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Global epidemics and international conflicts disrupt supply chain operations. Many enterprises employ emerging information technology (IT) to reduce supply chain vulnerability and enhance supply chain resilience. Technologies like artificial intelligence and blockchain facilitate more robust supply chain operations, such as remanufacturing, just-in-time production, and automated workflow, leading to corporate sustainability along economic, environmental, and social dimensions. From a dynamic capability perspective, this article conceptualizes emerging IT capability and investigates its role in helping enterprises survive supply chain disruptions and prosper in the long run. A research model depicts the relationships among environmental uncertainty, supply chain vulnerability vigilance, emerging IT capability, supply chain resilience, and corporate sustainability. A partial least square analysis on survey observations collected from more than 200 enterprises in China that are highly susceptible to supply chain disruptions provides supporting evidence to most research hypotheses. The results show that high vigilance to potential supply chain disruptions will motivate enterprises to develop emerging IT capability, which will enhance supply chain resilience as well as economic, environmental, and social performances. The mediating role of emerging IT capability suggests a viable path for enterprises to adapt to the increasingly turbulent environment and improve supply chain resilience and corporate sustainability.

Intuitionistic fuzzy sets have been widely studied and applied as an important means of dealing with information uncertainty. However, the existing intuitionistic fuzzy sets and their extension methods are limited and single in their fuzzy spatial representation of information. Under this environment, this paper proposes a new generalized fuzzy set, called qth Rung Root Orthopair Fuzzy Sets (q-RROFS). Since the q-RROFS can adjust the range of fuzzy space expression by the parameter q, it is superior to intuitionistic fuzzy sets, SR-fuzzy sets, and CR-fuzzy sets. We give some definitions and properties of q-RROFS and give their proofs. Under the q-RROFS, we give its operations and properties and introduce four new weighted aggregation operators, namely, qth Rung Root Orthopair Fuzzy-weighted average operator (q-RROFWA), qth Rung Root Orthopair Fuzzy-weighted geometric operator (q-RROFWG), qth Rung Root Orthopair Fuzzy-weighted power average operator (q-RROFWPA), and qth Rung Root Orthopair Fuzzy-weighted power geometric operator (q-RROFWPG). We discuss the properties of these operators in detail and follow the proof procedure. Then, we give a Multi-criteria decision-making approach under q-RROFS. Finally, we illustrate the effectiveness and applicability of the proposed methodology through practical application examples and comparisons with other methods.

In many business disciplines, impact metrics and measurements of productivity are well established, including institutionally-approved journal lists available for the use of both faculty and administration. Faculty in business analytics related fields generally have no such tool available, leading at times to confusion, undervaluing of their scholarship, and even litigation. In this study, we take the preliminary steps for establishing objective assessment tools for business analytics faculty by studying the publication patterns of the most productive current practitioners. An initial list of 700 publishing outlets was narrowed down to approximately 100 that account for 30% of all published scholarship in the field. We suggest this list can be used as an initial benchmark for future institution-based conversations about faculty review.

This paper presents a new optimization criterion considering stress weight based on Ds-optimality to solve the low estimation accuracy problem of some stress model parameters when using the existing optimization design criteria to optimize the multistress accelerated degradation test scheme. First, the accelerated degradation model and constraints are determined by analyzing the test characteristics of step-stress accelerated degradation test (SSADT) with multistress. Then, the weight of each stress is identified by fault tree analysis and potential improvement value methods. Combined with the tabu search–particle swarm optimization (TS-PSO) algorithm, the SSADT with multiple stresses of the optimization design process is given. Finally, taking the SSADT with multistress optimization design of motorized spindle as an example, the practicability of the method is verified, and the optimization results are compared with those under D-optimality and Ds-optimality to validate the effectiveness of the method.

ABSTRACTIn this article, a multi-objective optimization method for the accelerated degradation test is proposed to solve the problem that the single objective optimization cannot meet the needs in practice gradually. Firstly, the Gamma process is assumed to describe the degradation path of product. Then, three optimization objectives are considered to establish the multi-objective optimization model based on the analytic hierarchy process, under the constraint that the total experimental cost does not exceed a predetermined budget. To solve the established optimization model, the self-adaption searching algorithm is proposed to search the optimal test plan, in which the searching interval of the decision variable is dynamically adjusted according to the feedback of the optimization function. Finally, the effectiveness of the proposed method is illustrated by a group of examples of motorized spindles.

The dynamic model can provide high capabilities at accurate simulation for rolling element bearings (REBs), but to simulate the continuous dynamic response over the whole life time is difficult. This paper proposes a hybrid method based on a data-driven and dynamic model to obtain continuous parameters of dynamic model, which can be used to predict the remaining useful life (RUL) of REBs. First, four dynamic models of the REB with the variable parameters of roughness, crack growth rate, crack length and crack depth are established to describe the degradation process of REB with three stages. In particular, the self-healing phenomenon in bearing fault stage is analysed, and the three models are used to describe the trend of fluctuating degradation process in this stage. The dynamic model parameters are updated for the degradation process of REBs with the interacting multiple-model particle filtering, which taken root mean square (RMS) as the observation. Then, the continuously growing crack length is used as the index to predict the RUL. The proposed method realises the continuity of dynamic model in the whole life time, and the fluctuating RMS is transformed into a continuously growing parameter for prediction to avoid the prediction difficulty caused by the decrease in RMS in the degradation process. Finally, The bearing datasets of Xi’an Jiaotong University are used to verify the effectiveness of the proposed method. The comparative test results show that the proposed method can predict the results more accurately without sample training and obtain a clearer degradation mechanism.

Due to the powerful DNA loading capacity and excellent proton sponge effect, the cationic polymer polyethyleneimine (PEI) has been demonstrated as a versatile, efficient DNA delivery tool both in vitro and in vivo. However, the excess surface positive charge of PEI and the common capture/clearance of PEI/DNA complex by the immune system limit its further clinical applications. To reduce the cytotoxicity resulting from surface charge and avoid the clearance of nanoparticles interacting with proteins and circulating immune cells in the blood, a bionic gene delivery system was developed by coating PEI/DNA complexes with natural cell membranes. The obtained RAW Cell membrane-coated PEI/DNA capsules (RAWm-PDc) and Red blood Cell membrane-coated PEI/DNA capsules (RBCm-PDc) complex showed excellent dispersibility and stability with an average particle size of 200–300 nm. Moreover, the RAWm-PDc/RBCm-PDc complex had great DNA loading capacity and protected the bound DNA effectively from nuclease hydrolysis. Most importantly, the RAWm-PDc/RBCm-PDc complex exhibited low protein adsorption, reduced cytotoxicity and high gene delivery efficiency. All the results demonstrated the potential of RAWm-PDc/RBCm-PDc as a promising non-viral gene delivery vector.

Traditional reliability assessment of spindle systems of machine tools suffers from long testing time and high cost. Accelerated life testing is an alternative that overcomes the shortcomings of traditional reliability testing. In a life testing, identification of critical factors of service life and an accurate model are important. Based on the characteristic analysis and engineering experience, four reliability factors, which are the average power of spindle systems, the number of tool changing, the number of spindles restarting and environment temperature, are selected as accelerating environment variables. An accelerated failure time model is used to describe the inverse relationship between the variables and reliability for the catastrophic failure mode and the degradation failure mode separately. Then a competing risk model is built by considering competing risks of two modes. Parametric reliability models are proposed to capture the statistical independency and dependency separately, in which the Gumbel–Hougaard copula function is used to establish the joint cumulative distribution for dependency. Thereby the hypothesis testing is developed to determine the failure modes dependency. The reliability sensitivity of each environment variable is analyzed. Finally, the proposed model is illustrated with a real field case study.

A new compiling method based on cutting force model is proposed for an eight-block program-loading spectrum of a motorized spindle. In the proposed method, all loads exerted on the motorized spindle are dependent, which is accurate for loading in reliability tests. A cutting force measuring system is set up to obtain cutting forces accurately. Then, two concluded cutting force models are compared to choose the better one through fitting the measured cutting force signals under different machining process parameters. In accordance with the characteristic of the milling load, program-loading spectrum for the amplitude of radial force is compiled while neglecting other factors. Thereafter, the compiled spectrum is converted into a complete program-loading spectrum where torque and loads’ correlation are calculated by the chosen cutting force model. Finally, the accelerated factor of the program-loading spectrum relative to actual machining conditions is solved.

The hazard rate curve of the numerical control machine tool is a bathtub curve. The change point between the early failure period and the random failure period of the curve is difficult to obtain with a small data sample; thus, a Bayesian method is proposed. A method to build the prior distributions of the Weibull parameters is developed, which integrates the multi-source prior information of the target numerical control machine tool and the reference numerical control machine tool. The Markov chain Monte Carlo method is adopted to calculate the estimators of the Weibull parameters corresponding to each failure, which solves the problem of the absence of an analytical solution. The total working time of the numerical control machine tool when the estimator of the shape parameter is equal to 1 is estimated by taking the estimator of the shape parameter as the function of time. As a result, the change point and the early failure period are obtained. Comparison result shows that the result obtained through an existing change point solving method with a large dataset is close to the result generated through the proposed method with a small dataset. The change point and the early failure period obtained with the proposed method can be used to guide the early failure test and to design a rational maintenance strategy, which are of vital engineering significance.

Fe3O4nanoparticles (NPs) are widely used in the construction of drug and gene delivery vectors because of their particular physicochemical properties. Surface modification can not only reduce the cytotoxicity of Fe3O4, but also further improve the biocompatibility and delivery efficiency. In this work, firstly, polydopamine (PDA)-coated Fe3O4NPs (named Fe3O4@PDA) were prepared by using the self-polymerization characteristics of dopamine in alkaline environment. Then, polyamidoamine (PAMAM) was modified by the Michael addition reaction to prepare water-soluble core—shell magnetic NPs of Fe3O4@PDA@PAMAM, and its potential as gene vector was further evaluated. The results revealed that Fe3O4@PDA@PAMAM had the ability to condense and protect DNA, and showed lower cytotoxicity, higher cell uptake and transfection efficiency than those of PAMAM. It has the potential to become a magnetic targeted gene vector for further study.

Intuitionistic cubic fuzzy sets (ICFSs), as a hybrid fuzzy set consisting of interval-valued fuzzy sets and intuitionistic fuzzy sets, can deal with the uncertainty of information in decision problems more comprehensively. Muirhead mean (MM) operators can deal with the correlation between attributes in decision problems more realistically. However, there has been no research on MM operators under intuitionistic cubic fuzzy sets so far. In this study, some new operators are proposed under the intuitionistic cubic fuzzy set. It contains the intuitionistic cubic fuzzy MM (ICFMM) operator, intuitionistic cubic fuzzy weighted MM (ICFWMM) operator, intuitionistic cubic fuzzy dual MM (ICFDMM) operator, and intuitionistic cubic fuzzy dual weighted MM (ICFDWMM) operator. Their proof procedure, properties, and proof of properties are given. Two MCDM decision models based on ICFWMM and ICFDWMM operators are proposed, and the proposed decision models are applied to supplier selection, and the better reliability and accuracy of the proposed decision methods in this study are verified through comparative analysis with existing methods.

Although Markov chain Monte Carlo(MCMC) algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread engineering applications. Thus, a reliability modeling and assessment solution aimed at small-sample data of numerical control(NC) machine tools is proposed on the basis of Bayes theories. An expert-judgment process of fusing multi-source prior information is developed to obtain the Weibull parameters’ prior distributions and reduce the subjective bias of usual expert-judgment methods. The grid approximation method is applied to two-parameter Weibull distribution to derive the formulas for the parameters’ posterior distributions and solve the calculation difficulty of high-dimensional integration. The method is then applied to the real data of a type of NC machine tool to implement a reliability assessment and obtain the mean time between failures(MTBF). The relative error of the proposed method is 5.8020×10-4compared with the MTBF obtained by the MCMC algorithm. This result indicates that the proposed method is as accurate as MCMC. The newly developed solution for reliability modeling and assessment of NC machine tools under small-sample data is easy, practical, and highly suitable for widespread application in the engineering field; in addition, the solution does not reduce accuracy.

Since the beginning of e-commerce, there has been a debate on whether customer service should be included as a component of website quality. This study reexamines the question in the context of e-commerce maturity. Based on the more general service quality framework, it proposes e-commerce service quality as a broader construct that covers technical service quality, content service quality, and customer service quality. The empirical results based on the survey observations collected from USA and China suggest that online shoppers emphasize different quality aspects at different stages of e-commerce development. When e-commerce gets mature, customer service becomes more salient.

Metformin is the only first-line oral hypoglycaemic drug for type 2 diabetes recommended by international guidelines with proven efficacy, safety, and cost-effectiveness. However, little information exists about its use in Asian populations. We aimed to ascertain the effectiveness of the α-glucosidase inhibitor acarbose, extensively adopted in China, compared with metformin as the alternative initial therapy for newly diagnosed type 2 diabetes.

Data about the occurrences of software applications and operating systems piracy around the globe is examined and reported in this study. The trends extracted and analysed are based on the piracy rates and commercial values of 116 countries and regions that are also divided into six major geographic areas. This study found that the major affected country rankings are relatively stable and there are always new countries making the list. In particular, the annual changes in the commercial values and rates are always significant upwards in the case of almost all the nations examined. Put simply, based on the period examined, the major countries affected and their rankings in the respective geographic areas are quite systematic.

Based on the generating principle of generating line of spiral bevel gears with spherical involute, a new method for building the model of spiral bevel gears with spherical involute is presented by utilizing the modules of part design, assembly design and kinematic simulation in CATIA. In the part design module of CATIA, the models of base cone, tangent surface, and generating line are built respectively. And the built models are assembled in the assembly environment; the simulation of pure rolling is accomplished in the environment of kinematics; and the model of the gear surface is built using the function of tracks. Then the solid model of the spiral bevel gear is built through the functions of transferring the model's file format, multi-section sweep and solid fill. Finally, the analysis to the performance of the bevel gear transmission is conducted. In the environment of the assembly design, the solid model of the gearwheel and the pinion are inserted respectively, and then the assembly is accomplished by applying the constraints. And in the environment of kinematics, the meshing simulation of the bevel gear pair is accomplished by applying angle drive. The research indicates that this method can build the model of spiral bevel gears accurately and rapidly, and the model can illustrate the gearing correctly.

Heavy-duty machine tools are composed of many subsystems with different functions, and their reliability is governed by the reliabilities of these subsystems. It is important to rank the weaknesses of subsystems and identify the weakest subsystem to optimize products and improve their reliabilities. However, traditional ranking methods based on failure mode effect and critical analysis (FMECA) does not consider the complex maintenance of products. Herein, a weakness ranking method for the subsystems of heavy-duty machine tools is proposed based on generalized FMECA information. In this method, eight reliability indexes, including maintainability and maintenance cost, are considered in the generalized FMECA information. Subsequently, the cognition best worst method is used to calculate the weight of each screened index, and the weaknesses of the subsystems are ranked using a technique for order preference by similarity to an ideal solution. Finally, based on the failure data collected from certain domestic heavy-duty horizontal lathes, the weakness ranking result of the subsystems is obtained to verify the effectiveness of the proposed method. An improved weakness ranking method that can comprehensively analyze and identify weak subsystems is proposed herein for designing and improving the reliability of complex electromechanical products.

The functional parts of a machine tool determine its reliability level to a great extent. The failure prediction of the functional part is helpful to prepare the maintenance scheme in time, in order to ensure a stable manufacturing process and the required production quality. Due to the rise of digital twin (DT), which has the characteristics of virtual reality interaction and real-time mapping, a DT-based real-time prediction method of the remaining useful life (RUL) and preventive maintenance scheme is proposed in this study. In this method, a DT model of the manufacturing workshop is established based on real-time perceptual information obtained by the proposed acquisition method. Subsequently, the real-time RUL of the functional part is predicted by establishing an RUL prediction model based on the nonlinear-drifted Brownian motion, which takes the working conditions and measurement errors into consideration. On this basis, the optimal preventive maintenance scheme can be determined and fed back to the manufacturing workshop, in order to guide the maintenance of relevant parts. Finally, an example case study is presented to illustrate the feasibility and effectiveness of the proposed method.

Polyethyleneimine (PEI) has a good spongy proton effect and is an excellent nonviral gene vector, but its high charge density leads to the instability and toxicity of PEI/DNA complexes. Cell membrane (CM) capsules provide a universal and natural solution for this problem. Here, CM-coated PEI/DNA capsules (CPDcs) were prepared through extrusion, and the extracellular matrix was coated on CPDcs (ECM-CPDcs) for improved targeting. The results showed that compared with PEI/DNA complexes, CPDcs had core–shell structures (PEI/DNA complexes were coated by a 6–10 nm layer), lower cytotoxicity, and obvious homologous targeting. The internalization and transfection efficiency of 293T-CM-coated PEI70k/DNA capsules (293T-CP70Dcs) were 91.8 and 74.5%, respectively, which were higher than those of PEI70k/DNA complexes. Then, the internalization and transfection efficiency of 293T-CP70Dcs were further improved by ECM coating, which were 94.7 and 78.9%, respectively. Then, the internalization and transfection efficiency of 293T-CP70Dcs were further improved by ECM coating, which were 94.7 and 78.9%, respectively. Moreover, the homologous targeting of various CPDcs was improved by ECM coating, and other CPDcs also showed similar effects as 293T-CP70Dcs after ECM coating. These findings suggest that tumor-targeted CPDcs may have considerable advantages in gene delivery.