Background and purpose: Evaluation of the quality of FOOD proteins has a great importance from of biological and economical perspectives. That is why; biological, microbiological, chemical and integrated methods have been used and introduced for determining the quality of Proteins. Among existing methods, NPR, RNPR and TPD have been suggested as appropriate methods to determine the quality of Proteins. Considering the importance of protein quality in FOODs, especially in low scale families, this study has been conducted to evaluate the aim the protein quality by the use of the mentioned methods in a sample HOMEMADE FOOD BASED on rice (a variety of Mazandaran rice) -lentil mixture in 2007.Materials and Methods: This experimental study was conducted on wistar rats, aged 21 days under 6 diets in 8 groups including case (HOME MADE FOOD), standard (Casein+Methionine) and basal (Protein free) to determine NPR and RNPR and other 3 diets (case, standard and basal) to study TPD. Duration of study for NPR was 14 days. Protein intake and increase in weight were determined to calculate NPR. Duration of study for TPD was 9 days. The amounts of nitrogen intake and fecal nitrogen were determined to calculate TPD. NPR, RNPR and TPD of the group Casein+Methionine with HOMEMADE FOOD were analyzed by t-test.Results: NPR values for casein+methionine protein of HOME-MADE FOOD were 4.3±0.4 and 3.6±0.6, respectively (P=0.02). TPD values were 92.8±4 and 75.8±5.8 (P<0.0001), for Casein+Methionine and HOME MADE FOOD proteins, respectively. Also, RNPR was 83.6% and HOMEMADE FOOD/Casein TPD were 81.6.Conclusion: Findings showed that HOMEMADE FOOD TPD and NPR BASED on RICE-LENTIL mixture is lower than Casein.

Background and Aim: Evaluation of the quality of FOOD proteins has a great importance because of biological and economical impacts. Among existing methods, true Protein digestibility, net protein ratio and protein efficiency ratio have been suggested as appropriate methods to determine the quality of proteins. Considering the importance of protein quality in FOODs, this study has been conducted to compare the value protein Cerelac (FOOD industry baby) with HOME MADE FOOD (Rice -Bean MIXED) in male rats.Materials and Methods: This experimental study was performed on 64 male rats (wistar), aged 21days under 8 diets in 8 groups including of: 2 case diets (HOME MADE FOOD and Cerelac), 1 diet standard (casein + Methionine) and 1 basal diet (protein free) in order to determine TPD, AD and 2 case diets, 1 standard diet and 1 basal diet in order to determine NPR, PER and FER. Comparison of TPD, AD, NPR, PER and FER between the groups was analyzed by ANOVA and Tukey methods.Results: TPD were 92.8±4, 87±8 and 79.7±1.6, NPR were 4.3±0.4, 4.3±0.9 and 3.8±0.6 and PER were 3±0.2, 2.5±0.4 and 2.9±0.2 for Casein + Methionine, Cerelac and HOME MADE FOOD  groups respectively. So difference TPD ANOVA between three groups was significant (p<0.0001) but NPR and PER were not significant.Conclusion: TPD and NPR are HOME MADE FOOD BASED on Rice -Bean MIXED in comparison with cereal in protein was higher and it is acceptable

The purpose of the present study was to investigate the effect of generative learning teaching BASED to pattern cognitive Load on the memorization math of 7th grade students of in the academic year of 2021- 2022. The research method is quasi-experimental with pre-test and post-test with four groups: two control group and two experimental groups. The statistical population of the study consisted of all 7th grade male and female students of District 2 of Mashhad city that 112 person sample was selected by single stage cluster sampling method. The subjects in the experimental group involved in generative learning BASED to cognitive Load in 16 sessions and the control group did not receive any interventions. The research instrument consisted of a 20-questions researcher-MADE test. To analyze the obtained data, Multivariate analysis of covariance and SPSS version 24 software were used. The results showed that generative learning teaching BASED to approach cognitive Load have a positive and significant effect on 7th grade students' memorization math. BASED on the findings, it can be concluded that one of the effective training on math memorization students is the use of generative learning on the BASED load cognitive pattern.

Purpose: The future of the construction industry is increasingly influenced by new technologies. In order to adopt appropriate strategies in facing new technologies, it is necessary to know the possible futures of the construction industry. This research was done with the aim of explaining the technological uncertainties and compiling the future scenarios of the construction industry.  Method: The research method is applied and was carried out with a combination of quantitative and qualitative methods. First, the library study was used to determine the technological drivers, then the Structural Analysis was used to explain the technological uncertainties, and finally, the Schwartz method was used to compile the scenarios. The statistical population is experts of construction industry. Findings: Nine technological uncertainties affecting the future of the construction industry have been identified and for each of them, three states of decline, stagnation and progress have been considered. Data analysis by Scenario Wizard shows eight probable scenarios. The portfolio of scenarios including four groups of progress scenarios, towards progress, towards stagnation, and towards wane has been compiled. Conclusion: In the progress scenario, the 89% of uncertainties have developed. In  towards progress, 56% of the factors are in the development status, which indicates the development of the technological factor application. In the stagnation scenario, no progress has been MADE in the application of uncertainties and they are in a static state. In towards wane, uncertainties have been placed in a situation of reduced use.

Inertial Navigation System (INS) is one of the navigation systems widely used in various land-BASED, aerial, and marine applications. Among all types of INS, Microelectromechanical System (MEMS)-BASED INS can be widely utilized, owing to their low cost, lightweight, and small size. However, due to the manufacturing technology, MEMS-BASED INS suffers from deterministic and stochastic errors, which increase positioning errors over time. In this paper, a new effective noise reduction method is proposed that can provide more accurate outputs of MEMS-BASED inertial sensors. The intelligent method in this paper is a combined denoising method that combines Wavelet Transform (WT), Permutation Entropy (PE), Support Vector Regression (SVR), and Genetic Algorithm (GA). Firstly, WT is employed to obtain a time-frequency representation of raw data. Secondly, a four-element feature vector is formed. These four features are (1) amplitude of frequency, (2) its ratio to mean of amplitudes of all frequencies, (3) location of frequency in time-frequency representation, and (4) judgment on behaviors of frequency that is obtained by utilizing PE. Thirdly, BASED on the feature vector, the GA-SVR algorithm predicts amplitudes of all frequencies in the time-frequency representation of the denoised signal. Finally, by employing inverse WT the denoised signal is obtained. In this work, the outputs of the Inertial Measurement Unit (IMU) in ADIS16407 sensor, as a low-cost and MEMS-BASED INS, have been utilized for data collection. The proposed method has been compared with other noise reduction methods and the achieved results verify superior improvement than other methods.

This research endeavors to introduce a novel concept in ethics, namely ethics BASED on the primacy of existence, drawing upon Aṣālat al-wujūd, the theory of the primacy of existence in ontology. Mullā Sadrā's philosophy, which has three basic tenets—the primacy of existence, substantial motion (Ḥarakat-i Juharī), and gradation in existence (Tashkīk-i wujūd)—is the basis for this doctrine. The primacy of existence holds that quiddity is a mental construct and that existence is fundamental. The writers distinguished between two conceptions of ethics in this regard: one BASED on existence and the other on quiddity. Human quiddity is fixed and does not grade, hence ethics BASED on quiddity's primacy will always be fixed and the same for every individual. Moral obligations are universal and shared by all individuals. On the other hand, moral obligations for humans might vary depending on their existential status, according to ethics grounded in the primacy of existence. Moral oughts and ought nots are established by human existential grades in this ethics. This ethical model is flexible and dynamic.

Introduction & Objective: Evaluation of the quality of FOOD proteins have a great importance because of biological and economical impacts. Different biological, microbiological, chemical and combined methods have been used and introduced for determining quality of proteins. Considering the importance of protein quality in FOODs especially in downscale families, this study was conducted to compare protein digestibility of a commercial FOOD sample (Homana BASED on rice) with a sample of HOME MADE FOOD (BASED on MIXED rice -bean) in rats.Materials & Methods: This experimental study was conducted on 32 male Wistar rats, aged 21 days under 4 diets in 8 groups including: 2 cases diet (Homana and MIXED rice -bean), 1 standard diet (casein plus methionine) and 1 basal diet (protein free) with a weight mean of 65.4 gr/groups. The study was conducted in biochemistry department of Kashan University of Medical Sciences in 2007. The duration of follow up for true protein digestibility and apparent digestibility was 9 days. True protein digestibility and apparent digestibility were analyzed by ANOVA and Tukey methods through SPSS software.Results: True protein digestibility was 92.8±4, 87±8 and 79.7±1.6 while apparent digestibility was 89.8±4.3, 80.6±4.2 and 76.8±1.6 for casein plus methionine, commercial FOOD and HOME MADE FOOD groups, respectively. The differences between three groups were significant (p<0.0001).Conclusion: The findings showed that protein digestibility of HOME MADE FOOD BASED on rice and bean mixture is nearly almost equal to the industrial FOOD of Homana.

The purpose of the study was to design a curriculum for the elderly education BASED on dialogue education approach. Jane K. Vella is the setter of this approach and the most important feature of this approach can be considered its attention to the audience and their special needs. The method of conducting this research is the application of the recommendations of the dialogue education approach. Sampling among the elderly participating in the course was voluntary and by sending an invitation. In sending the invitation, an effort was MADE to cover the maximum diversity of education, gender, and social status. In order to select the content BASED on the participants' needs, the list of Iranian elderly's educational needs was given to the six elderly who attended the educational meetings for selection. After selecting the content, the elements of the dialogical curriculum were determined. In the implementation phase, changes were MADE to adapt to the context, in the design and implementation process, and all the implementation and design phases were validated by Vella and the team members. Considering the special characteristics of the elderly, such as having experience, independence and self-directedness, the curriculum used for them should be able to take into account these characteristics, and considering the high flexibility of the dialogue and listening approach, as well as the achievement of all learners to the goals of each meeting, the approach to design educational courses in centers whose audience is the elderly, can increase the effectiveness and attractiveness of the courses.

One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive control method BASED on dynamic programming has been used to design a stabilizing power system and a complementary static var compensator (SVC) controller. By applying a single line to ground fault in the network, the robustness of the designed control systems is demonstrated. Also, the simulation results of the method used in this paper are compared with controllers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive control method BASED on dynamic programming for the stabilizing design of the power system and the complementary SVC controller. The performance of the control method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

Face recognition from digital images is used for surveillance and authentication in cities, organizations, and personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors and one or more servers to process data. All sensor data from initial methods was sent to the central server for processing, raising concerns about sensitive data disclosure. The main concern was that all data from all sectors that could contain confidential information was placed in a central server. Federated learning can solve this problem by using several local model training servers for each region and a central aggregation server to form a global model in IoT networks. This article presents a novel approach to optimize data transfer and convergence time in federated learning for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time and model accuracy in a federated learning environment. The results demonstrate the effectiveness of the proposed approach in reducing data transfer and convergence time, leading to improved performance in face recognition accuracy. This research provides insights for researchers and practitioners to enhance the efficiency of federated learning in real-world applications.