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With the rapid development of internet technology, open online social networks provide a broader platform for information spreading. While dissemination of information provides convenience for life, it also brings many problems such as security risks and public opinion orientation. Various negative, malicious and false information spread across regions, which seriously affect social harmony and national security. Therefore, this paper aims to minimize negative information such as online rumors that has attracted extensive attention. The most existing algorithms for blocking rumors have prevented the spread of rumors to some extent, but these algorithms are designed based on entire social networks, mainly focusing on the microstructure of the network, i.e. the pairwise relationship or similarity between nodes. The blocking effect of these algorithms may be unsatisfactory in some networks because of the sparse data in the microstructure.

An algorithm for minimizing the influence of dynamic rumor based on community structure is proposed in this paper. The algorithm first divides the network into communities, and integrates the influence of each node within communities and rumor influence probability to measure the influence of each node in the entire network, and then selects key nodes and bridge nodes in communities as blocked nodes. After that, a dynamic blocking strategy is adopted to improve the blocking effect of rumors.

Community structure is one of the most prominent features of networks. It reveals the organizational structure and functional components of a network from a mesoscopic level. The utilization of community structure can provide effective and rich information to solve the problem of data sparsity in the microstructure, thus effectively improve the blocking effect. Extensive experiments on two real-world data sets have validated that the proposed algorithm has superior performance than the baseline algorithms.

As an important research direction of social network analysis, rumor minimization has a profound effect on the harmony and stability of society and the development of social media. However, because the rumor spread has the characteristics of multiple propagation paths, fast propagation speed, wide propagation area and time-varying, it is a huge challenge to improve the effectiveness of the rumor blocking algorithm.

Dry eye syndrome is one of the most common reasons for eye-related discomfort which, without treatment, in some cases may even lead to corneal damage. Blinking, baseline and reflex lachrymation and drainage compromise the topical application of therapeutics demanding repeated, often hourly applications of common lubricants. In contrast, topically administered chitosan-N-acetylcysteine-based eye drops were reported to sustain on the ocular surface for more than 24 h. The thiolated biopolymer can interact with the corneal mucin layer thereby forming covalent disulphide bridges, which may contribute to extended residence times.

In this study, the tribological characteristics of four different lubricants including hyaluronic acid and chitosan-N-acetylcysteine containing commercially available eye drops were investigated. For this purpose, a representative test setup was developed, which mimics the contact between the cornea and the eyelid wiper. Gels with different elastic properties coated with a mucin layer were used as a substrate to mimic the corneal surface. Tests were conducted with a micro-tribometer, and friction values were recorded. Contact zones were characterized by X-ray photoelectron spectroscopy to investigate wear and thiol bonding on the surface.

Results revealed the lowest average coefficient of friction values for chitosan-N-acetylcysteine-based eye drops and substrate dependence of the test setup.

In this study, the authors introduced an in vitro system to test different types of eye drops so that chemical interaction with the mucin layer can be observed. These interactions change the tribological performance significantly and must be considered to have results relevant to the actual application.

Seaports play an immeasurable role in the advancement of international trade. They have been the common avenue for the transportation of goods and services from one continent to another, and it has also been the linking transport of one mode of transport to another. The study sought to assess the effect of paperless information technology (IT)-based custom clearance at Ghana Seaports on businesses and industrial supply chains in Ghana.

The study conducted a survey with a sample size of 200 trading firms in Ghana.

The study discovered that IT-based port clearance has positive impact on customer order fulfillment, transaction cost reduction and supply chain relationships.

With the aim of making Ghana the transportation hub of businesses in the sub region, the paperless custom clearance has the potential to reduce delays at the port and improve their supply chain.

This paper provides researchers with a contemporary perspective toward understanding the effect of paperless custom clearance on the supply chain of businesses in the West African sub region.

This paper aims to investigate the wear behaviour of different materials for cylinder liners and piston rings in a linear reciprocating tribometer with special focus on the wear of the cylinder liner in the boundary lubrication regime.

Conventional nitrided steel, as well as diamond-like carbon and chromium nitride-coated piston rings, were tested against cast iron, AlSi and Fe-coated AlSi cylinder liners. The experiments were carried out with samples produced from original engine parts to have the original surface topography available. Radioactive tracer isotopes were used to measure cylinder liner wear continuously, enabling separation of running-in and steady-state wear.

A ranking of the material pairings with respect to wear behaviour of the cylinder liner was found. Post-test inspection of the cylinder samples by scanning electron microscopy (SEM) revealed differences in the wear mechanisms for the different material combinations. The results show that the running-in and steady-state wear of the liners can be reduced by choosing the appropriate material for the piston ring.

The use of original engine parts in a closely controlled tribometer environment under realistic loading conditions, in conjunction with continuous and highly sensitive wear measurement methods and a detailed SEM analysis of the wear mechanisms, forms an intermediate step between engine testing and laboratory environment testing.

Sustainable manufacturing is one of the most important and most challenging issues in present industrial scenario. With the intention of diminish negative effects associated with cutting fluids, the machining industries are continuously developing technologies and systems for cooling/lubricating of the cutting zone while maintaining machining efficiency. In the present study, three regression based machine learning techniques, namely, polynomial regression (PR), support vector regression (SVR) and Gaussian process regression (GPR) were developed to predict machining force, cutting power and cutting pressure in the turning of AISI 1045. In the development of predictive models, machining parameters of cutting speed, depth of cut and feed rate were considered as control factors. Since cooling/lubricating techniques significantly affects the machining performance, prediction model development of quality characteristics was performed under minimum quantity lubrication (MQL) and high-pressure coolant (HPC) cutting conditions. The prediction accuracy of developed models was evaluated by statistical error analyzing methods. Results of regressions based machine learning techniques were also compared with probably one of the most frequently used machine learning method, namely artificial neural networks (ANN). Finally, a metaheuristic approach based on a neural network algorithm was utilized to perform an efficient multi-objective optimization of process parameters for both cutting environment.

This study aims to focus on the development of an experimental setup for testing tribological pairings under a gas atmosphere at pressures up to 10 bar.

A pressure chamber allowing oscillating movement through an outer shaft was constructed and mounted on an oscillating tribometer. Due to a metal spring bellows system, a methodology for the evaluation of the coefficient of friction values separately from the spring forces was developed.

The selected material concept was qualitatively and quantitatively assessed. An evaluation of the static and the dynamic coefficient of friction was performed, which was crucial for the understanding of the adhesion effects of the tested material pairing. The amount of information that is lost due to averaging the measured friction values is higher than one would expect.

The developed experimental setup is unique and, compared with the existing tribometers for testing under gas ambient pressures, allows testing under contact conditions that are closer to real applications, such as compressors and expanders. An in-depth observation of the adhesion and stick–slip effects of the tested material pairings is possible as well.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2023-0173/

Increasing carbon productivity is an effective way to reduce carbon emissions, while boosting economic prosperity. For appropriate formulating and enforcement of energy saving and carbon emissions reduction policies in various sectors, it is of great significance to investigate the evolution characteristics and convergence modes of carbon productivity across the manufacturing sectors.

Using slack-based measure directional distance function (SBM-DDF) and global Malmquist–Luenberger (GML) productivity index, this paper measures the carbon productivities of 29 manufacturing subsectors in Shanghai, China, from 2001 to 2016 under the total factor framework. Furthermore, based on the convergence theories, it empirically examines the convergence of carbon productivity across these manufacturing sectors.

The measurement results suggest that the carbon productivities of the manufacturing sectors in Shanghai show an increasing tendency on the whole, and technical efficiency instead of technological change makes a main contribution to the increase. It is found that there is no obvious σ convergence across the manufacturing sectors in Shanghai, but there exist both absolute ß convergence and conditional ß convergence. Moreover, there is heterogeneity in convergence characteristics between the clean sectors and polluting sectors. The findings also show that firm size and industry structure have significant positive impacts on the growth of carbon productivities of the manufacturing sectors, whereas the impacts of capital deepening and energy consumption structure are significantly negative.

This paper measures the carbon productivities of the manufacturing subsectors by applying SBM-DDF and GML index, so as to improve the accuracy. It provides an insight into the convergence of carbon productivity across the manufacturing sectors.

This research aimed to investigate the mediating role of social media engagement in the relationship between differentiation-oriented content and purchase intentions. Additionally, this research studies the moderating impact of entrepreneurial social media skills in the relationship between social media engagement and purchase intentions.

The research proposes a positivist research philosophy, deductive research approach and survey research strategy. Data were collected from followers of social media pages of small and medium businesses operating in the fields of groceries, food items, apparel and supplies in Pakistan. Respondents were selected randomly. The descriptive statistics were calculated first, followed by reliability and validity analysis as part of the measurement model. Finally, mediation and moderation analyses were run by using structural equation modeling.

Results of the study confirm that differentiation-oriented content has a positive relationship with purchase intentions and social media engagement mediates this relationship. Results further confirm that the social media skills of entrepreneurs moderate the relationship between social media engagement and purchase intentions.

From a practical point of view, this study will potentially help entrepreneurs in Pakistan unveil the undiscovered potential of social media and understand the importance of social media marketing campaigns in crisis situations. It will unlock the importance of entrepreneurial training and development to better adapt to the dynamic and vibrant world of social media.

This is the first study that investigates the relationship between differentiation-oriented content and purchase intentions. Additionally, the current study adds to existing knowledge by proposing entrepreneurial social media skills as moderators in the relationship of social media engagement with purchase intentions.

Striving to achieve the goal of carbon neutrality before 2060 indicates that China, as the most extensive power system in the world and a country based on coal power, is imperative to improve the technical level of electric power utilization. This paper aims to explore the nonlinear evolution mechanism of power technology progress under the constraints of net-zero carbon dioxide emissions in China.

This paper, first, based on China’s provincial panel data from 2000 to 2019, uses global direction distance function to measure power technological progress. Second, the threshold regression model is used to explore the nonlinear relationship between carbon emission reduction constraints on electric power technological progress.

There is a significant inverted U-shaped relationship between China’s provincial carbon emission reduction constraints and electric power technological progress. Meanwhile, the scale of regional economic development has a significant moderating effect on the relationship between carbon emission reduction constraints and power technological progress.

This paper puts forward targeted suggestions for perfecting regional carbon emission reduction policy and improving electric power technological progress.

Based on the global directional distance function, this paper extracts power as a production factor in total factor productivity and calculates the total factor electric power technological progress. This paper objectively reveals the influence mechanism of carbon emission reduction constraints on electric power technology progress based on the threshold regression model.

The purpose of this paper is to analyze the effect of environmental policy China’s national program to address climate change on carbon emission efficiency.

Based on the directional distance function, the provincial total factor carbon emission efficiency was measured. Then, the authors analyzed the effect of environmental policy on carbon emission efficiency based on a difference in difference model.

Carbon emission efficiency has been significantly improved since the environmental policy China’s national program to address climate change was put forwarded, but the positive impact in different periods and regions is different. In addition, the environmental policy improves the carbon emission efficiency through the reduction of energy intensity and adjustment of the industrial structure.

This is the first time to use difference in difference model to use a difference in difference model to quantitatively assess the influence of environmental policy China’s national program to address climate change on carbon emission efficiency.