The impact of environmental information disclosure quality on green innovation of high-polluting enterprises

With the gradual increase of social awareness of environmental protection, environmental information disclosure has become the key for enterprises to accept social supervision and fulfill their social responsibility. This study examines the high-polluting enterprises that were listed on Chinese A-shares between 2008 and 2021. The influence of environmental information disclosure quality on green innovation is examined using ordinary least squares (OLS) as a benchmark model. The results show that the improvement of environmental information disclosure quality of high-polluting enterprises can significantly improve the quantity and quality of green innovation of enterprises and are mediated by alleviating financing constraints and enhancing cash reserves. Moreover, improving the quality of environmental information disclosure of highly polluting enterprises has a more significant contribution to the quantity and quality of green patents of non-state-owned enterprises, enterprises located in central and eastern China, and large enterprises. The findings of this paper provide theoretical support for achieving a “win-win” situation of environmental protection and green innovation

STF-based diagnosis of AUV thruster faults

The diagnosis of thruster faults of autonomous underwater vehicles is studied in this paper. Based on the theory of strong tracking filter (STF), the AUV motion model and the thruster fault model are established. The STFs are designed for each thruster for the purpose of fault diagnosis. The AUV state and the fault deviation of the thruster are estimated online before the thruster faults are diagnosed based on residual analysis. The simulation experiments were conducted to verify the feasibility and effectiveness of the STF-based diagnosis of AUV thruster faults

A Model Free Adaptive Scheme for Integrated Control of Civil Aircraft Trajectory and Attitude

The adaptive trajectory and attitude control is essential for the four-dimensional (4D) trajectory operation of civil aircraft in symmetric thrust flight. In this work, an integrated trajectory and attitude control scheme is proposed based on the =multi-input multi-output (MIMO) model free adaptive control (MFAC) method. First, the full-form dynamic linearization technique is adopted to build the equivalent data model of aircraft. Also, the MIMO MFAC scheme with saturation constraint is designed to achieve an accurate tracking control for a given 4D trajectory and attitude. Besides, the performance limitations of aircraft are taken into consideration, and the MIMO MFAC scheme with hard constraints is designed. In addition, to improve the simulation efficiency, a control scheme with mixed constraints, i.e., saturation and hard constraints, is further proposed. It can be seen from the simulation results that the proposed method can perform an integrated control of the aircraft 4D trajectory and attitude without precise modeling, and the control performance is better than that of the model-based control method in terms of flight altitude and yaw angle control. The integrated data-driven control scheme proposed in this paper provides a theoretical solution for the precise operation of aircraft under 4D trajectory

Deep Learning-Enhanced Inverse Modeling of Terahertz Metasurface Based on a Convolutional Neural Network Technique

The traditional design method for terahertz metasurface biosensors is cumbersome and time-consuming, requires expertise, and often leads to significant discrepancies between expected and actual values. This paper presents a novel approach for the fast, efficient, and convenient inverse design of THz metasurface sensors, leveraging convolutional neural network techniques based on deep learning. During the model training process, the magnitude data of the scattering parameters collected from the numerical simulation of the THz metasurface served as features, paired with corresponding surface structure matrices as labels to form the training dataset. During the validation process, the thoroughly trained model precisely predicted the expected surface structure matrix of a THz metasurface. The results demonstrate that the proposed algorithm realizes time-saving, high-efficiency, and high-precision inversion methods without complicated data preprocessing and additional optimization algorithms. Therefore, deep learning algorithms offer a novel approach for swiftly designing and optimizing THz metasurface sensors in biomedical detection, bypassing the complex and specialized design process of electromagnetic devices, and promising extensive prospects for their application in the biomedical field

Comparing Statistical and Semi-Distributed Rainfall–Runoff Models for a Large Subtropical Watershed: A Case Study of Jiulong River Catchment, China

In this contribution, the authors present their preliminary investigations into modeling the rainfall⁻runoff generation relation in a large subtropical catchment (Jiulong River catchment) on the southeast coast of China. Previous studies have mostly focused on modeling the streamflow and water quality of its small rural subcatchments. However, daily runoff on the scale of the whole catchment has not been modeled before, and hourly runoff data are desirable for some oceanographic applications. Three methods are proposed for modeling streamflow using rainfall outputted by the Weather Research Forecast (WRF) model, calculated potential evaporation (PET), and land cover type: (i) a ridge regression model; (ii) NPRED-KNN: a nonparametric k-nearest neighbor model (KNN) employing a parameter selection method (NPRED) based on partial information coefficient; (iii) the Hydrological Simulation Program-Fortran (HSPF) model with an hourly time step. Results show that the NPRED-KNN approach is the most unsuitable method of those tested. The HSPF model was manually calibrated, and ridge regression performs no worse than HSPF based on daily verification, whilst HSPF can produce realist daily flow time series, of which ridge regression is incapable. The HSPF model seems less prone to systematic underprediction when replicating monthly-annual water balance, and it successfully replicates the baseflow index (the flow intensity) of the Jiulong River catchment system

Numerical Simulation Research on Radial Force of Centrifugal Pump with Guide Vanes

To reveal the internal unsteady flow state of the guide vane centrifugal pump, in this paper, the standard SST k‐ω turbulent flow model is used for unsteady numerical simulation of the centrifugal pump. The characteristics of the flow field inside the centrifugal pump are analyzed, the resultant force and vector distribution of the radial force of the guide vane and impeller of the centrifugal pump under different flow rates are obtained, which were verified by experiments. The results show that the main reason of radial force of the impeller is the pressure asymmetry in each flow passage. The radial force will show periodic fluctuations due to the rotor-stator interference between the impeller and the guide vanes under different flow rates. The radial force on the impeller decreases gradually with the increase of the flow, the distribution is hexagonal or hexagonal shape, and the number of impeller blades is the same. The results can provide reference for the design of impeller and guide vane of centrifugal pump

Microstructure Evolution and Mechanical Properties of 20%SiCp/Al Joint Prepared via Laser Welding

SiC particles-reinforced Al matrix composites (SiCp/AMCs) have been widely used in the aerospace structural components. In this work, 20 vol% SiCp/2A14 joint was fabricated by laser welding technology. The effects of different laser power/welding velocity on the 20 vol% SiCp/2A14 joint forming, microstructure evolution and mechanical properties were studied in detail. The results showed that, under the same heat input, the high power/high welding velocity was beneficial to reduce the porosity of SiCp/2A14 joint and inhibited the formation of brittle phase of Al4C3. At 8 kW-133 mm/s welding parameters, the maximum tensile strength of the SiCp/2A14 joint reached 199 MPa, which is ~64% higher than that of the SiCp/2A14 joint prepared at 4 kW-66 mm/s welding parameters. By analyzing the fracture morphology and SEM image of SiCp/2A14 joint section, it is was found that the porosity of weld and Al4C3 brittle phase were the important factors limiting the strength of SiCp/2A14 joint. This work provides a reference for the process window design of laser welding SiCp/2A14 composites

Effect of pulverising process on the luminescence properties of Sr

Sr2MgSi2O7:Eu2+, Dy3+ was selected to study the effect of pulverising process on the luminescence properties. The samples were characterised by X-ray diffraction (XRD), photoluminescence (PL), decay curves, thermoluminescence spectra (TL), scanning electron microscopy (SEM) and energy dispersive spectrometers (EDS). Results show that the pulverising process has no obvious effect on the position of the peak in the excitation and emission spectra, and the long afterglow performance of Sr2MgSi2O7:Eu2+, Dy3+ phosphor is impaired gradually with the increase of specific surface area. When the specific surface area is below 3500 cm2/g, both the decay constant of the afterglow and the depth of trap increase simultaneously. Once the specific surface area is more than 3500 cm2/g, however, both of them remain almost constant. Further, the decrease of the density of traps shows a linear relationship with the specific surface area. In addition, the agglomeration of Dy3+ is clearly observed in the Sr2MgSi2O7:Eu2+, Dy3+ samples after smashing, and the element O tends to exist in the grain rather than on the grain surface

Influence of Impeller Gap Drainage Width on the Performance of Low Specific Speed Centrifugal Pump

The centrifugal pump is one of the most important pieces of energy-consuming equipment in various hydraulic engineering applications. This paper takes a low specific speed centrifugal pump as the research object. Based on the research method combining numerical calculation and experimental verification, the influence of the gap drainage structure on the performance of the low specific speed centrifugal pump and its internal flow field distribution were investigated. The flow field inside the low specific speed centrifugal pump impeller under different gap widths was studied. The comparison between the numerical calculation results and the experimental results confirms that the numerical calculations in this paper have high accuracy. It was found that the gap drainage will reduce the head of the low specific speed centrifugal pump, but increase its hydraulic efficiency. Using a smaller gap width could greatly improve the performance of the low specific speed centrifugal pump on the basis of a slight reduction in the head. The high-pressure leakage flow at the gap flows from the blade pressure surface to the suction surface can effectively suppress the low-pressure area at the impeller inlet. The flow rate of the high-pressure leakage flow increases with the gap width. Excessive gap width may cause a low-pressure zone at the inlet of the previous flow passage. These results could serve as a reference for the subsequent gap design to further improve the operating stability of the low specific speed centrifugal pump

An expression recognition algorithm based on convolution neural network and RGB-D Images

Aiming at the problem of recognition effect is not stable when 2D facial expression recognition in the complex illumination and posture changes. A facial expression recognition algorithm based on RGB-D dynamic sequence analysis is proposed. The algorithm uses LBP features which are robust to illumination, and adds depth information to study the facial expression recognition. The algorithm firstly extracts 3D texture features of preprocessed RGB-D facial expression sequence, and then uses the CNN to train the dataset. At the same time, in order to verify the performance of the algorithm, a comprehensive facial expression library including 2D image, video and 3D depth information is constructed with the help of Intel RealSense technology. The experimental results show that the proposed algorithm has some advantages over other RGB-D facial expression recognition algorithms in training time and recognition rate, and has certain reference value for future research in facial expression recognition