a. mohtashami

The prediction of groundwater level fluctuations is one of the most remarkable issues in water resources management, especially in arid and semiarid regions. The present study uses a numerical meshless method, named meshless local Petrov-Galerkin, to predict the groundwater level over a ten-year period. This method makes up for the shortcomings of mesh-dependent methods and increases modeling accuracy significantly. The study site is the unconfined aquifer of the Birjand plain with 190 groundwater discharge wells. The groundwater head is predicted based on two scenarios. The first scenario is defined as the discharge rate increased by 10% compared to the year before. Due to this scenario, the groundwater level in the aquifer is significantly reduced, especially in the central part (in the location of piezometer No. 8) and southwestern part (in the location of piezometer No. 5) of the aquifer, where groundwater table experiences 11.74 m and 35.80 m drawdown, respectively over a 10-year period. In that area, the high density of groundwater wells is the main reason for the depletion of the aquifer. Within the second scenario, the effect of rainfall rate is assessed by decreasing it by 20% and increasing discharge rate of groundwater wells by 5% compared to the year before. The results of this scenario show that the declines of groundwater level in the southwestern and central parts of the aquifer around 14.81 m and 5.05 m, respectively during the considered ten-year period.

The aim of this study was to design a model to nurture enthusiastic employees in the Iranian public sector.

The research method included meta-synthesis, survey and fuzzy expert system. Corpus of the study in meta-synthesis was 158 academic papers. In the survey, the statistical population was 1039 employees from West Azerbaijan province's three general directorates and in mathematical modeling, the population included 20 employees. Sampling in meta-synthesis was conducted by selecting 65 articles from among 158 papers published in prestigious Iranian and foreign English journals between years 2010 and 2016; in survey method selecting 60 subjects from among all employees and in mathematical modeling selecting 20 employees to complement the research tool. To determine the scale validity, exploratory and confirmatory factor analyses were conducted and the convergent validity was calculated via computing correlations through a 56-item questionnaire approved by experts in the spring of 2017. In order to determine internal reliability, Cronbach's alpha coefficient and retest reliability coefficient were calculated and after eliminating six incomplete questionnaires and three missing data, 281 subjects were analyzed. Findings: Results revealed that total path coefficient between Iranian-Islamic culture and psychological moods (β=0.375, P=0.001), and the indirect path coefficient between components of job conditions (β=0.125, P=0.001), personal (β=0.134, P=0.01) and organizational conditions (β=0.231, P=0.002) were positive and significant with employees' enthusiasm variable.

Since the target population, confirmed the dimensions, components and indices extracted from meta-synthesis, considering indices with higher factor weight in employees’ enthusiasm, could expand their psychological capacities.

The supply chain management is regarded as an important infrastructure in managing material ow. Cross docking is considered to be as an ecient method in supply chain management to control the inventory ow, which is essential in supply chain management. The other objectives of the cross dock are inventory reduction, increased levels of customer responsiveness and better control of the distribution operation. Since this system plays a key role in the supply chain, setting up multi objective approaches may help to solve real world issues and problems of such systems, in which many of the objectives are dierent and even con icting. This paper proposes a new multi-objective mathematical model which, unlike the previous works, considers transportation from suppliers to customers, from suppliers to other suppliers, from suppliers to cross sock, from cross dock to customers and from a customer node to other customer nodes. In this paper, three dierent types of objective functions are considered: to minimize the total time in supply chain, to minimize transportation cost, and to minimize the number of transportation times in the network. As mentioned earlier, these three objectives are in con ict with each other; and by considering three objective functions simultaneously the control of the supply chain is more appropriate. Since these three models belong to the NP-hard class, their solving time severely increases with increasing the problem dimensions. In this paper, to solve these three models, meta-heuristic algorithms have been used. The algorithms used in solving the model are Multiple Objective Particle Swarm Optimization and Non-Dominated Sorting Genetic Algorithm. The model is solved using both algorithms and computational experiments are reported.