Development of Biomimetic-Based Controller Design Methods for Advanced Energy Systems

A biologically inspired optimal control strategy, denoted as BIO-CS, is proposed for advanced energy systems applications. This strategy combines the ant\u27s rule of pursuit idea with multi-agent and optimal control concepts. The BIO-CS algorithm employs gradient-based optimal control solvers for the intermediate problems associated with the leader-follower agents\u27 local interactions. The developed BIO-CS is integrated with an Artificial Neural Network (ANN)-based adaptive component for further improvement of the overall framework. In particular, the ANN component captures the mismatch between the controller and the plant models by using a single-hidden-layer technique with online learning capabilities to augment the baseline BIO-CS control laws. The resulting approach is a unique combination of biomimetic control and data-driven methods that provides optimal solutions for dynamic systems.;The applicability of the proposed framework is illustrated via an Integrated Gasification Combined Cycle (IGCC) process with carbon capture as an advanced energy system example. Specifically, a multivariable control structure associated with a subsystem of the IGCC plant simulation in DYNSIMRTM software platform is addressed. The proposed control laws are derived in MATLAB RTM environment, while the plant models are built in DYNSIM RTM, and a previously developed MATLABRTM-DYNSIM RTM link is employed for implementation purposes. The proposed integrated approach improves the overall performance of the process up to 85% in terms of reducing the output tracking error when compared to stand-alone BIO-CS and Proportional-Integral (PI) controller implementations, resulting in faster setpoint tracking.;Other applications of BIO-CS addressed include: i) a nonlinear fermentation process to produce ethanol; and ii) a transfer function model derived from the cyber-physical fuel cell-gas turbine hybrid power system that is part of the Hybrid Performance (HYPER) project at the National Energy Technology Laboratory (NETL). Other theoretical developments in this work correspond to the integration of the BIO-CS approach with Multi-Agent Optimization (MAO) techniques and casting BIO-CS as a Model Predictive Controller (MPC). These developments are demonstrated by revisiting the fermentation process example. The proposed biologically-inspired approaches provide a promising alternative for advanced control of energy systems of the future

An Effective and Efficient Intrusion Detection System of Network Attacks Using Stacked CNN and Voting Technique

IDS are crucial to network security because they can identify malicious activity and halt it in its tracks. Network intrusion data is often masked by a sea of benign data, making it difficult to train a model or perform a detection with a high FPR. This is because networks are inherently dynamic and change over time. In this research, we offer a ML & DL model-based method to ID, and we demonstrate how to deal with the issue of data imbalance by using a hybrid sampling technique. Conventional firewalls and data encryption technologies are unable to provide the level of security required by current networks. As a result, IDSs have been endorsed for use against network threats. Recent mainstream ID approaches have benefited from ML, but they have low detection rates & need a lot of feature engineering to be truly useful. Using layered CNN and Voting classifier (XGBoost and LGBM), this study introduces ML-DL-NIDS to address the issue of subpar detection precision. Using a publicly available NSL-KDD & UNSW-15 benchmark datasets for network intrusion detection, we find that this model outperforms competing methods according to accuracy and F1-score obtained from experimental evaluations

Tumor promoting roles of IL-10, TGF-β, IL-4, and IL-35: Its implications in cancer immunotherapy

Cytokines play a critical role in regulating host immune response toward cancer and determining the overall fate of tumorigenesis. The tumor microenvironment is dominated mainly by immune-suppressive cytokines that control effector antitumor immunity and promote survival and the proliferation of cancer cells, which ultimately leads to enhanced tumor growth. In addition to tumor cells, the heterogeneous immune cells present within the tumor milieu are the significant source of immune-suppressive cytokines. These cytokines are classified into a broad range; however, in most tumor types, the interleukin-10, transforming growth factor-β, interleukin-4, and interleukin-35 are consistently reported as immune-suppressive cytokines that help tumor growth and metastasis. The most emerging concern in cancer treatment is hijacking and restraining the activity of antitumor immune cells in the tumor niche due to a highly immune-suppressive environment. This review summarizes the role and precise functions of interleukin-10, transforming growth factor-β, interleukin-4, and interleukin-35 in modulating tumor immune contexture and its implication in developing effective immune-therapeutic approaches

Development of Chemical Process Design and Control for Sustainability

This contribution describes a novel process systems engineering framework that couples advanced control with sustainability evaluation for the optimization of process operations to minimize environmental impacts associated with products, materials and energy. The implemented control strategy combines a biologically-inspired method with optimal control concepts for finding more sustainable operating trajectories. The sustainability assessment of process operating points is carried out by using the U.S. EPA’s Gauging Reaction Effectiveness for the ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) tool that provides scores for the selected indicators in the economic, material efficiency, environmental and energy areas. The indicator scores describe process performance on a sustainability measurement scale, effectively determining which operating point is more sustainable if there are more than several steady states for one specific product manufacturing. Through comparisons between a representative benchmark and the optimal steady states obtained through the implementation of the proposed controller, a systematic decision can be made in terms of whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous fermentation process for fuel production, whose material and energy time variation models are characterized by multiple steady states and oscillatory conditions

Carbon nanospheres mediated delivery of nuclear matrix protein SMAR 1 to direct experimental autoimmune encephalomyelitis in mice

Owing to the suppression of immune responses and associated side effects, steroid based treatments for inflammatory encephalitis disease can be detrimental. Here, we demonstrate a novel carbon nanosphere (CNP) based treatment regime for encephalomyelitis in mice by exploiting the functional property of the nuclear matrix binding protein SMAR1. A truncated part of SMAR1 ie, the DNA binding domain was conjugated with hydrothermally synthesized CNPs. When administered intravenously, the conjugate suppressed experimental animal encephalomyelitis in T cell specific conditional SMAR1 knockout mice (SMAR-/-). Further, CNP-SMAR1 conjugate delayed the onset of the disease and reduced the demyelination significantly. There was a significant decrease in the production of IL-17 after re-stimulation with MOG. Altogether, our findings suggest a potential carbon nanomaterial based therapeutic intervention to combat Th17 mediated autoimmune diseases including experimental autoimmune encephalomyelitis

B Cell Receptor Signaling and Protein Kinase D2 Support Regulatory B Cell Function in Pancreatic Cancer

B cells can act as potent suppressors of anti-tumor T cell immunity, presenting a mechanism of resistance to immunotherapy. In pancreatic ductal adenocarcinoma, B cells can display a T cell-suppressive or regulatory phenotype centered on the expression of the cytokine Interleukin 35 (IL-35). While B cell-mediated immunosuppression presents a barrier to anti-tumorigenic T cell function, it is not clear how regulatory B cell function could be targeted, and the signals that promote this suppressive phenotype in B cells are not well understood. Here we use a novel IL-35 reporter model to understand which signaling pathways are important for immunosuppressive properties in B cells. In vitro analysis of IL-35 reporter B cells revealed a synergy between the BCR and TLR4 signaling pathways is sufficient to induce IL-35 expression. However, in vivo, B cell receptor activation, as opposed to MyD88 signaling in B cells, is central to B cell-mediated suppression and promotion of pancreatic cancer growth. Further analysis identified protein kinase D2 (PKD2) as being a key downstream regulator of IL-35 expression in B cells. Regulatory B cells with an inactivating mutation in PKD2 failed to produce IL-35 or fully suppress effector T cell function in vitro. Furthermore, inhibition of PKD in B cells decreased tumor growth and promoted effector T cell function upon adoptive transfer into B cell-deficient mice. Collectively, these data provide insight into how regulatory B cell function is promoted in pancreatic cancer and identify potential therapeutic targets to restrain this function

Chromatin Remodeling Protein SMAR1 Is a Critical Regulator of T Helper Cell Differentiation and Inflammatory Diseases

T cell differentiation from naïve T cells to specialized effector subsets of mature cells is determined by the iterative action of transcription factors. At each stage of specificT cell lineage differentiation, transcription factor interacts not only with nuclear proteins such as histone and histone modifiers but also with other factors that are bound to the chromatin and play a critical role in gene expression. In this review, we focus on one of such nuclear protein known as tumor suppressor and scaffold matrix attachment region-binding protein 1 (SMAR1) in CD4+ T cell differentiation. SMAR1 facilitates Th1 differentiation by negatively regulating T-bet expression via recruiting HDAC1–SMRT complex to its gene promoter. In contrast, regulatory T (Treg) cell functions are dependent on inhibition of Th17-specific genes mainly IL-17 and STAT3 by SMAR1. Here, we discussed a critical role of chromatin remodeling protein SMAR1 in maintaining a fine-tuned balance between effector CD4+ T cells and Treg cells by influencing the transcription factors during allergic and autoimmune inflammatory diseases

Balance between immunoregulatory B cells and plasma cells drives pancreatic tumor immunity

Plasma cell responses are associated with anti-tumor immunity and favorable response to immunotherapy. B cells can amplify anti-tumor immune responses through antibody production; yet B cells in patients and tumor-bearing mice often fail to support this effector function. We identify dysregulated transcriptional program in B cells that disrupts differentiation of naive B cells into anti-tumor plasma cells. The signaling network contributing to this dysfunction is driven by interleukin (IL) 35 stimulation of a STAT3-PAX5 complex that upregulates the transcriptional regulator BCL6 in naive B cells. Transient inhibition of BCL6 in tumor-educated naive B cells is sufficient to reverse the dysfunction in B cell differentiation, stimulating the intra-tumoral accumulation of plasma cells and effector T cells and rendering pancreatic tumors sensitive to anti-programmed cell death protein 1 (PD-1) blockade. Our findings argue that B cell effector dysfunction in cancer can be due to an active systemic suppression program that can be targeted to synergize with T cell-directed immunotherapy

Antitumor Responses in the Absence of Toxicity in Solid Tumors by Targeting B7-H3 via Chimeric Antigen Receptor T Cells

The high expression across multiple tumor types and restricted expression in normal tissues make B7-H3 an attractive target for immunotherapy. We generated chimeric antigen receptor (CAR) T cells targeting B7-H3 (B7-H3.CAR-Ts) and found that B7-H3.CAR-Ts controlled the growth of pancreatic ductal adenocarcinoma, ovarian cancer and neuroblastoma in vitro and in orthotopic and metastatic xenograft mouse models, which included patient-derived xenograft. We also found that 4-1BB co-stimulation promotes lower PD-1 expression in B7-H3.CAR-Ts, and superior antitumor activity when targeting tumor cells that constitutively expressed PD-L1. We took advantage of the cross-reactivity of the B7-H3.CAR with murine B7-H3, and found that B7-H3.CAR-Ts significantly controlled tumor growth in a syngeneic tumor model without evident toxicity. These findings support the clinical development of B7-H3.CAR-Ts