Mechanical behavior of implant assisted removable partial denture for Kennedy class II

This study evaluated the mechanical response of a removable partial denture (RPD) in Kennedy Class II according to being associated or not with implants. Four RPDs were manufactured for a Kennedy Class II: CRPD - Conventional RPD, RPD+1M, RPD+2M and RPD+12M, respectively, signifying implant assisted RPDs with the implant installed in the first molar, second molar, and in the first and second molars. The finite element method was used to determine the most damaged support tooth under compressive load (300N, 10s) and strain gauge analysis was used to evaluate the microstrain. All groups were submitted to a retentive force analysis (0.5 mm/mm, 100kgf). Microstrain and retentive force data were submitted to One-way ANOVA and the Tukey test, all with ?=5%. High microstrain was observed in the second premolar adjacent to the edentulous space under compression load (p< 0.01). RPD+12M presented lower microstrain, however being similar to RPD+2M. RPD+1M presented a higher mean value of retentive force, but similar to RPD+12M. FEM showed RPD assisted by implants concentrates less stress in the periodontal ligament. The association of two implants was sufficient to decrease the stress generated in the implants. The most stressed region for the o-ring abutment was the threads, and the group with two implants showed the lowest stress concentration. In cases of Kennedy Class II, the association of RPD with implants in the molar region is a favorable option for patient rehabilitation, reducing the movement of the direct retainer adjacent to the edentulous space, increasing the removal force and decreasing the stress magnitude in the periodontal ligament

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

ATLANTIC-PRIMATES: a dataset of communities and occurrences of primates in the Atlantic Forests of South America

Primates play an important role in ecosystem functioning and offer critical insights into human evolution, biology, behavior, and emerging infectious diseases. There are 26 primate species in the Atlantic Forests of South America, 19 of them endemic. We compiled a dataset of 5,472 georeferenced locations of 26 native and 1 introduced primate species, as hybrids in the genera Callithrix and Alouatta. The dataset includes 700 primate communities, 8,121 single species occurrences and 714 estimates of primate population sizes, covering most natural forest types of the tropical and subtropical Atlantic Forest of Brazil, Paraguay and Argentina and some other biomes. On average, primate communities of the Atlantic Forest harbor 2 ± 1 species (range = 1–6). However, about 40% of primate communities contain only one species. Alouatta guariba (N = 2,188 records) and Sapajus nigritus (N = 1,127) were the species with the most records. Callicebus barbarabrownae (N = 35), Leontopithecus caissara (N = 38), and Sapajus libidinosus (N = 41) were the species with the least records. Recorded primate densities varied from 0.004 individuals/km 2 (Alouatta guariba at Fragmento do Bugre, Paraná, Brazil) to 400 individuals/km 2 (Alouatta caraya in Santiago, Rio Grande do Sul, Brazil). Our dataset reflects disparity between the numerous primate census conducted in the Atlantic Forest, in contrast to the scarcity of estimates of population sizes and densities. With these data, researchers can develop different macroecological and regional level studies, focusing on communities, populations, species co-occurrence and distribution patterns. Moreover, the data can also be used to assess the consequences of fragmentation, defaunation, and disease outbreaks on different ecological processes, such as trophic cascades, species invasion or extinction, and community dynamics. There are no copyright restrictions. Please cite this Data Paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data. © 2018 by the The Authors. Ecology © 2018 The Ecological Society of Americ

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Mechanical behavior of implant assisted removable partial denture for Kennedy class II

Background: This study evaluated the mechanical response of a removable partial denture (RPD) in Kennedy Class II according to being associated or not with implants. Material and Methods: Four RPDs were manufactured for a Kennedy Class II: CRPD-Conventional RPD, RPD+ 1M, RPD+2M and RPD+12M, respectively, signifying implant assisted RPDs with the implant installed in the first molar, second molar, and in the first and second molars. The finite element method was used to determine the most damaged support tooth under compressive load (300N, 10s) and strain gauge analysis was used to evaluate the microstrain. All groups were submitted to a retentive force analysis (0.5 mm/mm, 100kgf). Microstrain and retentive force data were submitted to One-way ANOVA and the Tukey test, all with α=5%. Results: High microstrain was observed in the second premolar adjacent to the edentulous space under compression load (p < 0.01). RPD+12M presented lower microstrain, however being similar to RPD+2M. RPD+1M presented a higher mean value of retentive force, but similar to RPD+12M. FEM showed RPD assisted by implants concentrates less stress in the periodontal ligament. The association of two implants was sufficient to decrease the stress generated in the implants. The most stressed region for the o-ring abutment was the threads, and the group with two implants showed the lowest stress concentration. Conclusions: In cases of Kennedy Class II, the association of RPD with implants in the molar region is a favorable option for patient rehabilitation, reducing the movement of the direct retainer adjacent to the edentulous space, increasing the removal force and decreasing the stress magnitude in the periodontal ligament

Comparação dos Conteúdos do POSCOMP com o Currículo de Referência dos Cursos de Computação da SBC

O Exame Nacional para Ingresso na Pós-Graduação em Computação (POSCOMP) é uma avaliação organizada pela Sociedade Brasileira de Computação (SBC) cujo objetivo é avaliar o egresso de Computação. Este trabalho apresenta uma análise comparativa das edições de 2014 a 2019 do POSCOMP com o Currículo de Referência (CR) da SBC homologado em 2016. A partir dessa comparação, foram observados: (i) a ausência de aproximadamente 60% dos conteúdos do CR nos exames;  (ii) apenas 14 conteúdos apresentam incidências significativas e contínuas nos exames; (iii) os eixos de formação definidos pelo CR têm diferenças significativas nos números de questões correspondentes que foram exploradas ao longo das edições do exame