Guayule seedling response to nitrogen fertilizers

Slow growth and high seedling mortality limit direct seeding establishment of guayule (Parthenium argentatum G.). This study was conducted to assess seedling growth enhancement by the addition of different rates and forms of N fertilizers and Ca salts. Experiments were conducted in a greenhouse with cultivar 593 under both surface and subirrigated conditions using water low in salts (salinity of 0.8 dSm^–1, SAR of 5.0 and 10 mg Ca L^–1). Under surface-irrigated conditions, seedling height and fresh plant weight increased with N application to the irrigation water to 70 mg L^–1. The best seedling growth was observed when (NH₄)₂SO₄ was added in combination with CaCl₂ or CaSO₄. Progressively less growth was observed by addition of (NH₄)₂SO₄ alone, CO(NH₂)₂ plus CaSO₄, CO(NH₂)₂ alone and Ca(NO₃)₂. When seedlings were subirrigated, however, the best growth was observed with Ca(NO₃)₂. Intermediate growth was obtained with (NH₄)₂SO₄ plus CaSO₄ and lowest growth rates with (NH₄)₂SO₄ alone. These differential responses may be explained by the differences in leaching and volatile characteristics of the N forms. Growth enhancement from N and Ca additions increased with time with significant increases 45 days after seeding. Nitrogen application with Ca may be effective amendment in promoting subsequent growth of direct seeded guayule.     

Enzymic adaptations in leaf-feeding insects to host-plant allelochemicals

Herbivorous insects have the capacity to develop behavioral, physiological, and biochemical resistance mechanisms in response to chemical selection pressures. Among natural insect-plant associations, there are several cases of target-site insensitivity to and enhanced metabolism of plant allelochemicals. There are also known instances of physiological defenses such as extra rapid excretion or storage of toxic compounds. Multiple defenses seem to be prevalent in natural insect-plant interactions that involve toxic compounds, possibly reflecting the long time these interactions have had to evolve compared to insect-synthetic insecticide interactions. Synthetic insecticides were introduced about 45 years ago. Until recently they have been used as single-active-component preparations. As such, they have been and are very effective in producing insect populations with enhanced detoxification ability and target-site insensitivity. Most insecticide-resistant insect populations have one major defense mechanism. This feature makes the synthetic insecticides very useful tools for studies of insect defenses against toxic chemicals. Information gained from studies with insecticides can shed light on the capabilities of insects to adapt to toxicants in their environment. In assessing the validity of work with synthetic insecticides for natural systems, the fundamental differences between these substances and allelochemicals, and in their presentation to the insects, must, however, be considered. The prevalence of multiple defenses and reliance on modified physiological processes in natural interactions may reflect different properties of the natural chemicals in being generally highly biodegradable and often less acutely toxic than synthetic insecticides. In many cases, the plant allelochemicals are presented to the insects as mixtures. It is, however, to be expected that pest insects will evolve effective multiple defenses against synthetic insecticides. About 20% of all resistant populations have already developed multiple defenses, in most cases combinations of enhanced metabolism and target-site insensitivity. This implies that current crop protection practices need to be modified to ensure the continued usefulness of synthetic insecticides. To achieve this, it is important to study intensively not only insect-insecticide interactions but also the interactions operating in natural insect-plant associations.     

A weighted multivariate Fuzzy C-Means method in interval-valued scientific production data

Clustering is the process of organizing objects into groups whose members are similar in some way. Most of the clustering methods involve numeric data only. However, this representation may not be adequate to model complex information which may be: histogram, distributions, intervals. To deal with these types of data, Symbolic Data Analysis (SDA) was developed. In multivariate data analysis, it is common some variables be more or less relevant than others and less relevant variables can mask the cluster structure. This work proposes a clustering method based on fuzzy approach that produces weighted multivariate memberships for interval-valued data. These memberships can change at each iteration of the algorithm and they are different from one variable to another and from one cluster to another. Furthermore, there is a different relevance weight associated to each variable that may also be different from one cluster to another. The advantage of this method is that it is robust to ambiguous cluster membership assignment since weights represent how important the different variables are to the clusters. Experiments are performed with synthetic data sets to compare the performance of the proposed method against other methods already established by the clustering literature. Also, an application with interval-valued scientific production data is presented in this work. Clustering quality results have shown that the proposed method offers higher accuracy when variables have different variabilities.     

利用C++Builder对处理ESCR数据方法的改进

介绍一种利用C＋＋Builder编程工具自动处理聚乙烯环境应力开裂(ESCR)试验数据的方法。此方法利用计算机简化试验数据的处理过程,消除标准试验方法中作图法所引入的人为误差,并可以大幅度缩短试验时间。     

Discourse cues to deception in the case of multiple receivers

Behavioral cues to deception are instrumental in detecting deception. As one of the primary sources of deception behavior, text has been analyzed at the level of sub-sentence or message but not the discourse of interaction. Additionally, empirical studies on cues to deception in the case of multiple receivers remain nonexistent. To fill these voids, we propose a discourse framework and six hypotheses about deception behaviors in a multi-receiver environment. The deception behaviors are operationalized by discourse features based on an analysis of real-world data. The results of statistical analysis validate the efficacy of discourse features in discriminating deceivers from truth-tellers.     

实时数据仓库中一种改进的数据流更新算法

为实现数据仓库中数据的高效集成,针对数据偏斜分布现象,提出一种改进的数据流更新算法EH-JOIN。该算法对传统散列连接方法进行改进,利用索引将部分频繁使用的主数据存储在内存中,解决了高速数据流下的磁盘频繁访问问题。实验结果表明,与MESHJOIN算法和R-MESHJOIN算法相比,EH-JOIN算法的服务速率在磁盘存储关系集保持适当大小时分别提高了96%和81%,在内存大小不同时提高了57%和48%。     

Polymer/surfactant interaction—Its relevance to detergent systems

The field of polymer/surfactant interaction is reviewed in this work. Results from two investigative methods,viz., dialysis and surface tension, are discussed, illustrating the main behavioral patterns and outlining the principles of the interactions. Next, aspects of the interaction phenomena that appear to have relevance to detergent formulation are presented. These include solution rheology, solubility control and surface conditioning. Lastly, the importance of surface activity of the polymer itself is stressed, culminating in a discussion of the properties of hydrophobically modified water-soluble polymers (“polymeric surfactants”), both alone and in the presence of conventional surfactants. Based on the Samuel Rosen Memorial Award lecture, given at the AOCS Annual Meeting, Anaheim, CA, April 1993.     

企业各软件的数据共享和整合分析浅谈

本文主要根据大多数企业存在各种软件各自独立运行,各软件之间数据不能相互共享,一些旧软件或不适用的软件与目前主流操作系统不兼容等问题,分析问题并用接口和整合方法解决,此平台利用云计算技术,解决大多数企业建设信息平台投资大的问题,同时方便企业使用和维护.     

改进的APRIORI算法在试卷系统数据挖掘中的应用

本文通过对数据挖掘技术的研究,采用关联规则法对学生答题数据进行分析,并在关联规则使用中采用改进型的Apriori算法进行运算,构建高频集,并对于高分学生和低分学生的试卷进行了加权处理,使得高频集中的试题在知识点和难度上的关联更加突出,便于在自动组卷时更科学地评价试卷.     

基于大数据背景下的企业生态系统架构研究

随着全球网络技术与移动通信设备的融合发展,“大数据”时代已经引起社会各界的重点关注。苹果、三星、华为、IBM、微软、腾讯等国际知名企业都开始建构出“大数据”时代的企业生态系统。本文将对“大数据”时代的企业生态系统的演化和建构进行深入分析。