مصطفی لطفی

The Islamic Revolution of Iran stands as one of the most significant socio-political events of the last century. Like all major revolutions, it possesses a strategic model essential for sustaining its trajectory, achieving its multifaceted ideals, and serving as a paradigm for other nations. By establishing a framework underpinned by the principles of Islamic jurisprudence (Velayat-e Faqih) and the Constitution, the revolution aimed to extend spiritual blessings globally through the Iranian nation. To ensure the revolution’s evolutionary progress and to effectively address emerging challenges, a strategic model must be developed based on an analysis of the nation's experiences over the years. This study seeks to propose such a model, drawing from the discourse of the Imams and the Constitution. The research is developmental in purpose and employs a descriptive-analytical, exploratory approach. The primary sources include the guidance and directives of Imam Khomeini (May God Bless him), Imam Khamenei (May God Protect him), and the Constitution of the Islamic Republic. Using qualitative methods and MAXQDA software, the findings are categorized into three dimensions: fundamental values, objectives, and policies of the Islamic Revolution. The study also offers actionable recommendations for sustaining the revolution's core ideals and addressing its future challenges effectively.

Background & the efficient supply chain is one of the important factors in increasing the combat power of defense organizations. Then, in the present research, the design of the smart  Warehouse Managment System of defense organizations is discussed with regard to the fourth industrial revolution.
In terms of its purpose, this research is an applied research and was done qualitatively with the aim of designing smart warehouses. The participants of this stage included selected experts with whom semi-structured interviews were conducted. Thematic analysis method was used to analyze the interview data.
The warehouse design was identified in three main categories; criteria (reliability, cost, productivity and security), requirements (the state of competent human resources, the necessary technical ability to use and implement artificial intelligence, securing warehouses and the state of a suitable mechanized system) and identifying activities (availability of information, stakeholders and decisions key process, task assignment, input process, inventory management, order fulfillment, location management, output process, problem management and financial collection).
Paying attention to the intelligent warehousing management system in defense organizations will improve the supply chain, increase efficiency and reduce costs, and will improve the defense capability.

Today, one of the important concerns and priorities of the officials and commanders of the system is paying special attention to the improvement of the defense and combat readiness of the armed forces, especially in the aspect of readiness and support. Jerusalem operation; It is a milestone and an epic point during the defense of the holy era that the naval forces; Air and ground forces of the army were present at the same time, and in addition, the Islamic Revolutionary Guard Corps; Constructive Jihad and popular forces also cooperated due to the existence of consecutive operations such as the battle of: Saman Al-Aima; Tariq Al-Quds; Fath-ul-Mobin before this operation and the short period of one month to prepare for this operation, logistics management in this operation is one of its positive points. The purpose of this research is to examine the role of the logistics system (readiness and support) of the army c. A. It is in the operation of Beit Al-Maqdis (Karbala 3).

The current research is a descriptive-survey research in terms of purpose, application, and in terms of how to obtain data. For the sample, theoretical and targeted saturation of available sources and interviews with experts have been done. In this direction, the answers of the interview, the method of restating the questions in a different way from the initial interview and re-presenting them at another time, as well as the selection of the number of interviewees and the appropriate use of the views and opinions of experts have been used.

To achieve the goal by examining the library resources and registered documents of the Holy Defense and on the other hand by analyzing the interviews conducted with the commanders and decision makers of the Jerusalem operation using MAXQDA23 software; Tips on how to manage logistics and how to prepare ground forces were identified.

Based on interviews and research questions that is in sixth scope which are predicting, preparation, repair and maintenance, transportation and assignation have discussed about managing this six scope in logistics facilities for Jerusalem operation which is intended for grouping and pivotal coding that pivotal codes is extracted in three dimension which are predicting, preparation and assignation management, maintenance management which each mentioned aspect included of variant table and pivotal factor has been inducted and at the end applied suggestions is presented.

This study was conducted to investigate the effects of mixer added fat, crude protein and conditioning temperature on the pellet durability index, and electrical energy consumption during feed production using computational modeling tools. A total of 192 broiler feed samples with different levels of mixer added fat and crude protein in feed components and different conditioning temperatures to determine the pellet durability index, modified pellet durability index and electrical energy consumption during feed production were used. Multiple linear regression and artificial neural network were used to analyze data. Both models had the ability to predict the value of the pellet durability index, modified pellet durability index and the electrical energy consumption during feed production; but the prediction accuracy of the artificial neural network model was higher than that of the multiple linear regression model for all three outputs. Optimization was done using the artificial neural network model, and in these calculations, in order to achieve the highest possible level of pellet physical quality and the lowest possible level of electrical energy consumption, the crude protein amount was 20-20.5% and the conditioning temperature was predicted to be 85 C. However, the amount of fat was predicted to be 1% for the highest amount of pellet physical quality and 4% for the lowest amount of electrical energy consumption during production. In practical conditions, this model can help in more accurate prediction of electricity consumption and the quality of produced feed in order to achieve the optimal situation in feed production factories.

Contrary to the standard approach of classical economics, many studies show that all people somewhat engage in wrongdoing and break the law in order to gain profit as long as their self-image is not affected. The current study, which is a branch of this new psychological view on breaking the law, using two tests, identifies and examines the factors affecting the possibility of breaking the law among people. In the first test, the relationship between the amount of legal restrictions and the amount of participation in price manipulation was investigated on an international sample including 347 cryptocurrency traders. In the second test, the relationship between the probability of breaking the law in one field and the probability of breaking the law in another field was investigated on a sample of 189 entrepreneurs. According to the results of the current study, breaking the law in one field can make people more indifferent to all laws. In addition, the increase in legal restrictions can make people more indifferent to laws, which itself reduces the amount of attention to the law. Among other factors affecting the probability of breaking the law, one can refer to the person's understanding of the extent of breaking the law among others. The more someone estimates the amount of law-breaking by their peers in similar circumstances, the more they will break the law. This study provides policymakers and planners with practical suggestions.

The purpose of this study was to develop multiple linear regression (MLR) model to predict the nitrogen-corrected true metabolizable energy (TMEn) value of wheat bran. The amount of crude fat, ash, crude protein, crude fiber (all used as % of DM) and TMEn (Kcal/kg DM) were measured in 25 wheat bran samples with 4 replicates. The force-fed method has been used to estimate TMEn and excreta were collected for 48 h. There were significant (P < 0.001) differences in chemical composition and TMEn of wheat bran samples. The average crude fat, ash, crude protein, crude fiber and TMEn content of samples was determined to be 4.80, 5.68, 16.23, 8.60 (all used as % of DM) and 2062 (Kcal/kg DM), respectively. The calculated MLR model to predict the TMEn value (Kcal/kg) based on chemical composition (% of DM) was obtained as follows: TMEn = 2364 + (19×crude protein) + (46.1×crude fat) – (63×crude fiber) – (51.1×ash). The R2 value revealed that developed model could accurately predict the TMEn of wheat bran samples (R2=0.82). Crude fat and crude protein had a positive effect on TMEn, while ash and crude fiber had a negative impact on TMEn. The sensitivity analysis on the model indicated that dietary crude fiber (%) is the most important variable in the TMEn, followed by dietary ash, crude fat and crude protein. The results suggest that the MLR model may be used to accurately estimate the TMEn value of wheat bran from its corresponding chemical composition.