Previous studies highlighted the health benefits of coffee and tea, but they only focused on the comparisons between different consumptions. Consequently, the association estimate lacked a clear interpretation, as the substitution of beverages and distribution of doses were not explicitly prescribed. We focused on the ‘relative association’ to ascertain the optimal consumption strategy (including total intake and optimal allocation strategy) for coffee, tea and plain water associated with decreased mortality. Self-reported coffee, tea and plain water intake were used from the UK Biobank. Within a compositional data analysis framework, a multivariate Cox model was used to assess the relative associations after adjusting for a range of potential confounders. The lower mortality risk was observed with at least approximately 7–8 drinks/d of total consumption. When the total intake > 4 drinks/d, substituting plain water with coffee or tea was linked to reduced mortality; nevertheless, the benefit was not seen for ≤ 4 drinks/d. Besides, a balanced consumption of coffee and tea (roughly a ratio of 2:3) associated with the lowest hazard ratios of 0·55 (95 % CI 0·47, 0·64) for all-cause mortality, 0·59 (95 % CI 0·48, 0·72) for cancer mortality, 0·69 (95 % CI 0·49, 0·99) for CVD mortality, 0·28 (95 % CI 0·15, 0·52) for respiratory disease mortality and 0·35 (95 % CI 0·15, 0·82) for digestive disease mortality than other combinations. These results highlight the importance of the rational combination of coffee, tea and plain water, with particular emphasis on ensuring adequate total intake, offering more comprehensive and explicit guidance for individuals.

The current study aims to assess associations between trimethylamine N-oxide (TMAO) levels and mortality and to investigate modification effects of genetics. A total of 500 participants from a family-based cohort study were enrolled from 2005 to 2017 and followed up until 2020 in Fangshan District, Beijing, China. Serum TMAO levels were measured using the ELISA kit. The primary outcomes were all-cause mortality and deaths from CVD and stroke. During a median follow-up time of 7·38 years, thirty-eight deaths were recorded, including twenty deaths due to CVD and nineteen deaths due to stroke. Compared with the lowest TMAO quartile group, the HR for all-cause mortality was 1·35 (95 % CI: 0·44, 4·15), 1·65 (95 % CI: 0·58, 4·64) and 2·45 (95 % CI: 0·91, 6·57), respectively, in higher groups. No association was observed between TMAO and CVD mortality. However, compared with the lowest TMAO concentration group, the HR for stroke mortality was 1·93 (95 % CI: 0·40, 9·39), 1·91 (95 % CI: 0·41, 8·96) and 4·16 (95 % CI: 0·94, 18·52), respectively, in higher groups (Pfor trend = 0·046). Furthermore, polygenic risk score (PRS) for longevity modified the association of TMAO with all-cause mortality (Pfor interaction = 0·008). The risk of mortality (HR = 2·20, 95 % CI: 1·06, 4·57) was higher among participants with lower PRS compared with higher PRS (HR = 1·00, 95 % CI: 0·71, 1·40). The study indicates that elevated serum TMAO levels are potentially associated with long-term mortality risk in rural areas of northern China, especially for stroke deaths. Additionally, it provides novel evidence that genetic variations might modify the association.

High gain greater than 106 is crucial for the preamplifiers of joule-class high-energy lasers. In this work, we present a specially designed compact amplifier using 0.5%Nd,5%Gd:SrF2 and 0.5%Nd,5%Y:SrF2 crystals. The irregular crystal shape enhances the gain length of the laser beam and helps suppress parasitic oscillations. The amplified spontaneous emission (ASE) induced by the high gain is analyzed through ray tracing. The balance between gain and ASE is estimated via numerical simulation. The gain spectral characteristics of the two-stage two-pass amplifier are examined, demonstrating the advantages of using different crystals, with bandwidths up to 8 nm and gains over 106. In addition, the temperature and stress distributions in the Nd,Gd:SrF2 crystal are simulated. This work is expected to contribute to the development of high-peak-power ($\ge$terawatt-class) high-energy (joule-class) laser devices.

Eclipta [Eclipta prostrata (L.) L.] is an important tropical weed that has recently emerged as a problematic weed in dry direct-seeded rice (Oryza sativa L.) (DSR) fields in China. Understanding its seed germination biology and ecology is crucial for developing integrated weed management strategies in the DSR system. Laboratory experiments were conducted to investigate seed germination of E. prostrata seeds under varying environmental conditions. Germination was greatest under alternating temperature regimes of 25/15 to 40/30 C, whereas it wa-s significantly reduced at 20/10 C and completely inhibited at 15/5 C. Germination was also fully suppressed under continuous darkness, indicating strong light dependency. Eclipta prostrata seeds tolerated a broad range of pH values (4 to 10) with germination rates consistently greater than 95%. However, germination declined sharply under osmotic potentials, falling below 2% at −0.6 MPa, and being completely inhibited at −0.7 MPa. Seeds also showed moderate salt tolerance, with 50% inhibition at 150 mM NaCl and no germination at 300 mM NaCl. Exposure to radiant heat (>90 C for 5 min) prevented germination, suggesting residue burning may be an effective control measure. Seedling emergence was highest (100%) on the soil surface but declined steeply with increasing burial depth, with no emergence observed beyond 0.5 cm. Similarly, surface application of wheat (Triticum aestivum L.) straw residue (2 to 6 Mg ha−1) significantly reduced seedling emergence and biomass. These findings provide essential insights into E. prostrata germination ecology and offer practical implications for its integrated management in DSR systems.

Within the broad context of design research, joint attention within co-creation represents a critical component, linking cognitive actors through dynamic interactions. This study introduces a novel approach employing deep learning algorithms to objectively quantify joint attention, offering a significant advancement over traditional subjective methods. We developed an optimized deep learning algorithm, YOLO-TP, to identify participants’ engagement in design workshops accurately. Our research methodology involved video recording of design workshops and subsequent analysis using the YOLO-TP algorithm to track and measure joint attention instances. Key findings demonstrate that the algorithm effectively quantifies joint attention with high reliability and correlates well with known measures of intersubjectivity and co-creation effectiveness. This approach not only provides a more objective measure of joint attention but also allows for the real-time analysis of collaborative interactions. The implications of this study are profound, suggesting that the integration of automated human activity recognition in co-creation can significantly enhance the understanding and facilitation of collaborative design processes, potentially leading to more effective design outcomes.

The heating effect of electromagnetic waves in ion cyclotron range of frequencies (ICRFs) in magnetic confinement fusion device is different in different plasma conditions. In order to evaluate the ICRF heating effect in different plasma conditions, we conducted a series of experiments and corresponding TRANSP simulations on the EAST tokamak. Both simulation and experimental results show that the effect of ICRF heating is poor at low core electron density. The decrease in electron density changes the left-handed electric field near the resonant layer, resulting in a significant decrease in the power absorbed by the hydrogen fundamental resonance. However, quite a few experiments must be performed in plasma conditions with low electron density. It is necessary to study how to make ICRF heating best in low electron density plasma. Through a series of simulation scans of the parallel refractive index (n//) of the ICRF antenna, it is concluded that the change of the ICRF antenna n// will lead to the change of the left-handed electric field, which will change the fundamental absorption of ICRF power by the hydrogen minority ions. Fully considering the coupling of ion cyclotron wave at the tokamak boundary and the absorption in the plasma core, optimizing the ICRF antenna structure and selecting appropriate parameters such as parallel refractive index, minority ion concentration, resonance layer position, plasma current and core electron temperature can ensure better heating effect in the ICRF heating experiments in the future EAST upgrade. These results have important implications for the enhancement of the auxiliary heating effect of EAST and other tokamaks.

The incorporation of trace metals into land snail shells may record the ambient environmental conditions, yet this potential remains largely unexplored. In this study, we analyzed modern snail shells (Cathaica sp.) collected from 16 sites across the Chinese Loess Plateau to investigate their trace metal compositions. Our results show that both the Sr/Ca and Ba/Ca ratios exhibit minimal intra-shell variability and small inter-shell variability at individual sites. A significant positive correlation is observed between the shell Sr/Ca and Ba/Ca ratios across the plateau, with higher values being recorded in the northwestern sites where less monsoonal rainfall is received. We propose that shell Sr/Ca and Ba/Ca ratios, which record the composition of soil solution, may be controlled by the Rayleigh distillation in response to prior calcite precipitation. Higher rainfall amounts may lead to a lower degree of Rayleigh distillation and thus lower shell Sr/Ca and Ba/Ca ratios. This is supported by the distinct negative correlation between summer precipitation and shell Sr/Ca and Ba/Ca ratios, enabling us to reconstruct summer precipitation amounts using the Sr/Ca and Ba/Ca ratios of Cathaica sp. shells. The potential application of these novel proxies may also be promising for other terrestrial mollusks living in the loess deposits globally.

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.

This study aimed to compare the clinical outcomes of using refrigerated versus pre-warmed media for preparing time-lapse dishes in in vitro fertilization (IVF). Patients undergoing their first IVF/ICSI cycle were divided into two groups. The control group used pre-warmed culture media, while the experimental group used refrigerated culture media. The osmotic pressure of the culture droplets in both groups was tested. No statistical differences were found between the two groups’ basic data. The proportion of air microbubbles affecting imaging significantly decreased (4.55% vs. 37.97%, P < 0.001) when using pre-warmed media. However, the blastocyst formation rate (56.62% vs. 49.70%, P = 0.046) and total high-quality embryo rate (22.26% vs. 17.06%, P = 0.047) were significantly higher in the refrigerated media group compared to the pre-warmed media group. The higher rate of high-quality embryos in the refrigerated media group might result in a higher single embryo transfer rate (45.10% vs. 18.52%, P = 0.020) and implantation rate (58.23% vs. 34.69%, P = 0.010). From day –1 to day 1, osmolality increased, with the P-3.5 group showing a significant elevation compared to the other three groups. After 5 days of incubation, the osmotic pressure of group R-4.0 was significantly lower than that of groups P-3.5, P-4.0 and P-3.5. In conclusion, refrigerated culture media dishes helped stabilize the osmotic pressure of the culture microenvironment and reduce water evaporation. The refrigerated group showed a higher rate of high-quality embryos and live births, although pre-warmed culture media effectively reduced the occurrence of air microbubbles that affect embryo imaging in the next day’s dishes.

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.

Regenerative involution is crucial for renewing the mammary gland and maximizing milk production. However, the temporal profiles indicators of oxidative status during this phase are still unclear. In this study, Experiment 1 aimed to investigate the dynamic changes in indicators of oxidative status in plasma during regenerative involution. The dairy goats were dried off at 8 weeks (wk) before kidding (−8 wk, n = 14) or −12 wk (n = 6). The blood samples taken at −8, −7, −6, −5, −4, −3, −2, −1 wk, on the day for kidding (0 wk) and the first week after kidding (+1 wk, milk production 1.28 ± 0.31 kg per day). Experiment 2 aimed to investigate the dynamic changes in indicators of oxidative status in mammary cells. Seven selected goats were biopsied for tissue collection and cell isolation at −8, −4, −1, +1 wk (milk production 1.28 ± 0.31 kg per day), respectively. Plasma analysis in Experiment 1 showed an increase in reactive oxygen species (ROS) levels, peaking at −4 wk (P < 0.01). No significant differences were observed between the dry-off treatments (P = 0.36). The activity of superoxide dismutase (SOD) in plasma remained stable from −7 wk to the first week after kidding (+1 wk), while glutathione peroxidase (GSH-Px) activity peaked at −4 wk. An increased catalase activity was observed at +1 wk (P < 0.01), indicating its response to lactation. In Experiment 2, an increase in ROS levels in isolated mammary cells was observed at −4 wk, while SOD, GSH-Px, and malondialdehyde levels in tissue homogenates rose around kidding (P < 0.01). The dynamic change of the oxidative status suggests that targeted antioxidant strategies would be helpful for regenerative involution of mammary gland in ruminants.

This paper introduces a novel ray-tracing methodology for various gradient-index materials, particularly plasmas. The proposed approach utilizes adaptive-step Runge–Kutta integration to compute ray trajectories while incorporating an innovative rasterization step for ray energy deposition. By removing the requirement for rays to terminate at cell interfaces – a limitation inherent in earlier cell-confined approaches – the numerical formulation of ray motion becomes independent of specific domain geometries. This facilitates a unified and concise tracing method compatible with all commonly used curvilinear coordinate systems in laser–plasma simulations, which were previously unsupported or prohibitively complex under cell-confined frameworks. Numerical experiments demonstrate the algorithm’s stability and versatility in capturing diverse ray physics across reduced-dimensional planar, cylindrical and spherical coordinate systems. We anticipate that the rasterization-based approach will pave the way for the development of a generalized ray-tracing toolkit applicable to a broad range of fluid simulations and synthetic optical diagnostics.

A reduced dispersion relation for multibeam laser–plasma instability is derived. The dispersion relation includes the combined effects of self-coupling and interaction with other beams by sharing a common scattered light (SL modes) and by sharing a common plasma wave (SP modes). The latter two have the most prominent collective effects of all. We have solved the dispersion relation numerically for stimulated Raman scattering, and set different beam configurations and polarizations to discuss the spatial distributions of the temporal growth rate. The instability in the beam overlapping region is complicated, but there are still a few simple rules that govern the system, such as the dominancy of SL modes and subdominancy of backscattering and SP modes. The maximum growth rate always occurs at these special modes, or a new mode formed by combining two or three of the special modes. The reduced model provides us with the ability to understand the underlying physics of multibeam instabilities under general laser and plasma conditions.

This paper presents an investigation of the secondary saturation characteristics of a HfTe2 saturable absorber. Pulse energies of 5.85 and 7.4 mJ were demonstrated with a high-order Hermite–Gaussian (HG) laser and a vortex laser, respectively, using alexandrite as the gain medium. To the best of our knowledge, these are the highest pulse energies directly generated with HG and vortex lasers. To broaden the applications of high-energy pulsed HG and vortex lasers, wavelength tuning in the region of 40 nm was achieved using an etalon.