Characterization of ghrelin mRNA expression in fasting Larimichthys crocea juveniles

Larimichthys crocea is a marine fish species cultured in China.Short-term starvation is often applied to improve the quality of cultured L.crocea,and the expression of ghrelin in tissues of stomach,muscle,brain,intestines,liver,and kidney,involved in starvation response,under starvation conditions were studied to understand the effect of starvation on the expression of ghrelin in L.crocea juveniles.The ghrelin expression was tissue-specific,and expression was significantly higher in the stomach compared to other tissues(P0.01).Additionally,ghrelin expression in different tissues changed along with prolongation of fasting.In the stomach,ghrelin expression levels increased gradually at the beginning of the fast,and then declined after eight days of fasting.Gene expression in the brain and intestines increased at the beginning of the fast,and then decreased with longer fasting time.Interestingly,ghrelin expression declined at the beginning of the fast,then increased with longer fasting in the kidneys and muscles.These results suggest that ghrelin is involved in starvation response in L.crocea juveniles.This study provids insights into ghrelin function and an important reference for the development of reasonable feeding strategies for L.crocea juveniles.     

浙江省高分辨率太阳直接辐射图的计算和绘制

以综合考虑天空因素和地面因素的起伏地形下太阳直接辐射分布式模型为基础,采用1∶25万高分辨率数字高程模型（DEM）数据和气象站观测资料,计算了100 m×100 m分辨率的浙江省气候平均月太阳直接辐射以及年直接辐射的精细分布,并分析了起伏地形下浙江省太阳直接辐射的逐月变化规律。结果表明：浙江省太阳直接辐射量以7、8月份最高,1、2月份最低,全省气候平均年太阳直接辐射量为2 083 MJ/m²;地形因子对起伏地形下浙江省太阳直接辐射的影响程度具有随季节变化的特性;局地地形对太阳直接辐射的影响程度随季节而变,在冬半年,太阳高度角较低的季节,局地地形的影响较为显著。     

夏季东天山中段一次强对流天气过程的数值模拟

利用常规气象观测资料、区域自动站观测资料和FY-2D卫星逐时TBB资料,采用WRF中尺度数值模式,对2011年夏季发生在东天山中段一次强对流天气过程进行数值模拟和诊断分析,研究了天山特殊地形对降水过程的动力结构、水汽输送和云降水微物理机制的影响。结果表明,西风气流东移时受东天山的阻挡,气流从东天山南北两侧绕流,北侧急流经博尔塔拉谷地越过北天山西段后,急流右侧气流反气旋转向形成北支气流;南侧急流遇吐鲁番地区反气旋系统阻挡而转向北进形成南支气流。两支气流受地形动力抬升在东天山中段北坡汇合,为此区域局地强对流降水的形成和发展提供动力条件,北支气流为主要的水汽供应源。高空西南气流引导的冰相云系与低层局地对流云在东天山中段北坡结合,分别持续提供冰晶和云水,促使云微物理过程发展旺盛,致使局地暴雨过程产生。     

广西猫儿山主峰区巨砾非冰川成因的遥感地质地貌学解疑

在被称为"华南第一峰"的猫儿山主峰区,散落着一些具有钝形外观的花岗岩巨砾。它们是否是冰川成因?探明这一现象具有多重意义。为此,笔者从遥感、地质学和地貌学角度开展了调查研究。基于TM、Quickbird-2及TM-DEM的多尺度多模式遥感地貌学解译表明,在猫儿山主峰部位不具备形成冰川漂砾的地貌环境条件。通过成山期与冰期年代对比,虽然猫儿山成山过程经历了第四纪冰期,但不能就此断定它形成了冰川,并导致巨型漂砾形成。对主峰基岩和巨砾的矿物岩石学特征比较表明,两者为同源关系,因此巨砾并非由远处搬来,而就是来自主峰的基岩。遥感线性构造解译表明,猫儿山花岗岩体中存在五组发育的断裂构造,它们造成了花岗岩岩体的内伤,是导致巨砾形成的重要内因。而强烈的物理与化学风化作用,加上陡峭地势的斜坡重力作用,是最终导致这些巨砾形成的重要外因。我们的实地调查证实了这五方面的分析与推测。结论很清楚,猫儿山主峰区分布的花岗岩巨砾成因于断裂构造、风化剥蚀与斜坡重力三种因素的共同作用,它们只是主峰基岩的简单风化-崩塌物,而非冰川漂砾。     

Automatic Seamless Stitching Method for CCD Images of Chang’E-1 Lunar Mission

A novel automatic seamless stitching method is presented.Compared to the traditional method,it can speed the processing and minimize the utilization of human resources to produce global lunar map.Meanwhile,a new global image map of the Moon with spatial resolution of ～120 m has been completed by the proposed method from Chang’E-1 CCD image data.     

城市地面沉降研究进展及其发展趋势

地面沉降是城市主要地质灾害之一。随着中国城市化进程的加快，地面沉降规模扩大，危害加剧，本文简述了国内外地面沉降概况，对地面沉降的成因、危害、机制、数学模拟、监测、防治等方面的研究进展进行了综合论述，并指出，建设工程性地面沉降，孔隙水运移机制、地下水和地面沉降模型耦合、地面沉降生态-经济-社会影响评估、地下水采灌优化设计、地面沉降系统防治、地面变形高精度监测、城市化建设与地面沉降的相互关系等，是今后城市地面沉降研究的主要方向。     

基于生态参数的岩溶峰丛区石灰岩基岩表面溶蚀率遥感反演

为了探索岩溶峰丛区生态参数与石灰岩基岩表面溶蚀率的相关性,用相关生态参数反演土层下石灰岩基岩表面的溶蚀率,从而间接估算其变形。选择桂林丫吉村岩溶峰丛区为研究区,以Landsat5 TM多光谱数据为信息源,提取归一化差值植被指数(normalized difference vegetation index,NDVI)、地面温度及土壤湿度等遥感参数;运用SPSS统计软件对这3种参数分别与石灰岩溶蚀率进行了相关分析,确定其相关系数分别为-0.91,0.85及0.93;在此基础上,通过逐步回归分析,建立了运用NDVI估算植被覆盖下石灰岩表面溶蚀率的遥感反演模型。结果表明:NDVI与石灰岩溶蚀率相关性最大,所以植被信息是石灰岩表层基岩溶蚀的主要间接标志;溶蚀率与NDVI指数存在线性关系,因此只要已知研究区其他地区的NDVI指数,即可估算出该地区的石灰岩基岩表面溶蚀率。     

基于能量竞争载荷模型的海洋立管双向涡激振动时域预报方法研究

海洋立管是深海油气开发中用于连接海底井口和水面浮体的唯一通道。立管在洋流作用下极易发生涡激振动（vortex-induced vibration,简称VIV）,发展快速经验性涡激振动时域预报方法对立管的安全设计具有重要意义。通过柔性立管模型试验,结合载荷重构方法和最小二乘法,识别建立了能量竞争载荷模型下的经验水动力载荷系数模型。应用识别建立的经验水动力载荷系数模型,发展形成了海洋立管顺流向及横流向双向涡激振动时域预报方法。将预报结果与试验结果对比,结果表明：基于能量竞争载荷模型的海洋立管双向涡激振动预报方法能够有效预报海洋立管涡激振动主导模态、主导频率、流向平均位移响应和涡激振动位移响应等力学行为特性。研究成果对发展更为有效的涡激振动预报手段具有有益参考。     

A visualization approach for discovering colocation patterns

Colocation mining is one of the major spatial data mining tasks. When discovering colocation patterns, spatial statistics or data mining approaches are commonly used. Colocation mining results are typically presented in a textual form and do not provide any spatial information; thus, the results lack an intuitive approach to obtain cognition of colocation rules. Here, we propose a visualization approach to discover colocation patterns for two independent point distributions and generate visual results. This approach makes use of the ability of human color perception. For two geographic features, our approach first generates density surfaces of the input features and then visualizes the density surfaces using a red or green light with different intensities. Then, based on the law of additive color mixing, our approach mixes the colors of the two density surfaces to generate a colocation rule map. The visualization approach can also provide local details of colocation and be used for local colocation analysis. Users can detect colocation patterns and their distribution from the colocation rule maps. We use both synthetic data and real data to test the performance of our approach.