94 resultados para Pharmaceuticals formulations

em Indian Institute of Science - Bangalore - Índia


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This work deals with the formulation and implementation of finite deformation viscoplasticity within the framework of stress-based hybrid finite element methods. Hybrid elements, which are based on a two-field variational formulation, are much less susceptible to locking than conventional displacement-based elements. The conventional return-mapping scheme cannot be used in the context of hybrid stress methods since the stress is known, and the strain and the internal plastic variables have to be recovered using this known stress field.We discuss the formulation and implementation of the consistent tangent tensor, and the return-mapping algorithm within the context of the hybrid method. We demonstrate the efficacy of the algorithm on a wide range of problems.

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We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. Both approaches guarantee that the radii of the spheres are properly ordered at the optimal solution. The size of the optimization problem is linear in the number of training samples. The popular SMO algorithm is adapted to solve the resulting optimization problem. Numerical experiments on some real-world data sets verify the usefulness of our approaches for data mining.

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The equilibrium solubility of a pharmaceutical compound. 1,5-dimethy1-2-phenyl-4-propan-2-ylpyrazol-3-one (propyphenazone, isopropylantipyrine) in supercritical carbon dioxide (SCCO2) was experimentally determined by a saturation method at 308, 318 and 328 K. over the pressure range of 9.0-19.0 MPa. The solubility data satisfied the self-consistency test, proposed by Mendez-Santiago and Teja. A new association model was derived to correlate the solubilities of pharmaceutical compounds in SCCO2. Solubility data from 54 different pharmaceutical compounds including steroids, antibiotics, anti-inflammatory, antioxidants, statins and specific functional drugs were collected from literature. The model successfully correlated the experimental results for the solubilities of all these compounds in SCCO2 within 12% AARD. (C) 2010 Elsevier B.V. All rights reserved.

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Six models (Simulators) are formulated and developed with all possible combinations of pressure and saturation of the phases as primary variables. A comparative study between six simulators with two numerical methods, conventional simultaneous and modified sequential methods are carried out. The results of the numerical models are compared with the laboratory experimental results to study the accuracy of the model especially in heterogeneous porous media. From the study it is observed that the simulator using pressure and saturation of the wetting fluid (PW, SW formulation) is the best among the models tested. Many simulators with nonwetting phase as one of the primary variables did not converge when used along with simultaneous method. Based on simulator 1 (PW, SW formulation), a comparison of different solution methods such as simultaneous method, modified sequential and adaptive solution modified sequential method are carried out on 4 test problems including heterogeneous and randomly heterogeneous problems. It is found that the modified sequential and adaptive solution modified sequential methods could save the memory by half and as also the CPU time required by these methods is very less when compared with that using simultaneous method. It is also found that the simulator with PNW and PW as the primary variable which had problem of convergence using the simultaneous method, converged using both the modified sequential method and also using adaptive solution modified sequential method. The present study indicates that pressure and saturation formulation along with adaptive solution modified sequential method is the best among the different simulators and methods tested.

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We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we derive a formulation which is robust to such noise. The resulting formulation applies when the noise is Gaussian, or has finite support. The formulation in general is non-convex, but in several cases of interest it reduces to a convex program. The problem of uncertainty in kernel matrix is motivated from the real world problem of classifying proteins when the structures are provided with some uncertainty. The formulation derived here naturally incorporates such uncertainty in a principled manner leading to significant improvements over the state of the art. 1.

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The topology optimization problem for the synthesis of compliant mechanisms has been formulated in many different ways in the last 15 years, but there is not yet a definitive formulation that is universally accepted. Furthermore, there are two unresolved issues in this problem. In this paper, we present a comparative study of five distinctly different formulations that are reported in the literature. Three benchmark examples are solved with these formulations using the same input and output specifications and the same numerical optimization algorithm. A total of 35 different synthesis examples are implemented. The examples are limited to desired instantaneous output direction for prescribed input force direction. Hence, this study is limited to linear elastic modeling with small deformations. Two design parameterizations, namely, the frame element based ground structure and the density approach using continuum elements, are used. The obtained designs are evaluated with all other objective functions and are compared with each other. The checkerboard patterns, point flexures, the ability to converge from an unbiased uniform initial guess, and the computation time are analyzed. Some observations are noted based on the extensive implementation done in this study. Complete details of the benchmark problems and the results are included. The computer codes related to this study are made available on the internet for ready access.

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Thyroxine is a naturally occurring human hormone produced by the thyroid gland. Clinical applications of thyroxine to treat several chronic disorders are limited by poor water solubility and instability under physiological conditions. An inclusion complex of levo-thyroxine (l-thyroxine), the active form of the hormone with gamma cyclodextrin (gamma-CD) has been obtained and studied with the aim of improving oral delivery rather than the injection formulation of the sodium salt. In addition to greater patient acceptability, inclusion complexes often improve aqueous solubility and bioavailability, stability, and reduce toxicity of drugs, thus providing enhanced pharmaceutical formulations. Physicochemical characterization of the inclusion complex was carried out using Fourier transform infrared spectroscopy, X-ray diffractometry, differential scanning calorimetry, scanning electron microscopy and proton nuclear magnetic resonance spectroscopy. Intermolecular dipolar interactions for the inclusion complex were also studied using 2 dimensional ROESY experiments. Formation of the inclusion complex between the protons H3 and H5 of cyclodextrin with aromatic protons of thyroxine was confirmed by their dipolar interaction. Molecular modelling was used to understand the basis for the complex formation and predict the formation of other complexes. Interestingly, we found that l-thyroxine forms an inclusion complex only with the larger gamma-CD and not with other available alpha and beta forms.

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Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.

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Some of the well known formulations for topology optimization of compliant mechanisms could lead to lumped compliant mechanisms. In lumped compliance, most of the elastic deformation in a mechanism occurs at few points, while rest of the mechanism remains more or less rigid. Such points are referred to as point-flexures. It has been noted in literature that high relative rotation is associated with point-flexures. In literature we also find a formulation of local constraint on relative rotations to avoid lumped compliance. However it is well known that a global constraint is easier to handle than a local constraint, by a numerical optimization algorithm. The current work presents a way of putting global constraint on relative rotations. This constraint is also simpler to implement since it uses linearized rotation at the center of finite-elements, to compute relative rotations. I show the results obtained by using this constraint oil the following benchmark problems - displacement inverter and gripper.

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he Dirac generator formalism for relativistic Hamiltonian dynamics is reviewed along with its extension to constraint formalism. In these theories evolution is with respect to a dynamically defined parameter, and thus time evolution involves an eleventh generator. These formulations evade the No-Interaction Theorem. But the incorporation of separability reopens the question, and together with the World Line Condition leads to a second no-interaction theorem for systems of three or more particles. Proofs are omitted, but the results of recent research in this area is highlighted.

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PIP: A delphi study was conducted to identify or envision health scenarios in India by the year 2000. Questionnaires consisting of 48 questions on 5 areas (diagnosis and therapy; family planning; pharmaceuticals and drugs; biochemical and biomedical research; health services) were mailed to 250 experts in India. 36 responded. Results were compiled and mailed back to the respondents for changes and comments. 17 people responded. Results of the delphi study shows that policy decisions with respect to compulsory family planning as well as health education at secondary school level will precede further breakthroughs in birth control technology. Non operation reversible sterilization procedures, immunological birth control, Ayurvedic medicines for contraception and abortion, and selection of baby's sex are all possible by 2000 thereafter. Complete eradication of infectious diseases, malnutrition and associated diseases is considered unlikely before 2000, as are advances in biomedical research. Changes in health services (e.g., significant increases in hospital beds and doctors, cheap bulk drugs), particularly in rural areas, are imminent, leading to prolonging of life expectancy to 70 years. Genetic engineering may provide significant breakthroughs in the prevention of malignancies and cardiac disorders. The India delphi study is patterned after a similar delphi study conducted in the U.S. by Smith, Kline and French (SKF) Laboratories in 1968. The SKF study was able to predict some breakthroughs with basic research which have been realized.

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In the case of an ac cable, power transmission is limited by the length of the cable due to the capacitive reactive current component. It is well known that high-voltage direct current (HVDC) cables do not have such limitations. However, insulation-related thermal problems pose a limitation on the power capability of HVDC cables. The author presents a viable theoretical development, a logical extension to Whitehead's theory on thermal limitations of the insulation. The computation of the maximum power-carrying capability of HVDC cables subject to limits on the maximum operable temperature of the insulation is presented. The limitation on the power-carrying capability is closely associated with the electrothermal insulation failure. The effect of environmental interaction by way of external thermal resistance, an important aspect, is also considered in the formulations. The Lagrange multiplier method has been used to handle the ensuing optimization problem. The theory is based on an accepted theory of thermal breakdown in insulation and is an important and a coherent extension of great significance.