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Wireless sensor networks (WSN) commonly have energy consumption as a remarkable issue. Due to the popularity of Internet of Things (IoT) systems, attention has been devoted to low-power wide-area networks (LPWAN), concerning the influence of transceivers on energy utilization. For instance, the energy for a communication transceiver to send one single bit can be 1500 to 2000 times higher than the energy required to execute a single instruction. Therefore, evaluating the energy consumption of network physical layer for IoT systems is prominent for system design. This work presents a Colored Petri nets (CPN)-based framework for evaluating the energy consumption of LPWAN-based IoT systems, focusing on CPU and communication transceivers. The proposed model has been validated using a hardware platform with ARM7DMI and LoRa, and results indicate an error less than 1.4% and 0.14% for the CPU and network, respectively, and show the feasibility of the proposed model to estimate the impact of packet losses and timeout on the system performance. [ABSTRACT FROM AUTHOR]

The success of restoration projects depends on the genetic diversity of the implanted species. It is a limiting factor, often because the seed sources are immersed in highly fragmented landscapes. In this work, we compare the genetic diversity of the juveniles, and the adult trees of Schinus terebinthifolia Raddi in a native mixed-species planting, both in the restoration process and in the remaining natural vegetation Atlantic Forest Biome. Polymorphic DNA fragments using five SSR primers were used to estimate the restored population that showed a higher genetic diversity index (He) (0.553 adults and 0.505 juveniles) compared to the wild population (0.487 adults and 0.483 juveniles). The forested area was established with individuals of high genetic diversity. There is a reduced genetic diversity for juveniles, with the loss of exclusive alleles and maintenance of endogamy and coancestry in reforested populations, and we can infer that there was a low gene flow inter fragments. The effective population size in both (adults and juveniles) was lower than the value recommended for the sustainability of populations in the short and long term. The results indicated that continuous monitoring of this particular area is of absolute necessity and should use techniques that promote the connectivity of the fragments. It would allow for a more significant reduction of genetic drift and the persistence of the planted populations. [ABSTRACT FROM AUTHOR]

Hancornia speciosa is one target species for genetic diversity ethnobotanical and medicinal applications within the Brazilian Northeast Atlantic Forest biodiversity hotspot. However, information on the genetic variability of populations associated with modeling the potential distribution in the state of Sergipe has not yet been performed. Therefore, the objective of this study was to predict the potential occurrence of H. speciosa in areas in which fruits are intensively used in an extractive practice. The maximum entropy method was used to detect the distribution patterns of H. speciosa in variable environments within the referred hotspot. The diversity of four natural populations, situated in areas of extractivism, was determined by ISSR molecular markers. The species appears to occur more densely in the coastal regions of the state of Sergipe. However, data prediction occurrence indicates that the areas of natural presence have been reduced due to anthropic actions. [ABSTRACT FROM AUTHOR]