Public Research Institutions and Their Connections with Patents of Companies in Technological and Regional Development

The interaction between companies and universities is a central theme in discussions on technology transfer. In Brazil, there is an urgent need to raise awareness of the importance of this cooperative relationship for local and regional development. In this sense, it is observed that the innovation process is strategic so that an institution is strengthened and can fulfill its social mission in economic and regional development. Piauí, according to the IBGE census, has a population estimate of 3,273,227 in 2019. Piaui\u27s per capita income is R$ 817.00 and ranks 24th in Brazil in this regard. With these data, the need arises to intervene scientifically in this reality. The objective of this study is to investigate the partnership relationships between companies and public research institutions in Piauí, in the development and transfer of technologies. Research Institutions are the main promoters of technological development in the state, however, for these technologies to reach productive arrangements, strategic alignment in the management of these technologies is necessary. Documentary research was used, with a quantitative approach. In the exploratory search, INPI\u27s databases (National Institute of Industrial Property) and of Espacenet ( European Patent Office ) was used. We sought to select the companies with relevant economic representativeness in the state scenario and investigated the patent information. In the analysis of the data obtained, the Competitiveness Ranking of the CLP States (Public Leadership) was used to compare Piauí with well positioned states. According to the results found, it is observed that the transfer of technology between research institutions and companies is not evident. However, we can see that there are partnership initiatives with small companies in conducting research that can project a change in this scenario. The low number of patents and public/private partnerships in driving innovation in the state of Piauí, may be related to the low index evidenced by the Competitiveness Ranking of States - CLP

Inteligência Artificial na Prevenção da COVID-19: prospecção no contexto epidemiológico no mundo pós-pandêmico

The pandemic caused by COVID-19 motivated scientific and technological development to face it. Artificial Intelligence (AI) enters as a branch capable of assisting in epidemiological control and disease prevention. The objective of this article is to carry out scientific and technological prospecting on AI in the epidemiological and prevention context. Such information can contribute to combating new health crises. The Lens.org platform was used to investigate scientific works and patents relating AI, prevention, epidemiology and COVID-19. 57 articles and 19 patents were found, of these, one patent that cites an article and four patents that are cited in new technologies. It is observed that AI is an ally in epidemiological control, in the prevention and diagnosis of COVID-19 and can contribute to the analysis of large volumes of data, in the generation of control strategies, in the conduct of tests and in the creation of medicine or vaccines.A pandemia ocasionada pela COVID-19 motivou o desenvolvimento científico e tecnológico para seu enfrentamento. A Inteligência Artificial (IA) entra como um ramo capaz de auxiliar no controle epidemiológico e na prevenção da doença. O objetivo deste artigo é realizar a prospecção científica e tecnológica sobre IA no contexto epidemiológico e de prevenção no mundo pós-pandêmico. Tais informações podem contribuir para combater novas crises de saúde. A plataforma Lens.org foi utilizada para averiguar trabalhos científicos e patentes relacionando IA, prevenção e epidemiologia com a COVID-19. Foram encontrados 57 artigos e 19 patentes, destas, uma patente que cita um artigo e quatro patentes que são citadas em novas tecnologias. Observa-se que a IA se tornou um aliado no controle epidemiológico, na prevenção e no diagnóstico da COVID-19 e pode contribuir com a análise de grande volume de dados, na geração de estratégias de controle, na condução de testes e na criação de medicamento ou vacinas

Instituições Públicas, Empresas e Governo: uma análise dos acordos de parceria no contexto no agronegócio nos moldes da Hélice Tríplice

With the projected increase in global population density and urban area expansion, there is a crucial need to enhance productivity in agribusiness. Employing the triple helix approach, partnerships between Federal Institutes and various stakeholders are examined, analyzing collaborations and outcomes. This study aims to analyze partnership agreements involving Federal Institutes of Education, Science, and Technology (ICTs) in Brazilian states and other stakeholders. The methodology evaluates these partnerships in light of innovation laws, Law n. 10.973/2004 and Law n. 13.243/2016. Results highlight Mato Grosso, Paraná, and São Paulo as major producers, with São Paulo standing out with 144 agreements, demonstrating effectiveness in applying innovation laws to agribusiness. The study underscores the significance of strategic partnerships in promoting agricultural innovation, especially in leading states like São Paulo.Com o aumento previsto da densidade populacional global e a expansão das áreas urbanas, surge a necessidade crucial de aumentar a produtividade no agronegócio. Utilizando-se da abordagem da hélice tríplice, foram examinadas parcerias entre Institutos Federais e diversos stakeholders, analisando colaborações e resultados. Este estudo teve como objetivo analisar os acordos de parceria entre os Institutos Federais de Educação, Ciência e Tecnologia (ICTs) dos estados brasileiros, empresas e governos. Coletou-se extratos de documentos no Diário Oficial da União que fazem referência às leis de inovação, Lei n. 10.973/2004 e Lei n. 13.243/2016, bem como o Valor Bruto de Produção Agrícola dos estados. Os resultados destacam Mato Grosso, Paraná e São Paulo como principais produtores, sendo que este último se destaca com 144 acordos, evidenciando eficácia na aplicação das leis de inovação no agronegócio. O estudo ressalta a relevância das parcerias estratégicas na promoção da inovação agrícola, especialmente em estados líderes como São Paulo

Análise da eficácia do uso terapêutico da trimetazidina nas principais síndromes coronarianas agudas

A injúria de reperfusão, ou isquemia, é um mecanismo fisiopatológico que ocorre nas etiopatogenias do miocárdio, como na angina instável. Assim, são utilizados fármacos adjuvantes citoprotetores, como a trimetazidina (TMZ), que visam à diminuição do tempo de hospitalização e melhora na função cardíaca com ação profilática contra essa lesão. No entanto, apesar dos seus potenciais benefícios no tratamento da síndrome coronariana aguda, ainda não está clara a sua eficácia em relação a outras terapias disponíveis. Nesse sentido, o objetivo do estudo é analisar a eficácia do uso terapêutico da trimetazidina nas principais síndromes coronarianas agudas. Foi realizada uma revisão sistemática usando as bases de dados PubMed, Cochrane Library e Embase. Um total de 3 estudos foi incluído na análise. Os resultados mostraram que a terapia com trimetazidina reduziu significativamente a incidência de eventos cardíacos adversos maiores (ECAM) (OR = 0,33, IC 95% 0,15-0,75, p = 0,007), menor dano miocárdico (p < 0,05) e fração de ejeção ventricular esquerda mais elevada e menos eventos adversos em comparação com o grupo placebo (p < 0,05). Não foram observadas diferenças significativas entre os grupos de trimetazidina e controle em termos de mortalidade por todas as causas, mortalidade cardiovascular ou incidência de eventos adversos. Os resultados deste estudo sugerem que a terapia adjuvante com trimetazidina pode melhorar os resultados clínicos e a função cardíaca em pacientes com IAM sem aumentar o risco de eventos adversos. No entanto, são necessários mais ensaios clínicos randomizados em larga escala para confirmar esses resultados e determinar a duração e dose ideais da terapia com trimetazidina nessa população de pacientes

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

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Ambientes virtuais de aprendizagem com biometria facial

A Educação a Distância tem obtido grande importância no cenário educacional brasileiro. Através da facilidade de acesso às novas Tecnologias de Informação e Comunicação, tem-se expandido em alcance geográfico e numérico. Com isso, a Educação a Distância vem democratizando o ensino e o conhecimento, levando-os para áreas remotas em que o ensino presencial encontra inúmeras dificuldades para atender a população. O desenvolvimento de ferramentas que auxiliem na qualidade dos Ambientes Virtuais de Aprendizagem (AVA) tem se tornado uma prática para melhorar a Educação a Distância. O tópico da presente pesquisa é Segurança da Informação nos AVAs, tendo como hipótese que a biometria facial pode contribuir com esse aspecto através do monitoramento dos alunos nas plataformas virtuais de ensino em cursos na modalidade de Educação a Distância. Nossa proposta é melhorar o procedimento de autenticação na plataforma com a utilização da biometria facial, possibilitando a verificação da presença desse aluno com o reconhecimento facial. O estudo foi composto de três etapas. Na primeira etapa foi realizada uma pesquisa bibliográfica. Na segunda etapa foi realizado a elaboração e aplicação de um questionário para os integrantes da EAD do Instituto Federal do Piauí e da Universidade Federal do Piauí, no qual detectamos uma opinião positiva sobre a criação de novas ferramentas de autenticação. Partindo-se da pesquisa bibliográfica e da análise dos dados coletados através do questionário, a terceira etapa consistiu no desenvolvimento de um protótipo de reconhecimento facial para os AVAs. Participaram da pesquisa um total de 83 indivíduos, entre estudantes, tutores presenciais, tutores a distância, coordenadores, professores conteudistas e professores pesquisadores. Como inovação tecnológica para a Educação a Distância, nosso protótipo de reconhecimento facial foi implementado com as linguagens PHP e PYTHON, e a biblioteca de visão computacional OPENCV para detecção facial com haarcascade e reconhecimento facial com Padrões Binários Locais de Histogramas (LBPH). A ferramenta foi desenvolvida de forma a reconhecer o aluno através de padrões faciais, registrando a sua presença nos Ambientes Virtuais de Aprendizagem. Nos testes do protótipo foi utilizado um banco de dados com 167 imagens, além da realização do cadastro e reconhecimento de 20 usuários e testes de simulação de fraudes. Para testes de desempenho foi montado um banco de dados com 226 imagens. O protótipo demonstrou eficiência no desempenho e na efetivação do reconhecimento facial dos usuários, embora necessite de novas implementações.Online education has achieved great importance in Brazil’s education. Through the ease of access to the new Information and Communication Technologies, it has expanded in geographical and numerical reach. This way, Online Education has been democratizing teaching and knowledge, taking them to remote areas where face-to-face teaching encounters numerous difficulties in serving the population. The development of tools that support the quality of Virtual Learning Environments (VLE) has become frequent in order to improve Online Education. The topic of this research is Information Security in VLEs, and its hypothesis is that facial biometry can contribute to this aspect through the monitoring of students in the virtual platforms of teaching in courses in the modality of Online Education. Our proposal is to improve the authentication procedure on the pallet with the use of facial biometrics, enabling a verification of the vision with facial recognition. The study was composed of three stages. In the first stage, a bibliographical research was carried out. In the second stage, a questionnaire was developed and applied to the Online Education members at Instituto Federal do Piauí and Universidade Federal do Piauí, in which we detected a positive opinion about the creation of new authentication tools. Based on the bibliographical research and the analysis of the data collected through the questionnaire, the third step consisted in the development of a prototype of facial recognition for VLE. A total of 83 individuals, including students, face-to-face tutors, online tutors, coordinators, content teachers and research professors participated in the study. As a technological innovation for Online Education, our facial recognition prototype was implemented with the PHP and PYTHON languages, and the OPENCV computer vision library for haarcascade facial detection and facial recognition with Local Binary Histogram Patterns (LBPH). The tool was developed in order to recognize the student through facial patterns, recording their presence in Virtual Learning Environments. In the prototype tests, a database with 167 images was used, as well as the registration and recognition of 20 users and fraud simulation tests. For performance tests a database with 226 images was set up. The prototype demonstrated efficient performance and effective facial recognition of users, although it requires new implementations