润滑油废白土的应用探索

针对炼油企业废白土排放污染环境问题,在实验室中利用溶剂进行脱油处理,其脱油率及脱油废渣活性度都较高,但再生后的脱油废渣仍难以重复利用。而利用废白土作型砂添加剂的试验研究,其工业试验结果较为理想,且能彻底解决废渣的污染问题,实现其环保利用。     

基于广义可加模型和案例推理的东南太平洋智利竹筴鱼中心渔场预报

根据2001～2008年我国渔船在东南太平洋海域的智利竹筴鱼生产统计数据以及同期卫星遥感数据反演的海表温度、叶绿素浓度、海表温度梯度等数据,利用广义可加模型定量分析了智利外海竹筴鱼资源分布同环境因子的关系。根据GAM模型的研究结果,确定海表温度作为竹筴鱼中心渔场预报指标。利用案例推理方法,通过三级相似检索对智利竹筴鱼中心渔场进行预报。试验性预报实例的结果与渔船实际作业情况比较表明,预报精度达到68%,能一定程度上反映竹筴鱼资源的分布。     

添加剂对水泥固化体机械性能的影响

以蛭石、分子筛、玻璃纤维为添加剂进行水泥固化并进行抗压强度和抗冲击性测试,结果表明:在抗压强度方面,以玻璃纤维作为添加剂的固化体抗压强度最大,分子筛次之,蛭石最差。在抗冲击性方面,蛭石对水泥固化体的抗冲击性能没有改善作用;以分子筛为添加剂在一定程度上可以改善水泥固化体的抗冲击性;以玻璃纤维为添加剂的水泥固化体有很好的抗冲击性。     

Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions

Two statistical modelling techniques, generalized additive models (GAM) and multivariate adaptive regression splines (MARS), were used to analyse relationships between the distributions of 15 freshwater fish species and their environment. GAM and MARS models were fitted individually for each species, and a MARS multiresponse model was fitted in which the distributions of all species were analysed simultaneously. Model performance was evaluated using changes in deviance in the fitted models and the area under the receiver operating characteristic curve (ROC), calculated using a bootstrap assessment procedure that simulates predictive performance for independent data. Results indicate little difference between the performance of GAM and MARS models, even when MARS models included interaction terms between predictor variables. Results from MARS models are much more easily incorporated into other analyses than those from GAM models. The strong performance of a MARS multiresponse model, particularly for species of low prevalence, suggests that it may have distinct advantages for the analysis of large datasets. Its identification of a parsimonious set of environmental correlates of community composition, coupled with its ability to robustly model species distributions in relation to those variables, can be seen as converging strongly with the purposes of traditional ordination techniques.     

两种工艺下某天线微通道冷板特性的实验研究

目的研究不同工艺下微通道冷板的特性及成因。方法以实验研究为基础,对两种工艺方式(增材制造和真空钎焊)下的某天线微通道冷板进行流动和传热分析。另外,还使用CT技术对两种冷板的内部结构进行成像。结果获得了冷板特性数据和内部成像图片。结论分析表明,增材制造的微通道冷板具有良好的性能,具备工程应用的潜力。     

Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty

The Eastern Arc Mountains (EAMs) of Tanzania and Kenya support some of the most ancient tropical rainforest on Earth. The forests are a global priority for biodiversity conservation and provide vital resources to the Tanzanian population. Here, we make a first attempt to predict the spatial distribution of 40 EAM tree species, using generalised additive models, plot data and environmental predictor maps at sub 1 km resolution. The results of three modelling experiments are presented, investigating predictions obtained by (1) two different procedures for the stepwise selection of predictors, (2) down-weighting absence data, and (3) incorporating an autocovariate term to describe fine-scale spatial aggregation. In response to recent concerns regarding the extrapolation of model predictions beyond the restricted environmental range of training data, we also demonstrate a novel graphical tool for quantifying envelope uncertainty in restricted range niche-based models (envelope uncertainty maps). We find that even for species with very few documented occurrences useful estimates of distribution can be achieved. Initiating selection with a null model is found to be useful for explanatory purposes, while beginning with a full predictor set can over-fit the data. We show that a simple multimodel average of these two best-model predictions yields a superior compromise between generality and precision (parsimony). Down-weighting absences shifts the balance of errors in favour of higher sensitivity, reducing the number of serious mistakes (i.e., falsely predicted absences); however, response functions are more complex, exacerbating uncertainty in larger models. Spatial autocovariates help describe fine-scale patterns of occurrence and significantly improve explained deviance, though if important environmental constraints are omitted then model stability and explanatory power can be compromised. We conclude that the best modelling practice is contingent both on the intentions of the analyst (explanation or prediction) and on the quality of distribution data; generalised additive models have potential to provide valuable information for conservation in the EAMs, but methods must be carefully considered, particularly if occurrence data are scarce. Full results and details of all species models are supplied in an online Appendix.     

添加剂PEG对共混超滤膜结构和性能的影响

以不同分子量聚乙二醇 (PEG)作为PSf/A共混超滤膜的添加剂 ,测定所制备膜的水通量、截留率 .结果表明 ,膜的水通量随PEG分子量的变化呈现非线性关系 .当PEG分子量为4000时 ,水通量达到最大值115.2mL·(cm²·h)^-1,是不加PEG时的6倍 .通过超滤实验结果以及膜结构的电镜照片的观察 ,研究了PSf/A共混超滤膜体系中PEG作用的规律 .PEG分子量的增加改变了PSf/A铸膜液体系的相平衡关系 ,使铸膜液成为热力学不稳定体系 ,加速了相分离的发生 ;另外 ,PEG分子量的增加提高了铸膜液的粘度 ,引起相分离的延迟,这2种作用影响了膜的最终结构和性能.     

甲基叔丁基醚的研究进展

甲基叔丁基醚(MTBE)用作汽油添加剂具有很多优点,但由于MTBE本身的性质,决定了其对生态环境也有一定的影响。介绍了MTBE的基本性质、国内外生产概况、制备工艺、对环境的潜在危害及替代品等。     

Long-term exposure to air pollution and cerebrovascular disease: findings from Beijing Health Management Cohort study

● This study explored the long-term association by double robust additive models. ● Individual exposure concentrations were assessed by integrating GAM, LUR and BPNN. ● PM_2.5, SO₂ and NO₂ are positively associated with cerebrovascular disease. ● CO could reduce the risk of cerebrovascular disease with the highest robustness. ● The elderly, women and people with normal BMI are at higher risk for air pollution. The relationship between air pollution and cerebrovascular disease has become a popular topic, yet research findings are highly heterogeneous. This study aims to investigate this association based on detailed individual health data and a precise evaluation of their exposure levels. The integrated models of generalized additive model, land use regression model and back propagation neural network were used to evaluate the exposure concentrations. And doubly robust additive model was conducted to explore the association between cerebrovascular disease and air pollution after adjusted for demographic characteristics, physical examination, disease information, geographic and socioeconomic status. A total of 25097 subjects were included in the Beijing Health Management Cohort from 2013 to 2018. With a 1 μg/m³ increase in the concentrations of PM_2.5, SO₂ and NO₂, the incidence risk of cerebrovascular disease increased by 1.02 (95% CI: 1.008–1.034), 1.06 (95% CI: 1.034–1.095) and 1.02 (95% CI: 1.010–1.029) respectively. Whereas CO exposure could decrease the risk, with an odds ratio of 0.38 (95% CI: 0.212–0.626). In the subgroup analysis, individuals under the age of 50 with normal BMI were at higher risk caused by PM_2.5, and SO₂ was considered more hazardous to women. Meanwhile, the protective effect of CO on women and those with normal BMI was stronger. Successful reduction of long-term exposure to PM_2.5, SO₂ and NO₂ would lead to substantial benefits for decrease the risk of cerebrovascular disease especially for the health of the susceptible individuals.