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In this paper, a valve piezoelectric pump structure is proposed, which provides a method for the cooling of metallurgical equipment and avoids the hidden danger of damage to key components due to long-term exposure to high temperatures. In this paper, the research results of simulated flow rate and test flow rate of valved piezoelectric pump are introduced. The results show that the flow rate of the pump is sensitive to the influence of driving voltage, and it has certain feasibility for the cooling of metallurgical equipment.

Multi-componentization can further improve the heating resistance of Cu–Ni–Al alloys, enabling them to withstand more demanding situations. Unfortunately, the limited researches have been done on the wear and corrosion resistance of the heat-resistant Cu–Ni–Al alloys, resulting in the lack of relevant evidence in the practical application. In this work, a comparative study of differential types of trace element, Si (the stronger enthalpy interaction element), Sn (the weaker enthalpy interaction element) Cr or Zr (grain boundary strengthening element), effects on microstructure, wear and corrosion resistance will be done, Furthermore, the effect of different trace elements on the surface electron work function and electrochemical behavior of Cu–Ni–Al alloys is reflected by SPM surface potential model. The results indicate that the precipitation of dual nano-phase and accelerated precipitation of γ′ phase can be realized through the addition of Si, Sn, Cr and Zr, in which the value of δγ-γ′ increase sharply after adding Si and it is not conducive to the preservation of cuboidal γ′ phase. The addition of Si, Cr and Zr can improve electron work function distribution and mechanical property, wear, and corrosion resistance of the alloys, in which Si is more conducive to the improvement of wear resistance and mechanical properties of the alloy, while the alloy with Cr and Zr shows the excellent corrosion resistance. The addition of Sn will weaken the enthalpy interaction of the alloy system, reduce the electron work function of the alloy, and have adverse effects on the wear and corrosion resistance of the alloy.

The Chlorophyll-a (Chla) concentration is an important parameter characterizing the water quality of rivers and lakes. Satellite remote sensing provides new opportunities for the quantitative monitoring of Chla concentration in large-scale water bodies. In this study, Sentinel-2 satellite remote sensing data integrated on the Google Earth Engine (GEE) remote sensing big data platform are employed, along with hourly measured water quality site data, to establish a quantitative inversion model for Chla concentration water quality parameters in Jiujiang City within Jiangxi Province, China. The Chla concentration is estimated for each quarter from 2020 to 2022, and the spatial distribution is analyzed, revealing the changing trend of Chla concentration over the past three years. The key findings are as follows: (1) The quantitative inversion model for Chla concentration has been validated with measured data, achieving a model accuracy of 0.53; (2) The spatial inversion results of Chla concentration exhibit an increasing trend that is consistent with actual measurement site results; (3) Owing to the influence of human activities and the peak-low water level of rivers and lakes, Chla concentration shows a discernible seasonal variation pattern. This methodology offers a new perspective for analyzing the seasonal variation characteristics of Chla concentration in rivers and lakes, providing valuable insights for the sustainable management of river and lake water quality.

Urban lakes serve an indispensable role in maintaining the ecological balance of cities, ensuring flood safety, and providing recreational spaces for tourism. With the development of human activities and economic, the extent of urban lakes are inevitably influenced. Currently, the ability to detect detailed temporal changes in urban lake areas using high resolution data still has limitations. This study proposed a novel method by combining time series Gaofen-1 (GF-1) remote sensing data and random forest machine learning algorithm to explore the urban lakes change Zhushan Lake located in Wuhan. The research conducted the extraction of surface water for Zhushan Lake and its surrounding pit-ponds from 2013 to 2020. And then, a quantitative analysis of the characteristics and driving factors of lake changes is conducted. We find that (1) the accuracy of surface water extraction using the random forest classification method consistently exceeded 96%. The Kappa coefficient ranges from a minimum of 0.86 to a maximum of 0.99. (2) A noticeable decline was observed in the water areas of Zhushan Lake and its surrounding pit-ponds, predominantly along the northwestern shoreline and in the eastern pond regions. This decline is primarily attributed to pressures from building construction. The methodology proposed in this study is suitable for the area management of lakes in urban areas.

Feature matching plays a crucial role in 3D reconstruction to provide correspondences between overlapped images. The accuracy and efficiency of feature matching significantly impact the performance of 3D reconstruction. The widely used framework with the exhaustive nearest neighbor searching (NNS) between descriptors and RANSAC-based geometric estimation is, however, low-efficient and unreliable for large-scale UAV images. Inspired by indexing-based NNS, this paper implements an efficient feature matching method for large-scale images based on Cascade Hashing and local geometric constraints. Our proposed method improves upon traditional feature matching approaches by introducing a combination of image retrieval, data scheduling, and GPU-accelerated Cascade Hashing. Besides, it utilizes a local geometric constraint to filter matching results within a matching framework. On the one hand, the GPU-accelerated Cascade Hashing technique generates compact and discriminative hash codes based on image features, facilitating the rapid completion of the initial matching process, and significantly reducing the search space and time complexity. On the other hand, after the initial matching is completed, the method employs a local geometric constraint to filter the initial matching results, enhancing the accuracy of the matching results. This forms a three-tier framework based on data scheduling, GPU-accelerated Cascade Hashing, and local geometric constraints. We conducted experiments using two sets of large-scale UAV image data, comparing our method with SIFTGPU to evaluate its performance in initial matching, outlier rejection, and 3D reconstruction. The results demonstrate that our method achieves a feature matching speed 2.0 times that of SIFTGPU while maintaining matching accuracy and producing comparable reconstruction results. This suggests that our method holds promise for efficiently addressing large-scale image matching.

The presence of exceptionally old ice and relative ease of access make Antarctic blue-ice areas (BIAs) attractive paleoclimate archives. However, only a handful of BIAs, mostly situated in West Antarctica and along the Transantarctic Mountains, have been investigated for this purpose. Here, we present the age of surface ice from the Grove Mountains BIA in Princess Elizabeth Land, East Antarctica, determined by measuring 81Kr in the trapped air. Two samples yield an average age of 143-29+33 kyr. Together with the reported terrestrial age of a chondrite, we conclude that the Grove Mountains BIA holds considerable potential for paleoclimate studies.

Magnetic reconnection is a fundamental mechanism for energy conversion in the realms of space physics, astrophysics, and plasma physics. Over the past few decades, obtaining analytical solutions for three-dimensional (3D) magnetic reconnection has remained a challenging endeavor. Due to the complexity and nonlinearity of the equations, analytical solutions can only be obtained when specific spatiotemporal distributions of magnetic fields or plasma flows are provided. Particularly, the evolution of reconnection flows in time-dependent 3D reconnection has not been analytically discussed. Additionally, quasi-steady magnetic reconnection persisting for several hours can be observed in the turbulent solar wind, which raises an important question: can steady reconnection flows theoretically exist in a time-dependent 3D magnetic reconnection model? In this study, a generalized analytical model for time-dependent kinematic 3D magnetic reconnection has been constructed. In the framework of pure analytical approach, it is firstly demonstrated that steady reconnection outflows can theoretically exist within a time-varying magnetic field. We have also analytically discussed the possibility of the existence of quasi-steady reconnection flows in 3D magnetic reconnection for turbulent magnetic fields in the solar wind. These findings broaden our understanding of the stability and necessary conditions for time-dependent 3D magnetic reconnection, offering new insights into quasi-steady reconnection phenomena in real cosmic environments.

The image quality received for clinical evaluation is often suboptimal. The goal is to develop an image quality analysis tool to assess patient- and primary care physician–derived images using deep learning model. Dataset included patient- and primary care physician–derived images from August 21, 2018 to June 30, 2022 with 4 unique quality labels. VGG16 model was fine tuned with input data, and optimal threshold was determined by Youden’s index. Ordinal labels were transformed to binary labels using a majority vote because model distinguishes between 2 categories (good vs bad). At a threshold of 0.587, area under the curve for the test set was 0.885 (95% confidence interval = 0.838–0.933); sensitivity, specificity, positive predictive value, and negative predictive value were 0.829, 0.784, 0.906, and 0.645, respectively. Independent validation of 300 additional images (from patients and primary care physicians) demonstrated area under the curve of 0.864 (95% confidence interval = 0.818–0.909) and area under the curve of 0.902 (95% confidence interval = 0.85–0.95), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for the 300 images were 0.827, 0.800, 0.959, and 0.450, respectively. We demonstrate a practical approach improving the image quality for clinical workflow. Although users may have to capture additional images, this is offset by the improved workload and efficiency for clinical teams.

Fog/cloud drops and aerosol liquid water are important sites for the transformations of atmospheric species, largely through reactions with photoformed oxidants such as the hydroxyl radical (⚫OH), singlet molecular oxygen (1O2∗), and oxidizing triplet excited states of organic matter (3C∗). Despite their importance, few studies have measured these oxidants or their seasonal variations. To address this gap, we collected ambient PM2.5 from Davis, California, over the course of a year and measured photooxidant concentrations and light absorption in dilute aqueous extracts. Mass absorption coefficients (MACs) normalized by dissolved organic carbon range from 0.4–3.8 m2 per gram C at 300 nm. Concentrations of ⚫OH, 1O2∗, and 3C∗ in the extracts range from (0.2–4.7) × 10−15 M, (0.7–45) × 10−13 M, and (0.03–7.9) × 10−13 M, respectively, with biomass burning brown carbon playing a major role in light absorption and the formation of 1O2∗ and 3C∗. Extrapolating photooxidant kinetics from our dilute particle extracts to concentrated aerosol liquid water (ALW) conditions gives an estimated ⚫OH concentration of 7 × 10−15 M and ranges for 1O2∗ and 3C∗ of (0.6–7) × 10−12 M and (0.2–1) × 10−12 M, respectively. Compared to the results in Kaur et al. (2019), our ALW predictions show roughly 10 times higher ⚫OH, up to 5 times higher 3C, and 1O2∗ concentrations that are lower by factors of 20–100. These concentrations suggest that 3C∗ and 1O2∗ in ALW dominate the processing of organic compounds that react quickly with these oxidants (e.g., phenols and furans, respectively), while ⚫OH is more important for less reactive organics.

Structure from Motion (SfM) is a 3D reconstruction framework that has achieved great success on large-scale Unmanned Aerial Vehicle (UAV) images. Due to the high time consumption of feature matching, a matching candidate subset is obtained by image retrieval to improve efficiency. Bag of Word (BoW) based image retrieval has been widely used in SfM systems, but the large number of local features and the high dimension of the BoW vector cause the retrieval method time-consuming. Vector of Locally Aggregated Descriptors (VLAD) and learning-based NetVLAD perform well in image retrieval, and these vector representation methods are evaluated in this study. After images are transformed into vectors, Nearest Neighbour (NN) searching methods like Brute-force and KD-Tree are used to find similar images. But as the number of images and the vector dimension increase, Approximate Nearest Neighbour (ANN) searching methods like Hierarchical Navigable Small World (HNSW) and Locality-Sensitive Hashing (LSH) are considered to replace NN searching to avoid efficiency degradation. These vector searching methods are also evaluated in this study. The test results demonstrate that the optimal method VLAD with HNSW can speed up about 100 times in finding matching candidate subset. A view graph that guides scene partition and sub-scene reconstruction in parallel SfM can be created by the optimal method. With this view graph construction method, the efficiency of SfM is significantly improved.

Dense matching plays an important role in 3D modeling from satellite images. Its purpose is to establish pixel-by-pixel correspondences between two stereo images. The most well-known algorithm is the semi-global matching (SGM), which can generate high-quality 3D models with high computational efficiency. Due to the complex coverage and imaging condition, SGM cannot cope with these situation well. In recent years, deep learning-based stereo matching has attracted wide attention and shown overwhelming benefits over traditional algorithms in terms of precision and completeness. However, existing models are usually evaluated by using close-ranging datasets. Thus, this study investigates the recent deep learning models and evaluate their performance on both close-ranging and satellite image datasets. The results demonstrate that deep learning network can better adapt to the satellite dataset than the typical SGM. Meanwhile, the generalization ability of deep learning-based models is still low for the real application at recent time.

The EPICA (European Project for Ice Coring in Antarctica) Dome C (EDC) ice core drilling in East Antarctica reaches a depth of 3260 m. The reference EDC chronology, the AICC2012 (Antarctic Ice Core Chronology 2012), provides an age vs. depth relationship covering the last 800 kyr (thousands of years), with an absolute uncertainty rising up to 8000 years at the bottom of the ice core. The origins of this relatively large uncertainty are twofold: (1) the δ18Oatm, δO2/N2 and total air content (TAC) records are poorly resolved and show large gaps over the last 800 kyr, and (2) large uncertainties are associated with their orbital targets. Here, we present new highly resolved δ18Oatm, δO2/N2 and δ15N measurements for the EDC ice core covering the last five glacial–interglacial transitions; a new low-resolution TAC record over the period 440–800 ka BP (ka: 1000 years before 1950); and novel absolute 81Kr ages. We have compiled chronological and glaciological information including novel orbital age markers from new data on the EDC ice core as well as accurate firn modeling estimates in a Bayesian dating tool to construct the new AICC2023 chronology. For the first time, three orbital tools are used simultaneously. Hence, it is possible to observe that they are consistent with each other and with the other age markers over most of the last 800 kyr (70 %). This, in turn, gives us confidence in the new AICC2023 chronology. The average uncertainty in the ice chronology is reduced from 1700 to 900 years in AICC2023 over the last 800 kyr (1σ). The new timescale diverges from AICC2012 and suggests age shifts reaching 3800 years towards older ages over marine isotope stages (MISs) 5, 11 and 19. But the coherency between the new AICC2023 timescale and independent chronologies of other archives (Italian Lacustrine succession from Sulmona Basin, Dome Fuji ice core and northern Alpine speleothems) is improved by 1000 to 2000 years over these time intervals.

Aerosol liquid water (ALW) is a unique reaction medium, but its chemistry is poorly understood. For example, little is known of photooxidant concentrations – including hydroxyl radicals (⚫OH), singlet molecular oxygen (1O2*), and oxidizing triplet excited states of organic matter (3C*) – even though they likely drive much of ALW chemistry. Due to the very limited water content of particles, it is difficult to quantify oxidant concentrations in ALW directly. To predict these values, we measured photooxidant concentrations in illuminated aqueous particle extracts as a function of dilution and used the resulting oxidant kinetics to extrapolate to ALW conditions. We prepared dilution series from two sets of particles collected in Davis, California: one from winter (WIN) and one from summer (SUM). Both periods are influenced by biomass burning, with dissolved organic carbon (DOC) in the extracts ranging from 10 to 495 mg C L−1. In the winter sample, the ⚫OH concentration is independent of particle mass concentration, with an average value of 5.0 (± 2.2) × 10−15 M, while in summer ⚫OH increases with DOC in the range (0.4–7.7) × 10−15 M. In both winter and summer samples, 3C* concentrations increase rapidly with particle mass concentrations in the extracts and then plateau under more concentrated conditions, with a range of (0.2–7) × 10−13 M. WIN and SUM have the same range of 1O2* concentrations, (0.2–8.5) × 10−12 M, but in WIN the 1O2* concentration increases linearly with DOC, while in SUM 1O2* approaches a plateau. We next extrapolated the relationships of oxidant formation rates and sinks as a function of particle mass concentration from our dilute extracts to the much more concentrated condition of aerosol liquid water. Predicted ⚫OH concentrations in ALW (including mass transport of ⚫OH from the gas phase) are (5–8) × 10−15 M, similar to those in fog/cloud waters. In contrast, predicted concentrations of 3C* and 1O2* in ALW are approximately 10 to 100 times higher than in cloud/fogs, with values of (4–9) × 10−13 M and (1–5) × 10−12 M, respectively. Although ⚫OH is often considered the main sink for organic compounds in the atmospheric aqueous phase, the much higher concentrations of 3C* and 1O2* in aerosol liquid water suggest these photooxidants will be more important sinks for many organics in particle water.

Rock moisture, which is a hidden component of the terrestrial hydrological cycle, has received little attention. In this study, frequency domain reflectometry is used to monitor fluctuating rock water content (RWC) in a sandstone cave of the Yungang Grottoes, China. We identified two major cycles of rock moisture addition and depletion, one in summer affected by air vapour concentration and the other in winter caused by freezing–thawing. For the summer-time RWC, by using the long short-term memory (LSTM) network and the SHapley Additive exPlanations (SHAP) method, we find relative humidity, air temperature and wall temperature have contributions to rock moisture, and there is a good match between predicted and measured RWC using the three variables as model inputs. Moreover, by using summer-time vapour concentration and the difference between dew point temperature and wall temperature as input variables of the LSTM network, which belongs to physics-informed machine learning, the predicted RWC has a better agreement with the measured RWC, with increased Nash–Sutcliffe efficiency (NSE) and decreased mean absolute error (MAE) and root mean square error (RMSE). After identifying the causal factors of RWC fluctuations, we also identified the mechanism controlling the inter-day fluctuations of vapour condensation. The increased vapour concentration accompanying a precipitation event leads to transport of water vapour into rock pores, which is subsequently adsorbed onto the surface of rock pores and then condensed into liquid water. With the aid of the physics-informed deep learning model, this study increases understanding of sources of water in caves, which would contribute to future strategies of alleviating weathering in caves.

The nearby radio galaxy M87 is a very high-energy (VHE) gamma-ray emitter established by observations with ground-based gamma-ray detectors. Here we report the long-term monitoring of M87 from 2021 to 2024 with the Large High Altitude Air Shower Observatory (LHAASO). M87 has been detected by LHAASO with a statistical significance ∼ 9 σ . The observed energy spectrum extends to 20 TeV, with a possible hardening at ∼20 TeV and then a clear softening at higher energies. Assuming that the intrinsic spectrum is described by a single power law up to 20 TeV, a tight upper bound on the extragalactic background light intensity is obtained. A strong VHE flare lasting 8 days, with a rise time of ${\tau }_{r}^{\mathrm{rise}}=1.05\pm 0.49$ days and decay time of ${\tau }_{d}^{\mathrm{decay}}=2.17\pm 0.58$ days, was found in early 2022. A possible GeV flare is seen also in Fermi Large Area Telescope data during the VHE flare period. The variability time as short as 1 day seen in the LHAASO data suggests a compact emission region with a size of ∼3 × 10 ^15 δ cm ( δ being the Doppler factor of the emitting region), corresponding to a few Schwarzschild radii of the central supermassive black hole in M87. The continuous monitoring of the source reveals a duty cycle of ∼1% for VHE flares with a flux above 10 ^−11 erg cm ^−2 s ^−1 .

The first source catalog of the Large High Altitude Air Shower Observatory (LHAASO) reported the detection of a very high energy gamma-ray source, 1LHAASO J1219+2915. This Letter presents a further detailed study of the spectral and temporal behavior of this pointlike source. The best-fit position of the TeV source (R.A. = 185.°05 ± 0.°04, decl. = 29.°25 ± 0.°03) is compatible with NGC 4278 within ∼0.°03. Variation analysis shows an indication of variability on a timescale of a few months in the TeV band, which is consistent with low-frequency observations. Based on these observations, we report the detection of TeV γ -ray emissions from this low-luminosity active galactic nucleus. The observation by LHAASO's Water Cherenkov Detector Array during the active period has a significance level of 8.8 σ with a best-fit photon spectral index Γ = 2.56 ± 0.14 and a flux f _1–10 TeV = (7.0 ± 1.1 _sta ± 0.35 _syst ) × 10 ^−13 photons cm ^−2 s ^−1 , or approximately 5% of the Crab Nebula. The discovery of VHE gamma-ray emission from NGC 4278 indicates that compact, weak radio jets can efficiently accelerate particles and emit TeV photons.

While gas-phase reactions are well established to have significant impacts on the mass concentration, chemical composition, and optical properties of secondary organic aerosol (SOA), the aqueous-phase aging of SOA remains poorly understood. In this study, we performed a series of long-duration photochemical aging experiments to investigate the evolution of the composition and light absorption of the aqueous SOA (aqSOA) from guaiacyl acetone (GA), a semivolatile phenolic carbonyl that is common in biomass burning smoke. The aqSOA was produced from reactions of GA with hydroxyl radical (•OH-aqSOA) or a triplet excited state of organic carbon (3C∗-aqSOA) and was then photoaged in water under conditions that simulate sunlight exposure in northern California for up to 48 h. The effects of increasing aqueous-phase •OH or 3C∗ concentration on the photoaging of the aqSOA were also studied. High-resolution aerosol mass spectrometry (HR-AMS) and UV–Vis spectroscopy were utilized to characterize the composition and the light absorptivity of the aqSOA and to track their changes during aging. Compared to •OH-aqSOA, the 3C∗-aqSOA is produced more rapidly and shows less oxidation, a greater abundance of oligomers, and higher light absorption. Prolonged photoaging promotes fragmentation and the formation of more volatile and less light-absorbing products. More than half of the initial aqSOA mass is lost, and substantial photobleaching occurs after 10.5 h of prolonged aging under simulated sunlight illumination for 3C∗-aqSOA and 48 h for •OH-aqSOA. By performing positive matrix factorization (PMF) analysis of the combined HR-AMS and UV–Vis spectral data, we resolved three generations of aqSOA with distinctly different chemical and optical properties. The first-generation aqSOA shows significant oligomer formation and enhanced light absorption at 340–400 nm. The second-generation aqSOA is enriched in functionalized GA species and has the highest mass absorption coefficients in 300–500 nm, while the third-generation aqSOA contains more fragmented products and is the least light absorbing. These results suggest that intermediately aged phenolic aqSOA is more light absorbing than other generations, and that the light absorptivity of phenolic aqSOA results from a competition between brown carbon (BrC) formation and photobleaching, which is dependent on aging time. Although photoaging generally increases the oxidation of aqSOA, a slightly decreased O/C of the •OH-aqSOA is observed after 48 h of prolonged photoaging with additional •OH exposure. This is likely due to greater fragmentation and evaporation of highly oxidized compounds. Increased oxidant concentration accelerates the transformation of aqSOA and promotes the decay of BrC chromophores, leading to faster mass reduction and photobleaching. In addition, compared with •OH, photoaging by 3C∗ produces more low-volatility functionalized products, which counterbalances part of the aqSOA mass loss due to fragmentation and evaporation.

Abstract Solar flares are one of the severest solar activities that have important effects on near-Earth space. Previous studies have shown that flight arrival delays increase as a result of solar flares, but the intrinsic mechanism behind this relationship is still unknown. In this study, we conducted a comprehensive analysis of flight departure delays during 57 solar X-ray events by using a huge amount of flight data (~ 5 × 106 records) gathered over a 5-year period. It is found that the average flight departure delay time during solar X-ray events increased by 20.68% (7.67 min) compared to quiet periods. Our analysis also revealed apparent time and latitude dependencies, with flight delays being more serious on the dayside than on the nightside and longer (shorter) delays tending to occur in lower (higher) latitude airports during solar X-ray events. Furthermore, our results suggest that the intensity of solar flares (soft X-ray flux) and the Solar Zenith Angle directly modulate flight departure delay time and delay rate. These results indicate that communication interferences caused by solar flares directly affect flight departure delays. This work expands our conventional understanding of the impacts of solar flares on human society and provides new insights for preventing or coping with flight delays.

The ground-based Global Positioning System (GPS) has been used extensively to retrieve integrated water vapour (IWV) and has been adopted as a unique tool for the assessments of atmospheric reanalyses. In this study, we investigated the multi-temporal-scale variabilities and trends of IWV over Europe by using IWV time series from 108 GPS stations for more than 2 decades (1994–2018). We then adopted the GPS IWV as a reference to assess six commonly used atmospheric reanalyses, namely the Climate Forecast System Reanalysis (CFSR); ERA5; ERA-Interim; the Japanese 55-year Reanalysis (JRA-55); the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2); and NCEP-DOE AMIP-II Reanalysis (NCEP-2). The GPS results show that the peaks of the diurnal harmonics are within 15:00–21:00 in local solar time at 90 % of the stations. The diurnal amplitudes are 0–1.2 kg m−2 (0 %–8 % of the daily mean IWV), and they are found to be related to seasons and locations with different mechanisms, such as solar heating, land–sea breeze, and orographic circulation. However, mismatches in the diurnal cycle of ERA5 IWV between 09:00 and 10:00 UTC as well as between 21:00 and 22:00 UTC were found and evaluated for the first time, and they can be attributed to the edge effect in each ERA5 assimilation cycle. The average ERA5 IWV shifts are −0.08 and 0.19 kg m−2 at the two epochs, and they were found to be more significant in summer and in the Alps and in Eastern and central Europe in some cases. Nevertheless, ERA5 outperforms the other reanalyses in reproducing diurnal IWV anomalies at all the 1-, 3-, and 6-hourly temporal resolutions. ERA5 is also superior to the others in modelling the annual cycle and linear trend of IWV. For instance, the IWV trend differences between ERA5 and GPS are quite small, with a mean value and a standard deviation of 0.01 % per decade and 0.97 % per decade, respectively. However, due to significant discrepancies with respect to GPS, CFSR and NCEP-2 are not recommended for the analysis of IWV trends over southern Europe and the whole of Europe, respectively.

Abstract Although the sun is really far away from us, some solar activities could still influence the performance and reliability of space-borne and ground-based technological systems on Earth. Those time-varying conditions in space caused by the sun are also called solar storm or space weather. It is known that aviation activities can be affected during solar storms, but the exact effects of space weather on aviation are still unclear. Especially how the flight delays, the top topic concerned by most people, will be affected by space weather has never been thoroughly researched. By analyzing huge amount of flight data (~ 4 × 106 records), for the first time, we quantitatively investigate the flight delays during space weather events. It is found that compared to the quiet periods, the average arrival delay time and 30-min delay rate during space weather events are significantly increased by 81.34% and 21.45% respectively. The evident negative correlation between the yearly flight regularity rate and the yearly mean total sunspot number during 22 years also confirms such correlation. Further studies show that the flight delay time and delay rate will monotonically increase with the geomagnetic field fluctuations and ionospheric disturbances. These results indicate that the interferences in communication and navigation during space weather events may be the most probable reason accounting for the increased flight delays. The above analyses expand the traditional field of space weather research and could also provide us with brand new views for improving the flight delay predications.

We developed a high-quality global integrated water vapour (IWV) dataset from 12 552 ground-based global positioning system (GPS) stations in 2020. It consists of 5 min GPS IWV estimates with a total number of 1 093 591 492 data points. The completeness rates of the IWV estimates are higher than 95 % at 7253 (58 %) stations. The dataset is an enhanced version of the existing operational GPS IWV dataset provided by the Nevada Geodetic Laboratory (NGL). The enhancement is reached by employing accurate meteorological information from the fifth generation of European ReAnalysis (ERA5) for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. A dedicated data screening algorithm is also implemented. The GPS IWV dataset has a good agreement with in situ radiosonde observations at 182 collocated stations worldwide. The IWV biases are within ±3.0 kg m−2 with a mean absolute bias (MAB) value of 0.69 kg m−2. The standard deviations (SD) of IWV differences are no larger than 3.4 kg m−2. In addition, the enhanced IWV product shows substantial improvements compared to NGL's operational version, and it is thus recommended for high-accuracy applications, such as research of extreme weather events and diurnal variations of IWV and intercomparisons with other IWV retrieval techniques. Taking the radiosonde-derived IWV as reference, the MAB and SD of IWV differences are reduced by 19.5 % and 6.2 % on average, respectively. The number of unrealistic negative GPS IWV estimates is also substantially reduced by 92.4 % owing to the accurate zenith hydrostatic delay (ZHD) derived by ERA5. The dataset is available at https://doi.org/10.5281/zenodo.6973528 (Yuan et al., 2022).

The quasi-biennial oscillation (QBO), as the dominant mode in the equatorial stratosphere, modulates the dynamical circulation and the distribution of trace gases in the stratosphere. While the zonal mean QBO signals in stratospheric ozone have been relatively well documented, the zonal (longitudinal) differences in the QBO ozone signals have been less studied. Using satellite-based total column ozone (TCO) data from 1979 to 2020, zonal mean ozone data from 1984 to 2020, three-dimensional (3-D) ozone data from 2002 to 2020, and ERA5 reanalysis and model simulations from 1979 to 2020, we demonstrate that the influences of the QBO (using a QBO index at 20 hPa) on stratospheric ozone are zonally asymmetric. The global distribution of stratospheric ozone varies significantly during different QBO phases. During QBO westerly (QBOW) phases, the TCO and stratospheric ozone are anomalously high in the tropics, while in the subtropics they are anomalously low over most of the areas, especially during the winter–spring of the respective hemisphere. This confirms the results from previous studies. In the polar region, the TCO and stratospheric ozone (50–10 hPa) anomalies are seasonally dependent and zonally asymmetric. During boreal winter (December–February, DJF), positive anomalies of the TCO and stratospheric ozone are evident during QBOW over the regions from North America to the North Atlantic (120∘ W–30∘ E), while significant negative anomalies exist over other longitudes in the Arctic. In boreal autumn (September–November, SON), the TCO and stratospheric ozone are anomalously high from Greenland to Eurasia (60∘ W–120∘ E) but anomalously low in other regions over the Arctic. Weak positive TCO and stratospheric ozone anomalies exist over the South America sector (90∘ W–30∘ E) of the Antarctic, while negative anomalies of the TCO and stratospheric ozone are seen in other longitudes. The consistent features of TCO and stratospheric ozone anomalies indicate that the QBO signals in TCO are mainly determined by the stratospheric ozone variations. Analysis of meteorological conditions indicates that the QBO ozone perturbations are mainly caused by dynamical transport and also influenced by chemical reactions associated with the corresponding temperature changes. QBO affects the geopotential height and the polar vortex and subsequently the transport of ozone-rich air from lower latitudes to the polar region, which therefore influences the ozone concentrations over the polar region. The geopotential height anomalies associated with QBO (QBOW–QBOE) are zonally asymmetric with clear wave number 1 features, which indicates that QBO influences the polar vortex and stratospheric ozone mainly by modifying the wave number 1 activities.

We present the first catalog of very-high-energy and ultra-high-energy gamma-ray sources detected by the Large High Altitude Air Shower Observatory. The catalog was compiled using 508 days of data collected by the Water Cherenkov Detector Array from 2021 March to 2022 September and 933 days of data recorded by the Kilometer Squared Array from 2020 January to 2022 September. This catalog represents the main result from the most sensitive large coverage gamma-ray survey of the sky above 1 TeV, covering decl. from −20° to 80°. In total, the catalog contains 90 sources with an extended size smaller than 2° and a significance of detection at >5 σ . Based on our source association criteria, 32 new TeV sources are proposed in this study. Among the 90 sources, 43 sources are detected with ultra-high energy ( E > 100 TeV) emission at >4 σ significance level. We provide the position, extension, and spectral characteristics of all the sources in this catalog.

Calcinosis cutis is the deposition of calcium salts in the skin and subcutaneous tissue, manifesting as variably shaped papules, nodules, and plaques that can substantially impair quality of life. The pathophysiology of calcinosis cutis involves dysregulation of proinflammatory cytokines, leukocytes, and other components of the innate immune system. In some conditions associated with calcinosis cutis, elevated serum calcium, phosphate, and vitamin D may also perturb innate immunity. The mechanisms by which these lead to cutaneous and subcutaneous calcification likely parallel those seen in vascular calcification. The role of aberrant innate immunity is further supported by the association between various autoantibodies with calcinosis cutis, such as anti-MDA5, anti-NXP2, anti-centromere, and anti-topoisomerase I. Treatments for calcinosis cutis remain limited and largely experimental, although mechanistically many therapies appear to focus on dampening innate immune responses. Further research is needed to better understand the innate immune pathophysiology and establish treatment options based on randomized-controlled trials.

Modeling plays an important role in predicting the long-term effects of biochar on soil organic carbon dynamics. The objective of our study was to apply the Century model to assess changes in temporal soil organic carbon in soil amended with manure and nitrogen fertilizer (MN), with manure and biochar (MB) or with manure, nitrogen fertilizer and biochar (MNB). We determined that, after 115 years, soil organic carbon stocks could not reach a steady state (equilibrium) or pre-cultivation levels, regardless of amendment type. Our results showed that a biennial input of manure and nitrogen fertilizer (MN) led to a 84% increase in soil organic carbon compared to a 79% (MNB) and 70% (MB) increase when amendments contained biochar. However, the quantity of organic matter input from crop residues and amendments was sufficient to increase the active fraction, with a turnover time of months to years, by 86%. In fact, carbon associated with the slow fraction, with a turnover time of 20 to 50 years, was the key driver for soil organic carbon accumulation in all amendment types. Although the passive fraction is the most stable form of carbon in the soil, with a turnover time of 400 to 100 years, once manure and biochar were added to the soil, this fraction increased up to 32%. Our results provided further insight into the ability of Century to accurately predict changes in soil organic carbon stocks when a combination of manure, nitrogen fertilizer or biochar were added to soil. Century predicted soil organic carbon stocks within -1% to +9% of measured values. However, further fine-tuning of the model is required since biochar undergoes chemical transformations (e.g., ageing) and changes soil physical parameters (e.g., bulk density) that can not be currently accounted for in the Century model. Addressing these limitations of Century will also help to increase the relationship between measured and predicted values.

In blue-ice areas (BIAs), deep ice is directly exposed at the surface, allowing for the cost-effective collection of large-sized old-ice samples. However, chronostratigraphic studies on blue-ice areas are challenging owing to fold and fault structures. Here, we report on a surface transect of ice with an undisturbed horizontal stratigraphy from the Larsen BIA, northern Victoria Land, East Antarctica. Ice layers defined by dust bands and ground-penetrating radar (GPR) surveys indicate a monotonic increase in age along the ice flow direction on the downstream side, while the upstream ice exhibits a potential repetition of ages on scales of tens of meters, which result from a complicated fold structure. Stable water isotopes (δ18Oice and δ2Hice) and components of the occluded air (i.e., CO2, N2O, CH4, δ15N–N2, δ18Oatm (=δ18O-O2), δO2/N2, δAr/N2​​​​​​​, 81Kr, and 85Kr) are analyzed for surface ice and shallow ice core samples. Correlating δ18Oice, δ18Oatm, and CH4 records from the Larsen BIA with ice from previously drilled ice cores indicates that the gas age at various shallow vertical coring sites ranges between 9.2–23.4 kyr BP, while the ice age sampled from the surface ranges from 5.6 to 24.7 kyr BP. Absolute radiometric 81Kr dating for the two vertical cores confirms ages within acceptable levels of analytical uncertainty. A tentative climate reconstruction suggests a large deglacial warming of 15 ± 5 ∘C (1σ) and an increase in snow accumulation by a factor of 1.7–4.6 (from 24.3 to 10.6 kyr BP). Our study demonstrates that BIAs in northern Victoria Land may help to obtain high-quality records for paleoclimate and atmospheric greenhouse gas compositions through the last deglaciation, although in general climatic interpretation is complicated by the need for upstream flow corrections, evidence for strong surface sublimation during the last glacial period, and potential errors in the estimated gas age–ice age difference.

Equipped with a high-precision atomic clock can significantly improve the ranging accuracy of the underwater acoustic ranging system. However, the adverse characteristic of underwater acoustic channel (UAC) seriously deteriorates the ranging accuracy. In addition, as a timing device typically commercial cesium atomic clock is only designed to output second-level time reference, which cannot be applied to underwater ranging systems directly. To overcome this limitation, a new underwater acoustic modem with high precision ranging capability based on second-level cesium atomic clock is developed in this paper. The spread spectrum technology is chosen for highly reliable communication and the second-level commercial cesium atomic clock is used to ensure accurate clock synchronization. The proposed modem executes a predetermined ranging scheme based on spread spectrum technology. Specifically, at a certain specified second-level, the transmitter modem sends the ranging signal, and the receiver modem starts timing. Until the receiving modem detects the ranging signal, the propagation time is obtained and the single-item ranging capability is realized. The pool experiment shows the effectiveness of the modem, its ranging accuracy can reach cm level, and the average absolute error of ranging is 8 cm.

Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. Existing global compilations are not geographically comprehensive and do not provide consistent metadata for all sites. Furthermore, the age models provided for these records are not harmonised and many are based on older calibrations of the radiocarbon ages. These issues limit the use of existing compilations for research into past fire regimes. Here, we present an expanded database of charcoal records, accompanied by new age models based on recalibration of radiocarbon ages using IntCal20 and Bayesian age-modelling software. We document the structure and contents of the database, the construction of the age models, and the quality control measures applied. We also record the expansion of geographical coverage relative to previous charcoal compilations and the expansion of metadata that can be used to inform analyses. This first version of the Reading Palaeofire Database contains 1676 records (entities) from 1480 sites worldwide. The database (RPDv1b – Harrison et al., 2021) is available at https://doi.org/10.17864/1947.000345.

Ab initio has been used as a label in nuclear theory for over two decades. Its meaning has evolved and broadened over the years. We present our interpretation, briefly review its historical use, and discuss its present-day relation to theoretical uncertainty quantification.

Cardiac endothelial cells (ECs) are important targets for cardiovascular gene therapy. However, the approach of stably transducing ECs in vivo using different vectors, including adeno-associated virus (AAV), remains unexamined. Regarding this unmet need, two AAV libraries from DNA shuffling and random peptide display were simultaneously screened in a transgenic mouse model. Cardiac ECs were isolated by cell sorting for salvage of EC-targeting AAV. Two AAV variants, i.e., EC71 and EC73, enriched in cardiac EC, were further characterized for their tissue tropism. Both of them demonstrated remarkably enhanced transduction of cardiac ECs and reduced infection of liver ECs in comparison to natural AAVs after intravenous injection. Significantly, persistent transgene expression was maintained in mouse cardiac ECs in vivo for at least 4 months. The EC71 vector was selected for delivery of the endothelial nitric oxide synthase (eNOS) gene into cardiac ECs in a mouse model of myocardial infarction. Enhanced eNOS activity was observed in the mouse heart and lung, which was correlated with partially improved cardiac function. Taken together, two AAV capsids were evolved with more efficient transduction in cardiovascular endothelium in vivo, but their endothelial tropism might need to be further optimized for practical application to cardiac gene therapy.

Freezing-induced groundwater-level decline is widely observed in regions with a shallow water table, but many existing studies on freezing-induced groundwater migration do not account for freezing-induced water-level fluctuations. Here, by combining detailed field observations of liquid soil water content and groundwater-level fluctuations at a site in the Ordos Plateau, China, and numerical modeling, we showed that the interaction of soil water and groundwater dynamics was controlled by wintertime atmospheric conditions and topographically driven lateral groundwater inflow. With an initial water table depth of 120 cm and a lateral groundwater inflow rate of 1.03 mm d−1, the observed freezing and thawing-induced fluctuations of soil water content and groundwater level are well reproduced. By calculating the budget of groundwater, the mean upward flux of freezing-induced groundwater loss is 1.46 mm d−1 for 93 d, while the mean flux of thawing-induced groundwater recharge is as high as 3.94 mm d−1 for 32 d. These results could be useful for local water resources management when encountering seasonally frozen soils and for future studies on two- or three-dimensional transient groundwater flow in semi-arid and seasonally frozen regions. By comparing models under a series of conditions, we found the magnitude of freezing-induced groundwater loss decreases with initial water table depth and increases with the rate of groundwater inflow. We also found a fixed-head lower boundary condition would overestimate freezing-induced groundwater migration when the water table depth is shallow. Therefore, an accurate characterization of freezing-induced water table decline is critical to quantifying the contribution of groundwater to hydrological and ecological processes in cold regions.

BackgroundStore-and-forward (SAF) teledermatology uses electronically stored information, including patient photographs and demographic information, for clinical decision-making asynchronous to the patient encounter. The integration of SAF teledermatology into clinical practice has been increasing in recent years, especially during the COVID-19 pandemic. Despite this growth, data regarding the outcomes of SAF teledermatology are limited. A key distinction among current literature involves comparing the quality and utility of images obtained by patients and trained clinicians, as these metrics may vary by the clinical expertise of the photographer. ObjectiveThis narrative literature review aimed to characterize the outcomes of SAF teledermatology through the lens of patient- versus clinician-initiated photography and highlight important future directions for and challenges of the field. MethodsA literature search of peer-reviewed research was performed between February and April 2021. Key search terms included patient-initiated, patient-submitted, clinician-initiated, clinician-submitted, store-and-forward, asynchronous, remote, image, photograph, and teledermatology. Only studies published after 2001 in English were included. In total, 47 studies were identified from the PubMed electronic database and Google Scholar after omitting duplicate articles. ResultsImage quality and diagnostic concordance are generally lower and more variable with patient-submitted images, which may impact their decision-making utility. SAF teledermatology can improve the efficiency of and access to care when photographs are taken by either clinicians or patients. The clinical outcomes of clinician-submitted images are comparable to those of in-person visits in the few studies that have investigated these outcomes. Coinciding with the onset of the COVID-19 pandemic, asynchronous teledermatology helped minimize unnecessary in-person visits in the outpatient setting, as many uncomplicated conditions could be adequately managed remotely via images captured by patients and referring clinicians. For the inpatient setting, SAF teledermatology minimized unnecessary contact during dermatology consultations, although current studies are limited by the heterogeneity of their outcomes. ConclusionsIn general, photographs taken by trained clinicians are higher quality and have better and more relevant diagnostic and clinical outcomes. SAF teledermatology helped clinicians avoid unnecessary physical contact with patients in the outpatient and inpatient settings during the COVID-19 pandemic. Asynchronous teledermatology will likely play a greater role in the future as SAF images become integrated into synchronous teledermatology workflows. However, the obstacles summarized in this review should be addressed before its widespread implementation into clinical practice.

Seaweed farming is widely perceived as one of the most environmentally benign types of aquaculture activity. In the past 10 yr, global seaweed production has doubled and reached 31.8 million t. Farmed seaweed also has important functions in local ecosystems. We focus on the production, bioavailability, and bacterial degradation rates of dissolved organic carbon (DOC) from cultured kelp Saccharina japonica. Semi in situ incubations in 2 growing seasons were conducted to estimate DOC production, and laboratory incubations were used to determine bioavailability and decay rates of DOC from cultured kelp. Results showed that DOC production was 6.2-7.0 mg C (g dry wt)-1 d-1 in the growing seasons, and the proportion of DOC in net primary production was 23.7-39.1%. The decomposition rate of DOC was 4 ± 1% d-1 and 9 ± 1% d-1 in January and April, respectively. About 37.8% remained as refractory DOC after 150 d incubation. It was calculated that the total DOC from kelp in Sanggou Bay was approximately 11.3 times of that from phytoplankton for the whole bay (144 km2). Our results suggest that more than half of the bioavailable DOC will be exported out of the bay to potentially support the wider food chain through bacterial uptake. Cultured kelp is therefore an important source of DOC in the embayment, contributes to the coastal DOC pool and provides a potential pathway for carbon dioxide sequestration.

The gushing of water from flowing wells attracted public attention and scientific curiosity as early as the 17th century, but little attention has been paid to the influence of flowing wells on the evolution of groundwater science. This study asserts that questions posed by flowing wells since the early 19th century led to the birth of many fundamental concepts and principles of physical hydrogeology. Due to the widespread occurrence of flowing wells in basins with regional aquitards, there is a long-lasting misconception that flowing wells could only occur in regionally confined aquifers. However, the recognition of possible occurrence of flowing wells in unconfined aquifers was anticipated at the turn of the 20th century based on observed increases in hydraulic head with depth in topographic lows of basins without apparent aquitards. This was later verified in the 1960s by field and modeling studies that gave birth to quantitative analysis of topographically driven groundwater flow systems, which was a paradigm shift in hydrogeology. Following this paradigm, several preconditions for flowing wells established in the 19th century were found unnecessary. Intermingled in the evolution of flow system concepts are inconsistencies and confusion concerning the use of the term “artesian”, so we propose avoidance of this term. This historical perspective of the causes of flowing well conditions and the influence of flowing wells on groundwater science could lead to a deeper understanding of the evolution of groundwater science and guide future studies on hydraulics of flowing wells.

Water body plays an irreplaceable role in the global ecosystem and climate system. Sentinel-2 is a new satellite data with higher spatial and spectral resolution. Through analysing spectral characteristics of Sentinel-2 satellite imagery, the brightness of water body in vegetation red edge band and shortwave infrared band showe sharply different than that of the not water body. Therefore, a new type of water index SWI (Sentinel-2 Water Index) was proposed by combing those two bands. Four representative water types, which included Taihu Lake, the Yangtze River Estuary, the ChaKa Salt Lake and the Chain Lake, were selected as experimental areas. Normalized difference water index (NDWI) and Sentinel-2 Water Index (SWI) with Otsu method were employed to extract water body. The results showed that overall accuracy and Kappa coefficient of SWI were higher than that of NDWI and SWI was efficient index to rapidly and accurately extract water for Sentinel-2 data. Therefore, SWI had application potential for larger scale water mapping in the future.

Land use change is an important theme of the research on the impact of human interaction on global change. In this paper, two phases of land use data were interpretated from remote sensing images of 1978 and 2018, and the spatial-temporal characteristics of land use change in China's Inner Mongolia Region from 1978 to 2018 were analyzed. The results indicated that grasslands and arable land are mainly distributed in the central and eastern region of Inner Mongolia, forest land are mainly distributed in the eastern region, and unused land is mainly distributed in the western region. From 1978 to 2018, the area of arable land in Inner Mongolia decreased by 9,000 km2, forest land increased by 900 km2, and the area of grassland decreased by 1,400 km2. Urban and rural, industrial mines, and residential land continued to increase with an area of 7,800 km2; and unused land increased by an area of 11,500 km2. It was indicated that after 40 years of development, land use in urban and rural areas, industrial mines, and residential areas caused by human activities in the Inner Mongolia Region has increased significantly. At the same time, the policy of returning farmland to forests to protect the environment has achieved significant results.

Remote sensing system fitted on UAV (Unmanned Aerial Vehicle) can obtain clear images and high-resolution aerial photographs. It has advantages of flexibility, convenience and ability to work full-time. However, there are some problems of UAV image such as small coverage area, large number, irregular overlap, etc. How to obtain a large regional map quickly becomes a major obstacle to UAV remote sensing application. In this paper, a new method of fast registration of UAV remote sensing images was proposed to meet the needs of practical application. This paper used Progressive Sample Consensus (PROSAC) algorithm to improve the matching accuracy by removed a large number of mismatching point pairs of remote sensing image registration based-on SURF (Speed Up Robust Feature) algorithm, and GPU (Graphic Processing Unit) was also used to accelerate the speed of improved SURF algorithm. Finally, geometric verification was used to achieve mosaic accuracy in survey area. The number of feature points obtained by using improved SURF based-on PROSAC algorithm was only 9.5% than that of SURF algorithm. Moreover, the accuracy rate of improved method was about 99.7%, while the accuracy rate of improved SURF algorithm was increased by 8% than SURF algorithm. Moreover, the improved running time of SURFGPU algorithm for UAV remote sensing image registration was a speed of around 16 times than SURF algorithm, and the image matching time had reached millisecond level. Thus, improved SURF algorithm had better matching accuracy and executing speed to meet the requirements of real-time and robustness in UAV remote sensing image registration.

Quantification of vegetation change and its coupling relationship with climate change has become the central topic in current global change researches. The Normalized Difference Vegetation Index (NDVI) time series data and meteorological data from 1998 to 2016 were collected to investigate the temporal and spatial variations of NDVI in growing season in the Yellow River source region and its response to climate change, based on the trend analysis, Mann-Kendall test and correlation analysis．The results indicated that: (1) In the past 19 years, the average NDVI in the region showed a slow increase, with a growth rate of 0.002/a and a catastrophe point in 2005, and the area with an upward trend accounted for 71.4% of the total area. (2) The climate of the area had been becoming warm and moist since the recent 19 years, both precipitation and temperature in growing season showed an upward trend. The partial correlation analysis showed that NDVI was positively correlated with precipitation and temperature, significantly relevant area accounting for 31.01% and 56.40% of the total area individually. The sensitivity of NDVI to temperature was higher than that of precipitation. According to residual analysis over the 19 years, human activities had negative effects on NDVI accounting 53.58% of the study area, and the implementation of a series of ecological protection engineering measures was the main cause leading to an increasing trend of NDVI after 2005.

Soil moisture is an important physical parameter to investigate water circulation, while it is difficult to be measured with spatiotemporal consistency. During the past several decades, a larger number of soil moisture verification methods were proposed, however, the review of soil moisture verification method from multi-scale perspective is still lacking. This paper investigates the verification method of soil moisture from three scale, such as point-scale, regional scale and remote sensing data verification. The prospect of soil moisture verification is proposed to serve retrieval algorithm validation.

Complex aerosol and photochemical pollution (ozone and peroxyacetyl nitrate, PAN) frequently occur in eastern China, and mitigation strategies to effectively alleviate both kinds of pollution are urgently needed. Although the effectiveness of powerful control measures implemented by the Chinese State Council has been comprehensively evaluated in terms of reducing atmospheric primary pollutants, the effectiveness in mitigating photochemical pollution is less assessed and therefore the underlying mechanisms are still poorly understood. The stringent emission controls implemented from 24 August to 6 September 2016 during the summit for the Group of Twenty (G20) provide us a unique opportunity to address this issue. Surface concentrations of atmospheric O3, PAN, and their precursors including volatile organic compounds (VOCs) and nitrogen dioxides (NOx), in addition to the other trace gases and particulate matter, were measured at the National Reference Climatological Station (NRCS) (30.22∘ N, 120.17∘ E, 41.7 m a.s.l) in urban Hangzhou. We found significant decreases in atmospheric PAN, NOx, total VOCs, PM2.5, and sulfur dioxide (SO2) under the unfavorable meteorological conditions during G20 (DG20) relative to the adjacent period before and after G20 (BG20 and AG20), indicating that the powerful control measures were effective in reducing the pollutant emissions in Hangzhou. Unlike with the other pollutants, daily maximum 8 h average (DMA8) O3 exhibited a slight increase and then decrease from BG20 to AG20, which was mainly attributed to the variation in the solar irradiation intensity and regional transport in addition to the contribution from the implementation of stringent control measures. Results from an observation-based chemical model (OBM) indicated that acetaldehyde and methylglyoxal (MGLY) were the most important second-generation precursors of PAN, accounting for 37.3 %–51.6 % and 22.8 %–29.5 % of the total production rates including the reactions of OVOCs, propagation of other radicals, and other minor sources. Moreover, we confirmed the production of PAN and O3 was sensitive to VOCs throughout the whole period, specifically dominated by aromatics in BG20 and DG20 but by alkenes in AG20. These findings suggested that reducing emissions of aromatics, alkenes, and alkanes would mitigate photochemical pollution including PAN and O3. Source appointment results attributed the reductions of VOC source and ozone formation potentials (OFPs) during G20 to the effective emission controls on traffic (vehicle exhaust) and industrial processes (solvent utilization and industrial manufacturing). However, fuel combustion and biogenic emissions both weakened such an effect with a sizable contribution to the VOC mixing ratios (18.8 % and 20.9 %) and OFPs (25.6 % and 17.8 %), especially during the latter part of G20 (G20 II) when anthropogenic VOCs were substantially reduced. This study highlights the effectiveness of stringent emission controls in relation to traffic and industrial sources, but a coordinated program related to controlling fuel combustion and biogenic emissions is also required to address secondary pollution.

Brown carbon (BrC) contributes significantly to aerosol light absorption and thus can affect the Earth's radiation balance and atmospheric photochemical processes. In this study, we examined the light absorption properties and molecular compositions of water-soluble (WS-BrC) and water-insoluble (WI-BrC) BrC in PM2.5 collected from a rural site in the Guanzhong Basin – a highly polluted region in northwest China. Both WS-BrC and WI-BrC showed elevated light absorption coefficients (Abs) in winter (4–7 times those in summer) mainly attributed to enhanced emissions from residential biomass burning (BB) for heating of homes. While the average mass absorption coefficients (MACs) at 365 nm (MAC365) of WS-BrC were similar between daytime and nighttime in summer (0.99±0.17 and 1.01±0.18 m2 g−1, respectively), the average MAC365 of WI-BrC was more than a factor of 2 higher during daytime (2.45±1.14 m2 g−1) than at night (1.18±0.36 m2 g−1). This difference was partly attributed to enhanced photochemical formation of WI-BrC species, such as oxygenated polycyclic aromatic hydrocarbons (OPAHs). In contrast, the MACs of WS-BrC and WI-BrC were generally similar in winter and both showed few diel differences. The Abs of wintertime WS-BrC correlated strongly with relative humidity, sulfate and NO2, suggesting that aqueous-phase reaction is an important pathway for secondary BrC formation during the winter season in northwest China. Nitrophenols on average contributed 2.44±1.78 % of the Abs of WS-BrC in winter but only 0.12±0.03 % in summer due to faster photodegradation reactions. WS-BrC and WI-BrC were estimated to account for 0.83±0.23 % and 0.53±0.33 %, respectively, of the total down-welling solar radiation in the ultraviolet (UV) range in summer, and 1.67±0.72 % and 2.07±1.24 %, respectively, in winter. The total absorption by BrC in the UV region was about 55 %–79 % relative to the elemental carbon (EC) absorption.

How to use modern information technology to efficiently and quickly obtain the personalized recommendation information required by students, and to provide high-quality intelligent services for schools, parents and students has become one of the hot issues in college research. This paper uses FP-growth association rule mining algorithm to infer student behavior and then use the collaborative filtering recommendation method to push information according to the inference result, and then push real-time and effective personalized information for students. The experimental results show that an improved FP-growth algorithm is proposed based on the classification of students. The algorithm combines the student behavior inference method of FP-growth algorithm with the collaborative filtering hybrid recommendation method, which not only solves the FP-tree tree branch. Excessive and collaborative filtering recommendation algorithm data sparseness problem, can also analyze different students' behaviors and activities, and accurately push real-time, accurate and effective personalized information for students, to promote smart campus and information intelligence The development provides better service.

Surface water system is an important part of global ecosystem, and the changes in surface water may lead to disasters, such as drought, waterlog, and water-borne diseases. The rapid development of remote sensing technology has supplied better strategies for water bodies extraction and further monitoring. In this study, AdaBoost and Random Forest (RF), two typical algorithms in integrated learning, were applied to extract water bodies in Chaozhou area (mainly located in Guangzhou Province, China) based on GF-1 data, and the Decision Tree (DT) was used for comparative tests to comprehensively evaluate the performance of classification algorithms listed above for surface water body extraction. The results showed that: (1) Compared with visual interpretation, AdaBoost performed better than RF in the extraction of several typical water bodies, such as rivers, lakes and ponds Moreover, the water extraction results of the strong classifiers using AdaBoost or RF were better than the weak basic classifiers. (2) For the quantitative accuracy statistics, the overall accuracy (96.5%) and kappa coefficient (93%) using AdaBoost exceeded those using RF (5.3% and 10.6%), respectively. The classification time of AdaBoost increased by 403 seconds and 918 seconds relative to RF and DT methods. However, in terms of visual interpretation, quantitative statistical accuracy and classification time, AdaBoost algorithm was more suitable for the water body extraction. (3) For the sample proportion comparison experiment of AdaBoost, four sampling proportions (0.1%, 0.2%, 1% and 2%) were chosen and 0.1% sampling proportion reached the optimum classification accuracy (93.9%) and kappa coefficient (87.8%).

In recent years, with high accuracy, high frequency, considerable coverage of remote sensing images, map tiles, video surveillance, web crawlers, social networking platforms and other types of spatiotemporal data have exploded in geometric progression. Human society has come into the era of big data in time and space. In view of the characteristics of multi-attribute, multi-dimensional, multisource and heterogeneous spatiotemporal big data, how to make use of the emerging information technology means, combined with the geographic information data analysis means, the rapid mining and utilization of spatiotemporal big data has become a key problem to be solved. Built on the background of spatiotemporal big data and the process of geospatial cognition, this paper proposes a "cell-cube" spatiotemporal object data model. This paper constructs a model system of geo-spatiotemporal big data from the aspects of data organization, data storage and data partition, and abstracts the geo-space into an infinite number of geo-cells, and the adjacent geo-cells gather around the core cells to form geographical clusters, and the geographical clusters with similar attributes are clustered into geographical blocks. At the level of data organization, the spatial and temporal characteristics of structured data and unstructured data are considered as organizational dimensions, and a multi-factor extended cube data model is proposed. In the aspect of data storage, the organization model is further abstracted into the cell-cube structure of distributed data warehouse, and then the spatiotemporal data is stored uniformly. At the level of data segmentation, the mathematical table and space calculation method of multi-feature extended cube are proposed, and the geographical cell data division model based on connection is established. It solves the organization and management problem of spatiotemporal big data, provides a more complete data organization framework and solution for the application of geo-spatiotemporal big data, and promotes the development of deep mining of spatiotemporal extensive data in GIS. And to achieve space-time big data in the geographical space microscopic and the macroscopic unification cognition.