Enhancement of nitrate removal in synthetic groundwater using wheat rice stone

To enhance the efficiency of nitrate removal from synthetic groundwater, wheat rice stone (WRS) and granular activated carbon (GAC) were employed as biofilm carriers for denitrification under different HRT (hydraulic retention time) and C/N ratios. Four different ratios of GAC to WRS (0, 0.5, 1.0, and 2.0) were investigated to determine the most appropriate ratio of GAC and WRS. The NO(3)(-)-N, NO(2)(-)-N, COD levels and pH of the effluent were also investigated under various HRT and C/N ratios. The results showed that the column at a GAC/WRS ratio of 1.0 performed best under a C/N ratio of 0.9 and an HRT of 8 h, with 99% nitrate being removed. In addition, little nitrite accumulation and chemical oxygen demand (COD) were observed in effluent under these conditions. These results demonstrated that, with no addition of phosphor in the influent, the nitrate removal efficiency can be enhanced by WRS because WRS can leach trace elements and phosphor to promote the growth of bacteria.     

浅论水行政过程中的正当法律程序

水行政执法是水行政管理工作的主要内容之一,依照正当的法律程序进行水行政执法可以充分保障行政相对人的合法权益,并对水政执法机关的执法行为形成必要监督,使水行政执法更加高效、有序.在法律的框架内严格依照法律程序实施水行政执法,推动水利改革发展,是水行政主管部门必须认真对待的问题.     

振动梁信号自动检测系统的设计与实现

以ZY13Sens12SB传感器技术实验台为平台,以振动梁为对象,利用应变传感器检测振动梁的振动。给出了系统硬件设计原理框图、各模块之间的接口连接,通过调节实验台上音频振荡器的频率,达到调制和改变振动梁的振动频率,可实现振动梁以不同频率和幅度振动,利用示波器可实时观察振动波形。     

基于ZigBee网络的智能铁鞋系统设计

针对目前现有的无线通信铁鞋系统在使用过程中出现的问题,提出一种新型的智能铁鞋设计方案。该系统的拓扑结构由协调器和采集器节点构成,利用ZigBee无线传感器网络实现节点间的互联组网,采用CC2531作为协调器节点的核心控制芯片,CC2530作为采集器的核心控制芯片。此外,采用CC2591作为末端放大器,以提高发射功率,进一步增大传输距离(由传统的75 m提高到1 km以上)。最后,利用VC++和SQL Server 2005实现了控制室铁鞋检测控制系统上位机的设计。实践表明,该系统可靠性高、传输距离远,能满足现场需求。     

协同系统中基于误比特率的波束成形设计

针对频率选择性信道下放大转发模式的多中继协同系统的波束成形因子设计问题进行研究。以最小化接收端总误比特率(BER)为目标,提出了一种两阶段的波束成形设计方法。所提方法可以有效降低设计的难度和复杂度,并且可以使接收端的总BER最小。仿真结果表明,与现有算法相比,本算法可以显著降低接收端的误比特率。     

Error Analysis of Chebyshev-Legendre Pseudo-spectral Method for a Class of Nonclassical Parabolic Equation

Many physical phenomena are modeled by nonclassical parabolic initial boundary value problems which involve a nonclassical term u _xxt in the governed equation. Combining with the Crank-Nicolson/leapfrog scheme in time discretization, Chebyshev-Legendre pseudo-spectral method is applied to space discretization for numerically solving the nonclassical parabolic equation. The proposed approach is based on Legendre Galerkin formulation while the Chebyshev-Gauss-Lobatto (CGL) nodes are used in the computation. By using the proposed method, the computational complexity is reduced and both accuracy and efficiency are achieved. The stability and convergence are rigorously set up. The convergence rate shows ??spectral accuracy??. Numerical experiments are presented to demonstrate the effectiveness of the method and to confirm the theoretical results.     

Identification of Breast Cancer Prognosis Markers via Integrative Analysis

In breast cancer research, it is of great interest to identify genomic markers associated with prognosis. Multiple gene profiling studies have been conducted for such a purpose. Genomic markers identified from the analysis of single datasets often do not have satisfactory reproducibility. Among the multiple possible reasons, the most important one is the small sample sizes of individual studies. A cost-effective solution is to pool data from multiple comparable studies and conduct integrative analysis. In this study, we collect four breast cancer prognosis studies with gene expression measurements. We describe the relationship between prognosis and gene expressions using the accelerated failure time (AFT) models. We adopt a 2-norm group bridge penalization approach for marker identification. This integrative analysis approach can effectively identify markers with consistent effects across multiple datasets and naturally accommodate the heterogeneity among studies. Statistical and simulation studies demonstrate satisfactory performance of this approach. Breast cancer prognosis markers identified using this approach have sound biological implications and satisfactory prediction performance.     

A consistency and consensus based decision support model for group decision making with multiplicative preference relations

In group decision making (GDM) with multiplicative preference relations (also known as pairwise comparison matrices in the Analytical Hierarchy Process), to come to a meaningful and reliable solution, it is preferable to consider individual consistency and group consensus in the decision process. This paper provides a decision support model to aid the group consensus process while keeping an acceptable individual consistency for each decision maker. The concept of an individual consistency index and a group consensus index is introduced based on the Hadamard product of two matrices. Two algorithms are presented in the designed support model. The first algorithm is utilized to convert an unacceptable preference relation to an acceptable one. The second algorithm is designed to assist the group in achieving a predefined consensus level. The main characteristics of our model are that: (1) it is independent of the prioritization method used in the consensus process; (2) it ensures that each individual multiplicative preference relation is of acceptable consistency when the predefined consensus level is achieved. Finally, some numerical examples are given to verify the effectiveness of our model.     

Extended Gaussian Kriging for computer experiments in engineering design

Metamodeling or surrogate modeling is becoming increasingly popular for product design optimization in manufacture industries. In this paper, an extended Gaussian Kriging method is proposed to improve the prediction performance of widely used ordinary Kriging in engineering design. Unlike the forgoing approaches, the proposed method places a variance-varying Gaussian prior on the unknown regression coefficients in the mean model of Kriging and makes prediction at untried design points based on the principle of Bayesian maximum a posterior. The achieved regression mean model is adaptive, therefore capable of capturing more effectively the overall trend of computer responses and leading to a more accurate metamodel. Particularly, the regression coefficients in the mean model are estimated by a fast numerical algorithm, making extended Gaussian Kriging implemented roughly as efficient as ordinary Kriging. Experiment results on several examples are presented, showing remarkable improvement in prediction using extended Gaussian Kriging over ordinary Kriging and several other metamodeling methods.     

A new view of fuzzy ideals in \Upgamma-rings

By means of a kind of new idea, we redefine fuzzy ideals and fuzzy interior ideals in a $\Upgamma$ -ring and investigate some of their related properties. In particular, we show that the regular and semisimple $\Upgamma$ -rings can be described by using these kinds of generalized fuzzy ideals.