A model- and simulation-based approach for tolerancing and verifying the functional capability of micro/nano-structured workpieces

The evaluation of functional features of manufactured workpieces is based on GO- and NO-GO-test results, which are obtained by comparing measured geometric characteristics with nominal dimensions and tolerances specified by the designer. These geometrical specifications are based on a tolerancing system, which was originally defined for the function mating capability. Against the background of upcoming lots of other new functions (like reduction of flow resistance, light absorption, reduction of friction, diffraction of light, self-cleaning or mass transmission) are to be realized with our products – particularly by micro- and nano scaled features. If the verification process will deliver the prediction of the achievable degree of functionality, the usability of a part can be assessed more accurately and in consequence quality and economics can be improved. So, a new principle for tolerancing and verifying turns out to be necessary. In this paper the fundamental deficit of the actual tolerancing and specification systems GPS and ASME Y14.5 is derived and the path for enlarging the system by preposing a functional model is shown. To verify the functional capability of the workpieces an approach based on simulations done with the parameterized mathematical–physical model of the function is suggested. Advantages of this approach will be discussed and demonstrated by examples with microstructured inking rolls, crankshafts and injection valves.     

Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

Achieving Rich and Active Alkaline Hydrogen Evolution Heterostructures via Interface Engineering on 2D 1T‐MoS2 Quantum Sheets

Large‐scale production of hydrogen from water‐alkali electrolyzers is impeded by the sluggish kinetics of hydrogen evolution reaction (HER) electrocatalysts. The hybridization of an acid‐active HER catalyst with a cocatalyst at the nanoscale helps boost HER kinetics in alkaline media. Here, it is demonstrated that 1T–MoS₂ nanosheet edges (instead of basal planes) decorated by metal hydroxides form highly active ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ sites, the fabricated 1T–MoS₂ QS/Ni(OH)₂ hybrid (quantum sized 1T–MoS₂ sheets decorated with Ni(OH)₂ via interface engineering) only requires overpotentials of 57 and 112 mV to drive HER current densities of 10 and 100 mA cm^?2, respectively, and has a low Tafel slope of 30 mV dec^?1 in 1 m KOH. So far, this is the best performance for MoS₂‐based electrocatalysts and the 1T–MoS₂ QS/Ni(OH)₂ hybrid is among the best‐performing non‐Pt alkaline HER electrocatalysts known. The HER process is durable for 100 h at current densities up to 500 mA cm^?2. This work not only provides an active, cost‐effective, and robust alkaline HER electrocatalyst, but also demonstrates a design strategy for preparing high‐performance catalysts based on edge‐rich 2D quantum sheets for other catalytic reactions.     

Effects of different carbon sources and C/N values on nonvolatile taste components of Pleurotus eryngii

Pleurotus eryngii, the second largest industrial cultivation mushroom in China, is usually cultivated on substrates mainly consisting of sawdust and corncob. In this study, experiments were performed to determine the effects of different carbon sources and C/N values on nonvolatile taste components of P. eryngii. The effects of different carbon sources on nonvolatile taste components levels revealed that sawdust was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while corncob was beneficial to high contents of carbohydrate, polysaccharides and trehalose. At the similar C/N values, relatively higher sawdust content was beneficial to umami amino acid production, while relatively higher corncob content was beneficial to high contents of carbohydrate, polysaccharides and mannitol. Higher C/N value was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while lower C/N value was beneficial to high contents of carbohydrate, polysaccharides and trehalose. These results provided information for P. eryngii fruit body industrial cultivation to obtain specific nonvolatile taste components with high levels.     

Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

Reactive Oxygen and Nitrogen Species in Defense/Stress Responses Activated by Chitosan in Sycamore Cultured Cells

Chitosan (CHT) is a non-toxic and inexpensive compound obtained by deacetylation of chitin, the main component of the exoskeleton of arthropods as well as of the cell walls of many fungi. In agriculture CHT is used to control numerous diseases on various horticultural commodities but, although different mechanisms have been proposed, the exact mode of action of CHT is still unknown. In sycamore (Acer pseudoplatanus L.) cultured cells, CHT induces a set of defense/stress responses that includes production of H₂O₂ and nitric oxide (NO). We investigated the possible signaling role of these reactive molecules in some CHT-induced responses by means of inhibitors of production and/or scavengers. The results show that both reactive nitrogen and oxygen species are not only a mere symptom of stress conditions but are involved in the responses induced by CHT in sycamore cells. In particular, NO appears to be involved in a cell death form induced by CHT that shows apoptotic features like DNA fragmentation, increase in caspase-3-like activity and release of cytochrome c from the mitochondrion. On the contrary, reactive oxygen species (ROS) appear involved in a cell death form induced by CHT that does not show these apoptotic features but presents increase in lipid peroxidation.     

In Silico Analysis and Experimental Validation of Active Compounds from Cichorium intybus L. Ameliorating Liver Injury

This study aimed at investigating the possible mechanisms of hepatic protective activity of Cichorium intybus L. (chicory) in acute liver injury. Pathological observation, reactive oxygen species (ROS) detection and measurements of biochemical indexes on mouse models proved hepatic protective effect of Cichorium intybus L. Identification of active compounds in Cichorium intybus L. was executed through several methods including ultra performance liquid chromatography/time of flight mass spectrometry (UPLC-TOF-MS). Similarity ensemble approach (SEA) docking, molecular modeling, molecular docking, and molecular dynamics (MD) simulation were applied in this study to explore possible mechanisms of the hepato-protective potential of Cichorium intybus L. We then analyzed the chemical composition of Cichorium intybus L., and found their key targets. Furthermore, in vitro cytological examination and western blot were used for validating the efficacy of the selected compounds. In silico analysis and western blot together demonstrated that selected compound 10 in Cichorium intybus L. targeted Akt-1 in hepatocytes. Besides, compound 13 targeted both caspase-1 and Akt-1. These small compounds may ameliorate liver injury by acting on their targets, which are related to apoptosis or autophagy. The conclusions above may shed light on the complex molecular mechanisms of Cichorium intybus L. acting on hepatocytes and ameliorating liver injury.     

Developmental and Reproductive Effects of Iron Oxide Nanoparticles in Arabidopsis thaliana

Increasing use of iron oxide nanoparticles in medicine and environmental remediation has led to concerns regarding exposure of these nanoparticles to the public. However, limited studies are available to evaluate their effects on the environment, in particular on plants and food crops. Here, we investigated the effects of positive (PC) and negative (NC) charged iron oxide (Fe₂O₃) nanoparticles (IONPs) on the physiology and reproductive capacity of Arabidopsis thaliana at concentrations of 3 and 25 mg/L. The 3 mg/L treated plants did not show evident effects on seeding and root length. However, the 25 mg/L treatment resulted in reduced seedling (positive-20% and negative-3.6%) and root (positive-48% and negative-negligible) length. Interestingly, treatment with polyethylenimine (PEI; IONP-PC coating) also resulted in reduced root length (39%) but no change was observed with polyacrylic acid (PAA; IONP-NC coating) treatment alone. However, treatment with IONPs at 3 mg/L did lead to an almost 5% increase in aborted pollen, a 2%–6% reduction in pollen viability and up to an 11% reduction in seed yield depending on the number of treatments. Interestingly, the treated plants did not show any observable phenotypic changes in overall size or general plant structure, indicating that environmental nanoparticle contamination could go dangerously unnoticed.     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.