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The purpose of this paper is to explore the experiences of officers/civilians with dyslexia serving in the police service in England and Wales. Although there has been a growing body of research which has analysed the experiences of offenders and victims with dyslexia, there have been few studies focusing on the experiences of police officers/civilians with this condition. This study employs the social model of disability to conceptualise the experiences of these police officers/civilians from a disability rights perspective.

This applies a quantitative methodology to analyse data on disabling environments experienced by officers/civilians serving in a police service situated in the North of England. The paper collected data from 56 police employees previously diagnosed with dyslexia.

The findings reveal that a significant number of officers were reluctant to disclose that they had dyslexia to their police service. The choice to disclose was a key concern for officers/civilians, as this was directly linked to their experiences of stigmatisation, as well as the risk of their competences being questioned at work. The analysis presents evidence that, although officers/civilians have legal protections under the Equality Act 2010 (c15) in the UK, very few had experienced any form of “reasonable adjustment” in the workplace.

Drawing on the social model of disability, the paper concludes that the police service must improve access to reasonable adjustment, for example, through the use of assistive technologies, to create a more inclusive and supportive working environment for their employees.

Even if there is a wealth of research highlighting the key role of values and cultural significance for heritage management and, defining specific interventions on built heritage, seldom the relation to their leading values and values hierarchy have been researched. How do values and interventions relate? What values trigger most and least interventions on heritage? How do these values relate and characterize interventions? And what are the values hierarchy that make the interventions on built heritage differ?

This paper conducts a systematic content analysis of 69 international doctrinal documents – mainly adopted by Council of Europe, UNESCO, and ICOMOS, during 1877 and 2021. The main aim is to reveal and compare the intervention concepts and their definitions, in relation to values. The intensity of the relationship between intervention concepts and values is determined based on the frequency of mentioned values per intervention.

There were three key findings. First, historic, social, and aesthetical values were the most referenced values in international doctrinal documents. Second, while intervention concepts revealed similar definitions and shared common leading values, their secondary values and values hierarchy, e.g. aesthetical or social values, are the ones influencing the variation on their definitions. Third, certain values show contradictory roles in the same intervention concepts from different documents, e.g. political and age values.

This paper explores a novel comparison between different interventions concepts and definitions, and the role of values. The results can contribute to support further research and practice on clarifying the identified differences.

The research approach is based on the concept that a failure event is rarely random and is often generated by a chain of previous events connected by a sort of domino effect. Thus, the purpose of this study is the optimal selection of the components to predictively maintain on the basis of their failure probability, under budget and time constraints.

Assets maintenance is a major challenge for any process industry. Thanks to the development of Big Data Analytics techniques and tools, data produced by such systems can be analyzed in order to predict their behavior. Considering the asset as a social system composed of several interacting components, in this work, a framework is developed to identify the relationships between component failures and to avoid them through the predictive replacement of critical ones: such relationships are identified through the Association Rule Mining (ARM), while their interaction is studied through the Social Network Analysis (SNA).

A case example of a process industry is presented to explain and test the proposed model and to discuss its applicability. The proposed framework provides an approach to expand upon previous work in the areas of prediction of fault events and monitoring strategy of critical components.

The novel combined adoption of ARM and SNA is proposed to identify the hidden interaction among events and to define the nature of such interactions and communities of nodes in order to analyze local and global paths and define the most influential entities.

Erosion and abrasion are the prominent wear mechanisms reducing the lifetime of machine components. Both wear mechanisms are playing a role meanwhile, generating a synergy, leading to a material removal on the target. The purpose of study is to create a mathematical expression for erosive abrasive wear.

Many factors such as environmental cases and material character have an influence in erosive abrasive wear. In the work, changes in abrasive size and material hardness have been analyzed. As an abrasive particle, quartz sand has been used. All tests have been done in 20 wt.% slurry. Heat treatment has been applied to different steel specimens (steel grades C15, St 37 and Ck45) to change hardness value, which ranged from 185 to 880 Vickers hardness number.

After the four-hour test, it is determined that by an increase in abrasive size and decrease in material hardness, wear rate increases. Worn surfaces of the targets have been examined to figure out the wear mechanisms at different conditions under scanning electron microscopy. The results indicate that by an increase in material hardness, the number and diameter of micro-craters on the worn surfaces decrease. The diameters of micro-craters have been about 3–8 µm in hard materials and about 120–140 µm in soft materials.

It is determined that by an increase in abrasive size and decrease in material hardness, wear rate increases. The results indicate that by an increase in material hardness, the number and diameter of micro-craters on the worn surfaces decrease.

The study enables to indicate the dominant factor in worn steel used in mechanical components.

After analyzing the test results, a novel mathematical expression, considering both abrasive size and material hardness, has been developed.

The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.

In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.

In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.

This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.

The purpose of this paper is to investigate the ability of transition metals (TMs) of iron-, nickel- and zinc-doped graphene nanosheet for adsorption of toxic gas of nitric oxide (NO). The results of this paper have provided a favorable understanding of the interaction between TM-doped graphene nanosheet and NO molecule.

A high performance of TM-doped graphene nanosheet as a gas sensor is demonstrated by modeling the material’s transport characteristics by means of the Langmuir adsorption and three-layered ONIOM/ density functional theory method. The Langmuir adsorption model has been done with a three-layered ONIOM using CAM-B3LYP functional and LANL2DZ and 6–311G (d, p) basis sets by Gaussian 16 revision C.01 program towards the formation of of NO→TM(Mn, Co, Cu)-doped on the Gr nanosheet.

The changes of charge density for Langmuir adsorption of NO on Mn-, Co- and Cu-doped graphene nanosheet orderly have been achieved as: ΔQ_Co-doped = +0.309 >> ΔQ_Mn-doped = −0.074 > ΔQ_Cu-doped = −0.051. Therefore, the number of changes of charge density have concluded a more remarkable charge transfer for Mn-doped graphene nanosheet. However, based on nuclear magnetic resonance spectroscopy, the sharp peaks around Cu doped on the surface of graphene nanosheet and C19 close to junction of N2 and Co17 have been observed. In addition, Cu-doped graphene sheet has a large effect on bond orbitals of C8–Cu 17, C15–Cu 17 and C16–Cu17 in the adsorption of NO on the Cu-doped/Gr which has shown the maximum occupancy. The amounts of ΔGads,NO→Mn−Co through IR computations based on polarizability have exhibited that ΔGads,NO→Mn−Co has indicated the most energy gap because of charge density transfer from the nitrogen atom in NO to Mn-doped graphene nanosheet, though ΔG(NO→Cu−C)0> ΔG(NO→Co−C)0>ΔG(NO→Mn−C)0.

This research aims to explore the adsorption of hazardous pollutant gas of “NO” by using carbon nanostructure doped by “TM” of iron, nickel and zinc to evaluate the effectiveness of adsorption parameters of various TM-doped graphene nanosheets.

This paper aims to explore consumers’ voluntary disposition practices through swapping events organised by community-based enterprises. The paper investigates consumers’ decision-making strategies and factors affecting voluntary clothing disposition via public swapping events across the UK.

This paper investigates UK swapping events, through conducting 18 semi-structured consumer interviews. Data were transcribed and analysed using the seven-step guide proposed by Easterby-Smith et al. (2018).

Findings indicate that within community-based enterprises an implicit social contract emerges between the enterprises and swappers which has an influence on the clothing brought to swaps, thereby impacting the competence and meaning elements of practice. This is linked to peer-pressure susceptibility which affects consumers’ participation in swapping. The findings further reveal an emerging consumer strategy aiding decision-making process regarding items brought to swaps. The use of a particular strategy is found to be linked with the respective level of swapping expertise.

Though the interviews provide a rich narrative, this paper is limited by its sample size meaning data cannot be generalised. Although the data is limited by singular country perspective, research participants were recruited from across the UK, thus, offering a broad picture of the swapping practice.

This paper contributes to and advances an understanding of swapping events organised by community-based enterprises. The theory of social practice lens offers a unique viewpoint on the elements influencing the consumers’ decision-making process with reference to voluntary disposition.

Increasingly, dynamic market environments lead to growing complexity in manufacturing and pose a severe threat for the competitiveness of manufacturing companies. Systematic guidance to manage this complexity, especially in the context of Industry 4.0 and the therewith rising trends such as digitalization and data-driven production optimization, is lacking. To address this deficit a case-based reasoning (CBR) system for providing knowledge about managing complexity in Industry 4.0 is presented.

First, the explicit knowledge representation for managing complexity in IT-based manufacturing is introduced. Second, the CBR process step to retrieve knowledge from an artificially composed case base with in total 70 cases of data-based complexity management in the context of Industry 4.0 is set out. Third, knowledge transfer alongside several maturity levels of information technology capabilities of manufacturing systems for reuse in new problem scenarios is introduced.

The paper comprises the conceptual approach for designing a CBR system to support data-based complexity management in manufacturing systems. Furthermore, the appropriateness of the CBR system to provide applicable knowledge for reducing and managing complexity in corporate practice is shown.

The presented research results are evaluated in the course of an embedded single case study and may therefore lack generalizability. Future research to test and enhance the appropriateness of the developed CBR system will strengthen the research contribution.

The paper provides a novel approach to systematically support knowledge transfer for data-based complexity management by transferring the well-known and established methodology of CBR to the rising application domain of manufacturing systems in the context of Industry 4.0.

The purpose of this study is to explore a sustainable hierarchical framework for the business environment in smart cities. However, this hierarchical framework must consider unnecessary attributes and interrelationships between criteria to capture the difference between smart cities and traditional cities.

Hence, the fuzzy set theory is used for screening unnecessary attributes, the decision-making and trial evaluation laboratory (DEMATEL) is applied to manage the complex interrelationships among the aspects and attributes and interpretive structural modeling (ISM) is used to divide the hierarchy and construct a hierarchical theoretical framework. Ultimately, this research is applied to develop a sustainable hierarchical framework of the business environment in smart cities.

The results show that traditional social problems are still at the core of business environment development in smart cities, new smart opportunities may be discovered, but they are still limited by traditional social factors, the economy is still the main aspect of the business environment and there are still obstacles to solving social problems with smart technologies.

This theoretical hierarchical framework aims to guide smart cities toward sustainability. This study also proposes creating a predictable business environment by improving administrative efficiency, transparency, social mobility and infrastructure services and cultivating new business opportunities with intelligent technology.

The purpose of this paper is to implement the mathematical models to predict concretes physico-mechanical characteristics made with binary and ternary sands using a mixture design method. It is a new technique that optimizes mixtures without being obliged to do a lot of experiments. The goal is to find the law governing the responses depending on mixture composition and capable of taking into account the effect of each parameter separately and in interaction between several parameters on the characteristics studied.

Mixture design method was used for optimizing concretes characteristics and studying the effects of river sand (RS), dune sand (DS) and crushed sand (CS) in combinations of binary system and ternary on workability, the compressive and flexural strengths of concretes at 7 and 28 days. A total of 21 mixtures of concrete were prepared for this investigation. The modeling was carried out by using JMP7 statistical software.

Mixture design method made it possible to obtain, with good precision, the statistical models and the prediction curves of studied responses. The models have relatively good correlation coefficients (R² = 0.70) for all studied responses. The use of binary and ternary mixtures sands improves the workability and their mechanical strengths. The obtained results proved that concrete, based on binary mixture C15, presents the maximum compressive strength (MCS) on 28 day with an improvement of around 20%, compared to reference concrete (C21). For ternary mixtures, MCS on 28 day was obtained for the mixture C10 with an improvement of around 15% compared to C21. Increase in compressive strength during the progress of hydration reactions was accompanied by an increase in the flexural strength, but in different proportions.

The partial incorporation of DS (= 40%) in the concrete formulation can provide a solution for some work in the southern regions of country. In addition, the CS is an interesting alternative source for replacing 60% of RS. The concrete formulation based on local materials is really capable of solving the economic and technical problems encountered in the building field, as well as environmental problems. Local resources therefore constitute an economic, technological and environmental alternative.