Aquaculture production in areas with high seasonal temperature variations: Development of planning tools

Postprint (published version)

Functional EF-hands in neuronal calcium sensor GCAP2 determine its phosphorylation state and subcellular distribution in vivo, and are essential for photoreceptor cell integrity

The neuronal calcium sensor proteins GCAPs (guanylate cyclase activating proteins) switch between Ca2+-free and Ca2+-bound conformational states and confer calcium sensitivity to guanylate cyclase at retinal photoreceptor cells. They play a fundamental role in light adaptation by coupling the rate of cGMP synthesis to the intracellular concentration of calcium. Mutations in GCAPs lead to blindness. The importance of functional EF-hands in GCAP1 for photoreceptor cell integrity has been well established. Mutations in GCAP1 that diminish its Ca2+ binding affinity lead to cell damage by causing unabated cGMP synthesis and accumulation of toxic levels of free cGMP and Ca2+. We here investigate the relevance of GCAP2 functional EF-hands for photoreceptor cell integrity. By characterizing transgenic mice expressing a mutant form of GCAP2 with all EF-hands inactivated (EF(-)GCAP2), we show that GCAP2 locked in its Ca2+-free conformation leads to a rapid retinal degeneration that is not due to unabated cGMP synthesis. We unveil that when locked in its Ca2+-free conformation in vivo, GCAP2 is phosphorylated at Ser201 and results in phospho-dependent binding to the chaperone 14-3-3 and retention at the inner segment and proximal cell compartments. Accumulation of phosphorylated EF(-)GCAP2 at the inner segment results in severe toxicity. We show that in wildtype mice under physiological conditions, 50% of GCAP2 is phosphorylated correlating with the 50% of the protein being retained at the inner segment. Raising mice under constant light exposure, however, drastically increases the retention of GCAP2 in its Ca2+-free form at the inner segment. This study identifies a new mechanism governing GCAP2 subcellular distribution in vivo, closely related to disease. It also identifies a pathway by which a sustained reduction in intracellular free Ca2+ could result in photoreceptor damage, relevant for light damage and for those genetic disorders resulting in 'equivalent-light'' scenarios.

A survey on coverage path planning for robotics

Coverage Path Planning (CPP) is the task of determining a path that passes over all points of an area or volume of interest while avoiding obstacles. This task is integral to many robotic applications, such as vacuum cleaning robots, painter robots, autonomous underwater vehicles creating image mosaics, demining robots, lawn mowers, automated harvesters, window cleaners and inspection of complex structures, just to name a few. A considerable body of research has addressed the CPP problem. However, no updated surveys on CPP reflecting recent advances in the field have been presented in the past ten years. In this paper, we present a review of the most successful CPP methods, focusing on the achievements made in the past decade. Furthermore, we discuss reported field applications of the described CPP methods. This work aims to become a starting point for researchers who are initiating their endeavors in CPP. Likewise, this work aims to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful works

Reconeixement de gestos de la mà amb el sensor Kinect

El reconeixement dels gestos de la mà (HGR, Hand Gesture Recognition) és actualment un camp important de recerca degut a la varietat de situacions en les quals és necessari comunicar-se mitjançant signes, com pot ser la comunicació entre persones que utilitzen la llengua de signes i les que no. En aquest projecte es presenta un mètode de reconeixement de gestos de la mà a temps real utilitzant el sensor Kinect per Microsoft Xbox, implementat en un entorn Linux (Ubuntu) amb llenguatge de programació Python i utilitzant la llibreria de visió artifical OpenCV per a processar les dades sobre un ordinador portàtil convencional. Gràcies a la capacitat del sensor Kinect de capturar dades de profunditat d’una escena es poden determinar les posicions i trajectòries dels objectes en 3 dimensions, el que implica poder realitzar una anàlisi complerta a temps real d’una imatge o d’una seqüencia d’imatges. El procediment de reconeixement que es planteja es basa en la segmentació de la imatge per poder treballar únicament amb la mà, en la detecció dels contorns, per després obtenir l’envolupant convexa i els defectes convexos, que finalment han de servir per determinar el nombre de dits i concloure en la interpretació del gest; el resultat final és la transcripció del seu significat en una finestra que serveix d’interfície amb l’interlocutor. L’aplicació permet reconèixer els números del 0 al 5, ja que s’analitza únicament una mà, alguns gestos populars i algunes de les lletres de l’alfabet dactilològic de la llengua de signes catalana. El projecte és doncs, la porta d’entrada al camp del reconeixement de gestos i la base d’un futur sistema de reconeixement de la llengua de signes capaç de transcriure tant els signes dinàmics com l’alfabet dactilològic.