磁化水膜下滴灌对棉田水盐分布特征及棉花生长特性的影响

：通过田间小区磁化水滴灌试验，研究了磁化水膜下滴灌对土壤水盐分布特征、棉花生长特性及产量 的影响。结果表明：磁化水灌溉可以提高土壤含水量，促进棉花根系对水分的吸收，０&mdash;１００ｃｍ土层内磁化 强度为３ ０００Ｇｓ时的土壤含水量最大，保水效果最好。磁化水灌溉可以有效降低土壤盐分含量，加快土壤 盐分的淋洗，０&mdash;１００ｃｍ土层内各磁化水处理土壤平均含盐量表现为３ ０００Ｇｓ＜４ ０００Ｇｓ＜１ ０００Ｇｓ＜ ５ ０００Ｇｓ＜０Ｇｓ，磁化淡水处理的土壤脱盐率为２．７％～２８．２％，３ ０００Ｇｓ磁化处理的土壤脱盐率最高；磁化 微咸水处理的土壤积盐率为２１．７％～３３．９％。磁化水滴灌可以促进棉花生物量及产量的增长，淡水、微咸 水磁化处理的产量较未磁化处理增加了８．９８％～３１．４％，３ ０００Ｇｓ磁化处理下的棉花产量最高。从棉花生 长特征、产量、水分利用效率等方面综合考虑，３ ０００Ｇｓ为最佳磁化强度处理。</p

Electrochemical Preparation and&nbsp;Photo-Electro Catalytic Properties of Flexible ZnNi/Al-LDHs/Carbon Fibers Composite

本文采用电化学方法，制备了一种便于回收和分离的柔性锌镍/铝层状双羟基/碳纤维(ZnNi/Al-LDHs/CFs) 复合材料. 采用X 射线衍射、红外光谱、场发射扫描电镜、电感耦合等离子体原子发射光谱和电化学阻抗光谱技术表征了ZnNi/Al-LDHs/CFs 复合材料的结构、形貌和光电催化性能. 与单独使用Zn/Al-LDHs/CFs 作为光催化剂或Ni/Al-LDHs/CFs 作为电催化剂相比较，ZnNi/Al-LDHs/CFs 复合材料显示了良好的光-电双功能催化特性，既可被用作乙醇和甲醇氧化的电催化剂，也可光电协同催化 2，6-二氯苯酚降解. &nbsp;In this work, a promising flexible composite consisting of zinc (Zn), nickel (Ni) and aluminum (Al) layered double hydroxide coated carbon fibers (ZnNi/Al-LDHs/CFs) was prepared by electrochemical method with convenient recovery and separation. The structures, morphologies, and photo-electro catalytic properties of ZnNi/Al-LDHs/CFs were characterized by X-ray diffraction, infrared spectroscopy, field emission scanning electron microscopy, inductively coupled plasma atomic emission spectrometry and electrochemical impedance spectroscopy techniques. The excellent photo-electro bifunctional catalytic properties were obtained with the ZnNi/Al-LDHs/CFs composite as compared to that of Zn/Al-LDHs/CFs (photo catalyst) or Ni/Al-LDHs/CFs (electrocatalyst) alone, which could be used in the electro-catalytic oxidations of methanol and ethanol, as well as the photo-electro synergistically catalytic degradation of 2,6-dichlorophenol.国家自然科学基金&nbsp;(NSFC, No. U140710231)和国家级大学生创新训练计划项目 (No. 201710359028).National Natural Science Foundation of China (NSFC,&nbsp;No. U140710231) and National College students' innovative training program project (No. 201710359028).作者联系地址：合肥工业大学化学化工学院，合肥可控化学反应及材料化工重点实验室，安徽 合肥 230009Author's Address: Anhui Key Lab of Controllable Chemical Reaction &amp; Material Chemical Engineering, School of Chemistry and Chemical Engineering, Hefei University of Technology, Hefei 230009, Anhui, China通讯作者E-mail：[email protected]

面向对象的山区湖泊信息自动提取方法/A Method for Object - oriented Automatic Extraction of Lakes in the Mountain Area from Remote Sensing Image[J]

传统的水体信息提取主要利用水体反射与吸收光谱特征构建各种光谱指数模型,进行全局像元级的提取.然而,不同水体类型的光谱、空间形态与空间分布特征均有显著差异.对于山区图像而言,山体阴影、冰雪、裸岩等地物的干扰使全局性水体光谱指数模型难以取得很好的提取精度.面向对象的图像分析方法通过对遥感图像进行分割,从全域一局部上耦合分析水体的光谱、空间形态、空间分布与空间关系等特征,构建了通用性强的湖泊信息提取规则集,最终实现湖泊水体信息的自动化提取.通过eCognition软件对Landsat TM图像的实验结果表明,该方法可以完全避免像元级阈值水体信息提取中出现的一些错误的“零星水体”,自动且高效地提取出了山区湖泊水体信息,在无云情况下提取精度达95％以上