Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Soil properties and crop productivity as influenced by flyash incorporation in soil

Field experiments were carried out during 1996–97at Gulawathi, Muthiani and Salarpur Villages, IARI Farm, NewDelhi and NCPP Campus, Dadri to evaluate changes in soilcharacteristics and growth of wheat (Triticum aestivum L.),mustard (Brassica juncea L.), lentil (Lence esculentaMoench.), rice (Oryza sativa L.) and maize (Zea mays L.) byvarying amounts of flyash addition (up to 50t ha^-1) in soils atsowing/transplanting time of crops. Flyash addition in areasadjoining NCPP Thermal Power Plant, Dadri, Ghaziabad, U.P.ranged from 5–12 t ha^-1 yr^-1 in 1995–96. Shoot and root growthand yield of test crops at different locations after flyashincorporation resulted in beneficial effects of flyashaddition in most cases. The silt dominant texture of flyashimproved loamy sand to sandy loam textures of the surfacesoils at the farmers' fields. The increased growth in yield ofcrops with flyash incorporation was possibly due tomodifications in soil moisture retention and transmissioncharacteristics, bulk density, physico-chemical characterssuch as pH and EC and organic carbon content. The response offlyash addition in the soil on soil health and cropproductivity needs to be evaluated on long-term sustainableaspects.     

温差拉深法在制造大型杯形件中的应用

用温差拉深法制造大型杯形件毛坯,可避免毛坯拉断和起皱,最大限度地降低拉深系数、减少拉深次数、降低加工成本。     

炼油污水气浮絮凝处理中试

气浮絮凝是炼油污水处理工艺中重要的一步 ,它是确保炼油污水生化处理顺利运行的关键 ,而开发和筛选优良的絮凝剂则又是提高气浮处理效果的保证。采用无机—有机复合絮凝剂进行炼油污水的中试试验 ,通过一系列条件试验 ,确定了复合絮凝剂投药剂量、投药间隔时间和投药方式 ,取得了令人满意的试验效果 ,CODCr的去除率 5 5 % ,石油类去除率 >75 % ,为后续的生化处理提供了合格的水质     

兰州市城市生活垃圾处理研究

城市生活垃圾是指在城市日常生活中或者为城市日常生活提供服务的活动中产生的固体废物以及法律、行政规定视为城市生活垃圾的固体废弃物.随着中国城市化进程的加快和人民生活水平的提高,城市生活垃圾也在以每年8%～10%的速度增长,若垃圾问题得不到妥善解决,就会制约兰州市的发展.在对兰州市城市生活垃圾处理现状及存在问题分析的基础上,根据兰州市生活垃圾的特性,提出兰州市城市生活垃圾的处理办法:兰州市城市生活垃圾应当推行分类收集制度,由目前单一的卫生填埋处理走向资源化综合处理.     

重型柴油车污染物排放量计算方法比较分析

目的 计算大功率大吨位级重型柴油车的污染物排放量.方法 根据《公路隧道通风设计细则》和世界道路协会(PIARC)2012年技术报告,分别计算32 t重型柴油车的污染物排放量和稀释污染物所需的通风量,对比分析两种计算方法的差异.结果 对《公路隧道通风设计细则》中柴油车的车型系数和海拔高度系数提出建议.根据世界道路协会(PIARC)2012年技术报告,在0～2000 m低海拔地区,国产32 t柴油车的CO、NOx和烟尘排放量分别为88.6、166.0 m3/(h·veh)和84.2 m2/(h·veh),如果考虑NOx的空气污染,稀释单辆国产32 t柴油车排放污染物所需空气量约为33000 m3/h;如果不考虑NOx的空气污染,所需空气量约为28000 m3/h.结论 结合工程实际,建议大功率大吨位级重型柴油车的污染物排放量根据世界道路协会(PIARC)2012年技术报告进行计算.     

我国生态工业园区稳定性的调研报告

作为可持续发展的重要实践工具，生态工业园（EIPs）建设得到快速推进的同时，也由于多方面存在的影响因素制约，使园区面临“不稳定”风险．本调研报告通过专家调查和全国范围内的统计调查确认了“技术充足，政府支持，行业多样，核心组员，成员沟通”等5个影响因素对我国生态工业园区稳定发展具有显著影响，并对数据结果做了进一步的讨论，提出了相应的政策建设。     

Detection of low-grade mosaicism in fetal cells isolated from maternal blood

Recovering and analysing fetal erythrocytes from maternal blood is being pursued for non-invasive prenatal genetic diagnosis. We report the observation of 46, XY/47, XXY mosaicism in fetal cells from a woman whose first-trimester chorionic villus sampling (CVS) initially showed only 46, XY. Only after exhaustive (500 cells) analysis were four XXY cells found in cultured villi.     

The nature of the redshift and directly observed quasar statistics

The nature of the cosmic redshift is one of the most fundamental questions in modern science. Hubble's discovery of the apparent Expansion of the Universe is derived from observations on a small number of galaxies at very low redshifts. Today, quasar redshifts have a range more than 1000 times greater than those in Hubble's sample, and represent more than 100 times as many objects. A recent comprehensive compilation of published measurements provides the basis for a study indicating that quasar observations are not in good agreement with the original predictions of the Expanding Universe theory, but are well fit by the predictions of an alternative theory having fewer adjustable parameters.