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Abstract Amorphous powder cores are promising components for next-generation power electronics. However, they present inherent challenges of internal air gaps and stresses during cold compaction, which significantly deteriorate soft magnetic properties. Here, we report the formation of a local adaptive insulation structure of biconcave lens in amorphous powder cores by ultrasonic rheomolding. Consequently, compared with conventional cold-compacted powder cores, the ultrasonic rheomolded powder cores offer significant simultaneous improvements in the permeability from 31.3–32.4 to 41.8–43.3 and the direct-current bias performance from 69.4–69.7% to 87.4–87.8% (7960 A/m), thereby overcoming the trade-off between permeability and direct-current bias performance. In particular, their core losses are as low as 13.73–15.45 kW/m3, approximately one twentieth of that of the cold-compacted powder cores (282.84–304.03 kW/m3) at a magnetic field of 100 mT and 100 kHz. The biconcave-lens insulation structure can effectively buffer the impact of high mechanical stress on the magnetization of magnetic powder particles, allowing for the ultrasonic rheomolded powder cores to maintain better magnetization efficiency and consequently resulting in excellent soft magnetic properties under the cooperative effect of very low internal stresses and low porosity. The ultrasonic rheomolded powder cores can be used as alternative core components in next generation miniaturized power electronics.

Abstract We report multi-differential measurements of strange hadron production ranging from mid- to target-rapidity in Au+Au collisions at a center-of-momentum energy per nucleon pair of s NN $$ \sqrt{s_{\textrm{NN}}} $$ = 3 GeV with the STAR experiment at RHIC. K S 0 $$ {K}_S^0 $$ meson and Λ hyperon yields are measured via their weak decay channels. Collision centrality and rapidity dependences of the transverse momentum spectra and particle ratios are presented. Particle mass and centrality dependence of the average transverse momenta of Λ and K S 0 $$ {K}_S^0 $$ are compared with other strange particles, providing evidence of the development of hadronic rescattering in such collisions. The 4π yields of each of these strange hadrons show a consistent centrality dependence. Discussions on radial flow, the strange hadron production mechanism, and properties of the medium created in such collisions are presented together with results from hadronic transport and thermal model calculations.

Synchronized positioning and mapping techniques based on multi-line LIDAR are mainly used for mobile platforms that require high-precision positioning, such as UAVs and self-driving cars. However, multi-line LiDAR is limited by vertical field of view and vertical angular resolution, which can affect the vertical accuracy of attitude estimation. In this paper, we aim to extract the ground information in the environment and fuse it into a factor map to constrain the vertical accuracy of the attitude. Different from the traditional geometric information-based ground plane segmentation, this paper utilizes point cloud distribution information to extract the ground cloud and uses high-confidence ground features to constrain the attitude drift by considering their distribution weights. Finally, the laser range factor, ground constraint factor and closed-loop factor are integrated under the factor graph optimization framework. The effectiveness of the method is validated on a self-constructed dataset.

Ultra-wideband (UWB) technology stands out among numerous indoor positioning techniques due to its high operating frequency, low interception capability, resistance to multipath effects, and strong penetration. The UWB uses the time-of-arrival (TOA) to estimate the distance between the transmitter and receiver anchors in centimeter accuracy. However, in complex indoor positioning environments, obstacles such as walls, glass windows, metal plates, and wooden doors may block and reflect signals, inevitably causing non-line-of-sight (NLOS) errors that significantly affect positioning accuracy. The NLOS signal has lower signal energy due to the reflections. Thus, the channel impulse responses (CIR) from NLOS and LOS are different. To address the NLOS signal identification issue in UWB positioning, we utilize UWB CIR data collected from various positioning scenarios as the data source. CIR waveform input features are provided for the NLOS signal recognition model, and four machine learning models—Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), K-Nearest Neighbors (KNN), and XGBoost—are trained and optimized for NLOS signal recognition. The aim of the study is to analyze the performance of different machine learning algorithms for NLOS signal recognition in UWB indoor localization using these features. Experimental results indicate that machine learning-based NLOS signal recognition algorithms can achieve an accuracy of approximately 77.46%, precision of 80.46%, and an F1 score of 0.81. Among the four models, the XGBoost model demonstrates generally better recognition performance.

With the evolution of satellite video technology, the domain has garnered increasing attention. Concurrently, advancements in deep learning have yielded numerous outcomes in target detection. This paper introduces a novel method for detecting moving targets, offering a broader detection range compared to traditional satellite video techniques, facilitating orbital target recognition from dual panchromatic image strips. Our experimental setup on the Taijing-IV 01 satellite, launched on February 27, 2022, successfully acquired two image strips separated by one second. These strips contain speed and directional information of moving objects, extractable through the frame differencing technique. We propose combining frame differencing with lightweight deep learning for target detection, extracting regions of interest (ROIs) to focus on areas with potential moving targets. This approach reduces the workload of wholeimage target detection, decreasing data processing volume by 89%. By optimizing the YOLOv8 network and using techniques like feature map fusion of low-level and high-resolution features, we enhance sensitivity to small targets. Consequently, the model size is reduced by 79%, the mean Average Precision (mAP) increases by approximately 1.8% and 4.5%, and detection speed rises by 26%. This method introduces a new paradigm in remote sensing data services, facilitating rapid acquisition and real-time transmission of positions and image information of moving targets to the ground. This significantly reduces bandwidth requirements for transmitting remote sensing information, presenting a novel strategy for data acquisition and processing in large-scale Earth observation systems and geoscientific applications.

In this paper, we explore different prognostic methods to account for skin sea surface temperature diurnal variations in a coupled ocean–atmosphere regional model of the Mediterranean Sea. Our aim is to characterise the sensitivity of the considered methods with respect to the underlying assumption of how the solar radiation shapes the warm layer of the ocean. All existing prognostic methods truncate solar transmission coefficient at a warm-layer reference depth that is constant in space and time; instead, we implement a new scheme where this latter is estimated from a chlorophyll dataset as the e-folding depth of solar transmission, which thus allows it to vary in space and time depending on seawater's transparency conditions. Comparison against satellite data shows that our new scheme, compared to the one already implemented within the ocean model, improves the spatially averaged diurnal signal, especially during winter, and the seasonally averaged one in spring and autumn, while showing a monthly basin-wide averaged bias smaller than 0.1 K year-round. In April, when most of the drifters' measurements are available, the new scheme mitigates the bias during nighttime, keeping it positive but smaller than 0.12 K during the rest of the monthly averaged day. The new scheme implemented within the ocean model improves the old one by about 0.1 K, particularly during June. All the methods considered here showed differences with respect to objectively analysed profiles confined between 0.5 K during winter and 1 K in summer for both the eastern and the western Mediterranean regions, especially over the uppermost 60 m. The new scheme reduces the RMSE on the top 15 m in the central Mediterranean for summertime months compared to the scheme already implemented within the ocean model. Overall, the surface net total heat flux shows that the use of a skin sea surface temperature (SST) parameterisation brings the budget about 1.5 W m−2 closer to zero on an annual basis, despite all simulations showing an annual net heat loss from the ocean to the atmosphere. Our “chlorophyll-interactive” method proved to be an effective enhancement of existing methods, its strength relying on an improved physical consistency with the solar extinction implemented in the ocean component.

Satellite remote sensing of sea surface chlorophyll products sometimes yields a significant amount of sporadic missing data due to various variables, such as weather conditions and operational failures of satellite sensors. The limited nature of satellite observation data impedes the utilization of satellite data in the domain of marine research. Hence, it is highly important to investigate techniques for reconstructing satellite remote sensing data to obtain spatially and temporally uninterrupted and comprehensive data within the desired area. This approach will expand the potential applications of remote sensing data and enhance the efficiency of data usage. To address this series of problems, based on the demand for research on the ecological effects of multiscale dynamic processes in the South China Sea, this paper combines the advantages of the optimal interpolation (OI) method and SwinUnet and successfully develops a deep-learning model based on the expected variance in data anomalies, called OI-SwinUnet. The OI-SwinUnet method was used to reconstruct the MODIS chlorophyll-a concentration products of the South China Sea from 2013 to 2017. When comparing the performances of the data-interpolating empirical orthogonal function (DINEOF), OI, and Unet approaches, it is evident that the OI-SwinUnet algorithm outperforms the other algorithms in terms of reconstruction. We conduct a reconstruction experiment using different artificial missing patterns to assess the resilience of OI-SwinUnet. Ultimately, the reconstructed dataset was utilized to examine the seasonal variations and geographical distribution of chlorophyll-a concentrations in various regions of the South China Sea. Additionally, the impact of the plume front on the dispersion of phytoplankton in upwelling areas was assessed. The potential use of reconstructed products to investigate the process by which individual mesoscale eddies affect sea surface chlorophyll is also examined. The reconstructed daily chlorophyll-a dataset is freely accessible at https://doi.org/10.5281/zenodo.10478524 (Ye et al., 2024).

We report on the charged-particle multiplicity dependence of net-proton cumulant ratios up to sixth order from s=200 GeV p+p collisions at the Relativistic Heavy Ion Collider (RHIC). The measured ratios C4/C2, C5/C1, and C6/C2 decrease with increased charged-particle multiplicity and rapidity acceptance. Neither the Skellam baselines nor PYTHIA8 calculations account for the observed multiplicity dependence. In addition, the ratios C5/C1 and C6/C2 approach negative values in the highest-multiplicity events, which implies that thermalized QCD matter may be formed in p+p collisions.

In this study, a Ni50.4Ti49.6 shape memory alloy (SMA) was fabricated by selective laser melting (SLM), and it is found that heat treatments were effective to change the phase transformation behavior, microstructure, and superelasticity under compression for SLM Ni50.4Ti49.6. Detailed results based on EBSD demonstrated that, for SLM Ni50.4Ti49.6 during solid solution and aging (450 °C) treatment, the ultrafine cellular and columnar grains (∼16.5 μm) in as-fabricated Ni50.4Ti49.6 became equiaxed grains (∼70.2 μm), and the frequency of low-angle grain boundaries (26.7%→13.5%) and kernel average misorientation (0.37 → 0.21) decreased. The SEM and TEM analyses show that Ti-rich Ti2Ni/Ti4Ni2Ox and Ni-rich Ni4Ti3 precipitate phases were formed in the matrix simultaneously. After solid solution treatment, the size and distribution of Ti2Ni/Ti4Ni2Ox almost unchanged with aging temperature increasing from 350 °C to 550 °C, however, the size of Ni4Ti3 in aging-treated NiTi samples increased with aging temperature obviously, and it is interesting to find that the distribution of Ni4Ti3 became uneven and dislocation networks were formed in the matrix when the aging treatment reached up to 550 °C, which originated from the internal stress generated by supersaturated Ni atoms. Furthermore, the results of superelasticity for aging-treated NiTi demonstrated that the characteristics of Ni4Ti3 precipitate phase were powerful to influence the process of superelasticity decay/fatigue instead of determining the ultimately recovery strain after 10 compressive cycles. The aging-treated NiTi with evenly-distributed, high-density, and relatively-small Ni4Ti3 precipitate phase shows minimum recovery strain at 1st cycle compression and best superelasticity stability among three aging-treated NiTi, which was attributed to strong obstruction effect of these Ni4Ti3 precipitate for the occurrence of stress-induced martensitic transformation process and formation of dislocations. In contrast, the aging-treated NiTi with unevenly-distributed and low-density Ni4Ti3 precipitate shows maximum recovery strain at 1st cycle compression and worst superelasticity stability. These results in this work can bring some meaningful insights into tailoring the microstructure and superelasticity of SLM NiTi SMAs.

This paper investigates the dynamic modeling and performance analysis of the 2PRU-PUU reconfigurable parallel mechanism (RPM); here, P, R, and U denote the prismatic, revolute, and universal joints, respectively. By altering one of the rotation axes of the reconfigurable universal joint in limb 3, the mechanism can be switched into two operation modes, 1R2T and 2R1T. The authors resort to the Lagrangian equations of the first kind to derive the dynamic model of the 2PRU-PUU RPM. The optimal driving force distribution is determined to solve the problem of the non-uniqueness solution in dynamic analysis. The dynamic formulations are verified with the results obtained in ADAMS software. The dynamic manipulability ellipsoid index, which offers a quantitative assessment of the ability in manipulating the end effector, is used to assess the dynamic performance of the mechanism. Then, the distribution characteristics of the rotational and translational dynamic performance of the RPM are derived.

We report the first measurements of cumulants, up to 4th order, of deuteron number distributions and proton-deuteron correlations in Au+Au collisions recorded by the STAR experiment in phase-I of Beam Energy Scan (BES) program at the Relativistic Heavy Ion Collider. Deuteron cumulants, their ratios, and proton-deuteron mixed cumulants are presented for different collision centralities covering a range of center-of-mass energy per nucleon pair sNN=7.7 to 200 GeV. It is found that the cumulant ratios at lower collision energies favor a canonical ensemble over a grand canonical ensemble in thermal models. An anti-correlation between proton and deuteron multiplicity is observed across all collision energies and centralities, consistent with the expectation from global baryon number conservation. The UrQMD model coupled with a phase-space coalescence mechanism qualitatively reproduces the collision-energy dependence of cumulant ratios and proton-deuteron correlations.

The chiral magnetic effect (CME) is a phenomenon that arises from the QCD anomaly in the presence of an external magnetic field. The experimental search for its evidence has been one of the key goals of the physics program of the Relativistic Heavy-Ion Collider. The STAR Collaboration has previously presented the results of a blind analysis of isobar collisions (_{44}^{96}Ru+_{44}^{96}Ru, _{40}^{96}Zr+_{40}^{96}Zr) in the search for the CME. The isobar ratio (Y) of CME-sensitive observable, charge separation scaled by elliptic anisotropy, is close to but systematically larger than the inverse multiplicity ratio, the naive background baseline. This indicates the potential existence of a CME signal and the presence of remaining nonflow background due to two- and three-particle correlations, which are different between the isobars. In this postblind analysis, we estimate the contributions from those nonflow correlations as a background baseline to Y, utilizing the isobar data as well as Heavy Ion Jet Interaction Generator simulations. This baseline is found consistent with the isobar ratio measurement, and an upper limit of 10% at 95% confidence level is extracted for the CME fraction in the charge separation measurement in isobar collisions at sqrt[s_{NN}]=200 GeV.

The differential cross section for Z0 production, measured as a function of the boson's transverse momentum (pT), provides important constraints on the evolution of the transverse momentum dependent parton distribution functions (TMDs). The transverse single spin asymmetry (TSSA) of the Z0 is sensitive to one of the polarized TMDs, the Sivers function, which is predicted to have the opposite sign in p+p →W/Z+X from that which enters in semi-inclusive deep inelastic scattering. In this Letter, the STAR Collaboration reports the first measurement of the Z0/γ⁎ differential cross section as a function of its pT in p+p collisions at a center-of-mass energy of 510 GeV, together with the Z0/γ⁎ total cross section. We also report the measurement of Z0/γ⁎ TSSA in transversely polarized p+p collisions at 510 GeV.

An Al-7Si-1.5Cu-Mg alloy was synthesized through the modification of a commercial A356 alloy with the inclusion of alloying elements. This alloy underwent a treatment regime comprising solid solution, cryogenic treatment, and ageing. The results indicate that cryogenic treatment increased nucleation rate of precipitates, which increases the number of precipitates and reduces their sizes, ultimately improving the mechanical properties and reduce secondary dendrite arm spacing of the alloy. Under the optimal treatment conditions (solid solution at 520 °C for 10 hours, followed by deep cooling for 48 hours, and ageing at 160 °C for 10 hours), the secondary dendrite arm spacing of the alloy was reduced by approximately 37,5 %, exhibiting hardness of 102,8 HV and plasticity of 4,2 %.

The hollow slender shaft is characterized by intricate component features such as a significant depth-to-diameter ratio, variable cross-sections, and non-uniform thin walls. Uneven deformation of the hollow slender shaft during deformation results in degradation of service performance. In this study, the deformation uniformity is explored from a microscopic point of view, the numerical simulation model of dynamic recrystallization of 6061 aluminum alloy is established with the DEFORM-3D software. And grain evolution during the aluminum alloy extrusion process was theoretically analyzed using the cellular automata.

ABSTRACT: Effects of replacing canola meal with dehulled hemp meal in the diet of lactating dairy cows on the dry matter intake (DMI), milk production, milk fatty acid profile, blood metabolites, total-tract nutrient digestibility, and transfer of cannabinoids were determined in 12 lactating, nonpregnant Holstein cows. These cows were used in a 3 × 3 Latin square design with three 3-wk experimental periods consisting of 2 wk of adaptation and 1 wk of sampling. Cows received basal partial mixed rations supplemented with either 15% dry matter (DM) canola meal (CM15), 15% DM dehulled hemp meal (HM15), or 7.5% DM dehulled hemp meal and 7.5% DM canola meal (CM7.5HM7.5). Diets were formulated to be isoenergetic and isonitrogenous, but the HM15 and CM7.5HM7.5 diets contained, on average 1.2 percentage units more crude protein (CP) that the CM15 diet. The CP of the dehulled hemp meal contained less soluble protein than that of canola meal. Hence, the intake of soluble protein did not differ among diets. Canola meal contained less crude fat than hemp seed meal (3.46% vs. 8.25% DM). The lipid fraction of canola meal fat contained more oleic acid (C18:1 cis-9; 47.3 vs. 14.9 g/100 g of fatty acids, FA) and vaccenic acid (18:1 cis-11; 13.7 vs. 1.2 g/100 g of FA) and less linoleic acid (C18:2n-6; 21.9 vs. 55.7 g/100 g of FA) and α linolenic acid (C18:3n-3; 3.2 vs. 8.9 g/100 g of FA) than the lipid fraction of hemp seed meal. The hemp seed meal contained 4.9 µg/g cannabidiol, 5.1 µg/g cannabidiolic acid, and 0.1 µg/g tertahydroxycannabinolic acid A. Treatments did not differ in DMI, yields of milk, milk protein and milk fat, total-tract neutral detergent fiber digestibility, and blood plasma concentrations of β-hydroxybutyrate and nonesterified FA. Apparent total-tract DM digestibility was lowest in the HM15 treatment, whereas the CP digestibility and the concentrations of urea in blood, urine, and milk were lowest in the CM15 treatment. Cannabinoids were not detected in urine, milk, and blood plasma. Replacing canola meal with hemp seed meal increased milk fat contents of polyunsaturated fatty acids (PUFA), which were 3.42, 3.90, and 4.25 g/100 g of FA for the CM15, CM7.5HM7.5, and HM15 treatments, respectively. Especially, the milk fat contents of 18:2n-6 (1.99 vs. 1.56 g/100 g FA) and 18:3n-3 (0.31 vs. 0.43 g/100 g FA) were increased by hemp meal feeding. Especially, the milk fat contents of 18:2n-6 (1.99 vs. 1.56 g/100 g FA) and 18:3n-3 (0.31 vs. 0.43 g/100 g FA) were increased by hemp meal feeding. Our data show that hemp seed meal is a suitable and safe replacement for canola meal as a feed for lactating dairy cows and that this replacement increases CP digestibility and urea in urine, milk, and blood plasma, as well the PUFA content of milk fat.

We report results on an elastic cross section measurement in proton–proton collisions at a center-of-mass energy s=510 GeV, obtained with the Roman Pot setup of the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The elastic differential cross section is measured in the four-momentum transfer squared range 0.23≤−t≤0.67 GeV2. This is the only measurement of the proton-proton elastic cross section in this t range for collision energies above the Intersecting Storage Rings (ISR) and below the Large Hadron Collider (LHC) colliders. We find that a constant slope B does not fit the data in the aforementioned t range, and we obtain a much better fit using a second-order polynomial for B(t). This is the first measurement below the LHC energies for which the non-constant behavior B(t) is observed. The t dependence of B is also determined using six subintervals of t in the STAR measured t range, and is in good agreement with the phenomenological models. The measured elastic differential cross section dσ/dt agrees well with the results obtained at s=540 GeV for proton–antiproton collisions by the UA4 experiment. We also determine that the integrated elastic cross section within the STAR t-range is σelfid=462.1±0.9(stat.)±1.1(syst.)±11.6(scale) μb.

In order to quantify the relative importance of individual boundary conditions and forcings, including greenhouse gases, ice sheets, and Earth's orbital parameters, on determining Last Glacial Maximum (LGM) climate, we have performed a series of LGM experiments using a state-of-the-art climate model AWI-ESM, in which different combinations of boundary conditions and forcings have been applied following the protocol of Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). In good agreement with observational proxy records, a general colder and drier climate is simulated in our full-forced LGM experiment as compared to the present-day simulation. Our simulated results from non-full-forced sensitivity simulations reveal that both the greenhouse gases and ice sheets play a major role in defining the anomalous LGM surface temperature compared to today. Decreased greenhouse gases in LGM as compared to present day leads to a non-uniform global cooling with polar amplification effect. The presence of LGM ice sheets favors a warming over the Arctic and northern Atlantic oceans in boreal winter, as well as a cooling over regions with the presence of ice sheets. The former is induced by a strengthening in the Atlantic meridional overturning circulation (AMOC) transporting more heat to high latitudes, whilst the latter is due to the increased surface albedo and elevation of ice sheets. We find that the Northern Hemisphere monsoon precipitation is influenced by the opposing effects of LGM greenhouse gases and ice sheets. Specifically, the presence of ice sheets leads to significant drying in the Northern Hemisphere monsoon regions, while a reduction in greenhouse gases results in increased monsoon rainfall. Based on our model results, continental ice sheets exert a major control on atmospheric dynamics and the variability of El Niño–Southern Oscillation (ENSO). Moreover, our analysis also implies a nonlinearity in climate response to LGM boundary conditions and forcings.

ABSTRACT: Hemp seed meal may be a suitable protein supplement for dairy cows, but its quality and safety as a dairy cow feed has not yet been fully investigated. As a result, dry matter intake (DMI), rumen fermentation, blood metabolites, total-tract digestibility, and concentrations of cannabinoids in blood plasma, urine, muscle, and adipose tissues were compared among nonlactating Holstein dairy cows receiving a basal partial mixed ration that was supplemented with either 10.2% dry matter (DM) hemp meal (HM treatment), 13.5% DM canola meal (CM treatment), or 6.25% DM hemp meal and 6.16% DM canola meal (HC treatment). Diets were formulated to be isoenergetic and isonitrogenous. Six nonlactating, nonpregnant Holstein cows were used in a repeated 3 × 3 Latin square design trial with three 3-wk experimental periods. The first 2 weeks of each served as adaptation. Sample and data collection occurred during the third week of each period. Neither the partial mixed ration nor canola meal contain cannabidiol (CBD), cannabidiolic acid (CBDA), d9-tetrahydrocannabinol (THC), or tetrahydrocannabinolic acid A (THCA). However, the hemp meal contained 3.0, 4.4, 0, and 0.1 μg/g DM of CBD, CBDA, THC, and THCA, respectively. Treatment did not affect DMI, pH, concentrations of volatile fatty acids or ammonia in the rumen, total-tract digestibilities of DM and crude protein, or blood plasma concentrations of glucose, urea, β-hydroxybutyrate, and nonesterified fatty acids. Hence, based on these metabolites, treatment did not affect the nutritional status of the cows. However, the total-tract neutral detergent fiber digestibility of the CM treatment (43%) was higher than that of the HM treatment (38%). No cannabinoids were detected in blood plasma, rumen fluid, and urine. Cannabinoids were also not detected in kidney, liver, urine, muscle, or adipose tissues at the end of the experiment when cows had undergone all treatments. Feces from all treatments did not contain detectable concentrations of THC or THCA, but feces of cows on the HC treatment contained 0.42 and 0.40 μg/g DM of CBD and CBDA, respectively. Feces of cows on the HM treatment contained 0.68 and 0.67 μg/g DM of CBD and CBDA, respectively. This indicated that most ingested CBD and CBDA were not absorbed but instead were excreted in the feces. Our data show dietary inclusion rates of up to 10.2% of DM. We find that hemp meal is a high-quality and safe protein supplement for nonlactating dairy cows.

In this work, we developed a semi-solid sintering method for constructing a core-shell architecture in Ti68.8Nb13.6Co6.8Cr5.1Al6.5 alloy and revealed the underlying mechanism of microstructure evolution and deformation behavior. Fundamentally, the semi-solid state was achieved by sintering amorphous powders at temperatures between the melting point of the CoTi2 phase and the β-Ti matrix. During the process, the liquid CoTi2 phase was squeezed towards the β-Ti boundaries due to the sintering pressure and the growth of β-Ti grains. Subsequently, it transformed into a hard ultrafine CoTi2 phase distributed along the β-Ti boundaries, constructing a core-shell structure. The resulting core-shell structure exhibited a high compressive yield strength of 1560 MPa, an ultimate strength of 3006 MPa, and a remarkable compressive strain of 40.1%, surpassing typical Ti-based alloys under compressive loading. The high strength was attributed to dislocation-impeding effect of the CoTi2 phase, while the activation of multiple slip systems triggered by the CoTi2 shell contributed to plasticity. The results provide fundamental insights into the fabrication of Ti-based alloys with exceptional mechanical properties for structural materials applications.

In this work, a multi-objective optimization design method is proposed based on principal component analysis (PCA) and a neural network to obtain a mechanism's optimal comprehensive performance. First, multi-objective optimization mathematical modeling, including design parameters, objective functions, and constraint functions, is established. Second, the sample data are obtained through the design of the experiment (DOE) and are then standardized to eliminate the adverse effects of a non-uniform dimension of objective functions. Third, the first k principal components are established for p performance indices (k

Regional coupled and Earth system models are fundamental numerical tools for climate investigations, downscaling of predictions and projections, process-oriented understanding of regional extreme events, and many more applications. Here we introduce a newly developed coupled regional modeling framework for the Mediterranean region, called MESMAR (Mediterranean Earth System model at ISMAR) version 1, which is composed of the Weather Research and Forecasting (WRF) atmospheric model, the NEMO oceanic model, and the hydrological discharge (HD) model, coupled via the OASIS coupler. The model is implemented at about 1/12∘ of horizontal resolution for the ocean and river routing, while roughly twice coarser for the atmosphere, and it is targeted to long-term investigations. We focus on the evaluation of skill score metrics from several sensitivity experiments devoted to (i) understanding the best vertical physics configuration for NEMO, (ii) identifying the impact of the interactive river runoff, and (iii) choosing the best-performing physics–microphysics suite for WRF in the regional coupled system. The modeling system has been developed for downscaling reanalyses and long-range predictions, as well as coupled data assimilation experiments. We then formulate and show the performance of the system when weakly coupled data assimilation is embedded in the system (variational assimilation in the ocean and spectral nudging in the atmosphere), in particular for the representation of extreme events like intense Mediterranean cyclones (i.e., medicanes). Finally, we outline plans for future extension of the modeling framework.

The mixing of oil and gas forms the foundation of deep-sea oil and gas extraction and transportation. However, traditional conveying equipment has low efficiency and high failure rates. In this study, a spiral axial flow gas and liquid multiphase pump was used as the base model. The Eulerian multiphase flow model and RNG turbulence model were used for numerical simulations to analyze the internal flow field of the multiphase pump. A modification scheme was proposed to twist the airfoil shape and create a twisted vane. The twisted blade with the center of the hub-side flange chord length as the twisting center was twisted in the counterclockwise direction to help reduce the relative volume of gas in the flow channel. When the twisted vane with the hub-side airfoil type trailing edge point as the twisting center was twisted in the suction side direction, it helped to accelerate the movement of the gas-liquid mixture at the trailing edge of the back of the vane and further reduced the low velocity zone at the back of the vane. When the twist center is located at the hub side wing type trailing edge point of the twist vane, the twist degree is 0.214. This results in the maximum head and efficiency of the pump, improves gas phase aggregation phenomenon, and enhances the performance of the multiphase pump.

This work presents a new model-free inversion estimation framework (MFIEF) using daily TROPOspheric Monitoring Instrument (TROPOMI) NO2 columns and observed fluxes from the continuous emission monitoring system (CEMS) to quantify 3 years of daily scale emissions of NOx at 0.05∘×0.05∘ over Shanxi Province, a major world-wide energy-producing and energy-consuming region. The NOx emissions, day-to-day variability, and uncertainty on a climatological basis are computed to be 1.86, 1.03, and 1.05 Tg yr−1 respectively. The highest emissions are concentrated in the lower Fen River valley, which accounts for 25 % of the area, 53 % of the NOx emissions, and 72 % of CEMS sources. Two major forcing factors (10th to 90th percentile) are horizontal transport distance per day (63–508 km) and lifetime of NOx (7.1–18.1 h). Both of these values are consistent with NOx emissions to both the surface layer and the free troposphere. The third forcing factor, the ratio of NOx/NO2, on a pixel-to-pixel basis, is demonstrated to correlate with the combustion temperature and energy efficiency of large energy consuming sources. Specifically, thermal power plants, cement, and iron and steel companies have a relatively high NOx/NO2 ratio, while coking, industrial boilers, and aluminum oxide factories show a relatively lower ratio. Variance maximization is applied to daily TROPOMI NO2 columns, which facilitates identification of three orthogonal and statistically significant modes of variability, and successfully attributes them both spatially and temporally to (a) this work's computed emissions, (b) remotely sensed TROPOMI ultraviolet aerosol index (UVAI), and (c) computed transport based on TROPOMI NO2.

In this work, a new processing technology of pressure plus pulsed electric current treatment (PPEC) was proposed to treat CP-Ti to simultaneously enhance its strength and ductility. Specifically, the CP-Ti was subjected to 50 MPa pressure and pulsed electric current (PEC) with variable intensities (1400A, 1600A, and 1900A) using a spark plasma sintering system. Afterwards, the microstructure evolution, texture change, and mechanical properties were characterized by XRD, EBSD, and tensile tests. The increased grain size and noticeable microstructure change occurred with increasing PEC intensity. Additionally, applying 50 MPa pressure leads to the formation of finer α lamellae colonies and higher content of high-angle grain boundaries, which act as barriers for dislocation motion after yielding, resulting in enhanced strain hardening rate and consequently improved mechanical properties. The processed CP-Ti exhibits a yield strength of 350 MPa, an ultimate strength of 702 MPa, and a significant plastic strain of 39.1%, superior to those of CP-Ti processed by severe plastic deformation and pure PEC treatment. The results provide a new strategy to develop Ti materials for demanding structural applications.

This study investigates the evolutions of microstructure and performance of TiNbZrTaHf-based alloys from equiatomic high-entropy alloys to Ti-rich dilute alloys. A novel biocompatible alloy, Ti50Nb12.5Zr12.5Ta12.5Hf12.5, was developed with a high yield strength of 839 ± 12 MPa, low modulus of 61.5 GPa, low magnetic susceptibility of ∼1.99 × 10−6 cm3g−1, and unprecedented tensile plasticity of 28.7 ± 2.2%. The study discusses the underlying mechanisms responsible for these superior performances, attributing the exceptional plasticity to the activation of cross-slip dislocations, enhanced dynamic recovery and high resistance to crack propagation. The findings provide new insights into the development of biomedical titanium alloys.

Since modern times, Western immigrants have constructed summer resorts in subtropical regions of Asia, resulting in a unique historical occurrence. These summer resorts have loose and flexible distributions that reflect the specific needs and aesthetic preferences of the developers. In the Kuliang summer resort in Fuzhou, China, the seemingly random distribution of buildings and historical landscapes actually conceals complex social relationships between the hosts and managers. This paper discovered that the expansion of housing distribution in Kuliang is closely related to the social network of residents. The research employed various technological methods such as social network analysis and geographic information systems to compute and process complex social relationships and big data. Their analysis has led to three conclusions: (1) The seemingly randomized distribution of buildings and historical landscapes in Kuliang is a result of social relationship development. (2) The formation of Kuliang's summer resort is correlated with the selection of "central members" in the community and has distinct temporal characteristics. (3) Information technology has great potential for the analysis of the formation process of cultural landscapes. These research findings provide important reference for the protection of cultural heritage and understanding the role of social relationships in shaping cultural landscapes.

Abstract We report a new measurement of the production of electrons from open heavy-flavor hadron decays (HFEs) at mid-rapidity (|y| < 0.7) in Au+Au collisions at s NN $$ \sqrt{s_{\textrm{NN}}} $$ = 200 GeV. Invariant yields of HFEs are measured for the transverse momentum range of 3.5 < p T < 9 GeV/c in various configurations of the collision geometry. The HFE yields in head-on Au+Au collisions are suppressed by approximately a factor of 2 compared to that in p + p collisions scaled by the average number of binary collisions, indicating strong interactions between heavy quarks and the hot and dense medium created in heavy-ion collisions. Comparison of these results with models provides additional tests of theoretical calculations of heavy quark energy loss in the quark-gluon plasma.

Classical Chinese gardens built in scenic areas have characteristics in rich scales, multi-type elements, and a complex development history. Due to the designed landscape characteristics of "hidden the garden in bigger landscapes", it is often difficult to obtain high-quality heritage information through traditional surveying approaches. The aim of this research is to establish a digital 3D documentation technology system for the classical gardens in scenic areas. Suiyuan Garden, a classical Chinese garden with a history of more than 300 years, was used as a case study. We have integrated UAV low-altitude photogrammetry, handheld laser scanning, ground-mounted laser scanning, macro structured light scanning and other technologies to obtain the 3D data, and to build a digital twin by developing the technical workflow and data standard. The innovation of the research lies in: 1) We used a variety of digital mapping methods to record the pattern between the garden and the surrounding landscape; 2) We adopted a combination of handheld and ground-mounted laser scanning systems to build spatial structures and better cover the ground spaces; 3) We established a workflow for the conversion from point cloud to mesh model for different garden features, which can improve the usability of 3D heritage information; 4) We used the 3D cultural heritage modelling approach to improve the standards of the digital conservation of historic plants. The outcomes of this research could be used as the basis for the construction of Historic Landscape Information Model (HLIM) in the near future.

Abstract The Aria cryogenic distillation plant, located in Sardinia, Italy, is a key component of the DarkSide-20k experimental program for WIMP dark matter searches at the INFN Laboratori Nazionali del Gran Sasso, Italy. Aria is designed to purify the argon, extracted from underground wells in Colorado, USA, and used as the DarkSide-20k target material, to detector-grade quality. In this paper, we report the first measurement of argon isotopic separation by distillation with the 26 m tall Aria prototype. We discuss the measurement of the operating parameters of the column and the observation of the simultaneous separation of the three stable argon isotopes: $${}^{36}\hbox {Ar}$$ 36 Ar , $${}^{38}\textrm{Ar}$$ 38 Ar , and $${}^{40}\textrm{Ar}$$ 40 Ar . We also provide a detailed comparison of the experimental results with commercial process simulation software. This measurement of isotopic separation of argon is a significant achievement for the project, building on the success of the initial demonstration of isotopic separation of nitrogen using the same equipment in 2019.

With the rapid development of GNSS, high-resolution remote sensing, InSAR, LiDAR and other earth observation technologies, advanced technical conditions are provided for the training of talents in the field of geomatics. The discipline of surveying and mapping science and technology in Chang'an University has been integrated with engineering geology and geohazards over decades, forming one of the special research directions, that is, development of earth observation techniques and the applications in geological disasters. Therefore, we have formed the "integration of science and education, international cooperation" characteristic talent training mode. The specific initiatives include six aspects, namely, concentrating featured discipline directions, building scientific research platforms and teams, recruiting and developing outstanding talents, undertaking major scientific projects, strengthening the integration of science and education, and expanding international exchanges and cooperation, which ultimately serves the goal of improving the quality of personnel training in geomatics.

The Budyko framework is a simple and effective tool for estimating the water balance of watersheds. Quantification of the watershed-characteristic-related parameter (Pw) is critical for accurate water balance simulations with the Budyko framework. However, there is no universal method for calculating Pw as the interactions between hydrologic, climatic, and watershed characteristic factors differ greatly across watersheds. To fill this research gap, this study introduced the principle of hydrologically similar groups into the Budyko framework for quantifying the Pw of watersheds in similar environments. We first classified the 366 selected watersheds worldwide into six hydrologically similar groups based on watershed attributes, including climate, soil, and vegetation. Results show that soil moisture (SM) and fractional vegetation cover (FVC) are two controlling factors of the Pw in each group. The SM exhibits a power-law relationship with the Pw values, with increasing SM leading to higher Pw values in dry watersheds (SM ≤ 20 mm) and lower Pw values in humid watersheds (SM > 20 mm). Additionally, the FVC shows to be linearly correlated with the Pw values in most hydrologically similar groups, except in that group with moist soil and no strong rainfall seasonality (SM >20 mm and seasonal index (SI) ≤ 0.4). Multiple non-linear regression models between Pw and the controlling factors (SM and FVC) were developed to individually estimate the Pw of six hydrologically similar groups. Cross-validations using the bootstrap sampling method (R2=0.63) and validations of time-series Global Runoff Data Centre (GRDC) data (R2=0.89) both indicate that the proposed models perform satisfactorily in estimating the Pw parameter in the Budyko framework. Overall, this study is a new attempt to quantify the unknown Pw in the Budyko framework using the method for hydrologically similar groups. The results will be helpful in improving the applicability of the Budyko framework for estimating the annual runoff of watersheds in diverse climates and with different characteristics.

Abstract We present a novel approach for the search of dark matter in the DarkSide-50 experiment, relying on Bayesian Networks. This method incorporates the detector response model into the likelihood function, explicitly maintaining the connection with the quantity of interest. No assumptions about the linearity of the problem or the shape of the probability distribution functions are required, and there is no need to morph signal and background spectra as a function of nuisance parameters. By expressing the problem in terms of Bayesian Networks, we have developed an inference algorithm based on a Markov Chain Monte Carlo to calculate the posterior probability. A clever description of the detector response model in terms of parametric matrices allows us to study the impact of systematic variations of any parameter on the final results. Our approach not only provides the desired information on the parameter of interest, but also potential constraints on the response model. Our results are consistent with recent published analyses and further refine the parameters of the detector response model.

Density fluctuations near the QCD critical point can be probed via an intermittency analysis in relativistic heavy-ion collisions. We report the first measurement of intermittency in Au+Au collisions at sNN = 7.7-200 GeV measured by the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The scaled factorial moments of identified charged hadrons are analyzed at mid-rapidity and within the transverse momentum phase space. We observe a power-law behavior of scaled factorial moments in Au+Au collisions and a decrease in the extracted scaling exponent (ν) from peripheral to central collisions. The ν is consistent with a constant for different collisions energies in the mid-central (10-40%) collisions. Moreover, the ν in the 0-5% most central Au+Au collisions exhibits a non-monotonic energy dependence that reaches a minimum around sNN = 27 GeV. The physics implications on the QCD phase structure are discussed.

We report on new measurements of elliptic flow (v2) of electrons from heavy-flavor hadron decays at mid-rapidity (|y|

Abstract Partons traversing the strongly interacting medium produced in heavy-ion collisions are expected to lose energy depending on their color charge and mass. We measure the nuclear modification factors for charm- and bottom-decay electrons, defined as the ratio of yields, divided by the number of binary nucleon–nucleon collisions, in $$\sqrt{s_{\textrm{NN}}}=200$$ s NN = 200 GeV Au+Au collisions to p+p collisions ( $$R_{\textrm{AA}}$$ R AA ), or in central to peripheral Au+Au collisions ( $$R_{\textrm{CP}}$$ R CP ). We find the bottom-decay electron $$R_{\textrm{AA}}$$ R AA and $$R_{\textrm{CP}}$$ R CP to be significantly higher than those of charm-decay electrons. Model calculations including mass-dependent parton energy loss in a strongly coupled medium are consistent with the measured data. These observations provide evidence of mass ordering of charm and bottom quark energy loss when traversing through the strongly coupled medium created in heavy-ion collisions.

For the precipitation-strengthened aluminum alloys such as Al–Mg–Si alloys, the friction stir welded (FSW) joints produced with T6-treated plates usually exhibit obvious softening in the heat-affected zones (HAZ), significantly reducing the joint strength. When bobbin tool FSW (BT-FSW) is used, severer softening of the HAZ occurred compared to conventional FSW. It is therefore crucial to achieve precipitate morphology control in the HAZ for BT-FSW through original plate state selecting, welding parameter optimizing, and post-weld artificial aging (PWAA). Compared to the conventional welding process (plates welded directly under T6 condition, T6-BT), in the present work, a post-weld aging process was proposed: the plates under T4 condition were BT-FSWed using optimizing parameters (T4-BT), and then subjected to PWAA (T4-BT-PWAA). The intrinsic microstructural differences between the T6-BT and T4-BT-PWAA joints were revealed. More attentions were paid on the microstructural evolution in the lowest hardness zone (LHZ) during PWAA for the T4-BT joint. The LHZ of the T6-BT joint exhibited an over-aged state characterized by coarsened β′ phase and the hardness in this zone had very limited enhancing space when subjected to post-weld peak aging. For the T4-BT joint, the LHZ was characterized by a low density of precipitates and presented excellent re-precipitating ability of β'' phase during PWAA, with the ultimate tensile strength increased by ∼11.4% compared to its T6 counterpart, which is very beneficial for engineering applications.

Abstract We have studied effects of metal–dielectric substrates on photopolymerization of [2,2ʹ-Bi-1H-indene]-1,1ʹ-dione-3,3ʹ-diyl diheptanoate (BITh) monomer. We synthetized BITh and spin-coated it onto a variety of dielectric, metallic, and metal–dielectric substrates. The films were exposed to radiation of a UV–Visible Xe lamp, causing photo-polymerization of monomer molecules. The magnitude and the rate of the photo-polymerization were monitored by measuring the strength of the ~ 480 nm absorption band, which existed in the monomer but not in the polymer. Expectedly, the rate of photo-polymerization changed nearly linearly with the change of the pumping intensity. In contrast with our early study of photo-degradation of semiconducting polymer P3HT, the rate of photo-polymerization of BITh is getting modestly higher if the monomer film is deposited on top of silver separated from the monomer by a thin insulating MgF2 layer preventing a charge transfer. This effect is partly due to a constructive interference of the incident and reflected light waves, as well as known in the literature effects of metal/dielectric substrates on a variety of spectroscopic and energy transfer parameters. At the same time, the rate of photopolymerization is getting threefold larger if monomer is deposited on Ag film directly and charge transfer is allowed. Finally, Au substrates cause modest (~ 50%) enhancement of both monomer film absorption and the rate of photo-polymerization.

The long-term monitoring of atmospheric mercury is an important part of the effective evaluation of the Minamata Convention on Mercury. Gaseous elemental mercury (GEM), along with conventional air pollutants and meteorological parameters, was simultaneously observed in Xiamen, Southeast China, in January and July over the period 2012–2020. GEM concentrations in January were highest in 2015 (4.47 ng m−3) and decreased by 2020 (3.93 ng m−3), while GEM concentrations in July were highest in 2017 (2.65 ng m−3) and lowest in 2020 (1.56 ng m−3). The temporal variation of GEM was typically characterized by higher concentrations in winter than in summer and in nighttime than in daytime. Bivariate polar plots and the concentration-weighted trajectory (CWT) model were used to identify the source regions of GEM on a local and regional scale. The results indicate that the high GEM concentrations in January 2015 were likely due to a combination of high-level Hg emissions and adverse meteorological conditions. Generalized additive models (GAMs), which use a regression analysis method, were established and applied to investigate the influencing factors on the inter-annual variation of GEM. The factors anthropogenic emissions, meteorological conditions, and transportation explained 37.8 %±11.9 %, 31.4 %±9.0 %, and 30.8 %±9.9 % on average of the variation of GEM concentrations, respectively. There was a positive relationship of daily GEM concentrations with T and RH, mostly linking to natural surface emissions and Hg chemical transformations. The interpretation rate of anthropogenic emissions has significantly decreased since 2012, indicating the effectiveness of emission mitigation measures in reducing GEM concentrations in the study region.

Intro: Pulmonary fibrosis has been reported as a common complication of severe COVID-19, especially in patients who have undergone ARDS or mechanical ventilation treatment. As innate lymphocytes, NK cells play important roles in antiviral immunity and inhibit the progression of organ fibrosis.The exploration of key NK populations will clarify their role in the progression of COVID-19 and provide crucial cues for the treatment of post-COVID pulmonary fibrosis. Methods: Single-cell transcriptome data from bronchoalveolar lavage fluid (BALF) of COVID-19 patients and healthy donors were analyzed on normalized expression matrices of all cells screened. After annotation according to the marker genes, NK cells were extracted for further clustering and subsequent analyses of gene expression profiling, gene set enrichment, and molecular interaction. Findings: Reduced-dimensional clustering showed that NK cells in BALF were divided into 10 subpopulations. Compared with healthy persons, NK cells in the lungs of COVID-19 patients showed higher activated features and up-regulation of IFN-related genes. However, the GZMs+PRF1+ subpopulation was only 30% of the total NK cells and highly expressed apoptotic genes of Bax and BCL2L11 in severe patients, which may lead to insufficiency and poor cytotoxicity. In severe patients, AREG+ subpopulation was enriched in the lungs and decreased the expression of TNFSF10, FasL, and CCR2, which indicated under-recruitment and impaired antifibrosis function. Conclusion: Our data showed that NK cells decreased in BALF of severe COVID-19 patients, especially the effector/cytotoxic NK subset very significantly decreased. The impaired activity of antifibrotic NK cells may be associated with collagen deposition and senescent cell accumulation in the lungs with severe SARS-COV-2 infection. Improving the antiviral function and antifibrosis ability may be valid measures to prevent severe COVID-19 and reduce fibrosis complications.

Additive manufacturing involves the process of track-by-track melt pools accompanied by the localized rapid melting/solidification, which can determine unique nonequilibrium microstructures. In this study, we report formation of heterogeneous nonequilibrium microstructures in near-equiatomic NiTi fabricated via laser powder bed fusion (LPBF) additive manufacturing, and further discuss their underlying formation mechanisms and influences on shape memory effect of the LPBF NiTi. Specifically, the heterogeneous microstructures include the core (HCP α-Ti)-shell (Ti2Ni) structural nano-sized precipitation phases in columnar grains, which were resulted from high undercooling and cooling rate during LPBF solidification, the intermediate R phase in cellular and columnar grains, which was stemmed from residual thermal stress during LPBF, the nano-sized cellular substructure in columnar grains with boundaries decorated with Ti2Ni precipitates, which was originated from enriched Ti atoms at the solidification front during directional and orderly solidification of melt pools, together with the abundant dislocations. Interestingly, the two-way shape memory strain of 0.8% in LPBF NiTi was obtained by cycle loading–unloading-heating–cooling training process. These findings achieved in this work enrich the knowledge on formation mechanism of heterogeneous microstructures in LPBF NiTi SMAs, and further pave the way for engineering applications of two-way shape memory effect of LPBF NiTi shape memory alloys.

The deconfined quark-gluon plasma (QGP) created in relativistic heavy-ion collisions enables the exploration of the fundamental properties of matter under extreme conditions. Noncentral collisions can produce strong magnetic fields on the order of 10^{18} G, which offers a probe into the electrical conductivity of the QGP. In particular, quarks and antiquarks carry opposite charges and receive contrary electromagnetic forces that alter their momenta. This phenomenon can be manifested in the collective motion of final-state particles, specifically in the rapidity-odd directed flow, denoted as v_{1}(y). Here, we present the charge-dependent measurements of dv_{1}/dy near midrapidities for π^{±}, K^{±}, and p(p[over ¯]) in Au+Au and isobar (_{44}^{96}Ru+_{44}^{96}Ru and _{40}^{96}Zr+_{40}^{96}Zr) collisions at sqrt[s_{NN}]=200 GeV, and in Au+Au collisions at 27 GeV, recorded by the STAR detector at the Relativistic Heavy Ion Collider. The combined dependence of the v_{1} signal on collision system, particle species, and collision centrality can be qualitatively and semiquantitatively understood as several effects on constituent quarks. While the results in central events can be explained by the u and d quarks transported from initial-state nuclei, those in peripheral events reveal the impacts of the electromagnetic field on the QGP. Our data put valuable constraints on the electrical conductivity of the QGP in theoretical calculations.

Additive manufacturing (AM) is an orderly construction process involving track-by-track melt pools, which can modulate three characteristic zones between two adjacent melt pools: the heat-affected zone, transition zone, and cellular grain zone. These three zones constitute a function domain that determines the properties of AM metallic materials. In this study, we constructed a novel ordered function domain by AM of modified Ni50.6Ti49.4 shape memory alloy powder, which was produced by adding uniform Ni nanoparticles into atomised Ni49.6Ti50.4 powder. Interestingly, the three zones of the function domain had the same B2 austenite matrix but inhomogeneous Ni4Ti3 clusters and Ti2Ni nanoprecipitates, which caused different compressive recovery and residual strains in the three zones. The synergetic effect of the three zones generated a stable recovery strain and small hysteresis area in the AMed Ni50.6Ti49.4. Our results provide a novel strategy for modulating the microstructure of NiTi by AM to yield superior properties.

China is one of the major forest countries in the world, and the accurate estimation of its forest biomass carbon (C) pool is critical for evaluating the country's C budget and ecosystem services of forests. Although several studies have estimated China's forest biomass using national forest inventory data, most of them were limited to the period of 2004–2008. In this study, we extended our estimation to the most recent period of 2014–2018. Using datasets of eight inventory periods from 1977 to 2018 and the continuous biomass expansion factor method, we estimated that the total biomass C pool and average biomass C density in Chinese forests increased from 4717 Tg C (1 Tg = 1012 g) in the period of 1977–1981 to 7975 Tg C in the period of 2014–2018 and 38.2 Mg C ha−1 to 45.8 Mg C ha−1 (1 Mg = 106 g), respectively, with a net increase of 3258 Tg C and an annual sink of 88.0 Tg C yr−1. Over the most recent 10 years (2009–2018), the average national forest biomass C density and C sink were 44.6 Mg C ha−1 and 154.8 Tg C yr−1, respectively, much larger than those of 39.6 Mg C ha−1 and 63.3 Tg C yr−1 in the period 1977–2008. These pronounced increases were largely attributed to afforestation practices, forest growth, and environmental changes. Our results have documented the importance of ecological restoration practices, provided an essential basis for assessing ecosystem services, and helped to achieve China's C neutrality target.

As observed by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), the migrating diurnal tide (DW1) in the upper mesosphere and lower thermosphere (MLT) region decreased by ∼ 10 % during El Niño in the Northern Hemisphere (NH) winter (December–January–February) from 2002 to 2020. According to the multiple linear regression (MLR) analysis, the linear effects of El Niño on the tropical MLT DW1 are significantly negative in both SABER observations and SD-WACCM (the Specified-Dynamics version of the Whole Atmosphere Community Climate Model) simulations. The DW1 response to El Niño in NH winter is much stronger than its annual mean response. As suggested by SD-WACCM simulation, Hough mode (1, 1) dominates the DW1 tidal variation in the tropical MLT region. The consistency between the (1, 1) mode in the tropopause region and the MLT region and the downward phase progression from 15 to 100 km indicates the direct upward propagation of DW1 from the excitation source in the troposphere. The suppressed DW1 heating rates in the tropical troposphere (averaged over ∼ 0–16 km and 35∘ S–35∘ N) during El Niño winter contribute to the decreased DW1 tide. To evaluate the effect of the gravity waves (GWs) on the tide, the GW forcing is calculated as the GW drag weighted by the phase relation between DW1 GW drag and DW1 wind. The negative GW forcing in the tropical upper mesosphere would significantly suppress the MLT DW1 tide during El Niño winter. This tide–GW interaction could be a dominant mechanism for DW1 response in the MLT to El Niño. During El Niño winter, the increased ratio of the absolute and planetary vorticity (R) suppresses the waveguide and thus the DW1 amplitude in the subtropical mesosphere. However, the effect of the waveguide might play a secondary role due to its relatively weak response.

Precipitation forecasting is an important mission in weather science. In recent years, data-driven precipitation forecasting techniques could complement numerical prediction, such as precipitation nowcasting, monthly precipitation projection and extreme precipitation event identification. In data-driven precipitation forecasting, the predictive uncertainty arises mainly from data and model uncertainties. Current deep learning forecasting methods could model the parametric uncertainty by random sampling from the parameters. However, the data uncertainty is usually ignored in the forecasting process and the derivation of predictive uncertainty is incomplete. In this study, the input data uncertainty, target data uncertainty and model uncertainty are jointly modeled in a deep learning precipitation forecasting framework to estimate the predictive uncertainty. Specifically, the data uncertainty is estimated a priori and the input uncertainty is propagated forward through model weights according to the law of error propagation. The model uncertainty is considered by sampling from the parameters and is coupled with input and target data uncertainties in the objective function during the training process. Finally, the predictive uncertainty is produced by propagating the input uncertainty in the testing process. The experimental results indicate that the proposed joint uncertainty modeling framework for precipitation forecasting exhibits better forecasting accuracy (improving RMSE by 1 %–2 % and R2 by 1 %–7 % on average) relative to several existing methods, and could reduce the predictive uncertainty by ∼28 % relative to the approach of Loquercio et al. (2020). The incorporation of data uncertainty in the objective function changes the distributions of model weights of the forecasting model and the proposed method can slightly smooth the model weights, leading to the reduction of predictive uncertainty relative to the method of Loquercio et al. (2020). The predictive accuracy is improved in the proposed method by incorporating the target data uncertainty and reducing the forecasting error of extreme precipitation. The developed joint uncertainty modeling method can be regarded as a general uncertainty modeling approach to estimate predictive uncertainty from data and model in forecasting applications.

Intro: Two rotavirus vaccines are licensed in China (RotaTeq and Lanzhou Lamb Rotavirus [LLR] vaccine), but their use is not widespread. We sought to understand the public health impact of widespread rotavirus vaccination with these two vaccines on public health outcomes, in China, among children ages 0- 7 years old. Methods: We developed a Markov Model to simulate a birth cohort from 0 to 7 years of age under three scenarios- i) vaccination with RotaTeq; ii) vaccination with LLR; iii) no-vaccination; and calculated each scenario's expected number of health outcomes. The model was parameterized using published information on rotavirus epidemiology, RotaTeq and LLR effectiveness in China, as abstracted from national estimates and peer-reviewed literature. We assumed individuals could have up to five rotavirus infections, the first two being the ones that could lead to hospitalization. We considered high (90%) and low (50%) vaccination coverage scenarios (since rotavirus vaccines are not reimbursed) and fitted the model by changing the percent of immunity conferred by previous infection and the asymptomatic to symptomatic ratio. Findings: For a cohort of 100,000 children over the first 7 years of life, and in the absence of a rotavirus vaccine in China, 899 hospitalizations, 11,708 outpatient visits, and 64,746 symptomatic rotavirus cases are expected. Using RotaTeq, 67% (39%) of hospitalizations, and 61% (35%) of outpatient visits and rotavirus cases can be averted under the high (low) vaccination coverage scenario. Given lower vaccine effectiveness estimates for LLR, its use would avert 24% (14%) hospitalizations, 24% (14%) outpatient visits, and 24% (14%) rotavirus symptomatic cases compared to no vaccination, in the high (low) vaccination coverage scenario. Conclusion: Widespread use of rotavirus vaccination can avert a significant number of rotavirus gastroenteritis outcomes, with a three to two times higher potential public health impact for RotaTeq compared to LLR.

A decisive experimental test of the Chiral Magnetic Effect (CME) is considered one of the major scientific goals at the Relativistic Heavy-Ion Collider (RHIC) towards understanding the nontrivial topological fluctuations of the Quantum Chromodynamics vacuum. In heavy-ion collisions, the CME is expected to result in a charge separation phenomenon across the reaction plane, whose strength could be strongly energy dependent. The previous CME searches have been focused on top RHIC energy collisions. In this Letter, we present a low energy search for the CME in Au+Au collisions at sNN=27 GeV. We measure elliptic flow scaled charge-dependent correlators relative to the event planes that are defined at both mid-rapidity |η|

The linear and mode-coupled contributions to higher-order anisotropic flow are presented for Au+Au collisions at sNN = 27, 39, 54.4, and 200 GeV and compared to similar measurements for Pb+Pb collisions at the Large Hadron Collider (LHC). The coefficients and the flow harmonics' correlations, which characterize the linear and mode-coupled response to the lower-order anisotropies, indicate a beam energy dependence consistent with an influence from the specific shear viscosity (η/s). In contrast, the dimensionless coefficients, mode-coupled response coefficients, and normalized symmetric cumulants are approximately beam-energy independent, consistent with a significant role from initial-state effects. These measurements could provide unique supplemental constraints to (i) distinguish between different initial-state models and (ii) delineate the temperature (T) and baryon chemical potential (μB) dependence of the specific shear viscosity ηs(T,μB).