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394 results for “Amazonas”
Figure 9. - Type locality of Palaemonyuna sp. n. Lago Tupé beach, lower Rio Negro tributary, Manaus, Amazonas, Brazil (003°02'42"S, 060°15'10"W).
Figure 9. - Type locality of Palaemonyuna sp. n. Lago Tupé beach, lower Rio Negro tributary, Manaus, Amazonas, Brazil (003°02'42"S, 060°15'10"W).
Figure 2. - Bayesian (GTR+Γ+I and HKY+Γ models) and maximum likelihood 50% majority-rule consensus tree. Numbers in the nodes represent posterior probabilities (GTR+Γ+I and HKY+Γ, respectively), and bootstrap value for maximum likelihood and parsimony analyses, respectively. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas. MYBP–million years before present.
Figure 2. - Bayesian (GTR+Γ+I and HKY+Γ models) and maximum likelihood 50% majority-rule consensus tree. Numbers in the nodes represent posterior probabilities (GTR+Γ+I and HKY+Γ, respectively), and bootstrap value for maximum likelihood and parsimony analyses, respectively. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas. MYBP–million years before present.
Figure 1. - Sample sites of Palaemoncarteri, Palaemonivonicus and Palaemonyuna sp. n. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas; AC-Acre; AM-Amazonas; AP-Amapá; MS-Mato Grosso do Sul; MT-Mato Grosso; PA-Pará and RO-Rondônia.
Figure 1. - Sample sites of Palaemoncarteri, Palaemonivonicus and Palaemonyuna sp. n. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas; AC-Acre; AM-Amazonas; AP-Amapá; MS-Mato Grosso do Sul; MT-Mato Grosso; PA-Pará and RO-Rondônia.
A FRAGILIDADE DO SISTEMA DE SEGURANÇA NAS INSTITUIÇÕES DE ENSINO SUPERIOR NO ESTADO DO AMAZONAS.
<p>Trata-se de um artigo científico que estuda o sistema de segurança implantado nas universidades públicas e privadas na cidade de Manaus, capital do Estado do Amazonas. Tem por objetivo demonstrar a dificuldade em estabelecer políticas de segurança e mecanismo adequados para o enfrentamento dos atos de violência na cidade com foco no ambiente acadêmico, e identificar melhorias necessárias para evitar situações comprometedoras a instituição, aos prestadores de serviço, ao corpo docente e discente. Entre os temas abordados, incluem-se: o crescente índice de atos de violência na cidade, a análise da prestação do serviço de segurança privada, propostas e recomendações das universidades para a melhoria da segurança interna do campus e casos de sucesso aplicáveis a realidade do Amazonas. A metodologia empregada foram pesquisas bibliográficas, baseadas em outros artigos publicados e dados disponibilizados em bancos de informações oficiais da União e do Estado, a fim de fomentar a elaboração deste referido estudo. Os resultados esperados incluem a conscientização da problemática pelos leitores, apresentação de soluções tecnológica que foram implantadas em outras instituições de ensino superior em território nacional, para que de forma indicativa, possa-se expor a integração de medidas de monitoramento e prevenção, segurança física e o uso da inteligência artificial para estes fins.</p>
Burned areas dataset for the enclaves of grasslands and savannah of the Mapinguari National Park (Amazonas, Brazil)
<p><span>The present dataset includes annual mapping of fire scars for the enclaves of grasslands and savannah of the Mapinguari National Park (Amazonas, Brazil), at 30-meter spatial resolution, for the period 2000-2023. The enclave areas occupy a total of 241,000 hectares.</span></p> <p><span>The detection of burned areas was carried out using Burned Area Mapping (BAMS) algorithm (Bastarrika et al, 2014), followed by the performance of visual supervision processes and the use of active fire products to optimize the detection date of each fire event. The algorithm is applied to the Surface Reflectance series of Landsat (TM, ETM+, OLI and OLI-2) – Collection II, accessed using Google Earth Engine (Gorelick et al, 2017). Data from active fire products MCD14DL V006, VIIRS-NPP, VIIRS-NOA20 and GOES16, as well as burned area data from product MCD64A1 v006, were used to optimize the detection date of each fire scar.</span></p> <p><span>_________________________________________________________________________________________________________</span></p> <p><span>July 08, 2023 – The version 1.0 includes the period 2000-2023, with a total of 356,688.5 hectares of fire affected areas, distributed across 453 fire scars.</span></p> <p><span>_________________________________________________________________________________________________________</span></p> <p><span>The files available include: </span></p> <p><span>i) “fire_scars_dataset.rar”: annual burned areas vector files, in shapefile format (*.shp), projected at WGS84 UTM 20S. Each observation is an individual fire scar, with his attribute table indicating:</span></p> <p><span>- ID: Identification number for each;</span></p> <p><span>- area_ha - area of each fire scar, calculated in hectares.</span></p> <p><span>- date - detection date of the fire scar</span></p> <p><span>- date_preci - precision flag of the fire detection date:</span></p> <p><span>0 - fire date detected using only Landsat data</span></p> <p><span>1 - fire date optimized based on active fires dataset (MCD14DL V006; VIIRS-NPP; VIIRS-NOA20; or GOES16)</span></p> <p><span>ii) “enclaves_Mapinguari_National_Park.rar”: vector file of study area location, in shapefile format (*.shp), projected at WGS84 UTM 20S. Includes 8 enclaves of grasslands and savannah situated inside Mapinguari National Park.</span></p> <p><span>iii) “dataset_description.pdf”: description of the dataset.</span></p> <p><span>_________________________________________________________________________________________________________</span></p> <p><span>We thank the Conselho Nacional de Pesquisa e Desenvolvimento (CNPq) and the Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO) (process number 126772/2022-3) for the grant conceded to the second and third authors.</span></p> <p><span>_________________________________________________________________________________________________________</span></p> <p> </p> <p><span>References</span></p> <p> </p> <p><span>Bastarrika, Aitor, Maite Alvarado, Karmele Artano, Maria Pilar Martinez, Amaia Mesanza, Leyre Torre, Rubén Ramo, and Emilio Chuvieco. 2014. “BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data.” Remote Sensing 6: 12360–80. https://doi.org/10.3390/rs61212360.</span></p> <p><span>Gorelick, Noel, Matt Hancher, Mike Dixon, Simon Ilyushchenko, David Thau, and Rebecca Moore. 2017. “Google Earth Engine: Planetary-Scale Geospatial Analysis for Everyone.” Remote Sensing of Environment 202: 18–27. https://doi.org/10.1016/j.rse.2017.06.031.</span></p>
Fig. 1 in Characterization of Leishmania spp. causing cutaneous leishmaniasis in Manaus, Amazonas, Brazil
Fig. 1 Locations of case occurrence in Manaus and its metropolitan regions
Material suplementar da tese intitulada "Degradação de matéria orgânica terrestre por microrganismos do rio Amazonas - Metagenômica e Genômica Populacional"
<p>Estes arquivos representam os apêndices da tese "Degradação de matéria orgânica terrestre por microrganismos do rio Amazonas - Metagenômica e Genômica Populacional" de autoria de Célio Dias Santos Júnior e apresentada no dia 14 de dezembro de 2018 como requisito para obtenção do título de Doutor em Biologia molecular e Bioquímica pelo programa de pós-graduação em genética evolutiva e biologia molecular (PPGGEV) da Universidade Federal de São Carlos. A tese foi realizada sob a supervisão do professor Dr. Flávio Henrique Silva, e co-orientação do Dr. Ramiro Logares.</p>
Fig. 1 in A survey of necrophagous blowflies (Diptera: Oestroidea) in the Amazonas-Negro interfluvial region (Brazilian Amazon)
Fig. 1. Collecting sites and sampling points in the Amazonas state, Brazil.
Fig. 2 in A survey of necrophagous blowflies (Diptera: Oestroidea) in the Amazonas-Negro interfluvial region (Brazilian Amazon)
Fig. 2. Rarefaction curve for necrophagous blowflies in the three interfluvial collecting sites.
Fig. 1. Scoloplax baskini, INPA 28658 in Scoloplax baskini: a new spiny dwarf catfish from rio Aripuanã, Amazonas, Brazil (Loricarioidei: Scoloplacidae)
Fig. 1. Scoloplax baskini, INPA 28658, holotype, 14.4 mm SL. Photo by R. R. de Oliveira.
Fig. 2 in Entomocorus melaphareus, a new species of auchenipterid catfish (Osteichthyes: Siluriformes) from the lower and middle reaches of the rio Amazonas
Fig. 2. Entomocorus melaphareus, paratype, MZUSP 76445, 43.1 mm SL.
Fig. 1 in Entomocorus melaphareus, a new species of auchenipterid catfish (Osteichthyes: Siluriformes) from the lower and middle reaches of the rio Amazonas
Fig. 1. Entomocorus melaphareus, holotype, MZUSP 76413, 58.6 mm SL.
Fig 3 in Entomocorus melaphareus, a new species of auchenipterid catfish (Osteichthyes: Siluriformes) from the lower and middle reaches of the rio Amazonas
Fig 3. Distribution of Entomocorus melaphareus. Type locality is indicated by the number 1.
Análise realizada durante a pesquisa "Diagnóstico editorial dos periódicos hospedados no portal da Universidade Federal do Amazonas"
<p>Quadros gerados a partir da análise realizada durante a pesquisa "Diagnóstico editorial dos periódicos hospedados no portal da Universidade Federal do Amazonas".</p> <p>Apresenta o mapeamento de revistas ativas no portal, bem como as quais que aplicam as boas práticas para qualificação de periódicos parametrizadas no estudo de Santos (2021).</p>
Distribution. Amazonian Basin in NE Ecuador (Orellana Province), NE Peru (Loreto Department), E Colombia (Vaupés Department), S & W Venezuela, the Guianas, and N Brazil (Amazonas, Amapa, and Para states), with one additional record from Atlantic Dry Forest of SE Brazil (Sâo Paulo State). in Emballonuridae
Distribution. Amazonian Basin in NE Ecuador (Orellana Province), NE Peru (Loreto Department), E Colombia (Vaupés Department), S & W Venezuela, the Guianas, and N Brazil (Amazonas, Amapa, and Para states), with one additional record from Atlantic Dry Forest of SE Brazil (Sâo Paulo State).
FIGURE 6. Phylloicus amazonas Prather 2003, pupa. 6a in Immature stages of three species and new records of five species of Phylloicus Müller (Trichoptera, Calamoceratidae) in the northern region of Brazil
FIGURE 6. Phylloicus amazonas Prather 2003, pupa. 6a, dorsal habitus (scale bar = 2 mm); 6b, head of pupal exuviae, dorsal; 6c, hook plates of abdominal segments I–VIII, dorsal (a = anterior, p = posterior position); 6d–6e, abdominal segments VIII and IX, left dorsal and right ventral views, respectively.
FIGURE 5. Phylloicus amazonas Prather 2003 in Immature stages of three species and new records of five species of Phylloicus Müller (Trichoptera, Calamoceratidae) in the northern region of Brazil
FIGURE 5. Phylloicus amazonas Prather 2003, larval gill diagram with positions of gills and number of gill filaments on abdominal segments I–VIII.
FIGURE 4. Phylloicus amazonas Prather 2003, larval case. 4a–4c in Immature stages of three species and new records of five species of Phylloicus Müller (Trichoptera, Calamoceratidae) in the northern region of Brazil
FIGURE 4. Phylloicus amazonas Prather 2003, larval case. 4a–4c, ventral, left lateral, and anterior, respectively (scale bar = 4 mm); 4d, case partially built with plastic material (marking tape).
FIGURE 2. Phylloicus amazonas Prather 2003, larva. 2a in Immature stages of three species and new records of five species of Phylloicus Müller (Trichoptera, Calamoceratidae) in the northern region of Brazil
FIGURE 2. Phylloicus amazonas Prather 2003, larva. 2a, right lateral habitus (scale = 2 mm); 2b, head, thorax and abdominal segment I, dorsal (scale = 1 mm); 2c, thorax, dorsal (scale = 1 mm); 2d, pronotal plates, dorsal (scale = 0.5 mm); 2e, right foretrochantin (arrow) and right pronotal plate, right lateral (scale = 0.5 mm); 2f–2h, right fore-, mid-, and hind legs, respectively, right lateral (scale = 1 mm); 2i, right lateral sclerite and anal claw of abdominal segment IX; 2j, abdominal segment I, ventrolateral humps, ventral (scale = 0.5 mm); 2k, abdominal segment IX, sclerite, and anal claw,dorsal.
FIGURE 3. Phylloicus amazonas Prather 2013, larva. 3a–3c in Immature stages of three species and new records of five species of Phylloicus Müller (Trichoptera, Calamoceratidae) in the northern region of Brazil
FIGURE 3. Phylloicus amazonas Prather 2013, larva. 3a–3c, head, dorsal, ventral, and right lateral, respectively (scale = 0.5 mm); 3d, labrum, dorsal (scale = 0.12 mm); 3e–3g, left and right mandibles, dorsal, respectively, and right mandible, mesal, respectively (scale = 0.2 mm); 3h, mentum and ventral apotome, ventral (scale bar = 0.25 mm); 3i, frontoclypeal apotome, dorsal; 3j, right foretrochantin (arrow), forecoxa, foretrochanter, and forefemur, right lateral (scale bar = 0.25 mm).
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OpenNeuro
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