A generalized bayesian inference method for constraining the interiors of super Earths and sub-Neptunes

We aim to present a generalized Bayesian inference method for constraining interiors of super Earths and sub-Neptunes. Our methodology succeeds in quantifying the degeneracy and correlation of structural parameters for high dimensional parameter spaces. Specifically, we identify what constraints can be placed on composition and thickness of core, mantle, ice, ocean, and atmospheric layers given observations of mass, radius, and bulk refractory abundance constraints (Fe, Mg, Si) from observations of the host star's photospheric composition. We employed a full probabilistic Bayesian inference analysis that formally accounts for observational and model uncertainties. Using a Markov chain Monte Carlo technique, we computed joint and marginal posterior probability distributions for all structural parameters of interest. We included state-of-the-art structural models based on self-consistent thermodynamics of core, mantle, high-pressure ice, and liquid water. Furthermore, we tested and compared two different atmospheric models that are tailored for modeling thick and thin atmospheres, respectively. First, we validate our method against Neptune. Second, we apply it to synthetic exoplanets of fixed mass and determine the effect on interior structure and composition when (1) radius, (2) atmospheric model, (3) data uncertainties, (4) semi-major axes, (5) atmospheric composition (i.e., a priori assumption of enriched envelopes versus pure H/He envelopes), and (6) prior distributions are varied. Our main conclusions are: [...]Comment: Astronomy & Astrophysics, 597, A37, 17 pages, 11 figure

MicroRNA-23a promotes myelination in the central nervous system.

Demyelinating disorders including leukodystrophies are devastating conditions that are still in need of better understanding, and both oligodendrocyte differentiation and myelin synthesis pathways are potential avenues for developing treatment. Overexpression of lamin B1 leads to leukodystrophy characterized by demyelination of the central nervous system, and microRNA-23 (miR-23) was found to suppress lamin B1 and enhance oligodendrocyte differentiation in vitro. Here, we demonstrated that miR-23a-overexpressing mice have increased myelin thickness, providing in vivo evidence that miR-23a enhances both oligodendrocyte differentiation and myelin synthesis. Using this mouse model, we explored possible miR-23a targets and revealed that the phosphatase and tensin homologue/phosphatidylinositol trisphosphate kinase/Akt/mammalian target of rapamycin pathway is modulated by miR-23a. Additionally, a long noncoding RNA, 2700046G09Rik, was identified as a miR-23a target and modulates phosphatase and tensin homologue itself in a miR-23a-dependent manner. The data presented here imply a unique role for miR-23a in the coordination of proteins and noncoding RNAs in generating and maintaining healthy myelin

Generalized thermo vacuum state derived by the partial trace method

By virtue of the technique of integration within an ordered product (IWOP) of operators we present a new approach for deriving generalized thermo vacuum state which is simpler in form that the result by using the Umezawa-Takahashi approach, in this way the thermo field dynamics can be developed. Applications of the new state are discussed.Comment: 5 pages, no figure, revtex

Strong decays of heavy baryons in Bethe-Salpeter formalism

In this paper we study the properties of diquarks (composed of $u$ and/or $d$ quarks) in the Bethe-Salpeter formalism under the covariant instantaneous approximation. We calculate their BS wave functions and study their effective interaction with the pion. Using the effective coupling constant among the diquarks and the pion, in the heavy quark limit $m_Q\to\infty$, we calculate the decay widths of $\Sigma_Q^{(*)}$ ($Q=c,b$) in the BS formalism under the covariant instantaneous approximation and then give predictions of the decay widths $\Gamma(\Sigma_b^{(*)}\to\Lambda_b+\pi)$.Comment: 41 pages, 1 figure, LaTex2e, typos correcte

Digital twin for intelligent maintenance towards sustainable bridges

Aging steel bridges constitute a significant portion of transportation infrastructure, requiring more efficient and intelligent maintenance to enhance their sustainability. This work presents a digital twin (DT) framework for the intelligent maintenance of aging steel bridges subject to time-dependent deterioration, by fully exploiting the prediction model and the data from monitoring and inspection. A tied-arch bridge, subjected to prominent corrosion fatigue (CF) in its hanger system, is selected as a case study. The DT framework comprises three modules: digital data perception, deterioration prognosis, and condition-based decision making. First, a finite element (FE) model of the bridge is developed as the mechanical backbone of the DT, based on the design document and updated with the latest inspection result. Then, the traffic data collected by the structural health monitoring (SHM) system are converted into fatigue stress spectra. Next, the stress spectra and site-specific environmental data are integrated to perform a hybrid deterioration prognosis using a time-variant probability-stress-life model. Finally, optimal maintenance actions are determined based on the prognosis results, by constructing a stochastic environment and adopting a customized deep learning-based solution algorithm. The research outcome demonstrates the value of incorporating SHM data in deterioration prognosis and maintenance planning, and provides a promising framework for the interoperable DT of aging structures at the mechanistic level. The result reveals the nonlinear evolution of C-F deterioration in steel bridge hangers, with increasing failure probability and dispersity. Consequently, different strategies are recommended by the proposed DT framework, such as regular repairs in the early life and frequent inspections and timely replacement in the late life. Furthermore, the present DT framework suggests that the appropriate use of SHM systems can effectively reduce the life-cycle costs and risks, with a value of information that exceeds the initial investment

Coupled KdV equations derived from atmospherical dynamics

Some types of coupled Korteweg de-Vries (KdV) equations are derived from an atmospheric dynamical system. In the derivation procedure, an unreasonable $y$-average trick (which is usually adopted in literature) is removed. The derived models are classified via Painlev\'e test. Three types of $\tau$-function solutions and multiple soliton solutions of the models are explicitly given by means of the exact solutions of the usual KdV equation. It is also interesting that for a non-Painlev\'e integrable coupled KdV system there may be multiple soliton solutions.Comment: 19 pages, 2 figure

The Dynamical Yang-Baxter Relation and the Minimal Representation of the Elliptic Quantum Group

In this paper, we give the general forms of the minimal $L$ matrix (the elements of the $L$-matrix are $c$ numbers) associated with the Boltzmann weights of the $A_{n-1}^1$ interaction-round-a-face (IRF) model and the minimal representation of the $A_{n-1}$ series elliptic quantum group given by Felder and Varchenko. The explicit dependence of elements of $L$-matrices on spectral parameter $z$ are given. They are of five different forms (A(1-4) and B). The algebra for the coefficients (which do not depend on $z$) are given. The algebra of form A is proved to be trivial, while that of form B obey Yang-Baxter equation (YBE). We also give the PBW base and the centers for the algebra of form B.Comment: 23 page