Very metal-poor (VMP, [Fe/H]<-2.0) stars serve as invaluable repositories of insights into the nature and evolution of the first-generation stars formed in the early galaxy. The upcoming China Space Station Telescope (CSST) will provide us with a large amount of spectral data that may contain plenty of VMP stars, and thus it is crucial to determine the stellar atmospheric parameters (Teff , log g, and [Fe/H]) for low-resolution spectra similar to the CSST spectra (R ∼ 200). This study introduces a novel two-dimensional Convolutional Neural Network (CNN) model, comprised of three convolutional layers and two fully connected layers. The model’s proficiency is assessed in estimating stellar parameters, particularly metallicity, from low-resolution spectra (R ∼ 200), with a specific focus on enhancing the search for VMP stars within the CSST spectral data. We mainly use 10,008 spectra of VMP stars from LAMOST DR3, and 16,638 spectra of non-VMP stars ([Fe/H]>-2.0) from LAMOST DR8 for the experiments and apply random forest and support vector machine methods to make comparisons. The resolution of all spectra is reduced to R ∼ 200 to match the resolution of the CSST, followed by preprocessing and transformation into two-dimensional spectra for input into the CNN model. The validation and practicality of this model are also tested on the MARCS synthetic spectra. The results show that using the CNN model constructed in this paper, we obtain Mean Absolute Error (MAE) values of 99.40 K for Teff , 0.22 dex for log g, 0.14 dex for [Fe/H], and 0.26 dex for [C/Fe] on the test set. Besides, the CNN model can efficiently identify VMP stars with a precision rate of 94.77%, a recall rate of 93.73%, and an accuracy of 95.70%. This paper powerfully demonstrates the effectiveness of the proposed CNN model in estimating stellar parameters for low-resolution spectra (R ∼ 200) and recognizing VMP stars that are of interest for stellar population and galactic evolution work.

A typical feature of thermal convection is the formation of large-scale flow (LSF) structures of the order of system size. How this structure affects global heat transport is an important issue in the study of thermal convection. We present an experimental study of the coupling between the flow structure and heat transport in liquid metal convection with different degrees of spatial confinement, characterized by the aspect ratio $\varGamma$ of the convection cell. Combining measurements in two convection cells with $\varGamma =1.0$ and 0.5, the study shows that a large-scale circulation (LSC) transports ${\sim }35\,\%$ more heat than a twisted LSC. It is further found that when the LSF is in the form of the LSC state, the system is in a fully developed turbulence state with a $Nu\sim Ra^{0.29}$ scaling for the heat transport. However, the twisted LSC state with a heat transport scaling of $Nu\sim Ra^{0.37}$ appears when the system is not in the fully developed turbulence state. Bistability is observed when the system evolves from the twisted-LSC-dominated to the LSC-dominated state.

We show that for any $\varepsilon \gt 0$ and $\Delta \in \mathbb{N}$, there exists $\alpha \gt 0$ such that for sufficiently large $n$, every $n$-vertex graph $G$ satisfying that $\delta (G)\geq \varepsilon n$ and $e(X, Y)\gt 0$ for every pair of disjoint vertex sets $X, Y\subseteq V(G)$ of size $\alpha n$ contains all spanning trees with maximum degree at most $\Delta$. This strengthens a result of Böttcher, Han, Kohayakawa, Montgomery, Parczyk, and Person.

This study examined the impact of coherent structures on the aerodynamic forces exerted on a NACA0012 aerofoil with angles of attack $7.5^{\circ }$ and $10^{\circ }$, and a chord-based Reynolds number $50\,000$. The study utilized the spectral proper orthogonal decomposition (SPOD) algorithm to identify the coherent structures, and vorticity force analysis to quantify their impact on lift and drag forces. Results showed that at $10^{\circ }$, the zeroth frequency of the first SPOD mode had a significant impact on drag and lift forces due to a large vortex structure that caused a strong flow along the suction side of the aerofoil. The first and second frequencies of the first SPOD mode represented asymmetric vortex pairs and a series of vortex pairs that determined the leading-edge separation, respectively. At $7.5^{\circ }$, the zeroth frequency of the first mode corresponded to an oscillating near-wall stream that followed the reattachment flow pattern, while the first frequency corresponded to a counter-rotating vortex pair that originated where the flow reattaches. Finally, the second frequency of the first mode corresponded to smaller counter-rotating vortex pairs at the shear layer originated near the reattachment point. These findings suggest that coherent structures have a significant impact on aerodynamic forces exerted on aerofoils, and can be identified and quantified using the SPOD algorithm and vorticity force analysis.

This meta-analysis synthesized 35 English studies (130 effect sizes, N = 1,981) that employed online tasks to investigate the processing of multiword sequences (MWSs). We examined (a) to what extent MWSs enjoy a processing advantage over novel word combinations; (b) how such a processing advantage is moderated by statistical regularities (i.e., phrasal frequency, association strength), MWS type, and explicitness of experimental tasks; and (c) whether such moderating patterns differ between L1 speakers and L2 speakers. The results confirmed the processing advantage for most subtypes of MWSs, with effect sizes ranging from small to medium. For L1 speakers and L2 speakers, the processing advantage of MWSs was found across the continuum of phrasal frequency and association strength and varied. Interestingly, task explicitness moderated the processing advantage of MWSs but only for L2 speakers. Taken together, our results shed light on the understanding of MWSs as well as directions for future research.

This study presents a comprehensive analysis on the extreme positive and negative events of wall shear stress and heat flux fluctuations in compressible turbulent boundary layers (TBLs) solved by direct numerical simulations. To examine the compressibility effects, we focus on the extreme events in two representative cases, i.e. a supersonic TBL of Mach number $M=2$ and a hypersonic TBL of $M=8$, by scrutinizing the coherent structures and their correlated dynamics based on conditional analysis. As characterized by the spatial distribution of wall shear stress and heat flux, the extreme events are indicated to be closely related to the structural organization of wall streaks, in addition to the occurrence of the alternating positive and negative structures (APNSs) in the hypersonic TBL. These two types of coherent structures are strikingly different, namely the nature of wall streaks and APNSs are shown to be related to the solenoidal and dilatational fluid motions, respectively. Quantitative analysis using a volumetric conditional average is performed to identify and extract the coherent structures that directly account for the extreme events. It is found that in the supersonic TBL, the essential ingredients of the conditional field are hairpin-like vortices, whose combinations can induce wall streaks, whereas in the hypersonic TBL, the essential ingredients become hairpin-like vortices as well as near-wall APNSs. To quantify the momentum and energy transport mechanisms underlying the extreme events, we proposed a novel decomposition method for extreme skin friction and heat flux, based on the integral identities of conditionally averaged governing equations. Taking advantage of this decomposition method, the dominant transport mechanisms of the hairpin-like vortices and APNSs are revealed. Specifically, the momentum and energy transports undertaken by the hairpin-like vortices are attributed to multiple comparable mechanisms, whereas those by the APNSs are convection dominated. In that, the dominant transport mechanisms in extreme events between the supersonic and hypersonic TBLs are indicated to be totally different.

This experiment was conducted to investigate whether dietary chenodeoxycholic acid (CDCA) could attenuate high-fat (HF) diet-induced growth retardation, lipid accumulation and bile acid (BA) metabolism disorder in the liver of yellow catfish Pelteobagrus fulvidraco. Yellow catfish (initial weight: 4·40 (sem 0·08) g) were fed four diets: the control (105·8 g/kg lipid), HF diet (HF group, 159·6 g/kg lipid), the control supplemented with 0·9 g/kg CDCA (CDCA group) and HF diet supplemented with 0·9 g/kg CDCA (HF + CDCA group). CDCA supplemented in the HF diet significantly improved growth performance and feed utilisation of yellow catfish (P < 0·05). CDCA alleviated HF-induced increment of hepatic lipid and cholesterol contents by down-regulating the expressions of lipogenesis-related genes and proteins and up-regulating the expressions of lipololysis-related genes and proteins. Compared with the control group, CDCA group significantly reduced cholesterol level (P < 0·05). CDCA significantly inhibited BA biosynthesis and changed BA profile by activating farnesoid X receptor (P < 0·05). The contents of CDCA, taurochenodeoxycholic acid and glycochenodeoxycholic acid were significantly increased with the supplementation of CDCA (P < 0·05). HF-induced elevation of cholic acid content was significantly attenuated by the supplementation of CDCA (P < 0·05). Supplementation of CDCA in the control and HF groups could improve the liver antioxidant capacity. This study proved that CDCA could improve growth retardation, lipid accumulation and BA metabolism disorder induced by HF diet, which provided new insight into understanding the physiological functions of BA in fish.

Several meta-analyses investigating the efficacy of n-3 PUFA in alleviating depression symptoms have reported conflicting findings. In the present study, we aimed to perform an umbrella meta-analysis to provide a definite conclusion. A comprehensive systematic search of PubMed, Scopus, Embase, Web of Science and Cochrane Central Library was performed up to June 2021. Meta-analysis studies evaluating the effects of n-3 PUFA on depression symptoms were included. The quality of the included meta-analyses was assessed using AMSTAR questionnaire. Out of 101 studies, twenty-two studies with twenty-six effect sizes (ES) were eligible for inclusion. Sixteen ES showed significant improving effect of n-3 supplementation on depression symptoms among which eleven ES had small ES. The other studies observed no significant effect. Available evidence suggests that n-3 PUFA (EPA, DHA) supplementation could be considered as an effective add-on therapeutic approach in relieving depression symptoms.