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This paper presents a pioneering investigation into the barriers impeding the adoption of reverse logistics (RL) in the Iranian construction industry, addressing a significant gap in the current literature within the country.

Through a meticulous examination of the literature, complemented by 19 in-depth interviews, a battery of barriers to RL implementation was initially identified, distilled into a final set of 30 barriers, which served as the basis for the design of a structured survey questionnaire. Employing Partial Least Squares–Structural Equation Modeling (PLS-SEM), an analysis was conducted on a dataset that comprised of 80 responses. Subsequently, the barriers approved through the PLS- SEM were subjected to prioritization through the application of Fuzzy TOPSIS.

Findings reveal the critical inadequacy of contemporary technology and infrastructure, a foundation essential for the efficacious enactment of RL. This shortfall manifests in procurement and logistics processes plagued by inefficiency and ineffectiveness, as consequences of an immature information and technology ecosystem. Furthermore, the study underscores the dominance of traditional markets where the adoption of secondary materials/products remains sporadic, signaling a crucial area for further research and intervention.

This study offers original insights into the significant hurdles that hinder the adoption and integration of RL practices within the Iranian construction industry, an under-explored area within the RL research domain. For industry practitioners, findings point to recommendations for overcoming these barriers in the specific Iranian context while also offering broader insights and lessons that may be relevant to other countries and similar contexts.

This study aims to short-therm forecasting of power generation output for this purpose, an adaptive neuro-fuzzy inference system (ANFIS) is designed to forecast the output power of power plant based on climate factors considering wind speed and wind direction simultaneously.

Several methods and algorithms have been proposed for systems forecasting in various fields. One of the strongest methods for modeling complex systems is neuro-fuzzy that refers to combinations of artificial neural network and fuzzy logic. When the system becomes more complex, the conventional algorithms may fail for network training. In this paper, an integrated approach, including ANFIS and metaheuristic algorithms, is used for increasing forecast accuracy.

Power generation in power plants is dependent on various factors, especially climate factors. Operating power plant in Iran is very much influenced because of climate variation, including from tropical to subpolar, and severely varying temperature, humidity and air pressure for each region and each season. On the other hands, when wind speed and wind direction are used simultaneously, the training process does not converge, and the forecasting process is unreliable. The real case study is mentioned to show the ability of the proposed approach to remove the limitations.

First, ANFIS is applied for forecasting based on climate factors, including wind speed and wind direction, that have rarely been used simultaneously in previous studies. Second, the well-known and more widely used metaheuristic algorithms are applied to improve the learning process for forecasting output power and compare the results.

The purpose of this paper is to present an overview of different aspects of inulin functionality in meat and poultry products.

Several studies on the physiochemical, textural and sensorial effects of inulin incorporated in meat and poultry products as fat replacer and texture modifier were reviewed.

Inulin is a plant-derived carbohydrate composed of fructose units and glucosyl moieties at the end of the chain that exhibits unique nutritional and technological benefits. Among its main healthy characteristics, it has been reported to reduce the risk of colon cancer, arteriosclerosis, osteoporosis, diabetes and obesity, to maintain low levels of triglycerides and cholesterol in serum and stimulate the immune system. As a functional food ingredient, it can be used in various foods as a fat replacer, improves water-holding capacity and emulsion stability, as well as modifying the texture and viscosity of foods. Incorporation of inulin into meat and poultry products can be beneficial in producing low-fat products with desirable texture and sensory attributes.

There are limited reviews regarding the application of inulin in meat and poultry products. In this review, chemical composition and physicochemical properties of inulin, its health effects and various effects of inulin incorporation into meat and poultry products including, physicochemical, textural and sensory characteristics of these products are discussed.