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To solve the problems of difficult sealing, poor effect and low efficiency in the construction process of deep hole blasting with large inclination angle, a new type of fast sealing material and process of deep hole blasting are developed. The material has the characteristics of fast setting, easy transportation, early strength, etc. The material solidification time is shortened to 1.5 min under the condition of water-cement ratio 0.8∶1, the 1 h strength of the consolidated body can reach 3.2 MPa, the 2 h strength is up to 10.5 MPa, and the impact resistance of the material is analyzed. Combined with the new simple and fast pumping process for deep hole blasting sealing material, the fast and accurate requirements of sealing hole length can achieve. At the same time, the new material and technology are applied in the engineering practice. The field test results show that sealing a single blasting hole only takes 15 minutes, the number of hole sealing operators is reduced to 2, and it takes only 4 h to detonate three holes at a time, which reduces the difficulty of operation and the working time. The roof is complete after blasting, and the blasting effect is good.

Background: We reported the concept of patient‐specific deep learning (DL) for real‐time markerless tumor segmentation in image‐guided radiotherapy (IGRT). The method was aimed to control the attention of convolutional neural networks (CNNs) by artificial differences in co‐occurrence probability (CoOCP) in training datasets, that is, focusing CNN attention on soft tissues while ignoring bones. However, the effectiveness of this attention‐based data augmentation has not been confirmed by explainable techniques. Furthermore, compared to reasonable ground truths, the feasibility of tumor segmentation in clinical kilovolt (kV) X‐ray fluoroscopic (XF) images has not been confirmed. Purpose: The first aim of this paper was to present evidence that the proposed method provides an explanation and control of DL behavior. The second purpose was to validate the real‐time lung tumor segmentation in clinical kV XF images for IGRT. Methods: This retrospective study included 10 patients with lung cancer. Patient‐specific and XF angle‐specific image pairs comprising digitally reconstructed radiographs (DRRs) and projected‐clinical‐target‐volume (pCTV) images were calculated from four‐dimensional computer tomographic data and treatment planning information. The training datasets were primarily augmented by random overlay (RO) and noise injection (NI): RO aims to differentiate positional CoOCP in soft tissues and bones, and NI aims to make a difference in the frequency of occurrence of local and global image features. The CNNs for each patient‐and‐angle were automatically optimized in the DL training stage to transform the training DRRs into pCTV images. In the inference stage, the trained CNNs transformed the test XF images into pCTV images, thus identifying target positions and shapes. Results: The visual analysis of DL attention heatmaps for a test image demonstrated that our method focused CNN attention on soft tissue and global image features rather than bones and local features. The processing time for each patient‐and‐angle‐specific dataset in the training stage was ∼30 min, whereas that in the inference stage was 8 ms/frame. The estimated three‐dimensional 95 percentile tracking error, Jaccard index, and Hausdorff distance for 10 patients were 1.3–3.9 mm, 0.85–0.94, and 0.6–4.9 mm, respectively. Conclusions: The proposed attention‐based data augmentation with both RO and NI made the CNN behavior more explainable and more controllable. The results obtained demonstrated the feasibility of real‐time markerless lung tumor segmentation in kV XF images for IGRT. [ABSTRACT FROM AUTHOR]

High ice water content (HIWC) regions in tropical deep convective clouds, composed of high concentrations of small ice crystals, were not reproduced by Weather Research and Forecasting (WRF) model simulations at 1-km horizontal grid spacing using four different bulk microphysics schemes (i.e., the WRF single-moment 6-class microphysics scheme (WSM6), the Morrison scheme and the Predicted Particle Properties (P3) scheme with one-and two-ice options) for conditions encountered during the High Altitude Ice Crystals (HAIC)-HIWC experiment. Instead, overestimates of radar reflectivity and underestimates of ice number concentrations were realized. To explore formation mechanisms for large numbers of small ice crystals in tropical convection, a series of quasi-idealized WRF simulations varying the model resolution, aerosol profile, and representation of secondary ice production (SIP) processes are conducted based on an observed radiosonde released at Cayenne during the HAIC-HIWC field campaign. The P3 two-ice scheme, which has two "free" ice categories to represent all ice-phase hydrometeors, is used. Regardless of the horizontal grid spacing or aerosol profile used, without including SIP processes the model produces total ice number concentrations about two orders of magnitude less than observed at -10°C and about an order of magnitude less than observed at -30°C, but slightly overestimates the total ice number concentrations at -45°C. Three simulations including one of three SIP mechanisms separately (i.e., the Hallett-Mossop mechanism, fragmentation during ice-ice collisions, and shattering of freezing droplets) also do not replicate observed HIWCs, with the results of the simulation including shattering of freezing droplets most closely resembling the observations. The simulation including all three SIP processes successfully produces HIWC regions at all temperature levels remarkably consistent with the observations in terms of ice number concentrations and radar reflectivity, which is not replicated using the original P3 two-ice scheme. This simulation shows that primary ice production plays a key role in generating HIWC regions at t < 30 min at temperatures < -40°C, shattering of freezing droplets dominates ice particle production in HIWC regions at temperatures > -15°C during the early stage of convection, and fragmentation during ice-ice collisions dominates at temperatures > -15°C during the later stage of convection and at temperatures < -20°C over the whole convection period. This study confirms the dominant role of SIP processes in the formation of numerous small crystals in HIWC regions. [ABSTRACT FROM AUTHOR]

Regions with high ice water content (HIWC), composed of mainly small ice crystals, frequently occur over convective clouds in the tropics. Such regions can have median mass diameters (MMDs) < 300 μm and equivalent radar reflectivities < 20 dBZ. To explore formation mechanisms for these HIWCs, high resolution simulations of tropical convective clouds observed on 26 May 2015 during the High Altitude Ice Crystals - High Ice Water Content (HAIC-HIWC) international field campaign based out of Cayenne, French Guiana, are conducted using the Weather Research and Forecasting (WRF) model with four different bulk microphysics schemes: the WRF single-moment 6-class microphysics scheme (WSM6), the Morrison scheme and the Predicted Particle Properties (P3) scheme with one- and two-ice options. The simulations are evaluated against data from airborne radar and multiple cloud microphysics probes installed on the French Falcon 20 and Canadian National Research Council (NRC) Convair 580 sampling clouds at different heights. WRF simulations with different microphysics schemes generally reproduce the vertical profiles of temperature, dew-point temperature and winds during this event compared with radiosonde data, and the coverage and evolution of this tropical convective system compared to satellite retrievals. All of the simulations overestimate the intensity and spatial extent of radar reflectivity by over 30 % above the melting layer compared to the airborne X-band radar reflectivity data. They also miss the peak of the observed ice number distribution function for 0.1 < Dmax < 1 mm. Even though the P3 scheme has a very different approach representing ice, it does not produce greatly different total condensed water content or better comparison to other observations in this tropical convective system. Mixed-phase microphysical processes at -10 °C are associated with the overprediction of liquid water content in the simulations with the Morrison and P3 schemes. The ice water content at -10 °C increases mainly due to the collection of liquid water by ice particles, which does not increase ice particle number but increases the mass/size of ice particles and contributes to greater simulated radar reflectivity. [ABSTRACT FROM AUTHOR]