69 research outputs found

    HULL SHAPE OPTIMIZATION OF SMALL UNDERWATER VEHICLE BASED ON KRIGING-BASED RESPONSE SURFACE METHOD AND MULTI-OBJECTIVE OPTIMIZATION ALGORITHM

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    Small underwater vehicles have unique advantages in ocean exploration. The resistance and volume of a vehicle are key factors affecting its operation time underwater. This paper aims to develop an effective method to obtain the optimal hull shape of a small underwater vehicle using Kriging-based response surface method (RSM) and multi-objective optimization algorithm. Firstly, the hydrodynamic performance of a small underwater vehicle is numerically investigated using computational fluid dynamics (CFD) method and the value range of related design variables is determined. The mesh convergence is verified to ensure the accuracy of the calculation results. Then, by means of the Latin hypercube sampling (LHS) design of simulation, the Kriging-based RSM model is developed according to the relation between each design variable of the vehicle and the output parameters applied to the vehicle. Based on the Kriging-based RSM model, the optimal hull shape of the vehicle is determined by using Screening and MOGA. As results, the vehicle resistance reduces and volume increases obviously

    Design and control of a novel variable stiffness soft arm

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    Soft robot arms possess such characteristics as light weight, simple structure and good adaptability to the environment, among others. On the other hand, robust control of soft robot arms presents many difficulties. Based on these reasons, this paper presents a novel design and modelling of a fuzzy active disturbance rejection control (FADRC) controller for a soft PAM arm. The soft arm comprises three contractile and one extensor PAMs, which can vary its stiffness independently of its position in space. Force analysis for the soft arm is conducted, and stiffness model of the arm is established based on the relational model of contractile and extensor PAM. The accuracy of stiffness model for the soft arm was verified through experiments. Associated to this, a controller based on the fuzzy adaptive theory and ADRC, FADRC, has been designed to control the arm. The fuzzy adaptive theory is used to adjust the parameters of the ADRC, the control algorithm has the ability to control stiffness and position of the soft arm. In this paper, FADRC was further verified through comparative experiments on the soft arm. This paper reinforces the hypothesis that FADRC control, as an algorithm, indeed possesses good robustness and adaptive abilities. Key words: soft robot, variable stiffness, PAM, stiffness modelling, FADR

    Identification and validation of biomarkers for epithelial-mesenchymal transition-related cells to estimate the prognosis and immune microenvironment in primary gastric cancer by the integrated analysis of single-cell and bulk RNA sequencing data

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    Background: The epithelial-mesenchymal transition (EMT) is associated with gastric cancer (GC) progression and immune microenvironment. To better understand the heterogeneity underlying EMT, we integrated single-cell RNA-sequencing (scRNA-seq) data and bulk sequencing data from GC patients to evaluate the prognostic utility of biomarkers for EMT-related cells (ERCs), namely, cancer-associated fibroblasts (CAFs) and epithelial cells (ECs). Methods: scRNA-seq data from primary GC tumor samples were obtained from the Gene Expression Omnibus (GEO) database to identify ERC marker genes. Bulk GC datasets from the Cancer Genome Atlas (TCGA) and GEO were used as training and validation sets, respectively. Differentially expressed markers were identified from the TCGA database. Univariate Cox, least-absolute shrinkage, and selection operator regression analyses were performed to identify EMT-related cell-prognostic genes (ERCPGs). Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses were adopted to evaluate the prognostic utility of the ERCPG signature. An ERCPG-based nomogram was constructed by integrating independent prognostic factors. Finally, we evaluated the correlations between the ERCPG signature and immune-cell infiltration and verified the expression of ERCPG prognostic signature genes by in vitro cellular assays. Results: The ERCPG signature was comprised of seven genes (COL4A1, F2R, MMP11, CAV1, VCAN, FKBP10, and APOD). Patients were divided into high- and low-risk groups based on the ERCPG risk scores. Patients in the high-risk group showed a poor prognosis. ROC and calibration curves suggested that the ERCPG signature and nomogram had a good prognostic utility. An immune cell-infiltration analysis suggested that the abnormal expression of ERCPGs induced the formation of an unfavorable tumor immune microenvironment. In vitro cellular assays showed that ERCPGs were more abundantly expressed in GC cell lines compared to normal gastric tissue cell lines. Conclusions: We constructed and validated an ERCPG signature using scRNA-seq and bulk sequencing data from ERCs of GC patients. Our findings support the estimation of patient prognosis and tumor treatment in future clinical practice

    The dimer state of GyrB is an active form: implications for the initial complex assembly and processive strand passage

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    In a previous study, we presented the dimer structure of DNA gyrase Bā€² domain (GyrB C-terminal domain) from Mycobacterium tuberculosis and proposed a ā€˜sluice-likeā€™ model for T-segment transport. However, the role of the dimer structure is still not well understood. Cross-linking and analytical ultracentrifugation experiments showed that the dimer structure exists both in the Bā€² protein and in the full-length GyrB in solution. The cross-linked dimer of GyrB bound GyrA very weakly, but bound dsDNA with a much higher affinity than that of the monomer state. Using cross-linking and far-western analyses, the dimer state of GyrB was found to be involved in the ternary GyrAā€“GyrBā€“DNA complex. The results of mutational studies reveal that the dimer structure represents a state before DNA cleavage. Additionally, these results suggest that the dimer might also be present between the cleavage and reunion steps during processive transport

    MSMEG_2731, an Uncharacterized Nucleic Acid Binding Protein from Mycobacterium smegmatis, Physically Interacts with RPS1

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    While the M. smegmatis genome has been sequenced, only a small portion of the genes have been characterized experimentally. Here, we purify and characterize MSMEG_2731, a conserved hypothetical alanine and arginine rich M. smegmatis protein. Using ultracentrifugation, we show that MSMEG_2731 is a monomer in vitro. MSMEG_2731 exists at a steady level throughout the M. smegmatis life-cycle. Combining results from pull-down techniques and LS-MS/MS, we show that MSMEG_2731 interacts with ribosomal protein S1. The existence of this interaction was confirmed by co-immunoprecipitation. We also show that MSMEG_2731 can bind ssDNA, dsDNA and RNA in vitro. Based on the interactions of MSMEG_2731 with RPS1 and RNA, we propose that MSMEG_2731 is involved in the transcription-translation process in vivo

    Fieldā€assisted electrocatalysts spark sulfur redox kinetics: From fundamentals to applications

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    Abstract The chief culprit impeding the commercialization of lithiumā€“sulfur (Liā€“S) batteries is the parasitic shuttle effect and restricted redox kinetics of lithium polysulfides (LiPSs). To circumvent these key stumbling blocks, incorporating electrocatalysts with rational electronic structure modulation into sulfur cathode plays a decisive role in vitalizing the higher electrocatalytic activity to promote sulfur utilization efficiency. Breaking the stereotype of contemporary electrocatalyst design kept on pretreatment, fieldā€assisted electrocatalysts offer strategic advantages in dynamically controllable electrochemical reactions that might be thorny to regulate in conventional electrochemical processes. However, the highly interdisciplinary fieldā€assisted electrochemistry puzzles researchers for a fundamental understanding of the ambiguous correlations among electronic structure, surface adsorption properties, and catalytic performance. In this review, the mechanisms, functionality explorations, and advantages of fieldā€assisted electrocatalysts including electric, magnetic, light, thermal, and strain fields in Liā€“S batteries have been summarized. By demonstrating pioneering work for customized geometric configuration, energy band engineering, and optimal microenvironment arrangement in response to decreased activation energy and enriched reactant concentration for accelerated sulfur redox kinetics, cuttingā€edge insights into the holistic periscope of chargeā€spinā€orbitalā€lattice interplay between LiPSs and electrocatalysts are scrutinized, which aspires to advance the comprehensive understanding of the complex electrochemistry of Liā€“S batteries. Finally, future perspectives are provided to inspire innovations capable of defeating existing restrictions

    Promotion Effect of the Keggin Structure on the Sulfur and Water Resistance of Pt/CeTi Catalysts for CO Oxidation

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    Developing a catalyst with high SO2 and H2O resistance to achieve high-performance CO oxidation for specific industrial applications is highly desirable. Here, three catalysts were prepared using cerium titanium composite oxide (CeTi), molybdophosphate with Keggin structure-modified CeTi (Keg-CeTi), and molybdophosphate without Keggin structure-modified CeTi (MoP-CeTi) as supports, and their sulfur and water resistance in CO oxidation were tested. The characterization of XRD, BET, SO2/H2O-DRIFTS, XPS, TEM, SEM, NH3/SO2-TPD, H2-TPR, and ICP techniques revealed that the high SO2 and H2O resistance of Pt/Keg-CeTi in CO oxidation was related to its stronger surface acidity, better reduction of surface cerium and molybdenum species, and lower SO2 adsorption and transformation compared to Pt/CeTi and Pt/MoP-CeTi
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