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Narrowing surface ozone disparities between urban and nonurban areas escalate health risks in densely populated urban zones. A comprehensive understanding of the impact of ozone photochemistry on this transition remains constrained by current knowledge of aerosol effects and the availability of surface monitoring. Here we reconstructed spatiotemporal gapless air quality concentrations using a novel transformer deep learning (DL) framework capable of perceiving spatiotemporal dynamics to analyze ozone urban–nonurban differences. Subsequently, the photochemical effect on these discrepancies was analyzed by elucidating shifts in ozone regimes inferred from an interpretable machine learning method. The evaluations of the model exhibited an average out-of-sample cross-validation coefficient of determination of 0.96, 0.92, and 0.95 for ozone, nitrogen dioxide, and fine particulate matter (PM2.5), respectively. The ozone sensitivity in nonurban areas, dominated by a nitrogen-oxide-limited (NOx-limited) regime, was observed to shift towards increased sensitivity to volatile organic compounds (VOCs) when extended to urban areas. A third “aerosol-inhibited” regime was identified in the Jiaodong Peninsula, where the uptake of hydroperoxyl radicals onto aerosols suppressed ozone production under low NOx levels during summertime. The reduction of PM2.5 could increase the sensitivity of ozone to VOCs, necessitating more stringent VOC emission abatement for urban ozone mitigation. In 2020, urban ozone levels in Shandong surpassed those in nonurban areas, primarily due to a more pronounced decrease in the latter resulting from stronger aerosol suppression effects and less reduction in PM2.5. This case study demonstrates the critical need for advanced spatially resolved models and interpretable analysis in tackling ozone pollution challenges.

This paper provides an overview of the United States (US) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2 (E3SMv2) fully coupled regionally refined model (RRM) and documents the overall atmosphere, land, and river results from the Coupled Model Intercomparison Project 6 (CMIP6) DECK (Diagnosis, Evaluation, and Characterization of Klima) and historical simulations – a first-of-its-kind set of climate production simulations using RRM. The North American (NA) RRM (NARRM) is developed as the high-resolution configuration of E3SMv2 with the primary goal of more explicitly addressing DOE's mission needs regarding impacts to the US energy sector facing Earth system changes. The NARRM features finer horizontal resolution grids centered over NA, consisting of 25→100 km atmosphere and land, a 0.125∘ river-routing model, and 14→60 km ocean and sea ice. By design, the computational cost of NARRM is ∼3× of the uniform low-resolution (LR) model at 100 km but only ∼ 10 %–20 % of a globally uniform high-resolution model at 25 km. A novel hybrid time step strategy for the atmosphere is key for NARRM to achieve improved climate simulation fidelity within the high-resolution patch without sacrificing the overall global performance. The global climate, including climatology, time series, sensitivity, and feedback, is confirmed to be largely identical between NARRM and LR as quantified with typical climate metrics. Over the refined NA area, NARRM is generally superior to LR, including for precipitation and clouds over the contiguous US (CONUS), summertime marine stratocumulus clouds off the coast of California, liquid and ice phase clouds near the North Pole region, extratropical cyclones, and spatial variability in land hydrological processes. The improvements over land are related to the better-resolved topography in NARRM, whereas those over ocean are attributable to the improved air–sea interactions with finer grids for both atmosphere and ocean and sea ice. Some features appear insensitive to the resolution change analyzed here, for instance the diurnal propagation of organized mesoscale convective systems over CONUS and the warm-season land–atmosphere coupling at the southern Great Plains. In summary, our study presents a realistically efficient approach to leverage the fully coupled RRM framework for a standard Earth system model release and high-resolution climate production simulations.

The E3SM Diagnostics Package (E3SM Diags) is a modern, Python-based Earth system model (ESM) evaluation tool (with Python module name e3sm_diags), developed to support the Department of Energy (DOE) Energy Exascale Earth System Model (E3SM). E3SM Diags provides a wide suite of tools for evaluating native E3SM output, as well as ESM data on regular latitude–longitude grids, including output from Coupled Model Intercomparison Project (CMIP) class models. E3SM Diags is modeled after the National Center for Atmospheric Research (NCAR) Atmosphere Model Working Group (AMWG, 2022) diagnostics package. In its version 1 release, E3SM Diags included a set of core essential diagnostics to evaluate the mean physical climate from model simulations. As of version 2.7, more process-oriented and phenomenon-based evaluation diagnostics have been implemented, such as analysis of the quasi-biennial oscillation (QBO), the El Niño–Southern Oscillation (ENSO), streamflow, the diurnal cycle of precipitation, tropical cyclones, ozone and aerosol properties. An in situ dataset from DOE's Atmospheric Radiation Measurement (ARM) program has been integrated into the package for evaluating the representation of simulated cloud and precipitation processes. This tool is designed with enough flexibility to allow for the addition of new observational datasets and new diagnostic algorithms. Additional features include customizable figures; streamlined installation, configuration and execution; and multiprocessing for fast computation. The package uses an up-to-date observational data repository maintained by its developers, where recent datasets are added to the repository as they become available. Finally, several applications for the E3SM Diags module were introduced to fit a diverse set of use cases from the scientific community.

Marine self-potential (SP) investigation is an effective method to study deep-sea hydrothermal vents and seafloor sulfide deposits. At present, one of the commonly used marine self-potential systems is a towed array of electrodes. Large noises are recorded when great changes in electrode distance and array attitude occur due to the complex seafloor topography. In this paper, a new multicomponent electrical field observation system based on an autonomous underwater vehicle (AUV) was introduced for the measurement of seafloor self-potential signals. The system was tested in a lake, and the multicomponent self-potential data were collected from there. Observed data involve the navigational information of the AUV, which could be corrected using a rotation transform. After navigational correction, measured data can recover the location of the artificial source using self-potential tomography. The experimental results showed that the new SP system can be applied to marine SP observations, providing an efficient and low-noise SP acquisition method for marine resources and environmental investigations.

We apply the color–magnitude intercept calibration method (CMAGIC) to the Nearby Supernova Factory SNe Ia spectrophotometric data set. The currently existing CMAGIC parameters are the slope and intercept of a straight line fit to the linear region in the color–magnitude diagram, which occurs over a span of approximately 30 days after maximum brightness. We define a new parameter, ω _XY , the size of the “bump” feature near maximum brightness for arbitrary filters X and Y . We find a significant correlation between the slope of the linear region, β _XY , in the CMAGIC diagram and ω _XY . These results may be used to our advantage, as they are less affected by extinction than parameters defined as a function of time. Additionally, ω _XY is computed independently of templates. We find that current empirical templates are successful at reproducing the features described in this work, particularly SALT3, which correctly exhibits the negative correlation between slope and “bump” size seen in our data. In 1D simulations, we show that the correlation between the size of the “bump” feature and β _XY can be understood as a result of chemical mixing due to large-scale Rayleigh–Taylor instabilities.

Herein, we introduce HydrothermalFoam, a three-dimensional hydro-thermo-transport model designed to resolve fluid flow within submarine hydrothermal circulation systems. HydrothermalFoam has been developed on the OpenFOAM platform, which is a finite-volume-based C++ toolbox for fluid-dynamic simulations and for developing customized numerical models that provides access to state-of-the-art parallelized solvers and to a wide range of pre- and post-processing tools. We have implemented a porous media Darcy flow model with associated boundary conditions designed to facilitate numerical simulations of submarine hydrothermal systems. The current implementation is valid for single-phase fluid states and uses a pure-water equation of state (IAPWS-97). We here present the model formulation; OpenFOAM implementation details; and a sequence of 1-D, 2-D, and 3-D benchmark tests. The source code repository further includes a number of tutorials that can be used as starting points for building specialized hydrothermal flow models. The model is published under the GNU General Public License v3.0.

Fast-changing cities need efficient management. Accurate classification of urban functional zone (UFZ) can provide important reference for cities management. Remote sensing imagery (RSI) is large scale, high resolution and fast update, which can provide massive data for UFZ extraction. However, UFZ are more concerned with social attributes such as industrial production and commercial activities, while images can only provide visual features, which is not enough for an elaborate UFZ classification. To solve this problem, in this paper, we combine RSI and point of interest (POI) data together for UFZ classification, and propose a Social Information Fused Urban Functional Zones Classification Network (SIF-Net). For RSI, we simply use a Xception CNNs network extract the visual information. For POI data, we first build a coarse heatmap for each type of POI (e.g. retail, apartment…), and then combine them as a POI tensor. Afterward, we use a channel attention module (CAM) based CNN model to fuse heatmaps from each type of POI, and then build a fine distribution of UFZ as the social information. Finally, we fuse the visual information extracted from RSI and social information extracted from POI by concatenating them. By fusing this two complementary information, our method makes up for the shortcomings of extracting UFZ based on RSI and general CNNs only. Compared with current state-of-the-art methods, experiments show that the proposed SIF-Net can significantly improve the UFZ classification result.

Fixed-time artificial insemination (FTAI) technology uses exogenous reproductive hormones to regulate the sexual cycle and ovulation of sows without oestrus identification, which improves the sow breeding utilisation rate, reduces the number of non-productive days, and elevates the efficiency of pig farm management. In this study, we aimed to optimise FTAI procedures. Healthy 190-day-old and about 90 kg Large White × Landrace crossing breed replacement gilts (n = 166) which were of unknown reproductive status were randomly selected and divided into three groups: a control group (n = 62), an eCG-15D group in which the gilts were pretreated with equine chorionic gonadotropin (eCG) injection 15 days before starting FTAI (n = 50), and an eCG-20D group pretreated with eCG injection 20 days before starting FTAI (n = 54). All three groups were then subjected to the same conventional FTAI procedure. Pigs were orally administered Altrenogest (ALT, 20 mg per pig per day) for 18 days and then 42 h after ALT feeding was stopped, they were injected with 1 000 IU eCG followed by 100 μg GnRH 80 h later. The gilts were inseminated for the first time 24 h after gonadotropin-releasing hormone (GnRH) injection and then again 16 h later. After 42 h of ALT feeding, gilts in the eCG-15D group displayed a higher follicular diameter until artificial insemination (AI) than those from the other groups (P

Abstract Dawn storms are among the brightest events in the Jovian aurorae. Up to now, they had only been observed from Earth‐based observatories, only showing the Sun‐facing side of the planet. Here, we show for the first time global views of the phenomenon, from its initiation to its end and from the nightside of the aurora onto the dayside. Based on Juno's first 20 orbits, some patterns now emerge. Small short‐lived spots are often seen a couple of hours before the main emission starts to brighten and evolve from a straight arc to a more irregular one in the midnight sector. As the whole feature rotates dawn‐ward, the arc then separates into two arcs with a central initially void region that is progressively filled with emissions. A gap in longitude then often forms before the whole feature dims. Finally, it transforms into an equatorward‐moving patch of auroral emissions associated with plasma injection signatures. Some dawn storms remain weak and never fully develop. We also found cases of successive dawn storms within a few hours. Dawn storms thus share many fundamental features with the auroral signatures of the substorms at Earth, despite the substantial differences between the dynamics of the magnetosphere at the two planets.

The main auroral emission at Jupiter generally appears as a quasi-closed curtain centered around the magnetic pole. This auroral feature, which accounts for approximately half of the total power emitted by the aurorae in the ultraviolet range, is related to corotation enforcement currents in the middle magnetosphere. Early models for these currents assumed axisymmetry, but significant local time variability is obvious on any image of the Jovian aurorae. Here we use far-UV images from the Hubble Space Telescope to further characterize these variations on a statistical basis. We show that the dusk side sector is ~ 3 times brighter than the dawn side in the southern hemisphere and ~ 1.1 brighter in the northern hemisphere, where the magnetic anomaly complicates the interpretation of the measurements. We suggest that such an asymmetry between the dawn and the dusk sectors could be the result of a partial ring current in the nightside magnetosphere.

The aurorae at Jupiter are made up of many different features associated with a variety of generation mechanisms. The main auroral emission, also known as the main oval, is the most prominent of them as it accounts for approximately half of the total power emitted by the aurorae in the ultraviolet range. The energy of the precipitating electrons is a crucial parameter to characterize the processes at play which give rise to these auroral emissions, and the altitude of the emissions directly depends on this energy. Here we make use of far-UV (FUV) images acquired with the Advanced Camera for Surveys on board the Hubble Space Telescope and spectra acquired with the Space Telescope Imaging Spectrograph to measure the vertical profile of the main emissions. The altitude of the brightness peak as seen above the limb is ~ 400 km, which is significantly higher than the 250 km measured in the post-dusk sector by Galileo in the visible domain. However, a detailed analysis of the effect of hydrocarbon absorption, including both simulations and FUV spectral observations, indicates that FUV apparent vertical profiles should be considered with caution, as these observations are not incompatible with an emission peak located at 250 km. The analysis also calls for spectral observations to be carried out with an optimized geometry in order to remove observational ambiguities.

Selenium (Se) is a significant trace element for human and livestock animals because of its physiological functions. Se in plants, especially in the crop plants, is treated as a critical dietary source. The effects of foliar spray together with soil application of Se on Se uptake, distribution in common buckwheat (Fagopyrum esculentum M.) plants were discussed in this study. The results showed that both foliar spray and soil application of Se increased Se uptake in common buckwheat significantly (P < 0.05). The highest Se content was observed in leaves (113.37-690.75 μg/kg), followed by roots (28.98-283.78 μg/kg), grains (26.49-135.89 μg/kg) and stems (23.19-86.80 μg/kg). Se content in grains had the highest correlation coefficient (0.827 and 0.845) with soil Se application treatments. Grain yield of F1 (5 g Se/ha for foliar spray) was 3.65% and 10.25% higher than that of F0 (0 g Se/ha for foliar spray) in two study years, respectively. Under soil Se application conditions, mean grain yields fluctuated from 2890.5-3058.6 kg/ha, 2966.4-3352.8 kg/ha in 2012/2013, respectively. These results indicated a significant interaction effect of foliar spray Se and soil Se application on Se accumulation in common buckwheat. Appropriate Se application might improve common buckwheat grain yield.

This paper presents the analysis of Ricean K-factor for wideband high-speed railway channels at 2.35 GHz, based on radio channel measurements under viaduct and U-shape cutting scenarios. We characterize the K-factor from the perspective of narrowband, wideband and delay, according to the measured channel responses. The timefrequency varying narrowband K-factors in the two scenarios are analyzed and compared. A distance-based statistical narrowband K-factor model that covers the frequency variability is proposed. Then, the channel bandwidth dependent property of the wideband K-factor is investigated and we establish a simple bandwidth-based wideband K-factor model. Moreover, the K-factor for each delay bin is discussed. These results are provided for use in wireless system design and channel modeling of high-speed railway.

Orthogonal frequency-division multiplexing (OFDM) is well-known as a high-bit-rate transmission technique, but the Doppler frequency offset due to the high speed movement destroys the orthogonality of the subcarriers resulting in the intercarrier interference (ICI), and degrades the performance of the system at the same time. In this paper a novel OFDM channel estimation algorithm with ICI mitigation based on the ICI self-cancellation scheme is proposed. With this method, a more accurate channel estimation is obtained by comb-type double pilots and then ICI coefficients can be obtained to mitigate the ICI on each subcarrier under the assumption that the channel impulse response (CIR) varies in a linear fashion. The theoretical analysis and simulation results show that the bit error rate (BER) and spectral efficiency performances are improved significantly under high-speed mobility conditions (350 km/h – 500 km/h) in comparison to ZHAO’s ICI self-cancellation scheme.

This paper deals with carrier synchronization problem in coherent communication system, such as BPSK and QPSK. First, this paper surveys and analyzes currently existing carrier synchronization algorithms and relevant receiver structures. After an analysis of those methods, a novel algorithm called feedback compensation is proposed, including the receiver structures based on this new synchronization algorithm. This new algorithm can not only simplify the signal processing stage but also decouple the demodulator and carrier synchronization module. At last, FPGA implementation results are presented and discussed.

Due to implementation complexity, the transform domain channel estimation based on training symbols or comb-type pilots has been paid more attention because of its efficient algorithm FFT/IFFT. However, in a comb-type OFDM system, the length of the channel impulse response is much smaller than the pilot number. In this case, the comb-pilot transform domain channel estimation only works as interpolation like the Least Squares (LS) algorithm, but loses the noise suppression function. In this paper, we propose a novel frequency diversity channel estimation method via grouped pilots combining. With this estimator, not only the channel frequency response on non-pilot subcarriers can be interpolated, but also the noise can be better suppressed. Moreover, it does not need prior statistical characteristics of the wireless channel.

We simulate auroral electron precipitation into the Jovian atmosphere in which electron multi-directional scattering and energy degradation processes are treated exactly with a Monte Carlo technique. We make a parameterization of the calculated ionization rate of the neutral gas by electron impact in a similar way as used for the Earth's aurora. Our method allows the altitude distribution of the ionization rate to be obtained as a function of an arbitrary initial energy spectrum in the range of 1–200 keV. It also includes incident angle dependence and an arbitrary density distribution of molecular hydrogen. We show that there is little dependence of the estimated ionospheric conductance on atomic species such as H and He. We compare our results with those of recent studies with different electron transport schemes by adapting our parameterization to their atmospheric conditions. We discuss the intrinsic problem of their simplified assumption. The ionospheric conductance, which is important for Jupiter's magnetosphere-ionosphere coupling system, is estimated to vary by a factor depending on the electron energy spectrum based on recent observation and modeling. We discuss this difference through the relation with field-aligned current and electron spectrum.

Six genes, which encode enzymes involved in ascorbic acid (AsA) biosynthesis, including guanosine diphosphate (GDP)-mannose pyrophosphorylase (GMP), GDP-mannose-3',5'-epimerase (GME), GDP-galactose guanylyltransferase (GGT), L-galactose-1-phosphate phosphatase (GPP), L-galactose dehydrogenase (GDH) and L-galactono-1,4-lactone dehydrogenase (GLDH) were transformed into Arabidopsis thaliana, to evaluate the contribution of each gene to AsA accumulation. Additionally, two combinations, GGT-GPP and GGT-GLDH, were co-transformed into Arabidopsis with a reliable double-gene transformation system. AsA content of GGT transgenic lines was 2.9-fold higher as compared to the control, and co-transformation led up to 4.1-fold AsA enhancement. These results provided further evidence that GGT is the key enzyme in plant AsA biosynthesis.