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To better understand factors that lead to business model innovation (BMI) in organizations, this study argues that inclusive leadership is the primary source that motivates employee engagement in boundary-spanning activities, which fosters BMI by generating and integrating employee knowledge through boundary-spanning exploration.

This paper analyzes the relationships between inclusive leadership, boundary-spanning exploration and BMI to discover how they influence each other. This is achieved by a survey of more than 30 enterprises in Zhejiang Province, China. The survey data are analyzed using SPSS.

Inclusive leaders who display characteristics of openness, accessibility and availability have a positive effect on BMI and boundary-spanning exploration; openness and accessibility have more significant positive effect on BMI and boundary-spanning exploration.

Because this study covers only in Zhejiang Province, in China, the findings may not be easily generalizable to other contexts. Other factors, such as organizational structure and contextual characteristics, could also be added as antecedents in a future investigation. Moreover, the scales could be revised more suitable for China in the future.

The empirical findings can be used as guidelines for firms seeking to take advantage of inclusive leadership and to help firms motivate their employees to engage in boundary-spanning exploration to acquire, generate and integrate knowledge from diverse sources to promote BMI.

This study provides insights that will be of value by adding to the theoretical foundation of our understanding of the antecedents to firms' BMI. This study argues that employees' boundary-spanning exploration is important to BMI as well. Inclusive leadership is crucial to stimulate boundary-spanning exploration by employees. Therefore, how to encourage inclusive leadership in firms is well worth examining.

This paper aims to study the issues of output reachable set estimation for the linear singular Markovian jump systems (SMJSs) with time-varying delay based on a proportional plus derivative (PD) bumpless transfer (BT) output feedback (OF) control scheme.

To begin with, a sufficient criterion is given in the form of a linear matrix inequality based on the Lyapunov stability theory. Then, a PD-BT OF controller is designed to keep all the output signs of the system are maintain within a predetermined ellipsoid. Finally, numerical and practical examples are used to demonstrate the efficiency of the approach.

Based on PD control and BT control method, an OF control strategy for the linear SMJSs with time-varying delay is proposed.

The output reachable set synthesis of linear SMJSs with time-varying delay can be solved by using the proposed approach. Besides, to obtain more general results, the restrictive assumptions of some parameters are removed. Furthermore, a sufficiently small ellipsoid can be obtained by the design scheme adopted in this paper, which reduces the conservatism of the existing results.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.

The purpose of this paper is to improve the seal performance by proper design of the cavity shape of the damping holes, especially the rotordynamics characteristics of the hole-pattern damped seal (HPDS).

A new damping seal structure that comprises a circle-shaped cavity and two directional leaf-shaped cavities with a dovetail-shaped diversion groove is proposed. The comparative study on the sealing characteristics of dovetail-shape, leaf-shape and classical circular HPDSs was carried out using ANSYS CFX.

The dovetail-shaped HPDS significantly outperformed two other damping seal designs in leakage and rotordynamic performance. At a rotating speed of 7,500 rpm, it showed a 25% reduction in leakage, a 23% increase in average effective damping and a 119% increase in average effective stiffness. The cross-coupled stiffness K_xy shifted from positive to negative, reducing circumferential flow. The dovetail's inclined leaf-shaped grooves create a double vortex that slows jet velocity in the seal clearance and alters spiral flow direction, resulting in a uniform pressure distribution and enhanced rotor stability at low frequencies.

This study proposes a novel HPDS with dovetail-shaped diversion grooves. The seal can realize the simultaneous improvement of rotordynamics and leakage characteristics compared to the current seal structure.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0127/

This study aims to investigate the effect of V doping on the microstructure, chemical stability, mechanical and vacuum tribological behavior of sputtered MoS₂ coatings.

The MoS₂-V coatings are fabricated via tuning V target current by magnetron sputtering technique. The structural characteristic and elemental content of the coatings are measured by field emission scanning electron microscopy, X-ray diffractometer, electron probe X-ray micro-analyzer, Raman, X-ray photoelectron spectroscopy, high resolution transmission electron microscope and energy dispersive spectrometer. The hardness of the deposited coatings are tested by a nanoindentation technique. The vacuum tribological properties of MoS₂-V coatings are studied by a ball-on-disc tribometer.

Introducing V into the MoS₂ coatings results in a more compact microstructure. The hardness of the coatings increases with the doping of V. The MoS₂-V coating deposited at a current of 0.2 A obtains the lowest friction coefficient (0.043) under vacuum. As the amount of V doping increases, the wear rate of the coating decreases first and then increases, among which the coating deposited at a current of 0.5 A has the lowest wear rate of 2.2 × 10–6 mm³/N·m.

This work elucidates the role of V doping on the lubrication mechanism of MoS₂ coatings in a vacuum environment, and the MoS₂-V coating is expected to be applied as a solid lubricant in space environment.

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/

In general, the existing compressor design methods require abundant knowledge and inspiration. The purpose of this study is to identify an intellectual design optimization method that enables a machine to learn how to design it.

The airfoil design process was solved using the reinforcement learning (RL) method. An intellectual method based on a modified deep deterministic policy gradient (DDPG) algorithm was implemented. The new method was applied to agents to learn the design policy under dynamic constraints. The agents explored the design space with the help of a surrogate model and airfoil parameterization.

The agents successfully learned to design the airfoils. The loss coefficients of a controlled diffusion airfoil improved by 1.25% and 3.23% in the two- and four-dimensional design spaces, respectively. The agents successfully learned to design under various constraints. Additionally, the modified DDPG method was compared with a genetic algorithm optimizer, verifying that the former was one to two orders of magnitude faster in policy searching. The NACA65 airfoil was redesigned to verify the generalization.

It is feasible to consider the compressor design as an RL problem. Trained agents can determine and record the design policy and adapt it to different initiations and dynamic constraints. More intelligence is demonstrated than when traditional optimization methods are used. This methodology represents a new, small step toward the intelligent design of compressors.

Based on DNase I and reduced graphene oxide (rGO)-magnetic silicon microspheres (MNPS), a highly sensitive and selective fluorescent probe for the detection of PD-L1 was developed.

Here °C we present a feasibility of biosensor to detection of PD-L1 in lung tumors plasma. In the absence of PD-L1°C the PD-L1 aptamer is absorbed on the surface of graphene oxide modified magnetic nanoparticles °8rGO-MNPS°9 and leading to effective fluorescence quenching. Upon adding PD-L1°C the aptamer sequences could be specifically recognized by PD-L1 and the aptamer/PD-L1 complex is formed°C resulting in the recovery of quenched fluorescence.

This sensor can detect PD-L1 with a linear range from 100 pg mL⁻¹ to 100 ng mL⁻¹, and a detection limit of 10 pg•m⁻¹ was achieved.

This method provides an easy and sensitive method for the detection of PD-L1 and will be beneficial to the early diagnosis and prognosis of tumors.

The purpose of this paper is to study the working characteristics of hydro-viscous clutch at high rotational speeds and obtain the trend of flow field variation of oil film.

The FLUENT simulation model of the oil film between the friction disks is built. The effect of variation of working parameters such as input rotational speed, oil flow rate and film thickness on two-phase flow regime and transmission torque is studied by using the volume of fluid model.

The results show that the higher the rotational speed, the severer the cavitation is. In addition, the two-phase flow region makes the coverage of oil film over the friction pairs’ surface reduce, which results in a decrease in transmission torque for the hydro-viscous clutch.

These simulation results are of interest for the study of hydro-viscous drive and its applications. This study can also provide a theoretical basis for power transmission mechanism of oil film by considering the existence of a two-phase flow regime consisting of oil and air.

The leakage problem caused by machining error, assembly error, wearing and thermal deformation has been the main factor hindering the development of scroll compressor. This paper aims to investigate the lubrication characteristics of radial clearance and further optimize the radial clearance, which can reduce the leakage in the tangential direction of the working chamber.

This paper establishes a model of radial clearance oil film lubrication in scroll compressor. And, the method to solve the Reynolds and energy equations is presented, as well as the dimensionless and discretization by finite element difference method. To verify the established model, performance experiment of scroll compressor for electric vehicle air conditioning system is also carried out.

Based on the presented model, the temperature field and distribution of the oil film in the radial clearance are analyzed. And the influence of the structural parameter on the radial clearance is further discussed. The optimum radial clearance could be achieved at β = 40°–42°, where the orbiting scroll is in the state of rotary balance. And, the simulation results coincide well with the experimental results.

This work provides an effective model to evaluate the lubrication characteristics of radial clearance in scroll compressor, which can provide guidance for the design of scroll compressor.