Are absorbable sutures inadequate to close the sternum?

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On the Role of Gas Cooling in the Dynamics of Circumbinary Disks

Hydrodynamical interactions between binaries and circumbinary disks (CBDs) play an important role in a variety of astrophysical systems, from young stellar binaries to supermassive black hole binaries. Previous simulations of CBDs have mostly employed locally isothermal equation of state. We carry out two-dimensional viscous hydrodynamic simulations of CBDs around equal-mass, circular binaries, treating the gas thermodynamics by thermal relaxation towards equilibrium temperature (the constant-$\beta$ cooling ansatz, where $\beta$ is the cooling time in units of the local Keplerian time). As an initial study, we use the grid-based code Athena++ on a polar grid, covering an extended disk outside the binary co-orbital region. We find that with a longer cooling time, the accretion variability is gradually suppressed, and the morphology of the CBD becomes more symmetric. The disk also shows evidence of hysterisis behavior depending on the initial conditions. Gas cooling also affects the rate of angular momentum transfer between the binary and the CBD, where given our adopted disk thickness and viscosity ($H/r\sim 0.1$ and $\alpha\sim 0.1$), the binary orbit expands while undergoing accretion for most $\beta$ values between 0 and 4.0 except over a narrow range of intermediate $\beta$ values. The validity of using polar grid excising the central domain is also discussed.Comment: 14 pages, 12 figures, resubmitted to AP

2,2′-(Piperazine-1,4-di­yl)diacetonitrile

The complete mol­ecule of the title compound, C8H12N4, is generated by a crystallographic inversion centre. The piperazine ring adopts a chair conformation with the N-bonded substituents in equatorial positions. In the crystal, mol­ecules are linked by C—H⋯Nc (c = cyanide) hydrogen bonds

Investigation of methane adsorption mechanism on Longmaxi shale by combining the micropore filling and monolayer coverage theories

Understanding the methane adsorption mechanism is critical for studying shale gas storage and transport in shale nanopores. In this work, we conducted low-pressure nitrogen adsorption (LPNA), scanning electron microscopy (SEM), and high-pressure methane adsorption experiments on seven shale samples from the Longmaxi formation in Sichuan basin. LPNA and SEM results show that pores in the shale samples are mainly nanometer-sized and have a broad size distribution. We have also shown that methane should be not only adsorbed in micropores (< 2 nm) but also in mesopores (2-50 nm) by two hypotheses. Therefore, we established a novel DA-LF model by combining the micropore filling and monolayer coverage theories to describe the methane adsorption process in shale. This new model can fit the high-pressure isotherms quite well, and the fitting error of this new model is slightly smaller than the commonly used D-A and L-F models. The absolute adsorption isotherms and the capacities for micropores and mesopores can be calculated using this new model separately, showing that 77% to 97% of methane molecules are adsorbed in micropores. In addition, we conclude that the methane adsorption mechanism in shale is: the majority of methane molecules are filled in micropores, and the remainder are monolayer-adsorbed in mesopores. It is anticipated that our results provide a more accurate explanation of the shale gas adsorption mechanism in shale formations.Cited as: Zhou, S., Ning, Y., Wang, H., Liu, H., Xue, H. Investigation of methane adsorption mechanism on Longmaxi shale by combining the micropore filling and monolayer coverage theories. Advances in Geo-Energy Research, 2018, 2(3): 269-281, doi: 10.26804/ager.2018.03.0

Autophagy protects against palmitate-induced apoptosis in hepatocytes

BACKGROUND: Non-alcoholic fatty liver disease, one of the most common liver diseases, has obtained increasing attention. Palmitate (PA)-induced liver injury is considered a risk factor for the development of non-alcoholic fatty liver disease. Autophagy, a cellular degradative pathway, is an important self-defense mechanism in response to various stresses. In this study, we investigated whether autophagy plays a protective role in the progression of PA-induced hepatocytes injury. RESULTS: Annexin V-FITC/PI staining by FCM analysis, TUNEL assay and the detection of PARP and cleaved caspase3 expression levels demonstrated that PA treatment prominently induced the apoptosis of hepatocytes. Meanwhile, treatment of PA strongly induced the formation of GFP-LC3 dots, the conversion from LC3I to LC3II, the decrease of p62 protein levels and the increase of autophagosomes. These results indicated that PA also induced autophagy activation. Autophagy inhibition through chloroquine pretreatment or Atg5shRNA infection led to the increase of cell apoptosis after PA treatment. Moreover, induction of autophagy by pretreatment with rapamycin resulted in distinct decrease of PA-induced apoptosis. Therefore, autophagy can prevent hepatocytes from PA-induced apoptosis. In the further study, we explored pathway of autophagy activation in PA-treated hepatocytes. We found that PA activated PKCα in hepatocytes, and had no influence on mammalian target of rapamycin and endoplasmic reticulum stress pathways. CONCLUSIONS: These results demonstrated that autophagy plays a protective role in PA-induced hepatocytes apoptosis. And PA might induce autophagy through activating PKCα pathway in hepatocytes

Cardinality and Bounding Constrained Portfolio Optimization Using Safe Reinforcement Learning

Portfolio optimization is a strategic approach aiming at achieving an optimal balance between risk and returns through the judicious allocation of limited capital across various assets. In recent years, there has been a growing interest in leveraging Deep Reinforcement Learning (DRL) to tackle the complexities of portfolio optimization. Despite its potential, a notable limitation of DRL algorithms is their inherent difficulty in integrating conflicted objectives with the reward functions throughout the learning process. Typically, DRL's reward function prioritizes the maximization of returns or other performance indicators, often overlooking the integration of risk aspects. Furthermore, the standard DRL framework struggles to incorporate practical constraints, such as cardinality and bounding, into the decision process. Without these constraints, the investment strategies developed might be unrealistic and unmanageable. To this end, in this paper, we propose an adaptive and safe DRL framework, which can dynamically optimize the portfolio weights while strictly respecting practical constraints. In our method, any infeasible action (i.e., one that violates the constraints) decided by the RL agent will be mapped to a feasible region using a safety layer. The extended Markowitz Mean-Variance (M-V) model is explicitly encoded in the safety layer to ensure the feasibility of the actions from the alternative views. In addition, we utilize Projection-based Interior-point Policy Optimization (IPO) to resolve multiple objectives and constraints in the examined problem. Extensive results on real-world datasets show that our method is effective in strictly respecting constraints under dynamic market environments, in contrast to prevailing data- driven trading strategies and conventional model-based static solutions

Research progress on the relationship between axonal transport dysfunction in neuronal cells and Alzheimer’s disease

Alzheimer’s disease is known as one of the “top ten killers in the world”. Due to lack of effective therapy at present， early pathological changes have captivated widespread attention. Axonal transport dysfunction has been reported as an early pathological feature of many neurodegenerative diseases. However， multiple factors can cause axonal transport dysfunction. In this article， the relationship between axonal transport dysfunction caused by kinesins， microtubules and mitochondria and Alzheimer’s disease was discussed， aiming to provide new ideas for the prevention and treatment of Alzheimer’s disease by in-depth study on axonal transport mechanism of neure

A Sialidase‐Deficient Porphyromonas gingivalis Mutant Strain Induces Less Interleukin‐1β and Tumor Necrosis Factor‐α in Epi4 Cells Than W83 Strain Through Regulation of c‐Jun N‐Terminal Kinase Pathway

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142178/1/jpere129.pd