基于CAPE-OPEN标准的简捷炼油过程建模及常减压蒸馏流程在线模拟

简捷炼油过程模型广泛应用于运行监测、在线计算、实时优化等领域,但大多数模型只是将输入、输出变量进行关联,无法计算出各组分流量组成,难以集成在模拟软件中进行全流程模拟。本研究简化了炼油分离过程,开发了基于CAPE-OPEN标准的简捷炼油塔模型。首先,将炼油过程简化为连续的分离单元,根据实际产品数据校正模型参数,实现某一实际工况流程模拟;其次,将模型参数与实际工况操作变量数据相结合,采用径向基函数插值确定操作变量对模型参数的影响关系,实现多种工况流程模拟;最后,通过常减压蒸馏工业装置实例的3种工况进行验证。结果表明:各工况模拟结果与Aspen计算结果相比,初馏塔塔顶油馏出温度点偏差大多在2%以内,常减压蒸馏塔各侧线油的馏出温度点平均偏差在3%以内;与实际结果相比,平均误差都在5%以内,符合工程允许误差范围要求。所建模型的计算速度快,各塔均在0.2 s左右完成计算,适用于在线生产、调度等。

我国高质量教育资源供给机制创新与路径研究——来自美国“#GoOpen”计划的启示

数字化是当下教育改革的重点,也是未来教育发展的趋势。无论是作为“十四五”规划中的战略举措,还是党的二十大中提出的必然要求,构建数字化教育资源为主体的高质量教育资源体系在当下具有必要性与迫切性。美国#GoOpen计划自实施以来,在教育资源数字化、个性化、均等化三个方面均取得了一定成果。通过对该计划官方文件与政策进行解读,对其内涵与特点进行分析,我国在进行高质量教育资源建设及其供给路径探究过程中应当重视统筹规划,循序渐进,同时完善多重考核与评估机制,结合社会多方力量,保证每个学习者的享有权利,最终走向教育公平,共同发展。

基于YOLO-OpenMax的水声通信信号开集识别方法

水声通信信号调制方式随着技术进步从典型的传统调制方式发展为水声通信机厂商私有开发的新型调制方式,这使得现有的水声通信信号闭集调制识别技术实用性受到制约,但现阶段鲜有研究基于深度学习的水声通信信号调制方式的开集识别方法。针对此现状,提出一种基于YOLO图像检测识别网络和OpenMax模型的开集识别方法。利用YOLOv5网络的输出特点,将传统OpenMax模型的处理方法进行改进,提出一种两步测试方法,实现了在多径信道下的水声通信信号的开集识别。仿真实验表明:在归一化系数为0.5,信噪比等于10 dB条件下的归一化开集识别准确率达到90%以上,实测数据同样验证了本文方法的有效性。

Air-Ground Collaborative Mobile Edge Computing:Architecture,Challenges,and Opportunities

By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.

WPA1 encodes a vWA domain protein that regulates wheat plant architecture

Plant height,spike,leaf,stem and grain morphologies are key components of plant architecture and related to wheat yield.A wheat(Triticum aestivum L.)mutant,wpa1,displaying temperaturedependent pleiotropic developmental anomalies,was isolated.The WPA1 gene,encoding a von Willebrand factor type A(vWA)domain protein,was located on chromosome arm 7DS and isolated by map-based cloning.The functionality of WPA1 was validated by multiple independent EMS-induced mutants and gene editing.Phylogenetic analysis revealed that WPA1 is monocotyledon-specific in higher plants.The identification of WPA1 provides opportunity to study the temperature regulated wheat development and grain yield.

Evolutionary Neural Architecture Search and Its Applications in Healthcare

Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human intervention.Evolutionary algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures.Using multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered efficiently.Furthermore,hardware-accelerated NAS methods can improve the efficiency of the NAS.While existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for NAS.In this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS methods.NAS performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health monitoring.EAs for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare task.Deep neural network has been successfully used in healthcare,but it lacks interpretability.Medical data is highly sensitive,and privacy leaks are frequently reported in the healthcare industry.To solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy protection.Moreover,we also point out future research directions for evolutionary NAS.Overall,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.

Multilevel carbon architecture of subnanoscopic silicon for fast‐charging high‐energy‐density lithium‐ion batteries

Silicon(Si)is widely used as a lithium‐ion‐battery anode owing to its high capacity and abundant crustal reserves.However,large volume change upon cycling and poor conductivity of Si cause rapid capacity decay and poor fast‐charging capability limiting its commercial applications.Here,we propose a multilevel carbon architecture with vertical graphene sheets(VGSs)grown on surfaces of subnanoscopically and homogeneously dispersed Si–C composite nanospheres,which are subsequently embedded into a carbon matrix(C/VGSs@Si–C).Subnanoscopic C in the Si–C nanospheres,VGSs,and carbon matrix form a three‐dimensional conductive and robust network,which significantly improves the conductivity and suppresses the volume expansion of Si,thereby boosting charge transport and improving electrode stability.The VGSs with vast exposed edges considerably increase the contact area with the carbon matrix and supply directional transport channels through the entire material,which boosts charge transport.The carbon matrix encapsulates VGSs@Si–C to decrease the specific surface area and increase tap density,thus yielding high first Coulombic efficiency and electrode compaction density.Consequently,C/VGSs@Si–C delivers excellent Li‐ion storage performances under industrial electrode conditions.In particular,the full cells show high energy densities of 603.5 Wh kg^(−1)and 1685.5 Wh L^(−1)at 0.1 C and maintain 80.7%of the energy density at 3 C.

Exploration of Graduate Student Cultivation Mode of Landscape Architecture under the Background of“Artificial Intelligence+X”

Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper analyzes the cultivation demand of landscape architecture graduate students in the context of the new era,and identifies the problems by comparing the original professional graduate training mode.The new cultivation mode of graduate students in landscape architecture is proposed,including updating the target orientation of the discipline,optimizing the teaching system,building a“dualteacher”tutor team,and improving the“industry-university-research-utilization”integrated cultivation,so as to cultivate high-quality compound talents with disciplinary characteristics.

基于OpenVPX标准的异构融合处理模块软硬件协同设计研究

随着计算机软硬件技术的持续进步,机载计算平台集成的任务功能日益增多,导致平台内部的计算需求在规模和复杂性上不断攀升。面对智能化应用的迅猛增长,传统的单一处理器架构已不足以应对多样化的复杂任务。为此,基于OpenVPX标准,定义并设计了一种符合硬件开放式架构的3U异构融合处理模块,以适应多种复杂任务的需求。文中还提出了一种异构计算资源池化技术,旨在实现多类型任务应用的快速部署和高效运行,同时降低通信延迟,显著提升计算平台的处理能力和适用性。最后进行了实验验证,结果表明与多CPU架构相比,文中所设计的异构融合处理模块在执行特定神经网络算法时,处理时间缩短了约4.8倍,证明了其在性能上的显著提升。该研究成果不仅展示了异构融合处理模块在机载智能计算应用中的显著性能优势,而且为航空计算平台的未来发展提供了创新的解决方案和技术支持。

Intelligent architecture modeling for multilevel fluvial reservoirs based on architecture interface and elements

At present,the architecture modeling method of fluvial reservoirs are still developing.Traditional methods usually use grids to characterize architecture interbeds within the reservoir.Due to the thin thickness of this type of the interlayers,the number of the model grids must be greatly expanded.The number of grids in the tens of millions often makes an expensive computation;however,upscaling the model will generate a misleading model.The above confusion is the major reason that restricts the largescale industrialization of fluvial reservoir architecture models in oilfield development and production.Therefore,this paper explores an intelligent architecture modeling method for multilevel fluvial reservoirs based on architecture interface and element.Based on the superpositional relationship of different architectural elements within the fluvial reservoir,this method uses a combination of multilevel interface constraints and non-uniform grid techniques to build a high-resolution 3D geological model for reservoir architecture.Through the grid upscaling technology of heterogeneous architecture elements,different upscaling densities are given to the lateral-accretion bedding and lateral-accretion bodies to simplify the model gridding.This new method greatly reduces the number of model grids while ensuring the accuracy of lateral-accretion bedding models,laying a foundation for large-scale numerical simulation of the subsequent industrialization of the architecture model.This method has been validated in A layer of X oilfield with meandering fluvial channel sands as reservoirs and B layer of Y oilfield with braided river sands as reservoirs.The simulation results show that it has a higher accuracy of production history matching and remaining oil distribution forecast of the targeted sand body.The numerical simulation results show that in the actual development process of oilfield,the injected water will not displace oil in a uniform diffusive manner as traditionally assumed,but in a more complex pattern with oil in upper part of sand body being left behind as residual oil due to the influences of different levels of architecture interfaces.This investigation is important to guiding reservoir evaluation,remaining oil analysis,profile control and potential tapping and well pattern adjustment.

Long-Term Impacts of Tree Architectures and Branch Configurations on Tree Growth, Yield, Fruit Quality Attributes, and Leaf Minerals in “Aztec Fuji” Apple

Canopy and branch architectures in high-density orchards can be crucial in production and fruit quality. The influence of two canopy orientations (Upright and Tilted) in combination with two arm (branch) architectures (Shortened or Overlapped) on tree growth, yield components, fruit quality, and leaf mineral nutrients in an “Aztec Fuji” apple (Malus domestica Bork.) high-density orchard was studied over five years. Tilted trees with shortened arm configuration (TilShArm) always had significantly larger trunk cross-sectional area (TCSA) than Upright trees with an Overlapped arm configuration (UpOverArm) every year from 2012 to 2016. Trees with a TilShArm system had more cumulative fruit per tree than those with an Upright orientation. Trees with a tilted canopy (TilShArm and TilOverArm) tended to have higher yield per tree and yield per hectare than those with an upright system. Trees with a TilShArm system were more precocious and had more yield per tree than those with an upright canopy orientation in 2012. When values were polled over five years, trees with an upright canopy-shortened arm system (UpShArm) treatment had a lower biennial bearing index (BBI) than those with an upright canopy-overlapped system (UpOverArm). Trees receiving an arm shortening (UpShArm or TilShArm) configuration often had larger fruits than those with overlapped arms (UpOverArm and TilOverArm). Fruit from trees receiving an UpOverArm had higher fruit firmness than those from trees with other canopy-branch arrangements at harvest due to their smaller size. Fruit from trees with a TilShArm and TilOverArm had significantly higher water core and bitter pit but lower sunburn than trees with an upright canopy (UpShArm and UpOverArm). Leaves from trees with an UpOverArm canopy-branch configuration had the lowest leaf Ca but the highest leaf K and Fe concentrations among all treatments.

Artificial Self-Recovery Opens up a New Journey of Autonomous Health of Mechanical Equipments

1.Introduction With the implementation of modern production strategies,such as“Industry 4.0”and“Made in China 2025,”the development of high-end mechanical equipment is gradually reaching a high degree of parameterization,digitalization,networking,and intelligence[1].High-end mechanical equipment no longer consists of traditional single devices,but is closely linked to the overall production process;that is,a variety of devices interact with each other and collectively form a complex system.However,faults can lead to production delays throughout the system and even seriously threaten the safety of workers[2].In addition,equipment operating in unmanned air or space vehicles(including space robots)cannot be repaired by humans if they break down[3].Until recently,the typical method of addressing machine faults was primarily the“fault cure”method,which involves manually shutting down,inspecting,and repairing the equipment to restore normal operation.Accordingly,the maintenance cycle of the traditional“fault cure”method is time-consuming,and the quality of the maintenance depends on the skills of the technician[4].

基于OpenFaaS的多边缘管理框架

移动边缘计算(Mobile Edge Computing,MEC)是一种利用靠近移动设备的边缘节点提供的计算能力,来提升性能的前沿技术。现有的一些先进的计算卸载方法,已能够支持在MEC环境中基于函数粒度进行动态卸载。函数即服务(Function as a Service,FaaS)作为无服务架构的一种经典范式,提供了一种在函数粒度上构建和拓展应用程序的新方式。相比传统的方式,FaaS提供了理想的资源弹性。OpenFaaS作为当下流行的开源FaaS项目,为FaaS平台的搭建提供了良好的基础。将先进的计算卸载方法与FaaS解决方案(OpenFaaS)进行整合,是有意义且具有挑战的。为此,文中设计并实现了一个基于OpenFaaS的多边缘管理框架,该框架实现了对多个边缘上OpenFaaS的搭建与状态管理。同时,对于需要部署的函数,将其重构并部署到OpenFaaS上,在运行时能够灵活地在多个OpenFaaS间调度函数执行。针对5个实际的Java智能应用对该框架进行了评估,结果表明该框架可以有效管理多个边缘,且与本地运行相比,该框架平均可节省10.49%~49.36%的响应时间。

Timing effect of high temperature exposure on the plasticity of internode and plant architecture in maize

The occurrence of high temperature(HT)in crop production is becoming more frequent and unpredictable with global warming,severely threatening food security.The state of an organ’s growth and development is largely determined by the temperature conditions it is exposed to over time.Maize is the main cereal crop,and its stem growth and plant architecture are closely related to lodging resistance,and especially sensitive to temperature.However,systematic research on the timing effect of HT on the sequentially developing internode and stem is currently lacking.To identify the timing effect of HT on the morphology and plasticity of the stem in maize,two hybrids(Zhengdan 958(ZD958),Xianyu 335(XY335))characterized by distinct morphological traits in the stem were exposed to a 7-day HT treatment from the V6 to V17 stages(Vn presents the vegetative stage with n leaves fully expanded)in 2019-2020.The results demonstrated that exposure to HT during V6-V12 accelerated the rapid elongation of stems.For instance,HT occurring at V7 and V12 specifically promoted the lengths and weights of the 3rd-5th and 9th-11th internodes,respectively.Meanwhile,HT slowed the growth of internodes adjacent to the promoted internodes.Interestingly,compared with control,the plant height was significantly increased soon after HT treatment,but the promotion effect became narrower at the subsequent flowering stage,demonstrating a self-adjusting mechanism in the maize plant in response to HT.Importantly,HT altered the plant architectures,including a rising of the ear position and increase in the ear position coefficient.XY335 exhibited greater sensitivity in stem development than ZD958 under HT treatment.These findings improve our systematic understanding of the plasticity of internode and plant architecture in response to the timing of HT exposure.

Auxin-brassinosteroid crosstalk:Regulating rice plant architecture and grain shape

Rice(Oryza sativa)plant architecture and grain shape,which determine grain quality and yield,are modulatedby auxin and brassinosteroid via regulation of cell elongation and proliferation.We review the signaltransduction of these hormones and the crosstalk between their signals on the regulation of rice plantarchitecture and grain shape.

Apical meristem transcriptome analysis identifies a role for the blue light receptor gene GhFKF1 in cotton architecture development

Cotton architecture is determined by the differentiation fate transition of axillary meristem(AM),and influences cotton yield and the efficiency of mechanized harvesting.We observed that the initiation of flowering primordium was earlier in early-maturing than that in late-maturing cultivars during the differentiation and development of AM.The RNA-Seq and expression level analyses showed that genes FLAVIN BINDING,KELCH REPEAT,F-BOX1(GhFKF1),and GIGANTEA(GhGI)were in response to circadian rhythms,and involved in the regulation of cotton flowering.The gene structure,predicted protein structure,and motif content analyses showed that in Arabidopsis,cotton,rapseed,and soybean,proteins GhFKF1 and GhGI were functionally conserved and share evolutionary origins.Compared to the wild type,in GhFKF1 mutants that were created by the CRISPR/Cas9 system,the initiation of branch primordium was inhibited.Conversely,the knocking out of GhGI increased the number of AM differentiating into flower primordium,and there were much more lateral branch differentiation and development.Besides,we investigated that proteins GhFKF1 and GhGI can interact with each other.These results suggest that GhFKF1 and GhGI are key regulators of cotton architecture development,and may collaborate to regulate the differentiation fate transition of AM,ultimately influencing plant architecture.We describe a strategy for using the CRISPR/Cas9 system to increase cotton adaptation and productivity by optimizing plant architecture.

A 48-bp deletion upstream of LIGULELESS 1 alters rice panicle architecture

Panicle architecture is an agronomic determinant of crop yield and a target for cereal crop improvement.To investigate its molecular mechanisms in rice,we performed map-based cloning and characterization of OPEN PANICLE 1(OP1),a gain-of-function allele of LIGULELESS 1(LG1),controlling the spread-panicle phenotype.This allele results from a 48-bp deletion in the LG1 upstream region and promotes pulvinus development at the base of the primary branch.Increased OP1 expression and altered panicle phenotype in chimeric transgenic plants and upstream-region knockout mutants indicated that the deletion regulates spread-panicle architecture in the mutant spread panicle 1(sp1).Knocking out BRASSINOSTEROID UPREGULATED1(BU1)gene in the background of OP1 complementary plants resulted in compact panicles,suggesting OP1 may regulate inflorescence architecture via the brassinosteroid signaling pathway.We regard that manipulating the upstream regulatory region of OP1 or genes involved in BR signal pathway could be an efficient way to improve rice inflorescence architecture.

Enhancing MXene-based supercapacitors:Role of synthesis and 3D architectures

MXene has been the limelight for studies on electrode active materials,aiming at developing supercapacitors with boosted energy density to meet the emerging influx of wearable and portable electronic devices.Despite its various desirable properties including intrinsic flexibility,high specific surface area,excellent metallic conductivity and unique abundance of surface functionalities,its full potential for electrochemical performance is hindered by the notorious restacking phenomenon of MXene nanosheets.Ascribed to its two-dimensional(2D)nature and surface functional groups,inevitable Van der Waals interactions drive the agglomeration of nanosheets,ultimately reducing the exposure of electrochemically active sites to the electrolyte,as well as severely lengthening electrolyte ion transport pathways.As a result,energy and power density deteriorate,limiting the application versatility of MXene-based supercapacitors.Constructing 3D architectures using 2D nanosheets presents as a straightforward yet ingenious approach to mitigate the fatal flaws of MXene.However,the sheer number of distinct methodologies reported,thus far,calls for a systematic review that unravels the rationale behind such 3D MXene structural designs.Herein,this review aims to serve this purpose while also scrutinizing the structure–property relationship to correlate such structural modifications to their ensuing electrochemical performance enhancements.Besides,the physicochemical properties of MXene play fundamental roles in determining the effective charge storage capabilities of 3D MXene-based electrodes.This largely depends on different MXene synthesis techniques and synthesis condition variations,hence,elucidated in this review as well.Lastly,the challenges and perspectives for achieving viable commercialization of MXene-based supercapacitor electrodes are highlighted.

Dust-Holding Capacity and Bio-Chemical Changes of Plant Species Growing in an Around Opencast Mining Area of Bundelkhand Region of Uttar Pradesh, India

The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bundelkhand University campus treated as control site. Plant species existing under a polluted environment for a long time may be considered as potentially resistant species and recommended for green belt design in mining areas, especially to cope with dust pollution. Results showed the pollution level, especially of mining-originated dust particles holding capacity of leaves and effects of different biochemical parameters (Total Chlorophyll, Protein and Carotenoid) of existing plant species both from mining areas as well as from Bundelkhand University campus. Based on their performances, Tectona grandis L., Ficus hispida L., Calotropis procera Aiton., Butea monosperma Lam. and Ficus benghalensis L., etc. are highly tolerant species while Ficus infectoria L., Artocarpus heterophyllus Lam., Ipomoea purpurea L., Allianthus excelsa Roxb. and Bauhinia variegata L. are intermediate tolerant species. T. grandis had shown the highest dust-holding capacity (2.566 ± 0.0004 mg/cm2) whereas Albizia procera (0.018 ± 0.0002 mg/cm2) was found to be the lowest dust-holding capacity. Our findings also showed that the T. grandis and F. hispida have significant dust deposition with minimal effect of dust on their leaf chlorophyll (17.447 ± 0.019 mg/g and 14.703 ± 0.201 mg/g), protein (0.699 ± 0.001 mg/g and 0.604 ± 0.002 mg/g) and carotenoid (0.372 ± 0.003 mg/g and 0.354 ± 0.003 mg/g) content respectively among all selected plant species. Therefore, in the present investigation, plant species with high tolerance to high dust-holding capacity on their leaf surfaces are preferable for green corridors as open cast granite mines and their adjacent areas.

基于CAPE-OPEN标准的乙苯脱氢反应器模块开发与全流程模拟

基于某乙苯负压绝热脱氢制苯乙烯装置转化率低于设计值的现状,建立了包括小分子水蒸气转化反应在内的乙苯绝热脱氢制苯乙烯反应动力学模型和反应器模型,基于工业数据,估计了模型动力学参数,模型具有较高的精度;采用C++语言和COM技术开发了符合CAPE-OPEN标准的乙苯脱氢制苯乙烯反应器单元模块;在Aspen Plus平台构建了内嵌反应器模块的乙苯脱氢制苯乙烯全流程模型,反应器与精馏塔的模拟结果与实际相吻合;进一步考察了工艺参数对装置运行中期反应的影响,提出了适宜的工艺参数,为乙苯脱氢制苯乙烯的工艺设计、生产优化提供有益的支持。