Effect of the climate change on honey bee colonies in a temperate Mediterranean zone assessed through remote hive weight monitoring system in conjunction with exhaustive colonies assessment.

Honey bee plays the leading role in the pollination of many wild plants and crops, but it currently faces serious threats. Climate change is pointed out as one of the causes of the colony collapse disorder. Understanding the response of bees to the new climate change scenario is essential to face this challenge. Especially in the most sensitive bioclimatic zones, such as the Mediterranean areas. In this work, we remotely monitored the weight of the hives with an electronic device during a flowering period in the beekeeping seasons of 2016 and 2017, marked by extreme episodes of drought and high temperatures. We assessed bee colonies at the beginning, middle and at the end of the flowering as well, considering the adult bee population, bee brood, and pollen and honey reserves. The results showed that the flowering was reduced in three weeks in 2017 in comparison to 2016. In those years weight gain was 7.67 kg and 18.92 kg, respectively. The adverse conditions affected the evolution of the populations of bees and the reserves of honey and pollen in a meaningful way, increasing food stress for bees. It also affected the pollen spectrum and commercial characteristics of honey. Our results provide objective data about the effect of climate change on bees, but it also proved the relevant role of bees in the study of changes in the environment.

Entropy improvement by the Temporal-Window method for alternating and non-alternating 3D wavelet transform over angiographies.

The three-dimensional wavelet transform (3D-WT) has been proposed for volumetric data coding, since it can provide lossless coding and top-quality reconstruction: two key features highly relevant to medical imaging applications. In this paper, we present experimental results for four new algorithms based on the Classic 3D-WT. The proposed algorithms are capable of obtaining the wavelet coefficients after the spatial and, mainly, the temporal decomposition processes, reducing most redundancies in the video sequence and getting lower entropy values than the Classic algorithm. The new algorithms are based on the Temporal-Window method for carrying out the temporal decomposition. We have conducted a set of experimental evaluations for a representative data set of a modality of intrinsically volumetric medical imaging: angiography sequences.