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Examining the impact of socioeconomic status (SES) and expenses spent on food preparation on nutritional intake has always been one of the critical concerns for policymakers. This study aims to investigate the association between household food expenditure as well as SES and dietary nutrient intake in Kermanshah, Iran.

In this cross-sectional study, households were randomly selected from different strict in Kermanshah, Iran. Data were collected with an SES questionnaire, a demographic data collection form, a weekly food purchase checklist and a food record. The authors performed the analysis of covariance to determine the relationship of dietary nutrient intake of study participants across quintile categories of SES and total food expenses per day.

Out of 125 households, 119 households including 401 people finished the study. A significant association was observed between higher SES and higher intake of vitamin B2 (p-value = 0.03). Moreover, the household members at the top level of total food expenses per day had significantly greater dietary nutrient intake of energy (p < 0.001), potassium (p < 0.001), magnesium (p < 0.001), calcium (p < 0.001), zinc (p < 0.001), vitamin B2 (p < 0.001), B6 (p < 0.001), B12 (p = 0.002) and vitamin C (p = 0.04).

In our study, higher dietary nutrient intake was observed in the household members at the highest level of total food expenses daily as well as SES. Therefore, governments and policymakers should pay basic attention to optimizing food costs and improving the economic status of people.

The housing policies targeting low-income households have not been effective to address the housing needs of target groups in Iran over the past four decades. According to the World Bank’s data on population living in slums (% of urban population) in Iran in 2018 was 25% which is slightly higher than the rate 23% of upper-middle-income countries. This study aims to understand what major revisions are required in the process of housing policymaking to have more effective policies.

The authors conduct one-to-one interviews with 41 housing experts and apply discourse analysis and interpretive–structural modeling to achieve the goals.

The panel of experts argue that the success of housing policies in Iran depends on the following: all academic disciplines should be included in the process of housing policymaking process; land policymaking should be modified; housing policy is a regional issue, and it should be designed and implemented differently in each province; main modifications are required in the tax and tenancy system; and new policies are required to push vacant houses into the rental market.

This study is a prescriptive study based on a general trend (four decades).

This paper aims to determine whether there is a relationship between intellectual capital and social capital and internal control weaknesses and assess the relationship between the variables of intellectual capital and social capital and internal control weaknesses.

The statistical population consists of 1,309 firm-year observations from 2014 to 2020. The research hypothesis is tested using statistical methods, including multivariate, least-squares and fixed-effects regression.

The results demonstrate a negative and significant relationship between intellectual capital, social capital and internal control weaknesses. The study also finds that increased intellectual and social capital quality improves human resource utilization, control mechanism, creativity and firm performance. The results also show that intellectual capital and social capital enhancement will reduce internal control weaknesses in the upcoming years.

This paper is the pioneer study on the relationship between intellectual capital and social capital and internal control weaknesses in Iran, carried out separately and in exploratory factor analysis. This paper considers intellectual capital components for theoretical factor analysis, including human capital, structural capital and customer capital. Internal control weakness is assessed based on financial, non-financial and information technology (IT) weaknesses.

The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete structure. However, FRP bars are not practically used due to a lack of standard codes. Various codes, including ACI-440-17 and CSA S806-12, have been established to provide guidelines for the incorporation of FRP bars in concrete as reinforcement. The application of these codes may result in over-reinforcement. Therefore, this research presents the use of a machine learning approach to predict the accurate flexural strength of the FRP beams with the use of 408 experimental results.

In this research, the input parameters are the width of the beam, effective depth of the beam, concrete compressive strength, FRP bar elastic modulus and FRP bar tensile strength. Three machine learning algorithms, namely, gene expression programming, multi-expression programming and artificial neural networks, are developed. The accuracy of the developed models was judged by R², root means squared and mean absolute error. Finally, the study conducts prismatic analysis by considering different parameters. including depth and percentage of bottom reinforcement.

The artificial neural networks model result is the most accurate prediction (99%), with the lowest root mean squared error (2.66) and lowest mean absolute error (1.38). In addition, the result of SHapley Additive exPlanation analysis depicts that the effective depth and percentage of bottom reinforcement are the most influential parameters of FRP bars reinforced concrete beam. Therefore, the findings recommend that special attention should be given to the effective depth and percentage of bottom reinforcement.

Previous studies revealed that the flexural strength of concrete beams reinforced with FRP bars is significantly influenced by factors such as beam width, effective depth, concrete compressive strength, FRP bars’ elastic modulus and FRP bar tensile strength. Therefore, a substantial database comprising 408 experimental results considered for these parameters was compiled, and a simple and reliable model was proposed. The model developed in this research was compared with traditional codes, and it can be noted that the model developed in this study is much more accurate than the traditional codes.