SummaryObjectivesPatients' loyalty to a health care institution can lead to the aggregation of patients' medical history in an institution and facilitating access to records by health care providers. Considering the increase of the competition between providers, it is important to gain patients' satisfaction, which leads to their return and loyalty. Therefore, this study evaluated the effect of patients' satisfaction with service quality on their loyalty.MethodsA cross‐sectional descriptive and analytical study was carried out in academic hospitals. A sample of 260 patients admitted to these hospitals was recruited. The data gathering tool was an expert‐validated questionnaire which its reliability was confirmed by Cronbach's alpha. Data were analyzed using descriptive statistics, correlation coefficient, and multivariate regression analysis in SPSS20.ResultsThe mean score of service quality was calculated 74.23 out of 100. Among the quality dimensions, “physician visit” had the highest score with 84.01 ± 20, and the “waiting time” dimension had the lowest score with the mean score of 62.45 ± 27.53. The mean score of patients' loyalty was 67.88 ± 29.79. Satisfaction with the six dimensions of service quality: “cost of services,” “hospital environment,” “delivered services,” “access to physicians and health care institutions,” “provision of information to patients,” and “acquaintance with hospitals” were identified as the most influencing factors on loyalty.ConclusionsThe results showed that patient satisfaction with service quality affects their hospital choices and increases loyalty. In order to increase patient loyalty to academic hospitals, improving the services quality along with delivering cost‐effective cares, improving hospital environment, and providing useful information to patients are recommended.

Multi-level (ML) quantum logic can potentially reduce the number of inputs/outputs or quantum cells in a quantum circuit which is a limitation in current quantum technology. In this paper we propose theorems about ML-quantum and reversible logic circuits. New efficient implementations for some basic controlled MLquantum logic gates, such as three-qudit controlled NOT, Cycle, and Self Shift gates are proposed. We also propose lemmas about r -level quantum arrays and the number of required gates for an arbitrary n-qudit ML gate. An equivalent definition of quantum cost (QC) of binary quantum gates for ML-quantum gates is introduced and QC of controlled quantum gates is calculated.

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Mobile robots are the robots that can move through the environment and be used in many applications, including the industrial environment, planet exploration, warehousing, and daily household chores. They can be controlled by an operator, set to do some specific jobs, or work autonomously. Robot path planning is the task of an autonomous robot to move safely from one position to another. In this paper, three new objective functions are introduced in the structure of improved grey wolf optimizer (IGWO) and improved particle swarm optimization (IPSO) for the robot path planning problems. As another part of our proposed method, a reduction of laser range finder (LRF) data is performed, and the avoidance collision approach is also introduced. Robots determine the next position by using LRF data and IGWO (IPSO) algorithms in a local approach. The initial and the goal positions are predefined for each robot. Moreover, the location of static obstacles and other robots are unknown for each robot. Finally, the experimental results of the robot path planning using IGWO are compared to different algorithms. The results indicate that the proposed method performs better in determining an optimal, short, safe, and smooth path. Also, it has less power and time consumption than other methods. All the algorithms are implemented in the V-REP robot simulator.

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