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Although the use of diverse types of bricks as the primary construction materials has been considered for many years, vernacular earthen materials are also widely used for construction with low potential environmental impacts in developing countries. In this study, the life cycle of two types of building materials for wall building is investigated.

For this purpose, life cycle carbon emissions (LCCO₂) are compared and embodied energy calculation for rammed earth and fired clay bricks as two construction materials. The complete construction chain using rammed earth, as a modern norm, and fired clay bricks, as the most common construction materials in buildings, is investigated in this research.

Studies on the constructions in Kashan city in the north of Isfahan province, Iran, as a case study, showed that replacing the fired bricks with rammed earth would reduce the CO₂ emissions up to 1,245 kg/ton and 4,646 MJ/ton (i.e. more than 95%) of the embodied energy. It also shows that the choice of building materials should be important for building practitioners to consider the environmental impact.

This paper provide life cycle assessment of building materials. The findings of this study help builders and owner to choose sustainable building materials.

This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW).

The objective of this problem is minimization of the total traveling cost and the time window violations. Two meta-heuristic algorithms, namely, simple genetic algorithm (GA) and hybrid genetic algorithm (HGA) are used to find the best solution for this problem. A comparison on the results of these two algorithms has been done and based on the outcome, it has been proved that HGA has better performance than GA.

A comparison on the results of these two algorithms has been done and based on the outcome, it has been proved that HGA has better performance than GA.

This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW). The defined problem is a practical problem in the supply management and logistic. The repair vehicle services the customers who have goods, while the pickup vehicle visits the customer with nonrepaired goods. All the vehicles belong to an internal fleet of a company and have different capacities and fixed/variable cost. Moreover, vehicles have different limitations in their time of traveling. The objective of this problem is minimization of the total traveling cost and the time window violations. Two meta-heuristic algorithms (simple genetic algorithm and hybrid one) are used to find the best solution for this problem.

The purpose of this study is to investigate a joint economic lot-size model with the possibility of cofinancing between members of a three-echelon supply chain (SC) including one supplier, one manufacture and one retailer. Given the differences in credit as well as differences in access to capital markets, SC members will be able to create a financial alliance to maximize the profits of each member. This study proposed a model to maximize the annuity stream of the SC by considering the financial interaction between SC members.

This joint economic lot-sizing problem was described and modeled mathematically. To evaluate the mathematical model, different scenarios were considered with (and without) the possibility of financial interaction.

It is suggested that, in addition to the goods and information flow among SC members, proper financial flow can also have an impact on the improvement of SC performance.

While previous studies consider cofinancing between members of a two-echelon SC, this paper considers a three-echelon SC including one supplier, one manufacturer and one retailer where financial cooperation between different levels of the SC in both upstream and reverse directions will be possible.

This study seeks to investigate the interrelationships among sector reputation, purchasing stock intention, sector engagement and attitude toward the sector. Moreover, it aims to explore the moderating role of sector knowledge in the indirect relationship between sector reputation and purchasing stock intention, mediated by sector engagement and/or attitude toward the sector.

Drawing upon the theory of planned behavior, the research framework is empirically tested. A survey involving 300 potential and actual investors was conducted, representing individuals investing in tourism brands within the Egyptian stock market. The validity and reliability of the constructs were assessed using AMOS, while Hayes’s PROCESS macro was employed to examine the mediation and moderated mediation effects.

The findings reveal that sector reputation significantly influences sector engagement, attitude toward the sector and purchasing stock intention. Furthermore, the attitude toward the sector serves as an explanatory factor for investors’ propensity to purchase stocks of tourism brands. The study confirms the serial mediation effect of sector engagement and attitude toward the sector, respectively, in the relationship between sector reputation and purchasing stock intention. Additionally, it confirms the moderated mediation role of sector knowledge in the relationship between sector reputation and purchasing stock intention, mediated by attitude toward the sector.

The research outcomes suggest that executives in the tourism industry should identify key determinants to enhance purchasing stock intention by fostering greater sector engagement and fostering positive attitudes toward the tourism sector.

This study contributes to the existing literature by shedding light on the importance of maintaining a positive brand reputation and emphasizing the influential role of investors’ knowledge, engagement and attitude in shaping investment decisions in the stock market. These insights contribute to the understanding of investor behavior and have practical implications for organizations in managing their brand reputation and fostering positive customer–brand interactions in the stock market context, thus the current study was conducted.

This paper aims to present a numerical investigation on laboratory-scale segmental baffles shell-and-tube heat exchanger (STHX) having various tube bundles and baffle configuration.

To discover the higher performance the thermohydraulic behavior of shell-side fluid flow with circular, elliptical and twisted oval tube bundles with segmental and inclined segmental baffled is compared. Shell side turbulent flow and heat transfer are simulated by a finite volume discretization approach using SolidWorks Flow Simulation. To achieve greater configuration performance of this device, the following two approaches is considered: using the inclined baffle with 200 angles of inclination and applying the different tube bundle.

Different parameters as heat transfer rate, pressure drop (Δp), heat transfer coefficient (h) and heat transfer coefficient to pressure drop ratio (h/Δp) are presented and discussed. Besides, for considering the effect of pressure penalty and heat transfer improvement instantaneously, the efficiency evaluation coefficient (EEC) in the fluid flow and heat transfer based on the power required to provide the real heat transfer augmentation are used.

Obtained results displayed that, at the equal mass flow rate, the twisted oval tubes with segmental baffle decrease the pressure drop 53.6% and 35.64% rather than that the circular and elliptical tubes bundle, respectively. By comparing the (h/Δp) ratio, it can result that the STHX with twisted oval tubes bundle (both segmental and inclined baffle) has better performance than other kinds of the tube bundles. Present results showed that the values of the EEC for all provided models are higher than 1, except for elliptical tube bundles with segmental baffles. The STHX with twisted oval tube bundles and segmental baffle gives the highest EEC value equal to 1.16 in the range of investigated mass flow.

The purpose of this study is to design a plasmonic structure that can be used simultaneously as a heater and a refractive index sensor applicable for heating and sensing cycles of lab-on-chip (LOC).

The authors report on the full optical method applicable in the heating and sensing cycles of LOC based on the plasmonic nanostructure. The novelty of this proposed structure is due to the fact that a structure simultaneously acts as a heater and a sensor.

In terms of the performance of the proposed structure as an analyte detection sensor, in addition to the real-time measurement, there is no need to labeling the sample. In terms of the performance of the proposed structure as a plasmonic heater, the uniformity and speed of the heating and cooling cycles have been greatly improved. Also, there is no need for experts and laboratory conditions; therefore, our proposed method can meet the conditions of point of care testing.

The authors confirm that this work is original and has not been published elsewhere nor it is currently under consideration for publication elsewhere.

In recent years, governmental regulations and the pressure of non-governmental organizations have convinced corporations to consider sustainable issues in their decisions. A simultaneous design of forward and reverse logistics can keep us away from sub-optimality caused by tackling these two phases (forward and reverse logistics) separately.

Hence, this paper presents a new multi-objective mathematical model for integrated forward and reverse logistics regarding economic, environmental and social issues. A new hybrid multi-objective metaheuristic algorithm is developed to obtain a set of efficient solutions (Pareto solutions). The proposed algorithm hybridizes a well-known, non-dominated genetic algorithm (NSGA-II) with a simulated annealing algorithm.

To validate the algorithm, its results are compared to the obtained solutions from simple NSGA-II with respect to some comparison metrics. The numerical results show the efficiency of the proposed algorithm. Finally, concluding remarks and future research directions are provided.

By applying a model presented in this paper, one can reach to sustainable and integrated logistics network which considers forward and reverse flow of commodities simultaneously.

The purpose of this paper is to analyze the dynamics of budgetary biasing in the context of public hospitals.

The study applies theories of accounting and budgeting behaviors in the specific institutional context of health care systems. Based on the theoretical framework, data from interviews with hospital budget officers were analyzed using qualitative content analysis.

A typology of biases is provided. It proved to be useful and highlighted the central empirical assumptions and preliminary results of biasing dynamics.

Understanding the logic of budgeting actors and the drivers of bias may help explain why bias so often appears in health care budgeting. It further contributes to understanding whether the bias is functional or dysfunctional.

The concepts of budgetary bias are rarely used in the context of health care budgeting, so the study fills a gap in research knowledge.

The task of identifying activity classes from sensor information in smart home is very challenging because of the imbalanced nature of such data set where some activities occur more frequently than others. Typically probabilistic models such as Hidden Markov Model (HMM) and Conditional Random Fields (CRF) are known as commonly employed for such purpose. The paper aims to discuss these issues.

In this work, the authors propose a robust strategy combining the Synthetic Minority Over-sampling Technique (SMOTE) with Cost Sensitive Support Vector Machines (CS-SVM) with an adaptive tuning of cost parameter in order to handle imbalanced data problem.

The results have demonstrated the usefulness of the approach through comparison with state of art of approaches including HMM, CRF, the traditional C-Support vector machines (C-SVM) and the Cost-Sensitive-SVM (CS-SVM) for classifying the activities using binary and ubiquitous sensors.

Performance metrics in the experiment/simulation include Accuracy, Precision/Recall and F measure.

The purpose of this study is evaluate the optical properties of polyacrylonitrile (PAN) nanofibers containing fluorescent agents such as fluorescent dye and carbon quantum dots (CQDs) by using image-processing technique of Fluorescence microscope image.

The fluorescence microscope image of the pure PAN, PAN/CQDs and PAN/fluorescent dye nanofibers composite was analyzed using several image-processing techniques such as color histogram, lookup table (LUT), Fourier transform, RGB profile and surface plot analysis.

The fluorescence microscope image indicates that the fluorescence emission of nanocomposites depends on the type of fluorescent agent. The fluorescence intensity of nanofiber containing CQDs is more than nanofiber containing fluorescent dye. Various image-processing methods provide similar results for optical property of nanocomposites. Analyzing the LUT, the blue value of CQDs/PAN nanocomposite image was significantly higher than other nanocomposites. This was confirmed by other methods such as Fourier transform, color histogram and 3D topography of the electrospun nanofibers. According to analysis of colorimetric parameters, higher negative value of b* indicates bluer color for CQDs/PAN nanofibers than other nanocomposites. The obtained results indicate that the image-processing technique can be used to evaluate the optical property of fluorescent nanocomposite.

This study evaluates the optical properties of fluorescent nanocomposites by using image-processing techniques such as Fourier transform, color histogram, RGB profiles, LUT, surface plot and histogram analysis.