Effects of photoperiod and feeding regimes on Neuropeptide Y (NPY) and Agouti-related Protein (AgRP) expression in central areas of senegalese sole, Solea senegalensis

In the present study, we have tried to expand our knowledge about the endocrine mechanisms that regulate feeding and growth in cultured fish, which could be relevant for the improvement of fish farming conditions and feeding strategies. In order to reach this goal, we have investigated some orexigenic hormones, Neuropeptide Y (NPY) and the paralogues of Agouti-related protein, (AgRP1, AgRP2) in Solea senegalensis, an important species for Mediterranean aquaculture. We focused on hormones synchronization to different feeding regimes (diurnal vs nocturnal and random feeding) and photoperiod (light-dark cycle vs constant darkness). Therefore, the achieved results could also be relevant from a chronobiological perspective. Solea senegalensis specimen were reared in two different photoperiods, i.e.LD Light-Dark conditions as well as in DD conditions (constant darkness) along with different feeding regimes (fed at ML, Med and RND times), so to determine if mRNA expression of orexigenic hormones (NPY, AgRP1 and AgRP2) are entrained by feeding time and/or photoperiod. Our results show an independence of npy mRNA expression from the feeding time and suggest an endogenous control of npy expression in telencephalon of sole, while in optice tectum, npy expression could be entrained by the light-dark cycle. Our results on Senegalese sole AgRP1 and AgRP2 showed the same pattern of expression, indicating that expression of AgRPs is related to photoperiod in optic tectum, instead to feeding time. However the involvement of AgRP1 and AgRP2 in feeding behaviour should not be discarded in sole, as further research will be carried out with specimens maintained under different fasting conditions. our results reinforce the role of the telencephalon as the main neural area involved in the neuroendocrine control of food intake in fish, where endogenous NPY rhythms have been found, while diencephalon statistical variations weren’t observed suggesting that this brain area could be less involved in the neuroendocrine control of food intake in fish than previously thought.

Quality and Aspect based Argument Generation

Natural Language Processing has always been one of the most popular topics in Artificial Intelligence. Argument-related research in NLP, such as argument detection, argument mining and argument generation, has been popular, especially in recent years. In our daily lives, we use arguments to express ourselves. The quality of arguments heavily impacts the effectiveness of our communications with others. In professional fields, such as legislation and academic areas, arguments of good quality play an even more critical role. Therefore, argument generation with good quality is a challenging research task that is also of great importance in NLP. The aim of this work is to investigate the automatic generation of arguments with good quality, according to the given topic, stance and aspect (control codes). To achieve this goal, a module based on BERT [17] which could judge an argument's quality is constructed. This module is used to assess the quality of the generated arguments. Another module based on GPT-2 [19] is implemented to generate arguments. Stances and aspects are also used as guidance when generating arguments. After combining all these models and techniques, the ranks of the generated arguments could be acquired to evaluate the final performance. This dissertation describes the architecture and experimental setup, analyzes the results of our experimentation, and discusses future directions.