An experimentally-validated framework for interpreting active-DTS measurements conducted in fully saturated porous media

<p>            Our ability to characterize aquifers, predict contaminant transport and understand biogeochemical reactions occurring in the subsurface directly depends on our ability of characterizing the distribution of groundwater flow. In this context, recently-developed active-Distributed Temperature Sensing (DTS) experiments are particularly promising, offering the possibility to characterize groundwater flows resulting from heterogeneous flow fields. Here, based on theoretical developments and numerical simulations, we propose a general framework for estimating active-DTS measurements, which can be easily applied and takes into account the spatial distribution of the thermal conductivities of sediments.</p><p>            Two independent methods for interpreting active-DTS experiments are proposed to estimate both the porous media thermal conductivities and the groundwater fluxes in sediments. These methods rely on the interpretation of the temperature increase measured along a single heated fiber optic (FO) cable and consider heat transfer processes occurring both through the FO cable itself and through the porous media. In order to validate these interpretation methods with independent experimental data, active-DTS measurements were collected under different flow-conditions during laboratory tests in a sandbox. First, the combination of a numerical model with laboratory experiments allowed improving the understanding of the thermal processes controlling the temperature increase. Then, the two complementary and independent interpretation methods providing an estimate of both the thermal conductivity and the groundwater flux were fully validated and the excellent accuracy of groundwater flux estimates (< 5%) was demonstrated.</p><p>            Our results suggest that active-DTS experiments allow investigating groundwater fluxes over a large range spanning 1x10<sup>-6</sup> to 5x10<sup>-2</sup> m/s, depending on the duration of the experiment. The active-DTS method could thus be potentially applied to a very wide range of flow systems since groundwater fluxes can be investigated over more than three orders of magnitude. In the field, the reliable and direct estimation of the distribution of fluxes could replace the measurement of hydraulic conductivity, whose distribution and variability still remains difficult and time consuming to evaluate.</p>

The control of acidity in tumor cells: a biophysical model

ABSTRACTAcidosis of the tumor microenvironment leads to cancer invasion, progression and resistance to therapies. We present a biophysical model that describes how tumor cells regulate intracellular and extracellular acidity while they grow in a microenvironment characterized by increasing acidity and hypoxia. The model takes into account the dynamic interplay between glucose and O2 consumption with lactate and CO2 production and connects these processes to H+ and fluxes inside and outside cells. We have validated the model with independent experimental data and used it to investigate how and to which extent tumor cells can survive in adverse micro-environments characterized by acidity and hypoxia. The simulations show a dominance of the H+ exchanges in well-oxygenated regions, and of exchanges in the inner hypoxic regions where tumor cells are known to acquire malignant phenotypes. The model also includes the activity of the enzyme Carbonic Anhydrase 9 (CA9), a known marker of tumor aggressiveness, and the simulations demonstrate that CA9 acts as a nonlinear pHi equalizer at any O2 level in cells that grow in acidic extracellular environments.SIGNIFICANCEThe activity of cancer cells in solid tumors affects the surrounding environment in many ways, and an elevated acidity is a common feature of the tumor microenvironment. In this paper we propose a model of intracellular/extracellular acidity that is linked to cellular metabolism and includes all the main molecular players. The model is reliable, robust and validated with experimental data and can be used as an essential building block of more comprehensive in silico research on solid tumors.

Determination of Protein Structural Ensembles by Hybrid-Resolution SAXS Restrained Molecular Dynamics.

<div><div><div><p>SAXS experiments provide low-resolution but valuable information about the dynamics of biomolecular systems, which could be ideally integrated into MD simulations to accurately determine conformational ensembles of flexible proteins. The applicability of this strategy is hampered by the high computational cost required to calculate scattering intensities from three-dimensional structures. We previously presented a hybrid resolution method that makes atomistic SAXS-restrained MD simulation feasible by adopting a coarse-grained approach to efficiently back-calculate scattering intensities; here, we extend this technique, applying it in the framework of metainference with the aim to investigate the dynamical behavior of flexible biomolecules. The efficacy of the method is assessed on the K63-diubiquitin, showing that the inclusion of SAXS-restraints is effective in generating a reliable conformational ensemble, improving the agreement with independent experimental data.</p></div></div></div>

Determination of Protein Structural Ensembles by Hybrid-Resolution SAXS Restrained Molecular Dynamics.

<div><div><div><p>SAXS experiments provide low-resolution but valuable information about the dynamics of biomolecular systems, which could be ideally integrated into MD simulations to accurately determine conformational ensembles of flexible proteins. The applicability of this strategy is hampered by the high computational cost required to calculate scattering intensities from three-dimensional structures. We previously presented a hybrid resolution method that makes atomistic SAXS-restrained MD simulation feasible by adopting a coarse-grained approach to efficiently back-calculate scattering intensities; here, we extend this technique, applying it in the framework of metainference with the aim to investigate the dynamical behavior of flexible biomolecules. The efficacy of the method is assessed on the K63-diubiquitin, showing that the inclusion of SAXS-restraints is effective in generating a reliable conformational ensemble, improving the agreement with independent experimental data.</p></div></div></div>

Kinetic Parameter Estimation and Mathematical Modelling of Lipase Catalysed Biodiesel Synthesis in a Microreactor

Development of green, clean, and sustainable processes presents new challenges in today’s science. Production of fuel is no exception. Considering the utilisation of various renewable sources, the synthesis of biodiesel, characterised as more environmentally-friendly then fossil fuel, has drawn significant attention. Even though the process based on chemical transesterification in a batch reactor still presents the most used method for its production, enzyme catalysed synthesis of biodiesel in a microreactor could be a new approach for going green. In this research, edible sunflower oil and methanol were used as substrates and lipase from Thermomyces lanuginosus (Lipolase L100) was used as catalyst for biodiesel synthesis. Experiments were performed in a polytetrafluoroethylene (PTFE) microreactor with three inlets and in glass microreactors with two and three inlets. For a residence time of 32 min, the fatty acids methyl esters (FAME) yield was 30% higher than the yield obtained for the glass microreactor with three inlets. In comparison, when the reaction was performed in a batch reactor (V = 500 mL), the same FAME yield was achieved after 1.5 h. In order to enhance the productivity of the process, we used proposed reaction kinetics, estimated kinetic parameters, and a mathematical model we developed. After validation using independent experimental data, a proposed model was used for process optimization in order to obtain the highest FAME yield for the shortest residence time.

Determination of Protein Structural Ensembles by Hybrid-Resolution SAXS Restrained Molecular Dynamics.

<div><div><div><p>SAXS experiments provide low-resolution but valuable information about the dynamics of biomolecular systems, which could be ideally integrated in MD simulations to accurately determine conformational ensembles of flexible proteins. The applicability of this strategy is hampered by the high computational cost required to calculate scattering intensities from three-dimensional structures. We previously presented a metainference-based hybrid resolution method that makes atomistic SAXS-restrained MD simulation feasible by adopting a coarse-grained approach to efficiently back-calculate scattering intensities; here, we extend this technique, applying it in the framework of multiple-replica simulations with the aim to investigate the dynamical behavior of flexible biomolecules. The efficacy of the method is assessed on the K63-diubiquitin multi-domain protein, showing that inclusion of SAXS-restraints is effective in generating reliable and heterogenous conformational ensemble, also improving the agreement with independent experimental data.</p></div></div></div>

Continuous phenomenological modeling for the viscosity of shear thickening fluids

In general, shear thickening fluids show a marked increase in viscosity beyond a critical shear rate, which can be attributed to the hydrodynamic clustering effects, where in any external energy acting on a shear thickening fluid is dissipated quickly. However, there is a lack of theoretical modeling to predict the viscosity curve of shear thickening fluids, which changes continuously with the increasing shear rate. In this article, a phenomenological continuous viscosity modeling for a class of shear thickening fluids is proposed. The modeling predicts shear thickening and thinning behaviors that are naturally exhibited by shear thickening fluids for high and high enough values of the shear rate. The result shows that the phenomenological modeling provides a very good fit for several independent experimental data sets. Therefore, the proposed modeling can be used in numerical simulations and theoretical analysis across different engineering fields.

The Structure and Thermal Conductivity of Multicomponent Polymer Composites Filled with Hollow Ceramic and Silicone Microspheres

The structure of polymer composites has been investigated, and a procedure has been developed for calculating their effective thermal conductivity. Thermal conductivity measurements have been carried out, and the results of calculations have been compared with the authors' own experimental data and with independent experimental data, and also with manufacturers' data which are shown to be hundreds of percent too low.

Development of Predictive Techniques for Estimating Liquid Water-Hydrate Equilibrium of Water-Hydrocarbon System

In this communication, we review recent studies by these authors for modeling the -H equilibrium. With the aim of estimating the solubility of pure hydrocarbon hydrate former in pure water in equilibrium with gas hydrates, a thermodynamic model is introduced based on equality of water fugacity in the liquid water and hydrate phases. The solid solution theory of Van der Waals-Platteeuw is employed for calculating the fugacity of water in the hydrate phase. The Henry's law approach and the activity coefficient method are used to calculate the fugacities of the hydrocarbon hydrate former and water in the liquid water phase, respectively. The results of this model are successfully compared with some selected experimental data from the literature. A mathematical model based on feed-forward artificial neural network algorithm is then introduced to estimate the solubility of pure hydrocarbon hydrate former in pure water being in equilibrium with gas hydrates. Independent experimental data (not employed in training and testing steps) are used to examine the reliability of this algorithm successfully.