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This paper aims to explore prisoner dental health in Haryana, India.

The authors assessed the prevalence of dental caries and the treatment needs of prisoners in all 19 prisons in Haryana. The results were compared with the prison populations of other countries and the general population of Haryana.

The mean age of 1,393 subjects examined was 35.26±12.29 years. A large number of the subjects reported to be in need of dental treatment. The number of decayed teeth was found to be similar to the general population of Haryana but the number of filled teeth was quite low. The number of teeth missing and the need for tooth extraction was high.

Long‐standing prisoner dental problems indicated a need for dental treatment in prisons.

This is the first study of its kind covering all 19 prisons in Haryana, India. The results indicate that the government needs to further consider and address the oral health needs of prisoners.

This chapter aims to highlight the existing applications and future prospects of Artificial Intelligence (AI) in the tourist business. In addition, this chapter investigates the obstacles in using AI in the Indian tourist industry.

To achieve the study's aims, both primary and secondary data are used. Using secondary sources, desk research was conducted to investigate the existing uses and future prospects of AI application in the global tourism industry. In addition, qualitative interviews with 25 executives in the Indian tourist business were undertaken to study the obstacles to using AI in the Indian tourism industry.

The research found that the applications of AI in the worldwide tourist business are extensive. Nonetheless, corporations are actively using AI-based technology to improve the customer experience via chatbots, intelligent forecasting and smart, tailored travel experiences. The qualitative interviews found that the implementation of AI technology in the Indian tourist industry is hindered by budgetary restrictions, knowledge constraints and barriers relating to human resources.

The use of AI in the tourism business may significantly improve the client experience. As a consequence, the use of AI-based chatbots and intelligent travel aides is growing exponentially. The research examined the many uses of AI in the worldwide tourist industry as well as the obstacles associated with the deployment of AI in the Indian tourism industry.

The purpose of this paper is to design an electromechanical actuator which can inherently tolerate a stuck or loose failure without any need for fault detection isolation and reconfiguration.

Generalized design methodology for a thrust vector control application is adopted to reduce the design iterations during the initial stages of the design. An optimum ball screw pitch is selected to minimize the motor sizing and maximize the load acceleration.

A high redundancy electromechanical actuator for thrust vector control has lower self-inertia and higher reliability than a direct drive simplex configuration. This configuration is a feasible solution for thrust vector control application because it offers a more acceptable and graceful degradation than a complete failure.

Future work will include testing on actual hardware to study the transient disturbances caused by a fault and their effect on launch vehicle dynamics.

High redundancy electromechanical actuator concept can be extended to similar applications such as solid motor nozzle in satellite launch vehicles and primary flight control system in aircraft.

High redundancy actuators can be useful in safety critical applications involving human beings. It can also reduce the machine downtime in industrial process automation.

The jam tolerant electromechanical actuator proposed for the launch vehicle application has a unique configuration which does not require a complex fault detection isolation and reconfiguration logic in the controller. This enhances the system reliability and allows a simplex controller having a lower cost.