Aquaculture is a fast-growing food sector but is plagued by a plethora of bacterial pathogens that infect fish. The rearing of fish at high population densities in aquaculture facilities makes them highly susceptible to disease outbreaks, which can cause significant economic loss. Thus, immunity development in fish through vaccination against various pathogens of economically important aquaculture species has been extensively studied and has been largely accepted as a reliable method for preventing infections. Vaccination studies in aquaculture systems are strategically associated with the economically and environmentally sustainable management of aquaculture production worldwide. Historically, most licensed fish vaccines have been developed as inactivated pathogens combined with adjuvants and provided via immersion or injection. In comparison, live vaccines can simulate a whole pathogenic illness and elicit a strong immune response, making them better suited for oral or immersion-based therapy methods to control diseases. Advanced approaches in vaccine development involve targeting specific pathogenic components, including the use of recombinant genes and proteins. Vaccines produced using these techniques, some of which are currently commercially available, appear to elicit and promote higher levels of immunity than conventional fish vaccines. These technological advancements are promising for developing sustainable production processes for commercially important aquatic species. In this review, we explore the multitude of studies on fish bacterial pathogens undertaken in the last decade as well as the recent advances in vaccine development for aquaculture.

Heat Exchangers are widely used in many field for the purpose of heat from one medium to another. In heat exchanger one or more fluids are used, and which are various types based on its flow and construction. Design of heat exchanger is one of the important field, in the research due to its application. In recent decade the simulation is used in most of the engineering application. A proper simulation technique can effectively analysis the functionality and behaviour of any machine before its construction or production. In this sense the machine learning techniques are used in some simulation analysis to model the machine or engine. In this work we used a hybrid neural network for the modelling of shell and tube type heat exchanger and its heat transfer rate is predicted effectively. The computational performance of the proposed technique is compared with the conventional technique and it is proved the effectiveness of the hybrid machine learning technique.