A reduced order variational multiscale approach for turbulent flows

The purpose of this work is to present different reduced order model strategies starting from full order simulations stabilized using a residual-based variational multiscale (VMS) approach. The focus is on flows with moderately high Reynolds numbers. The reduced order models (ROMs) presented in this manuscript are based on a POD-Galerkin approach. Two different reduced order models are presented, which differ on the stabilization used during the Galerkin projection. In the first case, the VMS stabilization method is used at both the full order and the reduced order levels. In the second case, the VMS stabilization is used only at the full order level, while the projection of the standard Navier-Stokes equations is performed instead at the reduced order level. The former method is denoted as consistent ROM, while the latter is named non-consistent ROM, in order to underline the different choices made at the two levels. Particular attention is also devoted to the role of inf-sup stabilization by means of supremizers in ROMs based on a VMS formulation. Finally, the developed methods are tested on a numerical benchmark. © 2019, Springer Science+Business Media, LLC, part of Springer Nature

Promotion of proliferation and metastasis of hepatocellular carcinoma by LncRNA00673 based on the targeted-regulation of notch signaling pathway

we read with great interest the paper by Dr. Chen et al1, recently published in European Review for Medical and Pharmacological Sciences and titled ‘‘Promotion of proliferation and metastasis of hepatocellular carcinoma by LncRNA00673 based on the targeted-regulation of notch signaling pathway’’. Authors concluded that lncRNA00673 is highly expressed and may be a potential target for the treatment of Hepatocellular Carcinoma (HCC). Moreover, according to authors, it can promote the proliferation and metastasis of HCC by the regulation of Notch signaling pathway. We congratulate the authors for their interesting work

Stress granules in Ciona robusta: molecular expression of tiar and ttp and early evidence of their gene expression under stress conditions induced by metals

Stress granules are non-membranous cytoplasmic foci composed of messengers (not translated), ribonucleoproteins, translation initiation components and other additional proteins, that represent a primary mechanism by which gene expression is rapidly modulated when cells are subjected to adverse environmental conditions. Very few works have been devoted to study the presence ofmolecular components of stress granules in invertebrate animals. In this work, we characterized, for the first time in the solitary ascidian Ciona robusta, the genetic sequences of two important protein components of stress granules, TIAR (TIA-1 related to proteins) and TTP (tristetraprolin), and carried out the first studies on their gene expression. The sequences characterized for tiar and ttp genes have allowed to start a study on the molecular evolution of these proteins in animals: for TIAR the obtained results are consistent with recent phylogenetic analysis that place tunicates as sister group of vertebrates, whereas the phylogenetic position of TTP remains still uncertain. The data on mRNA expression, provided by qRT-PCR analysis, are absolutely the first obtained in non-mammalian animals. As expected, the exposure to each metal (Cu, Zn and Cd) led to a generalized decrease in mRNA expression levels for both TIAR and TTP, suggesting that the metal accumulation induce acute stress and the inhibition of the transcription of tiar and ttp genes. The data presented here improved our knowledge about the molecular evolution anti-stress proteins in metazoans and emphasize the importance of the transcription of tiar and ttp genes, which represents an efficient physiological response allowing C. robusta to survive in the presence of metals in the marine environment (Supported by M.I.U.R. grant)

Projection-based reduced order models for a cut finite element method in parametrized domains

This work presents a reduced order modeling technique built on a high fidelity embedded mesh finite element method. Such methods, and in particular the CutFEM method, are attractive in the generation of projection-based reduced order models thanks to their capabilities to seamlessly handle large deformations of parametrized domains and in general to handle topological changes. The combination of embedded methods and reduced order models allows us to obtain fast evaluation of parametrized problems, avoiding remeshing as well as the reference domain formulation, often used in the reduced order modeling for boundary fitted finite element formulations. The resulting novel methodology is presented on linear elliptic and Stokes problems, together with several test cases to assess its capability. The role of a proper extension and transport of embedded solutions to a common background is analyzed in detail. \ua9 2019 Elsevier Lt

Basic ideas and tools for projection-based model reduction of parametric partial differential equations

We provide first the functional analysis background required for reduced order modeling and present the underlying concepts of reduced basis model reduction. The projection-based model reduction framework under affinity assumptions, offline-online decomposition and error estimation is introduced. Several tools for geometry parametrizations, such as free form deformation, radial basis function interpolation and inverse distance weighting interpolation are explained. The empirical interpolation method is introduced as a general tool to deal with non-affine parameter dependency and non-linear problems. The discrete and matrix versions of the empirical interpolation are considered as well. Active subspaces properties are discussed to reduce high-dimensional parameter spaces as a pre-processing step. Several examples illustrate the methodologies

Advances in geometrical parametrization and reduced order models and methods for computational fluid dynamics problems in applied sciences and engineering: Overview and perspectives

Several problems in applied sciences and engineering require reduction techniques in order to allow computational tools to be employed in the daily practice, especially in iterative procedures such as optimization or sensitivity analysis. Reduced order methods need to face increasingly complex problems in computational mechanics, especially into a multiphysics setting. Several issues should be faced: stability of the approximation, efficient treatment of nonlinearities, uniqueness or possible bifurcations of the state solutions, proper coupling between fields, as well as offline-online computing, computational savings and certification of errors as measure of accuracy. Moreover, efficient geometrical parametrization techniques should be devised to efficiently face shape optimization problems, as well as shape reconstruction and shape assimilation problems. A related aspect deals with the management of parametrized interfaces in multiphysics problems, such as fluid-structure interaction problems, and also a domain decomposition based approach for complex parametrized networks. We present some illustrative industrial and biomedical problems as examples of recent advances on methodological developments

Rapamycin and HIV Replication in Liver Transplant Recipients

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Semi-continuous Chlorella vulgaris Cultivation Using Anaerobic Digestate Liquid Fraction Pre-treated by Ultrasonic Cavitation to Improve Carbon Dioxide Solubilization

Nutrients-enriched effluents such as digestate can represent a suitable and economically appealing substrate for microalgae growth since they combine the effluent treatment with biomass production. Then, microalgae biomass can be exploited to produce several bio-based compounds. However, the use of digestate for microalgae cultivation can be challenging due to its high levels of ammonia nitrogen and its low C/N ratio. For this reason, an ultrasonic cavitation (UC) process combined with carbon dioxide (CO2) insufflation was tested on digestate, in order to obtain a faster solubilization of the CO2 in the medium and thus an increase in the C/N ratio. The test was carried out growing Chlorella vulgaris on both digestate (mixotrophic condition) and BG-11 medium (autotrophic condition) in 1 L photobioreactors. For the first 14 days of the experiment the reactors were maintained in batch conditions to acclimatize microalgae. Then, they were switched to semi-continuous for 32 days. The reactors were fed three times a week, with an HRT (Hydraulic Retention Time) of 10.5 d as weekly average. Regarding the test on digestate, both UC pre-treated and untreated conditions reached the highest biomass production at the end of the batch (4.8 and 4.1 g L-1 respectively) and a complete ammonium (NH4+) removal after 9 days. The switch to semi-continuous caused an increase in NH4+ concentration and a consistent decrease in biomass concentration. Biomass production reached the steady-state, with a concentration of 1.9 and 1.2 g L-1 for the UC pre-treated and untreated digestate, respectively (+55.6 % biomass production obtained with UC pre-treated digestate). Moreover, an NH4+ removal of 93.5 % and 92.3 % was reached for UC pre-treated and untreated conditions, respectively