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Since concrete infrastructure may lose its expected physical and functional properties over time, accurate inspection and assessment of such infrastructure systems is necessary to ensure safety and serviceability and prevent unsafe working conditions and the occurrence of hazards. In this paper, an experimental investigation was conducted on several concrete specimens under uniaxial compression to fully explore the fracture process and mechanical characteristics of concrete materials under compressive loading conditions. More specifically, a high-resolution industrial camera and a real-time geophysical acquisition system were employed to capture the fracture process and the microseismic (MS) and electromagnetic emission (EME) signals simultaneously. Based on digital image processing, a robust crack extraction algorithm was proposed for automatically identifying cracks on a concrete surface at the pixel level, and then two novel crack features were introduced to depict the dynamic crack propagation process quantitatively. Then, the correlation between MS, EME, stress drop and dynamic crack evolution characteristics was analyzed. The results indicate that: (1) the MS and EME signals of the concrete specimens have good consistency in the time domain, especially in the fully fractured stage; (2) the crack area, to a certain extent, can reflect the stress drop of a concrete specimen under the compression fracture process; (3) the crack propagation velocity parallel to the loading axis (along the vertical direction) is faster than that the perpendicular one to the loading axis (along the horizontal direction); and (4) the crack area, stress, MS signal, and EME signal reach their peak values nearly simultaneously. Finally, a novel mesh-free numerical model based on peridynamic (PD) theory was established to simulate the fracture process, and the displacement fields were presented to further reveal the failure mechanism of concrete under compressive loading. • A crack detection algorithm was proposed to identify cracks on the concrete surface. • Two crack morphological features were introduced to depict crack propagation. • The relationship of MS, EME, and crack propagation features has been investigated. • A Peridynamic model was built to simulate the fracture process of concrete. [ABSTRACT FROM AUTHOR]

Accurately detecting the presence and evolving boundaries of cracks on rock surfaces is critical for understanding the behavior of crack evolutions and facture mechanism of rock and rock-like material, which could cause engineering disasters if proper operation were not taken to deal with the evolving cracks. In this paper, we investigate the problem of vision-based automatic detection of cracks on rock surface at pixel-level, which is a preliminary step of crack evolution analysis. We build a Split Hopkinson Pressure Bar (SHPB) system to simulate the crack evolution process and capture the process as video data using a high frame camera, where a dataset of evolving cracks is created consisting of rock crack images that are manually labeled in pixel-level granularity. We propose a two-stage method to detect cracks in video data: the first stage employs Convolution Neural Network (CNN) based deep learning method to obtain preliminary results for each image frame while the second stage relies on novel variant Bayesian Inference to further refine the detection results. Specifically, in the first stage, a variant of U-Net model (denoted as CrackUNet) is developed to obtain intermediate classifications (crack or non-crack) that can better combine with other processing techniques for further improvement. Then in the second stage, a novel Spatial-Temporal Bayesian Inference (STBI) method is developed to further improve detection accuracy by taking advantages of the spatial and temporal correlations of the evolving cracks in video data. Experimental results show that the proposed method outperforms all the baselines. • A video dataset of evolving rock cracks is established. • A U-Net variant is developed for crack detection on the unique dataset. • Spatial-Temporal Bayesian Inference is proposed to further improve performance. [ABSTRACT FROM AUTHOR]

• The dynamic test of coal specimens with different beddings was conducted using SHPB. • The crack propagation properties of coal were analyzed using fractal theory. • Peridynamic theory was used to simulate the dynamic fracture properties of coal. To investigate the crack propagation and dynamic mechanical properties of coal under high strain rate loading, 24 sets of Brazilian disk (BD) coal specimens with vertical and horizontal beddings were made, and tests were conducted by a split Hopkinson pressure bar (SHPB) system. Under different impact velocities, a high-frame and high-resolution camera was employed to capture the fracture process, and two high-dynamic strain gauges were used to record the stress pulse signals simultaneously. Using one-dimensional stress wave theory, the dynamic mechanical properties of coal with different bedding directions under different impact velocities were analyzed and discussed. Experimental results indicate that bedding directions not only have a major influence on dynamic mechanical properties such as dynamic tensile strength, strain rate and strain energy but also have a great influence on the crack propagation path. Then, based on the image processing technique and fractal method, cracks conforming to the fractal have been proven, and the results further illustrate that the fractal dimension of cracks on the coal surface increased in the fracture process under SHPB loading. Finally, a numerical model based on bond-based Peridynamic theory was proposed to simulate crack propagation and dynamic mechanical properties of coal under the SHPB test, and the displacement-strain-stress fields were also calculated, which further reveal the fracture mechanism and dynamic behavior of coal under different impact loading conditions. [ABSTRACT FROM AUTHOR]

Coal and gas outburst is the mechanical damage behavior of gas-containing coal in a complex environment. In this paper, the established experimental system is used to carry out hammer damage experiments on coal adsorption of different gases under different gas pressures and analyze the mass distribution and surface area distribution characteristics of coal samples in each particle size interval after the hammer damage of coal samples. The energy of the crushing process was analyzed by using the specific work of crushing, mass of newly generated particle size added per unit of energy, newly added surface area per unit of energy, and newly added specific surface area per unit of energy. The results show that the crushing effect of gas-containing coal samples during hammer damage is related to the type and pressure of the adsorbed gas. The stronger the gas adsorption performance and the higher the gas pressure, the weaker the effect of gas-containing coal hammer damage. Meanwhile, the energy required for the mass and surface area of coal samples with newly generated particle size decreased, indicating that the stronger the gas adsorption and the higher the gas pressure, the more serious the energy dissipation in the hammering damage process of gas-containing coal samples. The research results are conducive to an in-depth understanding of the coal and gas outburst processes, which can provide a theoretical basis for the damage characteristics and energy dissipation of coal and gas outbursts., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Coalbed methane (CBM) is a clean energy source, but its utilization is inefficient due to the complexity and low accuracy of its emission prediction model. In this research, we constructed a mathematical model of gas emission from the excavation workface, and combined the experimental results to propose a new model for accurate and concise prediction. The new model was validated in the field workface and compared with the traditional prediction model. Moreover, the sensitivity of gas emission parameters and the participation ratio of gas emission sources were analyzed. The study results show that the new model has higher calculation accuracy than the old model prediction, with an average error reduction of 4.693%. In the excavation workface, the coal fall gas emission conforms to the negative power function equation, and the coal wall gas emission conforms to the negative exponential function equation. In the early stage of excavation, the proportion of coal fall gas emission is higher than that of coal wall gas emission, and the peak proportion reaches 58.5%. In the later stage, the proportion of coal fall gas emission gradually decreases to below 30%. The order of the sensitivity of gas emission parameters is coal wall gas initial velocity > coal fall gas decay coefficient > coal fall gas initial velocity > coal wall gas decay coefficient. The new model is successfully applied in engineering, which helps to improve the efficiency of coal mine gas disaster control and utilization., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Glucagon-like peptide-1 (GLP-1) can improve cardiac function and cardiovascular outcomes in diabetic cardiomyopathy; however, the beneficial effect of GLP-1 on human diabetic cardiomyocytes (DCMs) and its mechanism have not been fully elucidated. Here, the DCMs model by human-induced pluripotent stem cells-derived cardiomyocytes is developed. Two subtypes of GLP-1, GLP-1 7-36 and GLP-1 9-36 , are evaluated for their efficacy on the DCMs model. Diabetogenic condition is sufficient to induce most characteristics of diabetic cardiomyopathy in vitro, such as cardiac hypertrophy, lipid accumulation, impaired calcium transients, and abnormal electrophysiological properties. GLP-1 7-36 and GLP-1 9-36 can restore cardiomyocyte hypertrophic phenotype, impaired calcium transient frequency, abnormal action potential amplitude, depolarization, and repolarization velocity. Interestingly, RNA-seq reveals different pathways altered by GLP-1 7-36 and GLP-1 9-36 , respectively. Differentially expressed gene analysis reveals that possible targets of GLP-1 7-36 involve the regulation of mitotic nuclear division and extracellular matrix-receptor interaction, while possible targets of GLP-1 9-36 involve kinetochore assembly, and the complement and coagulation cascades. This study demonstrates the therapeutic effects of GLP-1 on human DCMs and provides a novel platform to unveil the cellular mechanisms of diabetic cardiomyopathy, shedding light on discovering better targets for novel therapeutic interventions., (© 2022 Wiley-VCH GmbH.)

A stainless steel template for the fabrication of plastic microfluidic devices has been developed by photolithography and chemical etching technique. The preparation process of the template is simple, rapid, and low-cost. The cross sectional profiles of raised microchannels on the template are trapezoidal. The surface roughness of the templates was controlled down to 190 nm. The template can be used repeatedly to generate devices reproducibly. The microfluidic devices of poly(methyl methacrylate) (PMMA) were fabricated by in situ polymerization using the templates. The reproducibility of the fabricated microchannel is high and the relative standard deviation is 0.7% by the in situ polymerization approach. Some physical properties of the polymerized microchannels were characterized including the transparency, the thermal deformation temperature, and the dimensional information. Current monitoring was used to evaluate the electroosmotic flow within the microchannels under the electric field strength of 300 V/cm.