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SHEMAT-Suite: An open-source code for simulating flow, heat and species transport in porous media
(2020)
SHEMAT-Suite is a finite-difference open-source code for simulating coupled flow, heat and species transport in porous media. The code, written in Fortran-95, originates from geoscientific research in the fields of geothermics and hydrogeology. It comprises: (1) a versatile handling of input and output, (2) a modular framework for subsurface parameter modeling, (3) a multi-level OpenMP parallelization, (4) parameter estimation and data assimilation by stochastic approaches (Monte Carlo, Ensemble Kalman filter) and by deterministic Bayesian approaches based on automatic differentiation for calculating exact (truncation error-free) derivatives of the forward code.
Masked hypertension is known to induce microvascular complications. However, it is unclear whether early microvascular changes are already occurring in young, otherwise healthy adults. We therefore investigated whether retinal microvascular calibers and acute responses to a flicker stimulus are related to masked hypertension. We used the baseline data of 889 participants aged 20–30 years who were taking part in the African Prospective study on the Early Detection and Identification of Cardiovascular Disease and Hypertension. Clinic and 24-h ambulatory blood pressure were measured. The central retinal artery equivalent (CRAE) and central retinal vein equivalent were calculated from fundus images, and retinal vessel dilation was determined in response to flicker light-induced provocation. A smaller CRAE was observed in those with masked hypertension vs. those with normotension (157.1 vs. 161.2 measuring units, P < 0.001). In forward multivariable-adjusted regression analysis, only CRAE was negatively related to masked hypertension [adjusted R² = 0.267, β = −0.097 (95% CI = −0.165; −0.029), P = 0.005], but other retinal microvascular parameters were not associated with masked hypertension. In multivariable logistic regression analyses, masked hypertension [OR = 2.333, (95% CI = 1.316; 4.241), P = 0.004] was associated with a narrower CRAE. In young healthy adults, masked hypertension was associated with retinal arteriolar narrowing, thereby reflecting early microvascular alterations known to predict cardiovascular outcomes in later life.
To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.
There is a growing body of evidence for the effects of vitamin D on intestinal host-microbiome interactions related to gut dysbiosis and bowel inflammation. This brief review highlights the potential links between vitamin D and gut health, emphasizing the role of vitamin D in microbiological and immunological mechanisms of inflammatory bowel diseases. A comprehensive literature search was carried out in PubMed and Google Scholar using combinations of keywords “vitamin D,” “intestines,” “gut microflora,” “bowel inflammation”. Only articles published in English and related to the study topic are included in the review. We discuss how vitamin D (a) modulates intestinal microbiome function, (b) controls antimicrobial peptide expression, and (c) has a protective effect on epithelial barriers in the gut mucosa. Vitamin D and its nuclear receptor (VDR) regulate intestinal barrier integrity, and control innate and adaptive immunity in the gut. Metabolites from the gut microbiota may also regulate expression of VDR, while vitamin D may influence the gut microbiota and exert anti-inflammatory and immune-modulating effects. The underlying mechanism of vitamin D in the pathogenesis of bowel diseases is not fully understood, but maintaining an optimal vitamin D status appears to be beneficial for gut health. Future studies will shed light on the molecular mechanisms through which vitamin D and VDR interactions affect intestinal mucosal immunity, pathogen invasion, symbiont colonization, and antimicrobial peptide expression.
Innovative breeds of sugar cane yield up to 2.5 times as much organic matter as conventional breeds, resulting in a great potential for biogas production. The use of biogas production as a complementary solution to conventional and second-generation ethanol production in Brazil may increase the energy produced per hectare in the sugarcane sector. Herein, it was demonstrated that through ensiling, energy cane can be conserved for six months; the stored cane can then be fed into a continuous biogas process. This approach is necessary to achieve year-round biogas production at an industrial scale. Batch tests revealed specific biogas potentials between 400 and 600 LN/kgVS for both the ensiled and non-ensiled energy cane, and the specific biogas potential of a continuous biogas process fed with ensiled energy cane was in the same range. Peak biogas losses through ensiling of up to 27% after six months were observed. Finally, compared with second-generation ethanol production using energy cane, the results indicated that biogas production from energy cane may lead to higher energy yields per hectare, with an average energy yield of up to 162 MWh/ha. Finally, the Farm²CBG concept is introduced, showing an approach for decentralized biogas production.
Design, evaluation and comparison of endorectal coils for hybrid MR-PET imaging of the prostate
(2020)
Prostate cancer is one of the most common cancers among men and its early detection is critical for its successful treatment. The use of multimodal imaging, such as MR-PET, is most advantageous as it is able to provide detailed information about the prostate. However, as the human prostate is flexible and can move into different positions under external conditions, it is important to localise the focused region-of-interest using both MRI and PET under identical circumstances. In this work, we designed five commonly used linear and quadrature radiofrequency surface coils suitable for hybrid MR-PET use in endorectal applications. Due to the endorectal design and the shielded PET insert, the outer face of the coils investigated was curved and the region to be imaged was outside the volume of the coil. The tilting angles of the coils were varied with respect to the main magnetic field direction. This was done to approximate the various positions from which the prostate could be imaged. The transmit efficiencies and safety excitation efficiencies from simulations, together with the signal-to-noise ratios from the MR images were calculated and analysed. Overall, it was found that the overlapped loops driven in quadrature were superior to the other types of coils we tested. In order to determine the effect of the different coil designs on PET, transmission scans were carried out, and it was observed that the differences between attenuation maps with and without the coils were negligible. The findings of this work can provide useful guidance for the integration of such coil designs into MR-PET hybrid systems in the future.
Large scale central receiver systems typically deploy between thousands to more than a hundred thousand heliostats. During solar operation, each heliostat is aligned individually in such a way that the overall surface normal bisects the angle between the sun’s position and the aim point coordinate on the receiver. Due to various tracking error sources, achieving accurate alignment ≤1 mrad for all the heliostats with respect to the aim points on the receiver without a calibration system can be regarded as unrealistic. Therefore, a calibration system is necessary not only to improve the aiming accuracy for achieving desired flux distributions but also to reduce or eliminate spillage. An overview of current larger-scale central receiver systems (CRS), tracking error sources and the basic requirements of an ideal calibration system is presented. Leading up to the main topic, a description of general and specific terms on the topics heliostat calibration and tracking control clarifies the terminology used in this work. Various figures illustrate the signal flows along various typical components as well as the corresponding monitoring or measuring devices that indicate or measure along the signal (or effect) chain. The numerous calibration systems are described in detail and classified in groups. Two tables allow the juxtaposition of the calibration methods for a better comparison. In an assessment, the advantages and disadvantages of individual calibration methods are presented.
The application of atomic layer deposition in the production of sorbents for ⁹⁹Mo/⁹⁹ᵐTc generator
(2020)
New production routes for ⁹⁹Mo are steadily gaining importance. However, the obtained specific activity is much lower than currently produced by the fission of U-235. To be able to supply hospitals with ⁹⁹Mo/⁹⁹ᵐTc generators with the desired activity, the adsorption capacity of the column material should be increased. In this paper we have investigated whether the gas phase coating technique Atomic Layer Deposition (ALD), which can deposit ultra-thin layers on high surface area materials, can be used to attain materials with high adsorption capacity for ⁹⁹Mo. For this purpose, ALD was applied on a silica-core sorbent material to coat it with a thin layer of alumina. This sorbent material shows to have a maximum adsorption capacity of 120 mg/g and has a ⁹⁹ᵐTc elution efficiency of 55 ± 2% based on 3 executive elutions.
Extracellular acidification is a basic indicator for alterations in two vital metabolic pathways: glycolysis and cellular respiration. Measuring these alterations by monitoring extracellular acidification using cell-based biosensors such as LAPS plays an important role in studying these pathways whose disorders are associated with numerous diseases including cancer. However, the surface of the biosensors must be specially tailored to ensure high cell compatibility so that cells can represent more in vivo-like behavior, which is critical to gain more realistic in vitro results from the analyses, e.g., drug discovery experiments. In this work, O2 plasma patterning on the LAPS surface is studied to enhance surface features of the sensor chip, e.g., wettability and biofunctionality. The surface treated with O2 plasma for 30 s exhibits enhanced cytocompatibility for adherent CHO–K1 cells, which promotes cell spreading and proliferation. The plasma-modified LAPS chip is then integrated into a microfluidic system, which provides two identical channels to facilitate differential measurements of the extracellular acidification of CHO–K1 cells. To the best of our knowledge, it is the first time that extracellular acidification within microfluidic channels is quantitatively visualized as differential (bio-)chemical images.
Molecular Modeling Approach to the Prediction of Mechanical Properties of Silica-Reinforced Rubbers
(2014)
Recently, we have suggested a nanomechanical model for dissipative loss in filled elastomer networks in the context of the Payne effect. The mechanism is based on a total interfiller particle force exhibiting an intermittent loop, due to the combination of short-range repulsion and dispersion forces with a long-range elastic attraction. The sum of these forces leads, under external strain, to a spontaneous instability of “bonds” between the aggregates in a filler network and attendant energy dissipation. Here, we use molecular dynamics simulations to obtain chemically realistic forces between surface modified silica particles. The latter are combined with the above model to estimate the loss modulus and the low strain storage modulus in elastomers containing the aforementioned filler-compatibilizer systems. The model is compared to experimental dynamic moduli of silica filled rubbers. We find good agreement between the model predictions and the experiments as function of the compatibilizer's molecular structure and its bulk concentration.
Elastomers are exceptional materials owing to their ability to undergo large deformations before failure. However, due to their very low stiffness, they are not always suitable for industrial applications. Addition of filler particles provides reinforcing effects and thus enhances the material properties that render them more versatile for applications like tyres etc. However, deformation behavior of filled polymers is accompanied by several nonlinear effects like Mullins and Payne effect. To this day, the physical and chemical changes resulting in such nonlinear effect remain an active area of research. In this work, we develop a heterogeneous (or multiphase) constitutive model at the mesoscale explicitly considering filler particle aggregates, elastomeric matrix and their mechanical interaction through an approximate interface layer. The developed constitutive model is used to demonstrate cluster breakage, also, as one of the possible sources for Mullins effect observed in non-crystallizing filled elastomers.
Rubber materials filled with reinforcing fillers display nonlinear rheological behavior at small strain amplitudes below γ0 < 0.1. Nevertheless, rheological data are analyzed mostly in terms of linear parameters, such as shear moduli (G′, G″), which loose their physical meaning in the nonlinear regime. In this work styrene butadiene rubber filled with carbon black (CB) under large amplitude oscillatory shear (LAOS) is analyzed in terms of the nonlinear parameter I3/1. Three different CB grades are used and the filler load is varied between 0 and 70 phr. It is found that I3/1(φ) is most sensitive to changes of the total accessible filler surface area at low strain amplitudes (γ0 = 0.32). The addition of up to 70 phr CB leads to an increase of I3/1(φ) by a factor of more than ten. The influence of the measurement temperature on I3/1 is pronounced for CB levels above the percolation threshold.
We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed to be computationally effective at each scale. Density fluctuations in the melt structure above the tube scale are minimized through a Monte Carlo simulated annealing of a lattice polymer model. Subsequently the melt structure below the tube scale is equilibrated via the Rouse dynamics of a force-capped Kremer-Grest model that allows chains to partially interpenetrate. Finally the Kremer-Grest force field is introduced to freeze the topological state and enforce correct monomer packing. We generate 15 melts of 500 chains of 10.000 beads for varying chain stiffness as well as a number of melts with 1.000 chains of 15.000 monomers. To validate the equilibration process we study the time evolution of bulk, collective, and single-chain observables at the monomeric, mesoscopic, and macroscopic length scales. Extension of the present method to longer, branched, or polydisperse chains, and/or larger system sizes is straightforward.
The Kremer-Grest (KG) bead-spring model is a near standard in Molecular Dynamic simulations of generic polymer properties. It owes its popularity to its computational efficiency, rather than its ability to represent specific polymer species and conditions. Here we investigate how to adapt the model to match the universal properties of a wide range of chemical polymers species. For this purpose we vary a single parameter originally introduced by Faller and Müller-Plathe, the chain stiffness. Examples include polystyrene, polyethylene, polypropylene, cis-polyisoprene, polydimethylsiloxane, polyethyleneoxide and styrene-butadiene rubber. We do this by matching the number of Kuhn segments per chain and the number of Kuhn segments per cubic Kuhn volume for the polymer species and for the Kremer-Grest model. We also derive mapping relations for converting KG model units back to physical units, in particular we obtain the entanglement time for the KG model as function of stiffness allowing for a time mapping. To test these relations, we generate large equilibrated well entangled polymer melts, and measure the entanglement moduli using a static primitive-path analysis of the entangled melt structure as well as by simulations of step-strain deformation of the model melts. The obtained moduli for our model polymer melts are in good agreement with the experimentally expected moduli.
The Kremer–Grest (KG) polymer model is a standard model for studying generic polymer properties in molecular dynamics simulations. It owes its popularity to its simplicity and computational efficiency, rather than its ability to represent specific polymers species and conditions. Here we show that by tuning the chain stiffness it is possible to adapt the KG model to model melts of real polymers. In particular, we provide mapping relations from KG to SI units for a wide range of commodity polymers. The connection between the experimental and the KG melts is made at the Kuhn scale, i.e., at the crossover from the chemistry-specific small scale to the universal large scale behavior. We expect Kuhn scale-mapped KG models to faithfully represent universal properties dominated by the large scale conformational statistics and dynamics of flexible polymers. In particular, we observe very good agreement between entanglement moduli of our KG models and the experimental moduli of the target polymers.