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In this paper, the Artificial Neural Network (ANN) was utilized to predict the peak discharge of dam failures, which was based on the combined Genetic Algorithm (GA) and Back Propagation (BP) neural network. The dataset comprises 40 samples from self-conducted experiments and available literature. To compare the efficiency of the suggested approach, three evaluation metrics, including the coefficient of determination (R2), the root mean square error (RMSE) and the mean absolute error (MAE), were analyzed for both the BP neural network and the GA-BP neural network. The findings suggest that (1) The prediction accuracy of the GA-BP was better than that of the BP; and (2) Compared to BP, GA-BP demonstrated a 9.07% average improvement in R2, a 57.36% average reduction in MAE, and a 57.53% average reduction in RMSE. In addition, the results of GA-BP and semi-empirical formulas were compared and the effect of three parameters on the peak discharge was analyzed. The results showed that the GA-BP model could effectively predict the peak discharge of dam failures. [ABSTRACT FROM AUTHOR]

The need to manufacture components out of copper is significantly increasing, particularly in the solar technology, semiconductor, and electric vehicle sectors. In the past few decades, infrared laser (IR) and green laser (GL) have been the primary technologies used to address this demand, especially for small or thin components. However, with the increased demand for energy saving, alternative joint techniques such as blue diode laser (BDL) are being actively explored. In this paper, bead-on-plate welding experiments on 0.2 mm thick pure copper samples employing a BDL are presented. Two sets of parameters were carefully selected in this investigation, namely Cu-1: Power (P) = 200 W; Speed (s) = 1 mm/s; and angle = 0°, and Cu-2: P = 200 W; s = 5 mm/s; and angle = 10°. The results from both sets of parameters produced defect-free full penetration welds. Hardness test results indicated relatively softer weld zones compared with the base metal. Tensile test samples fractured in the weld zones. Overall, the samples welded with Cu-1 parameters showed better mechanical properties, such as strength and elongation, than those welded with the Cu-2 parameters. The tensile strength and elongation obtained from Cu-1 were marginally lower than those of the unwelded pure copper. The outcomes from this research provide an alternative welding technique that is able to produce reliable, strong, and precise joints, particularly for small and thin components, which can be very challenging to produce. [ABSTRACT FROM AUTHOR]

The use of static solution-assisted laser drilling can effectively improve hole roundness, decrease taper angle, and reduce recast layer thickness and hole wall slag adhesion. However, the enormous energy of the laser will evaporate the solution to form a suspension droplet and reduce the quality and efficiency of laser drilling. To deal with this defect, the mist-blowing method was used to reduce the influence of droplets on the taper angle and recast layer. In this work, the effect of wind speed on drilling quality was examined, and laser drilling in air, water, and NaCl solution was carried out to analyse the effect of solution composition on hole wall morphology. The results showed that a speed fan with a proper wind speed that disperses the droplets formed in the processing area can significantly reduce the refraction and scattering of the laser, and the taper angle and roundness of the drilling hole were also reduced by 15.6% and improved by 2.4%, respectively, under the wind speed of 2 m/s. The hole wall morphology showed a thicker recast layer and cracking in air, while it was thinner in water and there was little or no layer in the NaCl solution in the same current. When drilling in NaCl, the taper angle and roundness of the drilling hole were reduced by 4.13% and improved by 2.11%, respectively, compared to water. Due to the mechanical effect of the laser in the NaCl solution, the impact force on the material was much greater than that in water. The solution cavitation effect, generated by the absorption of laser energy, caused an explosive impact on the molten material adhered to the surface of the hole wall. Above all, drilling in the NaCl solution with a current of 200 A and a wind speed of 2 m/s was the optimal condition for obtaining the best processing quality. [ABSTRACT FROM AUTHOR]

We applied the time-series clustering method to analyze the trajectory data of rummy-nose tetra (Hemigrammus rhodostomus), with a particular focus on their spontaneous paired turning behavior. Firstly, an automated U-turn maneuver identification method was proposed to extract turning behaviors from the open trajectory data of two fish swimming in an annular tank. We revealed two distinct ways of pairwise U-turn swimming, named dominated turn and non-dominated turn. Upon comparison, the dominated turn is smoother and more efficient, with a fixed leader–follower relationship, i.e., the leader dominates the turning process. Because these two distinct ways corresponded to different patterns of turning feature parameters over time, we incorporated the Toeplitz inverse covariance-based clustering (TICC) method to gain deeper insights into this process. Pairwise turning behavior was decomposed into some elemental state compositions. Specifically, we found that the main influencing factor for a spontaneous U-turn is collision avoidance with the wall. In dominated turn, when inter-individual distances were appropriate, fish adjusted their positions and movement directions to achieve turning. Conversely, in closely spaced non-dominated turn, various factors such as changes in distance, velocity, and movement direction resulted in more complex behaviors. The purpose of our study is to integrate common location-based analysis methods with time-series clustering methods to analyze biological behavioral data. The study provides valuable insights into the U-turn behavior, motion characteristics, and decision factors of rummy-nose tetra during pairwise swimming. Additionally, the study extends the analysis of fish interaction features through the application of time-series clustering methods, offering a fresh perspective for the analysis of biological collective data. [ABSTRACT FROM AUTHOR]

Light pollution is one of the environmental pollution problems facing the world. The research on the measurement standard of light pollution is not perfect at present. In this paper, we proposed a Markov random field model to determine the light pollution risk level of a site. Firstly, the specific data of 12 indicators of 5 typical cities were collected, and 10-factor indicators were screened using the R-type clustering algorithm. Then, the entropy weight method was used to determine the weight, and the light pollution measurement method of the Markov random field was established. The model was tested by five different data sets, and the test results show that the model is very effective. Three kinds of potential effects were proposed, and the relationship between the factor index and potential effects was established by using the partial least square method. Three possible intervention strategies for solving the problem of light pollution are pointed out: road lighting system planning, increasing vegetation coverage, and building system planning. Finally, a simulated annealing algorithm was used to determine the best intervention strategy, concluding that using strategy 1 in urban neighborhood 2 was the most effective measure, reducing the risk level of light pollution by 17.2%. [ABSTRACT FROM AUTHOR]

Physical urban boundaries (PUBs) are basic geographic information data for defining the spatial extent of urban landscapes with non-agricultural land and non-agricultural economic activities. Accurately mapping PUBs provides a spatiotemporal database for urban dynamic monitoring, territorial spatial planning, and ecological environment protection. However, traditional extraction methods often have problems, such as subjective parameter settings and inconsistent cartographic scales, making it difficult to identify PUBs objectively and accurately. To address these problems, we proposed a self-supervised learning approach for PUB extraction. First, we used nighttime light and OpenStreetMap road data to map the initial urban boundary for data preparation. Then, we designed a pretext task of self-supervised learning based on an unsupervised mutation detection algorithm to automatically mine supervised information in unlabeled data, which can avoid subjective human interference. Finally, a downstream task was designed as a supervised learning task in Google Earth Engine to classify urban and non-urban areas using impervious surface density and nighttime light data, which can solve the scale inconsistency problem. Based on the proposed method, we produced a 30 m resolution China PUB dataset containing six years (i.e., 1995, 2000, 2005, 2010, 2015, and 2020). Our PUBs show good agreement with existing products and accurately describe the spatial extent of urban areas, effectively distinguishing urban and non-urban areas. Moreover, we found that the gap between the national per capita GDP and the urban per capita GDP is gradually decreasing, but regional coordinated development and intensive development still need to be strengthened. [ABSTRACT FROM AUTHOR]

The entanglement in multipartite quantum system is hard to characterize and quantify, although it has been intensively studied in bipartite systems. The monogamy of entanglement, as a special property of multipartite systems, shows the distribution of entanglement in the system. In this paper, we investigate the monogamy relations for multi-qubit systems. By using two entangled measures, namely the concurrence C and the negativity N c , we establish tighter monogamy inequalities for their α -th power than those in all the existing ones. We also illustrate the tightness of our results for some classes of quantum states. [ABSTRACT FROM AUTHOR]

Drainage coefficient has an important influence on the determination of the scale of drainage engineering and agricultural production. This paper calculated the drainage coefficient based on the calculation results of theoretical runoff using the empirical formula (QE) and the average draining method (QA), and discussed the drainage duration (TE) corresponding to the empirical formula and the area range (FA) corresponding to the average draining formula. The results showed that the observed runoff was less than the theoretical runoff. The design flow of the Wanyan River pumping station does not meet the drainage demand of the 5-year rainfall return period. For the 1-day rainfall with 3-year return period and 3-day rainfall, QE was higher than QA, and the design drainage duration was higher than TE, so it was safer to calculate the drainage coefficient using the empirical formula in the drainage engineering design. For 1-day rainfall greater than the 3-year return period, QA was higher than QE, and the design drainage duration was less than TE, and the results of the average draining formula were safer in the drainage engineering design. FA increased with the increase in rainfall duration and decreased with the increase in return period. When the rainfall duration and the drainage duration were long, the calculation results of the average draining formula were much smaller. [ABSTRACT FROM AUTHOR]

Global navigation satellite system (GNSS) has been widely used in many deformation monitoring fields in recent years and can achieve centimeter-level or even sub-centimeter-level real-time monitoring accuracy through the carrier phase double-differenced technique. However, this technique cannot eliminate or weaken multipath errors, which become the main error source for GNSS deformation monitoring. Therefore, extracting deformation information from coordinate series mixed with multipath errors has become a key issue for further improving the accuracy of GNSS deformation monitoring. In this paper, we propose an approach to overcome this issue called empirical wavelet transform-independent component analysis with reference (EWT-ICA-R). The specific process is as follows. First, EWT is employed to model the multipath errors from a priori GNSS coordinate series, and the model is input to ICA-R as a reference signal. Then, the GNSS deformation monitoring series mixed with multipath errors and deformation information is decomposed into sub-series of different scales using EWT, and these sub-series are input to ICA-R as multi-channel signals. Finally, ICA-R is used to calculate the input signals together to obtain the multipath errors in the GNSS deformation monitoring series and then subtract the multipath errors from the GNSS deformation monitoring series to obtain accurate deformation information. Experiments show the following: (1) For the vibration deformation experiments, the correlation coefficients between the deformation information extracted by the proposed method and the real values reached 0.981, 0.981, and 0.885 in the E, N, and U directions, respectively, and the corresponding root mean square errors decrease to 0.694 mm, 0.694 mm, 1.852 mm, respectively. (2) For the slow-deformation experiment, the correlation coefficients in the three directions were all higher than 0.98, and the corresponding root mean square errors decrease to 1.345 mm, 1.546 mm, and 3.866 mm, respectively. The experiments verified the feasibility of the proposed method to accurately extract deformation information, which makes it possible to obtain sub-millimeter GNSS deformation information and provide effective technical support for deformation monitoring in related fields. [ABSTRACT FROM AUTHOR]

Earthquake disaster assessment is one of the most critical aspects in reducing earthquake disaster losses. However, traditional seismic intensity assessment methods are not effective in disaster-stricken areas with insufficient observation data. Social media data contain a large amount of disaster information with the advantages of timeliness and multiple temporal-spatial scales, opening up a new channel for seismic intensity assessment. Based on the earthquake disaster information on the microblog platform obtained by the network technique, a multi-model coupled seismic intensity assessment method is proposed, which is based on the BERT-TextCNN model, constrained by the seismaesthesia intensity attenuation model, and supplemented by the method of ellipse-fitting inverse distance interpolation. Taking four earthquakes in Sichuan Province as examples, the earthquake intensity was evaluated in the affected areas from the perspective of seismaesthesia. The results show that (1) the microblog data contain a large amount of earthquake information, which can help identify the approximate scope of the disaster area; (2) the influences of the subjectivity and uneven spatial distribution of microblog data on the seismic intensity assessment can be reduced by using the seismaesthesia intensity attenuation model and the method of ellipse-fitting inverse distance interpolation; and (3) the accuracy of seismic intensity assessment based on the coupled model is 70.81%. Thus, the model has higher accuracy and universality. It can be used to assess seismic intensity in multiple regions and assist in the formulation of earthquake relief plans. [ABSTRACT FROM AUTHOR]

In this research, we propose a novel wheel-legged mobile robot to address the problems of insufficient obstacle-crossing performance and poor motion flexibility of mobile robots in non-structural environments. Firstly, we designed the transformable wheel mechanism and tail adaptive mechanism. Secondly, the kinematic model of the robot is established and solved by analyzing the whole motion and wheel-legged switching motion for the operation requirements under different road conditions. By synthesizing the constraint relationships among the modules and analyzing the robot's obstacle-crossing abilities, we systematically established the mechanical model of the robot when it encounters obstacles. Thirdly, we studied the stability of the robot based on the stable cone method in the case of slope and unilateral transformation wheel deployment and achieved the tipping condition in the critical state. Finally, we used ADAMS software to simulate and analyze the driving process of the robot in various types of terrain and obstacles in order to verify that it has superior performance through obstacles and motion flexibility. The analysis shows that the robot can passively adapt to various complex and variable obstacle-filled terrains with obstacle heights which are much higher than its center of gravity range. The results of the study can provide a reference for the structural optimization and the obstacle-crossing performance improvement of mobile robots. [ABSTRACT FROM AUTHOR]

Leaching characteristics of filter materials of the improved subsurface drainage are very important for nitrogen and phosphorus loss. In this paper, the leaching characteristic of soil, sand, straw, and zeolite under different layouts were studied by HYDRUS-2D simulation based on calibration and validation according to laboratory data. Two scenarios were considered, including different soil and filter layouts, and mixed filter materials of straw and sand or zeolite. The results indicate that zeolite showed good adsorption characteristics of both ammonia nitrogen and phosphorus, while the straw's adsorption characteristics were very different between ammonia nitrogen and phosphorus. Nitrogen and phosphorus concentrations of the outflow were mostly determined by the materials around the outlet. Compared with the cases of no lower soil, when the lower soil depth was 5 cm, the ammonia nitrogen concentrations under sand and straw decreased 54.5% and 96.3%, and the corresponding decreased phosphorus concentrations were 84.1% and 96.2%. In views of mixed filter with straw and the different layouts, that the ratio of straw and sand was 1:1, or the ratio of straw and zeolite was 2:1; at the same time, sand and zeolite should be set around the outlet, and may be better for ammonia nitrogen and total phosphorus concentrations reduction. [ABSTRACT FROM AUTHOR]

The risk assessment of water environments provides important references for water environment risk management. In this paper, the water environment risk of the upper rivers of the Baiyangdian Lake is assessed, considering both cumulative and sudden environmental risk. For the cumulative environmental risk assessment of the rivers, the characteristics of pollution transmissibility and accumulation in rivers was considered firstly. Furthermore, suggestions for the control of water environment pollution in the Baiyangdian Basin are given. The results indicate that the cumulative water environment risks of the Xiaoyi River—Dingzhou County, Xiaoyi River—Anguo County, Xiaoyi River—Boye County, and Xiaoyi River—Li County are high. The amount of fertilizer applied per unit of cultivated area, water quality, rate of water quality above the standard in water function zoning, and the ratio of environmental investment to gross domestic product (GDP) are important factors influencing the cumulative water environment risk. For sudden water environment assessments, the Xiaoyi River—Boye County is high. In the future, reducing the intensity of fertilizer application, strengthening the water quality control of the rivers, as well as upgrading the industry, should be carried out to protect the water environment in the Baiyangdian Basin. [ABSTRACT FROM AUTHOR]

In the 5G intelligent edge scenario, more and more accelerator-based single-board computers (SBCs) with low power consumption and high performance are being used as edge devices to run the inferencing part of the artificial intelligence (AI) model to deploy intelligent applications. In this paper, we investigate the inference workflow and performance of the You Only Look Once (YOLO) network, which is the most popular object detection model, in three different accelerator-based SBCs, which are NVIDIA Jetson Nano, NVIDIA Jetson Xavier NX and Raspberry Pi 4B (RPi) with Intel Neural Compute Stick2 (NCS2). Different video contents with different input resize windows are detected and benchmarked by using four different versions of the YOLO model across the above three SBCs. By comparing the inference performance of the three SBCs, the performance of RPi + NCS2 is more friendly to lightweight models. For example, the FPS of detected videos from RPi + NCS2 running YOLOv3-tiny is 7.6 times higher than that of YOLOv3. However, in terms of detection accuracy, we found that in the process of realizing edge intelligence, how to better adapt a AI model to run on RPi + NCS2 is much more complex than the process of Jetson devices. The analysis results indicate that Jetson Nano is a trade-off SBCs in terms of performance and cost; it achieves up to 15 FPSs of detected videos when running YOLOv4-tiny, and this result can be further increased by using TensorRT. [ABSTRACT FROM AUTHOR]

Accurate load forecasting guarantees the stable and economic operation of power systems. With the increasing integration of distributed generations and electrical vehicles, the variability and randomness characteristics of individual loads and the distributed generation has increased the complexity of power loads in power systems. Hence, accurate and robust load forecasting results are becoming increasingly important in modern power systems. The paper presents a multi-layer stacked bidirectional long short-term memory (LSTM)-based short-term load forecasting framework; the method includes neural network architecture, model training, and bootstrapping. In the proposed method, reverse computing is combined with forward computing, and a feedback calculation mechanism is designed to solve the coupling of before and after time-series information of the power load. In order to improve the convergence of the algorithm, deep learning training is introduced to mine the correlation between historical loads, and the multi-layer stacked style of the network is established to manage the power load information. Finally, actual data are applied to test the proposed method, and a comparison of the results of the proposed method with different methods shows that the proposed method can extract dynamic features from the data as well as make accurate predictions, and the availability of the proposed method is verified with real operational data. [ABSTRACT FROM AUTHOR]

Featured Application: The investigation in this article puts forward an innovative and rapid way to design a subsonic tandem blade and shows a good application prospect for a subsonic/transonic axial compressor with tandem blades. Tandem blade technology has been developed for years due to its capacity to bear higher aerodynamics than conventional configurations. Even so, there is still the tough problem of how to design tandem blades effectively and further improve blade performance. This paper tries to further understand the flow characteristics of tandem blades in order to present a new method of designing them under subsonic inflow conditions. Firstly, efforts were made to reveal the aerodynamic interaction between the forward blade (FB) and the aft blade (AB). Secondly, considering this aerodynamic interaction, the design principles and the camber line modification method were put forward, with which typical controlled diffusion airfoil (CD airfoil) isentropic Mach number distributions can be achieved for both FB and AB. Lastly, the optimizations were conducted on a 2D tandem blade and a transonic compressor with a tandem blade, respectively. The computation fluid dynamic (CFD) results show that the optimized tandem blade achieves a significant improvement for both 2D blade performance and transonic compressor characteristics at low speeds. [ABSTRACT FROM AUTHOR]

Featured Application: The results in this article show good application prospects for a transonic axial compressor/fan with a tandem blade. In addition, the results in this paper show an innovative way to improve the transonic tandem blade performance. Tandem blade technology has become an effective method to break the load limit of conventional aerodynamic configurations. To expand the application range of tandem blades, the supersonic tandem blade flow characteristic was studied and an optimal design was conducted by using a computational fluid dynamics (CFD) solver, with an inflow Mach number of 1.2. The main conclusions follow: (1) the tandem blade loss is difficult to control because of the complicated flow structures with supersonic inflow; (2) the forward blade loss dominates the tandem blade overall loss in the whole operating conditions; and (3) the tandem blade profile was optimized by considering the aerodynamic interaction between forward and aft blade. The numerical simulation results show that the total pressure loss declines by 20% at the design point, and the incidence range increases by about 0.5°. [ABSTRACT FROM AUTHOR]

Equivalent circuits of piezoelectric structures such as bimorphs and unimorphs conventionally focus on the bending vibration modes. However, the longitudinal vibration modes are rarely considered even though they also play a remarkable role in piezoelectric devices. Losses, especially elastic loss in the metal substrate, are also generally neglected, which leads to discrepancies compared with experiments. In this paper, a novel equivalent circuit with four kinds of losses is proposed for a beamlike piezoelectric structure under the longitudinal vibration mode. This structure consists of a slender beam as the metal substrate, and a piezoelectric patch which covers a partial length of the beam. In this approach, first, complex numbers are used to deal with four kinds of losses--elastic loss in the metal substrate, and piezoelectric, dielectric, and elastic losses in the piezoelectric patch. Next in this approach, based on Mason's model, a new equivalent circuit is developed. Using MATLAB, impedance curves of this structure are simulated by the equivalent circuit method. Experiments are conducted and good agreements are revealed between experiments and equivalent circuit results. It is indicated that the introduction of four losses in an equivalent circuit can increase the result accuracy considerably. [ABSTRACT FROM AUTHOR]

Vegetation is an important part of terrestrial ecosystems. Although vegetation dynamics have explicit spatial and temporal dimensions, the study of the temporal process is in its infancy. Evaluation of temporal scaling behavior could provide a unique perspective for exploring the temporal nature of vegetation dynamics. In this study, the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) was used to reflect vegetation dynamics, and the temporal scaling behavior of the NDVI in China was determined via detrended fluctuation analysis (DFA). Our main objectives were to reveal the temporal scaling behavior of NDVI time series and to understand variation among vegetation types. First, DFA revealed similar exponents, which ranged from 0.6 to 0.9, for all selected pixels, implying that a long-range correlation was generally present in the NDVI time series at the individual pixel scale. We then extended the analysis to all of China and found that 99.30% of the pixel exponents ranged from 0.5 to 1. These results suggest that the NDVI time series displays strong long-range correlation throughout most of China; however, the exponents exhibited regional variability. To explain these differences, we further analyzed the exponents for 12 vegetation types based on a vegetation map of China. All of the vegetation types exhibited well-defined long-range correlation, with exponents ranging from 0.7189 to 0.8436. For all vegetation types, the maximum and average value and standard deviation of the exponents decreased with increasing annual maximum NDVI values, suggesting that low vegetation density is much more sensitive to external factors. These findings may be useful for understanding vegetation dynamics as a complex, temporally varying phenomenon. [ABSTRACT FROM AUTHOR]

The partial discharge (PD) process in liquid dielectrics is influenced by several factors. Although the PD current contains the information representing the discharge process during the PD event, it is difficult to determine the detailed dynamics of what is happening in the bulk of the liquid. In this paper, a microscopic model describing the dynamics of the charge carriers is implemented. The model consists of drift-diffusion equations of electrons, positive and negative ions coupled with Poisson's equation. The stochastic feature of PD events is included in the equation. First the model is validated through comparison between the calculated PD current and experimental data. Then experiments are conducted to study the effects of the amplitude of the applied voltage, gap distance and electrode type on the PD process. The PD currents under each condition are recorded. Simulations based on the model have been conducted to analyze the dynamics of the PD events under each condition, and thus explain the mechanism of how these factors influence the PD events. The space charge generated in the PD process is revealed as the main reason affecting the microscopic process of the PD events. [ABSTRACT FROM AUTHOR]

To investigate the microphysics mechanism and the factors that influence arc development along a polluted surface, the arc was considered as a plasma fluid. Based on the image method and the collision ionization theory, the electric field of the arc needed to maintain movement with different degrees of pollution was calculated. According to the force of the charged particle in an arc plasma stressed under an electric field, a calculation model of arc velocity, which is dependent on the electric field of the arc head that incorporated the effects of airflow around the electrode and air resistance is presented. An experiment was carried out to measure the arc velocity, which was then compared with the calculated value. The results of the experiment indicated that the lighter the pollution is, the larger the electric field of the arc head and arc velocity is; when the pollution is heavy, the effect of thermal buoyancy that hinders arc movement increases, which greatly reduces the arc velocity. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to establish a signal decomposition system aiming at mixed over-voltages in power systems. In an electric power system, over-voltage presents a great threat for the system safety. Analysis and identification of over-voltages is helpful to improve the stability and safety of power systems. Through statistical analysis of a collection of field over-voltage records, it was found that a kind of complicated signals created by mixing of multiple different over-voltages is difficult to identify correctly with current classification algorithms. In order to improve the classification and identification accuracy of over-voltages, a mixed over-voltage decomposition system based on the atomic decomposition and a damped sinusoid atom dictionary has been established. This decomposition system is optimized by using particle swarm optimization and the fast Fourier transform. Aiming at possible fault decomposition results during decomposition of the over-voltage signal, a double-atom decomposition algorithm is proposed in this paper. By taking three typical mixed over-voltages as examples, the validity of the algorithm is demonstrated. [ABSTRACT FROM AUTHOR]

This paper proposes a simple and effective method for classification of fundamental ferroresonance, single phase-to-ground and wire breakage over-voltages. In isolated neutral networks, power frequency over-voltages due to ferroresonance, single phase-to-ground and wire breakage may exist for a long time, and have very highly similar voltage features. If the improper suppression operation is applied due to incorrect identification, the accident is likely to worsen further. In this paper, the voltage and current features of these faults are analyzed, and a new effective classification criterion for fundamental ferroresonance and single phase-to-ground based on zero sequence current is proposed. A comprehensive identification method based on voltage, current and zero sequence current features is proposed, which is feasible and promising for real applications. [ABSTRACT FROM AUTHOR]

This paper proposes a complete and effective smart over-voltage monitoring and identification system. In recent years, smart grids are of the greatest interest in power system research. One of the main features of smart grid is their self-healing, which can continuously carry out online self-evaluation, discover existing faults, and correct them immediately. The over-voltage smart monitoring-identification-suppression systems play a key role in the construction of self-healing grids. In this paper, eight kinds of common over-voltage are discussed and analyzed. The S-transform algorithm is used to extract features of over-voltage. Aiming at the main features of each kind of over-voltage, six different characteristic quantities are proposed. A well designed fuzzy expert system and a support vector machine are employed as the classifiers to build a two-step identification model. The accuracy of the identification system is verified by field records. Results show that this system is feasible and promising for real applications. [ABSTRACT FROM AUTHOR]

In this paper, we proposed and experimentally demonstrated an opto-mechatronics system to detect the micro-deformation of tracks caused by running trains. The fiber Bragg grating (FBG) array acting as sensing elements has a low peak reflectivity of around −40 dB. The center wavelengths were designed to alternate between 1551 nm and 1553 nm at 25 °C. Based on dual-wavelength, wavelength-division multiplexing (WDM)/time-division multiplexing (TDM) hybrid networking, we adopted optical time-domain reflectometry (OTDR) technology and a wavelength-scanning interrogation method to achieve FBG array signal demodulation. The field experimental results showed that the average wavelength shift of the FBG array caused by the passage of the lightest rail vehicle was −225 pm. Characteristics of the train-track system, such as track occupancy, train length, number of wheels, train speed, direction, and loading can be accurately obtained in real time. This opto-mechatronics system can meet the requirements of 600 mm spatial resolution, long distance, and large capacity for monitoring the train-track system. This method exhibits great potential for applications in large-scale train-track monitoring, which is meaningful for the safe operation of rail transport. [ABSTRACT FROM AUTHOR]

Farmland in southern China is prone to flooding and waterlogging alternation after short-term heavy rainfall. Single drainage form cannot meet the requirements of the farmland flooding and waterlogging removal. Drainage measures and layout forms should be explored to alleviate flooding and waterlogging threat and improve crop yield. So, based on an indoor sand tank experiment, this paper presents a combined drainage form: conventional subsurface drainage as an auxiliary drainage measure and is alternatively combined with open ditch (OD), filter drainage (FD), conventional (CD) and improved subsurface drainage (ID), respectively, under equal and unequal drain depth. The performance of different combined drainage forms and the effect of auxiliary drainage measures are discussed for stable ponding and receding water. During the experiment, two factors—drainage measure and drain depth—are considered. The results indicate that compared with the conventional subsurface drainage alone, the flow rates of the open-ditch, thin-improved, and thick-improved subsurface drainage combined with conventional subsurface drainage can be increased by 22.4–32.3%, 10.6–16.2%, and 29.8–32%, respectively, under equal drain depth in stable ponding water. Among the four combined drainage forms, the flow rate of shallow–deep combination is 8.1–17.1% higher than that of the shallow–shallow combination. Compared with a single drainage form, the flow rates of the combined drainage have the same change characteristics over time. Additionally, the use of auxiliary, conventional, subsurface drainage can improve the flooding and waterlogging removal efficiency in farmland. For the combined drainage forms, the contribution degree of the open-ditch and thin-improved subsurface drainage is 51.3–56.7%, while the thick-improved subsurface drainage is approximately 61.0%, under equal drain depth conditions in the flooding removal process. Moreover, open-ditch and thick-improved subsurface drainage combined with conventional subsurface drainage have significant advantages in flooding and waterlogging removal, which were 11.5–38.1% and 37.1–48.6% faster than conventional subsurface drainage in flooding removal time, 14.3–157.1% and 14.3–44.4% faster than conventional subsurface drainage in the waterlogging removal time. The synergistic application of shallow–deep and medium–medium combinations can be carried out by exploiting the advantages of each drainage measure. The experimental flow rate observation is in good agreement with the theoretically calculated value, with a relative error of less than 5%. These research findings could provide technical support for the increased application of combined drainage forms in areas prone to flooding and waterlogging. [ABSTRACT FROM AUTHOR]

An investigation of mechanical properties of Ti6Al4V produced by additive manufacturing (AM) in the as-printed condition have been conducted and compared with wrought alloys. The AM samples were built by Selective Laser Melting (SLM) and Electron Beam Melting (EBM) in 0°, 45° and 90°—relative to horizontal direction. Similarly, the wrought samples were also cut and tested in the same directions relative to the plate rolling direction. The microstructures of the samples were significantly different on all samples. α′ martensite was observed on the SLM, acicular α on EBM and combination of both on the wrought alloy. EBM samples had higher surface roughness (Ra) compared with both SLM and wrought alloy. SLM samples were comparatively harder than wrought alloy and EBM. Tensile strength of the wrought alloy was higher in all directions except for 45°, where SLM samples showed higher strength than both EBM and wrought alloy on that direction. The ductility of the wrought alloy was consistently higher than both SLM and EBM indicated by clear necking feature on the wrought alloy samples. Dimples were observed on all fracture surfaces. [ABSTRACT FROM AUTHOR]

The BeiDou Navigation Satellite System (BDS) features a heterogeneous constellation so that it is difficult to mitigate the multipath in the coordinate-domain. Therefore, mitigating the multipath in the observation-domain becomes more important. Sidereal filtering is commonly used for multipath mitigation, which needs to calculate the orbit repeat time of each satellite. However, that poses a computational challenge and damages the integrity at the end of the multipath model. Therefore, this paper proposes a single-difference model based on the multipath hemispherical map (SD-MHM) to mitigate the BDS-2/BDS-3 multipath in a short baseline. The proposed method is converted from double-difference residuals to single-difference residuals, which is not restricted by the pivot satellite transformation. Moreover, it takes the elevation and the azimuth angles of the satellite as the independent variables of the multipath model. The SD-MHM overcomes the unequal observation time of some satellites and does not require specific hardware. The experimental results show that the SD-MHM reduces the root mean square of the positioning errors by 56.4%, 63.9%, and 67.4% in the east, north, and vertical directions; moreover, it contributes to an increase in the baseline accuracy from 1.97 to 0.84 mm. The proposed SD-MHM has significant advantages in multipath mitigation compared with the advanced sidereal filtering method. Besides, the SD-MHM also features an excellent multipath correction capability for observation data with a period of more than seven days. Therefore, the SD-MHM provides a universal strategy for BDS multipath mitigation. [ABSTRACT FROM AUTHOR]

This study uses the undesirable output and super-efficiency slacks-based measure combined with window (WIN-US-SBM) data envelopment analysis (DEA) to evaluate the environmental efficiency (EE) in 30 Chinese provinces, from 2005 to 2016, explores regional differences in the EE, and uses the dynamic spatial Durbin model (DSDM) to analyze regional differences in effects of important factors on the convergence of EE. It reveals that EE in the eastern area is higher than EE in the central and western areas, and a positive spatial autocorrelation exists in the interregional EE. The difference in provincial EE gradually narrows over time and tends to converge to its own steady-state level. Economic growth reduces EE for the central and western areas and improves efficiency for the eastern area; economic growth from surrounding areas indirectly promotes local EE for the eastern area. Foreign direct investment (FDI) promotes EE in the eastern and central areas, and FDI in the adjacent areas has a positive effect on local EE for the eastern area. Export reduces EE for all areas, and export in surrounding areas indirectly promotes local EE for the central area. Industrialization reduces EE in the western area, and industrialization in the surrounding areas increases local EE for the eastern area. Energy efficiency promotes EE for the central area, urbanization increases EE for the central area, and urbanization of the surrounding areas reduces local EE for the eastern area. [ABSTRACT FROM AUTHOR]

Agricultural drainage plays an effective role in preventing waterlogging and salinity disasters and also is the main transport pathway for agricultural non-point source pollutants into rivers and lakes. Hence, the water quality of agricultural drainage should be a point of focus. In this paper, nitrogen and phosphorus loss under improved subsurface drainage with different filter materials (gravel, layered sand-gravel, mixed sand-gravel, straw) were studied by a three-year field experiment (2016–2018) compared with the conventional subsurface drainage. The pH values, total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus and soluble reactive phosphate were considered. The results showed that the nitrogen and phosphorus concentrations of drain outflow under improved subsurface drainage with gravel filter were larger than that with layered sand-gravel filter and mixed sand-gravel filter. The improved subsurface drainages with layered sand-gravel filter and mixed sand-gravel filter had an effect on reducing the ammonia nitrogen, total phosphorus and soluble reactive phosphate concentrations of the outflow. Meanwhile, the characteristics of nitrogen and phosphorus loss under the improved subsurface drainage with straw filter were different from that with layered sand-gravel filter and mixed sand-gravel filter. For the improved subsurface drainage with layered sand-gravel filter outflow, the ammonia nitrogen, total phosphorus, and soluble reactive phosphate concentrations were about 13%–78%, 38%–63%, 40%–68% less, and total nitrogen, nitrate nitrogen concentrations were 24%–80%,18%–96% more than that under conventional subsurface drainage. Meanwhile, for the improved subsurface drainage with straw filter outflow, compared with conventional subsurface drainage outflow, the percentage changes of the total nitrogen, nitrate nitrogen, ammonia nitrogen, total phosphorus and the soluble reactive phosphate concentrations were about −76%–62%, −77%–78%, −152%–−274%, −103%–−400% and −221%–−291%, respectively. Additionally, in the outflow of all subsurface drainage patterns, there were much higher total nitrogen and nitrate nitrogen concentrations which should be focused on and the agricultural water management should be adopted. [ABSTRACT FROM AUTHOR]

A Chebyshev pseudospectral–two-step three-order boundary value coupled method is proposed and presented for handling the issue associated with complicated calculation, low precision, and poor stability in the process of transient response of transmission line. The first order differential equation in time domain is obtained via dispersing the telegraph equation in space domain by utilizing the pseudospectral method (PSM) based on Chebyshev polynomial. Then the two-step three-order boundary value method (BVM3) is presented and employed to resolve the obtained differential equation, so the numerical solution of the space discrete points can be obtained. Furthermore, the Chebyshev pseudospectral–two-step three-order boundary value coupled method (PSM-BVM3) is presented and compared with the Chebyshev pseudospectral–two-step two order boundary value coupled method (PSM-BVM2), the pseudospectral–differential quadrature method (PSM-DQM), and the pseudospectral method–trapezoid rule (PSM-TR) to validate the feasibility of the new proposed method. Theoretical analysis and numerical simulation reveal that the proposed Chebyshev PSM-BVM3 has a higher performance than the conventional method. For the proposed Chebyshev PSM-BVM3, the higher precision, efficiency, and numerical stability can be obtained and achieved only with fewer discrete points in the space domain, which is suitable for solving the transient response of transmission line. The proposed PSM-BVM3 can improve the drawback of numerical instability of the PSM and can also improve the disadvantage of the BVM as it is not easy to change the latter's timestep size. [ABSTRACT FROM AUTHOR]

Achieving cooperation to address social dilemmas has long been a global problem. This study examined, using an environment-focused step-level public-goods-dilemma game, the effect a consistent contributor (CC) has on group cooperation, as well as the mediating role moral elevation and the moderating role social value orientation (SVO) play in this process. A total of 196 students were recruited and classified as "pro-selfs" or "pro-socials" based on their SVOs; individuals with the same SVO characterization were randomly allocated to groups of four, and then randomly assigned to the CC condition or the control condition to play 15 rounds of public-goods-dilemma games. In the CC condition, additional computer-controlled players represented the CCs. The results showed that the CC groups cooperated and earned more than the control groups did. Multi-level mediation analysis confirmed that moral elevation partially mediates the CC effect. Although the CCs had a direct impact on both pro-socials and pro-selfs, multi-level moderated-mediation analysis demonstrated that CCs influenced pro-socials directly, but affected pro-selfs' decision-making indirectly, through moral elevation. This study contributes to a better understanding of sustainability of cooperation in social dilemmas by showing that consistent cooperative behaviors are contagious, and that their effects differ based on an individuals' SVO. [ABSTRACT FROM AUTHOR]

Smart grids (SGs) have been widely recognized as an enabling technology for delivering sustainable energy transitions. SGs have a positive effect on the development of the world economy and society. SG construction plays an important role in responding to global climate change and promoting the sustainable development of the world economy and society. Under such a background, this paper attempts to investigate patent collaborations of the SG field in China. Based on the application data of collaborative patents from State Intellectual Property Office (SIPO) in China, this study employs complex network theory and social network analysis (SNA) method and conducts in-depth research on the patent collaboration network of SG field in China. The trend of patent collaboration was examined, the collaboration network of SG-related patents was investigated, the network characteristics, and the network structure were also explored. The results show that the proportion of enterprises participating in patent collaboration is relatively large for SG field in China, the percentage of collaboration relationships formed by different patent applicants varies greatly, and that the State Grid Corporation of China (SGCC) plays an important role in patent collaboration in SG field currently. It can also be found that patent collaboration is an effective form of cooperative innovation among different entities. Finally, three suggestions are provided in response to the existing problems. [ABSTRACT FROM AUTHOR]

Plastic mulching on farmland has been increasing worldwide for decades due to its superior advantages for improving crop yields. Monitoring Plastic-Mulched Land-cover (PML) can provide essential information for making agricultural management decisions and reducing PML's eco-environmental impacts. However, mapping PML with remote sensing data is still challenging and problematic due to its complicated and mixed characteristics. In this study, a new Object-Based Image Analysis (OBIA) approach has been proposed to investigate the potential for combined use of Sentinel-1 (S1) SAR and Sentinel-2 (S2) Multi-spectral data to extract PML. Based on the ESP2 tool (Estimation of Scale Parameter 2) and ED2 index (Euclidean Distance 2), the optimal Multi-Resolution Segmentation (MRS) result is chosen as the basis of following object-based classification. Spectral and backscattering features, index features and texture features from S1 and S2 are adopted in classifying PML and other land-cover types. Three machine-learning classifiers known as the—Classification and Regression Tree (CART), the Random Forest (RF) and the Support Vector Machine (SVM) are carried out and compared in this study. The best classification result with an overall accuracy of 94.34% is achieved by using spectral, backscattering, index and textural information from integrated S1 and S2 data with the SVM classifier. Texture information is demonstrated to contribute positively to PML classifications with SVM and RF classifiers. PML mapping using SAR information alone has been greatly improved by the object-based approach to an overall accuracy of 87.72%. By adding SAR data into optical data, the accuracy of object-based PML classifications has also been improved by 1–3%. [ABSTRACT FROM AUTHOR]

In China, the stress on agricultural water resources is becoming increasingly severe. In response, a range of water-saving irrigation (WSI) policies and practices have been promoted to improve irrigation efficiency. In this study, a water-balance model in paddy fields was calibrated and validated using a 2-year field experimental dataset collected from an irrigated area in Gaoyou, China, in 2014–2015. The model was used to assess the effects of WSI practices and provides options for implementing water-price reforms. Results show that paddy fields effectively retain rainfall with utilization rates greater than 70% for both shallow wet irrigation (SWI) and shallow humidity-regulated irrigation (SHRI) scenarios. The estimated average water-saving rates from 1960 to 2015 using SWI and SHRI are 33.7% and 43%, respectively, which represent considerable reductions in water consumption. The benefits of WSI practices combined with water management policies are also evident. For example, conversion of irrigation water to industrial water yields a 3-year average water fee of 205.2 yuan/ha using SWI and 20.6 yuan/ha using SHRI, considerably reducing farmers' financial burden for agricultural water supplies. In conclusion, we recommend the adoption of SWI and SHRI practices in southern China as a means of partially alleviating China's water-shortage problem. [ABSTRACT FROM AUTHOR]

In 2015, a new round reform of the marketization for the electricity sales in China is launched. This paper investigates the policy selection for this reform in China, from the perspective of political economics. We analyze the policy selection of the 2015 reform from two aspects of market structure and pricing mechanism. According to the policy of the 2015 reform, China’s power industry is of great potential to develop the market structures of “integration of generation and retail services while integrating transmission and distribution” versus “integration of generation, distribution and retail services while independent of transmission”. Those two market structures have advantages on competition efficiency and political practicability. For the pricing mechanisms, the power exchange market of China can take bilateral contracts for the long-term trading and double-sided auctions for the short-term trading, as well as for the spot market. In addition, electricity financial market can be set up as a supplement for the power exchange market, which is of potential contribution to manage the risk and discover the effective price. The 2015, reform assigns two state-owned grid companies the responsibility of the demand side management. The intelligent system to improve the information management of energy consumption can be established. Utilization of renewable energy is also emphasized in the 2015 reform for energy sustainability in China. Effective policy instruments, such as the efficient subsidy policy, an independent exchange market, and a quota system, for the promotion of renewable energy utilization, can be implemented. [ABSTRACT FROM AUTHOR]

Classic core-based instrument transformers are more prone to magnetic saturation. This affects the measurement accuracy of such transformers and limits their applications in measuring large direct current (DC). Moreover, protection and control systems may exhibit malfunctions due to such measurement errors. This paper presents a more accurate method for current measurement based on a circular magnetic field sensing array. The proposed measurement approach utilizes multiple hall sensors that are evenly distributed on a circle. The average value of all hall sensors is regarded as the final measurement. The calculation model is established in the case of magnetic field interference of the parallel wire, and the simulation results show that the error decreases significantly when the number of hall sensors n is greater than 8. The measurement error is less than 0.06% when the wire spacing is greater than 2.5 times the radius of the sensor array. A simulation study on the off-center primary conductor is conducted, and a kind of hall sensor compensation method is adopted to improve the accuracy. The simulation and test results indicate that the measurement error of the system is less than 0.1%. [ABSTRACT FROM AUTHOR]

Atrial fibrillation (AF), characterized by structural remodeling involving atrial myocardial degradation and fibrosis, is linked with obesity and transforming growth factor beta 1 (TGF-β1). Aldehyde dehydrogenase 2 (ALDH2) deficiency, highly prevalent in East Asian people, is paradoxically associated with a lower AF risk. This study investigated the impact of ALDH2 deficiency on diet-induced obesity and AF vulnerability in mice, exploring potential compensatory upregulation of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme-oxygenase 1 (HO-1). Wild-type (WT) and ALDH2*2 knock-in (KI) mice were administered a high-fat diet (HFD) for 16 weeks. Despite heightened levels of reactive oxygen species (ROS) post HFD, the ALDH2*2 KI mice did not exhibit a greater propensity for AF compared to the WT controls. The ALDH2*2 KI mice showed equivalent myofibril degradation in cardiomyocytes compared to WT after chronic HFD consumption, indicating suppressed ALDH2 production in the WT mice. Atrial fibrosis did not proportionally increase with TGF-β1 expression in ALDH2*2 KI mice, suggesting compensatory upregulation of the Nrf2 and HO-1 pathway, attenuating fibrosis. In summary, ALDH2 deficiency did not heighten AF susceptibility in obesity, highlighting Nrf2/HO-1 pathway activation as an adaptive mechanism. Despite limitations, these findings reveal a complex molecular interplay, providing insights into the paradoxical AF-ALDH2 relationship in the setting of obesity.

Liver fibrosis is reversible when treated in its early stages and when liver inflammatory factors are inhibited. Limited studies have investigated the therapeutic effects of corylin, a flavonoid extracted from Psoralea corylifolia L. (Fabaceae), on liver fibrosis. Therefore, we evaluated the anti-inflammatory activity of corylin and investigated its efficacy and mechanism of action in ameliorating liver fibrosis. Corylin significantly inhibited inflammatory responses by inhibiting the activation of mitogen-activated protein kinase signaling pathways and the expression of interleukin (IL)-1β, IL-6, and tumor necrosis factor-alpha in human THP-1 and mouse RAW264.7 macrophages. Furthermore, corylin inhibited the expression of growth arrest-specific gene 6 in human hepatic stellate cells (HSCs) and the activation of the downstream phosphoinositide 3-kinase/protein kinase B pathway. This inhibited the activation of HSCs and the expression of extracellular matrix proteins, including α-smooth muscle actin and type I collagen. Additionally, corylin induced caspase 9 and caspase 3 activation, which promoted apoptosis in HSCs. Moreover, in vivo experiments confirmed the regulatory effects of corylin on these proteins, and corylin alleviated the symptoms of carbon tetrachloride-induced liver fibrosis in mice. These findings revealed that corylin has anti-inflammatory activity and inhibits HSC activation; thus, it presents as a potential adjuvant in the treatment of liver fibrosis.

Previous investigations have suggested an association between the PCSK9 common polymorphism E670G and Lipoprotein(a) (Lp(a)) levels, as well as a link between plasma PCSK9 levels and Lp(a) concentrations. However, the causal relationship between plasma PCSK9 and Lp(a) levels remains uncertain. In this study, we explored the association between PCSK9 E670G polymorphism and Lp(a) levels in 614 healthy Taiwanese individuals. Employing a two-sample Mendelian randomization (MR) analysis using openly accessible PCSK9 and Lp(a) summary statistics from the genome-wide association studies (GWAS) and UK Biobank, we aimed to determine if a causal link exists between plasma PCSK9 levels and Lp(a) concentrations. Our findings reveal that the E670G G allele is independently associated with a decreased likelihood of developing elevated Lp(a) levels. This association persists even after adjusting for common cardiovascular risk factors and irrespective of lipid profile variations. The MR analysis, utilizing six PCSK9 GWAS-associated variants as instrumental variables to predict plasma PCSK9 levels, provides compelling evidence of a causal relationship between plasma PCSK9 levels and Lp(a) concentration. In conclusion, our study not only replicates the association between the PCSK9 E670G polymorphism and Lp(a) levels but also confirms a causative relationship between PCSK9 levels and Lp(a) concentrations through MR analysis.

KCNH2 loss-of-function mutations cause long QT syndrome type 2 (LQT2), an inherited cardiac disorder associated with life-threatening ventricular arrhythmia. Through whole-exome sequencing, we discovered a novel AGCGACAC deletion (S981fs) in the hERG gene of an LQT2 patient. Using a heterologous expression system and patch clamping, we found that the mutant K channel had reduced cell surface expression and lower current amplitude compared to the wild type. However, functional expression was restored by lowering temperature and using potassium channel inhibitors or openers (E4031, cisapride, nicorandil). Co-immunoprecipitation experiments confirmed the assembly of mutant proteins with wild-type hERG. Confocal imaging showed decreased hERG distribution on the cell membrane in cells expressing S981fs. Notably, treatment with G418 significantly increased hERG current in wild-type/S981fs heterozygotes. In conclusion, our study identifies a novel hERG mutation leading to impaired Kv11.1 function due to trafficking and nonsense-mediated RNA decay defects. These findings shed light on the mechanisms underlying LQT2 and offer potential therapeutic avenues.

In this study, we developed a series of Au/electroactive polyimide (Au/EPI-5) composite for the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) using NaBH 4 as a reducing agent at room temperature. The electroactive polyimide (EPI-5) synthesis was performed by chemical imidization of its 4,4'-(4.4'-isopropylidene-diphenoxy) bis (phthalic anhydride) (BSAA) and amino-capped aniline pentamer (ACAP). In addition, prepare different concentrations of Au ions through the in-situ redox reaction of EPI-5 to obtain Au nanoparticles (AuNPs) and anchored on the surface of EPI-5 to form series of Au/EPI-5 composite. Using SEM and HR-TEM confirm the particle size (23-113 nm) of the reduced AuNPs increases with the increase of the concentration. Based on CV studies, the redox capability of as-prepared electroactive materials was found to show an increase trend: 1Au/EPI-5 < 3Au/EPI-5 < 5Au/EPI-5. The series of Au/EPI-5 composites showed good stability and catalytic activity for the reaction of 4-NP to 4-AP. Especially, the 5Au/EPI-5 composite shows the highest catalytic activity when applied for the reduction of 4-NP to 4-AP within 17 min. The rate constant and kinetic activity energy were calculated to be 1.1 × 10 -3 s -1 and 38.9 kJ/mol, respectively. Following a reusability test repeated 10 times, the 5Au/EPI-5 composite maintained a conversion rate higher than 95%. Finally, this study elaborates the mechanism of the catalytic reduction of 4-NP to 4-AP.

This study investigates the effect of laser volume energy density (VED) on the properties of AISI 420 stainless steel and TiN/AISI 420 composite manufactured by selective laser melting (SLM). The composite contained 1 wt.% TiN and the average diameters of AISI 420 and TiN powders were 45 µm and 1 µm, respectively. The powder for SLMing the TiN/AISI 420 composite was prepared using a novel two-stage mixing scheme. The morphology, mechanical, and corrosion properties of the specimens were analyzed, and their correlations with microstructures were investigated. The results showed that the surface roughness of both SLM samples decreases with increasing VED, while relative densities greater than 99% were achieved at VEDs higher than 160 J/mm 3 . The SLM AISI 420 specimen fabricated at a VED of 205 J/mm 3 exhibited the highest density of 7.7 g/cm 3 , tensile strength (UTS) of 1270 MPa, and elongation of 3.86%. The SLM TiN/AISI 420 specimen at a VED of 285 J/mm 3 had a density of 7.67 g/cm 3 , UTS of 1482 MPa, and elongation of 2.72%. The microstructure of the SLM TiN/AISI 420 composite displayed a ring-like micro-grain structure consisting of retained austenite on the grain boundary and martensite in the grain. The TiN particles strengthened the mechanical properties of the composite by accumulating along the grain boundary. The mean hardnesses of the SLM AISI 420 and TiN/AISI 420 specimens were 635 and 735 HV, respectively, which exceeded previously reported results. The SLM TiN/AISI 420 composite exhibited excellent corrosion resistance in both 3.5 wt.% NaCl and 6 wt.% FeCl 3 solutions, with a resulting corrosion rate as low as 11 µm/year.

Research on the development of flexible silica aerogels (FSAs) has been ongoing due to their excellent thermal insulation, low density, and high elasticity. However, the physical properties of FSAs, such as density, thermal conductivity, mechanical strength, and surface wettability, are highly dependent on the preparation conditions. To achieve the desired properties of FSAs for various applications, it is necessary to develop a method to fine-tune their physical properties. In this paper, two modifiers of methyltrimethoxysilane (MTMS)/trimethylethoxysilane (TMES) were employed to fine-tune the bulk density of a series of flexible silica aerogels (FSAs), reflecting a series of FSAs with fine-tunable physical properties. First, the precursor was synthesized by a click reaction between vinyltrimethoxysilane (VTMS) and 2,2' (ethylenedioxy) diethanethiol (EDDET). The VTMS, EDDET, and the as-prepared precursor were characterized by FT-IR and NMR spectroscopy. Subsequently, the precursor was converted into a series of FSAs (denoted by FSA, FSA-M, and FSA-T) through conventional sol-gel reactions with/without MTMS/TMES. Chemical structures of synthesized FSAs were confirmed by 13 C and 29 Si solid-state NMR spectroscopy. The porous structure of FSAs was identified by BET and SEM, respectively. Physical properties, such as thermal conductivity, mechanical strength, and surface wettability of FSAs were determined by a Hot Disk, durometer/DMA in compression mode, and contact angle measurements, respectively. This study found FSAs containing none, 1 wt%, 5 wt%, and 10 wt% of MTMS increase the density of FSAs from 0.419 g/cm 3 (FSA), 0.423 g/cm 3 (FSA-M1), 0.448 g/cm 3 (FSA-M5), and 0.456 g/cm 3 (FSA-M10). It should be noted that the thermal conductivity, surface hardness, bulk mechanical strength, and hydrophobicity of FSA-Ms of increasing MTMS loading were all found to show a rising trend, while FSA-Ts exhibited lower density. FSA-T10 exhibited lower thermal conductivity, surface hardness, and bulk mechanical strength as compared to FSA. However, it was found to show higher hydrophobicity as compared to that of FSA.