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Fodder supply in Iran is considered as one of the most important limiting factors in the field of livestock breeding and production. Camelina (Camelina sativa L. Crantz) plant from the Brassicaceae family is able to grow in different weather and soil conditions and needs less water, fertilizer, and pesticides than other oilseeds. This medicinal-oil product is a rich source of oil (28 to 40 percent) and omega-3 fatty acids, which can also be consumed in human diets. On the other hand, about 90 percent of the fatty acids in camelina oil are unsaturated, and due to its high alpha-tocopherols and vitamin E content, it does not require any additives to increase the shelf life of the oil, which is why it can be considered a high-quality edible oil. This research was conducted to introduce camelina and to evaluate the effects of planting date and spacing on oil yield and the quality of camelina fodder in Mazandaran Province.

This experiment was carried out as factorial based on a randomized complete block design in three replications at Bayekola Agricultural Research Station (Mazandaran Agricultural and Natural Resources Research and Training Center). Five planting dates (November 5, November 21, December 5, December 21, and January 4) and five planting distances (15, 20, 25, 30, and 35 cm) were selected as the study factors. Each treatment was planted in a plot consisting of six lines, and the distance between the plots was determined as one unplanted line. At the 50% flowering stage, biomass yield was determined by harvesting four square meters from the middle rows of each plot. Additionally, forage quality traits were assessed, including oil percentage, neutral detergent fiber percentage (NDF%), acid detergent fiber percentage (ADF%), crude protein percentage (CP%), nitrogen percentage (N%), and ash percentage.

The results of analysis variance of the studied traits showed that the interaction between planting distance and planting date had a significant effect on most of the traits of camelina. The results indicated that the planting date of December 5 produced the highest oil percentages at planting distances of 25 cm, 20 cm, and 30 cm (6.1%, 6.0%, and 6.0%, respectively). Oil content increased from the November 5 planting date to the December 5 planting date, but declined with the January 4 planting date. The lowest values for neutral detergent fiber (NDF) and acid detergent fiber (ADF) were observed in the 30 cm planting distance treatment with the December 5 planting date (60.7%) and the November 21 planting date (39.8%), respectively. Planting distance of 25 cm and planting date of December 5 showed the highest percent of crude protein (15.8), while, the treatment of planting distance of 25 cm and planting date of November 5 showed the highest plant ash percent (10.0), which had no significant difference with the treatment of 30 cm planting distance and planting date of December 5 (9.3). The highest biomass yield of camelina was obtained in the treatment with a planting date of November 21 and a planting distance of 25 cm (1778 g m-2). In all planting distances, the biomass yield reached its maximum on the planting date of November 21, and with a delay in planting, a downward trend in the trait was observed, when the lowest value was obtained in the treatment of planting date of January 4 and a planting distance of 35 cm (972 g m-2).

In general, according to the obtained results, planting distance of 25 to 30 cm and planting date of November 21 to December 5 with high oil and protein content and low NDF and ADF and can be a suitable candidate for the production of high quality and quantity camellia fodder.

With the expansion and spread of the Internet of Things, the ineffectiveness of the old encryption methods was proven. PUF was introduced as a hardware solution and is currently the best choice for securing IoT devices. The PUF structure based on the ring oscillator (RO-PUF) is one of the most well-known and desirable PUFs. It is also the best structure for the implementation of FPGA. Compared to other schemes, the responses generated by RO-PUF are the most reliable. This paper introduces an RO-PUF that provides maximum reliability, has a vast challenge-response pair (CRP) space, and is resistant to modeling attacks. A new comparator block is added to the CRO-PUF structure to evaluate the response bits and, when the value difference of the two counters is significant enough, to determine the stable response bits at the output. The proposed structure was implemented on the Xilinx FPGA board. The experiment shows that the proposed structure has ideal reliability, uniqueness, and uniformity close to the ideal value. This structure is resistant to modeling attacks due to its reconfigurability. Due to its maximum reliability and CRP, this structure can be the best choice for lightweight cryptographic applications.

Automated Guided Vehicles (AGVs) have been widely used in industrial factories and seaport due to their high efficiency and ability to move in recent years. Nevertheless, controlling AGVs to keep moving in the predefined (correct) direction is one of their most important challenges. In this paper, an automated guided control system is designed using the direct current of servomotor. In order to guide the automatic control robot in the predefined and rotational paths, the Proportional-Integral-Derivative (PID) control system with proportional, integral, and derivative parts is used. Adaptive adjustment of PID controller coefficients is difficult due to the nature of the used control system location. Hence in this study, an optimally set up of the coefficients of PID controller is used in control system of AGV by applying adaptive Radial Basis Function Neural Network (RBFNN). The simulation results indicate that the proposed controlling scheme can optimally increase the accuracy rather than traditional PID-based method. In addition, the proposed scheme is practically implemented as a prototype robot leading to provide an experimental validation to be used as an applicable solution in AGV control systems due to the low cost of design and optimal performance.

Rice is a staple food source and the most important grain in developing countries, which is most commonly consumed by more than 90 percent of the world populations. Moreover, this plant is produced and consumed in Asia. However this major crop faces severe limitations such as water scarcity and other environmental stresses. Limited water resources along with climate change effects, have increased attention to methods which improve water use efficiency in crops such as rice cultivation. On the other hand, traditional irrigation methods for rice production often waste considerable fraction of irrigation water. Therefore, it is necessary to modify irrigation and other farming methods. Furthermore, using biochar and nitrogen fixing bacteria as organic biofertilizers can be effective methods to improve water use efficiency and yield attributes of rice plant. Therefore, the present research was conducted to investigate the effect of biochar and Azosprillum lipoferum rhizobacteria on yield and water use efficiency on Tarom Hashemi rice cultivar of under flooded and alternating irrigation regimes. 

This study was conducted at the research fields of the Sari Agricultural Sciences and Natural Resources University in 2017 and 2018. The experimental site is located at 36º 39ʹ42ʺ N latitude and 53º03´54ʺ E longitude with -11 m above sea level. Soil samples were taken from depths of 0-30 cm before land preparation. The experiment was done in factorial split-split plot arrangement with complete randomized blocks based design with three replications. Treatments included two irrigation management methods (flooding and irrigation regimes) in combination with nine fertilizers levels (100% of recommended nitrogen or N100, N100+ 10 ton biochar or biochar 10, N100+ biochar 20, N75, N75+ biochar 10, N100+ biochar 20, N50, n50+ biochar 10 and N100+ biochar 20) as main plots and seedling inoculation with Azospirillum lipoferum bacteria (without inoculation was also included as control) as sub plots.Plot ridges were covered by plastic sheets and inserted into the soil at 50 cm to prevent water flowing from one plot to the others. The plots were then leveled and 3-4 leaf seedlings stage. A specific number of seedlings were gently washed and placed for 30 minutes in a pan containing 10 L of water mixed with 1 L of bacterial inoculum. Carboxymethyl cellulose, 15 g, was added to increase adhesion of bacteria into the plant roots. Nitrogen, phosphorus and potassium fertilizers were applied according to the results of soil analysis. Weeds and pests were controlled mechanically or by hand and no herbicides or pesticides were used.

Results showed that biochar and nitrogen fertilizers, irrigation methods, and seedling inoculation with bacteria had significant effects on water use efficiency indices. Comparison of means of interaction effects showed that the highest paddy yield (5950.43 and 5330.78 kg/ha, respectively) were observed by flooding irrigation method in combination with N50 + biochar 20 treatment and inoculated by Azospirillum lipoferum bacteria and alternating irrigation management method which was along with N50 + biochar 20 without inoculation. Alternating irrigation plots experienced water shortage in some growth stages and therefore slightly lower paddy yield is acceptable. Application of biochar 20 and flooding or alternating methods which treated by N75 and N50, respectively showed 49.1% increase in economic efficiency index.

In general, application of 20 ton biachar along with 75% nitrogen fertilizers led to 42.8% increase in economic advantages in alternating irrigation method as compared to the flooding systems. These observation indicates beneficial effect of fertilizer in economic advantage enhancement in rice cultivation.

One of the major challenges of Interferometric Synthetic Aperture Radar (InSAR) technique is the existence of tropospheric effect on the results. The tropospheric effect is due to the changes of atmospheric parameters including temperature, pressure, and humidity between the master and slave images. In this research, two different methods based on spatial-temporal filters and calculation of phase delay using MERIS data were evaluated. The main objective is to monitor the interseismic deformation across the Tasouj fault located in West and East Azarbaijan provinces. To this end, Stanford Method for Persistent Scatterer (StaMPS) is applied on 12 ascending ENVISAT ASAR images spanning between 2004 and 2008. The deformation time series obtained from StaMPS are two rough due to the atmospheric effect. In the first method employed for the atmospheric effect reduction,  considering that the atmospheric effect is a temporally-decorrelated and spatially-correlated signal, two different high pass and low pass filters are applied in the temporal and spatial space in order to extract the atmospheric signal which is then subtracted from the time series analysis results. In the second method, the phase delay due to the troposphere is estimated using the MERIS water vapor product. GPS measurements are finally used in order to evaluate the performance of different atmospheric reduction methods. Two quantitative criteria, i.e. Root Mean Square Error (RMSE) calculated from GPS and corrected time series and standard deviation of atmospherically-corrected time series are considered as two relevant methods for evaluating the fluctuations reduction. The method based on spatial-temporal filters shows more superiority over the other one with RMSE and standard deviation of 13 mm and 40 mm, respectively, at its best case.

Researches have shown that converting bioactive compounds to nanoscales increases their effectiveness due to their size surface area. Therefore, use of antimicrobial compounds at nanoscales can progress their effectiveness, decreasing their necessary concentrations. Salvia leriifolia, with valuable secondary metabolites such as flavonoids and alkaloids, includes a high antimicrobial activity against a wide range of microorganisms. In the present study, possibility of producing nanocapsules containing leaf extract of S. leriifolia and antimicrobial effects of the extract and nanocapsules containing the extract on sausage samples were investigated.

Emulsion method was used for the preparation of calcium alginate nanocapsules containing the extract. The ratio of extract (at a concentration of 500 mg/ml) to sodium alginate was 1:4. Nanocapsules containing extract was produced by adding calcium chloride nanoparticles to alginate nanoparticles containing extract in three ratios of 1:6, 1:9 and 1:12 within 3, 4 and 5 h. To investigate antimicrobial potency of the extract and nanocapsules containing extract, microbial properties of sausage samples were assessed during two months of storage.

Encapsulation efficiency and zeta potential were high in all samples. Based on the particle size and dispersion index, nanocapsules with an alginate to calcium chloride ratio of 6 to 1 and formation time of 4 h were selected as the best treatment. Results of microbial analysis showed that only in the sample with no preservatives on day 60 of storage, the total microbial count exceeded the national standard limit. After 2 months of storage, the lowest number of molds and yeasts was achieved in sausage samples with nanocapsules containing the extract. None of the sausage samples were contaminated with Escherichia coli, Salmonella, coagulase-positive staphylococci and Clostridium perfringens during the shelf life; however, addition of the extract, nanocapsules containing the extract or nitrite did not prevent growth of the coliforms.

Results of the present study showed that use of herbal extracts containing antimicrobial compounds such as leaf extract of Salvia leriifolia, especially in nanoscales and appropriate concentrations as alternatives to synthetic preservatives, facilitates production of healthier foods with longer shelf life.

The prevalence of Covid 19 disease has different consequences in economic, social and psychological levels. Anxiety is one of the psychological consequences of this disease. Some individual variables, such as defense mechanisms has important role in anxiety. Therefore, the aim of the present study was to determine and investigate the relationship between the use of various defense mechanisms and the anxiety of corona virus.

The present descriptive correlational study was conducted in 2020. The statistical population of the study was selected from all people aged 20 to 80 years in the southern provinces of the country, including Fars, Khuzestan, Chaharmahal and Bakhtiari and Isfahan. Sampling method was available and based on the consent of individuals for cooperation. This method was selected due to Covid 19 disease limitations. The anxiety questionnaires and Andrewsm singh and Bond defense mechanisms were completed virtually through social networks. The collected data were analyzed using multiple regression tests.

The results revealed that high levels of Coronavirus anxiety (in physical and mental dimensions) were positively correlated with high scores in psychologically disturbed and underdeveloped defense mechanisms. Defense mechanisms furthermore predicted 58% of Coronavirus anxiety. Based on beta coefficients, among the three defense mechanisms, the highest positive and statistically significant effect power was not statistically related to the defense mechanism (β=29) and the lowest effect was the psychologically disturbed defense mechanism (β=21) and the defense mechanism was developed. It had a negative predictive power(β= -27).

The results disclosed that proper use of defense mechanisms is one of the ways to maintain mental health and in dealing with any crisis, apart from health measures, attention to intrapersonal variables, especially in the field of defense styles and confrontations, can help to develop more complete and indigenous treatment protocols.

The purpose of this study was to investigate the effectiveness of verbal creativity storytelling and phonological awareness of dyslexic students which was done by a quasi-experimental design with pretest-posttest with control group. The sample included 28 dyslexic male students who completed the third elementary school in the academic year of 2018 selected through convenient sampling from the centers of diagnosis and treatment of state and private learning disorders in the cities of Tehran, Shahryar and Karaj. The students were randomly assigned into two experimental and control groups of 14 people. The instruments used in this research were Dastjerdi and Solaymani Phonological awareness and Torrance Creativity Test of Verbal Section (Form A). The data were analyzed using covariance analysis. The results indicated that the method of storytelling was based on the overall score of verbal creativity, the score of each of the subscales (originality, fluency and flexibility), the overall score of phonological awareness, and the score of its levels (syllabic, intra-syllabic and phonological awareness). These have been effective and led to higher scores. Based on the findings of the study, the storytelling method is effective in improving the performance of dyslexic students.

Garlic (Allium sativum L.) is an important Allium crop in the world. Due to its therapeutic properties, it was cultivated in many countries. Furthermore, garlic is usually used as a flavoring agent; it may be used in the shape of powder or granule as a valuable condiment for foods. In addition to its use in food products, it was also widely used as an anticancer agent. Shallot (Allium hiertifolium Boiss. L) is a perennial and bulbous plant. It is from Alliaceae family and is an important medicinal plant. The shallot is native of Iran, and grows in the high pastures. Shallot is consumed in dry areas in most parts of the country. Also shallots have been well known in Iranian folk medicine and its bulbs have been widely used for treating rheumatic and inflammatory disorders. In addition, this plant is used in the preparation of significant amounts of potassium, phosphorus, calcium, magnesium, sodium, pickles and as an additive to yogurt and pickles. ANN as a modern approach has successfully been used to solve an extensive variety of problems in the science and engineering, exclusively for some space where the conventional modeling procedure fail. A well-trained ANN can be used as a predictive model for a special use, which is a data processing system inspired by biological neural system. When mathematical equations are difficult to extrapolate, and fuzzy logic is better when decisions must be made with the estimated values below the incomplete information. The fuzzy logic theory effectively addresses the uncertainty problems that solve the ambiguity. The aim of this study was to predict moisture ratio of garlic and shallot during the drying process with fluidized bed dryer using mathematical model, artificial neural networks and fuzzy logic methods. Tests were carried out on three levels of inlet air temperature (40, 55 and 70 °C) and three inlet air velocities (0.5, 1.5 and 2.5 m/s). To estimate the drying kinetic of garlic and shallot, five mathematical models were used to fit the experimental data of thin layer drying. Three factors (air temperature, air velocity and drying time) to forecast moisture ratio in fluidized bed dryer as independent variables for artificial neural networks and fuzzy logic was considered. Cascade forward back propagation (CFBP) and feed forward back propagation (FFBP) with Levenberg-Marquardt (LM), Bayesian learning (BR) algorithms for ANN and the Mamdani Fuzzy Inference System using triangular membership function were used for training patterns. Consequently, the Page and Midilli et al. model was selected as the best mathematical model to describe the drying kinetics of the garlic and shallot slices, respectively. The results of artificial neural networks model for predicting MR showed that the R2 of 0.9994 and 0.9996; and and RMSE of 0.0036 and 0.0014 were obtained for garlic and shallot, respectively. Also, The fuzzy inference system presented the R2 of 0.9997 and 0.9998; and and RMSE of 0.0027 and 0.0011 for garlic and shallot, respectively. Comparing the results obtained from mathematical models, artificial neural networks and fuzzy logic, showed that the RMSE in the fuzzy logic was lower than artificial neural network and mathematical models. Three factors (air temperature, air velocity and drying time) were considered for forecasting moisture ratio in fluidized bed dryer as independent variables using mathematical model, artificial neural networks and fuzzy logic. Cascade forward back propagation (CFBP) and feed forward back propagation (FFBP) with Levenberg-Marquardt (LM), Bayesian learning (BR) algorithms and the Mamdani Fuzzy Inference System using triangular membership function were used for training the patterns. Comparing the results obtained from mathematical models, artificial neural networks and fuzzy logic, showed that the root mean square error in fuzzy logic was lower than others.

Tooth brushing along with a toothpaste is the most frequent and important method in managing a healthy oral hygiene. However, using such products also has its side-effects and shortcomings. Considering the large range of toothpastes available and the insufficiency of proper researches in this area in Iran, this study was designed to evaluate the abrasiveness of a toothpaste for sensitive teeth and a whitening one with two similar Iranian brands.

This was an invitro experimental study. Four groups of enamel samples consisting of each 6 specimens were prepared and embedded in acrylic blocks. The initial surface profile for each specimen was calculated using a profilometer. The samples undertook the wear phase in a V8 Cross Brushing machine using toothbrushes and a toothpaste solution. The samples were then dried and the surface profile was again calculated. The variation of the first and second profilometer calculations demonstrate the amount of wear for each specimen. Data was analyzed using the SPSS program by means of One way ANOVA and Repeated Measure ANOVA tests.

The amount of wear recorded for the 4 experimental groups was significantly different (p=0.039). However, the two by two comparision tests showed that the Iranian brands did not appear to have a significant difference with their foreign counterparts (p>0.05). The only difference was apperant between the two Iranian brand groups.

According to the present study, it seems that there is no significant difference in the abrasive properties of the Iranian and foreign made toothpastes. However, similar researches considering different effects of toothpastes and especially in more clinical conditions and by utilizing different measurement methods appears to be necessary in Iran.