Critical Assessment of Scoring Schemes for Protein-Protein Docking Predictions

Protein-protein interactions (PPI) play a crucial role in many biological processes such as cell signalling, transcription, translation, replication, signal transduction, and drug targeting, etc. Structural information about protein-protein interaction is essential for understanding the molecular mechanisms of these processes. Structures of protein-protein complexes are still difficult to obtain by biophysical methods such as NMR and X-ray crystallography, and therefore protein-protein docking computation is considered an important approach for understanding protein-protein interactions. However, reliable prediction of the protein-protein complexes is still under way. In the past decades, several grid-based docking algorithms based on the Katchalski-Katzir scoring scheme were developed, e.g., FTDock, ZDOCK, HADDOCK, RosettaDock, HEX, etc. However, the success rate of protein-protein docking prediction is still far from ideal. In this work, we first propose a more practical measure for evaluating the success of protein-protein docking predictions,the rate of first success (RFS), which is similar to the concept of mean first passage time (MFPT). Accordingly, we have assessed the ZDOCK bound and unbound benchmarks 2.0 and 3.0. We also createda new benchmark set for protein-protein docking predictions, in which the complexes have experimentally determined binding affinity data. We performed free energy calculation based on the solution of non-linear Poisson-Boltzmann equation (nlPBE) to improve the binding mode prediction. We used the well-studied thebarnase-barstarsystem to validate the parameters for free energy calculations. Besides,thenlPBE-based free energy calculations were conducted for the badly predicted cases by ZDOCK and ZRANK. We found that direct molecular mechanics energetics cannot be used to discriminate the native binding pose from the decoys.Our results indicate that nlPBE-based calculations appeared to be one of the promising approaches for improving the success rate of binding pose predictions.

Adaptive Multi-Camera Shooting System Based on Dynamic Workflow in a Compact Studio

We developed a multi-camera control system that a (one) cameraman can operate several cameras at a compact studio. we analyzed a workflow of a cameraman of some program shootings with two cameras and clarified their heavy tasks. The system based on a dynamic workflow which adapts a program progressing and recommends of cameraman. we perform the automation of multicamera controls by modeling of studio environment and perform automatic camera adjustment for suitable angle of view with face detection. Our experiment at a real program shooting showed that one cameraman can carry out the task of shooting sufficiently.

Optimal Calculation of Partial Transmission Ratios of Four-Step Helical Gearboxes for Getting Minimal Gearbox Length

This paper presents a new study on the applications of optimization and regression analysis techniques for optimal calculation of partial ratios of four-step helical gearboxes for getting minimal gearbox length. In the paper, basing on the moment equilibrium condition of a mechanic system including four gear units and their regular resistance condition, models for determination of the partial ratios of the gearboxes are proposed. In particular, explicit models for calculation of the partial ratios are proposed by using regression analysis. Using these models, the determination of the partial ratios is accurate and simple.

Mathematical Modeling of Gas Turbine Blade Cooling

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Verifying X.509 Certificates on Smart Cards

This paper presents a smart-card applet that is able to verify X.509 certificates and to use the public key contained in the certificate for verifying digital signatures that have been created using the corresponding private key, e.g. for the purpose of authenticating the certificate owner against the card. The approach has been implemented as an operating prototype on Java cards.

Nanocrystalline Mg-3%Al Alloy: its Synthesis and Investigation of its Tensile Behavior

The tensile properties of Mg-3%Al nanocrystalline alloys were investigated at different test environment. Bulk nanocrystalline samples of these alloy was successfully prepared by mechanical alloying (MA) followed by cold compaction, sintering, and hot extrusion process. The crystal size of the consolidated milled sample was calculated by X-Ray line profile analysis. The deformation mechanism and microstructural characteristic at different test condition was discussed extensively. At room temperature, relatively lower value of activation volume (AV) and higher value of strain rate sensitivity (SRS) suggests that new rate controlling mechanism accommodating plastic flow in the present nanocrystalline sample. The deformation behavior and the microstructural character of the present samples were discussed in details.

The Role of Work Ethic in the Development of Singapore, South Korea, Malaysia, Japan and European Countries

Work ethic and labour productivity issues are extremely important for any society. It has been long proven by the global practice and various scholars that the country promoting the labour has always been way forward from the other countries. This paper studies the thoughts suggested by M.Weber, Confucius, Lee Kuan Yew, Mahathir Mohammad and other prominent thinkers concerning the issues of work ethics and labour productivity. The article analyzes why developed nations are way more advanced in their development compared to other nations.

Investigation of Tool Temperature and Surface Quality in Hot Machining of Hard-to-Cut Materials

Production of hard-to-cut materials with uncoated carbide cutting tools in turning, not only cause tool life reduction but also, impairs the product surface roughness. In this paper, influence of hot machining method were studied and presented in two cases. Case1-Workpiece surface roughness quality with constant cutting parameter and 300 ºC initial workpiece surface temperature. Case 2- Tool temperature variation when cutting with two speeds 78.5 (m/min) and 51 (m/min). The workpiece material and tool used in this study were AISI 1060 steel (45HRC) and uncoated carbide TNNM 120408-SP10(SANDVIK Coromant) respectively. A gas flam heating source was used to preheating of the workpiece surface up to 300 ºC, causing reduction of yield stress about 15%. Results obtained experimentally, show that the method used can considerably improved surface quality of the workpiece.

Effect of Chromatic Dispersion on Optical Generation of Tunable Millimeter-Wave Signals

In this paper, the optical generation of three bands of continuously tunable millimeter-wave signals using an optical phase modulator (OPM) and a polarization state rotation filter (PSRF) as an optical notch filter is analyzed. The effect of the chromatic dispersion on millimeter-wave signals is presented.

Factors Influencing Knowledge Management Process Model: A Case Study of Manufacturing Industry in Thailand

The objectives of this research were to explore factors influencing knowledge management process in the manufacturing industry and develop a model to support knowledge management processes. The studied factors were technology infrastructure, human resource, knowledge sharing, and the culture of the organization. The knowledge management processes included discovery, capture, sharing, and application. Data were collected through questionnaires and analyzed using multiple linear regression and multiple correlation. The results found that technology infrastructure, human resource, knowledge sharing, and culture of the organization influenced the discovery and capture processes. However, knowledge sharing had no influence in sharing and application processes. A model to support knowledge management processes was developed, which indicated that sharing knowledge needed further improvement in the organization.

New Proxy Signatures Preserving Privacy and as Secure as ElGamal Signatures

Digital signature is a useful primitive to attain the integrity and authenticity in various wire or wireless communications. Proxy signature is one type of the digital signatures. It helps the proxy signer to sign messages on behalf of the original signer. It is very useful when the original signer (e.g. the president of a company) is not available to sign a specific document. If the original signer can not forge valid proxy signatures through impersonating the proxy signer, it will be robust in a virtual environment; thus the original signer can not shift any illegal action initiated by herself to the proxy signer. In this paper, we propose a new proxy signature scheme. The new scheme can prevent the original signer from impersonating the proxy signer to sign messages. The proposed scheme is based on the regular ElGamal signature. In addition, the fair privacy of the proxy signer is maintained. That means, the privacy of the proxy signer is preserved; and the privacy can be revealed when it is necessary.

A Rough Sets Approach for Relevant Internet/Web Online Searching

The internet is constantly expanding. Identifying web links of interest from web browsers requires users to visit each of the links listed, individually until a satisfactory link is found, therefore those users need to evaluate a considerable amount of links before finding their link of interest; this can be tedious and even unproductive. By incorporating web assistance, web users could be benefited from reduced time searching on relevant websites. In this paper, a rough set approach is presented, which facilitates classification of unlimited available e-vocabulary, to assist web users in reducing search times looking for relevant web sites. This approach includes two methods for identifying relevance data on web links based on the priority and percentage of relevance. As a result of these methods, a list of web sites is generated in priority sequence with an emphasis of the search criteria.

A Generator from Cascade Markov Model for Packet Loss and Subsequent Bit Error Description

In this paper we present a novel error model for packet loss and subsequent error description. The proposed model simulates the error performance of wireless communication link. The model is designed as two independent Markov chains, where the first one is used for packet generation and the second one generates correctly and incorrectly transmitted bits for received packets from the first chain. The statistical analyses of real communication on the wireless link are used for determination of model-s parameters. Using the obtained parameters and the implementation of the generator, we collected generated traffic. The obtained results generated by proposed model are compared with the real data collection.

Waste Management, Strategies and Situation in South Africa: An Overview

This paper highlights some interesting facts on South African-s waste situation and management strategies, in particular the Integrated Waste Management. South Africa supports a waste hierarchy by promoting cleaner production, waste minimisation, reuse, recycling and waste treatment with disposal and remediation as the last preferred options in waste management. The drivers for waste management techniques are identified as increased demand for waste service provision; increased demand for waste minimisation; recycling and recovery; land use, physical and environmental limitations; and socio-economic and demographic factors. The South African government recognizes the importance of scientific research as outlined on the white paper on Integrated Pollution and Waste Management (IP and WM) (DEAT, 2000).

Examining the Pearlite Growth Interface in a Fe-C-Mn Alloy

A method of collecting composition data and examining structural features of pearlite lamellae and the parent austenite at the growth interface in a 13wt. % manganese steel has been demonstrated with the use of Scanning Transmission Electron Microscopy (STEM). The combination of composition data and the structural features observed at the growth interface show that available theories of pearlite growth cannot explain all the observations.

Visual Object Tracking and Interception in Industrial Settings

This paper presents a solution for a robotic manipulation problem. We formulate the problem as combining target identification, tracking and interception. The task in our solution is sensing a target on a conveyor belt and then intercepting robot-s end-effector at a convenient rendezvous point. We used an object recognition method which identifies the target and finds its position from visualized scene picture, then the robot system generates a solution for rendezvous problem using the target-s initial position and belt velocity . The interception of the target and the end-effector is executed at a convenient rendezvous point along the target-s calculated trajectory. Experimental results are obtained using a real platform with an industrial robot and a vision system over it.

Using Data Mining Techniques for Estimating Minimum, Maximum and Average Daily Temperature Values

Estimates of temperature values at a specific time of day, from daytime and daily profiles, are needed for a number of environmental, ecological, agricultural and technical applications, ranging from natural hazards assessments, crop growth forecasting to design of solar energy systems. The scope of this research is to investigate the efficiency of data mining techniques in estimating minimum, maximum and mean temperature values. For this reason, a number of experiments have been conducted with well-known regression algorithms using temperature data from the city of Patras in Greece. The performance of these algorithms has been evaluated using standard statistical indicators, such as Correlation Coefficient, Root Mean Squared Error, etc.

The Importance of Bridge Health Monitoring

In the past, there were many bridge-s collapses due to lack of bridge structural capacity information. Most of concrete bridge health was relied on information from visual inspection, which sometime was inadequate. This study was conducted in order to investigate relationship between bridge structural condition and bridge visual condition. This study was a part of a big project conducted at Department of Highways of Thailand. In this study, 31 bridges including slab-type bridges, plank-girder bridges, prestressed box-beam bridges, prestressed I-girder bridges and prestressed multibeam bridges were selected for visual inspection and load test. It was found a positive correlation between bridge appearance and bridge-s load carrying capacity. However, statistical characteristic revealed low correlation between them.

The Investors- Reaction to Investment Rating Change Announcements

This study investigates the investors- behavioral reaction to the investment rating change announcements from the views of behavioral finance. The empirical results indicate that self-interest does affect the intention of securities firms to release investment ratings for individual stocks. In addition, behavioral pitfalls are also found in the response of retail investors to investment rating change announcements.

A Novel Neighborhood Defined Feature Selection on Phase Congruency Images for Recognition of Faces with Extreme Variations

A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.