Instructions for Authors

1.Aims,The provision of low carbon energy to our society is a key issue at the heart of sustainable development of global energy supply.The Global Energy Interconnection(GEI)publishes original research on theories and developments as well practical applications on principles of large scale low carbon energy generation,transmission,distribution&storage technologies,global energy interconnection&system developments,global energy policy and energy market operations,global climate changes&environmental impacts,global energy transition strategies and global energy governance.

Provision of Preconception Care by Midwives, Nurses and Doctors at Ndola Teaching Hospital in Ndola District, Zambia

Background: The goal of preconception care is to improve the outcome of a mother’s pregnancy and childbirth. Nevertheless, in most developing nations;Zambia included, there are still issues with implementation of preconception care. Therefore, the aim of this study was to establish the provision of preconception care by midwives, nurses and doctors at Ndola Teaching Hospital in Zambia. Methods: A concurrent embedded mixed methodology utilising a descriptive explorative study design, where 107 respondents were randomly selected using the lottery technique for quantitative part and two focused group discussions for qualitative part of the study was used. A self-administered questionnaire was used to collect quantitative data and a focus group discussion guide was used for the focus group discussions. Statistical Package of Social Sciences version 26 with significance set at 0.05 and at 95% confidence level and thematic analysis were used for data analysis. Results: 75% of the respondents in this study were not providing preconception care and only 25% of respondents were providing preconception care;however, this was provided randomly because there were no guidelines to follow. Among the respondents, 81.3% had medium knowledge, 70.1% had good practices and 92.5% had positive attitudes towards preconception care. Further analysis showed that the association between preconception care and knowledge, practices and attitudes was not statistically significant (p = values 0.336;0.344;1.000 respectively). Multivariate logistic regression revealed that participants with high knowledge were five times more likely to provide preconception care (OR = 5.00, CI = 0.42 - 59.7, P = 0.203). Generally, all the participants acknowledged that preconception care was an important package that could prevent maternal and child morbidities and mortalities. Conclusions: The study revealed that most of the respondents were not providing preconception care. Provision of preconception was done by a small fraction of the respondents and it was done in an unorderly manner due to lack of set standards and guidelines. Despite medium levels of knowledge and generally good practices and positive attitudes towards preconception care, its random provision indicates a need for established standards to enhance maternal and child health outcomes.

Comparative Performance Measurement of the Pareto Optimal Combination and Multi-Objective Combination Models for Controller Placement in Software-Defined Networks

The evolution of the current network has challenges of programmability, maintainability and manageability, due to network ossification. This challenge led to the concept of software-defined networking (SDN), to decouple the control system from the infrastructure plane caused by ossification. The innovation created a problem with controller placement. That is how to effectively place controllers within a network topology to manage the network of data plane devices from the control plane. The study was designed to empirically evaluate and compare the functionalities of two controller placement algorithms: the POCO and MOCO. The methodology adopted in the study is the explorative and comparative investigation techniques. The study evaluated the performances of the Pareto optimal combination (POCO) and multi-objective combination (MOCO) algorithms in relation to calibrated positions of the controller within a software-defined network. The network environment and measurement metrics were held constant for both the POCO and MOCO models during the evaluation. The strengths and weaknesses of the POCO and MOCO models were justified. The results showed that the latencies of the two algorithms in relation to the GoodNet network are 3100 ms and 2500 ms for POCO and MOCO respectively. In Switch to Controller Average Case latency, the performance gives 2598 ms and 2769 ms for POCO and MOCO respectively. In Worst Case Switch to Controller latency, the performance shows 2776 ms and 2987 ms for POCO and MOCO respectively. The latencies of the two algorithms evaluated in relation to the Savvis network, compared as follows: 2912 ms and 2784 ms for POCO and MOCO respectively in Switch to Controller Average Case latency, 3129 ms and 3017 ms for POCO and MOCO respectively in Worst Case Switch to Controller latency, 2789 ms and 2693 ms for POCO and MOCO respectively in Average Case Controller to Controller latency, and 2873 ms and 2756 ms for POCO and MOCO in Worst Case Switch to Controller latency respectively. The latencies of the two algorithms evaluated in relation to the AARNet, network compared as follows: 2473 ms and 2129 ms for POCO and MOCO respectively, in Switch to Controller Average Case latency, 2198 ms and 2268 ms for POCO and MOCO respectively, in Worst Case Switch to Controller latency, 2598 ms and 2471 ms for POCO and MOCO respectively, in Average Case Controller to Controller latency, 2689 ms and 2814 ms for POCO and MOCO respectively Worst Case Controller to Controller latency. The Average Case and Worst-Case latencies for Switch to Controller and Controller to Controller are minimal, and favourable to the POCO model as against the MOCO model when evaluated in the Goodnet, Savvis, and the Aanet networks. This simply indicates that the POCO model has a speed advantage as against the MOCO model, which appears to be more resilient than the POCO model.

Tree-based ecosystem services supply and multifunctionality of church forests and their agricultural matrix near Lake Tana,Ethiopia

Ecosystem services(ES)are the connection between nature and society,and are essential for the well-being of local communities that depend on them.In Ethiopia,church forests and the surrounding agricultural matrix supply numerous ES.However,the ES delivered by both land use types have not yet been assessed simultaneously.Here we surveyed both church forests and their agricultural matrices,aiming to quantify,compare and unravel the drivers underlying tree-based ES supply,density and multifunctionality.We found that almost all church forests and half of the agricultural matrices provided high ES densities.ES multifunctionality was higher in the agricultural matrices,suggesting that people deliberately conserve or plant multifunctional tree species.Furthermore,the supply of all categories of ES was positively correlated with church forest age(p-value<0.001)in the agricultural matrix,while the extent of church forest was positively correlated with the density of all categories ecosystem services score in the church forests(p-value<0.001).Our results can be used to prioritize conservation efforts at sites that provide high levels of ES supply,ES density and ES multifunctionality,and to prioritize restoration efforts at sites with low levels thereof.

Instructions for Authors

1.Aims The provision of low carbon energy to our society is a key issue at the heart of sustainable development of global energy supply.The Global Energy Interconnection(GEI)publishes original research on theories and developments as well practical applications on principles of large scale low carbon energy generation,transmission,distribution&storage technologies,global energy interconnection&system developments,global energy policy and energy market operations,global climate changes&environmental impacts,global energy transition strategies and global energy governance.

Instructions for Authors

1.Aims The provision of low carbon energy to our society is a key issue at the heart of sustainable development of global energy supply.The Global Energy Interconnection(GEI)publishes original research on theories and developments as well practical applications on principles of large scale low carbon energy generation,transmission,distribution&storage technologies,global energy interconnection&system developments,global energy policy and energy market operations,global climate changes&environmental impacts,global energy transition strategies and global energy governance.

Instructions for Authors

1.Aims The provision of low carbon energy to our society is a key issue at the heart of sustainable development of global energy supply.The Global Energy Interconnection(GEI)publishes original research on theories and developments as well practical applications on principles of large scale low carbon energy generation,transmission,distribution&storage technologies,global energy interconnection&system developments,global energy policy and energy market operations,global climate changes&environmental impacts,global energy transition strategies and global energy governance.

Instructions for Authors

1.Aims,The provision of low carbon energy to our society is a key issue at the heart of sustainable development of global energy supply.The Global Energy Interconnection(GEI)publishes original research on theories and developments as well practical applications on principles of large scale low carbon energy generation,transmission,distribution&storage technologies.

Failure Prediction for Scientific Workflows Using Nature-Inspired Machine Learning Approach

Scientific workflows have gained the emerging attention in sophisti-cated large-scale scientific problem-solving environments.The pay-per-use model of cloud,its scalability and dynamic deployment enables it suited for executing scientific workflow applications.Since the cloud is not a utopian environment,failures are inevitable that may result in experiencingfluctuations in the delivered performance.Though a single task failure occurs in workflow based applications,due to its task dependency nature,the reliability of the overall system will be affected drastically.Hence rather than reactive fault-tolerant approaches,proactive measures are vital in scientific workflows.This work puts forth an attempt to con-centrate on the exploration issue of structuring a nature inspired metaheuristics-Intelligent Water Drops Algorithm(IWDA)combined with an efficient machine learning approach-Support Vector Regression(SVR)for task failure prognostica-tion which facilitates proactive fault-tolerance in the scheduling of scientific workflow applications.The failure prediction models in this study have been implemented through SVR-based machine learning approaches and the precision accuracy of prediction is optimized by IWDA and several performance metrics were evaluated on various benchmark workflows.The experimental results prove that the proposed proactive fault-tolerant approach performs better compared with the other existing techniques.

Impact of Mandatory Provisions on the Validity of Juristic Acts: A Path for Legal Policy Analysis

Contrary to the approach in judicial practice,Paragraph 1,Article 153,of the Civil Code of the People’s Republic of China,as a rule of invalidity for violating mandatory provisions,does not adopt a dichotomy towards mandatory provisions with effectiveness and administrative characteristics,yet it maintains the legislative philosophy of differentiation.It leaves unspecified whether mandatory provisions that do not explicitly render a juristic act invalid impact the act’s validity,entrusting this determination to the discretion of judges on a case-by-case basis.When judges,under the authority of Paragraph 1,Article 153 of the Civil Code,explore the normative intent of mandatory provisions to assess their effect on the validity of juristic acts,they should engage in legal policy analysis centered on consequence-based argumentation to overcome the limitations of norm typological analysis.This analysis employs a reasoning model predicated on the normative purpose,utilizing a consequencefocused interpretative approach for formulating and arguing propositions of rules applicable to pending cases,thereby arriving at case-specific conclusions.Since the invalidation of juristic acts serves as an auxiliary regulatory tool for the state economy and society,a consequence-oriented interpretation needs to be based on the idea of mutual instrumentalization of public and private laws.This entails predicting the outcomes of negating the validity of a juristic act in industrial regulatory scenarios and assessing these outcomes within the framework of public and private regulatory instruments.

美国建筑抗震设计的法规体系与设计地震动的确定

本文论述了美国建筑抗震设计法规体系发展演变过程及其代表性的规范、标准与技术文档;分析了美国当前建筑法规中设计地震动参数的重要技术见解,设计地震动的不同层次与作用,基于目标风险的最大考虑地震概念等技术的进展,同时,也总结了美国抗震设计相关法规中设计地震动确定的基本规定。本文旨在从美国庞大复杂的建筑设计法规体系中,梳理出清晰的建筑抗震设计的法规体系脉络与设计地震动的要求,为我国建筑抗震设计中设计地震动的相关研究提供参照。

无盘系统在计算机实验室管理中的应用

在学校的计算机实验室管理中,计算机软件安装、升级和维护是一件繁杂的事情。快速而易用的无盘系统是网络技术的一个重要分支,可以大大降低计算机软件安装、升级和维护的成本。BXP无盘和锐起无盘是无盘系统领域中最具代表性的两个技术产品,速度和稳定性好,功能强大。

Provisioning Services与XenApp联合组建局域网应用环境的研究

Citrix公司推出的基于应用流技术的Provisioning Services软件可以实现客户端通过PXE技术获取服务端采用VDisk磁盘存放的操作系统镜像文件,实现无盘启动;而同公司的基于应用虚拟化技术的XenApp软件则可以实现瘦客户端对服务器端所发布程序的访问。将两者相互结合来组建局域网应用环境,不但可以节省软硬件成本,而且对局域网络环境的管理也变得更加轻松和安全。此外还可以指定客户端可运行的应用程序,对服务器端的访问也不仅限于局域网内部。

可编程的网络——软件定义网络

本文描述了软件定义网络(SDN)的需求、概念及关键技术,重点分析了SDN的网络结构、OpenFlow模型和OpenFlow交换机。最后,讨论了SDN的应用。

可编程的网络——软件定义网络(续)

本文描述了软件定义网络(SDN)的需求、概念及关键技术,重点分析了SDN的网络结构、OpenFlow模型和OpenFlow交换机。最后,讨论了SDN的应用。

Joint optimization of maintenance inspection and spare provisioning for aircraft deteriorating parts

With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.

Adaptive Service Provisioning for Mobile Edge Cloud

A mobile edge cloud provides a platform to accommodate the offloaded traffic workload generated by mobile devices.It can significantly reduce the access delay for mobile application users.However,the high user mobility brings significant challenges to the service provisioning for mobile users,especially to delay-sensitive mobile applications.With the objective to maximize a profit,which positively associates with the overall admitted traffic served by the local edge cloud,and negatively associates with the access delay as well as virtual machine migration delay,we study a fundamental problem in this paper:how to update the service provisioning solution for a given group of mobile users.Such a profit-maximization problem is formulated as a nonlinear integer linear programming and linearized by absolute value manipulation techniques.Then,we propose a framework of heuristic algorithms to solve this Nondeterministic Polynomial(NP)-hard problem.The numerical simulation results demonstrate the efficiency of the devised algorithms.Some useful summaries are concluded via the analysis of evaluation results.

The Revision of Aluminum-containing Food Additive Provisions in China

The aim of this study was to revise the provisions for aluminum-containing food additives in GB 2760-2011 （The National Food Safety Standard for Use of Food Additives）, in order to reduce aluminum exposure among the Chinese population. According to the latest risk assessment results of JECFA and China on aluminum and the actual use of aluminum-containing food additives in certain products, the aluminum-containing food additive-related provisions in GB 2760-2011 were revised. Those revisions included narrowing down the applicable food categories and adjusting the maximum use level of aluminum potassium sulfate and aluminum ammonium sulfate, repealing nine aluminum-containing food additives in puffed food and repealing the use of sodium aluminum phosphate, sodium aluminosilicate and starch aluminum octenylsuccinate in all food.

Finite element modeling assumptions impact on seismic response demands of MRF-buildings

Recent seismic events have raised concerns over the safety and vulnerability of reinforced concrete moment resisting frame ＂RC-MRF＂ buildings. The seismic response of such buildings is greatly dependent on the computational tools used and the inherent assumptions in the modelling process. Thus, it is essential to investigate the sensitivity of the response demands to the corresponding modelling assumption. Many parameters and assumptions are justified to generate effective structural finite element（FE） models of buildings to simulate lateral behaviour and evaluate seismic design demands. As such, the present study focuses on the development of reliable FE models with various levels of refinement. The effects of the FE modelling assumptions on the seismic response demands on the design of buildings are investigated. the predictive ability of a FE model is tied to the accuracy of numerical analysis; a numerical analysis is performed for a series of symmetric buildings in active seismic zones. The results of the seismic response demands are presented in a comparative format to confirm drift and strength limits requirements. A proposed model is formulated based on a simplified modeling approach, where the most refined model is used to calibrate the simplified model.

Spatial matching and flow in supply and demand of water provision services: A case study in Xiangjiang River Basin

Global climate change and increased human consumption have aggravated the uneven spatiotemporal distribution of watershed water resources, affecting the water provision supply and demand state. However, this problem has often been ignored. The present study used the Xiangjiang River basin(XRB) as the study area, and the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST) model, demand quantification model,supply–demand ratio, and water flow formula were applied to explore the spatial heterogeneity, flow, and equilibrium between water supply and demand. The results demonstrated significant spatial heterogeneity in the upstream, midstream, and downstream regions.The areas of water shortage were mainly located the downstream of the Changsha–Zhuzhou–Xiangtan urban agglomeration, and the Hengyang basin was the most scarcity area. Affected by terrain gradients and human needs, water flow varied from-16.33 × 10^(8) m^(3) to 13.69 × 10^(8) m^(3)from the upstream to the downstream area, which provided a possibility to reduce spatial heterogeneity. In the future, measures such as strengthening water resource system control,sponge city construction, and dynamic monitoring technology should be taken to balance the supply and demand of water in different river sections of the basin. This study can provide references for regulating water resources allocation in different reaches of the basin.