The System Architecture of the Open European Nephrology Science Centre

The amount and heterogeneity of data in biomedical research, notably in interdisciplinary research, requires new methods for the collection, presentation and analysis of information. Important data from laboratory experiments as well as patient trials are available but come out of distributed resources. The Charite Medical School in Berlin has established together with the German Research Foundation (DFG) a new information service center for kidney diseases and transplantation (Open European Nephrology Science Centre - OpEN.SC). The system is based on a service-oriented architecture (SOA) with main and auxiliary modules arranged in four layers. To improve the reuse and efficient arrangement of the services the functionalities are described as business processes using the standardised Business Process Execution Language (BPEL).

A Study on Polymer Coated Colour Pigments for Water-Based Ink

The pigments covered by film-forming polymers have opened a prospect to improve the quality of water-based printing inks. In this study such pigments were prepared by the initiated polymerization of styrene and methacrylate derivative monomers in the aqueous pigment dispersions. The formation of polymer films covering pigment cores depends on the polymerization time and the ratio of pigment to monomers. At the time of 4 hours and the ratio of 1/10 almost pigment particles are coated by the polymer. The formed polymer covers of pigments have the average thickness of 5.95 nm. The size increasing percentage of the coated particles after a week is 4.5 %, about fourteen-fold lower than of the original ones. The obtained results indicate that the coated pigments are improved dispersion stability in water medium along with a guarantee for the optical colour.

Relationship between Facebook Usage and the Student Engagement of Sri Lankan Management Undergraduates

Academics and researchers are interested in the effects of social media on college students, with a specific focus on the most popular social media website; Facebook. Previous studied have found contradictory result on the relationship between Facebook usage and the student engagement with positive, detrimental and no significant relationships. However, these studies were limited to western higher education system. This paper fills a gap in the literature by using a sample (300) of Sri Lankan management undergraduates to examine the relationship between Facebook usage and student engagement. Student engagement was measured 35 item scale based on the National Survey of Student Engagement and Facebook usage by Facebook intensity scale. Descriptive statistics, path analysis and structural equation modeling were applied as statistical tools and techniques. Results indicate that student engagement scale was significantly negatively related with the Facebook usage with the influence from student engagement on Facebook usage.

Optimum Neural Network Architecture for Precipitation Prediction of Myanmar

Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.

The Development of a Narrative Management System: Storytelling in Knowledge Management

This paper presents a narrative management system for organizations to capture organization's tacit knowledge through stories. The intention of capturing tacit knowledge is to address the problem that comes with the mobility of workforce in organisation. Storytelling in knowledge management context is seen as a powerful management tool to communicate tacit knowledge in organization. This narrative management system is developed firstly to enable uploading of many types of knowledge sharing stories, from general to work related-specific stories and secondly, each video has comment functionality where knowledge users can post comments to other knowledge users. The narrative management system allows the stories to browse, search and view by the users. In the system, stories are stored in a video repository. Stories that were produced from this framework will improve learning, knowledge transfer facilitation and tacit knowledge quality in an organization.

The Minimum PAPR Code for OFDM Systems

In this paper, a block code to minimize the peak-toaverage power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals is proposed. It is shown that cyclic shift and codeword inversion cause not change to peak envelope power. The encoding rule for the proposed code comprises of searching for a seed codeword, shifting the register elements, and determining codeword inversion, eliminating the look-up table for one-to-one correspondence between the source and the coded data. Simulation results show that OFDM systems with the proposed code always have the minimum PAPR.

Influence of Sire Breed, Protein Supplementation and Gender on Wool Spinning Fineness in First-Cross Merino Lambs

Our objectives were to evaluate the effects of sire breed, type of protein supplement, level of supplementation and sex on wool spinning fineness (SF), its correlations with other wool characteristics and prediction accuracy in F1 Merino crossbred lambs. Texel, Coopworth, White Suffolk, East Friesian and Dorset rams were mated with 500 purebred Merino dams at a ratio of 1:100 in separate paddocks within a single management system. The F1 progeny were raised on ryegrass pasture until weaning, before forty lambs were randomly allocated to treatments in a 5 x 2 x 2 x 2 factorial experimental design representing 5 sire breeds, 2 supplementary feeds (canola or lupins), 2 levels of supplementation (1% or 2% of liveweight) and sex (wethers or ewes). Lambs were supplemented for six weeks after an initial three weeks of adjustment, wool sampled at the commencement and conclusion of the feeding trial and analyzed for SF, mean fibre diameter (FD), coefficient of variation (CV), standard deviation, comfort factor (CF), fibre curvature (CURV), and clean fleece yield. Data were analyzed using mixed linear model procedures with sire fitted as a random effect, and sire breed, sex, supplementary feed type, level of supplementation and their second-order interactions as fixed effects. Sire breed (P

Dimension Reduction of Microarray Data Based on Local Principal Component

Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.

High-Speed High-Gain CMOS OTA for SC Applications

A fast settling multipath CMOS OTA for high speed switched capacitor applications is presented here. With the basic topology similar to folded-cascode, bandwidth and DC gain of the OTA are enhanced by adding extra paths for signal from input to output. Designed circuit is simulated with HSPICE using level 49 parameters (BSIM 3v3) in 0.35mm standard CMOS technology. DC gain achieved is 56.7dB and Unity Gain Bandwidth (UGB) obtained is 1.15GHz. These results confirm that adding extra paths for signal can improve DC gain and UGB of folded-cascode significantly.

Optimization of Two-Stage Pretreatment Combined with Microwave Radiation Using Response Surface Methodology

Pretreatment is an essential step in the conversion of lignocellulosic biomass to fermentable sugar that used for biobutanol production. Among pretreatment processes, microwave is considered to improve pretreatment efficiency due to its high heating efficiency, easy operation, and easily to combine with chemical reaction. The main objectives of this work are to investigate the feasibility of microwave pretreatment to enhance enzymatic hydrolysis of corncobs and to determine the optimal conditions using response surface methodology. Corncobs were pretreated via two-stage pretreatment in dilute sodium hydroxide (2 %) followed by dilute sulfuric acid 1 %. Pretreated corncobs were subjected to enzymatic hydrolysis to produce reducing sugar. Statistical experimental design was used to optimize pretreatment parameters including temperature, residence time and solid-to-liquid ratio to achieve the highest amount of glucose. The results revealed that solid-to-liquid ratio and temperature had a significant effect on the amount of glucose.

The Relationship between Depression Interpersonal Communication and Media Using Among International Students

Student-s movements have been going increasing in last decades. International students can have different psychological and sociological problems in their adaptation process. Depression is one of the most important problems in this procedure. This research purposed to reveal level of foreign students- depression, kinds of interpersonal communication networks (host/ethnic interpersonal communication) and media usage (host/ethnic media usage). Additionally study aimed to display the relationship between depression and communication (host/ethnic interpersonal communication and host/ethnic media usage) among foreign university students. A field research was performed among 283 foreign university students who have been attending 8 different universities in Turkey. A purposeful sampling technique was used in this research cause of data collect facilities. Results indicated that 58.3% of foreign students- depression stage was “intermediate" while 33.2% of foreign students- depression level was “low". Add to this, host interpersonal communication behaviors and Turkish web sites usages were negatively and significantly correlated with depression.

Investigation of the Synthesis of Alcohols Byproducts in Fischer-Tropsch Synthesis on Modified Fe-Cu Catalyst: Reactivity and Mechanism

The influence of copper promoters and reaction conditions on the formation of alcohols byproducts of a common Fischer-Tropsch synthesis used iron-based catalysts were investigated. A good compromise of 28%Cu/FeKLaSiO2 can lead to the optimization of an improved Fischer-Tropsch catalyst. The product distribution shifts towards hydrocarbons with increasing the reaction temperature, while pressure promotes the formation of alcohols. It was found that the production of either alcohols or hydrocarbons followed A-S-F distributions, and their α parameters were essentially different which indicated a competition in the growing chain between the two species. TPD after acetaldehyde adsorption gave strong evidence of the insertion of a C1 oxygen-containing species into an alkyl chain.

Lithofacies Classification from Well Log Data Using Neural Networks, Interval Neutrosophic Sets and Quantification of Uncertainty

This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.

Influence of Ammonium Concentration on the Performance of an Inorganic Biofilter Treating Methane

Among the technologies available to reduce methane emitted from the pig industry, biofiltration seems to be an effective and inexpensive solution. In methane (CH4) biofiltration, nitrogen is an important macronutrient for the microorganisms growth. The objective of this research project was to study the effect of ammonium (NH4 +) on the performance, the biomass production and the nitrogen conversion of a biofilter treating methane. For NH4 + concentrations ranging from 0.05 to 0.5 gN-NH4 +/L, the CH4 removal efficiency and the dioxide carbon production rate decreased linearly from 68 to 11.8 % and from 7.1 to 0.5 g/(m3-h), respectively. The dry biomass content varied from 4.1 to 5.8 kg/(m3 filter bed). For the same range of concentrations, the ammonium conversion decreased while the specific nitrate production rate increased. The specific nitrate production rate presented negative values indicating denitrification in the biofilter.

Math Curriculum Adaptation for Disadvantaged Students in an Inclusive Classroom

This study was a part of the three-year longitudinal research on setting up an math learning model for the disadvantaged students in Taiwan. A target 2nd grade class with 10 regular students and 6 disadvantaged students at a disadvantaged area in Taipei participated in this study. Two units of a market basal math textbook concerning fractions, three-dimensional figures, weight and capacity were adapted to enhance their math learning motivations, confidences and effects. The findings were (1) curriculum adaptation was effective on enhancing students- learning motivations, confidences and effects; (2) story-type problems and illustrations decreased difficulties on understanding math language for students from new immigrant families and students with special needs; (3) “concrete – semiconcrete – abstract" teaching strategies and hands-on activities were essential to raise students learning interests and effects; and (4) curriculum adaptation knowledge and skills needed to be included in the pre- and in-service teacher training programs.

An Experimental Investigation of Heating in Induction Motors

The ability to predict an accurate temperature distribution requires the knowledge of the losses, the thermal characteristics of the materials, and the cooling conditions, all of which are very difficult to quantify. In this paper, the impact of the effects of iron and copper losses are investigated separately and their effects on the heating in various points of the stator of an induction motor, is highlighted by using two simple tests. In addition, the effect of a defect, such as an open circuit in a phase of the stator, on the heating is also obtained by a no-load test. The squirrel cage induction motor is rated at 2.2 kW; 380 V; 5.2 A; Δ connected; 50 Hz; 1420 rpm and the class of insulation F, has been thermally tested under several load conditions. Several thermocouples were placed in strategic points of the stator.

Constructing a Suitable Model of Distance Training for Community Leader in the Upper Northeastern Region

The objective of this research intends to create a suitable model of distance training for community leaders in the upper northeastern region of Thailand. The implementation of the research process is divided into four steps: The first step is to analyze relevant documents. The second step deals with an interview in depth with experts. The third step is concerned with constructing a model. And the fourth step takes aim at model validation by expert assessments. The findings reveal the two important components for constructing an appropriate model of distance training for community leaders in the upper northeastern region. The first component consists of the context of technology management, e.g., principle, policy and goals. The second component can be viewed in two ways. Firstly, there are elements comprising input, process, output and feedback. Secondly, the sub-components include steps and process in training. The result of expert assessments informs that the researcher-s constructed model is consistent and suitable and overall the most appropriate.

A General Segmentation Scheme for Contouring Kidney Region in Ultrasound Kidney Images using Improved Higher Order Spline Interpolation

A higher order spline interpolated contour obtained with up-sampling of homogenously distributed coordinates for segmentation of kidney region in different classes of ultrasound kidney images has been developed and presented in this paper. The performance of the proposed method is measured and compared with modified snake model contour, Markov random field contour and expert outlined contour. The validation of the method is made in correspondence with expert outlined contour using maximum coordinate distance, Hausdorff distance and mean radial distance metrics. The results obtained reveal that proposed scheme provides optimum contour that agrees well with expert outlined contour. Moreover this technique helps to preserve the pixels-of-interest which in specific defines the functional characteristic of kidney. This explores various possibilities in implementing computer-aided diagnosis system exclusively for US kidney images.

Optimum Design of an Absorption Heat Pump Integrated with a Kraft Industry using Genetic Algorithm

In this study the integration of an absorption heat pump (AHP) with the concentration section of an industrial pulp and paper process is investigated using pinch technology. The optimum design of the proposed water-lithium bromide AHP is then achieved by minimizing the total annual cost. A comprehensive optimization is carried out by relaxation of all stream pressure drops as well as heat exchanger areas involving in AHP structure. It is shown that by applying genetic algorithm optimizer, the total annual cost of the proposed AHP is decreased by 18% compared to one resulted from simulation.

A Micro-Watt Second Order Filter for a Chopper Stabilized MEMS Pressure Sensor Interface

This paper describes a low-power second-order filter for a continuous-time chopper stabilized capacitive sensor interface, integrated with a fully differential post-CMOS surface-micromachined MEMS pressure sensor. The circuit uses a single-ended folded-cascode operational amplifier and two GM-C filters connected in cascade. The circuit is realized in a 0.18 μm CMOS process and offers differential to single-ended conversion. The novelty of the scheme is the cascade of two GM-C filters to achieve a second-order filter while minimizing power dissipation. The simulated filter cutoff frequency is 1.14 kHz at common-mode voltage 1.65 V, operating from a 3.3 V supply while dissipating 172μW of power. The filter achieves an operating range of 1V for an output load of 1MOhm and 10pF.