Offshore oil and gas production is increasingly growing popular globally. Produced water (PW), which is the largest byproduct of oil and gas production, is a complex mixture of dissolved and ...undissolved organic and inorganic substances. PW contributes considerably to oil pollution in the offshore petroleum and gas industry owing to the organic substances, which mainly include hydrocarbons; this is a major concern to researchers because of the long-term adverse effects on the ecosystem. Since the development of offshore petroleum and gas industry, the PW treatment process has been classified into pretreatment, standard-reaching treatment, and advanced purification treatment based on the characteristics of PW and has been coupled with the environmental, economic, and regulatory considerations. The mechanism, design principle, application, and development of conventional technologies for PW treatment, such as gravity and enhanced gravity sedimentation, hydrocyclone, gas flotation, and medium filtration, are summarized in this study. Novel methods for further application, such as tubular separation, combined fibers coalescence, and membrane separation, are also discussed. Enhancement of treatment with multiple physical fields and environmentally friendly chemical agents, coupled with information control technology, would be the preferred PW treatment approach in the future. Moreover, the PW treatment system should be green, efficient, secure, and intelligent to satisfy the large-scale, unmanned, and abyssal exploration of offshore oil and gas production in the future.
Classical offshore gas field platforms with connecting bridges in the South China Sea and the standby ship beside the platforms. Functions of three platforms in the figure are well drilling and workover, gas production, and accommodation of personnel Display omitted
•Produced water (PW) has danger or potential danger to the ocean environment.•Oil and suspend solid removal were two important steps for PW treatment.•PW management is based on fundamental characteristics, regulations and standards.•Intellectualization and automation will be the development trend for this industry.•Physical devices coupled with chemical agents are the realistic treatment process.
Mechanically driven light generation is an exciting and under‐exploited phenomenon with a variety of possible practical applications. However, the current driving mode of mechanoluminescence (ML) ...devices needs strong stimuli. Here, a flexible sensitive ML device via nanodopant elasticity modulus modification is introduced. Rigid ZnS:M2+(Mn/Cu)@Al2O3 microparticles are dispersed into soft poly(dimethylsiloxane) (PDMS) film and printed out to form flexible devices. For various flexible and sensitive scenes, SiO2 nanoparticles are adopted to adjust the elasticity modulus of the PDMS matrix. The doped nanoparticles can concentrate stress to ZnS:M2+(Mn/Cu)@Al2O3 microparticles and achieve intense ML under weak stimuli of the moving skin. The printed nano‐/microparticle‐doped matrix film can achieve skin‐driven ML, which can be adopted to present fetching augmented animations expressions. The printable ML film, amenable to large areas, low‐cost manufacturing, and mechanical softness will be versatile on stress visualization, luminescent sensors, and open definitely new functional skin with novel augmented animations expressions, the photonic skin.
A flexible, sensitive mechanoluminescence (ML) device is demonstrated via matrix elasticity modulus modification. Rigid ZnS:M2+(Mn/Cu)@Al2O3 microparticles are dispersed into soft poly(dimethylsiloxane) (PDMS) film and printed for preparing flexible devices. Via a SiO2‐nanoparticle dopant, the ML intensity for small strain is significantly increased. The ML devices achieve intense ML under the weak stimuli of moving skin, which will be significant for photonic‐skin devices.
Demands for the detection of harmful gas in daily life have arisen for a period and a gas nano-sensor acting as a kind of instrument that can directly detect gas has been of wide concern. The ...spinel-type nanomaterial is suitable for the research of gas sensors because of its unique structure. However, the existing instability, higher detection limit, and operating temperature of the spinel materials limit the extension of the spinel material sensor. This paper reviews the research progress of spinel materials in gas sensor technology in recent years and lists the common morphological structures and material sensitization methods in combination with previous works.
Abstract
Cyclin D1 is one of the most important oncoproteins that drives cancer cell proliferation and associates with tamoxifen resistance in breast cancer. Here, we identify a lncRNA, DILA1, ...which interacts with Cyclin D1 and is overexpressed in tamoxifen-resistant breast cancer cells. Mechanistically, DILA1 inhibits the phosphorylation of Cyclin D1 at Thr286 by directly interacting with Thr286 and blocking its subsequent degradation, leading to overexpressed Cyclin D1 protein in breast cancer. Knocking down DILA1 decreases Cyclin D1 protein expression, inhibits cancer cell growth and restores tamoxifen sensitivity both in vitro and in vivo. High expression of DILA1 is associated with overexpressed Cyclin D1 protein and poor prognosis in breast cancer patients who received tamoxifen treatment. This study shows the previously unappreciated importance of post-translational dysregulation of Cyclin D1 contributing to tamoxifen resistance in breast cancer. Moreover, it reveals the novel mechanism of DILA1 in regulating Cyclin D1 protein stability and suggests DILA1 is a specific therapeutic target to downregulate Cyclin D1 protein and reverse tamoxifen resistance in treating breast cancer.
•We analyzed variations in eco-environmental quality within Minjiang River Basin.•Two species distribution models effectively extracted the driving factors.•Degree of landscape fragmentation and ...drastic land use were the main factors.•Remote sensing ecological index well quantified the eco-environmental quality.
Understanding the spatial variations in regional eco-environmental quality and their driving factors is essential for environmental management and protection. However, the lack of quantitative analyses in relevant studies has often hindered the formulation and implementation of effective eco-environmental policies. Taking Minjiang River Basin as an example, we used the remote sensing ecological indices (RSEI) to objectively and quantitatively characterize the eco-environmental quality. We also introduced and compared the maximum entropy (MaxEnt) and the random forest models to identify the critical driving factors. Results showed that the eco-environmental quality of Minjiang River Basin in 2020 was good overall, and the areas with good or excellent eco-environmental quality accounted for 58%. The areas with poor eco-environmental quality were mainly distributed in the periphery of the basin and the riverine areas. Both the MaxEnt and the random forest models were applicable to identify the critical driving factors and indicated that the degrees of landscape fragmentation and drastic land use were the main factors causing spatial variation of eco-environmental quality in the Minjiang River Basin. This study provides a new perspective and method for quantitative analysis of the driving factors of the spatial variations in regional eco-environmental quality for future eco-environmental management and protection.
Various autonomous or assisted driving strategies have been facilitated through the accurate and reliable perception of the environment around a vehicle. Among the commonly used sensors, radar has ...usually been considered as a robust and cost-effective solution even in adverse driving scenarios, e.g., weak/strong lighting or bad weather. Instead of considering fusing the unreliable information from all available sensors, perception from pure radar data becomes a valuable alternative that is worth exploring. In this paper, we propose a deep radar object detection network, named RODNet, which is cross-supervised by a camera-radar fused algorithm without laborious annotation efforts, to effectively detect objects from the radio frequency (RF) images in real-time. First, the raw signals captured by millimeter-wave radars are transformed to RF images in range-azimuth coordinates. Second, our proposed RODNet takes a snippet of RF images as the input to predict the likelihood of objects in the radar field of view (FoV). Two customized modules are also added to handle multi-chirp information and object relative motion. The proposed RODNet is cross-supervised by a novel 3D localization of detected objects using a camera-radar fusion (CRF) strategy in the training stage. Due to no existing public dataset available for our task, we create a new dataset, named CRUW,<xref ref-type="fn" rid="fn1"> 1 1
The dataset and code are available at https://www.cruwdataset.org/ .
which contains synchronized RGB and RF image sequences in various driving scenarios. With intensive experiments, our proposed cross-supervised RODNet achieves 86% average precision and 88% average recall of object detection performance, which shows the robustness in various driving conditions.
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•Wood lignin derived carbon quantum dots for in-situ photothermal thermogenesis.•Green fabrication strategy of wood resources with ecological and economic merits.•Evaporation ...performance of 1.18 kg·m−2 with efficiency up to 79.5% was achieved.•Fast induced thermogenesis performance and water adsorption via capillary force.•Water transportation and evaporation mechanisms were comprehensively revealed.
Photothermal evaporation and desalination via renewable solar energy has promising potential to alleviate freshwater scarcity. However, recent reported systems usually lack sufficient environmental compatibility, ecological security, and energy-saving concern. Here, a novel and green photothermal evaporation system with ecological and economic advantages was designed. An evaporation performance of 1.18 kg·m−2 (1.09 kg·m−2·h−1) with up to 79.5% efficiency at one sun illumination (1 kW·m−2) was achieved. More importantly, a series of simulation and numerical modelling was synchronously developed to analyze in-depth the main factors that affect water transportation and evaporation processes. The channel size, temperature distribution, and formed gradient were carefully investigated and discussed. Notably, this system exhibited satisfactory repeatability and stability. In addition, only a few photothermal components are required in this system, which will also bring a significant economic merit. Taken together, this work successfully provides new insights into developing a sustainable photothermal evaporation system with ecologically friendly property and satisfactory performance in practical application. Moreover, it also reveals the corresponding water transportation and photothermal evaporation mechanisms, and maximizes the evaporation efficiency.
There is concern regarding the long-term vibration effects caused by metro trains on historic buildings. In this paper, the impact of metro train-induced vibrations on the Bell Tower in Xi’an above ...two spatially overlapping tunnels was studied.
Metro Line 2 has been operational since 2011, and Line 6 is still under construction. To study and control the effect of micro vibrations on the Bell Tower, a metro train–track–tunnel–soil 3D dynamic FE model was developed. The vibration response generated by Line 2 was then predicted, and the influences of train speed on ground vibration were analysed. In addition, a detailed in situ measurement, which helped calibrate the numerical model and determine the dynamic behaviour of timber structures, was performed. Finally, the calibrated models and measured results were used to predict vibrations caused by road traffic and trains from two spatially overlapping metro lines. This was performed under different route schemes and train operation conditions.
The results showed that installing steel spring floating slab tracks (FST) and decreasing train speeds had obvious effects on controlling the ground peak particle velocity (PPV). Simulated results from both the input impulse and output response generated by metro Line 2 matched well with actual measurements. If correct designs are employed, it is possible to resolve the vibration problem on historic buildings caused by metro trains.
•A case study on traffic induced vibrations on historic buildings was performed.•Vibration caused by road traffic and two metro lines were considered.•Decreasing train speed has obvious effects on the controlling of ground vibrations.•Solving the vibration problem on historic buildings caused by metro trains is possible.
Greenland ice cores are high-resolution archives of atmospheric dust loadings, and a better understanding of the driving factors for Greenland ice core dust concentration changes across different ...timescales provides valuable insights into changes in atmospheric circulation pattern and benefits accurate prediction of the future climate change. In this review, based on the dust record of the NGRIP ice core, we systematically characterize the Greenland ice core dust concentration changes during the last glacial, and explore the major driving factors.
Based on the previously published and own isotope geochemical data, we estimated the contributions of provenances for the Greenland ice core dust using Bayesian mixing model. The results show that the dust was primarily derived from the Asian sources (71.5%) during the last glacial. Dust contributions from Africa include 10% (6.9%–12.0%) for North Africa and 6.9% (4.6%–8.3%) for West Africa; East Central & Eastern European sources yield a contribution of 11.7% (8.3%–14.2%). Subsequently, we revealed the contributions of multiple influencing factors to the Greenland dust concentration changes on orbital scale using the Lindeman-Merenda-Gold method. Overall, the findings highlight a crucial role of the aeolian activity in sources in controlling the Greenland dust concentration changes during the last glacial (63%). A greater effect of the atmospheric transport efficiency is also found (31%); by contrast, the spilt of jet stream contributes little (5%). We further argue that the variations in contribution of intensity of aeolian activity in sources through MIS2–5 may be related to glacial grinding by high-altitude mountain glaciers, with more significant influences exerted on variations in the Greenland dust concentration during MIS4. Inversely, more contributions from the atmospheric transport efficiency (wet deposition and reduced atmospheric residence time of dust in transport pathways) are observed during MIS2 and MIS3 than those during MIS4 and maybe MIS5. The results about changes of the contributing proportions of intensities of the different source areas throughout MIS2–5 reveal the major roles of sediment availability, displacement of the westerlies, and the Northern Hemisphere ice volume. The variations in contribution of the split of jet stream through MIS2–5 also demonstrate its minor role in influencing the Greenland dust concentration changes. In addition, it is suggested that the 21-ka precessional period found in the Greenland dust records possibly reflects the integrated response of paleoclimate changes to Milankovitch forcing (northern summer insolation). As for variations in the last glacial maximum (LGM) dust concentration, the enhanced dust emissions induced by changes of the North Atlantic jet stream over the Central and Eastern Europe and the Tarim Basin promoted the sharp dust concentration increases during the early-LGM. Such a scenario was intimately related to more frequent Rossby-wave breakings under negative NAO/AO phases. Furthermore, loss of dust aerosol due to wet deposition en route and ice accumulation rates could also have affected the Greenland dust concentration changes during the LGM. The findings are thought to enable interpretation of the observed decoupled relationship between the CLP loess accumulation rates and the Greenland dust concentrations during the LGM.
•Systematically characterizing the Greenland ice core dust flux changes.•Provenances of the Greenland ice core dust were identified in detail.•Drivers of the last glacial dust content changes were quantitatively assessed.•Providing a full explanation of the sharply changing dust contents during the LGM.
Forest fires may have devastating consequences for the environment and for human lives. The prediction of forest fires is vital for preventing their occurrence. Currently, there are fewer studies on ...the prediction of forest fires over longer time scales in China. This is due to the difficulty of forecasting forest fires. There are many factors that have an impact on the occurrence of forest fires. The specific contribution of each factor to the occurrence of forest fires is not clear when using conventional analyses. In this study, we leveraged the excellent performance of artificial intelligence algorithms in fusing data from multiple sources (e.g., fire hotspots, meteorological conditions, terrain, vegetation, and socioeconomic data collected from 2003 to 2016). We have tested several algorithms and, finally, four algorithms were selected for formal data processing. There were an artificial neural network, a radial basis function network, a support-vector machine, and a random forest to identify thirteen major drivers of forest fires in China. The models were evaluated using the five performance indicators of accuracy, precision, recall, f1 value, and area under the curve. We obtained the probability of forest fire occurrence in each province of China using the optimal model. Moreover, the spatial distribution of high-to-low forest fire-prone areas was mapped. The results showed that the prediction accuracies of the four forest fire prediction models were between 75.8% and 89.2%, and the area under the curve (AUC) values were between 0.840 and 0.960. The random forest model had the highest accuracy (89.2%) and AUC value (0.96). It was determined as the best performance model in this study. The prediction results indicate that the areas with high incidences of forest fires are mainly concentrated in north-eastern China (Heilongjiang Province and northern Inner Mongolia Autonomous Region) and south-eastern China (including Fujian Province and Jiangxi Province). In areas at high risk of forest fire, management departments should improve forest fire prevention and control by establishing watch towers and using other monitoring equipment. This study helped in understanding the main drivers of forest fires in China over the period between 2003 and 2016, and determined the best performance model. The spatial distribution of high-to-low forest fire-prone areas maps were produced in order to depict the comprehensive views of China’s forest fire risks in each province. They were expected to form a scientific basis for helping the decision-making of China’s forest fire prevention authorities.
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