Unload Pull-out Test of Full-length Grouted Bolts in Slope Reconstruction and Expansion

The Unloading Pull-out Test Method (UPTM) is proposed to evaluate the residual stress of existing anchorage systems and explore the actual stable state of the slope before excavation. A series of destructive pull-out tests are applied to detect the working state of the existing rock bolts. The working load and ultimate load of the existing bolts are determined by field test measurement of the P-S curve. The experimental result showed that a displacement increment of the bolts was present in the elastic stage, the elastoplastic stage, the slip stage, and the debonding stage. The working load and the ultimate load were in the elastoplastic stage and the debonding stage respectively. The working load of the bolts is closely related to the sliding deformation. The ultimate load of the bolts, however, is only related to the design parameters, slope lithology and other factors. After 20 years of natural forces acting on the bolts in the slope, their ultimate bearing capacity had a stress loss of 24.0% ~ 32.0%

Optimization calculation of stope structure parameters based on Mathews stabilization graph method

Mathews stability graphic method, based on the rock classification system, measures the stability of the ore roof area of a relatively simple calculation method and provides a theoretical basis for mine rational design stope structure size parameters. In this study, we used a large-scale tungsten mine in Jiangxi Province as the engineering background and performed on-site engineering geological surveys and indoor ore rock mechanics tests in the middle section of mine 417 to obtain multiple engineering quality indicators for the mines and surrounding rocks. The Mathews stability map method and Barton limit span theory were used. The reasonable size range of the exposed face of the stope was calculated by performing theoretical analysis on the ultimate span. Then, FLAC3D calculation and analysis software were used for the simulation of the stope structure, and the most reasonable design of the exposed surface dimension was selected and used as reference for ensuring the safe production of the mine

A hybrid data assimilation system based on machine learning

In the earth sciences, numerical weather prediction (NWP) is the primary method of predicting future weather conditions, and its accuracy is affected by the initial conditions. Data assimilation (DA) can provide high-precision initial conditions for NWP. The hybrid 4DVar-EnKF is currently an advanced DA method used by many operational NWP centres. However, it has two major shortcomings: The complex development and maintenance of the tangent linear and adjoint models and the empirical combination of the results of 4DVar and EnKF. In this paper, a new hybrid DA method based on machine learning (HDA-ML) is presented to overcome these drawbacks. In the new method, the tangent linear and adjoint models in the 4DVar part of the hybrid algorithm can be easily obtained by using a bilinear neural network to replace the forecast model, and a CNN model is adopted to fuse the analysis of 4DVar and EnKF to adaptively obtain the optimal coefficient of combination rather than the empirical coefficient as in the traditional hybrid DA method. The hybrid DA methods are compared with the Lorenz-96 model using the true values as labels. The experimental results show that HDA-ML improves the assimilation performance and significantly reduces the time cost. Furthermore, using observations instead of the true values as labels in the training system is more realistic. The results show comparable assimilation performance to that in the experiments with the true values used as the labels. The experimental results show that the new method has great potential for application to operational NWP systems

Understanding how and under what circumstances decision coaching works for people making healthcare decisions: a realist review

Background - Decision coaching is non-directive support delivered by a trained healthcare provider to help people prepare to actively participate in making healthcare decisions. This study aimed to understand how and under what circumstances decision coaching works for people making healthcare decisions. Methods - We followed the realist review methodology for this study. This study was built on a Cochrane systematic review of the effectiveness of decision coaching interventions for people facing healthcare decisions. It involved six iterative steps: (1) develop the initial program theory; (2) search for evidence; (3) select, appraise, and prioritize studies; (4) extract and organize data; (5) synthesize evidence; and (6) consult stakeholders and draw conclusions. Results - We developed an initial program theory based on decision coaching theories and stakeholder feedback. Of the 2594 citations screened, we prioritized 27 papers for synthesis based on their relevance rating. To refine the program theory, we identified 12 context-mechanism-outcome (CMO) configurations. Essential mechanisms for decision coaching to be initiated include decision coaches’, patients’, and clinicians’ commitments to patients’ involvement in decision making and decision coaches’ knowledge and skills (four CMOs). CMOs during decision coaching are related to the patient (i.e., willing to confide, perceiving their decisional needs are recognized, acquiring knowledge, feeling supported), and the patient-decision coach interaction (i.e., exchanging information, sharing a common understanding of patient’s values) (five CMOs). After decision coaching, the patient’s progress in making or implementing a values-based preferred decision can be facilitated by the decision coach’s advocacy for the patient, and the patient’s deliberation upon options (two CMOs). Leadership support enables decision coaches to have access to essential resources to fulfill their role (one CMOs). Discussion - In the refined program theory, decision coaching works when there is strong leadership support and commitment from decision coaches, clinicians, and patients. Decision coaches need to be capable in coaching, encourage patients’ participation, build a trusting relationship with patients, and act as a liaison between patients and clinicians to facilitate patients’ progress in making or implementing an informed values-based preferred option. More empirical studies, especially qualitative and process evaluation studies, are needed to further refine the program theory

Ocean response offshore of Taiwan to super typhoon Nepartak (2016) based on multiple satellite and buoy observations

Multi-satellite and buoy observation data were used to systematically analyze the ocean response offshore of Taiwan to Super Typhoon Nepartak in 2016. The satellite data showed that a high sea surface temperature combined with a thick warm water layer and deep mixed layer provided a good thermal environment for continuous intensification of the typhoon. Two high-resolution buoys (NTU1 and NTU2) moored 375 and 175 km offshore of southeastern Taiwan were used to clarify the typhoon–ocean interaction as the typhoon approached Taiwan. The ocean conditions were similar at the two buoys before the typhoon, and both buoys were on the left side of the typhoon track and suffered similar typhoon factors (e.g., typhoon intensity and translation speed) during its passage. However, the ocean response differed significantly at the two buoys. During the forced period, the entire upper ocean was cooled at NTU1. In contrast, there was a clear three-layer vertical structure at NTU2 consisting of cool surface and deep layers with a warmer layer between the two cool layers. These responses can be attributed to strong upwelling of a cold eddy at NTU1 and vertical mixing at NTU2. These results indicate that, under similar preexisting conditions and typhoon factors, the movement of ocean eddies under typhoon forcing is an unexpected mechanism that results in upwelling and thus needs to be considered when predicting changes in the ocean environment and typhoon intensity

Pollen tube emergence is mediated by ovary-expressed ALCATRAZ in cucumber

Pollen tube guidance within female tissues of flowering plants can be divided into preovular guidance, ovular guidance and a connecting stage called pollen tube emergence. As yet, no female factor has been identified to positively regulate this transition process. In this study, we show that an ovary-expressed bHLH transcription factor Cucumis sativus ALCATRAZ (CsALC) functions in pollen tube emergence in cucumber. CsALC knockout mutants showed diminished pollen tube emergence, extremely reduced entry into ovules, and a 95% reduction in female fertility. Further examination showed two rapid alkalinization factors CsRALF4 and CsRALF19 were less expressed in Csalc ovaries compared to WT. Besides the loss of male fertility derived from precocious pollen tube rupture as in Arabidopsis, Csralf4 Csralf19 double mutants exhibited a 60% decrease in female fertility due to reduced pollen tube distribution and decreased ovule targeting efficiency. In brief, CsALC regulates female fertility and promotes CsRALF4/19 expression in the ovary during pollen tube guidance in cucumber. Pollen tube growth is guided towards ovules. Here the authors show that a bHLH transcriptional factor CsALC functions in pollen tube emergence towards ovules to regulate female fertility in cucumber and promotes the expression of two rapid alkalinization factors CsRALF4/19 in the ovary