Search

Abstract Based on the idea of harmonic extraction, the problem of reducing the damage of the coal seam waiting for upward mining. Using the theoretical analysis method, a schematic diagram of coordinated mining along the dip direction of coal seam is established, and the calculation method of reasonable layout parameters of coal seam working face early mining is given. Based on the upward mining problem of the No.1 coal seam in the fifth panel of Zaoquan Coal Mine, the influence parameters of the No.2 coal seam, No.6 coal seam and No.7 coal seam mining on the No.1 coal seam were determined by similar simulation test. Then, the layout parameters of working face were determined. The research method of numerical calculation was used to evaluate the degree and uniformity of movement and deformation of the No.1 coal seam, combining five indicators: subsidence, horizontal movement, inclined deformation, curvature deformation, and horizontal deformation. The results indicate that when the working face is arranged using the layout parameters provided in this article, it can promote the further subsidence of the No.1 coal seam at the position of the remaining coal pillar. The movement and deformation indicators of the No.1 coal seam all reach the most uniform degree of the geological mining conditions, which can effectively offset the uneven deformation problem of the No.1 coal seam caused by the influence of the remaining coal pillars, making multiple mining operations a favorable condition for upward mining and achieving the goal of reducing the damage of the No.1 coal seam.

BackgroundIncreasing cases of diabetes, a general lack of routinely operational prevention, and a long history of separating disease prevention and treatment call for immediate engagement of frontier clinicians. This applies especially to village doctors who work in rural China where the majority of the nation’s vast population lives. ObjectiveThis study aims to develop and test an online Smart Web Aid for Preventing Type 2 Diabetes (SWAP-DM2) capable of addressing major barriers to applying proven interventions and integrating diabetes prevention into routine medical care. MethodsDevelopment of SWAP-DM2 used evolutionary prototyping. The design of the initial system was followed by refinement cycles featuring dynamic interaction between development of practical and effective standardized operation procedures (SOPs) for diabetes prevention and Web-based assistance for implementing the SOPs. The resulting SOPs incorporated proven diabetes prevention practices in a synergetic way. SWAP-DM2 provided support to village doctors ranging from simple educational webpages and record maintenance to relatively sophisticated risk scoring and personalized counseling. Evaluation of SWAP-DM2 used data collected at baseline and 6-month follow-up assessment: (1) audio recordings of service encounters; (2) structured exit surveys of patients’ knowledge, self-efficacy, and satisfaction; (3) measurement of fasting glucose, body mass index, and blood pressure; and (4) qualitative interviews with doctors and patients. Data analysis included (1) descriptive statistics of patients who received SWAP-DM2–assisted prevention and those newly diagnosed with prediabetes and diabetes; (2) comparison of the variables assessed between baseline and follow-up assessment; and (3) narratives of qualitative data. ResultsThe 17 participating village doctors identified 2219 patients with elevated diabetes risk. Of these, 84.85% (1885/2219) consented to a fasting glucose test with 1022 new prediabetes and 113 new diabetes diagnoses made within 6 months. The prediabetic patients showed substantial improvement from baseline to 6-month follow-up in vegetable intake (17.0%, 43/253 vs 88.7%, 205/231), calorie intake (1.6%, 4/253 vs 71.4%, 165/231), leisure-time exercises (6.3%, 16/253 vs 21.2%, 49/231), body weight (mean 62.12 kg, SD 9.85 vs mean 58.33 kg, SD 9.18), and body mass index (mean 24.80 kg/m2, SD 3.21 vs mean 23.36 kg/m2, SD 2.95). The prediabetic patients showed improvement in self-efficacy for modifying diet (mean 5.31, SD 2.81 vs mean 8.53, SD 2.25), increasing physical activities (mean 4.52, SD 3.35 vs mean 8.06, SD 2.38), engaging relatives (mean 3.93, SD 3.54 vs mean 6.93, SD 2.67), and knowledge about diabetes and risks of an imbalanced diet and inadequate physical activity. Most participating doctors and patients viewed SWAP-DM2 as useful and effective. ConclusionsSWAP-DM2 is helpful to village doctors, acceptable to patients, and effective in modifying immediate determinants of diabetes at least in the short term, and may provide a useful solution to the general lack of participation in diabetes prevention by frontier clinicians in rural China. Trial RegistrationInternational Standard Randomized Controlled Trial Number (ISRCTN): 66772711; http://www.controlled-trials.com/ISRCTN66772711 (Archived by WebCite at http://www.webcitation.org/6OMkAqyEy).

Obtaining mine pressure data through traditional monitoring methods and using statistical or machine learning algorithms to predict mine pressure can no longer meet the requirements of intelligent development in mines. It is necessary to seek new methods to improve the accuracy and real-time performance of mine pressure data monitoring and prediction. Based on three-dimensional similar physical model experiments, a distributed fiber optic monitoring system is constructed. The distributed fiber optic cables are pre-embedded along the model's direction and height. Pressure data is collected during the simulated mining process of the working face, and the optical fiber Brillouin frequency shift mean variation degree is introduced as an indicator to determine whether the pressure is coming. By preprocessing the optical fiber monitoring data such as noise removal, normalization and phase space reconstruction, the one-dimensional initial monitoring data is converted into three-dimensional data. The method uses Bayesian algorithm to iteratively optimize the parameters of the CatBoost algorithm. After reaching the maximum number of iterations, the optimal parameter combination is loaded into the CatBoost algorithm. The prediction model for mine pressure appearance is obtained by training. The results show that the Bayesian algorithm has fewer iterations and smaller errors than traditional grid search methods. Compared with random forest (RF), gradient boosting decision tree (GBDT) and extreme gradient boosting (XGBoost), the CatBoost algorithm has higher prediction accuracy and stronger generalization capability. The CatBoost mine pressure appearance prediction model optimized by the Bayesian algorithm can accurately predict the three weighting in the test set. The overall prediction trend is in line with the measured value, with mean absolute error of 0.0091, root-mean-square error of 0.0077, and determination coefficient of 0.933 9.

Rolling circle amplification is a widely used biosensing technique. Although various secondary structures have been employed in RCA, their effects on RCA efficiency have seldom been reported. Here, we find that stems in circular templates can strongly inhibit RCA, and the primer-stem distance is responsible for the inhibition. Based on the results, we propose an initiation inhibition mechanism and present a design principle for a general RCA assay. Inspired by this mechanism, we further propose a new nucleic acid detection method. The results verify that this method can increase RCA detection sensitivity according to the target recycling principle. Besides DNA detection, it can also achieve single mismatch discrimination of miRNA detection after optimization. This method also shows convenient visualization detection. The initiation inhibition of RCA could be helpful for RCA applications as promising detection techniques.

The traditional convergence instrument, 3D laser scanning and other monitoring technologies for the deformation of surrounding rock in the mine roadway can not meet the comprehensive monitoring requirements of complex projects. The technologies have low real-time and automatic monitoring degree, and do not have the capability of long-distance, high-precision and large-area monitoring. The existing optical fiber sensing technology only monitors the single parameter of the surrounding rock in the roadway. It can not comprehensively analyze the stability of the surrounding rock in the roadway. Taking the main adit of a coal mine as the engineering background, the stability of surrounding rock before and after the filling above the adit is studied by numerical simulation. The results show that the filling engineering causes the bearing pressure of surrounding rock on both sides of the adit to rise with asymmetric distribution. The maximum subsidence of the top plate increases from 8.3 mm before filling to 22.1 mm. The maximum floor heave increases from 4.0 mm to 8.5 mm. The maximum increase of the displacement of the two sides is 16.2 mm. The deformation of the surrounding rock corresponds strongly to the bearing pressure, which increases with the thickness of the filling above the adit. The fiber Bragg grating (FBG) sensor is used to construct the adit surrounding rock deformation monitoring system. The FBG sensor is set at the adit section to monitor the opening of the adit arch crown crack, the deformation of the roof, floor and both sides, and the stress and strain of the section. The local deformation of the surrounding rock is analyzed through the real-time spectrum. The results show that the adit roof is obviously under pressure under the influence of the disturbance of the overburden load under the existing condition of stone masonry arch support. The maximum subsidence of the roof is about 30 mm, forming a crack about 2 mm wide. The monitoring results are consistent with the numerical simulation and field observation results. The result verifies the effectiveness of the FBG-based adit surrounding rock stability monitoring method. According to the monitoring results, the reinforcement support scheme of bolt+T-shaped steel plate is proposed for the weak part of the adit support. The support effect is verified by numerical simulation. The results show that after the optimized support scheme, the maximum subsidence of the adit roof under the disturbance of overburden load is 11.3 mm. The maximum displacement of the two sides is 12.04 mm, and the average reduction of the surrounding rock deformation is 48.8%. The scheme improves the stability of the surrounding rock.

With the deepening of coal mining and the upsizing of mining equipment, the floor heave of the mining roadway has become an important problem that restricts the efficient and safe mining of the working face. It is of great significance to reveal the occurrence law of floor heave of the mining roadway for the stability control of the roadway floor. Based on the analysis of the deformation and failure characteristics of the mining roadway floor, com-bined with the key characteristics of the roadway floor heave, this paper studies the distributed optical fiber strain characterization method, and embeds the distributed sensing optical cable into the roadway floor through the borehole. Based on a large number of field measured data in the coal mine, the oc-currence of the roadway floor heave in the mining process of the working face is systematically analyzed. The results show that the distributed optical fiber has a positive strain peak and a negative strain peak respectively corresponding to the uncoordinated bending deformation characteristics of delamination and extrusion of the floor rock, and the local tension of the optical fiber corresponds to the crushing and extrusion expansion deformation characteristics of the floor rock. The strain value and strain growth rate of the optical fiber in the crushing characteristic area reflect the intensity of extrusion between the broken rock blocks. The evolution process of mining roadway floor heave is divided into three stages: disturbance, failure and relief uplift. The failure characteristics of floor strata in each stage are pointed out, and the key information of distributed optical fiber strain characteristic values in the crushing area in each stage is established. The conclusion of the study provides a new idea for the realization of large-scale distributed optical fiber monitoring of roadway surrounding rock, and has guiding significance for the floor heave control of mining roadway.

In order to study the roof stability of large-section open-off cut in lower slice of slicing mining, the 14 boreholes in the top coal of the 203 open-off cut in the lower slice of 1−2 coal seam in Huojitu Mine of Daliuta Mine is taken as the research background. The influence of the upper slice mining and the lower slice open-off cut driving on the plastic zone of the top coal of the open-off cut is analyzed by theoretical analysis, numerical simulation and field borehole peep technology. And the stability of the roof structure is evaluated by the rock mass integrity index. From the perspective of the top coal structure form, the top coal of the open-off cut is partially over-excavated or under-excavated due to the upper slicing mining. The maximum over-excavation of the open-off cut is 1.2 m, the maximum under-excavation is 0.8 m, and top-coal uneven rate is 27.7%. The result of theoretical analysis show that due to the influence of upper slice mining of the top coal of the open-off cut, the depth of plastic zone in the floor is 2.02 m. Due to the disturbance of the lower slice mining of the open-off cut, the depth of the plastic zone in the top coal is 1.50 m. Borehole peep results show that the plastic zone of the open-off cut top coal is divided into the theoretical plastic zone and the measured plastic zone according to the theoretical calculation and borehole peep respectively. Due to the influence of upper slice mining, the depth of the measured plastic zone in the floor is 1.06-2.04 m. Due to the disturbance of the lower slice mining of the open-off cut, the depth of the measured plastic zone in the top coal is 0.34-1.50 m. The measured plastic zone caused by the influence of upper slice mining on floor is 17.63% smaller than the theoretical plastic zone. The measured plastic zone of the top coal caused by the disturbance of lower slice mining of the open-off cut is 25.82% smaller than the theoretical plastic zone. The result of numerical simulation analysis shows that due to the influence of upper slice mining, the depth of plastic zone in the floor is 1-2 m. Due to the disturbance of the lower slice mining of the open-off cut, the depth of plastic zone in the top coal is 1 m. The results obtained by the above three methods are highly consistent. The stability evaluation results of the top coal in the open-off cut show that the top coal integrity index ranges from 42.9% to 87.9%. The top coal thickness is positively correlated with the integrity index and negatively correlated with the fracture development. The proportion of top coal integrity evaluation as good or above is more than 1/2, indicating that the overall structure of top coal is basically complete. The research results can provide reference for the design of top coal thickness retention standard and support scheme of large section open-off cut in lower slice of slicing mining under similar mining conditions.

In the process of using optical fiber frequency shift value monitored by optical fiber sensor to characterize the strata behaviors law, the data collected by the sensor is missing, and the strata behaviors law can not be accurately predicted. In order to solve this problem, taking Qianqiu Coal Mine as the engineering background, under the premise of partial data loss of the lower half of the optical fiber, two prediction models, GRU (Gated Recurrent Unit) and LSTM (Long Short-Term Memory), are introduced to compare and predict the missing optical fiber frequency shift value. The convergence speed of the GRU model is better than that of the LSTM model, which shows that the missing value processing method based on the GRU model is better. The original and complete optical fiber frequency shift value is converted into the average optical fiber frequency shift change which can characterize the strata behaviors position, and the XGBoost (eXtreme Gradient Boosting) model and the BP neural network model are introduced for comparative prediction. The XGBoost model can predict all the 'peak' positions in the test set accurately. However, the BP neural network model can only predict two 'peak' positions, which shows that the prediction effect of the XGBoost model is better than that of the BP neural network model. The predicted optical fiber frequency shift missing value is replaced to the missing position to form 'complete' optical fiber frequency shift value data. The data is converted into the average optical fiber frequency shift change and then the XGBoost model is used for prediction. The results show that both the LSTM model and the GRU model can predict the data of the lower half of the optical fiber accurately, and the GRU model has higher accuracy than the LSTM model. The XGBoost model can predict the periodic pressure in the test set accurately. After the missing data predicted by the GRU model is integrated into the missing position, the XGBoost model can still predict the strata behaviors effectively.

High-quality, chromosome-scale genomes are essential for genomic analyses. Analyses, including 3D genomics, epigenetics, and comparative genomics rely on a high-quality genome assembly, which is often accomplished with the assistance of Hi-C data. Curation of genomes reveal that current Hi-C-assisted scaffolding algorithms either generate ordering and orientation errors or fail to assemble high-quality chromosome-level scaffolds. Here, we offer the software Puzzle Hi-C, which uses Hi-C reads to accurately assign contigs or scaffolds to chromosomes. Puzzle Hi-C uses the triangle region instead of the square region to count interactions in a Hi-C heatmap. This strategy dramatically diminishes scaffolding interference caused by long-range interactions. This software also introduces a dynamic, triangle window strategy during assembly. Initially small, the window expands with interactions to produce more effective clustering. Puzzle Hi-C outperforms available scaffolding tools. [ABSTRACT FROM AUTHOR]