Forecasting China’s primary energy demand based on an improved AI model

An improved energy demand forecasting model is built based on the autoregressive distributed lag (ARDL) bounds testing approach and an adaptive genetic algorithm (AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization, and technological progress as the input variables. On the basis of historical annual data from 1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.     

中国FDI环境效应的再检验

改革开放以来,外商直接投资(FDI)的涌入为中国经济发展注入了新活力,并成为中国经济高速增长的重要引擎之一。然而,随着康菲石油渤海漏油事故、江苏启东王子造纸排污和阿玛尼污染投诉等涉外污染事件报道频出,学术界对于FDI涌入可能带来的负面环境效应表现出一定担忧。现有文献多聚焦于整体层面的FDI环境效应检验,而对其区域差异及原因产生机制的系统探究并不多见。为此,本文从理论判断和命题推演出发,利用2003—2014年中国省际面板数据,以改进熵值法拟合环境污染综合指数,并构建普通面板模型,实证检验了FDI流入对中国环境污染的影响及其区域差异。结果表明,总体而言,"污染光环"假说在中国基本成立,即FDI流入在一定程度上改善了中国环境质量,但不同地区FDI的环境效应有所不同,其主要表现为沿海和内陆地区FDI具有显著的"污染光环"效应,且前者强于后者,而沿边地区FDI具有不明显的"污染天堂"效应。在此基础上,构造面板门槛模型,进一步系统考察了FDI对中国环境污染影响的4种主要吸收能力因素的门槛效应。门槛回归结果表明,FDI对中国环境污染的影响显著存在基于经济发展、环境规制、人力资本和金融发展水平的双门槛效应。经济发展、人力资本和金融发展水平越高,FDI的"污染光环"效应越明显,而适度的环境规制才更有利于FDI环境技术溢出的发挥。基于此,本文建议应进一步全方位地提高对外开放水平,一如既往地积极引进并监督FDI;同时地方政府也需认清地区发展的不平衡性,进而采取差异化的引资政策。     

遗传投影寻踪回归在城市环境质量评价中的应用

引入投影降维的思想,将遗传投影寻踪与回归分析技术运用到城市环境质量评价中。将此技术与神经网络方法进行实例比较,投影寻踪回归方法不但可以合理地作出环境质量的综合评价,而且消除了神经网络方法中类别判断不够精确的影响。     

Metabolic diversity of the heterotrophic microorganisms and potential link to pollution of the Rouge River

The heterotrophic microbial communities of the Rouge River were tracked using Biolog Ecoplates to understand the metabolic diversity at different temporal and spatial scales, and potential link to river pollution. Site less impacted by anthrophogenic sources (site 1), showed markedly lower metabolic diversity. The only substrates that were utilized in the water samples were carbohydrates. Sites more impacted by anthrophogenic sources (sites 8 and 9) showed higher metabolic diversity. Higher functional diversity was linked to the physico-chemical and biological properties of the water samples (i.e. higher concentrations of DO, DOC, chlorophyll, and bacterial density). Biolog analysis was found to be useful in differentiating metabolic diversity between microbial communities; in determining factors that most influence the separation of communities; and in identifying which substrates were most utilized by the communities. It can also be used as an effective ecological indicator of changes in river function attributable to urbanization and pollution.     

响应面法和神经网络优化Acinetobactersp．DNS32发酵基质

为了提高阿特拉津降解菌Acinetobactersp．DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分（玉米粉、豆饼粉、K：HPO。）进行优化研究。响应曲面法确定3种成分的含量为玉米粉39．494g／L,豆饼粉25．638g／L和K。HPO。3．265g／L时,预测发酵活菌最大生物量为7．079×10^8CFU／mL,实测量为7．194×10^8CFU／mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39．650g／L,豆饼粉为25．500g／L,K2HPO4为2．624g／L时,预测最大值为7．199×10^8CFU／mL,实测量为7．244×10。CFU／mL;最终确定培养基配方：玉米粉为39．650g／L,豆饼粉为25．500g／L,K2HPO4为2．624g／L,CaCO3为3．000g／L,MgSO4·7H2O和NaCl均为0．200g／L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36．6％。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

响应面法和神经网络优化Acinetobacter sp. DNS32发酵基质

为了提高阿特拉津降解菌Acinetobacter sp.DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分(玉米粉、豆饼粉、K2HPO4)进行优化研究。响应曲面法确定3种成分的含量为玉米粉39.494 g/L,豆饼粉25.638 g/L和K2HPO43.265 g/L时,预测发酵活菌最大生物量为7.079×108CFU/mL,实测量为7.194×108CFU/mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L时,预测最大值为7.199×108CFU/mL,实测量为7.244×108CFU/mL;最终确定培养基配方:玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L,CaCO3为3.000 g/L,MgSO4.7H2O和NaCl均为0.200 g/L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36.6%。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

16S rDNA克隆文库解析AO-MBR系统中细菌种群多样性

采用分子生物学手段16S rDNA克隆文库方法对缺氧/好氧膜生物反应器(AO-MBR)的好氧池与缺氧池中细菌进行了多样性研究.实验结果表明,好氧池污泥样品的克隆文库包括9个类群,其中变形菌(Proteobacteria)和拟杆菌(Bacteroidetes)在文库中所占比例最大,分别为37.04％和14.81％;其次是酸杆菌(Acidobacteria)、未培养菌(uncultured bacterium)、绿菌(Chlorobi)和未培养的绿弯菌(uncultured Chloroflexi bacterium)、浮霉状菌(Planctomycetes),分别为11.11％、11.11％、7.41％、7.41％和5.56％;硝化螺旋菌(Nitrospirae)和裸藻门(Euglenozoa)所占比例相对较小,均为1.85％.缺氧池样品克隆文库包括10个类群,其中变形菌(Proteobacteria)、拟杆菌(Bacteroidetes)和未培养菌(uncultured bacterium)在文库中所占比例最大,分别为27.91％、13.95％和12.79％;其次是浮霉状菌(Planctomycetes)、酸杆菌(Acidobacteria)和绿弯菌(Chloroflexi),在文库中所占比例分别为9.3％、9.3％和9.3％;硝化螺旋菌(Nitrospirae)、裸藻门(Euglenozoa)、芽单胞菌(Gemmatimonadetes)和放线菌(Actinobacteria)所占比例相对较少,分别为6.98％、8.14％、1.16％和1.16％.两池细菌的主要类群相似,但菌属及比例有所差异,变形菌是系统中的主要脱氮菌属.     

Post-flooding disaster crop diversity recovery: a case study of Cowpea in Mozambique

To restore food security to a traditional African cropping system following a sudden loss of seed, genetic diversity must be re-established. This study examines the extent to which Cowpea diversity was reinstated two years after a flood disaster in Gaza Province, Mozambique. The contribution that seed from various sources made to the recovery was assessed using semi-structured interviews and morphological and molecular data. Data suggest that diversity had recovered to some extent yet there was evidence of a narrowing of the genetic base, with fewer rare alleles and differences in the distribution of allele frequencies. Although the main channels for accessing seed after the flood were seed relief and markets, these sources contributed to minimal and different diversity. It appears that diversity was regained primarily through social networking in the form of loans or gifts of seed from friends and relatives. The results of the study are discussed in relation to seed relief approaches.     

Human Influence and Classical Biogeographic Predictors of Rare Species Occurrence

Biogeographic theory predicts that rare species occur more often in larger, less‐isolated habitat patches and suggests that patch size and connectivity are positive predictors of patch quality for conservation. However, in areas substantially modified by humans, rare species may be relegated to the most isolated patches. We used data from plant surveys of 81 meadow patches in the Georgia Basin of Canada and the United States to show that presence of threatened and endangered plants was positively predicted for patches that were isolated on small islands surrounded by ocean and for patches that were isolated by surrounding forest. Neither patch size nor connectivity were positive predictors of rare species occurrence. Thus, in our study area, human influence, presumably due to disturbance or introduction of competitive non‐native species, appears to have overwhelmed classical predictors of rare species distribution, such that greater patch isolation appeared to favor presence of rare species. We suggest conservation planners consider the potential advantages of protecting geographically isolated patches in human‐modified landscapes because such patches may represent the only habitats in which rare species are likely to persist. Influencia Humana y Predictores Biogeográficos Clásicos de la Ocurrencia de Especies Raras