吉林油田低注入井吸水剖面施工工艺控制

本文对吉林油田低注入井五参数测井过程中遇到的一些问题进行分析,并相应提出一系列行之有效的解决方法。     

SND生物脱氮过程N_2O的产生与关键酶及其活性

废水生物脱氮是目前水处理中重要的去除含氮废水的方法。随着国内外学者的深入研究,一些新型的生物脱氮工艺被开发和应用到污水处理中,从而经济高效地去除废水中的含氮污染物,达到国家的排放标准。同步硝化反硝化(SND)是具有发展潜力的新型脱氮工艺,但在运行过程中不可避免地会产生N2O。N2O是最重要的三种温室气体之一,其温室效应约为CO2的300倍。因此,在注重SND的脱氮效率的同时,也应该关注其产生的气态物对大气环境的影响。文章阐述了SND脱氮过程中N2O产生的机理及相关酶,并分析了SND工艺过程中主要影响N2O释放量的工艺因素。     

Auto-registration of medium and high spatial resolution satellite images by integrating improved SIFT and spatial consistency constraints

Feature-based methods have been developed in the past decades for the registration of optical satellite images. However, it is still a challenging problem to handle well the registration between medium and high spatial resolution images due to the large difference of the spatial structural features and local details for the same objects. In this study, an automated co-registration technique is proposed that integrates an improved SIFT (I-SIFT) and a novel matching strategy called spatial consistency constraints (SCC) to cope with the large difference in spatial resolutions between the image pair. Three constraints on angle, distance, and ratio are introduced to re the initial matching features obtained by I-SIFT. Three groups of experiments were conducted to validate the effectiveness of the proposed method. The experiments used high resolution multispectral and panoramic SPOT 5/6 images and Landsat 5/8 orthorectification images. Experimental results show that the registration error lies in about 1 pixel of high-resolution images and demonstrate that the proposed I-SIFT-SCC approach is suitable for fine registration of optical satellite images from medium spatial resolution to high spatial resolution with resolution ratio up to 6.     

Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.     

和成矿业洗矿系统改造实践

针对和成矿业井下原矿含泥量和含水量较大，且矿泥中存在绿泥石、高岭土等黏土类矿物，造成供矿系统粘堵严重，系统台时量仅为设计水平一半的问题，对原矿进行了洗矿工艺研究。通过洗矿工艺，将原矿中的矿块和矿泥分离，实现矿块和矿泥按粒度分选，彻底解决了供矿系统粘堵严重的问题，稳定了磨选系统给矿量。     

Evaluation of Scale and Corrosion Inhibition of Modified Polyaspartic Acid

Amino acid modified polyaspartic acids were evaluated as calcium-scale inhibitors. Feasibility of scale inhibition experiments was analyzed by molecular dynamics simulation and Gaussian optimization, and the scale inhibition mechanism was theoretically analyzed. Scale inhibition performance was studied by scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, static scale inhibition experiments, and electrochemical performance testing, which provided an experimental basis for the molecular dynamics simulation. The experimental results showed that Arg-SA-PASP has better scale inhibition and corrosion inhibition performance than His-SA-PASP. The scale inhibition effect increased with increasing concentration. Electrochemical tests indicated that Arg-SA-PASP is an excellent scale and corrosion inhibitor.