新疆210金矿床黄铁矿标型特征及地质意义

研究新疆210金矿床中黄铁矿产状、形态特征及不同粒级黄铁矿的化学特征和晶胞参数等。结果表明,210金矿床为蚀变破碎带型金矿床,矿石中黄铁矿含量、粒径与金含量密切相关,含量高、粒径小的黄铁矿可作为强矿化标志。通常含金黄铁矿与无金黄铁矿相比颜色加深,晶胞参数轴长加长,亦可作为金矿化找矿标志及贫金、富金的评价准则。矿床具沉积矿床及热液矿床成因特点,初步认为矿床成因属"双源成因",其黄铁矿形成于中深成环境。     

徕卡全站仪GSI数据格式转换模块设计

基于全站仪的数字测图是获取地理空间信息数据的重要手段,由于全站仪品牌不同,其数据格式区别较大,且不能直接导入到成图软件中。本文对徕卡系列全站仪数据存储所采用的GSI-8格式进行了分析,介绍了GSI-8转CASS7.0所需的*.dat格式的原理,给出了程序实现的核心代码,利用实例数据对数据格式转换模块进行了验证。本文所介绍的文件格式转换方法对于测量中其它数据格式的转换具有一定的参考意义。     

浅谈水文地质参数的计算与应用

结合多个场地的抽水试验和室内试验资料,分析评价了工程勘察中不同水文地质参数的应用范围及在参数求取过程中应注意的问题,根据实测数据得出野外抽水试验渗透系数是室内渗透试验所测得的10~14倍,影响半径约为裘布依影响半径的5.8~17.7倍;分析了产生这种情况的原因,指出在工程实践中应根据不同的要求选取不同方法计算得出的水文地质参数;针对导水系数、释水系数及给水度在计算及应用过程中应注意的问题进行了评述。     

FBG温度低敏传感器在大型钢结构施工监测中的运用

目前在桥梁、钢结构等表面应力监测领域中,光纤光栅因具有抗电磁干扰能力强、灵敏度高、环境适应能力强、使用寿命长等优点,已经成为一种新的先进监测、检测手段,但FBG波长随温度变化而产生的漂移往往严重影响监测系统的性能,因此需要对FBG进行温度补偿。介绍了一种新型的FBG传感器并结合具体的工程项目,论述了其温度低敏技术能精确地剔除温度对应变的影响,实现结构物的长期健康监测。     

河南省农作物虚拟水含量时空分异特征

在GIS技术的支持下,通过对1978—2013年河南省冬小麦、夏玉米、花生、棉花、油料作物、蔬菜6种主要农作物虚拟水量的计算与分析,探讨了其时空分异规律。河南省6种农作物单位质量虚拟水量在不断下降的趋势下有波动,2003年出现峰值,与当年大旱、所有农作物大面积减产有关;在农作物类型中,棉花单位质量虚拟水含量最高,多年平均值达到8 077.4 m3/t,蔬菜最低,多年平均值仅为159.95 m3/t。6种作物的虚拟水含量在空间分布上有明显差异,按其2013年的产量进行加权分析得到,第一等级区域为三门峡、郑州、信阳,第二等级为平顶山、洛阳、济源、开封,第三等级为南阳、驻马店、新乡、鹤壁、安阳、濮阳,第四等级为漯河,最低为许昌、周口、商丘、焦作。从整体看,西部、南部虚拟水含量高,而北部、东部虚拟水含量低。     

准噶尔盆地玛湖凹陷深层油气流体相态研究

准噶尔盆地玛湖凹陷深层(5000m)是我国深层油气勘探当前的一个热点风险领域。为给区域下步油气勘探提供参考,通过对区内烃源岩和油气进行系统的地质地球化学正演、反演对比综合研究,重点分析了油气流体相态。结果表明,研究区深层稳定发育石炭系—二叠系四套烃源岩,有机质丰度高,普遍达到中等—好质量,类型多种多样,既可生油亦可生气,加之所有烃源岩均已基本进入高—过成熟演化,因此深层油气流体相态总体应高熟轻质,可能包括高熟轻质油、干酪根裂解气、油裂解气等。原油地球化学研究表明,原油随埋藏深度增加、层位变老,油质有逐渐变轻的趋势,成熟度有逐渐增大的趋势,保存条件亦逐渐变好,因此预测深层原油油质更轻、成熟度更高、保存条件更好。天然气地球化学研究表明,中浅层天然气可能属于混合来源,包括干酪根裂解气和油裂解气,规模性的高过成熟天然气可能在深层。因此,研究区深层油气资源丰富,相态轻质,成藏有利,值得勘探。这些认识还可供具有相似油气地质背景地区在研究和勘探时类比参考。     

Exploring the hydrologic response to the urban building coverage ratio by model simulation

Theoretical and Applied Climatology - The increasing building coverage ratio accompanied by the increase in impervious surfaces during the urbanization process may change the flow concentration...     

Active Region Coronal Rain Event Observed by the Fast Imaging Solar Spectrograph on the NST

The Fast Imaging Solar Spectrograph (FISS) is being operated on the New Solar Telescope of the Big Bear Solar Observatory. It simultaneously records spectra of Hα and Ca ii 8542 Å lines, and this dual-spectra measurement provides an estimate of the temperature and nonthermal speed components. We observed a loop structure in AR 11305 using the FISS, SDO/AIA, and STEREO/EUVI in 304 Å, and found plasma material falling along the loop from a coronal height into the umbra of a sunspot, which accelerated up to 80 km?s^?1. We also observed C2 and C7 flare events near the loop. The temperature of the downflows was in the range of 10?000?–?33?000 K, increasing toward the umbra. The temperature of the flow varied with time, and the temperature near the footpoint rose immediately after the C7 flare, but the temperature toward the umbra remained the same. There seemed to be a temporal correlation between the amount of downflow material and the observed C-class flares. The downflows decreased gradually soon after the flares and then increased after a few hours. These high-speed red-shift events occurred continuously during the observations. The flows observed on-disk in Hα and Ca ii 8542 Å appeared as fragmented, fuzzy condensed material falling from the coronal heights when seen off-limb with STEREO/EUVI at 304 Å. Based on these observations, we propose that these flows were an on-disk signature of coronal rain.     

Reconstruct light curves from unevenly sampled variability data with artificial neural networks

Light curves are usually constructed from discrete observational data by interpolation. In most cases, the observation data is temporally uneven, and therefore the light curve is usually derived by the interpolation of the binned data with the spline function, which is intended for reducing the “high sample noise” (i.e., the variability in the timescales comparable with the bin width). Such a practice of course reduces the time resolution of the light curve. It is known that function approximation is one of the most important applications of the artificial neural networks (ANN). In this work, for the first time we tentatively use the ANN to construct light curves from unevenly sampled variability data. To demonstrate the advantages of ANN for signal reconstruction over commonly used cubic spline function scheme, two sets of simulated periodic functions are used with random noises of varying magnitudes, one single frequency based and one multiple (two) frequency based. These signal reconstruction tests show that the ANN is clearly superior to the cubic spline scheme. As a case study, we use the uneven long-term multi-band monitoring data of BL lacertae to derive the light curves with ANN. It is found that the light curves derived with ANN have higher time resolution than those with the cubic spline function adopted in previous works. We recommend using ANN for the signal reconstruction in astrophysical data analysis as well as that of in other fields.     

Effect of germanium dioxide on growth of Spirulina platensis

This study on the effect of different concentrations of germanium dioxide (GeO₂) on the specific growth rate (SGR), pigment contents, protein content and amino acid composition ofSpirulina platensis showed that Ge was not the essential element of this alga; that GeO₂ could speed up growth and raise protein content ofS. platensis, and could possibly influence the photosynthesis system. The concentration range of GeO₂ beneficial to growth ofS. platensis is from 5–100mg/l. GeO₂ is proposed to be utilized to remove contamination byChlorella spp. usually occurring in the cultivation ofSpirulina.