scholarly journals An Improvement of a Non-uniform Concentration Inequality for Randomized Orthogonal Array Sampling Designs

2009 ◽  
Vol 1 (2) ◽  
Author(s):  
Kittipong Laipaporn ◽  
Kritsada Sungkamongkol
Keyword(s):  
Orthogonal Array ◽  
Concentration Inequality

Formulation Development of Tamoxifen Loaded Lipid Nanoparticle by Taguchi (L12 (2 11)) Orthogonal Array Design

2020 ◽  
Vol 16 ◽  
Author(s):  
Poovi Ganesan ◽  
N Damodharan
Keyword(s):  
Orthogonal Array ◽  
Drug Loading ◽  
Optimization Technique ◽  
Pharmaceutical Products ◽  
Water Soluble ◽  
Nanostructured Lipid Carrier ◽  
Orthogonal Array Design ◽  
Formulation Development ◽  
Array Design ◽  
Lipid Nanoparticle

Background: A better understanding of the biopharmaceutical and physicochemical properties of drugs and the pharmaco-technical factors would be of great help for developing pharmaceutical products. But, it is extremely difficult to study the effect of each variable and interaction among them through the conventional approach Objective: To screen the most influential factors affecting the particle size (PS) of lipid nanoparticle (LNPs) (solid lipid nanoparticle (SLN) and nanostructured lipid carrier (NLC)) for poorly water-soluble BCS class-II drug like tamoxifen (TMX) to improve its oral bioavailability and to reduce its toxicity to tolerable limits using Taguchi (L12 (2 11)) orthogonal array design by applying computer optimization technique. Results: The size of all LNPs formulations prepared as per the experimental design varied between 172 nm and 3880 μm, polydispersity index between 0.033 and 1.00, encapsulation efficiency between 70.8% and 75.7%, and drug loading between 5.84% and 9.68%. The study showed spherical and non-spherical as well as aggregated and non-aggregated LNPs. Besides, it showed no interaction and amorphous form of the drug in LNPs formulation. The Blank NLCs exhibited no cytotoxicity on MCF-7 cells as compared to TMX solution, SLNs (F5) and NLCs (F12) suggests that the cause of cell death is primarily from the effect of TMX present in NLCs. Conclusions: The screening study clearly showed the importance of different individual factors significant effect for the LNPs formulation development and its overall performance in an in-vitro study with minimum experimentation thus saving considerable time, efforts, and resources for further in-depth study.

Application of L6 Orthogonal Array for Optimal Selection of Some Process Parameters in GMAW Process

2012 ◽  
Vol 45 (4) ◽  
pp. 41 ◽  
Author(s):  
M. K. Saha ◽  
Santanu Das ◽  
A. Bandyopadhyay ◽  
S. Bandyopadhyay
Keyword(s):  
Process Parameters ◽  
Orthogonal Array ◽  
Optimal Selection ◽  
Selection Of

Application of L6 Orthogonal Array for Optimal Selection of Some Process Parameters in GMAW Process

2012 ◽  
Vol 45 (4) ◽  
pp. 41
Author(s):  
M. K. Saha ◽  
Santanu Das ◽  
A. Bandyopadhyay ◽  
S. Bandyopadhyay
Keyword(s):  
Process Parameters ◽  
Orthogonal Array ◽  
Optimal Selection ◽  
Selection Of

4-GHz band bandpass filter using orthogonal array coupling TM110 dual mode dielectric resonator

1990 ◽  
Vol 73 (10) ◽  
pp. 10-18
Author(s):  
Toshio Nishikawa ◽  
Youhei Ishikawa ◽  
Jun Hattori ◽  
Yoshio Kobayashi
Keyword(s):  
Orthogonal Array ◽  
Dielectric Resonator ◽  
Bandpass Filter ◽  
Dual Mode

Supercritical CO2 Extraction of Rhizoma Atractylodis macrocephalae

2012 ◽  
Vol 549 ◽  
pp. 60-64
Author(s):  
Zhen Huang ◽  
Xiao Han Shi ◽  
Shao Fang Liu ◽  
Wei Juan Jiang
Keyword(s):  
Particle Size ◽  
Orthogonal Array ◽  
Time Pressure ◽  
Extraction Yield ◽  
Extraction Time ◽  
Time Varying ◽  
Orthogonal Array Design ◽  
Array Design ◽  
Different Sources

An orthogonal array design was employed for optimizing the supercritical CO2 extraction of Rhizoma Atractylodis Macrocephalae. The extraction was performed at temperature from 40 to 60oC, pressure from 15 to 35MPa, extraction time varying from 30 to 90min and particle size spanning from 20 to 80 mesh. The results reflect that the extraction yield is more significantly influenced by the extraction time, pressure and particle size but less by temperature. The experiments show that the extraction yield obviously increases with increasing pressure, different from the literatures. In terms of the sample origin, a comparison shows that outstanding differences exist among the extraction yields from different sources.

scholarly journals Functional Inequalities for Two-Level Concentration

2021 ◽  
Author(s):  
Franck Barthe ◽  
Michał Strzelecki
Keyword(s):  
Sobolev Inequality ◽  
Poincaré Inequality ◽  
Logarithmic Sobolev Inequality ◽  
Probability Measures ◽  
Exponential Rate ◽  
Functional Inequalities ◽  
Concentration Inequality ◽  
Poincare Inequality ◽  
Free Concentration ◽  
Concentration Property

AbstractProbability measures satisfying a Poincaré inequality are known to enjoy a dimension-free concentration inequality with exponential rate. A celebrated result of Bobkov and Ledoux shows that a Poincaré inequality automatically implies a modified logarithmic Sobolev inequality. As a consequence the Poincaré inequality ensures a stronger dimension-free concentration property, known as two-level concentration. We show that a similar phenomenon occurs for the Latała–Oleszkiewicz inequalities, which were devised to uncover dimension-free concentration with rate between exponential and Gaussian. Motivated by the search for counterexamples to related questions, we also develop analytic techniques to study functional inequalities for probability measures on the line with wild potentials.

scholarly journals $$L_2$$-norm sampling discretization and recovery of functions from RKHS with finite trace

2021 ◽  
Vol 19 (2) ◽  
Author(s):  
Moritz Moeller ◽  
Tino Ullrich
Keyword(s):  
Random Function ◽  
Additional Assumption ◽  
Main Tool ◽  
Singular Values ◽  
Rates Of Convergence ◽  
Concentration Inequality ◽  
Worst Case ◽  
Mercer Kernels ◽  
Finite Trace ◽  
Complex Valued

AbstractIn this paper we study $$L_2$$ L 2 -norm sampling discretization and sampling recovery of complex-valued functions in RKHS on $$D \subset \mathbb {R}^d$$ D ⊂ R d based on random function samples. We only assume the finite trace of the kernel (Hilbert–Schmidt embedding into $$L_2$$ L 2 ) and provide several concrete estimates with precise constants for the corresponding worst-case errors. In general, our analysis does not need any additional assumptions and also includes the case of non-Mercer kernels and also non-separable RKHS. The fail probability is controlled and decays polynomially in n, the number of samples. Under the mild additional assumption of separability we observe improved rates of convergence related to the decay of the singular values. Our main tool is a spectral norm concentration inequality for infinite complex random matrices with independent rows complementing earlier results by Rudelson, Mendelson, Pajor, Oliveira and Rauhut.

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