الهام قنبری

Urmia Lake is the largest saltwater in the Middle East, which has been located in the northwest of Iran. Nowadays, various factors have exposed it to dryness and wind erosion, the result of which is the increase in soil salinity, the thinning of solute crystals, and the occurrence of dust storms. Identifying the nature of these dusts specially the mineralogy of them is important in providing solutions to deal with the crisis. Investigating the characteristics and mineralogy of dusts in the region are useful in predicting and controlling ways to reduce their damages, and dust mineralogy is a practical method to determine their origin. In other words, the deposition of dust in different areas can affect the nearby ecosystems by making changes in the texture, composition of elements and even the acidity of the soils of the affected areas. The source of dust is very important in the mineralogy of sedimentary particles and depends on various factors such as geology and soil characteristics as well as climatic conditions. Also, the height of atmosphere which the dusts are there can be useful in studying the affect of mineralogy in this height.

For this purpose, three flat sites without vegetation and prone to fine dust production were selected from the eastern shore of Urmia Lake, and each site was divided into 3 layers based on the height from sea level, but the first layer was omitted from the studying areas because of the high soil moisture due to low distance to lake, which results in decreasing dust production by this layer, and eventually 2 random samples (0-5 cm) were picked up from each layer. This research work carried out based on 12 selected soil samples from 3 sites and their layers. The soil samples from 0 to 5 cm depth as a surface soil of layers were transferred to trays with dimensions of 3 x 40 x 30 cm in the wind tunnel of agriculture faculty of Tabriz University, with 370cm length, 50cm width and 70cm height, and wind erosion was simulated by applying the maximum wind speed of 45 meters per second to it was done for 15 minutes at each height. Then, the dust particles released at 2 heights of the wind tunnel (10 and 30 cm from the floor of the device) and the control soil sample were subjected to XRD analysis and the obtained diffractions were interpreted using High Score software. Finally, statistical analysis was performed using a nested design to find the effect of factors such as the location, layer and height of the wind tunnel on the content of minerals in windblown dust.

The obtained results showed that the dominant minerals in the most dust samples, were quartz, calcite, halite and gypsum with the highest average percent of quartz, because of the widespread occurrences of this mineral in the earth crust. The statistical analysis results revealed the significant effect of layer on quartz at the p<0.01 level, but the effect of site on calcite was significant at the p<0.05 level. But the maximum amount of quartz appeared in layer 2 of site 2, while its minimum amount has observed in layer 2 of site 1. The maximum and minimum amount of calcite was found in site 2 and 3 respectively, but predominance of quartz in the dust samples can be attributed to the wind blow within a short distance. This differences can be related to the nature of the parent materials of sites from which soils were derived. The presence of calcite as the main mineral in samples is due to study area temperature and precipitation increase and decrease respectively, which cause lake dryness, while gypsum and halite are produced in result of chemical equilibrium process and distribute in salty soils. Gypsum also can be produced during the reaction of calcite and sulfates of sea salts. The dryness of the lake also results in rising the gypsum minerals from dried floor of lake. Also, the presence of halite is affected by Urmia Lake salts that remain after water evaporation in dried land as a main mineral in soil and dust samples of affected lands.Key Words: XRD analyze, Wind erosion, Mineralogy, Wind tunnel, Urmia Lake.

Gas turbines are complex and expensive machines that the cost of repairing unexpected failures is very high. There are many sensors installed in each gas turbine that record and collect large amounts of data. With the data mining of such big data, failure prediction is possible before the occurrence. The data set for the present study is the recorded quantities of sensors mounted on a 9-frame gas turbine in one of the country's power plants. The one column of data matrix rows was first labeled to identify healthy and defective row in each data sample. Then, by using the Principal Component Analysis method, the dimensions of the data matrix were reduced from seven to four dimensions and the main features were extracted. Following this, a model was developed by applying Artificial Neural Network method that was able to identify fault rows in the data matrix and identify the class of the data samples as healthy or defective. Accuracy, precision, and convergence of the model for two-to-six-dimensional model reductions were studied after machine learning was performed on 80% of the data. After matrix dimensionality reduction, and feature extraction by using "Principal Component Analysis" method, our well-designed model was also able to identify and classify the fault by using "Artificial Neural Network" method. In this thesis, it was found that our mode l by combining "Principal Component Analysis" method with "Artificial Neural Network" was able to show more than 90% precision with good accuracy and maximum degree of data matrix convergence. Moreover, it was able to specify the gas turbine fault class.

Analyzing the influence of people and nodes in social networks has attracted a lot of attention. Social networks gain meaning, despite the groups, associations, and people interested in a specific issue or topic, and people demonstrate their theoretical and practical tendencies in such places. Influential nodes are often identified based on the information related to the social network structure and less attention is paid to the information spread by the social network user. The present study aims to assess the structural information in the network to identify influential users in addition to using their information in the social network. To this aim, the user’s feelings were extracted. Then, an emotional or affective score was assigned to each user based on an emotional dictionary and his/her weight in the network was determined utilizing centrality criteria. Here, the Twitter network was applied. Thus, the structure of the social network was defined and its graph was drawn after collecting and processing the data. Then, the analysis capability of the network and existing data was extracted and identified based on the algorithm proposed by users and influential nodes. Based on the results, the nodes identified by the proposed algorithm are considered high-quality and the speed of information simulated is higher than other existing algorithms.

Urmia Lake, which has been located in the northwest of Iran, is the largest saltwater in the Middle East. Unfortunately, nowadays various factors have exposed it to dryness and wind erosion, the result of which is the increase in soil salinity, the thinning of solute crystals, and the occurrence of dust storms. If this lake becomes dry, the climate of the area will change to hot climate and salt storms will start. Therefore, we must find new ways to control and prevent the occurrence of wind erosion. Identifying the nature of these dusts, especially their morphology, is important in providing solutions to deal with the crisis. Investigating the characteristics and morphology of dusts in the region is also useful in predicting ways and controlling factors to reduce their damages, and dust morphology is a practical method to determine their origin. Investigation of the properties and characteristics of rising dusts from this area can be useful in predicting and controlling ways to contrast/withstand their damages.

For this purpose, three flat sites without vegetation and prone to fine dust production were selected from the eastern shore of Urmia Lake. Each site was divided into 3 layers based on the height from sea level, but the first layer was omitted from the studying areas because of the high soil moisture due to low distance to lake, which results in decreasing dust production by this layer, and eventually 2 random samples (0-5 cm) were picked up from each layer. This research study was carried out based on 12 selected soil samples from 3 sites and their layers. The soil samples from 0 to 5 cm depth, as a surface soil of layers, were transferred to trays with dimensions of 3 x 40 x 30 cm in the wind tunnel of agriculture faculty of Tabriz University, with 370cm length, 50cm width and 70cm height. Subsequently, wind erosion was simulated by applying the maximum wind speed of 45 meters per second for 15 minutes at each height. Then, the dust particles released at 2 heights of the wind tunnel (10 and 30 cm from the floor of the device) and the control soil sample were sent to SEM to get their images. After processing these row images, the quantitative amounts of morphological properties were obtained. Finally, the statistical analyses were performed on these properties. Using a nested design to find the effect of factors such as the location, layer and height of the wind tunnel on the morphological characteristics of soils in the windblown dust.

The images which had been adopted from SEM were analyzed in Image J application and 5 parameters (perimeter, circularity, roundness, accept ratio and solidity) were calculated for each particle in samples and the average of these parameters for each soil sample was listed. The presented data were analyzed in Minitab application by using the fully nested method and for conducting these analyses, the test of normality of data was performed on data list. The results for each parameter were presented in a table which showed the effect of site, layer and location height of the sediments in wind tunnel.

The obtained results in this research (Table 3) revealed the significant effect of site (5%) on circularity and solidity properties. Also, the effect of height in wind tunnel from floor was significant in 5% just on roundness, and the effect of other factors on morphological properties were not significant. In other words, the size of particles, the area and their parameter in soil samples did not have significant differences and even the wind erosion with given speed in explained time duration didn’t act optional on the size of particles. There were no significant differences between size of diameter, area and parameters of particles before and after the wind erosion. The reason of these results can be dependent on the preparing method of samples for SEM study, in which the samples were rubbed on pin of device and the great grains were separated. Also, the effect of site and height of wind tunnel on roundness and circularity were significant, respectively. As for other morphological properties, the effects of site, layer and the wind tunnel height were not significant and there were no significant differences between the samples.

Because of the impact of void ratio parameter on liquefaction and static strength of sandy soils, preparation of samples which are homogenous in their heights in monotonic and cyclic triaxial tests is an important issue. Undercompaction method is an extended preparation method of wet tamping that is a suitable procedure to make homogenous sandy soil with fines. In this research, undercompaction method is used in order to prepare samples of carbonated silty sand from Boushehr Port and a method called injection of gelatin solution is used to control the homogeneity of samples. In order to investigate the effect of silt content on homogeneity of prepared samples, Boushehr carbonated sand is mixed with silt percent of 0 to 40%, and gelatin solution is injected in the samples. Results show that samples prepared with undercompaction method are homogenous, also variation of silt content, changes the parameter of reduced compation percent of first layer (Un). In silt percent 0 to 20%, Un parameter limited to 4 and 6%, and in silt percent of 30 to 40%, Un parameter is obtained 6 and 8%. It can be concluded that in lesser percent of silt, intergranular voids of sandy soil are filled with silt particles, thus first layer is compacted close to the desired density, and the final compacted sample is more homogenous than the samples with higher percent of silt.

This study aimed to compare attachment styles and perceived social support in people who approached a fortune teller and those who did not. The research was causal-comparative study and the research population consisted of people referred to forger in year 1398 in Shiraz. The sample was 50 people who approached a fortune teller and 50 who didn’t that they were selected by using available sampling method. Research instruments included Adult Attachment Inventory (AAI) and Perceived Social Support (MSPSS). The validity and reliability for tow scales are satisfactory. To analyze data were used the analysis of variance method with SPSS-21 software. The results indicated that the difference between attachment styles and social support was significant between the groups. The difference between avoidant attachment, ambivalent attachment between the groups was significant. Other results showed that there was a significant difference between the scores of family social support and social support of other groups.

Overweight is one of the problems in people nowadays, one of which is psychological, especially attentional bias. Different approaches have emerged apart from Cognitive-Behavioral Therapy (CBT) such as transcranial direct current stimulation (tDCS). Therefore, the purpose of the present study was to compare the effectiveness of tDCS and CBT on attention bias in overweight people.

The research method used was quasi-experimental research with pretest-posttest design and control group. The statistical population of the study included all overweight people referred to Aramesh Psychology Center in Tehran in year 2019. Using purposive sampling method, 36 individuals were selected and randomly divided into three groups based on inclusion and exclusion criteria. The mean and standard deviation of age was 34.27±6.45 and mean body mass index was 28.12±2.23. The research instrument was standard attentional bias questionnaire. Data were analyzed using analysis of covariance.

The results showed that tDCS and CBT were effective on The results showed that between the mean scores of pre-test and post-test tDCS on bias, attention to the component of life goals and the component of food (01.001, 0.001) and the mean of pre-test and post-CBT scores on bias, respectively The components of life goals and the component of foods (0.002, 0.001) have a significant effect, respectively. (05/0≥p). Also, there was no significant difference between the mean score of tDCS and CBT posttest on attention bias (component of life goals and food component, respectively) (p <0.299, p <0.441).

It seems that tDCS and CBT can be used to reduce people's bias in preventing the desire to eat more food. Given that this study has only been studied in one psychology center, it is suggested to investigate it in other centers to enhance the external validity of the research.

A mental health condition that causes the excessive consumption of food, leading to obesity, is food craving. According to brain imaging data, the Dorsal Lateral Prefrontal Cortex (DLPFC) plays an important role in craving. Anxiety can also occur in overweight individuals. Anxiety and obesity affect each other and are related. Furthermore, anxiety is a negative emotion that in some individuals, causes emotional eating behavior. Besides, weight gain increases anxiety, which requires neuropsychological therapies. A therapy used in the present study was Transcranial Direct Current Stimulation (tDCS), i.e., a non-invasive, painless, and safe method of cerebral stimulation. The tDCS seems to be able to modulate cortical irritability and be applied as a treatment for managing psychiatric disorders. Another intervention implemented in the present study was Cognitive-Behavioral Therapy (CBT). Psychological factors significantly impact the development of obesity. Thus, such interventions could significantly help to reduce weight and modify the negative perception of body image, and of course, self-concept and social anxiety among overweight and obese individuals. Therefore, the present study aimed to compare the effects of tDCS and CBT on craving and anxiety in overweight individuals.

This was an applied and experimental study with a pretest-posttest and a control group design. The statistical population of the study included all overweight individuals who referred to Aramesh Psychology Center in Tehran City, Iran, in 2019. Using the targeted sampling method, 36 of them were selected as the study participants and placed in two experimental groups and one control group (n=12/group). The study inclusion criteria included having a diploma and higher education, the age range of 18 to 47 years, having a body mass index of <40 kg/m2, presenting an uncontrollable tendency to consume at least one of the following foods three times a week during at least the last month: sweets and nuts, too much of fatty foods, the concurrent consumption of fast food and drugs, due to no other disorder. The study exclusion criteria included a history of epilepsy; a history of concussion or brain surgery; using anticonvulsants or antipsychotics or the regular use of benzodiazepines in the past month; a major cognitive or psychiatric condition, e.g., a history of suicidal attempt; having metal objects, like electronic implants, e.g., pacemakers or cochlear implants; pregnancy; a personal or family history of seizures; a history of endocrine or autoimmune diseases; a history of brain surgery or the loss of consciousness for >15 minutes, and a history of consuming weight loss medications or attending frequent weight loss programs. The Food Craving Questionnaire (Cepeda-Benito et al., 2000) and the Beck Anxiety Inventory (Steer & Beck, 1997) were used to collect the required information. The tDCS intervention sessions were performed for 3 sessions every other day and the CBT sessions were conducted in 8 weekly 90-minute sessions; however, the controls received no intervention. The obtained data were analyzed in SPSS using descriptive statistics, e.g., mean and standard deviation; the employed inferential statistics consisted of Analysis of Covariance (ANCOVA) and Bonferroni post-hoc test.

The mean posttest scores of craving and anxiety, after controlling the pretest scores, were significant in both test groups; in other words, both provided interventions were effective in reducing craving (p<0.001), craving intensity (p<0.001), and anxiety (p<0.001) among the study subjects. The mean of squares for cravings (a component of craving), craving (a component of craving intensity), and anxiety were 0.74, 0.68, and 0.68, respectively. Bonferroni post-hoc test was used to compare the study participants’ posttest scores after controlling the pretest values. The relevant results indicated a significant difference between the tDCS and control groups in terms of craving (inclination component) (p=0.023), craving (craving intensity component) (p<0.001), and anxiety (p<0.001). The research findings also suggested a significant difference between the CBT and control groups concerning craving (inclination component) (p=0.035), and craving (craving intensity component) (p<0.001). However, there was no significant difference between the tDCS and CBT groups for craving (inclination component) (p=0.884). Additionally, there was no significant difference between the mean scores of tDCS and CBT groups in craving (the component of craving intensity) (p=0.972). Furthermore, there was no significant difference between the mean anxiety values of the tDCS and CBT groups (p=0.165).

The provided tDCS and CBT approaches were effective in reducing craving and anxiety in the study participants. Therefore, these interventions could be used as therapeutic or educational methods to improve these conditions in overweight individuals.

E-learning is a method of teaching that uses a combination of information and communication technology capabilities to facilitate and improve learning. The combination of these facilities provides opportunities for the learner to access the course and curriculum at any time, in accordance with their job and family commitments. The ability to access tools, the ability to choose the time and place of training, and the availability of different content formats in this environment put the learner in a position to make a variety of choices. In this environment, the learner can use different tools to communicate with classmates, teachers and other people at the same time and at the same time. Implementing quality and sustainable e-learning programs requires understanding the requirements for establishing and developing e-learning systems. Designing, setting up and maintaining e-learning environments requires a variety of knowledge and skills in the technical, educational and managerial fields. The purpose of this study is to evaluate and rank the effective factors in developing e- learning in higher education. In this study, the effective factors in developing e- learning in higher education were identified in terms of measuring factors of e-learning development including organizational, social, technical and human factors, based on previous studies and the opinion of experts.

Statistical methods were used to test and confirm the research hypotheses and fuzzy AHP ranking method was used to rank the indicators. To this purpose two questionnaires were prepared. The first one is for evaluating the accuracy of the research hypotheses and the second one, a pairwise questionnaire, is for rating the indicators. The statistical population of the research is all students and professors of electronic unit of Islamic Azad University in academic year of 2016-2017. The statistical sample size was considered 384 individuals based on Cochran formula; and was selected through the random sampling method. The questionnaires were distributed among 384 individuals from which, 84 questionnaires were omitted due to different reasons such as wrong answers to the questions and the lack of enough time, and 300 questionnaires were accepted.

A list of 8 indicators (student characteristics, teacher characteristics, content quality, structure management, training process, software infrastructure, hardware infrastructure, university image) is extracted based on technical, human, social, and organizational factors to evaluate the effectiveness of e-learning. The results showed that the introduced scale was a valid and reliable instrument for evaluating the effectiveness of e-learning.  

The results show that student characteristics are more important while software infrastructure is considered as the second influential factor in this regard. Also, the characteristics of the instructor, the quality of the content, the management of the structure, the infrastructure of the hardware, the teaching process and the image of the university were ranked third to eighth, respectively  .

In today’s world, humankind is exposed upon a wide spectrum of diseases and tissue damages,
which some of them are untreatable with current medical approaches. The untreated damaged tissues
encompasses a widespread of destroyed parts with loss function in which natural repair mechanisms are not able
to reconstruct them. Therefore, remedy for these lesions is related to a branch of medical sciences called
regenerative medicine. One of the tools in regenerative medicine is transplantation of tissue-like structures via
tissue engineering. We searched several databases such as PubMed, Scientific Information Database (SID),
Springer, Medline, Magiran, ScienceDirect, and Sivilica, and used Google Scholar search engine to find the
articles in this issue. Different researches and clinical results show that with the help of tissue engineering,
structures similar to natural tissues for repair can be designed. These structures are made up of three parts of
scaffold, cell, and growth factors. In the construction of these structures, the design of ideal scaffold with the
desired properties and mechanical strength is important, depending on the type of material and method of its
construction. Regenerative medicine and tissue engineering are successful and necessary in repairing or replacing
damaged tissues

Diabetes mellitus is one of the most common metabolic disorders worldwide. Numerous natural compounds have been developed to treat diabetes mellitus. Royal jelly (RJ) has antioxidant and antidiabetic properties. This study was carried out to investigate the effects of RJ on antioxidant status, lipid peroxidation and liver tissue in diabetic rats.
In this experimental study, 32 adult male Wistar rats (190-200 gr) were randomly divided into 4 groups including control, royal jelly, diabetic and diabetic treated with royal jelly. Diabetes was induced by intraperitoneal injection of streptozotocin (50 mg/kg) and Royal Jelly (100 mg/kg) was gavaged for 42 days. At the end of our study, serum levels of malondialdehyde, total antioxidant capacity (TCA) and superoxide dismutase/glutathione peroxidase activity were determined spectrophotometrically, while the rat’s livers were isolated for histological study.
Consumption of RJ showed a significant decrease in malondialdehyde serum levels (P= 0.007) and a significant increase in total antioxidant capacity, superoxide dismutase (P=0.0019) and glutathione peroxidase activity in the RJ treated diabetic rats compared to diabetic rats (P= 0.003). Administration of royal jelly improved liver histological states.
RJ increases antioxidant power and prevents the occurrence of histopathological changes resulting from diabetes in rats.

Nowadays, due to the population growing and agriculture lands degradation, optimum land use and management become essential. Consequently land suitability evaluation and prediction of the production potential are important processes. The goal of the present research is the comparison of AEZ and Wageningen models in estimation of the Thermal-Radiation production that it is one of parameters in calculation of the Production Potential in FAO method for irrigated wheat. Soil morphological, physical and chemical characteristics of 10 land units of Khajeh region with 1100 ha extension located in East Azarbaijan province were selected. The soils of the study region have Aridic border to xeric moisture and mesic temperature regimes, and were classified in Aridisols orders according to keys to soil taxonomy 2014. Coefficient of correlation values between land production potential and observed yield were 0.74 and 0.72 for AEZ and Wageningen models respectively. Geometric mean error ratio (GMER) index was used for studying the model accuracy. The values of this index have been calculated for the AEZ and wageningen models 1.02 and 2.28 respectively. According to the coincidence of agreement maps of the AEZ or wageningen models and observed yield the agreement in AEZ method 52.8 % is more than of the Wageningen method 12.8%. Finally, the AEZ model is more efficient than the other because it has high precision, accuracy, overall map agreement with observed yield and low calculating process.

Prosopis farcta has antidiabetic and antioxidant properties and may be effective in preventing destructive effects of diabetes on the testes. The present study aims to analyze the effect of Prosopis farcta on fertility parameters, antioxidant status and the structure of testicular tissue in diabetic rats.
In this experimental study, 32 male adult Wistar rats (200-220 g) were divided into 4 groups including control, Prosopis farcta, diabetic and diabetic plus Prosopis farcta. Streptozotocin (55 mg/kg) was administered intraperitoneally to induce diabetes in rats. Prosopis farcta group and Prosopis farcta extract treated diabetic group received 300 mg/ml hydroalcoholic extract of Prosopis farcta intraperitoneally for 30 days. At the end of the study, the animals were weighed and dissected. Then, fertility, antioxidant and histopathology parameters of testis were analyzed.
FINDINGS: The level of total antioxidant capacity (12.4±0.5) and superoxide dismutase (1.9±0.5) in testicular tissue of diabetic rats treated with Prosopis Farcta increased significantly compared with diabetic group (7.9±0.7 and 0.6±0.18, respectively) (p=0.001), while Prosopis Farcta extract significantly decreased the level of Malondialdehyde in the diabetic group (373.9±16.6) (p=0.000). Furthermore, a significant increase in serum testosterone levels, count and motility of sperm was observed in diabetic rats treated with Prosopis Farcta (p=0.003). Moreover, Prosopis Farcta decreased testicular tissue damage caused by diabetes.
Results of the study demonstrated that hydroalcoholic extract of Prosopis farcta improves fertility parameters and testicular tissue structure in diabetic rats through increasing antioxidant activity and decreasing oxidative stress.

Diabetes is the most common endocrine disease. It has adverse effects on male reproductive function. Royal Jelly (RJ) has antioxidant and anti-diabetic effects and show protective effects against diabetes.

This study was conducted to evaluate the effect of RJ on histopathological alterations of the testicular tissue in streptozotocin (STZ)-induced diabetic rats.

In this experimental study, 28 adult Wistar rats were randomly divided into control (C), royal jelly (R), diabetic (D) and RJ-treated diabetic (D) groups. Diabetes was induced by a single intraperitoneal injection of STZ at 50 mg/kg body weight (BW). The rats from the R and D groups received daily RJ (100 mg/kg BW) for 6 wks orally. Hematoxylin-Eosin staining was used to analyze histopathological changes including: tunica albuginea thickness (TAT), seminiferous tubules diameter (STsD), Johnsen’s score, tubular differentiation index (TDI), spermiogenesis index (SPI), Sertoli cell index (SCI), meiotic index (MI), and mononuclear immune cells (MICs) in testes. The antioxidant status was examined by evaluating testicular levels of ferric reducing antioxidant power (FRAP) and catalase (CAT) activity.

Histological results of the testis from diabetic rats showed significant decrease in STsD, Johnsen’s score, TDI, SPI, SCI and MI, and significant increase in TAT and MICs, while administration of RJ significantly reverted these changes (p

RJ improved diabetes-induced impairment in testis, probably through its antioxidant property.

Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank has been shown to be useful in many applications of information retrieval, natural language processing, and data mining. Learning to rank can be described by two systems: a learning system and a ranking system. The learning system takes training data as input and constructs a ranking model. The ranking system then makes use of the learned ranking model for ranking prediction. In this paper, a new learning algorithm based on ensemble learning for learning ranking models in information retrieval is proposed. This algorithm iteratively constructs weak learners using a fraction of the training data whose weight distribution is determined based on previous weak learners. The proposed algorithm combines the weak rankers to achieve the final ranking model. This algorithm constructs a ranking model on a fraction of the training data to increase the accuracy and reduce the learning time. Experimental results based on Letor.3 benchmark dataset shows that the proposed algorithm significantly outperforms other ensemble learning algorithms.

There are several methods of soil improvement. In present study, rapid impact compaction (RIC) method is illustrated. The method is based on falling a 7 to 9 tons tamper from a height of about 1 meter on the soil. Due to the compaction of thick layer compared to the conventional static methods, speed of improvement is much faster in rapid impact compaction. In present paper, fundamentals of the method, definitions and limitations besides its characteristics and applications are illustrated. Moreover, design methods and compaction patterns besides its verification methods are investigated.