Modularization of smart product service: A framework integrating smart product service blueprint and weighted complex network

Modularization of smart product service (SPS) emerges as a priority strategy to agilely satisfy the dynamic customization requirement and to flexibly response to the rapid market change. Compared with the traditional product service, the SPS have more complicated interactions between the service components due to the novel characteristics caused by the application of smart technologies. The SPS modularization presents great differences from the identification of service component, correlation evaluation and module partition with the traditional product service modularization. However, most the existing research mainly focuses on the context of traditional product service, while containing scant study of smart product service. Therefore, this study proposes a hybrid framework for SPS modularization. In the framework, a cyber-physical product service blueprint is firstly proposed to represent the SPS operation process and identify the SPS components. Then, a rough-fuzzy correlation matrix is presented to determine the comprehensive interdependence between all pairs of SPS components with fully considering the hybrid decision uncertainties involved in the evaluation process, i.e., intrapersonal linguistic vagueness and interpersonal preference diversity. After that, the complex network theory is used to construct the SPS network and a modified Girvan-Newman algorithm is adopted for the SPS module partition. Finally, an illustrative modularization case of smart gearbox maintenance service and some caparisons with other methods demonstrate the feasibility and validity of the proposed approach

Efficient L 0 resampling of point sets

Abstract(#br)The point data captured by laser scanners or consumer depth cameras are often contaminated with severe noises and outliers. In this paper, we propose a resampling method in an L 0 minimization framework to process such low quality data. Our framework can produce a set of clean, uniformly distributed, geometry-maintaining and feature-preserving oriented points. The L 0 norm improves the robustness to noises (outliers) and the ability to keep sharp features, but introduces a significant efficiency degradation. To further improve the efficiency of our L 0 point set resampling, we propose two accelerating algorithms including optimization-based local half-sampling and interleaved regularization. As demonstrated by the experimental results, the accelerated method is about an order of magnitude faster than the original, while achieves state-of-the-art point set consolidation performance

Overexpression of miR-489 enhances efficacy of 5-fluorouracil-based treatment in breast cancer stem cells by targeting XIAP

Population of cancer stem cells (CSCs) in breast cancer is reported to be resistant to chemotherapy. Furthermore, many cases of treatment failure are induced by the chemoresistance of CSCs in breast cancer patients. Therefore, novel strategies should be explored urgently to reverse drug-resistance in breast cancer stem cells (BCSCs). In this study, we isolated and cultured the BCSCs from the T-47D and SKBR3 breast cancer cell lines. We observed significant resistance to 5-fluorouracil in BCSCs. Mechanically, we found that expression of miR-489 was decreased in BCSCs. Furthermore, overexpression of miR-489 was found to increase the cytotoxicity of 5-fluorouracil to BCSCs. XIAP, a key anti-apoptotic protein, was proved to be the target of miR-489. We found that enforced expression of XIAP through its recombinant expression vector abolished the effect of miR-489 on reversing the 5-fluorouracil resistance. On the contrary, embelin, a XIAP specific inhibitor, was found to sensitize BCSCs to 5-fluorouracil similarly with miR-489. In summary, our data demonstrate that introduction with miR-489 represents a novel strategy to enhance efficacy of 5-fluorouracil-based treatment in BCSCs

Effect of the LncRNA GAS5-MiR-23a-ATG3 Axis in Regulating Autophagy in Patients with Breast Cancer

Background/Aims: An increasing body of evidence shows that long noncoding RNAs (lncRNAs) are involved in many different cancers. In this study, we aimed to investigate the competing endogenous RNA (ceRNA)-dependent mechanism by which the lncRNA GAS5 contributes to the development of breast cancer. Methods: A total of 68 breast cancer patients were enrolled, and breast cancer and adjacent normal tissues were collected. The human breast cancer cell lines MDA-MB-231, MDA-MB-453, BT549, SK-BR-3 and MCF-7 and human breast cell line MCF10A were utilized in this study. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blotting were performed to detect expression of relative factors. RNA immunoprecipitation (RIP) was used to evaluate the relationship between GAS5 and miR-23a, and a dual luciferase reporter gene assay was employed to assess the relationship between ATG3 and miR-23a. A subcutaneous xenograft nude mouse model was generated to examine the role of GAS5 and its regulatory pathway in autophagy. Results: GAS5 levels were frequently decreased in breast cancer tissues and cell lines, and its relatively low expression was closely related to a larger tumour size, advanced tumour-node-metastasis (TNM) stage and estrogen receptor-negative (ER-) breast cancer tissues. More importantly, we found that GAS5 promoted autophagy, with enhanced autophagosome formation after GAS5 overexpression. GAS5 was found to act as a microRNA sponge in a pathway that included miR-23a and its target gene ATG3. The GAS5-miR-23a-ATG3 axis significantly regulated autophagy in vivo and in vitro. Conclusions: In summary, we report that the GAS5-miR-23a-ATG3 axis can be regarded as a key regulator of autophagy pathways in breast cancer; it may constitute a promising biomarker and therapeutic target in the future

Understanding Data-Driven Cyber-Physical-Social System (D-CPSS) Using a 7C Framework in Social Manufacturing Context

The trend towards socialization, personalization and servitization in smart manufacturing has attracted the attention of researchers, practitioners and governments. Social manufacturing is a novel manufacturing paradigm responding to this trend. However, the current cyber–physical system (CPS) merges only cyber and physical space; social space is missing. A cyber–physical–social system (CPSS)-based smart manufacturing is in demand, which incorporates cyber space, physical space and social space. With the development of the Internet of Things and social networks, a large volume of data is generated. A data-driven view is necessary to link tri-space. However, there is a lack of systematical investigation on the integration of CPSS and the data-driven view in the context of social manufacturing. This article proposes a seven-layered framework for a data-driven CPSS (D-CPSS) along the data–information–knowledge–wisdom (DIKW) pyramid under a social manufacturing environment. The evolution, components, general model and framework of D-CPSS are illustrated. An illustrative example is provided to explain the proposed framework. Detailed discussion and future perspectives on implementation are also presented

Dynamic Optimization for IPS2 Resource Allocation Based on Improved Fuzzy Multiple Linear Regression

The study mainly focuses on resource allocation optimization for industrial product-service systems (IPS2). The development of IPS2 leads to sustainable economy by introducing cooperative mechanisms apart from commodity transaction. The randomness and fluctuation of service requests from customers lead to the volatility of IPS2 resource utilization ratio. Three basic rules for resource allocation optimization are put forward to improve system operation efficiency and cut unnecessary costs. An approach based on fuzzy multiple linear regression (FMLR) is developed, which integrates the strength and concision of multiple linear regression in data fitting and factor analysis and the merit of fuzzy theory in dealing with uncertain or vague problems, which helps reduce those costs caused by unnecessary resource transfer. The iteration mechanism is introduced in the FMLR algorithm to improve forecasting accuracy. A case study of human resource allocation optimization in construction machinery industry is implemented to test and verify the proposed model

Construction of Sustainable Digital Factory for Automated Warehouse Based on Integration of ERP and WMS

The integration and application of a warehouse system and manufacturing system has become a manufacturing problem for enterprises. The main reason is that the information control system based on automation and stereo warehouse is inconsistent with the production and management information system of the enterprise in terms of business, data, functions, etc. Based on this, this paper studies the implementation of an automated warehouse based on the integration of ERP (enterprise resource planning) and WMS (warehouse management system) with the method and technology of the intermediate table. Moreover, MES (manufacturing execution system) is the brain and the core part of a sustainable digital factory. The enterprise adopts advanced intelligent and information technology to build and deploy the MES, realize fine management and agile production, and meet the personalized needs of the market. Therefore, this paper studies the implementation path and effect based on MES from an industrial realization to construct a sustainable digital factory. The research results of this paper can improve industrial efficiency and reduce costs for enterprises in storage capacity, handling capacity, response rate, rate of error, number of operators, etc

Determination of the Topological Shape of Integral Membrane Protein Light-Harvesting Complex LH2 from Photosynthetic Bacteria in the Detergent Solution by Small-Angle X-Ray Scattering

The topological shape of the integral membrane protein light-harvesting complex LH2 from photosynthetic bacteria Rhodobacter spheroides 2.4.1 in detergent solution has been determined from synchrotron small-angle X-ray scattering data using direct curve-fitting by the ellipsoid, ab initio shape determination methods of simulated annealing algorithm and multipole expansion, respectively. The results indicate that the LH2 protein in aqueous solution is encapsulated by a monolayered detergent shell. The detergent-stabilized structure has the shape of an oblate plate, with a thickness of 40 Å, a long axis of 110 Å, and a short axis of 85 Å . After correction for the detergent shell, the shape of the LH2 core is also an oblate plate with a height of 40 Å, a long axis of 80 Å, and a short axis of 55 Å. In contrast to the cylindrical crystal structure with a height of 40 Å and a diameter of 68 Å, the molecular shape of the LH2 complex in detergent solution clearly deviates from the ringlike crystal structure, with an eccentricity found to be 0.59—consistent with the result of single molecular spectroscopy study of the isolated single LH2 molecules

A Fuzzy ANP-QFD Methodology for Determining Stakeholders in Product-Service Systems Development from Ecosystem Perspective

Recently the competition between firms is transforming from “firm vs. firm” to “ecosystem vs. ecosystem”. To fulfil the personalized customer requirements for a high-quality product-service in the age of servitization and sustainability, it is difficult for an individual actor to realize it. The product-service system (PSS) is naturally an integration of product and service. The final product-service of PSS that depends on a tangible product and intangible service, calls for value co-creation of multi-stakeholders. However, most existing related works have investigated PSS from the perspective of a supply chain or network, PSS in the view of an ecosystem of multi-stakeholders lacks sufficient exploration, especially the topic on the relationship between product-service and stakeholders. To fill the gap, this paper proposed a framework for the PSS ecosystem with quality function deployment (QFD) and fuzzy analytic network process (fuzzy ANP) to determine the stakeholders by clarifying the relationship between the final integrated product-service and stakeholders. Firstly, the PSS ecosystem structure was presented, including the stakeholders. Secondly, a model with the three-stage fuzzy ANP-QFD approach to determine stakeholders was employed. Thirdly, the specific process of the three-stage approach was presented. An illustrative case study of the automobile aftermarket was presented to verify the proposed model and approach. Discussions and future directions concluded this paper