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Analyses of datasets from manned research flights that penetrated hurricane eyes and tropical cyclone (TC) damage surveys strongly suggest the existence of tornado-scale vortices in the turbulent boundary layer of the TC eyewall. However, their small horizontal scale, their fast movement, and the associated severe turbulence make the tornado-scale vortex very difficult to observe directly. To understand tornado-scale vortices in the TC eyewall and their influence on the TC vortex, mesoscale rainbands, and convective clouds, a numerical experiment including seven nested domains with the smallest horizontal grid interval of 37 m is conducted to perform a large eddy simulation (LES) with the Advanced Weather Research and Forecast (WRF) model. We show that most of the observed features associated with tornado-scale vortices can be realistically simulated in the WRF-LES framework. The numerical simulation confirms the existence of simulated tornado-scale vortices in the turbulent boundary layer of the TC eyewall. Our numerical experiment suggests that tornado-scale vortices are prevalent at the inner edge of the intense eyewall convection.

Parameterizing momentum flux under light wind conditions poses a challenge in the development of air-sea flux parameterizations. In this study, we evaluated some modifications to air–sea momentum flux parameterizations under light wind conditions, including surface layer effects (smooth flow and capillary waves), gustiness effects, and non-local effects. By coupling these modifications into the Community Atmosphere Model version 6 (CAM6), we conducted six sensitivity experiments to assess their direct impact on air–sea momentum flux under light wind conditions and their indirect impact on the simulation performance in low-latitude sea areas. During the iteration process in model, the complex negative feedback between wind speed and momentum flux led to differences in momentum flux patterns among experiments in the three key sea areas and inconsistency between offline and online test results. Based on the comprehensive evaluation metric Distance between Indices of Simulation and Observation (DISO), we assessed the simulation performance of experiments in the entire low-latitude sea area, the three key sea areas, and under light wind conditions. The discrepancy in the 10-m wind speeds deviation between light wind conditions and medium to strong wind conditions led to a reversal in the ranking of the simulation performance of the six experiments under light wind conditions compared to the entire low-latitude sea area.

This study investigated two random forest (RF) models for the non‐iterative parametrization of surface‐layer turbulent fluxes: (a) the RF scheme, a calculation model that is directly trained using correlated variables, and (b) the RF_Li10 scheme, a random forest correction model based on the Li10 scheme (Li et al., 2010, https://doi.org/10.1007/s10546-010-9523-y). A comparison between these two new models and the Li10 scheme against an iterative scheme revealed the hierarchy of maximum relative errors in estimating stability parameters, as well as momentum and heat transfer coefficients. This hierarchy is as follows: the Li10 scheme is the greatest, followed by the RF scheme, with the RF_Li10 scheme exhibiting the least errors. Plain Language Summary The computation module for surface‐layer turbulent fluxes is an essential component of numerical weather prediction models. Based on the Monin‐Obukhov Similarity Theory, many parameterization schemes for surface fluxes have been proposed. With the advancement of artificial intelligence, machine learning methods have been applied in meteorology. This study applies the RF model in machine learning to the parametrization of surface‐layer turbulent fluxes. The RF scheme directly calculates the stability parameter after training, and the RF_Li10 scheme is designed to refine the stability parameter derived from the Li10 scheme, by utilizing the RF algorithm for this correction process. In addition, the two new schemes have also been used to calculate the momentum and heat transfer coefficients. The values calculated from the Li10 scheme, RF scheme, and RF_Li10 scheme are compared with the values calculated from the iterative scheme. Under different surface roughness conditions, the average relative errors of the stability parameter obtained from the Li10 scheme, RF scheme, and RF_Li10 scheme are 3.17%, 3.42%, and 0.17%, respectively; the maximum average relative errors of the stability parameter are 5.67%, 3.52%, and 0.52% respectively. Key Points Two Random Forest models (RF and RF_Li10) for the non‐iterative parametrization of near‐surface turbulent fluxes are proposed Compared to the iterative schemes and existing parameterization schemes, the RF_Li10 scheme exhibits the lowest calculation error Compared to the iterative schemes, the RF scheme and RF_Li10 scheme reduce the computation time by 91.0% and 78.4%, respectively

One of the most important characteristics of porphyry copper deposits (PCDs) is the type and distribution pattern of alteration zones which can be used for screening and recognizing these deposits. Hydrothermal alteration minerals with diagnostic spectral absorption properties in the visible and near-infrared (VNIR) through the shortwave infrared (SWIR) regions can be identified by multispectral and hyperspectral remote sensing data. Six Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands in SWIR have been shown to be effective in the mapping of Al-OH, Fe-OH, Mg-OH group minerals. The five VNIR bands of Landsat-8 (L8) Operational Land Imager (OLI) are useful for discriminating ferric iron alteration minerals. In the absence of complete hyperspectral coverage area, an opportunity, however, exists to integrate ASTER and L8-OLI (AO) to compensate each other’s shortcomings in covering area for mineral mapping. This study examines the potential of AO data in mineral mapping in an arid area of the Duolong porphyry Cu-Au deposit(Tibetan Plateau in China) by using spectral analysis techniques. Results show the following conclusions: (1) Combination of ASTER and L8-OLI data (AO) has more mineral information content than either alone; (2) The Duolong PCD alteration zones of phyllic, argillic and propylitic zones are mapped using ASTER SWIR bands and the iron-bearing mineral information is best mapped using AO VNIR bands; (3) The multispectral integration data of AO can provide a compensatory data of ASTER VNIR bands for iron-bearing mineral mapping in the arid and semi-arid areas.

Background Monozygotic twins (MZTs) are associated with high risks of maternal and fetal complications. Even with the widely used elective single embryo transfer (SET), the risk of MZTs following assisted reproductive technology (ART) treatments remains. However, most studies of MZTs focused on the relevant etiology, with few studies describing pregnancy and neonatal outcomes. Methods This retrospective cohort study included 19,081 SET cycles resulting from in-vitro fertilization (IVF), intracytoplasmic sperm injection (ICSI), preimplantation genetic testing (PGT) and testicular sperm aspiration (TESA) performed between January 2010 and July 2020 in a single university-based center. A total of 187 MZTs were included in this investigation. The main outcome measures were the incidence, pregnancy and neonatal outcomes of MZTs. Multivariate logistic regression analysis was performed to figure out the risk factors for pregnancy loss. Results The overall rate of MZTs from ART treatment in SET cycles was 0.98%. No significant difference was found in the incidence of MZTs among the four groups ( p  = 0.259). The live birth rate of MZTs in the ICSI group (88.5%) was significantly more favorable than in the IVF, PGT and TESA groups (60.5%, 77.2% and 80%, respectively). IVF resulted in a significantly increased risk of pregnancy loss (39.4%) and early miscarriage (29.5%) in MZT pregnancies compared to ICSI (11.4%, 8.5%), PGT (22.7%, 16.6%) and TESA (20%, 13.3%). The total rate of twin-to-twin transfusion syndrome (TTTS) in MZTs was 2.7% (5/187); however, the TESA group had the highest rate at 20% and was significantly higher than the PGT group ( p  = 0.005). The four ART groups had no significant effect on the occurrence of congenital abnormalities or other neonatal outcomes in newborns from MZT pregnancies. Multivariate logistic regression analysis revealed that infertility duration, cause of infertility, the total dose of Gn used, history of miscarriages, and the number of miscarriages were not related to the risk of pregnancy loss ( p  > 0.05). Conclusions The rate of MZTs was similar among the four ART groups. The pregnancy loss and the early miscarriage rate of MZTs was increased in IVF patients. Neither the cause of infertility nor the history of miscarriage was correlated with the risk of pregnancy loss. MZTs in the TESA group had a higher risk of TTTS, placental effects influenced by sperm and paternally expressed genes may play a role. However, due to the small total number, studies with larger sample sizes are still needed to validate these result. Pregnancy and neonatal outcomes of MZTs after PGT treatment seem to be reassuring but the duration of the study was short, and long-term follow-up of the children is needed.

Inflammatory bowel disease (IBD) is a chronic and relapsing intestinal inflammatory condition with no effective treatment. Probiotics have gained wide attention because of their outstanding advantages in intestinal health issues. In previous studies, a novel soluble protein, HM0539, which is derived from GG (LGG), showed significant protective effects against murine colitis, but no clear precise mechanism for this effect was provided. In this study, we hypothesized that the protective function of HM0539 might be derived from its modulation of the TLR4/Myd88/NF-κB axis signaling pathway, which is a critical pathway widely involved in the modulation of inflammatory responses. To test this hypothesis, the underlying anti-inflammatory effects and associated mechanisms of HM0539 were determined both in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages and in dextran sulfate sodium (DSS)-induced murine colitis. Our results showed that HM0539 inhibited the expression of cyclooxygenase-2 (COX-2) and the expression inducible nitric oxide synthase (iNOS) by down-regulating the activation of their respective promoter, and as a result this inhibited the production of prostaglandin E2 (PGE2) and nitric oxide (NO). Meanwhile, we demonstrated that HM0539 could ultimately modulate the activation of distal NF-κB by reducing the activation of TLR4 and suppressing the transduction of MyD88. However, even though the overexpression of TLR4 or MyD88 obviously reversed the effect of HM0539 on LPS-induced inflammation, HM0539 still retained some anti-inflammatory activity. Consistent with the findings, we found that HM0539 inhibited to a great extent the production of inflammatory mediators associated with the suppression of the TLR4/Myd88/NF-κB axis activation in colon tissue. In conclusion, HM0539 was shown to be a promising anti-inflammatory agent, at least in part through its down-regulation of the TLR4-MyD88 axis as well as of the downstream MyD88-dependent activated NF-κB signaling, and hence might be considered as a potential therapeutic option for IBD.

This study evaluates the uncertainties of turbulent flux calculation using eddy covariance (EC) and wavelet analysis (WA) methods. First, a non‐stationary data set is concocted by adding periodic waves and random perturbations which mimic the large eddies, turbulent intermittency, and asymmetry into an observational stationary data set, and the theoretical “true” fluxes are used to quantitatively evaluate the accuracy of these methods. Results show that EC and Morlet‐wavelet generate biases ranging 50%–100% of the “true” values at different non‐stationarity grades, whereas the Mexican hat (Mexhat) wavelet has a bias of about half of them. Furthermore, there is a high correlation of the Mexhat‐derived fluxes to the benchmark values, the regression slopes of the values of these two can be improved to almost 1 by adding a correction coefficient. The results suggest the potential of using the Mexhat‐wavelet method to calculate turbulent fluxes with high accuracy under non‐stationary conditions. Plain Language Summary Eddy covariance (EC) method is the well‐accepted technique to calculate turbulent flux under stationary conditions. However, the observational turbulence data sometimes show non‐stationarity, and in this case, the EC method is not applicable and wavelet analysis (WA) is frequently used. However, because turbulent fluxes are calculated values, and there are no true flux measurements, the accuracy of WA‐calculated fluxes remains unknown. In this study, we constructed a non‐stationary data set and used their theoretical true values to evaluate the accuracy of EC and WA methods in flux calculation under non‐stationary conditions. It is found that EC and Morlet‐wavelet bias 50%–100% of the true values at different non‐stationarity grades, while the Mexican hat (Mexhat) wavelet has the bias about half of them. Besides, there is a high correlation of the Mexhat‐derived fluxes to the true values, and Mexhat‐derived fluxes can be corrected to near true values by adding a correction coefficient. Therefore, the Mexhat‐wavelet method has the potential to be used to calculate turbulent fluxes under non‐stationary conditions. Key Points A method to concoct non‐stationary data series is proposed Eddy covariance and wavelet analysis methods underestimate turbulent momentum flux under non‐stationary condition by about 50% Mexican hat wavelet method has the potential to accurately calculate flux of non‐stationary turbulence after correction

Anxiety is a future-oriented unpleasant and negative mental state induced by distant and potential threats. It could be subdivided into momentary state anxiety and stable trait anxiety, which play a complex and combined role in our mental and physical health. However, no studies have systematically investigated whether these two different dimensions of anxiety share a common or distinct topological mechanism of human brain network. In this study, we used macro-scale human brain morphological similarity network and functional connectivity network as well as their spatial and temporal variations to explore the topological properties of state and trait anxiety. Our results showed that state and trait anxiety were both negatively correlated with the coefficient of variation of nodal efficiency in the left frontal eyes field of volume network; state and trait anxiety were both positively correlated with the median and mode of pagerank centrality distribution in the right insula for both static and dynamic functional networks. In summary, our study confirmed that state and trait anxiety shared common human brain network topological mechanisms in the insula and the frontal eyes field, which were involved in preliminary cognitive processing stage of anxiety. Our study also demonstrated that the common brain network topological mechanisms had high spatiotemporal robustness, and would enhance our understanding of human brain temporal and spatial organization.

This study presents a rapid and highly sensitive method for the determination of trace rubidium (Rb) and cesium (Cs) in high-salinity brines using inductively coupled plasma mass spectrometry (ICP-MS) equipped with an all-matrix sampling (AMS) device. The AMS system achieves online gas dilution by vertically introducing argon gas into the brine sample flow, effectively reducing the severe matrix suppression effect caused by 35 g·L −1 salinity to an intermediate level. Experimental results demonstrated that the signal suppression induced by coexisting cations (K + , Na + , Ca 2+ , Mg 2+ ) in actual brine samples was minimal (< 1.5%), thereby eliminating the need for conventional matrix matching or standard addition approaches. Accurate quantification was achieved through a straightforward calibration process based on standard curves (Rb: 5–400 μg·L −1 ; Cs: 5–400 μg·L −1 ; R 2  > 0.999), enhanced by dynamic internal standard correction using yttrium (Y) and rhodium (Rh), along with optimized instrument parameters (RF power and nebulizer gas flow rate). The method demonstrates excellent limits of detection (LOD: 0.039 μg·L −1 for Rb; 0.005 μg·L −1 for Cs), high precision (RSD < 5%), and acceptable recovery rates (85%–108%). The accuracy was further validated through comparison with AAS standard addition for high-concentration samples (> 200 μg·L −1 ), yielding consistent recoveries (98.6% –114%) and inter-method deviations ≤ 12.2%. Additionally, the simplification of the sample pretreatment procedure—from a traditional multi-step dilution to a single-step dilution without acid-washed containers—enhances analytical efficiency by over 70%. This approach provides a robust, sensitive, and operationally efficient solution for the analysis of extreme high-salinity environmental samples.

The advancement of Numerical Weather Prediction (NWP) is pivotal for enhancing high-impact weather forecasting and warning systems. However, due to the high spatial and temporal inhomogeneity, the moisture field is difficult to describe by initial conditions in NWP models, which is the essential thermodynamic variable in the simulation of various physical processes. Data Assimilation techniques are central to addressing these challenges, integrating observational data with background fields to refine initial conditions and improve forecasting accuracy. This study evaluates the effectiveness of integrating observations from the Fengyun-4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) and ground-based microwave radiometer (MWR) in forecasts and mechanism analysis of a heavy rainfall event in the Kaifeng region of central China. Our findings reveal that jointly assimilating AGRI radiance and MWR data significantly enhances the model’s humidity profile accuracy across all atmospheric layers, resulting in improved heavy rainfall predictions. Analysis of the moisture sources indicates that the storm’s water vapor predominantly originates from westward air movement ahead of a high-altitude trough, with sustained channeling towards the rainfall zone, ensuring a continuous supply of moisture. The storm’s development is further facilitated by a series of atmospheric processes, including the interplay of high and low-level vorticity and divergence, vertical updrafts, the formation of a low-level jet, and the generation of unstable atmospheric energy. Additionally, this study examines the influence of Tai-hang Mountain’s terrain on precipitation patterns in the Kaifeng area. Our experiments, comparing a control setup (CTL) with varied terrain heights, demonstrate that reducing terrain height by 50–60% significantly decreases precipitation coverage and intensity. In contrast, increasing terrain height enhances precipitation, although this effect plateaus when the elevation increase exceeds 100%, closely mirroring the precipitation changes observed with a 75% terrain height increment.