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This paper aims to determine a suitable anti-wear and friction-reducing compounding additive for lithium greases (LG) by investigating the effects of three single additives potassium borate (PB), zinc dialkyl dithiophosphate and molybdenum dialkyl dithiophosphate (MoDDP) and two compound additives on the friction, wear and extreme pressure properties of LG.

The effects of the above five additives on the friction, wear and extreme pressure properties of LG were investigated using an SRV-5 friction tester. An X-ray photoelectron spectrometer was used to analyze the various elements presented on the wear surface as well as the types of compounds.

The compound additive suitable for grease consists of PB and MoDDP, which have excellent friction reduction, anti-wear and extreme pressure properties. And a boundary protection film consisting of oxide and MoS₂ is formed on the friction surface, thus improving the friction reduction and anti-wear performance of the grease.

This study can improve the anti-wear and friction-reduction performance of greases, which is of great importance in the field of industrial lubrication. The results of this paper are expected to be useful to researchers and academics of grease.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2022-0350/

The moral hazard problem which obstructs external equity financing of farm businesses is studied using the principal‐agent framework. We assume that the supplier of external equity capital (the principal) cannot directly observe the farmer’s (agent’s) effort, but can observe the random outcome of the effort. We solve for the optimal farm income‐sharing rule that includes an extra share to the agent. The extra share is dependent on the random outcome and is provided to induce optimal effort from the agent. Results show a farmer’s effort is inversely related to the level of risk aversion and the riskiness of the project. Thus, an investor must share more income when a farmer is more risk averse or a project is more risky.

The “Fed Model” postulates a cointegrating relationship between the equity yield on the S&P 500 and the bond yield. We evaluate the Fed Model as a vector error correction forecasting model for stock prices and for bond yields. We compare out-of-sample forecasts of each of these two variables from a univariate model and various versions of the Fed Model including both linear and nonlinear vector error correction models. We find that for stock prices the Fed Model improves on the univariate model for longer-horizon forecasts, and the nonlinear vector error correction model performs even better than its linear version.

The editors are pleased to offer the following papers to the reader in recognition and appreciation of the contributions to our literature made by Robert Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics. Please see the previous dedication page of this volume. The basic themes of this part of Volume 20 of Advances in Econometrics are time-varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modeling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, the application of the technique of boosting in volatility forecasting, the use of different time scales in Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) modeling, out-of-sample evaluation of the ‘Fed Model’ in stock price valuation, structural change as an alternative to long memory, the use of smooth transition autoregressions in stochastic volatility modeling, the analysis of the “balancedness” of regressions analyzing Taylor-type rules of the Fed Funds rate, a mixture-of-experts approach for the estimation of stochastic volatility, a modern assessment of Clive's first published paper on sunspot activity, and a new class of models of tail-dependence in time series subject to jumps. Of course, we are also pleased to include Rob's and Clive's remarks on their careers and their views on innovation in econometric theory and practice that were given at the Third Annual Advances in Econometrics Conference held at Louisiana State University, Baton Rouge, on November 5–7, 2004.

The purpose of this paper is to study the resonance failure sensitivity analysis of straight-tapered assembled pipe conveying nonuniform axial fluid by an active learning Kriging (ALK) method.

In this study, first, the motion equation of straight-tapered assembled pipe conveying nonuniform fluid is built. Second, the Galerkin method is used for calculating the natural frequency of assembled pipe conveying nonuniform fluid. Third, the ALK method based on expected risk function (ERF) is used to calculate the resonance failure probability and moment independent global sensitivity analysis.

The findings of this paper highlight that the eigenfrequency and critical velocity of uniform fluid-conveying pipe are less than the reality and the error is biggest in first-order natural frequency. The importance ranking of input variables affecting the resonance failure can be obtained. The importance ranking is different for a different velocity and mode number. By reducing the uncertainty of variables with a high index, the resonance failure probability can be reduced maximally.

There are no experiments on the eigenfrequency and critical velocity. There is no experiments about natural frequency and critical velocity of straight tapered assembled pipe to verify the theory in this paper.

The originality of this paper lies as follows: the motion equation of straight-tapered pipe conveying nonuniform fluid is first obtained. The eigenfrequency of nonuniform fluid and uniform fluid inside the assembled pipe are compared. The resonance reliability analysis of straight-tapered assembled pipe is first proposed. From the results, it is observed that the resonance failure probability can be reduced efficiently.

The authors investigated how and when work connectivity behavior after-hours (WCBA) spilled over to cyberloafing, considering ego depletion as a mediator and motivations and workaholism as moderators. This paper aims to discuss the aforementioned objective.

In Study 1, 380 employees participated in a scenario experiment with a 2 × 2 between-subjects design. Studies 2 and 3 involved 483 and 406 employees, respectively in two two-wave surveys.

WCBA was indirectly linked to cyberloafing via ego depletion. However, when WCBA was driven by high autonomous and low controlled motivation, it exerted less influence on ego depletion, thus weakening the mediating effect of ego depletion. Moreover, the association between WCBA and ego depletion was not significant among employees accustomed to excessive work. The indirect effect of ego depletion also operated contingently on the level of excessive work.

The findings shed light on the spillover effects of WCBA, suggesting that WCBA may lead to cyberloafing by depleting resources. However, the influence of WCBA on ego depletion is concealed when employees engage in WCBA autonomously or are habituated to excessive work.

The study focuses on influential factors of collaboration on government data security by the Chinese government.

The article explores the case of e-government in the Chinese centralized unitary state system context, using a structured–pragmatic–situational (SPS) approach and the boundary theory as an analytical lens.

The findings indicate that e-government operates in highly interconnected environments where the safe flow of government data requires collaborative and cross-boundary strategies. Any organization is a potential “weakest link”. In addition, collaboration is fragmented by ambiguous accountability and organizational inertia across government departments, resources differences and limited visibility and measurability of security efforts across government levels and conflicts and uncertainties in principal–agent relationships. The solutions for those obstacles are also discussed from the multi-function, multi-level and multi-actor dimensions, respectively. A multi-dimensional overarching security model for the flow of government data is proposed.

The study advances the technology-oriented micro-analysis of previous studies on government data security to cross-organizational revealing at the macrolevel by connecting streams of research in information systems and public administration. These findings will contribute to making the safe flow of government data more resilient in the transformation of e-government.

In response to the challenges of maintaining the configuration and navigation stability of low-cost unmanned aerial vehicle swarms under intermittent global navigation satellite system (GNSS) signal conditions, this study aims to introduce a fast network topology generation algorithm and a hybrid covariance filter.

First, using spatially stable structures and the principle of three-sphere intersection, connectivity between nodes is rapidly generated, ultimately forming a network topology with tetrahedrons as the basic unit. This ensures the stability of the configuration. Subsequently, a problem arises from the improper distribution of internal confidence within the system when some nodes are connected to GNSS, whereas others rely solely on ranging. In response, a hybrid covariance method with independent relative and absolute covariance matrices is proposed, which can improve the overall navigation precision of the swarm.

Simulation results show that the approach achieves rapid convergence of relative positioning errors to less than 0.5 m for internode distances over 100 m. When one, two and three anchor nodes are accessed, the positioning accuracy of the proposed method is improved by 31.59 %, 64.53 % and 64.48 %, respectively, compared with the existing methods.

The proposed method can stabilize configurations and improve overall positioning accuracy, providing support for addressing distributed navigation issues in intermittent GNSS signals.