Dynamizing Innovation Systems through Induced Innovation Networks: A Conceptual Framework and the Case of the Oil Industry in Brazil

Based on the evolution of National, Regional, Sectoral and Technological Innovation Systems concepts, a conceptual framework is proposed to explain the configuration and coordination of innovation networks through an induction process. The networks may better cope with the growing complexity in innovation processes by promoting a more fine-tuning articulation between the innovation systems’ elements. The Induced Innovation Network suggested by the article is particularly relevant in less matured Innovation Systems. The framework proposed is illustrated with the case of the PETRO-RS Network, a multi-sectoral innovation network located in the South of Brazil

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Synthesis and characterization of 3-[(thiourea)-propyl]-functionalized silica gel and its application in adsorption and catalysis

The objective of this research was the preparation of a silica gel functionalized successively with 3-chloropropyltrimethoxysilane (SG-PrCl) and thiourea (SG-Pr-THIO), and its application in adsorption and catalysis. The materials were characterized by 13C and 29Si NMR, FTIR, scanning electron micrographs (SEM), analysis of nitrogen and elemental analysis. Aiming at its application in adsorption, the [3-(thiourea)-propyl] silica gel (SG-Pr-THIO) was tested as an adsorbent for transition-metal ions using a batchwise process. The organofunctionalized surface showed the ability to adsorb the metal ions Cd(ii), Cu(ii), Ni(ii), Pb(ii) and Co(ii) from water, ethanol and acetone. The adsorption isotherms were fitted by Langmuir, Freundlich, Temkin and Dubinin-Radushkevich (D-R) models. The kinetics of adsorption of metals were performed using three models such as pseudo-first order, pseudo-second order and Elovich. The Langmuir and pseudo-first order models were the most appropriate to describe the adsorption and kinetic data, respectively. With the purpose of application in catalysis, the SG-Pr-THIO was reacted with a Mo(ii) organometallic complex, forming the new material SG-Pr-THIO-Mo. Only a few works in the literature have reported this type of reaction, and none dealt with thiourea and Mo(ii) complexes. The new Mo-silica gel organometallic material was tested as catalyst in the epoxidation of cyclooctene and styrene. © 2013 The Royal Society of Chemistry and the Centre National de la Recherche Scientifique

Determinantes do nível de disclosure de instrumentos financeiros derivativos em firmas brasileiras

A pesquisa teve por objetivo verificar a existência de associação entre a divulgação de informações acerca de instrumentos financeiros derivativos e características econômicas de sociedades brasileiras de Capital Aberto. Para tanto, realizou-se levantamento em demonstrações financeiras padronizadas de 75 companhias listadas nos Níveis Diferenciados de Governança Corporativa da BM&FBovespa. Na primeira etapa, pesquisa documental identificou as informações acerca dos instrumentos financeiros derivativos divulgados pelas empresas, adotando-se métrica desenvolvida a partir dos dispositivos constantes do Pronunciamento Técnico CPC 14 - Instrumentos Financeiros: Reconhecimento, Mensuração e Evidenciação. Em análise preliminar, verificou-se que nenhuma das empresas da amostra apresentou todos os itens de evidenciação requeridos, bem como que apenas 11, dos 30 itens de evidenciação, foram divulgados por mais de 50% das companhias constantes da amostra. Em seguida, procedeu-se à Análise de Correspondência (ANACOR) para verificar a associação entre os atributos das firmas e seu nível de evidenciação. No que tange aos resultados obtidos, verificou-se que os atributos 'Tamanho' e 'Lucro' estão, positivamente, associados à divulgação de informações sobre instrumentos financeiros derivativos, não se verificando associação significante entre os atributos 'Endividamento' e 'Rentabilidade', com a divulgação de informações sobre instrumentos financeiros derivativos