Potential applications of phase change materials in concrete technology

In internal curing, pre-wetted lightweight aggregates (LWA) serve as internal reservoirs to supply the extra water needed by the cementitious and pozzolanic components of the concrete during their hydration processes. Due to their porous nature and reasonably high absorption capacity, the LWA can also be filled with other materials, such as phase change materials (PCMs). In this paper, three potential applications of PCM-filled LWA in concrete technology are presented. In addition to the previously explored application of increasing the energy storage capacity of concrete in residential and commercial construction by using a PCM with a transition temperature near room temperature, applications for higher and lower temperature PCMs also exist. In the former case, a PCM can be used to reduce the temperature rise (and subsequent rate of temperature decrease) of a large concrete section during (semi)adiabatic curing, to minimize thermal cracking, etc. In the latter case, a PCM can perhaps reduce the number or intensity of freeze/thaw cycles experienced by a bridge deck or other concrete exposed to a winter environment. In this paper, these latter two applications are preliminarily explored from both experimental and modeling viewpoints.     

Effect of Magnetotactic bacteria on the susceptibility in Chinese loess–paleosol sequences

A simulated experiment of Magnetotactic bacteria (MB) effect on susceptibility in the samples from the 5th to 6th loess layers (L₅–S₅–L₆) in Xifeng and Duangjiapo sections was performed. It is demonstrated that MB can increase the susceptibility of the samples and promote newly produced magnetic minerals from paleosol layers under the suitable condition. The tiny magnetic particles and arranged as a chain in the minerals less than 30 μm were found in the paleosol sample of Duangjiapo section.     

Chloride ingress data from field and laboratory exposure – Influence of salinity and temperature

Marine exposure conditions provide an aggressive environment for reinforced concrete structures, mainly due to the occurrence of chloride-induced reinforcement corrosion. There are several influencing factors, but despite a lot of research little is known about the influence from variations in the exposure conditions. Therefore an exposure programme has been made, where concrete specimens, made from one single concrete composition, have been exposed at 12 marine locations around the world, along with a parallel study under laboratory conditions. The specimens have been constantly submerged during the exposure to get well-defined exposure conditions. The purpose was to get a quantitative measure of how different exposure conditions influence the durability of reinforced concrete, measured in terms of chloride ingress into the concrete. The results indicate that the exposure conditions (salinity and temperature of seawater), as expected, influenced the chloride ingress. This is further analysed and discussed in the paper.     

Machine-learning paradigms for selecting ecologically significant input variables

Harmful algal blooms, which are considered a serious environmental problem nowadays, occur in coastal waters in many parts of the world. They cause acute ecological damage and ensuing economic losses, due to fish kills and shellfish poisoning as well as public health threats posed by toxic blooms. Recently, data-driven models including machine-learning (ML) techniques have been employed to mimic dynamics of algal blooms. One of the most important steps in the application of a ML technique is the selection of significant model input variables. In the present paper, we use two extensively used ML techniques, artificial neural networks (ANN) and genetic programming (GP) for selecting the significant input variables. The efficacy of these techniques is first demonstrated on a test problem with known dependence and then they are applied to a real-world case study of water quality data from Tolo Harbour, Hong Kong. These ML techniques overcome some of the limitations of the currently used techniques for input variable selection, a review of which is also presented. The interpretation of the weights of the trained ANN and the GP evolved equations demonstrate their ability to identify the ecologically significant variables precisely. The significant variables suggested by the ML techniques also indicate chlorophyll-a (Chl-a) itself to be the most significant input in predicting the algal blooms, suggesting an auto-regressive nature or persistence in the algal bloom dynamics, which may be related to the long flushing time in the semi-enclosed coastal waters. The study also confirms the previous understanding that the algal blooms in coastal waters of Hong Kong often occur with a life cycle of the order of 1–2 weeks.     

探索行动导向教学法在网络架构课程教学改革中的应用

技工学校是以技术型人才培养为目的的学生能力养成和技能操作的教育基地,为确保人才培养质量,学校需要加强对市场形势的把握和教学改革的控制。行动导向教学法是目前广泛应用于技校和职校教学课堂的、有较好实际作用的教学方法,文章以行动导向教学法为重点,以配置交换机实现VLAN学习任务为案例,在教学方法和手段等几个方面讨论了行动导向教学法在网络架构课程教学改革中的研究与实践。     

基于工作流导向的“网络信息安全”实训教材建设

针对"网络信息安全"教材建设的现状进行分析,提出建设基于工作流导向的任务式实训模式教材的必要性,并从教材的指导思想、整体结构、内容结构及其特色等方面进行了阐述。实践证明,该新型教材的建设和使用能够激发学生学习网络安全知识的兴趣,提升动手能力,有效提高教学质量和效率。     

高素质人才加入公务员队伍的制约因素和对策研究

治国重在治吏,善治来于"善吏",政府的社会作用是通过全体公务员的有效工作体现出来。随着我国公务员制度的逐步完善,公务员的素质已有所提高,但高素质人才占公务员总体的比例仍然不高,这与我国的人才外流、公务员制度运行及人才服务体系不健全等现象也有一定关系。本文通过对我国公务员队伍现状的分析,指出了阻碍高素质人才加入公务员队伍的原因,并相应地提出了吸引和激励更多高素质的人才加入到公务员队伍对策。     

高速公路收费站车辆能耗研究

车辆通过高速公路收费站时,需要减速或停车缴费,当车辆较多时,容易形成排队,产生大量延误,大大削弱了车辆的运行效率,增加了车辆的能耗,同时使得车辆尾气的排放量增加,严重污染了环境。本文使用排队论知识对收费站车辆排队与疏散情况进行分析,减少车辆的排队等候时间和驶离站口所需时间,以达到减少行车能耗的目的。最后,通过一个实例给出几种收费方式下的能耗,并给出了相应的分析和建议,可为高速公路收费方式和能耗研究提供一定的参考。