Towards Modular and Plug-and-Produce Manufacturing Apps

Industry 4.0 redefines manufacturing systems as smart and connected systems where software solutions provide additional capabilities to the manufacturing equipment. However, the connection of manufacturing equipment with software solutions is challenging due to poor interoperability between different original equipment manufacturers (OEMs), making it difficult to integrate into the manufacturing system. Hence, there is a need for a methodology to develop modular "plug-and-produce" applications in the manufacturing domain to meet the requirements of Industry 4.0. This work investigates the "appification" of manufacturing processes where the goal is to subdivide the process into independent, re-configurable digital manufacturing applications. In this context, "appification" means separating the digital implementation from the physical implementation of the system by making the former modular and independent so that digital implementations can be re-used without depending on the physical parts of the system. In this paper a framework for the development of such manufacturing "apps" is presented. This framework consists of four main elements: a modular plug-and-produce architecture, a manufacturing apps development kit, a communication protocol, and a construction methodology. The modular plug-and-produce architecture is developed using the recent advances in microservices, containerization, and communication technologies. The manufacturing apps development kit (MAPPDK) has been developed to facilitate the implementation of manufacturing apps using high-level programming languages. MAPPDK allows to control manufacturing equipment from external computational devices. The methodology for developing different modules for different types of manufacturing processes is also provided. The proof of concept is shown experimentally by the "appification" of a sorting process using an industrial robot arm, a gripping end-effector, a third-party vision camera, and an intelligent vision module

Semantic models and knowledge graphs as manufacturing system reconfiguration enablers

Reconfigurable Manufacturing System (RMS) provides a cost-effective approach for manufacturers to adapt to fluctuating market demands by reconfiguring assets through automated analysis of asset utilization and resource allocation. Achieving this automation necessitates a clear understanding, formalization, and documentation of asset capabilities and capacity utilization. This paper introduces a unified model employing semantic modeling to delineate the manufacturing sector's capabilities, capacity, and reconfiguration potential. The model illustrates the integration of these three components to facilitate efficient system reconfiguration. Additionally, semantic modeling allows for the capture of historical experiences, thus enhancing long-term system reconfiguration through a knowledge graph. Two use cases are presented: capability matching and reconfiguration solution recommendation based on the proposed model. A thorough explication of the methodology and outcomes is provided, underscoring the advantages of this approach in terms of heightened efficiency, diminished costs, and augmented productivity

Sphingosine-1-phosphate activates chemokine-promoted myeloma cell adhesion and migration involving α4β1 integrin function

51 p.-7 fig.-1 tab.-2 fig.supl.Myeloma cell adhesion dependent on α4β1 integrin is crucial for the progression of multiple myeloma (MM). The α4β1-dependent myeloma cell adhesion is up-regulated by the chemokine CXCL12, and pharmacological blockade of the CXCL12 receptor CXCR4 leads to defective myeloma cell homing to bone marrow (BM). Sphingosine-1-phosphate (S1P) regulates immune cell trafficking upon binding to G-protein-coupled receptors. Here we show that myeloma cells express S1P1, a receptor for S1P. We found that S1P up-regulated the α4β1-mediated myeloma cell adhesion and transendothelial migration stimulated by CXCL12. S1P promoted generation of high-affinity α4β1 that efficiently bound the α4β1 ligand VCAM-1, a finding that was associated with S1P-triggered increase in talin-β1 integrin association. Furthermore, S1P cooperated with CXCL12 for enhancement of α4β1-dependent adhesion strengthening and spreading. CXCL12 and S1P activated the DOCK2-Rac1 pathway, which was required for stimulation of myeloma cell adhesion involving α4β1. Moreover, in vivo analyses indicated that S1P contributes to optimizing the interactions of MM cells with the BM microvasculture and for their lodging inside the bone marrow. The regulation of α4β1-dependent adhesion and migration of myeloma cells by CXCL12-S1P combined activities might have important consequences for myeloma disease progressionThis study was supported by the Ministerio de Ciencia e Innovación (Grant Nos SAF2011-24022 to JT, SAF2009-07035 to AGP, SAF2009-11037 to AH, RD06/0020/0011 to JT and AGP, RD06/0020/0006 to NCG and MG and PI081825 to MG), the Comunidad de Madrid (Grant No. P2010/BMD-2314 to AGP, JT and AH) and the Fundación de Investigación Médica Mutua Madrileña (to AGP and MG). AH was also funded by the FP7-People-2009-RG (Grant No. 246655), a Ramón y Cajal Fellowship (Grant No. RYC-2007-00697) and the Pro-CNIC Foundation.Peer reviewe

Lifetime mental health problems in Adult Lower Secondary Education: a student survey

Background/Objective: Adult Lower Secondary Education is an education program for basic qualifications for the labor market. Our study aimed to compare lifetime mental health problems between current Adult Lower Secondary Education students and higher Vocational Education students, as the former constitutes a highly distinct and understudied group. Methods: Findings were based on a cross-sectional self-report survey. Lifetime relative odds of occurrence of mental disorders [i.e., psychiatric disorders typically diagnosed in adults, learning difficulties or deficit hyperactivity disorder (ADHD)] were compared between Adult Lower Secondary Education students (n = 134) and Vocational Education students (n = 149). Results: While the frequency of mental health problems was high in both groups, psychiatric disorders typically diagnosed in adults were more common in Adult Lower Secondary Education students than among other students. Vocational Education students reported higher rates of ADHD. Conclusion: There is a need for additional psychological resources for Adult Lower Secondary Education students, an educational level that is the last path for many to acquire a basic degree

Recall of government healthy eating campaigns by consumers in five countries.

OBJECTIVE: To examine awareness and recall of healthy eating public education campaigns in five countries. DESIGN: Data were cross-sectional and collected as part of the 2018 International Food Policy Study. Respondents were asked whether they had seen government healthy eating campaigns in the past year; if yes (awareness), they were asked to describe the campaign. Open-ended descriptions were coded to indicate recall of specific campaigns. Logistic models regressed awareness of healthy eating campaigns on participant country, age, sex, ethnicity, education, income adequacy and BMI. Analyses were also stratified by country. SETTING: Online surveys. PARTICIPANTS: Participants were Nielsen panelists aged ≥18 years in Australia, Canada, Mexico, UK and the USA (n 22 463). RESULTS: Odds of campaign awareness were higher in Mexico (50·9 %) than UK (18·2 %), Australia (17·9 %), the USA (13·0 %) and Canada (10·2 %) (P 0·05), and age was associated with campaign awareness in UK (P < 0·001). Common keywords in all countries included sugar/sugary drinks, fruits and vegetables, and physical activity. The top five campaigns recalled were Chécate, mídete, muévete (Mexico), PrevenIMSS (Mexico), Change4Life (UK), LiveLighter® (Australia), and Actívate, Vive Mejor (Mexico). CONCLUSIONS: In Mexico, UK and Australia, comprehensive campaigns to promote healthy lifestyles appear to have achieved broad, population-level reach

Phosphate Deficiency Negatively Affects Early Steps of the Symbiosis between Common Bean and Rhizobia

Phosphate (Pi) deficiency reduces nodule formation and development in different legume species including common bean. Despite significant progress in the understanding of the genetic responses underlying the adaptation of nodules to Pi deficiency, it is still unclear whether this nutritional deficiency interferes with the molecular dialogue between legumes and rhizobia. If so, what part of the molecular dialogue is impaired? In this study, we provide evidence demonstrating that Pi deficiency negatively affects critical early molecular and physiological responses that are required for a successful symbiosis between common bean and rhizobia. We demonstrated that the infection thread formation and the expression of PvNSP2, PvNIN, and PvFLOT2, which are genes controlling the nodulation process were significantly reduced in Pi-deficient common bean seedlings. In addition, whole-genome transcriptional analysis revealed that the expression of hormones-related genes is compromised in Pi-deficient seedlings inoculated with rhizobia. Moreover, we showed that regardless of the presence or absence of rhizobia, the expression of PvRIC1 and PvRIC2, two genes participating in the autoregulation of nodule numbers, was higher in Pi-deficient seedlings compared to control seedlings. The data presented in this study provides a mechanistic model to better understand how Pi deficiency impacts the early steps of the symbiosis between common bean and rhizobia

Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning

In manufacturing, different costs must be considered when selecting the optimal manufacturing configuration. Costs include manufacturing costs, material costs, labor costs, and overhead costs. Optimal manufacturing configurations are those that minimize production criteria, such as costs, production speed, and flexibility, while still meeting the required production levels and quality standards. To find the optimal manufacturing configuration, manufacturers often use a combination of traditional techniques, e.g., mathematical modeling, simulation, and optimization, to evaluate the tradeoffs between different cost factors and identify configurations that provide the best balance between cost and performance. However, these techniques may require long development and simulation time, and/or may require expert knowledge. This paper presents a method for selecting the optimal manufacturing configuration, focusing on cost optimization, using a reinforcement learning (RL) approach for sequential decision-making. The proposed method involves developing a RL environment, requiring lower development and simulation times than traditional techniques, that captures the incurred costs, recurring costs, production rates, and setup times of manufacturing configurations. The problem is then solved using the Proximal Policy Optimization algorithm to identify the configuration that minimizes costs while still meeting the required production levels and quality standards. The effectiveness of the proposed method is validated through a machining process planning case study with multiple cost factors and production constraints. In particular, the machining process plan was developed for an industry-relevant product prototype. The results show that the proposed method can find solutions that are robust to stochastic noise, providing valuable insights for manufacturers looking to optimize manufacturing operations

Estimating Fixed Effects: Perfect Prediction and Bias in Binary Response Panel Models, with an Application to the Hospital Readmissions Reduction Program

The maximum likelihood estimator for the regression coefficients, β, in a panel binary response model with fixed effects can be severely biased if N is large and T is small, a consequence of the incidental parameters problem. This has led to the development of conditional maximum likelihood estimators and, more recently, to estimators that remove the O(T–1) bias in β^. We add to this literature in two important ways. First, we focus on estimation of the fixed effects proper, as these have become increasingly important in applied work. Second, we build on a bias-reduction approach originally developed by Kosmidis and Firth (2009) for cross-section data, and show that in contrast to other proposals, the new estimator ensures finiteness of the fixed effects even in the absence of within-unit variation in the outcome. Results from a simulation study document favourable small sample properties. In an application to hospital data on patient readmission rates under the 2010 Affo

Decentralization and regional government size in Spain

The aim of this paper is to investigate the impact of fiscal decen- tralization on the size of regional governments in Spain, by controlling for economies of scale, interregional heterogeneity and institutional framework. We study it over 1985 to 2004 using a panel dataset of seventeen spanish regions. The results can be easily summarized. Firstly, it supports the classic public goods theory of a trade-off-between the economic benefits of size and the costs of heterogeneity. Secondly, it doesn’t reject the “Leviathan” hypoth- esis and neither does the “common pool” hypothesis. Thirdly, by contrast, the paper partly rejects the “Wallis”’ hypothesis. It argues that government size is mediated by financial resources obtained through intergovernmental grants, consistent with welfare economics and positive economic policies. We conclude that later advances in the decentralisation process must be compatible with the goal of reducing fiscal imbalances that emanate from the vertical structure of fiscal power.info:eu-repo/semantics/publishedVersio

Using Unexpected Recalls to Examine the Long-Term Earnings Effects of Job Displacement

This paper examines the long-term earnings consequences of permanent layoffs initiated during the early 1990s, using a sample of Massachusetts workers who enrolled in Job Training Partnership Act Title III programs, and who remained strongly attached to the state's labor force. The comparison group is formed by workers who were unexpectedly recalled. On average, recalled workers incurred substantial annual earnings reductions upon reemployment. Nevertheless, one decade later, permanently displaced workers were still earning between 11 and 17 percent less per year than recalled workers with comparable pre-layoff skills and experience. Workers with limited education experienced particularly large earnings reductions from permanent job loss