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Black carbon (BC) exerts a notable warming effect due to its strong light absorption, largely influenced by its “mixing state”. However, due to computational constraints, the mixing state is challenging to accurately represent in large-scale models. In this study, we employ a particle-resolved model to simulate the evolution of BC mixing state based on field observation. Our result shows that aerosol compositions, coating thickness (CT) distribution, and optical properties of BC aerosols all exhibit a tendency toward a steady state with a characteristic timescale of less than 1 d, considerably shorter than the BC atmospheric lifetime. The rapid attainment of a steady state suggests that it is reasonable to disregard this pre-steady-state period and instead concentrate on the average properties of BC across extensive spatial and temporal scales. The distribution of CT follows an exponential linear distribution and can be characterized by a single slope parameter k. This distribution is independent of the BC core's distribution. In the model simulation, the mean CT, equivalent to the 1/k, is 62 nm, which is consistent with the statistical results indicating a mean CT of 63 nm. Utilizing the slope parameter k, which effectively characterizes the CT distribution under the steady-state simplifying assumption, the BC absorption enhancement closely corresponds to the results obtained via the particle-resolved method. This study simplifies the BC mixing state description and yields a precise evaluation of the BC optical properties, which has the potential utility for modeling efforts in the refinement of the assessment of BC's radiative effects.

Rock glaciers – periglacial landforms commonly found in high-mountain systems – are of significant scientific value for inferring the presence of permafrost, understanding mountain hydrology, and assessing climate impacts on high-mountain environments. However, inventories remain patchy in many alpine regions, and as a result they are poorly understood for some areas of High Mountain Asia such as the Tibetan Plateau. To address this gap, we compiled a comprehensive inventory of rock glaciers for the Tibetan Plateau, i.e., TPRoGI (v1.0), developed using an innovative deep learning method. This inventory consists of a total of 44 273 rock glaciers, covering approximately 6000 km2, with a mean area of 0.14 km2. They are predominantly situated at elevations ranging from 4000 to 5500 m a.s.l., with a mean of 4729 m a.s.l. They tend to occur on slopes with gradients between 10 and 25°, with a mean of 17.7°. Across the plateau, rock glaciers are widespread in the northwestern and southeastern areas, with dense concentrations in the Western Pamir and Nyainqêntanglha, while they are sparsely distributed in the inner part. Our inventory serves as a benchmark dataset, which will be further maintained and updated in the future. This dataset constitutes a significant contribution towards understanding, future monitoring, and assessment of permafrost on the Tibetan Plateau in the context of climate change. The dataset is available at https://doi.org/10.5281/zenodo.10732042 (Sun et al., 2024a).

Atmospheric sulfur (S) deposition has been increasingly recognized as a major driver of soil acidification. However, little is known about how soil acidification influences above- and belowground biomass by altering leaf and root traits. We conducted a 3-year S-addition experiment to simulate soil acidification in a meadow. Grass (Leymus chinensis (Trin.) Tzvelev) and sedge (Carex duriuscula C.A.Mey) species were chosen to evaluate the linkage between plant traits and biomass. Sulfur addition led to soil acidification and nutrient imbalances. Soil acidification decreased specific leaf area (SLA) but increased leaf dry-matter content (LDMC) in L. chinensis, showing a conservative strategy and thus suppressing aboveground instead of belowground biomass. However, in C. duriuscula, soil acidification increased plant height and root nutrients (N, P, S, and Mn), favoring competition for natural resources through enhanced above- and belowground biomass, i.e., adoption of an acquisitive strategy. Increased soil acidity resulted in an overall reduction in aboveground community biomass by 3 %–33 %, but it led to an increase in community root biomass by 11 %–22 % due to upregulation as a result of higher soil nutrient availability. Our results demonstrate that both above- and belowground plant biomass is affected by S-induced acidification. Understanding the linkage between plant biomass and functional traits contributes to a better understanding of plant–soil feedback in grassland ecosystems.

New particle formation (NPF) is a major source of aerosol particles and cloud condensation nuclei in the troposphere, playing an important role in both air quality and climate. Frequent NPF events have been observed in heavily polluted urban environments, contributing to the aerosol number concentration by a significant amount. The Po Valley region in northern Italy has been characterized as a hotspot for high aerosol loadings and frequent NPF events in southern Europe. However, the mechanisms of NPF and growth in this region are not completely understood. In this study, we conducted a continuous 2-month measurement campaign with state-of-the-art instruments to elucidate the NPF and growth mechanisms in northern Italy. Our results demonstrate that frequent NPF events (66 % of all days during the measurement campaign) are primarily driven by abundant sulfuric acid (8.5×106 cm−3) and basic molecules in this area. In contrast, oxygenated organic molecules from the atmospheric oxidation of volatile organic compounds (VOCs) appear to play a minor role in the initial cluster formation but contribute significantly to the consecutive growth process. Regarding alkaline molecules, amines are insufficient to stabilize all sulfuric acid clusters in the Po Valley. Ion cluster measurements and kinetic models suggest that ammonia (10 ppb) must therefore also play a role in the nucleation process. Generally, the high formation rates of sub-2 nm particles (87 cm−3 s−1) and nucleation-mode growth rates (5.1 nm h−1) as well as the relatively low condensational sink (8.9×10-3 s−1) will result in a high survival probability for newly formed particles, making NPF crucial for the springtime aerosol number budget. Our results also indicate that reducing key pollutants, such as SO2, amine and NH3, could help to substantially decrease the particle number concentrations in the Po Valley region.

Lakes are important components of the Earth's surface water bodies, and their fluctuating water levels and changing water volumes can have an important impact on ecological processes and landscape patterns within a watershed. Climate change and human activities are the main drivers of water volume changes in lakes. We applied a long time series analysis approach using classical statistics and geographic information system (GIS) technics to quantitatively attribute water volume variations in Lake Victoria from 2000 to 2019. We examined several drivers of lake water volume variations: meteorological factors including regional climate change (precipitation, evaporation) and global climate change (El Niño/Southern Oscillation events), and anthropogenic factors including socio-economic development and land use/cover change. The results show that regional climate change has a greater impact on lake water volume variations than global climate change; among them, the correlation coefficient between precipitation and lake water volume variations is the largest (0.410), with an impact lag of 1 month. For anthropogenic factors, variations in lake water volume are more pronounced in areas with rapid economic development and high population growth, with correlation coefficients greater than 0.440. Different types of land use/cover have varying impacts on Lake Victoria's water volume variations. Overall, the influence of anthropogenic factors is greater than that of meteorological factors. This study results not only provides a scientific basis for exploring the hydrological changes and their drivers in the world's large transboundary lakes, but also be great scientific significance to rational use of water resources and sustainable regional development.

Abstract Recent experiments demonstrated that proton transport through graphene electrodes can be accelerated by over an order of magnitude with low intensity illumination. Here we show that this photo-effect can be suppressed for a tuneable fraction of the infra-red spectrum by applying a voltage bias. Using photocurrent measurements and Raman spectroscopy, we show that such fraction can be selected by tuning the Fermi energy of electrons in graphene with a bias, a phenomenon controlled by Pauli blocking of photo-excited electrons. These findings demonstrate a dependence between graphene’s electronic and proton transport properties and provide fundamental insights into molecularly thin electrode-electrolyte interfaces and their interaction with light.

This paper provides a summary of the work done within Phase III of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project, under the International Energy Agency Wind Technology Collaboration Programme Task 30. This phase focused on validating the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure. Numerical models of the Technical University of Denmark 10 MW reference wind turbine were validated using measurement data from a 1:75 scale test performed during the UNsteady Aerodynamics for FLOating Wind (UNAFLOW) project and a follow-on experimental campaign, both performed at the Politecnico di Milano wind tunnel. Validation of the models was performed by comparing the loads for steady (fixed platform) and unsteady (harmonic motion of the platform) wind conditions. For the unsteady wind conditions, the platform was forced to oscillate in the surge and pitch directions under several frequencies and amplitudes. These oscillations result in a wind variation that impacts the rotor loads (e.g., thrust and torque). For the conditions studied in these tests, the system aerodynamic response was almost steady. Only a small hysteresis in airfoil performance undergoing angle of attack variations in attached flow was observed. During the experiments, the rotor speed and blade pitch angle were held constant. However, in real wind turbine operating conditions, the surge and pitch variations would result in rotor speed variations and/or blade pitch actuations, depending on the wind turbine controller region that the system is operating. Additional simulations with these control parameters were conducted to verify the fidelity of different models. Participant results showed, in general, a good agreement with the experimental measurements and the need to account for dynamic inflow when there are changes in the flow conditions due to the rotor speed variations or blade pitch actuations in response to surge and pitch motion. Numerical models not accounting for dynamic inflow effects predicted rotor loads that were 9 % lower in amplitude during rotor speed variations and 18 % higher in amplitude during blade pitch actuations.

Air ions are the key components for a series of atmospheric physicochemical interactions, such as ion-catalyzed reactions, ion-molecule reactions, and ion-induced new particle formation (NPF). They also control atmospheric electrical properties with effects on global climate. We performed molecular-level measurements of cluster ions at the high-altitude research station Chacaltaya (CHC; 5240 m a.s.l.), located in the Bolivian Andes, from January to May 2018 using an atmospheric-pressure-interface time-of-flight mass spectrometer. The negative ions mainly consisted of (H2SO4)0–3⚫HSO4-, (HNO3)0–2⚫NO3-, SO5-, (NH3)1–6⚫(H2SO4)3–7⚫HSO4-, malonic-acid-derived, and CHO / CHON⚫(HSO4- / NO3-) cluster ions. Their temporal variability exhibited distinct diurnal and seasonal patterns due to the changes in the corresponding neutral species' molecular properties (such as electron affinity and proton affinity) and concentrations resulting from the air masses arriving at CHC from different source regions. The positive ions were mainly composed of protonated amines and organic cluster ions but exhibited no clear diurnal variation. H2SO4–NH3 cluster ions likely contributed to the NPF process, particularly during the wet-to-dry transition period and the dry season, when CHC was more impacted by air masses originating from source regions with elevated SO2 emissions. Our study provides new insights into the chemical composition of atmospheric cluster ions and their role in new particle formation in the high-altitude mountain environment of the Bolivian Andes.

Measurements of the molecular composition of organic aerosol (OA) constituents improve our understanding of sources, formation processes, and physicochemical properties of OA. One instrument providing such data at a time resolution of minutes to hours is the chemical ionization time-of-flight mass spectrometer with filter inlet for gases and aerosols (FIGAERO-CIMS). The technique collects particles on a filter, which are subsequently desorbed, and the evaporated molecules are ionized and analyzed in the mass spectrometer. However, long-term measurements using this technique and/or field deployments at several sites simultaneously require substantial human and financial resources. The analysis of filter samples collected outside the instrument (offline) may provide a more cost-efficient alternative and makes this technology available for the large number of particle filter samples collected routinely at many different sites globally. Filter-based offline use of the FIGAERO-CIMS limits this method, albeit to particle-phase analyses, which is likely at a reduced time resolution compared to online deployments. Here we present the application and assessment of offline FIGAERO-CIMS, using Teflon and quartz fiber filter samples that were collected in autumn 2018 in urban Beijing. We demonstrate the feasibility of the offline application with a “sandwich” sample preparation for the over 900 identified organic compounds with (1) high signal-to-noise ratios, (2) high repeatability, and (3) linear signal response to the filter loadings. Comparable overall signals were observed between the quartz fiber and Teflon filters for 12 and 24 h samples but with larger signals for semi-volatile compounds for the quartz fiber filters, likely due to adsorption artifacts. We also compare desorption profile (thermogram) shapes for the two filter materials. Thermograms are used to derive volatility qualitatively based on the desorption temperature at which the maximum signal intensity of a compound is observed (Tmax⁡). While we find that Tmax⁡ can be determined with high repeatability (±5.7 ∘C) from the duplicate tests for one filter type, we observe considerable differences in Tmax⁡ between the quartz and Teflon filters, warranting further investigation into the thermal desorption characteristics of different filter types. Overall, this study provides a basis for expanding OA molecular characterization by FIGAERO-CIMS to situations where and when deployment of the instrument itself is not possible.

Direct observation of electric field effects in the water dissociation reaction remains elusive. Here, the authors report an exponential acceleration of the reaction as function of the interfacial electric field using graphene electrodes decorated with Pt.

During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5–3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3–7 and 7–15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration; instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.

Within the 9th European Framework programme, since 2021 EUROfusion is operating five tokamaks under the auspices of a single Task Force called ‘Tokamak Exploitation’. The goal is to benefit from the complementary capabilities of each machine in a coordinated way and help in developing a scientific output scalable to future largre machines. The programme of this Task Force ensures that ASDEX Upgrade, MAST-U, TCV, WEST and JET (since 2022) work together to achieve the objectives of Missions 1 and 2 of the EUROfusion Roadmap: i) demonstrate plasma scenarios that increase the success margin of ITER and satisfy the requirements of DEMO and, ii) demonstrate an integrated approach that can handle the large power leaving ITER and DEMO plasmas. The Tokamak Exploitation task force has therefore organized experiments on these two missions with the goal to strengthen the physics and operational basis for the ITER baseline scenario and for exploiting the recent plasma exhaust enhancements in all four devices (PEX: Plasma EXhaust) for exploring the solution for handling heat and particle exhaust in ITER and develop the conceptual solutions for DEMO. The ITER Baseline scenario has been developed in a similar way in ASDEX Upgrade, TCV and JET. Key risks for ITER such as disruptions and run-aways have been also investigated in TCV, ASDEX Upgrade and JET. Experiments have explored successfully different divertor configurations (standard, super-X, snowflakes) in MAST-U and TCV and studied tungsten melting in WEST and ASDEX Upgrade. The input from the smaller devices to JET has also been proven successful to set-up novel control schemes on disruption avoidance and detachment.

In the study of urban sustainable development, accurate classification of land use has become an important basis for monitoring urban dynamic changes. Hence it is necessary to develop the appropriate recognition model for urban-rural land use. Although deep learning algorithms have become a research hotspot in image classification tasks in recent years, and many good results have been achieved. But other machine learning algorithms are not going away. Compared deep learning with machine learning, there are some advantages and disadvantages in data dependence, hardware dependence, feature processing, problem solving methods, execution time, and interpretability, etc. Especially in the classification for remote sensing images, the continuous research and development of traditional machine learning algorithms is still of great significance. In this paper, the performances of several SLFN-based classification algorithms were studied and compared, including ELM, RBF K-ELM, mixed K-ELM, A-ELM and SVM. Extreme Learning Machine (ELM) is a new algorithm for single-hidden-layer feedforward neural network (SLFN). It has simple structure, fast speed and is easy to train. In some applications, however, standard ELM is prone to be overfitting and its performance will be affected seriously when outliers exist. In order to explore the performance of ELM and its improved algorithm for urban-rural land use classification, comparative experiments between three improved ELM algorithms (RBF K-ELM, mixed K-ELM and A-ELM), ELM and SVM with image data from several study areas were performed, and the classification accuracy and efficiency were analysed. The results show that the three improved ELM algorithms perform better than the standard ELM and SVM both in overall accuracy and Kappa coefficient. However, it is worth noting that the computation efficiency of RBF K-ELM and mixed K-ELM decreases greatly with larger image, the time cost is much more than other algorithms. Compared with other algorithms, A-ELM has the advantages of higher Overall Accuracy and less classification time.

Timely and accurate socioeconomic indicators are the prerequisite for smart social governance. For example, the level of economic development and the structure of population are important statistics for regional or national policy-making. However, the collection of these characteristics usually depends on demographic and social surveys, which are time- and labor-intensive. To address these issues, we propose a machine learning-based approach to estimate and map the economic development from multi-source open available geospatial data, including remote sensing imagery and OpenStreetMap road networks. Specifically, we first extract knowledge-based features from different data sources; then the multi-view graphs are constructed through different perspectives of spatial adjacency and feature similarity; and a multi-view graph neural network (MVGNN) model is built on them and trained in a self-supervised learning manner. Then, the handcrafted features and the learned graph representations are combined to estimate the regional economic development indicators via random forest models. Taking China’s county-level gross domestic product (GDP) as an example, extensive experiments have been conducted and the results demonstrate the effectiveness of the proposed method, and the combination of the knowledge-based and learning-based features can significantly outperform baseline methods. Our proposed approach can advance the goal of acquiring timely and accurate socioeconomic variables through widely accessible geospatial data, which has the potential to extend to more social indicators and other geographic regions to support smart governance and policy-making in the future.

The flux-weighted average cross sections and isomeric ratios of 92Mo(γ, n)91m,gMo and 92Mo(γ, 3n)89Mo reactions were measured through activation methods. Laser-driven bremsstrahlung γ-ray were generated by the laser wakefield accelerated quasi-monoenergetic electrons using the 200 TW laser in the Compact Laser Plasma Accelerator laboratory, Peking University. The results showed good agreements with previous works using traditional γ-ray sources, and were compared with TALYS 1.9 calculations. We extended the experimental results of 92Mo photonuclear reactions to higher energies, the experimental discrepancies of 92Mo(γ, n)91m,gMo isomeric ratios at high energy region were clarified, and the cross sections of 92Mo(γ, 3n)89Mo reaction were first obtained.

With increasing adoption of advanced meter infrastructure, smart sensors together with SCADA (Supervisory Control and Data Acquisition) systems, it is imperative to develop novel data analytics and couple the results with hydraulic modeling to improve the quality and efficiency of water services. One important task is to timely detect and localize anomaly events, which may include, but not be limited to, pipe bursts and unauthorized water usages. In this paper, a comprehensive solution framework has been developed for anomaly detection and localization by formulating and integrating data-driven analytics with hydraulic model calibration. Data analysis for anomaly detection proceeds in multiple steps including the following: (1) data pre-processing to eliminate and correct erroneous data records, (2) outlier detection by statistical process control methods and deep machine learning, and (3) system anomaly classification by correlation analysis of multiple sensor events. Classified system anomaly events are subsequently localized via hydraulic model calibration. The integrated solution framework is developed as a user-friendly and effective software tool, tested, and validated on the selected target areas in Singapore. HIGHLIGHTS Comprehensive solution framework for anomaly detection and localization.; Integration of data-driven analytics with hydraulic model calibration.; Data analysis for anomaly detection.; Classification of system anomaly events.; Testing and validating the solution on the selected target areas in Singapore.;

Organic aerosol (OA) is a major component of fine particulate matter (PM), affecting air quality, human health, and the climate. The absorptive and reflective behavior of OA components contributes to determining particle optical properties and thus their effects on the radiative budget of the troposphere. There is limited knowledge on the influence of the molecular composition of OA on particle optical properties in the polluted urban environment. In this study, we characterized the molecular composition of oxygenated OA collected on filter samples in the autumn of 2018 in Beijing, China, with a filter inlet for gases and aerosols coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (FIGAERO–CIMS). Three haze episodes occurred during our sampling period with daily maximum concentrations of OA of 50, 30, and 55 µg m−3. We found that the signal intensities of dicarboxylic acids and sulfur-containing compounds increased during the two more intense haze episodes, while the relative contributions of wood-burning markers and other aromatic compounds were enhanced during the cleaner periods. We further assessed the optical properties of oxygenated OA components by combining detailed chemical composition measurements with collocated particle light absorption measurements. We show that light absorption enhancement (Eabs) of black carbon (BC) was mostly related to more oxygenated OA (e.g., dicarboxylic acids), likely formed in aqueous-phase reactions during the intense haze periods with higher relative humidity, and speculate that they might contribute to lensing effects. Aromatics and nitro-aromatics (e.g., nitrocatechol and its derivatives) were mostly related to a high light absorption coefficient (babs) consistent with light-absorbing (brown) carbon (BrC). Our results provide information on oxygenated OA components at the molecular level associated with BrC and BC particle light absorption and can serve as a basis for further studies on the effects of anthropogenic OA on radiative forcing in the urban environment.

Topographic development via paraglacial slope failure (PSF) represents a complex interplay between geological structure, climate, and glacial denudation. Southeastern Tibet has experienced amongst the highest rates of ice mass loss in High Mountain Asia in recent decades, but few studies have focused on the implications of this mass loss on the stability of paraglacial slopes. We used repeat satellite- and unpiloted aerial vehicle (UAV)-derived imagery between 1990 and 2020 as the basis for mapping PSFs from slopes adjacent to Hailuogou Glacier (HLG), a 5 km long monsoon temperate valley glacier in the Mt. Gongga region. We observed recent lowering of the glacier tongue surface at rates of up to 0.88 m a−1 in the period 2000 to 2016, whilst overall paraglacial bare ground area (PBGA) on glacier-adjacent slopes increased from 0.31 ± 0.27 km2 in 1990 to 1.38 ± 0.06 km2 in 2020. Decadal PBGA expansion rates were ∼ 0.01 km2 a−1, 0.02 km2 a−1, and 0.08 km2 in the periods 1990–2000, 2000–2011, and 2011–2020 respectively, indicating an increasing rate of expansion of PBGA. Three types of PSFs, including rockfalls, sediment-mantled slope slides, and headward gully erosion, were mapped, with a total area of 0.75 ± 0.03 km2 in 2020. South-facing valley slopes (true left of the glacier) exhibited more destabilization (56 % of the total PSF area) than north-facing (true right) valley slopes (44 % of the total PSF area). Deformation of sediment-mantled moraine slopes (mean 1.65–2.63 ± 0.04 cm d−1) and an increase in erosion activity in ice-marginal tributary valleys caused by a drop in local base level (gully headward erosion rates are 0.76–3.39 cm d−1) have occurred in tandem with recent glacier downwasting. We also observe deformation of glacier ice, possibly driven by destabilization of lateral moraine, as has been reported in other deglaciating mountain glacier catchments. The formation, evolution, and future trajectory of PSFs at HLG (as well as other monsoon-dominated deglaciating mountain areas) are related to glacial history, including recent rapid downwasting leading to the exposure of steep, unstable bedrock and moraine slopes, and climatic conditions that promote slope instability, such as very high seasonal precipitation and seasonal temperature fluctuations that are conducive to freeze–thaw and ice segregation processes.

Although the anthropogenic emissions of SO2 have decreased significantly in China, the decrease in SO42- in PM2.5 is much smaller than that of SO2. This implies an enhanced formation rate of SO42- in the ambient air, and the mechanism is still under debate. This work investigated the formation mechanism of particulate sulfate based on statistical analysis of long-term observations in Shijiazhuang and Beijing supported with flow tube experiments. Our main finding was that the sulfur oxidation ratio (SOR) was exponentially correlated with ambient RH in Shijiazhuang (SOR = 0.15+0.0032×exp⁡(RH/16.2)) and Beijing (SOR = -0.045+0.12×exp⁡(RH/37.8)). In Shijiazhuang, the SOR is linearly correlated with the ratio of aerosol water content (AWC) in PM2.5 (SOR = 0.15+0.40×AWC/PM2.5). Our results suggest that uptake of SO2 instead of oxidation of S(IV) in the particle phase is the rate-determining step for sulfate formation. NH4NO3 plays an important role in the AWC and the change of particle state, which is a crucial factor determining the uptake kinetics of SO2 and the enhanced SOR during haze days. Our results show that NH3 significantly promoted the uptake of SO2 and subsequently the SOR, while NO2 had little influence on SO2 uptake and SOR in the presence of NH3.

Despite the numerous studies investigating haze formation mechanism in China, it is still puzzling that intensive haze episodes could form within hours directly following relatively clean periods. Haze has been suggested to be initiated by the variation of meteorological parameters and then to be substantially enhanced by aerosol–radiation–boundary layer feedback. However, knowledge on the detailed chemical processes and the driving factors for extensive aerosol mass accumulation during the feedback is still scarce. Here, the dependency of the aerosol number size distribution, mass concentration and chemical composition on the daytime mixing layer height (MLH) in urban Beijing is investigated. The size distribution and chemical composition-resolved dry aerosol light extinction is also explored. The results indicate that the aerosol mass concentration and fraction of nitrate increased dramatically when the MLH decreased from high to low conditions, corresponding to relatively clean and polluted conditions, respectively. Particles having their dry diameters in the size of ∼400–700 nm, and especially particle-phase ammonium nitrate and liquid water, contributed greatly to visibility degradation during the winter haze periods. The dependency of aerosol composition on the MLH revealed that ammonium nitrate and aerosol water content increased the most during low MLH conditions, which may have further triggered enhanced formation of sulfate and organic aerosol via heterogeneous reactions. As a result, more sulfate, nitrate and water-soluble organics were formed, leading to an enhanced water uptake ability and increased light extinction by the aerosols. The results of this study contribute towards a more detailed understanding of the aerosol–chemistry–radiation–boundary layer feedback that is likely to be responsible for explosive aerosol mass growth events in urban Beijing.

Gaseous hydrochloric (HCl) and hydrobromic acid (HBr) are vital halogen species that play essential roles in tropospheric physicochemical processes. Yet, the majority of the current studies on these halogen species were conducted in marine or coastal areas. Detection and source identification of HCl and HBr in inland urban areas remain scarce, thus limiting the full understanding of halogen chemistry and potential atmospheric impacts in the environments with limited influence from the marine sources. Here, both gaseous HCl and HBr were concurrently measured in urban Beijing, China, during winter and early spring of 2019. We observed significant HCl and HBr concentrations ranging from a minimum value at 1 × 108 molecules cm−3 (4 ppt) and 4 × 107 molecules cm−3 (1 ppt) up to 6 × 109 molecules cm−3 (222 ppt) and 1 × 109 molecules cm−3 (37 ppt), respectively. The HCl and HBr concentrations are enhanced along with the increase of atmospheric temperature, UVB and levels of gaseous HNO3. Based on the air mass analysis and high correlations of HCl and HBr with the burning indicators (HCN and HCNO), gaseous HCl and HBr are found to be related to anthropogenic burning aerosols. The gas–particle partitioning may also play a dominant role in the elevated daytime HCl and HBr. During the daytime, the reactions of HCl and HBr with OH radicals lead to significant production of atomic Cl and Br, up to 2 × 104 molecules cm−3 s−1 and 8 × 104 molecules cm−3 s−1, respectively. The production rate of atomic Br (via HBr + OH) is 2–3 times higher than that of atomic Cl (via HCl + OH), highlighting the potential importance of bromine chemistry in the urban area. On polluted days, the production rates of atomic Cl and Br are faster than those on clean days. Furthermore, our observations of elevated HCl and HBr may suggest an important recycling pathway of halogen species in inland megacities and may provide a plausible explanation for the widespread halogen chemistry, which could affect the atmospheric oxidation in China.

Although secondary particulate matter is reported to be the main contributor of PM2.5 during haze in Chinese megacities, primary particle emissions also affect particle concentrations. In order to improve estimates of the contribution of primary sources to the particle number and mass concentrations, we performed source apportionment analyses using both chemical fingerprints and particle size distributions measured at the same site in urban Beijing from April to July 2018. Both methods resolved factors related to primary emissions, including vehicular emissions and cooking emissions, which together make up 76 % and 24 % of total particle number and organic aerosol (OA) mass, respectively. Similar source types, including particles related to vehicular emissions (1.6±1.1 µg m−3; 2.4±1.8×103 cm−3 and 5.5±2.8×103 cm−3 for two traffic-related components), cooking emissions (2.6±1.9 µg m−3 and 5.5±3.3×103 cm−3) and secondary aerosols (51±41 µg m−3 and 4.2±3.0×103 cm−3), were resolved by both methods. Converted mass concentrations from particle size distributions components were comparable with those from chemical fingerprints. Size distribution source apportionment separated vehicular emissions into a component with a mode diameter of 20 nm (“traffic-ultrafine”) and a component with a mode diameter of 100 nm (“traffic-fine”). Consistent with similar day- and nighttime diesel vehicle PM2.5 emissions estimated for the Beijing area, traffic-fine particles, hydrocarbon-like OA (HOA, traffic-related factor resulting from source apportionment using chemical fingerprints) and black carbon (BC) showed similar diurnal patterns, with higher concentrations during the night and morning than during the afternoon when the boundary layer is higher. Traffic-ultrafine particles showed the highest concentrations during the rush-hour period, suggesting a prominent role of local gasoline vehicle emissions. In the absence of new particle formation, our results show that vehicular-related emissions (14 % and 30 % for ultrafine and fine particles, respectively) and cooking-activity-related emissions (32 %) dominate the particle number concentration, while secondary particulate matter (over 80 %) governs PM2.5 mass during the non-heating season in Beijing.

Secondary aerosols are a major component of PM2.5, yet their formation mechanisms in the ambient atmosphere are still unclear. Based on field measurements in downtown Beijing, we show that the photolysis of nitrous acid (HONO) may promote the formation of organic and nitrate aerosols in winter in Beijing, which is supported by the fact that the mass concentrations of organic and nitrate aerosols linearly increase as a function of HONO consumed from early morning to noon. The increased nitrate content also leads to the formation of ammonium particulate matter through enhancing the neutralization of nitrate and sulfate by ammonia. We further illustrate that during pollution events in winter in Beijing, over 50 % of the ambient HONO may be related to traffic-related emissions, including direct emissions and formation via the reaction between OH and vehicle-emitted NO. Overall, our results indicate that traffic-related HONO may play an important role in the oxidative capacity and in turn contribute to haze formation in winter in Beijing. The mitigation of HONO and NOx emissions from vehicles may be an effective way to reduce the formation of secondary aerosols and severe haze events in winter in Beijing.

The climate and air quality effects of aerosol particles depend on the number and size of the particles. In urban environments, a large fraction of aerosol particles originates from anthropogenic emissions. To evaluate the effects of different pollution sources on air quality, knowledge of size distributions of particle number emissions is needed. Here we introduce a novel method for determining size-resolved particle number emissions, based on measured particle size distributions. We apply our method to data measured in Beijing, China, to determine the number size distribution of emitted particles in a diameter range from 2 to 1000 nm. The observed particle number emissions are dominated by emissions of particles smaller than 30 nm. Our results suggest that traffic is the major source of particle number emissions with the highest emissions observed for particles around 10 nm during rush hours. At sizes below 6 nm, clustering of atmospheric vapors contributes to calculated emissions. The comparison between our calculated emissions and those estimated with an integrated assessment model GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) shows that our method yields clearly higher particle emissions at sizes below 60 nm, but at sizes above that the two methods agree well. Overall, our method is proven to be a useful tool for gaining new knowledge of the size distributions of particle number emissions in urban environments and for validating emission inventories and models. In the future, the method will be developed by modeling the transport of particles from different sources to obtain more accurate estimates of particle number emissions.

Two single-particle aerosol mass spectrometers (SPAMSs) were deployed simultaneously at an urban and a rural site in Beijing during an intensive field campaign from 1 to 29 November 2016 to investigate the source and process of airborne particles in Beijing. In the first part of this research, we report the single-particle chemical composition, mixing state, and evolution at both sites. A total of 96 % and 98 % of collected particles were carbonaceous at the urban and rural sites, respectively. Five particle categories, including elemental carbon (EC), organic carbon (OC), internal-mixed EC and OC (ECOC), potassium-rich (K-rich), and metals, were observed at both sites. The categories were partitioned into particle types depending on different atmospheric processing stages. A total of 17 particle types were shared at both sites. In the urban area, nitrate-containing particle types, such as EC-Nit (Nit: nitrate) and ECOC-Nit, were enriched especially at night, sulfate-containing particles were transported when wind speed was high, and ECOC-Nit-Sul (Sul: sulfate) were mostly aged locally. In sum, these processed particles added up to 85.3 % in the urban areas. In the rural area, regional particles were abundant, but freshly emitted ECOC and OC had distinct patterns that were pronounced at cooking and heating times. Biomass burning, traffic, and coal burning were major sources of particulate matter (PM2.5) in both rural and urban areas. Moreover, particles from the steel industry located in the south were also identified. In summary, the chemical composition of urban and rural particle types was similar in Beijing; the urban particles were influenced significantly by rural processing and transport. The work is useful to understand the evolution of urban and rural particles in Beijing during winter.

Two parallel field studies were conducted simultaneously at both urban and rural sites in Beijing from 1 to 29 November 2016. An online single-particle chemical composition analysis was used as a tracer system to investigate the impact of heating activities and the formation of haze events. Central heating elevated EC-Nit (elemental carbon-nitrate), EC-Nit-Sul (EC-nitrate-sulfate), and ECOC-Nit (ECOC: internal-mixed elemental carbon and organic carbon) levels by 1.5–2.0 times due to the increased use of coal in the urban areas. However, in the rural areas, residential heating, which mainly consumes low-quality coal, and biomass burning elevated ECOC-Nit-Sul, NaK-Nit, and OC-Sul levels by 1.2–1.5 times. Four severe haze events (hourly PM2.5 > 200 µg m−3) occurred at both sites during the studies. In each event, a pattern of transport and accumulation was found. In the first stage of the pattern, particles were regionally transported from the south and southwest and accumulated under air stagnation, creating significant secondary formation, then PM2.5 was elevated to 300 µg m−3. At both sites, the severe haze occurred due to different patterns of local emission, transport, and secondary processes. At Pinggu (PG), the sulfate-rich residential coal burning particles were dominant. The regional transport between PG and Peking University (PKU) was simulated using the Weather Research and Forecasting HYbrid Single-Particle Lagrangian Integrated Trajectory (WRF-HYSPLIT) model, confirming that the transport from PG to PKU was significant, but PKU to PG occurred occasionally. These cases can explain the serious air pollution in the urban areas of Beijing and the interaction between urban and rural areas. This study can provide references for enhancing our understanding of haze formation in Beijing.

The automatic classification technology of remote sensing images is the key technology to extract the rich geo-information in remote sensing images and to monitor the dynamic changes of land use and ecological environment. Remote sensing images have the characteristics of large amount of information and many dimensions. Therefore, how to classify and extract the information in remote sensing images has become a crucial issue in the field of remote sensing science. With the development of neural network theory, many scholars have carried out research on the application of neural network models in remote sensing image classification. However, there are still some problems to be solved in artificial neural network methods. In this study, considering the problem of large-scale land classification for medium resolution and multi-spectral remote sensing imagery, an improved machine learning algorithm based on extreme learning machine for remote sensing classification has been developed via regularization theory. The improved algorithm is more suitable for the application of post-classification change monitoring of features in large scale imaging. In this study, our main job is to evaluate the performance of ELM with A-optimal design regularization (here we call it simply as A-optimal RELM). So the accuracy and efficiency of A-optimal RELM algorithm for remote sensing imagery classification, as well as the algorithms of support vector machine (SVM) and original ELM are compared in the experiments. The experimental results show that A-optimal RELM performs the best on all three different images with overall accuracy of 97.27% and 95.03% respectively. Besides, the A-optimal RELM performs better on the details of distinguish similar and confusing terrestrial object pixels.

Photochemistry plays an important role in the evolution of atmospheric water-soluble organic carbon (WSOC), which dissolves into clouds, fogs, and aerosol liquid water. In this study, we tentatively examined the molecular composition and evolution of a WSOC mixture extracted from field-collected wheat straw burning aerosol (WSBA) samples upon photolysis, using direct infusion electrospray ionisation (ESI) coupled to high-resolution mass spectrometry (HRMS) and liquid chromatography (LC) coupled with HRMS. For comparison, two typical phenolic compounds (i.e. phenol and guaiacol) emitted from lignin pyrolysis in combination with hydrogen peroxide (H2O2) as a typical OH radical precursor were simultaneously exposed to simulated sunlight irradiation. Their photochemical products such as phenolic dimers (e.g. m∕z 185.0608 for phenol dimer and m∕z 245.0823 for guaiacol dimer) or their isomers, were also observed in field-collected WSBA samples, suggesting that the aqueous-phase reactions might contribute to the formation of emitted biomass burning aerosols. The aqueous photochemistry of both the phenols (photooxidation) and WSBA extracts (direct photolysis) could produce a series of highly oxygenated compounds, which in turn increases the oxidation degree of organic composition and acidity of the bulk solution. In particular, the LC/ESI-HRMS technique revealed significant photochemical evolution of the WSOC composition in WSBA samples, e.g. the photodegradation of low oxygenated species and the formation of highly oxygenated products. We also tentatively compared the mass spectra of photolytic time-profile WSBA extracts with each other for a more comprehensive description of the photolytic evolution. The calculated average oxygen-to-carbon ratio (O∕C) of oxygenated compounds in bulk extract increases from 0.38±0.02 to 0.44±0.02 (mean ± standard deviation), while the intensity (S∕N)-weighted average O∕C (O∕Cw) increases from 0.45±0.03 to 0.53±0.06 as the time of irradiation extends from 0 to 12 h. These findings indicate that the water-soluble organic fraction of combustion-derived aerosols has the potential to form more oxidised organic matter, contributing to the highly oxygenated nature of atmospheric organic aerosols.

The influence of plasma beta effects on the edge plasma transport in the Wendelstein 7-X standard configuration is studied systematically by using EMC3-EIRENE combined with a 3D equilibrium code named HINT. The magnetic topology changes induced by plasma beta effects are significantly reflected in plasma transport behaviors and heat flux patterns on divertor targets. After validating the modeling strategy by comparisons with experimental data, the extended simulations for high performance plasmas show that the threshold separatrix density for accessing the power detachment is reduced in higher beta plasmas. Compared with the vacuum field case, the impurity radiation distributions with finite beta effects are modified in the magnetic island region. The divertor heat flux is distributed more evenly along the toroidal direction on the strike line at the vertical target. The strike line on the horizontal target moves towards the pumping gap with an increase in the plasma beta. In addition, the different pressure profiles with the same central beta also result in a modified heat flux pattern on the divertor targets.

In order to deepen the understanding of the thermochemical behavior of reactive inorganics, which play an important role in slagging and fouling during combustion of agro-stalks, the oxidation behavior of the water-soluble fraction of corn stover, wheat straw and rice straw was examined using a simultaneous thermogravimetric analyzer. The oxidation characteristics were discussed in combination with elemental analysis of water-soluble fractions. Results showed that reactive inorganics elements account for 30–40% in water-soluble fractions of the three agro-stalks and carbon was oxidized at two separate stages. Four stages were found during oxidation of water-soluble fractions – (1) devolatilisation of organics (100‒400 °C); (2) oxidation of char (400–650 °C); (3) oxidation of char with melting of salts or decomposition of carbonate (650–800 °C); (4) vaporization of KCl (800–1000 °C). This work provides a base study for an optimized design of combustion for agro-stalks and pharmaceutical waste.

Here we investigated the effects of P compounds (KH2PO4 and Ca(H2PO4)2) with different addition rates of 0, 20, 40, 60, 80, and 100 kg P ha−1 yr−1 and NH4NO3 addition (0 and 100 kg N ha−1 yr−1) on soil labile inorganic phosphorus (IP) (dicalcium phosphate, Ca2-P), moderate-cycling IP, and recalcitrant IP fractions in a calcareous grassland of northeastern China. Soil moderate-cycling IP fractions, not readily available to plants but transforming into soil-available P quickly, include variscite (Al-P), strengite (Fe-P) and octacalcium phosphate (Ca8-P); recalcitrant IP fractions include hydroxylapatite (Ca10-P) and occluded P (O-P). Soil labile and moderate-cycling IP fractions and total P significantly increased with increasing P addition rates, with higher concentrations detected for KH2PO4 than for Ca(H2PO4)2 addition. Combined N and P treatments showed lower soil labile IP and moderate-cycling IP fractions compared to ambient N conditions, due to enhanced plant productivity. Moderate-cycling IP was mainly regulated by P addition and plant P uptake to further enhance labile IP and total P concentrations with KH2PO4 and Ca(H2PO4)2 addition. Soil labile IP was also directly and negatively affected by soil pH and plant P uptake with Ca(H2PO4)2 addition. Ca(H2PO4)2 addition significantly increased the soil recalcitrant IP (Ca10-P) fraction, while KH2PO4 addition showed no impact on it. A significant positive correlation was detected between soil labile IP, moderate-cycling IP fractions and soil Olsen-P which illustrated that labile IP and moderate-cycling IP fractions were important sources for soil-available P. Our results suggest that moderate-cycling IP fractions are essential for grassland P biogeochemical cycling and the chemical form of P fertilizer should be considered during fertilization management for maintaining soil-available P.

One of the proposed explanations for the unusual pseudogap behaviour of cuprate superconductors is the formation of an electron nematic phase. Murayama et al. find magnetic anisotropy in the pseudogap regime of HgBa2CuO4+δ, providing evidence for anomalous nematic ordering.

During its second operational campaign (OP 1.2a) W7-X operated with an edge island divertor. Much higher densities (1020m−3) than in to the previous, limiter campaign were achieved. In order to asses this improved performance and the nature of transport with regard to the expected higher densities and other parameters such as the electron and ion temperature, the electric field and plasma flow, measurements at the plasma edge were conducted with reciprocating probe, mounted on a Manipulator. The probe contains a set of Langmuir pins, Mach probes, compensation coils and a set of 3D pick up coils for the measurement of the local magnetic field and fluctuations, and an ion sensitive probe. It has been observed, in addition to differences due to the magnetic configurations, that the magnetic topology is sensitive to the plasma conditions, especially to changes due to a evolving toroidal plasma current. Measurements from divertor cameras showed that an increasing toroidal current in the standard configuration broadened the heat flux and shifted the strike line considerably. These down-stream observation can be complemented with the measurements at the mid-plane with the manipulator mounted probes. During the experiments the edge island remnant was identified with the measured edge plasma profiles and compared with the predictions from the field line tracing code. Those electron densities and temperatures have been used as an input for understanding edge transport with the EMC3-EIRENE modeling. The results from EMC3-EIRENE also help improve the caculated density profiles, since the modelling provides a profile of the effective charge Zeff. Keywords: W7-X, Langmuir probes, Magnetic islands, Plasma edge transport

Sequences of decisions that occur under uncertainty arise in a variety of settings, including transportation, communication networks, finance, defence, etc. The classic approach to find an optimal decision policy for a sequential decision problem is dynamic programming; however its usefulness is limited due to the curse of dimensionality and the curse of modelling, and thus many real-world applications require an alternative approach. Within operations research, over the last 25 years the use of Approximate Dynamic Programming (ADP), known as reinforcement learning in many disciplines, to solve these types of problems has increased in popularity. These efforts have resulted in the successful deployment of ADP-generated decision policies for driver scheduling in the trucking industry, locomotive planning and management, and managing high-value spare parts in manufacturing. In this article we present the first review of applications of ADP within a defence context, specifically focusing on those which provide decision support to military or civilian leadership. This article’s main contributions are twofold. First, we review 18 decision support applications, spanning the spectrum of force development, generation, and employment, that use an ADP-based strategy and for each highlight how its ADP algorithm was designed, evaluated, and the results achieved. Second, based on the trends and gaps identified we discuss five topics relevant to applying ADP to decision support problems within defence: the classes of problems studied; best practices to evaluate ADP-generated policies; advantages of designing policies that are incremental versus complete overhauls when compared to currently practiced policies; the robustness of policies as scenarios change, such as a shift from high to low intensity conflict; and sequential decision problems not yet studied within defence that may benefit from ADP.

Summary Objective Numerous equation to predict percent body fat using demographics and anthropometrics have been published but external validation of these equations is limited. The objective of this study was to validate published equations that use anthropometrics for prediction of percent body fat using external data. Methods Data were from the Visceral Fat, Metabolic Rate, and Coronary Heart Disease Risk I (VIM I) Study and the Fels Longitudinal Study (Fels). VIM I was conducted in a subset of subjects from the CARDIA study and included black and white adults 28–40 years (n = 392). Fels consisted of white participants 8–88 years (n = 1,044). Percent body fat assessed by dual X‐ray absorptiometry (DXA) in these two studies was compared to results calculated using 13 equations from Stevens et al. and nine other published equations. Results In general, the Stevens equations performed better than equations from other studies. For example, equation “I“ in women in VIM I, Fels adults, and Fels youth, R2 estimates were 0.765, 0.757 and 0.789, respectively. In men the estimates were 0.702 in VIM I, 0.822 in Fels adults and 0.905 in Fels youth. None of the results from the nine published equations showed R2 this high in corresponding groups. Conclusions Our results indicate that several of the Stevens equations have external validity superior to that of nine other published equations among varying age groups, genders and races.

With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM2.5 concentrations are high, meteorological influences on PM2.5 concentrations are strong. The dominant meteorological influence for PM2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

Previous studies showed that spermine could protect the organism from oxidative damage in vivo. However, in vivo information on the antioxidant-related underlying molecular mechanism of spermine is limited. In this experiment, we further evaluated the effects of spermine supplementation and extended spermine administration on the antioxidant status and antioxidant-related signaling molecules gene expression in the liver and longissimus dorsi of piglets. A total of 80 piglets were randomly distributed to two groups, that is, those with adequate nutrient intake administrated with spermine (0.4 mmol/kg BW) or those with restricted nutrient intake supplemented by saline. The piglets were fed in pairs for 7 h or 3, 6, or 9 days. The results are as follows: (1) spermine can promote the antioxidant capacity by increasing enzymatic antioxidant capacity, glutathione content and clearance of oxygen radicals; (2) spermine significantly increased the mRNA levels of enzymatic antioxidant substances, NF-E2-related nuclear factor 2, Kelch-like ECH-associated protein 1, and the mammalian target of rapamycin but decreased the mRNA levels of ribosomal p70 S6 kinase in the liver and longissimus dorsi of the piglets.

Brown carbon (BrC) draws increasing attention due to its effects on climate and other environmental factors. In China, household coal burned for heating and cooking purposes releases huge amounts of carbonaceous particles every year; however, BrC emissions have rarely been estimated in a persuasive manner due to the unavailable emission characteristics. Here, seven coals jointly covering geological maturity from low to high were burned in four typical stoves as both chunk and briquette styles. The optical integrating sphere (IS) method was applied to measure the emission factors (EFs) of BrC and black carbon (BC) via an iterative process using the different spectral dependence of light absorption for BrC and BC and using humic acid sodium salt (HASS) and carbon black (CarB) as reference materials. The following results have been found: (i) the average EFs of BrC for anthracite coal chunks and briquettes are 1.08 ± 0.80 and 1.52 ± 0.16 g kg−1, respectively, and those for bituminous coal chunks and briquettes are 8.59 ± 2.70 and 4.01 ± 2.19 g kg−1, respectively, reflecting a more significant decline in BrC EFs for bituminous coals than for anthracites due to briquetting. (ii) The BrC EF peaks at the middle of coal's geological maturity, displaying a bell-shaped curve between EF and volatile matter (Vdaf). (iii) The calculated BrC emissions from China's residential coal burning amounted to 592 Gg (1 Gg = 109 g) in 2013, which is nearly half of China's total BC emissions. (iv) The absorption Ångström exponents (AAEs) of all coal briquettes are higher than those of coal chunks, indicating that the measure of coal briquetting increases the BrC ∕ BC emission ratio and thus offsets some of the climate cooling effect of briquetting. (v) In the scenario of current household coal burning in China, solar light absorption by BrC (350–850 nm in this study) accounts for more than a quarter (0.265) of the total absorption. This implies the significance of BrC to climate modeling.

This paper presents a new method to correct rail errors of Ground Based Synthetic Aperture Radar (GB-SAR) in the discontinue mode. Generally, “light positioning” is performed to mark the GB-SAR position in the dis-continuous observation mode. Usually we assume there is no difference between the marked position and the real installation position. But in fact, it is hard to keep the GB-SAR positions of two campaigns the same, so repositioning errors can’t be neglected. In order to solve this problem, we propose an algorithm to correct the rail error after analyzing the GB-SAR rail error geometry. Results of the simulation experiment and the real experiment of a landslide in Lvliang, Shanxi, China, show the proposed method achieves an mm-level precision, enabling the D-GBSAR mode to be used in engineering projects.

In this article, we revisit the radical roots of adult education for social change by developing community-based anti-racism education through participatory action research. Drawing on critical race theory (CRT) as its theoretical framework, we incorporate principles of participatory action research (PAR) to conceptualize community-based anti-racism education where community members and academics collaborate as equal partners throughout the process. Three key features emerged out of this analysis to characterize this approach: using people's lived experiences as an entry point to understand contemporary forms of racism, underscoring the importance of participation at the grassroots level, and prioritizing an action-oriented feature of community-based anti-racism education. By combining synergies between CRT and PAR, this approach has the potential to contribute to facilitating collaborative, equitable partnerships in practicing anti-racism education in diverse communities and enabling action-oriented anti-racism education as a site of advocacy, emancipation, and institutional practice for social change.

Mudstones in the Sha-3 member of the Shahejie Formation, in the Tanggu area of the Huanghua Depression, have been found to contain analcime and ankerite. Hydrothermal sedimentation has been invoked to explain the origin of these two minerals, raising the question of whether hydrothermal activity occurred at a sufficient scale to significantly raise the salinity of the depositional environment. We applied a suite of organic petrological and geochemical methods to directly address this question. Maceral composition, kerogen type, and the distribution of n-alkanes, hopanes, and steranes indicate that the organic matter contained in these mudstones and dolomitic mudstones is mainly derived from algae and bacteria. The dominant acritarch genera, C31R/C30 hopane ratio, gammacerane index, Pr/Ph ratio, and the relationship between Pr/n-C17 and Ph/n-C18 suggest that the mudstones and dolomitic mudstones were deposited in an anoxic, saline lacustrine environment. Tmax, biomarker maturity indices, the Thermal Alteration Index (TAI) and Acritarch Alteration Index (AAI), and vitrinite reflectance all indicate that the organic matter is at an immature to early mature stage. The estimated maximum paleotemperature is close to the present-day burial temperature, and much lower than the homogenization temperature of the analcime veins in dolostones. Combined with the absence of unresolved complex mixtures on the n-alkane pattern, this suggests that hydrothermal activity had a negligible impact on the salinity and alkalinity of the depositional lake.

Rice chromosome single segment substitution line (SSSL) W23-19-06-06-11 with the genotype Rf3Rf3/Rf4Rf4, a strong restorer line for wild-abortive (WA) cytoplasmic male sterility (CMS), was recently identified from the SSSL library. To investigate the genetic mode of Rf genes and the genetic relationship among WA, yegong (Y), and dwarf-wildabortive (DA) CMS systems, the plants derived from three BC3F2 populations involving W23-19-06-06-11 and the three CMS lines, that carried the Rf3Rf3/Rf4Rf4, Rf3Rf3/rf4rf4, and rf3rf3/Rf4Rf4 genotypes and WA-, Y-, and DA-CMS cytoplasm, were selected and their pollen and spikelet fertility were evaluated. The results show that the genetic effect displayed a trend of Y-CMS > WA-CMS > DA-CMS in the genetic background of W23-19-06-06-11, the effect of Rf4 appeared to be slightly larger than that of Rf3, and their effects were additive for the three CMS systems. Two pairs of dominant genes governed the fertility restoration in pollen and spikelet in the W23-19-06-06-11 which indicates that the genetic mode of the Rf genes was a qualitative character for the three CMS systems.

To reveal the allelic differentiations at the two genes for fertility restoration (Rf) on chromosomes 1 (Rf3) and 10 (Rf4), 15 chromosome single segment substitution lines (SSSLs) with the Rf3 locus and 18 SSSLs with the Rf4 locus were crossed with Bobai A (BbA), a cytoplasmic male sterility line with wild abortive type of cytoplasm (WA-CMS), respectively. Based on the pollen and seed fertility of the F1 hybrids, the Rf3 and Rf4 genes were each classified into four alleles, namely Rf3-1, Rf3-2, Rf3-3, and Rf3-4 for Rf3, and Rf4-1, Rf4-2, Rf4-3, and Rf4-4 for Rf4. Out of the 33 SSSLs, an SSSL W23-19-06-06-11 carrying the genotype Rf3-4Rf3-4/Rf4-4Rf4-4 possessed the strongest restoring ability for BbA. To determine the genetic effects of Rf3 and Rf4 for WA-CMS, one BC3F2 population possessing the genetic background of W23-19-06-06-11 was generated from the cross between W23-19-06-06-11 and BbA by backcrossing and marker-assisted selection. In the BC3F2 population, the plants carrying the Rf3Rf3/Rf4Rf4, Rf3Rf3/rf4rf4, and rf3rf3/Rf4Rf4 genotypes were selected and their phenotyping for pollen and spikelet fertility were evaluated. The result showed that under the genetic background of SSSL W23-19-06-06-11, the effect of Rf4 appeared to be slightly larger than that of Rf3 and their effects were additive for WA-CMS system. These studies will lead to the transfer of Rf genes into adapted cultivars through marker-assisted selection in active hybrid rice breeding programs.

Hilar cholangiocarcinoma (HCCA) is an invasive hepatic malignancy that is difficult to biopsy; therefore, novel markers of HCCA prognosis are needed. Here, the level of canonical Wnt activation in patients with HCCA, intrahepatic cholangiocarcinoma (IHCC), and congenital choledochal cysts (CCC) was compared to understand the role of Wnt signaling in HCCA. Pathology specimens from HCCA (n=129), IHCC (n=31), and CCC (n=45) patients were used to construct tissue microarrays. Wnt2, Wnt3, β-catenin, TCF4, c-Myc, and cyclin D1 were detected by immunohistochemistry. Parallel correlation analysis was used to analyze differences in protein levels between the HCCA, IHCC, and CCC groups. Univariate and multivariate analyses were used to determine independent predictors of successful resection and prognosis in the HCCA group. The protein levels of Wnt2, β-catenin, TCF4, c-Myc, and cyclin D1 were significantly higher in HCCA compared to IHHC or CCC. Wnt signaling activation (Wnt2+, Wnt3+, nuclear β-catenin+, nuclear TCF4+) was significantly greater in HCCA tissues than CCC tissues. Univariable analyses indicated that expression of cyclin D1 as well as Wnt signaling activation, and partial Wnt activation (Wnt2+ or Wnt3+ and nuclear β-catenin+ or nuclear TCF4+) predicted successful resection, but only cyclin D1 expression remained significant in multivariable analyses. Only partial Wnt activation was an independent predictor of survival time. Proteins in the canonical Wnt signaling pathway were present at higher levels in HCCA and correlated with tumor resecility and patient prognosis. These results suggest that Wnt pathway analysis may be a useful marker for clinical outcome in HCCA.