The Rising,Recession and Revitalization of the Traditional Industrial Base in the Northeastern United States

The distribution of American industries has been unbalanced and most of the early industrial regions were centered in northeastern America.The northeastern traditional industrial base once was called"manufacturing belt".Since the 1950s,old industrial bases in the United States have been under recession.The northeastern region was then even called"rust belt".Some issues and measures of policy were set up by the government to adjust and restructure the old industrial bases,and some are useful experience and inspirations for our country,such as setting up special branches and organizations,establishing and implementing strategic planning for the adjustment and restructure of old industrial bases,adjusting the industrial branch and system,emphasizing on environment control and preservation and so on was achieved.Learning the successful experience from America,effective countermeasures and steps must be taken to accelerate the revival of the old industrial base in Northeastern China.

Simulation of Low TDS and Biological Units of Fajr Industrial Wastewater Treatment Plant Using Artificial Neural Network and Principal Component Analysis Hybrid Method

Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of outputs.

Performance Simulation of H-TDS Unit of Fajr Industrial Wastewater Treatment Plant Using a Combination of Neural Network and Principal Component Analysis

Nowadays, with regard to environmental issues, proper operation of wastewater treatment plants is of particular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems and environmental engineers are dealing with them mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant, powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the multilayer perceptron (MLP) feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant located in Mahshahr—Iran that qualitative and quantitative characteristics of its units were used for training, calibration and evaluation of the neural model. Also, Principal Component Analysis technique was applied to modify and improve performance of generated models of neural networks. The results of this model showed good accuracy of the model in estimating qualitative pro- file of wastewater. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of output.

Industrial Preparation and Acid Resistance of Ultra-stable Y Zeolite with Small Cell Size Produced by Gas-phase Method

Small-cell HSY-S zeolite prepared by the gas-phase ultra-stable method had been researched and developed,and industrial preparation tests of HSY-S have been successfully carried out for the first time.The acid resistance of industrially prepared HSY-S was investigated by acid solutions with different pH values.The structures and properties of HSY-S and its acid-treated samples were characterized by XRD,XRF,BET,and IR.Results show that the HSY-S samples have the characteristics of high crystallinity,good stability,large specific surface area,and good acid resistance.

Impacts of the COVID-19 pandemic on the dairy industry: Lessons from China and the United States and policy implications

The purposes of this study are to assess the COVID-19 pandemic’s impacts on the dairy industries in China and the United States and to derive policy recommendations for enhancing the diary industries’resilience to pandemics and other market shocks.Specifically,data from the two nations are used to analyze and compare the mechanisms through which the pandemic has affected their dairy industries and to discuss potential lessons from their experiences.The findings suggest that this pandemic has heavily affected the dairy industries in both China and the United States through similar mechanisms,such as decreased farmgate milk prices,disruption and difficulties of moving milk within the supply chains,worker shortages,increased production costs,and lack of operating capital.There were also significant differences in the affecting mechanisms between the two nations,including transportation difficulties from widespread road closures and significant reduction in holiday sales of dairy products in China,and the shutdown of many dairy processors in the United States due to the closing of schools,restaurants,and hotels.While government financial reliefs are highly needed to help many dairy farms and processors survive this pandemic in the short term,the dairy industries and governments need to work together to develop long-term strategies and policies to balance the industries’efficiency and flexibility,product specialization and diversification,supply chain integration and local food systems,and market mechanisms and policy regulations and interventions.

The Key Factor of Acid Mine Drainage (AMD) in the History of the Contribution of Mining Industry to the Prosperity of the United States and South Africa: A Review

Mining industry has significantly contributed to the prosperity of the nation with economic growth, whereas mining operation has caused Acid Mine Drainage (AMD) with the abandonment of mines. As some researchers suggest, the history of AMD is, generally, affected by the change in not only mining industry but also in social and economic conditions. Thus, historical analysis is an effective way to find the key factors of AMD. In this study, in order to find the key factors of AMD, we examine the history of the United States (U.S.) and South Africa, where their economy had been developed owing to the large-scale mining, based on the findings in the previous studies. The results indicated that the abandoned mines due to the economic depression triggered AMD in the U.S. and South Africa. While the U.S. had progressively adopted anti-AMD methods in terms of prevention, prediction, and remediation (PPR) as a comprehensive approach, especially since the 1970s onwards because of the rise of environmental consciousness as well as strict regulations, South Africa is at the early stage of implementing the regulations following PPR. The public attention should be directed to environmental conservation in addition to the implementation of the regulations in South Africa. The improvement in socio-economic conditions is, additionally, necessary for the rise of environmental consciousness in South Africa in the light of the three pillars of sustainable development: social, economic, and environmental elements.

High-tech Interest Groups in the United States and Its Political Influence

Representing the appeals of its industry,the high-tech interest group has recently become an emerging political force in the United States.With abundant financial resources and proficiency in political communication,the group rapidly grows to be a significant force in the American political sphere.It has started to affect the internal and foreign affairs of the U.S.and played a proactive role in the latest presidential election.Since the high-tech interest group has already become and will continue to be a big player in Sino-U.S.relations,China should carefully deal with its appeals and conflict of interests,and try to develop this group into a stabilizer between the two countries.

美国产业政策复兴:目标、特征与启示

长期以来,自由市场经济被认为是美国经济的主要特征,美国政府也在国际上反对产业政策的使用。但近年来美国产业政策出现复兴,主要体现在直接干预型产业政策明显增多、推动产业本土化归岸化、加强供应链韧性与安全、加大新兴产业扶持力度等方面。从历史上看,产业政策在美国的崛起中发挥过重要作用。随着二战后美国取得全方位遥遥领先的地位,其支持产业发展的政策转向更加重视发挥市场的作用,重点支持科技创新,鼓励自由市场竞争,也不排除在特殊情况下实施适度干预。当前美国产业政策复兴呈现出产业补贴的使用增加和力度加大、竞争前环节仍是产业政策的重点、联邦产业政策多以法案形式出台、注重不同政策间盟友间的协调配合等新特征。中国已经进入新的发展阶段,面对百年未有之大变局,产业政策仍然是促进产业转型升级、构建现代化产业体系的重要手段,但随着我国向全球价值链高端攀升、向战略性新兴产业迈进,也需要对产业政策进行调整。美国产业政策复兴对于我国全面认识产业政策的作用、更好地制定和实施产业政策具有重要的启示。

2023年中国炼油工业发展状况及展望

2023年,中国炼油能力增长继续放缓,新增炼油能力1200万吨/年,总能力升至9.36亿吨/年,装置结构优化调整持续推进。2023年我国成品油需求快速反弹、市场整顿持续推进等利好因素推动炼油行业生产明显好转,多项主要生产经营指标显著回升。国家政策为我国炼油行业高质量发展指明了路径,炼油企业持续推进绿色、低碳、数字化、智能化发展,并积极“走出去、引进来”,扩大合作。展望未来,2024年中国炼油能力将继续较快增长,但能力峰值基本显现,预计炼油能力峰值将在2027年左右出现;“十五五”期间,我国炼油能力过剩的压力有一定缓解,但不能掉以轻心,淘汰落后产能、调整产品结构、节能降碳等转型升级措施需长期推进。

发达国家职业教育与产业发展的契合经验及对我国的启示——以德国、美国为例

职业教育发端于产业发展的需要,产业发展反过来又催生了职业教育的发展,要求职业教育与产业发展具有一致性、契合性。国家一系列政策都提出要推动职业教育融入产业发展的需要,发达国家职业教育与产业发展的契合性为我国提供了可资借鉴的经验,启示我国应通过全面加强政府引导、建构产教全面融合机制、提高职业教育学历层次、充分发挥企业特定作用、完善培养质量考核制度等措施,以有效增强我国职业教育与产业发展的契合性。

基于数字孪生的工业机器人建模及监测方法

针对工业机器人数据不透明、监测存在死角等问题,通过对实体工业机器人分析和研究,构建数字孪生机器人监测系统。首先从几何、物理、逻辑3个维度完成虚拟机器人的建模;其次基于开放平台通信联合架构(open platform communications united architecture,OPC UA),实现机器人的数据采集和通信,设计用户显示界面,达到数据实时可视化的效果;最后,通过机器人仿真实验得出机器人末端执行器X、Y、Z坐标的相对位置误差分别为0.48%、0.32%、0.27%,通过数字孪生机器人监测同步实验验证机器人关节角度误差最大值为0.31°。实验结果表明:该方法能够实现数字孪生工业机器人的运动数据监测,减少工业机器人在生产过程中发生意外和故障的风险,为智能工业机器人的发展提供思路和方向。

农业科研院所创建文明单位的实践与探索——以河南省农业科学院粮食作物研究所为例

开展文明单位创建活动,以文明单位创建促进科技创新,提高科技创新能力对农业科研院所尤为重要。文章以河南省农业科学院粮食作物研究所为例,介绍了省级农业科研院所结合农科特色开展文明单位创建活动的主要举措及取得的成效,针对创建过程中存在的问题,从提高政治站位、创新工作模式、压实领导责任、健全创建制度等方面提出了加强科研院所文明单位创建工作的对策建议,并对未来文明单位的建设工作提出了设想和展望。

美国有机食品全产业链融合发展的国际经验与政策启示

有机食品全产业链融合发展是应对中国消费结构转型升级、助力有机食品产业高质量发展的有效途径。本文从产业链视角出发,探究中美有机食品产业的发展现状,总结国际有益经验并提出中国有机食品全产业链融合发展的政策启示。研究发现:(1)中国有机食品产业链协同性水平不高,市场渗透率较低,呈现出“弱”而“散”的发展格局;(2)美国有机食品全产业链融合是一个由政府监督、企业参与和消费者驱动的复杂系统,其以分工协作为前提、以品牌信任为依托、以产业生态为纽带,打造产业联合体,以挖掘全链条的增值潜力。借鉴国际经验,本文政策启示如下:健全利益联结机制,完善有机认证体系,提高监管水平,引入现代生产要素,强化政策支持,推动有机食品全产业链创新性、融合式发展。

美国培育发展未来产业的经验研究

未来产业是大国之间角力和竞争的焦点。美国不断加强量子信息科技、人工智能、先进制造、下一代通信网络和生物技术等前沿科技和未来产业发展,不同产业间的主要共性举措主要有:强化政策引导,系统研发布局;部门各司其职,相互协调推进;注重平台建设,产学研紧密融合;加强人才培养,建设多层梯队;推动国际合作,提升产业韧性等,产生了较好效果。中国可从中吸取经验,通过统筹协调、完善生态、搭建平台、培育人才和国际合作等方面持续推动未来产业发展壮大,加快培育和发展新质生产力。

“双碳”目标下我国油气田绿色低碳发展路径研究

油气田绿色低碳发展是必然趋势。近年来国内油气行业绿色低碳转型步伐不断加快,但同时也面临油气资源禀赋较差,油气生产单位能耗和单位碳排放强度较大,新能源在油气生产用能结构中占比低,油气绿色开发技术体系不完善等问题。为保持国内原油产量长期稳定,需要加大勘探开发力度,而这势必带来更大规模的碳排放,因此需要统筹推进油气增储上产和绿色低碳油气田建设。我国陆上油气田绿色低碳发展可分为三个阶段:2024~2030年为清洁替代阶段,2030年前后建成一批绿色低碳开发示范油气田,温室气体排放达到峰值;2030~2035年为战略过渡阶段,大幅提高清洁能源生产供应能力和碳减排能力,温室气体排放量较峰值下降20%以上;2035~2050年为绿色低碳转型阶段,2050年全面实现陆上油气田绿色低碳开发。油气田绿色低碳发展应以油气勘探开发全过程、全环节碳足迹为主线,通过“源头洁净化、过程高效能、末端捕集封存利用”,实现油气生产全生命周期减碳、降碳、固碳。要做好顶层设计,促进油气与新能源融合发展,加大技术攻关力度,形成全产业链油气绿色开发技术。

汽车总线技术课程ECU控制专项实训改革与实践

基于产学合作协同育人模式,以培养智能汽车电子控制器(ECU)相关岗位技能人才为目标,对汽车总线技术课程ECU控制专项实训进行系统设计及实施,探索多学科交叉融合实践教学改革的实现途径,以满足新工科背景下汽车行业对ECU相关岗位复合型紧缺人才的需求。该研究为应用型本科院校车辆工程及其他机械类专业培养ECU控制相关岗位的技术人才提供了参考与借鉴。

行业协会参与现代学徒制试点:境况、困顿与路向

行业协会是架构产教协同发展的纽带和桥梁。提升行业协会在我国现代学徒制试点中的服务指导能力,是全面推进现代学徒制工作的重要保障。然而,在我国现代学徒制试点的进程中,行业协会参与现代学徒制试点的程度却相当有限,其根本原因在于行业协会参与现代学徒制试点存在着系统性的短板:现代学徒制建设的政策体系不完善、行业协会与职业院校之间缺乏有效合作、部分企业对现代学徒制建设存在着消极应对态度、行业协会自身发展不足。要改变这样的被动局面,亟需及时优化行业协会参与现代学徒制建设的政策机制、建立健全职业院校与行业协会间的有效合作机制、强化合作企业的重要育人主体作用、以及加强行业组织自身建设。

煤电行业建设项目碳排放环境影响评价技术方法研究:以黄河流域为例

煤电行业是黄河流域内二氧化碳和大气污染物排放的主要来源,将煤电行业碳排放影响评价纳入环境影响评价体系,能够有效助推黄河流域实现减污降碳协同增效.本文以煤电行业碳排放主要影响因素为基础,设计了能够涵盖碳排放全过程的评价指标体系,并结合先进技术、标准规范要求等设定差异化评价基准,构建以约束评价为主、兼顾指导性评价的评价方法,并采用评价方法中的核心评价指标碳排放绩效,对黄河流域现役煤电机组和“十四五”期间新增煤电机组进行碳减排潜力分析.结果表明,通过优化项目设计可实现流域内现役煤电机组碳排放量下降12.7%,“十四五”期间新建煤电机组碳排放增量下降27.1%,其中新增煤电机组装机占比较高的内蒙古自治区、陕西省可实现新增煤电机组碳排放分别下降30.7%和23.0%.研究显示,黄河流域内碳减排潜力大,建议针对黄河流域内碳排放绩效水平较差的特点,从燃煤小机组淘汰、低碳清洁燃料替代等方式推动煤电行业综合治理,建立协同技术相关指标数据管理台账,出台火电行业碳排放影响评价指南,为煤电行业新增建设项目减污降碳协同增效提供有力有效的政策工具.