Design of a fuel cell generation system using a PEMFC simulator

In this paper, a PCS (power conditioner system) design for a fuel cell generation system has been proposed. In order to analyze the dynamic performance of the PCS, a fuel cell stack simulator is also designed, which can consider the dynamic V–I characteristics of the PEMFC (proton exchange membrane fuel cell). First, we explain the PCS design for a fuel cell generation system in detail along with the system configuration and operational principle of the developed PEMFC simulator that has been investigated. In addition, we cover the validity of the proposed system that has been verified by informative simulation and experimental results.     

A Multi-service Group Key Management Scheme for Stateless Receivers in Wireless Mesh Networks

Wireless mesh networks facilitate the development of the many group oriented applications by extending the coverage area of the group communication. Group communication in a wireless mesh network is complicated due to dynamic intermediate mesh points, access control for communications between different administrative domains, and the absence of a centralized network controller. In this study, we propose a topology-matching decentralized multi-service group key management scheme for wireless mesh networks. It allows service providers to update and deliver their group keys to valid members in a distributed manner using the identity-based encryption scheme. The analysis result indicates that the proposed scheme has advantages with regard to the rekeying cost and storage overhead for a member and a mesh point in multi-sender group communication environments. The stateless property is also achieved such that a stateless member, who could not be constantly online, can easily decrypt the rekeying messages without recording the past history of transmission.     

Torque characteristic analysis considering the manufacturing tolerance for electric machine by stochastic response surface method

Manufacturing tolerances as well as measuring errors have a great influence on products designed by optimization technique, etc., to improve their characteristics and reduce the production cost. Therefore, tolerance analysis technique is required to find the tolerance band of design variables for minimizing the effect and estimating the characteristic distribution of the products. This paper represents the torque characteristics considering the manufacturing tolerance of an electric machine. In order to analyze the tolerance of the brushless DC (BLDC) motor, stochastic response surface methodology (SRSM), which treats input data as stochastic variables, is introduced. It can analyze the tolerances from the electrical point of view and find a robust optimal solution that has insensitive performance on its change of the design variables by applying the optimization technique. A surface permanent-magnet BLDC motor is used to confirm the validity of this method. It must be noted that the statistical torque characteristics analyzed by SRSM has a great advantage in the design and manufacture stage over conventional method.     

The GNAQ T96S Mutation Affects Cell Signaling and Enhances the Oncogenic Properties of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), the most common malignant tumor in the liver, grows and metastasizes rapidly. Despite advances in treatment modalities, the five-year survival rate of HCC remains less than 30%. We sought genetic mutations that may affect the oncogenic properties of HCC, using The Cancer Genome Atlas (TCGA) data analysis. We found that the GNAQ T96S mutation (threonine 96 to serine alteration of the Gαq protein) was present in 12 out of 373 HCC patients (3.2%). To examine the effect of the GNAQ T96S mutation on HCC, we transfected the SK-Hep-1 cell line with the wild-type or the mutant GNAQ T96S expression vector. Transfection with the wild-type GNAQ expression vector enhanced anchorage-independent growth, migration, and the MAPK pathways in the SK-Hep-1 cells compared to control vector transfection. Moreover, cell proliferation, anchorage-independent growth, migration, and the MAPK pathways were further enhanced in the SK-Hep-1 cells transfected with the GNAQ T96S expression vector compared to the wild-type GNAQ-transfected cells. In silico structural analysis shows that the substitution of the GNAQ amino acid threonine 96 with a serine may destabilize the interaction between the regulator of G protein signaling (RGS) protein and GNAQ. This may reduce the inhibitory effect of RGS on GNAQ signaling, enhancing the GNAQ signaling pathway. Single nucleotide polymorphism (SNP) genotyping analysis for Korean HCC patients shows that the GNAQ T96S mutation was found in only one of the 456 patients (0.22%). Our data suggest that the GNAQ T96S hotspot mutation may play an oncogenic role in HCC by potentiating the GNAQ signal transduction pathway.     

Highly efficient ring-opening polymerization of tetrahydrofuran by anhydrous ferric chloride

Poly(tetramethylene ether glycol) (PTMG), widely used as a precursor in the fabrication of commodity polymers, is typically produced byacid-catalyzed polymerization of tetrahydrofuran (THF). Herein, we report a detailed investigation of the cationic ring-opening polymerization of THF catalyzed by ferric chloride (FeCl₃), which can be considered as a strong Lewisacid. The polymerization reactions were performed in the presence of acetic anhydride at 20°C with FeCl₃, which readily produced poly(tetramethylene ether glycol diester) (PTMG_DE). A maximum yield of 79.2% was obtained within 30 min using a FeCl₃ to acetic anhydride molar ratio of 5:4. The resulting polymers generally exhibited low molecular weights and a narrow polydispersity index and could be easily converted into PTMG using aqueous NaOH. In contrast with the FeCl₃-acetic anhydride system, other iron-based catalysts such as FeCl₂ and FeCl₃·6H₂O did not show any noticeable activity in the polymerization of THF. The proposed mechanism involves initiation of the acetyl cation generated by FeCl₃, propagation by nucleophilic addition of THF, and termination by the acetate anion, accounting for the high activity of the FeCl₃ catalyst for THF polymerization. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47999.     

Optimization of the influential factors for the improvement of CO2 utilization efficiency and CO2 mass transfer rate

Microalgae fix CO₂ as energy source and afford biomass and high valued products such as carotenoids, pigments, proteins, and vitamins that can be used for the production of nutraceuticals, pharmaceuticals, animal feed additives, cosmetics, etc. Carbon dioxide is the sole source of carbon and it is supplied continuously for the microalgal cultivation. But undissolved CO₂ is lost by outgassing and sufficient dissolved CO₂ should be provided to avoid carbon limitation. The effect of CO₂ mass transfer with different CO₂ concentrations, aeration rate of gas, bubble size, baffle type and baffle number on the growth of Chlorella sp. AG10002 was investigated and the optimized conditions for the enhancement of biomass productivity were determined. We confirm that these results can be provided as basic data to improve the CO₂ mass transfer ability for the high density culture of Chlorella sp. and some microalgae having commercial value.     

Optimization of alkaline protease production from Shewanella oneidensis MR‐1 by response surface methodology

BACKGROUND: The proteases are among the most important groups of enzymes. Therefore, it is important to produce inexpensive and optimized media for large‐scale commercial production. In the present work, three different Shewanella species were screened on skim milk agar medium for their ability to produce alkaline protease. The effects of different culture conditions were optimized for alkaline protease production by S. oneidensis MR‐1 using a Box–Behnken design combined with response surface methodology (RSM). RESULTS: Highest yield (112.90 U mL^?1) of protease production was obtained at pH 9.0, a temperature of 30 °C, glucose (12.5 g L^?1), tryptone (12.5 g L^?1) and an incubation period of 36 h. A second‐order polynomial regression model was used for analysis of the experiment. The experimental values were in good agreement with predicted values, with correlation coefficient 0.9996. CONCLUSION: Carbon and nitrogen, pH, temperature and incubation period were chosen as the main factors to be used in an experimental design for optimization to produce low‐cost enzymes, potentially for use on an industrial scale. A 60% increase in enzyme activity was achieved in the optimized medium compared with the original medium. Copyright © 2008 Society of Chemical Industry     

A study on the development of a substitution process by powder metallurgy in automobile parts

Powder metallurgy processes using sintering are able to form net-shaped products and have been used widely in the production of automobile parts to improve productivity. However, the toughness of powder products is generally poor because they contain pores. Therefore, forged products are used in parts subjected to severe fatigue loads, but in the case of powder products having high toughness, they could substitute for forged products. In this study, the choice of powder materials and production processes, including mixing, compaction, sintering, and heat treatment are studied to produce the clutch disc spline hub of an automobile. For this, three types of materials are selected and processed and the mechanical properties and microstructure of the sample are investigated, along with the performance of a dynamic test carried out under real conditions.     

Predicting metamorphic relations for testing scientific software: a machine learning approach using graph kernels

Comprehensive, automated software testing requires an oracle to check whether the output produced by a test case matches the expected behaviour of the programme. But the challenges in creating suitable oracles limit the ability to perform automated testing in some programmes, and especially in scientific software. Metamorphic testing is a method for automating the testing process for programmes without test oracles. This technique operates by checking whether the programme behaves according to properties called metamorphic relations. A metamorphic relation describes the change in output when the input is changed in a prescribed way. Unfortunately, finding the metamorphic relations satisfied by a programme or function remains a labour‐intensive task, which is generally performed by a domain expert or a programmer. In this work, we propose a machine learning approach for predicting metamorphic relations that uses a graph‐based representation of a programme to represent control flow and data dependency information. In earlier work, we found that simple features derived from such graphs provide good performance. An analysis of the features used in this earlier work led us to explore the effectiveness of several representations of those graphs using the machine learning framework of graph kernels, which provide various ways of measuring similarity between graphs. Our results show that a graph kernel that evaluates the contribution of all paths in the graph has the best accuracy and that control flow information is more useful than data dependency information. The data used in this study are available for download at http://www.cs.colostate.edu/saxs/MRpred/functions.tar.gz to help researchers in further development of metamorphic relation prediction methods. Copyright © 2015 John Wiley & Sons, Ltd.