Pattern of Influence of the Mining Direction of the Protective Seam on the Stress of the Surrounding Rock

The maximum principal stress of the original rock has obvious directionality, and the pressure relief effect is different when the protective seam is mined along different directions. In this paper, the Fast Lagrangian Analysis of Continua (FLAC3D 6.0) numerical simulation software was used to establish a numerical calculation model according to the actual stratum conditions of the Pingdingshan No. 8 Coal Mine. The distribution and evolutionary characteristics of three-dimensional stress and three-dimensional displacement of the stope are studied under the condition that the mining direction of the protective seam is parallel to or vertical to the maximum principal stress direction of the original rock; the pattern of influence of the mining direction on the pressure relief and outburst prevention effect of the protective seam mining is analyzed. For the protective seam, the maximum principal stress in the coal in front of the protective seam cut–hole is significantly reduced, and the outburst potential is reduced in parallel mining. However, in vertical mining, the maximum principal stress in the coal in front of the protective seam cut–hole increases significantly, and the outburst potential increases. For the protective seam and surrounding rock, parallel mining can more fully reduce the maximum principal stress of the protective seam, reduce the difference in the three-dimensional stress, and effectively reduce the outburst potential of the protective seam. Therefore, parallel mining can not only improve the safety of the protective seam but also improve the pressure relief and outburst prevention effect of the protective seam. This conclusion is verified by the outburst prevention effect of the parallel mining of the remote upper protective seam in the Pingdingshan No. 8 Coal Mine. The research results are helpful for optimizing mine outburst potential prevention and control work from the aspect of mining layout. Through parallel mining, the outburst potential of the mine can be effectively reduced overall

Sensitively humidity-driven actuator and sensor derived from natural skin system

Precise control over the smart materials exhibiting reversible shape changes in response to environmental stimuli presents a considerable challenge. Here, with a self-assembly strategy by extracting natural materials from pigskin, a single layer bio-inspired, transparent, soft biological film (BF) with the primary characteristics of self-actuation and self-sensing is successfully developed. The self-assembly constructed BF can exchange water and reflect environmental humidity gradients rapidly to activate continuous rotary movement. Temperature which affects the thermal motion of water molecules will induce different orientation movement of the film, and on this basis, a humidity-driven energy transfer motor is developed. More characterizations highlight the behavior mechanism of BF through water exchanging by a hydrogen bonding interaction with the hydrophilic group of amino acids residues on the BF surface. Finally, a wearable, steady and ultrafast-response sensor to detect human breathing, especially for real-time obstructive sleep apnea (OSA) state, is fabricated. This study offers great potential in emerging applications including micro-sensors, switches, soft robots and power source technologies

Hydrothermal synthesis of nitrogen-doped carbon dots as a sensitive fluorescent probe for the rapid, selective determination of Hg²⁺

<p>In the present work, a green synthetic method for producing nitrogen-doped carbon dots (NCDs) by using ammonium citrate and urea is introduced. The obtained NCDs were characterised by transmission electron microscopy, Fourier transform infrared spectra, UV–vis absorption and fluorescence spectra. The results showed that the prepared NCDs were spherical with a size of about 3.5 nm, emitting strong and stable blue fluorescence when excited at 352 nm. It was noting that the NCDs enable sensitive and selective determination of Hg²⁺ in tap water with a linear range of 0.01–5 mg L⁻¹ based on a possible charge transfer process. The detection limit was 9.4 µg L⁻¹.</p

Hydrothermal synthesis of fluorescent nitrogen-doped carbon quantum dots from ascorbic acid and valine for selective determination of picric acid in water samples

<p>Nitrogen doped carbon quantum dots (N-CQDs) were synthesised by a hydrothermal method using ascorbic acid and valine as precursors. The as-synthesised N-CQDs were characterised by transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, UV−vis absorption spectra, as well as fluorescence spectrophotometer. The results revealed that the as-prepared N-CQDs were spherical shaped with an average diameter of 4 nm and emitted bright blue photoluminescence with a quantum yield of approximately 4.8 %. Additionally, we found that the fluorescence of the N-CQDs was intensively quenched by the addition of picric acid (PA). The decrease of the fluorescence intensity made it possible to determine PA in the linear range of 0.06–7.81 µg ml^–¹ based on the fluorescence resonance energy transfer between PA and N-CQDs. The detection limit was as low as 11.46 ng ml^–¹. The proposed approach was further successfully applied for the determination of PA in water sample collected from Fenhe river for public safety and security, suggesting its great potential towards water routine analysis.</p

Large-Area Full-Coverage Remote Sensing Image Collection Filtering Algorithm for Individual Demands

Remote sensing is the main technical means for urban researchers and planners to effectively observe targeted urban areas. Generally, it is difficult for only one image to cover a whole urban area and one image cannot support the demands of urban planning tasks for spatial statistical analysis of a whole city. Therefore, people often artificially find multiple images with complementary regions in an urban area on the premise of meeting the basic requirements for resolution, cloudiness, and timeliness. However, with the rapid increase of remote sensing satellites and data in recent years, time-consuming and low performance manual filter results have become more and more unacceptable. Therefore, the issue of efficiently and automatically selecting an optimal image collection from massive image data to meet individual demands of whole urban observation has become an urgent problem. To solve this problem, this paper proposes a large-area full-coverage remote sensing image collection filtering algorithm for individual demands (LFCF-ID). This algorithm achieves a new image filtering mode and solves the difficult problem of selecting a full-coverage remote sensing image collection from a vast amount of data. Additionally, this is the first study to achieve full-coverage image filtering that considers user preferences concerning spatial resolution, timeliness, and cloud percentage. The algorithm first quantitatively models demand indicators, such as cloudiness, timeliness, resolution, and coverage, and then coarsely filters the image collection according to the ranking of model scores to meet the different needs of different users for images. Then, relying on map gridding, the image collection is genetically optimized for individuals using a genetic algorithm (GA), which can quickly remove redundant images from the image collection to produce the final filtering result according to the fitness score. The proposed method is compared with manual filtering and greedy retrieval to verify its computing speed and filtering effect. The experiments show that the proposed method has great speed advantages over traditional methods and exceeds the results of manual filtering in terms of filtering effect