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This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

This study aims to clarify the evolution law of stress field and fracture field during the mining process of inclined coal seam, to prevent the occurrence of roof burst water and impact ground pressure accident during the advancing process of working face.

The evolution law of stress-fracture field under different mining conditions of inclined coal seam was studied by using discrete element method and similar material simulation method.

The overburden stress at the lower end of the coal seam was mainly transmitted to the deep rock mass on the left side, and the overburden stress at the upper end was mainly transmitted to the floor direction. With the increase of the inclined length of the mining coal seam, the development of the fracture zone gradually evolves from the “irregular arch” form to the “transversely developed trapezoid” form. The development range of the fracture zone was always in the internal area of the stress concentration shell.

An original element of this paper is based on the condition that the dip angle of coal seam is 35°, and the evolution law of overburden stress-fracture field during the excavation of coal seam with different lengths was analyzed by UDEC numerical simulation software. The coupling relationship between stress shell and fracture field was proposed, and the development range of fracture zone was determined by stress. The value of this paper is to provide technical support and practical basis for the safety production of a mine working face.

The purpose of this study is to test the hypotheses proposed by Konadu et al. (2023) for the first time and provide empirical insight on the subject. Corruption concerns affect all economies, but those attempting to avoid foreign grants are especially vulnerable. Stakeholders in these economies have pushed for more honest public sector (PS) workers and better oversight of public funds in an effort to build a more trustworthy and efficient government to improve PS performance. Just as the mechanisms through which employee integrity (EI) influences work performance (WP) have not been proven empirically, neither has the effect of EI on WP in African economies. Also, how purposeful leadership (PL) interacts with EI to boost WP is yet to be empirically examined in the integrity literature.

This paper surveyed and analysed the responses of 875 workers across the three most corrupt large PS organisations in Ghana using Smart PLS 4. Perceived organisational support and contract fulfilment functioned as control factors influencing job satisfaction (JS, a mediator). Psychological need satisfaction and perceived procedural justice serve as control factors for organisational identification (OI, an additional mediator). Education, tenure, job position, sex and age were used as control variables in WP. Product indicator and variance accounted for (VAF) methods were used to estimate the impacts of moderation and mediation, respectively. A 5% level of significance was determined.

As hypothesised, this study found that EI and WP had a significantly positive connection (ß = 0.119, p = 0.026), and both JS (VAF = 25.16%) and OI (VAF = 39.59%) partially mediated this connection. Moreover, PL positively moderated the EI–JS (ß = 0.155, p = 0.000) and EI–OI (ß = 0.095, p = 0.000) connections.

This paper affords empirical insight on the EI–WP relationship, how this relationship is mediated and how the EI–JS and EI–OI relationships are amplified. In this context, it sheds light on new ways in which EI and WP in the PS are improved. In addition, this paper provides a roadmap for forthcoming academics to test the hypotheses in diverse PS contexts globally to triangulate the results.

Leadership in PS organisations must maintain a “values-grounded approach” to all parts of human resource (HR) practices, including hiring, performance reviews, leadership enhancement programmes, training and promotions, if they are to attract, develop and retain employees who stand for the sector’s ethics and beliefs.

This research gives African nations proof that enhancing EI in the PS is important, and it lays out the many ways in which EI transforms into WP. It also draws attention to the challenges that purposeful leaders may help alleviate and the opportunities that they may present.

To the best of the authors’ knowledge, the hypotheses put forward in the conceptual research by Konadu et al. (2023) are tested empirically for the first time in this study. It also adds to the empirical literature that already exists on EI, JS, OI, WP and PL in the PS. This contributes to the disciplines of integrity, performance and leadership by enhancing theoretical frameworks and expanding upon existing knowledge.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

Aero-engine exhaust plume length can be more than the aircraft length, making it easier to detect and track by infrared seeker. Aim of this study is to analyze the effect of free stream Mach number (M_∞) on length of potential core of plume. Also, change in infrared (IR) signature of plume and aircraft surface with variation in elevation angle (θ) is examined.

Convergent divergent (CD) nozzle is located outside the rear fuselage of the aircraft. A two dimensional axisymmetric computational fluid dynamics (CFD) study was carried out to study effect of M_∞ on potential core. The CFD data with aircraft and plume was then used for IR signature analysis. The sensor position is changed with respect to aircraft from directly bottom towards frontal section of aircraft. The IR signature is studied in mid wave IR (MWIR) and long wave IR (LWIR) band.

The potential plume core length and width increases as M_∞ increases. At higher altitudes, the potential core length increases for a fixed M_∞. The plume emits radiation in the MWIR band, whereas the aerodynamically heated aircraft surface emits IR in the LWIR band. The IR signature in the MWIR band continuously decreases as the sensor position changes from directly bottom towards frontal. In the LWIR band the IR signature initially decreases as the sensor moves from the directly bottom to the frontal, as the sensor begins to see the wing leading edges and nose cone, the IR signature in the LWIR band slightly increases.

The novelty of this study comes from the data reported on the effect of free stream Mach number on the potential plume core and variation of the overall IR signature of aircraft with change in elevation angle from directly below towards frontal section of aircraft.

With the rapid advancement in the automotive industry, the friction coefficient (FC), wear rate (WR) and weight loss (WL) have emerged as crucial parameters to measure the performance of automotive braking systems, so the FC, WR and WL of friction material are predicted and analyzed in this work, with an aim of achieving accurate prediction of friction material properties.

Genetic algorithm support vector machine (GA-SVM) model is obtained by applying GA to optimize the SVM in this work, thus establishing a prediction model for friction material properties and achieving the predictive and comparative analysis of friction material properties. The process parameters are analyzed by using response surface methodology (RSM) and GA-RSM to determine them for optimal friction performance.

The results indicate that the GA-SVM prediction model has the smallest error for FC, WR and WL, showing that it owns excellent prediction accuracy. The predicted values obtained by response surface analysis are closed to those of GA-SVM model, providing further evidence of the validity and the rationality of the established prediction model.

The relevant results can serve as a valuable theoretical foundation for the preparation of friction material in engineering practice.

Access to media is more available now than ever before, both physically and digitally. This study was used to investigate the underlying personality traits that influence the decision to purchase either physical or digital books, and extend theory on access to art and provide a unique lens through which marketers can sell digital media.

Study 1 is a field study in which data were collected from several comic book readers and collectors to look at the role that psychological ownership plays in influencing the likelihood of buying physical or digital comics. Specifically, study 1 includes consumers' need for uniqueness and tech savviness as potential influencers. Study 2 extends the findings of study into a new context and manipulates, rather than measures, the identity of the participants. Study 2 looks at the effects of turning a digital object into a non-fungible token (NFT).

This paper demonstrates that consumers who have a high consumer need for uniqueness (CNFU) are more likely to prefer physical media to digital media. Further, it is shown that preference for physical media leads, on average, to more purchases and that the consumer's psychological ownership mediates the effects of CNFU. In addition, this paper shows that higher degrees of tech savviness led to a preference for digital media. Finally, this paper shows that when consumers identify with a collector identity, turning a digital item into an NFT increases their preference for that object.

This work builds off recent research into physical and digital media and is one of the first to examine the specific personality types that prefer each.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.