The Effect of Selective Cyclooxygenase (COX) Inhibitors on Japanese Medaka (Oryzias latipes) Reproduction Parameters

Our results showed that treatment with both cyclooxygenase (COX1 or COX2) inhibitors impair reproduction parameters of the medaka. Resveratrol (COX1 inhibitor) caused an decrease in the number of spawning females at the first week of feeding fish with experimental diets. In the group treated with NS- 398 (COX2 inhibitor) we found the lowest sperm velocity parameters and decreased linearity of movement. The ovaries of the medaka fed feed supplemented with Resveratrol or NS-398 were confirmed to have a lower share of matured oocytes however during the experiment (four weeks) the number of eggs spawned by females was similar. Both inhibitors in fish diet (20 mg/kg body weight/day) caused a decrease in the embryo survival. Our results revealed that for the medaka female reproduction, activity of both COX enzymes might be necessary whereas males reproduction competence, as expressed by sperm motility parameters, might be related to COX2 activity.

Implementation of a “DIVA“ Concept withspecific Elisa Kits; When Subunit H5 Avian Influenza Vaccine is used

The main objective of this study was to demonstrate that differentiation of infected and vaccinated animals (DIVA) strategy using different ELISA tests is possible when a subunit vaccine (Haemagglutinin protein) is used to prevent Avian influenza. Special emphasis was placed on the differentiation in the serological response to different components of the AIV (Nucleoprotein, Neuraminidase, Haemagglutinin, Nucleocapsid) between chickens that were vaccinated with a whole virus kill vaccine and recombinant vaccine. Furthermore, the potential use of this DIVA strategy using ELISA assays to detect Neuraminidase 1 (N1) was analyzed as strategy in countries where the field virus is H5N1 and the vaccine used is formulated with H5N2. Detection of AIV-s antibodies to any component in serum was negative for all animals on the study days 0-13. At study day 14 the titers of antibodies against Nucleoprotein (NP) and Nucleocapsid (NC) rose in the experimental groups vaccinated with Volvac® AI KV and were negatives during all the trial in the experimental groups vaccinated with a subunit H5; significant statistically differences were observed between these groups (p < 0.05). The seroconversion either Haemagglutinin or Neuraminidase was evident after 21 days post-vaccination in the experimental groups vaccinated with the respective viral fraction. Regarding the main aim of this study and according with the results that were obtained, use a combination of different ELISA test as a DIVA strategy is feasible when the vaccination is carry out with a subunit H5 vaccine. Also is possible to use the ELISA kit to detect Neuraminidase (either N1 or N2) as a DIVA concept in countries where H5N1 is present and the vaccination programs are done with H5N2 vaccine.

Equilibrium Modeling of Carbon Dioxide Adsorption on Zeolites

High pressure adsorption of carbon dioxide on zeolite 13X was investigated in the pressure range (0 to 4) Mpa and temperatures 298, 308 and 323K. The data fitting is accomplished with the Toth, UNILAN, Dubinin-Astakhov and virial adsorption models which are generally used for micro porous adsorbents such as zeolites. Comparison with experimental data from the literature indicated that the virial model would best determine results. These results may be partly attributed to the flexibility of the virial model which can accommodate as many constants as the data warrants.

Identification of Nonlinear Predictor and Simulator Models of a Cement Rotary Kiln by Locally Linear Neuro-Fuzzy Technique

One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using nonlinear identification technique on the Locally Linear Neuro- Fuzzy (LLNF) model. For the first time, a simulator model as well as a predictor one with a precise fifteen minute prediction horizon for a cement rotary kiln is presented. These models are trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these models. The data collected from White Saveh Cement Company is used for modeling.

Collaborative Web Platform for Rich Media Educational Material Creation

This paper describes a platform that faces the main research areas for e-learning educational contents. Reusability tackles the possibility to use contents in different courses reducing costs and exploiting available data from repositories. In our approach the production of educational material is based on templates to reuse learning objects. In terms of interoperability the main challenge lays on reaching the audience through different platforms. E-learning solution must track social consumption evolution where nowadays lots of multimedia contents are accessed through the social networks. Our work faces it by implementing a platform for generation of multimedia presentations focused on the new paradigm related to social media. The system produces videos-courses on top of web standard SMIL (Synchronized Multimedia Integration Language) ready to be published and shared. Regarding interfaces it is mandatory to satisfy user needs and ease communication. To overcome it the platform deploys virtual teachers that provide natural interfaces while multimodal features remove barriers to pupils with disabilities.

Iterative Process to Improve Simple Adaptive Subdivision Surfaces Method with Butterfly Scheme

Subdivision surfaces were applied to the entire meshes in order to produce smooth surfaces refinement from coarse mesh. Several schemes had been introduced in this area to provide a set of rules to converge smooth surfaces. However, to compute and render all the vertices are really inconvenient in terms of memory consumption and runtime during the subdivision process. It will lead to a heavy computational load especially at a higher level of subdivision. Adaptive subdivision is a method that subdivides only at certain areas of the meshes while the rest were maintained less polygons. Although adaptive subdivision occurs at the selected areas, the quality of produced surfaces which is their smoothness can be preserved similar as well as regular subdivision. Nevertheless, adaptive subdivision process burdened from two causes; calculations need to be done to define areas that are required to be subdivided and to remove cracks created from the subdivision depth difference between the selected and unselected areas. Unfortunately, the result of adaptive subdivision when it reaches to the higher level of subdivision, it still brings the problem with memory consumption. This research brings to iterative process of adaptive subdivision to improve the previous adaptive method that will reduce memory consumption applied on triangular mesh. The result of this iterative process was acceptable better in memory and appearance in order to produce fewer polygons while it preserves smooth surfaces.

On Solving Single-Period Inventory Model under Hybrid Uncertainty

Inventory decisional environment of short life-cycle products is full of uncertainties arising from randomness and fuzziness of input parameters like customer demand requiring modeling under hybrid uncertainty. Prior inventory models incorporating fuzzy demand have unfortunately ignored stochastic variation of demand. This paper determines an unambiguous optimal order quantity from a set of n fuzzy observations in a newsvendor inventory setting in presence of fuzzy random variable demand capturing both fuzzy perception and randomness of customer demand. The stress of this paper is in providing solution procedure that attains optimality in two steps with demand information availability in linguistic phrases leading to fuzziness along with stochastic variation. The first step of solution procedure identifies and prefers one best fuzzy opinion out of all expert opinions and the second step determines optimal order quantity from the selected event that maximizes profit. The model and solution procedure is illustrated with a numerical example.

Design and Development of Pico-hydro Generation System for Energy Storage Using Consuming Water Distributed to Houses

This paper describes the design and development of pico-hydro generation system using consuming water distributed to houses. Water flow in the domestic pipes has kinetic energy that potential to generate electricity for energy storage purposes in addition to the routine activities such as laundry, cook and bathe. The inherent water pressure and flow inside the pipe from utility-s main tank that used for those usual activities is also used to rotate small scale hydro turbine to drive a generator for electrical power generation. Hence, this project is conducted to develop a small scale hydro generation system using consuming water distributed to houses as an alternative electrical energy source for residential use.

Density Clustering Based On Radius of Data (DCBRD)

Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.

Monitoring of Dielectric Losses and Use of Ferrofluids for Bushing Cooling

At present, the tendency to implement the conditionbased maintenance (CBM), which allows the optimization of the expenses for equipment monitoring, is more and more evident; also, the transformer substations with remote monitoring are increasingly used. This paper reviews all the advantages of the on-line monitoring and presents an equipment for on-line monitoring of bushings, which is the own contribution of specialists who are the authors of this paper. The paper presents a study of the temperature field, using the finite element method. For carrying out this study, the 3D modelling of the above mentioned bushing was performed. The analysis study is done taking into account the extreme thermal stresses, focusing at the level of the first cooling wing section of the ceramic insulator. This fact enables to justify the tanδ variation in time, depending on the transformer loading and the environmental conditions. With a view to reducing the variation of dielectric losses in bushing insulation, the use of ferrofuids instead of mineral oils is proposed.

Surface Topography Assessment Techniques based on an In-process Monitoring Approach of Tool Wear and Cutting Force Signature

The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of the different elements of the system: tool-machineworkpart- cutting parameters. However, one of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Time-dependent modeling is beneficial when modern machining systems, such as adaptive control techniques are considered, where the state of the machined surface and the health of the cutting edge are monitored, assessed and controlled online using realtime information provided by the variability encountered in the measured force signals. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge-s random deformation.

Transient Heat Transfer Model for Car Body Primer Curing

A transient heat transfer mathematical model for the prediction of temperature distribution in the car body during primer baking has been developed by considering the thermal radiation and convection in the furnace chamber and transient heat conduction governing equations in the car framework. The car cockpit is considered like a structure with six flat plates, four vertical plates representing the car doors and the rear and front panels. The other two flat plates are the car roof and floor. The transient heat conduction in each flat plate is modeled by the lumped capacitance method. Comparison with the experimental data shows that the heat transfer model works well for the prediction of thermal behavior of the car body in the curing furnace, with deviations below 5%.

The Effect of Increment in Simulation Samples on a Combined Selection Procedure

Statistical selection procedures are used to select the best simulated system from a finite set of alternatives. In this paper, we present a procedure that can be used to select the best system when the number of alternatives is large. The proposed procedure consists a combination between Ranking and Selection, and Ordinal Optimization procedures. In order to improve the performance of Ordinal Optimization, Optimal Computing Budget Allocation technique is used to determine the best simulation lengths for all simulation systems and to reduce the total computation time. We also argue the effect of increment in simulation samples for the combined procedure. The results of numerical illustration show clearly the effect of increment in simulation samples on the proposed combination of selection procedure.

Designing a Novel General Sorting Network Constructor Using Artificial Evolution

A method is presented for the construction of arbitrary even-input sorting networks exhibiting better properties than the networks created using a conventional technique of the same type. The method was discovered by means of a genetic algorithm combined with an application-specific development. Similarly to human inventions in the area of theoretical computer science, the evolved invention was analyzed: its generality was proven and area and time complexities were determined.

Electromagnetic Flow Meter Efficiency

A study of electromagnetic flow meter is presented in the paper. Comparison has been made between the analytical and the numerical results by the use of FEM numerical analysis (Quick Field 5.6) for determining polarization voltage through the circle cross section of the polarization transducer. Exciting and geometrical parameters increasing its effectiveness has been examined. The aim is to obtain maximal output signal. The investigations include different variants of the magnetic flux density distribution around the tube: homogeneous field of magnitude Bm, linear distribution with maximal value Bm and trapezium distribution conserving the same exciting magnetic energy as the homogeneous field.

Numerical Solution of the Equations of Salt Diffusion into the Potato Tissues

Fick's second law equations for unsteady state diffusion of salt into the potato tissues were solved numerically. The set of equations resulted from implicit modeling were solved using Thomas method to find the salt concentration profiles in solid phase. The needed effective diffusivity and equilibrium distribution coefficient were determined experimentally. Cylindrical samples of potato were infused with aqueous NaCl solutions of 1-3% concentrations, and variations in salt concentrations of brine were determined over time. Solute concentrations profiles of samples were determined by measuring salt uptake of potato slices. For the studied conditions, equilibrium distribution coefficients were found to be dependent on salt concentrations, whereas the effective diffusivity was slightly affected by brine concentration.

On Problem of Parameters Identification of Dynamic Object

In this paper, some problem formulations of dynamic object parameters recovery described by non-autonomous system of ordinary differential equations with multipoint unshared edge conditions are investigated. Depending on the number of additional conditions the problem is reduced to an algebraic equations system or to a problem of quadratic programming. With this purpose the paper offers a new scheme of the edge conditions transfer method called by conditions shift. The method permits to get rid from differential links and multipoint unshared initially-edge conditions. The advantage of the proposed approach is concluded by capabilities of reduction of a parametric identification problem to essential simple problems of the solution of an algebraic system or quadratic programming.

The Diophantine Equation y2 − 2yx − 3 = 0 and Corresponding Curves over Fp

In this work, we consider the number of integer solutions of Diophantine equation D : y2 - 2yx - 3 = 0 over Z and also over finite fields Fp for primes p ≥ 5. Later we determine the number of rational points on curves Ep : y2 = Pp(x) = yp 1 + yp 2 over Fp, where y1 and y2 are the roots of D. Also we give a formula for the sum of x- and y-coordinates of all rational points (x, y) on Ep over Fp.

VLSI Design of 2-D Discrete Wavelet Transform for Area-Efficient and High-Speed Image Computing

This paper presents a VLSI design approach of a highspeed and real-time 2-D Discrete Wavelet Transform computing. The proposed architecture, based on new and fast convolution approach, reduces the hardware complexity in addition to reduce the critical path to the multiplier delay. Furthermore, an advanced twodimensional (2-D) discrete wavelet transform (DWT) implementation, with an efficient memory area, is designed to produce one output in every clock cycle. As a result, a very highspeed is attained. The system is verified, using JPEG2000 coefficients filters, on Xilinx Virtex-II Field Programmable Gate Array (FPGA) device without accessing any external memory. The resulting computing rate is up to 270 M samples/s and the (9,7) 2-D wavelet filter uses only 18 kb of memory (16 kb of first-in-first-out memory) with 256×256 image size. In this way, the developed design requests reduced memory and provide very high-speed processing as well as high PSNR quality.

Effect of Genotype, Explant Type and Growth Regulators on The Accumulation of Flavonoides of (Silybum marianum L.) in In vitro Culture

The extract of milk thistle contains a mix of flavonolignans termed silymarine.. In order to analysis influence of growth regulators, genotype, explant and subculture on the accumulation of flavonolignans, a study was carried out by using two genotype (Budakalszi and Noor abad moghan cultivars), cotyledon and hypocotyle explants, solid media of MS supplemented by different combinations of two growth regulators; Kinetin (0.1, 1 mg/l) and 2,4-D (1, 2 mg/l). Seeds of the plant were germinated in MS media whitout growth regulators in growth chamber at 26°C and darkness condition. In order to callus induction, the culture media was supplemented whit different concentrations of 2,4-D and kinetin. Calli obtained from explants were sub-cultured four times into the fresh media of the first experiment. flavonoides was extracted from calli in four subcultures. The flavonoid components were determined by high- performance liquid choromatography (HPLC) and separated into Taxifolin, Silydianin+Silychristin, Silybin A+B and Isosilybin A+B. Results showed that with increasing callus age, increased accumulation of silybin A+B, but reduced Isosilybin A+B content. Highest accumulation of Taxifolin was observed at first calli. Calli produced from cotyledon explant of Budakalszi cultivar were superior for Silybin A+B, where calli from hypocotyl explant produced higher amount of Taxifolin and Silydianin+Silychristin. The best cultivar for Silymarin production in this study was Budakalszi cultivar. High amount of SBN A+B and TXF were obtained from hypocotil explant.