Antibiotic-Resistant Bacterial Group in Field Soil Evaluated by a Newly Developed Method Based on Restriction Fragment Length Polymorphism Analysis

Spreading of antibiotic resistant bacteria into environment is becoming a major public health problem, implicating affair of the indirect transmission of antibiotic resistant bacteria to human through drinking water, or vegetables, or daily products. Until now, the risk of nosocomial infection of antibiotic resistant bacteria has mainly been evaluated using clinical isolates by phenotypic method. To evaluate a risk of community-acquired infection of antibiotic resistant bacteria, a new method has been developed based on PCR-RFLP without isolation. By comparing restriction fragment lengths of the 16S rDNA gene from bacterial mixture grown under antibiotic treatment to those simulated from the DNA sequence, bacterial taxonomies were elucidated using the method of Okuda and Watanabe [1] [2]. In this study, taxonomies of polymyxin B resistant bacteria group in field soils, paddy field with organic manure and upland field without organic manure were estimated without isolation. In the both field soils, the major bacteria grown under the antibiotic were B. cereus group, which had natural resistance to this antibiotic. In field applied with organic manure, Prevotella spp., and the other Cytophagales, which were suggested to be of feces origin and to acquire resistance to the antibiotic, were detected. When numbers of each bacterial group were roughly estimated by the most probable number method, B. cereus group was enumerated to be 3.30 × 106 MPN/g dry soil in paddy field soil and 1.32 × 106 MPN/g dry soil in upland filed. Prevotella spp. and the other Cytophagales in paddy field were enumerated to be 1.31 × 106 MPN, and 1.07 × 106 MPN·g-1 dry soil.

Probability Analysis for the Damage of Gravity Dam

Damage reliability analysis is an emerging field of structural engineering which is very significant in structures of great importance like arch dams, large concrete gravity dams etc. The research objective is to design and construct an improved method for damage reliability analysis for concrete gravity dam. Firstly, pseudo excitation method and Mazar damage model were used to analyze how to calculate damage expected value excited by random seismic loading and deterministic static load on the condition that initial elastic modulus was deterministic. Moreover, response surface method was improved from the aspects of the regression of sample points, the selection of experimental points, the determined method of weight matrix and the calculation method of checking point respectively. Then, the above method was used to analyze guarantee rate of damage expected value excited by random seismic loading and deterministic static load on the condition that initial elastic modulus was random. Finally, a test example was given to verify and analyze the convergence and stability of this method. Compared with other conventional algorithm, this method has some strong points: this algorithm has good convergence and stability and greatly enhances calculation efficiency and the storage efficiency. From what has been analyzed, we find that damage expected value is insensitive to the randomness of initial elastic modulus so we can neglect the randomness of initial elastic modulus in some extent when we calculate damage expected value.

Bacterial Groups Concerned with Maturing Process in Manure Production Analyzed by a Method Based on Restriction Fragment Length Polymorphism Analysis

Composting is a biological aerobic decomposition process consisted from different phases. Although the Japanese Standards for manure recommended that it took at least 6 months to complete the maturing phase, there was no reliable ground. In order to find out shortening method of the maturing phase, the microorganisms concerned with a progress of the maturing was determined by using the most probable number method (MPN) and PCR-RFLP of the 16S rDNA, which was found effective to provide numbers and taxonomy of polymyxin B resistant bacterial groups in the former paper [1]. Compared to the numbers after thermophilic phase, those of Actinobacteria, δ-proteobacteria, and the other gram negative bacteria increased to 50 times, 20 times, and 105 times, respectively, after maturing phase, while those of Bacillus spp., and α and β-proteobacteria decreased to 1/10, and 1/105 after maturing phase. Numbers of the other Fumicutes, and γ-proteobacteria remained in the same revel. Actinobacteria, δ-proteobacteria, and the other gram negative bacteria might be concerned with a progress of the maturing phase, because these bacterial groups were detected and enumerated due to their proliferation ability. Although number of Acitinobacteria might be underestimated because of a PCR bias, the method was found effective for the purpose to monitor bacteria actively proliferated in culture medium.

Evaluation of the Method Based on Restriction Fragment Length Polymorphism Analysis as Simple Analysis Method of Lactic Acid Bacteria in Foods

Lactic acid bacteria have not only been used to produce various kinds of fermented food, but also used as probiotic products. As lactic acid bacterial group was consisted from diverse genera, a simple inspection method by which numbers and contained microorganisms could be automatically analyzed without any preliminary information was required to use them more effectively. In this manuscript, lactic acid bacterial groups in commercial products of kimuchi, komekouji-miso, and yoghurt were identified and enumerated by our newly developed method [1]-[3], to evaluate whether the method could be used as an inspection method of various food samples. In kimuchi, numerically dominant bacteria were Lactobacillus sakei, and L. casei (1.4 × 104 MPN g-1) and Leuconostoc spp. (l.4 × 104 MPN). In kouji-miso, numerically dominant bacteria was Bacillus spp. (3 × 103 MPN), which mainly included B. subtilis group and B. cereus group. Lactic acid bacteria such as Lactobacillus spp., or Lactococcus spp., included in the komekouji-miso, could be enumerated after 3 days incubation (1.24 × 104 MPN), but not detected after 7 days incubation. In yoghurt A and C, Lactococcus lactis was detected as numerically dominant lactic acid bacteria (3.0 × 105 MPN). In yoghurt B, Lactobacillus spp., or Lactococcus spp., was detected not only by a culturebased method but also by an unculture-based method, although there was a difference between the both estimated numbers. The present results suggested that the method might become useful as a simple inspection method of food microorganisms, because time and labor of the analysis could be reduced by using an unculture-based method and MCE-202 MultiNA. In this study, Bifidobacteriium spp. was not detected in B and C yoghurt, in spite of indicating their existence, and numbers of lactic acid bacteria were lower than the level of the daily product regulation, because 16S rDNA of Bifidobacteriium spp. might not be amplified by the used PCR condition. The PCR condition must be changed so as to amplify Bifidobacterium spp., before the method will be used as an inspection method for lactic acid bacteria.

Reliability analysis of piles constructed on slopes under laterally loading

Response surface method is used to study the reliability analysis of laterally loaded piles in sloping ground. A development load-displacement （p-y） curve for laterally loaded pile response in sloping ground is used to model the pile-soil system, both the pile head displacement and the maximum bending moment of the piles are used as the performance criteria in this study. The reliability analysis method of the laterally loaded pile in sloping ground under the pile head displacement and the maximum bending moment failure modes is proposed, which is in good agreement with the Monte Carlo method. The influences on the probability index of failure by a number of parameters are discussed. It is shown that the variability of pile head displacement increases with the increase in the coefficients of variation of ultimate bearing capacity factor （Npu）, secant elastic modulus at 50%（E50） and level load （H）. A negative correlation between Npu and non-dimensional factor （λ） leads to less spread out probability density function （PDF） of the pile head displacement;in contrast, a positive correlation between Npu andλgives a great variation in the PDF of pile head displacement. As for bearing capacity factor on ground surface （Npo） and λ, both negative and positive correlations between them give a great variation in the PDF of pile head displacement, and a negative correlation will obviously increase the variability of the response.

Probabilistic model and analysis of coupled train-ballasted track-subgrade system with uncertain structural parameters

Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduced a computational model for analyzing probabilistic dynamic responses of three-dimensional(3D)coupled train-ballasted track-subgrade system(TBTSS),where the coupling effects of uncertain rail irregularities,stiffness and damping properties of ballast and subgrade layers were simultaneously considered.The number theoretical method(NTM)was employed to design discrete points for the multi-dimensional stochastic parameters.The time-histories of stochastic dynamic vibrations of the TBSS with systematically uncertain structural parameters were calculated accurately and efficiently by employing the probability density evolution method(PDEM).The model-predicted results were consistent with those by the Monte Carlo simulation method.A sensitivity study was performed to assess the relative importance of those uncertain structural parameters,based on which a case study was presented to explore the stochastic probability evolution mechanism of such train-ballasted track-subgrade system.

Orthogonal expansion of ground motion and PDEM-based seismic response analysis of nonlinear structures

This paper introduces an orthogonal expansion method for general stochastic processes. In the method, a normalized orthogonal function of time variable t is first introduced to carry out the decomposition of a stochastic process and then a correlated matrix decomposition technique, which transforms a correlated random vector into a vector of standard uncorrelated random variables, is used to complete a double orthogonal decomposition of the stochastic processes. Considering the relationship between the Hartley transform and Fourier transform of a real-valued function, it is suggested that the first orthogonal expansion in the above process is carried out using the Hartley basis function instead of the trigonometric basis function in practical applications. The seismic ground motion is investigated using the above method. In order to capture the main probabilistic characteristics of the seismic ground motion, it is proposed to directly carry out the orthogonal expansion of the seismic displacements. The case study shows that the proposed method is feasible to represent the seismic ground motion with only a few random variables. In the second part of the paper, the probability density evolution method （PDEM） is employed to study the stochastic response of nonlinear structures subjected to earthquake excitations. In the PDEM, a completely uncoupled one-dimensional partial differential equation, the generalized density evolution equation, plays a central role in governing the stochastic seismic responses of the nonlinear structure. The solution to this equation will yield the instantaneous probability density function of the responses. Computational algorithms to solve the probability density evolution equation are described. An example, which deals with a nonlinear frame structure subjected to stochastic ground motions, is illustrated to validate the above approach.

Kernel Generalization of Multi-Rate Probabilistic Principal Component Analysis for Fault Detection in Nonlinear Process

In practical process industries,a variety of online and offline sensors and measuring instruments have been used for process control and monitoring purposes,which indicates that the measurements coming from different sources are collected at different sampling rates.To build a complete process monitoring strategy,all these multi-rate measurements should be considered for data-based modeling and monitoring.In this paper,a novel kernel multi-rate probabilistic principal component analysis(K-MPPCA)model is proposed to extract the nonlinear correlations among different sampling rates.In the proposed model,the model parameters are calibrated using the kernel trick and the expectation-maximum(EM)algorithm.Also,the corresponding fault detection methods based on the nonlinear features are developed.Finally,a simulated nonlinear case and an actual pre-decarburization unit in the ammonia synthesis process are tested to demonstrate the efficiency of the proposed method.

Quantitative Human Reliability Analysis for Crew During Shipping Operation

A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and error analysis method(CREAM) to take into account the characteristics of shipping operations. After the influencing factors are identified, Markov method is used to calculate the values of human reliability. The proposed method does not rely on the involvement of experts in the field of human factor nor depend on historical accidents or human error statistics. It is applied to the case of the crew on board of an ocean going dry bulk carrier. The caculated results agree with the actual case, which verifies the validity of the model.

A Framework for Modern Risk-Informed Root Cause Analysis Process

The paper discusses the framework for a risk-informed root cause analysis process.Such process enables scaling of the analysis performed based on the risk associated with the undesired event or condition,thereby creating tiers of analysis where the greater the risk,the more sophisticated the analysis.In a risk-informed root cause analysis process,a situation is normally not analyzed at a level less than what actually occurred.However,a situation may be investigated as though the consequence were greater than actually happened,especially if only slight differences in circumstances could result in a significantly higher consequence.While operational events or safety issues are normally expected to result only with negligible or marginal actual consequences,many of those would actually have certain potential to develop or propagate into catastrophic events.This potential can be expressed qualitatively or quantitatively.Risk-informing of root cause analysis relies on mapping the event or safety issue into a risk matrix which,traditionally,is a two-dimensional probability-consequence matrix.A new concept employed in the risk matrix for root cause analysis is that,while the probability reflects the observed or expected range of values(retaining,thus,its“traditional”meaning),the consequence reflects not only the observed or materialized impact(such as failure of equipment)but,also,its potential to propagate or develop into highly undesirable final state.The paper presents main elements of risk-informed root cause analysis process and discusses qualitative and quantitative aspects and approaches to determination of risk significance of operational events or safety issues.

基于随机动力分析的高土石坝极限抗震能力研究

地震动的随机性对大坝的动力响应影响较大,极限抗震能力作为大坝抗震安全性能的重要环节,在评估过程中也应该充分考虑荷载随机性的影响。基于大量高土石坝随机动力有限元计算,探究坝顶震陷率和坝坡累计滑移量两个重要坝体变形指标之间的关系,并建议了土石坝安全控制标准。利用概率密度演化法对高土石坝进行极限抗震能力分析。结果表明:震陷率随着累计滑移量的增大而增大,二者之间符合逻辑斯蒂增长模型;取10%的超越概率,以250m规则高面板堆石坝和高心墙堆石坝为例,极限抗震能力分别为0.7g~0.75g和0.8g~0.85g;从概率角度提出了评估大坝极限抗震能力的新方法。

COVID-19对太湖重金属污染及水生生态风险的影响

自COVID-19爆发以来,人类生活和经济受到很大负面影响,但同时疫情期间自然环境得到一定改善.为探究COVID-19管控对太湖重金属污染和水生生态风险的影响,将疫情期间(2021.6—2021.7)和爆发前(2019.9—2020.1)太湖重金属污染和水生生态风险进行对比分析,并通过PCAAPCS-MLR(主成分-绝对主因子分析-多元线性回归受体模型)对重金属进行定量源解析.结果表明,疫情期间太湖重金属污染水平和对水生生物的生态风险皆显著降低,降幅分别为39.9%—92.8%和0.19%—87.66%.整体水质优良比例提升了33.65%.重金属中受影响最大的元素为铜和铬.定量源解析结果表明,工业源对铜和铬的贡献率分别为79.75%和84.26%,疫情期间工业活动的减少是太湖重金属污染和生态风险降低的主要原因.为更好地管控太湖重金属污染和保护太湖水生生物,建议优先监管太湖周边电镀、冶炼和化学三大工业企业铜和铬的排放.

考虑套筒灌浆随机缺陷的装配式剪力墙结构可靠度评估

在装配整体式剪力墙结构中,由于套筒灌浆连接的质量具有一定的随机性,势必影响结构的竖向连接性能和结构抗震性能。根据不同缺陷程度的套筒灌浆拉拔试验,建立了一套等效套筒灌浆缺陷连接承载力模型,并基于某实际工程结构,建立了装配整体式剪力墙结构有限元模型。通过考虑灌浆缺陷的随机性,赋予连接接头相应缺陷程度的力学连接性能,来反映套筒灌浆中可能存在的缺陷。通过非线性有限元分析并结合概率密度演化方法(probability density evolution method,PDEM)进行了结构随机非线性反应分析和可靠度评估。结果表明:在动力作用下,结构非线性与随机性具有明显的耦合效应;缺陷的随机性会随着时间的推移,逐渐放大对结构响应的影响;在不同的安全域内,结构的整体可靠度将存在较大的差异。

基于直接概率积分法的列车-轨道-桥梁系统随机分析

由于施工和制造误差使得铁路工程结构参数不可避免地具有不确定性,同时作为系统主要自激励的轨道不平顺亦具有明显的随机性和时变性,因此,探明不确定因子对列车和轨道-桥梁结构动态性能的影响非常重要。为了高效地完成列车-轨道-桥梁系统随机性能分析,建立列车-轨道-桥梁空间振动分析模型,采用轨道不平顺概率模型和谱表达-随机函数的方式在有限随机变量空间中实现轨道不平顺随机过程的高效模拟。引入概率密度积分方程和直接概率积分法发展了列车-轨道-桥梁系统随机动力方程和相应的计算求解策略。基于MATLAB实现了列车-轨道-桥梁随机振动的直接概率积分法分析程序,计算了全概率不平顺激励和参数随机条件下车-轨-桥系统振动响应的均值、标准差和时变的概率密度信息。研究结果表明:与概率密度演化分析方法相比,直接概率积分法可较好地反映行车过程中系统响应的概率密度特征,然而其在系统响应随机后处理时更为高效,其效率可提高1~2个数量级。此外,考虑轨道不平顺全概率激励更能准确地反映行车过程系统响应的概率特征,平均概率谱可能使得计算结果偏于保守;行车速度对于列车和桥梁动态行为的影响是显著的,随着行车速度的增加系统响应的范围逐渐变大。研究结果进一步拓展了列车-轨道-桥梁随机系统的分析方法,可以高效地用于系统状态评估和设计优化。

济宁岱庄煤矿采空区注浆治理工程建设适宜性评价

济宁市任城区五里屯建设项目位于岱庄煤矿注浆治理采空区的上方,本文根据该采空区注浆治理工程后地表变形监测数据,采用概率分析法计算充填后地表残余变形,残余下沉量2~16mm,地表残余倾斜最大值为0.06mm/m,残余水平移动最大值为4mm,残余水平变形最大值为0.06mm/m,确定采空区场地为稳定场地。按采空区对建筑工程的影响和拟建工程项目对采空区的影响两个方面评价工程建设的适宜性,为工程设计提供依据。

近断层地震下连续梁桥随机振动与易损性分析

由于桥梁建设场地难免会靠近地震活动断层,为了评定近断层地震动作用下连续梁桥的地震安全性水平以及提高抗震性能,亟待发展连续梁桥非线性随机地震动力响应与易损性分析的统一、准确方法。考虑到近断层地震动是典型的随机过程激励,本文提出了基于直接概率积分法的连续梁桥结构非线性随机振动响应与地震易损性准确、通用分析的新框架。发展直接概率积分法,准确高效地计算连续梁桥结构的随机振动响应;结合连续梁桥多种失效状态,根据动力可靠度的首次超越破坏准则,利用直接概率积分法对连续梁桥进行了地震易损性分析。最后,展示了近断层随机地震动激励作用下四跨非线性连续梁桥算例结果,验证了直接概率积分法的准确性特点。比较了近断层脉冲型和无脉冲地震动对非线性连续梁桥地震易损性曲线的影响。结果表明:近断层地震动的速度脉冲显著加剧了连续梁桥结构受到的地震破坏,增大了桥梁结构进入不同破坏状态的超越概率。

综合能源系统建模与能流计算方法研究综述

围绕综合能源系统的能流计算问题,从网络模型及求解、不确定性能流分析方法2个层面综述了各类能流计算方法。首先,在综合能源系统网络特性建模方面,讨论了偏微分方程模型、动态特性模型和稳态特性模型及其求解方法。其次,归纳了应对系统外部输入不确定性的概率和区间2类传统能流分析方法,以及概率-区间混合不确定性能流分析方法。最后,从工程应用角度分析当前综合能源系统能流计算的难点与热点,进而对其发展方向进行展望。

基于CNN-Swin Transformer Network的LPI雷达信号识别

针对在低信噪比(SNR)条件下,低截获概率雷达信号调制方式识别准确率低的问题,提出一种基于Transformer和卷积神经网络(CNN)的雷达信号识别方法。首先,引入Swin Transformer模型并在模型前端设计CNN特征提取层构建了CNN+Swin Transformer网络(CSTN),然后利用时频分析获取雷达信号的时频特征,对图像进行预处理后输入CSTN模型进行训练,由网络的底部到顶部不断提取图像更丰富的语义信息,最后通过Softmax分类器对六类不同调制方式信号进行分类识别。仿真实验表明:在SNR为-18 dB时,该方法对六类典型雷达信号的平均识别率达到了94.26%,证明了所提方法的可行性。

A novel refined dynamic model of high-speed maglev train-bridge coupled system for random vibration and running safety assessment

Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.

深水导管架平台波浪动力响应及参数敏感性分析

考虑到300 m级导管架平台的自振周期与自升式平台极为接近,自升式平台的波浪动力响应分析方法在理论上可应用于深水导管架平台,但应用前需要进行参数敏感性分析,采用SACS软件建立300 m级导管架平台有限元模型,结合JONSWAP波浪谱、利用线性叠加法构造满足高斯性条件的随机波浪;基于时域分析法,进行在随机波浪载荷下的结构动力响应分析;采用Winterstein/Jensen方法计算平台基底剪力和倾覆力矩的最可能最大值,以及动力放大系数;对波浪瞬态变化、模拟步长和时长、随机种子等参数对动力放大系数进行敏感性分析,结果表明,动力放大系数对波浪瞬态变化较为敏感、对模拟步长和时长,以及随机种子极为敏感。采用Winterstein/Jensen方法进行深水导管架平台动力响应分析时,基于敏感性分析得出的参数可获得更合理、准确的动力放大系数。