Search results

There are limited studies on the effects of coffee consumption, which has become part of popular culture and is highly common among young people, on the attention levels of female university students. This paper aims to examine the effects of caffeine consumption given at different doses (0, 100 and 200 mg) to female university students (n = 100) studying at the faculty of health sciences on attention performance with the Stroop Color and Word Test (SCWT).

Participants' test completion time, number of errors and corrections were tested. In addition, the frequencies of weekly coffee consumption were also recorded.

It was found that consumption of coffee containing 200 mg of caffeine reduced the time to complete the sections of the SCWT test (p < 0.05), as well as the total test completion time (55.81 ± 8.67 s) compared to no coffee consumption (58.25 ± 9.46 s) and coffee consumption with 100-mg caffeine (57.56 ± 8.87 s) (p < 0.05; effect size: 0.268). The effect of caffeine on attention level was induced by 200-mg caffeine consumption, but was unapparent at 100-mg dose. In addition, SCWT completion times were reduced in the student group with more weekly coffee consumption (=3 cups/week) at 200-mg caffeine dose.

In this context, caffeine dose is a factor that should be taken into account in determining the performance of individuals in the SCWT test. It is thought that coffee consumption can increase the concentration of students and have positive effects on academic achievement.

Diabetes is one of the health problems of increasing importance owing to the increase in its incidence and the problems it causes, and it is closely related to nutrition. This study aims to determine the relationship between the dietary inflammatory index (DII) scores of individuals with type 2 diabetes, depression, anxiety and quality of life.

In this cross-sectional study, 158 individuals with type 2 diabetes who applied to a nutrition and diet outpatient clinic of a private hospital in Istanbul were included. Their depression status was evaluated using the Beck Depression Inventory; their anxiety status was evaluated using the Beck Anxiety Inventory; and their quality of life was evaluated using the Short Form 36 Quality of Life scale. One-way ANOVA test was used to define the difference between groups. All test results were evaluated at a significance level of 0.05.

There was no significant relationship between DII scores, depression (p = 0.814) and anxiety (p = 0.817). However, a significant decrease was observed in the scores of the quality of life criterion in the groups with high depression and anxiety scores (p < 0.05). In addition, participants with high anxiety states had higher HbA1c levels (p = 0.043).

Individuals in this sample with no known psychiatric diagnosis or treatment history demonstrated a significant relationship between depression and anxiety scores and quality of life.

This study aims to investigate the interconnectedness across the risk appetite of distinct investor types in Borsa Istanbul. This study also examines the causal impact of global implied volatility indices on the risk appetite of these investor groups.

The authors use a novel time-varying frequency connectedness framework of Chatziantoniou et al. and a new time-varying Granger causality test with a recursive evolving procedure by Shi et al. over June 2008 and July 2022.

The results show a high level of interconnectedness across the risk appetite of different investor types. The sizable spillovers to domestic types of investors either occur from professional or foreign investors, indicating the long-term dominant effect of foreign and more qualified investors on the domestic investors in Borsa Istanbul. The authors provide significant evidence of causality from the global implied volatility to the Borsa Istanbul risk appetite indices, which are getting stronger after the COVID-19 outbreak.

Unlike the previous studies, the authors analyze the risk appetite sub-indices of various types of investors to reveal behavioral distinctions and interconnectedness across them. The authors use a novel econometric framework to assess investors’ risk appetite in different investment horizons in a time-varying system. Together with volatility index (VIX), the authors also use volatilities of oil (OVX), gold (GVZ) and currency (EVZ), considering the information transmission not only from stock markets but also energy, metals and currency markets. The present data set covers significant financial crises, socioeconomic events and the COVID-19 outbreak.

This study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.

A panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.

The preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.

To the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.

The purpose of this paper is to perform the computational fluid dynamics (CFD) simulation with experimental validation to investigate the particle segregation effect in abrupt and smooth shapes circulating fluidized bed (CFB) risers.

The experimental investigations were carried out in lab-scale CFB systems and the CFD simulations were performed by using commercial software BARRACUDA. Special attention was paid to investigate the gas-particle flow behavior at the top of the riser with three different superficial velocities, namely, 4, 6 and 7.7 m/s. Here, a CFD-based noble simulation approach called multi-phase particle in cell (MP-PIC) was used to investigate the effect of traditional drag models (Wen-Yu, Ergun, Wen-Yu-Ergun and Richardson-Davidson-Harrison) on particle flow characteristics in CFB riser.

Findings from the experimentations revealed that the increase in gas velocity leads to decrease the mixing index inside the riser. Moreover, the solid holdup found more in abrupt riser than smooth riser at the constant gas velocity. Despite the more experimental investigations, the findings with CFD simulations revealed that the MP-PIC approach, which was combined with different drag models could be more effective for the practical (industrial) design of CFB riser. Well agreement was found between the simulation and experimental outputs. The simulation work was compared with experimental data, which shows the good agreement (<4%).

The experimental and simulation study performed in this research study constitutes an easy-to-use with different drag coefficient. The proposed MP-PIC model is more effective for large particles fluidized bed, which can be helpful for further research on industrial gas-particle fluidized bed reactors. This study is expected to give throughout the analysis of CFB hydrodynamics with further exploration of overall fluidization.

The purpose of this paper is to examine the influence of organizational culture (OC) on the building blocks of innovation culture (IC) in Iranian auto companies.

In total, a sample of six large auto companies were examined and 245 questionnaires completed by employees. A conceptual model was developed and the hypotheses analyzed by using exploratory factor analysis and then the direct and indirect effects of constructs were analyzed by path analysis technique.

Findings suggest that the constructs of OC correlate with those of IC. These correlations are all positive except for the relations between consistency and organizational learning, as well as of that between consistency and creativity and improvement.

First, this paper has checked the validity of both questionnaires in an Iranian context so that they could be used with more confidence. Second, innovation can flow in the organizations when organizational culture supports it. This research specified those elements which can help managers and executives find the aspects of OC which can increase IC.

The paper serves as a reference for fostering an IC in auto companies. Paying attention to different aspects of OC can have a positive effect on making innovation pervasive in organizations. This research was done for the first time in an Asian context and is literally unprecedented in Iran.

A major challenge facing the fresh‐cut industry is maintaining and preserving the quality of minimally processed or fresh‐cut produce. A low temperature regime, although insufficient, has been the main method of overcoming this challenge so far. Thus, methods preserving the quality and extending the shell life of minimally processed or fresh‐cut produce are needed. This paper seeks to propose that honey could be used to preserve the fresh‐like quality of minimally processed pomegranate arils and extend their shelf life.

Manually extracted pomegranate arils were treated with water as control, 10 or 20 per cent diluted honey solution each for five minutes, then held at 4°C for ten days. Changes in organoleptic and visual quality, softening, soluble solids content, pH, absorbance at 446 and 510nm, and total aerobic count were recorded during the ten‐day storage period.

The study found that honey solution dip treatments extended the fresh‐like quality of minimally processed arils by delaying quality loss, microbial development, and pigment changes.

The paper shows that honey dip treatment may be used, depending on commodity, to preserve quality and extend the shelf life of minimally processed or fresh‐cut produce in the food‐processing industry.

The study pays particular attention to minimally processed pomegranate arils, by adapting a potentially safe organic method, the use of honey dips.

The abnormality of the month-of-the-year and Ramadan effects has extensively existed in the stock and other markets. The commercial strategy pattern and the computation of such predictable patterns in the market allow investors to make money. By using anomalies such as the month-of-the-year and the Ramadan effects on earnings management (EM), it is possible to achieve such a goal. This study aims to investigate the month-of-the-year effect and the Ramadan effect on the relationship between accrual earnings management and real earnings management (AEM and REM, respectively) and liquidity in the Iranian capital market.

This empirical analysis comprises a panel data set of 80 listed firms (400 observations) on the Tehran Stock Exchange from 2016 to 2020.

The findings exhibit that when AEM and REM increase, information asymmetry also increases. The simultaneous increase of these variables leads to a decrease in stock liquidity. Furthermore, the results indicate that the month-of-the-year and Ramadan effects intensify the negative relationship between AEM and REM with stock liquidity. Therefore, EM is affected by the investor’s behavior in specific months.

Anomalies caused by the Ramadan effect and the month-of-the-year effect on reducing liquidity in the Iranian stock market were confirmed. Investors can use these anomalies to identify predictable patterns, exchange securities according to those patterns and earn abnormal returns.

To the best of the authors’ knowledge, this is the first study that empirically examined the simultaneous effect of Gregorian and Islamic calendar anomalies on the relationship between EM and liquidity, and while helping managers and other readers, it can be the basis for future research.

The major aim of this research is to determine the socio‐economic level of geographical investment regions through fuzzy multi‐criteria decision‐making (MCDM) method. The results obtained from this method are analyzed and compared with the current system and the differences are interpreted.

A user friendly MCDM method, the fuzzy TOPSIS, was selected and ten independent criteria out of 53 were used, that have been evaluated by reduction according to the correlations among them. Therefore, the rankings of the 26 geographical investment regions of Turkey were calculated based on their criteria.

The examinations of the rankings have shown that only four regions had similar rankings but the rankings of the remaining 22 regions differed according to the authority rankings. Furthermore, significant differences have been observed for eight regions.

In globalization process, certain issues are of particular importance in shaping the resource allocation policies of countries, through which they adjust their resources for manufacturing and service sectors to the changing competitive conditions and govern the effect of global economics on the human resources of their countries. The allowances taken from social and economic criteria have indicated the inter‐regional differences in terms of development.

From a policy perspective, this study highlighted that a large number of social and economic criteria failed in identifying homogenous groups of provinces and hence failed in producing realistic policies. However, the proposed method significantly contributed to obtaining more accurate rankings by using fuzzy decision‐making under multi‐criteria.

The purpose of this paper is to develop an empiricism free, first principle‐based model to simulate fluid flow and heat transfer through porous media.

Conventional approaches to the problem are reviewed. A multi‐scale approach that makes use of the sample simulations at the individual pore levels is employed. The effect of porous structures on the global fluid flow is accounted for via local volume averaged governing equations, while the closure terms are accounted for via averaging flow characteristics around the pores.

The performance of the model has been tested for an isothermal flow case. Good agreement with experimental data were achieved. Both the permeability and Ergun coefficient are shown to be flow properties as opposed to the empirical approach which typically results in constant values of these parameters independent of the flow conditions. Hence, the present multi‐scale approach is more versatile and can account for the possible changes in flow characteristics.

Further validation including non‐isothermal cases is necessary. Current scope of the model is limited to incompressible flows. The methodology can accommodate extension to compressible flows.

This paper proposes a method that eliminates the dependence of the numerical porous media simulations on empirical data. Although the model increases the fidelity of the simulations, it is still computationally affordable due to the use of a multi‐scale methodology.