Divergence Behavior of Thermodynamic Curvature Scalar at Critical Point in the Extended Phase Space of Generic Black Holes

The $P$-$V$ phase transition and critical behavior in the extended phase space of asymptotic Anti-de Sitter (AdS) black holes have been widely investigated, in which four critical exponents around critical point are found to be consistent with values in the mean field theory. Recently, another critical exponent $\nu$ related to divergent correlation length at critical point is proposed by using thermodynamic curvature scalar $R_N$ in the charged AdS black hole. In this paper, we develop a method to investigate the divergent behavior of $R_N$ at critical point, and find that the divergent behavior of $R_N$ around the critical point expresses a universal property in generic black holes. We further directly apply this method to investigate black holes in de Rham-Gabadadze-Tolley (dRGT) massive gravity to check this universality. Those results shed new lights on the microscopic properties of black holes.Comment: 10 pages, no figure, version accepted by PL

First Principle Study of Gravitational Pressure and Thermodynamics of FRW Universe

We make a first principle study of gravitational pressure in cosmic thermodynamics. The pressure is directly derived from the unified first law, which is the first integral of Einstein field equation in spherically symmetric spacetime. By using this pressure, we obtain the thermodynamics for the FRW universe, especially presenting the gravitational equation of state for the FRW spacetime itself, i.e. $P=P(R_A, T)$ for the first time. Furthermore, we study the Joule-Thomson expansion as an application of the thermodynamic equation of state to find the cooling-heating property of the FRW universe. We demonstrate that there is an inversion temperature for a FRW universe, interestingly also corresponding to acceleration/deceleration transition, if its enthalpy ${\cal H}$ is negative. These investigations shed insights on the evolution of our universe in view of thermodynamics.Comment: Version added with interesting new results, discussions and an appendix, 12 pages and 2 figure

Interpreting Distributional Reinforcement Learning: A Regularization Perspective

Distributional reinforcement learning~(RL) is a class of state-of-the-art algorithms that estimate the whole distribution of the total return rather than only its expectation. Despite the remarkable performance of distributional RL, a theoretical understanding of its advantages over expectation-based RL remains elusive. In this paper, we attribute the superiority of distributional RL to its regularization effect in terms of the value distribution information regardless of its expectation. Firstly, by leverage of a variant of the gross error model in robust statistics, we decompose the value distribution into its expectation and the remaining distribution part. As such, the extra benefit of distributional RL compared with expectation-based RL is mainly interpreted as the impact of a \textit{risk-sensitive entropy regularization} within the Neural Fitted Z-Iteration framework. Meanwhile, we establish a bridge between the risk-sensitive entropy regularization of distributional RL and the vanilla entropy in maximum entropy RL, focusing specifically on actor-critic algorithms. It reveals that distributional RL induces a corrected reward function and thus promotes a risk-sensitive exploration against the intrinsic uncertainty of the environment. Finally, extensive experiments corroborate the role of the regularization effect of distributional RL and uncover mutual impacts of different entropy regularization. Our research paves a way towards better interpreting the efficacy of distributional RL algorithms, especially through the lens of regularization

Numerical simulation on the aerodynamic performance of the high-speed train under crosswinds

With the continuously increased speed of the high-speed train, the lateral aerodynamic performance of high-speed trains has attracted more and more attention. Under strong crosswinds, the aerodynamic performance of trains deteriorate and air drag, lift and lateral forces borne by trains quickly increase, which has an impact on the lateral stability of trains and even leads to train derailment. This paper adopted computational fluid dynamics theory to establish an aerodynamic model for a high-speed train, computed aerodynamic forces and moments acting on the high-speed train and obtained the unsteady flow field of the high-speed train. In the meanwhile, this paper combined with multi-body system dynamics theory to establish a system dynamics model for the train and analyzed the safe aerodynamic performance of the high-speed train under cross winds. Computational results showed: Under cross winds, the aerodynamic performance of the high-speed train had a random fluctuation. When wind direction angle was 90°, aerodynamic forces (drag, lift and lateral forces) and moments (overturning moment, shaking moment and nodding moment) borne by the high-speed train were the largest; train speed was a main factor affecting the size of positive pressures of train and cross wind velocity had no obvious impacts on the positive and negative pressures of train body; the aerodynamic forces and moments of the high-speed train had a random fluctuation within a certain range with time; the frequency for the peak value of power spectral density of lateral forces of head train was within 25 Hz and the peak value of power spectral density was the largest when the main frequency was 1.6 Hz; the frequency for the peak value of power spectral density of overturning moment of head train was within 20 Hz and main frequency was 0.57 Hz. When the cross wind speed was 15 m/s, all safety indexes of the high-speed train running at the speed of 250 km/h were within the range of limited values and satisfied design requirements. Aerodynamic performance of the high-speed train with the suction chamber under the cross wind was computed and compared with original results. Aerodynamic force and force moments of the high-speed train under cross wind will be reduced obviously and running safety of the high-speed train can be improved through application of the suction chamber

Novel norcantharidin-loaded liver targeting chitosan nanoparticles to enhance intestinal absorption

In this paper, two novel liver-targeting nanoparticles, norcantharidin-loaded chitosan nanoparticles (NCTD-CS-NPs) and norcantharidin-associated galactosylated chitosan nanoparticles (NCTD-GC-NPs), were prepared using ionic cross-linkage. The physical properties, particle size, encapsulation efficiency, and drug release characteristics of the nanoparticles were investigated in vitro. To investigate the intestinal absorption mechanisms of the two preparations, a series of experiments was carried out, including in situ circulation method, in vitro everted gut sacs, and Ussing chamber perfusion technique. The absorption rate constants (Ka) of NCTD at different segments were found to be duodenum > jejunum > ileum > colon. The concentration had no distinctive effect on absorption kinetics, suggesting that drug absorption is not dose-dependent. The transport of NCTD was found to be inhibited by P-glycoprotein (P-gp) inhibitor, indicating that NCTD might be the substrate of P-gp. The order of the absorption enhancer effects were as follows: low molecular weight chitosan (CS-8kDa) > high molecular weight chitosan (CS-30kDa) > Poloxamer > sodium dodecyl sulfate (SDS) > sodium deoxycholate (SDCh). The results indicate that the chitosan nanoparticles can improve intestinal absorption of NCTD

Universal screening for Lynch syndrome in a large consecutive cohort of Chinese colorectal cancer patients: High prevalence and unique molecular features

The prevalence of Lynch syndrome (LS) varies significantly in different populations, suggesting that ethnic features might play an important role. We enrolled 3330 consecutive Chinese patients who had surgical resection for newly diagnosed colorectal cancer. Universal screening for LS was implemented, including immunohistochemistry for mismatch repair (MMR) proteins, BRAFV600E mutation test and germline sequencing. Among the 3250 eligible patients, MMR protein deficiency (dMMR) was detected in 330 (10.2%) patients. Ninety‐three patients (2.9%) were diagnosed with LS. Nine (9.7%) patients with LS fulfilled Amsterdam criteria II and 76 (81.7%) met the revised Bethesda guidelines. Only 15 (9.7%) patients with absence of MLH1 on IHC had BRAFV600E mutation. One third (33/99) of the MMR gene mutations have not been reported previously. The age of onset indicates risk of LS in patients with dMMR tumors. For patients older than 65 years, only 2 patients (5.7%) fulfilling revised Bethesda guidelines were diagnosed with LS. Selective sequencing of all cases with dMMR diagnosed at or below age 65 years and only of those dMMR cases older than 65 years who fulfill revised Bethesda guidelines results in 8.2% fewer cases requiring germline testing without missing any LS diagnoses. While the prevalence of LS in Chinese patients is similar to that of Western populations, the spectrum of constitutional mutations and frequency of BRAFV600E mutation is different. Patients older than 65 years who do not meet the revised Bethesda guidelines have a low risk of LS, suggesting germline sequencing might not be necessary in this population

Non-Coding RNAs in Cardiac Aging

Aging has a remarkable impact on the function of the heart, and is independently associated with increased risk for cardiovascular diseases. Cardiac aging is an intrinsic physiological process that results in impaired cardiac function, along with lots of cellular and molecular changes. Non-coding RNAs include small transcripts, such as microRNAs and a wide range of long non-coding RNAs (lncRNAs). Emerging evidence has revealed that non-coding RNAs acted as powerful and dynamic modifiers of cardiac aging. This review aims to provide a general overview of non-coding RNAs implicated in cardiac aging, and the underlying mechanisms involved in maintaining homeo-stasis and retarding aging