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When an aircraft malfunctions, quickly and accurately identifying the faulty unit is essential for ensuring normal operation. Unfortunately, maintenance engineers often struggle to acquire the necessary fault-related knowledge due to poor management and utilization of aircraft fault documents. To address this issue, we introduce knowledge graph technology into the field of aircraft fault diagnosis, exploring its construction and application for effective knowledge management. Our work starts by analyzing the critical knowledge elements required for aircraft fault diagnosis and designing a schema layer for fault knowledge graphs. We then we then combine deep learning and heuristic rules to extract fault knowledge from both structured and unstructured data, enabling the construction of aircraft fault knowledge graphs. Finally, we develop a fault question-answering system based on fault knowledge graphs that can accurately give solutions to questions posed by maintenance engineers. Our practice demonstrates that knowledge graphs provide an effective means of managing aircraft fault knowledge, assisting engineers in locating fault reasons accurately and quickly.

In engineering design problems, intervals refer to any kind of lack of information. This paper presents an improved entorpy-based methodology for a probabilistic representation of a stochastic quantity for which only sparse point data and/or interval data may be available. The combined entropy function is used to measure the uncertainty in data, which is evaluated from the non-parametric probability density function for sparse point data and the cumulative distribution function for interval data, Wherein the entire non-parametric distribution can be discretized at a finite number of points and the probability density values at these points can be inferred using the principle of maximum-entropy, thus avoiding the assumption of any particular distribution. The proposed improved Entorpy-based methodology is then employed in the attempt of interval uncertainty propagation, with the results compared with previous studies. Examples are provided to demonstrate the effectiveness of present method. The study reveals great potentials of the probabilistic method for the treatment of the uncertainty in presence of the sparse point data and/or interval data.

The drainage of granular assembly from a flat-bottomed silo can be in either funnel flow mode or mixed flow mode. The primary motivation of this work is to investigate whether there exist fundamental differences between the rheological behavior of particles under these two discharge modes. The developments and evolutions of flowing zone and also the characteristics of particle velocity fluctuation during funnel and mixed flow discharges were analyzed and compared by performing 3D Discrete Element Method (DEM) simulations. For funnel flow discharge, the characteristic width of flowing zone at the early discharge state presented a clear history-dependent feature. For mixed flow discharge, the flowing zone sharply shrunk when the upper free surface of the material approached a critical height and the discharge mode then shifted to funnel flow mode. Discrete Fourier transform results demonstrate that resonant motion of particles appeared during both funnel and mixed flow discharges. The correlation analyses indicate that for these two flow modes, there both existed an intermediate region in the converging part of the flowing zone. Its upper boundary located at the position where the flowing zone started to converge along the vertical direction and was featured as the maximum particle compressive force. And its bottom boundary corresponded to the location of free-fall arch and acted as the source of the resonant motion of particles. Our simulation results thus suggest that from the perspective of particle velocity fluctuation, there is no essential difference between granular flows under funnel and mixed discharge modes.

In this work, poly(aniline-co-pyrrole)/single-walled carbon nanotubes (poly(ANi-co-Py)/SWCNTs) composites are prepared using a simple electropolymerization method. In the fabrication process, SWCNTs are used as working electrodes, on which an aniline pyrrole copolymer is synthesized by an electropolymerization method. Using sodium dodecyl sulfate (SDS) as an auxiliary dopant, the thermoelectric properties, electrical conductivity (σ) and power factor (PF) of the composites can be further improved. Scanning electron microscopy (SEM) images, powder X-ray diffraction (XRD) patterns, and Raman spectroscopy are used to characterize the properties of the as-prepared composites. Compared with the sample prepared by blending SWCNTs with the aniline–pyrrole copolymer, the formation of a uniform poly(ANi-co-Py) layer on the surface of SWCNTs endows the poly(ANi-co-Py)/SWCNTs composite with the highest PF up to 111.4 ± 3.2 μW m−1 K−2 at room temperature, which is above the PF of most PANi/PPy/CNT composites.

This paper aims to identify the main cause of the hose whipping phenomenon (HWP) in air refueling, and come up with effective preventive measures. The system-theoretic accident model and process (STAMP), i.e., the system-theoretic process analysis (STPA), was adopted to evaluate the safety of air refueling. Then, the evaluation results were verified with a self-designed simulation validation model. The results show that the HWP is controlled by the docking speed, reel mechanism, and designed hose length; the swing range and tension change of the hose increased under inappropriate speed control; reel control could end the hazardous state of the hose within 50s after docking; the HWP occurred after the hose length was shortened from 22m to 14m. The research findings provide a reference for the prevention of the HWP.

This paper studies the preview tracking control problem for linear discrete-time periodic switched systems. Firstly, an augmented error system is constructed for each subsystem by stabilizing the augmented error systems through the method of optimal preview control, and the tracking problem of the switched system is transformed into the switched stability problem of closed-loop augmented error systems. Secondly, a switched Lyapunov function method is applied to search the minimal dwell time satisfying the switched stability of the closed-loop augmented error systems. Thirdly, the switched preview control input is solved from the controller of the individual augmented error system, and then the sufficient conditions and the preview controller can be obtained to guarantee the solvability of the original periodic switched preview tracking problem. Finally, numerical simulations show the effectiveness of the stabilization design method.

The antibiotic mycelial residue (AMR) generated from cephalosporin C production is a hazardous organic waste, which is usually disposed of by landfilling that causes potential secondary environmental pollution. AMR combustion can be an effective method to treat AMR. In order to develop clean combustion technologies for safe disposal and energy recovery from various AMRs, the emission characteristics of NOx and SO2 from AMR combustion were studied experimentally in this work. It was found that the fuel-N is constituted by 85% protein nitrogen and 15% inorganic nitrogen, and the fuel-S by 78% inorganic sulfur and 22% organic sulfur. Nitrogen oxide emissions mainly occur at the volatile combustion stage when the temperature rises to 400 °C, while the primary sulfur oxide emission appears at the char combustion stage above 400 °C. Increasing the combustion temperature and airflow cause higher NOx emissions. High moisture content in AMR can significantly reduce the NOx emission by lowering the combustion temperature and generating more reducing gases such as CO. For the SO2 emission, the combustion temperature (700 to 900 °C), airflow and AMR water content do not seem to exhibit obvious effects. The presence of CaO significantly inhibits SO2 emission, especially for the SO2 produced during the AMR char combustion because of the good control effect on the direct emission of inorganic SO2. Employing air/fuel staging technologies in combination with in-situ desulfurization by calcium oxide/salts added in the combustor with operation temperatures lower than 900 °C should be a potential technology for the clean disposal of AMRs.

The antibiotic mycelial residue (AMR) generated from cephalosporin C production is a hazardous organic waste, which is usually disposed of by landfilling that causes potential secondary environmental pollution. AMR combustion can be an effective method to treat AMR. In order to develop clean combustion technologies for safe disposal and energy recovery from various AMRs, the emission characteristics of NO

The lotus (Nelumbo Adans.) is an important aquatic plant with ornamental, medicinal and edible values and cultural connotations. It has single-, semi-double-, double- and thousand-petalled types of flower shape and is an ideal material for developmental research of flower doubling. The lotus is a basal eudicot species without a morphological difference between the sepals and petals and occupies a critical phylogenetic position in flowering plants. In order to investigate the genetic relationship between the sepals and petals in the lotus, the class E genes which affect sepal formation were focused on and analyzed. Here, SEPALLATA 1(NnSEP1) and its homologous genes AGAMOUS-LIKE MADS-BOXAGL9 (NnAGL9) and MADS-BOX TRANSCRIPTION FACTOR 6-like (NnMADS6-like) of the class E gene family were isolated from the flower buds of the Asian lotus (Nelumbo nucifera Gaertn.). The protein structure, subcellular localization and expression patterns of these three genes were investigated. All three genes were verified to locate in the nucleus and had typical MADS-box characteristics. NnSEP1 and NnMADS6-like were specifically expressed in the sepals, while NnAGL9 was highly expressed in the petals, suggesting that different developmental mechanisms exist in the formation of the sepals and petals in the lotus. The significant functional differences between NnSEP1, NnMADS6-like and NnAGL9 were also confirmed by a yeast two-hybrid assay. These results expand our knowledge on the class E gene family in sepal formation and will benefit fundamental research on the development of floral organs in Nelumbo.

The formation of a more porous zone in the near wall region has been commonly suggested to be one of the main mechanisms of the delayed onset of fluidization in micro fluidized beds (MFBs). If such geometrical effect still plays a major role once the bed is fluidized, it will challenge the applications of Two-Fluid Model (TFM) to simulate micro fluidized beds. In this work this issue is assessed by taking the simulation results of the Computational Fluid Dynamics coupled with the Discrete Element Method (CFD-DEM) as the benchmark data. Both the delayed onset of fluidization and the advanced onset of turbulent fluidization predicted by CFD-DEM simulations are successfully captured by the TFM simulations. The radial profiles of solids volume fraction and solids axial velocity predicted by TFM and CFD-DEM simulations are also in well agreement. Such results demonstrate that TFM can be appropriately used to model micro fluidized beds systems. Parameter analyses show that TFM simulation results are closely related to the input parameter setting. The minimum bubbling velocity predicted by TFM simulations closely depends on the chosen value of frictional packing limit. And the specularity coefficient has a significant impact on the predicted solids flow behavior.

Strike-slip faults can play an important role in hydrocarbon accumulation. Therefore advanced studies on the interpretation of intra-basinal strike-slip faults are crucial. Hybrid attributes computed from conditioned 3D seismic data via artificial neural networks may enhance subsurface fault images. Jurassic formations within the C36 3D Prospect located in the Central Depression of the Junggar Basin are important to hydrocarbon accumulation. However, the geometry of strike-slip faults and their relationship with hydrocarbon accumulation are inadequately understood. The present study highlights these strike-slip faults using 3D seismic data from the C36 3D Prospect. Several conditioning approaches have enabled enhanced imaging of the strike-slip faults using computed hybrid attributes. They are based on implementing a dip-steering cube extracted from the original seismic data, along with analyses of multiple seismic attributes and a supervised neural network. Analysis of the hybrid attributes reveals the development of isolated, soft-linked, hard-linked, and coalesced faults along an approximately NE-SW trend. Various types of interactions were observed between the upper and lower fault systems. The different types of vertical linkages between the strike-slip faults provide hydrocarbon migration paths and thus, contribute differently to hydrocarbon migration.

Building a model of flight accident scenario and quantitatively assessing flight risk are of great significance in improving system design and guiding aircraft's using. In view of the deficiency of traditional Probabilistic Risk Assessment (PRA), an evolution model of flight accident scenario is established based on Bow-Tie, and flight risk is evaluated based on Bayesian Networks. Taking engine shutdown in flight for an aircraft as an example, simulation results show that the method proposed can sort weak parts of flight safety system, and provide basis for system improvement. Comparing with traditional method, Bayesian Networks is more suitable for modeling of complex system and easy in calculation. So rationality of the method proposed above is validated.

The dynamics of wealth distribution plays a critical role in the economic market, hence an understanding of its nonequilibrium statistical mechanics is of great importance to human society. For this aim, a simple and efficient one-dimensional (1D) lattice gas automaton (LGA) is presented for wealth distribution of agents with or without saving propensity. The LGA comprises two stages, i.e., random propagation and economic transaction. During the former phase, an agent either remains motionless or travels to one of its neighboring empty sites with a certain probability. In the subsequent procedure, an economic transaction takes place between a pair of neighboring agents randomly. It requires at least 4 neighbors to present correct simulation results. The LGA reduces to the simplest model with only random economic transaction if all agents are neighbors and no empty sites exist. The 1D-LGA has a higher computational efficiency than the 2D-LGA and the famous Chakraborti–Chakrabarti economic model. Finally, the LGA is validated with two benchmarks, i.e., the wealth distributions of individual agents and dual-earner families. With the increasing saving fraction, both the Gini coefficient and Kolkata index (for individual agents or two-earner families) reduce, while the deviation degree (defined to measure the difference between the probability distributions with and without saving propensities) increases. It is demonstrated that the wealth distribution is changed significantly by the saving propensity which alleviates wealth inequality.

Aviation safety has been an eternal theme since aircraft is invented, and safety risk assessment is taken as the important method to evaluate the aircraft safety, but it is usually difficult to compute and compare because the aviation risk is often composite, discontinuous and difficult to quantitative. To overcome these drawbacks, a new aircraft safety index under uncertainty conditions is proposed after the definition of aircraft safety was suggested based on the safety concept. After that, the safety performance function under given accident severity was provided through analyzing and describing uncertain factors of the aviation action. Combing with the application of Bow-tie model in the aviation accident fields, the flowchart and solution are suggested to compute the proposed aircraft safety index. Finally, taking the tire burst accident as an example, the feasibility of the proposed index and property of the solution are testified.

Cholesterol is an essential ingredient in mammals, and serum cholesterol is a major component of atherosclerotic plaques. The level of cholesterol in human serum has become an important index for clinical diagnosis and prevention of cardiovascular disease. In this paper, a simple and ultrasensitive cholesterol biosensor based on graphene oxide (GO) and gold nanoparticles (Au NPs) co-mediated enzymatic silver deposition was designed by immobilizing cholesterol oxidase (CHOD), cholesterol esterase (CHER) and GO onto the surface of Au NPs modified screen-printed carbon electrode (SPE). Under the synergistic effect of CHER, CHOD and GO, the cholesterol was hydrolyzed to generate hydrogen peroxide, which can reduce the silver (Ag) ions in the solution to metallic Ag which deposited on the surface of Au NPs modified SPE. The ultrasensitive detection of cholesterol was achieved by anodic stripping voltammetry measurement of the enzymatically deposited Ag. Under optimal conditions, the anodic stripping peak current of Ag increased with the increasing cholesterol concentration in the range from 0.01μg/mL to 5000μg/mL with a limit of detection of 0.001μg/mL (S/N = 3). In addition, the ultrasensitive cholesterol biosensor exhibited higher specificity, acceptable reproducibility and excellent recoveries for cholesterol detection.

With the rapid growth of Internet services in smart cities, large network flow has caused network congestion among users, thereby deteriorating network service quality and user experience. In this study, a distributed proxy cache management platform based on autonomous decision is proposed. The platform realizes highly efficient automatic cache management by taking the advantages of autonomous perception and decision. First, the platform establishes the autonomous management framework of proxy cache on the basis of the idea of feedback loop. Next, the URL is distributed evenly among cache nodes through the hash ring storage mechanism with virtual nodes. Cache status adjustment strategies are made based on historical status sequences and the gray prediction model. A method that is used to predict content hot-rank based on domain name set is proposed to reduce loads of cache nodes. Second, the platform designs a distributed proxy cache management system by depending on the autonomous management framework of proxy cache and the cache management mechanism of autonomous decision, and the Cache Hot Spots Migrate algorithm is suggested for the dynamic migration and integration of virtual nodes on the hash ring. A system knowledge base is established through status sequence and corresponding adjustment strategies. Finally, experimental results on the hash ring, content hot-rank prediction, and adjustment of autonomous decision of cache status are analyzed, thereby confirming that the distributed proxy cache management mechanism based on autonomous decision could manage cache nodes effectively and automatically, and could improve the overall performance of the system.

In this study, a Fe3O4@Au-based pseudo-homogeneous electrochemical immunosensor was prepared for detection of alpha fetoprotein (AFP), a well-known hepatocellular carcinoma biomarker. The primary antibody (Ab1) was immobilized on Fe3O4@Au NPs as the capture probe. Horseradish peroxidase (HRP) and secondary antibody (Ab2) were conjugated on gold nanoparticles (GNPs) through electrostatic adsorption to form signal-amplifying labels. In the presence of AFP, a sandwich immunocomplex was formed via specific recognition of antigen-antibody in a Fe3O4@Au-basedpseudo-homogeneousreaction system. After the immunocomplex was captured to the surface of magnetic glassy carbon electrode (MGCE), the labeling HRP catalyzed the decomposition of H2O2, resulting in a substantial current for the quantitative detection of AFP. The amperometric (i-t) method was employed to record the response signal of the immunosensor based on the catalysis of the immobilized HRP toward the reduction of H2O2 with hydroquinone (HQ) as the redox mediator. Under the optimal conditions, the amperometric current response presented a linear relationship with AFP concentration over the range of 20 ng/mL-100 ng/mLwith a correlation coefficient of 0.9940, and the detection limit was 0.64 ng/mL at signal/noise [S/N] = 3. Moreover, the electrochemical immunosensor exhibited higher anti-interference ability, acceptable reproducibility and long-term stability for AFP detection.

Chalcone synthases (CHS, EC 2.3.1.74) are key enzymes that catalyze the first committed step in flavonoid biosynthesis. In this study, we isolated a chalcone synthase, named NtCHS6, from Nicotiana tabacum. This synthase shared high homology with the NSCHSL (Y14507) gene and contained most of the conserved active sites that are in CHS proteins. The phylogenetic analysis suggested that NtCHS6 protein shared a large genetic distance with other Solanaceae CHS proteins and was the most closely-related to an uncharacterized CHS from Solanum lycopersicum. The expression analysis indicated that NtCHS6 was abundantly expressed in leaves, especially in mature leaves. By scrutinizing its upstream promoter sequences, multiple cis-regulatory elements involved in light and drought responsive were detected. Furthermore, NtCHS6 expression decreased significantly under dark treatment and increased significantly under drought stress. Our results suggested that NtCHS6 expression exhibited both light responsiveness and drought responsiveness, and might play important roles in ultraviolet protection and drought tolerance.

In this study, a light-addressable potentiometric sensor (LAPS) based on gold nanoparticles (AuNPs) enhancing enzymatic silver (Ag) deposition was developed for 1,5-anhydroglucitol (1,5-AG) determination. The pyranose oxidase enzyme (PROD), immobilized on the surface of AuNPs modified LAPS chip, could catalyze the hydrolysis of 1,5-AG and produce a reductive product H2O2 that enhanced the deposition of Ag. When a bias voltage was provided to the LAPS, a photocurrent which depended on the concentration of 1, 5-AG can be generated. Because the concentration of Ag ions in the electrolyte solution decreased with the deposition of metallic Ag on the surface of AuNPs modified LAPS chip, the potential shift (ΔV) has originated from local surface potential changes and reflected the changes of 1,5-AG concentration. The linear relationship between ΔV and 1,5-AG concentration were very well over the range from 60 μg/mL to 225 μg/mL with a correlation coefficient of 0.9977. The limit of detection was 40 μg/mL at signal/noise [S/N] = 3. In addition, LAPS detection system also showed higher specificity, acceptable stability and excellent recovery for 1, 5-AG detection.

The effect of InSb/In0.9Al0.1Sb buffer layers on InSb thin films grown on GaAs (0 0 1) substrate by molecular beam epitaxy (MBE) is investigated. The crystal quality and the surface morphology of InSb are characterized by XRD and AFM. The carrier transport property is researched through variable temperature hall test. The sharp interface between InSb/In0.9Al0.1Sb is demonstrated important for the high quality InSb thin film. We try different superlattice buffer layers by changing ratios, 2–0.5, thickness, 300–450 nm, and periods, 20–50. According to the function of the dislocation density to the absolute temperature below 150 K with different periods of SL buffers, we can find that the number of periods of superlattice is a major factor to decrease the density of threading dislocations. With the 50 periods SL buffer layer, the electron mobility of InSb at the room temperature and liquid nitrogen cooling temperature is ∼63,000 and ∼4600 cm2/V s, respectively. We deduce that the interface in the SL structure works as a filter layer to prevent the dislocation propagating to the upper InSb thin films.

The mixing performance of a multi-bladed baffle inserted into a traditional Gallay tote blender is explored by graphic processing unit-based discrete element method software. The mixing patterns and rates are investigated for a binary mixture, represented by two different colors, under several loading profiles. The baffle effectively enhances the convective mixing both in the axial and radial directions, because of the disturbance it causes to the initial flowing layer and solid-body zone, compared with a blender without a baffle. The axial mixing rate is affected by the gap between the baffle and the wall on the left and right sides, and an optimal blade length corresponds to the maximum mixing rate. However, the radial mixing rate increases with the blade length almost monotonically.