High-molecular-weight glutenin subunits (HMW-GS) contribute to dough elasticity and bread baking quality in wheat. In this study, wheat varieties were classified based on their HMW-GS composition into three groups: 1Dx5 (5 + 10, Gaoyou 8901, Xinmai 28, Xinmai 19, Xinmai 26 and Jinbaoyin), 1Dx2 (2 + 12, Zhoumai 24, Xinmai 9 and Yumai) and 1Dx4 (4 + 12, Aikang 58). Sequence analysis showed that 1Dx-GY8901, 1Dx-XM28, 1Dx-XM19 and 1Dx-XM26 were similar to the 1Dx5 gene and clustered on the same branch, while 1Dx-AK58, 1Dx-ZM24, 1Dx-JBY, 1Dx-YM, 1Dx-XM9 and 1Dx-JBY were more similar to the 1Dx2 gene and clustered on the same branch with 1Dx.2.2. There was a mutation of Ser to Cys at position S2, for an extra Cys in the repeat regions of 1Dx-XM19, 1Dx-XM26, 1Dx-XM28 and 1Dx-GY8901. The wheat HMW-GS genes exhibited similar percentages of α-helix, extended strand, β-turn and random coil structure, with ranges of 13.33–13.59, 4.77–5.78, 7.08–9.18 and 72.3–73.94%, respectively. Sequence conservation and the composition of HMW-GS subunits were also analysed for a series of strong gluten wheat varieties, Xinmai 9 (1, 7 + 8, 2 + 12), Xinmai 19 (1, 7 + 9, 5 + 10), Xinmai 26 (1, 7 + 8, 5 + 10) and Xinmai 28 (1, 7 + 9, 5 + 10). The results of this work should facilitate future breeding efforts and provide the theoretical basis for wheat quality improvement.

Detecting the turbulent/non-turbulent interface is a challenging topic in turbulence research. In the present study, machine learning methods are used to train detectors for identifying turbulent regions in the flow past a circular cylinder. To ensure that the turbulent/non-turbulent interface is independent of the reference frame of coordinates and is physics-informed, we propose to use invariants of tensors appearing in the transport equations of velocity fluctuations, strain-rate tensor and vortical tensor as the input features to identify the flow state. The training samples are chosen from numerical simulation data at two Reynolds numbers, $Re=100$ and 3900. Extreme gradient boosting (XGBoost) is utilized to train the detector, and after training, the detector is applied to identify the flow state at each point of the flow field. The trained detector is found robust in various tests, including the applications to the entire fields at successive snapshots and at a higher Reynolds number $Re=5000$. The objectivity of the detector is verified by changing the input features and the flow region for choosing the turbulent training samples. Compared with the conventional methods, the proposed method based on machine learning shows its novelty in two aspects. First, no threshold value needs to be specified explicitly by the users. Second, machine learning can treat multiple input variables, which reflect different properties of turbulent flows, including the unsteadiness, vortex stretching and three-dimensionality. Owing to these advantages, XGBoost generates a detector that is more robust than those obtained from conventional methods.

Phase-resolved wave simulation and direct numerical simulation of turbulence are performed to investigate the surface wave effects on the energy transfer in overlying turbulent flow. The JONSWAP spectrum is used to initialize a broadband wave field. The nonlinear wave field is simulated using a high-order spectral method, and the resultant wave surface provides the bottom boundary conditions for direct numerical simulation of the overlying turbulent flow. Two wave ages of $c_{p}/u_{\ast }=2$ and 25 are considered, corresponding to slow and fast wave fields, respectively, where $c_{p}$ denotes the celerity of the peak wave and $u_{\ast }$ denotes the friction velocity. The energy transfer of turbulent motions in the presence of surface waves is investigated through the spectral analysis of the two-point correlation transport equation. It is found that the production term has an extra peak at the dominant wavelength scale in the vicinity of the surface, and the energy transported to the surface via viscous and spatial turbulent transport is enhanced in the region of $y^{+}<10$. The presence of surface waves results in an inverse turbulent energy cascade in the near-surface region, where small-scale wave-related motions transfer energy back to the dominant wavelength scale. Pressure-related terms reflecting the spatial and inter-component energy transfer are strongly dependent on the wave age. Furthermore, triadic interaction analysis reveals that the energy influx at the dominant wavelength scale is due to the contribution of the neighbouring streamwise turbulent motions, and those at the harmonic wavelength scales contribute the most.

Underground Nuclear Astrophysics in China (JUNA) will take the advantage of the ultra-low background in Jinping underground lab. High current accelerator with an ECR source and detectors were commissioned. JUNA plans to study directly a number of nuclear reactions important to hydrostatic stellar evolution at their relevant stellar energies. At the first period, JUNA aims at the direct measurements of 25Mg(p,γ)26 Al, 19F(p,α) 16 O, 13C(α, n) 16O and 12C(α,γ) 16O near the Gamow window. The current progress of JUNA will be given.

In the present study, two experiments were conducted to investigate the effect of Mn source on Mn transport and the expression of a Mn transporter, divalent metal transporter 1 (DMT1), in the small intestine of broilers. In Expt 1, in situ ligated duodenal loops from Mn-deficient chicks (29-d-old) were perfused with solutions containing 0–8·74 mmol Mn/l from either MnSO4, or one of two organic chelates of Mn and amino acids with moderate (OM) or strong (OS) chelation strength (Qf) up to 30 min. In Expt 2, Mn-deficient intact broilers (14-d-old) were fed a control diet (12·45 mg Mn/kg) or the control diet supplemented with 100 mg Mn/kg as one of all Mn sources for 14 d. The uptake kinetics of Mn from different Mn sources in the ligated duodenal loops followed a saturable process as determined by regression analysis of concentration-dependent uptake rates. The maximum transport rate (Jmax) and Km values, and DMT1 mRNA levels in the ligated duodenal loops were higher (P < 0·01) for OM and OS than for MnSO4. DMT1 mRNA levels were much higher (P < 0·01) in the duodenum than in the jejunum and ileum. Both DMT1 mRNA levels in the duodenum and plasma Mn contents from the hepatic portal vein of intact chicks on day 14 post-feeding increased (P < 0·05) in the following order: control < MnSO4 < OM < OS. These results indicated that organic Mn sources with stronger Qf showed higher Mn transport and absorption, and DMT1 might be involved in the regulation of organic Mn transport in the proximal small intestine of broilers.

Structural origin of the high glass-forming ability (GFA) in multicomponent bulk metallic glasses (BMGs) caused by minor alloying was investigated using state-of-the-art synchrotron radiation techniques. It is found that a two-shell icosahedral cluster with one Y center is the basic structural unit in the representative Cu46Zr42Al7Y5 BMG, which may be densely packed with the help of shared and glue atoms, leading to enhanced ordering at short and medium range. This cluster dense packing may play a key role in achieving the high GFA in CuZrAlY alloy, which also explains the strong dependence of GFA on Y content observed in many experiments. The present work may be extended to a series of multicomponent amorphous alloys, the formation of which is strongly dependent on minor alloying.

Al/Mg2Si composites were in situ fabricated by the usual die-casting technique, and effects of the Si contents in the composites on microstructures and tensile strengths were investigated. Experimental results show that extra Si contents in Al/Mg2Si composites induce a ductile matrix and a uniform distribution of in situ particles. The refined microstructures lead to an obvious increase in both strength and ductility of the metal matrix composites (MMCs). The effects of extra Si on both the solidification process and fracture characteristics of the Al/Mg2Si composites were analyzed.