A Novel Model of the Ideal Point Method Coupled with Objective and Subjective Weighting Method for Evaluation of Surrounding Rock Stability

The classification of surrounding rock stability is the critical problem in tunneling engineering. In order to decrease engineering disasters, the surrounding rock stability should be accurately evaluated. The ideal point method is applied to the classification of surrounding rock stability. Considering the complexity of surrounding rock classification, some factors such as rock uniaxial compressive strengthen, integrality coefficient of rock mass, the angle between tunnel axis and the main joint, joints condition, and seepage measurement of groundwater are selected as evaluation indices. The weight coefficients of these evaluation indices are determined by the objective and subjective weighting method, consisting with the delphi method and the information entropy theory. The objective and subjective weighting method is exact and reliable to determine the weights of evaluation indices, considering not only the expert’s experiences, but also objectivity of the field test data. A new composite model is established for evaluating the surrounding rock stability based on the ideal point method and the objective and subjective weighting method. The present model is applied to Beigu mountain tunnel in Jiangsu province, China. The result is in good agreement with practical situation of surrounding rock, which proves that the ideal point method used to classify the surrounding rock in tunnels is reasonable and effective. The present model is simple and has very strong operability, which possesses a good prospect of engineering application

Informed anytime fast marching tree for asymptotically-optimal motion planning

In many applications, it is necessary for motion planning planners to get high-quality solutions in high-dimensional complex problems. In this paper, we propose an anytime asymptotically-optimal sampling-based algorithm, namely Informed Anytime Fast Marching Tree (IAFMT*), designed for solving motion planning problems. Employing a hybrid incremental search and a dynamic optimal search, the IAFMT* fast finds a feasible solution, if time permits, it can efficiently improve the solution toward the optimal solution. This paper also presents the theoretical analysis of probabilistic completeness, asymptotic optimality, and computational complexity on the proposed algorithm. Its ability to converge to a high-quality solution with the efficiency, stability, and self-adaptability has been tested by challenging simulations and a humanoid mobile robot

Genome-wide identification of the heat shock transcription factor gene family in two kiwifruit species

High temperatures have a significant impact on plant growth and metabolism. In recent years, the fruit industry has faced a serious threat due to high-temperature stress on fruit plants caused by global warming. In the present study, we explored the molecular regulatory mechanisms that contribute to high-temperature tolerance in kiwifruit. A total of 36 Hsf genes were identified in the A. chinensis (Ac) genome, while 41 Hsf genes were found in the A. eriantha (Ae) genome. Phylogenetic analysis revealed the clustering of kiwifruit Hsfs into three distinct groups (groups A, B, and C). Synteny analysis indicated that the expansion of the Hsf gene family in the Ac and Ae genomes was primarily driven by whole genome duplication (WGD). Analysis of the gene expression profiles revealed a close relationship between the expression levels of Hsf genes and various plant tissues and stress treatments throughout fruit ripening. Subcellular localization analysis demonstrated that GFP-AcHsfA2a/AcHsfA7b and AcHsfA2a/AcHsfA7b -GFP were localized in the nucleus, while GFP-AcHsfA2a was also observed in the cytoplasm of Arabidopsis protoplasts. The results of real-time quantitative polymerase chain reaction (RT-qPCR) and dual-luciferase reporter assay revealed that the majority of Hsf genes, especially AcHsfA2a, were expressed under high-temperature conditions. In conclusion, our findings establish a theoretical foundation for analyzing the potential role of Hsfs in high-temperature stress tolerance in kiwifruit. This study also offers valuable information to aid plant breeders in the development of heat-stress-resistant plant materials

A novel risk stratification model for STEMI after primary PCI: global longitudinal strain and deep neural network assisted myocardial contrast echocardiography quantitative analysis

BackgroundIn ST-segment elevation myocardial infarction (STEMI) with the restoration of TIMI 3 flow by percutaneous coronary intervention (PCI), visually defined microvascular obstruction (MVO) was shown to be the predictor of poor prognosis, but not an ideal risk stratification method. We intend to introduce deep neural network (DNN) assisted myocardial contrast echocardiography (MCE) quantitative analysis and propose a better risk stratification model.Methods194 STEMI patients with successful primary PCI with at least 6 months follow-up were included. MCE was performed within 48 h after PCI. The major adverse cardiovascular events (MACE) were defined as cardiac death, congestive heart failure, reinfarction, stroke, and recurrent angina. The perfusion parameters were derived from a DNN-based myocardial segmentation framework. Three patterns of visual microvascular perfusion (MVP) qualitative analysis: normal, delay, and MVO. Clinical markers and imaging features, including global longitudinal strain (GLS) were analyzed. A calculator for risk was constructed and validated with bootstrap resampling.ResultsThe time-cost for processing 7,403 MCE frames is 773 s. The correlation coefficients of microvascular blood flow (MBF) were 0.99 to 0.97 for intra-observer and inter-observer variability. 38 patients met MACE in 6-month follow-up. We proposed A risk prediction model based on MBF [HR: 0.93 (0.91–0.95)] in culprit lesion areas and GLS [HR: 0.80 (0.73–0.88)]. At the best risk threshold of 40%, the AUC was 0.95 (sensitivity: 0.84, specificity: 0.94), better than visual MVP method (AUC: 0.70, Sensitivity: 0.89, Specificity: 0.40, IDI: −0.49). The Kaplan-Meier curves showed that the proposed risk prediction model allowed for better risk stratification.ConclusionThe MBF + GLS model allowed more accurate risk stratification of STEMI after PCI than visual qualitative analysis. The DNN-assisted MCE quantitative analysis is an objective, efficient and reproducible method to evaluate microvascular perfusion

Functional Characterization of MicroRNA-27a-3p Expression in Human Polycystic Ovary Syndrome

The goal of this study was to characterize the function of microRNA-27a-3p (miR-27a-3p) in polycystic ovary syndrome (PCOS). miR-27a-3p expression was analyzed in excised granulosa cells (GCs) from 21 patients with PCOS and 12 normal patients undergoing in vitro fertilization cycle treatments and in 17 nontreated cuneiform ovarian resection PCOS samples and 13 control ovarian samples from patients without PCOS. We found that the expression of miR-27a-3p was significantly increased in both excised GCs and the ovaries of patients with PCOS compared with the controls. Insulin treatment of the human granulosa-like tumor cell line (KGN) resulted in decreased downregulated expression of miR-27a-3p, and this effect appeared to be mediated by signal transducer and activator of transcription STAT1 and STAT3. The overexpression of miR-27a-3p in KGN cells inhibited SMAD5, which in turn decreased cell proliferation and promoted cell apoptosis. After KGN cells were stimulated with insulin for 48 hours, there was increased expression of SMAD5 protein and decreased apoptosis. Additionally, knockdown/overexpression of SMAD5 in KGN cells reduced/increased cell number and promoted/inhibited cell apoptosis. Insulin-stimulated primary GCs isolated from patients with PCOS, in contrast to normal GCs or KGN cells, did not exhibit decreased miR-27a-3p expression. The differences in the expression levels in KGN cells and human PCOS GCs are likely explained by increased miR-27a-3p expression in the GCs caused by insulin resistance in PCOS. Taken together, our data provided evidence for a functional role of miR-27a-3p in the GCs' dysfunction that occurs in patients with PCOS

Estimating the Effect of Fractal Dimension on Representative Elementary Volume of Randomly Distributed Rock Fracture Networks

The effect of fractal dimension (Df) on the determination of representative elementary volume (REV) was investigated through numerical experimentations, in which a new method was adopted to extract submodels that have different length-width ratios from original discrete facture networks (DFNs). Fluid flow in 1610 DFNs with different geometric characteristics of fractures and length-width ratios was simulated, and the equivalent permeability was calculated. The results show that the average equivalent permeability (KREV) at the REV size for DFNs increases with the increase in Df. The KREV shows a downward trend with increasing length-width ratio of the submodel. A strong exponent functional relationship is found between the REV size and Df. The REV size decreases with increasing Df. With the increment of the length-width ratio of submodels, the REV size shows a decreasing trend. The effects of length-width ratio and Df on the REV size can be negligible when Df≥1.5, but are significant when Df<1.5

Laboratory Investigation of Granite Permeability after High-Temperature Exposure

This study experimentally analysed the influence of temperature levels (200, 300, 400, 500, 600, and 800 &deg;C) on the permeability of granite samples. At each temperature level, the applied confining pressure was in the range of 10&ndash;30 MPa, and the inlet hydraulic pressure varied below the corresponding confining pressure. The results are as follows: (i) With an increase in the temperature level, induced micro-fractures in the granites develop, and the decrement ratios of both the P-wave velocity and the density of the granite increase; (ii) The relationship between the volume flow rate and the pressure gradient is demonstrably linear and fits very well with Darcy&rsquo;s law. The equivalent permeability coefficient shows an increasing trend with the temperature, and it can be best described using the mathematical expression K0 = A &times; 1.01T; (iii) For a given temperature level, as the confining pressure increases, the transmissivity shows a decrease, and the rate of its decrease diminishes gradually