In this work we propose a physics-constrained machine learning approach to enhance the generalisability of neural-network-represented turbulence models across different flow regimes. Machine learning-augmented turbulence modelling has emerged to improve the predictive accuracy of the Reynolds-averaged Navier–Stokes method based on high-fidelity data. However, such data-driven models face difficulties in generalising well in different flow scenarios outside training datasets. Here we show that this issue can be alleviated by incorporating physical constraints of the Reynolds stress during the learning process. It is achieved with a physics-constrained learning approach based on the regularised ensemble Kalman method, which allows for model learning from limited velocity data and is flexible in imposing physical constraints. The method is used to learn a nonlinear eddy viscosity model, represented by a tensor-basis neural network, from velocity data in separated flows over periodic hills. Two physical constraints are incorporated during the model learning, i.e. the baseline coefficients to capture the log law of the wall and the algebraic Reynolds stress equation to inform the Reynolds stress anisotropy. Moreover, an adaptive penalty method is developed to enforce physical constraints in the feature space associated with canonical flows, avoiding the incompatibility with the training data from separated flows. Our results show that the proposed method can learn a generalisable turbulence model across different flow scenarios, including similar separated flows, canonical wall-bounded flows and complex flow configurations. Finally, the learned neural-network-based model function is discussed, demonstrating its consistency with the imposed physical constraints.

A fiber-based route to mid-infrared nanosecond pulse laser generation in gas-filled hollow-core anti-resonant fiber at 4.3 μm with 10-W-level average power is demonstrated. The demonstration experiments, harnessing a single pump pulse with 37 ns duration and 125 W output power at 2 μm in a CO2-filled large-mode-field hollow-core anti-resonant fiber, produce nanosecond pulses centered at the 4.3 μm band with the output power of 10.27 W, with a pulse width of 29 ns and a repetition rate of 10 MHz. Efficient high-power mid-infrared laser generation is realized by detuning the pump wavelength from the CO2 molecular absorption peak, leading to mitigating the gain saturation issue in the CO2-filled hollow-core anti-resonant fiber laser under high-power pumping. To the best of our knowledge, this represents the highest power reported for CO2-filled hollow-core fiber nanosecond pulse laser sources to date, demonstrating a 34-fold power improvement over previous works.

Shipwrecks provide invaluable insights into human society and trade. Their unique preservation conditions also mean that they can serve as exceptional biobanks, recording traces of organisms carried aboard or arriving post wreck. Yet only limited research has explored the genetic potential of onboard sediments. Here, the authors present environmental and metagenomic analyses of sediments contained in a large amphora from the 150-year-old Yangzi Estuary II shipwreck. Weaving the results with historic texts, they reconstruct part of the history of the wrecked vessel, elucidating cargo-packing techniques, its likely season and port of sailing, and its ultimate submersion within the estuarine environment.

This study explored the effects of different preparations of Akkermansia muciniphila (AKK) on the gut microbiota and jejunal transcriptome of lipopolysaccharide (LPS) challenged yellow-feathered broilers. A total of 100 one-day-old broilers were divided into five groups, including control group (Control), LPS injection (LPS), gavage of AKK broth culture plus LPS injection (AKK), gavage of viable AKK suspension plus LPS injection (Active) and gavage of heat-inactivated AKK suspension plus LPS injection (Inactive). Growth performance results showed that LPS significantly reduced the body weight of broilers. Alpha diversity showed no significant group differences. At the phylum level, Firmicutes was significantly lower in groups with AKK gavage. At the genus level, Bacteroides was relatively more abundant, whereas Streptococcus was numerically less abundant in AKK-treated groups. The Active group had the highest abundance of Akkermansia. Transcriptome analysis revealed the Inactive group had significantly lower Occludin. Combined KEGG and GO analyses revealed that the LPS challenge suppressed innate immunity by downregulating the Retinoic acid-inducible gene (RIG)-I-like receptor signaling pathway. In response, different interventions distinctly modulated the transcriptome. The AKK group counteracted this suppression by upregulating innate immune and antiviral defense responses. The Active group primarily influenced metabolism, downregulating pathways for drug and glutathione metabolism and xenobiotic responses while upregulating retinol metabolism. In addition, the Inactive group demonstrated an upregulation of ribosome biogenesis, and energy metabolism, suggesting a restoration of core cellular functions. In summary, all gavaged AKK preparations maintained broiler gut microbiome stability, while AKK broth culture demonstrated superior efficacy in alleviating LPS-induced jejunal stress.

Team innovation is nurtured by the combination of team members’ diverse knowledge and collaborative teamwork. Previous research predominantly assumed a linear interaction between knowledge diversity and network density in predicting team innovation. A pivotal question arises: How do varying levels of knowledge diversity and network density interact to influence team innovation? To address this complex question, we conducted a machine-learning inductive study, leveraging its ability to uncover curvilinear interactive patterns between knowledge diversity and network density in fostering team innovation. We collected comprehensive, multisource data from 1,883 teams within a prominent high-technology firm in China over a four-year period from 2014 to 2017. The results indicate that knowledge diversity and network density exhibit a curvilinear interactive effect on team innovation. The two factors reinforce each other in the initial stage and foster peak innovation with an optimal balance at a medium-to-high level. Beyond this threshold, however, the two factors begin to restrain each other’s effectiveness. Consistent with the perspective of yin-yang balancing, this study deepens our understanding of the paradoxical joint effects of knowledge diversity and network density on team innovation.

We present the flexible delivery of picosecond laser pulses with up to 20 W average power over a 3-m-long sample of anti-resonant hollow-core fiber (AR-HCF) for laser-micromachining applications. Our experiments highlight the importance of optical-mode purity of the AR-HCF for manufacturing precision. We demonstrate that compared with an AR-HCF sample with a capillary to core (d/D) ratio of approximately 0.5, the AR-HCF with a d/D ratio of approximately 0.68 exhibits better capability of high-order-mode suppression, giving rise to improved micromachining quality. Moreover, the AR-HCF delivery system exhibits better pointing stability and setup flexibility than the free-space beam delivery system. These results pave the way to practical applications of AR-HCF in developing advanced equipment for ultrafast laser micromachining.

Mamyshev oscillators (MOs) demonstrate extraordinarily superior performance compared with fiber laser counterparts. However, the realization of a fully fiberized, monolithic laser system without pulse degradation remains a key challenge. Here we present a high-energy MO using large mode area Yb-doped fiber and fiber-integrable interferometric super-Gaussian spectral filters that directly generates a nearly diffraction-limited beam with approximately 9.84 W average power and 533 nJ pulse energy. By implementing pre-chirp management with anti-resonant hollow-core fiber (AR-HCF), the adverse effects of super-Gaussian filtering on pulse quality are effectively mitigated, enabling pulse compression to 1.23 times the transform limit. Furthermore, AR-HCF is employed to provide negative dispersion to compensate for the positive chirp of output pulses, resulting in approximately 37 fs de-chirped pulses with approximately 10 MW peak power. This approach represents a significant step toward the development of monolithic fiber lasers capable of generating and flexible delivery of sub-50-fs pulses with tens of megawatts peak power.

Machine learning (ML) models have been developed to identify randomised controlled trials (RCTs) to accelerate systematic reviews (SRs). However, their use has been limited due to concerns about their performance and practical benefits. We developed a high-recall ensemble learning model using Cochrane RCT data to enhance the identification of RCTs for rapid title and abstract screening in SRs and evaluated the model externally with our annotated RCT datasets. Additionally, we assessed the practical impact in terms of labour time savings and recall improvement under two scenarios: ML-assisted double screening (where ML and one reviewer screened all citations in parallel) and ML-assisted stepwise screening (where ML flagged all potential RCTs, and at least two reviewers subsequently filtered the flagged citations). Our model achieved twice the precision compared to the existing SVM model while maintaining a recall of 0.99 in both internal and external tests. In a practical evaluation with ML-assisted double screening, our model led to significant labour time savings (average 45.4%) and improved recall (average 0.998 compared to 0.919 for a single reviewer). In ML-assisted stepwise screening, the model performed similarly to standard manual screening but with average labour time savings of 74.4%. In conclusion, compared with existing methods, the proposed model can reduce workload while maintaining comparable recall when identifying RCTs during the title and abstract screening stages, thereby accelerating SRs. We propose practical recommendations to effectively apply ML-assisted manual screening when conducting SRs, depending on reviewer availability (ML-assisted double screening) or time constraints (ML-assisted stepwise screening).

A recent study published in Oryx proposed that the extinct Javan tiger Panthera tigris sondaica may still survive on the Island of Java, Indonesia, based on mitochondrial DNA analysis of a single hair sample collected from a location where a tiger was reportedly encountered. However, upon reanalysing the genetic data presented in that study, we conclude that there is little support for this claim. The sequences of the putative tiger hair and Javan tiger museum specimens generated are not from tiger cytoplasmic mitochondrial DNA but more likely the nuclear pseudogene copies of mitochondrial DNA. In addition, the number of mismatches between the two Javan tiger sequences is unusually high for homologous sequences that are both from tigers, suggesting potential issues with data reliability. The paper provides insufficient details on quality control measures, making it impossible to rule out the possibility that errors were introduced during the analysis. Consequently, it is inappropriate to use the sequences presented in that study to infer the existence of the Javan tiger.

The incidence of obesity-related glomerulopathy (ORG) is rising worldwide with very limited treatment methods. Paralleled with the gut–kidney axis theory, the beneficial effects of butyrate, one of the short-chain fatty acids (SCFA) produced by gut microbiota, on metabolism and certain kidney diseases have gained growing attention. However, the effects of butyrate on ORG and its underlying mechanism are largely unexplored. In this study, a mice model of ORG was established with a high-fat diet feeding for 16 weeks, and sodium butyrate treatment was initiated at the 8th week. Podocyte injury, oxidative stress and mitochondria function were evaluated in mice kidney and validated in vitro in palmitic acid-treated-mouse podocyte cell lines. Further, the molecular mechanisms of butyrate on podocytes were explored. Compared with controls, sodium butyrate treatment alleviated kidney injuries and renal oxidative stress in high-fat diet-fed mice. In mouse podocyte cell lines, butyrate ameliorated palmitic acid-induced podocyte damage and helped maintain the structure and function of the mitochondria. Moreover, the effects of butyrate on podocytes were mediated via the GPR43-Sirt3 signal pathway, as evidenced by the diminished effects of butyrate with the intervention of GPR43 or Sirt3 inhibitors. In summary, we conclude that butyrate has therapeutic potential for the treatment of ORG. It attenuates high-fat diet-induced ORG and podocyte injuries through the activation of the GPR43-Sirt3 signalling pathway.

Cowl-induced incident shock wave/boundary layer interactions (ISWBLIs) under the influence of shoulder expansion represent one of the dominant phenomena in supersonic inlets. To provide a more comprehensive understanding of how an expansion corner affects the ISWBLI, a detailed experimental and analytical study is performed in a Mach 2.73 flow in this work. Pressure measurement, schlieren photography and surface oil-flow visualisation are used to record flow features, including the pressure distribution, separation extent and surface-flow topological structures. Our results reveal three types of ISWBLIs influenced by the expansion corner. When the shock intensity is weak, the separation is small scale with the expansion waves emanating from the expansion corner. This is the first type of expansion-corner-affected ISWBLI (EC-ISWBLI). When the incident shock wave is strong, large-scale separation occurs, accompanied by the disappearance of expansion waves, forming the second type of EC-SWBLI. The expansion corner induces a ‘lock-in’ effect in which the separation onset is consistently locked near the expansion corner regardless of the incident shock intensity and impingement position. The third type of EC-ISWBLI occurs when the shock is sufficiently strong and the impingement point is close to the expansion corner. In this interaction, the ‘lock-in’ effect ceases to manifest. Moreover, a shock polar-incorporating inviscid model is employed to elucidate the shock patterns. Two criteria are established by combining free interaction theory with this model. The first criterion provides valuable insights into the evolution of separations with a minimal overall pressure rise and the second criterion determines the threshold for the occurrence of the ‘lock-in’ effect.

Epilepsy ranks fourth among neurological diseases, featuring spontaneous seizures and behavioural and cognitive impairments. Although anti-epileptic drugs are currently available clinically, 30 % of epilepsy patients are still ineffective in treatment and 52 % of patients experience serious adverse reactions. In this work, the neuroprotective effect of α-linolenic acid (ALA, a nutrient) in mice and its potential molecular mechanisms exposed to pentylenetetrazol (PTZ) was assessed. The mice were injected with pentetrazol 37 mg/kg, and ALA was intra-gastrically administered for 40 d. The treatment with ALA significantly reduced the overall frequency of epileptic seizures and improved the behaviour impairment and cognitive disorder caused by pentetrazol toxicity. In addition, ALA can not only reduce the apoptosis rate of brain neurons in epileptic mice but also significantly reduce the content of brain inflammatory factors (IL-6, IL-1 and TNF-α). Furthermore, we predicted that the possible targets of ALA in the treatment of epilepsy were JAK2 and STAT3 through molecular docking. Finally, through molecular docking and western blot studies, we revealed that the potential mechanism of ALA ameliorates PTZ-induced neuron apoptosis and neurological impairment in mice with seizures by down-regulating the JAK2/STAT3 pathway. This study aimed to investigate the anti-epileptic and neuroprotective effects of ALA, as well as explore its potential mechanisms, through the construction of a chronic ignition mouse model via intraperitoneal PTZ injection. The findings of this research provide crucial scientific support for subsequent clinical application studies in this field.

The sophisticated relationship between the intake of dietary carbohydrates and host immunity is mediated in large part by the gut microbiota. This comprehensive review explores the multifaceted connections linking human gut microbiota with nondigestible carbohydrate metabolism and immune responses, highlighting the critical importance of this symbiotic relationship in maintaining overall host health. Understanding the mechanisms by which gut microbiota act as a bridge between carbohydrate intake and host immunity has significant implications for precision nutrition strategies and the development of therapeutic interventions.

High temperature and a large salt content weaken the surface hydration ability of clay particles in drilling fluid, reduce zeta potential, agglomerate clay particles, increase particle size, and destroy the stability of drilling mud. A filtrate reducer is required, therefore, to maintain the zeta potential of the clay, prevent the agglomeration of clay particles, and maintain good performance of the drilling mud at high temperature and high salt content. To prepare temperature- and salt-resistant polymer filtrate reducer, a betaine monomer was synthesized and copolymerized with a conventional monomer. A betaine monomer 3-(dimethyl (4-vinyl benzyl) ammonia) propyl sulfonate (DVBAPS) was synthesized and then used to create a copolymer filtrate reducer. The copolymer filtrate reducer, referred to as PAAAND, was prepared by free radical copolymerization with 2-acrylamide-2-methylpropane sulfonic acid, acrylic acid, N-vinyl pyrrolidone, acrylamide, and DVBAPS. The optimum synthesis conditions were determined by single factor evaluation, and the chemical structure of the PAAAND was confirmed by Fourier-transform infrared spectroscopy and 1H nuclear magnetic resonance spectroscopy. Results from particle-size distribution and zeta-potential measurements showed that PAAAND increased the zeta potential of clay particles and the distribution width of particles size, which served to maintain the stability of the drilling mud under high-temperature and high-salt conditions. The results of scanning electron microscopy showed that PAAAND made the filter cake formed by clay particles smoother and denser, which reduced filtration loss. The reduction in filtrate loss continued even after aging at high temperature, and, thus, PAAAND performed better than commercial products.

Adsorption of nanoparticles on minerals affects the fate and transport of nanoparticles directly and is of great significance to many fields, including research into ore deposits, geochemistry, the environment and mineral materials. Whereas many previous studies have been conducted under the equilibrium pH and low solid (mineral) to liquid (nanoparticle suspension) ratio conditions, adsorption processes under initial pH and high solid/liquid ratio conditions may represent many important yet underexamined complex scenarios. To fill in this research gap, the adsorption of gold nanoparticles on illite was investigated experimentally at a relatively high solid/liquid ratio of 5 g L–1 and the effects of initial pH, ionic strength, citrate concentration, temperature and illite particle size were evaluated. The adsorbed amount of gold nanoparticles (from <5% to nearly 100%) increased with increasing ionic strength, temperature and citrate concentration and decreased with increasing pH and illite particle size. The presence of illite resulted in the dynamic evolution of the pH of the suspension, which, along with solution chemistry parameters, controlled the electrostatic interaction of illite and gold nanoparticles. The adsorption results, scanning electron microscopy observations and surface properties of illite suggest that the negatively charged gold nanoparticles were adsorbed predominantly on the positive illite edges through electrostatic interaction. The electrostatic attraction between illite and gold nanoparticles appeared to be strong, supported by the minor amount of desorption. These research findings are expected to provide a valuable reference regarding many critical issues in the geosciences as well as for industrial applications.

Polymers maintain colloidal stability by adsorbing onto the surface of sepiolite particles, and changes in temperature and salinity can affect this process. We chose three typical polymers to investigate their interactions with sepiolite under high-salinity (15 wt.% NaCl) conditions at >180°C. Sepiolite samples were characterized using infrared testing, X-ray diffraction testing, contact angle testing, thermogravimetric testing, filtration loss testing and rheological testing. The experimental results showed that the desorption of the polymers under high-temperature and high-salinity conditions reduces the stability and filtration control of the suspension significantly. Adding polymers to sepiolite suspensions can maintain good stability even after thermal ageing at 240°C. In terms of drilling fluid regulation, sepiolite can play a role in regulating rheological properties, and the interactions between various polymers and sepiolite can be utilized to maintain the stable colloidal state of the drilling fluid. Studying the adsorption behaviour of various types of polymers on the surface of sepiolite under high-temperature and high-salinity conditions has important implications for the design and selection of sepiolite drilling fluid treatment agents.