the proposed algorithms significantly improve the original RNN, NN and kNN in low dimension, respectively. The tradeoff is that the additional space cost of the revised k-d tree is approximately O(αnlog (n))

Screen printing directed synthesis of covalent organic framework membranes with water sieving property

Screen printing is introduced to direct the synthesis of crack-free and thickness-tunable TpPa(OH)2 covalent organic framework membranes. A smooth precursor layer is firstly screen printed and then fully crystallised into TpPa(OH)2 membrane. Molecular-scale pores endow the membrane fast water-sieving property, which is promising in water desalination

Shikonin Prolongs Allograft Survival via Induction of CD4+FoxP3+ Regulatory T Cells

A transplanted organ is usually rejected without any major immunosuppressive treatment because of vigorous alloimmune responsiveness. However, continuous global immunosuppression may cause severe side effects, including nephrotoxicity, tumors, and infections. Therefore, it is necessary to seek novel immunosuppressive agents, especially natural ingredients that may provide sufficient efficacy in immunosuppression with minimal side effects. Shikonin is a bioactive naphthoquinone pigment, an ingredient originally extracted from the root of Lithospermum erythrorhizon. Previous studies have shown that shikonin regulates immunity and exerts anti-inflammatory effects. In particular, it can ameliorate arthritis in animal models. However, it is unclear whether shikonin inhibits alloimmunity or allograft rejection. In this study and for the first time, we demonstrated that shikonin significantly prolonged the survival of skin allografts in wild-type mice. Shikonin increased the frequencies of CD4+Foxp3+ regulatory T cells (Tregs) post-transplantation and induced CD4+Foxp3+ Tregs in vitro as well. Importantly, depleting the Tregs abrogated the extension of skin allograft survival induced by shikonin. It also decreased the frequencies of CD8+CD44highCD62Llow effector T cells and CD11c+CD80+/CD11c+CD86+ mature DCs after transplantation. Moreover, we found that shikonin inhibited the proliferation of T cells in vitro and suppressed their mTOR signaling. It also reduced the gene expression of pro-inflammatory cytokines, including IFNγ, IL-6, TNFα, and IL-17A, while increasing the gene expression of anti-inflammatory mediators IL-10, TGF-β1, and indoleamine-2, 3-dioxygenase (IDO) in skin allografts. Further, shikonin downregulated IDO protein expression in skin allografts and DCs in vitro. Taken together, shikonin inhibits allograft rejection via upregulating CD4+Foxp3+ Tregs. Thus, shikonin is a novel immunosuppressant that could be potentially used in clinical transplantation