Overview of bio nanofabric from bacterial cellulose

Nanofibers and bio-nonwoven fabrics of pure cellulose can be made from some bacteria such as Acetobacter xylinum. Bacterial cellulose fibers are very pure, 10?nm in diameter and about 0.5?micron long. The molecular formula of bacterial cellulose is similar to that of plant cellulose. Its fibers are very stiff and it has high tensile strength, high porosity, and nanofibrillar structure. They can potentially be produced in industrial quantities at greatly lowered cost and water content, and with triple the yield by a new process. This article presents a critical review of the available information on bacterial cellulose as a biological nonwoven fabric with special emphasis on its fermentative production and applications. Characteristics of bacterial cellulose biofabric with respect to its structure and physicochemical properties are discussed. Current and potential applications of bacterial cellulose in textile, nonwoven cloth, paper, films, synthetic fiber coating, food, pharmaceutical, and other industries are also presented.     

Saffron (Crocus sativus L.) increases glucose uptake and insulin sensitivity in muscle cells via multipathway mechanisms

Saffron (Crocus sativus Linn.) has been an important subject of research in the past two decades because of its various biological properties, including anti-cancer, anti-inflammatory, and anti-atherosclerotic activities. On the other hand, the molecular bases of its actions have been scarcely understood. Here, we elucidated the mechanism of the hypoglycemic actions of saffron through investigating its signaling pathways associated with glucose metabolism in C₂C₁₂ skeletal muscle cells. Saffron strongly enhanced glucose uptake and the phosphorylation of AMPK (AMP-activated protein kinase)/ACC (acetyl-CoA carboxylase) and MAPKs (mitogen-activated protein kinases), but not PI 3-kinase (Phosphatidylinositol 3-kinase)/Akt. Interestingly, the co-treatment of saffron and insulin further improved the insulin sensitivity via both insulin-independent (AMPK/ACC and MAPKs) and insulin-dependent (PI 3-kinase/Akt and mTOR) pathways. It also suggested that there is a crosstalk between the two signaling pathways of glucose metabolism in skeletal muscle cells. These results could be confirmed from the findings of GLUT4 translocation. Taken together, AMPK plays a major role in the effects of saffron on glucose uptake and insulin sensitivity in skeletal muscle cells. Our study provides important insights for the possible mechanism of action of saffron and its potential as a therapeutic agent in diabetic patients.     

Two-stage robust energy management of a hybrid charging station integrated with the photovoltaic system

The optimal management of charging stations has become a critical issue in recent years. In this paper, the energy management of a hybrid charging station composed of an electrolyzer, fuel cell and hydrogen storage is analyzed that is integrated with a photovoltaic system. As well, the station is connected to the local power market to increase flexibility and it is assumed that the manager of the charging station is an intelligent decision-maker who tries to minimize the cost of vehicle. Due to the existence of uncertainties, generation of photovoltaic, market price and load demand are considered as uncertain parameters and two-stage stochastic programming is applied to model them. To achieve optimal management, a robust optimization approach is proposed for the uncertainty of day-ahead market price where the decision-maker adjusts the conservatism level. The presented method is linear risk-constrained programming that the results for risk-neutral and risk-averse strategies are compared. To validate the accuracy and robustness of the approach, interval-based stochastic programming is also implemented. According to the robust optimization, day-ahead market price uncertainty increases the total expected cost by about 8.9%. In return, the risk of scheduling is reduced significantly with the risk-averse strategy.     

Evolution of the crystalline and amorphous phases of high-density polyethylene subjected to equal-channel angular pressing

Polymer Bulletin - In the current research, physical and morphological properties of high-density polyethylene (HDPE) were investigated after equal-channel angular pressing (ECAP) for up to three...     

Experience on horizontal‐tube falling‐film evaporation simulation by lattice‐Boltzmann method

Complex heat and mass transfers through falling‐film or spray‐film evaporation are widely used in chemical, refrigeration, petroleum refining, desalination, and food industries. Considering that microscopic effects, like surface tension, flow, mass, and heat transfers, are interdependent phenomena, the high‐precision simulation of falling‐film evaporation through a mesoscopic method is of great importance. In the current study, the lattice‐Boltzmann method and the phase‐field model with a proper source term are used for evaporation simulation in a horizontal‐tube falling film. Here, the curvature of the tube is captured by appropriate boundary conditions. Nondimensional numbers and the geometry of the model are determined in a range of practical values. By comparing the film thickness, mass, and heat transfer with valid references in the literature, an acceptable agreement is observed, which reveals the effectiveness of this method in understanding the details and predictions. Overall, the time evolution of temperature contours and streamlines during falling‐film evaporation approves the superiority of this method in keeping details along with lower difficulty and cost compared with the classical methods.     

Parametric study of automotive composite bumper beams subjected to low-velocity impacts

Fuel efficiency and emission gas regulations are the main causes for reducing the weight of passenger cars by using composite structures. Bumper beams are one of the main structures of passenger cars that protect them from front and rear collisions. In this paper, a commercial front bumper beam made of glass mat thermoplastic (GMT) is studied and characterized by impact modeling using LS-DYNA ANSYS 5.7 according to the E.C.E. UNITED NATIONS AGREEMENT [UNITED NATIONS AGREEMENT, Uniform Provisions concerning the Approval of Vehicles with regards to their Front and Rear Protective Devices (Bumpers, etc.), E.C.E., 1994]. Three main design factors for this structure: shape, material and impact conditions are studied and the results are compared with conventional metals like steel and aluminum. Finally the aforementioned factors are characterized by proposing a high strength SMC [Composite and metallic crash performance, Hawaii University, 1999, Available from: http://www.eng.hawaii.edu/˜nejhad/BUMPER/bumper.html] (sheet molding compound) bumper instead of the current GMT. The advantages of the proposed model: equal strength and rigidity of the structure, reduction of material, ease of manufacturing by simplifying geometrical shape and reduction of production cost are studied and proved.     

A conceptual design aid environment for expert-database systems

With the actual penetration of expert systems into the business world, the question is, how the expert system idea can be used to enhance the existing information systems with more intelligence in usage and operation. This interest is not surprising due to the advancement of the fifth generation of computer technology, and avid interest in the field of Artificial Intelligence. Therefore design of an information system for an application becomes more complex, and the inability of the human designer to deal with it increases. For designing intelligent systems, we have to be able to forecast the behavior of the information system more precisely before implementing it, i.e. we'have to support the specification process.Clearly the technology, such as Data base systems, is leading on efficiency issues as those needed for the construction, retrieval and manipulation of large shared data base. On the other hand, the AI techniques have improved significantly with function such as deductive reasoning and natural language processing. It is important to find way to merge these technologies into one mainstream of computing. A meeting point for the two areas is the issue of conceptual knowledge modelling, so that models can be created that will define the role and the ways to use data in AI systems. In the framework of this study, one possible expert system design aid environment has been suggested to assist the designer in his work.In a conceptual modelling environment a model is given for analysing complex real world problems known as the Conceptual Knowledge Model (CKM), represented by a Graphical and a Formal Representation. The Graphical Representation consists of three graphs: Conceptual Requirement Graph, Conceptual Behavior Graph, and Conceptual Structure Graph. These graphs are developed by involving the expert during the design process. The graphs are then transformed into first-order predicate logic to represent the logical axioms of a theory, which constitutes the knowledge base of the Expert System. The model suggested here is a step towards closing the gap between the theory of the conventional data base theory and AI databases.     

Synergistic Effect of Graphene Oxide for Impeding the Dendritic Plating of Li

Dendritic growth of lithium (Li) has severely impeded the practical application of Li‐metal batteries. Herein, a 3D conformal graphene oxide nanosheet (GOn) coating, confined into the woven structure of a glass fiber separator, is reported, which permits facile transport of Li‐ions thought its structure, meanwhile regulating the Li deposition. Electrochemical measurements illustrate a remarkably enhanced cycle life and stability of the Li‐metal anode, which is explained by various microscopy and modeling results. Utilizing scanning electron microscopy, focused ion beam, and optical imaging, the formation of an uniform Li film on the electrode surface in the case of GO‐modified samples is revealed. Ab initio molecular dynamics (AIMD) simulations suggest that Li‐ions initially get adsorbed to the lithiophilic GOn and then diffuse through defect sites. This delayed Li transfer eliminates the “tip effect” leading to a more homogeneous Li nucleation. Meanwhile, C? C bonds rupture observed in the GO during AIMD simulations creates more pathways for faster Li‐ions transport. In addition, phase‐field modeling demonstrates that mechanically rigid GOn coating with proper defect size (smaller than 25 nm) can physically block the anisotropic growth of Li. This new understanding is a significant step toward the employment of 2D materials for regulating the Li deposition.     

MMLT: A mutual multilevel trust framework based on trusted third parties in multicloud environments

In this article, a mutual multilevel trust framework is proposed, which involves managing trust from the perspective of cloud users (CUs) and cloud service providers (CSPs) in a multicloud environment based on a set of trusted third parties (TTPs). These independent agents are trusted by CUs and CSPs and distributed on different clouds. The TTPs evaluate the CUs' trustworthiness based on the accuracy of feedback ratings and assess the CSPs' trustworthiness based on the quality of service monitoring information. They are connected themselves through the trusted release network, which enables a TTP to obtain trust information about CSPs and CUs from other clouds. With the objective of developing an effective trust management framework, a new approach has been provided to improve trust-based interactions, that is, able to rank the trusted cloud services (CSs) based on CU's priorities via fuzzy logic. Fuzzy logic is applied to manage the different priorities of CUs, all the CUs do not have the same priorities to use trusted CSs. Customizing service ranking allows CUs to apply trusted CSs based on their priorities. Experiments on real datasets well matched the analytical results, indicating that our proposed approach is effective and outperforms the existing approaches.