134 research outputs found

    A Study on the Practice of Folk Dance Culture in Kindergarten

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    China is characterized by a long history of development and a rich and colorful national culture. Folk dance culture shines in the field of excellent traditional culture. However, the progress of social development has led to the gradual extinction of folk dance. Preschool education, as the beginning stage of education in a person’s life, is a favorable time to embrace folk dance culture. By integrating folk dance into the stage of preschool education, it is conducive to carry forward the traditional culture of the nation and fostering national self-confidence and national pride in children while passing on the excellent traditional culture. Therefore, it is urgent to explore the path of combining folk dance culture with early childhood education

    Scaling BDD-based timed verification with simulation reduction

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    Digitization is a technique that has been widely used in real-time model checking. With the assumption of digital clocks, symbolic model checking techniques (like those based on BDDs) can be applied for real-time systems. The problem of model checking real-time systems based on digitization is that the number of tick transitions increases rapidly with the increment of clock upper bounds. In this paper, we propose to improve BDD-based verification for real-time systems using simulation reduction. We show that simulation reduction allows us to verify timed automata with large clock upper bounds and to converge faster to the fixpoint. The presented approach is applied to reachability and LTL verification for real-time systems. Finally, we compare our approach with existing tools such as Rabbit, Uppaal, and CTAV and show that our approach outperforms them and achieves a significant speedup.No Full Tex

    The Oncogene IARS2 Promotes Non-small Cell Lung Cancer Tumorigenesis by Activating the AKT/MTOR Pathway

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    A limited number of studies have indicated an association between isoleucyl-tRNA synthetase 2 (IARS2) and tumorigenesis. We evaluated IARS2 protein expression in lung tumor tissues and paired non-tumor tissues. We found higher IARS2 expression in the tumor tissues, which was associated with the late Tumor and Node stages of the Tumor, Node, Metastasis staging system. Silencing IARS2 inhibited the activity of A549 and H1299 cells, resulting in G0/G1 stasis of A549 cells and mitochondrial apoptosis. IARS2 silencing was also found to inhibit NSCLC tumor growth in nude mice. Complementary DNA microarray analysis revealed 742 differentially expressed genes (507 upregulated and 235 downregulated) in IARS2-silenced A549 cells compared to controls. Ingenuity Pathway Analysis of the differential expression data suggested that multiple pathways are associated with IARS2 silencing in NSCLC cells; upstream analysis predicted the activation or inhibition of transcriptional regulators. Correlation analysis revealed that AKT and MTOR activities were significantly inhibited in IARS2-silenced cells, but were partially restored by the AKT-stimulating agent SC79. IARS2 appears to regulate lung cancer cell proliferation via the AKT/MTOR pathway. Our results help clarify the complex roles of IARS2 in tumorigenesis and suggest that it may be a novel regulator of lung cancer development

    Development and validation of ferroptosis-related lncRNAs signature for hepatocellular carcinoma

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    Background Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors throughout the world. However, there is no research to establish a ferroptosis-related lncRNAs (FRlncRNAs) signature for the patients with HCC. Therefore, this study was designed to establish a novel FRlncRNAs signature to predict the survival of patients with HCC. Method The expression profiles of lncRNAs were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. FRlncRNAs co-expressed with ferroptosis-related genes were utilized to establish a signature. Cox regression was used to construct a novel three FRlncRNAs signature in the TCGA cohort, which was verified in the GEO validation cohort. Results Three differently expressed FRlncRNAs significantly associated with prognosis of HCC were identified, which composed a novel FRlncRNAs signature. According to the FRlncRNAs signature, the patients with HCC could be divided into low- and high-risk groups. Patients with HCC in the high-risk group displayed shorter overall survival (OS) contrasted with those in the low-risk group (P  1, P  1, P < 0.05). Meanwhile, it was also a useful tool in predicting survival among each stratum of gender, age, grade, stage, and etiology,etc. This signature was connected with immune cell infiltration (i.e., Macrophage, Myeloid dendritic cell, and Neutrophil cell, etc.) and immune checkpoint blockade targets (PD-1, CTLA-4, and TIM-3). Conclusion The three FRlncRNAs might be potential therapeutic targets for patients, and their signature could be utilized for prognostic prediction in HCC

    Significant decrease of maternal mitochondria carryover using optimized spindle-chromosomal complex transfer.

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    Mutations in mitochondrial DNA (mtDNA) contribute to a variety of serious multi-organ human diseases, which are strictly inherited from the maternal germline. However, there is currently no curative treatment. Attention has been focused on preventing the transmission of mitochondrial diseases through mitochondrial replacement (MR) therapy, but levels of mutant mtDNA can often unexpectedly undergo significant changes known as mitochondrial genetic drift. Here, we proposed a novel strategy to perform spindle-chromosomal complex transfer (SCCT) with maximal residue removal (MRR) in metaphase II (MII) oocytes, thus hopefully eliminated the transmission of mtDNA diseases. With the MRR procedure, we initially investigated the proportions of mtDNA copy numbers in isolated karyoplasts to those of individual oocytes. Spindle-chromosomal morphology and copy number variation (CNV) analysis also confirmed the safety of this method. Then, we reconstructed oocytes by MRR-SCCT, which well developed to blastocysts with minimal mtDNA residue and normal chromosomal copy numbers. Meanwhile, we optimized the manipulation order between intracytoplasmic sperm injection (ICSI) and SCC transfer and concluded that ICSI-then-transfer was conducive to avoid premature activation of reconstructed oocytes in favor of normal fertilization. Offspring of mice generated by embryos transplantation in vivo and embryonic stem cells derivation further presented evidences for competitive development competence and stable mtDNA carryover without genetic drift. Importantly, we also successfully accomplished SCCT in human MII oocytes resulting in tiny mtDNA residue and excellent embryo development through MRR manipulation. Taken together, our preclinical mouse and human models of the MRR-SCCT strategy not only demonstrated efficient residue removal but also high compatibility with normal embryo development, thus could potentially be served as a feasible clinical treatment to prevent the transmission of inherited mtDNA diseases

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Single cell atlas for 11 non-model mammals, reptiles and birds.

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    The availability of viral entry factors is a prerequisite for the cross-species transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Large-scale single-cell screening of animal cells could reveal the expression patterns of viral entry genes in different hosts. However, such exploration for SARS-CoV-2 remains limited. Here, we perform single-nucleus RNA sequencing for 11 non-model species, including pets (cat, dog, hamster, and lizard), livestock (goat and rabbit), poultry (duck and pigeon), and wildlife (pangolin, tiger, and deer), and investigated the co-expression of ACE2 and TMPRSS2. Furthermore, cross-species analysis of the lung cell atlas of the studied mammals, reptiles, and birds reveals core developmental programs, critical connectomes, and conserved regulatory circuits among these evolutionarily distant species. Overall, our work provides a compendium of gene expression profiles for non-model animals, which could be employed to identify potential SARS-CoV-2 target cells and putative zoonotic reservoirs

    GRU Neural Network Based on CEEMDAN–Wavelet for Stock Price Prediction

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    Stock indices are considered to be an important indicator of financial market volatility in various countries. Therefore, the stock market forecast is one of the challenging issues to decrease the uncertainty of the future direction of financial markets. In recent years, many scholars attempted to use different conventional statistical and deep learning methods to predict stock indices. However, the non-linear financial noise data will usually cause stochastic deterioration and time lag in forecast results, resulting in existing neural networks that do not demonstrate good prediction results. For this reason, we propose a novel framework to combine the gated recurrent unit (GRU) neural network with the complete ensemble empirical mode decomposition of adaptive noise (CEEMDAN) to predict the stock indices with better accuracy, in which the wavelet threshold method is especially used to denoise high-frequency noises in the sub-signals to exclude noise interference for future data predictions. Firstly, we choose representative datasets collected from the closing prices of S&P500 and CSI 300 stock indices to evaluate the proposed GRU-CEEMDAN–wavelet model. Additionally, we compare the improved model to the traditional ARIMA and several modified neural network models using different gate structures. The result shows that the mean values of MSE and MAE for GRU based on CEEMDAN–wavelet are the smallest by significance analysis. Overall, we found that our model could improve prediction accuracy and alleviates the time lag problem

    Wrinkling Patterns and Stress Analysis of Tensile Membrane with Rigid Elements

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    Heterogeneous membrane structures with rigid elements are often used in flexible electronic and aerospace structures. In heterogeneous membrane structures under tension, the disturbance stress caused by the rigid element changes the stress distribution of the membrane, and it is difficult to calculate the stress distribution of the heterogeneous membrane structure using the traditional stress functions method. In this article, we propose a method for calculating the non-uniform stress field based on the Eshelby elastic inclusion theory, which states that tension membrane structures contain square rigid elements. The wrinkle distribution of the rigid element at different positions is predicted by a stress analysis, and the influence of the position and size of the rigid element on the wrinkle distribution of the membrane is studied by a finite-element simulation. The research results show that the wrinkle pattern of the stretched membrane can be controlled by changing the position of the rigid element to meet some special needs

    Who Needs to Save Energy and Reduce Emissions? Perspective of Energy Misallocation and Economies of Scale

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    With the rapid development of the economy, human survival and socio-economic development are facing the severe challenges of climate threats. Global warming is one of the greatest threats to human survival and political stability that has occurred in human history. The main factor causing global warming is the extensive use of energy; therefore, it is imperative to spend more effort in energy conservation and emission reduction. In this context, this paper provides a reference and basis for decision making on emission-reduction paths through the perspective of energy input misallocation and economies of scale of CO2 emissions. The results show that for cities with relatively low energy inputs, the impact of excessive energy input on CO2 emissions is stronger than the effect of the scale of energy input on reducing CO2 emissions. Therefore, these cities need to prioritize energy conservation and emission reduction. On the other hand, in cities with large energy inputs, the impact of the scale of energy input on reducing CO2 emissions is more significant than the effect of excessive energy input on CO2 emissions. Therefore, these areas should also focus on energy conservation and emission reduction. The results of this paper have theoretical value and practical significance for scientifically implementing energy conservation and emission reduction strategies, as well as reasonably planning energy conservation pathways
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