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。     

高效阿特拉津降解菌株DNS10降解条件优化

从长期施用阿特拉津的寒地黑土耕层(0～10 cm)土壤中筛选到一株能以除草剂阿特拉津为氮源生长的降解菌株,结合16S rRNA序列分析结果,将该菌株命名为Arthrobacter sp.DNS10。在接种量为108CFU/mL的条件下,菌株DNS10在24 h内对100 mg/L阿特拉津的降解率为99.41%。单因子实验结果表明,菌株DNS10适宜生长和降解的条件范围是:温度25～35℃,pH值5.0～8.0,培养液盐度0.1%～2%,对阿特拉津最大耐受浓度可达1 200 mg/L。正交实验法进一步表明,该菌株保持较好生长及降解能力的最优方案是温度30℃,pH值7.5,培养液盐度0.5%。影响其降解能力的环境因素的主次顺序依次是:温度>盐度>pH值。     

高速公路路面沉积物的污染特性

对湖南省长潭西高速公路不同采样点的路面沉积物进行取样分析,并检测了样品的颗粒级配、COD、重金属(Cu、Zn、Pb和Cd)和有机质。结果表明,路面沉积物主要以粒径<0.15 mm的颗粒为主;较小颗粒物中的COD含量高于较大颗粒中的COD含量;粒径在0.15 mm以下的颗粒物所含重金属Cu、Zn、Pb和Cd的浓度普遍高于所选的土壤标准值,降雨一旦形成径流将会产生严重的污染危害;沉积物中的有机质含量对重金属的吸附有一定的影响,有机质含量越高,沉积物中重金属含量相对也高。     

中国与美国对外直接投资区位选择的比较研究

基于邓宁的国际生产折衷理论,对比了中美两国投资规模、空间分布和发展阶段,利用灰色关联分析法比较了影响两国投资区位的因子.结果表明,影响美国对外投资的主要因子是人均GNP、CH和CO2的排放量,影响中国的主要因子是直接投资净流入量、航空运输量和CPI;美国对外直接投资属于市场导向型,而中国尚处于转型期,为对外投资第三阶段.     

大学生英语口语交流障碍的心理因素及克服办法

目前大学生的英语口语表达能力总体很差,在口语交流上也出现各种障碍,其原因除学生英语学习能力较差以外,态度问题、动机偏差、缺乏自信、不耐挫折、缺乏热情、过于紧张、性格内向等心理因素也起着关键的作用。对于大学生英语口语交流存在的障碍,可以通过激发兴趣、心理暗示、教师鼓励、减少心理压力、结交外国朋友等有效方法,指导学生进行口语训练,提高学生口语水平。     

Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.     

Is Urban Stream Restoration Worth It?1

Kenney, Melissa A., Peter R. Wilcock, Benjamin F. Hobbs, Nicholas E. Flores, and Daniela C. Martínez, 2012. Is Urban Stream Restoration Worth It? Journal of the American Water Resources Association (JAWRA) 48(3): 603-615. DOI: 10.1111/j.1752-1688.2011.00635.x Abstract: Public investment in urban stream restoration is growing, yet little has been done to quantify whether its benefits outweigh its cost. The most common drivers of urban stream projects are water quality improvement and infrastructure protection, although recreational and aesthetic benefits are often important community goals. We use standard economic methods to show that these contributions of restoration can be quantified and compared to costs. The approach is demonstrated with a case study in Baltimore, Maryland, a city with a legal mandate to reduce its pollutant load. Typical urban stream restoration costs of US$500-1,200 per foot are larger than the cost of the least expensive alternatives for management of nitrogen loads from stormwater (here, detention ponds, equivalent to $30-120 per foot of restored stream) and for protecting infrastructure (rip-rap armoring of streambanks, at $0-120 per foot). However, the higher costs of stream restoration can in some cases be justified by its aesthetic and recreational benefits, valued using a contingent valuation survey at $560-1,100 per foot. We do not intend to provide a definitive answer regarding the worth of stream restoration, but demonstrate that questions of worth can be asked and answered. Broader application of economic analysis would provide a defensible basis for understanding restoration benefits and for making restoration decisions.     

Mapping adaptation opportunities and activities in an interactive atlas

The need for transparency is taking more prominence in international climate negotiations as developed countries pledge large sums of money to foster adaptation efforts in developing countries. Tools that provide accurate and up-to-date spatial information that can be easily used and vetted by local practitioners may provide effective and affordable ways to improve transparency. The Global Adaptation Atlas is such a tool, combining vetted, publicly available climate impact data with timely maps of on the ground adaptation projects to highlight confluences of effects of climate change with actions taken to address those effects. Here, we describe the structure and general functions of the Global Adaptation Atlas and explain how it may be utilized to track short-term investments in adaptation. Over longer time scales, it may also help gauge the effectiveness of specific adaptation investments as well as reveal how different climate impacts affect long-term investment in differing regions.     

Enhanced resistance of yeast mutants deficient in low-affinity iron and zinc transporters to stannous-induced toxicity

Tin or stannous (Sn²⁺) compounds are used as catalysts, stabilizers in plastic industries, wood preservatives, agricultural biocides and nuclear medicine. In order to verify the Sn²⁺ up-take and toxicity in yeast cells we utilized a multi-elemental analysis known as particle-induced X-ray emission (PIXE) along with cell survival assays and quantitative real-time PCR. The detection of Sn²⁺ by PIXE was possible only in yeast cells in stationary phase of growth (STAT cells) that survive at 25 mM Sn²⁺ concentration. Yeast cells in exponential phase of growth (LOG cells) tolerate only micro-molar Sn²⁺ concentrations that result in intracellular concentration below of the method detection limit. Our PIXE analysis showed that STAT XV185-14c yeast cells demonstrate a significant loss of intracellular elements such as Mg, Zn, S, Fe and an increase in P levels after 1 h exposure to SnCl₂. The survival assay showed enhanced tolerance of LOG yeast cells lacking the low-affinity iron and zinc transporters to stannous treatment, suggesting the possible involvement in Sn²⁺ uptake. Moreover, our qRT-PCR data showed that Sn²⁺ treatment could generate reactive oxygen species as it induces activation of many stress-response genes, including SOD1, YAP1, and APN1.