Novel Process Formulation of Multiple Unit Tablet of Pantoprazole

The present invention relates to multiple-unit tablet dosage forms, which is composed of several subunits (multiparticulates/pellets). Each small multiparticulate further composed of many layers. Some layer contains drug substance; others are rate controlling polymer. The resulting multiple-unit tablet dosage forms of pantoprazole were satisfactory fabricated. Pelletization technique has some advantages over coated tablet formulation. In coated tablet the coating may be damaged and a pinhole possibly formed that would result in increased release of drug in stomach and may be deactivated in stomach juices. If the coat of some pellets may be damaged that would not affect the release properties of the multiple-unit tablet. Hence they are beneficial in this aspect. The results confirmed the successful preparation of stable and bioequivalent once daily controlled release multiple-unit tablets of pantoprazole.

CMOS-Compatible Deposited Materials for Photonic Layers Integrated above Electronic Integrated Circuit

Silicon photonics has generated an increasing interest in recent years mainly for optical communications optical interconnects in microelectronic circuits or bio-sensing applications. The development of elementary passive and active components (including detectors and modulators), which are mainly fabricated on the silicon on insulator platform for CMOS-compatible fabrication, has reached such a performance level that the integration challenge of silicon photonics with microelectronic circuits should be addressed. Since crystalline silicon can only be grown from another silicon crystal, making it impossible to deposit in this state, the optical devices are typically limited to a single layer. An alternative approach is to integrate a photonic layer above the CMOS chip using back-end CMOS fabrication process. In this paper, various materials, including silicon nitride, amorphous silicon, and polycrystalline silicon, for this purpose are addressed.

ALD HfO2 Based RRAM with Ti Capping

HfOx based Resistive Random Access Memory (RRAM) is one of the most widely studied material stack due to its promising performances as an emerging memory technology. In this work, we systematically investigated the effect of metal capping layer by preparing sample devices with varying thickness of Ti cap and comparing their operating parameters with the help of an Agilent-B1500A analyzer.

Secondary Ion Mass Spectrometry of Proteins

The adsorption of bovine serum albumin (BSA), immunoglobulin G (IgG) and fibrinogen (Fgn) on fluorinated selfassembled monolayers have been studied using time of flight secondary ion mass spectrometry (ToF-SIMS) and Spectroscopic Ellipsometry (SE). The objective of the work has to establish the utility of ToF-SIMS for the determination of the amount of protein adsorbed on the surface. Quantification of surface adsorbed proteins was carried out using SE and a good correlation between ToF-SIMS results and SE was achieved. The surface distribution of proteins were also analysed using Atomic Force Microscopy (AFM). We show that the surface distribution of proteins strongly affect the ToFSIMS results.

Semi-automatic Construction of Ontology-based CBR System for Knowledge Integration

In order to integrate knowledge in heterogeneous case-based reasoning (CBR) systems, ontology-based CBR system has become a hot topic. To solve the facing problems of ontology-based CBR system, for example, its architecture is nonstandard, reusing knowledge in legacy CBR is deficient, ontology construction is difficult, etc, we propose a novel approach for semi-automatically construct ontology-based CBR system whose architecture is based on two-layer ontology. Domain knowledge implied in legacy case bases can be mapped from relational database schema and knowledge items to relevant OWL local ontology automatically by a mapping algorithm with low time-complexity. By concept clustering based on formal concept analysis, computing concept equation measure and concept inclusion measure, some suggestions about enriching or amending concept hierarchy of OWL local ontologies are made automatically that can aid designers to achieve semi-automatic construction of OWL domain ontology. Validation of the approach is done by an application example.

Cardiac Disorder Classification Based On Extreme Learning Machine

In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.

Intelligent Neural Network Based STLF

Short-Term Load Forecasting (STLF) plays an important role for the economic and secure operation of power systems. In this paper, Continuous Genetic Algorithm (CGA) is employed to evolve the optimum large neural networks structure and connecting weights for one-day ahead electric load forecasting problem. This study describes the process of developing three layer feed-forward large neural networks for load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. We find good performance for the large neural networks. The proposed methodology gives lower percent errors all the time. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Effect of Initial Conditions on Aerodynamic and Acoustic Characteristics of High Subsonic Jets from Sharp Edged Circular Orifice

The present work involves measurements to examine the effects of initial conditions on aerodynamic and acoustic characteristics of a Jet at M=0.8 by changing the orientation of sharp edged orifice plate. A thick plate with chamfered orifice presented divergent and convergent openings when it was flipped over. The centerline velocity was found to decay more rapidly for divergent orifice and that was consistent with the enhanced mass entrainment suggesting quicker spread of the jet compared with that from the convergent orifice. The mixing layer region elucidated this effect of initial conditions at an early stage – the growth was found to be comparatively more pronounced for the divergent orifice resulting in reduced potential core size. The acoustic measurements, carried out in the near field noise region outside the jet within potential core length, showed the jet from the divergent orifice to be less noisy. The frequency spectra of the noise signal exhibited that in the initial region of comparatively thin mixing layer for the convergent orifice, the peak registered a higher SPL and a higher frequency as well. The noise spectra and the mixing layer development suggested a direct correlation between the coherent structures developing in the initial region of the jet and the noise captured in the surrounding near field.

Fault Detection via Stability Analysis for the Hybrid Control Unit of HEVs

Fault detection determines faultexistence and detecting time. This paper discusses two layered fault detection methods to enhance the reliability and safety. Two layered fault detection methods consist of fault detection methods of component level controllers and system level controllers. Component level controllers detect faults by using limit checking, model-based detection, and data-driven detection and system level controllers execute detection by stability analysis which can detect unknown changes. System level controllers compare detection results via stability with fault signals from lower level controllers. This paper addresses fault detection methods via stability and suggests fault detection criteria in nonlinear systems. The fault detection method applies tothe hybrid control unit of a military hybrid electric vehicleso that the hybrid control unit can detect faults of the traction motor.

Effect of Hormonal Manipulations on the Pattern of the Vaginal Tissue Structure

Design of experiments made for correlated the hormonal activity of steroids and their effect on the vaginal structure properties. Vaginal wall consists of distinct layers of cells which strongly differ regarding growth in answer to steroid hormones. The presence study carried out for functional evaluation and sustained replacement effect of the reproductive hormones on the vaginal morphometry in the rabbit. Rabbits were maintained control (Co) or ovariectomized (Ovz) and continuously treated with estradiol (Ovz E) and estradiol mixture with testosterone (Ovz ET). Relative to control rabbits with the distinct tissue distribution pattern, ovariectomized animals displayed declined epithelial thickness and atrophy of the muscularis layer that cause the vaginal wall thinning. Estradiol treatment of Orz rabbits inverted these changes to status of the preovariectomy. Histometric measurements in Ovz ET group completely including of thickness of the epithelial and muscular layers was greater in comparison to that of control animals.

Thermosolutal MHD Mixed Marangoni Convective Boundary Layers in the Presence of Suction or Injection

The steady coupled dissipative layers, called Marangoni mixed convection boundary layers, in the presence of a magnetic field and solute concentration that are formed along the surface of two immiscible fluids with uniform suction or injection effects is examined. The similarity boundary layer equations are solved numerically using the Runge-Kutta Fehlberg with shooting technique. The Marangoni, buoyancy and external pressure gradient effects that are generated in mixed convection boundary layer flow are assessed. The velocity, temperature and concentration boundary layers thickness decrease with the increase of the magnetic field strength and the injection to suction. For buoyancy-opposed flow, the Marangoni mixed convection parameter enhances the velocity boundary layer but decreases the temperature and concentration boundary layers. However, for the buoyancy-assisted flow, the Marangoni mixed convection parameter decelerates the velocity but increases the temperature and concentration boundary layers.

Dynamic Threshold Adjustment Approach For Neural Networks

The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.

An Efficient Technique for Extracting Fuzzy Rulesfrom Neural Networks

Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.

Improved Automated Classification of Alcoholics and Non-alcoholics

In this paper, several improvements are proposed to previous work of automated classification of alcoholics and nonalcoholics. In the previous paper, multiplayer-perceptron neural network classifying energy of gamma band Visual Evoked Potential (VEP) signals gave the best classification performance using 800 VEP signals from 10 alcoholics and 10 non-alcoholics. Here, the dataset is extended to include 3560 VEP signals from 102 subjects: 62 alcoholics and 40 non-alcoholics. Three modifications are introduced to improve the classification performance: i) increasing the gamma band spectral range by increasing the pass-band width of the used filter ii) the use of Multiple Signal Classification algorithm to obtain the power of the dominant frequency in gamma band VEP signals as features and iii) the use of the simple but effective knearest neighbour classifier. To validate that these two modifications do give improved performance, a 10-fold cross validation classification (CVC) scheme is used. Repeat experiments of the previously used methodology for the extended dataset are performed here and improvement from 94.49% to 98.71% in maximum averaged CVC accuracy is obtained using the modifications. This latest results show that VEP based classification of alcoholics is worth exploring further for system development.

Radio over Fiber as a Cost Effective Technology for Transmission of WiMAX Signals

In this paper, an overview of the radio over fiber (RoF) technology is provided. Obstacles for reducing the capital and operational expenses in the existing systems are discussed in various perspectives. Some possible RoF deployment scenarios for WiMAX data transmission are proposed as a means for capital and operational expenses reduction. IEEE 802.16a standard based end-to-end physical layer model is simulated including intensity modulated direct detection RoF technology. Finally the feasibility of RoF technology to carry WiMAX signals between the base station and the remote antenna units is demonstrated using the simulation results.

Effect of Thermal Radiation on Temperature Variation in 2-D Stagnation-Point flow

Non-isothermal stagnation-point flow with consideration of thermal radiation is studied numerically. A set of partial differential equations that governing the fluid flow and energy is converted into a set of ordinary differential equations which is solved by Runge-Kutta method with shooting algorithm. Dimensionless wall temperature gradient and temperature boundary layer thickness for different combinaton of values of Prandtl number Pr and radiation parameter NR are presented graphically. Analyses of results show that the presence of thermal radiation in the stagnation-point flow is to increase the temperature boundary layer thickness and decrease the dimensionless wall temperature gradient.

Design of Adaptive Sliding Mode Controller for Robotic Manipulators Tracking Control

This paper proposes an adaptive sliding mode controller which combines adaptive control and sliding mode control to control a nonlinear robotic manipulator with uncertain parameters. We use an adaptive algorithm based on the concept of sliding mode control to alleviate the chattering phenomenon of control input. Adaptive laws are developed to obtain the gain of switching input and the boundary layer parameters. The stability and convergence of the robotic manipulator control system are guaranteed by applying the Lyapunov theorem. Simulation results demonstrate that the chattering of control input can be alleviated effectively. The proposed controller scheme can assure robustness against a large class of uncertainties and achieve good trajectory tracking performance.

QCM-D Study of E-casein Adsorption on Bimodal PEG Brushes

Adsorption of proteins onto a solid surface is believed to be the initial and controlling step in biofouling. A better knowledge of the fouling process can be obtained by controlling the formation of the first protein layer at a solid surface. A number of methods have been investigated to inhibit adsorption of proteins. In this study, the adsorption kinetics of

Numerical Investigation of Two-dimensional Boundary Layer Flow Over a Moving Surface

In this chapter, we have studied Variation of velocity in incompressible fluid over a moving surface. The boundary layer equations are on a fixed or continuously moving flat plate in the same or opposite direction to the free stream with suction and injection. The boundary layer equations are transferred from partial differential equations to ordinary differential equations. Numerical solutions are obtained by using Runge-Kutta and Shooting methods. We have found numerical solution to velocity and skin friction coefficient.

Paleoclimate Reconstruction during Pabdeh, Gurpi, Kazhdumi and Gadvan Formations (Cretaceous-Tertiary) Based on Clay Mineral Distribution

Paleoclimate was reconstructed by the clay mineral assemblages of shale units of Pabdeh (Paleocene- Oligocene), Gurpi (Upper Cretaceous), Kazhdumi (Albian-Cenomanian) and Gadvan (Aptian-Neocomian) formations in the Bangestan anticline. To compare with clay minerals assemblages in these formations, selected samples also taken from available formations in drilled wells in Ahvaz, Marun, Karanj, and Parsi oil fields. Collected samples prepared using standard clay mineral methodology. They were treated as normal, glycolated and heated oriented glass slides. Their identification was made on X-Ray diffractographs. Illite % varies from 8 to 36. Illite quantity increased from Pabdeh to Gurpi Formation. This may be due to dominant dry climate. Kaolinite is in range of 12-49%. Its variation style in different formations could be a marker of climate changes from wet to dry which is supported by the lithological changes. Chlorite (4-28%) can also be detected in those samples without any kaolinite. Mixed layer minerals as the mixture of illite-chlorite and illite-vermiculite-montmorillonite are varied from 6 to 36%, decreased during Kazhdumi deposition from the base to the top. This result may be according to decreasing of illite leaching process. Vermiculite was also determined in very less quantity and found in those units without kaolinite. Montmorillonite varies from 8 to 43%, and its presence is due to terrestrial depositional condition. Stratigraphical documents is also supported this idea that clay mineral distribution is a function of the climate changes. It seems, thus, the present results can be indicated a possible procedure for ancient climate changes evaluation.