Protein Profiling in Alanine Aminotransferase Induced Patient cohort using Acetaminophen

Sensitive and predictive DILI (Drug Induced Liver Injury) biomarkers are needed in drug R&D to improve early detection of hepatotoxicity. The discovery of DILI biomarkers that demonstrate the predictive power to identify individuals at risk to DILI would represent a major advance in the development of personalized healthcare approaches. In this healthy volunteer acetaminophen study (4g/day for 7 days, with 3 monitored nontreatment days before and 4 after), 450 serum samples from 32 subjects were analyzed using protein profiling by antibody suspension bead arrays. Multiparallel protein profiles were generated using a DILI target protein array with 300 antibodies, where the antibodies were selected based on previous literature findings of putative DILI biomarkers and a screening process using pre dose samples from the same cohort. Of the 32 subjects, 16 were found to develop an elevated ALT value (2Xbaseline, responders). Using the plasma profiling approach together with multivariate statistical analysis some novel findings linked to lipid metabolism were found and more important, endogenous protein profiles in baseline samples (prior to treatment) with predictive power for ALT elevations were identified.

FEM Investigation of Induction Heating System for Pipe Brazing

The paper deals with determination of electromagnetic and temperature field distribution of induction heating system used for pipe brazing. The problem is considered as coupled – time harmonic electromagnetic and transient thermal field. It has been solved using finite element method. The detailed maps of electromagnetic and thermal field distribution have been obtained. The good understanding of the processes in the considered system ensures possibilities for control, management and increasing the efficiency of the welding process.

Spatial Services in Cloud Environment

Cloud Computing is an approach that provides computation and storage services on-demand to clients over the network, independent of device and location. In the last few years, cloud computing became a trend in information technology with many companies that transfer their business processes and applications in the cloud. Cloud computing with service oriented architecture has contributed to rapid development of Geographic Information Systems. Open Geospatial Consortium with its standards provides the interfaces for hosted spatial data and GIS functionality to integrated GIS applications. Furthermore, with the enormous processing power, clouds provide efficient environment for data intensive applications that can be performed efficiently, with higher precision, and greater reliability. This paper presents our work on the geospatial data services within the cloud computing environment and its technology. A cloud computing environment with the strengths and weaknesses of the geographic information system will be introduced. The OGC standards that solve our application interoperability are highlighted. Finally, we outline our system architecture with utilities for requesting and invoking our developed data intensive applications as a web service.

A Comparative Study of International Tourists- Safety Needs and Thai Tourist Polices- Perception towards International Tourists- Safety Needs

While service quality is acceptably most valued in the tourism industry, the issue of safety and security plays a key role in sustaining the industry success. Such an issue has been part of Thailand-s tourism development and promotion for several years. Evidently, the Tourist Police Department was set up for this purpose. Its main responsibility is to deal with international tourists- safety and confidence in travelling within Thai territory. However, to strengthen the tourism safety of the country, it is important to better understand international tourists- safety concerns about Thailand. This article seeks to compare international tourists- safety needs and Thai tourist polices- perception towards the tourists- safety concern to determine what measure should be taken to assure the tourist of Thailand-s secure environment. Through the employment of quantitative and qualitative methodological approaches, the tourism safety need of international tourists from Europe, North America and Asia was excavated, how Thai tourist polices and local polices perceived the international tourist-s safety concern was investigated, and opinion and experiences about how the police deal with international tourists- problems in eight touristic areas were also explored. A comparative result reveals a certain degrees of differences in international tourists- safety needs and Thai polices- perception towards their needs. The tourism safety prevention and protection measure and practice are also suggested.

Hardness Variations as Affected by Bar Diameter of AISI 4140 Steel

Hardness of the widely used structural steel is of vital importance since it may help in the determination of many mechanical properties of a material under loading situations. In order to obtain reliable information for design, properties homogeneity should be validated. In the current study the hardness variation over the different diameters of the same AISI 4140 bar is investigated. Measurements were taken on the two faces of the stock at equally spaced eight sectors and fifteen layers. Statistical and graphical analysis are performed to asses the distribution of hardness measurements over the specified area. Hardness measurements showed some degree of dispersion with about ± 10% of its nominal value provided by manufacturer. Hardness value is found to have a slight decrease trend as the diameter is reduced. However, an opposite behavior is noticed regarding the sequence of the sector indicating a nonuniform distribution over the same area either on the same face or considering the corresponding sector on the other face (cross section) of the same material bar.

Mobile Robot Navigation Using Local Model Networks

Developing techniques for mobile robot navigation constitutes one of the major trends in the current research on mobile robotics. This paper develops a local model network (LMN) for mobile robot navigation. The LMN represents the mobile robot by a set of locally valid submodels that are Multi-Layer Perceptrons (MLPs). Training these submodels employs Back Propagation (BP) algorithm. The paper proposes the fuzzy C-means (FCM) in this scheme to divide the input space to sub regions, and then a submodel (MLP) is identified to represent a particular region. The submodels then are combined in a unified structure. In run time phase, Radial Basis Functions (RBFs) are employed as windows for the activated submodels. This proposed structure overcomes the problem of changing operating regions of mobile robots. Read data are used in all experiments. Results for mobile robot navigation using the proposed LMN reflect the soundness of the proposed scheme.

Discovery of Fuzzy Censored Production Rules from Large Set of Discovered Fuzzy if then Rules

Censored Production Rule is an extension of standard production rule, which is concerned with problems of reasoning with incomplete information, subject to resource constraints and problem of reasoning efficiently with exceptions. A CPR has a form: IF A (Condition) THEN B (Action) UNLESS C (Censor), Where C is the exception condition. Fuzzy CPR are obtained by augmenting ordinary fuzzy production rule “If X is A then Y is B with an exception condition and are written in the form “If X is A then Y is B Unless Z is C. Such rules are employed in situation in which the fuzzy conditional statement “If X is A then Y is B" holds frequently and the exception condition “Z is C" holds rarely. Thus “If X is A then Y is B" part of the fuzzy CPR express important information while the unless part acts only as a switch that changes the polarity of “Y is B" to “Y is not B" when the assertion “Z is C" holds. The proposed approach is an attempt to discover fuzzy censored production rules from set of discovered fuzzy if then rules in the form: A(X) ÔçÆ B(Y) || C(Z).

Heart Rate Variability in Responders and Non- Responders to Live-Moderate, Train-Low Altitude Training

The aim of this study was to compare the effects of an altitude training camp on heart rate variability and performance in elite triathletes. Ten athletes completed 20 days of live-high, train-low training at 1650m. Athletes underwent pre and post 800-m swim time trials at sea-level, and two heart rate variability tests at 1650m on the first and last day of the training camp. Based on their time trial results, athletes were divided into responders and non-responders. Relative to the non-responders, the responders sympathetic-toparasympathetic ratio decreased substantially after 20 days of altitude training (-0.68 ± 1.08 and -1.2 ± 0.96, mean ± 90% confidence interval for supine and standing respectively). In addition, sympathetic activity while standing was also substantially lower post-altitude in the responders compared to the non-responders (-1869 ± 4764 ms2). Results indicate that responders demonstrated a change to more vagal predominance compared to non-responders.

A Comparative Study on the Financial Characteristics for Development Methods of Urban Development Project - Focusing on Multi-level Replotting Method -

The purpose of this study is comparing and analysing of the financial characteristics for development methods of the urban development project in the established area, focusing on the multi-level replotting. Analysis showed that the type of the lowest expenditure was 'combination type of group-land and multi-level replotting' and the type of the highest profitability was 'multi-level replotting type'. But 'multi-level replotting type' has still risk of amount of cost for the additional architecture. In addition, we subdivided standard amount for liquidation of replotting and analysed income-expenditure flow. Analysis showed that both of 'multi-level replotting type' and 'combination type of group-land and multi-level replotting' improved profitability of project and property change ratio. However, when the standard was under a certain amount, amount of original property for the replotting was increased exponentially, and profitability of project.

Nitrogen and Phosphorus Removal from Livestock Wastewater by Zeolite Ion Exchange and Ionizing Radiation

The ionizing radiation of livestock wastewater for the removal of nitrogen and phosphorus was studied in the presence of a natural zeolite. The feasibility of a combined process of zeolite ion exchange and electron beam irradiation of livestock wastewater was also investigated. The removal efficiencies of NH4 +-N, T-N and T-P were significantly enhanced by electron beam irradiation after zeolite ion exchange as a pre-treatment. The presence of silica zeolite accelerated the decomposition rate of livestock wastewater in the electron beam irradiation process. These results indicate that the combined process of zeolite ion exchange and electron beam irradiation has the potential for the treatment of livestock wastewater

A Novel Microarray Biclustering Algorithm

Biclustering aims at identifying several biclusters that reveal potential local patterns from a microarray matrix. A bicluster is a sub-matrix of the microarray consisting of only a subset of genes co-regulates in a subset of conditions. In this study, we extend the motif of subspace clustering to present a K-biclusters clustering (KBC) algorithm for the microarray biclustering issue. Besides minimizing the dissimilarities between genes and bicluster centers within all biclusters, the objective function of the KBC algorithm additionally takes into account how to minimize the residues within all biclusters based on the mean square residue model. In addition, the objective function also maximizes the entropy of conditions to stimulate more conditions to contribute the identification of biclusters. The KBC algorithm adopts the K-means type clustering process to efficiently make the partition of K biclusters be optimized. A set of experiments on a practical microarray dataset are demonstrated to show the performance of the proposed KBC algorithm.

Fuzzy Logic Based Determination of Battery Charging Efficiency Applied to Hybrid Power System

Battery storage system is emerging as an essential component of hybrid power system based on renewable energy resources such as solar and wind in order to make these sources dispatchable. Accurate modeling of battery storage system is ssential in order to ensure optimal planning of hybrid power systems incorporating battery storage. Majority of the system planning studies involving battery storage assume battery charging efficiency to be constant. However a strong correlation exists between battery charging efficiency and battery state of charge. In this work a Fuzzy logic based model has been presented for determining battery charging efficiency relative to a particular SOC. In order to demonstrate the efficacy of proposed approach, reliability evaluation studies are carried out for a hypothetical autonomous hybrid power system located in Jaisalmer, Rajasthan, India. The impact of considering battery charging efficiency as a function of state of charge is compared against the assumption of fixed battery charging efficiency for three different configurations comprising of wind-storage, solar-storage and wind-solar-storage.

Airfoils Aerodynamic Efficiency Study in Heavy Rain via Two Phase Flow Approach

Heavy rainfall greatly affects the aerodynamic performance of the aircraft. There are many accidents of aircraft caused by aerodynamic efficiency degradation by heavy rain. In this Paper we have studied the heavy rain effects on the aerodynamic efficiency of NACA 64-210 & NACA 0012 airfoils. For our analysis, CFD method and preprocessing grid generator are used as our main analytical tools, and the simulation of rain is accomplished via two phase flow approach-s Discrete Phase Model (DPM). Raindrops are assumed to be non-interacting, non-deforming, non-evaporating and non-spinning spheres. Both airfoil sections exhibited significant reduction in lift and increase in drag for a given lift condition in simulated rain. The most significant difference between these two airfoils was the sensitivity of the NACA 64-210 to liquid water content (LWC), while NACA 0012 performance losses in the rain environment is not a function of LWC . It is expected that the quantitative information gained in this paper will be useful to the operational airline industry and greater effort such as small scale and full scale flight tests should put in this direction to further improve aviation safety.

Experimental Investigation on Excess Pore Water Pressure in Soft Soil-Foundations under Minor Shocks

In this study, shaking table tests are performed to investigate the behavior of excess pore water pressure in different soft soil-foundations of soil-structure interaction (SSI) system. The variation of the behaviors under cycled minor shock is observed. Moreover, The generation and variation mechanism of excess pore water pressure under earthquake excitation in different soft soilfoundations are analyzed and discussed.

Eukaryotic Gene Prediction by an Investigation of Nonlinear Dynamical Modeling Techniques on EIIP Coded Sequences

Many digital signal processing, techniques have been used to automatically distinguish protein coding regions (exons) from non-coding regions (introns) in DNA sequences. In this work, we have characterized these sequences according to their nonlinear dynamical features such as moment invariants, correlation dimension, and largest Lyapunov exponent estimates. We have applied our model to a number of real sequences encoded into a time series using EIIP sequence indicators. In order to discriminate between coding and non coding DNA regions, the phase space trajectory was first reconstructed for coding and non-coding regions. Nonlinear dynamical features are extracted from those regions and used to investigate a difference between them. Our results indicate that the nonlinear dynamical characteristics have yielded significant differences between coding (CR) and non-coding regions (NCR) in DNA sequences. Finally, the classifier is tested on real genes where coding and non-coding regions are well known.

Pressure Induced Isenthalpic Oscillations with Condensation and Evaporation in Saturated Two-Phase Fluids

Saturated two-phase fluid flows are often subject to pressure induced oscillations. Due to compressibility the vapor bubbles act as a spring with an asymmetric non-linear characteristic. The volume of the vapor bubbles increases or decreases differently if the pressure fluctuations are compressing or expanding; consequently, compressing pressure fluctuations in a two-phase pipe flow cause less displacement in the direction of the pipe flow than expanding pressure fluctuations. The displacement depends on the ratio of liquid to vapor, the ratio of pressure fluctuations over average pressure and on the exciting frequency of the pressure fluctuations. In addition, pressure fluctuations in saturated vapor bubbles cause condensation and evaporation within the bubbles and change periodically the ratio between liquid to vapor, and influence the dynamical parameters for the oscillation. The oscillations are conforming to an isenthalpic process at constant enthalpy with no heat transfer and no exchange of work. The paper describes the governing non-linear equation for twophase fluid oscillations with condensation and evaporation, and presents steady state approximate solutions for free and for pressure induced oscillations. Resonance criteria and stability are discussed.

Development of a Project Selection Method on Information System Using ANP and Fuzzy Logic

Project selection problems on management information system (MIS) are often considered a multi-criteria decision-making (MCDM) for a solving method. These problems contain two aspects, such as interdependencies among criteria and candidate projects and qualitative and quantitative factors of projects. However, most existing methods reported in literature consider these aspects separately even though these two aspects are simultaneously incorporated. For this reason, we proposed a hybrid method using analytic network process (ANP) and fuzzy logic in order to represent both aspects. We then propose a goal programming model to conduct an optimization for the project selection problems interpreted by a hybrid concept. Finally, a numerical example is conducted as verification purposes.

Influence of Thermo-fluid-dynamic Parameters on Fluidics in an Expanding Thermal Plasma Deposition Chamber

Technology of thin film deposition is of interest in many engineering fields, from electronic manufacturing to corrosion protective coating. A typical deposition process, like that developed at the University of Eindhoven, considers the deposition of a thin, amorphous film of C:H or of Si:H on the substrate, using the Expanding Thermal arc Plasma technique. In this paper a computing procedure is proposed to simulate the flow field in a deposition chamber similar to that at the University of Eindhoven and a sensitivity analysis is carried out in terms of: precursor mass flow rate, electrical power, supplied to the torch and fluid-dynamic characteristics of the plasma jet, using different nozzles. To this purpose a deposition chamber similar in shape, dimensions and operating parameters to the above mentioned chamber is considered. Furthermore, a method is proposed for a very preliminary evaluation of the film thickness distribution on the substrate. The computing procedure relies on two codes working in tandem; the output from the first code is the input to the second one. The first code simulates the flow field in the torch, where Argon is ionized according to the Saha-s equation, and in the nozzle. The second code simulates the flow field in the chamber. Due to high rarefaction level, this is a (commercial) Direct Simulation Monte Carlo code. Gas is a mixture of 21 chemical species and 24 chemical reactions from Argon plasma and Acetylene are implemented in both codes. The effects of the above mentioned operating parameters are evaluated and discussed by 2-D maps and profiles of some important thermo-fluid-dynamic parameters, as per Mach number, velocity and temperature. Intensity, position and extension of the shock wave are evaluated and the influence of the above mentioned test conditions on the film thickness and uniformity of distribution are also evaluated.

Combine a Population-based Incremental Learning with Artificial Immune System for Intrusion Detection System

This research focus on the intrusion detection system (IDS) development which using artificial immune system (AIS) with population based incremental learning (PBIL). AIS have powerful distinguished capability to extirpate antigen when the antigen intrude into human body. The PBIL is based on past learning experience to adjust new learning. Therefore we propose an intrusion detection system call PBIL-AIS which combine two approaches of PBIL and AIS to evolution computing. In AIS part we design three mechanisms such as clonal selection, negative selection and antibody level to intensify AIS performance. In experimental result, our PBIL-AIS IDS can capture high accuracy when an intrusion connection attacks.

Improving University Operations with Data Mining: Predicting Student Performance

The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.