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Formic acid (FA) dehydrogenation and CO2 hydrogenation to FA/formate represent promising methodologies for the efficient and clean storage and release of hydrogen, forming a CO2‐neutral energy cycle. Here, we report the synthesis of highly dispersed and stable bimetallic Pd‐based nanoparticles, immobilized on self‐pillared silicalite‐1 (SP‐S‐1) zeolite nanosheets using an incipient wetness co‐impregnation technique. Owing to the highly accessible active sites, effective mass transfer, exceptional hydrophilicity, and the synergistic effect of the bimetallic species, the optimized PdCe0.2/SP‐S‐1 catalyst demonstrated unparalleled catalytic performance in both FA dehydrogenation and CO2 hydrogenation to formate. Remarkably, it achieved a hydrogen generation rate of 5974 molH2 molPd−1 h−1 and a formate production rate of 536 molformate molPd−1 h−1 at 50 °C, surpassing most previously reported heterogeneous catalysts under similar conditions. Density functional theory calculations reveal that the interfacial effect between Pd and cerium oxide clusters substantially reduces the activation barriers for both reactions, thereby increasing the catalytic performance. Our research not only showcases a compelling application of zeolite nanosheet‐supported bimetallic nanocatalysts in CO2‐mediated hydrogen storage and release but also contributes valuable insights towards the development of safe, efficient, and sustainable hydrogen technologies. [ABSTRACT FROM AUTHOR]

Polymer-plugging agents are widely employed in profile control and water-plugging measures, serving as a crucial component for efficient reservoir development. However, quantitatively monitoring the emplacement depth of polymer-plugging agents in low-permeability and high-permeability layers remains a challenging bottleneck. Presently, insufficient attention on shear thinning, a critical rheological property for water shut-off and profile control, has limited our understanding of polymer distribution laws. In this study, polymer shear-thinning experiments are firstly conducted to explore polymer variations with flow rate. The novelty of the research is that varying polymer viscosity is implemented instead of the fixed-fluid viscosity that is conventionally used. The fitted correlation is then integrated into the 2D and 3D heterogeneous numerical models for simulations, and a multivariate nonlinear regression analysis is performed based on the simulation results. The results show that lower polymer emplacement depth ratios corresponded to higher viscosity loss rates under the same flow rate. An increase in the initial permeability ratio corresponds to a decrease in the emplacement ratio, along with a reduction in the fraction of the plugging agent penetrating the low permeability formations. The model was applied to the Kunan Oilfield and demonstrated a polymer reduction of approximately 3000 tons compared to traditional methods. Despite the slightly complex nature of the multivariate nonlinear mathematical model, it presents clear advantages in controlling plugging agent distribution and estimating dosage, laying good theoretical ground for the effective and efficient recovery of subsurface resources. [ABSTRACT FROM AUTHOR]

Featured Application: (1) A gas explosion simulation combining the chemical reaction mechanism and tunnel structure is described; (2) the shock wave flow fields in tunnels with uneven walls and smooth walls are compared; and (3) the dynamic responses in tunnels with uneven walls and smooth walls are analyzed. A numerical simulation method combining the detailed chemical reaction mechanism of methane deflagration with an approximate real tunnel structure was proposed to confirm whether the unevenness of the tunnel wall during a coal mine gas explosion can be ignored. The approximate real tunnel model and smooth wall tunnel model were developed using 3D modeling methods. The propagation and attenuation processes of shock waves in the two tunnel models, as well as the different dynamic responses of the two tunnel walls, were compared and analyzed. Research results show that the non-uniformity of the tunnel wall decreases the shock wave overpressure and propagation velocity. The peak overpressure reduction value of the shock wave reaches 81.91 kPa, and the shock wave overpressure reaches its peak at an extended maximum time of 7.4 ms. The stress distribution on the approximate real tunnel wall is discontinuous, the propagation speed of stress waves in the bend tunnel is slower, and the duration of high load is relatively low. The displacement of the approximate real tunnel after gas explosion is lower than that of tunnels with smooth walls, and the displacement of most measuring points on the tunnel on the right is only 1/3–1/2 that of the smooth tunnel. [ABSTRACT FROM AUTHOR]

Accurate quantitative analysis and prediction of dust concentration in mines play a vital role in avoiding pneumoconiosis to a certain extent, improving industrial production efficiency, and protecting the ecological environment. The research has far-reaching significance for the prediction of dust concentration in mines in the future. Aiming at the shortcomings of the grey GM (1, 1) model in forecasting the data sequence with large random fluctuation, a grey Markov chain forecasting model is established. Firstly, considering the timeliness of monitoring data, the new dust concentration data is supplemented by using the method of cubic spline interpolation in the original data sequence. Therefore, the GM (1, 1) model is established by the method of metabolism. Then, the GM (1, 1) model is optimized by the theory of the Markov chain model. According to the relative error range generated during the prediction, the state interval is divided. Subsequently, the corresponding state probability transition matrix is constructed to obtain the grey Markov prediction model. The model was applied to the prediction of mine dust concentration and compared with the prediction results of the BP neural network model, grey prediction model, and ARIMA (1, 2, 1) model. The results showed that the prediction accuracy of the grey Markov model was significantly improved compared with other traditional prediction models. Therefore, the rationality and accuracy of this model in the prediction of mine dust concentration were verified.

In order to solve the security problems caused by malicious nodes in wireless sensor networks, a TS‐BRS reputation model based on time series analysis is proposed in this paper. By using the time series analysis method, the matching analysis of two time series is carried out to reduce the interference of channel conflicts on the reputation evaluation model and improve the accuracy of model recognition. In order to improve the adaptability of the evaluation model, the adaptive maintenance function μ is introduced into the update of credit value, which aggravates the influence of node behaviour on credit value at the present stage. The simulation results show that the new reputation evaluation model can effectively improve the detection rate and detection speed of malicious nodes in the network. After the introduction of maintenance function, the reputation value of the captured malicious nodes in the network has a faster convergence speed. [ABSTRACT FROM AUTHOR]

Featured Application: The XGBoost–GR–stacking gas outburst early warning model established in this article demonstrates high accuracy and practical performance, making it suitable for gas outburst risk warning in mining safety. To improve the accuracy of gas outburst early warning, this paper proposes a gas outburst risk warning model based on XGBoost–GR–stacking. The statistic is based on gas outburst data from 26 mines and establishes a data generation model based on XGBoost. The obtained virtual datasets are analyzed through visualization analysis and ROC curve analysis with respect to the original data. If the augmented data has an ROC area under the curve of 1, it indicates good predictive performance of the augmented data. Grey correlation analysis is used to calculate the grey correlation degrees between each indicator and the "gas emission". The indicator groups with correlation degrees greater than 0.670 are selected as the main control factor groups based on the sorting of correlation degrees. In this study, SVM, RF, XGBoost, and GBDT are selected as the original models for stacking. The original data and virtual data with correlation degrees greater than 0.670 are used as inputs for SVM, RF, XGBoost, GBDT, and stacking fusion models. The results show that the stacking fusion model has an MAE, MSE, and R2 of 0.031, 0.031, and 0.981. Comparing the actual and predicted values for each model, the stacking fusion model achieves the highest accuracy in gas outburst prediction and the best model fitting effect. [ABSTRACT FROM AUTHOR]

In order to solve the defects of traditional coal spontaneous combustion prevention technology in a closed goaf, a strain of aerobic endogenous bacteria was isolated from coal and used as a blocking raw material. Based on the metabolic and reproductive characteristics of microorganisms, the experimental study on the inhibition of coal spontaneous combustion by microorganisms was carried out. The colonies were isolated and purified by the dilution concentration plate method and the scribing plate method. The growth morphology of microorganisms was analyzed, and the growth curve was determined. The strains were identified by seamless cloning technology for high-throughput sequencing. The surface morphology of coal was analyzed by SEM, the differences of oxidation characteristic temperature points were analyzed by TG–DTG–DSC images, a programmed heating experiment was used to analyze the concentration of the indicator gas CO, and the changes in microscopic groups before and after microbial action were analyzed by FTIR and XPS spectra. Therefore, the inhibition of coal oxidation by endogenous bacteria was verified from macroscopic and microscopic perspectives. The results show that the coal bacteria isolated from the coal is Lysinibacilus sp. After the culture of Lysinibacilus sp., the surface of the coal demonstrated less detritus, and was relatively smooth. In the early stage of low temperature oxidation of coal spontaneous combustion, the characteristic temperature point of coal oxidation and the reaction between coal and O2 could be delayed by Lysinibacilus sp., and the total heat release was reduced in the combustion process. Not only that, Lysinibacilus sp. could also reduce the CO concentration during coal heating. After the coal was decomposed by Lysinibacilus sp., the C=C thick ring skeleton structure had little effect; however, the aromatic substitution pattern changed. This bacterium had an effect on the C-O bond, reducing the percentage of -CH2- and increasing the percentage of -CH3. It might also use the crystalline water in coal for life activities. The carboxyl carbon in coal changed the most, with a decrease of 12.03%, so it might become the carbon source required for microbial growth. The reproductive metabolism of microorganisms also affected the form of nitrogen, and the percentage of pyridine nitrogen in coal was reduced. The ratio of single-bond carbon to double-bond carbon in raw coal was about 3:2, but after this bacterial action, the ratio of the two was about 1:1. The analytical conclusions of XPS and FTIR spectra were consistent, and the results supported each other. [ABSTRACT FROM AUTHOR]

The analysis of geomagnetic suitability is the basis and premise of geomagnetic matching navigation and positioning. A geomagnetic suitability evaluation model using mixed sampling and an improved back propagation neural network (BPNN) based on the gray wolf optimization (GWO) algorithm by incorporating the dimension learning-based hunting (DLH) search strategy algorithm was proposed in this paper to accurately assess the geomagnetic suitability. Compared with the traditional geomagnetic suitability evaluation model, its generalization ability and accuracy were better improved. Firstly, the key indicators and matching labels used for geomagnetic suitability evaluation were analyzed, and an evaluation system was established. Then, a mixed sampling method based on the synthetic minority over-sampling technique (SMOTE) and Tomek Links was employed to extend the original dataset and construct a new dataset. Next, the dataset was divided into a training set and a test set, according to 7:3. The geomagnetic standard deviation, kurtosis coefficient, skewness coefficient, geomagnetic information entropy, geomagnetic roughness, variance of geomagnetic roughness, and correlation coefficient were used as input indicators and put into the DLH-GWO-BPNN model for model training with matching labels as output. Accuracy, recall, the ROC curve, and the AUC value were taken as evaluation indexes. Finally, PSO (Particle Swarm Optimization)-BPNN, WOA (Whale Optimization Algorithm)-BPNN, GA (Genetic Algorithm)-BPNN, and GWO-BPNN algorithms were selected as compared methods to verify the predictable ability of the DLH-GWO-BPNN. The accuracy ranking of the five models on the test set was as follows: PSO-BPNN (80.95 %) = WOA-BPNN (80.95%) < GA-BPNN (85.71%) = GWO-BPNN (85.71%) < DLH-GWO-BPNN (95.24%). The results indicate that the DLH-GWO-BPNN model can be used as a reliable method for underground geomagnetic suitability research, which can be applied to the research of geomagnetic matching navigation. [ABSTRACT FROM AUTHOR]

Featured Application: It solves the bottleneck problem of the low permeability of deep coal seams and the difficulty of coalbed methane mining, greatly improves the efficiency of coalbed methane mining, and reduces the risk of coal mining, which is of great significance to the project. To solve the bottleneck problem of low deep coal seam permeability and difficult coalbed methane (CBM) mining. Combining hydraulic splitting technology and directional drilling technology, a directional hydraulic splitting enhancement method of deep CBM mining was proposed. The selection equation for the directional hydraulic splitting of deep coalbed was constructed. The numerical simulation reveals the variation in coal fractures around different split angles. The split angle under the maximum coal damage effect was obtained. It was found that the combined effect of the double crack damage disturbance region led to reciprocal stress fluctuations during crack development and, eventually, the formation of a zigzag fracture. The larger the splitting angle, the larger the fissure development length and the larger the coal-damaged area. A double crack takes 25% less time to complete propagation than a single crack. When the splitting angle is 90°, the disturbed area occupies 2/3 of the area around the borehole, and the overall fracturing effect is the best. In the application process, the new directional hydraulic splitting technology can increase CBM mining by 5.08%, greatly improve CBM mining efficiency, and reduce the coal mining risk, which is of great significance to the project. [ABSTRACT FROM AUTHOR]

In order to investigate P-containing flame retardant on coal spontaneous combustion, trisodium phosphate, sodium hexametaphosphate, and ammonium polyphosphate were selected. Raw coal and inhibitor solution (10 wt%) were mixed at weight ratio 4:1. Coal (raw coal, inhibited coals) oxidation reaction was measured by own designed temperature-programming device. Simultaneous TG-DSC was carried out. Evolution of CO with increasing temperature and cross point temperature (CPT) were obtained of coal oxidation reaction; these results showed that the addition of (NaPO3)6 and ammonium polyphosphate (APP) to raw coal had an obvious suppression effect during low-temperature oxidation. CPT of APP-inhibited coal was 16°C higher than that of raw coal. TG-DTG curve results revealed that characteristic temperatures and mass fraction (ω) of APP-inhibited coal were significantly higher than other coal samples. Initial exothermal temperatures, thermal peak temperatures, and inhibition ratio were obtained from DSC curves. The results all demonstrated that APP had obvious inhibition effects on the whole coal oxidation. Infrared spectrograms of release gases showed that temperatures of the maximum release value and the whole quantity of gas products (CO2, CH4, CO, and H2O) were decreased due to the addition of APP by eliminating free radicals and diluting the amount of oxygen in the surrounding coal sample. [ABSTRACT FROM AUTHOR]

The impact force and effective impact area of are water jet are two important indexes for evaluating jet performance, and the outlet shape of the nozzle has a great influence on jet performance. In this study, five nozzles with different outlet shapes were designed, and water jet test experiments were conducted at different inlet pressures using an independently built water jet impact test platform, and the influence law of nozzle shape on the center impact pressure and flow coefficient of the water jet was investigated. The influence of nozzle shape on the effective impact area and entrainment rate of water jet was further investigated by numerical simulation. The results showed that the center impact pressure of the circular nozzle was the greatest when the inlet pressure and the target distance were small. The center impact pressure, the flow coefficient, and the effective area of the triangular nozzle with sharp edges were better than the traditional circular nozzle when the inlet pressure and the target distance were increased. Although the center impact pressure of the square nozzle is lower than that of the circular nozzle, its flow coefficient and effective impact area are higher than those of the circular nozzle with increasing target distance. The water jets of the elliptical and cross nozzles were the most divergent, and the jet performance was poor. [ABSTRACT FROM AUTHOR]

The technology of coal breaking and punching by a high-pressure water jet can increase the permeability of coal seam and prevent gas explosion accidents. As one of the key components of this technology, the structural parameters of the nozzle have an important effect on the performance of the water jet. At present, the relationship between multiple optimization indexes and structural parameters of the nozzle is mostly studied separately. In fact, the influence of the nozzle structural parameters on different optimization indexes is different. When there are multiple optimization indexes, they should be considered collaboratively to achieve the best water jet performance of the nozzle. Therefore, a multi−objective collaborative optimization method is proposed which takes the maximum velocity in X-axis and effective extension distance in Y-axis as the performance evaluation indexes of the water jet. The numerical simulation of the nozzle jet is carried out by computational fluid dynamics(CFD) method, and an orthogonal test database is established. The weight of multi-objective is analyzed, and the key structural parameters of the nozzle are optimized by the combination of BP (back propagation) neural network and genetic algorithms. The results show that the primary and secondary sequence of each structural parameter on is γ > θ > l ∕ d , which could reflect the comprehensive influence on the maximum velocity in the X-axis and effective extension distance in the Y-axis. The optimal structural parameters of the nozzle are, θ = 42.512°, l/d = 2.5608, γ = 12.431°. The field erosion experiment shows that compared with the original nozzle, the water jet performance of the optimized nozzle has been improved, the punching depth has been increased by 72.71%, and the punching diameter has been increased by 106.72%. This study provides a certain reference for the design and optimization of coal breaking and punching nozzle. [ABSTRACT FROM AUTHOR]

Karst cave collapse usually occurs during the process of drilling and reservoir development. Karst cave collapse increases drilling risk and seriously affects oil production. In order to reveal the collapse mechanism of karst caves in fractured-vuggy reservoirs in Tahe oil field, rock mechanic experiments and numerical simulation studies were conducted. In rock mechanic experiments, three types of rock mechanics tests (uniaxial compression, triaxial compression, and Brazilian splitting) were carried out to obtain the basic rock mechanics parameters. In numerical simulation studies, the collapse conditions of a single karst cave and a cave system were studied. Numerical simulation results indicate that for a single karst cave, the size and geometrical features of karst caves are the main factors influencing collapse condition. For a cave system, a combination pattern and distance between caves are two main factors affecting collapse condition. In order to facilitate the application of these research results, the authors present formulas for calculating the critical conditions of karst cave collapse by means of multivariate linear regression method. The calculation formulas and prediction chart were verified as consistent with actual field results. The research results in this paper have great theoretical and practical value for revealing the mechanism of karst cave collapse in fractured-vuggy carbonate reservoirs. [ABSTRACT FROM AUTHOR]

Coal seam gas pressure is one of the fundamental parameters used to assess coal seam gas occurrence and is an important index in assessing the risk of gas disaster. However, the geological characteristics of coal seams become increasingly complex with increasing mining degree, thus decreasing the accuracy and success rate of direct methods for measuring gas pressure. To address such issues, we have developed a new method for direct measurement of gas pressure in water-bearing coal seams. In particular, we developed a pressure measurement device based on theoretical analysis and quantified the basic parameters of the device based on well testing. Then, we verified the applicability of our method based on comparative analysis of the results of field experiments and indirect measurements. Our results demonstrate that this new method can resolve the effects of water pressure, coal slime, and other factors on the estimation of gas pressure. The performance of this new method is considerably better than that of traditional methods. In particular, field test results demonstrate that our method can accurately and efficiently measure gas pressure in water-bearing coal seams. These results will be of great significance in the prevention and control of coal seam gas disaster. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to investigate the role of Yes1 associated transcriptional regulator (YAP1) in the pathology of hepatocellular carcinoma (HCC) and its potential as a therapeutic target. Methods: YAP1 expression in HCC and adjacent tissues was determined via immunohistochemistry; in HCC and human normal liver cell lines, expression was examined via Western blotting. The effects of YAP1 knockdown and overexpression were detected following transfection of HCC cells with siRNA-YAP1 recombinants or pcDNA3.1-YAP1 plasmids. A tumor xenograft model was constructed by implanting YAP1-knockdown lentivirus-infected Hep-3B cells into nude mice, and the animals were treated with sorafenib. Results: In patients with HCC, YAP1 was upregulated in tumor tissue compared with adjacent tissue, and its high expression in the tumor was associated with increased Edmonson grade. In vitro, YAP1 expression was increased in Hep-3B, SK-HEP-1 and Huh7 cells, while it was similar in SMMC-7721 cells and LO2 cells. Meanwhile, YAP1 increased cell proliferation and invasion, promoted the progression of epithelial–mesenchymal transition, and inhibited cell apoptosis in HCC cells; furthermore, YAP1 knockdown combined with the administration of sorafenib decreased cell viability and increased cell apoptosis compared with YAP1 knockdown or treatment with sorafenib alone. In vivo, YAP1 knockdown inhibited tumor growth and metastasis, whereas it promoted apoptosis; meanwhile, YAP1 knockdown synergized with sorafenib to suppress tumor progression in HCC mice. Conclusion: YAP1 is upregulated in both HCC tumor tissues and cell lines. Moreover, it promotes cell proliferation and invasion and promoted the progression of epithelial–mesenchymal transition in vitro. Furthermore, targeting YAP1 inhibits HCC progression and improves sensitivity to sorafenib in vitro and in vivo. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the advantages and primary technical efficacy of an electromagnetic (EM) navigation system for computed tomography (CT)-guided thermal ablation of liver tumors. Material and methods: From August 2016 to January 2018, 40 patients scheduled for CT- guided thermal ablation were prospectively enrolled and divided into two groups. Twenty patients underwent CT-guided thermal ablation with an EM navigation system (navigation group), while the other 20 patients underwent conventional CT-guided thermal ablation (control group). Data on skin punctures, instrument adjustments, puncture time to target, CT scans, CT fluoroscopy time and dose-length-product (DLP) were compared between the two groups. Any postoperative complications were recorded and the primary technical efficacy was evaluated four to six weeks after the procedure. Results: All 20 patients in the navigation group successfully underwent EM navigation. Compared to the control group, there were fewer instrument adjustments (mean 2.40 vs. 4.95; p =.003), fewer CT scans (mean 7.10 vs. 10.30; p =.006), less CT fluoroscopy time (mean 40.47 vs. 59.98 s, p =.046), and less DLP (mean 807.39 vs. 1578.67 mGy × cm; p =.001). Although not statistically significant, EM navigation resulted in fewer skin punctures (mean 1.20 vs. 1.25; p =.803) and slightly longer puncture time to target (mean 16.50 vs. 15.20 min; p =.725). No patients experienced major complications and the primary efficacy rate was 90% and 84.21% in the navigation and control groups, respectively (p =.661). Conclusions: EM navigation system optimizes the thermal ablation process and reduces radiation exposure in patients. However, further studies are warranted to determine whether an EM navigation system can improve procedure time, complication rates, and primary technical efficiacy of thermal ablation. [ABSTRACT FROM AUTHOR]

Methane in coal seam is always under the dynamic process of adsorption and desorption. It has been demonstrated that the static blasting technology is an effective way to extract methane from coal. Although it is of great significance to understand the role of static blasting materials on methane extraction, the change of methane during static blasting is not well understood due to limited research studies. In this paper, we took the reaction pressure and heat from the hydration of the static blasting materials as the main factors. Microstructure changes in the static blasting materials and coal were analyzed by scanning electron microscopy, gas chromatography, infrared spectroscopy, and mercury injection. Changes of methane adsorption and adsorption rate before and after the static blasting were also measured. Our results demonstrated that the static blasting materials entered the microcracks of the coal body and the porosity of the coal was increased by heat expansion, improving methane migration. During the blasting process, methane began to desorb from the coal and its adsorption content was decreased. In contrast, the adsorption of methane was increased after the reaction. However, methane adsorption rate is higher than that of raw coal, indicating that the adsorbed methane is easier to convert into free methane, which is conducive to emission. This is of great significance to methane extraction and the safety of mines. [ABSTRACT FROM AUTHOR]