Emission line galaxies (ELGs) are crucial for cosmological studies, particularly in understanding the large-scale structure of the Universe and the role of dark energy. ELGs form an essential component of the target catalogue for the Dark Energy Spectroscopic Instrument (DESI), a major astronomical survey. However, the accurate selection of ELGs for such surveys is challenging due to the inherent uncertainties in determining their redshifts with photometric data. In order to improve the accuracy of photometric redshift estimation for ELGs, we propose a novel approach CNN–MLP that combines convolutional neural networks (CNNs) with multilayer perceptrons (MLPs). This approach integrates both images and photometric data derived from the DESI Legacy Imaging Surveys Data Release 10. By leveraging the complementary strengths of CNNs (for image data processing) and MLPs (for photometric feature integration), the CNN–MLP model achieves a $\sigma_{\mathrm{NMAD}}$ (normalised median absolute deviation) of 0.0140 and an outlier fraction of 2.57%. Compared to other models, CNN–MLP demonstrates a significant improvement in the accuracy of ELG photometric redshift estimation, which directly benefits the target selection process for DESI. In addition, we explore the photometric redshifts of different galaxy types (Starforming, Starburst, AGN, and Broadline). Furthermore, this approach will contribute to more reliable photometric redshift estimation in ongoing and future large-scale sky surveys (e.g. LSST, CSST, and Euclid), enhancing the overall efficiency of cosmological research and galaxy surveys.

This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.

In preparation for an experiment with a laser-generated intense proton beam at the Laser Fusion Research Center at Mianyang to investigate the 11B(p,α)2α reaction, we performed a measurement at very low proton energy between 140 keV and 172 keV using the high-voltage platform at the Institute of Modern Physics, Lanzhou. The aim of the experiment was to test the ability to use CR-39 track detectors for cross-section measurements and to remeasure the cross-section of this reaction close to the first resonance using the thick target approach. We obtained the cross-section σ = 45.6 ± 12.5 mb near 156 keV. Our result confirms the feasibility of CR-39 type track detector for nuclear reaction measurement also in low-energy regions.

The advent of time-domain sky surveys has generated a vast amount of light variation data, enabling astronomers to investigate variable stars with large-scale samples. However, this also poses new opportunities and challenges for the time-domain research. In this paper, we focus on the classification of variable stars from the Catalina Surveys Data Release 2 and propose an imbalanced learning classifier based on Self-paced Ensemble (SPE) method. Compared with the work of Hosenie et al. (2020), our approach significantly enhances the classification Recall of Blazhko RR Lyrae stars from 12% to 85%, mixed-mode RR Lyrae variables from 29% to 64%, detached binaries from 68% to 97%, and LPV from 87% to 99%. SPE demonstrates a rather good performance on most of the variable classes except RRab, RRc, and contact and semi-detached binary. Moreover, the results suggest that SPE tends to target the minority classes of objects, while Random Forest is more effective in finding the majority classes. To balance the overall classification accuracy, we construct a Voting Classifier that combines the strengths of SPE and Random Forest. The results show that the Voting Classifier can achieve a balanced performance across all classes with minimal loss of accuracy. In summary, the SPE algorithm and Voting Classifier are superior to traditional machine learning methods and can be well applied to classify the periodic variable stars. This paper contributes to the current research on imbalanced learning in astronomy and can also be extended to the time-domain data of other larger sky survey projects (LSST, etc.).

A 198.8 m deep borehole was drilled through ice to subglacial bedrock in the northwestern marginal part of Princess Elizabeth Land, ~12 km south of Zhongshan Station, in January–February 2019. Three years later, in February 2022, the borehole temperature profile was measured, and the geothermal heat flow (GHF) was estimated using a 1-D time-dependent energy-balance equation. For a depth corresponding to the base of the ice sheet, the GHF was calculated as 72.6 ± 2.3 mW m−2 and temperature −4.53 ± 0.27°C. The regional averages estimated for this area based, generally, on tectonic setting vary from 55 to 66 mW m−2. A higher GHF is interpreted to originate mostly from the occurrence of metamorphic complexes intruded by heat-producing elements in the subglacial bedrock below the drill site.

For the path planning of autonomous underwater vehicles (AUVs) in the ocean environment, in addition to the planned path length and safe obstacle avoidance, it is also necessary to pay attention to the impact of ocean currents on the planned path. Therefore, this paper improves the original D* algorithm, and adds the obstacle cost item and the steering angle cost item as constraints on the basis of the original cost function, thus ensuring the navigation safety of the AUV. Considering that ocean currents have a greater impact on the energy consumption of AUVs, this paper establishes a cost model for the impact of ocean currents on AUV energy consumption and applies it to the D* path planning algorithm, so that AUVs can use ocean currents to reduce energy consumption, which can be seen through simulation experiments. The simulation results show that the improvement of the algorithm can plan an optimal energy consumption path.

The southeastern Central Asian Orogenic Belt (CAOB) records the assembly process between several micro-continental blocks and the North China Craton (NCC), with the consumption of the Paleo-Asian Ocean (PAO), but whether the S-wards subduction of the PAO beneath the northern NCC was ongoing during Carboniferous–Permian time is still being debated. A key issue to resolve this controversy is whether the Carboniferous magmatism in the northern NCC was continental arc magmatism. The Alxa Block is the western segment of the northern NCC and contiguous to the southeastern CAOB, and their Carboniferous–Permian magmatism could have occurred in similar tectonic settings. In this contribution, new zircon U–Pb ages, elemental geochemistry and Sr–Nd isotopic analyses are presented for three early Carboniferous granitic plutons in the southwestern Alxa Block. Two newly identified aluminous A-type granites, an alkali-feldspar granite (331.6 ± 1.6 Ma) and a monzogranite (331.8 ± 1.7 Ma), exhibit juvenile and radiogenic Sr–Nd isotopic features, respectively. Although a granodiorite (326.2 ± 6.6 Ma) is characterized by high Sr/Y ratios (97.4–139.9), which is generally treated as an adikitic feature, this sample has highly radiogenic Sr–Nd isotopes and displays significantly higher K2O/Na2O ratios than typical adakites. These three granites were probably derived from the partial melting of Precambrian continental crustal sources heated by upwelling asthenosphere in lithospheric extensional setting. Regionally, both the Alxa Block and the southeastern CAOB are characterized by the formation of early Carboniferous extension-related magmatic rocks but lack coeval sedimentary deposits, suggesting a uniform lithospheric extensional setting rather than a simple continental arc.

Different from developed countries, there is a paucity of research examining how the Dietary Approaches to Stop Hypertension (DASH) and Mediterranean diets relate to lipids in less-developed ethnic minority regions (LEMR). A total of 83 081 participants from seven ethnic groups were retrieved from the baseline data of the China Multi-Ethnic Cohort study, which was conducted in less-developed Southwest China between May 2018 and September 2019. Multivariable linear regression models were then used to examine the associations of the DASH and alternative Mediterranean diet (AMED) scores, assessed by modified DASH score and AMED, as well as their components with total cholesterol (TC), LDL-cholesterol, HDL-cholesterol, TAG and TC/HDL-cholesterol. The DASH scores were negatively associated with TC, HDL-cholesterol and TAG. Comparing the highest quintiles with the lowest DASH scores, TC decreased 0·0708 (95 % CI −0·0923, −0·0493) mmol/l, HDL-cholesterol decreased 0·0380 (95 % CI −0·0462, −0·0299) mmol/l and TAG decreased 0·0668 (95 % CI −0·0994, −0·0341) mmol/l. The AMED scores were negatively associated with TC, LDL-cholesterol and HDL-cholesterol. Comparing the highest quintiles with the lowest AMED scores, TC decreased 0·0816 (95 % CI −0·1035, −0·0597) mmol/l, LDL-cholesterol decreased 0·0297 (95 % CI −0·0477, −0·0118) mmol/l and HDL-cholesterol decreased 0·0275 (95 % CI −0·0358, −0·0192) mmol/l. Although both the DASH diet and the Mediterranean diet were negatively associated with blood lipids, those associations showed different patterns in LEMR, particularly for TAG and HDL-cholesterol.

Little is known about the impact of modifiable risk factors on blood pressure (BP) trajectories and their associations with hypertension (HTN). We aimed to identify BP trajectories in normotensive Chinese adults and explore their influencing factors and associations with HTN. We used data from 3436 adults with at least four BP measurements between 1989 and 2018 in the China Health and Nutrition Survey, an ongoing cohort study. We measured BP using mercury sphygmomanometers with appropriate cuff sizes in all surveys. We used group-based trajectory modelling to identify BP trajectories between 1989 and 2009 and multiple logistic and Cox regression models to analyse their influencing factors and associations with HTN in 2011–2018. We identified five systolic blood pressure (SBP) trajectories, ‘Low-increasing (LI)’, ‘Low–stable (LS)’, ‘Moderate-increasing (MI)’, ‘High-stable (HS)’ and ‘Moderate-decreasing (MD)’, and four diastolic blood pressure (DBP) trajectories classified as ‘Low-increasing (LI)’, ‘Moderate–stable (MS)’, ‘Low-stable (LS)’ and ‘High-increasing (HI)’. People with higher physical activity (PA) levels and lower waist circumferences (WC) were less likely to be in the SBP LI, MI, HS and MD groups (P < 0·05). People with higher fruit and vegetable intakes, lower WCs and salt intakes and higher PA levels were less likely to be in the DBP LI, MS and HI groups (P < 0·05). Participants in the SBP HS group (hazard ratio (HR) 2·01) or the DBP LI, MS and HI groups (HR 1·38, 1·40, 1·71, respectively) had higher risks of HTN (P < 0·05). This study suggests that BP monitoring is necessary to prevent HTN in the Chinese population.

NaY zeolite was synthesized from kaolin/dimethyl sulfoxide (DMSO) intercalation composites using an in situ crystallization technique. The effects of the intercalation ratios and the amounts of the kaolin/DMSO intercalation composite on the synthesis of an NaY zeolite molecular sieve were studied. The samples were characterized by X-ray diffraction, Fourier-transform infrared spectroscopy, differential thermal analysis, N2 adsorption–desorption and scanning electron microscopy. In the in situ synthesis system, when the kaolin/DMSO intercalation composite was added, pure NaY zeolite was formed. By increasing the amount of kaolin/DMSO intercalation composite added, the crystallinity of the samples increased, and after reaching the maximum amount of kaolin/DMSO intercalation composite added, the crystallinity decreased with further increases of the amount of kaolin/DMSO intercalation composite added. To higher intercalation ratio, the crystallinity can be greatly improved at the lower addition content. At an intercalation ratio of 84%, the added amount of kaolin/DMSO intercalation composite was 2.5% and the crystallinity of the NaY zeolite molecular sieve reached a maximum value of 45%. At intercalation ratios of 55% and 22%, the amount of kaolin/DMSO intercalation composite added was 15% and the crystallinities of the NaY zeolite molecular sieves were 44% and 47%, respectively. The NaY zeolite has good thermal stability and a particle diameter of ~0.5 μm. The Brunauer–Emmett–Teller (BET) specific surface area and pore volume of the sample were 519 m2 g–1 and 0.355 cm3 g–1, respectively.

Poor utilisation efficiency of carbohydrate always leads to metabolic phenotypes in fish. The intestinal microbiota plays an important role in carbohydrate degradation. Whether the intestinal bacteria could alleviate high-carbohydrate diet (HCD)-induced metabolic phenotypes in fish remains unknown. Here, a strain affiliated to Bacillus amyloliquefaciens was isolated from the intestine of Nile tilapia. A basal diet (CON), HCD or HCD supplemented with B. amy SS1 (HCB) was used to feed fish for 10 weeks. The beneficial effects of B. amy SS1 on weight gain and protein accumulation were observed. Fasting glucose and lipid deposition were decreased in the HCB group compared with the HCD group. High-throughput sequencing showed that the abundance of acetate-producing bacteria was increased in the HCB group relative to the HCD group. Gas chromatographic analysis indicated that the concentration of intestinal acetate was increased dramatically in the HCB group compared with that in the HCD group. Glucagon-like peptide-1 was also increased in the intestine and serum of the HCB group. Thus, fish were fed with HCD, HCD supplemented with sodium acetate at 900 mg/kg (HLA), 1800 mg/kg (HMA) or 3600 mg/kg (HHA) diet for 8 weeks, and the HMA and HHA groups mirrored the effects of B. amy SS1. This study revealed that B. amy SS1 could alleviate the metabolic phenotypes caused by HCD by enriching acetate-producing bacteria in fish intestines. Regulating the intestinal microbiota and their metabolites might represent a powerful strategy for fish nutrition modulation and health maintenance in future.

A deep ice core was drilled at Dome A, Antarctic Plateau, East Antarctica, which started with the installation of a casing in January 2012 and reached 800.8 m in January 2017. To date, a total of 337 successful ice-core drilling runs have been conducted, including 118 runs to drill the pilot hole. The total drilling time was 52 days, of which eight days were required for drilling down and reaming the pilot hole, and 44 days for deep ice coring. The average penetration depths of individual runs were 1 and 3.1 m for the pilot hole drilling and deep ice coring, respectively. The quality of the ice cores was imperfect in the brittle zone (650−800 m). Some of the troubles encountered are discussed for reference, such as armoured cable knotting, screws falling into the hole bottom, and damaged parts, among others.

Subglacial lake exploration is of great interest to the science community. RECoverable Autonomous Sonde (RECAS) provides an exploration tool to measure and sample subglacial lake environments while the subglacial lake remains isolated from the glacier surface and atmosphere. This paper presents an electronic control system design of 200 m prototype of RECAS. The proposed electronic control system consists of a surface system, a downhole control system, and a power transfer and communication system. The downhole control system is the core element of RECAS, and is responsible for sonde status monitoring, sonde motion control, subglacial water sampling and in situ analysis. A custom RS485 temperature sensor was developed to cater for the limited size and depth requirements of the system. We adopted a humidity-based measurement to monitor for a housing leak. This condition is because standard leak detection monitoring of water conductivity may be inapplicable to pure ice in Antarctica. A water sampler control board was designed to control the samplers and monitor the on/off state. A high-definition camera system with built-in storage and self-heating ability was designed to perform the video recording in the subglacial lake. The proposed electronic control system is proven effective after a series of tests.

It was reported that about 10% of people suffer from painful knee arthritis, and a quarter of them were severely disabled. The core activities of daily living were severely limited by knee osteoarthritis (KOA). In order to reduce knee pain and prolong the life of the knee joint, there has been an increasing demand on the development of exoskeletons, for prevention and treatment. The course of KOA was closely related to the biomechanics of knee joint, and the pathogenesis was summarized based on the biomechanics of knee joint. For the prevention and clinical treatment, exoskeletons are classified into three categories: prevention, treatment, and rehabilitation after the operation. Furthermore, the design concepts, actuators, sensors, control strategies, and evaluation criteria were presented. Finally, the shortcomings and limitations were summarized. It is useful for researchers to develop suitable exoskeletons in the future.

A series of new synthetic armored cables were developed and tested to ensure that they were suitable for use with the RECoverable Autonomous Sonde (RECAS), which is a newly designed freezing-in thermal ice probe. The final version of the cable consists of two concentric conductors that can be used as the power and signal lines. Two polyfluoroalkoxy jackets are used for electrical insulation (one for insulation between conductors, and the other for insulation of the outer conductor). The outer insulation layer is coated by polyurethane jacket to seal the connections between the cable and electrical units. The 0.65 mm thick strength member is made from aramid fibers woven together. To hold these aramid fibers in place, a sheathing layer was produced from a polyamide fabric cover net. The outer diameter of the final version of the cable is ~6.1 mm. The permissible bending radius is as low as 17–20 mm. The maximal breaking force under straight tension is ~12.2 kN. The cable weight is only ~0.061 kg m−1. The mechanical and electrical properties and environmental suitability of the cable were determined through laboratory testing and joint testing with the probe.

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.