Variable valence metal Cu with univalent and divalent conversion capacity was developed to achieve the interlayer doping and intralayer co-doping of g-C3N4. Univalent Cu atom prefer to dope into the ...interlayer of g-C3N4 to form a steady bridged bond structure to improve the charge transfer capacity of g-C3N4. Divalent Cu atoms can be doped on the intralayer of g-C3N4, to form an unstable but active-catalysis site.
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•g-C3N4 co-doped by Cu (I) and Cu (II).•Interlayer doping of g-C3N4 by univalent Cu atom sites.•Intralayer doping by divalent Cu atom sites.•Photocatalytic mineralize antibiotic to CO2 and H2O completely by visible light.
Copper element was employed to achieve the interlayer doping and intralayer doping in g-C3N4 (CN). Univalent Cu single atom prefer to dope into the interlayer site of CN to form a steady bridged bond structure. Further increasing the doping amount of Cu, except for the univalent Cu at the interlayer, some divalent Cu single atoms can be doped on the intralayer site of CN to form an unstable but active-catalysis structure. Electrochemical and theoretical calculation results reveal that Cu-interlayer doping can form an energy gradient between the different CN layers to decrease the charge transfer energy barrier between them. More importantly, these interlayer photogenerated electrons will converge on the divalent Cu, a catalysis active site for the photogenerated electrons, inducing more superoxide radicals and high activity. This two-sites modified CN, can mineralize a refractory antibiotic Norfloxacin (NOR) to CO2 and H2O completely under visible light stimulation, and the two-sites co-doping method provides a reference for CN photocatalyst modification to solve the questions of insufficient redox energy and low photons quantum efficiency of CN.
Argon bubbles are usually injected into steel continuous casting mold to prevent the clogging of submerged entry nozzle (SEN), but some bubbles may be entrapped to form defects in the final slab. In ...order to provide a reference for improving the quality of steel, a mathematical model based on the Eulerian-Lagrangian approach with advanced bubble break-up and coalescence models was established to study the effect of operation conditions on bubble distribution in a steel continuous casting mold. A bubble break-up model based on a daughter bubble fraction, which is suitable for the continuous casting system, was considered. The mathematic model was validated by comparing of the size and number of captured bubbles with the plant measurements of previous work. The result shows that argon gas injection has obvious effect on the flow pattern in the upper recirculation zone of the mold. In the upper recirculation zone, the bubbles mean diameter decreases and the bubble number increases with increasing casting speed, and both of the bubble size and number increase with the increase of gas flow rate. From the result, it can be found that the number and diameter of bubbles arriving at the advancing solidified shell region increase with increasing casting speed. In addition, the increase of gas flow rate causes more bubbles arriving at the advancing solidified shell region, but has little effect on the size of bubbles.
Increasing human activity in polar areas is making ice-going ships more indispensable in multiple operation scenarios. An improvement in ice-resistance prediction, which cannot be performed without ...accurate ice parameters, will promote the development of hull design and operational safety in ice-infested waters. The Nataf transformation is applied to generate correlated pseudo-random numbers which represent ice parameters; then, as a numerical method, the circumferential crack method is introduced to calculate the ice resistance of R/V Xuelong in level ice. The main factors which may have a large influence on simulated ice load are studied. The simulation results show that the Burr distribution is the most suitable model to describe the distribution of ice resistance calculated and ice-force amplitude concentrated at a lower level. The statistical results are also discussed and compared with similar research through empirical formulas and Monte Carlo methods. The present simulation can obtain more detailed information during the icebreaking process compared to similar research: the ice force at each time step is achieved; the key ice-force amplitude can be collected, which can benefit studies on hull structure; and potential stress generated by sea ice can be predicted. The present numerical tools and simulation results can provide a reference for ice-going ships sailing in level ice in most scenarios with regard to ice resistance and operational safety.
Merchant ships, which are quite different from icebreakers, usually require the light ice-strengthened bow under the floe-ice condition. According to ice-class B, requirements of China Classification ...Society (CCS), intermediate frames and thick hull plates are necessary for the ice belt area to resist floe-ice impact. However, due to the limited space, it is not practical to set so many intermediate longitudinals from manufacture point of view. In this paper, a modification method is proposed to solve the problem by maintaining the frame spacing and increasing the plate thickness. The aim is to make sure that the bow owns the equivalent ice-bearing capacity with the original frame spacing. At first, a bulk carrier with ice-class B is used for case study. According to the requirements of the ice class rule, a designed ice thickness is used to calculate the ice load acting on the bow area due to the impact of ice floe. Two structural models are presented to perform the strength analysis under ice load, including the out-shell plate model and the longitudinal model. The results show that increasing the plate thickness is helpful to remove the negative effect induced by enlarging the spacing of the longitudinal. A reasonable curve is presented to modify the bow for the ice-strengthened merchant ship, which shows the relationship between the increase of plate thickness and the spacing of longitudinal. Moreover, a model test of floe-ice—ship interaction is conducted to measure the dynamic ice load, based on which nonlinear dynamic FE analysis is used to verify the presented plate-thickness—longitudinal spacing curve. The results show that the proposed method can be used to improve the ice-strengthened bow structure effectively, which provides theoretical foundation to modify the requirement of CCS’s ice class rule.
Abstract
The development of overhead lines has met the electricity demand of the rapidly developing society. However, the large-scale installation of overhead lines and the natural environmental ...differences in different regions increase the complexity of the real-time management of the lines. To improve the efficiency of line management, this article constructs a theoretical and simplified electromagnetic field model of 500 kV three-phase overhead lines and studies the method of monitoring the current-sag state of the lines based on analyzing the distribution of magnetic field intensity under the three-phase overhead lines. Moreover, the placement of the tunneling magnetoresistance (TMR) sensor array was analyzed, and the current and sag reconstruction algorithm of the line was further proposed. The calculation results show that the simplified magnetic field model is accurate in most areas under the overhead line. The comparison of condition number and sensor position sensitivity value on sensor placement evaluation shows that the sensor position sensitivity value is more comprehensive, and it is recommended to use dual-axis TMR magnetic sensors. The relative error of the line sag calculated by the proposed TMR sensor array and algorithm is less than 3% and 4% for balanced and unbalanced three-phase line currents, respectively.
Several randomized clinical trials showed that aspirin could decrease the incidence of preeclampsia (PE) in women at high risk, but data from sources other than traditional clinical trials that ...investigating the preventive effect of aspirin 75 mg on PE is still lacking, especially in mainland China. We aimed to use Chinese real-world data to estimate the preventive effect of low-dose aspirin (LDA) on PE.
Clinical data of pregnant women who were at high risk of PE and had their first prenatal visit at the affiliated Taicang People's Hospital of Soochow University during November 31, 2018 and May 10, 2021 was retrospectively analyzed. Among the 266 included pregnant women, 115 individuals treated with aspirin 75 mg per day and the other 151 without such treatment were considered as the LDA group and the control group, respectively.
In the LDA group, 64 (55.65%) of 115 pregnant women took aspirin before 16 weeks of gestation. Besides, 12 (10.43%) and 34 (22.52%) women developed PE in the LDA group and control group, respectively; the aspirin prophylaxis was associated with a lower risk of PE (odds ratio = 0.40, 95% confidence interval = 0.20-0.82, P = 0.0098). In addition, LDA is slightly more effective when initiated before 16 weeks of gestation or in those without chronic hypertension, when compared with their counterparts.
Prophylaxis with 75 mg per day of aspirin in high-risk women resulted in a significantly lower incidence of PE than that in the control group.
A hovercraft can adapt to an ice area, open water, land and other environments, owing to its unique hull structure. It also plays an important role in transporting supplies, rescuing people, breaking ...ice and conducting other tasks. Ice load prediction is very important for structural safety and navigation of a polar ship, especially in design of air cushion icebreakers or ice breaking platforms. In this paper, based on a simplified circumferential icebreaking pattern, the icebreaking force of the hovercraft operating on the ice sheet at low speed is simulated in a numerical way. Numerical analysis of the icebreaking process with different ice thicknesses and bending strengths are performed. The numerical results are compared with model test data in a time domain for three operating cases. By analyzing the average ice force, the errors between numerical simulation results and model test measurements are less than 30%. The present study is significant for the preliminary design of new icebreaking hovercraft and it assists the operation possibility for existing hovercraft.
In computer vision and pattern recognition applications, there are usually a vast number of unlabelled data whereas the labelled data are very limited. Active learning is a kind of method that ...selects the most representative or informative examples for labelling and training; thus, the best prediction accuracy can be achieved. A novel active learning algorithm is proposed here based on one-versus-one strategy support vector machine (SVM) to solve multi-class image classification. A new uncertainty measure is proposed based on some binary SVM classifiers and some of the most uncertain examples are selected from SVM output. To ensure that the selected examples are diverse from each other, Gaussian kernel is adopted to measure the similarity between any two examples. From the previous selected examples, a batch of diverse and uncertain examples are selected by the dynamic programming method for labelling. The experimental results on two datasets demonstrate the effectiveness of the proposed algorithm.
Conversational machine reading comprehension (MRC) is a new question answering task, which is more challenging compared to traditional single-turn MRC since it requires a better understanding of ...conversation history. In this paper, a novel neural network model for conversational reading comprehension, namely TT-Net, is proposed, which is capable of capturing topic transfer features using temporal convolutional network (TCN) in the dialog. The TT-Block packaged by the BiLSTM, TCN and Self-attention mechanism is presented to extract topic transfer features between questions. Our model is evaluated on the CoQA benchmark dataset compared with several baseline models including the strong baseline model named FlowQA. The results show that the model outperforms the baseline models: BiDAF++ by 7.6% and FlowQA by 0.7%, especially in children's story domain our model promotes FlowQA's performance by 3.9%, which indicates that the TT-Net contributes to a decent promotion for conversational reading comprehension.
In many real-world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attempts to discover the ...most informative data points for labeling. The challenge is which unlabeled samples should be labeled to improve the classifier the most. Classical optimal experimental design algorithms are based on least-square errors over the labeled samples only while the unlabeled points are ignored. In this paper, we propose a novel active learning algorithm called neighborhood preserving D-optimal design. Our algorithm is based on a neighborhood preserving regression model which simultaneously minimizes the least-square error on the measured samples and preserves the neighborhood structure of the data space. It selects the most informative samples which minimize the variance of the regression parameter. We also extend our algorithm to nonlinear case by using kernel trick. Experimental results on terrain classification show the effectiveness of proposed approach.
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