Recolonization of mortars by endolithic organisms on the walls of San Roque church in Campeche (Mexico): A case of tertiary bioreceptivity

San Roque church (Campeche, Mexico) was built at the end of the 17th century with a micritic limestone and lime mortar in baroque style. In 2005 the church exhibited heavy biodeterioration associated with the development of extensive dark green phototrophic-based biofilms. Several cyanobacteria belonging to the order Chroococcales and lichenized fungi (Toninia nordlandica, Lobaria quercizans, Lecanora subcarnea, Cystocoleus ebeneus) were predominant in the dark biofilm samples, as revealed by DNA-based molecular techniques. In 2009, a cleaning and restoration intervention was adopted; however, after few months, microbial recolonization started to be noticeable on the painted church walls, representing an early phototrophic-based recolonization. According to molecular analysis, scanning electron microscopy observations and digital image analysis of cross sections, new phototrophic-based colonization, composed of cyanobacteria and bryophytes, developed mainly beneath the restored mortars. The intrinsic properties of the mortars, the tropical climate of Campeche and the absence of a biocide treatment in the restoration protocol influenced the recolonization of the church façades and enhanced the overall rate of deterioration in a short-term period.

Smart Sentinel: Monitoring and Prevention System in the Smart Cities

Today, faced with the constant rise of the Smart cities around the world, there is an exponential increase of the use and deployment of information technologies in the cities. The intensive use of Information Technology (IT) in these ecosystems facilitates and improves the quality of life of citizens, but in these digital communities coexist individuals whose health is affected developing or increasing diseases such as electromagnetic hypersensitivity. In this paper we present a monitoring, detection and prevention system to help this group, through which it is reported the rates of electromagnetic radiation in certain areas, based on the information that the own Smart City gives us. This work provides a perfect platform for the generation of predictive models for detection of future states of risk for humans.