The Variability of the Narrow-line Seyfert 1 Galaxies from the Pan-STARRS's View

By means of the data sets from the Pan-STARRS1 survey,we have systematically examined the relationship between the variability characteristics and the physical ...     

西宁市区土层剪切波速随深度变化特征

通过对西宁市区67个钻孔剪切波速资料整理,采用最小二乘法进行统计回归分析,得到西宁市土层剪切波速Vs随土层埋深H的经验关系式,西宁市典型土类Vs与H的经验关系。并且通过实测剪切波速与预测剪切波速的对比,验证所得经验关系式的适用性。     

用于激光二极管泵浦的Nd：YAG激光器中声光Q开关的研究

近年来,激光二极管泵浦的Ｎｄ：ＹＡＧ激光器（ＤＰＬ）以其诸多优点引起人们的关注,因此开发小型和高效率,适用于ＤＰＬ中的声光Ｑ开关（ＭＡＯＱ）成为重要的研究方向,据文献报道,以熔石英玻璃为声光介质,研制成功的ＭＡＯＱ,工作了Ｂｒａｇｇ衍射区,驱动功率１～５Ｗ,衍射效率１０％－３０％可调。本文从激光原理出发,详细地探讨了ＭＡＯＱ的工作原理,对声光互作用长度的选取进行了分析,对入射角与衍射损失进行了实验     

土地利用和水环境因子对大型底栖动物次级生产力的影响:以东北地区连环湖为例

土地利用和水环境因子是影响湖泊生态系统的关键因素,探究大型底栖动物次级生产力受环境因子的作用机制,可揭示底栖动物栖息地的生态系统与外源环境的关系。为了解土地利用和水环境因子对大型底栖动物次级生产力的影响,2020年对连环湖13个主要湖泊的土地利用类型及6、8和10月的大型底栖动物、水环境因子进行调查,共采集到大型底栖动物75种,隶属于3门32科56属,其中优势种属及重要种属以摇蚊幼虫和腹足纲为主,前突摇蚊(Procladius sp.)为第一优势种。主成分分析表明,土地利用及水环境因子具备明显的时空梯度,而大型底栖动物次级生产力也存在明显的时空变化。春季、夏季、秋季次级生产力和P/B值分别为5.65、6.06、4.31 g/(m²·a)和2.74、2.55、2.40 a^-1,其中春季次级生产力集中于东北部湖区,龙虎泡集中于湖心区;夏季次级生产力逐渐向各湖区扩散,龙虎泡整体偏低;秋季次级生产力集中于西北部及东南部湖区,龙虎泡集中于东北部湖区。P/B值随季节的推移呈现由东部湖区向西部湖区逐渐递增的趋势,而龙虎泡始终集中于南部湖区。次级生产力和P/B值的结构分析表明,春季次级生产力主要由腹足纲构成,进入夏、秋季后以双壳纲对次级生产力的贡献最高。其中腹足纲、双壳纲、摇蚊幼虫和寡毛纲次级生产力主要集中于北部湖区、东南部湖区、中部湖区和龙虎泡,而甲壳纲仅出现于阿木塔泡。寡毛纲和双壳纲P/B 值随季节的推移逐渐降低,摇蚊幼虫和腹足纲P/B 值呈先升后降的趋势。通径分析表明,pH、人造地表和叶绿素a是影响年均大型底栖动物次级生产力的关键环境因子。典范对应分析表明,总磷和电导率是影响不同季节大型底栖动物次级生产力的重要环境变量。耕地、人造地表与总磷、电导率和悬浮物呈显著正相关,农业生产和城镇建设的增加是连环湖呈富营养化状态的重要原因,且此现象已对大型底栖动物次级生产力形成威胁。未来应通过控制农业面源污染、秸秆腐熟还田、鼓励粪便施肥、科学规划用地等措施改善连环湖流域的生态环境,以促进大型底栖动物资源合理的开发利用。     

华南热带水库丰水期浮游植物群落对氮、磷、铁加富的响应——以广东大沙河水库为例

富营养化是水生态系统主要的环境问题,自然条件下多种营养盐以组合形式进入水体,明确浮游植物群落对多种营养盐加富的响应对富营养化防治有重要意义。本研究以一座华南热带水库(大沙河水库)为例,分析了2021年枯水期(1—3月)和丰水期前期(4—6月)氮(N)、磷(P)、铁(Fe)和叶绿素a(Chl.a)浓度的变化趋势,并通过原位添加实验,解析浮游植物丰度和多样性对N、P、Fe加富的响应。结果表明:与1—3月相比,4—6月期间水体总磷浓度(TP)明显升高,总铁浓度(TFe)呈增加趋势但月度间波动较大,总氮浓度(TN)在4月最低,之后缓慢增加,期间Chl.a浓度从3月的5 μg/L快速增加到5月的29 μg/L。原位实验结果表明:浮游植物群落以蓝藻、绿藻和硅藻为主要组成,所有营养盐添加组浮游植物丰度均有增加,但只有NP同时添加时(NP和FeNP两组)生物量(以Chl.a表征)有显著升高;营养盐添加组细胞丰度的响应在门类和种类间差异明显,实验组组间群落结构和优势种类差异显著,所有处理组的群落多样性均明显高于对照组。N和P添加及其与Fe的联合添加(N、P、NP、FeN、FeP和FeNP)均导致蓝藻丰度升高,绿藻仅在NP添加组(FeNP组和NP组)显著升高且两组没有显著差异,硅藻仅在N和P单独添加组(N和P)显著升高。上述结果说明浮游植物生物量受N、P营养盐的共同影响而非单因子作用,N、P和Fe添加均影响群落结构和多样性,对水库富营养化的管理尤其是蓝藻水华防治应综合考虑3种营养盐的共同作用。     

Differentiation of Rural Households′ Consciousness in Land Use Activities: A Case from Bailin Village,Shapingba District of Chongqing Municipality,China

What rural households think and what kind of strategies they take, the basic driving force in land use activities, contribute greatly to the increase of their own revenues, the development of agricultural yields, and even the prosperity of rural areas. Differentiation in rural household behaviors and their consciousness in land use activities is widespread in rural China nowadays. It is important to understand the changing characteristics and laws of land use behaviors of rural households driven by their consciousness, so as to regulate their land use activities. In most empirical studies of land use change at rural household level, the land use consciousness, which acts directly on land use behaviors, is often neglected. In our research, the changes of land use behaviors of rural households are analyzed, through identifying how the land use consciousness affect the land use objectives, land management scales and land inputs of all the rural households in Bailin Village of Chongqing Municipality in the western mountainous China. Also, how the land use consciousness of different rural households comes into being under external stimuli is examined and the self-adjustment process of their consciousness according to their own conditions is also discussed. Finally, broad policy instruments are suggested to promote the rationalization of rural households′ land use consciousness and the standardization of their land use behaviors.     

应用反射波动力学特征解释煤层的研究

根据煤层分叉、合并及沉缺等地质模型,建立正演计算模型;并利用计算机技术提取煤层反射波动力学参数,研究上述地质现象对应的地震波形特征,再进行反演来研究煤层及厚度。经钻探验证效果较好。     

The use of digital technologies for landslide disaster risk research and disaster risk management: progress and prospects

Landslide is a serious natural disaster next only to earthquake and flood, which will cause a great threat to people’s lives and property safety. The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective , difficult to quantify, and no pertinence. As a new research method for landslide susceptibility assessment, machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models. Taking Western Henan for example, the study selected 16 landslide influencing factors such as topography, geological environment, hydrological conditions, and human activities, and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination (RFE) method. Five machine learning methods [Support Vector Machines (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Linear Discriminant Analysis (LDA)] were used to construct the spatial distribution model of landslide susceptibility. The models were evaluated by the receiver operating characteristic curve and statistical index. After analysis and comparison, the XGBoost model (AUC 0.8759) performed the best and was suitable for dealing with regression problems. The model had a high adaptability to landslide data. According to the landslide susceptibility map of the five models, the overall distribution can be observed. The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest, the Xiaoshan Mountain range in the west, and the Yellow River Basin in the north. These areas have large terrain fluctuations, complicated geological structural environments and frequent human engineering activities. The extremely high and highly prone areas were 12043.3 km² and 3087.45 km², accounting for 47.61% and 12.20% of the total area of the study area, respectively. Our study reflects the distribution of landslide susceptibility in western Henan Province, which provides a scientific basis for regional disaster warning, prediction, and resource protection. The study has important practical significance for subsequent landslide disaster management.     

On the impact of wind on the development of wave field during storm Britta

The observation of extreme waves at FINO 1 during storm Britta on the 1st November 2006 has initiated a series of research studies regarding the mechanisms behind. The roles of stability and the presence of the open cell structures have been previously investigated but not conclusive. To improve our understanding of these processes, which are essential for a good forecast of similarly important events offshore, this study revisits the development of storm Britta using an atmospheric and wave coupled modeling system, wind and wave measurements from ten stations across the North Sea, cloud images and Synthetic Aperture Radar (SAR) data. It is found here that a standard state-of-the-art model is capable of capturing the important characteristics of a major storm like Britta, including the storm path, storm peak wind speed, the open cells, and peak significant wave height (H _s ) for open sea. It was also demonstrated that the impact of the open cells has negligible contribution to the development of extreme H _s observed at FINO 1. At the same time, stability alone is not sufficient in explaining the development of extreme H _s . The controlling conditions for the development of Britta extreme H _s observed at FINO 1 are the persistent strong winds and a long and undisturbed fetch over a long period.