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It is difficult for the current differential protection to realize synchronous sampling in active distribution network. In order to deal with this problem, a novel data synchronization method based on zero-crossing point of pre-fault current is proposed in this paper. The influencing factors of the synchronization method are discussed in detail, including line capacitance current, line length and sampling time difference. The performance of zero-crossing data synchronization method is verified by simulation in PSCAD and MATLAB. The simulation results show that the proposed method can effectively realize the data synchronization under various conditions in active distribution network.

In order to study the insulation performance of DC XLPE cables in fire environment, the conductivity of XLPE used in DC cable was tested at different temperatures, and the breakdown field strength of XLPE at different high temperatures was measured, which was carried out in a high-temperature oven. Meanwhile, the field strength distribution inside the DC cable under high temperature environment was simulated. The research results show that long-term overload of XLPE cable or high ambient temperature can cause the electric field strength of the cable insulation to increase, which will induce various defects and eventually cause insulation breakdown.

Widespread dam construction has reduced the hydrological connectivity of catchments of various sizes. Nutrients lost from upper catchments can be intercepted by dams and deposited in reservoir sediments, and this reduces downstream nutrient transportation. Few previous studies have assessed historical nutrient deposition rates (NDRs) in man-made reservoirs. Using 137Cs and 210Pbex deposition chronologies, this paper examines the total nitrogen (TN), total phosphate (TP), and organic matter (OM) concentrations in six sediment cores recovered from Xujiaya reservoir (catchment area 580 km2), provides estimates of historical NDRs by referencing the original capacity curve, and explores temporal changes to the NDR since dam construction. The results show that anthropogenic sources resulted in the increase in nutrient concentrations in the upper parts of the cores, whereas natural sources were the main contributors to nutrient deposition across the whole reservoir. In addition, sediment supply from the catchment was the main source of the nutrients deposited in the reservoir, and the changing patterns of NDRs were overall regulated by sediment yields. The TN, TP, and OM profiles in the six cores, together with the historical NDRs, reflect the pattern of nutrient deposition in the reservoir derived from this agricultural catchment over the past 60 years. The results provide new insight into the effect of dam construction on nutrient deposition at a medium-sized catchment scale against a background of recent environmental change influenced by human activity.

Osteoarthritis (OA), a chronic joint disease, is characterized by cartilage surface erosion, subchondral bone rebuilding, and formation of osteophytes. To date, the nosogenesis and underlying mechanisms of OA have not yet been elucidated. However, it is widely accepted that TNF-α is a crucial cytokine in the development of OA. Glycitin, a natural isoflavone extracted from legumes, affects physiological reactions and pathological responses. Recently, the anti-inflammatory effect of glycitin has been reported. However, the function of glycitin in cartilage degeneration in OA remains to be investigated. In the current study, primary murine chondrocytes were isolated and stimulated by TNF-α to evaluate the anti-inflammatory effects and protective function of glycitin in chondrocytes. In vivo, the ACLT mouse model, a frequently-used OA model, was used to further examine the therapeutic role of glycitin in cartilage degeneration and inflammation in OA. Consequently, glycitin functions were examined both in vivo and in vitro. Moreover, the underlying mechanism of action of glycitin was investigated and was found to involve the NF-κB signaling pathway. Collectively, this study suggests that glycitin can be potentially used for the treatment of joint degenerative diseases, including OA.

Colloidal surface engineering is of particular importance to impart modular functionalities to the colloidal systems. Here, a layer of Mn/Ni layered hydroxides (Mn/Ni(OH)x LDHs) can be successfully coated on various colloidal particles, such as silica spheres, silica rods, ferrite nanocrystal supraparticles, as well as FeOOH nanorods. Such layered hydroxides have intrinsic oxidase-mimetic activities, as demonstrated by catalytic oxidation of tetramethyl benzidine in the presence of oxygen. Furthermore, Mn/Ni(OH)x LDHs structure seems to capture bacteria (both Gram positive and Gram negative) and exhibit antibacterial properties in vitro. Moreover, local delivery of Mn/Ni-LDH structure fights against infection and reverses delayed wound healing procedures in mice models. Importantly, such hierarchical structures may have strong adhesive properties to the bacteria, which may maximize the contact between Mn/Ni(OH)x LDHs and the bacteria's surface. Overall, the present versatile colloidal surface engineering strategy will bring new insights in the field of antibiotics for its high efficiency toward antibacterial activity.

In order to clarify the electromechanical coupling characteristics of polymer materials and extend their applications in MEMS (Micro-electromechanical Systems), electromechanical responses of PDMS (Polydimethylsiloxane) with different electrodes and thicknesses under different loading conditions have been performed experimentally and numerically. Basic electrical parameters measurement and quasi-static tensile experiment of PDMS specimens were conducted. Furthermore, the dynamic mechanical properties and polarization voltage of PDMS with different electrodes and thicknesses under different loading conditions have been studied by Split Hopkinson Pressure Bar (SHPB) system integrating with electrical output measuring system. Beyond that, Abaqus/Explicit numerical simulation of PDMS specimen under different loading conditions was carried out based on Yeoh viscoelastic model and Prony series, then the strain gradient and the flexoelectric coefficients were obtained. The results show that the maximum stress of PDMS increases with increasing of loading speed and decreases with increasing of thickness, the maximum polarization voltage increases with increasing of strain rate, the maximum polarization voltages of PDMS with “C” electrode and “+” electrode are about 14 times of that with circular electrode, the flexoelectric coefficients of PDMS are within the range of 10−11–10−9C/m.

Background Depression is a common complication after stroke and is closely related to the poor prognosis of stroke. Antidepressants are the priority drug in the treatment of post-stroke depression (PSD), but there are dependence and adverse reactions. Danzhi Xiaoyao Powder has a good effect on depression without obvious adverse reactions. At present, there is a lack of rigorous randomized controlled trials to evaluate the clinical efficacy of Danzhi Xiaoyao Powder in the treatment of PSD. Methods This is a prospective, randomized, double-blind, parallel controlled trial to explore the efficacy and safety of Danzhi Xiaoyao Powder in the treatment of PSD. The participants were randomly divided into treatment group and control group. The treatment group used Danzhi Xiaoyao Powder combined with escitalopram oxalate, and the control group used Danzhi Xiaoyao Powder simulant combined with citalopram oxalate. The two groups were both treated for 8 weeks and followed up for 3 months. Observational index includes: Total response rate, Hamilton depression scale, Barthel index, national institutes of health stroke scale, the modified Edinburgh-Scandinavian stroke scale, Incidence of adverse reactions. Finally, SPASS 22.0 software was used for statistical analysis of the data. Discussion This study will evaluate the clinical efficacy of Danzhi Xiaoyao Powder in the treatment of PSD. The results of this study will provide reliable evidence for the clinical use of Xiaoyao Powder in the treatment of PSD. Trial registration Open Science Framework Registration number: DOI 10.17605/OSF.IO/5V926.

The dynamic process of the hypervelocity impact induced microjet from the grooved metal surface is studied theoretically and experimentally. Based on shock wave theory and Bernoulli's equation, a physical model is proposed to theoretically analyze the formation process of the microjet and predict the spike (head) velocity of the microjet. The hypervelocity impact experiments of the cylindrical aluminum projectile on the metal target with grooves are conducted through two-stage light gas gun, and the sequence shadowgraphy images of the microjetting formation are recorded by using Ultra-high-speed camera. Then, the numerical simulations of the hypervelocity impact-induced microjet are performed by a self-developed SPH (smoothed particle hydrodynamics) code to examine the velocity distribution, mass distribution and density distribution in detail. These numerical results are compared with those obtained by experiments and theoretical analysis, which verifies the validity of numerical model. The numerical results reveal that the front of the shock wave generated by hypervelocity impact is not strictly planar in the target due to the shock wave releasing from both sides of the impact interface. Thus, the shape of the multiple jets generated from the grooves resembles a “trident”, and the upper microjet and the lower microjet deflect upward and downward respectively. The jetting velocity and mass of the middle microjet is larger than that of the microjets on both sides in the impact area. Last, the variation of the spike velocity and jetting mass with the impact velocity and the target thickness is obtained.

The surface mechanical properties of the Selective Laser Melting (SLM) formed Ti6Al4V samples were improved by adopting a novel laser cleaning pretreatment process combined with a jet electrodeposition process. This paper aimed to investigate the effects of different laser powers on the morphologies and adhesions of the nickel coatings. The advantages of the laser cleaning process are no grinding, no contact, high efficiency and environmental protection. The morphologies, adhesion, wear resistance, and hardness of the coatings were characterized. The results indicate that when the laser energy density reached 20% (4 J/cm2), the contaminations on the substrate and the oxide layer were removed and the crystalline grain of the coating was 15.3 nm. The shallow pits generated by laser burning increased the adhesion of the coatings. In addition, when the laser energy density increased to 6 J/cm2, a yellow oxide layer was produced on the surface of the cleaned titanium alloy. Moreover, the wear resistance of the titanium alloy after the nickel plating was improved. The wear volume was only 0.046 mm3, and the hardness increased to 1967.6 N/mm2.

Local volatility model is a relatively simple way to capture volatility skew/smile. In spite of its drawbacks, it remains popular among practitioners for derivative pricing and hedging. For long-dated options or interest rate/equity hybrid products, in order to take into account the effect of stochastic interest rate on equity price volatility stochastic interest rate is often modelled together with stochastic equity price. Similar to local volatility model with deterministic interest rate, a forward Dupire PDE can be derived using Arrow-Debreu price method, which can then be shown to be equivalent to adding an additional correction term on top of Dupire forward PDE with deterministic interest rate. Calibrating a local volatility model by the forward Dupire PDE approach with adaptively mixed grids ensures both calibration accuracy and efficiency. Based on Malliavin calculus an accurate analytic approximation is also derived for the correction term incorporating impacts from both interest rate volatility and correlation, which integrates along a more likely straight line path for better accuracy. Eventually, the hybrid local volatility model can be calibrated in a two-step process, namely, calibrate local volatility model with deterministic interest rate and add adjustment for stochastic interest rate. Due to the lack of analytic solution and path-dependency nature of some products, Monte Carlo is a simple but flexible pricing method. In order to improve its convergence, we develop a scheme to combine merits of different simulation schemes and show its effectiveness.

Implied volatility skew and smile are ubiquitous phenomena in the financial derivative market especially after the Black Monday 1987 crash. Various stochastic volatility models have been proposed to capture volatility skew and smile in derivative pricing and hedging. Almost 30 years after the advent of the first type of stochastic volatility model calibrating them to the market volatility surface still remains challenging, especially when stochastic interest rate has to be also taken into account for long-dated options. Many techniques have been applied to tackle this problem, including Fast Fourier Transform, singular perturbation expansion, heat kernel expansion, Markovian projection, to name a few. Although they have achieved some success in deriving either a close-form solution for a specific type of model or asymptotic solution in more general, none of them can really solve the calibration problem satisfying our need in term of both efficiency and accuracy. Monte Carlo method is a flexible numerical pricing method but has not been considering for calibration because of its slow convergence. However, with the great advance in computational power, in particular, parallel computation and the invention of other variance reduction techniques fast and accurate calibration using Monte Carlo becomes possible. This paper presents a Monte Carlo calibration method for stochastic volatility models with stochastic interest rate, which reduces simulation dimension by conditional expectation and further improves speed by vectorization. Numerical experiments show that both the calibration speed and accuracy of this generic method are satisfactory for almost all applications.

A simple and rapid electrochemical synthesis strategy for in-situ fabrication of toluidine blue (TB)-functionalized metal organic framework (TB@MOFs) thin films via one-step reduction approach was reported. The TB@MOFs thin layer has been synthesized on the working electrode surface in different times at room temperature, and its morphology and thickness was characterized by varied instruments, including scanning electron microscope, transmission electron microscope, and scanning ion conductance microscope. The prepared TB@MOFs shows exceptional electrochemical activity and stability under mild conditions, and its electrochemical response is dependent on the amount of TB molecules which are encapsulated in the MOFs. Based on the TB@MOFs sensing platform, a sensitive label-free electrochemical immunosensor for the detection of Indole-3-acetic acid (IAA, a plant hormone) was developed with a wide linear range (2.5 pg mL−1 - 5 ng mL−1) and a low detection limit (1.4 pg mL−1). Moreover, this immune sensor shows good sensitivity and selectivity in real samples for IAA detection.

The theories of impact dynamics and adiabatic temperature change were adopted to investigate the ionization degree of the plasma generated by the 2A12 aluminum target during 2A12 aluminum projectile hypervelocity impact, and the radiant temperature was also estimated during hypervelocity impact. A two-stage light gas gun combined with the plasma characteristic parameters measured by a triple Langmuir probe was applied, and then the fitting relationship between the plasma ionization degree and the theoretical impact temperature as well as the fitting relationship between the maximum electron density and impact velocity were obtained with the aid of the theoretical derivation of the plasma ionization degree and the electron temperature and electron density extracted from experiments.

To researching the damage characteristics of typical logical chip modules in spacecraft due to plasma generated by hypervelocity impacts, we have established a triple Langmuir probe diagnostic system and a logical chips measurement system, which were used to diagnose plasma characteristic parameters and the logical chip module's logical state changes due to the plasma created by a 7075 aluminum projectile hypervelocity impact on the 2A12 aluminum target. Three sets of experiments were performed with the collision speeds of 2.85 km/s, 3.1 km/s and 2.20 km/s, at the same incident angles of 30 degrees and logical chip module's positions by using a two-stage light gas gun loading system, a plasma characteristic parameters diagnostic system and a logical chip module's logical state measurement system, respectively. Electron temperature and density were measured at given position and azimuth, and damage estimation was performed for the logical chip module by using the data acquisition system. Experimental results showed that temporary damage could be induced on logical chip modules in spacecraft by plasma generated by hypervelocity impacts under the given experimental conditions and the sensors' position and azimuth.

Lactofen is a chiral herbicide and widely used against broadleaf weeds in agriculture. As a pesticide, it is directly released to the environment, and easily caused contamination in soil and aquatic ecosystem. The enantioselective degradation of lactofen in the environment has been reported, but the molecular biological mechanism of this phenomenon is still unclear. In this study, strain Edaphocola flava HME-24 could degrade 96.7% of 50 mg L−1 lactofen within 72 h. Lactofen was initially hydrolyzed to desethyl lactofen and subsequently acifluorfen by strain HME-24. A novel gene lanE, involved in lactofen transformation, was obtained from Edaphocola flava HME-24. Gene lanE encoded a protein of 471 amino acids that contained the conserved GXSXG esterase motif and clustered into esterase subfamily V. LanE shared the highest identity with esterase EstD (Q9WYH1) from Thermotoga maritima MSB8 (29.14%). This esterase was also able to transform p-nitrophenyl esters (C4–C8), and the activity decreased when the carbon chain length increased. LanE showed enantioselectivity during the degradation of lactofen, diclofop-methyl, and quizalofop-ethyl, with a higher degradation efficiency of (S)-enantiomers than (R)-enantiomers. The three-dimensional structure of LanE was simulated, and molecular docking revealed that when the (S)-enantiomers of lactofen occupied the active sites, the distance between the ligand molecule and the coordination atom was shorter than that when the (R)-enantiomers occupied the active sites, which facilitated the formation of the transition state complex. The results in this study enhanced our understanding of the preferential catabolism of the (S)-enantiomers of lactofen on the molecular level and could illustrate the reported enantioselective degradation of lactofen in the environment.

Assessment of long-term human impact on sediment yields from karst settings can improve our understanding of the pattern of soil erosion causing rocky desertification in the historical context of environmental change influenced by human activity. Few previous investigations have estimated this impact over time-scales longer than 50 years. This study used dated depression deposits to reconstruct human impact on sediment yields from a small karst catchment in the Three Gorges Reservoir Region, China, over the past 600 years. 137Cs, 210Pbex, and 14C techniques were used to determine short-term (~50 yr), medium-term (~100 yr), and long-term (~600 yr) sedimentation in the karst depression, respectively. Sedimentation rates and specific sediment yields in the catchment during six distinct stages (1351–1462, 1463–1701, 1702–1809, 1810–1916, 1917–1962, and 1963–2017) were determined from core samples. The results indicate that soil loss during the period 1351–1962 was more intensive than that since 1963, which reveals changing sediment yields impacted by human activity over the past 600 years. The high values during the three stages before 1810 can be attributed to the impacts of large-scale migration of people from Huguang to Sichuan during the Ming and Qing dynasties; the higher values during 1810–1916 might reflect increasing disturbance related to rapid population expansion; the highest values (1917–1962) were caused by large-scale deforestation in 1958 and a consistently increasing population; and low values since 1963 reflect constraints on the supply of sediment source materials. These results suggest that rocky desertification might be a long-term land-surface process induced by human activity over timescales of >100 years rather than a short-term modern process occurring over a number of decades. This is the first attempt to examine the long-term history of human impact on sediment yields from a karst catchment using depression deposits. This work improves our understanding of the influence of human activities on soil loss at a depression-catchment scale, and of the evolution and dynamics of rocky desertification in karst areas.

Given the potentially high impact of accurate financial market forecasting, there has been considerable research on time series analysis for financial markets. We present a new Intelligent Hybrid Weighted Fuzzy (IHWF) time series model to improve forecasting accuracy in financial markets, which are complex nonlinear time-sensitive systems, influenced by many factors. The IHWF model uniquely combines Empirical Mode Decomposition (EMD) with a novel weighted fuzzy time series method. The model is enhanced by an Adaptive Sine-Cosine Human Learning Optimization (ASCHLO) algorithm to help find optimal parameters that further improve forecasting performance. EMD is a time series processing technique to extract the possible modes of various kinds of institutional and individual investors and traders, embedded in a given time series. Subsequently, the proposed weighted fuzzy time series method with chronological order based frequency and Neighborhood Volatility Direction (NVD) is analyzed and integrated with ASCHLO to determine the effective universe discourse, intervals and weights. In order to evaluate the performance of proposed model, we evaluate actual trading data of Taiwan Capitalization Weighted Stock Index (TAIEX) from 1990 to 2004 and the findings are compared with other well-known forecasting models. The results show that the proposed method outperforms the listing models in terms of accuracy.

Online reviews often contain user’s specific opinions on aspects (features) of items. These opinions are very useful to merchants and customers, but manually extracting them is time-consuming. Several topic models have been proposed to simultaneously extract item aspects and user’s opinions on the aspects, as well as to detect sentiment associated with the opinions. However, existing models tend to find poor aspect-opinion associations when limited examples of the required word co-occurrences are available in corpus. These models often also assign incorrect sentiment to words. In this paper, we propose a Latent embedding structured Opinion mining Topic model, called the LOT, which can simultaneously discover relevant aspect-level specific opinions from small or large numbers of reviews and to assign accurate sentiment to words. Experimental results for topic coherence, document sentiment classification, and a human evaluation all show that our proposed model achieves significant improvements over several state-of-the-art baselines.

Visible light photocatalysts have stimulated great research efforts. In this contribution, graphene-like Co 3 S 4 nanosheet/Ag 2 S nanocomposite was prepared using a simple method, and characterized by transmission electron microscopy, X-ray diffraction, and UV–Vis DRS, etc. The photocatalytic properties of the nanocomposite was evaluated by the photocatalytic degradation of Methylene blue (MB) and Methyl orange (MO) under visible light irradiation. The nanocomposite photocatalyst displays excellent stability and photocatalytic activity compared with pure Co 3 S 4 nanosheet or Ag 2 S nanoparticles. The superior photocatalytic properties were attributed to its unique structures, which could promote efficiently electron/hole separation and transportation.

In order to obtain the elemental compositions of the projectile and target materials during 2A12 aluminum projectile shot on a natural dolomite plate, three kinds of experiments have been conducted using a spectral acquirement system established on a two-stage light gas gun for impact velocities ranging from 2.20 km/s to 4.20 km/s, at the same projectile incidence angle of 30°. Experimental results show that the elemental compositions of the projectile and target materials in the strong shock experiments have a good agreement with the original elemental compositions of the projectile and target. In addition, the relations between spectral radiant intensity and elemental compositions of the projectile and target materials have been obtained for different impact velocities, in which the spectral radiant intensity of the main elements in the material increases with increasing impact velocity, and more elements appear with increasing impact velocity since more energy would result from a higher velocity impact.

Topic modeling has been widely used for extracting the major topics from a corpus. Each discovered topic contains a set of related individual words that describe the topic itself. The discovered topics summarize the major themes of the corpus. Recently, a few phrase-based topic models have been proposed, which simultaneously model phrases and topics. The topics discovered by these models consist of phrases besides individual words, as phrases are typically more meaningful. However, these models typically require large amounts of data to provide reliable statistics for phrase-based topic modeling, thus limiting their performance in scenarios with limited data. To address this limitation, we propose a knowledge-based topic model that incorporates two types of pre-identified external knowledge for topical phrase discovery: Phrase knowledge, and phrase correlation knowledge. Phrase knowledge guides the discovery of meaningful phrases by leveraging a set of pre-identified exemplary phrases; Phrase correlation knowledge guides the discovery of meaningful topics by exploiting a set of pre-identified pairs of related phrases. Experimental results show that our method outperforms the state-of-the-art baseline on both small and large datasets, extracting more meaningful phrases and coherent topics.

We propose a latent-embedding-structured lifelong learning topic model, called the LLT model, to discover coherent topics from a corpus. Specifically, we exploit latent word embeddings to structure our model and mine word correlation knowledge to assist in topic modeling. During each learning iteration, our model learns new word embeddings based on the topics generated in the previous learning iteration. Experimental results demonstrate that our LLT model is able to generate more coherent topics than state-of-the-art methods.

Financial forecasting is an extremely challenging task given the complex, nonlinear nature of financial market systems. To overcome this challenge, we present an intelligent weighted fuzzy time series model for financial forecasting, which uses a sine-cosine adaptive human learning optimization (SCHLO) algorithm to search for the optimal parameters for forecasting. New weighted operators that consider frequency based chronological order and stock volume are analyzed, and SCHLO is integrated to determine the effective intervals and weighting factors. Furthermore, a novel short-term trend repair operation is developed to complement the final forecasting process. Finally, the proposed model is applied to four world major trading markets: the Dow Jones Index (DJI), the German Stock Index (DAX), the Japanese Stock Index (NIKKEI), and Taiwan Stock Index (TAIEX). Experimental results show that our model is consistently more accurate than the state-of-the-art baseline methods. The easy implementation and effective forecasting performance suggest our proposed model could be a favorable market application prospect.

Osteoarthritis (OA), a common and severe disease, is predominantly characterized by cartilage destruction, which results in the degeneration of joint surfaces. Nowadays, it is accepted that TNFα plays a critical role in OA. Scutellarin, the main bioactive flavonoid glycoside extracted form Erigeron breviscapus, has been reported to exert positive effects on anti-inflammatory reactions. However, the effect of scutellarin in OA is still unknown. In this study, we isolated and cultured primary murine chondrocytes, stimulating TNF-α, in the presence or absence of scutellarin treatment. We found that the inflammatory response stimulated by TNF-α was significantly inhibited by the addition of scutellarin. Moreover, we established OA mouse models induced by surgery. In this mouse model, both inflammatory reaction and cartilage degeneration were markedly inhibited by oral administration of scutellarin. Furthermore, the cellular mechanism underlying the protective effect of scutellarin in OA was clearly associated with the NF-κB and PI3K/AKT signaling pathways. Collectively, this study proposes scutellarin as a potential therapeutic to treat joint degenerative diseases, including OA.

A 3D Smoothed Particle Hydrodynamics (SPH) code was developed to investigate the generation of electromagnetic effect and flash during hypervelocity impact of an aluminum projectile on an aluminum target. The Arrhenius equation and the Biot-Savart law were incorporated into the SPH code for calculating the plasma charge and the magnetic field intensity from the plasma. Planck's law for the blackbody spectral radiance was introduced into the SPH code to determine the flash radiation intensities of different characteristic wavelengths. By using the SPH code, the effect of impact velocities and angles on the magnetic field intensity and flash intensity was explored. The numerical results show that the magnetic field intensity and flash intensity increase significantly with the impact velocity. By decreasing the incident angle from 90° to 45°, the magnetic field intensity and flash intensity decrease. Finally, based on the numerical simulations, two semiempirical formulae were proposed to accurately describe the variation of magnetic field intensity and the evolution of the flash radiation intensity with the impact velocity and the impact angle.

To improve the composite coating surface quality and performance, a magnetic-field-assisted method was used to manufacture Ni–SiC composite coating based on jet electrodeposition. The effect of different concentrations of SiC and the magnetic field on the surface morphology, microhardness, wear resistance, and corrosion resistance of the coating were investigated by (1) changing the content of nano-SiC particles in the bath, and (2) whether magnetic-field-assisted device was used. Results showed that adding nano-SiC can refine the coating grain size and reduce the surface roughness. The microhardness of the coating increased significantly from 442.65 HV to 514.03 HV for pure nickel coating, an increase of 16.12%; the microhardness increased to 542.76 HV with the introduction of a magnetic field. Magnetic field assistance can reduce cellular protrusions and improve flatness. The Ni–SiC coating wear resistance was strengthened with Magnetic-field-assisted, the wear mechanism changed from the fatigue wear to abrasive wear and adhesive wear. The corrosion resistance of Ni–SiC composite coating was also improved compared with pure Ni coating.