TEACHING KNOWLEDGE AND UNDERSTANDING OF THE INTERPRETATION OF CHARMING XIANGXI STAGE COSTUME SYMBOLS IN ZHANGJIAJIE, HUNAN PROVINCE, CHINA

For centuries, performers in Hunan Province, China, have adorned themselves in the Charming Xiangxi stage costume. The symbols on the costume might stand for things in nature, cultural beliefs, or important events in history. The interpretation of these symbols requires a deep understanding of Chinese culture and history. The objective of this study was to study and present the importance of teaching knowledge and understanding of the interpretation of Charming Xiangxi stage costume symbols in Zhangjiajie, Hunan Province, China. Using the methods of literature review and field investigation. The results of this study show that the "Maous Dance" of Tujia nationality, a traditional national dance in Tujia folk activities, is a symbol of spiritual externalization and national identity. It finds its universality and particularity, and its ontological characteristics are compatible with the commonness of the two arts but also have their own uniqueness. Through the "Maous Dance" performance in Charming Xiangxi, we can see that human beings still shine the light of humanity behind the dance sacrifice activities, and the production, living, reproduction, praying for good luck, and eliminating disasters represent the cultural phenomenon of longing for survival and pursuing survival.

Robust Deep Learning Models Against Semantic-Preserving Adversarial Attack

Deep learning models can be fooled by small $l_p$-norm adversarial perturbations and natural perturbations in terms of attributes. Although the robustness against each perturbation has been explored, it remains a challenge to address the robustness against joint perturbations effectively. In this paper, we study the robustness of deep learning models against joint perturbations by proposing a novel attack mechanism named Semantic-Preserving Adversarial (SPA) attack, which can then be used to enhance adversarial training. Specifically, we introduce an attribute manipulator to generate natural and human-comprehensible perturbations and a noise generator to generate diverse adversarial noises. Based on such combined noises, we optimize both the attribute value and the diversity variable to generate jointly-perturbed samples. For robust training, we adversarially train the deep learning model against the generated joint perturbations. Empirical results on four benchmarks show that the SPA attack causes a larger performance decline with small $l_{\infty}$ norm-ball constraints compared to existing approaches. Furthermore, our SPA-enhanced training outperforms existing defense methods against such joint perturbations.Comment: Paper accepted by the 2023 International Joint Conference on Neural Networks (IJCNN 2023

Experimental investigation and prediction of compressive strength of ultra-high performance concrete containing supplementary cementitious materials

Ultra-high performance concrete (UHPC) has superior mechanical properties and durability to normal strength concrete. However, the high amount of cement, high environmental impact, and initial cost are regarded as disadvantages, restricting its wider application. Incorporation of supplementary cementitious materials (SCMs) in UHPC is an effective way to reduce the amount of cement needed while contributing to the sustainability and cost. This paper investigates the mechanical properties and microstructure of UHPC containing fly ash (FA) and silica fume (SF) with the aim of contributing to this issue. The results indicate that, on the basis of 30% FA replacement, the incorporation of 10% and 20% SF showed equivalent or higher mechanical properties compared to the reference samples. The microstructure and pore volume of the UHPCs were also examined. Furthermore, to minimise the experimental workload of future studies, a prediction model is developed to predict the compressive strength of the UHPC using artificial neural networks (ANNs). The results indicate that the developed ANN model has high accuracy and can be used for the prediction of the compressive strength of UHPC with these SCMs

IFN-γ and TNF-α Synergistically Induce Mesenchymal Stem Cell Impairment and Tumorigenesis via NFκB Signaling

An inflammatory microenvironment may cause organ degenerative diseases and malignant tumors. However, the precise mechanisms of inflammation-induced diseases are not fully understood. Here we show that the proinflammatory cytokines interferon γ (IFN-γ) and tumor necrosis factor α (TNF-α) synergistically impair self-renewal and differentiation of mesenchymal stem cells (MSCs) via nuclear factor κB (NFκB)–mediated activation of Mothers against decapentaplegic homolog 7 (SMAD7) in ovariectomized (OVX) mice. More interestingly, a long-term elevated levels of IFN-γ and TNF-α result in significantly increased susceptibility to malignant transformation in MSCs through NFκB–mediated upregulation of the oncogenes c-Fos and c-Myc. Depletion of either IFN-γ or TNF-α in OVX mice abolishes MSC impairment and the tendency toward malignant transformation with no NFκB–mediated oncogene activation. Systemic administration of aspirin, which significantly reduces the levels of IFN-γ and TNF-α, results in blockage of MSC deficiency and tumorigenesis by inhibition of NF-κB/SMAD7 and NFκB/c-FOS and c-MYC pathways in OVX mice. In summary, this study reveals that inflammation factors, such as IFN-γ and TNF-α, synergistically induce MSC deficiency via NFκB/SMAD7 signaling and tumorigenesis via NFκB–mediated oncogene activation

An ontology-based approach supporting holistic structural design with the consideration of safety, environmental impact and cost

Early stage decision-making for structural design critically influences the overall cost and environmental performance of buildings and infrastructure. However, the current approach often fails to consider the multi-perspectives of structural design, such as safety, environmental issues and cost in a comprehensive way. This paper presents a holistic approach based on knowledge processing (ontology) to facilitate a smarter decision-making process for early design stage by informing designers of the environmental impact and cost along with safety considerations. The approach can give a reasoning based quantitative understanding of how the design alternatives using different concrete materials can affect the ultimate overall performance. Embodied CO2 and cost are both considered along with safety criteria as indicative multi-perspectives to demonstrate the novelty of the approach. A case study of a concrete structural frame is used to explain how the proposed method can be used by structural designers when taking multi performance criteria into account. The major contribution of the paper lies on the creation of a holistic knowledge base which links through different knowledge across sectors to enable the structural engineer to come up with much more comprehensive decisions instead of individual single objective targeted delivery

An Optimal Operating Strategy for Battery Life Cycle Costs in Electric Vehicles

Impact on petroleum based vehicles on the environment, cost, and availability of fuel has led to an increased interest in electric vehicle as a means of transportation. Battery is a major component in an electric vehicle. Economic viability of these vehicles depends on the availability of cost-effective batteries. This paper presents a generalized formulation for determining the optimal operating strategy and cost optimization for battery. Assume that the deterioration of the battery is stochastic. Under the assumptions, the proposed operating strategy for battery is formulated as a nonlinear optimization problem considering reliability and failure number. And an explicit expression of the average cost rate is derived for battery lifetime. Results show that the proposed operating strategy enhances the availability and reliability at a low cost

IFN-γ and TNF-α Synergistically Induce Mesenchymal Stem Cell Impairment and Tumorigenesis via NFκB Signaling

An inflammatory microenvironment may cause organ degenerative diseases and malignant tumors. However, the precise mechanisms of inflammation-induced diseases are not fully understood. Here we show that the proinflammatory cytokines interferon γ (IFN-γ) and tumor necrosis factor α (TNF-α) synergistically impair self-renewal and differentiation of mesenchymal stem cells (MSCs) via nuclear factor κB (NFκB)–mediated activation of Mothers against decapentaplegic homolog 7 (SMAD7) in ovariectomized (OVX) mice. More interestingly, a long-term elevated levels of IFN-γ and TNF-α result in significantly increased susceptibility to malignant transformation in MSCs through NFκB–mediated upregulation of the oncogenes c-Fos and c-Myc. Depletion of either IFN-γ or TNF-α in OVX mice abolishes MSC impairment and the tendency toward malignant transformation with no NFκB–mediated oncogene activation. Systemic administration of aspirin, which significantly reduces the levels of IFN-γ and TNF-α, results in blockage of MSC deficiency and tumorigenesis by inhibition of NF-κB/SMAD7 and NFκB/c-FOS and c-MYC pathways in OVX mice. In summary, this study reveals that inflammation factors, such as IFN-γ and TNF-α, synergistically induce MSC deficiency via NFκB/SMAD7 signaling and tumorigenesis via NFκB–mediated oncogene activation

Serial deletion reveals structural basis and stability for the core enzyme activity of human glutaminase 1 isoforms: relevance to excitotoxic neurodegeneration.

BACKGROUND: Glutaminase 1 is a phosphate-activated metabolic enzyme that catalyzes the first step of glutaminolysis, which converts glutamine into glutamate. Glutamate is the major neurotransmitter of excitatory synapses, executing important physiological functions in the central nervous system. There are two isoforms of glutaminase 1, KGA and GAC, both of which are generated through alternative splicing from the same gene. KGA and GAC both transcribe 1-14 exons in the N-terminal, but each has its unique C-terminal in the coding sequence. We have previously identified that KGA and GAC are differentially regulated during inflammatory stimulation and HIV infection. Furthermore, glutaminase 1 has been linked to brain diseases such as amyotrophic lateral sclerosis, Alzheimer\u27s disease, and hepatic encephalopathy. Core enzyme structure of KGA and GAC has been published recently. However, how other coding sequences affect their functional enzyme activity remains unclear. METHODS: We cloned and performed serial deletions of human full-length KGA and GAC from the N-terminal and the C-terminal at an interval of approximately 100 amino acids (AAs). Prokaryotic expressions of the mutant glutaminase 1 protein and a glutaminase enzyme activity assay were used to determine if KGA and GAC have similar efficiency and efficacy to convert glutamine into glutamate. RESULTS: When 110 AAs or 218 AAs were deleted from the N-terminal or when the unique portions of KGA and GAC that are beyond the 550 AA were deleted from the C-terminal, KGA and GAC retained enzyme activity comparable to the full length proteins. In contrast, deletion of 310 AAs or more from N-terminal or deletion of 450 AAs or more from C-terminal resulted in complete loss of enzyme activity for KGA/GAC. Consistently, when both N- and C-terminal of the KGA and GAC were removed, creating a truncated protein that expressed the central 219 AA - 550 AA, the protein retained enzyme activity. Furthermore, expression of the core 219 AA - 550 AA coding sequence in cells increased extracellular glutamate concentrations to levels comparable to those of full-length KGA and GAC expressions, suggesting that the core enzyme activity of the protein lies within the central 219 AA - 550 AA. Full-length KGA and GAC retained enzyme activities when kept at 4 °C. In contrast, 219 AA - 550 AA truncated protein lost glutaminase activities more readily compared with full-length KGA and GAC, suggesting that the N-terminal and C-terminal coding regions are required for the stability KGA and GAC. CONCLUSIONS: Glutaminase isoforms KGA and GAC have similar efficacy to catalyze the conversion of glutamine to glutamate. The core enzyme activity of glutaminase 1 protein is within the central 219 AA - 550 AA. The N-terminal and C-terminal coding regions of KGA and GAC help maintain the long-term activities of the enzymes