Nomadic regions of Iran with their unique cultural and natural attractions are considered as one of the most important options for the development of ecotourism in the country. However, the framework and factors of nomadic tourism development have been less considered in previous studies. Accordingly, the present study aims to provide a model for the development of nomadic tourism by using the structural modeling-interpretation approach. For this purpose, the required data were collected and analyzed from the Shahsavan nomadic areas in northwestern Iran with a qualitative-quantitative research approach. For this purpose, using snowball sampling and through semi-structured interviews with 19 tourism experts consisting of university professors, tourism experts and nomadic community, the dimensions and factors affecting the development of nomadic tourism were identified and categorized. In the next step, using interpretive structural modeling (ISM), the relationships between the dimensions were determined and analyzed in an integrated way, then using MICMAC analysis, independent, dependent, effective and two key aspects in the development of nomadic tourism were identified. The results showed that empowerment of nomadic community as the key two-way variable is one of the most important drivers of nomadic tourism development and its strengthening and development should be a priority in policy and planning for nomadic tourism development. On the other hand, social capital, government activism, structural-institutional factors were identified as strategic variables affecting the development of nomadic tourism.

Plant development can be defined as a programmed qualitative change in plant form, which leads plant to maturity, and researchers call it as phasic development or phenology. Recognizing the timing of occurring each development stage is necessary for managing system in order to yield increment. The timing of occurring development stages depend on climate, genotype specifications and sowing date then determination of these times in different regions is difficult and it is only possible through the using of crop simulation models which can predict the timing of occurrence each development stage by integrating effective factors. The model was constructed based on linear equation of plant temperature response. In order to model evaluation two experiments were carried out in agricultural and natural resources research center of Khuzistan in 2003-2004 and 2004-2005 cropping years. Wheat development stages were determined based on Kirby and Appleyard’s scale by stereoscopic microscope and required GDD for each development stage as well. The constructed model was calibrated and run for simulation. Comparison of simulated and observed data showed that the model can strongly predict wheat development stages.

Today, one of the most widely used natural language representation methods is meaning representation for text processing in different systems. Meaning representation methods have had many applications in the field of natural language processing in recent years, including automatic text summarization systems and question and answer systems, etc. Many text expressions may be different in terms of grammatical structure, but they are the same in terms of meaning, so how to apply a single and uniform meaning to them is one of the challenges of text processing. The main goal of this paper is to design an Integrated Semantic Representation (ISR) model for natural language. The proposed model, while maintaining its simplicity in annotation and understanding, does not depend on specific natural language features or on syntactic and lexical structure. In this regard, several examples in both English and Persian language, which have different in terms of written and grammatical structure, are presented in this paper. Moreover, by using the proposed model, the same representation is provided for texts with the same meaning and different grammatical structure. The proposed model is designed in graph and list format is recommended to annotate its corpuses. One of the main features of this model is that it can represent semantic relations at both sentence-level and document-level and is able to represent complex and important linguistic phenomena such as aspect, tense, and quantification. The simplicity of the proposed model helps to avoid making language processing slow or complicated in various applications, and the preparation of structures based on this model for different natural languages will not be too complicated, so that it can be used both for natural languages with low resources and for those with various resources. Further, features of the proposed model are compared with one of the most important related works.

Purpose: Resilience in start-ups is a challenging issue that has caught the attention of policymakers and business owners. The present study is an attempt to provide a model for designing the resilience model of start-up businesses as a path to the future of start-up businesses. Method: This research is practical in terms of purpose and from the perspective of data collection is a qualitative research that has been done by content analysis method. The data collection method is semi-structured interview. Interviews with participants continued until they reached the theoretical saturation point, which was achieved by conducting 15 interviews. Participants were selected by snowball and purposeful method and data analysis was done through three coding steps (open, axial, selective) with MAXQDA2020 software. Findings: Based on the research results, the components of "cognitive resilience, financial resilience, adaptive resilience" as well as the effective organizational factors of "precedent, drivers and boys and resilience consequences" were identified. In this research, foresight and futures studies were identified as the drivers of resilience of start-up businesses. Conclusion: Resilience enables businesses to respond effectively to the dynamic conditions of their environment and maximize their competencies through strategic foresight and as a result gain more value than their competitors in the field of business. In this regard, the integration of foresight in the process of business resilience can be suggested as a facilitator of drivers.

Background and Aim: Job enrichment is a method that has been used to increase employee satisfaction and work motivation. The Hackman and Oldham job characteristics model (1976) has served as the foundation for many job enrichment efforts. In particular, a considerable amount of research has been devoted to the study of the job characteristics-job satisfaction relations. Te purpose of this study was to statistically determine the relation between job characteristics and job satisfaction among employees of hospitals affiliated to Tehran University of Medical Sciences (TUMS) in 2007. Materials and Methods: This study was a cross-sectional one, including 6 TUMS-affiliated hospitals-Emam, Shariati, Baharlo, Ziaeian, Madaen and Azadi. The sample size was 400, consisting of 200 administrative employees (50%), 151 nurses (38%) and 49 physicians (12%). The random sampling and stratified proportional sampling methods were used to select the hospitals and interviewees, respectively. Two questionnaires were developed and used to identify job characteristics and job satisfaction: 1) job diagnostics surveys (JDS) and 2) Hertzberg's job satisfaction questionnaire. The reliability of the questionnaires was ascertained by test-retest using the Pearson correlation coefficient (r = 0.88). Linear-by-linear association and ordinal logistics regression analysis were used for analyzing the data gathered.Results:The relations between the Motivational Potential Score (MPS) and job characteristics (except for feedback) with job satisfaction were statistically significant (p<0.05). Task identity was the most effective determinant of job satisfaction. Conclusion: It appears that all the job characteristics (except feedback) are important determinants of job satisfaction of the hospital employees. Although the work environment is in need of restructuring, it is important to note, from a positive perspective, that the job characteristics discussed in this study are readily amenable to change job satisfaction at the organizational level.

Regional inequality as one of the existing forms of inequality is one of the issues in the system of opportunity and its presence / absence and intensity / weakness has an important effect on the order and cohesion of society at different levels and dimensions. This is a serious problem, especially in developing countries. Due to the importance of this issue, this study seeks to identify the factors affecting regional inequality in Iran. The present study is a descriptive-exploratory study and the statistical population of the study consists of experts familiar with the issue of inequality and development of regions in Iran. Snowball, 10 of them were selected as a statistical sample of the study. Also, Content analysis, structural-interpretive modeling (ISM) and MICMAC analysis were also used to analyze the data. The results showed that out of 47 initially identified factors, 14 factors, including factors of poor planning, decisions of managers and planners and poor access to facilities and equipment, in calculating content validity, CVR coefficient above 0. 75 and were recognized as the final factors of regional inequality. Also, the leveling of factors showed that the relevant factors can be classified into six levels. The factors of unique resources and capabilities were at the lowest level with 29% subscription and the factors of government centralism and inefficiency were at the highest level with 90% and 91% subscription. Their classification also showed that the factors of manpower constraint (with influence 10 and degree of dependence 5), lack of financial and investment resources (with influence 8 and degree of dependence 7) and lack of attention to research (with influence 13 and the degree of dependence 5) are the key factors of regional inequality and have a great impact on inequality.

Background & Aims: Different scoring systems are used in order to assess the functional quality of intensive care units (ICU) and to predict the required costs and facilities of intensive cares. Variety of scoring systems has been explained that each has advantages and disadvantages. In this study Simplified Acute Physiology Score-III (SAPS-III) and Mortality Probability model-III (MPM-III) were compared. Materials & Methods: The current cross-sectional study was conducted on 240 non-traumatic patients admitted at ICU of Al-Zahra Hospital in 2016-17. Patients' information including demographics, mean of systolic, diastolic and arterial pressure, pulse rate, respiratory rate, temperature, Glasgow Coma Scale(GCS), WBC, hematocrit, bilirubin, creatinine, arterial blood gas, and the presence of underlying diseases was gathered from the records for measurement of MPM-III and SAPS-III scores and then they were compared. Results: This study was conducted on 240 non-traumatic patients. Discrimination of MPM-III in cutoff point of 0. 17 was 0. 83(P<0. 001; 95%CI: 0. 765-0. 898), sensitivity and specificity of this test in prediction of non-traumatic mortality was 82% and 73%, respectively. Discrimination of SAPS-III in cut-off of 48. 5 was 0. 78(P<0. 001; 95%CI: 0. 72-0. 84), while its sensitivity and specificity was 83% and 70%, respectively. Duration of ICU hospitalization (P=0. 028 and 0. 002) and duration of intubation (P=0. 001 and <0. 001) had direct association with mortality based on both scoring systems while total duration of hospitalization was only significant in SAPSIII (P=0. 002). Conclusion: Comparison of SAPS-III and MPM-III in non-traumatic patients presented a higher discrimination ability for MPM-III. In addition, findings showed that mortality in MPM-III was in association with duration of ICU admission and intubation while for SAPS-III, in addition to previous factors, total duration of hospitalization was associated as well.