Impact of fertilization on chestnut growth, N and P concentrations in runo water on degraded slope land in South China

Growing fruit trees on the slopes of rolling hills in South China was causing serious environmental problems because of heavy application of chemical fertilizers and soil erosion. Suitable sources of fertilizers and proper rates of applications were of key importance to both crop yields and environmental protection. In this article, the impact of four fertilizers, i.e., inorganic compound fertilizer, organic compound fertilizer, pig manure compost, and peanut cake （peanut oil pressing residue）, on chestnut （Castanea mollissima Blume） growth on a slope in South China, and on the total N and total P concentrations in runoff waters have been investigated during two years of study, with an orthogonal experimental design. Results show that the organic compound fertilizer and peanut cake promote the heights of young chestnut trees compared to the control. In addition, peanut cake increases single-fruit weights and organic compound fertilizer raises single-seed weights. All the fertilizers increased the concentrations of total N and total P in runoff waters, except for organic compound fertilizer, in the first year experiment. The observed mean concentrations of total N varied from 1.6 mg/L to 3.2 mg/L and P from 0.12 mg/L to 0.22 mg/L, which were increased with the amount of fertilizer applications, with no pattern of direct proportion. On the basis of these experiment results, organic compound fertilizer at 2 kg/tree and peanut cake at 1 kg/tree are recommended to maximize chestnut growth and minimize water pollution.     

Modeling and optimization of activated sludge bulking for a real wastewater treatment plant using hybrid artificial neural networks-genetic algorithm approach

Prediction of sludge bulking is a matter of growing importance around the world. Sludge volume index (SVI) should be monitored to predict sludge bulking for a wastewater treatment plant. This study was an effort to develop hybrid artificial neural network-genetic algorithm models (MLPANN-GA and RBFANN-GA) to accurately predict SVI. Operating parameters, including MLVSS, pH, DO, temperature, TSS, COD and total nitrogen were the inputs of neural networks. Genetic algorithm was utilized in order to optimize weights and thresholds of the MLPANN and RFBANN models. Training procedures for SVI estimation were successful for both the MLPANN-GA and RBFANN-GA models. The training and validation models showed an almost perfect match between experimental and predicted values of SVI. The results indicated that with low experimental values of input data to train ANNs, the MLPANN-GA compared with the RBFANN-GA is more accurate due to higher coefficient of determination (R²) and lower root mean squared error (RMSE) values. The values of RMSE and R² for the optimal models approached 0 and 1, respectively. The mean average error for the ANN models did not exceed 3% of the input values of the measured SVI. The GA increased the accuracy of all the MLPANN and RBFANN models.     

套箍加固RC轴压中长柱的承载力理论研究∗

为研究套箍加固RC轴压中长柱的承载力理论计算分析方法,采用切线模量理论,根据材料本构关系和内外力平衡条件,推导了套箍加固RC轴压中长柱的弹塑性稳定承载力计算方法。将理论计算结果与试验结果进行了对比分析,结果表明:理论计算值均低于实测值,且二者的偏差在15%以内。根据所推导的计算分析方法,研究了核心柱初始荷载水平β、柱子长细比l0/b、套箍层混凝土强度、套箍层配筋量四种参数对加固柱承载力Nu的影响规律,结果表明:Nu总体上随β增大而减小,当β<0.7时,减小趋势不够明显,β>0.7后,减小趋势变得明显;l0/b对Nu有明显影响,Nu随l0/b的增大而减小,但二者不是线性关系;Nu随套箍层混凝土强度提高而增大,随套箍层配筋量增大而增大。     

环境质量综合评价的径向基函数网络模型

建立了一个环境质量综合评价的径向基函数人工神经网络(RBF-ANN)模型,同时提出了一种简便?快速的RBF-ANN的最小二乘算法(RBF-LS算法)?在城市环境质量综合评价的应用中表明,提出的RBF-ANN模型及其算法是合理?有效?通用的?      

水下爆炸空化研究进展

从理论研究、实验研究和数值模拟3个方面对水下爆炸局部空化和片空化的研究进展进行了综述,总结了理论及数值方面的研究进展,介绍了新的实验技术在水下爆炸空化研究中的应用。     

高校碳排放核算与分析：以北京A高校为例

在双碳背景下,我国各行业正积极核算自身碳排放,以有效应对气候变化,大学校园也应积极参与其中.以北京A高校为例,采用排放因子法和理论计算法核算了2021年其校园碳排放量.结果表明,A高校净碳排放量（以CO2计,下同）为43 249.04 t,人均碳排放量为1.52 t.电力、通勤与差旅、热力、天然气和食物是碳排放的主要来源.热力和天然气的碳排放与月份密切相关,而电力碳排放在不同的功能区和月份都有所不同.食物的碳排放与饮食结构有关,而污水和垃圾处理的碳排放则与处理过程有关.使用蒙特卡洛模拟法讨论了碳排放清单的不确定性,发现碳排放总量的不确定性在-13.61%～26.08%之间.尽管计算结果相对科学可靠,但通勤和差旅、电力、天然气和食品是主要的不确定性来源.总体来说,研究结果为校园和其他复杂系统的碳排放核算和不确定性计算提供了参考.     

海洋资源会计:基础·规范·核算

通过分析海洋资源与当代社会经济发展的关联关系,论证了运用会计方法来确认、计量和报告海洋资源性资产的理论价值与现实意义。指出建立海洋资源会计核算体系是可持续发展观念下加强海洋资源管理的重要形式,探讨了海洋资源的资产特性、产权决定与管理以及价值评估方法等会计核算的基础问题,并对海洋资源会计核算规范五个层次的基本内容进行了阐述。在此基础之上,从会计账户设置、会计交易事项分析与会计信息披露三个角度描述了海洋资源会计记录与报告的主要特点。     

如何克服锅炉安装施工设计编制中意识上的误区

阐明了锅炉安装施工组织设计的作用、重要性、编制依据及质量控制与管理体制的建立中存在意识上的误区,拾遗补缺,明确编制要领。     

服务外包产业发展规律和效应评估的研究进展

随着经济全球化及网络通讯技术进步,服务外包已成为重塑世界产业格局的重要力量,其相关研究引起了学者的广泛关注。主要对服务外包产业发展规律和效应评估的相关研究进行综述。首先介绍了服务外包产生的主要理论观点,并梳理其演进过程及空间分布的研究进展;其次讨论服务外包效应评估的研究内容,其中发包国效应围绕就业、工资、生产力3个方面展开,承接国效应从经济、社会、技术外溢3个角度分析;第三,从理论和实证两个层面对效应评估方法进行了总结,重点基于投入产出表数据、研究报告数据及贸易数据归纳了测度外包水平的不同方法;在综合评述的基础上,展望了未来的研究趋向     

Energy management in hybrid electric vehicles using optimized radial basis function neural network

This paper deals with energy management in hybrid electric vehicles. Use of radial basis function neural network (RBFNN) for the problem of energy management gains importance in the present decade. Use of genetic algorithm (GA) and particle swarm optimization (PSO) as optimization algorithms for parameter estimation is also well known. However, none of the researchers in the area tried to use GA and PSO as training algorithms for the problem. Hence in this paper, we propose two novel methods, based on RBFNN. The difference between RBFNN-based approaches in the literature and those used in this paper is the use of GA and PSO (i.e. optimising algorithms) as training algorithm to train RBFNNs. Interestingly, it is seen that the proposed approaches of this paper outperform RBFNN-based approaches in the literature with traditional training.