Sourcing faecal pollution: a combination of library-dependent and library-independent methods to identify human faecal pollution in non-sewered catchments

Library-dependent (LD) (biochemical fingerprinting of Escherichia coli and enterococci) and library-independent (LI) (PCR detection of human-specific biomarkers) methods were used to detect human faecal pollution in three non-sewered catchments. In all, 550 E. coli isolates and 700 enterococci isolates were biochemically fingerprinted from 18 water samples and compared with metabolic fingerprint libraries of 4508 E. coli and 4833 enterococci isolates. E. coli fingerprints identified human unique biochemical phenotypes (BPTs) in nine out of 18 water samples; similarly, enterococci fingerprints identified human faecal pollution in 10 water samples. Seven samples were tested by PCR for the detection of biomarkers. Human-specific HF134 Bacteroides and enterococci surface protein (esp) biomarkers were detected in five samples. Four samples were also positive for HF183 Bacteroides biomarker. The combination of biomarkers detected human faecal pollution in six out of seven water samples. Of the seven samples analysed for both the indicators/markers, at least one indicator/marker was detected in every sample. Four of the seven PCR-positive samples were also positive for one of the human-specific E. coli or enterococci BPTs. The results indicated human faecal pollution in the studied sub-catchments after storm events. LD and LI methods used in this study complimented each other and provided additional information regarding the polluting sources when one method failed to detect human faecal pollution. Therefore, it is recommended that a combination of methods should be used to identify the source(s) of faecal pollution where possible.     

Confirmation of putative stormwater impact on water quality at a Florida beach by microbial source tracking methods and structure of indicator organism populations

The effect of a stormwater conveyance system on indicator bacteria levels at a Florida beach was assessed using microbial source tracking methods, and by investigating indicator bacteria population structure in water and sediments. During a rain event, regulatory standards for both fecal coliforms and Enterococcus spp. were exceeded, contrasting with significantly lower levels under dry conditions. Indicator bacteria levels were high in sediments under all conditions. The involvement of human sewage in the contamination was investigated using polymerase chain reaction (PCR) assays for the esp gene of Enterococcus faecium and for the conserved T antigen of human polyomaviruses, all of which were negative. BOX-PCR subtyping of Escherichia coli and Enterococcus showed higher population diversity during the rain event; and higher population similarity during dry conditions, suggesting that without fresh inputs, only a subset of the population survives the selective pressure of the secondary habitat. These data indicate that high indicator bacteria levels were attributable to a stormwater system that acted as a reservoir and conduit, flushing high levels of indicator bacteria to the beach during a rain event. Such environmental reservoirs of indicator bacteria further complicate the already questionable relationship between indicator organisms and human pathogens, and call for a better understanding of the ecology, fate and persistence of indicator bacteria.     

Genotype diversity of Escherichia coli isolates in natural waters determined by PFGE and ERIC-PCR

Most library-dependent bacterial source tracking studies using Escherichia coli (E. coli) have focused on strain diversity of isolates obtained from known human and animal faecal sources for library development. In contrast, this study evaluated the genotype variation of E. coli isolated from natural surface water using pulsed field gel electrophoresis (PFGE) and enterobacterial repetitive intergenic consensus sequence polymerase chain reaction (ERIC-PCR) to better understand these naturally occurring populations. A total of 650 water samples were collected over a nine month period from eleven sampling stations from Lake Waco and Belton Lake in Central Texas. Of the 650 water samples collected, 412 were positive for E. coli, yielding a total of 631 E. coli isolates (1-12 isolates collected per sample). PFGE and ERIC-PCR patterns were successfully generated for 555 isolates and were compared using the curve-based Pearson's product-moment correlation coefficient. The 555 E. coli isolates represented 461 PFGE genotypes, with 84% (386/461) of the genotypes being represented by individual isolates. The remaining 75 genotypes were represented by 2-5 isolates each. Using ERIC-PCR, the 555 E. coli isolates represented 175 genotypes, with 63% (109/175) of the genotypes being represented by individual isolates. In contrast to the PFGE results, two ERIC-PCR genotypes represented 37% of the E. coli isolates, (83 and 124 isolates, respectively), and were found throughout the watersheds both spatially and temporally. Based on the PFGE genotype diversity of water isolates, there is little evidence that a small number of environmentally-adapted E. coli represent dominant populations in the studied waterbodies. However, with the lower discriminatory power technique ERIC-PCR, an opposing conclusion might have been drawn. These results emphasize the importance of considering the resolving power of the source tracking technique being used when assessing strain diversity and geographical stability.     

Presence of Enterococcus faecalis in broiler litter and wild bird feces for bacterial source tracking

When Enterococcus faecalis is isolated from fresh feces, its host range appears to be limited to humans and birds. Although E. faecalis is found in human sewage, the extent to which the bacterium is found in broiler litter and in the feces of wild birds is unclear. These results have implications for bacterial source tracking. We determined if media designed for the isolation of fecal enterococci affected this host range, and if E. faecalis was routinely found in broiler litter and in the feces of wild birds. Of five different isolation media, none affected the isolation of E. faecalis. Enterococcus faecalis was routinely found in fresh broiler feces (522 of 1092 isolates; 48%), but rarely in broiler litter (12 of 1452 isolates; <2%). Therefore, broiler litter selects against this bacterium, and broiler litter is an unlikely environmental source of this bacterium. The presence of E. faecalis in eight wild bird species was highly variable. Unless the fecal loading rate from migratory or resident wild birds is high, water samples collected during baseflow conditions with high numbers of E. faecalis may indicate human fecal contamination.     

迭代学习控制在GTAW焊接过程中的应用研究

针对相同工件的批量焊接,并且焊接轨迹相同的情况下,焊接过程具有极高的重复性。提出了基于迭代学习控制(ILC)的脉冲气体钨极氩弧焊(GTAW)焊接过程跟踪控制方法。根据GTAW焊接的动态过程模型,设计了GTAW焊接过程控制的ILC算法,并对算法的收敛性进行了证明。研究结果表明,ILC可以有效地利用焊接过程中的重复信息,经过60次迭代学习后,焊接系统输出可以较好的达到期望轨迹,并获得较高的控制精度,验证了方法的有效性。与PID控制相比ILC控制器不但可以获得较好的跟踪效果,而且还能有效抑制外部扰动的作用,具有较强的鲁棒性。     

基于自适应模糊滑模控制的机器人轨迹跟踪算法

针对控制参数的不确定性以及存在未知外部扰动情况下移动机器人的轨迹跟踪问题,提出一种基于光滑非线性饱和函数的自适应模糊滑模轨迹跟踪控制算法。通过建立不确定非线性移动机器人运动控制模型,利用自适应模糊逻辑系统构建自适应模糊滑模控制器。为了增强轨迹跟踪控制算法对随机不确定外部扰动适应能力的同时削弱滑模控制算法中的输入抖振现象,利用有界输入有界输出(BIBO)稳定的方法,通过带有自适应调节算法的模糊系统对滑模控制律中非线性函数项进行自适应逼近,并设计了模糊系统中可调参数的自适应控制律,保证了控制系统的稳定与收敛。实验结果表明,所设计的控制器对系统参数不确定性和外界扰动均具有较强的轨迹跟踪性能和鲁棒性。与传统的滑模控制算法相比,该算法不仅能有效减小输入抖振而且轨迹跟踪控制精度提高了18.89%。     

基于迭代学习与FIR滤波器的PMLSM高精密控制

针对永磁直线同步电机(PMLSM)运行时易受端部效应、摩擦力、负载扰动、参数变化等不确定性因素的影响而难以达到高精度跟踪控制的问题,提出一种基于迭代学习与有限冲击响应(FIR)滤波器的控制方案。PMLSM伺服系统执行重复任务时,迭代学习控制(ILC)可有效地抑制重复性扰动,具有很高的控制精度,但执行非重复性任务时很难获得较高的控制精度。为了进一步改善基于ILC的PMLSM伺服系统运行迭代1次的跟踪精度,利用ILC的输出信息来设计FIR滤波器,进而用FIR滤波器来代替ILC,使控制系统达到最优的ILC,以提高系统的跟踪精度。采用滑模控制(SMC)对FIR滤波器进行补充,使位置误差快速收敛到一定的界限内,以提高系统的抗扰能力。实验结果表明,所提出的控制方案使系统具有很高的位置跟踪精度和很强的鲁棒性。     

基于EM的多目标跟踪算法

为了提高多目标跟踪的鲁棒性,增强目标之间的区别性,使用了一种基于能量最小化(energy minimization,EM)的多目标跟踪算法,不同于现有算法,本算法专注于将多目标跟踪中的复杂问题表示为能量函数的模型,模型中包括了更优的目标区分策略(相似度模型)。通过将每个能量函数成本值对应一个多目标的跟踪轨迹方案,算法将多目标跟踪问题转化为能量最小化的问题。在能量函数模型的优化方法上,算法采用共轭梯度算法和一系列的跳转运动来找到能量最小的值。公开数据集的实验结果证明了本算法的有效性,而且定量分析结果证明了本算法提高了目标与背景、目标之间的相互区别性从而与其他算法相比能获得更好的鲁棒性能。     

结合SURF与Kalman滤波的CAMShift跟踪算法

针对传统的CAMShift目标跟踪算法,在出现颜色干扰,遮挡等复杂背景中容易跟丢的问题,提出了一种结合SURF特征匹配与Kalman滤波的CAMShift跟踪算法。该算法利用CAMShift算法跟踪得到的候选目标与模板目标的色度和梯度方向的综合直方图比较计算得到的Bhattacharyya系数作为判定依据,当系数大于给定阈值时,采用SURF算法对搜索窗口和上一帧跟踪结果进行特征匹配,重新计算目标的大小和位置。同时为了避免目标快速运动时跟踪失败和减少SURF匹配的计算量,利用Kalman滤波对运动目标窗口进行预测更新以确定下一帧搜索窗口的中心位置。实验表明,该算法在图像背景复杂,出现颜色干扰以及部分遮挡时能够稳定跟踪,其跟踪速度与结合SURF的CAMShift算法相比有显著提高。     

考虑异质性的定频空调负荷聚合建模及功率跟踪策略

为便于建立空调负荷聚合模型,目前研究往往假设空调个体参数一致,忽略了空调受控群内部参数差异较大的实际情况,亦未计及空调最小停运时间与整数设定温度的影响,因此该文考虑空调负荷的异质性,提出一种改进型聚合建模方法。该方法根据空调额定制冷量分组,并通过模糊C-均值聚类算法提高受控群电功率的模拟精度。引入最小停运时间以及设定温度的整数约束,使仿真结果更接近实际定频空调运行工况。同时,在实际运算中采用坐标格式存储稀疏矩阵,提高运算速度和模型的实用性。基于该改进型聚合模型,进一步提出一种功率跟踪策略,该策略计算各聚类群每一时刻的需求响应能力,通过求解0—1整数规划问题实现调控对象最优组合。仿真算例验证所提策略对目标功率跟踪的良好效果。