生物柴油中多元不饱和脂肪酸甲酯检测技术现状研究

分析了生物柴油中多元不饱和脂肪酸甲酯检测技术的发展现状,通过介绍生物柴油的制备工艺、制备过程,以及生物柴油中测算、提取不饱和脂肪酸甲酯的作用原理,介绍了生物柴油的可操作性。在随后的实验过程中,实践测算了样本生物柴油的不饱和脂肪酸甲酯含量。

新常态下的油气水井管理评价结构

油气水井管理是采油厂油气开发的基本单元。华北油田公司第四采油厂通过系统构建油气水井全方位管理评价结构、油井分类优选等方法,正确处理油气水井生产过程中的各种矛盾与影响因素,为降本增效、节能降耗、提升采油厂运营能力提供了有力的支持。

多元对位技术中的传统音乐神韵——贾国平木管五重奏《孤松吟风》复调思维诠释

贾国平教授创作的木管五重奏《孤松吟风》是一部在创作理念和多声写作技术上充满新意的作品。作曲家立足于传统音乐,通过多元化对位技术的综合运用,将音响事件与表现生动的传统音乐神韵相结合,体现了作曲家复调思维的深度和广度,以及立足传统、努力开拓的创新精神。

Fault detection of excavator’s hydraulic system based on dynamic principal component analysis

In order to improve reliability of the excavator's hydraulic system, a fault detection approach based on dynamic principal component analysis(PCA) was proposed. Dynamic PCA is an extension of PCA, which can effectively extract the dynamic relations among process variables. With this approach, normal samples were used as training data to develop a dynamic PCA model in the first step. Secondly, the dynamic PCA model decomposed the testing data into projections to the principal component subspace(PCS) and residual subspace(RS). Thirdly, T2 statistic and Q statistic performed as indexes of fault detection in PCS and RS, respectively. Several simulated faults were introduced to validate the approach. The results show that the dynamic PCA model developed is able to detect overall faults by using T2 statistic and Q statistic. By simulation analysis, the proposed approach achieves an accuracy of 95% for 20 test sample sets, which shows that the fault detection approach can be effectively applied to the excavator's hydraulic system.

高性能超硬涂层刀具的应用

采用最新表面改性技术——金属离子注入和多元多层复合涂层技术,在高速钢钻头和丝锥上进行高性能超硬涂层,同时简述涂层刀具的切削试验过程及生产应用效果,并指出了影响涂层刀具切削性能的因素。

Generic reconstruction technology based on RST for multivariate time series of complex process industries

In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.

Damage alarming for bridge expansion joints using novelty detection technique based on long-term monitoring data

Damage alarming and safety evaluation using long-term monitoring data is an area of significant research activity for long-span bridges. In order to extend the research in this field, the damage alarming technique for bridge expansion joints based on long-term monitoring data was developed. The effects of environmental factors on the expansion joint displacement were analyzed. Multiple linear regression models were obtained to describe the correlation between displacements and the dominant environmental factors. The damage alarming index was defined based on the multiple regression models. At last, the X-bar control chart was utilized to detect the abnormal change of the displacements. Analysis results reveal that temperature and traffic condition are the dominant environmental factors to influence the displacement. When the confidence level of X-bar control chart is set to be 0.003, the false-positive indications of damage can be avoided. The damage sensitivity analysis shows that the proper X-bar control chart can detect 0.1 cm damage-induced change of the expansion joint displacement. It is reasonably believed that the proposed technique is robust against false-positive indication of damage and suitable to alarm the possible future damage of the expansion joints.

Variable Rate Technology and Cotton Yield Response in Texas

Variable Rate Technology （VRT） takes within-field variability into consideration and aims to match resource application to crop requirement. Even though Texas is the most important cotton producing state in the US, the rate of VRT adoption is very low here. Hence, analyzing the factors influencing the adoption and providing a regional estimate of the impact of VRT adoption on cotton yield is very important. This study used the 2009 Southern Cotton Precision Farming Survey to analyze the farm and farmer characteristics affecting the adoption of VRT among Texas cotton farmers and to empirically estimate the impact of adoption of VRT on cotton yield in Texas. A two-stage least square procedure with a logistic regression model in the first stage and a multiple linear regression model in the second stage was used to analyze the data. The study revealed that there are significant regional differences in adoption pattern within the state of Texas; and the farmers from the coastal region, where there is higher within-field variability, were more likely to adopt VRT compared to other regions. Younger farmers, farmers managing larger farms, and farmers who use computers for farming operations were more likely to adopt VRT. The results also showed that, on an average, the adoption of VRT does not lead to significant yield improvements for cotton in Texas. Since the impact of VRT adoption on yield is not significant, the source of economic advantage of VRT adoption in Texas may be the reduction of input cost.

Efficient multiuser detector based on box-constrained dichotomous coordinate descent and regularization

The presented iterative multiuser detection technique was based on joint deregularized and box-constrained solution to quadratic optimization with iterations similar to that used in the nonstationary Tikhonov iterated algorithm.The deregularization maximized the energy of the solution,which was opposite to the Tikhonov regularization where the energy was minimized.However,combined with box-constraints,the deregularization forced the solution to be close to the binary set.It further exploited the box-constrained dichotomous coordinate descent algorithm and adapted it to the nonstationary iterative Tikhonov regularization to present an efficient detector.As a result,the worst-case and average complexity are reduced down as K2.8 and K2.5 floating point operation per second,respectively.The development improves the "efficient frontier" in multiuser detection,which is illustrated by simulation results.In addition,most operations in the detector are additions and bit-shifts.This makes the proposed technique attractive for fixed-point hardware implementation.

Paralinguistic and Kinesic Codes of Performance： An Intercultural Gilgamesh

This paper examines the directing, acting and rehearsal process in transforming the ancient Babylonian epic Gilgamesh for the stage using performers＇ journals as a means of determining the effect of corporeal non-western styles on actors whose prior experience was almost exclusively in naturalistic and text-based theatre. The introduction of theatrical elements from multiple cultures including puppetry and the masks and techniques of Noh drama created a multi-tiered field for intercultural exchange. While Patrice Pavis＇s hourglass model for the transfer of theatrical material from a source to a target culture may hold true for productions that use linear modes of transmission, translation and incorporation of text, music, costumes and styles, its limitations make it necessary to posit alternative theories that take into account intercultural rehearsal practices, the collaboration of source and target culture and the dynamic interactions that take place through the agency of actor training in the fleshly physical theatre.

FAIRNESS OF SHARING PROTECTION FOR MULTICAST IN WDM NETWORKS

In this paper,the sharing schemes of multicast in survivable Wavelength-Division Multi-plexed(WDM) networks are studied and the concept of Shared Risk Link Group(SRLG) is considered.While the network resources are shared by the backup paths,the sharing way is possible to make the backup paths selfish.This selfishness leads the redundant hops of the backup route and a large number of primary lightpaths to share one backup link.The sharing schemes,especially,the self-sharing and cross-sharing,are investigated to avoid the selfishness when computing the backup light-tree.In order to decrease the selfishness of the backup paths,it is important to make the sharing links fair to be used.There is a trade-off between the self-sharing and cross-sharing,which is adjusted through simulation to adapt the sharing degree of each sharing scheme and save the network resources.

A Modified Polynomial Preserving Recovery and Its Applications to A Posteriori Error Estimates

A modified polynomial preserving gradient recovery technique is proposed. Unlike the polynomial preserving gradient recovery technique,the gradient recovered with the modified polynomial preserving recovery(MPPR) is constructed element-wise, and it is discontinuous across the interior edges.One advantage of the MPPR technique is that the implementation is easier when adaptive meshes are involved.Superconvergence results of the gradient recovered with MPPR are proved for finite element methods for elliptic boundary problems and eigenvalue problems under adaptive meshes. The MPPR is applied to adaptive finite element methods to construct asymptotic exact a posteriori error estimates.Numerical tests are provided to examine the theoretical results and the effectiveness of the adaptive finite element algorithms.

时频电磁法在油气探测方面的应用及进展

近年来,针对复杂区油气勘探,时频电磁技术在应用中不断发展。在仪器性能方面,研发了大功率恒流发射系统,最大功率400 kW,能有效压制干扰并激发深层目标的电磁响应;在采集方法上,研究了规则化双方位激发宽线同步采集方法,提高了采集精度和施工效率;在处理方法上,研究了多元建模约束反演处理技术,提高了目标层纵、横向分辨率;在评价方法上,引入了基于多参数深度学习智能油气评价方法,挖掘了多参数信息,提高了油藏的评价精度。针对中国东部某盆地深层多期次火山岩难题和鄂尔多斯复杂油气藏,采用最新时频电磁技术,精细刻画了研究区多期火山岩储层和鄂尔多斯复杂油气分布规律,后钻井结果验证了时频资料的可靠性。

Denitrification Rates and Their Controlling Factors in Streams of the Han River Basin with Different Land-Use Patterns

Land-use patterns can affect various nutrient cycles in stream ecosystems, but little information is available about the effects of urban development on denitrification processes at the watershed scale. In the presented study, we investigated the controlling factors of denitrification rates within the streams of the Han River Basin, Korea, with different land-use patterns, in order to enhance the effectiveness of water resource management strategies. Ten watersheds were classified into three land-use patterns （forest, agriculture and urban） using satellite images and geographic information system techniques, and in-situ denitrification rates were determined using an acetylene blocking method. Additionally, sediment samples were collected from each stream to analyze denitrifier communities and abundance using molecular approaches. In-situ denitrification rates were found to be in the order of agricultural streams （289.6 mg N20-N m-2 d-1） 〉 urban streams （157.0 mg N20-N m-2 d-1） 〉 forested streams （41.9 mg N20-N m-2 d-l）. In contrast, the average quantity of denitrifying genes was the lowest in the urban streams. Genetic diversity of denitrifying genes was not affected by watershed land-use pattern, but exhibited stream-dependent pattern. More significance factors were involved in denitrification in the sites with higher denitrification rates. Multiple linear regression analysis revealed that clay, dissolved organic carbon and water contents were the main factors controlling denitrification rate in the agricultural streams, while dissolved organic carbon was the main controlling factor in the urban streams. In contrast, temperature appeared to be the main controlling factor in the forested streams.

Modulating Wnt signaling to improve cell replacement therapy for Parkinson＇s disease

Clinical trials have demonstrated the capacity for dopamine neurons, transplanted ectopicaUy into the striatum, to structurally inte- grate, restore dopamine transmission, and induce long-term functional benefits for Parkinson＇s disease （PD） patients. Despite this proof of principle, a number of limitations have hindered the development of cell replacement therapy over the past 20 years, particu- larly tissue availability, graft survival, and adequate reinnervation of the host brain. With a greater understanding of failure in prior clinical trials, increased knowledge of midbrain dopamine development （now including Wnts）, and the development of pluripotent stem cell technologies, we are better equipped than ever to re-address a number of these challenges. This review summarizes the trials, tribulations, and progress in cell replacement therapy for PD. We discuss the prospects of modulating canonical and non-canon- ical Wnt signalingto improve cell therapy based upon their roles in dopamine neural development and the adult brain. This will include the potential of Wnts to （i） expand fetaUy derived tissue in vitro and foUowing transplantation, （ii） promote the differentiation of pluripotent stem cells, （iii） increase graft integration and restoration of neural circuitry, and finally （iv） enhance graft survival.