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Southeast Asia has been actively undergoing land conversion into agricultural lands over past few decades. This creates the challenges to the nation in dealing with the non-point source pollutants in many fluvial systems, thus requiring an effective approach in sediment source apportionment for an appropriate target mitigation procedure. The trace element property from different source points was used for catchment classification of Galas River. Sediment sample collection was carried out at the sources and sink areas of the catchment system. Fine sediment was analysed using X-ray fluorescence to obtain elemental composition followed by the statistical test and numerical model. Out of 83 elements, 12 elements (Mn, Ca, Cr, Ga, Dy Hf, Y, V, Th, Pb, Zn and Sr) have been selected as best tracer signatures. The solver model has indicated Pergau River as the major sediment contributor to this large catchment system. The model output could directly be proportional with the land-use practice, indicating excessive terrestrial alteration has taken place within the sites for agricultural plantation purposes. Thus, this highly recommends for the decision-making use to the targeted areas to overcome the serious sedimentation issues caused by the tillage operation in affected stream points and to improve the watershed quality.

Culture is considered as one of the variables that influence the total quality management (TQM) adoption process. The purpose of this paper is to explore the relationship between cultural dimensions and the strategy of the firms in TQM implementation. These relationships are the subject of prior research. Furthermore, the authors make a comparative analysis of cultural dimensions on strategic choices of the firms, i.e. innovators, prospectors and defenders in TQM implementation.

From the existing literature review on TQM practices and organizational culture, 14 cultural dimensions were employed with organizational strategy in this present study. By using survey data collection method, 111 Indian firms were selected. The authors considered three strategy parameters and six structural attributes to identify the strategy of the firms, namely innovators, prospectors and defenders identified using cluster analysis. Furthermore, the relationship between organizational culture and strategy was examined using one-way ANOVA approach.

The results of the study revealed that eleven of the fourteen hypotheses supported which relating the cultural dimensions to TQM implementation with the strategic orientation. With the help of significant related values of cultural dimensions to the particular strategic firms, it is also found that implementation of TQM is easy or not. Some of the organizations with a particular strategic orientation will be able to implement TQM easily and successfully but some organizations will have difficulty to implement it successfully.

The firms hold their importance with respect to the different strategic orientation toward the various aspects of organizational cultures and TQM approaches in its implementation. Managerially, due to increased business competitiveness and economic pressures, top management sees the way in adopting TQM practices to achieve a competitive advantage. Apparently, it is evident that matching of TQM practices for a different strategy of the firms with various cultural dimensions leads to the smooth functioning of the organization. This study helps to the current organizations in implementing TQM with their respective culture.

This research can be useful for three strategic firms, namely innovators, prospectors and defenders to achieve effective implementation of TQM practices with consideration and understanding of the advantage of each culture dimension. The framework of the current study represents the effectiveness in assessing the TQM practices in individual cultural dimensions and its significant role.

The combined heat and power dispatch (CHPD) aims to optimize the outputs of online units in a power plant consisting thermal generators, co-generators and heat-only units. Identifying the operating point of a co-generator within its feasible operating region (FOR) is difficult. This paper aims to solve the CHPD problem in static and dynamic environments.

The CHPD plant operation is formulated as an optimization problem under static and dynamic load conditions with the objectives of minimizations of cost and emissions subject to various system and operational constraints. A novel bio-inspired search technique, grey wolf optimization (GWO) algorithm is used as an optimization tool.

The GWO-based algorithm has been developed to determine the preeminent power and heat dispatch of operating units within the FOR region. The proposed methodology provides fuel cost savings and lesser pollutant emissions than those in earlier reports. Particularly, the GWO always keeps the co-generator’s operating point within the FOR, whereas most of the existing methods fail.

The GWO is applied for the first time to solve the CHPD problems. New dispatch schedules are reported for 7-unit system with the objectives of total fuel cost and emission minimizations, 24-unit system for economic operation and 11-unit system in dynamic environment. The simulation experiments reveal that GWO converges quickly, consistent and the statistical performance clears its applicability to CHPD problems.

The purpose of this study is three-dimensional flow and heat transfer investigation of water/Al₂O₃ nanofluid inside a microchannel with different cross-sections in two-phase mode.

The effect of microchannel walls geometry (trapezoidal, sinusoidal and stepped microchannels) on flow characteristics and also changing circular cross section to trapezoidal cross section in laminar flow at Reynolds numbers of 50, 100, 300 and 600 were investigated. In this study, two-phase water/Al₂O₃ nanofluid is simulated by the mixture model, and the effect of volume fraction of nanoparticles on performance evaluation criterion (PEC) is studied. The accuracy of obtained results was compared with the experimental and numerical results of other similar papers.

Results show that in flow at lower Reynolds numbers, sinusoidal walls create a pressure drop in pure water flow which improves heat transfer to obtain PEC < 1. However, in sinusoidal and stepped microchannel with higher Reynolds numbers, PEC > 1. Results showed that the stepped microchannel had higher pressure drop, better thermal performance and higher PEC than other microchannels.

Review of previous studies showed that existing papers have not compared and investigated nanofluid in a two-phase mode in inhomogeneous circular, stepped and sinusoidal cross and trapezoidal cross-sections by considering the effect of changing channel shape, which is the aim of the present paper.

This study aims to examine how young consumers perceive the advertising effectiveness of endorsements by virtual idols and how endorsements by virtual idols differ from endorsements by real human celebrities such as traditional celebrities and online influencers.

An experimental study was conducted with 400 randomly selected young respondents in China in December 2022. A 3 × 2 factorial design was used to test how the type of celebrity endorser and level of product involvement influence the persuasiveness of advertising aimed at young adults. Among 400 respondents, the average age was 21.5 years. A total of 193 male and 207 female respondents participated in the experiment.

Young consumers find virtual idols, online influencers and traditional celebrities attractive. Although virtual idols are the least credible among the three types of celebrity endorsers, young consumers tend to be more convinced by their endorsements of products with low levels of consumer involvement than those with high levels of involvement. Among the three types of celebrity endorsements, young consumers find traditional celebrities the most effective. In addition, young consumers’ attitudes toward celebrity endorsers mediate the impact of celebrity endorsers’ attractiveness and credibility on their attitudes toward the advertisements. The perceived level of product involvement moderates the transfer of meaning from the attitude toward the celebrity endorsers to the attitude toward the advertisement.

First, when choosing celebrity endorsers to advertise products targeting young consumers, marketing communication practitioners should give priority to the endorsers’ perceived credibility, as young consumers have a variety of views about them that can significantly affect their attitudes toward the advertisement. Second, real human celebrity endorsers are more effective than virtual idols in celebrity endorsements. However, virtual idols may be suited for use in advertisements to promote products with low involvement levels, such as soft drinks.

To the best of the authors’ knowledge, this is the first experimental study to attempt to analyze the effectiveness of virtual idols in advertising aimed at young consumers. This is also the first comparative study to introduce virtual idols as celebrity endorsers in product advertising and to compare their effectiveness with that of the two other types of commonly discussed celebrity endorsers, traditional celebrities and online influencers.

Risk response decisions (RRDs) are vital for project risk mitigation. Although past research has focused on RRDs for independent single projects, it has scarcely explored how to make RRDs for single projects in project portfolios (SPPPs). Consequently, this study aims to bridge the gap in extant literature by developing an integrated approach to select risk response strategies (RRSs) for SPPPs considering objective adjustments and project interdependencies (PIs).

An integrated quality function deployment (QFD) method was used throughout this study. More so, a balanced score card (BSC) and stratified-Z-numbers-full consistency method (SZFUCOM) was applied to identify SPPP success criteria (SP3SC) to determine their weights. In addition, a spherical fuzzy set-design structure matrix (SFDSM) was used to quantify the correlation between the risks and the relationship between the risks and the predecessor projects. Consequently, the relationships between the risks and SP3SC and RRSs were described by the spherical fuzzy set (SFS) and Z-numbers, respectively. Besides, the results are weaved into QFD to transform SP3SC into risks and then into RRSs, while a linear optimization model is used to obtain the optimal RRSs. Lastly, a construction project portfolio (PP) was used to test the veracity of the results to prove their validity.

The approach to RRDs for single projects is observed to be different from that of SPPPs. In addition, this study finds that project portfolio objective adjustments (PPOAs) and PIs have significant impacts on RRDs given that they influence the risk priorities of independent single projects and SPPPs. Moreover, the application of an integrated QFD effectively synthesized the results from the findings of this study, as well as enabled companies to determine robust RRSs. Finally, the consistency results of the SZFUCOM were better than those of the triangular fuzzy number-full consistency method.

The study innovatively explores the method of RRDs for SPPP, which has been ignored by past research. SP3SC highly compatible with PP success is determined. Z-numbers are first used to evaluate the effect of RRSs to enhance the robustness of RRDs. The study proposes a method of RRDs comprehensively considering PPOAs and PIs, which provides robust methodological guidance for SPPP managers to control risks.

It can be said that the most important function of the health system is to provide health-care services. This directly affects society’s health and justice. To the best of the authors’ knowledge, this study is the first study that has meta-analyzed the percentage of health services utilization among Iranians to answer this question “How much is the percentage of health-care services utilization in Iran?”

This study is a systematic review and meta-analysis conducted in 2020. The literature review was done by searching the databases of Google Scholar, Scopus, PubMed, Web of Science, Science Direct, SID, Magiran and Irandoc from January 2010 to August 2020. Pooled utilization percentage (UP) was estimated by STATA 15 through random-effects meta-analysis with 95% confidence interval. The I² statistic was used to investigate the possibility of heterogeneity of articles (I² ≥ 50% indicate heterogeneity). A forest plot was applied to report the results. A funnel plot exploited due to publication bias assessment.

Approximately 22% of the reviewed articles have been done at the national level of Iran. Most studies have examined the utilization of outpatient and inpatient services. Based on the random effects method, the pooled value of UP was obtained at 47.82%, (95% CI: 39.33–56.31). Also, the pooled percentage of utilization was statistically significant (Test of UP = 0, Z = 456.44, p = 0.000).

Policymakers can improve the level of utilization from health services by expanding universal coverage, expanding insurance coverage and removing direct and indirect barriers.

To the best of the authors’ knowledge, this is the first systematic review and meta-analysis on health services utilization in Iran that completely considers the utilization rate in all health services and states the practical solutions to cope with utilization deficiencies and barriers.

Better membrane oxygenators need to be developed to enable efficient gas exchange between venous blood and air.

Optimal design and analysis of such devices are achieved through mathematical modeling tools such as computational fluid dynamics (CFD). In this study, a control volume-based one-dimensional (1D) sub-channel analysis code is developed to analyze the gas exchange between the hollow fiber bundle and the venous blood. DIANA computer code, which is popular with the thermal hydraulic analysis of sub-channels in nuclear reactors, was suitably modified to solve the conservation equations for the blood oxygenators. The gas exchange between the tube-side fluid and the shell-side venous blood is modeled by solving mass, momentum and species conservation equations.

Simulations using sub-channel analysis are performed for the first time. As the DIANA-based approach is well known in rod bundle heat transfer, it is applied to membrane oxygenators. After detailed validations, the artificial membrane oxygenator is analyzed for different bundle sizes (L/W) and bundle porosity (epsilon) values, and oxygen saturation levels are predicted along the bundle. The present sub-channel analysis is found to be reasonably accurate and computationally efficient when compared to conventional CFD calculations.

This approach is promising and has far-reaching ramifications to connect and extend a well-known rod bundle heat transfer algorithm to a membrane oxygenator community. As a variety of devices need to be analyzed, simplified approaches will be attractive. Although the 1D nature of the simulations facilitates handling complexity, it cannot easily compete with expensive and detailed CFD calculations.

This work has high practical value and impacts the design community directly. Detailed numerical simulations can be validated and benchmarked for future membrane oxygenator designs.

Future membrane oxygenators can be designed and analyzed easily and efficiently.

The DIANA algorithm is popularly used in sub-channel analysis codes in rod bundle heat transfer. This efficient approach is being implemented into membrane oxygenator community for the first time.

There are many problems in civil or mechanical engineering related to structural design. In such a case, the solution techniques which lead to deterministic results are no longer valid due to the heuristic nature of design problems. The purpose of this paper is to propose a computational tool based on genetic algorithms, applied to the optimal design of cross-sections (solid tubes) of 3D truss structures.

The main feature of this genetic algorithm approach is the introduction of a selective-smart method developed in order to improve the convergence rate of large optimization problems. This selective genetic algorithm is based on a preliminary sensitivity analysis performed over each variable, in order to reduce the search space of the evolutionary process. In order to account for the optimization of the total weight, the displacement (of a specific section) and the internal stresses distribution of the structure a multiobjective optimization function was proposed.

The numerical results presented in this paper show a significant improvement in the convergence rate as well as an important reduction in the relative error, compared to the exact solution.

The variables sensitivity analysis put forward in this approach introduces a significant improvement in the convergence rate of the genetic algorithm proposed in this paper.

The purpose of this study is to develop a precise Islamic securities index forecasting model using artificial neural networks (ANNs).

The data of daily closing prices of KMI-30 index span from Aug-2009 to Oct-2019. The data of 2,520 observations are divided into training and test data sets by using the 80:20 ratio, which corresponds to 2016 and 504 observations, respectively. In total, 25 features are used; however, in model selection step, based on maximum accuracy, top ten indicators are selected from several iterations of predictive models.

The results of feature selection show that top five influencing indicators on Islamic index include Bollinger Bands, Williams Accumulation Distribution, Aroon Oscillator, Directional Movement and Forecast Oscillator while Mesa Sine Wave is the least important. The findings show that the model captures much of the trend and some of the undulations of the original series.

The findings of this study may have important implications for investment and risk management by using index-based products.

Numerous studies proved that traditional econometric techniques face significant challenges in out-of-sample predictability due to model uncertainty and parameter instability. Recent studies show an upsurge of interest in machine learning algorithms to improve the prediction accuracy.