MODELS OF THE SPATIAL EVOLUTION OF MULTI-PLANT ENTERPRISES

Since the 1970s, the studies on the geography of enterprise have become increasingly concerned with the spatial evolution of an enterprises in the West developed countries. However, little attention has so far been given to the spatial evolution of an enterprise in China. With China's ongoing economy and political reforms, a number of fundamental changes of enterprise behavior have occurred. These changes have certainly important influences on the evolution of industrial location. Therefore, there is a need for examining the spatial evolution of an enterprise in China. The purpose of the paper is to review the mapjor models of both the growth,and associated spatial evolution of an enterprise, with an illustrative case study of the HeaVy Automobile Enterprise Group of China. The paper is organized by three parts. The first examines the spoilal groWth and location adjustment of multi-plant enterprise. The second reviews mapjor models of the spatial evolution of an enterprise. And the third analyzes the spatial evolution, over a period of time, of a representative sample of the Heavy Automobile Enterprise Group of China, and illustrates the findings with case studies. It is suggested that the models of spatial evolution of an enterprise would provide more evidence about micro-mechanism for evolution of micro- regional economic systems.

Using Stochastic Colored Petri nets for Designing Multi-Purpose Plants

Designing of a multi-purpose plant as one of the well-known manufacturing systems is more challenging than other manufacturing systems. This paper applies a stochastic colored Petri net (CPN) to design and analyze multi-purpose plants. A simple approach is proposed to determine the utilization of shared resources and to reduce the equipment’s idle times. Three scenarios are presented to describe the proposed model. Generally, according to desire of a decision maker, different scenarios can be considered in the model to achieve to the expected design or plant configuration. The main characteristics of the proposed model are flexibility, the easiness of practical application and the simulation of the model in an easy way.

Numerical and Experimental Study of a Multi-Generation Desalination Power Plant

The demand for more efficient power generation is not only a prominent subject for environmental reasons but for economic reasons as well. Continuing growth in population contributes to more and more consumption of fresh water, demanding less expensive desalination production, especially in the regions with little or no natural fresh water. Multigeneration desalination power plants may provide solutions to these issues through advanced and efficient designs that are capable of supplying fresh water and power to remote or arid regions of the world. This paper examines the flexibility and versatility of multigeneration systems to showcase the myriad of combinations that are available to accommodate any specific application. It also proposes a specific design for a multi-stage flash desalination system that is powered directly by the exhaust gases of a natural gas micro-turbine capable of producing around 1 MW of electrical power. The performance characteristics, the fresh water produced per kW and the overall plant efficiency, are numerically investigated and compared with previous designs that were analyzed on a larger scale. It is determined that the multigeneration system can produce 56,891 gallons of fresh water per day and an estimated 4.07 tons of salt per day and that a small scale multi-generation desalting systems is feasible.

Research on soil multi-media environmental pollution around a Pb-Zn mining and smelting plant in the karst area of Guangxi Zhuang Autonomous Region,Southwest China

The method of principal component analysis was applied to systematical research on the soil multi-media environment, including soil, surface water, ground water, waterbody sediment and agricultural crops, as well as pollution-inducing wastewater, mullock (or waste ore) and slag in the periphery of a large-sized Pb-Zn mining and smelting plant in a karst area of Guangxi Zhuang Autonomous Region. The results revealed that soils in the area studied have been heavily polluted by Cd, Zn, Pb and Hg, and the levels of these metals in the samples of agricultural crop greatly exceed the standards. The above-mentioned pollutants exist in all soil-multi-media environments. The mullock, slag, wastewater, surface water, ground water, soil, and agricultural crops constitute a composite ecological chain. Therefore, the improper disposal of mullock and slag, and the use of polluted wastewater for agricultural irrigation are the main causes of soil pollution. Heavy metals in the soil have three transition progresses: point (improved soil with slag, ground water inflow plot), linear (river transition) and non-point transition (regional pollution by slag) patterns, and the tailing yard is the most important locus for heavy metals to release into the environment.

A Multi-agent Framework of an Integrated Plant Maintenance System

Based on systematic analysis, an Integrated Plant Maintenance System (IPMS)is proposed in this paper to cope with challenges in plant maintenance. The characteristics of theIPMS are summarized and the necessity of its modeling is set forth. Based on the analysis andcomparison among structured, object-oriented and multi-agent modeling frameworks, a multi-agentmodeling framework is selected in this paper as a theoretical guidance and together with the Troposmethod for modeling, the system model of an integrated plant maintenance system is constructed. Thesystem model developed in this paper provides a guidance template for the Baling company in itsstepwise implementation of the IPMS.

铁线莲‘Multi-Blue’体细胞胚诱导和植株再生

以铁线莲品种‘Multi-Blue’的茎尖为外植体,1/2MS为基本培养基,进行胚性愈伤组织和体细胞胚的诱导及植株再生条件的选择。结果表明:茎尖外植体在1/2MS+TDZ(1.0 mg/L)+NAA(0.5 mg/L)+2%蔗糖+0.7%琼脂的固体培养基中培养时可形成淡黄色块状至颗粒状愈伤组织,经继代培养后可逐渐形成胚性愈伤组织;体细胞胚诱导以1/2MS+TDZ(0.2 mg/L)+IBA(0.1 mg/L)+ABA(0.3 mg/L)+CH(0.5 g/L)为佳,诱导率可达96%;而适宜的体细胞胚萌发培养基为1/2MS+6-BA(0.2 mg/L)+IBA(0.05 mg/L)。体胚再生植株经驯化后,移栽成活率可达80%以上。

Level of detail technique for plant models

Realistic modelling and interactive rendering of forestry and landscape is a challenge in computer graphics and virtual reality.Recent new developments in plant growth modelling and simulation lead to plant models faithful to botanical structure and development,not only representing the complex architecture of a real plant but also its functioning in interaction with its environment.Complex geometry and material of a large group of plants is a big burden even for high performances computers,and they often overwhelm the numerical calculation power and graphic rendering power.Thus,in order to accelerate the rendering speed of a group of plants,software techniques are often developed.In this paper,we focus on plant organs,i.e.leaves,flowers,fruits and inter-nodes.Our approach is a simplification process of all sparse organs at the same time,i.e.,Level of Detail(LOD),and multi-resolution models for plants.We do explain here the principle and construction of plant simplification.They are used to construct LOD and multi-resolution models of sparse organs and branches of big trees.These approaches take benefit from basic knowledge of plant architecture,clustering tree organs according to biological structures.We illustrate the potential of our approach on several big virtual plants for geometrical compression or LOD model definition.Finally we prove the efficiency of the proposed LOD models for realistic rendering with a virtual scene composed by 184 mature trees.

pLoc_Deep-mPlant: Predict Subcellular Localization of Plant Proteins by Deep Learning

Current coronavirus pandemic has endangered mankind life. The reported cases are increasing exponentially. Information of plant protein subcellular localization can provide useful clues to develop antiviral drugs. To cope with such a catastrophe, a CNN based plant protein subcellular localization predictor called “pLoc_Deep-mPlant” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 95% and its local accuracy is about 90%?-?100%. Both have substantially exceeded the?other existing state-of-the-art predictors. To maximize the convenience for most?experimental scientists, a user-friendly web-server for the new predictor has been established?at?http://www.jci-bioinfo.cn/pLoc_Deep-mPlant/, by which the majority of experimental?scientists can easily obtain their desired data without the need to go through the?mathematical details.

Determination of rice panicle numbers during heading by multi-angle imaging

Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have investigated automated rice panicle counting. This paper describes a novel method for automatically and nonintrusively determining rice panicle numbers during the full heading stage by analyzing color images of rice plants taken from multiple angles. Pot-grown rice plants were transferred via an industrial conveyer to an imaging chamber. Color images from different angles were automatically acquired as a turntable rotated the plant. The images were then analyzed and the panicle number of each plant was determined. The image analysis pipeline consisted of extracting the i2 plane from the original color image, segmenting the image, discriminating the panicles from the rest of the plant using an artificial neural network, and calculating the panicle number in the current image. The panicle number of the plant was taken as the maximum of the panicle numbers extracted from all 12 multi-angle images. A total of 105 rice plants during the full heading stage were examined to test the performance of the method. The mean absolute error of the manual and automatic count was 0.5, with 95.3% of the plants yielding absolute errors within ± 1. The method will be useful for evaluating rice panicles and will serve as an important supplementary method for high-throughput rice phenotyping.

种植技术和种植密度对吉花2号主要农艺性状和产量的影响

研究不同种植技术和种植密度对吉林省多粒型花生吉花2号主要农艺性状和产量的影响,筛选适宜吉林省生态环境的种植技术和最佳种植密度,完善吉花2号配套高效栽培技术。采用2种种植技术及5个种植密度(1.79×10^(5)、2.02×10^(5)、2.30×10^(5)、2.69×10^(5)、3.23×10^(5)株/hm^(2)),研究特定时期花生光合指标及产量变化。结果显示,吉花2号采用小垄双行种植技术、种植密度为2.02×10^(5)株/hm^(2)时生育期最短,较双粒穴播种植技术生育期提前1~2 d;植株的株高最小,有利于地下部干物质积累;叶面积系数最大,总光合势最大;产量最高(3651.15 kg/hm^(2)),较双粒穴播种植技术增产10.17%。小垄双行种植技术在不同密度下,吉花2号产量都高于双粒穴播种植技术。因此,小垄双行种植技术在生产上应大力推广。

同时测定亚麻荠植株中酚酸和黄酮含量的方法研究

建立一种采用液相色谱法同时测定亚麻荠植株中8种酚酸和黄酮化合物含量的方法,并探讨亚麻荠植株醇提物的体外抗氧化活性。试验确定采用体积分数75%乙醇回流提取样品,选用Angilent Eclipse XDB plus C_(18)柱为色谱柱。结果表明:8种化合物的标准曲线回归方程线性关系良好,相关系数均大于0.999;8种化合物的加标回收率为95.26%~102.61%,建立的方法可以对不同产地的亚麻荠植株样品进行区分。抗氧化试验表明,亚麻荠植株醇提取物对羟基自由基与DPPH自由基具有较好的清除能力。

基于1DCNN融合多源表型数据的杨树干旱胁迫评估方法

目前关于不同杨树品种抗旱性的研究主要集中在利用传统测量方法获取形态结构和生理生化表型参数进而分析杨树的抗旱性,依据多源成像传感器提取的表型参数指标确定杨树干旱胁迫等级的方法较为少见。为了阐明杨树耐旱的表型机制、筛选抗旱性树种和明确杨树抗旱等级,本文以杨树不同性别的喜水和耐旱品种为研究对象,在杨树苗期进行梯度干旱胁迫处理,通过热红外以及RGB多源成像传感器获取杨树冠层温度参数与颜色植被指数表型数据,并建立基于1DCNN的多任务分类模型划分杨树苗期品种抗旱等级与干旱胁迫等级等2个分类任务,探究杨树性别与生长时间对杨树干旱胁迫响应机制的影响。结果表明,以27组数据变量降维后的4个特征作为模型变量,与传统机器学习算法SVM、RF、XGBoost相比,本文提出的1DCNN多任务分类模型在杨树品种抗旱等级分类与单株干旱胁迫等级分类2个任务中的模型分类精度皆达到最优,分类准确率分别为81.8%和62.3%;引入杨树的性别和生长时间后共6个特征作为模型的输入变量后,杨树苗期品种抗旱等级与干旱胁迫等级的分类精度显著提高,1DCNN多任务分类模型在2个分类任务中的准确率分别达到93.5%与76.6%,模型分类准确率分别提高11.7个百分点与14.3个百分点。研究结果表明,通过热红外与RGB成像传感器获取多源表型数据,并建立1DCNN多任务分类模型对实现杨树干旱胁迫等级评估的可行性,同时表明杨树的性别和生长时间作为模型输入变量能够有效提升模型的分类精度,可为筛选杨树抗旱性品种提供新的思路与方法。

基于Plant Simulation的烟草柔性分拣系统仿真与优化

针对烟草物流配送中心场地限制和分拣效率低下等问题,根据柔性分拣系统的工作原理及流程,运用Plant Simulation仿真软件建立烟草柔性分拣系统模型,设计了条烟自动分拣的虚拟托盘算法。通过仿真分析得到限制其分拣效率的瓶颈工位,利用添加缓存区和增加码垛工位的优化方法对分拣系统进行初步优化,并且从Experiment Manager模块中的单因子多水平试验方法确定了最优缓存区容量。仿真结果表明该优化方法显著提高了分拣效率,使其达到8866.08条/h,是优化前的1.39倍,且缩短了配送时间,能够很好地满足烟草物流配送中心的分拣要求。

混合式抽水蓄能电站群容量计算研究Ⅱ:多尺度嵌套容量计算模型及实例

基于流域梯级水电站增建混合式抽水蓄能电站(简称混蓄电站),对保障新型电力系统安全稳定运行、促进新能源大规模发展和消纳具有重要意义。研究提出基于多尺度嵌套调度模型的混蓄电站群容量计算模型,该模型嵌套含混蓄电站的梯级水电站短期调峰模型、考虑短期调峰与综合利用供水任务的梯级水电站中长期优化调度模型两大核心模块;此外,针对该容量计算模型的高维特征,提出基于代理模型思想的求解方法。以黄河上游待规划的大型混蓄电站群为实例,分别计算混蓄电站单独开发、梯级开发、整体开发三种模式下电站装机容量以及抽水调峰效益,并推导理论公式揭示混蓄电站抽发循环效率及抽水时长对电站装机容量的影响机制。实例计算取得的结果:龙羊峡-拉西瓦混蓄电站推荐采用水泵机组+可逆式抽蓄机组形式开发,单独开发模式下,推荐装机160万kW;当其与拉西瓦-尼那混蓄电站梯级开发时,推荐装机205万kW。当混蓄电站设计抽水时长减小时,其装机容量可增加,调峰能力变大,但电站抽水耗电调峰效益不变。拉西瓦-尼那、李家峡-直岗拉卡、公伯峡-苏只混蓄电站推荐装机分别为75万、16万和59万kW。4座混蓄电站整体开发模式下,可用于新能源消纳的抽水调峰电量为年均87.42亿kWh。

Probabilistic Approach of Coastal Defense Against Typhoon Attacks for Nuclear Power Plant

With the global warming and sea level rising, it is widely recognized that there is an increasing tendency of typhoon occurrence frequency and intensity. The defenses code against typhoon attacks for nuclear power plant should be calibrated because of the increasing threat of typhoon disaster and severe consequences. This paper discusses the probabilistic approach of definitions about ＂probable maximum typhoon＂ and ＂probable maximum storm surge＂ in nuclear safety regulations of China and has made some design code calibrations by use of a newly proposed Double Layer Nested Mtdti-objective Probability Model （DLNMPM）.

基于深度强化学习的多能虚拟电厂优化调度

多能虚拟电厂(Multi-Energy VPP,MEVPP)能够聚合电能、热能等多种形式的分布式能源及需求侧灵活性资源。为实现MEVPP的优化调度,文中建立了包含发电单元、制热单元、储能装置以及空调负荷集群、需求响应负荷的MEVPP模型,并面向该模型提出一种基于深度强化学习(Deep Reinforcement Learning, DRL)的优化调度方法,并设计了相应的状态、动作空间与奖励函数。该方法以近端策略优化(Proximal Policy Optimization, PPO)算法为基础,能够根据预测负荷、风/光出力、室外气温等环境信息,对分布式能源和需求侧灵活性资源进行调节,并以最小化运行成本为目标得到MEVPP优化调度策略集。算例结果证明了DRL在MEVPP优化调度中的可行性与策略集的可拓展性。

基于EP-YOLO v8的瓶栽金针菇最优抓取位置定位方法

针对工厂化瓶栽金针菇自动切根过程中,夹持末端因结构设计导致行程固定,进而影响抓取效果甚至切根质量的问题,本文基于YOLO v8(You only look once)构建改进的Enoki-pick_region-YOLO v8(EP-YOLO v8),实现瓶栽金针菇整体及最佳受力区域(关键抓取区域)的精准定位与轮廓提取,保障抓取参数的可靠性。该方法在网络优化基础上,基于最小欧几里得距离(Euclidean distance,ED)构建掩膜关系归属与判断模型,明确金针菇菇体与关键抓取区域掩膜间父子关系并合并优化。通过解析合并前后关键抓取区域的相对位置编码,确定抓取参数并进行坐标转换,为建立末端控制映射模型实现末端机械手运动行程的精确控制提供基础。实验结果表明,本文所提算法的金针菇菇体掩膜识别精确率达99.3%,关键抓取区域掩膜识别精确率达99.6%。同时,对比发现掩膜质量得到了提高,获取的参数抓取区域宽度与实际宽度之间的误差仅为0.7%,抓取参数基本满足抓取条件,能有效实现最优抓取位置的精准识别与定位。

多感官维度下芳香植物对人体健康影响的研究进展

芳香植物是具有香气和可供提取芳香油的栽培植物和野生植物的总称,作为园林植物中的重要种类对人体健康发挥着较大功效。本文将近年来有关芳香植物的多感官研究动态进行整理,从嗅觉、视嗅、听嗅以及视听嗅角度阐述主要研究进展,并对研究成果进行梳理,旨在为芳香植物的深入研究提供理论参考。基于上述文献分析可知,多感官维度下芳香植物的研究已形成较为系统的研究方向,从单一感官维度逐渐向多感官联合维度发展,研究种类也在从单一走向多样化,研究方法与实验指标等也在不断丰富和发展。当前主要研究成果集中于芳香植物的单一嗅觉感官维度,多感官维度下芳香植物对人体健康的影响研究处于起步阶段,并将成为未来研究热点。

基于VPP碳流计算的多目标多时间尺度优化调度

为研究虚拟电厂低碳经济运行策略,以虚拟电厂能流和碳流模型为基础,执行了多目标多时间尺度优化调度。首先,基于碳流走向建立虚拟电厂低碳经济运行的非线性多目标规划模型,并采用归一化法向约束法进行求解。然后,建立了基于动态矩阵控制算法的有限时域优化模型,对日前结果进行跟踪优化和反馈校正,以降低不确定性因素的影响。最后,仿真对比实验验证了所提调度策略能在保证碳流计算精度超过95%的前提下实现虚拟电厂低碳经济运行。

多旋翼植保无人飞机施药研究进展及展望

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