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The in situ formation of SiC in Al–40Si alloys during the fabrication of SiC/Al–Si composites by high-pressure solidification were investigated. The results demonstrate that the in situ formation of SiC occurs by a gradual conversion of Al4C3 and Al4SiC4 to SiC. In situ SiC can be formed in an Al–40Si alloy solidified under a pressure of 3 GPa at a temperature of 1373 K. The SiC particles (SiCp) formed in situ was compatible with the α-Al matrix and the Si phases. The relative density of the SiC/Al-38.6Si composite was 99.9%. The bending strengths of the Al–40Si alloy and the SiC/Al-38.6Si composite obtained by solidification under a pressure of 3 GPa were 200.8 MPa and 322 MPa, respectively, which represents an enhancement of 60.3% as a result of reinforcement by the in situ-formed SiC.

Interference is an important factor affecting railway mobile communications, which leads to deterioration of communication quality. In serious cases, the link connection interruption will lead to degraded operation of train control system, then affect the operation efficiency of the railway system. In order to reduce the impact of interference on railway communications, the interference source should be localized and eliminated timely. However, the traditional interference localization methods require auxiliary equipment to be arranged along the track. In this paper, a data driven interference source localization method based on train real-time onboard interference monitoring is proposed, which can reduce the interference localization cost. Based on the collected Received Signal Strength (RSS) of interference signal, the particle filter principle is used to locate the target interference source combined with the data driven path-loss models. Besides, the modified whale optimization algorithm (MWOA) is introduced to further improve the positioning accuracy. The simulation and experiment results show that the proposed data driven interference source localization method outperforms the traditional localization method, and the positioning accuracy is improved from tens of meters degree to meters degree, which can meet the requirements of engineering practice to find the interference source.

Aims The use of 3D-printed titanium implant (DT) can effectively guide bone regeneration. DT triggers a continuous host immune reaction, including macrophage type 1 polarization, that resists osseointegration. Interleukin 4 (IL4) is a specific cytokine modulating osteogenic capability that switches macrophage polarization type 1 to type 2, and this switch favours bone regeneration. Methods IL4 at concentrations of 0, 30, and 100 ng/ml was used at day 3 to create a biomimetic environment for bone marrow mesenchymal stromal cell (BMMSC) osteogenesis and macrophage polarization on the DT. The osteogenic and immune responses of BMMSCs and macrophages were evaluated respectively. Results DT plus 30 ng/ml of IL4 (DT + 30 IL4) from day 3 to day 7 significantly (p < 0.01) enhanced macrophage type 2 polarization and BMMSC osteogenesis compared with the other groups. Local injection of IL4 enhanced new bone formation surrounding the DT. Conclusion DT + 30 IL4 may switch macrophage polarization at the appropriate timepoints to promote bone regeneration. Cite this article: Bone Joint Res 2021;10(7):411–424.

PurposeFollowing the hierarchy-of-effects model, this study aims to propose a two-step process framework to investigate social media post efficacy via attraction and likes.Design/methodology/approachThe study analyzes 113,785 social media posts from 126 WeChat official accounts to explore how external (headline features and account type) and internal (content features and media type) features impact social media post attractions and likes, respectively.FindingsThe antecedents of post attraction differ from those of post likes. First, headline features (punctuation, length, sentiment and lexical density) and account type significantly influence social media post attraction. Second, content features (depth, tone, domain specificity, lexical density and readability) and media type affect social media post likes.Originality/valueFirst, this study considers online user engagement as a two-step process regarding social media posts and explores different influencing factors. Second, the study constructs new variables (account type and domain specificity) in each stage of the two-step process model.

Remaining useful life (RUL) is a crucial indictor to measure the performance degradation of machine tools. It directly affects the accuracy of maintenance decision-making, thus affecting operational reliability of machine tools. Currently, most RUL prediction methods are for the parts. However, due to the interaction among the parts, even RUL of all the parts cannot reflect the real RUL of the whole machine. Therefore, an RUL prediction method for the whole machine is needed. To predict RUL of the whole machine, this paper proposes an RUL prediction method with dynamic prediction objects based on meta-action theory. Firstly, machine tools are decomposed into the meta-action unit chains (MUCs) to obtain suitable prediction objects. Secondly, the machining precision unqualified rate (MPUR) control chart is used to conduct an out of control early warning for machine tools’ performance. At last, the Markov model is introduced to determine the prediction objects in next prediction and the Wiener degradation model is established to predict RUL of machine tools. According to the practical application, feasibility and effectiveness of the method is proved.

The structures, equations of state, phase transitions, mechanical stability, and elastic anisotropies of five SiC polymorphs (wurtzite, 4H, 6H, zinc blende, and rocksalt phases) under pressure were investigated based on first-principles calculations. The optimal structural parameters, densities, and volumes of the five SiC polymorphs under zero and high pressure were obtained and analyzed. The pressures of the phase and stability–instability transitions were predicted using the minimum energy principle and improved Born mechanical stability criteria, respectively, and a new phase transition criterion was developed. The elastic anisotropies of SiC under zero and high pressure were systematically discussed, and the negative Poisson's ratio of zinc blende SiC was verified.

We consider the problem of user activity detection for grant-free massive connectivity, where a base station, equipped with a large number of antennas, serves a large number of machine type devices. Two massive multiple-input multiple-output (mMIMO) systems are studied, namely, a collocated mMIMO with physically collocated antennas and a cell-free mMIMO with geographically separated antennas. By utilizing the sporadic transmission nature and the asymptotical orthogonality of channel vectors associated with different users, we propose a correlation-based sparse signal recovery scheme to detect active users. Simulation results are provided to evaluate the performance of the proposed method. Our results show that the cell-free mMIMO achieves much better user activity detection performance than the collocated mMIMO, and thus is more suitable for grant-free massive connectivity. An empirical analysis is performed to explain the superiority of the cell-free system over the collocated system.

Capsaicin (CAP) is the main pungent component in capsicum fruits. Eating too much CAP leads to gastrointestinal injury. Previously, Qingke β-glucan combined with β-glucan-utilizing Lactobacillus plantarum S58 (LP.S58) ameliorated high fat-diet-induced obesity, but their effects on CAP-induced gastrointestinal injury have not been investigated. Our results showed that Qingke β-glucan reduced the CAP-induced gastrointestinal injury in Kunming mice. The serum levels of inflammatory cytokines and gastrointestinal hormones, and the localized inflammation and the expression of EGF, EGFR, VEGF, and ZO-1 in the gastrointestinal tissues in CAP-treated mice were partly restored by Qingke β-glucan. The CAP-induced increase in the abundances of proinflammatory intestinal bacteria was also reduced by Qingke β-glucan. More importantly, we found that these beneficial effects of Qingke β-glucan were markedly enhanced by β-glucan-utilizing LP.S58 supplementation. Our study indicated that Qingke β-glucan coupled with β-glucan-utilizing LP.S58 relieved CAP-induced gastrointestinal injury.

A novel feature extraction method based on the energy cumulant of Choi-Williams distribution has been proposed, which copes with the complex electromagnetic environment and varied signal styles. The energy cumulant of Choi-Williams distribution has been calculated from the accumulations of each frequency sample value with different time samples. Preceding this procedure, the time frequency distribution via Choi-Williams distribution has been processed through base noise reduction. Henceforth, a simulation analysis based on the discriminability and recognition effect of the proposed features in a low SNR environment has been carried out. In the discriminability experiment, the kernel fuzzy C-means clustering algorithm has been employed for classifying the radar pulse modulated radiation source signals. In the recognition effect analysis, the deep belief network has been proposed to employ the input feature vectors for training to achieve the radar emitter recognition and classification. Simulation results demonstrate that the proposed feature extraction method is feasible and robust in radar emitter classification and recognition even at a low SNR.

In order to further improve the braking performance of the nonlinear antilock braking system (ABS), an improved global sliding mode control scheme is presented. First, a nonlinear global sliding mode surface is designed. The method can eliminate the reaching phase compared with conventional linear sliding mode surface, and guarantee the system robustness during the whole control process. Then, a novel control law is proposed to satisfy the sliding mode reaching condition, and the theoretical proof is given. Simulation results demonstrate that the proposed global sliding mode control scheme enables the wheel slip-ratio to converge to optimal value quickly with the small oscillation, and has relatively short braking distance and braking time, which is very suitable to prevent the wheel from being locked during braking. The proposed global sliding mode control scheme is verified by joint simulation using MATLAB and CarSim, and shows good braking performance when the car is driving under extreme road conditions, which indicates the effectiveness of the proposed sliding mode control scheme.

Many recent examples have shown that rockfalls can occur in underground steep coal mines. The stratigraphic circumstances, block formation mechanism, and cumulative damage effects of rockfalls in the longwalls of a steeply dipping coal seam (SDCS) make them detrimental to workplace safety. Therefore, this study examined an approach for mitigating rockfall hazards in SDCSs. A passive mesh system was installed to prevent the propagation of rockfalls, which decreased the number of collisions between the falling rocks and mining equipment. The interactions of the falling rocks and passive mesh were studied using a series of full-scale numerical impact tests. The following conclusions could be drawn. The displacement of the mesh increased with the rockfall kinetic energy, showing the characteristic of strain hardening. The peak stress appeared near the contact area between the rockfall and mesh, and it spread to the mesh edge in an X-shaped pattern. Stress concentrations were likely to occur in areas that were in direct contact with the mesh and mesh edges. The displacement of the mesh increased when the incidence angle increased, and the number of mesh cells entering the plastic state increased significantly. The internal energy ratio increased with an increase in the incidence angle, indicating that a greater incidence angle led to a larger amount of kinetic energy being transferred from the block into the internal energy of the passive mesh. Finally, the method was verified by comparing the numerical test with the on-site damaged equipment. The high replacement frequency of a passive mesh system and the annual fatality rate in the longwalls of SDCS were significantly improved. This study provided the design for a drapery mesh system for rockfall disaster prevention, particularly the mitigation of rockfall hazard risks in underground SDCSs.

Nerve cells differentiated from embryonic stem cells (ESCs) play an important role in the treatment of neurodegenerative diseases. Heparin has great potential for inducing ESCs to differentiate into nerve cells, but due to the shortcomings of heparin itself, its effect on inducing differentiation of ESCs is limited. In this study, the thermosensitive copolymer pNIPAAm-b-p(MAG-co-SPA) (pNMS) was synthesized with N-isopropylacrylamide (NIPAAm) as monomer and heparin mimic p(MAG-co-SPA) (pMS) as macromolecular chain transfer agent. Considering the biocompatibility of AuNPs, the nanocomposites were prepared, and their effects on inducing differentiation of ESCs were studied in detail. Compared to heparin, nanocomposites have a stronger effect on the differentiation of ESCs, especially AuNPs–pNMS, which can better promote the expression of β3-tubulin and stimulate the synthesis of proteins required for neuronal maturation. The results show that AuNPs–pNMS has a stronger ability to induce differentiation than AuNPs–pMS due to the presence of the pNIPAAm segment. The synergistic effect of pNIPAAm and pMS in AuNPs–pNMS greatly increases the efficiency of nanocomposite binding to FGFR, further enhancing the effect of the neural differentiation of ESCs. The effect of AuNPs–pNMS in promoting the differentiation of ESCs is also related to the relative molecular weight of pNMS. Under the premise of controlling the relative molecular weight of pMS to be 8900 Da, when the molecular weight of pNMS is 28 100 Da, AuNPs–pNMS has the strongest effect of promoting neural differentiation of ESCs. This thermosensitive nanocomposite provides a new strategy for promoting the neural differentiation of ESCs.

This paper presents a dynamic reliability analysis method of rolling linear guide considering the uncertainty of geometric parameters. A three degree of freedom (DOF) dynamic motion model of rolling linear guide that considers the complexity of the actual load is established. In order to improve the accuracy of reliability evaluation, interval model is used to express the uncertainty of geometric parameters. The reliability range of dynamic response is determined according to the accuracy grade of rolling linear guide. The interval reliability calculation method is used to analyze and calculate the horizontal and vertical dynamic reliability of rolling linear guide. Then, the comprehensive dynamic reliability of rolling linear guide is obtained. Finally, the dynamic reliability of the SHS-45R rolling linear guide is analyzed by using the reliability evaluation method described in this paper. And the validity and accuracy of the result is demonstrated by comparing with the Monte Carlo simulation.

Purpose This paper aims to enable the robot to obtain human-like compliant manipulation skills for the peg-in-hole (PiH) assembly task by learning from demonstration. Design/methodology/approach A modified dynamic movement primitives (DMPs) model with a novel hybrid force/position feedback in Cartesian space for the robotic PiH problem is proposed by learning from demonstration. To ensure a compliant interaction during the PiH insertion process, a Cartesian impedance control approach is used to track the trajectory generated by the modified DMPs. Findings The modified DMPs allow the robot to imitate the trajectory of demonstration efficiently and to generate a smoother trajectory. By taking advantage of force feedback, the robot shows compliant behavior and could adjust its pose actively to avoid a jam. This feedback mechanism significantly improves the dynamic performance of the interactive process. Both the simulation and the PiH experimental results show the feasibility and effectiveness of the proposed model. Originality/value The trajectory and the compliant manipulation skill of the human operator can be learned simultaneously by the new model. This method adopted a modified DMPs model in Cartesian space to generate a trajectory with a lower speed at the beginning of the motion, which can reduce the magnitude of the contact force.

PurposeThis paper aims to explore the information needs and information-seeking behaviours of the new generation of engineering designers. A survey study is used to approach what their information needs are, how these needs change during an engineering design project and how their information-seeking behaviours have been influenced by the newly developed information technologies (ITs). Through an in-depth analysis of the survey results, the key functions have been identified for the next-generation management systems.Design/methodology/approachThe paper first proposed four hypotheses on the information needs and information-seeking behaviours of young engineers. Then, a survey study was undertaken to understand their information usage in terms of the information needs and information-seeking behaviours during a complete engineering design process. Through analysing the survey results, several findings were obtained and on this basis, further comparisons were made to discuss and evaluate the hypotheses.FindingsThe paper has revealed that the engineering designers' information needs will evolve throughout the engineering design project; thus, they should be assisted at several different levels. Although they intend to search information and knowledge on know-what and know-how, what they really require is the know-why knowledge in order to help them complete design tasks. Also, the paper has shown how the newly developed ITs and web-based applications have influenced the engineers' information-seeking practices.Research limitations/implicationsThe research subjects chosen in this study are engineering students in universities who, although not as experienced as engineers in companies, do go through a complete design process with the tasks similar to industrial scenarios. In addition, the focus of this study is to understand the information-seeking behaviours of a new generation of design engineers, so that the development of next-generation information and knowledge management systems can be well informed. In this sense, the results obtained do reveal some new knowledge about the information-seeking behaviours during a general design process.Practical implicationsThis paper first identifies the information needs and information-seeking behaviours of the new generation of engineering designers. On this basis, the varied ways to meet these needs and behaviours are discussed and elaborated. This intends to provide the key characteristics for the development of the next-generation knowledge management system for engineering design projects.Originality/valueThis paper proposes a novel means of exploring the future engineers' information needs and information-seeking behaviours in a collaborative working environment. It also characterises the key features and functions for the next generation of knowledge management systems for engineering design.

Liquid–liquid equilibrium (LLE) data of the ternary system 2-methyl-2-butanol + water + o-xylene were determined at 303.2, 313.2, and 323.2 K under 101.3 kPa. The extraction capacity of o-xylene is...

The studying motivation of this paper is that there exist many modeling issues of non-uniformly sampling nonlinear systems in industrial systems. Based on multi-model modeling principle, the corresponding model of non-uniformly sampling nonlinear systems is described by the nonlinear weighted combination of some linear models at local working points. Fuzzy modeling based on multimodel scheme is a common method to describe the dynamic process of non-linear systems. In this paper, the fuzzy modeling method of non-uniformly sampling nonlinear systems is studied. The premise structure of the fuzzy model is confirmed by GK fuzzy clustering, and the conclusion parameters of the fuzzy model are estimated by the recursive least squared algorithm. The convergence perfromance of the proposed identification algorithm is given by using lemmas and martingale theorem. Finally, the simulation example is given to demonstrate the effectiveness of the proposed method.

Most existing fault diagnosis methods may fail in the following three scenarios: (1) serial correlations exist in the process data; (2) fault data are much less than normal data; and (3) it is impractical to obtain enough labeled data. In this paper, a novel form of the bidirectional gated recurrent unit (BGRU) is developed to underpin effective and efficient fault diagnosis using cost sensitive active learning. Specifically, BGRU is devised to consider the dynamic behavior of a complex process. In the training phase of BGRU, the idea of weighting each training example is proposed to reduce the effect of class imbalance. Besides, in order to explore the unlabeled data, cost sensitive active learning is utilized to select the candidate instances. The effectiveness of the proposed method is evaluated on the Tennessee Eastman (TE) dataset and a real plasma etching process dataset. The experiment results show that the proposed cost senstive active learning bidirectional gated recurrent unit (CSALBGRU) method achieves better performance in both binary fault diagnosis and multi-class fault diagnosis.

The effect of Ni content on the microstructure and mechanical properties at elevated temperature of cast Al–2.5Li–1Cu–1.5Mg–xNi alloys (x = 0, 0.2, 0.4 and 0.8 wt.%) was investigated. The results showed that the main Ni-rich phase in alloys with 0.2 and 0.4Ni addition is Al3Ni, while the Al3CuNi intermetallic compounds appear in 0.8Ni alloy. The decrease of amount of solid-solution Cu atoms in matrix, due to Cu-rich phase precipitates adhere on the Ni-containing second particles, would suppress the formation or growth of Precipitations Free Zones (PFZs) is a noteworthy phenomenon. Moreover, 0.2Ni alloy showed the optimization mechanical properties (YS: 322 ± 23 MPa, UTS: 397 ± 7.7 MPa, Elongation: 7.8 ± 1.3%) at 25 °C. With the Ni content increases to 0.8 wt.%, the ultimate tensile strength increased by ∼12.6 % and ∼15.4 % compared with the base alloy at 200 and 300 °C, respectively. With test temperature increasing, the evolution of the fracture mode is as followed: intergranular/quasi-cleavage brittle fracture mode → mixing of brittle and ductile fracture mode → voids coalescence fracture mode, corresponding to 25, 200 and 300 °C.

By-product synergy (BPS) is an innovative method to dispose of waste and create value from waste. We examine a supply chain composed of two competing manufacturers and one downstream processing plant with limited BPS capacity. The plant generates a by-product with waste from manufacturers and sells the by-product in a market with uncertain prices. We derive each manufacturer’s equilibrium decisions (production quantity and disposal amount) and the plant’s capacity investment plan (ex ante) and optimal transfer price (ex post). We show that BPS always benefits manufacturers, and although two opposite effects (competition effect and cost saving effect) appear, each manufacturer’s profit in limited BPS capacity is always lower than that in infinite BPS capacity. The reason is that the plant has the power to determine the transfer price and manufacturers prefer highest cost saving (enough BPS capacity) at the expense of highest competition effect. The effects of BPS technology parameters (i.e., processing cost of waste and investment cost of capacity) on supply chain performance are also discussed. Finally, we further explore the scenario that the plant determines the transfer price before the by-product’s price uncertainty is realized.

The corrosion behavior of two types of low-carbon steel (denoted steel A and steel B) in H2S/CO2 was investigated through immersion tests, and the effect of Ti microalloying on the corrosion mechanism was analyzed. The microstructures, corrosion kinetics, corrosion surface morphologies, corrosion phases, cross-sectional morphologies and elemental distributions of the materials were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), electron backscatter diffraction (EBSD), energy-dispersive spectroscopy (EDS), x-ray diffraction (XRD) and electron probe microanalysis (EPMA). The results showed that the corrosion rate of steel B with Ti microalloying was lower than that of steel A; the amount and formation rate of corrosion products in these two materials were different. As the immersion time increased, the corrosion products changed from iron-rich mackinawite to sulfur-rich pyrrhotite. In the early stage of corrosion, the corrosion products were primarily mackinawite, which controlled the corrosion phase through the entire process. After 384 h of immersion, pyrrhotite was observed, which can effectively protect the steel substrate, providing excellent corrosion resistance. The corrosion products in steel B with Ti microalloying were more compact than those in steel A. Moreover, Ti enrichment in the oxide film was observed in steel B, which can further improve its corrosion resistance. The results from this study can provide an important reference for the oil and gas industry.

PurposeIn shield tunneling projects, human, shield machine and underground environment are tightly coupled and interacted. Accidents often occur under dysfunctional interactions among them. Therefore, this paper aims to develop a multi-agent based safety computational experiment system (SCES) and use it to identify the main influential factors of various aspects of human, shield machine and underground environment.Design/methodology/approachThe methods mainly comprised computational experiments and multi-agent technologies. First, a safety model with human-machine-environment interaction consideration is developed through the multi-agent technologies. On this basis, SCES is implemented. Then computational experiments are designed and performed on SCES for analyzing safety performance and identifying the main influential factors.FindingsThe main influential factors of two common accidents are identified. For surface settlement, the main influential factors are ranked as experience, soil density, soil cohesion, screw conveyor speed and thrust force in descending order of influence levels; for mud cake on cutter, they are ranked as soil cohesion, experience, cutter speed and screw conveyor speed. These results are consistent with intuition and previous studies and demonstrate the applicability of SCES.Practical implicationsThe proposed SCES provides comprehensive risk factor identification for shield tunneling projects and also insights to support informed decisions for safety management.Originality/valueA safety model with human-machine-environment interaction consideration is developed and computational experiments are used to analyze the safety performance. The novel method and model could contribute to system-based safety research and promote systematic understanding of the safety performance of shield tunneling projects.

PurposeGrounded on the cognition–affect–conation (C–A–C) framework, this study aims to explore how perceived information overload affects the information avoidance intention of social media users through fatigue, frustration and dissatisfaction.Design/methodology/approach/methodology/approachA quantitative research design is adopted. The data collected from 254 respondents in China are analyzed via structural equation modeling (SEM).FindingsPerceived information overload directly affects fatigue, frustration and dissatisfaction among social media users, thereby affecting their information avoidance intention. In addition, frustration significantly affects social media fatigue and dissatisfaction. Consequently, social media fatigue influences dissatisfaction among users.Originality/valueThe literature review indicates that social media overload and fatigue yield negative behavioral outcomes, including discontinuance. However, rather than completely abstaining or escaping, social media users adopt moderate strategies, including information avoidance, to cope with overload and fatigue owing to their high dependence on social media. Unfortunately, merely few studies are available on the information avoidance behavior of social media users. Focusing on this line of research, the current study develops a model to investigate the antecedents of information avoidance in social media.

Drones are increasingly used to deliver packages with high efficiency in several areas. We study a multi-warehouse drone delivery system, considering the allocation rule that all warehouses share t...

Subwavelength structures such as subwavelength gratings (SWGs) and subwavelength metamaterials are capable of tailoring the optical properties of materials and controlling the flow of light at the nanoscale. The effective indices of the subwavelength structured strip and slab waveguides can be changed in a wide range by choosing an appropriate duty cycle or a filling factor of silicon, which provides an effective method to manipulate the optical field and achieve effective index matching for functional devices. Recent advances in nanofabrication techniques have made it possible to implement subwavelength structures in silicon strip and slab waveguides. Here we review various approaches used to design subwavelength structures and achieve exotic optical responses and discuss how these structures can be used to realize high-performance silicon photonic devices. Both one-dimensional SWG devices and two-dimensional subwavelength metamaterial devices are covered in this review, including subwavelength structure–based polarization handling devices, mode manipulation devices, and building blocks for integrated optical interconnects. Perspectives on subwavelength structured silicon photonic devices are also discussed.

In recent years, the inverse design of artificial materials, in the format of thin-films and superlattices, has been an active sub-field in material science. From a joint effort from both experiment and theory, scientists are searching for new engineering methods or design rules so that the materials can be custom designed with desired functionalities in theory before the materials are actually synthesized by epitaxial growth technique in laboratory. In this article, we provide a short summary of the recently proposed epitaxial strain and interface design approaches for the functional artificial oxide heterostructures. The underlying physical mechanism enabling the enhanced functional properties, such as ferroelectricity and multiferroics, are briefly reviewed. In particular, focused discussions are made on the proper treatments of both mechanical and electric boundary conditions when the oxide thin-films and superlattices are theoretically modeled by first-principles computer simulations.

We consider the robust filtering problem for a nonlinear state-space model with outliers in measurements. To improve the robustness of the traditional Kalman filtering algorithm, we propose in this work two robust filters based on mixture correntropy, especially the double-Gaussian mixture correntropy and Laplace-Gaussian mixture correntropy. We have formulated the robust filtering problem by adopting the mixture correntropy induced cost to replace the quadratic one in the conventional Kalman filter for measurement fitting errors. In addition, a tradeoff weight coefficient is introduced to make sure the proposed approaches can provide reasonable state estimates in scenarios where measurement fitting errors are small. The formulated robust filtering problems are iteratively solved by utilizing the cubature Kalman filtering framework with a reweighted measurement covariance. Numerical results show that the proposed methods can achieve a performance improvement over existing robust solutions.

There is increasing demand for the large overhang toolholder to machine certain workpieces with complex cavities during milling operation, but this kind of toolholder may bring an undesired source of chatter. This paper develops a novel toolholder with high dynamic performance to suppress chatter. Firstly, the dynamics of the milling cutter are investigated according to the cantilever beam theory. The obtained analysis result shows that the increasing stiffness and damping ratio can effectively reduce the vibration amplitude; based on this finding, a novel toolholder is developed through embedding the strips and damping core into the toolholder body. Subsequently, the dynamic characteristic of the novel toolholder is studied qualitatively by the complex number method, and its geometrical parameters are optimized by the finite element method. Finally, modal tests and milling experiments are conducted to verify the chatter stability improvement of the novel toolholder. The experimental results demonstrate that the chatter stability of the developed toolholder is enhanced significantly.

Kinematics simulation is central to the control of serial manipulators in human machine interaction, which highly depends upon computational efficiency and accuracy for the sake of enabling real-time analysis and interaction. In this paper, a novel learning-based multiscale modelling approach is proposed to effectively address the efficiency and accuracy trade-offs through a combination of models with different levels of fidelity. Specifically, low-fidelity models are formulated using Kernel Ridge Regression (KRR) to achieve much lower computational cost as its kinematic approximation. Additionally, high-fidelity models are created based on the Long Short Term Memory (LSTM) neural network, which can calibrate fidelity by training the significant samples and eliminate position singularity of a serial manupulator. The proposed approach is evaluated both by using numerical tests and by applying it to a collaborative industrial robot arm. The experimental results obtained demonstrate that it can achieve better performance in terms of both accuracy and efficiency compared with the other popular methods.

By hetero-valence substituting Ba2+-Si4+ for Lu3+-Al3+ pair in Lu3Al5O12: Ce3+, a new green phosphor Ba1.5Lu1.5Al3.5Si1.5O12: Ce3+ (BLAS: Ce3+) has been obtained. It crystallizes in garnet structure with space group Ia-3d (230). In the structure, Ba2+ ions are incorporated into both dodecahedral Lu3+ and octahedral Al3+ sites while Si4+ ions only occupy tetrahedral Al3+ sites. Under the blue light irradiation of 450 nm, an intense green light peaking at 520 nm was observed and the PL spectrum can be fitted in two Gaussian components, due to the crystal field splitting of Ce3+ 5d states under D2 symmetry constrains. The optical doping concentration of BLAS: Ce3+ is 6% mol, of which the IQE and EQE are 89.1% and 51.8%, respectively. Furthermore, this sample exhibits an extremely good thermal stability, i.e. the integrated emission intensity is still more than 90% of the initial intensity at 480 K. Then, a w-LED device was fabricated from this new green phosphor BLAS: Ce3+ and commercial red phosphor (Ca,Sr)AlSiN3: Eu2+, which shows a quite high color rendering (Ra = 88.2) and a relatively low color temperature 4772 K. Besides, the phosphor exhibits a stable chromaticity under different acceleration voltages. The phosphor may be promising material for the development of solid-state lighting and display systems.

Purpose As the transmission component of a locomotive, the traction gear pair system has a direct effect on the stability and reliability of the whole machine. This paper aims to provide a detailed dynamic analysis for the traction system under internal and external excitations by numerical simulation. Design/methodology/approach A non-linear dynamic model of locomotive traction gear pair system is proposed, where the comprehensive time-varying meshing stiffness is obtained through the Ishikawa formula method and verified by the energy method, and then the sliding friction excitation is analyzed based on the location of the contact line. Meantime, the adhesion torque is constructed as a function of the adhesion-slip feature between wheelset and rail. Through Runge–Kutta numerical method, the system responses are studied with varying bifurcation parameters consisting of exciting frequency, load fluctuation, gear backlash, error fluctuation and friction coefficient. The dynamic behaviors of the system are analyzed and discussed from bifurcation diagram, time history, spectrum plot, phase portrait, Poincaré map and three-dimensional frequency spectrum. Findings The analysis results reveal that as control parameters vary the system experiences complex transition among a diverse range of motion states such as one-periodic, multi-periodic and chaotic motions. Specifically, the significant difference in system bifurcation characteristics can be observed under different adhesion conditions. The suitable gear backlash and error fluctuation can avoid the chaotic motion, and thus, reduce the vibration amplitude of the system. Similarly, the increasing friction coefficient can also suppress the unstable state and improve the stability of the system. Originality/value The numerical results may provide a systemic understanding of dynamic characteristics and present some available information to design and optimize the transmission performance of the locomotive traction system.

The mutual information (MI) is used as the target function to jointly optimize the space trajectory and radiated power of the airborne MIMO radar. By adjusting the space position of the radar and radiating energy in real time, the detection efficiency of the MIMO radar is improved. Firstly, the cooperative detection model of aviation swarm MIMO radar is constructed to quantitatively describe the relationship between radar position and radiated power parameters and echo. Therefore, the MI between the transmitted signal and the received signal at the same time is derived, and the MI of the radar echo at the current time and the next time is derived. Maximizing the amount of MI sent and received signals can improve the amount of information detected, and minimizing the amount of MI at adjacent moments can improve the quality of information. This paper designs a time-sharing optimization algorithm, and improves the Artificial Bee Colony algorithm (ABC) to optimize the above two MI to achieve real-time adjustment of radar position and power. Through simulation verification and algorithm comparison, the advantages of this algorithm are reflected.

In this paper, we have introduced a compact eight-element antenna array for triple-band MIMO (multi-input multi-output) operation in 5G (fifth generation) mobile terminals, which consists of two symmetric four-element sub-arrays disposed, respectively, along two long side-edges of the system ground plane of the mobile terminal. This antenna element can operate at two dual-wideband of 3250-3820 MHz and 4790-6200 MHz with three resonance frequencies which can fully cover 5G NR (New Radio) BandN78 (3300-3800 MHz), China 5G-Band of 4800-5000 MHz and LTE Band-46 (5150-5925 MHz). The main parameters that characterize the performance of the proposed MIMO antenna system, such as bandwidth, reflection coefficient, isolation (more than 10.5 dB), total radiation efficiency (more than 43%), ECC (envelope correlation coefficient, less than 0.12) and CC (channel capacity, 34.9-37.6 bps/Hz), are analyzed and presented in this paper. Besides, the effects of single-hand and dual-hand on performance of the MIMO antenna system are also discussed. The structure of antenna element is only 15 mm × 3 mm (0.175 λ0 × 0.035 λ0, λ0 is the free-space wavelength at the frequency of 3.5 GHz) with a very small ground clearance of 13 mm × 2 mm on the main board of the proposed mobile terminal. The antenna system has the possibility to be used in 5G mobile terminals with triple-band operation, narrow frame and large display. The corresponding antennas prototype is fabricated and measured; and a quite good agreement between simulation and measurement is obtained.

Steeply inclined seams buried at dip angles of 35–55° are considered hard-excavated seams in the mining industry. A partial backfilling method based on sub-regional features of surrounding rock deformations and failure and support stability was proposed to realize safe, efficient production, to promote sustainable development of coal mining and disaster prevention in western China. Through experiments, calculations, and theoretical analysis, a mechanical model was established, and governing equations for the deflection curve, bending moment, and rotation were deduced. Results reveal the filling percentage, filling ratio, and working-face dip angle as major factors causing roof failure. The degree of roof deformation decreases with increasing filling percentage, filling ratio, and working-face dip angle. With an increase in filling percentage and filling ratio, the range and magnitude of the stress-concentration zone at a T-junction increase, whereas those pertaining to the stress-release zone in the roof decrease. The stress-arch profile of the roof changes from a single peak to double peaks with reduction arch height. Additionally, the maximum arch height shifts towards the centre with increasing moderation of asymmetric features of stress arches. With an increase in working-face dip angle, stress concentration at the coal-wall head T-junction decreases, and a double-peak stress arch develops. Therefore, in order to obtain the best backfill mining effect, a higher filling percentage is preferred; with a maximum filling value of 0.93, the reasonable range for the filling ratio is 1/3 to 1/2 and the reasonable dip angle of the working face is approximately 35°.

A physical simulation model is constructed to study the characteristics of fault displacement evolution at Yima mining area, Henan Province, China. The geological condition at Yima mining area is complicated with high in situ stress, reverse faults and extremely thick conglomerate rock strata. In this study, the fault movement process during extraction of a coal seam is simulated and the precursory information on the fault slip is investigated. The fault displacement and shear stress, as well as the fault slip location are monitored in the simulation using digital speckle image correlation method, shear stress sensors, and acoustic emission monitoring. The investigations reveal the following: a relatively long suspension prior to the sharp increase in acoustic emission events might be used as the precursory information on an impending fault slip; the combined effect of the fault slip and extremely thick conglomerate rock strata may induce coal bursts; the interaction zone of thick conglomerate rock strata and fault structure is a high-risk region that can induce fault slips.

Since computer numerical control machine tool is composed of multiple meta-action units to achieve one specific function, including the meta-action units' own quality, it still needs to control the coupling relationships among different meta-action units' quality characteristics to guarantee the whole machine's quality. In this article, a method of quality characteristic decoupling planning based on meta-action unit for computer numerical control machine tool was proposed. Firstly, the coupling constraint models based on meta-action unit were established. Secondly, the comprehensive coupling strengths of meta-action units were calculated and introduced into the design structure matrices. Thirdly, multidisciplinary design optimization method was adopted to obtain the optimized control sequence of different meta-action units' quality characteristics. What is more, automatic pallet changer rotary motion of computer numerical control machine tool was taken as an example to illustrate the rightness and effectiveness of this method.

Radio frequency (RF) estimation plays a significant role in cellular network’s planning and optimization. The conventional methods for RF estimation are mainly based on radio propagation models, which suffer from low accuracy and coarse granularity. Distinguished from existing methods, we propose sparsely self-supervised generative adversarial nets (SS-GAN), a novel data-driven model to generate the RF maps of an area from irregularly distributed measurement samples. SS-GAN meticulously adopts the standard GAN framework, where the generator learns the distribution of true observations under the guidance of the discriminator that discriminates whether the input data is from real samples or from generated outputs. Competition in the minmax game between generator and discriminator drives them to improve their capability, until the generator is indistinguishable from the true RF distribution. Specifically, on top of the GAN framework, SS-GAN carries out a variety of operations to enhance the estimation: (1) In addition to observations of the measured RF coverage and RF interference, SS-GAN also employs a collection of crucial auxiliary information (e.g., geographic data) as additional input features to the GAN framework so as to precisely characterize the RF environment; (2) To dampen the training instability, a new lightweight reconstruction loss is introduced to the objective function of SS-GAN rather than solely using the adversarial loss, which aims to impose a weak supervision on the generated RF maps according to estimation accuracy; (3) Moreover, SS-GAN designs an innovative sparsely self-supervised ( ${\mathcal {SS}}$ ) learning mechanism that facilitates the validation of the estimated results for a model lacking direct ground truth knowledge. Extensive experiments on a real-world 4G LTE dataset demonstrate that SS-GAN can substantially improve the estimation accuracy over the state-of-the-art baselines. Comparison results are presented through visualized case studies and quantitative statistics.

In the process of transformer overhaul and maintenance in nuclear power plant, a large number of Chinese technical documents have been accumulated, including transformer structure and corresponding failure mode, failure cause analysis, maintenance test record, inspection and defect elimination record, fault problem and other information. It contains rich fault information, fault cause description and troubleshooting method and other key features of fault and maintenance, which is helpful for the maintenance of transformer To guide the operation and inspection work and fault diagnosis and analysis work. In CSCW and its related fields, artificial intelligence method and knowledge engineering technology, especially konwledge graphping technology and its intelligent application, have attracted extensive attention from academia and industry. Based on a series of data acquisition, analysis and algorithm flow, we have a deep understanding of the practical effect of applying intelligent algorithm directly to the construction of transformer fault konwledge graph and decision support application.

The maintenance of power plants highly relies upon precious knowledge and experience of handling faults, which is often stored in reports such as the event report. Simple string matching is the traditional means of retrieving relevant reports, and there is a failure of such methods in understanding the user's search intention properly. With a focus on improving the accuracy of information feedback, this work aims to develop a system of knowledge base question answering. Specifically, natural language processing is employed to improve question comprehension and information retrieval. The BiLSTM-CRF model and the fine-tuned BERT model are used to capture named entities and relations in the query. And the BM25 algorithm and the fine-tuned BERT model are combined to develop a scheme for better information retrieval. On this basis, the application interface of knowledge base question answering towards intelligent power plant maintenance is developed. With this question answering system, power plant operators can have better interaction with the knowledge base and improve collaboration.

Imbalanced fault diagnosis becomes increasingly im-portant as the number of fault samples is relatively small in practical situations. Sparse auto-encoder(SAE) has been well addressed in fault diagnosis while it is not suitable for imbalanced fault diagnosis. Cost sensitive learning can be utilized to extend the sparse auto-encoder to cost sensitive sparse auto-encoder(CS-SAE). However, the class weights assigned to different classes are usually unknown in practice. So we propose to use particle swarm optimization(PSO) to optimize the class weights for cost sensitive sparse auto-encoder(PSO-CSSAE). The experiments have shown that the proposed approach consistently outperforms the state of the art on Tennesse Eastman(TE) dataset.

Given the background of urbanization and rural revitalization in the new era, it is important to explore the synergy between regional macroeconomics and rural transformation, as a balanced and coordinated urban–rural relationship must be built to promote regional sustainable development and rural revitalization. This paper used the spatial econometric model to study the spatiotemporal synergy and interaction between Xinjiang’s county economy and rural transformation from 2007 to 2017. The conclusions were as follows. A clear spatial difference exists between the county economy and the rural transformation level, and regional bulk agricultural products lack competitiveness. The synergy between the county economy and rural transformation is weak, as the county economy is lagging while rural transformation progresses without collaboration, indicating different types of non-equivalence. The county economy has a stronger spatial dependence on rural transformation and insufficient spillover, a stagnating effect, mainly negative driving effects, and unstable interaction effects, while the unstable changes in rural transformation affect the county economy. The urbanization rate, urban wage level, rural employment structure, and planting area per capita were the main influencing factors. It is necessary to deepen rural transformation, consolidate and enhance its stability, cultivate regional growth poles, promote overall development, and promote regional coordination.

We consider robust smoothing for nonlinear state space models in which both the process and measurement noises have heavy tails. To improve the robustness of Kalman smoothing, we formulate the robust smoothing problem by replacing the quadratic loss in the conventional Gaussian Kalman smoother by Huber’s cost function. However, the Huber based smoother cannot be directly implemented within the Kalman smoothing framework, which has well recognized benefits in computational efficiency and stability. To address this issue, we introduce an auxiliary parameter to construct a surrogate function for the Huber cost function, leading to a reformulation of the robust Kalman smoothing problem. The reformulated robust smoothing is solved by an alternating minimization method, which iterates between a simple auxiliary parameter update step and a modified conventional Kalman smoothing step. Simulation results show that the proposed method achieves a performance improvement over several conventional and existing robust smoothers with a slight increase of computational time.

Although the effects of heat-moisture treatment on starch structures and digestibility have been evaluated, the changes in structures and digestion of starches in heat-moisture treated starch-based food systems with varying amylose contents are not well understood. In the present study, starches isolated from heat-moisture treated polished rice grains were characterized with multi-scale structures and digestibility to reveal the effect of amylose in rice grains on structures and digestibility of starch subjected to heat-moisture treatment. Results indicated that heat-moisture treatment contributed to the partial gelatinization of starch granules, but also significantly reinforced the molecular interactions between starch molecules and thus increased starch resistance to hydrothermal treatment and enzymes attack. The higher amylose content of the native starch was, the greater reduction in digestion was observed for heat-moisture treated starch. Pearson's correlation matrix showed that the amylose content highly correlated with the changes in structural features (e.g., molar mass, short-range ordered structure, crystalline structure, and lamellar structure) of starches followed by heat-moisture treatment. The amylose promoted the reinforcement of interactions between starch chains during heat-moisture treatment and then significantly contributed to the reduction in starch digestibility.

This paper studies a three-dimensional automated storage and retrieval system that uses conveyors for depth transportation and a crane for both horizontal and vertical transportation. While previou...

A large number of new electrode materials and novel structural designs are emerging for lithium-ion batteries, yet scalable synthesis and raw material costs still hinder the practical application of such materials. Here, we designed and fabricated a low-cost SiOx/C composite by a facile and scalable mechanofusion route with a ball-milling method. We selected aerosil and graphite precursor-needle coke, which are two widely used materials in industry, as a silicon source and carbon source, respectively. This SiOx/C composite shows a high reversible capacity (ca. 550 mAh g−1) at the 180th cycle and good rate performance. Our scalable synthesis route of electrode materials can stimulate the progress of other energy storage technologies for practical applications.

Designing an accurate vehicular channel simulator which generates samples at the high speed is a key issue to the vehicular communications transmission scheme and protocol design. Although the finite-state Markov channel (FSMC) models have been extensively investigated to describe fading channels, FSMC models cannot show the combined effect of shadowing and small-scale fading on the temporal statistical characteristic of the vehicular channel. In this letter, a vehicular channel simulator based on the FSMC is designed, which incorporates the impacts of shadowing with small-scale fading and movement speed on the temporal statistical characteristic. The steady-state probabilities and the closed-form expressions of state transition probabilities between channel states are derived based on the approximation of Lognormal–Nakagami distribution. To validate the accuracy of the proposed FSMC channel simulator, the derived model parameters and second-order statistical parameters of the simulated channel are compared with the real field measurements of high-speed vehicular channels.

Integration of system design models with software design has been employed as a common paradigm for model-driven design of control applications of distributed automation systems. However, there is ...

Recurrent Neural Networks (RNNs) have been widely used in processing natural language tasks and achieve huge success. Traditional RNNs usually treat each token in a sentence uniformly and equally. However, this may miss the rich semantic structure information of a sentence, which is useful for understanding natural languages. Since semantic structures such as word dependence patterns are not parameterized, it is a challenge to capture and leverage structure information. In this paper, we propose an improved variant of RNN, Multi-Channel RNN (MC-RNN), to dynamically capture and leverage local semantic structure information. Concretely, MC-RNN contains multiple channels, each of which represents a local dependence pattern at a time. An attention mechanism is introduced to combine these patterns at each step, according to the semantic information. Then we parameterize structure information by adaptively selecting the most appropriate connection structures among channels. In this way, diverse local structures and dependence patterns in sentences can be well captured by MC-RNN. To verify the effectiveness of MC-RNN, we conduct extensive experiments on typical natural language processing tasks, including neural machine translation, abstractive summarization, and language modeling. Experimental results on these tasks all show significant improvements of MC-RNN over current top systems.

Aims: Our study aimed to investigate the expression and prognostic role of homeobox C6 (HOXC6) in prostate cancer (PCa).Methods: Relative expression of HOXC6 at mRNA and protein levels in tissues a...

The experimental observation and analysis for the influence of clamping effect on the magnetoelectric properties of the bilayer La0.7Sr0.3MnO3/BaTiO3 (LSMO/BTO) and trilayer LSMO/BTO/LSMO heterostructures were reported. Because the significant two-dimensional clamping effect caused by the lattice mismatch of the constituting layers, the relative dielectric constant and the ferroelectric coercive field of the trilayer heterostructure was lower than that of the bilayer one. Furthermore, the variation in ME voltage coefficient (αE) as a function of frequency for the two heterostructures was found to exhibit a monotonous increasing tendency. The value of αE for the trilayer heterostructure was little lower than that of the bilayer one, that is because the clamping effect suppressed both the ferroelectric properties of BTO and the transferred strain at the hetero interface.