Improvement of type declaration of the IEC 61499 basic function block for developing applications of cyber-physical system

The cyber-physical system relies on a network of physical devices. The IEC 61499 standard entails a systematic solution to distributed system development. The basic function block (BFB) is the essential construct of the IEC 61499 architecture. However, the execution semantics of the BFB is not well defined by the standard, which leads to a part of the semantic ambiguity. In this paper, we contribute to improve BFB type declaration by proposing a compact interface model and a strict execution control chart (ECC) model. The improved BFB exhibits less semantic ambiguity, is easier to be created, and is more convenient to be applied in a function block network than the standard BFB

Prolonged drought regulates the silage quality of maize (Zea mays L.): Alterations in fermentation microecology

Prolonged drought stress caused by global warming poses a tremendous challenge to silage production of maize. Drought during maize growth and development resulted in altered micro-environment for silage fermentation. How fermentation of silage maize responds to moisture scales remains uncharted territory. In this research, Maize water control trials were conducted and the silage quality and microbial community of drought-affected maize were determined. The results showed that drought stress significantly reduced the dry matter but increased root-to-shoot ratio, soluble sugar and malonaldehyde content in maize. Before fermentation, the crude protein, crude ash and acid detergent fiber contents were significantly increased but the ether extract content was decreased under drought. The crude protein and acid detergent fiber were significantly decreased in the drought affected group after fermentation. Furthermore, water stress at maize maturity stage greatly reduced the number of total bacteria in silage fermentation but increased the proportion of the lactobacillus and lactic acid content of silage. Drought stress alters the microbial ecosystem of the fermentation process and reconstitutes the diversity of the bacterial community and its metabolites. This study provides a theoretical basis for the study of changes in silage fermentation as affected by abiotic stresses

Implementing Smart Factory of Industrie 4.0: An Outlook

With the application of Internet of Things and services to manufacturing, the fourth stage of industrialization, referred to as Industrie 4.0, is believed to be approaching. For Industrie 4.0 to come true, it is essential to implement the horizontal integration of inter-corporation value network, the end-to-end integration of engineering value chain, and the vertical integration of factory inside. In this paper, we focus on the vertical integration to implement flexible and reconfigurable smart factory. We first propose a brief framework that incorporates industrial wireless networks, cloud, and fixed or mobile terminals with smart artifacts such as machines, products, and conveyors. Then, we elaborate the operational mechanism from the perspective of control engineering, that is, the smart artifacts form a self-organized system which is assisted with the feedback and coordination blocks that are implemented on the cloud and based on the big data analytics. In addition, we outline the main technical features and beneficial outcomes and present a detailed design scheme. We conclude that the smart factory of Industrie 4.0 is achievable by extensively applying the existing enabling technologies while actively coping with the technical challenges

Knowledge Reasoning with Semantic Data for Real-Time Data Processing in Smart Factory

The application of high-bandwidth networks and cloud computing in manufacturing systems will be followed by mass data. Industrial data analysis plays important roles in condition monitoring, performance optimization, flexibility, and transparency of the manufacturing system. However, the currently existing architectures are mainly for offline data analysis, not suitable for real-time data processing. In this paper, we first define the smart factory as a cloud-assisted and self-organized manufacturing system in which physical entities such as machines, conveyors, and products organize production through intelligent negotiation and the cloud supervises this self-organized process for fault detection and troubleshooting based on data analysis. Then, we propose a scheme to integrate knowledge reasoning and semantic data where the reasoning engine processes the ontology model with real time semantic data coming from the production process. Based on these ideas, we build a benchmarking system for smart candy packing application that supports direct consumer customization and flexible hybrid production, and the data are collected and processed in real time for fault diagnosis and statistical analysis

Cloud-based smart manufacturing for personalized candy packing application

Industry 4.0 has been proposed to address personalized consumption demands by building cyber-physical production systems for smart manufacturing. Although cloud manufacturing and some integrated frameworks for smart factory have been presented in literatures, it still lacks industrial applications. In this paper, we use personalized candy packing application as a demonstration to illustrate our smart factory design. We first describe the component layers of the smart factory, i.e., physical devices, private cloud, client terminals, and network, to enable the smart factory to be integrated with other systems, such as banks and logistical network, to cope with personalized consumption demands. Then, we present a scheme for inter-layered interaction. As for the physical devices, we also design an intra-layered negotiation mechanism to implement dynamic reconfiguration, so that the system can support hybrid production of multi-typed products. Finally, we give experimental results to verify efficiency, self-organized process, and hybrid production paradigm of the proposed system. © 2016, Springer Science+Business Media New York

Functional Mechanism of MicroRNA-25-3p in Hilar Cholangiocarcinoma Cell Proliferation and Migration Through Regulation of Dual Specificity Phosphatase 5

Objective Hilar cholangiocarcinoma (HCCA) is a highly aggressive biliary tract tumor. microRNAs (miRs) exert dual actions in various cancers. This paper seeks to expound on the functional mechanisms of miR-25-3p/dual specificity phosphatase 5 (DUSP5) in HCCA cell proliferation and migration. Methods HCCA-related data were downloaded from GEO database to screen out differentially-expressed genes. The potential target miR (miR-25-3p) and its expression in HCCA were analyzed on Starbase. The binding relation between miR-25-3p and DUSP5 was confirmed by dual-luciferase assay. Levels of miR-25-3p and DUSP5 in FRH-0201 cells and HIBEpics were determined by RT-qPCR and Western blot. miR-25-3p and DUSP5 levels were intervened with to explore their effects on FRH-0201 cells. The apoptosis, proliferation, migration, and invasion of FRH-0201 cells were evaluated by TUNEL, CCK8, scratch healing, and Transwell assays. Flow cytometry was conducted to assess FRH-0201 cell cycle. Levels of cell cycle-related proteins were determined by Western blot. Results DUSP5 was weakly-expressed and miR-25-3p was highly-expressed in HCCA samples and cells. miR-25-3p targeted DUSP5. miR-25-3p suppressed FRH-0201 cell apoptosis and increased cell proliferation, migration, and invasion. DUSP5 overexpression partially abrogated miR-25-3p overexpression-exerted effects on FRH-0201 cells. miR-25-3p stimulated G1/S phase transition of FRH-0201 cells by targeting DUSP5. Conclusion miR-25-3p regulated HCCA cell cycle and facilitated cell proliferation and migration by targeting DUSP5

Fog Computing for Energy-Aware Load Balancing and Scheduling in Smart Factory

Due to the development of modern information technology, the emergence of the fog computing enhances equipment computational power and provides new solutions for traditional industrial applications. Generally, it is impossible to establish a quantitative energy-Aware model with a smart meter for load balancing and scheduling optimization in smart factory. With the focus on complex energy consumption problems of manufacturing clusters, this paper proposes an energy-Aware load balancing and scheduling (ELBS) method based on fog computing. First, an energy consumption model related to the workload is established on the fog node, and an optimization function aiming at the load balancing of manufacturing cluster is formulated. Then, the improved particle swarm optimization algorithm is used to obtain an optimal solution, and the priority for achieving tasks is built toward the manufacturing cluster. Finally, a multiagent system is introduced to achieve the distributed scheduling of manufacturing cluster. The proposed ELBS method is verified by experiments with candy packing line, and experimental results showed that proposed method provides optimal scheduling and load balancing for the mixing work robots

Cloud robotics: Current status and open issues

With the development of cloud computing, big data and other emerging technologies, the integration of cloud technology and multi-robot systems makes it possible to design multi-robot systems with improved energy efficiency, high real-time performance and low cost. In order to address the potential of clouds in enhancing robotics for industrial systems, this paper describes the basic concepts and development process of cloud robotics and the overall architecture of these systems. Then, the major driving forces behind the development of cloud robotics are carefully analyzed from the point of view of cloud computing, big data, open source resources, robot cooperative learning, and network connectivity. Subsequently, the key issues and challenges in the current cloud robotic systems are proposed, and some possible solutions are also given. Finally, the potential value of cloud robotic systems in different practical applications is discussed.Validerad; 2016; Nivå 2; 20160621 (andbra)</p

SARS-CoV-2 viral genes Nsp6, Nsp8, and M compromise cellular ATP levels to impair survival and function of human pluripotent stem cell-derived cardiomyocytes

Abstract Background Cardiovascular complications significantly augment the overall COVID-19 mortality, largely due to the susceptibility of human cardiomyocytes (CMs) to SARS-CoV-2 virus. SARS-CoV-2 virus encodes 27 genes, whose specific impacts on CM health are not fully understood. This study elucidates the deleterious effects of SARS-CoV-2 genes Nsp6, M, and Nsp8 on human CMs. Methods CMs were derived from human pluripotent stem cells (hPSCs), including human embryonic stem cells and induced pluripotent stem cells, using 2D and 3D differentiation methods. We overexpressed Nsp6, M, or Nsp8 in hPSCs and then applied whole mRNA-seq and mass spectrometry for multi-omics analysis. Co-immunoprecipitation mass spectrometry was utilized to map the protein interaction networks of Nsp6, M, and Nsp8 within host hiPSC-CMs. Results Nsp6, Nsp8, and M globally perturb the transcriptome and proteome of hPSC-CMs. SARS-CoV-2 infection and the overexpression of Nsp6, Nsp8, or M coherently upregulated genes associated with apoptosis and immune/inflammation pathways, whereas downregulated genes linked to heart contraction and functions. Global interactome analysis revealed interactions between Nsp6, Nsp8, and M with ATPase subunits. Overexpression of Nsp6, Nsp8, or M significantly reduced cellular ATP levels, markedly increased apoptosis, and compromised Ca2+ handling in hPSC-CMs. Importantly, administration of FDA-approved drugs, ivermectin and meclizine, could restore ATP levels, thereby mitigating apoptosis and dysfunction in hPSC-CMs overexpressing Nsp6, Nsp8, or M. Conclusion Overall, our findings uncover the extensive damaging effects of Nsp6, Nsp8, and M on hPSC-CMs, underlining the crucial role of ATP homeostasis in CM death and functional abnormalities induced by these SARS-CoV-2 genes, and reveal the potential therapeutic strategies to alleviate these detrimental effects with FDA-approved drugs