High-sensitivity observations of PSR J1919+1745 were conducted using the Five-hundred-meter Aperture Spherical Radio Telescope (FAST) at a central frequency of 1250 MHz, enabling a detailed investigation of its single-pulse behaviour. Our research indicates that this pulsar is a normal pulsar, exhibiting null behaviour, subpulse drifting, and occasional bright pulses. Moreover, we observed that the null events tend to be of short duration, with an estimated overall null fraction of approximately 29.5 ± 1.1%. Through Sliding Fluctuation Spectrum analysis, the modulation period of subpulse drifting is determined to be P3 =(6.1 ± 0.7)P1 (where P1denotes the pulsar rotation period), and a non-drifting behaviour is also observed besides this. Analysis using the Harmonic-Resolved Fourier Spectrum indicates that a combination of amplitude modulation and phase modulation causes the subpulse drifting behaviour of this pulsar. Furthermore, the value P2, derived from phase modulation, is approximately 360°/21 = 17.1°. polarisation analysis shows a moderate degree of linear polarization (37.22 ± 0.59%), an S-shaped swing in the polarisation position angle, and an approximate 90° orthogonal polarisation jump. The radiation characteristics of PSR J1919+1745 will expand the sample of pulsars with pulse null and subpulse drifting, thus contributing to future systematic studies on the physical origins of pulse null and subpulse drifting phenomena.

The Deerni copper deposit is one of the largest in Qinghai province, China, with proven copper reserves of 0.556 Mt. To explore new copper orebodies, we conducted a geological study at western Deerni focusing on hydrothermal alterations and ore-controlling structures. Field investigation shows that the deposit is hosted mainly within the central segment of the Deerni ophiolite. Additional hosts include Lower-Permian slate, limestone, gabbro and volcanic rock, as well as the contact zone between granite and slate. Such observations indicate that the Deerni copper deposit is not only associated with the ophiolite, but its formation is also controlled by faults. Alterations including serpentinization, carbonatization, silicification and malachite, and magnetite mineralization occurred along fractures within the wall rocks and surrounding strata. This means the alteration post-dated structural activity that affected the Lower Permian strata in the region. The Deerni copper deposit is controlled by the NW-striking faults. This is evidenced by (1) slate fragments and breccias within the orebodies, (2) saw-toothed boundaries between the orebodies and host rocks, (3) copper ore veinlets and (4) striations and step patterns on the orebody surface and hanging-wall-hosted quartz veins. Mineralization controlled by NW-trending faults suggests a major orebody (‘No. 2’) likely extends to either northwest or southeast. Field investigations along with geophysical and geochemical data, thus predicted the presence of concealed copper orebodies in western Deerni. Subsequent drilling projects have verified this prediction and revealed three concealed orebodies with widths of 7.15–13.87 m and Cu grade of 1.00–11.34 wt.%, adding 10,000 tonnes to the copper reserves.

This study investigates the transport of particles in turbulent channel flow with friction Reynolds number $Re_\tau = 1000$ by direct numerical simulation. We focus on how large-scale flow structures, namely the $Qs$ structures (Lozano-Durán et al. 2012, J. Fluid Mech., vol. 694, pp. 100–130), affect the wall-normal transport of particles. Despite occupying less than $10\,\%$ of the physical domain, our results highlight the critical role played by $Qs$ structures in the particle transport, namely that the particle number and momentum flux inside the $Qs$ structures are substantially higher than outside. The fraction of particle wall-normal momentum flux inside $Qs$ structures is considerably larger than their volume fraction, suggesting highly efficient transport inside the $Qs$ structures. This prominent role played by $Qs$ structures in the transport of inertial particles is more effective by diminishing the inertia of particles. Notably, the long-distance transport of particles in the wall-normal direction is driven primarily by the continuous effect of $Qs$ structures. In summary, our findings advance the understanding of the effects of $Qs$ structures on particle transport, and demonstrate their significant role in the process.

Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilise machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicentre cohort study including hospitalised oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined as a positive diagnosis of malnutrition upon patient admission which turned negative one month later. Time-series data on body weight and skeletal muscle were modelled using a long short-term memory architecture to predict RM. The model was named as WAL-net, and its performance, explainability, clinical relevance and generalisability were evaluated. We investigated 4254 patients with cancer-associated malnutrition (discovery set = 2977, test set = 1277). There were 2783 men and 1471 women (median age = 61 years). RM was identified in 754 (17·7 %) patients. RM/non-RM groups showed distinct patterns of weight and muscle dynamics, and RM was negatively correlated to the progressive stages of cancer cachexia (r = –0·340, P < 0·001). WAL-net was the state-of-the-art model among all ML algorithms evaluated, demonstrating favourable performance to predict RM in the test set (AUC = 0·924, 95 % CI = 0·904, 0·944) and an external validation set (n 798, AUC = 0·909, 95 % CI = 0·876, 0·943). Model-predicted RM using baseline information was associated with lower future risks of underweight, sarcopenia, performance status decline and progression of malnutrition (all P < 0·05). This study presents an explainable deep learning model, the WAL-net, for early identification of RM in patients with cancer. These findings might help the management of cancer-associated malnutrition to optimise patient outcomes in multidisciplinary cancer care.

A dual-beam platform is developed for all-optical Thomson/Compton scattering, with versatile parameter tuning capabilities including electron energy, radiation energy, radiation polarization, etc. By integrating this platform with a 200 TW Ti:sapphire laser system, we demonstrate the generation of inverse Compton scattering X-/gamma-rays with tunable energies ranging from tens of keV to MeV. The polarization of X-/gamma-rays is manipulated by adjusting the polarization of the scattering laser. In the near future, by combining this platform with multi-PW laser facilities, our goal is to explore the transition from nonlinear Thomson scattering to nonlinear Compton scattering, ultimately verifying theories related to strong-field quantum electrodynamics effects induced by extreme scattering.

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial membrane, leading to cartilage destruction and bone erosion. Due to the complex pathogenesis of RA and the limitations of current therapies, increasing research attention has been directed towards novel strategies targeting fibroblast-like synoviocytes (FLS), which are key cellular components of the hyperplastic pannus. Recent studies have highlighted the pivotal role of FLS in the initiation and progression of RA, driven by their tumour-like transformation and the secretion of pro-inflammatory mediators, including cytokines, chemokines and matrix metalloproteinases. The aggressive phenotype of RA-FLS is marked by excessive proliferation, resistance to apoptosis, and enhanced migratory and invasive capacities. Consequently, FLS-targeted therapies represent a promising avenue for the development of next-generation RA treatments. The efficacy of such strategies – particularly those aimed at modulating FLS signalling pathways – has been demonstrated in both preclinical and clinical settings, underscoring their therapeutic potential. This review provides an updated overview of the pathogenic mechanisms and functional roles of FLS in RA, with a focus on critical signalling pathways under investigation, including Janus kinase/signal transducer and activator of transcription (JAK/STAT), mitogen-activated protein kinase (MAPK), nuclear factor kappa B (NF-κB), Notch and interleukin-1 receptor-associated kinase 4 (IRAK4). In addition, we discuss the emerging understanding of FLS-subset-specific contributions to immunometabolism and explore how computational biology is shaping novel targeted therapeutic strategies. A deeper understanding of the molecular and functional heterogeneity of FLS may pave the way for more effective and precise therapeutic interventions in RA.

Chinese spelling correction has achieved significant progress, but critical challenges remain, especially in handling visually and phonetically similar errors within complex syntactic structures. This paper introduces a novel approach combining a Long Short-Term Memory Network (LSTM)-enhanced Transformer for error detection and Bidirectional Encoder Representations from Transformers (BERT)-based correction with a dynamic adaptive weighting scheme. Transformer uses global attention mechanism to capture dependencies between any two positions in the input sequence. By processing each token in the sequence recursively, LSTM is able to more finely capture local context and sequential information within the sequence. Based on adaptive weighting coefficient, weights of multi-task learning are automatically adjusted to help the model better balance the learning process between the detection and correction network, enabling it to converge faster and achieve higher precision. Comprehensive evaluations demonstrate improved performance over existing baselines, particularly in addressing complex error patterns.

Concentrations of sedimentary molybdenum (Mo) have been used as a proxy for palaeoceanographic redox conditions based on the distinctive behaviour of Mo under oxic versus euxinic (i.e., anoxic and sulfidic) conditions. However, the mechanisms that govern Mo sequestration in various euxinic settings are not fully resolved. It has previously been proposed that sulfate-reducing bacteria (SRB), the main drivers and regulators of euxinic conditions, can actively take up and reduce Mo intracellularly and passively induce Fe-independent Mo complexation and reduction at their cell surfaces. However, uncertainties remain regarding the underlying interactions and relative contributions of these proposed biotic Mo sequestration pathways. In this study, systematic experiments were carried out to examine the interactions among Mo(VI) species (MoO42- or MoS42-), ferrous iron (Fe2+) and SRB with a focus on combinations of conditions that lead to reductive Mo precipitation. The speciation of aqueous Mo and composition, structure, oxidation states and bonding environment of precipitated Mo-sulfides were analysed using UV-vis spectrophotometry (UV-vis), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and synchrotron-based X-ray absorption spectroscopy (XAS). Results indicate that SRB does not directly reduce Mo but, rather, plays a passive role in mediating Mo sequestration by providing sulfide and potential nucleation sites at their reactive cell surfaces for precipitation. However, even in the presence of SRB cells, Fe2+ was required for Mo precipitation in all conditions tested. By identifying the limiting (and non-limiting) factors in the Mo reduction and sequestration process, this study provides significant new insights for interpreting Mo palaeoredox proxies.

The single pulses of PSR J1921+1419 were examined in detail using high-sensitivity observations from the Five-hundred-meter Aperture Spherical radio Telescope (FAST) at a central frequency of 1250 MHz. The high-sensitivity observations indicate that the pulsar exhibits two distinct emission modes, which are classified as strong and weak modes based on the intensity of the single pulses. In our observations, the times spent in both modes are nearly equal, and each is about half of the total observation time. The minimum duration of both modes is $1\,P$ and the maximum duration is $13\,P$, where P is the pulsar spin period. Additionally, the mean intensity of the weak mode is less than half of that of the strong mode. Notably, the switching between these modes demonstrates a clear quasi-periodicity with a modulation period of approximately $10 \pm 2\,P$. An analysis of the polarisation properties of both modes indicates that they originate from the same region within the magnetosphere of the pulsar. Finally, the viewing geometry was analysed based on the kinematical effects.

The double-cone ignition scheme is a promising novel ignition method, which is expected to greatly save the driver energy and enhance the robustness of the implosion process. In this paper, ablation of the inner surface of the cone by the hard X-ray from coronal Au plasma is studied via radiation hydrodynamics simulations. It is found that the X-ray ablation of the inner wall will form strong pre-plasma, which will significantly affect the implosion process and cause the Au plasma to mix with the fuel, leading to ignition failure. The radiation and pre-ablation intensities in the system are estimated, and the evolutions of areal density, ion temperature and the distribution of Au ions are analysed. In addition, the mixing of Au in CH at collision is quantified. Then, a scheme to reduce the X-ray pre-ablation by replacing the gold cone with a tungsten cone is proposed, showing that it is effective in reducing high-Z mixing and improving collision results.

An optical spectrometer system based on 60 channels of fibers has been designed and employed to diagnose light emissions from laser–plasma interactions. The 60 fiber collectors cover an integrated solid angle of $\pi$, enabling the measurement of global energy losses in a symmetrical configuration. A detecting spectral range from ultraviolet to near-infrared, with angular distribution, allows for the understanding of the physical mechanisms involving various plasma modes. Experimental measurements of scattered lights from a conical implosion driven by high-energy nanosecond laser beams at the Shenguang-II Upgrade facility have been demonstrated, serving as reliable diagnostics to characterize laser absorption and energy losses from laser–plasma instabilities. This compact diagnostic system can provide comprehensive insights into laser energy coupling in direct-drive inertial confinement fusion research, which are essential for studying the driving asymmetry and improving the implosion efficiencies.

The importance of automating pavement maintenance tasks for highway systems has garnered interest from both industry and academia. Despite significant research efforts and promising demonstrations being devoted to reaching a level of semi-automation featuring digital sensing and inspection, site maintenance work still requires manual processes using special vehicles and equipment, reflecting a clear gap to transition to fully autonomous maintenance. This paper reviews the current progress in pavement maintenance automation in terms of inspection and repair operations, followed by a discussion of three key technical challenges related to robotic sensing, control, and actuation. To address these challenges, we propose a conceptual solution we term Autonomous Maintenance Plant (AMP), mainly consisting of five modules for sensing, actuation, control, power supply, and mobility. This AMP concept is part of the “Digital Roads” project’s cyber-physical platform where a road digital twin (DT) is created based on its physical counterpart to enable real-time condition monitoring, sensory data processing, maintenance decision making, and repair operation execution. In this platform, the AMP conducts high-resolution survey and autonomous repair operations enabled (instructed) by the road DT. This process is unmanned and completely autonomous with an expectation to create a fully robotized highway pavement maintenance system.

Previous animal studies found beneficial effects of choline and betaine on maternal glucose metabolism during pregnancy, but few human studies explored the association between choline or betaine intake and incident gestational diabetes mellitus (GDM). We aimed to explore the correlation of dietary choline or betaine intake with GDM risk among Chinese pregnant women. A total of 168 pregnant women with GDM cases and 375 healthy controls were enrolled at the Seventh People’s Hospital in Shanghai during their GDM screening at 24–28 gestational weeks. A validated semi-quantitative FFQ was used to estimate choline and betaine consumption through face-to-face interviews. An unconditional logistic regression model was adopted to examine OR and 95 % CI. Compared with the controls, those women with GDM incidence were likely to have higher pre-pregnancy BMI, be older, have more parities and have higher plasma TAG and lower plasma HDL-cholesterol. No significant correlation was observed between the consumption of choline or betaine and incident GDM (adjusted OR (95 % CI), 0·77 (0·41, 1·43) for choline; 0·80 (0·42, 1·52) for betaine). However, there was a significant interaction between betaine intake and parity on the risk of GDM (Pfor interaction = 0·01). Among those women with no parity history, there was a significantly inverse correlation between betaine intake and GDM risk (adjusted OR (95 % CI), 0·25 (0·06, 0·81)). These findings indicated that higher dietary betaine intake during pregnancy might be considered a protective factor for GDM among Chinese women with no parity history.

Repulsive guidance molecule b (RGMb), a glycosylphosphatidylinositol-anchored member of the RGM family, is initially identified as a co-receptor of bone morphogenetic protein (BMP) in the nervous system. The expression of RGMb is transcriptionally regulated by dorsal root ganglion 11 (DRG11), which is a transcription factor expressed in embryonic DRG and dorsal horn neurons and plays an important role in the development of sensory circuits. RGMb is involved in important physiological processes such as embryonic development, immune response, intercellular adhesion and tumorigenesis. Furthermore, RGMb is mainly involved in the regulation of RGMb–neogenin–Rho and BMP signalling pathways. The recent discovery of programmed death-ligand 2 (PD-L2)–RGMb binding reveals that the cell signalling network and functional regulation centred on RGMb are extremely complex. The latest report suggests that down-regulation of the PD-L2–RGMb pathway in the gut microbiota promotes an anti-tumour immune response, which defines a potentially effective immune strategy. However, the biological function of RGMb in a variety of human diseases has not been fully determined, and will remain an active research field. This article reviews the properties and functions of RGMb, focusing on its role under various physiological and pathological conditions.

Accurate online estimation of the payload parameters benefits robot control. In the existing approaches, however, on the one hand, only the linear friction model was used for online payload identification, which reduced the online estimation accuracy. On the other hand, the estimation models contain much noise because of using actual joint trajectory signals. In this article, a new estimation algorithm based on parameter difference for the payload dynamics is proposed. This method uses a nonlinear friction model for the online payload estimation instead of the traditionally linear one. In addition, it considers the commanded joint trajectory signals as the computation input to reduce the model noise. The main contribution of this article is to derive a symbolic relationship between the parameter difference and the payload parameters and then apply it to the online payload estimation. The robot base parameters without payload were identified offline and regarded as the prior information. The one with payload can be solved online by the recursive least squares method. The dynamics of the payload can be then solved online based on the numerical difference of the two parameter sets. Finally, experimental comparisons and a manual guidance application experiment are shown. The results confirm that our algorithm can improve the online payload estimation accuracy (especially the payload mass) and the manual guidance comfort.

In an isolate-free graph G, a subset S of vertices is a semitotal dominating set of G if it is a dominating set of G and every vertex in S is within distance 2 of another vertex of S. The semitotal domination number of G, denoted by $\gamma _{t2}(G)$, is the minimum cardinality of a semitotal dominating set in G. Goddard, Henning and McPillan [‘Semitotal domination in graphs’, Utilitas Math. 94 (2014), 67–81] characterised the trees and graphs of minimum degree 2 with semitotal domination number half their order. In this paper, we characterise all graphs whose semitotal domination number is half their order.

Trauma is a significant health issue that not only leads to immediate death in many cases but also causes severe complications, such as sepsis, thrombosis, haemorrhage, acute respiratory distress syndrome and traumatic brain injury, among trauma patients. Target protein identification technology is a vital technique in the field of biomedical research, enabling the study of biomolecular interactions, drug discovery and disease treatment. It plays a crucial role in identifying key protein targets associated with specific diseases or biological processes, facilitating further research, drug design and the development of treatment strategies. The application of target protein technology in biomarker detection enables the timely identification of newly emerging infections and complications in trauma patients, facilitating expeditious medical interventions and leading to reduced post-trauma mortality rates and improved patient prognoses. This review provides an overview of the current applications of target protein identification technology in trauma-related complications and provides a brief overview of the current target protein identification technology, with the aim of reducing post-trauma mortality, improving diagnostic efficiency and prognostic outcomes for patients.

Epidemiologic research has increasingly acknowledged the importance of developmental origins of health and disease (DOHaD) and suggests that prior exposures can be transferred across generations. Multigenerational cohorts are crucial to verify the intergenerational inheritance among human subjects. We carried out this scoping review aims to summarize multigenerational cohort studies’ characteristics, issues, and implications and hence provide evidence to the DOHaD and intergenerational inheritance. We adopted a comprehensive search strategy to identify multigenerational cohorts, searching PubMed, EMBASE, and Web of Science databases from the inception of each dataset to June 20th, 2022, to retrieve relevant articles. After screening, 28 unique multigenerational cohort studies were identified. We classified all studies into four types: population-based cohort extended three-generation cohort, birth cohort extended three-generation cohort, three-generation cohort, and integrated birth and three-generation cohort. Most cohorts (n = 15, 53%) were categorized as birth cohort extended three-generation studies. The sample size of included cohorts varied from 41 to 167,729. The study duration ranged from two years to 31 years. Most cohorts had common exposures, including socioeconomic factors, lifestyle, and grandparents’ and parents’ health and risk behaviors over the life course. These studies usually investigated intergenerational inheritance of diseases as the outcomes, most frequently, obesity, child health, and cardiovascular diseases. We also found that most multigenerational studies aim to disentangle genetic, lifestyle, and environmental contributions to the DOHaD across generations. We call for more research on large multigenerational well-characterized cohorts, up to four or even more generations, and more studies from low- and middle-income countries.