西太平洋深海海水中乙醛降解菌多样性及群落结构研究     

高波良  商谢谢  李丽  狄文婕  曾润颖 《海洋学报(英文版)》2018,37(8):54-64

As a major aldehyde pollutant widely existing in industry and our daily life, acetaldehyde is more and more harmful to human health. As characteristic habitat niche, bacteria from deep sea environments are abundant and distinctive in heredity, physiology and ecological functions. Thus, the development of acetaldehyde-degrading bacteria from deep sea provides a new method to harness acetaldehyde pollutant. Firstly, in this study,acetaldehyde-degrading bacteria in the deep sea water of the West Pacific Ocean were enriched in situ and in the laboratory respectively, and then the diversity of uncultured bacteria was studied by using 16 S r RNA genes. Then acetaldehyde-degrading strains were isolated from two samples, including enrichment in situ and enrichment in laboratory samples of deep sea water from the West Pacific Ocean using acetaldehyde as the sole carbon source,and then the ability of acetaldehyde degradation was detected. Our results showed that the main uncultured bacteria of two samples with different enrichment approaches were similar, including Proteobacteria,Actinobacteria, Firmicutes, Cyanobacteria, but the structure of bacterial community were significant different.Four subgroups, α, γ, δ and ε, were found in Proteobacteria group. The γ-Proteobacteria was dominant(63.5%clones in laboratory enriched sample, 75% clones in situ enriched sample). The species belonged to γ-Proteobacteria and their proportion was nearly identical between the two enrichment samples, and Vibrio was the predominant genus(45% in laboratory enriched sample, 48.5% in situ enriched sample), followed by Halomonas(9% in situ enriched sample) and Streptococcus(6% in laboratory enriched sample). A total of 12 acetaldehyde-degrading strains were isolated from the two samples, which belonged to Vibrio, Halomonas,Pseudoalteromonas, Pseudomonas and Bacillus of γ-Proteobacteria. Strains ACH-L-5, ACH-L-8 and ACH-S-12,belonging to Vibrio and Halomonas, have strong ability of acetaldehyde degradation, which could tolerate 1.5 g/L acetaldehyde and degrade 350 mg/L acetaldehyde within 24 hours. Our results indicated that bacteria of γ-Proteobacteria may play an important role in carbon cycle of deep sea environments, especial the bacteria belonging to Vibrio and Halomonas and these strains was suggested for their potentials in government of aldehyde pollutants.  相似文献   

基于卷积神经网络与条件随机场方法提取乡镇非正规固体废弃物     

刘懿兰  黄晓霞  李红旮  柳泽  陈崇  王新歌 《地球信息科学学报》2019,21(2):259-268

随着村镇经济建设发展,生活垃圾和工业固体废弃物造成的污染问题日益突出,已经成为制约新农村建设发展和生态文明建设的关键问题,而目前针对乡镇非正规固体废弃物的调查与统计主要依赖全国各乡镇相关部门逐级调查上报,工作量较大。本文基于高分辨率遥感影像,将深度学习模型和条件随机场模型相结合引入到乡镇固体废弃物的提取研究中,探索一种基于深度卷积神经网络的乡镇固体废弃物提取模型。由于固体废弃物在影像上表现为面积小,分布破碎等特点,为了提高工作效率,将模型特分为识别和提取2个部分：① 通过全连接卷积网络（CNN）对固体废弃物进行快速识别判断,筛选感兴趣区域影像块;② 在传统的全卷积神经网络(FCN)的基础上加入条件随机场模型(CRF)提取固体废弃物边界,提高整体分割精度。根据安徽、山西等地区相关部门上报固体废弃物堆放点以及住房与城乡建设部城乡规划管理中心进行野外检查的结果,实验最终识别精度达到86.87%以上;形状提取精度为89.84%,Kappa系数为0.7851,识别与提取精度均优于传统分类方法。同时,该方法已经逐步应用于住房和城乡建设部有关成都、兰州、河北等部分乡镇非正规固体废弃物的核查工作,取得了较为满意的结果。  相似文献   

开孔率对明基床上开孔沉箱波浪反射系数影响的数值研究     

蔡郁  孙大鹏  赵沛泓  吴浩 《海洋工程》2018,36(5):30-37

开孔率是开孔沉箱波浪反射系数的重要影响因素,迄今为止关于开孔沉箱的物模试验研究成果(包括《防波堤设计与施工规范》)中,开孔率μ通常以线性关系反映在开孔沉箱波浪反射系数的计算关系式中,适用范围为0.2~0.4。但当μ0.2或μ0.4时,开孔率μ对波浪反射系数Kr的影响规律尚需进一步的研究探讨。现借助二维数值波浪水槽,在扩大了的开孔率取值范围内,模拟不规则波与可渗明基床上开孔沉箱的相互作用。结果表明:在0.2≤μ≤0.4的范围内,用线性关系描述开孔率μ对波浪反射系数Kr的影响是合适的;在μ0.4时,数模值和物模试验拟合的经验关系式的趋势是一致的;在μ0.2时,开孔沉箱反射系数K_r随开孔率μ的减小而增大,用物模试验拟合的经验关系式及《防波堤设计与施工规范》中计算公式的线性关系来描述开孔率μ对反射系数K_r的影响是不恰当的。研究成果对开孔沉箱消浪机理的深入认识和开孔沉箱结构的优化设计具有重要意义。  相似文献   

Countermeasures for breakwater foundation subjected to foreshocks and main shock of earthquake loading     

Babloo Chaudhary  Hemanta Hazarika  Siavash Manafi Khajeh Pasha 《Marine Georesources & Geotechnology》2018,36(3):308-322

Coastal protective structures, such as composite breakwaters, are generally vulnerable to earthquake. It was observed that breakwaters damage mainly due to failure of their foundations. However, the seismically induced failure process of breakwater foundation has not been well understood. This study describes failure mechanism of breakwater foundation as well as a newly developed reinforcing model for breakwater foundation that can render resiliency to breakwater against earthquake-related disasters. Steel sheet piles and gabions were used as reinforcing materials for foundation. The experimental program consisted of a series of shaking table tests for conventional and reinforced foundation of breakwater. Numerical analyses were conducted using finite difference method, and it was observed that the numerical models were capable to elucidate the seismic behavior of soil–reinforcement–breakwater system. This paper presents an overview of the results of experimental and numerical studies of the seismic response of breakwater foundation. Overall, the results of these studies show the effectiveness of the reinforced foundation in mitigating the earthquake-induced damage to the breakwater. Moreover, numerical simulation was used for parametric study to determine the effect of different embedment depths of sheet piles on the performance of breakwater foundation subjected to seismic loading.  相似文献   

A hybrid integrated deep learning model for the prediction of citywide spatio-temporal flow volumes     

Yibin Ren  Huanfa Chen  Tao Cheng  Yang Zhang  Ge Chen 《International journal of geographical information science》2020,34(4):802-823

ABSTRACT

The spatio-temporal residual network (ST-ResNet) leverages the power of deep learning (DL) for predicting the volume of citywide spatio-temporal flows. However, this model, neglects the dynamic dependency of the input flows in the temporal dimension, which affects what spatio-temporal features may be captured in the result. This study introduces a long short-term memory (LSTM) neural network into the ST-ResNet to form a hybrid integrated-DL model to predict the volumes of citywide spatio-temporal flows (called HIDLST). The new model can dynamically learn the temporal dependency among flows via the feedback connection in the LSTM to improve accurate captures of spatio-temporal features in the flows. We test the HIDLST model by predicting the volumes of citywide taxi flows in Beijing, China. We tune the hyperparameters of the HIDLST model to optimize the prediction accuracy. A comparative study shows that the proposed model consistently outperforms ST-ResNet and several other typical DL-based models on prediction accuracy. Furthermore, we discuss the distribution of prediction errors and the contributions of the different spatio-temporal patterns.  相似文献   

Detecting regional dominant movement patterns in trajectory data with a convolutional neural network     

Can Yang  Győző Gidófalvi 《International journal of geographical information science》2020,34(5):996-1021

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A simple strategy for dynamic substructuring: I. Concept and development     

Aikaterini Stefanaki  M. V. Sivaselvan 《地震工程与结构动力学》2018,47(9):1801-1822

Dynamic substructuring refers to physical testing with computational models in the loop. This paper presents a new strategy for such testing. The key feature of this strategy is that it decouples the substructuring controller from the physical subsystem. Unlike conventional approaches, it does not explicitly include a tracking controller. Consequently, the design and implementation of the substructuring controls are greatly simplified. This paper motivates the strategy and discusses the main concept along with details of the substructuring control design. The focus is on configurations that use shake tables and active mass drivers. An extensive experimental assessment of the new strategy is presented in a companion paper, where the influence of various factors such as virtual subsystem dynamics, control gains, and nonlinearities is investigated, and it is shown that robustly stable and accurate substructuring is achieved.  相似文献   

基于深度学习理论的无人机影像分类     

阳成 《北京测绘》2020,(4):481-484

针对无人机影像深度学习分类方法缺乏现状,本文利用深度学习理论卷积神经网络方法对无人机影像进行了分类。该法首先抽取无人机影像作为训练集和检验集,然后建立一个2个卷积层-池化层的卷积神经网络模型进行深度学习,通过设定参数并运行模型实现无人机影像分类。实验表明,本文提出的方法可完成较复杂地区无人机影像分类,其分类精度与支持向量机方法相当,为无人机遥感影像分类提供了一个崭新的技术视点。  相似文献   

Modelling the Shimokita deep coalbed biosphere over deep geological time: Starvation,stimulation, material balance and population models     

Stephen A. Bowden  Abdalla Y. Mohamed  Ayad N. F. Edilbi  Yu-Shih Lin  Yuki Morono  Kai-Uwe Hinrichs  Fumio Inagaki 《Basin Research》2020,32(5):804-829

Basin models can simulate geological, geochemical and geophysical processes and potentially also the deep biosphere, starting from a burial curve, assuming a thermal history and utilizing other experimentally obtained data. Here, we apply basin modelling techniques to model cell abundances within the deep coalbed biosphere off Shimokita Peninsula, Japan, drilled during Integrated Ocean Drilling Program Expedition 337. Two approaches were used to simulate the deep coalbed biosphere: (a) In the first approach, the deep biosphere was modelled using a material balance approach that treats the deep biosphere as a carbon reservoir, in which fluxes are governed by temperature-controlled metabolic processes that retain carbon via cell-growth and cell-repair and pass it back via cell-damaging reactions. (b) In the second approach, the deep biosphere was modelled as a microbial community with a temperature-controlled growth ratio and carrying capacity (a limit on the size of the deep biosphere) modulated by diagenetic-processes. In all cases, the biosphere in the coalbeds and adjacent habitat are best modelled as a carbon-limited community undergoing starvation because labile sedimentary organic matter is no longer present and petroleum generation is yet to occur. This state of starvation was represented by the conversion of organic carbon to authigenic carbonate and the formation of kerogen. The potential for the biosphere to be stimulated by the generation of carbon-dioxide from the coal during its transition from brown to sub-bituminous coal was evaluated and a net thickness of 20 m of lignite was found sufficient to support an order of magnitude greater number of cells within a low-total organic carbon (TOC) horizon. By comparison, the stimulation of microbial populations in a coalbed or high-TOC horizon would be harder to detect because the increase in population size would be proportionally very small.  相似文献   

基于YOLOv3深度学习的海雾气象条件下海上船只实时检测     

王飞  刘梦婷  刘雪芹  秦志亮  马本俊  郑毅 《海洋科学》2020,44(8):197-204

海雾气象条件下船只高精度检测识别面临较大困难，传统的目标识别、定位方法效果差强人意。作者围绕海雾气象条件下不同类型船只的实时检测问题，提出一种基于YOLOv3深度学习的实时海上船只检测新思路。首先构建清晰图片和模糊图片（海雾、雨）的判别方法，实现图片清晰度分类处理；其次为提高海雾气象条件下海上船只的实时检测精度，消除海雾遮挡对目标识别的影响，运用暗通道先验去雾方法对含有海雾的图像实行去雾；最后基于YOLOv3深度学习算法对精细处理后的图像进行船只实时检测。实验结果表明该方法能够在海雾气象条件下高效、准确地检测到船只，对海上复杂环境条件下的船只实时检测研究具有一定的理论指导意义。  相似文献