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To evaluate the concentration and profile of fatty acids (FAs) among macrosomic neonates delivered by healthy pregnant women and pregnant women with type 1 diabetes mellitus (T1DM).

Laminar flow of ethylene glycol-based silicon nitride (EG-Si3N4) nanofluid in a smooth horizontal pipe subjected to forced heat convection with constant wall heat flux is computationally modeled and analyzed. Heat transfer is evaluated in terms of Nusselt number (Nu) and heat transfer coefficient for various volume fractions of Si3N4 nanoparticles in the base fluid and different laminar flow rates. The thermophysical properties of the EG-Si3N4 nanofluid are taken from a recently published experimental study. Computational modelling and simulation are performed using open-source software utilizing finite volume numerical methodology. The nanofluid exhibits non-Newtonian rheology and it is modelled as a homogeneous single-phase mixture, the properties of which are determined by the nanoparticle volume fraction. The existing features of the software to simulate single-phase flow are extended by implementing the energy transport coupled to the fluid flow and the interaction of the fluid flow with the surrounding pipe wall via the applied wall heat flux. In addition, the functional dependencies of the thermophysical properties of the nanofluid on the volume fraction of nanoparticles are implemented in the software, while the non-Newtonian rheological behavior of the nanofluid under consideration is also taken into account. The obtained results from the numerical simulations show very good predicting capabilities of the implemented computational model for the laminar flow coupled to the forced convection heat transfer. Moreover, the analysis of the computational results for the nanofluid reflects the increase of heat transfer of the EG-Si3N4 nanofluid in comparison to the EG for all the considered nanoparticle volume fractions and flow rates, indicating promising features of this nanofluid in heat transfer applications.

Context Type 1 diabetes mellitus (T1DM) is associated with a disturbance of carbohydrate and lipid metabolism. Objective To determine whether T1DM alters maternal and neonatal fatty acid (FA) levels. Design Observational study. Setting Academic hospital. Patients Sixty pregnant women (30 women with T1DM with good glycemic control and 30 healthy women) were included in the study. Maternal blood, umbilical vein, and artery blood samples were collected immediately upon delivery. Following lipid extraction, the FA profiles of the total FA pool of maternal serum and umbilical vein and artery serum were determined by gas chromatography. Results Total FA concentration in maternal serum did not differ between the study groups; it was significantly higher in umbilical vein serum of the T1DM group compared with that in the control group [median (interquartile range)]: T1DM 2126.2 (1446.4 to 3181.3) and control 1073.8 (657.5 to 2226.0; P < 0.001), and in umbilical artery vein serum: T1DM 1805.7 (1393.1 to 2125.0) and control 990.0 (643.3 to 1668.0; P < 0.001). Composition of FAs in umbilical vein serum showed significantly higher concentrations of saturated, monounsaturated, and polyunsaturated FAs (SFAs, MUFAs, and PUFAs, respectively) in the T1DM group than compared with those in the control group (P = 0.001). Furthermore, cord blood levels of leptin (P < 0.001), C-peptide (P < 0.001), and insulin resistance (P = 0.015) were higher in the T1DM group compared with controls. Conclusion The neonates born to mothers with T1DM had higher concentrations of total FAs, SFAs and MUFAs, as well as PUFAs, compared with control newborns.

The computational model for the simulation of freezing of supercooled water is presented. The model is based on the mesoscopic scale approach combining the analytical solution for the dendrite growth at small scales with the numerical solution for the temperature at larger scales. It utilizes the interface capturing methodology based on phase-field which is implemented in the open-source software OpenFOAM. The capability of the model is verified by computing cases of freezing of supercooled water at different initial supercoolings.