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Introduction: Cryphiops caementarius, is an endemic prawn from river ecosystems in Southern Perú and Northern Chile. In these watersheds, natural populations are threatened by multiple anthropic interventions such as mining activities and fishing pressure, but also, by increasing impacts of invasive exotic predators. Information related with predation on C. caementarius is scarce representing a major knowledge gap to ensure suitable management and conservation practices. Accordingly, the further deepening in relevant aspects such as the estimation of populations losses due to predators has been indicated as critical by relevant agencies as FAO. Objective: To conduct a complete registry and classification of C. caementarius predators, updating the knowledge for the Andean region. Methods: A thorough bibliographic review on existing information on C. caementarius' predators from Perú and Chile was carried out calculating percentage of occurrence, relative frequency of species, zoogeographic origin, trophic structure, phenotypic attributes, river zone that inhabits and life stage of incidence. The registry was complemented using semi-structured interviews from prawn's fishers in central-Northern Chile. Results: C. caementarius is predated along the entire fluvial network (estuary, potamon and rhithron) by 21 species of opportunists, carnivores, omnivores and herbivores, mostly aquatic vertebrates. In turn, these belong to 15 families and six guilds of native, exotic and cosmopolitan species. Approximately 86% predate on adult prawns, whilst, 71% on juveniles and 24% on larvae. More than 40% of the predation pressure seems to be exerted by native waterfowls and 24% by exotic fish. Conclusions: The results emphasize the relevance for conservation of native species of predators in the Andean region and the need of control measures on exotic species in a latitudinal basis. Accordingly, this review may serve as an initial decision-making tool for future conservation efforts both on prawns and native biota, but also supporting restocking actions, fisheries management plans and risk assessment for C. caementarius populations across the Andean region. [ABSTRACT FROM AUTHOR]

Automatic speech emotion recognition is an important research topic for human-computer interaction and affective computing. Over ten million people speak the Quechua language throughout South America, and one of the most known variants is the Quechua Collao one. However, this language can be considered a low resource for machine emotion recognition, creating a barrier for Quechua speakers who want to use this technology. Therefore, the contribution of this work is a 15 hours speech corpus in Quechua Collao, which is made publicly available to the research community. The corpus was created from a set of words and sentences explicitly collected for this task, divided into nine categorical emotions: happy, sad, bored, fear, sleepy, calm, excited, angry, and neutral. The annotation was performed on a 5-value discrete scale according to 3 dimensions: valence, arousal, and dominance. To demonstrate the usefulness of the corpus, we have performed speech emotion recognition using machine learning methods and neural networks., (© 2022. The Author(s).)