39 research outputs found

    NAQPMS-PDAF v2.0: A Novel Hybrid Nonlinear Data Assimilation System for Improved Simulation of PM2.5 Chemical Components

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    PM2.5, a complex mixture with diverse chemical components, exerts significant impacts on the environment, human health, and climate change. However, precisely describing spatiotemporal variations of PM2.5 chemical components remains a difficulty. In our earlier work, we developed an aerosol extinction coefficient data assimilation (DA) system (NAQPMS-PDAF v1.0) that is suboptimal for chemical components. This paper introduces a novel hybrid nonlinear chemical DA system (NAQPMS-PDAF v2.0) to accurately interpret key chemical components (SO42-, NO3-, NH4+, OC, and EC). NAQPMS-PDAF v2.0 improves upon v1.0 by effectively handing and balancing stability and nonlinearity in chemical DA, which is achieved by incorporating the non-Gaussian-distribution ensemble perturbation and hybrid Localized Kalman-Nonlinear Ensemble Transform Filter with an adaptive forgetting factor for the first time. The dependence tests demonstrate that NAQPMS-PDAF v2.0 provides excellent DA results with a minimal ensemble size of 10, surpassing previous reports and v1.0. A one-month DA experiment shows that the analysis field generated by NAQPMS-PDAF v2.0 is in good agreement with observations, especially reducing the underestimation of NH4+ and NO3- and the overestimation of SO42-, OC, and EC. In particular, the CORR values for NO3-, OC, and EC are above 0.96, and R2 values are above 0.93. NAQPMS-PDAF v2.0 also demonstrates superior spatiotemporal interpretation, with most DA sites showing improvements of over 50 %–200 % in CORR and over 50 %–90 % in RMSE for the five chemical components. Compared to the poor performance in global reanalysis dataset (CORR: 0.42–0.55, RMSE: 4.51–12.27 µg/m3) and NAQPMS-PDAF v1.0 (CORR: 0.35–0.98, RMSE: 2.46–15.50 µg/m3), NAQPMS-PDAF v2.0 has the highest CORR of 0.86–0.99 and the lowest RMSE of 0.14–3.18 µg/m3. The uncertainties in ensemble DA are also examined, further highlighting the potential of NAQPMS-PDAF v2.0 for advancing aerosol chemical component studies

    Using eDNA to detect the distribution and density of invasive crayfish in the Honghe-Hani rice terrace World Heritage site

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    The Honghe-Hani landscape in China is a UNESCO World Natural Heritage site due to the beauty of its thousands of rice terraces, but these structures are in danger from the invasive crayfish Procambarus clarkii. Crayfish dig nest holes, which collapse terrace walls and destroy rice production. Under the current control strategy, farmers self-report crayfish and are issued pesticide, but this strategy is not expected to eradicate the crayfish nor to prevent their spread since farmers are not able to detect small numbers of crayfish. Thus, we tested whether environmental DNA (eDNA) from paddy-water samples could provide a sensitive detection method. In an aquarium experiment, Real-time Quantitative polymerase chain reaction (qPCR) successfully detected crayfish, even at a simulated density of one crayfish per average-sized paddy (with one false negative). In a field test, we tested eDNA and bottle traps against direct counts of crayfish. eDNA successfully detected crayfish in all 25 paddies where crayfish were observed and in none of the 7 paddies where crayfish were absent. Bottle-trapping was successful in only 68% of the crayfish-present paddies. eDNA concentrations also correlated positively with crayfish counts. In sum, these results suggest that single samples of eDNA are able to detect small crayfish populations, but not perfectly. Thus, we conclude that a program of repeated eDNA sampling is now feasible and likely reliable for measuring crayfish geographic range and for detecting new invasion fronts in the Honghe Hani landscape, which would inform regional control efforts and help to prevent the further spread of this invasive crayfish

    3% diquafosol sodium eye drops in Chinese patients with dry eye: a phase IV study

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    IntroductionThe efficacy and safety of 3% diquafosol sodium eye drops in Chinese patients with dry eye in the real-world setting remains unclear.Methods3099 patients with dry eye symptoms were screened according to Asia Dry Eye Society latest recommendation. Among them, 3000 patients were enrolled for a phase IV study. We followed up with multiple clinical characteristics including corneal fluorescein staining, tear break up time, Schirmer’s tests, visual acuity, intraocular pressure, and others. The follow ups were performed at baseline, 2 weeks and 4 weeks after treatment.ResultsBased on the results of corneal fluorescein staining and tear break up time, all age and gender subgroups exhibited obvious alleviation of the symptoms among the patients with dry eye, and the data in elderly group showed the most significant alleviation. All the adverse drug reactions (ADRs, 6.17%) were recorded, among which 6% local ocular ADRs were included. Meanwhile, mild ADRs (91.8%) accounted for the most. Most of the ADRs (89.75%) got a quick and full recovery, with an average time at 15.6 days. 1.37% of patients dropped out of the study due to ADRs.DiscussionThe use of 3% diquafosol sodium eye drop is effective and safe in the treatment of dry eye, with a low incidence of ADRs showing mild symptoms. This trial was registered at Chinese Clinical Trial Registry ID: ChiCTR1900021999 (Registration Date: 19/03/2019)

    A Semantic++ MapReduce Parallel Programming Model

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    Guest Editors’ Introduction

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    Research advances on the dissociation dynamics of natural gas hydrates

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    Natural gas hydrate is a kind of clean energy with great development potential but is still not commercially developed due to the bottlenecks such as exploitation technology, economical efficiency, and environmental effects.In recent years, people have explored the application of hydrate technology in the field of CO2 capture, seawater desalination, energy storage, gas separation, etc. One of the most challenging and critical problems is how the hydrates are formed and decomposed at any time. This paper summarizes the fundamental research on hydrate decomposition dynamics, including hydrate decomposition properties, influencing factors, and dissociation mechanisms. Moreover, the paper reviews the development of hydrate dissociation dynamics models. The existing models are divided into four categories according to dissociation mechanisms: Thermal dissociation models, intrinsic dynamics models, mass transfer dissociation models and integrated models, and their assumptions, main understanding and limitations are highlighted. Future directions for improving hydrate dissociation dynamics research are foreseen to deepen the understanding of hydrate dissociation dynamics and promote the development and utilization of hydrates

    Coordinated Formation Design of Multi-Robot Systems via an Adaptive-Gain Super-Twisting Sliding Mode Method

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    This paper presents a super-twisting-based sliding mode control method for the formation problem of multi-robot systems. The multiple robots contain plenty of uncertainties and disturbances. Such a control method has two adaptive gains that can contribute to the robustness and improve the response of the formation maneuvers despite these uncertainties and disturbances. Based on the leader-follower frame, this control method was investigated. The closed-loop formation stability is theoretically guaranteed in the sense of Lyapunov. From the aspect of practice, the control method was carried out by a multi-robot system to achieve some desired formation patterns. Some numerical results were demonstrated to verify the feasibility of the control method. Some comparisons were also illustrated to support the superiority and effectiveness of the presented sliding mode control method

    Layered Co(OH)<sub>2</sub> Deposited Polymeric Carbon Nitrides for Photocatalytic Water Oxidation

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    Here we report a facile impregnation synthesis of layered Co­(OH)<sub>2</sub> deposited with g-C<sub>3</sub>N<sub>4</sub> while the pH value is adjusted by using ammonia solution for photocatalytic water oxidation with UV–vis and visible light illumination. This surface modification not only accelerates the interface transfer rate of charge carriers but also reduces the excessive energy barrier for O–O formation, thus leading to enhanced reaction kinetics for photocatalytic water oxidation. The optimum oxygen evolution rates (OERs) of the Co­(OH)<sub>2</sub>/g-C<sub>3</sub>N<sub>4</sub> sample reached 27.4 and 7.1 μmol h<sup>–1</sup> under UV–vis (λ >300 nm) and visible light (λ >420 nm) irradiation, which are 5.5 and 7 times faster than those for pristine g-C<sub>3</sub>N<sub>4</sub>, respectively. These results underline the possibility for the development of effective, robust, and earth-abundant WOCs for the promotion of water-splitting photocatalysis by sustainable g-C<sub>3</sub>N<sub>4</sub> polymer photocatalysts

    Aero-Engine Remaining Useful Life Estimation Based on CAE-TCN Neural Networks

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    With the rapid growth of the aviation fields, the remaining useful life (RUL) estimation of aero-engine has become the focus of the industry. Due to the shortage of existing prediction methods, life prediction is stuck in a bottleneck. Aiming at the low efficiency of traditional estimation algorithms, a more efficient neural network is proposed by using Convolutional Neural Networks (CNN) to replace Long-Short Term Memory (LSTM). Firstly, multi-sensor degenerate information fusion coding is realized with the convolutional autoencoder (CAE). Then, the temporal convolutional network (TCN) is applied to achieve efficient prediction with the obtained degradation code. It does not depend on the iteration along time, but learning the causality through a mask. Moreover, the data processing is improved to further improve the application efficiency of the algorithm. ExtraTreesClassifier is applied to recognize when the failure first develops. This step can not only assist labelling, but also realize feature filtering combined with tree model interpretation. For multiple operation conditions, new features are clustered by K-means++ to encode historical condition information. Finally, an experiment is carried out to evaluate the effectiveness on the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) datasets provided by the National Aeronautics and Space Administration (NASA). The results show that the proposed algorithm can ensure high-precision prediction and effectively improve the efficiency
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