Reversible logic has been emerged as a promising computing paradigm to design low power circuits in recent years. The synthesis of reversible circuits is very different from that of non-reversible circuits. Many researchers are studying methods for synthesizing reversible combinational logic. Some automated reversible logic synthesis methods use optimization algorithms Optimization algorithms are used in some automated reversible logic synthesis techniques. In these methods, the process of finding a circuit for a given function is a very time-consuming task, so it’, s better to design a processor which speeds up the process of synthesis. Application specific instruction set processors (ASIP) can benefit the advantages of both custom ASIC chips and general DSP chips. In this paper, a new architecture for automatic reversible logic synthesis based on an Application Specific Instruction set Processors is presented. The essential purpose of the design was to provide the programmability with the specific necessary instructions for automated synthesis reversible. Our proposed processor that we referred to as ARASP is a 16-bit processor with a total of 47 instructions, which some specific instruction has been set for automated synthesis reversible circuits. ARASP is specialized for automated synthesis of reversible circuits using Genetic optimization algorithms. All major components of the design are comprehensively discussed within the processor core. The set of instructions is provided in the Register Transform Language completely. Afterward, the VHDL code is used to test the proposed architecture.

In this paper, we have proposed a novel hardware caching technique to reduce the communication latency in ODYSSEY methodology. The main idea is to implement small fast split caches in a parallel way to connect the medium to capture and store ownership information as the data flows from the memory module to the requesting processor. One of the main factors for estimating the rate of modem processors is their memory access time. Using cache memory enhances the access time; therefore it remarkably increases the rate. However, this rate is not sure enough for the systems like ODYSSEY which require parallel memory access time. In this paper, we present a new method in which cache memory is split into parts, so that simultaneous accesses to these parts are possible; therefore, the memory access time is highly improved.

Deforestation in the past decades has risen. So, the proper development of human activities in forests requires the environmental limitations to be considered during forests management process. One of the appropriate measures is the determination of ecological vulnerability. In the present study, Patom District of Kheyrud Forest was classified based on the ecological sustainability, using Object- Oriented Vulnerability Method. The results showed that 26% of the study area is located in middle sensitive class, 46% in sensitive class and 28% in very sensitive class. Overall, we infer that Patom District of Kheyrud Forest has the high ecological vulnerability that it should be considered by forest managers.

Introduction: Sheep are the main source of wool and its fiber characteristics, such as diameter, length, and color, which are determined by genetics and environmental factors, are key features in the economic value of sheep wool. In sheep, white wool has the highest economic value due to its dyeability, thus, the identification of mechanisms responsible for coating color determination is very important from an economic point of view. In general, the coat color is determined based on the amounts and types of melanin produced and released by the melanocytes in the skin tissue (Ito et al., 2000). The genetic basis and genes involved in coat color are well understood in rodents, although many of these genes are incorporated in coat color regulation in other species; including Sheep also have a common role. In Iran, the Lori Bakhtiari sheep is one of the most important breeds of sheep in terms of the use of its wool in the textile and carpet industries. In his breed, the dominant coat of the wool is white, although sometimes a percentage of dark brown and pale brown is also observed (Saadat Nouri, M. & Siah Mansour, 1368). However, in this breed, some animals have black spots on their coat, which leads to a decrease in wool quality. Since MC1R, ASIP, KLF4 and MITF genes play an important role in controlling and determining coat color in mammals, the purpose of this study was to investigate the expression of these genes in two phenotypes of white and black spots in the skin tissue of Lori Bakhtiari sheep.Materials and Methods: Skin samples were obtained from both white and dark parts of 14 white-coated sheep with black spots and total RNA was extracted. The quality and quantity of extracted RNAs were evaluated by agarose gel electrophoresis and spectrophotometer. Extracted RNA samples were exposed to DNase1 enzyme digestion to remove the possible contamination of genomic DNA. Also, the quality of synthesized cDNA was evaluated using 1% agarose gel. In this research, in order to amplify a fragment of the studied genes, using the mRNA sequence of these genes in the GenBank database, appropriate primers were designed by Primer3plus software. To evaluate the relative expression of the target genes, β-actin and GAPDH genes were used as reference genes to normalize the data. Finally, BestKeeper and REST 2009 V2.0.13 software were used for the analysis of gene expression data.Results and Discussion: Based on the descriptive results of Ct values, MC1R and MITF genes revealed minimum and maximum expression stability among the target genes in skin samples with standard deviations of 1.34 and 3.62, respectively. In addition, the reference genes (β-actin and GAPDH) showed the highest stability among all the studied genes. No significant differences were observed in mRNA levels of MC1R, ASIP, KLF4, and MITF genes in the spotted skin tissue compared to the white part of the skin (p>0.05). However, the expression of the ASIP gene was more than 2 times in the spotted part compared to the white skin, but this difference was not significant (p=0.21). In addition, the MC1R gene showed minimum expression differences in black spots and white parts of the skin tissue. In addition, the MITF and MC1R genes showed the highest and lowest levels of expression in skin samples of Lori Bakhtiari breed sheep with average Ct of 25.86 and 30.42, respectively. However, among all the studied genes, the lowest mRNA level was observed for the GAPDH gene with an average Ct of 35.96.Conclusion: Mammalian coat color results from various factors such as the degree and distribution of melanin pigment and the interaction between genotype and environment (B. Li et al., 2018). In addition, melanogenesis is a complex process that includes melanocyte growth, melanosome formation, melanin synthesis, melanin transport, and melanosome release (Ito & Wakamatsu, 2011). According to the conducted studies, a large number of genes are involved in the mechanism of coat color determination, but two genes, MC1R and ASIP, play an essential role in the regulation and control of coat color (Searle, 1968). In our study, no significant difference was observed in the expression of MC1R, ASIP, KFL4, and MITF genes in the spotted compared to the white part of the skin tissue in Lori Bakhtiari sheep. These results showed that the development of skin spots is not under the control of the studied genes in Lori Bakhtiari sheep, and genes or other factors can play roles in the creation of dark spots in this breed.

Basic color in horses, such as black and white, brown and chestnut ASIP and MC1R gene is affected. The relationship between color horse and purity the study of gene polymorphism Aguti put special attention. The purpose of this study was to evaluate the polymorphism in exon 2 gene Aguti population of Arabic horse in Khuzestan. In this study, PCR-RFLP method for the detection of different alleles of the Aguti gene in horses used. Bleed extension of the 45 head of horses in the city of Ahvaz, Dezful and Shush were collected. Polymerase chain reaction 101 bp fragment of exon 2 gene and gene-specific primers were used Aguti. 11 bp deletion in exon 2 gene ASIP (Aguti signaling protein) occurred because of the In / del (delete and Insertion) of the gene Aguti. Finally three band pattern AA, Aa, aa abundance 0.414, 0.457, 0.127, respectively. The allele frequencies of A and a 0.644 and 0.356 respectively.The results showed that this fragment of gene polymorphism and genotype AA, Aa, aa population was established. The results showed that there is Hardy-Weinberg dis equilibrium in the studied population.

Change detection algorithms of remote sensing image can be divided into two categories: pixel-based and OBJECT-ORIENTED, according to the minimum processing unit.This paper deals with the comparison between application of pixel-based and objectoriented approaches in land use classification in Isfahan-Borkhar, Najafabad and Chadegan plains and evaluation of land use changes with Landsat TM (1985) and OLI (2015) data during the study period. The OBJECT-ORIENTED approach involved the segmentation of image data into objects with multi-resolution segmentation algorithm by eCognition software. Then objects were assigned and classified with the nearest neighbour algorithm in OBJECT-ORIENTED classification The supervised pixel-based classification involved the selection of training areas and a classification using a maximum likelihood algorithm. Accuracy assessments of both classifications were undertaken. The results show better overall accuracy (higher 90%) of the OBJECT-ORIENTED classification over the pixel-based classification. The land use maps indicate that residential area is increased 2.09, 9.66 and 3.74% and rangeland area are decreased 7.48, 10.94 and 17.73% in Isfahan-Borkhar, Najafabad and Chadegan plains in the study period, respectively. In Chadegan plain the increase in agriculture and fallow land use has been equal to 8.31 and 5.64%, respectively.

Safety is of primary principles of living in human communities. Preparation and provision of necessary considerations for encountering hazards are main targets of the crisis management. Nuclear risks are one of hazards threatening in the human life. Since radioactive contaminants sustain for years after the incident, investigation into nuclear hazards and its damage on living environment and urban features is so vital. This study essentially aims at evaluating the risk of radioactive contaminants to urban land uses. Due to high resolution satellite images, remote sensing technology has been considered as an advanced technology to generate information covering urban areas. Information on land cover is one of the most important tools of management during crisis. Land cover maps can be prepared through techniques for high resolution satellite image processing and extracting urban features. In this study, the fuzzy objectoriented method is applied to classify such phenomena. In the proposed method, a fuzzy rule-based strategy and hierarchical model are employed to overcome noise between classes. Fuzzy rule-based classification method is used as well as optimization and improving features of multi-scale analysis. Considering blocks of WorldView2 sensor, 91% of object detection is implemented with an average accuracy. When classification image of urban features is produced, the risk of radioactive contaminants to each recognized object is determined based on EDEM model.

Land use mapping is the basic tools for administrators and land planners. Severd methods have been proposed for land-use mapping. The latest and most important methods is using remotey sensed data for Land-use mapping. The aim of this study was performance evaluation of the pixelbased classification. (Fuzzy ARTMAP neural network and decision tree Methods) and objectoriented classification methods and using Landsat 8 image of 2013 for land-use mapping of arid and sem-iarid regions of Meimeh Ilam. Different land use classes were difined using training samples comperison of classification results of three different methods of fuzzy ARTMAP neural network, Gini decision tree and OBJECT-ORIENTED Show that the OBJECT-ORIENTED approach, has overall accuracy of 95.30 and Kappa coefficient of 90.88, and Gini tree decision and Fuzzy ARTMAP Neural Network methods has overall accuracy of 80.32 and 72.20 and Kappa coefficient of 68.75 and 36.18, respectively thus, OBJECT-ORIENTED classification method having a difference in overall accuracy 14.98% and 23.1% and Kappa coefficient of 22.13% and 54.7% has a higher accuracy compared with the Gini decision tree and fuzzy ARTMAP neural network. Map area defined by the three methods of classification, are similar in farmlands, poor rangeland, and urban area. The greatest differences were observed in area of medium rangeland and minimum differences were related to the urban area.