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

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

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

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)

Application Prospect and Preliminary Exploration of GelMA in Corneal Stroma Regeneration

Corneal regeneration has become a prominent study area in recent decades. Because the corneal stroma contributes about 90% of the corneal thickness in the corneal structure, corneal stromal regeneration is critical for the treatment of cornea disease. Numerous materials, including deacetylated chitosan, hydrophilic gel, collagen, gelatin methacrylate (GelMA), serine protein, glycerol sebacate, and decellularized extracellular matrix, have been explored for keratocytes regeneration. GelMA is one of the most prominent materials, which is becoming more and more popular because of its outstanding three-dimensional scaffold structure, strong mechanics, good optical transmittance, and biocompatibility. This review discussed recent research on corneal stroma regeneration materials and related GelMA

A Form-Finding Method for Branching Structures Based on Dynamic Relaxation

Branching structure is often used as a supporting structure of the grid shell due to its geometrical and force-transferring features, and the rationality of its shape is very important. The “physical” and “numerical” hanging models can be used for the joint form-finding of the branching structure and free-form grid shell. However, slack elements may exist in the equilibrium model which corresponds to the inefficient members in the form-found branching structure. To solve this problem, a form-finding method of branching structure based on dynamic relaxation is proposed in this study. The proposed method clusters the elements of the branching model and equalizes the axial forces of the elements in the same cluster, in other words, there are no slack elements in the equilibrium branching model. This method overcomes the defect that the equilibrium branching model may have slack elements and needs many manual adjustments during the procedure of determining the rational shape of a branching structure, and effectively prevents the inefficient members existing in the form-found structure. Numerical examples are provided to demonstrate the characteristics of the proposed method and its effectiveness is verified as well

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

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

Quantifying the Spatio-Temporal Variations and Impacts of Factors on Vegetation Water Use Efficiency Using STL Decomposition and Geodetector Method

Water use efficiency of vegetation (WUE), the ratio of carbon gain to water loss, is a valid indicator to describe the photosynthetic carbon–water coupling relationship. Understanding how and why WUE changes are essential for regional ecological conservation. However, the impacts of various factors and their interactions on the spatial variation of WUE remain uncertain in the arid land of Northwest China. Here, we selected the Qilian Mountains (QM) and Hexi Corridor (HC) as the study areas. Supported by the Google Earth Engine, we explored the spatio-temporal variations of WUE in QM and HC for 2002–2021 using STL decomposition (a seasonal-trend decomposition procedure), trend analysis, and the Hurst index. Then, the Geodetector method was applied to quantify impacts of geographical and eco-meteorological factors on the spatial variation of WUE. The WUE in HC was higher than that in QM. Interestingly, the opposite longitude zonality characteristics are shown in the QM and HC. In QM, the WUE showed an upward trend with longitude increasing, while a downward trend with longitude increasing in the oases of HC. The WUE of cropland was the highest (1.15 ± 0.35 gC kg−1 H2O), and that of alpine vegetation was the lowest (0.2 ± 0.15 gC kg−1 H2O). WUE showed a decreasing trend across the study area, almost certainly due to a drop from May to July during 2002–2021. The air temperature is the dominant factor influencing the spatial variation of WUE. In addition, the interaction of any two factors is greater than the independent influence of either factor alone. The Geodetector method proved to be effective for quantifying the impact of complex multi-factors on the spatial variation of WUE. This study provides a new technical scheme to analyze the spatio-temporal pattern and quantify the impact of multi-factors on the spatial variation of WUE. These findings aid in understanding underlying mechanisms of WUE variation and thereby will be beneficial for clarifying the response of vegetation to climate change

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

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)₂ Deposited Polymeric Carbon Nitrides for Photocatalytic Water Oxidation

Here we report a facile impregnation synthesis of layered Co­(OH)₂ deposited with g-C₃N₄ 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)₂/g-C₃N₄ sample reached 27.4 and 7.1 μmol h^–1 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-C₃N₄, 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-C₃N₄ polymer photocatalysts