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This study aims to propose the adoption of artificial neural network (ANN)-based prediction intervals (PIs) to give more reliable prediction of labour productivity using historical data.

Using the proposed PI method, various sources of uncertainty affecting predictions can be accounted for, and a PI is proposed instead of a less reliable single-point estimate. The proposed PI consists of a lower and upper bound in which the realization of the predicted variable, namely, labour productivity, is anticipated to fall with a defined probability and represented in terms of a confidence level (CL).

The proposed PI method is implemented on a case study project to predict labour productivity. The quality of the generated PIs for the labour productivity is investigated at three confidence levels. The results show that the proposed method can predict the value of labour productivity efficiently.

This study is the first attempt in construction management to undertake a shift from deterministic point predictions to interval forecasts to improve the reliability of predictions. The proposed PI method will help project managers obtain accurate and credible predictions of labour productivity using historical data. With a better understanding of future outcomes, project managers can adopt appropriate improvement strategies to enhance labour productivity before commencing a project.

Point predictions provided by traditional deterministic ANN-based forecasting methodologies may be unreliable due to the different sources of uncertainty affecting predictions. The current study proposes ANN-based PIs as an alternative and robust tool to give a more reliable prediction of labour productivity using historical data. Using the proposed method, various sources of uncertainty affecting the predictions are accounted for, and a PI is proposed instead of a less reliable single point estimate.

This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.

A new data augmentation approach that has improved the model robustness against different illumination conditions and overfitting is proposed. This study uses data augmentation at test time and adds outlier samples to training set to prevent over-fitted network training. For data augmentation at test time, five segments are extracted from each sample image and fed to the network. For these images, the network outputting average values is used as the final prediction. Then, the proposed approach is evaluated on multiple deep networks used as material classifiers. The fully connected layers are removed from the end of the networks, and only convolutional layers are retained.

The proposed method is evaluated on recognizing 11 types of building materials which include 1,231 images taken from several construction sites. Each image resolution is 4,000 × 3,000. The images are captured with different illumination and camera positions. Different illumination conditions lead to trained networks that are more robust against various environmental conditions. Using VGG16 model, an accuracy of 97.35% is achieved outperforming existing approaches.

It is believed that the proposed method presents a new and robust tool for detecting and classifying different material types. The automated detection of material will aid to monitor the quality and see whether the right type of material has been used in the project based on contract specifications. In addition, the proposed model can be used as a guideline for performing quality control (QC) in construction projects based on project quality plan. It can also be used as an input for automated progress monitoring because the material type detection will provide a critical input for object detection.

Several studies have been conducted to perform quality management, but there are some issues that need to be addressed. In most previous studies, a very limited number of material types were examined. In addition, although some studies have reported high accuracy to detect material types (Bunrit et al., 2020), their accuracy is dramatically reduced when they are used to detect materials with similar texture and color. In this research, the authors propose a new method to solve the mentioned shortcomings.

In general, Muslims consider Islamic consumption to be a religious obligation. Previous research, however, suggests that various socio-psychological factors may influence Islamic consumption. Failure to comprehend the true motivations for purchasing Islamic products may lead to marketing myopia. This research investigates the less explored motivational factors of religious compensatory consumption, namely religious hypocrisy, religious social control and religious guilt.

This research relied on an online questionnaire. Purposive sampling yielded a total of 238 Muslim respondents. The authors employed PLS-SEM analysis with the ADANCO software to test the hypotheses.

The results reveal the following: (1) Higher religious hypocrisy leads to higher religious social control. (2) Higher religious hypocrisy leads to higher religious guilt. (3) Higher religious social control leads to higher religious guilt. (4) Higher religious hypocrisy leads to higher religious compensatory consumption. (5) Higher religious social control leads to higher religious compensatory consumption. (6) Religious social control partially mediates the relationship between religious hypocrisy and religious compensatory consumption. (7) Higher religious guilt leads to higher religious compensatory consumption. (8) Religious guilt partially mediates the relationship between religious hypocrisy and religious compensatory consumption.

First, religious compensatory consumption in this research is limited to Muslim consumers. Future research may investigate compensatory consumption in different contexts, such as Judaism and Christianity, which have some common religious tenets. Second, compensatory consumption is a complex concept. The authors’ religious compensatory consumption scale only incorporated a few aspects of compensatory consumption. Future studies may retest the authors’ measurement scale for reliability. Lastly, the samples were dominated by the younger generation of Muslims (e.g. generation Z). Future studies may investigate older Muslim generations.

First, this research illustrates how religiosity, guilt and social control may contribute to Islamic compensatory consumption. Islamic business practitioners and retailers targeting Muslim consumers can benefit from this research by knowing that Islamic consumption may be driven by socio-psychological factors, such as religious hypocrisy and guilt. As a result, businesses targeting Muslim consumers can develop marketing strategies that incorporate these religious elements while also addressing their socio-psychological issues in order to promote Islamic products. Second, Islamic business practitioners and retailers may consider the social environments in which Muslims are raised. The authors’ findings show that religious social control has direct and indirect effects on Muslims' preferences for Islamic products as a form of compensatory strategy. Islamic business practitioners may design marketing programs that revolve around Muslim families and their Islamic values. It is in line with the previous studies that suggest the connections between religions, local cultures and buying behaviours (Ng et al., 2020; Batra et al., 2021). In some ways, Islamic products can be promoted to improve the well-being and cohesion of family members and Muslim society in general. In this research, the authors argue that businesses' failures to understand the socio-psychological motives of Islamic consumption may lead to marketing myopia.

As previously stated, religion (i.e. Islam) may be a source of well-being and a stable relationship among Muslims. Nevertheless, it may also become a source of negative emotions, such as guilt, because of one's inability to fulfil religious values, ideals or standards. According to the authors’ findings, Islamic products can be used to compensate for a perceived lack of religiosity. At the same time, these products may improve Muslims' well-being. The creations of products and services that revolve around Islamic values are expected to improve Muslims' economic conditions and strengthen their faith and love toward Islam in the globalized world. Moreover, Muslims, both as majority and minority groups, face increasing social pressures. On one hand there is the (in-group) pressure to uphold Islamic values and on the other hand there is the (out-group) pressure to preserve the local values and cultures. Indeed, living in the globalized world may require certain compromises. This research calls for various institutions and policymakers to work out solutions that enable all religious groups to work and live in harmony.

To the best of the authors’ knowledge, this research is the first to study religious compensatory consumption quantitatively. This research operationalized variables previously discussed using a qualitative approach, namely religious hypocrisy, social control, guilt and compensatory consumption. The authors designed and adapted their measurement scales to fit this context, paving the way for future research in this field. Second, this research provides new empirical evidence by examining the relationships among less explored variables. For instance, this research has proven that several aspects of religiosity (e.g. hypocrisy, social control and guilt) may influence compensatory consumption in the Islamic context. This research also reveals the mediation roles of religious social control and religious guilt that were less explored in the previous studies. To the best of their knowledge, previous studies had not addressed social control as a predictor of compensatory consumption. Therefore, the theoretical model presented in this research and the empirical findings extend the theory of compensatory consumption. Third, Muslims are underrepresented in the compensatory consumption research; therefore, this research fills the population gap. Finally, this research focuses on Islamic compensatory behaviour as the future direction of Islamic marketing. Previous Islamic marketing research had not addressed the sensitive motives of Islamic consumption, which have now been highlighted in this research.

Considering the important role of public libraries in providing health information service as well as user feedback in improving the quality of health information services, the purpose of this study is to evaluate the quality of health information service in public libraries of Hamadan, Iran, on the basis of the modified LibQUAL model

This practical research was conducted in an analytic-survey method. The statistical population consists of all members of public libraries of Hamadan over 18 years old (12,237 people), and the sample size is calculated to be 373 people. The stratified sampling method was used, and within each class, a convenience sampling method was used. The modified LibQUAL questionnaire was used to gather data. For checking normality of data distribution, the Kolmogorov–Smirnov test and for analyzing date, descriptive statistics and also Chi-square and Wilcoxon tests were applied using SPSS 25.

The users' minimum level of public libraries in all three dimensions is an average level. The users' desired level of “information control” is higher than other dimensions. The users' perceived level in dimensions of “human resources” and “information control” is high level, while users' perceived level in “educational service” is an “average” level. There is a superiority gap between desired and perceived level in all dimensions, but the adequacy gap was seen only in the dimension of “educational service.”

In this study, the quality of health information services provided in public libraries is evaluated by the LibQUAL model.

The results of this research can help managers and librarians of public libraries in measuring the quality of health information services and improving the quality of services provided by libraries. Besides, they can take a more accurate planning and pathologic approach, to eliminate the gap between minimum and desired expectations of users and libraries’ real services.

In this study, the quality of health information services provided in public libraries is evaluated by LibQUAL tool.

Considering the high impacts caused by manufacturers on sustainability, this research aims to analyse how Brazilian manufacturing companies deal with sustainability issues. To do this, sustainability parameters are analysed to verify possible improvement opportunities.

This research uses Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and grey relational analysis (GRA) to analyse data from a survey with Brazilian professionals regarding aspects of sustainability in Brazilian manufacturers. The average score levels and the ranking of these aspects are evaluated.

Through the analysis performed, it was possible to verify that manufacturers in Brazil still have a long path to travel in the search for sustainability. Comparatively, it was observed that practices related to local communities received the lowest scores, on average. In contrast, on average, practices related to productivity and efficiency, occupational accidents and diseases, and compliance with environmental legislation received the highest scores.

The results presented in this paper show that there are several improvement opportunities to be sought by Brazilian manufacturing companies regarding sustainability aspects. Particular attention should be given to local community practices. Besides companies, policymakers can also use this analysis to guide their future actions, encouraging manufacturing companies to better support the local community. Researchers can use the instrument of analysis (TOPSIS and GRA) to analyse other realities and compare them with the findings presented.

The analysis of Brazilian manufacturing companies’ reality regarding sustainability practices and considering a model based on Global Reporting Initiative (GRI) and Brazilian Institute of Corporate Governance (IBGC) is novel in the literature. The use of TOPSIS and GRA, as well as comparing their findings, generated interesting insights for companies, policymakers and researchers. The analysis presented shows the need for more significant concern for local communities and can be used to support further debates and action plans to minimise this gap.

The changing workplace and the disruption and transformation of business processes brought on by modern technology make it difficult for a firm to maintain its existing plans. A management's ability to succeed is related to sustaining and developing its employees to be innovative workers. The idea is to empower subordinates and share authority with them, which increases efficiency.

In this study, it was anticipated that there is a definite relationship between leadership empowerment and workplace cultures of self-esteem, emotional intelligence and creative thinking. Data were obtained using random sample techniques to confirm the hypothesis. A total of 291 Pakistani private-sector employees were surveyed for this study.

There were positive and substantial links between empowered leadership and creativity, while emotional intelligence and organizational self-esteem have an inverse relationship. For psychological appeal and inventiveness at work, empowerment alone is sufficient. Intellectual stimulus or culture of excessively positive self-esteem may cause numerous limits at work. Hence, management should avoid situations where leaders are predisposed to developing empowering techniques.

This study yields an additional understanding of organizational behavior literature. It was concluded from this study that empowering leaders should avoid using emotional intelligence when scaling up creative strategies. As an alternative, they should develop a culture of self-esteem through emotional intelligence.

Leaders may want to consider demographic values while developing empowerment strategies. It is not recommended to use emotional intelligence and empowerment simultaneously. As a result, this framework suggests a realistic and candid approach that is simple to implement.

Leaders make people aware of the ongoing importance of innovative processes to encourage staff to be creative. Successful leaders may use either empowering culture or leadership empowerment strategies for a more significant appeal. Self-esteem culture may provide a structure of interaction buffer against the other emotions that could counter disruption.

Bioenergy remains the largest branch of renewable energy, and microalgae are a promising object of research among other types of biomasses whose scale for energy purposes is increasing. On the other hand, the growth of global energy production and urbanization, which results in high rates of municipal waste and wastewater generation, requires the development of integrated technologies that allow waste to be disposed of as fully as possible. Sustainable investments in the production of energy by various technologies are one of the methods to solve this complex problem. In this chapter, we study the methods of microalgae utilization of nutrients from wastewater and by-product liquid waste of sustainable investments from microalgae by hydrothermal liquefaction (HTL) technology. Wastewater has a complex composition, and the treatment of nitrogen and phosphorus and other biogenic elements, as well as heavy metals, using biological objects is optimal and cost-effective. Also the water phase after HTL is a by-product that has limited energy value. Biofuel investments have higher growth rates and at the same time do not compete with the investments in fossil fuels. Biofuel investments' cost of seaweed fuel can be reduced through high-value-added related products, such as food and feed additives, and pharmaceutical and cosmetic products.

Aluminum is an exchange commodity. But physical trading of this metal in most cases does not occur on the stock exchange, since more than 90% of aluminum sales with physical delivery occur under direct contracts between producers and buyers of the metal (over-the-counter market). Aluminum as an exchange commodity has standardized consumer properties, namely: the goods are interchangeable, easily transported and stored, and can be divided into batches. That is why upstream products are traded on commodity exchanges, not semifinished products or finished products. When commodity exchanges were first created, they served as a place for concluding physical contracts for the supply of such exchange-traded goods, but with the increase in trading volumes and the development of financial instruments, the role of exchanges has changed. Today, futures contracts for raw materials are traded on them – financial instruments that almost never entail a real physical supply (at the same time, this possibility is not excluded). As a result of the bidding, a price is set that serves as a guideline for producers and consumers around the world.

In scientific works on forecasting price volatility (of which the overwhelming majority, in comparison with works on price forecasting) for energy products: crude oil, natural gas, fuel oil, the authors compared the effectiveness of forecasting models of generalized autoregressive heteroscedasticity (Generalized Autoregressive Conditional Heteroscedastic model, GARCH) with regression of support vectors for futures contracts. GARCH models are a standard tool used in the literature on volatility, and the vector machine nonlinear regression model is one of the machine learning methods that has been gaining huge popularity in recent years. The authors have shown that the accuracy of volatility forecasts for energy and aluminum prices significantly depends on the volatility proxy used. The model with correctly defined parameters can lead to fewer prediction errors than GARCH models when the square of the daily yield is used as an indicator of volatility in the evaluation. In addition, it is difficult to choose the best model among GARCH models, but forecasts based on asymmetric GARCH models are often the most accurate. The work is based on a model with a representative investor who solves the problem of optimizing utility in a two-period model. The key assumption of the model is the homogeneity of energy and aluminum investor preferences, that is, preferences do not change over time. There are also works with an attempt to solve this problem in a continuous state space. A completely new theory has been put forward that allows predicting the movement of the underlying asset without using historical data, so this topic is very relevant.

This study, a theory-based interventional study, aims to promote self-care behaviors regarding sexual and reproductive health in adolescents (female) in Karaj, Iran.

This study was conducted on 90 female students of the Alborz University of Medical Sciences in Iran. For selecting subjects, the researchers went to two girls' dormitories on working days and tried to observe the proportion of students with different fields. Initially, 200 eligible female students were identified in the dormitories of Alborz University of Medical Sciences. Based on the sample size estimation, 100 research units were divided into two groups of receiving counseling (intervention group) and not receiving counseling (control group) by four-digit block randomization. Sexual and reproductive health self-care questionnaire was used as a tool for data collection before, after and one month after intervention. Data were analyzed by using X² and ANOVA tests using SPSS (16).

Both groups were homogeneous in terms of demographic characteristics before the intervention. The results of the study indicated that after education, sexual and reproductive knowledge (p < 0.001), self-care of sexual health (p < 0.001), self-care of menstrual and genital health (p < 0.001) increased significantly. But, regarding parents' communications (p = 0.11), conversation barriers with parents (p = 0.83), interaction with (p = 0.79) and the perceptions of sexual risk behaviors relationships (p = 0.61) differences are not significant.

Failure of parents to participate in this study and the implementation of this study only on the female sex were main limitations of the present study.

Theory-based education can improve sexual and reproductive health in adolescents' girls.

All Authors declare the manuscript entitled “Sexual and reproductive health self-care: a theory-based intervention” is original work of the author. All data, tables, figures, etc. used in the manuscript are prepared originally by authors; otherwise, the sources are cited and reprint permission is attached.