Variations in Spectral Slope in Lake Taihu,a Large Subtropical Shallow Lake in China

Spectral slope (S), describing the exponential decrease of the absorption spectrum over a given wavelength range, is an important parameter in the study of of chromophoric dissolved organic matter (CDOM) dynamics, and also an essential input parameter in remote sensing models. Furthermore, S is often used as a proxy for CDOM composition, including the ratio of fulvic to humic acids and molecular weight. The relative broad range in S values reported in the literature can be explained by the different spectral ranges and fitting methods used. A single exponential model is used to fit the S values for 17 investigations involving 458 samples in Lake Taihu from January to October in 2004. The average S value was 15.18 ± 1.39 μm⁻¹ for the range of 280–500 nm, which fell within the range reported in the literature. The frequency distribution of S value basically obeyed a normal distribution. Significant differences in S values between summer and other seasons showed that phytoplankton degradation was one of the important sources of CDOM in summer, whereas CDOM mainly came from the river input in other seasons. Furthermore, the estimated S value decreased with increasing wavelength range used in regression. The maximum and minimum values derived from the regression were 17.89 ± 1.25 μm⁻¹ and 13.62 ± 2.11 μm⁻¹ for the wavelength ranges of 280–380 nm and 400–500 nm, respectively, a decrease of 23.9%. S values significantly decreased with the increase of CDOM absorption coefficients. CDOM absorption coefficients could be more appropriately estimated from exponential model introducing the variation of S with absorption coefficients, making them useful for a remote sensing bio-optical model of Lake Taihu. DOC-specific absorption coefficient a*(λ) and the parameter M describing molecular size of the humic molecules could also be used as a proxy for the sources and types of CDOM. A general relationship was found between S and a*(λ), and M values. S increased with the decrease of DOC-specific absorption coefficient and the increase of M corresponding to the decrease of molecular weight.     

Machine-learning paradigms for selecting ecologically significant input variables

Harmful algal blooms, which are considered a serious environmental problem nowadays, occur in coastal waters in many parts of the world. They cause acute ecological damage and ensuing economic losses, due to fish kills and shellfish poisoning as well as public health threats posed by toxic blooms. Recently, data-driven models including machine-learning (ML) techniques have been employed to mimic dynamics of algal blooms. One of the most important steps in the application of a ML technique is the selection of significant model input variables. In the present paper, we use two extensively used ML techniques, artificial neural networks (ANN) and genetic programming (GP) for selecting the significant input variables. The efficacy of these techniques is first demonstrated on a test problem with known dependence and then they are applied to a real-world case study of water quality data from Tolo Harbour, Hong Kong. These ML techniques overcome some of the limitations of the currently used techniques for input variable selection, a review of which is also presented. The interpretation of the weights of the trained ANN and the GP evolved equations demonstrate their ability to identify the ecologically significant variables precisely. The significant variables suggested by the ML techniques also indicate chlorophyll-a (Chl-a) itself to be the most significant input in predicting the algal blooms, suggesting an auto-regressive nature or persistence in the algal bloom dynamics, which may be related to the long flushing time in the semi-enclosed coastal waters. The study also confirms the previous understanding that the algal blooms in coastal waters of Hong Kong often occur with a life cycle of the order of 1–2 weeks.     

Pseudoelastic behavior in Y1−xPrxBa2Cu3Oy compounds

Tensile tests show that ferroelastic loops always occur at 100–150 K, 200–250 K and room temperature in the Y_1–xPr_xBa₂Cu₃O_y samples withx=0 and 0.1 for whichT _c is 92 K and 82.5 K respectively, and the shape memory effect is always observed in the compact sample near 130 K, just similar to that of thermal elastic martensitic alloys. The loss fraction (W/W) which is proportional to the area of ferroelastic loop as a function of temperature shows that there always exist static hysteresis (W/W) peaks at 130 K and 110 K which are attributed to the phaselike transition (PLT) characterized by the jump of lattice parameters. No ferroelastic loops and shape memory effect are observed in the range of 100 K to 150 K for the lowerT _c samples withx=0.3, 0.4 and 0.6.     

LNG汽车加气站设计的探讨

结合2座加气示范站的设计、运行情况,分析LNG汽车加气站的工艺流程。在国内目前无相应设计规范的情况下,探讨了LNG汽车加气站的选址、安全间距。进行了效益分析,提出了存在的问题与建议。     

PDP荧光粉浆料用有机载体的研制

使用混合溶剂,得到了具有层次挥发性的PDP(等离子体显示板)荧光粉浆料用有机载体,研究了有机载体对烧结后荧光粉亮度的影响。结果表明:使用了载体的荧光粉浆料烧结后亮度比达98%(147nm),包膜荧光粉亮度比可达106%(147nm)。此载体可以用于配制PDP荧光粉浆料。     

MgZn铁氧体（偏转）磁性材料的X射线光谱测定与研究

提出了用Ｘ射线光谱仪粉末压片法熔融片法测定ＭｇＺｎ铁氧体各组分浓度的方法,对粉料的制备,均匀性状态颗粒度进行了一系列试验。     

Ge_xSi_1-x/Si异质结构的近红外吸收光谱测量

测量分析了采用 RRH/VLP—CVD 方法外延生长的 Ge_xSi_(1-x)/Si 异质结构中 Ge_xSi_(1-x)合金薄层的近红外吸收光谱。由谱线计算出 Ge_(0.15)Si_(0.85)与 Ge_(0.45)Si(0.55)合金层的带隙分别为1.02eV 和O.88eV,与相同组分的体合金一致。结果表明用红外吸收光谱测量研究异质结构薄层材料的能带结构及带隙是一种准确、简便的方法。     

江苏省城乡居民网络信息消费水平研究

江苏省网络信息消费在居民实现能力、消费渠道和消费类型上均呈现逐年递增的发展趋势。文章在分析大量统计数据的基础上,通过线性回归方法构建江苏省城乡信息消费函数,居民收入与信息消费的关系,分析江苏省城乡居民网络信息消费水平,为引导网络信息消费的健康发展提供可参考的理论依据和切实可行的措施与建议。     

论顾客关注与关注顾客

论文以ISO 9000标准提出的8项管理原则的第一条-以顾客为关注的焦点为出发点,论述了如何关注顾客和顾客关注的内涵,以及两个关注之间的联系,从而在实践中真正做到以顾客为关注的焦点。     

基于神经网络的水平移动系数的求取方法

水平移动系数是开采沉陷预计的重要参数,对于确定地表变形值、从而准确判定建筑物的破坏程度具有决定性的作用,然而其影响因素十分复杂,很难用一定的理论公式来描述.利用神经网络自学习、自主对复杂的非线性关系的拟合原理,通过对大量样本的学习训练,获得了基于神经网络的水平移动系数求取方法,并通过样本测试,取得了较好的效果,为水平移动系数的求取提出了一种新的方法.