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Suitable evaluation of distress is beneficial to understanding the in situ performance of deck pavement. This study attempts to evaluate the long-term in situ performance of American ChemCo epoxy asphalt concrete on the Xihoumen Bridge (XHMB) after 12 years of service. The traditional performance indexes were adopted to reveal the performance of XHMB. Then, based on the typical distresses, a new pavement performance index (PPI) was proposed to characterize the authentic distress condition. Finally, the performance evaluation and evolution were conducted. According to the results, the rutting depth indexes and riding quality indexes of all lanes are higher than 97 and 94, respectively. The pavement condition indexes of the pass lanes and drive lanes in 2021 are greater than 94 and 86, respectively, which is contradictory to the distribution of numerous distresses on the pavement. According to the PPI results, the PPIs of the down direction pass lane are mostly 100. However, for the down direction drive lane, the PPIs of about 30% of segments are below 80 or 60. Finally, based on the limited data, the distress of American ChemCo epoxy asphalt concrete may initiate after serving for 4–5 years and then escalate after about 10 years.

Recently, the interactions between internal solitary waves (ISWs) and the seabed have directed increasing attention to ocean engineering and offshore energy. In particular, ISWs induce bottom currents and pressure fluctuations in deep water. In this paper, we propose a method for predicting the shear stress induced by shoaling ISWs based on machine learning, and the developed approach can be used to quickly determine the safety and stability of ocean engineering. First, we provided a basic dataset for model training. Four machine learning models were selected to predict the shear stress induced by shoaling ISWs under different trim conditions. The results indicated that the performance of the convolutional neural network-long short-term memory (CNN-LSTM) forest prediction model was significantly better than the three other tested models, including long short-term memory (LSTM), support vector regression (SVR) and deep neural network (DNN) models. Therefore, the CNN-LSTM forest prediction model was the optimal model for predicting the shear stress induced by shoaling ISWs. Specifically, each metric of the CNN-LSTM model was smaller than that of the other three, and the root mean squared error to the standard deviation ratio was closest to 0.7. In addition, the CNN-LSTM model significantly outperformed the SVR and DNN models in terms of the length of prediction time. The predicted values by the CNN-LSTM model were consistent with the experimental values. The method for predicting shear stress based on machine learning in this paper can be used to predict the shear stress induced by shoaling ISWs, guide future field experiment designs, reduce damage to the seabed caused by ISWs, and promote the development of ocean engineering in deep water.

The host innate immune response to viral infection often involves the activation of type I interferons (IFNs). Not surprisingly, many viruses have evolved various mechanisms to disable the IFN pathway and evade the antiviral response involving innate immunity. Rabbit hemorrhagic disease (RHD) is caused by RHD virus (RHDV), but whether it can antagonize the production of host IFN to establish infection has not been investigated. In this study, we found that during RHDV infection, the expressions of IFN and the interferon-stimulated gene were not activated. We constructed eukaryotic expression plasmids of all RHDV proteins, and found that RHDV 3C protein inhibited poly(I:C)-induced IFN expressions. Using siRNA to interfere with the expressions of TLR3 and MDA5, we found that the MDA5 signal pathway was used by the 3C protein to inhibit poly(I:C)-induced IFNs expression. This effect was mediated by cleaving the interferon promoter stimulated 1 (IPS-1) protein. Finally, our study showed that IFN was effective against RHDV infection. In summary, our findings showed that RHDV 3C protein was a new interferon antagonist. These results increased our understanding of the escape mechanism from innate immunity mediated by the RHDV 3C protein.

Objective Structural equation modelling was applied to data from the Research in Arthritis in Canadian Children emphasizing Outcomes (ReACCh-Out) cohort to help elucidate causal pathways to decreased health-related quality of life (HRQoL) in children with JIA. Methods Based on published literature and clinical plausibility, a priori models were constructed with explicit root causes (disease activity, treatment intensity) and mediators (pain, disease symptoms, functional impairments) leading to HRQoL [measured by the Quality of my Life (QoML) scale and the Juvenile Arthritis Quality of Life Questionnaire (JAQQ)] at five disease stages: (i) diagnosis, (ii) 3–9 months after diagnosis, (iii) flare, (iv) remission on medications, (v) remission off medications. Following structural equation modelling, a posteriori models were selected based on data fit and clinical plausibility. Results We included 561, 887, 137, 186 and 182 patients at each stage, respectively. In a posteriori models for active disease stages, paths from disease activity led through pain, functional impairments, and disease symptoms, directly or through restrictions in participation, to decreased QoML scores. Treatment intensity had detrimental effects through psychosocial domains; while treatment side effects had a lesser role. Pathways were similar for QoML and JAQQ, but JAQQ models provided greater specificity. Models for remission stages were not supported by the data. Conclusion Our findings support disease activity and treatment intensity as being root causes of decreased HRQoL in children with JIA, with pain, functional impairments, and participation restrictions being mediators for disease activity; they support psychosocial effects and side effects as being mediators for treatment intensity.

Nowadays, the recovery of added-value compounds by pre-treatment and extraction has become imperative in the recycling and transformation of bio-waste. Hence, to achieve efficient bio-waste recycling and avoid the drawbacks of solvent and time consumption in traditional pre-treatment, a green and facile method of efficient separation and enrichment of luteolin (LTL) from honeysuckle leaves has been developed via the green synthesis of novel magnetic molecularly imprinted polymers (Fe3O4-LTL-MIPs). Fe3O4-LTL-MIPs were prepared in aqueous solution using polyethyleneimine and dopamine as eco-friendly bifunctional monomers via layer-by-layer assembly onto the amino-modified Fe3O4 carriers. The thin sandwich-biscuit-like imprinting layer in Fe3O4-LTL-MIPs provides sufficient binding sites with enhanced uniformity and accessibility for the template molecules, thus facilitating excellent recognition ability and rapid mass transfer. The obtained nanomaterials show homogeneous morphology, good crystallinity, satisfactory superparamagnetism, ultra-fast adsorption kinetics, high recognition ability, and excellent reusability. Moreover, Fe3O4-LTL-MIPs as solid-phase extraction adsorbents exhibit high efficiency for the separation and enrichment of LTL from the honeysuckle leaves combined with HPLC analyses. Therefore, the Fe3O4-LTL-MIPs could be potentially exploited as a feasible and efficient way to meet the goals of green chemistry for selective recycling and enriching target compounds from complicated bio-waste matrices.

Distributed radar array brings several new forthcoming advantages in aerospace target detection and imaging. The two-dimensional distributed array avoids the imperfect motion compensation in coherent processing along slow time and can achieve single snapshot 3D imaging. Some difficulties exist in the 3D imaging processing. The first one is that the distributed array may be only in small amount. This means that the sampling does not meet the Nyquist sample theorem. The second one refers to echoes of objects in the same beam that will be mixed together, which makes sparse optimization dictionary too long for it to bring the huge computation burden in the imaging process. In this paper, we propose an innovative method on 3D imaging of the aerospace targets in the wide airspace with sparse radar array. Firstly, the case of multiple targets is not suitable to be processed uniformly in the imaging process. A 3D Hough transform is proposed based on the range profiles plane difference, which can detect and separate the echoes of different targets. Secondly, in the subsequent imaging process, considering the non-uniform sparse sampling of the distributed array in space, the migration through range cell (MTRC)-tolerated imaging method is proposed to process the signal of the two-dimensional sparse array. The uniformized method combining compressed sensing (CS) imaging in the azimuth direction and matched filtering in the range direction can realize the 3D imaging effectively. Before imaging in the azimuth direction, interpolation in the range direction is carried out. The main contributions of the proposed method are: (1) echo separation based on 3D transform avoids the huge amount of computation of direct sparse optimization imaging of three-dimensional data, and ensures the realizability of the algorithm; and (2) uniformized sparse solving imaging is proposed, which can remove the difficulty cause by MTRC. Simulation experiments verified the effectiveness and feasibility of the proposed method.

In this paper, we introduce our solution to the vehicle re-identification (vehicle ReID) track2 in AI City Challenge 2021. As the key point of intelligent Traffic System, vehicle ReID has been a challenging task due to the higher intra-class and inter-class errors which are owing to variable vehicle orientation, camera and lighting. To reduce this error, at first, we innovatively propose a progressive data mining method to obtain more valid data from testing set. Then, we use the image to the mean of each tracklet method in the matching stage which can ensure the precision of image matching by reducing the error with the information of tracklets. Besides, we propose an adaptive weighted ensemble method which effectively improve the model capability. Finally, our method achieves 0.6533 in the mAP score which yields 4th place in the competition.

Scholarly impact assessment has always been a hot issue. It has played an important role in evaluating researchers, scientific papers, scientific teams, and institutions within science of science. Scholarly impact assessment is also used to address fundamental issues, such as reward evaluation, funding allocation, promotion and recruitment decision. Scholars generally agree that it is more reasonable to use weighted citations to assess the scholarly impact. Although a great number of researchers use weighted citations to access the scholarly impact, there is a lack of a systematic summary of citation weighting methods. To fill the gap, this paper summarizes the existing classical indicators and weighting methods used in measuring scholarly impact from the perspectives of articles, authors and journals. We also summarize the focus of the indicators involved in this paper and the weighting factors that involved in the weighting methods. Finally, we discuss the open issues to try to discover the hidden trends of citation weighting. Through this paper, we can not only have a clearer understanding of the weighting methods in the scholarly impact assessment, but also think more deeply about the weighting factors to be explored. Refereed/Peer-reviewed

Organophosphates (OPs) are hazardous chemicals widely used in industry and agriculture. Distribution of their residues in nature causes serious risks to humans, animals, and plants. To reduce hazards from OPs, quantitative structure-activity relationship (QSAR) models for predicting their acute oral toxicity in rats and mice and inhibition constants concerning human acetylcholinesterase were developed according to the bioactivity data of 456 unique OPs. Based on robust, two-dimensional molecular descriptors and quantum chemical descriptors, which accurately reflect OP electronic structures and reactivities, the influences of eight machine-learning algorithms on the prediction performance of the QSAR models were explored, and consensus QSAR models were constructed. Several strict model validation indices and the results of applicability domain evaluations show that the established consensus QSAR models exhibit good robustness, practical prediction abilities, and wide application scopes. Poor correlation was observed between acute oral toxicity at the mammalian level and the inhibition constants at the molecular level, indicating that the acute toxicity of OPs cannot be evaluated only by the experimental data of enzyme inhibitory activity, their toxicokinetic characteristics must also be considered. The constructed QSAR models described herein provide rapid, theoretical assessment of the bioactivity of unstudied or unknown OPs, as well as guidance for making decisions regarding their regulation.

In order to achieve the goal of ecological restoration, plant irrigation, and water retention in the external dump of open-pit coal mine in the arid desert area, it is proposed to use the mudstone in the stripped material to reconstruct the surface aquiclude and improve the water holding capacity of the topsoil. By taking the Hongshaquan Open-Pit Coal Mine as the study object, the red mudstone of mining level +650 was selected as the topsoil aquiclude material through the geological survey. XRD diffraction experiments are used to determine the composition of red mudstone including kaolinite mineral, quartz, potash feldspar, albite, and illite. The moisture content of the red mudstone is 4.16% as measured by the indoor drying experiment. And the particle size of 0.5 mm, 1 mm, and 2 mm and the thickness of 5 cm, 10 cm, and 20 cm rock samples were selected to conduct the indoor soil column experiment. Three indicators of initial infiltration rate, stable infiltration rate, and average infiltration rate were obtained according to the analysis and calculation of the water column drop rate, wet peak drop rate, and cumulative infiltration rate so that the permeability law and coefficient of each group of tests can be known. The finite element transient analysis theory and numerical simulation method were adopted to verify the results of physical experiments. The research results show that +650 level red mudstone has a strong antiseepage ability, and the smaller the particle size, the better the antiseepage performance. For 0.5 mm and 2 mm particle sizes, as the paving height increases, the water-proof effect is better. The laying height of 1 mm particle size has no obvious influence on the water barrier effect. The physical simulation was confirmed to have the same result trend as the numerical simulation, both of which are quadratic functions with the error within a reasonable range.

Modular construction methods are adopted in many spatial and temporal limited projects. As the major equipment used in modular construction, the mobile crane affects the safety and efficiency of construction significantly. Currently, building information modeling (BIM) is widely adopted to improve the lifting operation planning of cranes. However, the inaccurate simulation of the dynamic construction environment makes those BIM-based lifting operation planning methods unsuitable for land mobile cranes operation planning, such as in the overpass bridge construction project, which may cause several safety risks during the lifting process. Based on an overpass steel bridge construction project, this paper attempted to integrate the BIM and unmanned aerial vehicles (UAVs) to streamline lifting operation planning and construction monitoring. Specifically, in the preliminary stage, a level of development (LOD) 400 steel superstructure model was built and then divided into eighty sections. In addition, a three-dimensional (3D) geology model of the as-is construction site was modeled by UAV-captured images. Then, a fusion model which contains the lifting modules models, the as-is site model, and the crane model was gathered, based on which the collision detection was conducted by 4D crane operating path simulation. According to the results, three potential collisions were found and eliminated by lengthening the jib of the crane from 43.5 m to 46.5 m. Furthermore, the optimum crane location for lifting each steel structure was determined based on the 3D geology model. The study shows that the UAV is able to acquire geological information and then 3D simulates the real construction environment quickly and accurately. Furthermore, BIM and UAV have the potential to optimize the design and construction as well as the monitoring of bridge projects.

In this paper, several classical DOA estimation methods are applied to density-tapered thinned array. The density-tapered thinned array has the advantage that there is no grating lobe in the whole angle scanning range, and the unambiguous angle estimation of the target is obtained. The experimental results show that the classical DOA estimation method can be applied directly to the density-tapered thinned array to obtain satisfactory results, which lays a foundation for the practical application of the density-tapered thinned array. In addition, the effects of sparsity and number of elements on DOA estimation are analyzed, and the advantages of density-tapered thinned array over uniform arrays are verified.

17β-estradiol (E2), as one of the pharmaceutical and personal care product, frequently contaminates environmental water as estrogen pollutant and possesses great risk to human survival as well as the sustainable development of the ecosystem. Herein, to achieve an effective adsorbent system for the selective removal of E2 from the environmental water, Fe3O4 nanoparticles are subjected to chemical etching to reduce the overall mass and then employed as carriers to prepare a novel type of lightweight daisy-like magnetic molecularly imprinted polymers (LD-MMIPs) adopting template immobilization strategy. The LD-MMIPs based etched magnetic nanoparticles not only exhibit light mass but also have plentiful imprinted sites in the etched channels, which significantly increases the adsorption capacity for E2. The daisy-like LD-MMIPs own strong magnetic responsiveness, well crystallinity, fast binding kinetics, high adsorption amount, and excellent selectivity. Moreover, combining with HPLC, the LD-MMIPs as adsorbents have been successfully used to specifically recognize and detect trace E2 in environmental water. Thus, the proposed LD-MMIPs with high adsorption capacity hold great potential in monitoring water pollution. Additionally, this work also provides an alternative strategy for improving the adsorption capacity of magnetic molecularly imprinted polymers through a convenient chemical etching technology.

Nowadays, the attraction to talents has become increasingly prodominent in determing the future development prospect of cities. How to quantify the attractiveness of cities to talents is an important issue in evaluating the comprehensive competitiveness of cities. This paper takes Xi’an and other emerging first-tier cities in China as the main research object, and classifies the indicators that affect the attractiveness of urban talents into five specific categories. A set of evaluation models are constructed by using entropy weight method, information entropy method and TOPSIS algorithm. The different indicators that measure the level of urban development are normalized and weighted to obtain the attractiveness index of urban talents to describe the attractiveness of talents in cities with similar development levels. To prove the rationality of the model, we apply this evaluation model to different cities and test its stability.

The density-tapered method is a method to simulate amplitude weighting of full array by using the density of antenna element. However, the probability of the existence and non-existence of the element is 0 and 1 respectively, which makes the performance of the side lobe level of the pattern worse than that of the amplitude weighting of full array. In this paper, by improving the density-tapered method, gradual and interdependent density-tapered method is proposed to realize the design of sparse linear array, and the simulation experiments are carried out to compare and analyze the performance of peak side lobe level. The experimental results show that the improved density-tapered method can further reduce the side lobe level of the pattern.

The electrical and electronic devices become more and more integrated and miniaturized. It is necessary to develop high performance lead-free energy storage ceramics. In this work, new relaxor ferroelectric (1-x)(0.76Bi0.5Na0.5TiO3-0.24SrTiO3)-xBi(Ni2/3Nb1/3)O3 ceramics were prepared by the traditional solid-state reaction method. Particularly, the 0.90(BNT-ST)-0.10BNN ceramic exhibits the excellent recoverable energy storage density (Wrec = 4.1 J/cm3) and efficiency (η = 83.15%) under a low electric field (250 kV/cm). The 0.90(BNT-ST)-0.10BNN ceramic has excellent stability between 25 °C and 120 °C. In addition, an ultrahigh power density of 49.8 WM/cm3 and a fast charge-discharge rate (t0.9 = 62.4 ns) can be obtained simultaneously. These properties indubitably reflect that the (1-x)(BNT-ST)-xBNN ceramics have a great potential for the applications of high energy storage capacitors.

Recently, NaNbO3 has aroused the enthusiasm of researchers due to its potential application for energy storage. In this work, lead-free (1-x)NaNbO3-xBi(Sn0.5Ni0.5)O3 ceramics or (1-x)NN-xBSN in abbreviation were prepared by the traditional solid-state reaction method. The microstructure, dielectric properties and energy storage performances of (1-x)NN-xBSN ceramics were investigated in detail. Superior breakdown strength and underdamped discharge abilities are achieved in 0.88NN-0.12BSN ceramic with a maximum recoverable energy storage density (2.01 J/cm3) and high efficiency (80.3%) at 310 kV/cm. The excellent stability of energy storage properties in the frequency range from 100 Hz to 1 MHz, and the temperature range from −150 to 300 °C, are observed in the 0.88NN-0.12BSN ceramic. Furthermore, the 0.88NN-0.12BSN ceramic exhibits a large current density (~979.59 A/cm2), an extremely high power density (~88.16 MW/cm3) and stable discharge period of about 51 ns.

Human pose estimation is one of the important challenges in computer vision tasks. In the past three years, various algorithms for pose estimation have emerged one after another and have achieved good results. However, from time to time, there are some keypoints that cannot be accurately predicted due to the ambiguity in images. To address such problems, we make corresponding improvements on RMPE multi-person pose estimator. On the one hand, we introduce a channel-attention mechanism to enhance the predictive ability of heat map on keypoints. On the other hand, we design a geometry constraint strategy during the test phase to control the way of keypoint connection which can compensate insufficient network functions and training samples. We carry out experiments on a standard benchmark for multi-person pose estimation, and the results prove that the proposed method can more effectively distinguish ambiguous keypoints and estimate poses.

Information systems (IS) is a vital research area in both science and engineering, whose revolutions in terms of theories, techniques, and applications promote the evolution of human society. At the same time, the complexity and dynamics of IS raise the challenge for exploring the topic in detail. In this paper, we present a quantitative analysis on bibliographic dataset to reveal the evolution of information systems in 2 decades (1996–2015). We select 39,767 papers published in 8 top-tier journals and conferences between 1996 and 2015 and explore the anatomy from manifold. We find that IS is experiencing the sustainable growth phase in terms of increased productivity, impact, and collaboration. The field is benefited from collaborative, open-minded, and in-depth efforts evidenced from the growing number of co-authors per paper, the continual declining of self-citation rate, and increased reference age, respectively. By applying topic detection models on paper titles, abstracts, and keywords, we infer the representative topics and research directions, which can also reveal the research landscape within this field. Finally, we measure the temporal trends of topics and identify the innovative years in the 20 years’ development history of IS. These discoveries can benefit not only researchers in terms of promoting understanding of the entire field, but also governments for funding agencies. Refereed/Peer-reviewed

Human pose estimation is a fundamental but challenging task in computer vision. Although batch normalization is widely used for deep learning, feature extraction in deep convolutional neural networks (DCNN) is still not well explored. In this work, we propose a pose encoding module (PEM) to enhance the learning ability and generalization ability of feature extraction. Given input images, PEM integration instance normalization and batch normalization, combining them in an appropriate way to learn to capture and eliminate appearance changes while maintaining the distinction between learning features can be seen as an integration and adjustment of global information. In addition, we use a simple and efficient up-sampling strategy to recover high-resolution representations for predicting more accurate human keypoint heatmaps, which has achieved better performance than the average network in recent missions. We studied our approach on a standard benchmark for human pose estimation.

In this study, the characteristics of a round turbulent jet in the vicinity of a free surface are investigated. The jet issued from a nozzle located at a depth five times the nozzle diameter (d = 10 mm) below and parallel to the free surface. The jet exit velocity was 2.8 m/s and the resulting Reynolds number was 28,000. Instantaneous two-dimensional PIV measurements were obtained in the vertical central plane and in several horizontal planes at various distances (y/d = 0,±1,±2,±3± 4) from the axis of the nozzle. All fields-of-view were positioned at streamwise locations in the range of 28