Effect of deuterium-depleted water on reproduction of rainbow trout

During the artificial reproduction of salmonides, the fecundity can be increased either by improving the viability of spermatozoa, or by extending the time period during which a roe micropile remains open, thus allowing its fecundation. Practically, this can be achieved by the use of some fertilising techniques suitable for fish species. Here, we show that the reproduction of rainbow trout in a 1:1 solution of deuterium-depleted water and distilled water led to a significant increase in survival of roes during their embryonic development. Moreover, the addition of glucose and fructose into the deuterium-depleted fertilising solutions led to a further increase in roe survival during embryonic development. The increase in survival is mainly explained by an increase in the motility of spermatozoa.     

Phosphate recovery with granular acid-activated neutralized red mud: Fixed-bed column performance and breakthrough curve modelling

Granular acid-activated neutralized red mud (AaN-RM) has been successfully prepared with good chemical stability and physical strength. However, its potential for industrial application remains unknown. Therefore, the performance of granular AaN-RM for phosphate recovery in a fixed-bed column was investigated. The results demonstrated that the phosphate adsorption performance of granular AaN-RM in a fixed-bed column was affected by various operational parameters, such as the bed depth, flow rate, initial solution pH and initial phosphate concentration. With the optimal empty-bed contact time (EBCT) of 24.27 min, the number of processed bed volumes and the phosphate adsorption capacity reached 496.95 and 84.80 mg/g, respectively. Then, the saturated fixed-bed column could be effectively regenerated with a 0.5 mol/L HCl solution. The desorption efficiency remained as high as 83.45% with a low weight loss of 3.57% in the fifth regeneration cycle. In addition, breakthrough curve modelling showed that a 5-9-1 feed-forward artificial neural network (ANN) could be effectively applied for the optimization of the fixed-bed adsorption system; the coefficient of determination (R²) and the root mean square error (RMSE) evaluated on the validation-testing data were 0.9987 and 0.0183, respectively. Therefore, granular AaN-RM fixed-bed adsorption exhibits promising potential for phosphate removal and recovery from polluted water.     

人工神经网络用于铅的化学形态模拟计算

用前馈线性网络法求解水体系中Ｐｂ（２＋）与ＯＨ－之间的反应常数，不同训练算法对求解结果的精度、收敛速度及权值均有影响．结果表明，批处理算法的精度最好，权值不出现负值，但运算时间最长；在线算法的精度虽不如批处理算法，而比数据变换－在线算法好，权值有时会出现负值．运算时间较长；数据变换－在线算法的优点是运算时间短，但相对误差较大，权值出现负值的机会多。采用反馈网络模拟计算铅的各种化学形态的浓度．用物料核算的方法对反馈网络模型进行检验表明，此种模型用于平衡计算是可行的，详细分析了理论模拟和实验曲线的差异的原因，温度的影响最小，在４＜ｐＨ＜９时，ＣＯ有重要的影响．在国代检验时，ｎ值取整所引入的误差的影响亦不可忽视。从本文的结果可以看到，采用前馈网络和反馈网络相结合的方法考察水体中的化学形态是可行的．从而为解决这一类问题提供了一种可能的途径．     

不同填料人工湿地处理系统的净化能力研究

研究了沸石、沸石－石灰石、石灰石3种填料的人工湿导的净化能力。结果表明：（1）沸石和石灰石混合使用，不会降低沸石吸附氨氮的能力；（2）沸石可促使难溶性P的释放，使得石灰石吸附P被植物和微生物吸收利用；（3）沸石和石灰石发生了协同作用，对TN、TP的去除效果均好于其单独使用。     

人工神经网络在湖泊富营养化评价中的应用研究

运用人工神经网络技术评价湖泊富营养化程度。详细阐述了神经网络的结构设计，样本生成及学习算法，给出了通过训练得出的网络权和阈值，最后将此神经网络用于１２个湖泊的富营养化评价，取得了较好的评价结果。     

建立土壤硫释放过程的人工神经网络模型

以温度、土壤含水率、胱氨酸添加量和土壤pH值作为土壤释放挥发性含硫化合物的主要影响因素,采用正交实验方法分析这些因素与土壤硫释速率的关系,利用BP神经网络算法对实验结果建模,并用模型对不同影响因素下的土壤硫释放情况进行预测。结果表明,网络模型对学习过的样本有较高预测精度,预测结果相对误差在2％以下,对未学生过的样本,误差为10％左右,表明人工神经网络方法建立的模型适用于土壤硫释放预测。     

人工湿地处理污水的研究

简要介绍了人工湿地的发展历史、原理及优点；并对沙井镇人工湿地进行探讨和检测，其ＣＯＤｃｒ去除率可达８３％，总氮去除率达４５％，出水水质达国家排放标准。     

神经网络及其在水库调洪演算中的应用

结合洪水灾害管理的特点建立了水库调洪演算的人工神经网络模型，阐述了其基本原理及算法，并结合某水库调洪演算实例说明了其应用。     

人为泥石流灾害严重等级的定量模糊综合评判

根据神府－东胜矿区人为泥石流的调查分析，选择１５个因素（含５个主控因素）作为其严重程度的评价因子，确定了四值逻辑（严、中、轻、否）评判的定量标准。应用模糊综合评判和分层定量模糊综合评判两种方法对该煤田６５条泥石流沟的严重等级进行综合判别，准确性达９３．１％，它为保护该地煤田建设和工农业生产提供了重要的科学依据。     

基于BP网络的建筑安装施工现场安全综合评价的研究

针对目前我国建筑安装施工现场安全评价技术的不成熟和欠科学性的现状 ,笔者分析和综合了目前安全评价技术 ,结合建筑业特点 ,提出了基于BP神经网络的建筑安装施工现场安全评价方法 ,并对该评价模型的原理、方法及算法进行了研究。首先 ,结合建筑安装施工现场安全生产的特点建立评价指标体系 ,随后 ,运用层次分析法确定指标及准则层的权重 ,并运用模糊综合评价法生成评价样本集 ,最后 ,利用样本集训练BP网络 ,待误差满足要求后 ,即可运用训练成功的BP神经网络进行安全评价。