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This paper aims to study the impact of consumers’ corporate social responsibility (CSR) associations on corporate financial performance and the moderating role of market competition.

The panel data set is analyzed using a random effects regression model. The analyzed data is based on the unique RepZ Responsibility scores published by the global research agency Kantar Millward Brown and contains information about consumer CSR associations.

This study reveals CSR associations' positive, lagged, direct impact on firms’ market value. Market competition moderates this relationship in the way that a company’s market value benefits more from consumers' CSR associations when facing high rather than low market competition.

Consumers' CSR perceptions increase the market value of a company. This effect is intensified when brands are exposed to intense competition, which allows conclusions about CSR as a differentiation strategy to be drawn: To stand out in a competitive market, brands should prioritize improving their CSR associations among consumers to differentiate themselves and increase their market value.

To the best of the authors’ knowledge, this study is the first to test the effect of consumers’ CSR associations on forward-looking financial performance measures. Moreover, by analyzing the moderating effect of market competition on the relationship between CSR associations and firms' market value, this study provides information about the differentiating power of CSR from a brand perspective using a panel-data analysis.

The purpose of this paper is to construct a statistical hypotheses test for process capability indices and compare the pairs of them with a fixed sample size.

Since the sampling distribution of the estimators of pairs of two process capability indices (PCIs) is very complex, an exact statistical hypothesis test for them cannot be constructed. Therefore, the authors have proposed a bootstrap method to construct the hypothesis test for them on the basis of p-value.

The authors have shown that by increasing n, the bootstrap method has better output relative to other methods and it can be easily implemented. The authors have also demonstrated that sometimes an exact hypotheses test cannot be constructed and need some assumptions.

In the present paper, several methods to test of hypotheses about the difference between two process capability indices have been compared.

Self‐compacting concrete (SCC) offers several economic and technical benefits; the use of steel fibers extends its possibilities. Steel fibers bridge cracks, retard their propagation, and improve several characteristics and properties of the SCC. The purpose of this paper is to investigate the effects of type and volume fraction of steel fiber on the compressive strength, split tensile strength, flexural strength and modulus of elasticity of steel fiber reinforced self‐compacting concrete (SFRSCC).

For this purpose, Micro wire and Wave type steel fibers with l/d ratios of 50 were used. Three different fiber volumes were added to concrete mixes at 0.5, 0.75 and 1 per cent by volume of SCC. Six different SFRSCC mixes were prepared. After 28 days of curing, compressive, split and flexural strength and modulus of elasticity were determined.

It was found that, inclusion of steel fibers significantly affect the split tensile and flexural strength of SCC accordance with type and v_f. Besides, mathematical expressions were developed to estimate the flexural, modulus of elasticity and split tensile strength of SFRSCCs regarding of compressive strength.

It was found that inclusion of steel fibers significantly affected the split tensile and flexural strength of SCC accordance with type and f v.

The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength development. This study aims to predict the compressive strength of normal concrete and high-performance concrete using four datasets.

In this paper, five established individual Machine Learning (ML) regression models have been compared: Decision Regression Tree, Random Forest Regression, Lasso Regression, Ridge Regression and Multiple-Linear regression. Four datasets were studied, two of which are previous research datasets, and two datasets are from the sophisticated lab using five established individual ML regression models.

The five statistical indicators like coefficient of determination (R²), mean absolute error, root mean squared error, Nash–Sutcliffe efficiency and mean absolute percentage error have been used to compare the performance of the models. The models are further compared using statistical indicators with previous studies. Lastly, to understand the variable effect of the predictor, the sensitivity and parametric analysis were carried out to find the performance of the variable.

The findings of this paper will allow readers to understand the factors involved in identifying the machine learning models and concrete datasets. In so doing, we hope that this research advances the toolset needed to predict compressive strength.

The purpose of this paper is to employ an extended Kalman filter for implementing an AHRS (attitude and heading reference system) with acceleration compensation, thereby improving the reliability of such systems, since this removes the usual restrictive assumption that the vehicle is undergoing a non‐accelerated maneuver.

MARG (magnetic, acceleration and rate gyros) sensors constitute the basic hardware, which are integrated by the Kalman filter. The error dynamics for attitude and gyro biases is obtained in the navigation frame, providing a much simpler approach than usually taken in the literature, since it relies on direct quaternion differentiation. The state vector associated to the error dynamics possesses six components: three are associated to the quaternion error and three concern gyro bias estimates.

The AHRS is implemented in an ARM (Advanced RISC Machine) processor and tested with experimental data. The accelerated case is treated by two complementary approaches: by changing the noise variance in the Kalman filter, and by obtaining an acceleration information from GPS (global positioning system) velocity measurements. Experimental results are presented and the performance is compared with commercial ARHS systems.

The proposed AHRS can be implemented with low cost MARG sensors, and GPS aiding, with use for instance in UAV (unmanned aerial vehicle) and small aircrafts' attitude estimation, for navigation and control applications.

Usually the AHRS designs employ as states total gyro bias and Euler angles, or quaternion, and do not consider the accelerated case. Here the state is comprised by gyro bias and quaternion error variables, which attenuates the effect of nonlinearities, and two complementary procedures tackle the accelerated case: acceleration correction by using a GPS derived acceleration signal and change in the output noise covariance used by the Kalman filter.

The purpose of this study is to perform comprehensive investigation to assess the mechanical properties of nano-modified ternary cement concrete blend. Nano silica (NS) (1%, 2% and 3%) and waste marble dust powder (MD) (5%, 10% and 15%) was incorporated as a fractional substitution of cement in the concrete matrix.

In this experimental study, 10 cementitious blends were prepared and tested for compressive strength, flexural strength, splitting tensile strength and static modulus of elasticity. The microstructural characteristics of these blends were also explored using a scanning electron microscope along with energy dispersive spectroscopy and X-ray reflection.

The results indicate an enhancement in mechanical properties and refinement in pore structure due to improved pozzolanic activities of NS and the filling effect of MD.

To the best of the authors’ knowledge, no study has reported the mechanical and microstructural behavior of concrete containing marble and NS.

This study aims to present the results of an experimental evaluation of low (M30), mid (M40) and high (M50) grade self-compacting concrete (SCC) with three nominal maximum aggregate sizes (NMAS), namely, 20 mm, 16 mm and 12.5 mm, with Bailey gradation (BG) in comparison with Indian standard gradation (ISG).

This study was conducted in a laboratory by testing the characteristics of fresh and hardened properties of self-compacting concrete.

Rheological and mechanical properties of SCC were evaluated in detail and according to the results, a concrete sample containing lower NMAS with BG demonstrated improvement in modulus of elasticity and compressive strength, while improving the rheological properties as well. Meanwhile, SCC demonstrated poor performance in split tensile and flexural strengths with lower NMAS gradations and a direct correlation was evident as the increase in NMAS caused an increase in the strength and vice-versa.

Upon comparison of BG with ISG, it was revealed that BG mixes succeeded to demonstrate superior performance. From the material optimization, rheological and mechanical performance study, it is recommended that BG with NMAS 16 mm can be used for conventional SCC.

This study aimed to present a model for the use of augmented reality (AR) in the libraries of universities of medical sciences. The goal was to introduce the applications, advantages, opportunities and challenges of AR.

This study adopted a qualitative approach, had an applied goal and was based on data theory. The statistical population comprised 20 experts in the field of AR, and the data were collected based on in-depth semi-structured interviews until achieving theoretical saturation. A model was proposed after open coding and the formation of the main categories, and the use of AR in the development of libraries of medical universities was discussed.

The category of application consisted of strengthening education, promoting users' information literacy, finding resources, user guidance, gamification, educational justice, helping management, enriching resources, providing new services and economic savings. The advantages were library services, sociocultural excellence, educational level, software potential and helping the librarian. The challenges were technical, economic and cultural barriers. Libraries can attract many users by enacting effective policies, using technology and enriching the content of resources. AR can greatly assist library management and improve the librarians' and users' professional activities.

The limitation of this study was that some experts could not participate in the interviews.

The results of this study are beneficial for managers, librarians, students and researchers. The use of AR in libraries is essential for achieving fourth-generation libraries. AR will be a necessity for the libraries of medical universities.

The study aimed to listen to refugee survivors of sexual and gender-based violence (SGBV) and/or torture and explore what justice meant to them in exile. This study argues that what the survivors who participated in this research wanted was “viable justice”. The research was funded by the British Academy and Leverhulme Trust.

Using a survivor-focussed justice lens combined with a trauma-informed approach, narrative interviews were held with 41 women and 20 men refugee survivors living in refugee settlements in Northern Uganda. The researchers also conducted semi-structured interviews with 37 key informants including refugee welfare councils, the UN, civil society, non-government and government organisations. Thematic analysis of the data resulted in the following themes being identified: no hope of formal justice for atrocities that occurred in South Sudan; insecurity; lack of confidence in transitional justice processes in Ugandan refugee settlements; abuse and loss of freedom in refugee settlements; and lack of access to health and justice services in refugee settlements.

This study argues that what the survivors who participated in this research wanted was “viable justice”. That is justice that is survivor-centred and includes elements of traditional and transitional justice, underpinned by social justice. By including the voices of both men and women survivors of SGBV and/or torture and getting the views of service providers and other stakeholders, this paper offers an alternative form of justice to the internationally accepted types of justice, which offer little relevance or restitution to refugees, particularly where the crime has been committed in a different country and where there is little chance that perpetrators will be prosecuted in a formal court of law.

The research findings are based on a small sample of South Sudanese refugees living in three refugee settlements in Northern Uganda. Thus, wider conclusions should not be drawn. However, the research does suggest that a “viable justice” approach should be implemented that is gender and culturally sensitive and which could also be trialled in different refugee contexts.

Improvements in refugee survivors’ dignity, resilience and recovery are dependent upon the active engagement of refugees themselves using a “survivor-focussed approach” which combines formal and community-based health services with traditional and transitional justice responses.

The provision of a “viable justice approach” ensures those who have experienced SGBV and/or torture, and their families, feel validated. It will assist them to use their internal, cultural and traditional resilience and agency in the process of recovery.

The research findings are original in that data was collected from men and women survivors of SGBV and/or torture and service providers. The empirical evidence supports this study’s recommendation for an approach that combines both formal and survivor-focussed approaches towards health and viable justice services to meet the needs of refugees living in refugee settlements. This is a response that listens to and responds to the needs of refugee survivors in a way that continues to build their resilience and agency and restores their dignity.