资源型城市是否走出了困境

本文利用最新的数据资料，对全国600余座城市近年来的经济增长、就业与贫困状况进行了考察，发现资源型城市2000年以来的经济增长速度显著高于非资源型城市，就业压力也在逐渐减轻，贫困发生率虽然没有显著降低，但也没有继续上升，资源型城市正面临加速改革以解决体制性障碍的大好时机。     

HN150型高效碾混机主体机构的应用研究

本文对HN150型高效混碾机进行了应用研究,通过对其主体的重新设计和局部改进来提高其性能,从而达到提高工作效率、降低运行费用的目的。     

餐厨垃圾湿热处理对其脱出液的影响

为探明湿热处理后餐厨垃圾脱出液水质、水量的变化规律，有效提高其处理效率，对不同湿热条件下单位餐厨垃圾脱水量、脱出液的pH、总悬浮固体（SS）、溶解性COD（SCOD）、氮的存在形式及其浓度、油脂含量的变化规律进行了试验研究。结果表明，随着温度的上升和加热时间的延长，餐厨垃圾脱出液pH值有所下降，并且在温度达180℃、加热时间为40min时pH〈4．5，故在生物处理前需进行调节；湿热处理使餐厨垃圾脱出液的SCOD值大幅上升，180℃下加热100min后达最高值（为211400mg／L）；湿热处理使SS值呈下降趋势；湿热处理初期有机氮浓度增加，达到180℃且加热时间〉60min后有机氮开始向氨氮转化。另外，湿热处理使餐厨脱出液的可浮油含量增加，有利于废油脂的分离、回收。     

除铁除锰生物滤层最优化厚度的研究

除铁除锰生物滤层的厚度对滤池除铁除锰效果有至关重要的影响，而地下水水质是确定除铁除锰生物滤层厚度的重要因素。实验室滤柱试验的结果表明：不同铁、锰含量的地下水，其适宜的生物滤层厚度不同。生产运行试验也证明了上述结论并进一步得出：对于铁、锰含量较低的地下水，滤层的适宜厚度为900～1000mm，而对于铁、锰含量较高的地下水，生物滤层相应地要增厚至1000～1300mm。     

选择性神经网络二次集成在火药近红外分析中的应用研究

针对建立近红外光谱定量分析的神经网络校正模型时,存在变量数过多以及容易出现过拟合等问题,采用小波变换对近红外光谱进行预处理,用以消除噪声,减少变量个数;并在此基础上,提出一种新的神经网络校正模型一基于改进贪心法的选择性神经网络二次集成,来提高神经网络的泛化能力。实验结果表明：在建立火药近红外分析的校正模型中,该模型不仅建立过程简单而且具有较好的泛化能力。     

New Clustering Method in High-Di mensional Space Based on Hypergraph-Models

Clustering of datain alarge di mensionspaceis ofa great interest in many data mining applications .Clustering methods have been studiedin several areasincluding statistics , machine learning and data min-ing. Most of the algorithms are effective whenthe di-mensionality of the datais relativelysmall .But ,theseschemes tend to break down when the di mensionalityof the datais very high.There are several reasons[1].First ,it is not trivial to define distance measure in alarge di mensional space .…     

Surface-effect on detection ability of fluorescent Eu(btc) metal-organic frameworks to metal ions

Eu(btc)metal organic frameworks(MOFs)were prepared by co-precipitation method via 1,2,4-benzenetricarboxylic acids(H3btc)connecting with Eu³⁺ions,and the morphology was controlled from compact spherical to irregular honeycomb by adjusting the pH of reaction solutions.The luminescence properties of Eu(btc)MOFs are found to be related to the surface morphology of products,and the compact spherical one performs stronger emission intensity.The sensing ability of Eu(btc)MOFs to 11 kinds of metal ions was investigated and a prominent quenching effect occurrs in Fe³⁺,or Ni²⁺solutions.Based on UV—vis absorption analysis,an“ion-fence”model presents the competition to absorb exciting light between Eu(btc)MOFs and adsorbed metal ions.Based on Stern-Volmer equation,the Eu(btc)detection is found with higher Ksv value and a lower detection limit.Meanwhile,a higher sensing efficiency is confirmed in the Eu(btc)MOFs with loose honeycomb due to aggravating porous surface offering much more sites for metal ions.     

Greenhouse gas emission monitoring system for manufacturing prefabricated components

Excessive greenhouse gas (GHG) emissions from construction stage pose an obvious and emerging challenge. Most previous studies on emissions from the construction phase only focused on emission prediction in advance of the actual construction activities or on quantitative analysis after building construction. A system that enables builders to monitor emissions from construction activities in real time is still lacked, although GHG emission monitoring (GEM) and analysis are considered as the top activities that must be performed to minimize excessive environmental impacts. As an initial exploration, this paper proposes a GEM system based on Internet of things (IoT) technology to real-time monitor emissions when manufacturing prefabricated components. In this system, Radio Frequency Identification (RFID) sensors are adopted to identify the component ID, and the corresponding material usage data are extracted from a database that is preset in the GEM system. Laser sensors are installed in the components production line to measure the running time of equipment so that energy usage can be calculated in real time. In addition, a data service platform was developed to implement wireless data transmission from production line to computing platform, where the monitoring results are visually presented. A production line of real-life prefabricated components in China is adopted to demonstrate that the IoT-based monitoring system can acquire and analyze real-time carbon emission data from the manufacturing process. The results indicate that GEM system can facilitate project teams to timely control irregular emissions, identify potential emission risks and explore possible strategies for minimizing carbon emissions in the construction sector.     

Effect of Organic Carbon on Tertiary Denitrification of the Secondary Effluent in Biofilters Packed with Suspended Carriers

Denitrifying biokinetics in biofilters packed with suspended carriers were evaluated under different empty bed residence times (EBRT) with ethanol or acetate as the electron donor. The two denitrifying biofilters removed nitrate (NO₃^––N) effectively after only 3–4 days operation. At EBRT of 30; 15 and 7.5 min, the NO₃^––N removal percentage was 84; 72 and 59% in the ethanol biofilter, and was 89; 70 and 62% in the acetate biofilter, respectively. With the influent NO₃^––N loading rate ranged from 0.4 to 1.8 g/(m²·d), the NO₃^––N removal loading rate increased with increasing influent NO₃^––N loading rates, and the system was substrate limited. While when the influent nitrate loading rate was above 3 g/(m²·d), the system was biomass limited. The half-order coefficients were 0.162; 0.175 and 0.274 (mg/L)^1/2/min for the ethanol biofilter with the influent NO₃^––N concentration of 7.3–7.7 mg/L, and were 0.107; 0.165 and 0.303 (mg/L)^1/2/min for the acetate biofilter with the influent NO₃^––N concentration of 6.8–8.0 mg/L. Denitrification efficiency varied slightly during the backwashing cycle, and the effect of backwashing on the effluent turbidity was relatively large, especially for the biofilter with ethanol as the organic carbon.     

生活饮用水和瓶装饮用水的细菌内毒素活性调查

2012年4月—5月对北京市城市生活饮用水和市售瓶装饮用水进行样品采集,采用动态浊度法鲎试验定量检测内毒素活性。北京市3个水源水的内毒素范围为21.3~68.2 EU/mL。北京市A水厂进、出水内毒素分别为11.2、4.1 EU/mL,水厂的整个处理流程对内毒素的去除率达63%;此外,A水厂的出水中均未检出异养菌和菌落总数(平板计数),说明水厂处理流程对水中微生物的控制效果有效。北京市城区12个管网末梢水的内毒素范围为0.1~9.1 EU/mL。市售的9种瓶装饮用水内毒素范围为(<0.004)~16.0 EU/mL。与国外相关报道相比,北京市水源水、水厂进出水和管网末梢水中内毒素范围明显偏低,瓶装饮用水中内毒素污染水平和国外相关报道基本一致。