光催化CO_(2)还原成C_(2+)产物催化剂及其反应机理研究进展

传统工业过程,尤其是依赖于煤炭、石油和天然气等化石燃料的生产活动,导致了CO_(2)的高浓度排放。工业烟气中的CO_(2)治理是降低重点行业污染排放、打好污染防治攻坚战的重中之重。近年来,我国在降污减碳方面取得了显著成果。光催化CO_(2)还原技术以直接利用清洁的太阳能和在室温下进行反应等诸多优势,目前广泛应用于CO_(2)资源化利用。在过去的几十年里,研究者致力于提高光催化CO_(2)转化的活性研究。然而,关于提高该过程选择性的研究相对缺乏,特别是关于高价值C_(2+)产品的生成。鉴于当前的研究趋势和新兴技术,首先阐述了目前应用广泛的CO_(2)资源化利用技术并进行了对比分析,接着阐明该反应中C—C偶联的热力学限制、动力学特征、光催化剂表面活化基本原理和机制,进而概述目前可用提高C_(2+)产物选择性的技术,并综述了各技术目前存在的缺点。最后,总结了目前研究现状并指明了现存的问题,并对该领域的未来前景和工业化应用做出了指引。

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.

Intelligent Agent Technologies: The Work Horse of ERP E-Commerce

Agents are the new defacto standard for inclusion in modules of today’s software systems such as ERP systems, mobile applications and operating systems. Agents are an integral part of today’s software design. The question is how do intelligent agents work in the specific area of ERP credit card processing e-commerce models? To answer this question, a specific area of ERP systems will be analyzed: credit card processing for merchants. One specific merchant credit card processor will be specifically investigated: EVO Merchants. This paper will research how exactly does ERP systems interact using Application Programing Interface or “API” specified by a credit card clearing house. Secure Socket Layers or SSL, and XML are discussed and elaborated on specifically how intelligent agents play such a pivotal role in ERP e-commerce systems for credit card processing.

Development of component geographic information systems applying in forest resources management

The history, current situation, and development trend of GIS (Geographic Information System) applied in the forest resources management were discussed in this paper. On the basis of geographic spatial characteristics of forest resources data, a component geographic information system (ComGIS) was developed for forest resources management. The system embeds a GIS ActiveX control MapObjects (Inc. ESRI) on Visual C++ platform. System design, data organization and achieving way were studied and expatiated by taking Xigangzi Forestry Centre as study object. The system has many useful functions,, such as adding and display of various map layers, zoom of map by wheeling mouse, attribute and spatial data querying, map auto roaming, features rendering based on the spatial trait of data, label controlling through attribute data band with vector graph, as well as output of 'Column chart' for showing the result of statistics. At the same time, parts of source codes are attached.

Reliable Scheduling Method for Sensitive Power Business Based on Deep Reinforcement Learning

The main function of the power communication business is to monitor,control and manage the power communication network to ensure normal and stable operation of the power communication network.Commu-nication services related to dispatching data networks and the transmission of fault information or feeder automation have high requirements for delay.If processing time is prolonged,a power business cascade reaction may be triggered.In order to solve the above problems,this paper establishes an edge object-linked agent business deployment model for power communication network to unify the management of data collection,resource allocation and task scheduling within the system,realizes the virtualization of object-linked agent computing resources through Docker container technology,designs the target model of network latency and energy consumption,and introduces A3C algorithm in deep reinforcement learning,improves it according to scene characteristics,and sets corresponding optimization strategies.Mini-mize network delay and energy consumption;At the same time,to ensure that sensitive power business is handled in time,this paper designs the business dispatch model and task migration model,and solves the problem of server failure.Finally,the corresponding simulation program is designed to verify the feasibility and validity of this method,and to compare it with other existing mechanisms.

Fluctuating resources,disturbance and plant strategies:diverse mechanisms underlying plant invasions

This paper examines the hypothesis that non-native plant invasions are related to fluctuating resource availability as proposed by Davis et al. （2000）. I measured relative functional responses of both invasive and native plants to changed resource availability due to nutrient enrichment and rainfall, and to increased disturbance. Data are presented from studies in two contrasting ecosystems. First is a series of glasshouse and field experiments on the invader Hieracium lepidulum and associated invasive and native species in subalpine temperate New Zealand. Second is a field study of invasive and native plant responses to altered disturbance regimes and rainfall from tropical savannas of north eastern Australia. Invaders responded differently from native species to changes in resource availability in both subalpine and tropical studies. However, invaders differed among themselves showing that different species exploit different functional niches to invade their respective habitats. These findings contribute to the contention that the fluctuating resource hypothesis does not provide a universal explanation for plant invasions. The diverse functional responses to increased resource availability among invaders in this and previous studies suggest that the cause of invasion depends on unique combinations of habitat and functional attributes of invaders and native assemblages. Such findings imply that universal predictions of what will happen under climate change scenarios across the globe will be difficult to make.

C-V2X环境下基于队友模型的多智能体通信切换优化

蜂窝车联网(cellular vehicle-to-everything,C-V2X)通信技术是未来智能交通系统(intelligent transportation systems,ITS)的重要组成部分.毫米波(millimeter wave,mmWave)作为C-V2X通信技术的主要载体之一,可以为用户提供高带宽.然而,由于传播距离有限和对遮挡的敏感性,毫米波基站必须密集部署以维持可靠的通信,这使得智能联网车辆(intelligent connected vehicle,ICV)在行驶过程中不得不频繁地进行通信切换,极易造成局部资源短缺,进而导致服务质量低下和用户体验不佳.为了应对这些挑战,每辆ICV被视为一个智能体,并将ICV的通信切换问题建模为一个合作型多智能体博弈问题.为了解决这一问题,提出了一个基于队友模型的合作型强化学习框架.具体来说,首先设计了一个队友模型,用于量化复杂动态环境下智能体之间的相互依赖关系;接着提出了一种动态权重分配方案,生成了队友间的加权互信息,用于混合网络的输入,旨在帮助队友切换到可以提供良好QoS和QoE的基站,以获得高吞吐量和低通信切换频率.在算法训练过程中,设计了一种激励相容训练算法,旨在协调智能体的个体目标与集体目标的一致性,提升通信吞吐量.实验结果显示,提出的方法在不同规模车辆的场景中均展示出了卓越的性能,相较于现有的基于通信基准方法有13.8%~38.2%的吞吐量提升.

Cooperation agreement reached between the Ministry of Land and Resources, Guangdong Province and C

On August 24, 2017, the Ministry of Land and Resources, Guangdong province and CNPC signed in Beijing a Strategic Cooperation Agreement on Promoting the Building of a Pilot Site for Exploring and Exploiting Gas Hydrate in the Shenhu Area of the South China Sea. The conclusion of this agreement will help accelerate the industrial development of gas hydrate in China, and is of great strategic significance to securing the country＇s energy security and optimizing its energy mix.

Agromorphological Characterization of Ginger (Zingiber officinale Rosc., Zingiberaceae) Accessions Grown in Côte d’Ivoire

In C?te d’Ivoire, ginger (Zingiber officinale Rosc.), generally used to make a drink called “Gnamankoudji”, has become an important source of agricultural income diversification. In order to assess the agromorphological diversity of a ginger collection from different regions of C?te d’Ivoire, a survey collection of accessions was carried out in the different production zones of the country. One hundred and eighty-eight ginger accessions were collected in 15 regions and one autonomous district of C?te d’Ivoire. Analysis of variance revealed that all the variables used in this study discriminated between the ginger accessions collected. Principal component analysis revealed morphological variability of 45.931% for the first two components. Ascending Hierarchical Classification was used to classify these accessions into three groups based on fourteen quantitative characters. These three groups were formed independently of collection areas and are characterized by moderate morphological variability. This variability has been structured into three distinct agromorphological groups, with thallus (rhizome) length and width, finger width, secondary finger length and yield in tons per hectare as distinctive characters. This revealed genetic diversity could be exploited in ginger breeding and improvement programs in C?te d’Ivoire.

5G蜂窝车联网(C-V2X)资源分配优化与性能评估

为改善蜂窝车联网(C-V2X)频谱利用效率,提出了一种针对系统下行吞吐量最大化、并保证车对车通讯(V2V)链路连接性的资源分配算法。定义蜂窝车联网信道模型,在最大发射功率、中断概率等约束条件下建立优化模型并对其进行分步求解,采用二分图最佳匹配(KM)算法动态调度信道资源,实现C-V2X通信系统中车辆到路边设施(V2I)下行链路与V2V链路之间动态分配网络资源,最后通过不同交通场景评估算法的优化性能。结果表明:本算法经7次迭代后进入稳态,在保证V2V链路连接性条件下实现了V2I链路资源的优化分配,下行链路频谱效率相较于贪心算法平均提升3.5%以上。

Intelligent Resources Management System Design in Information Centric Networking

Information centric networking(ICN) is a new network architecture that is centred on accessing content. It aims to solve some of the problems associated with IP networks, increasing content distribution capability and improving users' experience. To analyse the requests' patterns and fully utilize the universal cached contents, a novel intelligent resources management system is proposed, which enables effi cient cache resource allocation in real time, based on changing user demand patterns. The system is composed of two parts. The fi rst part is a fi ne-grain traffi c estimation algorithm called Temporal Poisson traffi c prediction(TP2) that aims at analysing the traffi c pattern(or aggregated user requests' demands) for different contents. The second part is a collaborative cache placement algorithm that is based on traffic estimated by TP2. The experimental results show that TP2 has better performance than other comparable traffi c prediction algorithms and the proposed intelligent system can increase the utilization of cache resources and improve the network capacity.

Spatial Availability of Nitrogen and Pesticides in the Surface Layers of Agricultural Soils of Tropical Hydrosystems in the Wet Season: Case of the BéréWatershed in Côte d’Ivoire (West Africa)

The objective of this study was to assess the contribution of the spatial organization of cropping systems and the physicochemical properties of surface layers of the agricultural zones soils in tropical hydrosystems to the spatial availability of nitrogen and pesticides during the wet season, such as the Béré watershed (BW) in C?te d’Ivoire. For this purpose, after mapping the spatial distribution of the BW cropping systems based on the likelihood classification methodology of satellite images of the study area, 27 samples from the 0 - 20 cm horizon of the soil surface layers of the agricultural areas were taken during the wet and agricultural season of the year 2016. The Kjeldahl method has been used to evaluate the total nitrogen concentration and high-performance liquid chromatography (HPLC) chain made it possible for the analysis of pesticide residues in the soil solutions. Geostatistical analysis and processing of spatial data and physicochemical and agrochemical soil parameters revealed that two major agricultural areas stand out in the BW, namely the Béré upstream watershed (BUW) dominated at 32.65% by annual croppings (maize, cotton, rainfed or lowland rice, market gardening, etc.) and the Béré downstream watershed (BDW) by large areas of perennial croppings (cashew nuts, cocoa, etc.), i.e. 21.47%. Agricultural soils in BW are usually of the moderately desaturated ferralitic type with a low acid pH and a quite strong temperature, such as those of tropical soils’ characteristics. However, agricultural soils in the BUW are characterized by higher proportions of sand and coarse sand. The parameters such as total porosity, cation exchange capacity, clay, organic matter, silt, fine silt, coarse silt, and potassium ions, are higher in the soils of the agricultural area of the BDW. Moreover, soils in the agricultural areas of the BUW are less rich in total nitrogen (0.84 g·kg-1) in contrast to those of the BDW (1.2 g·kg-1). On the other hand, the median concentrations of total pesticides remain very high in the BUW (193.80 μg·kg-1) in front of those of the BDW (94.81 μg·kg-1). In addition, the biological family of herbicides was the most notable in BW. The chemical families of triazines (100% detection;79.37 μg·kg-1) are the most important in the agricultural area of the BUW with the very significant presence of active molecules of pesticides such as simazine (92.86% detection;13.17 μg·kg-1). However, in the BDW, urea substitute (100% detection;44.02 μg·kg-1) dominate, including the active substance chlortoluron (84.62% detection;10.12 μg·kg-1). The presence and abundance of nitrogen and pesticides in the soils of the agricultural areas of BW are strongly linked to the intensive use of these agrochemicals in cropping systems in recent decades in West African countries, even though most of the active molecules found are forbidden in several countries, especially in European countries. These are applied to tropical agricultural soils with physicochemical characteristics favorable to their retention in wet weather, as confirmed by the case of BW’s agricultural soils. Therefore, the BW’s water resources present worrying risks of contamination during rainy events that deserve to be assessed and monitored. Hence the need to take mitigating measures to this effect in order to preserve the quality of the environment.

基于翻转课堂的C语言教学资源信息整合方法

基于翻转课堂的C语言教学资源信息整合方法,使教学资源配置均衡,便于教师在C语言教学前、中、后教学资源的管理与应用.利用翻转课堂构建C语言教学资源信息整合体系,资源信息层用于接收由翻转课堂产生并上传的C语言原始和新增教学资源信息,信息资源整合层采用自适应滑动窗口互信息方法提取信息资源层教学资源信息的特征向量,以此为依据,在满足C语言教学资源整合约束关系前提下,以整合后的C语言教学资源信息利用率最大化为目标,用概率整合方法对C语言教学资源信息进行均衡整合,并将整合结果通过资源应用层呈现给教师、学生及管理者使用.结果表明,该方法在窗口宽度为200字节时的信息特征提取效率最佳,整合后的C语言教学资源信息没有重复建设,且具有较好的均衡性和召回性.

基于BP和RBF神经网络的C-V2X无线资源管理

为了提升蜂窝车联网(Cellular Vehicle-to-Everything,C-V2X)资源复用的有效性和降低终端间的干扰,提出通过神经网络对未来时刻车流量的预测辅助无线资源管理方案。依据车载单元(On Board Unit,OBU)与路侧单元(Road Side Unit,RSU)间的车联网消息,获取RSU覆盖区域内各时刻的车流情况,分别采用BP(Back Propagation)神经网络和RBF(Radial Basis Function)神经网络进行短时交通流预测。RSU根据预测结果进行自适应分簇,簇间复用相同资源,簇内进行资源池的划分,RSU覆盖内的OBU在划分的资源池中选择发送资源,从而减少终端间的干扰,并保证热点区域车辆拥有更多的资源。仿真结果表明,在道路交通拥塞的场景下,所提方案的数据包接收率较标准中的方案提升14%,较典型文献方案提升10%,保证了通信的可靠性。

基于分布式反馈的C-V2X碰撞解除与重传机制

蜂窝车联网(Cellular Vehicle-to-Everything,C-V2X)系统中,针对调度算法不合理而造成的资源碰撞问题,提出一种基于分布式反馈的碰撞解除与丢包重传机制。该机制将C-V2X终端视为网络中的分布式节点,在各节点对周围碰撞进行识别的基础上,利用节点间的反馈信息进行碰撞的解除与恢复。首先终端依据设置的条件识别周围发生的碰撞事件,并在其传输中反馈观察到的碰撞事件。然后碰撞终端根据接收的反馈消息更换或保留资源,从而实现碰撞解除和资源协调。最后为了保证信息更新的实时性,解除碰撞的终端将发生碰撞的数据进行重传。仿真结果表明,与3GPP标准方案相比,在严重拥塞(300 veh./km)情况下所提出机制的数据包接收率提升约13%,数据包更新时延降低约200 ms,有利于满足车联网信息交互的高可靠低时延需求。

基于语义相似度匹配的C语言课程教学资源在线检索方法

为提升检索结果的精准性,提出基于语义相似度匹配的C语言课程教学资源在线检索方法,构建并扩展C语言课程教学资源本体,使得教学资源具备计算机可理解的语义,计算资源之间的语义相似度并进行匹配,实现C语言课程教学资源在线检索。实验结果表明,设计方法检索C语言课程教学资源的查准率为96.23%。

Preliminary Diversity Assessment of Lima Beans (<i>Phaseolus lunatus</i>) Cultivated in Côte D’Ivoire

Lima bean is a legume belonging to Fabaceae family cultivated for edible seeds known to generic name of “haricot”. In Côte d’Ivoire, it’s cultivated on small scale in rural zone by local farmers. The main objective of this study was to document and collect local varieties of Lima beans (Phaseolus lunatus) grown in Côte d’Ivoire in order to define efficient strategies for better conservation, preservation and improvement of its genetic resources. Investigations were carried out in seventeen localities of Côte d’Ivoire from November 2018 to September 2020. A total of 433 accessions were collected. Based on seed coat color, nineteen morphological types were identified. The length of seeds is ranged from 10 mm to 23 mm. The width of seeds varies from 7 mm and 15 mm. The 100-Seeds-weight are ranged from 31 g to 120 g. Comparison using analysis of variance (ANOVA) showed a significant difference between the nineteen morphological types of common bean. Two morphological types were observed: large seed cultivars and small seed cultivars. Data showed that the species studied have a good market potential. Thus, their promotion can contribute to the economic well-being of farmers due to their cultural and culinary importance.

基于ArcGIS Engine帽儿山森林多资源管理系统的研建与实现

以C#语言为开发平台,以ArcGIS Engine为开发组件,以帽儿山实验林场的森林资源调查数据和地理信息数据为基础,进行森林多资源管理系统的设计与实现。该系统实现帽儿山实验林场地区森林多种资源信息的查询、分析与决策,其中包括GIS基本功能、专题图的生成、森林灾害管理和伐区采伐管理等功能,最终完成帽儿山实验林场的一个较为完善、专题性强和可扩充的森林多资源管理系统。该系统的研究与实现对帽儿山林场的经营管理及外业调查工作都有一定的实际意义。

基于B/S架构的SCADA系统在水利工程中的应用

在Internet/Intranet环境下开发的基于B/S架构的实时监控系统,可以实现基于网络的远程指挥调度、监控、故障诊断及设备管理等功能。通过对B/S架构的分析,针对基于B/S架构的远程监控系统的数据实时性与网络安全保障进行研究和探讨,并对泵闸站远程监控系统软件的系统建设框架及功能进行介绍。经过实际应用,说明基于B/S架构的SCADA系统可在防汛抗旱及水资源调度中发挥出良好的作用。

Joint Resource Allocation and Coordinated Computation Offloading for Fog Radio Access Networks

The cloud radio access network(C-RAN) and the fog computing have been recently proposed to tackle the dramatically increasing traffic demands and to provide better quality of service(QoS) to user equipment(UE).Considering the better computation capability of the cloud RAN(10 times larger than that of the fog RAN) and the lower transmission delay of the fog computing,we propose a joint resource allocation and coordinated computation offloading algorithm for the fog RAN(F-RAN),which takes the advantage of C-RAN and fog computing.Specifically,the F-RAN splits a computation task into the fog computing part and the cloud computing part.Based on the constraints of maximum transmission delay tolerance,fronthaul and backhaul capacity limits,we minimize the energy cost and obtain optimal computational resource allocation for multiple UE,transmission power allocation of each UE and the event splitting factor.Numerical results have been proposed with the comparison of existing methods.