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.

Age patterns are a key scale for comparing internal or external Migration between countries or over time. The observed Migration rates show strong regularities in age patterns. These regularities can be showed by mathematical functions known as multi-dimensional Migration models. Multi-exponential models are a way of smoothing age patterns, correcting missing data, and comparing Migration age patterns. There are Migration questions in the censuses in Iran and it has gained considerable understanding into the patterns of Migration and the volume of population movements in the country. But these data are age-related error, and the appropriate age pattern for immigrants cannot be plotted. The present paper studies the age and sex patterns of Migration in the country using multivariate modeling system designed by Rogers and Castro (1981). The results showed that the 7-parameter model was in accordance with the age pattern of internal Migration of Iran and the age pattern of internal Migration is similar to the standard model. Finally, the estimated pattern of Migration by single ages and sex for researchers is presented.

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.

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.