Development and Evaluation of Gastro Retentive Floating Tablets of Ayurvedic Vati Formulation

Floating tablets of Marichyadi Vati were developed with an aim to prolong its gastric residence time and increase the bioavailability of drug. Rapid gastrointestinal transit could result in incomplete drug release from the drug delivery system above the absorption zone leading to diminished efficacy of the administered dose. The tablets were prepared by wet granulation technique, using HPMC E50 LV act as Matrixing agent, Carbopol as floating enhancer, microcrystalline cellulose as binder, Sodium bi carbonate as effervescent agent with other excipients. The simplex lattice design was used for selection of variables for tablets formulation. Formulation was optimized on the basis of floating time and in vitro drug release. The results showed that the floating lag time for optimized formulation was found to be 61 second with about 97.32 % of total drug release within 3 hours. The vitro release profiles of drug from the formulation could be best expressed zero order with highest linearity r2 = 0.9943. It was concluded that the gastroretentive drug delivery system can be developed for Marichyadi Vati containing Piperine to increase the residence time of the drug in the stomach and thereby increasing bioavailability.

Exploiting Non Circularity for Angle Estimation in Bistatic MIMO Radar Systems

The traditional second order statistics approach of using only the hermitian covariance for non circular signals, does not take advantage of the information contained in the complementary covariance of these signals. Radar systems often use non circular signals such as Binary Phase Shift Keying (BPSK) signals. Their noncicular property can be exploited together with the dual centrosymmetry of the bistatic MIMO radar system to improve angle estimation performance. We construct an augmented matrix from the received data vectors using both the positive definite hermitian covariance matrix and the complementary covariance matrix. The Unitary ESPRIT technique is then applied to the signal subspace of the augmented covariance matrix for automatically paired Direction-of-arrival (DOA) and Direction-of-Departure (DOD) angle estimates. The number of targets that can be detected is twice that obtainable with the conventional ESPRIT approach. Simulation results show the effectiveness of this method in terms of increase in resolution and the number of targets that can be detected.

Microstructure and Mechanical Characterization of Heat Treated Stir Cast Silica (Sea Sand) Reinforced 7XXX Al Alloy MMCs

Metal matrix composites consists of a metallic matrix combined with dispersed particulate phase as reinforcement. Aluminum alloys have been the primary material of choice for structural components of aircraft since about 1930. Well known performance characteristics, known fabrication costs, design experience, and established manufacturing methods and facilities, are just a few of the reasons for the continued confidence in 7XXX Al alloys that will ensure their use in significant quantities for the time to come. Particulate MMCs are of special interest owing to the low cost of their raw materials (primarily natural river sand here) and their ease of fabrication, making them suitable for applications requiring relatively high volume production. 7XXX Al alloys are precipitation hardenable and therefore amenable for thermomechanical treatment. Al–Zn alloys reinforced with particulate materials are used in aerospace industries in spite of the drawbacks of susceptibility to stress corrosion, poor wettability, poor weldability and poor fatigue resistance. The resistance offered by these particulates for the moving dislocations impart secondary hardening in turn contributes strain hardening. Cold deformation increases lattice defects, which in turn improves the properties of solution treated alloy. In view of this, six different Al–Zn–Mg alloy composites reinforced with silica (3 wt. % and 5 wt. %) are prepared by conventional semisolid synthesizing process. The cast alloys are solution treated and aged. The solution treated alloys are further severely cold rolled to enhance the properties. The hardness and strength values are analyzed and compared with silica free Al – Zn-Mg alloys. Precipitation hardening phenomena is accelerated due to the increased number of potential sites for precipitation. Higher peak hardness and lesser aging time are the characteristics of thermo mechanically treated samples. For obtaining maximum hardness, optimum number and volume of precipitate particles are required. The Al-5Zn-1Mg with 5% SiO2 alloy composite shows better result.

Contact Angle Measurement of the Vinyl Ester Matrix Nanocomposites Based On Layered Silicate

Contact angle measurement was utilized in order to study the subject of the wettability and surface chemistry of the nanocomposites materials. Water and glycerol droplets were used in this study. The incorporation of layered silicate into the vinyl ester matrix helped to improve the wettability and reduced the θ values of both liquids used. The addition of 2 wt.% clay loading reduced the θ values of water and glycerol by up to 21% and 6% respectively. Likewise, the incorporation of 4 wt.% clay loading reduced the water and glycerol θ values by 49% and 38% respectively. Also this study confirms the findings in the literature regarding the relationship between the intercalation nanocomposites level and the wettability. Wide Angle X-ray Diffraction, Scanning Electron Microscopy and Transmission Electron Microscopy were utilised in order to characterise the interlamellar structure of nanocomposites.

Improving Order Quantity Model with Emergency Safety Stock (ESS)

This study considers the problem of calculating safety stocks in disaster situations inventory systems that face demand uncertainties. Safety stocks are essential to make the supply chain, which is controlled by forecasts of customer needs, in response to demand uncertainties and to reach predefined goal service levels. To solve the problem of uncertainties due to the disaster situations affecting the industry sector, the concept of Emergency Safety Stock (ESS) was proposed. While there exists a huge body of literature on determining safety stock levels, this literature does not address the problem arising due to the disaster and dealing with the situations. In this paper, the problem of improving the Order Quantity Model to deal with uncertainty of demand due to disasters is managed by incorporating a new idea called ESS which is based on the probability of disaster occurrence and uses probability matrix calculated from the historical data. 

The Effect of Processing Parameters of the Vinyl Ester Matrix Nanocomposites Based On Layered Silicate on the Level of Exfoliation

The study of the effect of the processing parameters on the level of intercalation between the layered silicate and polymer of two different methodology took place. X-ray diffraction, Scanning Electron Microscopy, Energy Dispersive X-ray Spectrometry, and Transmission Electron Microscopy were utilized in order to examine the intercalation level of nanocomposites of both methodologies. It was found that drying the clay prior to mixing with the polymer, mixing time and speed, degassing time, and the curing method had major changes to the level of distribution of the nanocomposites structure. In methodology 1, the presence of aggregation layers was observed at only 2.5 wt.% clay loading whereas in methodology 2 the presence of aggregation layers was found at higher clay loading (i.e. 5 wt.%).

Mechanical and Thermal Properties Characterisation of Vinyl Ester Matrix Nanocomposites Based On Layered Silicate: Effect of Processing Parameters

The mechanical properties including flexural and tensile of neat vinyl ester and polymer based on layered silicate nanocomposite materials of two different methodologies are discussed. Methodology 1 revealed that the addition of layered silicate into the polymer matrix increased the mechanical and thermal properties up to 1 wt.% clay loading. The incorporation of more clay resulted in decreasing the properties which was traced to the existence of aggregation layers. The aggregation layers imparted a negative impact on the overall mechanical and thermal properties. On the other hand, methodology 2 increased the mechanical and thermal properties up to 4 wt.% clay loading. The different amounts of improvements were assigned to the various preparation parameters. Wide Angle X-ray Diffraction, Scanning Electron Microscopy and Transmission Electron Microscopy were utilized in order to characterize the interlamellar structure of nanocomposites.

Quantum Enhanced Correlation Matrix Memories via States Orthogonalisation

This paper introduces a Quantum Correlation Matrix Memory (QCMM) and Enhanced QCMM (EQCMM), which are useful to work with quantum memories. A version of classical Gram-Schmidt orthogonalisation process in Dirac notation (called Quantum Orthogonalisation Process: QOP) is presented to convert a non-orthonormal quantum basis, i.e., a set of non-orthonormal quantum vectors (called qudits) to an orthonormal quantum basis, i.e., a set of orthonormal quantum qudits. This work shows that it is possible to improve the performance of QCMM thanks QOP algorithm. Besides, the EQCMM algorithm has a lot of additional fields of applications, e.g.: Steganography, as a replacement Hopfield Networks, Bilevel image processing, etc. Finally, it is important to mention that the EQCMM is an extremely easy to implement in any firmware.

A Decision Matrix for the Evaluation of Triplestores for Use in a Virtual Research Environment

The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for cross-domain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Lime-Pozzolan Plasters with Enhanced Thermal Capacity

A new type of lightweight plaster with the thermal capacity enhanced by PCM (Phase Change Material) addition is analyzed. The basic physical characteristics, namely the bulk density, matrix density, total open porosity, and pore size distribution are measured at first. For description of mechanical properties, compressive strength measurements are done. The thermal properties are characterized by transient impulse techniques as well as by DSC analysis that enables determination of the specific heat capacity as a function of temperature. The resistivity against the liquid water ingress is described by water absorption coefficient measurement. The experimental results indicate a good capability of the designed plaster to moderate effectively the interior climate of buildings.

Effect of Silica Fume on the Properties of Steel-Fiber Reinforced Self-compacting Concrete

Implementing significant advantages in the supply of self-compacting concrete (SCC) is necessary because of the, negative features of SCC. Examples of these features are the ductility problem along with the very high cost of its constituted materials. Silica fume with steel fiber can fix this matter by improving the ductility and decreasing the total cost of SCC by varying the cement ingredients. Many different researchers have found that there have not been enough research carried out on the steel fiber-reinforced self-compacting concrete (SFRSCC) produced with silica fume. This paper inspects both the fresh and the mechanical properties of SFRSCC with silica fume, the fresh qualities where slump flow, slump T50 and V- funnel. While, the mechanical characteristics were the compressive strength, ultrasound pulse velocity (UPV) and elastic modulus of the concrete samples. The experimental results have proven that steel fiber can enhance the mechanical features. In addition, the silica fume within the entire hybrid mix may possibly adapt the fiber dispersion and strengthen deficits due to the fibers. It could also improve the strength plus the bond between the fiber and the matrix with a dense calcium silicate-hydrate gel in SFRSCC. The concluded result was predicted using linear mathematical models and was found to be in great agreement with the experimental results.

Dimensional Variations of Cement Matrices in the Presence of Metal Fibers

The objective of this study is to present and to analyze the feasibility of using steel fibers as reinforcement in the cementations matrix to minimize the effect of free shrinkage which is a major cause of cracks that have can observe on concrete structures, also to improve the mechanical resistances of this concrete reinforced. The experimental study was performed on specimens with geometric characteristics adapted to the testing. The tests of shrinkage apply on prismatic specimens, equipped with rods fixed to the ends with different dosages of fibers, it should be noted that the fibers used are hooked end of 50mm length and 67 slenderness. The results show that the compressive strength and flexural strength increases as the degree of incorporation of fibbers increases. And the shrinkage deformations are generally less important for fibers-reinforced concrete to those appearing in the concrete without fibers.

Effect of Alkali Treatment on Impact Behavior of Areca Fibers Reinforced Polymer Composites

Natural fibers are considered to have potential use as reinforcing agents in polymer composite materials because of their principal benefits: moderate strength and stiffness, low cost, and being an environmental friendly, degradable, and renewable material. A study has been carried out to evaluate impact properties of composites made by areca fibers reinforced urea formaldehyde, melamine urea formaldehyde and epoxy resins. The extracted areca fibers from the areca husk were alkali treated with potassium hydroxide (KOH) to obtain better interfacial bonding between fiber and matrix. Then composites were produced by means of compression molding technique with varying process parameters, such as fiber condition (untreated and alkali treated), and fiber loading percentages (50% and 60% by weight). The developed areca fiber reinforced composites were then characterized by impact test. The results show that, impact strength increase with increase in the loading percentage. It is observed that, treated areca fiber reinforcement increases impact strength when compared to untreated areca fiber reinforcement.

Clustering of Variables Based On a Probabilistic Approach Defined on the Hypersphere

We consider n individuals described by p standardized variables, represented by points of the surface of the unit hypersphere Sn-1. For a previous choice of n individuals we suppose that the set of observables variables comes from a mixture of bipolar Watson distribution defined on the hypersphere. EM and Dynamic Clusters algorithms are used for identification of such mixture. We obtain estimates of parameters for each Watson component and then a partition of the set of variables into homogeneous groups of variables. Additionally we will present a factor analysis model where unobservable factors are just the maximum likelihood estimators of Watson directional parameters, exactly the first principal component of data matrix associated to each group previously identified. Such alternative model it will yield us to directly interpretable solutions (simple structure), avoiding factors rotations.

Kano’s Model for Clinical Laboratory

The clinical laboratory has received considerable recognition globally due to the rapid development of advanced technology, economic demands and its role in a patient’s treatment cycle. Although various cross-domain experiments and practices with respect to clinical laboratory projects are ready for the full swing, the customer needs are still ambiguous and debatable. The purpose of this study is to apply Kano’s model and customer satisfaction matrix to categorize service quality attributes in order to see how well these attributes are able to satisfy customer needs. The result reveals that ten of the 26 service quality attributes have greater impacts on highly increasing customer’s satisfaction and should be taken in consideration firstly.

Isolation and Classification of Red Blood Cells in Anemic Microscopic Images

Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Augmented Reality on Android

Augmented Reality is an application which combines a live view of real-world environment and computer-generated images. This paper studies and demonstrates an efficient Augmented Reality development in the mobile Android environment with the native Java language and Android SDK. Major components include Barcode Reader, File Loader, Marker Detector, Transform Matrix Generator, and a cloud database.

Investigating the Influence of Porosity on Thermal and Mechanical Properties of a C/C Composite Using Image Based FE Modelling

In this paper, 3D image based composite unit cell is constructed from high resolution tomographic images. Through-thickness thermal diffusivity and in-plane Young’s modulus are predicted for the composite unit cell. The accuracy of the image based composite unit cell is tested by comparing its results with the experimental results obtained from laser flash and tensile test. The FE predictions are in close agreement with experimental results. Through-thickness thermal diffusivity and in-plane Young’s modulus of a virgin C/C composite are predicted by replacing the properties of air (porosity) with the properties of carbon matrix. The effect of porosity was found to be more profound on thermal diffusivity than young’s modulus.