Automatização de inventário utilizando a tecnologia RFID na Biblioteca Ministro Oscar Saraiva

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Faculdade de Ciência da Informação, 2018.O acervo de uma biblioteca passa por diversas alterações, de modo que se faz necessário a realização de um inventário, visando-se analisar a situação real do acervo, de forma manual ou com o auxílio da tecnologia. O objetivo deste trabalho é compartilhar a experiência da realização de um inventário automatizado dentro de uma biblioteca e analisar as ligações entre o inventário e o desenvolvimento de coleções. Desta forma acompanha-se o desenvolvimento do inventário da biblioteca Ministro Oscar Saraiva do STJ, analisa-se os passos necessários para completar o processo, os arquivos resultantes da leitura, e o resultado final da operação. Insere-se dentro do acompanhamento do inventário o estudo da tecnologia RFID, tecnologia aplicada pela biblioteca do STJ com o propósito de tornar automatizada a leitura de cada livro e a consolidação do relatório final. Conclui-se que a tecnologia RFID possui diversas aplicações no ambiente da biblioteca, e torna mais eficiente a prática de tarefas, como a do inventário.A library’s collection is subject to several changes, thus an inventory is necessary, in order to analyze the actual situation of the collection, either manually or with the aid of technology. The objective of this paper is to share the experience of realizing an automated inventory in a library and to analyze the connections between the inventory and the development of colections. This way it is monitored the development of the Ministro Oscar Saraiva library inventory, analizing the necessary steps to complete the process, the resulting archives of the reading, and the operation's final results. The study of the RFID technology, the one applied by the STJ's library, is inserted within the monitoring of the inventory, with the purpose of automating the reading of every book and the consolidation of the final report. It is concluded that RFID technology has several applications in a library environment, and makes the practice of tasks, such as inventory, more efficient

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

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

Seminário de Dissertação (2024)

Página da disciplina de Seminário de Dissertação (MPPP, UFPE, 2022) Lista de participantes == https://docs.google.com/spreadsheets/d/1mrULe1y04yPxHUBaF50jhaM1OY8QYJ3zva4N4yvm198/edit#gid=

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved

Growing knowledge: an overview of Seed Plant diversity in Brazil

Abstract An updated inventory of Brazilian seed plants is presented and offers important insights into the country's biodiversity. This work started in 2010, with the publication of the Plants and Fungi Catalogue, and has been updated since by more than 430 specialists working online. Brazil is home to 32,086 native Angiosperms and 23 native Gymnosperms, showing an increase of 3% in its species richness in relation to 2010. The Amazon Rainforest is the richest Brazilian biome for Gymnosperms, while the Atlantic Rainforest is the richest one for Angiosperms. There was a considerable increment in the number of species and endemism rates for biomes, except for the Amazon that showed a decrease of 2.5% of recorded endemics. However, well over half of Brazillian seed plant species (57.4%) is endemic to this territory. The proportion of life-forms varies among different biomes: trees are more expressive in the Amazon and Atlantic Rainforest biomes while herbs predominate in the Pampa, and lianas are more expressive in the Amazon, Atlantic Rainforest, and Pantanal. This compilation serves not only to quantify Brazilian biodiversity, but also to highlight areas where there information is lacking and to provide a framework for the challenge faced in conserving Brazil's unique and diverse flora