Preferred Handrail Height for Spiral Stairs—A Fitting Trial Study

Stairways are, in general, a thoroughly studied subject, but there is almost no scientific data available about spiral stairs. They are, however, widely used in homes, industrial sites and public buildings. The purpose of this study was to determine preferred handrail heights for a spiral stairway. The most preferred handrail height for descent was 105 cm. On the other hand, 95% of the participants regarded handrail heights between 95 and 100 cm satisfactory for descending. Participants’ anthropometric data was combined with the handrail height preference to develop a draft of a model to predict preferred handrail height for other user populations.     

线性拟合法对水质中镉的测量不确定度评定研究

应用top-down技术中的线性拟合法,通过对不同浓度标准样品的多次重复测定,利用方差分析确保校准曲线处于偏倚受控状态,并运用控制图技术对回归曲线的变异进行动态监控。在期间精密度条件下,通过合并较低和较高两个浓度标准样品检测结果方差的方法,对电感耦合等离子体质谱法测量水中镉的不确定度进行估计。这种方法避免了复杂的分量计算,减小了易造成失误的风险,有助于仪器分析领域的不确定度评定。     

水中BOD_5快速测定方法研究

生化需氧量是评价水体受有机物污染的相对耗氧指标。此生物氧化全过程进行的时间长,如在20℃培养时,完成此过程需100多天。BOD5标准测定方法采用稀释接种培养法,缺点是测定周期太长(需5天),不能及时反映水质指标,因此人们一直在研究BOD的快速测定方法。文章从BOD的特点研究BOD2和BOD5的关系,摸索了一种BOD5的快速测定方法;根据菲尔甫斯定律,找出了BOD2与BOD5的相关关系,通过BOD2与BOD5的拟合,建立相关方程,推导出BOD5速测公式,根据BOD2的值能够快速测定BOD5的值,缩短了分析周期,符合环境管理的要求。本方法较严密,省时,可供大家研讨。     

不同源汇信息提取方法对区域CO2源汇估算及其季节变化的影响评估

从大气二氧化碳(CO2)浓度观测资料中准确提取源汇或本底信息对区域及全球碳源汇及大气CO2浓度长期变化趋势的定量估计至关重要.本研究以瓦里关大气CO2浓度观测资料为例,探讨了同期地面风和同期一氧化碳(CO)浓度观测资料作为源汇信息提取或本底值筛选因子的有效性.结果表明,地面风和同期CO浓度在冬季可作为筛选因子,但是夏季将其作为筛选因子不是十分有效.采用局部近似回归法(robust estimation of background signal,REBS)、傅里叶变换法(Fourier transform algorithm,FTA)和新发展的平均移动过滤法(moving average filtering,MAF)进行大气CO2浓度源汇及本底信息提取.结果表明,MAF法因其以每2周为一个拟合窗口,采用不断变化和调整的过滤标准,避免了在局部将抬升浓度或吸收浓度百分比过高或者过低估计,优于另外两种方法.3种方法对因区域排放源导致的大气CO2的抬升量的结果无显著差异,但对因区域吸收汇导致的大气CO2降低量差异明显.结果表明,3种方法均可以对受到人类活动排放源影响的CO2抬升浓度合理地筛分,但只有MAF法可对夏季吸收浓度较好地判别.MAF法获得的1995~2008年瓦里关大气CO2多年平均季振幅为约10.3×10-6(摩尔分数,下同),与前期观测结果一致;而REBS法得到的大气CO2逐年季振幅约为9.1×10-6,将会导致低估区域或全球CO2通量值.     

Application of an evolutionary algorithm to the inverse parameter estimation of an individual-based model

Inverse parameter estimation of individual-based models (IBMs) is a research area which is still in its infancy, in a context where conventional statistical methods are not well suited to confront this type of models with data. In this paper, we propose an original evolutionary algorithm which is designed for the calibration of complex IBMs, i.e. characterized by high stochasticity, parameter uncertainty and numerous non-linear interactions between parameters and model output. Our algorithm corresponds to a variant of the population-based incremental learning (PBIL) genetic algorithm, with a specific “optimal individual” operator. The method is presented in detail and applied to the individual-based model OSMOSE. The performance of the algorithm is evaluated and estimated parameters are compared with an independent manual calibration. The results show that automated and convergent methods for inverse parameter estimation are a significant improvement to existing ad hoc methods for the calibration of IBMs.     

Quantifying parameter uncertainty in a coral reef model using Metropolis-Coupled Markov Chain Monte Carlo

Coral reefs are threatened ecosystems, so it is important to have predictive models of their dynamics. Most current models of coral reefs fall into two categories. The first is simple heuristic models which provide an abstract understanding of the possible behaviour of reefs in general, but do not describe real reefs. The second is complex simulations whose parameters are obtained from a range of sources such as literature estimates. We cannot estimate the parameters of these models from a single data set, and we have little idea of the uncertainty in their predictions.We have developed a compromise between these two extremes, which is complex enough to describe real reef data, but simple enough that we can estimate parameters for a specific reef from a time series. In previous work, we fitted this model to a long-term data set from Heron Island, Australia, using maximum likelihood methods. To evaluate predictions from this model, we need estimates of the uncertainty in our parameters. Here, we obtain such estimates using Bayesian Metropolis-Coupled Markov Chain Monte Carlo. We do this for versions of the model in which corals are aggregated into a single state variable (the three-state model), and in which corals are separated into four state variables (the six-state model), in order to determine the appropriate level of aggregation. We also estimate the posterior distribution of predicted trajectories in each case.In both cases, the fitted trajectories were close to the observed data, but we had doubts about the biological plausibility of some parameter estimates. We suggest that informative prior distributions incorporating expert knowledge may resolve this problem. In the six-state model, the posterior distribution of state frequencies after 40 years contained two divergent community types, one dominated by free space and soft corals, and one dominated by acroporid, pocilloporid, and massive corals. The three-state model predicts only a single community type. We conclude that the three-state model hides too much biological heterogeneity, but we need more data if we are to obtain reliable predictions from the six-state model. It is likely that there will be similarly large, but currently unevaluated, uncertainty in the predictions of other coral reef models, many of which are much more complex and harder to fit to real data.     

针铁矿的非生物还原解离特征及Slogistic模型拟合

以针铁矿为研究对象,分析了电子供体和针铁矿浓度以及氧化还原中介体AQS对针铁矿非生物还原解离作用的影响.结果表明,在没有氧化还原中介体的参与下,针铁矿的非生物还原作用十分微弱;AQS加入体系后,针铁矿的非生物还原程度在经历一定的反应时间后显著加剧,且还原过程中生成的解离态Fe(ΙΙ)含量随时间的变化趋势符合典型的Slogistic曲线特征.Slogistic拟合结果表明:一定电子供体浓度下,不同浓度针铁矿的非生物还原Slogistic模型拟合的校正R2在0.9887~0.9953之间.当针铁矿浓度维持为一恒定值时,电子供体浓度不足的情况下,针铁矿的非生物还原的Slogistic 曲线特征较弱;当电子供体浓度充足的条件下,Slogistic模型拟合的校正R2系数可高达0.9967.电子供体和针铁矿浓度以及氧化还原中介体AQS的参与对Slogistic模型拟合参数均有一定的影响.     

碳数和官能团对直链易挥发化合物异味阈值的影响规律

以具有代表性的异味特征-异味阈值为研究对象,采用三点比较式臭袋法测定了醇类、醛类、酮类、酸类和硫醇类5个系列常见异味化合物的异味阈值,研究了异味阈值与碳链长度之间的关系,并以官能团疏水性参数量化表征官能团结构,研究了异味阈值与官能团类型之间的关系.研究发现,分子碳链长度和官能团类型都能影响异味阈值的大小,其中异味阈值与碳链长度关系为y=axb或lgy=cx+d(y:异味阈值,x:碳原子数);异味阈值与官能团疏水常数π参数关系为y=aebx或lgy=cx+d(y:异味阈值,x:官能团疏水性参数).所得模型能定量描述碳链长度和官能团类型对异味阈值的影响,为异味机理的进一步探索提供了有力支撑.此外,对异味阈值与上述两因素的多元线性拟合及残差分析结果表明,碳链长度和官能团类型能够影响化合物异味阈值,但二者并非异味阈值的完全决定因素,研究决定异味阈值的全面结构因素,需大量后续工作.     

中小学校园拥挤踩踏事故风险评估指标研究

为研究诱发中小学校园拥挤踩踏事故风险因素,根据近年来21起典型事故统计结果,设计调查问卷,在问卷信度检验结果满足良好的相关水平和一致性的基础上得出中小学校园拥挤踩踏事故影响因素分为4个方面,9个因素。基于数据处理系统(DPS),引入非参数投影寻踪回归模型的理论方法,对多维拥挤踩踏事故影响因素数据进行投影降维分析,利用交叉核实,进行非参数拟合,得出每一因素的权重值及事故发生预测值。拟合结果表明:人群失控、人群密度、时间限制3个影响因素更为重要,在校园拥挤踩踏事故日常预防中应多予重视,同时初步探讨影响因素权重在中小学拥挤踩踏事故评估中的应用,为进一步有效防止校园拥挤踩踏事故发生提供技术支持。