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In the contemporary landscape of technology-driven industries, the integration of artificial intelligence into technology scouting is imperative for enhancing innovation and sustaining competitiveness. This research aims to forge a framework for technology scouting based on artificial intelligence, with a specific focus on technology-based companies. Employing a qualitative approach, data collection utilized the meta-synthesis method devised by Sandelowski and Barroso. This involved a systematic review of 28 articles relevant to the research goal out of a pool of 253 primary articles. The final selection of articles was based on predefined inclusion criteria. The research's validity was confirmed through adherence to criteria, team meetings, expert consultations, and an exhaustive audit for theoretical consensus, while reliability was ascertained through the Critical Evaluation Skills Programme. The framework spans five dimensions: technology scouting tools, technology life cycle, firm environment, firm's approach to the environment, and firm's absorptive capacity. The findings underscore the pivotal role of AI-based technology scouting tools, elucidate the nuanced dynamics of the technology life cycle, and reveal the multifaceted aspects of the enterprise environment. The research outlines strategic approaches for navigating the evolving technology landscape, underscoring the imperative of absorptive capacity for the effective utilization of artificial intelligence technologies. By delivering actionable insights and strategic counsel, this research serves to furnish technology-based companies with a robust underpinning for negotiating the intricate intersection of AI and technology surveillance. In doing so, it propels sustainable growth, fortifies competitive advantage, and fosters enduring innovation. [ABSTRACT FROM AUTHOR]

One of the most important issues in smart cities is identifying the factors that affect their services’ success. The purpose of this study is to provide a model for them and also to identify its indicators based on information and communication technology (ICT). In this research, data collection has been done by a desk research method and field studies, during which the factors (smart economy, smart citizens, smart governance, smart transportation, smart environment and smart living) affecting the services’ success in smart cities have been identified.. We designed and distributed a research questionnaire in order to gather data from related communities. At this stage, by fuzzy Delphi method, the indicators related to the identified factors were also identified. In the next step, by using the structural equations and Smart PLS software, the effect of factors on the main component of the research (Success of Smart City Services) was evaluated. The results show that all factors have a significant and positive impact on the services’ success of smart cities and government actions have the greatest impact on it. [ABSTRACT FROM AUTHOR]

Cornelian cherry (Cornus mas L.) is a popular and valuable small fruit. There are seedling-based orchards of cornelian cherry in Iran which are rich sources of genetic diversity for identifying superior genotypes for cultivation or improving cornelian cherry cultivars. However, little research has been conducted to evaluate the populations and identify superior cornelian cherry genotypes in Iran. In this study, characteristics of 36 superior cornelian cherry genotypes from seedling orchards in the Alamut region in Qazvin province were investigated. Fruit traits including fruit mass, fruit length, fruit diameter, fruit juice pH, soluble solids content, kernel mass, kernel length, kernel diameter and pulp/fruit ratio were measured. A large diversity was found in fruit size, shape and quality parameters of the genotypes. Fruit mass, fruit length, and fruit diameter ranged from 1.646-4.303g, 1.36-3.35cm, and 0.733-2.30cm, respectively. Fruit shape was obligated to semi-round in the genotypes. Kernel mass and pulp portion of the fruits ranged from 1.07-0.253g and 39.77-88.64%, respectively. Fruit juice pH and soluble solids content varied between 2.80-3.16 and 13.2-22.5°Brix, respectively. Based on the results, SOM2, KKP2, SOT1, KK7 and KKP3 genotypes with elongated (SOM2) to oval (KKP3) shaped fruits and weighing more than 3.50g, were introduced as superior genotypes for fresh consumption. The genotypes KKP2, KK7, SOT1, KK6 and KKP3 with the highest pulp mass and high pulp-to-fruit ratio represented suitable traits for processing and juice extraction. In sum, KKP2 and SOT1 genotypes with fruit mass over 4.0 g were the superior high-yielding genotypes. [ABSTRACT FROM AUTHOR]

The need for effective use of assets has become more important in the design of supply chain networks in today's competitive environment. Sale and leaseback (SLB) agreements are one of the appropriate tools to achieve this important goal. The proper use of these agreements increases the liquidity of assets, and provides financial resources required for other activities. However, the consideration of SLB possibility in a Closed-Loop Supply Chain (CLSC) that aims to minimize CO2 emissions as well as maximizing profit has never studied before. Therefore, this paper proposes a biobjective two-stage stochastic program for designing a CLSC network considering SLB agreements. The objective functions are: to maximize profit after tax and to minimize CO2 emissions of the supply chain. To assess the performance of the proposed model, 30 different-sized test problems are generated and solved by both LP-metric and max-min methods. Finally, sensitivity analysis is performed to assess the impact of SLB related parameters (the safety stock coefficient, the fair value of the leased asset, the interest rate implicit in the lease, and the lessee's incremental borrowing rate) on the objectives. The results show significant superiority of the proposed model over which do not consider SLB possibility. Outcomes also indicates that Lp-metric method provides better solutions for the problem. Finally, some managerial insights are suggested. [ABSTRACT FROM AUTHOR]

This research aimed to determine the most suitable time to harvest olive fruits (Olea euopeae cv. Zard) infected with olive fly larvae based on the quality and quantity of the extracted oil. The experiment factors included the fruit type at two levels (1: infected fruits, 2: healthy fruits) and the harvest time at six levels (0: the time of olive fly larvae exit, 1: one week after the fly larvae exit, 2: two weeks after the olive fly larvae exit, 3: three weeks after the olive fly larvae exit, 4: four weeks after the olive fly larvae exit and 5: five weeks after the fly larvae exit). The fresh oil of fruit was extracted and analyzed for measuring qualitative and quantitative characteristics. The results showed that the effect of fruit type was significant on the extinction coefficient at 232 and 270nm (K232 and K270). The effect of harvest times was significant on K320, oil percent (p=0.05) and acidity (p=0.05), but had no significant effect on K270 and peroxide (p=0.05). The interaction effect of fruit type and harvest time was significant only on acidity (p=0.05) and was not significant on other parameters. Based on the results, the healthy fruits had lower acidity and peroxide number and higher oil percentage than infected fruits and therefore had better quality. It can be concluded that the best time to harvest the fruit was two weeks after the larva leaves the fruit because, after that, the negative effects of olive fly larvae on the quantity and quality of fruit oil are high, while before that, quality indicators of the fruit are not affected by olive fly larvae. [ABSTRACT FROM AUTHOR]

Providing job rotation schedules among certain individuals of organizations has been the research focus in the field of job rotation. Obviously, any movement of people will cause a change in the position of others and if there are no properly defined criteria for movement, the resulting job rotation not only is not effective in the long run but also may cause serious damage to the organization. In this regard, the main purpose of this research is to find the best model developed for job rotation and solve the "job rotation scheduling problem" with respect to the factors influenced by the job. So, Health and Safety Executive (HSE) standard questionnaire was used for measuring job stress among the population of nurses in Iranian health centers (n=1221 of a 6148 population) to form databases required for the implementation of data mining. In order to make a smart model, the use of internal rules and patterns of existing data is considered and with the development of meta-heuristic models for this kind of problem, the model is solved with genetic algorithms. The current job rotation model has been developed compared to previous models because of using smart limitations resulting from the process of knowledge discovery by data mining method. In contrast with the results of the previous studies on job rotation, our results are applicable to all organizations need to have different leadership styles in order to practice corporate social responsibility(CSR) and use capabilities to identify rules that allow easy use of meta-heuristic algorithms. [ABSTRACT FROM AUTHOR]

Water deficit is one of the most important factors in reducing medicinal plants' yield. Origanum majorana L. grows in the some regions of world and it is cultivated for consumption and pharmaceutical purposes. In order to study the effects of methyl jasmonic acid (MeJA) on O. majorana L. under limited irrigation conditions, a factorial experiment was performed as a complete randomized design with three replications. Experimental factors including different limited irrigation conditions such as keeping the pots at field capacity during the experiment (control), irrigation pots in 75 % field capacity (mild limited irrigation), and irrigation plants in 50 % field capacity (moderate limited irrigation), and spraying treatments include 100 μM MeJA and control with water. At flowering stage, fresh weight, dry weight, and essential oil percentage (EO %) and yield, and essential oil composition were measured. Results indicated that moderate limited irrigation decreased plant weight and essential oil yield compared to the control. However, both mild and moderate limited irrigations increased EO % compared to the control. Foliar spray of MeJA improved growth parameters such as O. majorana L. fresh and dry weight just under mild limited irrigation conditions, while under moderate limited irrigation application of MeJA could not significantly change these parameters. Under mild limited irrigation conditions, MeJA causes significant reductions of 16.9 and 12.0 % in EO % and yield, respectively. Although limited irrigation did not have a significant effect on all of the O. majorana L. essential oil components, MeJA application changed O. majorana L. essential oil composition. With an increase in the limited irrigation level, MeJA application diminished the content of monoterpene hydrocarbons components from 20.56 to 18.21 % and increased oxygenated monoterpenes from 62.73 to 65.44 %. Results of this study revealed that MeJA could alleviate drought stress damages by stimulating oxygenated monoterpenes production and, therefore, could improve essential oil production under water stress conditions. [ABSTRACT FROM AUTHOR]