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This paper presents a parameter estimation method for the lifetime distribution of the Meta-Action Unit (MAU) with uncertainty failure modes under type-I censored data. The MAU is regarded as the basic functional unit to accomplish the function of mechanical equipment, and its failure modes are classified according to the abnormal kinematic parameters in Meta-Action (MA), which are more succinct than the traditional mechanical failure modes on parts. However, there is some uncertain information about the failure data and censored data of MAU because of the technology limitations and the space accessibility constraints for monitoring the kinematic parameters of MA, which uncertainty information can impact the parameter estimates of MAU lifetime distribution. In order to avoid the impacts on the estimating accuracy of distribution parameters, the evidential likelihood function based on the belief function theory is constructed in view of the credibility level of the failure data and censored data. In addition, the Evidential Expectation Maximization (E2M) algorithm is proposed to estimate the parameters of the mixed exponential distribution of MAU lifetime under type-I censored data. Finally, an application of an Automatic Pallet Changer (APC) is used to illustrate the validity of the MAU failure modes classification. The simulations of the E2M algorithm are conducted to show that the proposed parameters estimation method can integrate uncertain information in the failure data and the censored data, and obtain more stable results than those based on the conventional Expectation-Maximization (EM).

Background: irritable bowel syndrome (IBS) is one of the most common functional gastrointestinal disorders and considerably contributes to the global disease burden. Ambient air pollution, especially particulate matter (PM), could be a risk factor for IBS. However, limited evidence has linked PM exposure to IBS. Methods: we conducted a large-scale prospective cohort study based on the UK Biobank. The annual average concentrations of PM10, PM2.5–10, and PM2.5were obtained from the ESCAPE study using the land-use regression (LUR) model. The Cox proportional hazard model was used to calculate hazard ratios (HRs) at 95% confidence intervals (95% CIs) of PM with IBS incidence. We further explored the exposure–response relationship curve and performed several stratified analyses based on sex, age, BMI, and other factors. Results: during a follow-up period of 13.7 years, 5796 individuals diagnosed with IBS were identified. We estimated that the HRs of IBS associated with a 10 μg m−3increase in PM10, PM2.5–10, and PM2.5were 1.14 (95% CI: 1.01, 1.29), 1.16 (95% CI: 0.90, 1.50), and 1.33 (95% CI: 1.04, 1.68), respectively. We estimated an almost linear exposure–response relationship between PM10and PM2.5exposure and IBS. Individuals under 60 years old were more vulnerable to PM exposure. Conclusions: our study provided robust evidence on the association between long-term PM10and PM2.5exposure and IBS; and the impact of PM2.5was higher than that of PM10. We further suggest restricting the ambient PM standards to reduce the impact of PM exposure on IBS.

Na superionic conductor-structured phosphates have attracted wide interest due to their high working voltage and fast Na+migration facilitated by the robust 3D open framework. However, they usually suffer from low-rate capability and inferior cycling stability due to the low intrinsic electronic conductivity and limited activated Na+ions. Herein, a doping protocol with Na+in the V3+site is developed to activate extra electrochemical Na+ions and expand the migration path of Na+, leading to the improvement of the electronic conductivity and diffusion kinetics. It is also disclosed that the generated stronger Na–O bonds with high ionicity significantly conduce to the enhanced structural stability in the Na+-substituted Na3.05V1.975Na0.025(PO4)3/C cathode. The obtained composite can deliver an excellent rate capacity of 83.8 mA h g–1at 20 C and a moderate cycling persistence of 91.3% over 1500 cycles at 10 C with great fast-charging properties. The reversible structure evolution is confirmed by the ex situXRD, XPS, and ICP characterization. This work sheds light on awakening electroactive Na+ions and designing phosphates with superior electrochemical stability for practical Na-ion batteries.

Objective The objective of this study was to investigate the expression of enzymes involved in synthesis and modification of chondroitin sulfate (CS) in knee cartilage tissue of patients with osteoarthritis (OA) and Kashin-Beck disease (KBD).Methods The knee articular cartilage samples were obtained from 18 age- and gender-matched donors with 6 each in KBD, OA, and control groups. Hematoxylin and eosin (HE) staining, toluidine blue (TB) staining, and immunohistochemical (IHC) staining were performed to estimate the expression level and localization of aggrecan, along with FAM20B, GalT-II, and EXTL2, which are associated with CS synthesis and modification. Rank-based analyses of variance test was used for the multiple comparisons of discrepancy in the positive staining rate among the 3 groups.Results In HE and TB staining results, damaged morphology, decreased chondrocyte numbers and proteoglycans were observed in OA and KBD groups compared with the control group. In line with these trends, the positive staining rates of aggrecan were lower in KBD and OA groups than in the control group. Meanwhile, the positive staining rates of CS chain modifying enzymes FAM20B, GalT-II, and EXTL2 decreased in OA and KBD groups.Conclusions In conclusion, it was demonstrated that altered expression of CS chain modifying enzymes in OA and KBD groups influenced the synthesis procession of CS and could contribute to the damage of cartilage. Further investigation of these enzymes can provide new theoretical and experimental targets for OA and KBD pathogenesis studies.

In order to improve the lifetime and reliability of equipment operation stage, it is necessary to carry out maintenance for components. The typical selective maintenance model does not consider the maintenance quality uncertainty and the failure effects, which may make the decision-maker overestimates the reliability of completing the next task after system maintenance, resulting in incorrect maintenance decision and prone to serious consequences of failure. In this paper, the potential discrepancy between the target maintenance quality and the actual maintenance quality of the decision maker is considered. At the same time, a multi-state FMECA is proposed to measure the failure effects under different states. Finally, the selective maintenance model of the multi-state series systems is established and solved by the genetic algorithm. The results show that considering the effect of component failure and the uncertainty of maintenance quality has an influence on maintenance decision. The maintenance decision made in this way is more consistent with the engineering practice.

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.

Due to the existence of coupling relationships, quality characteristics form a variation propagation process, which increases the risk possibility of product quality. In order to improve the robustness of quality characteristics, this paper proposes a fuzzy clustering-based key quality characteristics decoupling planning considering risk criticality. Firstly, based on the design structure matrix, a modular correlation matrix of key quality characteristics was established to quantify the coupling relationships among them. Secondly, according to the variation characteristics of quality characteristics, the variation propagation model is constructed to identify the potential quality risk. Thirdly, the fuzzy clustering algorithm is used to obtain the optimal control sequence of key quality characteristics. Finally, the computerized numerical control machine tool is taken as an actual case, the effectiveness and superiority of this method are verified by the comparison of the numerical result and method. This method provides a new indicator system solution for the coupling analysis of product design.

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.

The concept of process capability has been widely used in production management and quality control. However, applying traditional process capability evaluation method to machine capability cannot eliminate the influence of other process factors other than machine. To solve the problem, we propose the sigma machine capability evaluation method in this paper. First, multivariate statistical analysis methods are used to analyze the influence of all factors. Second, we deleted the non-normal data through sample fitting. Then, on the basis of normal distribution, we used the sample variance as the evaluation index to calculate the sigma levels of single characteristic and multiple characteristic parts. Last, we applied the sigma evaluation method and the traditional one to conduct a case study and compare their results, which proves the feasibility and superiority of the sigma level evaluation method.

Potassium vanadate (K0.44V2O5, KVO) exhibiting high electrochemical activity in Zn2+-containing aqueous electrolytes are promising cathode materials for aqueous zinc metal batteries (AZMBs). However, the conventional electrodes with non-conductive and electrochemically inert binders limit the electrochemical kinetics of KVO in the electrodes. Herein, binder-free KVO nanowires@carbon cloth (CC) cathodes, KVO nanowires chemically deposited onto the CC current collector without the use of polymer binder, are proposed for AZMBs. The pseudocapacitive contribution at 1 mV s−1is improved from 49 % for conventional electrodes employing PVDF binder to 82 % for the as-fabricated KVO@CC binder-free electrodes, implying the promoted electrochemical kinetics. As result, the binder-free KVO@CC electrode demonstrates a high specific capacity of 391 mAh g−1at 0.1 A g−1and a stable cycle of 3100 cycles a 5 A g−1with a capacity retention of 89.5 %. In contrast, the conventional binder-containing KVO electrodes are only 234 mAh g−1and 53.8 %, respectively, under the same conditions. These results demonstrate that the optimization at the electrode level, i.e., the binder-free strategy, is feasible for designing high-performance AZMBs.

The thermal effect of lithium (Li)-ion batteries affects its performance and service life and threatens its safety. Therefore, a new tree-shaped channel heat sink was developed for cooling Li-ion battery packs and compared with fractal and serpentine channel heat sinks. Moreover, the electrical–thermal–fluidic multi-physics simulation was implemented based on the equivalent circuit model. The temperature distribution effect on the battery pack's consistency was investigated. Different circuits were established through various series–parallel topologies, and the battery pack's discharging and temperature characteristics were examined when the cells' initial parameters were different. The results demonstrated that the new tree-shaped channel heat sink offered effective heat dissipation and small flow resistance. The decreasing temperature difference enhanced the current consistency, while the decreasing temperature rise reduced the voltage consistency. The series or parallel connection between the battery modules slightly affected the battery pack's discharging and temperature characteristics. Within the module, a reduction in the number of batteries in series or augmentation in the parallel branches reduced the battery consistency and increased the battery pack's average temperature rise and temperature difference. The battery consistency in the parallel-first topology module was better than that in the series-first topology module under the same number of parallel branches. These results are helpful for the battery pack consistency studies.

Supply chain quality is the assurance of product quality in its full life-cycle. Although supply chain quality control is a hot topic among researchers, supply chain quality prediction is actually an important but unsolved problem in manufacturing industry. In this paper, an approach of manufacturing supply chain quality prediction based on quality satisfaction degree is proposed to control supply chain better, in order to help ensure product quality. Supply chain quality prediction 3D model and model based on customer satisfaction and process control are established firstly. And then technologies used in quality prediction are studied, including quality prediction index system established on Expert scoring -AHP and prediction workflow built on ABPM. Finally an example is given to illustrate this approach. The customer satisfaction prediction result of supply chain quality can help supply chain management, and the quality prediction software system can make it easier, which provides a new direction for the product quality control technology research.

•A novel tree-shaped channel is designed for the cooling of battery module.•The novel cooling plate offers good cooling efficiency.•Kriging models of the cooling plate exhibit good prediction abilities.•Lowering the cooling water temperature increases the temperature difference between the cells.

Aqueous zinc‐ion batteries (AZIBs) have become a promising alternative energy storage device due to their lower cost and better safety performance than lithium‐ion batteries (LIBs). However, the biggest challenge is the need to develop electrode materials with higher capacity and longer life than LIBs at present. Herein this work, a tunnel‐structured sodium vanadate (NaV6O15) is synthesized by molten salt method as the cathode materials for AZIBs. The prepared NaV6O15nanosheets have a high specific capacity of 325 mAh g−1at a current density of 0.1 A g−1, and the capacity retention rate is as high as 127.08% under 1000 cycling at a current density of 1 A g−1. This excellent performance is mainly attributed to the stable tunneled structure, which provides an effective diffusion path for Zn2+insertion and avoids structural damage. Herein the subsequent cycles, Zn2+is mainly inserted/extracted in NaV6O15and Zn3(OH)2V2O7·2H2O. The preparation of NaV6O15cathode materials and the molten salt method provide a certain reference value for the development of AZIBs in this work. Herein, NaV6O15nanosheets are synthesized by one‐step molten salt method as cathode materials for aqueous zinc‐ion batteries (AZIBs), which exhibit long cycle stability and high capacity retention. The synthesis method of the molten salt and mechanism analysis of NaV6O15nanosheets provide a new perspective and reference significance for the practical application of AZIBs.

Previous studies seldom consider the difference of preventive maintenance effect on different failure processes when establishing the preventive maintenance model. Meanwhile, preventive maintenance models usually assume that minimal repair is performed for each failure, but this assumption is not applicable in some systems. Once this assumption is made for the inapplicable system, the maintenance strategy obtained by the established preventive maintenance model will not be optimal. In order to get a better maintenance policy to reduce maintenance cost, this paper divides the system failure processes into two types: wear-out type and damage-type. The model assumes that preventive maintenance can reduce the probability of damage-type failure, but it has no effect on wear-out type failure. At the same time, for the system studied in this paper, it is assumed that after corrective maintenance, the overall state of the system is worse than the moment just prior to the failure. Then, an extended preventive maintenance optimization model based on generalized Polya process is established. Finally, a practical algorithm is designed to solve the model. The analysis of numerical examples shows the potential value of the proposed method, which may provide maintenance guidance for enterprises and save maintenance costs.

Let. This article considers the following degenerate semilinear parabolic initial-boundary value problem, where be constants. We obtained the conditions of global existence and blow-up.

n this paper, the periodic behavior of iced cable in the case of the in-plane fundamental parametric resonance-principal resonance, out-of-plane principal parametric resonance-principal resonance, and in 1:2 internal resonances is investigated. The sufficient condition for the existence of the periodic solutions about the system is obtained through using Melnikov function and Poincare mapping, then the stability of periodic solution is investigated by using blow-up transformations and the average method. Numerical simulations are performed to verify the analytical predictions and get three groups of diagrams.

n this paper, we study the Diophantine equation . By using the elementary method and algebaic number theroy , we proved that this equation has no integer soution.

This paper explains how the Lignin peroxidase and Manganese Peroxidase from Coriolus Versicolor were co-immobilized by chitosan microspheres.It studies kinetic character of the enzyme after co-immobilization.Optimum Lip and MnP activity obtained at 30-35℃ for 14 hours in pH 8.4 glutaraldehyde solutions during immobilized to chitosan microspheres which prepared by coagulation in NaOH: methanol=3:2. When kept at 50℃ for 6h, more than 80% of the immobilized enzyme activity remained, while the free enzymes were inactive under the same conditions. The co-immobilized enzyme can remain 70% activity after two weeks while both of the free enzymes inactive. Compared with the free enzymes, temperature and time stability of the co-immobilized enzyme was considerably improved.

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed.

•Multi-sized nanosheets Co-Fe LDHs on Ni foam was synthesized by a facile hydrothermal reaction.•Fabrication of Co-Fe LDHs with superior electrochemical performances.•Co-Fe LDHs exhibit great specific capacitance of 3340 mF cm−2at 1 mA cm−2and good cycling stability.

Reliability optimal allocation is a critical method in engineering and operation fields to improve and ensure product quality. However, conventional model generally uses the single objective with research and development (R & D) cost or product reliability. Moreover, the popular particle swarm optimization (PSO) algorithm solving the model has insufficient global search ability. In this paper, a novel reliability optimal allocation method is developed based on double-objective model and multi-population PSO (MPPSO) algorithm. The cost function is established considering all the cost related to reliability using analytical hierarchical process (AHP) and ordered weighted averaging (OWA) operator. Multi-population particle swarm optimization algorithm is developed based on information exchange mechanism among subpopulations. In the algorithm, the inertia weight is optimized by chaotic map, and different mutation operations are carried out on the subpopulations. An illustrative example, which implements to computer numerical control (CNC) grinding machine, is presented to illustrate the practicality and application of the proposed method. Finally, the comparison and analysis are implemented to show the advantage of proposed model and MPPSO algorithm.

•Nanosheets mixed structure CuCo2O4on Ni foam was synthesized by a facile hydrothermal reaction.•Nanosheets mixed structure CuCo2O4show the superior electrochemical performances.•CuCo2O4nanosheets exhibit specific capacitance of 1595 F g−1at 1 A g−1and good cycling stability.

For global optimal control strategy, it is not only necessary to know the driving cycle in advance but also difficult to implement online because of its large calculation volume. As an artificial intelligent-based control strategy, reinforcement learning (RL) is applied to an energy management strategy of a super-mild hybrid electric vehicle. According to time-speed datasets of sample driving cycles, a stochastic model of the driver’s power demand is developed. Based on the Markov decision process theory, a mathematical model of an RL-based energy management strategy is established, which assumes the minimum cumulative return expectation as its optimization objective. A policy iteration algorithm is adopted to obtain the optimum control policy that takes the vehicle speed, driver’s power demand, and state of charge (SOC) as the input and the engine power as the output. Using a MATLAB/Simulink platform, CYC_WVUCITY simulation model is established. The results show that, compared with dynamic programming, this method can not only adapt to random driving cycles and reduce fuel consumption of 2.4%, but also be implemented online because of its small calculation volume.