Farmland edge plants can support high butterfly richness. Our objective was determine if, even in farms under intensive cultivation, the diversity of plants (mostly native) in crop edges is enough to sustain a high species richness of butterfly. We characterized the vegetation on the edges of Medicago sativa farms in central Mexico and identified the species of diurnals butterflies (Rhopalocera) associated. Butterflies and plants were counted along transects at the edges of a cul-tivated field during 24 months. We found 2710 individuals of plants, belonging to 48 different species from 24 families; 1749 individuals of diurnal butterflies, belonging to 57 species from six families. Most than half of the plant species found were native flora of central Mexico and with ethnobotanical use. A similarity analysis test showed significant differences in floristic composi-tion between transects. The Canonical Correspondence Analysis between butterfly species and plant families showed three groups. Six butterfly species were migratory and four mexican en-demic species, most of them associated with a group formed by Amaranthaceae, Euphorbiaceae, Annonaceae Lamiaceae Apiaceae and Fabaceae families. The high diversity of plants in our agro-ecosystem plays an important role to sustain a high diversity of butterflies and could be useful as biological corridors.

Bladder cancer is one of the most common malignant diseases in the urinary system and a highly aggressive neoplasm. The prognosis is not favourable usually and its evolution for particular patients is very difficult to find out. In this paper we propose a dynamic mathematical model that describes the bladder tumor growth and the immune response evolution. This model is customized for a single patient, determining appropriate model parameter values via model calibration. Due to the uncertainty of the tumor evolution, using the calibrated model parameters, we predict the tumor size and the immune response evolution over the next few months assuming three different scenarios: favourable, neutral and unfavourable. In the former, the cancer disappears; in the second a 5mm tumor is expected around the middle of August 2018; in the worst scenario, a 5mm tumor is expected around the end of May 2018. The patient has been cited around June 15th, 2018, to check the tumor size, if it exists.

Maze navigation using one or more robots has become a recurring challenge in scientific literature and real life practice, with fleets having to find faster and better ways to navigate environments such as a travel hub (e.g. airports) or to evacuate a disaster zone. Many methods have been used to solve this issue, including the implementation of a variety of sensors and other signal receiving systems. Most interestingly, camera-based techniques have increasingly become more popular in this kind of applications, given their robustness and scalability. In this paper, we have implemented an end-to-end strategy to address this scenario, allowing a robot to solve a maze in an autonomous way, by using computer vision and path planning. In addition, this robot shares the generated knowledge to another by means of communication protocols, having to adapt its mechanical characteristics to be able to solve the same challenge. The paper presents experimental validation of the four components of this solution, namely camera calibration, maze mapping, path planning and robot communication. Finally, we present the integration and functionality of these methods applied in a pair of NAO robots.