1,213 research outputs found
Sensitivity analysis of wall-modeled large-eddy simulation for separated turbulent flow
In this study, we conduct a parametric analysis to evaluate the sensitivities
of wall-modeled large-eddy simulation (LES) with respect to subgrid-scale (SGS)
models, mesh resolution, wall boundary conditions and mesh anisotropy. While
such investigations have been conducted for attached/flat-plate flow
configurations, systematic studies specifically targeting turbulent flows with
separation are notably sparse. To bridge this gap, our study focuses on the
flow over a two-dimensional Gaussian-shaped bump at a moderately high Reynolds
number, which involves smooth-body separation of a turbulent boundary layer
under pressure-gradient and surface-curvature effects. In the simulations, the
no-slip condition at the wall is replaced by three different forms of boundary
condition based on the thin boundary layer equations and the mean wall-shear
stress from high-fidelity numerical simulation to avoid the additional
complexity of modeling the wall-shear stress. Various statistics, including the
mean separation bubble size, mean velocity profile, and eddy viscosity from SGS
model, are compared and analyzed. The results reveal that capturing the
separation bubble strongly depends on the choice of SGS model. While grid
convergence can be achieved at a resolution comparable to wall-resolved LES
mesh, above this limit, the LES predictions exhibit intricate sensitivities to
mesh resolution. Furthermore, both wall boundary conditions and the anisotropy
of mesh cells exert discernible impacts on the turbulent flow predictions, yet
the magnitudes of these impacts vary based on the specific SGS model chosen for
the simulation
Wall Modeling of Turbulent Flows with Various Pressure Gradients Using Multi-Agent Reinforcement Learning
We propose a framework for developing wall models for large-eddy simulation
that is able to capture pressure-gradient effects using multi-agent
reinforcement learning. Within this framework, the distributed reinforcement
learning agents receive off-wall environmental states including pressure
gradient and turbulence strain rate, ensuring adaptability to a wide range of
flows characterized by pressure-gradient effects and separations. Based on
these states, the agents determine an action to adjust the wall eddy viscosity,
and consequently the wall-shear stress. The model training is in-situ with
wall-modeled large-eddy simulation grid resolutions and does not rely on the
instantaneous velocity fields from high-fidelity simulations. Throughout the
training, the agents compute rewards from the relative error in the estimated
wall-shear stress, which allows the agents to refine an optimal control policy
that minimizes prediction errors. Employing this framework, wall models are
trained for two distinct subgrid-scale models using low-Reynolds-number flow
over periodic hills. These models are validated through simulations of flows
over periodic hills at higher Reynolds numbers and flow over the Boeing
Gaussian bump. The developed wall models successfully capture the acceleration
and deceleration of wall-bounded turbulent flows under pressure gradients and
outperform the equilibrium wall model in predicting skin friction.Comment: arXiv admin note: substantial text overlap with arXiv:2211.1642
Entangled two cavity modes preparation via a two-photon process
We propose a scheme for entangling two field modes in two high-Q optical
cavities. Making use of a virtual two-photon process, our scheme achieves
maximally entangled states without any real transitions of atomic internal
states, hence it is immune to the atomic decay.Comment: 4 pages, latex, 7 figure
Nostalgia as a psychological resource for people with dementia: A systematic review and meta-analysis of evidence of effectiveness from experimental studies
Objective: This review systematically examines evidence relating to the effect of nostalgia on psychological well-being through a meta-analysis of measures of social connectedness, self-esteem, meaning in life, self-continuity, optimism and positive and negative affect. Rationale: If nostalgia is to be used as a clinical intervention to boost well-being in dementia by reducing threat, then it is important to assess its therapeutic potential. Results: Searches carried out in July 2014 and updated in February 2018 identified 47 eligible experimental studies comparing nostalgic reminiscence and non-nostalgic reminiscence to be included in the meta-analysis. Nostalgic reminiscence had moderate effects on positive affect (0.51 (0.37, 0.65), p= 0.001), social connectedness (0.72 (0.57, 0.87), p= 0.001), self-esteem (0.50 (0.30, 0.70), p= 0.001), meaning in life (0.77 (0.47, 1.08), p= 0.001) and optimism (0.38 (0.28, 0.47), p= 0.001) and a large effect on self-continuity (0.81 (0.55, 1.07), p= 0.001). There was, however, no difference between the effect of nostalgic reminiscence and non-nostalgic reminiscence for negative affect (−0.06 (−0.20, 0.09), p= 0.443). Conclusion: This systematic review and meta-analysis provides an overview of the evidence base for nostalgia. This is an important stage in developing nostalgia as a clinical intervention for people with dementia which might be achieved, for instance, by adapting current reminiscence and life review techniques. This meta-analysis will therefore also serve as a valuable reference point for the continued exploration of nostalgia as an intervention
A p53-independent role for the MDM2 antagonist Nutlin-3 in DNA damage response initiation.
BACKGROUND: The mammalian DNA-damage response (DDR) has evolved to protect genome stability and maximize cell survival following DNA-damage. One of the key regulators of the DDR is p53, itself tightly regulated by MDM2. Following double-strand DNA breaks (DSBs), mediators including ATM are recruited to the site of DNA-damage. Subsequent phosphorylation of p53 by ATM and ATM-induced CHK2 results in p53 stabilization, ultimately intensifying transcription of p53-responsive genes involved in DNA repair, cell-cycle checkpoint control and apoptosis.
METHODS: In the current study, we investigated the stabilization and activation of p53 and associated DDR proteins in response to treatment of human colorectal cancer cells (HCT116p53+/+) with the MDM2 antagonist, Nutlin-3.
RESULTS: Using immunoblotting, Nutlin-3 was observed to stabilize p53, and activate p53 target proteins. Unexpectedly, Nutlin-3 also mediated phosphorylation of p53 at key DNA-damage-specific serine residues (Ser15, 20 and 37). Furthermore, Nutlin-3 induced activation of CHK2 and ATM - proteins required for DNA-damage-dependent phosphorylation and activation of p53, and the phosphorylation of BRCA1 and H2AX - proteins known to be activated specifically in response to DNA damage. Indeed, using immunofluorescent labeling, Nutlin-3 was seen to induce formation of γH2AX foci, an early hallmark of the DDR. Moreover, Nutlin-3 induced phosphorylation of key DDR proteins, initiated cell cycle arrest and led to formation of γH2AX foci in cells lacking p53, whilst γH2AX foci were also noted in MDM2-deficient cells.
CONCLUSION: To our knowledge, this is the first solid evidence showing a secondary role for Nutlin-3 as a DDR triggering agent, independent of p53 status, and unrelated to its role as an MDM2 antagonist
Why do authoritarian regimes provide public goods? Policy communities, external shocks and ideas in China’s rural social policy making
Recent research on authoritarian regimes argues that they provide public goods in order to prevent rebellion. This essay shows that the ‘threat of rebellion’ alone cannot explain Chinese party-state policies to extend public goods to rural residents in the first decade of the twenty-first century. Drawing on theories of policy making, it argues that China’s one-party regime extended public goods to the rural population under the influence of ideas and policy options generated by policy communities of officials, researchers, international organisations and other actors. The party-state centre adopted and implemented these ideas and policy options when they provided solutions to external shocks and supported economic development goals. Explanations of policies and their outcomes in authoritarian political systems need to include not only ‘dictators’ but also other actors, and the ideas they generate
Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms
Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms
Rare Decays of the
We have searched for the rare decays of the eta prime meson to e+ e- eta, e+
e- pizero, e+ e- gamma, and e mu in hadronic events at the CLEO II detector.
The search is conducted on 4.80 fb^-1 of e+ e- collisions at the Cornell
Electron Storage Ring. We find no signal in any of these modes, and set 90%
confidence level upper limits on their branching fractions of 2.4 X 10^-3, 1.4
X 10^-3, 0.9 X 10^-3, and 4.7 X 10^-4, respectively. We also investigate the
Dalitz plot of the common decay of the eta prime to pi+ pi- eta. We fit the
matrix element with the Particle Data Group parameterization and find Re(alpha)
= -0.021 +- 0.025, where alpha is a linear function of the kinetic energy of
the eta.Comment: 12 pages postscript, also available through
http://w4.lns.cornell.edu/public/CLN
The \u3cem\u3eChlamydomonas\u3c/em\u3e Genome Reveals the Evolution of Key Animal and Plant Functions
Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella
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