A neural system for deforestation monitoring on Landsat images of the Amazon Region

AbstractWe deal with the problem of automating the interpretation of satellite images of the Amazon region for deforestation monitoring. Our approach is based on a combination of image segmentation and classification techniques, the latter emplying a neural-network architecture that works on a fuzzy model of classification. The architecture implements a relaxation mechanism on top of a feedforward neural network, in order to take advantage of the interrelations among neighboring image segments. Our fuzzy, segment-based approach has numerous advantages over more traditional, pixel-based approaches employing statistical techniques. These advantages range from the possibility of treating transition and interference phenomena in the images to the ease with which complex information related to a region's geometry, texture, and contextual setting can be used. We report on a great variety of experiments on representative portions of the Amazon region, employing neural networks trained by the back-propagation algorithm. The results indicate very good overall performance, and allow us to draw some conclusions regarding the effectiveness of the various sources of information available as input to the system. In particular, it appears that simple spectral information, together with textural information on a region's entropy and correlation and simple contextual information, are effective in the classification for deforestation monitoring. It also appears that the effective incorporation of geometric information would require further investigation on possible enhancements to the system

Hydroxyapatite-filled osteoinductive and piezoelectric nanofibers for bone tissue engineering

In this study entitled “Hydroxyapatite-filled osteoinductive and piezoelectric nanofibers for bone tissue engineering”, we describe the development of novel hydroxyapatite (HAp)-filled osteoinductive piezoelectric poly(vinylidene fluoride-cotetrafluoroethylene) (PVDF-TrFE) electrospun nanofibers as a potential strategy for supporting bone repair in delayed-union and non-union osteoporotic-related fractures, for which current clinical techniques have proven to be largely inadequate and scaffold-based tissue engineering approaches hold significant promise. While the piezoelectric properties of native bone tissue have been extensively discussed in the literature, including their key role in preserving tissue homeostasis and promoting tissue repair, they have been widely neglected in the design of scaffolds for bone tissue engineering (BTE) applications. Piezoelectric scaffolds can be used not only for mimicking the native piezoelectric features of bone but also to provide a platform for applying electrical or mechanical stimuli to damaged tissue, contributing to an accelerated regeneration process. The nanofibrous scaffolds generated in this study were capable of replicating the main electrical, structural and compositional properties of bone extracellular matrix (ECM). To the best of our knowledge, this was the first time that the combination of HAp with the piezoelectric polymer PVDF-TrFE was found to induce key shifts in the chemical structure of the polymer and promote ß phase nucleation, not only enhancing the piezoelectric features of the constructs but also improving their surface properties, including their ability to support mineralization in vitro. The HAp nanoparticles also provided meaningful bone-like biological cues (osteoinduction), enhancing the osteogenic differentiation of seeded human mesenchymal stem/stromal cells (hMSCs), which was confirmed by an increased ALP activity, cellderived calcium deposition and expression of important osteogenic gene markers. Overall, our findings highlight, for the first time, the potential of combining PVDFTrFE and HAp for developing electroactive and osteoinductive nanofibrous constructs with improved piezoelectric properties, surface features and osteogenic potential capable of improving bone tissue regeneration.Peer ReviewedPostprint (published version

Anatomical characterization of the roots, leaves and culms of Guadua weberbaueri in different growing environments

There has been increasing interest in the use of bamboo for a variety of purposes. In the western Amazon region, specifically in the state of Acre, Brazil, native bamboo (Guadua weberbaueri Pilg.) grows in great abundance, which calls attention to its possible sustainable exploitation. Thus, this project aims to perform the anatomical characterization of the culms, leaves and roots of G. weberbaueri in different environments, both inside and along the border of a forest. For the analysis, samples were collected from culms, leaves and roots at the Zoobotanical Park of Federal University of Acre, and permanent slides were visualized by optical microscopy. We observed that the vascular bundles of the central leaf veins were wider in leaves from the border of the forest than in those from inside the forest. In contrast, the study of root anatomy showed differences in the diameter measurements of the xylem vessel elements, which were larger in those inside the forest than those from the border of the forest. The vascular bundles of culms did not present a difference, although a new characteristic found in this species is described