scholarly journals A Physico-chemical Model of Seepage Flows in Reservoirs during Alkaline Flooding

2011 ◽  
Author(s):  
Z. Zhang ◽  
J. C. Li ◽  
Jiachun Li ◽  
Song Fu
Keyword(s):  
Chemical Model ◽  
Seepage Flows ◽  
Physico Chemical

scholarly journals An improved physico-chemical model of hybridization on high-density oligonucleotide microarrays

2008 ◽  
Vol 24 (10) ◽  
pp. 1278-1285 ◽  
Author(s):  
N. Ono ◽  
S. Suzuki ◽  
C. Furusawa ◽  
T. Agata ◽  
A. Kashiwagi ◽  
...  
Keyword(s):  
High Density ◽  
Chemical Model ◽  
Oligonucleotide Microarrays ◽  
Physico Chemical

scholarly journals Influence of galactic arm scale dynamics on the molecular composition of the cold and dense ISM III. Elemental depletion and shortcomings of the current physico-chemical models

2020 ◽  
Vol 497 (2) ◽  
pp. 2309-2319
Author(s):  
V Wakelam ◽  
W Iqbal ◽  
J-P Melisse ◽  
P Gratier ◽  
M Ruaud ◽  
...  
Keyword(s):  
Gas Phase ◽  
Molecular Form ◽  
Dense Medium ◽  
Chemical Model ◽  
Physical Conditions ◽  
Dense Cores ◽  
Chemical Models ◽  
Physico Chemical ◽  
Galactic Model ◽  
Elemental Depletion

ABSTRACT We present a study of the elemental depletion in the interstellar medium. We combined the results of a Galactic model describing the gas physical conditions during the formation of dense cores with a full-gas-grain chemical model. During the transition between diffuse and dense medium, the reservoirs of elements, initially atomic in the gas, are gradually depleted on dust grains (with a phase of neutralization for those which are ions). This process becomes efficient when the density is larger than 100 cm−3. If the dense material goes back into diffuse conditions, these elements are brought back in the gas phase because of photo-dissociations of the molecules on the ices, followed by thermal desorption from the grains. Nothing remains on the grains for densities below 10 cm−3 or in the gas phase in a molecular form. One exception is chlorine, which is efficiently converted at low density. Our current gas–grain chemical model is not able to reproduce the depletion of atoms observed in the diffuse medium except for Cl, which gas abundance follows the observed one in medium with densities smaller than 10 cm−3. This is an indication that crucial processes (involving maybe chemisorption and/or ice irradiation profoundly modifying the nature of the ices) are missing.

A physico-chemical model for polyelectrolyte enhanced ultrafiltration

2011 ◽  
Vol 376 (1-2) ◽  
pp. 142-152 ◽  
Author(s):  
Sourav Mondal ◽  
Sonia Ben Mlouka ◽  
Mahmoud Dhahbi ◽  
Sirshendu De
Keyword(s):  
Chemical Model ◽  
Physico Chemical

scholarly journals Distinct and Quantitative Validation for Predictive Process Modelling in Steam Distillation of Caraway Fruits and Lavender Flower Following a Quality-By-Design (QbD) Approach

Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 594 ◽  
Author(s):  
Thorsten Roth ◽  
Lukas Uhlenbrock ◽  
Jochen Strube
Keyword(s):  
Quality By Design ◽  
Steam Distillation ◽  
Process Development ◽  
Model Development ◽  
Chemical Model ◽  
Maximum Information ◽  
Physico Chemical ◽  
Target Values ◽  
Different Types ◽  
Quantitative Validation

A quality by design (QbD) approach as part of process development in the regulated, pharmaceutical industry requires many experiments. Due to the large number, process development is time consuming and cost intensive. A key to modern process development to reduce the number of required experiments is a predictive simulation with a validated physico-chemical model. In order to expand the process expertise of steam distillation through maximum information, a model development workflow is used in this paper, which focuses on implementation, verification, parametrization and validation of a physico-chemical model. Process robustness and sensitivity of target values can be determined from the developed general model and design of experiments with statistical evaluations. The model validation is exemplified by two different types of plant systems, caraway fruits (Carum Carvi) and lavender flowers (Lavandula).

scholarly journals Measuring Selection Across HIV Gag: Combining Physico-Chemistry and Population Genetics

2017 ◽  
Author(s):  
Elizabeth Johnson ◽  
Michael A. Gilchrist
Keyword(s):  
Population Genetics ◽  
Viral Escape ◽  
Chemical Model ◽  
Saturated Model ◽  
Escape Time ◽  
Entropy Model ◽  
Restricted Form ◽  
Physico Chemical

AbstractWe present physico-chemical based model grounded in population genetics. Our model predicts the stationary probability of observing an amino acid residue at a given site. Its predictions are based on the physico-chemical properties of the inferred optimal residue at that site and the sensitivity of the protein’s functionality to deviation from the physico-chemical optimum at that site. We contextualize our physico-chemical model by comparing our model fit and parameters it to the more general, but less biologically meaningful entropy based metric: site sensitivity or 1/E. We show mathematically that our physico-chemical model is a more restricted form of the entropy model and how 1/E is proportional to the log-likelihood of a parameter-wise ‘saturated’ model. Next, we fit both our physico-chemical and entropy models to sequences for subtype C’s Gag poly-protein in the LANL HIV database. Comparing our model’s site sensitivity parameters G′ to 1/E we find they are highly correlated. We also compare the ability of G′, 1/E, and other indirect measures of HIV fitness to empirical in vitro and in vivo measures. We find G′ does a slightly better job predicting empirical fitness measures of in vivo viral escape time and in vitro spreading rates. While our predictive gain is modest, our model can be modified to test more complex or alternative biological hypotheses. More generally, because of its explicit biological formulation, our model can be easily extended to test for stabilizing vs. diversifying selection. We conjecture that our model could also be extended include epistasis in a more realistic manner than Ising models, while requiring many fewer parameters than Potts models.

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