Parameter optimization for the Gaussian model of protein folding

Computational models of protein folding and ligand docking are large and complex. Few systematic methods have yet been developed to optimize the parameters in such models. We describe here an iterative parameter optimization strategy that is based on minimizing a structural error measure by descent in parameter space. At the start, we know the ‘correct’ native structure that we want the model to produce, and an initial set of parameters representing the relative strengths of interactions between the amino acids. The parameters are changed systematically until the model native structure converges as closely as possible to the correct native structure. As a test, we apply this parameter optimization method to the recently developed Gaussian model of protein folding: each amino acid is represented as a bead and all bonds, covalent and noncovalent, are represented by Hooke's law springs. We show that even though the Gaussian model has continuous degrees of freedom, parameters can be chosen to cause its ground state to be identical to that of Go-type lattice models, for which the global ground states are known. Parameters for a more realistic protein model can also be obtained to produce structures close to the real native structures in the protein database.     

A method for evaluating fault coverage using simulated fault injection for digitalized systems in nuclear power plants

The fault coverage for digital system in nuclear power plants is evaluated using a simulated fault injection method. Digital systems have numerous advantages, such as hardware elements share and hardware replication of the needed number of independent channels. However, the application of digital systems to safety-critical systems in nuclear power plants has been limited due to reliability concerns. In the reliability issues, fault coverage is one of the most important factors. In this study, we propose an evaluation method of the fault coverage for safety-critical digital systems in nuclear power plants. The system under assessment is a local coincidence logic processor for a digital plant protection system at Ulchin nuclear power plant units 5 and 6. The assessed system is simplified and then a simulated fault injection method is applied to evaluate the fault coverage of two fault detection mechanisms. From the simulated fault injection experiment, the fault detection coverage of the watchdog timer is 44.2% and that of the read only memory (ROM) checksum is 50.5%. Our experiments show that the fault coverage of a safety-critical digital system is effectively quantified using the simulated fault injection method.     

Preparation of CuInSe2 thin films through metal organic chemical vapor deposition method by using di-μ-methylselenobis(dimethylindium) and bis(ethylisobutyrylacetato) copper(II) precursors

Highly polycrystalline copper indium diselenide (CuInSe₂) thin films on molybdenum substrate were successfully grown at 330 °C through two-stage metal organic chemical vapor deposition (MOCVD) method by using two precursors at relatively mild conditions. First, phase pure InSe thin film was prepared on molybdenum substrate by using a single-source precursor, di-μ-methylselenobis(dimethylindium). Second, on this InSe/Mo film, bis(ethylisobutyrylacetato) copper(II) designated as Cu(eiac)₂ was treated by MOCVD to produce CuInSe₂ films. The thickness and stoichiometry of the product films were found to be easily controlled in this method by adjusting the process conditions. Also, there were no appreciable amounts of carbon and oxygen impurities in the prepared copper indium diselenide films.     

A 60-GHz point-to-multipoint millimeter-wave fiber-radio communication system

A 60-GHz point-to-multipoint wireless access link with data rate of 156 Mb/s incorporating 60-GHz transceiver modules and full-duplex fiber-optic millimeter-wave transmission is developed for short-range applications such as indoor wireless local area networks and intelligent transport systems. For compact system configuration, a small-size millimeter-wave transceiver module with planar antennas is developed. The transceiver module is based on broadband planar integration and packaging of millimeter-wave circuits. The RF output power is +10 dBm and the measured 3-dB antenna beamwidth is 30/spl deg/. The total size of the developed 60-GHz transceiver module, except input and output connectors, is 50 mm /spl times/ 75 mm /spl times/ 35 mm. A point-to-point full duplex fiber-optic configuration is extended to the scheme with multiple access points (APs) by using a tree coupler and a dense wavelength division multiplexing multiplexer. The AP has a simple configuration without frequency conversion. The bit error rate and packet error rate performances of the 60-GHz fiber-radio access link are evaluated. Furthermore, the effect of the extension to the scheme with multiple APs is investigated.     

Effect of Hot Band Annealing on Magnetic Properties in 3% Si Grain‐oriented Electrical Steels

Hot band annealing is known to be a prerequisite for good magnetic properties irrespective of manufacturing methods in grain‐oriented Fe‐3 wt.% Si electrical steels. In this study, the effects of hot band annealing on magnetic properties were investigated in 3% grain‐oriented electrical steels of low soluble AI contents and one‐stage cold rolling. Microstructure and precipitate distribution were compared with hot band annealing conditions. Secondary recrystallization behaviour with hot band annealing condition was also discussed.     

A fast path planning by path graph optimization

A fast path planning method by optimization of a path graph for both efficiency and accuracy is proposed. A conventional quadtree-based path planning approach is simple, robust, and efficient. However, it has two limitations. We propose a path graph optimization technique employing a compact mesh representation. A world space is triangulated into a base mesh and the base mesh is simplified to a compact mesh. The compact mesh representation is object-dependent; the positions of vertexes of the mesh are optimized according to the curvatures of the obstacles. The compact mesh represents the obstacles as accurately as the quadtree even though using much fewer vertexes than the quadtree. The compact mesh distributes vertexes in a free space in a balanced way by ensuring that the lengths of edges are below an edge length threshold. An optimized path graph is extracted from the compact mesh. An iterative vertex pushing method is proposed to include important obstacle boundary edges in the path graph. Dijkstra's shortest path searching algorithm is used to search the shortest path in the path graph. Experimental results show that the path planning using the optimized path graph is an order of magnitude faster than the quadtree approach while the length of the path generated by the proposed method is almost the same as that of the path generated by the quadtree.     

A Personalized Defection Detection and Prevention Procedure based on the Self-Organizing Map and Association Rule Mining: Applied to Online Game Site

Customer retention is an increasinglypressing issue in today's competitiveenvironment. This paper proposes a personalizeddefection detection and prevention procedurebased on the observation that potentialdefectors have a tendency to take a couple ofmonths or weeks to gradually change theirbehaviour (i.e., trim-out their usage volume)before their eventual withdrawal. For thispurpose, we suggest a SOM (Self-Organizing Map)based procedure to determine the possiblestates of customer behaviour from pastbehaviour data. Based on this staterepresentation, potential defectors aredetected by comparing their monitoredtrajectories of behaviour states with frequentand confident trajectories of past defectors.Also, the proposed procedure is extended toprevent the defection of potential defectors byrecommending the desirable behaviour state forthe next period so as to lower the likelihoodof defection. For the evaluation of theproposed procedure, a case study has beenconducted for a Korean online game site. Theresult demonstrates that the proposed procedureis effective for defection prevention andefficiently detects potential defectors withoutdeterioration of prediction accuracy whencompared to that of the MLP (Multi-LayerPerceptron) neural networks.     

Hybrid approach to distribution planning reflecting a stochastic supply chain

Today’s business environment is experiencing as a period of expansion and the globalization. Therefore, a distribution plan with low cost and high customer satisfaction in supply chain management (SCM) has been widely investigated. The purpose of this study is to establish optimal distribution planning in the supply chain. In this paper, a hybrid approach involving a genetic algorithm (GA) and simulation is presented to solve this problem. The GA is employed in order to quickly generate feasible distribution sequences. Considering uncertain factors such as queuing, breakdowns and repairing time in the supply chain, the simulation is used to minimize completion time for the distribution plan. The computational results for an example of a simple supply chain are given and discussed to validate the proposed approach. We obtained a more realistic distribution plan with optimal completion time by performing the iterative hybrid GA simulation procedure which reflects the stochastic nature of supply chains.     

Device-based decision-making for adaptation of three-dimensional content

The goal of this research was the creation of an adaptation mechanism for the delivery of three-dimensional content. The adaptation of content, for various network and terminal capabilities – as well as for different user preferences, is a key feature that needs to be investigated. Current state-of-the art research of the adaptation shows promising results for specific tasks and limited types of content, but is still not well-suited for massive heterogeneous environments. In this research, we present a method for transmitting adapted three-dimensional content to multiple target devices. This paper presents some theoretical and practical methods for adapting three-dimensional content, which includes shapes and animation. We also discuss practical details of the integration of our methods into MPEG-21 and MPEG-4 architectures.     

The Protective Effect of Zebularine,an Inhibitor of DNA Methyltransferase,on Renal Tubulointerstitial Inflammation and Fibrosis

Renal fibrosis, the final pathway of chronic kidney disease, is caused by genetic and epigenetic mechanisms. Although DNA methylation has drawn attention as a developing mechanism of renal fibrosis, its contribution to renal fibrosis has not been clarified. To address this issue, the effect of zebularine, a DNA methyltransferase inhibitor, on renal inflammation and fibrosis in the murine unilateral ureteral obstruction (UUO) model was analyzed. Zebularine significantly attenuated renal tubulointerstitial fibrosis and inflammation. Zebularine decreased trichrome, α-smooth muscle actin, collagen IV, and transforming growth factor-β1 staining by 56.2%. 21.3%, 30.3%, and 29.9%, respectively, at 3 days, and by 54.6%, 41.9%, 45.9%, and 61.7%, respectively, at 7 days after UUO. Zebularine downregulated mRNA expression levels of matrix metalloproteinase (MMP)-2, MMP-9, fibronectin, and Snail1 by 48.6%. 71.4%, 31.8%, and 42.4%, respectively, at 7 days after UUO. Zebularine also suppressed the activation of nuclear factor-κB (NF-κB) and the expression of pro-inflammatory cytokines, including tumor necrosis factor-α, interleukin (IL)-1β, and IL-6, by 69.8%, 74.9%, and 69.6%, respectively, in obstructed kidneys. Furthermore, inhibiting DNA methyltransferase buttressed the nuclear expression of nuclear factor (erythroid-derived 2)-like factor 2, which upregulated downstream effectors such as catalase (1.838-fold increase at 7 days, p < 0.01), superoxide dismutase 1 (1.494-fold increase at 7 days, p < 0.05), and NAD(P)H: quinone oxidoreduate-1 (1.376-fold increase at 7 days, p < 0.05) in obstructed kidneys. Collectively, these findings suggest that inhibiting DNA methylation restores the disrupted balance between pro-inflammatory and anti-inflammatory pathways to alleviate renal inflammation and fibrosis. Therefore, these results highlight the possibility of DNA methyltransferases as therapeutic targets for treating renal inflammation and fibrosis.