中国加入CPTPP的农产品贸易效应研究--基于WITS-SMART模型

粮食安全是国家安全的基石,面对国际市场不稳定性,加入CPTPP有望为中国夯实农产品贸易韧性提供新契机。在考察中国与CPTPP国家农产品贸易竞合关系的基础上,运用WITS-SMART模型建立局部均衡分析框架,研究中国加入CPTPP的农产品贸易效应,结果发现:第一,中国农产品竞争力整体不强,但与CPTPP国家依存关系较高,双边贸易潜力在关税完全削减时充分释放。第二,零关税情境下,贸易创造效应普遍大于转移效应,中国对CPTPP多数国家农产品贸易规模大幅扩张,进口增长主要源自种植业、畜牧业部门以及加拿大、澳大利亚、英国、日本等国家,出口增长主要集中于种植业部门以及日本、英国、马来西亚、墨西哥等国家。第三,加入CPTPP显著改善了双边经济福利,不过关税损失较为严重。因此,中国应破除部门利益障碍,加强与墨西哥、日本、英国等国经贸联系以充分挖掘CPTPP国家市场潜力,释放贸易自由化福利,持续提高农产品出口质量和国际竞争力以应对加入CPTPP带来的挑战。

Stochastic Analysis and Modeling of Velocity Observations in Turbulent Flows

Highly turbulent water flows,often encountered near human constructions like bridge piers,spillways,and weirs,display intricate dynamics characterized by the formation of eddies and vortices.These formations,varying in sizes and lifespans,significantly influence the distribution of fluid velocities within the flow.Subsequently,the rapid velocity fluctuations in highly turbulent flows lead to elevated shear and normal stress levels.For this reason,to meticulously study these dynamics,more often than not,physical modeling is employed for studying the impact of turbulent flows on the stability and longevity of nearby structures.Despite the effectiveness of physical modeling,various monitoring challenges arise,including flow disruption,the necessity for concurrent gauging at multiple locations,and the duration of measurements.Addressing these challenges,image velocimetry emerges as an ideal method in fluid mechanics,particularly for studying turbulent flows.To account for measurement duration,a probabilistic approach utilizing a probability density function(PDF)is suggested to mitigate uncertainty in estimated average and maximum values.However,it becomes evident that deriving the PDF is not straightforward for all turbulence-induced stresses.In response,this study proposes a novel approach by combining image velocimetry with a stochastic model to provide a generic yet accurate description of flow dynamics in such applications.This integration enables an approach based on the probability of failure,facilitating a more comprehensive analysis of turbulent flows.Such an approach is essential for estimating both short-and long-term stresses on hydraulic constructions under assessment.

Augmented IoT Model for Smart Agriculture and Farm Irrigation Water Conservation

In Northern Nigeria, irrigation systems are operated manually. Agriculture has over the years been practiced primitively by farmers, especially in sub-Saharan Africa. This is due to the absence of intelligent technological know-how where its practice could be leveraged upon. Agricultural practice is constrained by some major challenges ranging from traditional way of farming, understating of concepts, practices, policy, environmental and financial factors. The aim of this study was to optimize an IoT-based model for smart agriculture and irrigation water management. The objectives of the study were to: design, implement, test and evaluate the performance of the optimized IoT-based model for smart agriculture and irrigation water management. The method used in the study was the prototyping model. The system was designed using balsamiq application tools. The system has a login page, dashboard, system USE-CASE diagrams, actuators page, sensor page and application interface design. Justinmind tool was used to show the flow of information in the system, which included data input and output, data stores and all the sub-processes the data moves through. The Optimized IoT model was implemented using four core platforms namely, ReactJS Frontend Application development platform, Amazon web services IoT Core backend, Arduino Development platform for developing sensor nodes and Python programming language for the actuator node based on Raspberry Pi board. When compared with the existing system, the results show that the optimized system is better than the existing system in accuracy of measurement, irrigation water management, operation node, platform access, real-time video, user friendly and efficiency. The study successfully optimized an IoT-based model for smart agriculture and irrigation water management. The study introduced the modern way of irrigation farming in the 21st century against the traditional or primitive way of irrigation farming that involved intensive human participation.

SMART模式在临床分子生物学检验技术课程思政中的应用

探讨SMART模式在临床分子生物学检验技术课程思政中应用的效果。结果表明,SMART模式应用于临床分子生物学检验技术课程思政教学中,能有效实现专业教育和思政育人有机融合,为医学检验技术专业课程思政教学改革提供新的思路。

Assessing the Water-Energy-Food-Ecosystems Nexus in Smart Irrigation: A Potato Farming Case Study in Lebanon

This study examines the Water-Energy-Food-Ecosystems (WEFE) nexus in Lebanese agriculture, with a focus on the shift from conventional surface irrigation techniques to advanced smart irrigation systems in the Bekaa region, specifically targeting potato cultivation. The study quantitatively analyzes the interaction among water, energy, and agricultural outputs at the farm scale using the WEFE Nexus framework for scenario analysis. It evaluates variations in water productivity, environmental effects, and economic outcomes, offering a detailed view of existing practices and their sustainable improvement potential. The WEFE Nexus assessment demonstrates that smart irrigation integration significantly decreased resource usage: water consumption was reduced by 58%, diesel fuel use for irrigation dropped by 57%, and the demand for labor and fertilizers decreased by 47% and 49%, respectively. This change led to enhanced crop yields and increased resource efficiency, demonstrating the potential of smart irrigation as a transformative strategy for sustainable agriculture in Lebanon and other arid areas. Economic analysis showed that farmers could recover the costs of installing the smart irrigation system within 3 months. The findings highlight the need for further research on integrating smart irrigation with renewable energy, showing potential for sustainable agricultural development. .

An extended smart driver model considering electronic throttle angle changes with memory

Based on the fact that the electronic throttle angle effect performs well in the traditional car following model,this paper attempts to introduce the electronic throttle angle into the smart driver model(SDM)as an acceleration feedback control term,and establish an extended smart driver model considering electronic throttle angle changes with memory(ETSDM).In order to show the practicability of the extended model,the next generation simulation(NGSIM)data was used to calibrate and evaluate the extended model and the smart driver model.The calibration results show that,compared with SDM,the simulation value based on the ETSDM is better fitted with the measured data,that is,the extended model can describe the actual traffic situation more accurately.Then,the linear stability analysis of ETSDM was carried out theoretically,and the stability condition was derived.In addition,numerical simulations were explored to show the influence of the electronic throttle angle changes with memory and the driver sensitivity on the stability of traffic flow.The numerical results show that the feedback control term of electronic throttle angle changes with memory can enhance the stability of traffic flow,which shows the feasibility and superiority of the proposed model to a certain extent.

Climate Change Impacts and Adaptation in Rainfed Farming Systems: A Modeling Framework for Scaling-Out Climate Smart Agriculture in Sub-Saharan Africa

Improving agricultural water productivity, under rainfed or irrigated conditions, holds significant scope for addressing climate change vulnerability. It also offers adaptation capacity needs as well as water and food security in the southern African region. In this study, evidence for climate change impacts and adaptation strategies in rainfed agricultural systems is explored through modeling predictions of crop yield, soil moisture and excess water for potential harvesting. The study specifically presents the results of climate change impacts under rainfed conditions for maize, sorghum and sunflower using soil-water-crop model simulations, integrated based on daily inputs of rainfall and evapotranspiration disaggregated from GCM scenarios. The research targets a vast farming region dominated by heavy clay soils where rainfed agriculture is a dominant practice. The potential for improving soil water productivity and improved water harvesting have been explored as ways of climate change mitigation and adaptation measures. This can be utilized to explore and design appropriate conservation agriculture and adaptation practices in similar agro-ecological environments, and create opportunities for outscaling for much wider areas. The results of this study can suggest the need for possible policy refinements towards reducing vulnerability and adaptation to climate change in rainfed farming systems.

Applications of smart proxies for subsurface modeling

Using artificial intelligence(AI) and machine learning(ML) techniques, we developed and validated the smart proxy models for history matching of reservoir simulation, sensitivity analysis, and uncertainty assessment by artificial neural network(ANN). The smart proxy models were applied on two cases, the first case study investigated the application of a proxy model for calibrating a reservoir simulation model based on historical data and predicting well production while the second case study investigated the application of an ANN-based proxy model for fast-track modeling of CO2 enhanced oil recovery, aiming at the prediction of the reservoir pressure and phase saturation distribution at injection stage and post-injection stage. The prediction effects for both cases are promising. While a single run of basic numerical simulation model takes hours to days, the smart proxy model runs in a matter of seconds, saving 98.9% of calculating time. The results of these case studies demonstrate the advantage of the proposed workflow for addressing the high run-time, computational time and computational cost of numerical simulation models. In addition, these proxy models predict the outputs of reservoir simulation models with high accuracy.

Enhancing Sustainable Development through Web Based 3D Smart City Model Using GIS and BIM. Case Study: Sheikh Hamad City

Smart sustainable city is that uses the technology to transform their core systems and optimize the exploitation of limited resources;it is a knowledge-based system that provides real-time insights to stakeholders. As a result of the challenges facing the cities of the Gaza Strip regarding population growth, lack of resources, increased demand for materials, the siege imposed on the Gaza Strip for more than twelve years, the smart city approach can contribute to mitigating these challenges and creating opportunities and solutions for many of these problems. Thus, this study aims to promote sustainable urban development through the adoption of smart city approaches using the city’s 3D representation and analysis capabilities to reflect and define the current situation and formulate a future vision using GIS and Building Information Modeling (BIM) considering Sheikh Hamad city as a case study. This involves developing a GIS web-based 3D model of the urban landscape of the city and creating a geometric descriptive database that includes the various elements of the city such as buildings, services and other facilities. The constructed database is to be automatically updated and can be used to facilitate documentation, transparency and help in decision-making process. The 3D smart city can also benefit stakeholders, government officials, private sectors as well as the city citizens. Therefore, urban services will be more efficient, and the cities of the Gaza Strip will be able to achieve sustainable development and competition in difficult economic, environmental and social conditions. This study recommends the use of BIM and GIS technologies in the transformation to a smart city concept as well as the rehabilitation of existing cadres to enable them to use those technologies to achieve the goal of improving the quality of life and facilitating the daily lives of people.

Discrete Methods Based on First Order Reversal Curves to Identify Preisach Model of Smart Materials

Preisach model is widely used in modeling of smart materials. Although first order reversal curves （FORCs） have often found applications in the fields of physics and geology, they are able to serve to identify Preisach model. In order to clarify the relationship between the Preisach model and the first order reversal curves, this paper is directed towards： （1） giving the reason a first order reversal curve is introduced; （2） presenting, for identifying Preisach model, two discrete methods, which are analytically based on first order reversal curves. Herein also is indicated the solution＇s uniqueness of these two identifying methods. At last, the validity of these two methods is verified by simulating a real smart actuator both methods have been applied to.

Risk Identification based on Hidden Semi-Markov Model in Smart Distribution Network

The smart distribution system is the critical part of the smart grid, which also plays an important role in the safe and reliable operation of the power grid. The self-healing function of smart distribution network will effectively improve the security, reliability and efficiency, reduce the system losses, and promote the development of sustainable energy of the power grid. The risk identification process is the most fundamental and crucial part of risk analysis in the smart distribution network. The risk control strategies will carry out on fully recognizing and understanding of the risk events and the causes. On condition that the risk incidents and their reason are identified, the corresponding qualitative / quantitative risk assessment will be performed based on the influences and ultimately to develop effective control measures. This paper presents the concept and methodology on the risk identification by means of Hidden Semi-Markov Model (HSMM) based on the research of the relationship between the operating characteristics/indexes and the risk state, which provides the theoretical and practical support for the risk assessment and risk control technology.

Research on Cyber-Physical Modeling for Smart Distribution Grid

Smart distribution network will achieve the optimal operation of the distribution network, provide high-quality and reliable power, guarantee the development of modern social economy. The deep integration of cyber system and power physical system is the key to smart distribution network. The emergence of cyber-physical system (CPS) provides a new way to solve this problem, the cyber-physical model for smart distribution grid becomes an urgent problem to be solved. In this paper, the content and method of cyber-physical model for smart distribution grid are analyzed by combining with the coupling of information flow and power flow of smart distribution network from the perspective of cyber-physical model. At last, taking 110 kV typical substation as an example, the coupling mechanism and function of power flow and information flow is studied.

基于赛教融合的智能交通课程实践教学研究

结合全国大学生智能汽车竞赛百度智慧交通创意组竞赛项目,设计智能交通课程实践教学内容,从竞赛内容凝练与课程知识点结合的教学案例和实验项目,实现赛教资源融合和赛教一体化实践平台共享。设计的实验教学项目融合了图像处理、数据分析、人工智能、智能车硬件平台等内容,包括数据采集、数据分析、数据集构建,深度学习模型建立与智能车平台部署等实践环节。学生从编写简单程序开始,不断提高,到构建复杂的深度学习模型实现智能车自动巡航控制实验。将竞赛任务具有挑战性和对抗性的特点融入课程教学,吸引学生兴趣,增强学生求知欲,提升学生创新能力和工程实践能力。

The Impact of User and Traffic Models on the Design of the Communications Network in the Smart Grid

A critical component of the smart grid (SG) infrastructure is the embedded communications network, where an important objective of the latter is the expansion of its throughput, in conjunction with the satisfaction of specified latency and accuracy requirements. For the effective design of the communications network, the user and traffic profiles, such as known-user vs. unknown-user populations and bursty vs. non-bursty data traffics, must be carefully considered and subsequently modeled. This paper relates user and traffic models to the deployment of effective multiple access transmission algorithms in the communications network of the SG.

An Inductor Model for Analyzing the Performance of Printed Meander Line Antennas in Smart Structures

Meander line antenna has been considered desirable on flight vehicles to reduce drag and minimize aerodynamic disturbance;however, the antenna design and performance analysis have made mostly by trial-and-error. An inductor model by simulating the meander line sections as electrical inductors and the interconnecting radiation elements as a quasi-monopole antenna is developed to analyze the antenna performance. Experimental verifications of the printed meander line antennas embedded in composite laminated substrates show that the inductor model is effective to design and analyze. Of the 4 antennas tested, the discrepancy of resonant frequency in simulation and experiment is within 4.6%.

AIGC驱动下图书馆智慧服务生态模式构建与实现路径研究

AIGC的出现和发展深度影响人机交互的情感体验,催生图书馆智慧服务的新方向,打造全新的图书馆服务业态。文章结合图书馆智慧服务特征提出AIGC驱动下图书馆智慧服务的价值机遇,并以信息生态理论为基础,从信息人、信息技术、信息实践、信息价值和信息环境五个关键要素出发,构建AIGC驱动下的图书馆智慧服务生态模式,同时提出AIGC驱动下图书馆智慧服务生态模式的实现路径。

智慧图书馆多模态阅读情感研究

文章基于阅读全生命周期情感阶段,立足基本情感、专有情感和高级情感3个层级,通过动因情感、实时情感和延伸情感3个扇区,构建智慧图书馆多模态阅读情感群喷泉模型,并从表情、语音、生理、肢体、文本和行为6个模态构建多模态阅读情感表征体系。基于此,设计智慧图书馆多模态阅读情感感知模型并阐释其运行机理,就动态阅读情感提出情感匹配、交流汇聚、双向反馈等阅读情感导引建议。

基于SMART模型的高校生活垃圾逆向物流提升策略研究

近年来,随着人们消费意愿的上涨,生活垃圾也在逐年递增。在因疫情被封闭的高校校园内,每天产生的生活垃圾将近数万吨,目前,很多高校尚未建立完整的垃圾收集和运输体系,而传统垃圾运输方式会在很大程度上造成资源的浪费。文中以资源的循环利用为目标,针对高校生活垃圾的处理现状,将高校生活垃圾与逆向物流相结合,根据SMART模型,从明确性、可衡量性、可以实现性、相关性、时限性五个角度为其提供合理化建议,以促进我国循环经济的发展,供学者进行参考。

基于侧链和信任管理模型的数据共享方案

为解决在不信任的区块链环境中由于数据转售而造成的用户不愿共享数据等问题,提出一种基于侧链和信任管理模型的数据共享方案。使用信任管理模型量化节点信任值,将节点信任值集成到数据共享智能合约中,为用户提供可信的共享环境和动态的访问控制接口。对联盟链进行侧链扩容,使用信任管理模型优化共识算法。规定主链使用具有拜占庭容错能力的T-PBFT算法,侧链使用仅适用于高信任场景的T-Raft算法。用户根据预先设置的阈值动态决定在主链或侧链共享数据。实验就方案的安全性和性能进行分析,表明了该方案的可行性和有效性。

RCEP下中日农产品贸易自由化的经济效应

利用单一市场局部均衡分析模型(WITS-SMART),模拟了RCEP下中日农产品贸易自由化的经济效应。结果表明:中日两国所有农产品的贸易创造效应均大于贸易转移效应,且随着降税幅度的加大,贸易效应显著提升,其中种植业降税给两国创造的贸易效应最突出;虽然中日两国关税收入会下降,但整体福利均将获得提升,且两国均是种植业降税的福利效应最大,随着减税力度的加大,福利效应进一步扩大;中日两国优势农产品均在关税减让中获得更多发展机遇,中国的麦芽等种植业产品和腌制鱼等水产品降税的贸易效应与福利效应均比较突出,但谷物、烟草等种植业产品将面临竞争压力。研究为更好把握RCEP下中日农产品贸易自由化带来的机遇及积极应对产生的挑战提供了参考。