Considering the prevalence of poetry in the Iranian culture, the present paper is of the belief that poetry is interwoven into Iranians’ poetic instincts and ethnic spirits, and that architectural poetics and inspirational qualities correspond with parts of sublime human desires of a people long associated with poetics. This study, therefore, reflects on the nature of ‘ poetics’ and its aspects in areas such as philosophy and literature, where poetics enjoys a clear definition, and then moves on to investigate ‘ architectural poetry’ in the related literature. It finds ‘ architectural poetics’ one of the essential sublime needs, a quality which arises from ‘ external affordances’ on one hand, and ‘ internal competence’ on the other. This ‘ internal competence’ is the individual’ s ability resonate the poetic potential of space, and the ‘ external affordance’ is the unveiling of the spirit of ‘ collective imagination’ in the visible. Imaginations which are archetypes of human life, timeless patterns dividable to ‘ embodiment imaginations’ , ‘ nature imaginations’ and ‘ time and timeliness imaginations’ . Incorporations of these imaginations in poetic works of architecture reify architectural poetics. Poetic works of architecture facilitate the unveiling of imaginations in incremental or reductive processes through which the visible is organised around the collective soul.

Despite the international community's best efforts the HIV pandemic countries unabated. In 2006, more than 39 million people were living with HIV worldwide. Over four million people became newly infected with HIV and an estimated 2.8 million lost their lives due to AIDS. On average, people require life-saving antiretroviral treatment (ARVs) 7-10 years after becoming infected. While there has been recent progress in increasing access to treatment and prevention programs, HIV continues to outplace the global response with at least 80% of those in clinical need of ARVs worldwide not receiving them. Further, while decline in national HIV prevalence has occurred in, for example, some sub-saharan African countries, these trends are not strong or widespread enough to have a major impact on the epidemics.

Introduction: Today modern teaching and learning approaches in medical education have received considerable attention. This paper aims to introduce WebQUEST as a new method of inquiry-based learning through the use of Internet. Also its application in medical sciences education in general, and especially nursing education is explained.Methods: To find articles related to the WebQUEST topic, the popular databases including PubMed, Google Scholar, Science Direct, Nursing Consult, CINAHL, Web of Knowledge were searched using WebQUEST related keywords. Very few medical articles were found, and there was no research article published in Iran.Results: WebQUEST is a new method of student-centered, inquiry-based learning which uses computer technology to engage and motivate students individually or collaboratively in exploring, analyzing, and synthesizing data to construct a new understanding or meaning. WebQUESTs, as a student-centered activity, enhance and facilitate higher order cognitive skills, including analysis, synthesis, evaluation and judgment, critical thinking. They also cultivate students’ exploratory and problem solving mentality.Based on constructivist learning theory and inquiry learning, WebQUESTs involve learners in collaborative learning process and group projects. There is a strong link between WebQUESTs and multi-media techniques which provide significant opportunity for utilizing internet resources in teaching and learning experiences.Conclusion: It seems the concept of WebQUEST is still less known both general and higher education, and particularly in medical education in Iran. Introducing this method in medical education which is based on new approaches of teaching and learning processes can provide a different view and encourage students to learn more effectively, deeply, and indelibly.

According to most of mystics, the first stage in the mystical conduct is the man's desire to return to his homeland. This desire and willpower to return to origin (Everything returns to its origin) is flowing, not only in humans, but also in all substances.The faces of particulars are set towards the universals nightingalesPlay game of love with the rose. (Mathnavi, 1.767).That which is of the sea is going to the sea: it is going to the place, Whence it came. (Mathnavi, 1.771).From the mountain the swift-rushing torrent, and from our body the soul, Whose motion is inspired by love. (Mathnavi, 1.772).Molavi also from the very beginning of his verses in Mathnavi(Ney Name) starts his speech by inviting people to listening to the sufferings of Ney for being abandoned from Neystan. Since all the researchers believe that all Mathnavi has been summarized in the eighteen verses of Ney Name, Maulana's Mathnavi is the story of this desire and many of the tales interpreted by Maulana, aim to inflame the fire of desire in seeker and mystic traveler's heart.This paper aims at investigating the" QUEST" subject from Maulana's point of view. Maulana's special belief in Mathnavi is discussed after some Sufi masters and ideas introduce. The manner of researching in this essay is mainly rational analysis and library method.Since Mathnavi has been composed full of emotions, mystic singing and dancing, mystical points have been interpreted and scattered among his stories. So, to find out Molana's point of view in each of them, one cannot help searching all six volumes of Mathnavi in great detail and care. This research is an effort to collect Molana's viewpoints regarding QUEST in logical and systematic method to leave no need for researchers of Mathnavi's mystical ideas to go through all six volumes of Mathnavi for this topic.

Introduction: The sugar industry usually gathers huge amounts of information during normal production operations, which is rarely used to study the relative importance of both management and environment on sugarcane yield performance. Yield prediction is a very significant problem of agricultural organizations. Each agronomist wants to know how much yield to expect as soon as possible. The aim of this study was to determine the performance of C5. 0 and QUEST algorithms to predict the yield of sugarcane production in Amir-Kabir agro-industry Company of Khuzestan province, Iran. However, the working method described in this paper is applicable to other geographical areas and other kinds of crops. Materials and Methods: The data for the study were collected from Amir-Kabir agro-industry Company. The data is obtained from 2012 to 2016 years. The study area is located in Khuzestan Province which is a major agricultural region in Iran. The geographical location of the study area is between latitudes 31 15′ to 31 40′ north and longitudes 48 12′ to 48 30′ east. It covers an area of about 12000 ha. The average elevation of the study area is 8m above sea level. Mean annual rainfall within the study area is 147. 1mm, the mean annual temperature is approximately 25 C and the mean soil temperature at 50cm depth is 21. 2 C. The used data were obtained from a survey with 15 variables carried out on 1201 sugarcane farms. Variables used in the study of data mining can be divided into two categories: target variable and predictor variables. The variable of yield was used as the target variable (dependent) and other variables as predictor variables (independent). In two models, the input data included crop cultivar, month of harvest, chemical fertilizer (Nitrogen), chemical fertilizer (Phosphate), age (plant or ratoon), times irrigation, ratio of surface spraying, soil texture, soil electrical conductivity (EC), water consumption per hectare, drain, farm management, crop duration, area, and yield-category. The study was included in 1201 farms. The necessary data were collected and pre-processing was performed. We propose to analyze different decision tree methods (C5. 0 and QUEST). Results and Discussion: First, decision tree methods were analyzed for variables. Then, according to C5. 0 method (error rate 0. 2319 for the training set and 0. 3306 for test set) performed slightly better than another method in predicting yield. Crop cultivar is found that an important variable for the yield prediction. 24 rules were found in this study, C4. 5 showed a better degree of separation. The measured prediction rate of C5. 0 was correct: 76. 81% and wrong: 23. 19% in the training data, and correct: 66. 94% and wrong: 33. 06% in the test data. The prediction rate of QUEST was correct: 68. 25% and wrong: 31. 75% in the training data, and correct: 70. 83% and wrong: 29. 17% in the test data. Using the training data comparison between the model types showed that the C5. 0 model produces a more accurate prediction model and was, therefore, the model to use. Using the testing data in comparison with the model types showed that the QUEST model produced a more accurate prediction model. The results of our assessment showed that C5. 0 and QUEST algorithms were capable to produce rules for sugarcane yield. Therefore, our proposed methods as an expert and intelligent system had an impressive impact on sugarcane yield prediction. Conclusions: In today's conditions, agricultural enterprises are capable of generating and collect large amounts of data. Growth of data size requires an automated method to extract necessary data. By applying data mining technique it is possible to extract useful knowledge and trends. Knowledge gained in this manner may be applied to increase work efficiency and improve decision making quality. Data mining techniques are directed towards finding those schemes of work in data which are valuable and interesting for crop management. In this research, decision tree algorithms (C5. 0 and QUEST) were used. This classification algorithm was selected because it has the potential to yield good results in prediction and classification applications. This study was performed to present a model-based data mining to predict sugarcane yield in 2012-2016. The 24 classification rules generated from the C5. 0 decision tree algorithm have great practical value in agricultural applications. The results showed the QUEST and C5. 0 decision tree algorithms produced the best prediction accuracy. Sensitivity analysis results indicated that crop cultivar was the most important variables. It was observed that efficient technique can be developed and analyzed using the appropriate data, which was collected from Khuzestan province to solve complex agricultural problems using data mining techniques (decision tree). The decision tree has been found useful in classification and prediction modeling due to the fact that it can capability to accurately discover hidden relationships between variables, it is capable of removing insignificant attributes within a dataset.

Endometriosis has baffled us for almost a century. Despite important advances, there is a constant struggle to confidently answer many fundamental QUESTions regarding this enigmatic disease. Lack of a widely accepted classification system that accurately describes the extent and severity of the disease and takes into account various phenotypes-in particular deep infiltrative disease- is amongst factors that have hindered research in the field. Furthermore, comparison of surgical outcomes and complication rates requires a tool that accurately describes surgical complexity.