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.

Progressive collapse studies generally assess the PERFORMANCE of the structure under gravity and blast loads, while earthquakes may also lead to the progressive collapse of a damaged structure. In this study, the progressive collapse response of concentrically braced dual systems with steel moment-resisting frames was assessed under seismic loads through pushover analysis using triangular and uniform lateral load patterns. Two different bracing types (X and inverted V braces) were considered, and their PERFORMANCEs were compared under different lateral load patterns using the nonlinear static alternate path method recommended in the Unified Facilities Criteria (UFC) guideline. Eventually, the seismic progressive collapse resistance of MODELs was compared to their progressive collapse response under gravity loads. These studies showed that MODELs under the seismic progressive collapse loads satisfied UFC acceptance criteria and limited rehabilitation objective. The structures had better PERFORMANCE under seismic progressive collapse than MODELs under gravity loads because of more resistance, ductility, suitable load redistribution, and more structural elements that participated in load redistribution. Furthermore, despite studies on progressive collapse under gravity loads, the dual system with X braces showed better progressive collapse PERFORMANCE (more resistance, residual reserve strength ratio and ductility) under seismic loads than the MODEL with inverted V braces.

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.

Face recognition from digital images is used for surveillance and authentication in cities, organizations, and personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors and one or more servers to process data. All sensor data from initial methods was sent to the central server for processing, raising concerns about sensitive data disclosure. The main concern was that all data from all sectors that could contain confidential information was placed in a central server. Federated learning can solve this problem by using several local MODEL training servers for each region and a central aggregation server to form a global MODEL in IoT networks. This article presents a novel approach to optimize data transfer and convergence time in federated learning for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time and MODEL accuracy in a federated learning environment. The results demonstrate the effectiveness of the proposed approach in reducing data transfer and convergence time, leading to improved PERFORMANCE in face recognition accuracy. This research provides insights for researchers and practitioners to enhance the efficiency of federated learning in real-world applications.

Introduction: Teeth loss and its consequences, such as mental discomfort, most often negatively affects one's health and well-being. Dental implants were introduced in an attempt to raise patients' satisfaction and improve health and quality of life in all dimensions. Hence, this study was performed to check the impact of implantation on the oral health indices in patients who were candidates for implant treatment in Isfahan city. Materials & Methods: In this analytical cross-sectional study, the lifestyle quality of 73 patients who were referred to Isfahan’, s Islamic Azad Dental University (Khorasgan) and its affiliated private centers, was assessed using the OIDP index before and after their implant treatment between 2019 and 2020. Also, data analysis was done using Independent ttest, Paired t-test and analysis of variance ANOVA test (α,= 0. 05). Results: In the current study, the most common problem and with the most effect on oral satisfaction quality were teeth lost and extractions, respectively. Majorly, the effects were evident on the eating habits (83. 6%), satisfaction of communication with others (68. 5%) and quality of smile (64. 4%). In the questionnaire, an attenuated score of OIDP was recorded, before the implant treatment compared to that of post-treatment, which was statistically meaningful (p value < 0. 05). Conclusion: According to the current study data, we can conclude that implant treatment can have a positive effect on the patients' lifestyle quality.