Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis

A multivariate statistical approach integrating the absolute principal components score (APCS) and multivariate linear regression (APCS-MLR), along with structural equation modeling (SEM), was used to model the influence of water chemistry variables on chlorophyll a (Chl a) in Lake Qilu, a severely polluted lake in southwestern China. Water quality was surveyed monthly from 2000 to 2005. APCS-MLR was used to identify key water chemistry variables, mine data for SEM, and predict Chl a. Seven principal components (PCs) were determined as eigenvalues >1, which explained 68.67% of the original variance. Four PCs were selected to predict Chl a using APCS-MLR. The results showed a good fit between the observed data and modeled values, with R² = 0.80. For SEM, Chl a and eight variables were used: NH₄-N (ammonia-nitrogen), total phosphorus (TP), Secchi disc depth (SD), cyanide (CN), arsenic (As), cadmium (Cd), fluoride (F), and temperature (T). A conceptual model was established to describe the relationships among the water chemistry variables and Chl a. Four latent variables were also introduced: physical factors, nutrients, toxic substances, and phytoplankton. In general, the SEM demonstrated good agreement between the sample covariance matrix of observed variables and the model-implied covariance matrix. Among the water chemistry factors, T and TP had the greatest positive influence on Chl a, whereas SD had the largest negative influence. These results will help researchers and decision-makers to better understand the influence of water chemistry on phytoplankton and to manage eutrophication adaptively in Lake Qilu.     

Learning habitat models for the diatom community in Lake Prespa

Habitat suitability modelling studies the influence of abiotic factors on the abundance or diversity of a given taxonomic group of organisms. In this work, we investigate the effect of the environmental conditions of Lake Prespa (Republic of Macedonia) on diatom communities. The data contain measurements of physical and chemical properties of the environment as well as the relative abundances of 116 diatom taxa. In addition, we create a separate dataset that contains information only about the top 10 most abundant diatoms. We use two machine learning techniques to model the data: regression trees and multi-target regression trees. We learn a regression tree for each taxon separately (from the top 10 most abundant) to identify the environmental conditions that influence the abundance of the given diatom taxon. We learn two multi-target regression trees: one for modelling the complete community and the other for the top 10 most abundant diatoms. The multi-target regression trees approach is able to detect the conditions that affect the structure of a diatom community (as compared to other approaches that can model only a single target variable). We interpret and compare the obtained models. The models present knowledge about the influence of metallic ions and nutrients on the structure of the diatom community, which is consistent with, but further extends existing expert knowledge.     

征地前后农民感知变化与征地意愿的结构方程模型研究——以武汉市江夏区被征农户为例

论文在感知价值的框架下讨论了土地征收前后农民感知维度的变化,构建土地征收前后农民感知维度变化的测度因子与评估指标,运用结构方程模型对土地征收前后农民感知变化与征地意愿之间的关系进行了衡量。结果显示:①土地征收前后农民感知变化包括农民经济状况变化、 农田资金投入变化、 农村公共基础服务变化、 农村公共社会服务变化与农田景观环境变化5个测量维度;②土地征收后农民的经济收入状况、 农田资金投入、 农村公共基础服务、 农田景观环境等变化感知对被征地农民的征地意愿具有正向的影响,而农村公共社会服务变化感知对于农民的征地意愿影响不显著;③感知变化维度上,土地征收前后农田资金投入变化是影响农民征地意愿的主导因素,其次分别为农民的经济收入状况变化、 农村公共基础服务变化和农田景观环境变化。土地征收前后农民感知维度的变化很明确地影响到农民的征地意愿,把握两者的关系有利于政府制定有效的征地补偿和安置政策、 引导失地农民适应身份转型,为解决被征地农民的现实问题提供参考依据。     

Suitability of various chemically prepared activated carbons for the removal of copper(II) ions

Studies on the suitability of various chemically prepared activated carbons (CPACs) like straw carbon (SC), sawdust carbon (SDC), dates nut carbon (DNC) and commercial activated carbon (CAC) for the removal of copper(II) ions by adsorption from simulated wastewater have been carried out under batch mode at 30?±?1°C and the results are compared. The percentage removal of Cu(II) ions increased with a decrease in initial concentration, particle size and added electrolytes (ionic strength) and increased with an increase in contact time, dose of adsorbent and initial pH of the solution. The adsorption data were fitted with the Langmuir isotherm. The applicability of the first order kinetic equation viz. Lagergren equation was tested by correlation analysis. The adsorption process is concluded to be a spontaneous, first order reaction, occurring with increased randomness at the solid–liquid interface. Studies on the desorption of Cu²⁺-loaded activated carbons (ACs) were carried out with nitric acid (0.2–1?N). The possibility of reuse of the regenerated ACs in cycle (in cue-one after another) was tested. SC was found to be a suitable adsorbent alternative to CAC among CPACs for the removal of metal ions, in general, and Cu²⁺ ions, in particular.     

Influence of some parameters on adsorption rate and toxicity of cadmium in activated sludge

The influence of pH, competitor ions (NaNO₃) and aerobic and anaerobic stabilization of activated sludge on the cadmium uptake by activated sludge solids was investigated. Above 0.08 mg L^‐1 cadmium in solution, biosorption was found to follow the Freundlich isotherm. Active cellular uptake of soluble cadmium does not appear to be a significant mechanism of the biosorption. In addition, the cadmium uptake is not completely reversible. The adsorption of cadmium by activated sludge seems to involve a physico‐chemical mechanism with especially weak electrostatic interactions with ion‐exchange reaction. The optimum adsorption pH was 7.5. Adsorption is influenced by sodium ion concentrations up to an equivalent conductivity of 10 000 μS cm^‐1. Aerobic and anaerobic stabilization of activated sludge increase systematically the initial adsorption capacities. Respirometric measurements were done to evaluate the inhibitive effects of cadmium on activated sludge. Monod's equation and the equation of non‐competitive inhibition were used to describe the toxicity related to cadmium uptake. These two equations appear to be complementary.     

磁粉活性污泥法处理城市生活污水的反应动力学特征

磁粉活性污泥法是在传统活性污泥法中加入磁性粉末(Fe3O4)的废水生物处理方法。在最佳运行状况下,对磁粉活性污泥法基质降解动力学进行了研究。磁粉活性污泥法基质降解符合一级反应规律,利用Monod方程对试验数据进行拟合,确定了其动力学参数,半速率常数Ks、有机底物的最大比降解速率vmax分别为10.39 mg/L和0.804 d-1。     

基于EFQM的建筑企业安全投入绩效评估SEM

为解决目前我国建筑业安全生产事故频发,安全投入不足及其绩效产出低下的现状,通过探索性因子分析,从建筑企业安全投入22项组成内容中提炼出6项要素;借鉴欧洲质量卓越(EFQM)模型,建立建筑企业安全投入绩效评估结构方程模型(SEM),实证分析安全投入构成要素之间的复杂交互影响关系:领导分别对人员、资源设施、政策战略具有正向直接影响;人员与资源受到政策战略的正向直接影响,并对生产过程与事故损失产生正向直接与间接影响。因此,在加强领导投入以提升整体安全投入绩效的前提下,提高政策战略对于人员、资源与设施的约束性,将最终保障安全生产与减少事故损失。     

组织及环境因素对员工不安全行为影响的SEM研究

为分析组织及环境因素对员工不安全行为意向和不安全行为的影响,收集7个煤矿的735名一线作业人员有效调查问卷,采用因子分析方法(FAM)和结构方程模型(SEM),构建组织与环境因素对不安全行为意向及其行为的SEM。结果表明:不安全行为意向与安全装备、安全理念、危险源管理、工作压力、违章处罚、安全管理行为显著相关;不安全行为与危险源管理、工作压力、管理承诺、物态环境、违章惩罚显著相关;不安全行为与安全理念、安全装备、安全管理行为关系不显著;不安全行为意向与管理承诺、物态环境关系不显著。     

滚石冲击作用下埋地高压输气管道的可靠性分析

地质灾害往往会对高压输气管线造成安全隐患,岩体崩塌引起的滚石冲击是导致埋地输气管道第三方破坏的主要破坏形式之一。通过概率分布求出滚石产生的偶然性载荷对管道的冲击频率,根据可靠性理论,用管线钢自身的强度和撞击产生的工作应力,建立强度应力的安全裕度方程。然后利用LS-DYNA有限元软件,建立滚石冲击管道模型,计算不同条件下埋地输气管道的最大应力Sm,确定Sm的分布规律。最后,根据应力和强度的分布求得管道可靠度指标和失效概率。本研究提供的方法和结论对埋地输气管道的风险评估、管道的设计及施工具有重要的参考价值。     

基于ANSYS的可靠度分析方法及应用

通过对可靠度分析的概述理解到现代工程分析中实体模型不确定因素众多,进而带来分析的不准确性。基于有限元分析软件ANSYS提供的概率设计系统(PDS)的概率分析功能,使对结构的概率分析非常容易。根据结构的失效模式来确定结构功能函数,由此建立结构极限状态方程,再运用结构可靠度分析中的蒙特卡洛法(MCS法)利用结构的失效频率来估算其失效概率。在本文中提出了利用ANSYS的概率分析功能结合MCS法进行结构的可靠性分析的方法,并通过一个实例具体说明了利用ANSYS的概率分析功能实现结构的可靠性分析的可行性。