“O Mar Está para Peixes?” – an Interactive Platform for Open Source Fishery Data in Rio De Janeiro State

Despite the wide dissemination of information access, open data scarcity in fisheries science is still seen as a challenge. Thus, initiatives such as Sea Around Us and Fish Stats stand out. Particularly in developing countries, fishery data collection systems are precarious and there is a lack of national platforms to make fisheries data available. In Brazil, some states such as São Paulo and Santa Catarina have their own data repositories in web platforms, but there are limitations for dynamic queries. In addition, fisheries management based on the “Ecosystem Approach to Fisheries” (EAF) have been discussed and adopted, and environmental variables have been used as indicators to increase the robustness of fishery models. In this sense, the present work proposes a fishery data compilation platform named O mar está para peixes? (Are there fish in the sea?), which contains fishery data and fishery-related satellite remote sensing data (i.e. sea surface temperature, chlorophyll concentration) for the State of Rio de Janeiro, Brazil. The platform is divided in five sections: Fishery, Habitat, Map, Satellite and Download. These sections make data available for dynamic and  personalized consultations, with the option of downloading the data. A standard spreadsheet developed for users to submit their own data is  presented, with the goal of promoting participation and the collective  construction of the platform. This is a new step towards the development of  an EAF in Rio de Janeiro, which will potentially open the pathway for the  integration of public agencies, research institutions, fishing industry and artisanal fishermen

Measurement of the Z/gamma* + b-jet cross section in pp collisions at 7 TeV

The production of b jets in association with a Z/gamma* boson is studied using proton-proton collisions delivered by the LHC at a centre-of-mass energy of 7 TeV and recorded by the CMS detector. The inclusive cross section for Z/gamma* + b-jet production is measured in a sample corresponding to an integrated luminosity of 2.2 inverse femtobarns. The Z/gamma* + b-jet cross section with Z/gamma* to ll (where ll = ee or mu mu) for events with the invariant mass 60 < M(ll) < 120 GeV, at least one b jet at the hadron level with pT > 25 GeV and abs(eta) < 2.1, and a separation between the leptons and the jets of Delta R > 0.5 is found to be 5.84 +/- 0.08 (stat.) +/- 0.72 (syst.) +(0.25)/-(0.55) (theory) pb. The kinematic properties of the events are also studied and found to be in agreement with the predictions made by the MadGraph event generator with the parton shower and the hadronisation performed by PYTHIA.Comment: Submitted to the Journal of High Energy Physic

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Comparação de técnicas de eliminação do efeito striping para imagens CCD CBERS-2B

The striping effect is a common type of noise presented in some remote sensing systems. In most of times, it is caused by poor relative calibration between detectors. Striping not only affects the quality and image interpretation but also compromise image processing. Some proposals have sought to correct this kind of effect. Among them we can mention the digital filters based on statistical operations, and filters based on Fourier transform. This study compared four filters, been tree statistical and one based on Fourier transform, named: the median filter, the multilevel median filter, the moment matching filter, and the one based on Fourier transform. Each filter was applied to all CCD sensor spectral bands from CBERS-2B (China Brazil Earth Resource Satellite). A visual interpretation was made in order to compare the four filter tested. Results showed that each band had a specific filter that better corrects their striping effect. The main problem in this case of noise correction was finding the best compromise between noise elimination and spatial resolution degradation, which creates the blurring effect. Filters have also shown not to vary drastically image mean and standard deviation which leads to just a small changing on image histogram.Pages: 2661-266

Realce de imagens CCD CBERS–2B com filtros multiescala ótimos ponderados

A feature of images generated by CCD CBERS-2B is the blurred appearance and also they show a very intense noise stripes in almost all bands, making it difficult to obtain information and to analyze the content present in these images. Enhancement strategies using traditional high-pass filtering not only enhance the features, but also the noise present in images. In this study we sought to improve these images initially decreasing noise stripes using the Fourier transform filter and the median and then highlighting the features using high-pass filters and low-pass as weights from a multiscale decomposition. To automate the process the optimum enhancement is obtained as a linear combination of elements of the set of weights defined by the outputs of the wavelet transform using minimum squares. The method is compared with the method of Richardson-Lucy, showing that it is possible to enhance with a quality equivalent and even superior because it takes a smaller amplification of noise in the image.Pages: 2561-256

Ajuste de bandas de modelos empíricos de estimativa de clorofila aplicados à região da planície de inundação do Lago Grande Curuai - PA

Empirical Models to estimate chlorophyll-a concentrations are among the most used in the remote sensing community. Historically, those models were applied to ocean monitoring, but in the last decade they were tested for Case II water types studies. In particular, in tropical water bodies characterized by highly complex mixture of optically active components. This complexity, based on high concentration of colored dissolved Organic Matter (CDOM), Total of Suspended Sediments (TSS) and Chlorophyll- (Chlo-a) that varies independently, one from each other, makes it necessary the search for a set of spectral bands able to improve the accuracy of chlorophyll estimates. This work uses a computational search method to find the best band set, for 295 samples distributed in 4 periods in a hydrological cycle. The samples are from the Curuai floodplain located in the Pará State in the Amazon Region. Results show good agreement to literature, but also shows some discrepancies, mostly because of tropical waters complexity. The new bands show better adjustments compared to standard bands intervals, found in literature. Models of Two and three band are adequate only for two periods with high degree of confidence. A discussion about the behavior of each period, and its empirical model best fit is also made.Pages: 8924-893

Retrieving Total and Inorganic Suspended Sediments in Amazon Floodplain Lakes: A Multisensor Approach

Remote sensing imagery are fundamental to increasing the knowledge about sediment dynamics in the middle-lower Amazon floodplains. Moreover, they can help to understand both how climate change and how land use and land cover changes impact the sediment exchange between the Amazon River and floodplain lakes in this important and complex ecosystem. This study investigates the suitability of Landsat-8 and Sentinel-2 spectral characteristics in retrieving total (TSS) and inorganic (TSI) suspended sediments on a set of Amazon floodplain lakes in the middle-lower Amazon basin using in situ Remote Sensing Reflectance (Rrs) measurements to simulate Landsat 8/OLI (Operational Land Imager) and Sentinel 2/MSI (Multispectral Instrument) bands and to calibrate/validate several TSS and TSI empirical algorithms. The calibration was based on the Monte Carlo Simulation carried out for the following datasets: (1) All-Dataset, consisting of all the data acquired during four field campaigns at five lakes spread over the lower Amazon floodplain (n = 94); (2) Campaign-Dataset including samples acquired in a specific hydrograph phase (season) in all lakes. As sample size varied from one season to the other, n varied from 18 to 31; (3) Lake-Dataset including samples acquired in all seasons at a given lake with n also varying from 17 to 67 for each lake. The calibrated models were, then, applied to OLI and MSI scenes acquired in August 2017. The performance of three atmospheric correction algorithms was also assessed for both OLI (6S, ACOLITE, and L8SR) and MSI (6S, ACOLITE, and Sen2Cor) images. The impact of glint correction on atmosphere-corrected image performance was assessed against in situ glint-corrected Rrs measurements. After glint correction, the L8SR and 6S atmospheric correction performed better with the OLI and MSI sensors, respectively (Mean Absolute Percentage Error (MAPE) = 16.68% and 14.38%) considering the entire set of bands. However, for a given single band, different methods have different performances. The validated TSI and TSS satellite estimates showed that both in situ TSI and TSS algorithms provided reliable estimates, having the best results for the green OLI band (561 nm) and MSI red-edge band (705 nm) (MAPE &lt; 21%). Moreover, the findings indicate that the OLI and MSI models provided similar errors, which support the use of both sensors as a virtual constellation for the TSS and TSI estimate over an Amazon floodplain. These results demonstrate the applicability of the calibration/validation techniques developed for the empirical modeling of suspended sediments in lower Amazon floodplain lakes using medium-resolution sensors