Burnt areas semantic segmentation from Sentinel data using the U-Net network trained with semi-automated annotations

The Pantanal biome is one of the most important wetlands on the planet, harboring a rich biodiversity whilst being critical in maintaining hydrological cycles and climate regulation. However, the occurrence of fires in the biome has represented a significant threat to this unique ecosystem and its multiple functions. Understanding the extent, intensity and environmental impacts caused by fires in the Pantanal, is of unique importance for the preservation of the biome's biodiversity. Remote sensing techniques have played an important role in detecting and mapping burnt areas, especially SAR (Synthetic Aperture Radar) orbital systems, that are able to collect data in regions with frequent cloud cover or during extreme fire events. In this context, the objective of this study was to evaluate the potential of the U-Net semantic segmentation network applied to SAR data in the detection of burnt areas in the Brazilian Pantanal. For this, a semi-automatic annotated dataset was generated and considered as ground truth to evaluate the result obtained by the network. Two input datasets were evaluated in the detection of burnt areas, one containing optical and SAR data whereas the other containing only SAR data. The predictions of the two datasets were consistent with the semi-automatically generated annotation, showing similar spatial distribution but presenting a greater number of burnt areas. The model using both optical and SAR data achieved IoU (Intersection of Union) of 0.69 whereas the SAR only model had 0.60. Considering the amount of available data and the complexity of burnt area detection, the predictions achieved were adequate

POTENTIAL OF MULTISPECTRAL IMAGES TAKEN BY SENSORS EMBEDDED IN UAVS FOR MONITORING THE COFFEE CROP IRRIGATION

Leaf Water Potential (LWP) is an indicator widely used to understand water relations in a coffee tree. Monitoring water potential is a challenge for remote sensing using low-cost multispectral cameras, with images taken by remotely piloted aircraft. The objective of this work was to evaluate the potential of a low-cost camera to discriminate different water treatments in the coffee tree. In addition, the accuracy of models to estimate LWP in the coffee crop was evaluated. The results showed that the NDVI (Normalized Difference Vegetation Index) vegetation index was able to discriminate 61.6 % more plots in a drought regime than the Near-InfraRed (NIR) band in the rainfall regime. For LWP, the architecture that presented the best performance in the detection of water stress was for the first flight (SMOreg algorithm using as predictor variables all bands, Red, Green, and NIR, and the NDVI vegetation index) with RMSE value of 0.1880 and RMSE% of 34.18. For the second flight (Random Tree algorithm, using as predictor variables all bands and NDVI) with RMSE (0.0520) and RMSE% (32.00) values

Retinal cells derived from patients with DRAM2-dependent CORD21 dystrophy exhibit key lysosomal enzyme deficiency and lysosomal content accumulation

\ua9 2024 The Author(s)Biallelic mutations in DRAM2 lead to an autosomal recessive cone-rod dystrophy known as CORD21, which typically presents between the third and sixth decades of life. Although DRAM2 localizes to the lysosomes of photoreceptor and retinal pigment epithelium (RPE) cells, its specific role in retinal degeneration has not been fully elucidated. In this study, we generated and characterized retinal organoids (ROs) and RPE cells from induced pluripotent stem cells (iPSCs) derived from two CORD21 patients. Our investigation revealed that CORD21-ROs and RPE cells exhibit abnormalities in lipid metabolism, defects in autophagic flux, accumulation of aberrant lysosomal content, and reduced lysosomal enzyme activity. We identified potential interactions of DRAM2 with vesicular trafficking proteins, suggesting its involvement in this cellular process. These findings collectively suggest that DRAM2 plays a crucial role in maintaining the integrity of photoreceptors and RPE cells by regulating lysosomal function, autophagy, and potentially vesicular trafficking

Beliefs and preferences regarding biological treatments for severe asthma

Background: Severe asthma is a serious condition with a significant burden on patients' morbidity, mortality, and quality of life. Some biological therapies targeting the IgE and interleukin-5 (IL5) mediated pathways are now available. Due to the lack of direct comparison studies, the choice of which medication to use varies. We aimed to explore the beliefs and practices in the use of biological therapies in severe asthma, hypothesizing that differences will occur depending on the prescribers’ specialty and experience. Methods: We conducted an online survey composed of 35 questions in English. The survey was circulated via the INterasma Scientific Network (INESNET) platform as well as through social media. Responses from allergists and pulmonologists, both those with experience of prescribing omalizumab with (OMA/IL5) and without (OMA) experience with anti-IL5 drugs, were compared. Results: Two hundred eighty-five (285) valid questionnaires from 37 countries were analyzed. Seventy-on percent (71%) of respondents prescribed biologics instead of oral glucocorticoids and believed that their side effects are inferior to those of Prednisone 5 mg daily. Agreement with ATS/ERS guidelines for identifying severe asthma patients was less than 50%. Specifically, significant differences were found comparing responses between allergists and pulmonologists (Chi-square test, p < 0.05) and between OMA/IL5 and OMA groups (p < 0.05). Conclusions: Uncertainties and inconsistencies regarding the use of biological medications have been shown. The accuracy of prescribers to correctly identify asthma severity, according to guidelines criteria, is quite poor. Although a substantial majority of prescribers believe that biological drugs are safer than low dose long-term treatment with oral steroids, and that they must be used instead of oral steroids, every effort should be made to further increase awareness. Efficacy as disease modifiers, biomarkers for selecting responsive patients, timing for outcomes evaluation, and checks need to be addressed by further research. Practices and beliefs regarding the use of asthma biologics differ between the prescriber's specialty and experience; however, the latter seems more significant in determining beliefs and behavior. Tailored educational measures are needed to ensure research results are better integrated in daily practice

DELINEAMENTO AMOSTRAL EM RESERVATÓRIOS UTILIZANDO IMAGENS LANDSAT-8/OLI: UM ESTUDO DE CASO NO RESERVATÓRIO DE NOVA AVANHANDAVA (ESTADO DE SÃO PAULO, BRASIL)

O uso do sensoriamento remoto voltado para a determinação de amostras de campo é de grande valia para estudos ambientais, uma vez que as imagens de satélite apresentam atributos capazes de avaliar a variabilidade espectral da superfície da água considerando uma área extensa. Desse modo, a abordagem deste trabalho objetiva definir um método de seleção estratificada de amostras baseada na variabilidade de imagens no espectro do visível e infravermelho oriundos do sensor Landsat-8/OLI. O método conta com a utilização de dados raster que representam o desvio padrão de uma série temporal de imagens Landsat-8/OLI e em seguida a definição automática de pontos de campo apoiada na técnica de amostragem estratificada aleatória. A escolha da imagem que deu origem a seleção dos pontos foi baseada na componente de maior variabilidade espectral por meio da técnica de Principal Componente. Como resultado foram obtidos vinte pontos representativos de um total de seis classes espectralmente semelhantes

Integração de imagem aérea de alta resolução e dados de varredura a laser na classificação de cenas urbanas para detectar regiões de via

O problema de extração automática da malha viária urbana é extremamente complexo, uma vez que em cenas urbanas as vias apresentam forte interação com os outros objetos da cena (vegetação, edificações, veículos etc.). Esse problema pode ser simplificado se regiões correspondente às vias forem previamente isoladas. Na sequência, a malha viária urbana pode ser extraída baseando-se apenas nessas regiões, reduzindo a área de busca e o esforço computacional. A classificação de imagens pode ser usada no intuito de isolar as regiões de via, mas em cenas urbanas complexas a utilização de somente dados espectrais pode não ser suficiente para separar com confiabilidade classes com comportamento espectral similar. Para contornar esse problema, é proposta a integração dos dados geométricos e radiométricos de varredura a laser com imagem aérea RGB de alta resolução numa classificação por Redes Neurais Artificiais, tendo por foco principal o isolamento de regiões de via. O benefício desta integração foi verificado usando diferentes combinações de dados de entrada na rede. Os experimentos mostraram que a combinação que integra diferentes fontes de dados permitiu separar a classe via com melhor acurácia e que problemas relacionados com as respostas espectrais similares foram minimizados

Credit Supply: Identifying Balance-Sheet Channels with Loan Applications and Granted Loans

To identify credit availability we analyze the extensive and intensive margins of lending with loan applications and all loans granted in Spain. We find that during the period analyzed both worse economic and tighter monetary conditions reduce loan granting, especially to firms or from banks with lower capital or liquidity ratios. Moreover, responding to applications for the same loan, weak banks are less likely to grant the loan. Our results suggest that firms cannot offset the resultant credit restriction by turning to other banks. Importantly the bank-lending channel is notably stronger when we account for unobserved time-varying firm heterogeneity in loan demand and quality