高铁网络可达性测度及经济潜力分析——以安徽省为例

高速铁路的开通给沿线城市的建设带来了重大影响。基于可达性测度以及修正的经济潜力模型,利用GIS对安徽省高铁可达性以及经济潜力进行深入分析。研究表明:(1)高铁开通后安徽省可达性显著提高,但总体格局保持不变,呈现出以合肥为中心,淮南、芜湖等地为副中心的"多核心"模式。池州、铜陵两城市可达性上升幅度最大,黄山紧随其后,芜湖、滁州变化最小。高铁开通后,滁州可达性排名下降5名,下降幅度最大,合肥、淮南、黄山最为稳定,其他城市均有小幅变化。(2)可达性的提升对城市经济潜力造成了一定影响,总体呈现出以合肥为中心的外围扩展模式。池州、铜陵经济潜力增长最为显著,黄山位列第3,可达性的提升直接影响了池州、铜陵、黄山三市的经济发展。高铁开通后,合肥、芜湖经济潜力排名始终位于前二,传统经济中心地位不变。马鞍山排名上升4名,幅度最大,池州、黄山两市处于末端,经济潜力仍然较为薄弱。(3)高铁开通后,时空收敛效应明显,可达性的提升令城市经济潜力增长显著,但受多方面因素影响,可达性与经济潜力呈现不完全契合关系。     

三峡库区移民贫困致因的精准识别与减贫路径的实证研究

随着我国经济发展和扶贫成效的显现,老区、山区、民族地区和移民库区等集中连片的特殊贫困区已经成为我国当前精准扶贫的主战场。由于面临生产资料匮乏、生态环境恶化和地质灾害频发等恶劣环境,库区移民贫困问题已成为新时期扶贫攻坚最难啃的"硬骨头"。因此,开展库区移民贫困致因的精准识别与减贫路径研究具有重要的现实意义。基于对库区移民贫困现状的扎根理论分析,本文提出了分析农户生计的新框架。在此基础上,本文以三峡库区26个县(区)为研究对象,随机抽取4县(区)796户移民作为样本,首先,采用灰色关联分析法和熵权法对库区移民主要致贫因子进行挖掘;接着,采用PLS-SEM模型分析影响库区移民生计状况的关键因子和关键路径。研究表明:(1)三峡库区移民贫困现象仍很严重,患病、劳动能力弱和失地是移民致贫的三大主因。三峡库区仍有175.94万人生活在贫困线以下,三大致贫原因依次是:因病致贫26.49%、因劳动能力弱致贫22.10%和失地致贫21.65%。(2)心理资本可有效促进移民其他资本效能的发挥,对生计状况存在着显著的直接效应和间接效应。(3)在影响生计状况的四类资本中,人力资本对库区移民生计状况影响最大。基于以上发现,本文提出了实现库区移民精准脱贫的政策建议:(1)国家应高度重视三峡库区移民贫困问题,大力开展精准扶贫;(2)增加心理干预措施以提高移民心理资本存量,帮助移民摆脱心理贫困;(3)开展劳动力技能培训,提高库区移民人力资本水平。     

Optimization-Based Atmospheric Plume Source Identification

This work applies optimization and an Eulerian inversion approach presented by Bagtzoglou and Baun in 2005 in order to reconstruct contaminant plume time histories and to identify the likely source of atmospheric contamination using data from a real test site for the first time. Present-day distribution of an atmospheric contaminant plume as well as data points reflecting the plume history allow the reconstruction and provide the plume velocity, distribution, and probable source. The method was tested to a hypothetical case and with data from the Forest Atmosphere Transfer and Storage (FACTS) experiment in the Duke experimental forest site. In the scenarios presented herein, as well as in numerous cases tested for verification purposes, the model conserved mass, successfully located the peak of the plume, and managed to capture the motion of the plume well but underestimated the contaminant peak.     

生物滴滤塔处理氯苯废气的工艺性能

将活性污泥培养及驯化后接种于生物滴滤塔中,挂膜启动后处理模拟氯苯废气（简称氯苯废气）,考察了生物滴滤塔在挂膜启动阶段及稳定运行阶段的性能。实验结果表明：接种41 d后生物滴滤塔成功挂膜,此时氯苯去除率稳定在90%以上;生物滴滤塔稳定运行阶段,随着进气中氯苯质量浓度由303.82 mg/m³逐渐增至1 489.05 mg/m³,氯苯去除率从85.1%降至70.1%。处理氯苯废气适宜的工艺条件为：空塔停留时间超过45 s,喷淋液流量31.8 mL/min,氯苯负荷23.97~128.01 g/（m³·h）。生物滴滤塔对喷淋液的酸性环境有较好的适应性,喷淋液pH的变化对氯苯去除率无显著影响。     

抗铬菌株的筛选鉴定及其生物学特性和吸附特性

利用微生物分离纯化技术,在培养基中加入不同浓度的Cr3+、Cr6+,经过长时间驯化,从污染土壤中筛选出2株对Cr具有较高抗性的菌株(A和B),对其进行了形态、生理生化特性及分子生物学鉴定,并研究了其最佳生长条件及对Cr3+的生物吸附规律。结果表明,菌株A和B分别为蜡状芽孢杆菌(Bacillus cereus)和米根霉菌(Rhizopus oryzae)。菌株A和B的最适生长pH值均为7,最适生长温度均为30℃,最佳装液量为80~100 mL(250 mL摇瓶)。在培养时间一定时,随着Cr3+浓度的增加,菌株对Cr3+的吸附率减少,而生物吸附量则逐渐增大;在Cr3+浓度一定时,随着培养时间的延长,菌体对Cr3+的吸附率呈现出先增加后减少的趋势,这与生物吸附量的变化趋势基本一致。在Cr3+浓度为100 mg/L时,菌株A和B对Cr3+的吸附率达到最大,分别为51.47%和46.36%。     

假单胞菌好氧降解四溴双酚A的特性

为了解四溴双酚A(TBBPA)的好氧降解特性,采用选择富集法从活性污泥中分离出一株能够高效降解四溴双酚A的菌株。根据其形态、生理生化特性及16S rDNA核苷酸序列分析,该菌株被鉴定为假单胞菌属(Pseudomonas sp.)。研究结果表明,该菌株可通过好氧共代谢方式实现四溴双酚A的降解,葡萄糖是四溴双酚A降解的最佳碳源,其最优降解条件为葡萄糖8 g/L,牛肉膏0.5 g/L,pH值为7.0,培养温度为35℃,摇床转速为150 r/min。在该条件下其生物降解过程符合一级动力学模型,6 d后的降解率高达95.6%。LC-MS结果表明,四溴双酚A在好氧降解过程中会生成异丙苯酚类物质。     

镍渣的重金属浸出特性

在分析镍渣的矿物相组成和重金属元素含量的基础上,鉴定了镍渣样品的浸出毒性,并考察了pH、液固比和浸出时间等条件对镍渣样中铬、铅、铜和锌等重金属浸出特性的影响。结果表明,镍渣中的重金属总量约为渣样的0.9%,且铬、铜和锌的含量较高,需进行安全管理。实验所用镍渣样品为第Ⅰ类一般工业固体废物。在强酸条件下镍渣中重金属浸出浓度较大,pH3后浸出浓度显著降低;液固比40 L/kg时,镍渣中重金属不断溶出,液固比40 L/kg后,浸出达到饱和,浸出浓度趋于平衡;随着浸出时间的增加,重金属离子的浸出浓度先增加后减少,但由于各重金属性质不同,各重金属达到最大浸出浓度的时间不同。     

Corynebacterium glutamicum as an indicator for environmental cobalt and silver stress–A proteome analysis

Cobalt and silver are toxic for cells, but mechanisms of this toxicity are largely unknown. Analysis of Corynebacterium glutamicum proteome from cells grown in control and cobalt or silver enriched media was performed by two dimensional gel electrophoresis (2DE) followed by mass spectrometry. Our results indicate that the cell adapted to cobalt stress by inducing five defense mechanisms: Scavenging of free radicals, promotion of the generation of energy, reparation of DNA, reparation and biogenesis of Fe-S cluster proteins and supporting and reparation of cell wall. In response to the detoxification of Ag⁺ many proteins were up-regulated, which involved reparation of damaged DNA, minimizing the toxic effect of reactive oxygen species (ROS) and energy generation. Overexpression of proteins involved in cell wall biosynthesis (1,4-alpha-glucan branching enzyme and nucleoside-diphosphate-sugar epimerase) upon cobalt stress and induction of proteins involved in energy metabolism (2-methylcitrate dehydratase and 1, 2-methylcitrate synthase) upon silver demonstrate the potential of these enzymes as biomarkers of sub-lethal Ag⁺ and Co toxicity.     

Effects of combinations of malathion and cypermethrin on survivability and time of metamorphosis of tadpoles of Indian cricket frog (Fejervarya limnocharis)

This study was undertaken to determine the effect of environmentally realistic concentrations of two commonly used pesticides viz., malathion and cypermethrin, using a fully 3 × 3 factorial experiments on the survivability and time of metamorphosis in a common rice paddy field frog (cricket frog) Fejervarya limnocharis under laboratory conditions. The results suggest that cypermethrin is more toxic than malathion and combinations of higher concentrations of cypermethrin (50 μg/L) with malathion (250 and 500 μg/L) are more deleterious to the survivability of tadpoles. With increasing cypermethrin concentration, the survivability of tadpole decreased (r = ?0.986, P = 0.108). But cypermethrin alone induced early metamorphosis among the surviving tadpoles. However, there was a delay in the time required for metamorphosis induced by malathion and its combination with cypermethrin. The delay in metamorphosis may indicate the altered physiological fitness of the individual. The emergent froglets will be subjected to environmental stressors like high temperature and less humidity of post-monsoon tropical climate that could enhance negative influence triggered by pesticides.     

Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande1

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10‐23. DOI: 10.1111/j.1752‐1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function‐noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross‐correlation statistical tests. The chi‐square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one‐ to three‐month‐ahead model forecasts for the testing period of 1984‐1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one‐month‐ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two‐month‐ahead and three‐month‐ahead forecasts. For three‐month‐ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one‐ to three‐month‐ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin.