A causal model of eating behaviors among Thai pregnant women working in industrial factories

Objective:This study aimed to examine the causal model of eating behaviors among pregnant women working in industrial factories.Methods:This cross-sectional study was conducted on 210 participants,attending 4 healthcare centers,at a tertiary care hospital in Chonburi province,Thailand.Data were collected using 7 questionnaires:demographic form,eating behavior questionnaire,perceived benefits of the healthy eating questionnaire,perceived barriers to the healthy eating questionnaire,perceived self-efficacy questionnaire,social support questionnaire,and accessibility to healthy foods questionnaire.Descriptive statistics and path analysis were used for data analysis.Results:The participants had relatively high mean scores for eating behaviors.The final model fitted well with the dataχ^(2)=12.86,df=10,P=0.23;χ^(2)/df=1.29;comparative fit index(CFI)=0.98;goodness-of-fit index(GFI)=0.98;adjusted goodness-of-fit index(AGFI)=0.95;root mean square error of approximation(RMSEA)=0.04.Four factors-perceived benefits(β=0.13,P<0.05),perceived self-efficacy in healthy eating(β=0.22,P<0.001),pregnancy planning(β=0.28,P<0.001),and accessibility to healthy foods in the factory(β=0.12,P<0.05)-positively affected eating behavior,while only perceived barriers to healthy eating had a negative effect on eating behavior(β=−0.24,P<0.001).All the above factors explained 27.2%of the variance in eating behaviors.Conclusions:Nurses or healthcare providers can apply these findings to create an eating behavior modification program,focusing on pregnancy planning,behavior-specific variables,and interpersonal and situational influence,to promote the nutritional status of pregnant women working in industrial factories.

Parallel Factories for Smart Industrial Operations:From Big AI Models to Field Foundational Models and Scenarios Engineering

The rapid advancement of fundamental theories and computing capacity has brought artificial intelligence,internet of things, extended reality, and many other new intelligent technologies into our daily lives. Due to the lack of interpretability and reliability guarantees, it is extremely challenging to apply these technologies directly to real-world industrial systems. Here we present a new paradigm for establishing parallel factories in metaverses to accelerate the deployment of intelligent technologies in real-world industrial systems: QAII-1.0. Based on cyber-physical-social systems,QAII-1.0 incorporates complex social and human factors into the design and analysis of industrial operations and is capable of handling industrial operations involving complex social and human behaviors. In QAII-1.0, a field foundational model called Eu Artisan combined with scenarios engineering is developed to improve the intelligence of industrial systems while ensuring industrial interpretability and reliability. Finally, parallel oil fields in metaverses are established to demonstrate the operating procedure of QAII-1.0.

Deciphering and engineering high-light tolerant cyanobacteria for efficient photosynthetic cell factories

Development and utilization of“liquid sunshine”could be one of key solutions to deal with the issues of fossil fuel depletion and increasing carbon dioxide.Cyanobacteria are the only prokaryotes capable of performing oxygenic photosynthesis,and their activity accounts for~25%of the total carbon fixation on earth.More importantly,besides their traditional roles as primary producers,cyanobacteria could be modified as“photosynthetic cell factories”to produce renewable fuels and chemicals directly from CO_(2) driven by solar energy,with the aid of cutting-edging synthetic biology technology.Towards their large-scale biotechnological application in the future,many challenges still need to be properly addressed,among which is cyanobacterial cell factories inevitably suffer from high light(HL)stress during large-scale outdoor cultivation,resulting in photodamage and even cell death,limiting their productivity.In this review,we critically summarized recent progress on deciphering molecular mechanisms to HL and developing HL-tolerant chassis in cyanobacteria,aiming at facilitating construction of HLresistant chassis and promote the future application of the large-scale outdoor cultivation of cyanobacterial cell factories.Finally,the future directions on cyanobacterial chassis engineering were discussed.

Architecture and biogenesis of plus-strand RNA virus replication factories

Plus-strand RNA virus replication occurs in tight association with cytoplasmic host cell membranes. Both, viral and cellular factors cooperatively generate distinct organelle-like structures, designated viral replication factories. This compartmentalization allows coordination of the different steps of the viral replication cycle, highly efficient genome replication and protection of the viral RNA from cellular defense mechanisms. Electron tomography studies conducted during the last couple of years revealed the three dimensional structure of numerous plus-strand RNA virus replication compartments and highlight morphological analogies between different virus families. Based on the morphology of virusinduced membrane rearrangements, we propose two separate subclasses: the invaginated vesicle/spherule type and the double membrane vesicle type. This review discusses common themes and distinct differences in the architecture of plus-strand RNA virus-induced membrane alterations and summarizes recent progress that has been made in understanding the complex interplay between viral and co-opted cellular factors in biogenesis and maintenance of plus-strand RNA virus replication factories.

MDA (Model-Driven Architecture) as a Software Industrialization Pattern: An Approach for a Pragmatic Software Factories

In this paper we show that the MDA can be considered as a software industrialization pattern (or a software factory). Nearly all industries today are haunted with how to reduce costs, improve quality, faster time-to-market and to maximize profits. These challenges are particularly relevant to the software industry, because it still lags behind other technology sectors as regards industrialization and the timely delivery of software products. Most software are still of poor quality, always finished after deadlines (most don’t finish at all), and are very labour intensive. Here, we discuss the MDA as an approach that may help solving at the same time both problems of industrialization and ever-changing software infrastructures. We propose a MDA Engine based on a real case study in an IT services company. It is a proposal for a framework to create custom MDA tools, based on XMI, XSLT and the Visitor Pattern.

Fast Trainable Capabilities in Software Engineering-Skill Development in Learning Factories

The increasing demand for software engineers cannot completely be fulfilled by university education and conventional training approaches due to limited capacities.Accordingly,an alternative approach is necessary where potential software engineers are being educated in software engineering skills using new methods.We suggest micro tasks combined with theoretical lessons to overcome existing skill deficits and acquire fast trainable capabilities.This paper addresses the gap between demand and supply of software engineers by introducing an actionoriented and scenario-based didactical approach,which enables non-computer scientists to code.Therein,the learning content is provided in small tasks and embedded in learning factory scenarios.Therefore,different requirements for software engineers from the market side and from an academic viewpoint are analyzed and synthesized into an integrated,yet condensed skills catalogue.This enables the development of training and education units that focus on the most important skills demanded on the market.To achieve this objective,individual learning scenarios are developed.Of course,proper basic skills in coding cannot be learned over night but software programming is also no sorcery.

Assessing Enabling Competence of Leagile Manufacturing Model and Its Impact on Performance of Small and Medium Factories in Uganda

Purpose: Leagile manufacturing is one of the time-based manufacturing practices used to improve factory performance. It is a practice that combines initiatives of Lean and agile manufacturing under certain enabling competences. Therefore, the purpose of this study is investigate the combinative nature of time-based manufacturing practices under unique enabling competences and their impact on performance of factories in Uganda. Methodology: Firstly, the underlying factor structure of competences and time-based manufacturing was examined was conducted using Principal Component Analysis (PCA). Enabling competences and time-base manufacturing practices were modelled and validated for each using confirmatory factor analysis, particularly composite reliability, average variance extracted and convergent validity. A fully fledged structural equation model was used to test the impact of leagile manufacturing on performance of factories. Findings: The study results revealed that time-based manufacturing of lean, and leagile are related but differ, in terms of their enabling competences and philosophical orientation. The findings also revealed that when small and medium factories in Uganda adopt leagile practice, they are likely not improve their performance. This is perhaps due to the fact that small and medium factories have inadequate resources. Practical Implications: The study findings shed more insights on the factors that enable adoption and implementation of time-based manufacturing practices. The extent to which these competences are orchestrated determines the benefits derived from the time-based manufacturing practices. In addition, small and medium enterprises should keenly make a choice on the appropriate practices that purposely reduce their lead time and cost of conversion. Originality: This study investigated the combinative nature of time-based manufacturing practices under unique enabling competences and their impact on performance of factories in Uganda. It is among the few studies that provide evidence on the leagile model anchored in the appropriate enabling competences in the context of developing countries. The empirical survey was done on small and medium factories to validate a leagile manufacturing model and tested its impact on factory performance.

Factorial Experimental Design to Study the Effects of Layers and Fiber Content on Concrete Flexural Behavior

Experimentation has come a long in helping researchers achieve breakthroughs in their different scientific areas and engineering happens to be one of those areas with the most impact from experimental advancement. The need for valid experimental results free from biases and confounding conclusions has prompted the development of new experimental techniques that takes consideration of all applicable factor and combinations in providing answers on a research topic, and the Factorial Experimental design credited to Sir Ronald Fisher is one technique yielding highly valid results. This paper uses the factorial design of experiments to research the flexural impact of polyvinyl acetate fiber and layered concrete in construction. The experiment considered two levels of fiber contents and two levels of layers, and prepared samples with all combinations of the variable factors. The samples were tested after 7 days from casting for flexural strength and an advance statistical analysis was performed on the flexural responses of the samples using R-program. The results from the analyses revealed the significance of the variables to the flexural strength of the samples, as well as their interactions. The experiment concluded that based on the number of layers and fiber content used for the experiment, casting concrete in layers does have a significant negative effect on the flexural strength of concrete, and the failure pattern of concrete members under flexural load in evidently influenced by the material composition of the concrete, and that it can be evidently influenced by casting the concrete in layers.

Factory IO在PLC应用技术课程虚拟仿真教学中的应用

提出一种基于Factory IO的PLC应用技术课程虚拟仿真教学方法。根据项目设计任务要求,从Factory IO的部件库中选择合适的零部件绘制虚拟设备图,按设计任务要求对虚拟设备进行手动调试,选择和配置PLC,将虚拟设备的信号连接到PLC I/O接口。根据项目的知识点和技能点,在TIA博途中选择合适的指令和编程方法进行程序设计。软硬件设计完成后,进行TIA博途与Factory IO的通信设置与连接,运行Factory IO中的虚拟设备,操作相关控制按钮,观察设备运行情况,修改完善设备和程序直到完全满足设计任务要求。

冷泉碳酸盐工厂的提出及古气候意义

【意义】碳酸盐工厂的提出及其分类研究对于推动碳酸盐岩沉积学发展具有重要意义,但现行分类方案不足以囊括所有碳酸盐沉积类型,因此亟须从机理和过程层面对碳酸盐工厂类型予以梳理、扩充。【进展】传统碳酸盐工厂的碳源主要为大气—海洋中的无机碳库,而一些特殊海相和陆相碳酸盐工厂的碳则主要源于外源碳库,因而两者具有本质上的区别。后者往往对于追溯深时水体环境和气候事件具有重大意义。【结论与展望】以冷泉碳酸盐岩为例,正式提出“冷泉碳酸盐工厂”概念,综述了其沉积特征、生物组成及生物地球化学过程,并举例阐述其古气候意义。基于外源碳库的碳酸盐工厂类型理应得到重视。

American Factories Continue to Increase Equipment Investment——Competitors in Asia also increased their consumption of machine tools.

去年美国金属加工工厂对新机床产品的需求量较 2004 年和 2003 年都有增加。消沉中的美国资本投资发生了一个转变,排在德国之前成为第三大消费国。然而对于美国机床业来说,不太好的消息是亚洲竞争对手同样增加了他们在机床的设备投资。来自第 41 次世界机床生产和消费的调查显示,中国、日本、韩国、印度以及中国台湾地区的机床消费都有显著增长。在 28 个国家和地区的调查中,四分之三的国家和地区消费都在增长,这同时也诠释了经济“表面消费”的含义。这一切表明美国的机床消费量还会继续保持增加,订购机器的数量会维持向上的势头,最新的数据也证明了这一点。此外,调查数据还罗列了其它国家,尤其是亚洲国家的机床生产情况(本刊2006 年第一期环球瞭望栏目文章图表中显示了世界主要机床生产状况):德国和日本领导着世界机床的生产;中国超过意大利成为第三大机床生产国;中国台湾地区排在第五位;美国机床的生产和出口排在台湾之后,保持小的增长;韩国与瑞士紧追其后;印度也毫不示弱。这28个被调查国家和地区的机床产量都比前一年平均增长了14% 。中国、日本、韩国、印度以及中国台湾地区占据了整个调查地区机床产量的 47.6% ,作为CECIMO 成员的由 15 个国家组成的西欧联盟占据了机床产量的 4 2 . 3 % 。

基于Factory IO和S7-1500PLC的组装分拣工作站设计与虚拟仿真

提出一种基于Factory IO的工作站设计与虚拟仿真方法。根据生产工艺要求,从Factory IO部件库中选择合适的零部件,进行工作站设计、安装、参数设置和手动调试。工作站硬件设计完成后,在TIA博途中运用模块化编程方法进行控制程序设计。软硬件设计完成后,进行TIA博途与Factory IO的通信设置与连接,启动TIA博途与Factory IO,操作相关控制按钮,观察设备运行情况,直到完全满足工作站生产工艺要求。

智能建造背景下工程管理本科生知识需求调查

智能建造快速发展,工程管理的内容也在迅速变革,亟需调查分析由此导致的工程管理本科层次人才知识需求的变化。从行业需求的角度面向智能建造相关企业开展问卷调查,共获得了102份有效问卷,涵盖50余家企业。结果表明:工程基础、传统工程管理、BIM、人工智能及大数据、工厂生产管理知识的“需要及非常需要”累计占比分别为90.19%、87.25%、80.39%、75.49%、75.49%。据此,建议高校工程管理专业应着重考虑上述类型知识的传授。当前,为满足工厂生产管理方面的知识需求,还迫切需要高校及行业单位联合编写相关教材。在当前智能建造快速发展背景下,研究结果可为高校工程管理本科生培养方案的修订提供关键依据。

植物工厂岩棉块种苗移植机移植部件设计与试验

目前植物工厂岩棉块种苗移植装备自动化程度低,作业时大多依赖于人工,劳动强度大,效率低。基于植物工厂水培叶菜种苗移植现状设计了一种二级变间距的高速移植部件,并配备有一种拨指式定植杯分离辅助机构。对移植手取苗过程中岩棉块种苗进行受力分析,为移植手设计提供依据;开展拨指式定植杯分离辅助机构落杯试验,为后续植苗至栽培槽孔的定植杯中奠定基础。搭建移植机构试验平台,以取苗深度、岩棉块含水率、移植部件横移速度、移植手升降速度、移植手夹苗间距为试验因素进行五因素三水平正交试验,通过方差分析各因素对移植成功率的影响。试验结果表明:当取苗深度为24 mm、岩棉块含水率为90%、移植部件横移速度为0.8 m/s、移植手升降速度为0.24 m/s、移植手夹苗间距为14 mm时,机构移植成功率为97.9%,移植速度为3132株/h,能够满足高速、高效、稳定的植物工厂岩棉块叶菜种苗移植机械化作业的技术需求。

我国植物油料油脂加工技术新进展

植物油料油脂加工的主要内容包括油脂及蛋白的初加工和深加工技术、综合利用技术、工程装备技术及品质控制技术等,概述了我国植物油料油脂加工技术新进展。我国已初步建立起基于营养和安全为评价标准的食用植物油精准适度加工体系;突破了零反式脂肪酸专用油脂生产技术,能满足各种食品加工场景需求;功能油脂制备技术成果渐次落地,推动产业进入蓬勃发展期,多款结构脂产品进入量产,跨国公司垄断局面得以改变;新油源开发方兴未艾;植物蛋白结构功效关系基础研究促进了植物基产品开发;油料油脂综合利用规模扩大;食用油安全防控技术、绿色储油技术研究不断深入;大型浸出器和浓缩蛋白制取装备的设计和制造水平达到国际先进水平;智能化工厂建设支撑我国油料油脂加工各项经济技术指标处于世界领先地位。

数控装备误差补偿关键技术研究

制造业虚拟工厂模式可以降本增效、优化服务质量,是应对全球化激烈竞争的不二选择。在该模式下,为不断提升产品质量,主要研究与之生产过程相关的数控装备精度提升关键技术即误差补偿关键技术,具体包括误差源分析、误差建模、误差测量及误差数据处理。由此,以五轴机床为数控装备的代表,找出了影响其精度的45项几何误差;并通过误差建模,构建了这45项误差与五轴机床系统总误差的关系;其次,根据五轴机床误差特性,构建了测量系统,并证实了该系统的有效性;最后,针对测量数据,展开误差处理分析,解决了非测量节点数据问题,同时大幅降低了数据量信息,为快速有效地进行误差补偿奠定了数据基础。

抗争与突破:民国时期辽宁电池工业探析(1918—1931)

在近代中国电池工业的发展历程中,辽宁的电池工业起步较早,并在国产干电池领域初步突破技术瓶颈。在辽宁本地的电池生产方面,以王秉乾创办的安东中华电气机械厂和张少亭兄弟创办的中国干电池制造工厂为代表的辽宁电池工业虽然规模弱小,但是发展势头良好。总体而言,民国时期辽宁电池工业是为打破外商垄断、重新夺回本地市场而产生的,符合近代中国工业“冲击—反应”发展模式。由于其规模弱小,并未形成与外资企业开展“商战”的能力,但折射出的国人不畏困难、勇于探索的奋进精神和不屈不挠、自强不息的抗争精神,时至今日仍然值得颂扬。

基于产教融合的项目式教学实践

借鉴德国“学习工厂”的经验,按照企业批量生产模式,建设面向真实产品生产的工程实践教学平台,构建“服务学习、真实体验”的工程实践学习情境,开展无限接近企业批量生产的全流程工程实践活动。串联工程问题,将工业生产过程成功转化为实践教学内容,实现企业生产与工程教育的深度融合。在教学过程中,探索以学生为中心的多元化工程训练教学模式,培养学生的工程观、质量观、系统观,为开展产教融合的创新创业教育提供新途径。

辽宁省黄瓜工厂化育苗产业现状及发展关键分析

黄瓜在辽宁省蔬菜种植面积占比大,开展黄瓜工厂化育苗研究对于提高农业生产效率、保障农产品质量安全、促进辽宁农业可持续发展具有重要意义。该文阐述了辽宁省蔬菜工厂化育苗产业的现状,分析了黄瓜工厂化育苗发展中存在的问题,并提出了相应的发展建议和对策,以期为辽宁省黄瓜工厂化育苗发展的科学规划提供参考。

基于多项式代理模型的车顶绝缘子背风侧沿面压力优化研究

高速气流下,车顶绝缘子背风侧出现低气压会使得闪络电压降低,影响列车安全运行,为了改善车顶绝缘子背风侧的低气压现象,使用代理模型对车顶绝缘子结构参数进行优化。在车顶绝缘子结构参数上选取了伞裙上、下倾角以及伞裙间距作为因子,以绝缘子背风侧沿面压力的最小值作为响应,采用全因子试验设计方法获取样本数据,并对因子的主效应和交互效应进行分析,在此基础上建立多项式代理模型,进一步得到最佳的结构参数,最后进行闪络试验验证其有效性。结果表明:伞裙上、下倾角的主效应与伞裙间距相比更加显著,各因子之间没有显著的交互效应;最佳参数:伞裙上、下倾角分别为8°和0°,伞裙间距为45mm,背风侧沿面压力最小值提高了25.62%,同时压力平均值提高了42.47%;在100m/s的风速条件下,车顶绝缘子的闪络电压提高了16.80%。研究结果可以为车顶绝缘子结构设计提供参考。