FINITE ELEMENT ANALYSIS OF MECHANICAL PROPERTIES OF SPECIMEN WITH UHPC AND STUD CONNECTOR

UHPC is different from ordinary concrete for mechanical properties. To study the stress state of stud connector when UHPC is used to strengthen RC beam and its influence on bearing capacity of the strengthened beam, in this paper, ABAQUS was adopted first to simulate the push-out test of  stud to verify  accuracy of the finite element model. The nonlinearity of materials and contact conditions was considered in the model, and then three parameters including concrete strength, stud length and stud diameter were studied. Results showed the finite element model established by surface to surface contact method was possible to simulate the force and failure of the stud connector. UHPC could improve the  bearing capacity of the stud specimens obviously, and the length of stud had little effect on bearing capacity of stud while failure of the stud may occur if length of the stud was too small. The increase of stud diameter could improve bearing capacity of elastic working stage

Convolutional Hierarchical Attention Network for Query-Focused Video Summarization

Previous approaches for video summarization mainly concentrate on finding the most diverse and representative visual contents as video summary without considering the user's preference. This paper addresses the task of query-focused video summarization, which takes user's query and a long video as inputs and aims to generate a query-focused video summary. In this paper, we consider the task as a problem of computing similarity between video shots and query. To this end, we propose a method, named Convolutional Hierarchical Attention Network (CHAN), which consists of two parts: feature encoding network and query-relevance computing module. In the encoding network, we employ a convolutional network with local self-attention mechanism and query-aware global attention mechanism to learns visual information of each shot. The encoded features will be sent to query-relevance computing module to generate queryfocused video summary. Extensive experiments on the benchmark dataset demonstrate the competitive performance and show the effectiveness of our approach.Comment: Accepted by AAAI 2020 Conferenc

Tropical storm-induced turbulent mixing and chlorophyll-a enhancement in the continental shelf southeast of Hainan Island

AbstractBased on moored observations and remote sensing data in July and August 2005, energy sources for enhancing turbulent mixing and possible mechanisms of phytoplankton bloom in the continental shelf southeast of Hainan Island under the influence of Washi, a fast-moving and weak tropical storm, are analyzed in this paper. Observations show that strong near-inertial internal waves were generated by the rapidly changing wind stress and the near-inertial energy was dissipated quickly across the thermocline. The strong turbulent mixing associated with the near-inertial baroclinic shear instability occurred with maximum eddy diffusivity above 3.2×10−4m2s−1, and the surface chlorophyll-a (Chl-a) concentration after the storm increased by 22.2%. The Chl-a concentration augment was inferred to be an upper ocean biophysical response to the enhanced near-inertial turbulent mixing which could increase the upward nutrient flux into the surface low eutrophic zone during the passage of Washi

A Simple Asymmetric Momentum Make SGD Greatest Again

We propose the simplest SGD enhanced method ever, Loss-Controlled Asymmetric Momentum(LCAM), aimed directly at the Saddle Point problem. Compared to the traditional SGD with Momentum, there's no increase in computational demand, yet it outperforms all current optimizers. We use the concepts of weight conjugation and traction effect to explain this phenomenon. We designed experiments to rapidly reduce the learning rate at specified epochs to trap parameters more easily at saddle points. We selected WRN28-10 as the test network and chose cifar10 and cifar100 as test datasets, an identical group to the original paper of WRN and Cosine Annealing Scheduling(CAS). We compared the ability to bypass saddle points of Asymmetric Momentum with different priorities. Finally, using WRN28-10 on Cifar100, we achieved a peak average test accuracy of 80.78\% around 120 epoch. For comparison, the original WRN paper reported 80.75\%, while CAS was at 80.42\%, all at 200 epoch. This means that while potentially increasing accuracy, we use nearly half convergence time. Our demonstration code is available at\\ https://github.com/hakumaicc/Asymmetric-Momentum-LCA

Identification of differentially expressed microRNAs and the potential of microRNA-455-3p as a novel prognostic biomarker in glioma.

Glioma is an aggressive central nervous system malignancy. MicroRNAs (miRNAs/miRs) have been reported to be involved in the tumorigenesis of numerous types of cancer, including glioma. The present study aimed to identify the differentially expressed miRNAs in glioma, and further explore the clinical value of miR-455-3p in patients with glioma. GEO2R was used for the identification of the differentially expressed miRNAs according to the miRNA expression profiles obtained from the Gene Expression Omnibus database. OncomiR was used to analyze the relationship of miRNAs with the survival outcomes of the patients with glioma. A total of 108 patients with glioma were recruited to examine the expression levels of miR-455-3p and further explore its clinical value. The bioinformatics analysis results suggested that a total of 64 and 48 differentially expressed miRNAs were identified in the GSE90603 and GSE103229 datasets, respectively. There were 12 miRNAs in the overlap of the two datasets, of which three were able to accurately predict overall cancer survival, namely hsa-miR-7-5p, hsa-miR-21-3p and hsa-miR-455-3p. In patients with glioma, miR-455-3p was determined to be significantly upregulated (P<0.001). Additionally, patients with high miR-455-3p expression had significantly lower 5-year overall survival than those with low miR-455-3p expression (log-rank test, P=0.001). Cox regression analysis further determined that miR-455-3p was an independent prognostic indicator for overall survival in patients with glioma (hazard ratio=2.136; 95% CI=1.177-3.877; P=0.013). In conclusion, the present study revealed a series of miRNAs with potential functional roles in the pathogenesis of glioma, and provides findings that indicate miR-455-3p as a promising biomarker for the prognosis of glioma

Caffeine regulates both osteoclast and osteoblast differentiation via the AKT, NF-κB, and MAPK pathways

Background: Although caffeine generally offers benefits to human health, its impact on bone metabolism remains unclear.Aim and Methods: This study aimed to systematically evaluate the long-term effects of caffeine administration on osteoclasts, osteoblasts, and ovariectomy-induced postmenopausal osteoporosis (OP).Results: Our in vitro findings revealed that 3.125 and 12.5 μg/mL caffeine inhibited RANKL-mediated osteoclastogenesis in RAW 264.7 cells through the MAPK and NF-κB pathways, accompanied by the inactivation of nuclear translocation of nuclear factor NFATc1. Similarly, 3.125 and 12.5 μg/mL of caffeine modulated MC3T3-E1 osteogenesis via the AKT, MAPK, and NF-κB pathways. However, 50 μg/mL of caffeine promoted the phosphorylation of IκBα, P65, JNK, P38, and AKT, followed by the activation of NFATc1 and the inactivation of Runx2 and Osterix, ultimately disrupting the balance between osteoblastogenesis and osteoclastogenesis. In vivo studies showed that gavage with 55.44 mg/kg caffeine inhibited osteoclastogenesis, promoted osteogenesis, and ameliorated bone loss in ovariectomized mice.Conclusion: Conversely, long-term intake of high-dose caffeine (110.88 mg/kg) disrupted osteogenesis activity and promoted osteoclastogenesis, thereby disturbing bone homeostasis. Collectively, these findings suggest that a moderate caffeine intake (approximately 400 mg in humans) can regulate bone homeostasis by influencing both osteoclasts and osteoblasts. However, long-term high-dose caffeine consumption (approximately 800 mg in humans) could have detrimental effects on the skeletal system

Construction of a High-Density Genetic Map and Identification of Leaf Trait-Related QTLs in Chinese Bayberry (Myrica rubra)

Chinese bayberry (Myrica rubra) is an economically important fruit tree that is grown in southern China. Owing to its over 10-year seedling period, the crossbreeding of bayberry is challenging. The characteristics of plant leaves are among the primary factors that control plant architecture and potential yields, making the analysis of leaf trait-related genetic factors crucial to the hybrid breeding of any plant. In the present study, molecular markers associated with leaf traits were identified via a whole-genome re-sequencing approach, and a genetic map was thereby constructed. In total, this effort yielded 902.11 Gb of raw data that led to the identification of 2,242,353 single nucleotide polymorphisms (SNPs) in 140 F1 individuals and parents (Myrica rubra cv. Biqizhong × Myrica rubra cv. 2012LXRM). The final genetic map ultimately incorporated 31,431 SNPs in eight linkage groups, spanning 1,351.85 cM. This map was then used to assemble and update previous scaffold genomic data at the chromosomal level. The genome size of M. rubra was thereby established to be 275.37 Mb, with 94.98% of sequences being assembled into eight pseudo-chromosomes. Additionally, 18 quantitative trait loci (QTLs) associated with nine leaf and growth-related traits were identified. Two QTL clusters were detected (the LG3 and LG5 clusters). Functional annotations further suggested two chlorophyll content-related candidate genes being identified in the LG5 cluster. Overall, this is the first study on the QTL mapping and identification of loci responsible for the regulation of leaf traits in M. rubra, offering an invaluable scientific for future marker-assisted selection breeding and candidate gene analyses