Water and Sediment Quality in Lakes along the Middle and Lower Reaches of the Yangtze River, China

Water and sediment samples were collected from 45 lakes along the middle-lower Yangtze River, China. Each lake was sampled seasonally, over a period of one year. Water quality variables and metals in sediments were measured. Lakes along the lowest part of the river, within the Yangtze River Delta, had highest nutrient concentrations and were eutrophic or hypereutrophic. Lakes displayed a gradient in many water chemistry variables, from the middle to the lower Yangtze River. Lakes of the Delta region had the highest conductivity, sulfate, turbidity, and Chl-a values, and the lowest dissolved oxygen concentrations. A number of lakes near urban areas in the study region also displayed similar conditions. Lakes polluted by heavy metals were found in the upper part of the lower Yangtze River and had high Cu, Cr, and Co concentrations in sediments. The mean I_geo (index of geoaccumulation) values for Cu, Cr, and Co classes ranged from 0 to 4, indicating moderate to heavy contamination, contributed mainly from untreated industrial waste water produced within the lake catchments. Lakes of the middle Yangtze River are generally in relatively better condition, except for those around urban zones, which experience higher nutrient and heavy metal loading. The spatial distribution of lake conditions in the area can be related to the policy of regional economic development. The Delta region in China is developed and includes such cities as Shanghai and Suzhou. Heavy industries have moved into the interior region of China too, and development of modern cities is now occurring under some level of environmental protection. Nevertheless, lakes in the central part are becoming seriously polluted with both heavy metals and nutrients because local authorities promote industrialization and urbanization to improve economic conditions, while often ignoring environmental protection. Pollution is increasingly occurring in upstream reaches, a tendency that will bring more environmental problems. Interior lakes of China require immediate attention to prevent further declines in water quality.     

Kidney injury and cell therapy: Preclinical study

The aim of this study is to show histological and immunofluorescence analysis of renal parenchyma of agoutis affected by gentamicin‐induced renal disease after the infusion of bone marrow mononuclear cells (BMMC) stained with Hoechst®. Nine agouti's males were divided into three groups: Test group (TG): renal disease by gentamicin induced (n = 3), cell therapy group (CTG): renal disease by gentamicin induced and BMMC infusion (n = 3), and control group (CG): nonrenal disease and BMMC infusion (n = 3). TG and CTG were submitted to the protocol of renal disease induction using weekly application of gentamicin sulfate for 4 months. CG and CTG received a 1 × 108 BMMC stained with Hoechst and were euthanized for kidney examination 21 days after BMMC injection and samples were collected for histology and immunofluorescence analysis. Histological analysis demonstrated typical interstitial lesions in kidney similarly to human disease, as tubular necrosis, glomerular destruction, atrophy tubular, fibrotic areas, and collagen deposition. We conclude that histological analysis suggest a positive application of agouti's as a model for a gentamicin inducing of kidney disease, beyond the immunofluorescence analysis suggest a significant migration of BMMC to sites of renal injury in CTG. Microsc. Res. Tech., 2012. © 2011 Wiley Periodicals, Inc.     

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.     

IEEE802.11p下删余卷积编码译码方法的研究

应用于智能交通系统的无线接入协议IEEE802.11p,其物理层卷积编码的码率可通过对(2,1,7)卷积编码器的删余来实现。讨论了删余位置的图案和算法,分析了在删余位置插入不同哑元时维特比译码后误码率的统计特性。仿真的同时比较了固定哑元下不同码率所引入的误比特率。     

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.     

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.