Status and development of UAV remote sensing technology in mining surface subsidence and fracture measuring
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摘要:
地下煤炭资源开发利用引发矿区地表沉陷与裂缝,不利于矿区生态环境保护和能源矿产持续稳定供应,对于矿区地表沉陷与裂缝的全面高效观测可提升采动地表损害认知水准、科学防治次生灾害。当前主流观测方法如地面测点人工施测、卫星遥感等存在人工作业强度高、造价昂贵、采集数据效率低等问题,卫星InSAR受波长限制难以获取大尺度变形。无人机遥感技术作为一种新兴地理信息获取方法,具备机动灵活、高效、可重复、全面覆盖等优势,在矿区地表沉陷与裂缝观测领域备受瞩目。系统梳理该领域国内外文献,分析前沿进展与发展态势,以促进矿山无人机遥感的技术革新与创新应用。首先,简要介绍无人机遥感技术要点及观测矿区地表沉陷与裂缝技术流程,无人机搭载可见光相机、激光雷达、红外热成像相机等传感器,生成数字高程模型(Digital Elevation Model, DEM)、数字正射影像(Digital Orthophoto Map, DOM)等遥感成果;在地表沉陷观测方面,分别列举文献案例分析沉陷区域地形获取、差分DEM沉陷模型及沉陷参数求取、水平位移观测3个方向的研究进展、技术难点与展望;在地表裂缝观测方面,介绍图像处理法、机器学习法与红外热成像观测识别裂缝的研究进展与问题;最终,从无人机遥感技术沉陷观测优势、裂缝背景噪声、裂缝预测及识别准确率、数据处理速度等方面展望未来发展方向。研究结果表明:① 无人机遥感技术可胜任矿区地表地形获取与沉陷观测,与InSAR等数据融合可提高沉陷参数求取精度;② 图像处理法、机器学习法等处理无人机遥感DOM可实现地表裂缝智能识别,深度学习被研究用于排除环境干扰、提高裂缝识别准确率;③ 地表水平位移与沉陷规律研究、裂缝识别率提高及其分布预测、航测数据的快速与自动化处理、多源遥感数据融合是该领域技术应用与研究的主要发展方向。无人机遥感技术在矿区地表沉陷与裂缝观测领域具有广阔前景,可从技术层面驱动矿山绿色、智能化发展转型。
Abstract:The development and utilization of underground coal resources can cause the mining area surface subsidence and fractures and other hazards, which is not conducive to the protection of ecological environment and the sustainable and stable supply of energy and minerals in mining areas. Comprehensive and efficient measuring of surface subsidence and fractures in mining areas can improve the awareness level of mining damage and scientifically prevent secondary disasters. At present, the mainstream measure methods, such as manual measure of ground observation points and satellite remote sensing, have problems such as high operation intensity and expensive cost, and InSAR is difficult to obtain large-scale deformation due to wavelength limitation. As a new method of geographic information acquisition, Unmanned Aerial Vehicle Remote Sensing (UAVRS) technology has the advantages of flexibility, efficiency, accuracy, repeatability, and comprehensive coverage, and has become a research hotspot in mining area surface subsidence and fractures measuring. Systematic review of domestic and abroad literatures and analysis of frontier progress and development trend are conducive to technological innovation and application in this field. Firstly, the main points of UAVRS and the technical process of measuring surface subsidence and fractures in mining areas are introduced briefly. The UAV is equipped with visible light camera, LiDAR, infrared thermal imaging camera and other sensors, generate remote sensing results such as Digital Elevation Model (DEM) and Digital Orthophoto Map (DOM); Then, in terms of surface subsidence measuring, the research progress, technical difficulties and prospects of terrain acquisition, differential DEM subsidence model, subsidence parameters acquisition and horizontal displacement measuring are analyzed by citing literature cases. In the field of surface fractures measuring, the research progress and problems of image processing, machine learning and infrared thermal imaging are introduced. Finally, the future development direction is forecasted from the advantages of UAVRS technology in subsidence measuring, fractures background noise, fractures prediction and identification accuracy, and data processing speed. Research shows that: (1) UAVRS technology is competent for surface topography acquisition and subsidence measuring in mining areas, and fusion with InSAR data can improve the measuring accuracy of subsidence parameters; (2) Based on DEM acquired by UAVRS, image processing and machine learning methods can realize intelligent recognition of surface fractures, and deep learning is studied to eliminate environmental interference and improve the accuracy of fractures recognition; (3) The research of surface horizontal displacement and subsidence law, the improvement of fracture identification rate and its distribution prediction, the rapid and automatic processing of aerial survey data, and the fusion of multi-source remote sensing data are the main development directions of technology application and research in this field. UAVRS technology has broad prospects in the field of mining surface subsidence and fractures measuring, can drive the transformation of green and intelligent development of mines from the technical level.
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Keywords:
- unmanned aerial vehicle /
- remote sensing /
- coal mining /
- surface subsidence /
- fracture detection
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0. 引 言
煤矸石是煤炭开采和分选过程中产生的工业固体废弃物,其化学组成主要为碳C (25%~30%)、硅SiO2 (40%~60%)、铝Al2O3 (15%~40%)等[1-2]。目前,针对煤矸石的资源化利用方式包括燃烧发电[3]、充填筑路[4]、建材生产[5]、农业利用[6]、元素回收[7]、功能材料制备[8]等。在这些利用过程中,对于煤矸石中无机灰分和有机质的资源化主要采用单独利用的方式,特别是在无机灰分的利用工艺中,通常也是先脱碳后利用,由此造成了碳排放量高、资源利用率低等的问题。而以煤矸石为原料,通过特定工艺制备碳−硅或碳−铝硅复合材料(如活性炭−介孔硅、活性炭−沸石等)是一种将煤矸石中无机质和有机碳耦合利用的高附加值利用方式。目前,关于煤矸石制备复合材料已有相关研究报道,如:崔明日等[9]以NaOH为活化剂,在Ar气氛下对煤矸石碱熔活化,后经NaOH水热反应,制得晶型完好的活性炭−沸石复合材料,对SO2吸附量为50.3 mg/g;ZHANG等[10]以KOH为活化剂,在N2气氛下对煤矸石进行酸浸−碱熔活化,得到多孔网状交联结构C/SiOx复合材料,在0.1 A/g下具有1175.8 mAh/g的高可逆容量,库仑效率达99.8%。LI等[11]以NaOH为活化剂,在CO2气氛下对煤矸石(辅以少量煤粉)碱熔活化,后经NaOH和NaAlO2水热反应制得比表面积为669.4 m2/g的活性炭−沸石复合材料,对Cu2+和罗丹明B的吸附量分别可达116.7 mg/g和32.8 mg/g;石凯等[12]以ZnCl2为活化剂,在He气氛下对煤矸石碱熔活化,后经HCl酸浸制得比表面积为412.23 m2/g,平均孔径为4.9 nm的活性炭−介孔硅复合材料,对罗丹明B的平衡吸附量达到49.81 mg/g。这些研究均证实了利用煤矸石制备复合材料的可行性;而且通过对比发现,以煤矸石为原料制备活性炭−介孔硅复合材料的工艺流程更为简单、产品性能更易调控。纵观现有研究,目前关于煤矸石制备活性炭−介孔硅复合材料的研究多侧重于制备工艺的建立和反应条件的探索,对于制备过程物相转变规律的认识尚不清晰,致使制备工艺的改进和优化方向难以确定,产品性能难以有效提升。
以煤矸石为主要原料,通过碱熔、酸浸等过程制备活性炭−介孔硅复合材料,考察了不同反应条件对煤矸石基活性炭−介孔硅复合材料孔容和比表面积的影响规律,并通过XRD、FTIR等分析方法研究了煤矸石基活性炭−介孔硅复合材料制备过程的物相转变机理,为煤矸石制备活性炭−介孔硅复合材料提供理论指导和技术支撑。
1. 试验部分
1.1 原料与试剂
试验所用煤矸石取自山西省朔州市中煤平朔安太堡露天煤矿选煤厂,经颚式破碎、行星式球磨后,粒径控制在<80 μm;粉磨样品于105 °C下烘干24 h后,贮于自封袋内保存备用。此外,试验所用其他化学试剂,如氢氧化钾(KOH)、盐酸(37% HCl)等,均为分析纯试剂。
采用GB/T 212—2008《煤的工业分析方法》对煤矸石进行了工业分析,并通过X射线荧光光谱仪测定了煤矸石的灰分组成,结果见表1。选用煤矸石原料的无机灰组成为:SiO2 (35.16%)、Al2O3 (25.90%)、Fe2O3 (3.81%)等,固定碳含量为13.04%。
表 1 煤矸石的工业分析及灰组成Table 1. Industrial analysis and ash composition of coal gangueMad/% Vad/% FCad/% 灰分组成及含量/% SiO2 Al2O3 Fe2O3 TiO2 MgO CaO K2O 其他 1.33 16.81 13.04 35.16 25.90 3.81 1.34 0.20 0.67 0.67 1.07 1.2 试验过程
以煤矸石为主要原料,通过碱熔、酸浸等过程制备活性炭−介孔硅复合材料的工艺流程如图1所示:
将煤矸石按照固液质量比为1∶5置于不同浓度(3.6~19.4 mol/L)KOH溶液中,于室温下搅拌24 h,经固液分离、干燥、研磨制得煤矸石浸渍样;在管式气氛滑轨炉(BTF-1200C-SC,安徽贝意克设备技术有限公司)中还原焙烧煤矸石浸渍样,焙烧气氛为N2气氛,焙烧温度为500~900 °C,焙烧时间为30~120 min;将煤矸石碱熔焙烧样按照固液质量比为1∶5置于不同浓度(1.4~7.8 mol/L)盐酸溶液中,在三口烧瓶中进行酸浸处理,酸浸温度为20~105 °C,酸浸时间为30~150 min;待到达反应设定时间后,将酸浸浆液进行固液分离,并用去离子水反复冲洗酸浸渣至中性,烘干所得样品即为活性炭−介孔硅复合材料(AC-SiO2)。
1.3 分析表征
比表面积与孔结构:采用Micromeritics公司制造的ASAP2460物理吸附仪(Brunner Emmet Teller Measurement,BET),对制得样品的比表面积、孔容和孔径进行测定分析,测定条件:样品经120 °C真空预处理8 h后,于−196 °C下进行N2吸脱附等温线测定,以相对压力范围为0.6~0.15的吸附等温线为基础,由相对压力为0.95时的液氮吸附值换算成液氮体积得到孔容V;通过Brunner Emmet Teller方法计算比表面积(SBET);基于非限定域密度泛函理论(NLDFT)计算样品微孔−介孔全范围分布[13]。
物相组成和特征基团分析:采用D2 PHASER型X射线衍射仪(X-ray Diffraction,XRD),对制得样品物相组成进行测定分析,测试条件:光源Cu Kα靶,电压30 kV,电流10 mA,扫描范围10°~80°,扫描间隔0.02°,步长0.1 s[14];采用Spectrum II傅里叶变换红外吸收光谱仪(Fourier Transform Infrared Spectroscopy,FTIR),对制得样品特征基团进行测定分析,测试条件:KBr压片法,激光功率1 mW,波长532 nm,扫描范围为4000~500 cm−1,分辨率 ≤ 2 cm−1[15]。
其他产品性能分析:采用JSM-7001F型热场发射扫描电子显微镜(Scanning Electron Microscope Energy Dispersive Spectrometer,SEM-EDS),对制得样品的微观形貌和元素分布进行测定分析,测试条件:待测样品通过导电胶固定于载样台上,经喷金预处理后,以背散射电子或二次电子成像模式观察样品形貌及其元素分布,电压10.0 kV,电流84.6 μA[16];采用754PC型紫外分光光度计(UV spectrophotometer),通过测定样品吸附反应前后溶液中甲基橙和罗丹明B的吸光度变化,评价AC-SiO2产品对不同分子量有机物的吸附性能,吸附条件:甲基橙或罗丹明B的初始质量浓度100 mg/L,pH=4,温度45 °C,吸附材料的投加量0.05 g/L[17-18]。
2. 结果与讨论
2.1 碱熔−酸浸条件对AC-SiO2孔容和比表面积的影响
对不同制备条件下所得AC-SiO2孔容和比表面积进行分析,结果如图2所示。
如图2所示,在碱熔过程中,随着KOH浸渍液浓度、焙烧温度、焙烧时间的增加,AC-SiO2的孔容和比表面积整体呈现上升趋势。其中,KOH浸渍液浓度对孔容和比表面积的影响较大,当浓度从3.6 mol/L增加至17.9 mol/L,AC-SiO2的比表面积由198.51 m2/g增加至782.1 m2/g,孔容由0.17 cm3/g增加至0.53 cm3/g;进一步提高浓度至19.6 mol/L,AC-SiO2的孔容和比表面积均不发生明显变化。而焙烧温度超过850 °C或者焙烧时间超过90 min后,AC-SiO2的孔容和比表面积均出现小幅下降,这可能与反应温度过高、反应时间过长导致样品发生熔融,导致孔道被堵塞有关。同样,在酸浸过程中,随着HCl酸浸浓度、酸浸温度、酸浸时间的增加,AC-SiO2的孔容和比表面积整体也呈现上升趋势。其中,HCl酸浸浓度对孔容和比表面积的影响较大,当浓度从1.4 mol/L增加至4.4 mol/L,AC-SiO2的比表面积由141.13 m2/g增加至627.40 m2/g,孔由0.2 cm3/g增加至0.51 cm3/g;进一步提高浓度超过6.0 mol/L时,AC-SiO2的孔容不发生明显变化,但比表面积出现一定程度下降,这可能与酸浸浓度过高导致溶出反应剧烈,介孔尺寸偏大有关。
2.2 煤矸石碱熔−酸浸过程物相转变
采用XRD分析方法,对煤矸石原料、焙烧样和酸浸渣进行物相组成测定,结果如图3所示。
煤矸石原样的物相组成主要包括石英(SiO2)、高岭石(Al2O3·2SiO2·2H2O)等。经KOH浸渍后,焙烧样的物相组成发生明显变化,高岭石衍射峰消失,而出现了钾霞石(KAlSiO4)和硅酸钾(K2SiO3)衍射峰,表明在此过程中发生了高岭石向钾霞石和硅酸钾物相的转变,具体反应见式(1)—式(2)[19]。焙烧样再经HCl酸浸处理后,钾霞石和硅酸钾物相溶解,其中KCl和AlCl3以离子形式存在于溶液,而SiO2则富集于酸浸渣,形成多孔的AC-SiO2产品,具体反应见式(3)—式(4)[19]。另外,酸浸渣的XRD图谱中,仅呈现漫反射“鼓包”,表明AC-SiO2产品主要以无定型形式存在[20]。
Al2O3⋅2SiO2⋅2H2O (高岭石) +2KOH→2KAlSiO4 (钾霞石) +3H2O (1) SiO2 (石英) +2KOH→K2SiO3 (硅酸钾) +H2O (2) KAlSiO4(钾霞石)+4HCl→SiO2(无定形硅)+KCl+AlCl3+2H2O (3) K2SiO3(硅酸钾)+2HCl→SiO2(无定形硅)+2KCl+H2O (4) 对不同碱熔−酸浸条件下制得AC-SiO2产品的物相组成进行分析,结果如图4所示。从图2和图4中可以看出,KOH浸渍液浓度和HCl酸浸浓度对AC-SiO2产品的孔容、比表面积和物相组成影响较大。在KOH浸渍液浓度较低(≤ 7.1 mol/L)或HCl酸浸浓度较低(≤1.4 mol/L)时,XRD图谱中仍有明显的石英或钾霞石衍射峰(图4a,图4b),前者是由于较少的KOH未能将石英完全转化所致,而后者则是由于较少的HCl未能将钾霞石完全溶解所致。相应地,该条件下制得AC-SiO2产品的孔容和比表面积均较小。当KOH浸渍液浓度超过10.7 mol/L,HCl酸浸浓度超过2.9 mol/L后, XRD图谱仅呈现无定形漫反射“鼓包”,说明原煤矸石经碱熔、酸浸处理后已转变为无定型结构;该条件下制得AC-SiO2的孔容和比表面积有所提升,但提升幅度仍有限。进一步提高KOH浸渍液浓度或HCl酸浸浓度,XRD图谱中漫反射“鼓包”逐渐宽化。特别是,当HCl酸浸浓度超过6 mol/L时,漫反射“鼓包”由原本集中分布在29°左右变为广泛分布在15°~35°,这主要与AC-SiO2产品中介孔硅占比逐渐提升有关。
此外,焙烧温度也将对AC-SiO2产品的孔容、比表面积和物相组成造成影响。当焙烧温度较低(≤ 600 °C)时,XRD图谱中仍呈现较弱的高岭石和石英衍射峰(图4c);相应地,AC-SiO2产品的孔容和比表面积均较小(图2c)。而当焙烧温度升高至800 °C后,高岭石和石英的衍射峰消失,AC-SiO2产品的孔容和比表面积也得到显著提升,表明煤矸石中的铝硅酸盐矿物的转化程度影响着AC-SiO2产品的孔容和比表面积。与KOH浸渍液浓度、HCl酸浸浓度和焙烧温度相比,焙烧时间、酸浸温度和酸浸时间等因素对AC-SiO2产品的孔容、比表面积和物相组成影响则较小。该结果与图2中碱熔−酸浸条件对AC-SiO2产品的孔容和比表面积影响规律一致。
2.3 煤矸石碱熔-酸浸过程特征基团变化
采用FT-IR对煤矸石原料、焙烧样和酸浸渣进行了分析,结果如图5所示。煤矸石原样在3692、3620和914 cm−1处存在吸收峰,是由煤矸石中高岭石矿相的羟基伸缩振动(外羟基、内羟基)和弯曲振动引起;1034、693和541 cm−1处呈现吸收峰,可归属于Si—O—Si、Al—O—Si或Al—O—Al的振动,表明煤矸石中含有大量铝硅酸盐物相;2921、2851和1383 cm−1处呈现吸收峰,源自于煤矸石中固定碳表面的C—H键伸缩振动和弯曲振动;而3432和1623 cm−1处吸收峰则是由于煤矸石样品中含有一定量的吸附水所导致的。KOH浸渍样经过焙烧处理后,羟基的特征吸收峰消失,C—H键的特征吸收峰变弱,且原本归属于高岭石中铝硅特征基团的吸收峰发生变化,这主要与焙烧样中生成大量钾霞石和硅酸钾(如1417 、987、891和693 cm−1)有关。焙烧样再经HCl酸浸处理后,钾霞石和硅酸钾的铝硅特征基团吸收峰消失,主要呈现1094 和964 cm−1处Si—O—Si反对称(对称)伸缩振动吸收峰和800 cm−1处Si—OH弯曲振动吸收峰,表明AC-SiO2产品中出现大量介孔硅[21];另外,在2921、2851和1383 cm−1处还保留有C—H键伸缩振动和弯曲振动的吸收峰,表明AC-SiO2产品中也含有一定量的活性炭。
对不同碱熔−酸浸条件下制得AC-SiO2产品的特征基团进行分析,结果如图6所示。从图6中可以看出, KOH浸渍液浓度、焙烧温度、焙烧时间、酸浸温度、酸浸时间对AC-SiO2产品的FT-IR图谱影响不显著,而不同HCl酸浸浓度下所得AC-SiO2产品的FT-IR图谱则呈现一定差异性。当HCl酸浸浓度为1.4 mol/L时,688 cm−1处呈现明显的吸收峰,可归属于Al—O振动,表明产品中尚存未被溶解的钾霞石;继续升高浓度超过2.9 mol/L后,则该吸收峰则消失。同时,随着HCl酸浸浓度从1.4 mol/L增加至4.4 mol/L,1012 cm−1处的Si−O−Si反对称伸缩振动吸收逐步偏移至1094 cm−1处,表明在此过程介孔硅的存在形态不断发生变化。该变化将导致AC-SiO2产品的孔容和比表面积不断增大(图2b)。
2.4 产品性能
综合考虑不同碱熔−酸浸条件下AC-SiO2的孔容和比表面积变化,得出制备煤矸石基AC-SiO2的优化反应条件,即:KOH浸渍液浓度为19.6 mol/L、焙烧温度为850 °C、焙烧时间为90 min、HCl酸浸浓度为6.0 mol/L、酸浸温度为105 °C、酸浸时间为120 min。在此条件下,计算AC-SiO2产品得率,即:100 g煤矸石浸渍后质量变为156.5 g(主要源自负载的氢氧化钠),浸渍样经焙烧处理后质量变为113.07 g(主要源自煤矸石挥发分脱除、高岭石脱羟基以及氢氧化钠分解),焙烧样再经酸浸处理后质量变为40.2 g(主要源自酸浸过程中含铝物相的溶出)。在此过程中,煤矸石中碳、硅组分基本无损失,转化率高达90.28%(少量损失主要源自碳受热分解);相应地,活性炭−介孔硅复合材料的产品得率与原煤矸石中碳、硅含量有关,产率可达40.2%。
对实验制得 AC-SiO2复合材料进行组分分析列于表2。从表2可以看出,AC-SiO2中主要包括固定碳16.89%和灰分 71.35%,其中灰分又以SiO2为主,即 AC-SiO2主要是由碳−硅组分构成。
表 2 AC-SiO2复合材料的工业分析及灰组成Table 2. Industrial analysis and ash composition of AC-SiO2Mad/% Vad/% FCad/% 灰分组成及含量/% SiO2 Al2O3 Fe2O3 TiO2 CaO K2O 其他 5.08 6.68 16.89 70.55 0.09 0.20 0.26 0.04 0.06 0.14 采用SEM-EDS考察了AC-SiO2的微观形貌以及碳、硅元素分布情况,结果如图7所示。从图7可以看出,AC-SiO2为不规则状颗粒,碳、硅元素在颗粒表面均匀分布,且颗粒表面分布着大小不一的孔道。通过测定AC-SiO2的N2气吸脱附曲线,发现所得吸脱附曲线为Ⅳ型标准曲线[22],并伴有因毛细凝聚现象出现的H4回滞环,证实了AC-SiO2表面孔道主要是由层状结构堆积形成(图8a)。
进一步考察了AC-SiO2的孔径分布,结果如图8所示。由图8分析可知,材料的比表面积可达835.1 m2/g,平均孔径为2.97 nm,总孔容为0.62 cm3/g,其中微孔和介孔各占近1/2。相较于孔径单一的活性炭或者介孔硅材料而言,AC-SiO2在吸附脱除多组分污染物方面的应用潜能更高。
选用分子量不同的甲基橙和罗丹明B作为目标污染物,在优化吸附条件下考察了AC-SiO2的吸附性能,结果如图9所示。由图9可知,当初始浓度100 mg/L、吸附剂投加量50 mg、温度45 °C、pH=4时,AC-SiO2对甲基橙和罗丹明B的吸附反应迅速进行,并在30 min左右达到吸附平衡,吸附容量分别为99.01 mg/g和99.87 mg/g。这进一步证实了所制得的AC-SiO2为多级孔材料,可用于吸附分子量不同的有机污染物。
3. 结 论
1)煤矸石基AC-SiO2制备过程中,原料所含的高岭石、石英经碱熔焙烧后生成钾霞石和硅酸钾物相,后在酸性溶液发生溶解,形成无定型硅渣;与此同时,煤矸石中的碳经碱熔焙烧后生成活性炭,同样保留于酸浸渣中。在此过程中,KOH浸渍液浓度、焙烧温度和HCl酸浸浓度显著影响AC-SiO2产品品质,当KOH浸渍液浓度低于10.7 mol/L或者焙烧温度低于700 °C时,煤矸石中铝硅物相活化不完全,将残留在AC-SiO2产品,导致AC-SiO2产品的孔容和比表面积较低;当HCl酸浸浓度低于2.9 mol/L时,焙烧样中钾铝硅酸盐溶解不完全,同样会对AC-SiO2产品的孔容和比表面积也将造成影响。
2)煤矸石经适宜条件的碱熔、酸浸等过程处理后,可制得AC-SiO2产品,优化反应条件为:KOH浸渍液浓度19.6 mol/L、焙烧温度850 °C、焙烧时间90 min、HCl酸浸浓度6.0 mol/L、酸浸温度105 °C、酸浸时间120 min;所制得的产品是由碳、硅为主要组分的复合材料,颗粒表面分布有层状结构堆积形成的微孔和介孔,比表面积可达835.1 m2/g,平均孔径为2.97 nm,总孔容为0.62 cm3/g,其中微孔和介孔各占近1/2;该材料可用于吸附分子量不同的有机污染物,对甲基橙和罗丹明B的吸附容量分别超过99.01 mg/g和99.87 mg/g。
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