Process Driven Access Control and Authorisation Approach

Compliance to regulatory requirements is key to successful collaborative business process execution. The review the EU general data protection regulation (GDPR) brought to the fore the need to comply with data privacy. Access control and authorization mechanisms in workflow management systems based on roles, tasks and attributes do not sufficiently address the current complex and dynamic privacy requirements in collaborative business process environments due to diverse policies. This paper proposes process driven authorization as an alternative approach to data access control and authorization where access is granted based on legitimate need to accomplish a task in the business process. Due to vast sources of regulations, a mechanism to derive and validate a composite set of constraints free of conflicts and contradictions is presented. An extended workflow tree language is also presented to support constraint modeling. An industry case Pick and Pack process is used for illustration

Predictive Maintenance in Industry 4.0

In the context of Industry 4.0, the manufacturing-related processes have shifted from conventional processes within one organization to collaborative processes cross different organizations, for example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. The development and application of the Internet of things, i.e. smart devices and sensors increases the availability and collection of diverse data. With new technologies, such as advanced data analytics and cloud computing provide new opportunities for flexible collaborations as well as effective optimizing manufacturing-related processes, e.g. predictive maintenance. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machinery using various analyses. RAMI4.0 is a framework for thinking about the various efforts that constitute Industry 4.0. It spans the entire product life cycle & value stream axis, hierarchical structure axis and functional classification axis. The Industrial Data Space (now International Data Space) is a virtual data space using standards and common governance models to facilitate the secure exchange and easy linkage of data in business ecosystems. It thereby provides a basis for creating and using smart services and innovative business processes, while at the same time ensuring digital sovereignty of data owners. This paper looks at how to support predictive maintenance in the context of Industry 4.0. Especially, applying RAMI4.0 architecture supports the predictive maintenance using the FIWARE framework, which leads to deal with data exchanging among different organizations with different security requirements as well as modularizing of related functions

Predictive Maintenance in Industry 4.0

In the context of Industry 4.0, the manufacturing-related processes have shifted from conventional processes within one organization to collaborative processes cross different organizations, for example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. The development and application of the Internet of things, i.e. smart devices and sensors increases the availability and collection of diverse data. With new technologies, such as advanced data analytics and cloud computing provide new opportunities for flexible collaborations as well as effective optimizing manufacturing-related processes, e.g. predictive maintenance. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machinery using various analyses. RAMI4.0 is a framework for thinking about the various efforts that constitute Industry 4.0. It spans the entire product life cycle & value stream axis, hierarchical structure axis and functional classification axis. The Industrial Data Space (now International Data Space) is a virtual data space using standards and common governance models to facilitate the secure exchange and easy linkage of data in business ecosystems. It thereby provides a basis for creating and using smart services and innovative business processes, while at the same time ensuring digital sovereignty of data owners. This paper looks at how to support predictive maintenance in the context of Industry 4.0. Especially, applying RAMI4.0 architecture supports the predictive maintenance using the FIWARE framework, which leads to deal with data exchanging among different organizations with different security requirements as well as modularizing of related functions

Removal of antibiotics (sulfamethazine, tetracycline and chloramphenicol) from aqueous solution by raw and nitrogen plasma modified steel shavings

© 2017 Elsevier B.V. The removal of sulfamethazine (SMT), tetracycline (TC) and chloramphenicol (CP) from synthetic wastewater by raw (M3) and nitrogen plasma modified steel shavings (M3-plN2) was investigated using batch experiments. The adsorption kinetics could be expressed by both pseudo-first-order kinetic (PFO) and pseudo-second-order kinetic (PSO) models, where correlation coefficient r2 values were high. The values of PFO rate constant k1p and PSO rate constant k2p decreased as SMT-M3 > SMT-M3-plN2 > TC-M3-plN2 > TC-M3 > CP-M3 > CP-M3-plN2 and SMT-M3 > SMT-M3-plN2 > TC-M3 > TC-M3-plN2 > CP-M3 > CP-M3-plN2, respectively. Solution pH, adsorbent dose and temperature exerted great influences on the adsorption process. The plasma modification with nitrogen gas cleaned and enhanced 1.7-fold the surface area and 1.4-fold the pore volume of steel shavings. Consequently, the removal capacity of SMT, TC, CP on the adsorbent rose from 2519.98 to 2702.55, 1720.20 to 2158.36, and 2772.81 to 2920.11 μg/g, respectively. Typical chemical states of iron (XPS in Fe2p3 region) in the adsorbents which are mainly responsible for removing antibiotics through hydrogen bonding, electrostatic and non- electrostatic interactions and redox reaction were as follows: Fe3O4/Fe2 +, Fe3O4/Fe3 +, FeO/Fe2 + and Fe2O3/Fe3 +

Large-scale dewetting assembly of gold nanoparticles for plasmonic enhanced upconversion nanoparticles

© 2018 The Royal Society of Chemistry. Plasmonic nanostructures have been broadly investigated for enhancing many photophysical properties of luminescent nanomaterials. Precisely controlling the distance between the plasmonic nanostructure and the luminescent material is challenging particularly for the large-scale production of individual nanoparticles. Here we report an easy and reliable method for the large-scale dewetting of plasmonic gold nanoparticles onto core-shell (CS) upconversion nanoparticles (UCNPs). A commensurate NaYF4 shell with a thickness between 5 nm and 15 nm is used as a tunable spacer to control the distance between the UCNP and the plasmonic gold nanoparticles. The upconversion emission intensity of single gold decorated core-inert shell (Au-CS) UCNPs is quantitatively characterized using a scanning confocal microscope. The results demonstrate the highest feasible enhancement of upconversion emission and a record reduction in lifetime for UCNPs fabricated in this manner. The Au-CS UCNPs are further investigated by simulation and synchrotron near edge X-ray absorption fine structure (NEXAFS) analysis

Tissue-Engineered Trachea Consisting of Electrospun Patterned sc-PLA/GO-g-IL Fibrous Membranes with Antibacterial Property and 3D-Printed Skeletons with Elasticity

In this study, a tissue-engineered trachea, consisting of multilevel structural electrospun polylactide (PLA) membranes enveloping 3D-printed thermoplastic polyurethane (TPU) skeletons, was developed to create a mechanically robust, antibacterial and bioresorbable graft for the tracheal reconstruction. The study design incorporated two distinct uses of stereocomplex PLA: patterned electrospun fibers to enhance tissue integration compared to the random layered fibers, meanwhile possessing good antibacterial property; and 3D-printed TPU scaffold with elasticity to provide external support and protection. Herein, ionic liquid (IL)-functioned graphene oxide (GO) was synthesized and presented enhanced mechanical and hydrophilicity properties. More interesting, antibacterial activity of the GO-g-IL modified PLA membranes were proved by Escherichia coli and Staphylococcus aureus, showing superior antibacterial effect compared to single GO or IL. The synergistic antibacterial effect could be related to that GO break cytomembrane of bacteria by its extremely sharp edges, while IL works by electrostatic interaction between its cationic structures and electronegative phosphate groups of bacteria membranes, leading to the loss of cell electrolyte and cell death. Hence, after L929 fibroblast cells were seeded on patterned fibrous membranes with phenotypic shape, further effective cell infiltration, cell proliferation and attachment were observed. In addition, the tissue-engineered trachea scaffolds were implanted into rabbit models. The in vivo result confirmed that the scaffolds with patterned membranes manifested favorable biocompatibility and promoted tissue regeneration