Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

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.     

秸秆发酵乳酸菌复合系SFC-2的构建及其组成多样性研究

为了获得促进作物干秸秆乳酸发酵的微生物,以玉米秸秆和水稻秸秆的自然发酵物为菌种来源,用MRS蔗糖培养基,通过连续定向继代培养,筛选出pH下降迅速、乳酸含量高、组成稳定的乳酸菌复合系SFC-2.DGGE分析表明,SFC-2经过连续继代培养,从第25代开始其微生物组成基本稳定.SFC-2 培养12 h后pH下降至3.8,乳酸含量达10.64 mg/mL,其中64%为L-(+) 乳酸.通过平板分离获得4株细菌,全部为Lactobacillus,其近缘种分别为L. fermentum、L. plantarum、L. paracasei和L. paracasei sub sp.;通过16S rDNA克隆文库分析获得7个克隆,其近缘种主要为L. fermentum、L. plantarum及L.paracasei;在16S rDNA的克隆文库中,76.3%为L. fermentum的近缘种,20.3%为L. plantarum的近缘种,3.4%为L. paracasei的近缘种.     

贵州喀斯特山区不同种植年限花椒根际土壤细菌群落结构特征研究

以贵州花江峡谷花椒(Zanthoxylum bungeamun)林为研究对象,采用16S rRNA高通量测序技术,分析种植5、10、20、30 a花椒根际土壤细菌群落结构和多样性特征,探讨不同种植年限花椒土壤理化因子对根际细菌群落分布的影响,为喀斯特石漠化地区花椒农业可持续发展提供有效的理论依据.结果表明,随着花椒种植...     

都昌县多宝砂山物种多样性研究及保护初探

对鄱阳湖都昌县多宝砂山地区土地风沙化过程中物种多样性的变化特征进行了分析,依据植物种在各类型风沙化土地的出现频率与不同风沙化阶段各生活型植物种的组成,探讨了风沙化过程中植物种的绝灭与定居特点.物种多样性指数分析表明:风沙化过程是物种多样性衰减的过程,风沙化首先导致特有种的绝灭,其次为稀有种.从植物的生活型来看,多年生草本与乔木类植物受风沙化影响最大,而灌木类植物可存活于风沙化过程的各个阶段,在风沙化过程中植物种的绝灭速率大于定居速率.最后,针对造成多宝砂山生物多样性衰减的原因,提出了治理对策,即在控制人类行为干扰的同时,要加强对固定沙丘的管理与保护.      

Ecological effects of crude oil residues on the functional diversity of soil microorganisms in three weed rhizospheres

Ecological effects of crude oil residues on weed rhizospheres are still vague. The quantitative and diversity changes and metabolic responses of soil-bacterial communities in common dandelion （Taraxacum officinale）, jerusalem artichoke （Silphiurn perfoliatum L.） and evening primrose （A colypha australis L.） rhizospheric soils were thus examined using the method of carbon source utilization. The results indicated that there were various toxic effects of crude oil residues on the growth and reproduction of soil bacteria, but the weed rhizospheres could mitigate the toxic effects. Total heterotrophic counting colony-forming units （CFUs） in the rhizospheric soils were significantly higher than those in the non-rhizospheric soils. The culturable soil-bacterial CFUs in the jerusalem artichoke （S. perfoliatum） rhizosphere polluted with 0.50 kg/pot of crude oil residues were almost twice as much as those with 0.25 kg/pot and without the addition of crude oil residues. The addition of crude oil residues increased the difference in substrate evenness, substrate richness, and substrate diversity between non-rhizospheric and rhizospheric soils of T. officinale and A. australis, but there was no significant （p〉0.05） difference in the Shannon＇s diversity index between non-rhizospheric and rhizospheric soils of S. perfoliatum. The rhizospheric response of weed species to crude oil residues suggested that S. perfoliatum may be a potential weed species for the effective plant-microorganism bioremediation of contaminated soils by crude oil residues.     

AHP与GA-SVM耦合模型在滑坡预警中的应用*

为了减少滑坡造成的损失,提高滑坡预测的准确性,通过搭建灾害模拟平台获得滑坡的实验数据,在获得多组模拟实验数据后,分析各变量的特性。首先,通过层次分析(Analytic Hierarchy Process,AHP)算法,对滑坡进行危险度划分;然后,通过支持向量机(Support Vector Machine,SVM)建立模型,遗传算法(Genetic Algorithm,GA)再优化SVM参数,提出1种层次分析法与GA-SVM相耦合的模型。研究结果表明:AHP方法划分后的数据,通过GA与SVM结合建立的模型精度较好,实验预测结果与实际结果较为吻合,与单一SVM相比,精度更高,结果更好,更加适用于多变量的复杂非线性滑坡预警。     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

The Influence of Linear Elements on Plant Species Diversity of Mediterranean Rural Landscapes: Assessment of Different Indices and Statistical Approaches

This paper mainly aims to study the linear element influence on the estimation of vascular plant species diversity in five Mediterranean landscapes modeled as land cover patch mosaics. These landscapes have several core habitats and a different set of linear elements -habitat edges or ecotones, roads or railways, rivers, streams and hedgerows on farm land- whose plant composition were examined. Secondly, it aims to check plant diversity estimation in Mediterranean landscapes using parametric and non-parametric procedures, with two indices: Species richness and Shannon index.Land cover types and landscape linear elements were identified from aerial photographs. Their spatial information was processed using GIS techniques. Field plots were selected using a stratified sampling design according to relieve and tree density of each habitat type. A 50×20 m² multi-scale sampling plot was designed for the core habitats and across the main landscape linear elements. Richness and diversity of plant species were estimated by comparing the observed field data to ICE (Incidence-based Coverage Estimator) and ACE (Abundance-based Coverage Estimator) non-parametric estimators.The species density, percentage of unique species, and alpha diversity per plot were significantly higher (p < 0.05) in linear elements than in core habitats. ICE estimate of number of species was 32% higher than of ACE estimate, which did not differ significantly from the observed values. Accumulated species richness in core habitats together with linear elements, were significantly higher than those recorded only in the core habitats in all the landscapes. Conversely, Shannon diversity index did not show significant differences.     

Selecting Species for Marine Assessment of Radionuclides Around Amchitka: Planning for Diverse Goals and Interests

Considerable attention has been devoted to selecting bioindicator species as part of monitoring programs for exposure and effects from contaminants in the environment. Yet the rationale for selection of bioindicators is often literature-based, rather than developed with a firm site-specific base of data on contaminant levels in a diverse range of organisms at different trophic levels in the same ecosystem. We suggest that this latter step is an important phase in the environmental assessment process that is often missing. In this paper we address the problem of how to select a wide range of species representing different trophic levels that serve as a basis for selecting a few species suitable as bioindicators. We illustrate this with our assessment of radionuclides on Amchitka Island, Alaska. We propose a multi-stage process for arriving at the list of available species that includes review of literature, review by experts experienced in the area, review by interested and affected parties, selection of trophic levels or groups for analysis, arraying of possible species, and selection of species within each trophic level group for sample collection. We first had to identify all likely species, then narrow our focus to those we could collect and analyze. In all cases, review includes suggestions for possible target species with justifications. While this method increases the up-front costs of developing bioindicators for an ecosystem, it has the advantage of providing information for selection of species that will be most informative in the long run, including those that are the best bioaccumulators, thus providing the earliest warning of any potential environmental consequences. Further, the recognition that a range of stakeholder's needs and interests should be included increases the utility for public-policy makers, and the potential for continued usage to establish long-term trends.