197 research outputs found

    Model Predictive Robustness of Signal Temporal Logic Predicates

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    The robustness of signal temporal logic not only assesses whether a signal adheres to a specification but also provides a measure of how much a formula is fulfilled or violated. The calculation of robustness is based on evaluating the robustness of underlying predicates. However, the robustness of predicates is usually defined in a model-free way, i.e., without including the system dynamics. Moreover, it is often nontrivial to define the robustness of complicated predicates precisely. To address these issues, we propose a notion of model predictive robustness, which provides a more systematic way of evaluating robustness compared to previous approaches by considering model-based predictions. In particular, we use Gaussian process regression to learn the robustness based on precomputed predictions so that robustness values can be efficiently computed online. We evaluate our approach for the use case of autonomous driving with predicates used in formalized traffic rules on a recorded dataset, which highlights the advantage of our approach compared to traditional approaches in terms of expressiveness. By incorporating our robustness definitions into a trajectory planner, autonomous vehicles obey traffic rules more robustly than human drivers in the dataset.Comment: 7 pages, 6 figures, conference paper in submissio

    Cell surface-specific N-glycan profiling in breast cancer

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    Aberrant changes in specific glycans have been shown to be associated with immunosurveillance, tumorigenesis, tumor progression and metastasis. In this study, the N-glycan profiling of membrane proteins from human breast cancer cell lines and tissues was detected using modified DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE). The N-glycan profiles of membrane proteins were analyzed from 7 breast cancer cell lines and MCF 10A, as well as from 100 pairs of breast cancer and corresponding adjacent tissues. The results showed that, compared with the matched adjacent normal tissue samples, two biantennary N-glycans (NA2 and NA2FB) were significantly decreased (p <0.0001) in the breast cancer tissue samples, while the triantennary glycan (NA3FB) and a high-mannose glycan (M8) were dramatically increased (p = 0.001 and p <0.0001, respectively). Moreover, the alterations in these specific N-glycans occurred through the oncogenesis and progression of breast cancer. These results suggested that the modified method based on DSA-FACE is a high-throughput detection technology that is suited for analyzing cell surface N-glycans. These cell surface-specific N-glycans may be helpful in recognizing the mechanisms of tumor cell immunologic escape and could be potential targets for new breast cancer drugs

    Structural stability for Forchheimer fluid in a semi-infinite pipe

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    In this paper, it is assumed that the Forchheimer flow goes through a semi-infinite cylinder. The nonlinear boundary condition is satisfied on the finite end of the cylinder, and the homogeneous boundary condition is satisfied on the side of the cylinder. Using the method of energy estimate, the structural stability of the solution in the semi-infinite cylinder is obtained

    STUDY ON THE RELATION BETWEEN SELF CONSISTENCY AND CONGRUENCE AND MENTAL HEALTH OF POSTGRADUATES

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    Reveal the Relation between Self consistency and congruence and Mental Health of Postgraduates. Adopt self-consistency and congruence questionnaire, mental health questionnaire to carry out questionnaire investigation on 500 postgraduates of four Nanjing colleges and universities. Mental health of postgraduates has extremely negative notable relevance with the disharmony of oneself and experience and it has extremely negative notable relevance with self-flexibility. The degree of self consistency and congruence and self-flexibility of postgraduates with better psychological health situation is higher than that of postgraduates with poor mental health situation. Disharmony of oneself and experience, flexibility function of oneself forecast mentality symptom dissociation amounts to a certain extent. The degree of self-consistency and congruence has a significant influence on mental health

    High-efficiency Algorithm for the Most Unfavourable Load Case Combinations of Multilayered Frame-Type Wharf Structure

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    The wharf, which was built in the Three Gorges Reservoir of China, is constructed as a layered frame-type structure for adapting to large water level fluctuations that exceed 30 m. These large fluctuations cause the frame-type structure to exhibit a considerably higher number of load case combinations than traditional marine high-piled wharfs. To estimate the most adverse combined internal force and the corresponding unfavourable load case combinations of significant components for multilayered frame-type wharf structures in the Three Gorges Reservoir of China, a high-efficiency algorithm is developed in this study. This algorithm can skilfully transform the computational mode of load case combinations into a matrix operations process by computer programming. By applying the proposed algorithm, the number of load case combinations for eight significant components of frame-type wharf, including piles, columns, beams, braces and berthing components, are resolved to a total of 21 from the original quantity of more than six billion. This high-efficiency algorithm can provide powerful technical support for evaluating the bearing capability of multilayered frame-type wharfs in the Three Gorges Reservoir of China

    Metal-Organic Framework-Derived Ni-S/C Catalysts for Selective Alkyne Hydrogenation

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    Acknowledgments This work was financially supported by the National Natural Science Foundation of China (22278017), the Fundamental Research Funds for the Central Universities (buctrc202303, JD2325), and the Young Elite Scientists Sponsorship Program by BAST (No. BYESS2023087).Peer reviewedPostprin

    Integrated Analysis and Identification of Novel Biomarkers in Parkinson’s Disease

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    Parkinson’s disease (PD) is a quite common neurodegenerative disorder with a prevalence of approximately 1:800–1,000 in subjects over 60 years old. The aim of our study was to determine the candidate target genes in PD through meta-analysis of multiple gene expression arrays datasets and to further combine mRNA and miRNA expression analyses to identify more convincing biological targets and their regulatory factors. Six included datasets were obtained from the Gene Expression Omnibus database by systematical search, including five mRNA datasets (150 substantia nigra samples in total) and one miRNA dataset containing 32 peripheral blood samples. A chip meta-analysis of five microarray data was conducted by using the metaDE package and 94 differentially expressed (DE) mRNAs were comprehensively obtained. And 19 deregulated DE miRNAs were obtained through the analysis of one miRNAs dataset by Qlucore Omics Explorer software. An interaction network formed by DE mRNAs, DE miRNAs, and important pathways was discovered after we analyzed the functional enrichment, protein–protein interactions, and miRNA targetome prediction analysis. In conclusion, this study suggested that five significantly downregulated mRNAs (MAPK8, CDC42, NDUFS1, COX4I1, and SDHC) and three significantly downregulated miRNAs (miR-126-5p, miR-19-3p, and miR-29a-3p) were potentially useful diagnostic markers in clinic, and lipid metabolism (especially non-alcoholic fatty liver disease pathway) and mitochondrial dysregulation may be the keys to biochemically detectable molecular defects. However, the role of these new biomarkers and molecular mechanisms in PD requires further experiments in vivo and in vitro and further clinical evidence
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