In vitro evaluation of inorganic and methyl mercury mediated cytotoxic effect on neural cells derived from different animal species

To extend the current understanding of the mercury-mediated cytotoxic effect,five neural cell lines established from different animal species were comparatively analyzed using three different endpoint bioassays:thiazolyl blue tetrazolium bromide,3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay(MTT),neutral red uptake assay(NRU),and Coomassie blue assay(CB).Following a 24-hr exposure to selected concentrations of mercury chloride(HgCl_2) and methylmercury(Ⅱ) chloride(MeHgCl),the cytotoxic effect on test cells was characterized by comparing their 50%inhibition concentration(IC_(50)) values.Experimental results indicated that both these forms of mercury were toxic to all the neural cells,but at very different degrees.The IC_(50)values of MeHgCl among these cell lines ranged from 1.15±0.22 to 10.31 ± 0.70 μmol/L while the IC_(50) values for HgCl_2 were much higher,ranging from 6.44 ± 0.36 to 160.97±19.63 μmol/L,indicating the more toxic nature of MeHgCl.The IC_(50) ratio between HgCl_2and MeHgCl ranged from 1.75 to 96.0,which confirms that organic mercury is much more toxic to these neural cells than inorganic mercury.Among these cell lines,HGST-BR and TriG44 derived from marine sea turtles showed a significantly high tolerance to HgCl_2 as compared to the three mammalian neural cells.Among these neural cells,SK-N-SH represented the most sensitive cells to both chemical forms of mercury.     

Comparing discriminant analysis, neural networks and logistic regression for predicting species distributions: a case study with a Himalayan river bird

We assessed the occurrence of a common river bird, the Plumbeous Redstart Rhyacornis fuliginosus, along 180 independent streams in the Indian and Nepali Himalaya. We then compared the performance of multiple discrimant analysis (MDA), logistic regression (LR) and artificial neural networks (ANN) in predicting this species’ presence or absence from 32 variables describing stream altitude, slope, habitat structure, chemistry and invertebrate abundance. Using the entire data (=training set) and a threshold for accepting presence in ANN and LR set to P≥0.5, ANN correctly classified marginally more cases (88%) than either LR (83%) or MDA (84%). Model performance was assessed from two methods of data partitioning. In a ‘leave-one-out’ approach, LR correctly predicted more cases (82%) than MDA (73%) or ANN (69%). However, in a holdout procedure, all the methods performed similarly (73–75%). All methods predicted true absence (i.e. specificity in holdout: 81–85%) better than true presence (i.e. sensitivity: 57–60%). These effects reflect species’ prevalence (=frequency of occurrence), but are seldom considered in distribution modelling. Despite occurring at only 36% of the sites, Plumbeous Redstarts are one of the most common Himalayan river birds, and problems will be greater with less common species. Both LR and ANN require an arbitrary threshold probability (often P=0.5) at which to accept species presence from model prediction. Simulations involving varied prevalence revealed that LR was particularly sensitive to threshold effects. ROC plots (received operating characteristic) were therefore used to compare model performance on test data at a range of thresholds; LR always outperformed ANN. This case study supports the need to test species’ distribution models with independent data, and to use a range of criteria in assessing model performance. ANN do not yet have major advantages over conventional multivariate methods for assessing bird distributions. LR and MDA were both more efficient in the use of computer time than ANN, and also more straightforward in providing testable hypotheses about environmental effects on occurrence. However, LR was apparently subject to chance significant effects from explanatory variables, emphasising the well-known risks of models based purely on correlative data.     

基于贝叶斯网络的航空器看错落错跑道事件研究

目前,航空器看错、落错跑道事件在国际上是一个相当突出的安全问题,这个问题在我国近年也突显出来。导致航空器看错落错跑道的原因十分复杂,且此类事件及易引发严重的后果,造成人、财、物等多方面的损失,本文特对此类问题开展了一系列的研究。为了预防航空器看错、落错跑道事故的发生,查找诱发该类事故的因素,针对航空器看错、落错跑道事故的形成特点,笔者运用贝叶斯网络探讨其各影响因素间的关系和相互作用,该网络强大的逻辑推理能力,克服了不完备样本空间带来的不足,揭示了人、机、环境与管理因素相互作用的内在规律。为改善机场安全管理的科学性、可靠性,进一步降低事故率,提供了可靠的技术支持。     

Simulation-based fault propagation analysis—Application on hydrogen production plant

Recently production of hydrogen from water through the Cu–Cl thermochemical cycle is developed as a new technology. The main advantages of this technology over existing ones are higher efficiency, lower costs, lower environmental impact and reduced greenhouse gas emissions. Considering these advantages, the usage of this technology in new industries such as nuclear and oil is increasingly developed. Due to hazards involved in hydrogen production, design and implementation of hydrogen plants require provisions for safety, reliability and risk assessment. However, very little research is done from safety point of view. This paper introduces fault semantic network (FSN) as a novel method for fault diagnosis and fault propagation analysis by using evolutionary techniques like genetic programming (GP) and neural networks (NN), to uncover process variables’ interactions. The effectiveness, feasibility and robustness of the proposed method are demonstrated on simulated data obtained from the simulation of hydrogen production process in Aspen HYSYS^®. The proposed method has successfully achieved reasonable detection and prediction of non-linear interaction patterns among process variables.     

基于HCNAM-BN的化工过程爆炸事故致因链分析

为了从源头上预防化工过程爆炸事故,依据风险耦合理论,探讨了各风险因子非线性耦合演化为爆炸事故的机理,构建了层次耦合网络分析模型（HCNAM）;从多因素风险耦合角度分析了国内外44起典型化工过程爆炸事故,统计了各风险因子之间的耦合概率并进行了耦合致因重要度分级;采用耦合概率与二态分布相结合的条件概率分布,将层次耦合网络分析模型转化为贝叶斯网络,并对氯乙烯单体槽爆炸性混合气体爆炸事故进行了应用研究。结果表明:91种双因子耦合风险状态中,47种呈现弱耦合致因特性;7种因子双耦合形成风险的概率较大;基于HCNAM-BN模型分析事故,可有效辨识事故最可能致因因素,获取各事故致因链的发生概率并确定事故网络关键节点。     

河湖水系连通的理论探讨

在全球气候变化和水资源形势日趋严峻的背景下,为了从根本上提高水资源统筹配置能力、改善河湖健康状况和增强抵御水旱灾害能力,河湖水系连通作为国家新时期的一个治水方略被提出。当前关于河湖水系连通的理论基础研究要落后于实践,尚在探索之中。论文尝试从河、湖与水系等水循环基本概念入手,探讨水系的结构、特征和连通性,揭示水系连通的水循环物理机制,并进一步分析河湖水系连通的战略思想,探明其中涉及的几个关键水循环基础问题,包括水量平衡、能量平衡、水资源可再生性、水循环尺度等问题,为河湖水系连通战略的实施和理论体系的建立奠定基础。     

Ecosystem network analysis indicators are generally robust to parameter uncertainty in a phosphorus model of Lake Sidney Lanier, USA

Understanding how data uncertainty influences ecosystem analysis is critical as we move toward ecosystem-based management. Here, we investigate how 18 Ecological Network Analysis (ENA) indicators that characterize ecosystem growth, development, and condition are affected by uncertainty in an ecosystem model of Lake Sidney Lanier (USA). We applied ENA to 122 plausible parameterizations of the ecosystem developed by Borrett and Osidele (2007, Ecological Modelling 200, 371-387), and then used the coefficient of variation (CV) to compare system indicator variability. We considered Total System Throughput (TST) as a measure of the underlying model uncertainty and tested three hypotheses. First, we hypothesized that non-ratio indicators whose calculation includes the TST would be at least as variable as TST if not more variable. Second, we postulated that indicators calculated as ratios, with TST in the numerator and denominator would tend to be less variable than TST because its influence will cancel. Last, we expected the Average Mutual Information (AMI) to be less variable than TST because it is a bounded function. Our work shows that the 18 indicators grouped into four categories. The first group has significantly larger CVs than the CV for TST. In this group, model uncertainty is amplified rendering these three indicators less useful. The second group of four indicators shows no significant difference in variability with respect to TST. Finally, there are two groups whose CV values are significantly lower than that for TST. The least variable group includes the ratio-based indicators and Average Mutual Information. Due to their low variability, we conclude that these indicators are the most robust to the parameter uncertainty and most useful for ecosystem assessment and comparative ecosystem analysis. In summary, this work suggests that we can be as certain, or more certain, in most of the selected ENA indicators as we are in the parameters of the model analyzed.     

Beyond identity crisis: The challenge of recontextualizing ecosystem delimitation

In a series of papers, three important system ecologists, Bernard C. Patten, Sven E. Jorgensen and Milan Straškraba attempt to revise the old ecosystem field and construct a new systems ecology. Inevitably, their attempt is faced with some of the same problems that led the field to decline. The indefiniteness of ecosystem boundaries is one of them, maybe the most important. Systems’ ecology failure to define ecosystem boundaries was considered a significant obstacle for the conceptualization of the ecosystem as a valid organizing unit of nature and resulted in a disciplinary identity crisis. To surmount this crisis, the authors introduce into the field innovative ideas which have their origin in the so-called postmodern network theories. These ideas reinforce the concept of environment and allow for a relative conception of space, which might have beneficial effects in delimiting ecosystems. However, the problem-solving potential of these ideas is not activated because the authors remain stitched to the Odumian mode of ecosystem thinking and avoid recontextualizing the old building blocks.     

Multiple structural modifications to dendritic ecological networks produce simple responses

Structural modifications to landscapes affect the ability of organisms to access different habitat patches. There exist, however, very few general methods by which to relate modifications to expectations of effects, and even fewer that enable understanding of how multiple modifications may interact. In the absence of any guiding principles, ecologists have assumed that interactions will result in complex landscape-scale effects. One way of understanding such effects is through rendering a landscape as a graph or network, among the simplest of which are dendritic networks typified by stream systems. Yet even for stream networks, there are no known general principles concerning the nature of interactions between multiple modifications. We developed a model to describe the ability of fish to access and use different habitat patches within dendritic networks. We used mathematical and numerical analyses of the model to investigate how the habitat value of a network is affected by changes in connectivity and habitat quality, and then to examine interactions between multiple modifications. Rather than showing complex interactions, our analytic and simulation-based results show that the combined effect of multiple modifications approximately equals the sum of individually predicted effects. Dendritic networks thus appear to respond far more simply to multiple modifications than has previously been assumed. These results have implications for stream management planning, and offer a firm foundation from which to better understand population processes within dendritic networks.     

学习率有限监督调整BP网络在水质评价中的应用

以地表水环境质量标准基本项目标准限值为依据,随机生成标准样本和检测样本,采用学习率有限监督调整BP网络建立水质评价模型。完成网络训练的模型对检测样本进行检验评价,检验结果表明,该人工神经网络水质评价模型具有较高的精度,同时,可以避免人为主观因素对水质评价的影响,保证了水质鉴定的科学性和公正性。