O TEATRO TRANSDISCIPLINAR DE JAN FABRE

RESUMO O presente ensaio vislumbra compreender as metamorfoses sofridas no teatro a partir da obra The Power of Theatrical Madness do artista belga Jan Fabre. É intenção, apresentar esse artista e desmembrar características do trabalho citado. Trata-se de uma obra específica, mas cuja análise crítica acaba por denunciar o modus operandi de Fabre como um todo. Desenvolvendo reflexões no campo das artes sobre as possibilidades (ou necessidades) do teatro para além do texto clássico (aristotélico) e das separações homogêneas das linguagens artísticas como já nos indicara Lehmann em seus estudos sobre o teatro pós-dramático. Palavras-chave: Teatro pós-dramático; Jan Fabre; The Power of Theatrical Madness; Corpo; Metamorfose. ABSTRACT The present study aims to understand the metamorphosis suffered in theater from the perspective of The Power of Theatrical Madness of the Belgian artist Jan Fabre. It’s the intention to introduce this artist and use his work as a base for I can dismember the features of Jan Fabre’s artwork. It’s a specific work, however this critical analysis turns out to reveal Fabre’s modus operandi as a whole. Developing considerations in the arts of the possibilities (or needs) of the theater beyond the classic text (Aristotelic) and homogeneous separation of artistic languages as already indicated Lehmann in his studies of post-dramatic theater. Keywords: Post-Dramatic Theater; Jan Fabre; The Power of Theatrical Madness; Body; Metamorphosis

Eficácia e Segurança de Regimes Antibióticos no Tratamento da Osteomielite em Pacientes Adultos: Revisão Sistemática

This systematic review examines the efficacy and safety of different antibiotic regimens in the treatment of osteomyelitis in adult patients. Searches were conducted in electronic databases to identify relevant studies, including randomized clinical trials, prospective cohort studies, and systematic reviews. Inclusion criteria were defined to select studies that directly addressed the comparison of different antibiotic regimens. Study selection was performed independently by two reviewers. Data were extracted and tabulated in a standardized format. The methodological quality of the included studies was assessed using appropriate tools. Results were analyzed qualitatively, highlighting the main findings and trends observed in the reviewed studies. Conclusions and recommendations were developed based on the results of the systematic review.Esta revisão sistemática examina a eficácia e segurança de diferentes regimes antibióticos no tratamento da osteomielite em pacientes adultos. Foram realizadas buscas em bases de dados eletrônicas para identificar estudos relevantes, incluindo ensaios clínicos randomizados, estudos de coorte prospectivos e revisões sistemáticas. Os critérios de inclusão foram definidos para selecionar estudos que abordassem diretamente a comparação de diferentes regimes antibióticos. A seleção dos estudos foi realizada por dois revisores de forma independente. Os dados foram extraídos e tabulados em um formato padronizado. A qualidade metodológica dos estudos incluídos foi avaliada usando ferramentas apropriadas. Os resultados foram analisados qualitativamente, destacando as principais descobertas e tendências observadas nos estudos revisados. Conclusões e recomendações foram elaboradas com base nos resultados da revisão sistemática

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

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM