Sixteen properties of Eucalyptus Tereticornis wood for structural uses

Forest Red Gum eucalypt provides a versatile wood and is converted into different purposes. However, such wood is somewhat limited in structural ends, which highlights the need to exploit this gap through diffusion of mechanical properties of such timber. Obtained results should assist engineers and architects in decision-making for its best building application. This paper studied two physical and fourteen mechanical properties evaluation of Eucalyptus tereticornis at two different moisture contents, following the prescriptions of Brazilian (ABNT NBR 7190: 1997) and North American (ASTM D-143-14: 2014) standard documents. Thus, 1091 repeats were carried out for all properties. By a moisture reduction from 30% to 12%, the bulk density and eleven strength properties statistically showed changes such as modulus of rupture (static bending, parallel and perpendicular compressions), modulus of elasticity (perpendicular compression and static bending), shear stress, tangential cleavage, and parallel and perpendicular hardnesses. Then, the Eucalyptus tereticornis timber could be better usable if is further applied for structural construction uses

Evaluation of Eucalyptus microcorys wood properties

Eucalypt varieties have been identified as multipurpose materials. With origins in those nations of Oceania, this genus has been applied for purposes such as pulp and paper, bioenergy, civil construction, and furniture. Very suitable as firewood and charcoal, Eucalyptus microcorys would have good potentialities as structural solutions for construction. But, this wood species is not easily found as building parts in the Brazilian market. This paper aimed to develop a broad evaluation of this species to highlight their features for the utilization as structural lumber. Based on the Brazilian standard document on wooden structures, sixteen properties were evaluated to emphasize such potentialities. Using two moisture contents, these conditions were adopted to identify each wood property at green and dried points. About 966 repeats were realized in these tests. Nine properties showed influences with the moisture reduction as well as perceptible increases in their resistances: static bending, parallel and perpendicular compressions, and parallel tensile in the modulus of rupture; perpendicular compression and parallel tensile in the modulus of elasticity; and, shear stress and hardness properties in parallel and perpendicular directions. Eucalyptus microcorys wood reached good resistance properties, justifying its potentiality for construction in structural uses

Classification of schizophrenic traits in transcriptions of audio spectra from patient literature: artificial intelligence models enhanced by geometric properties

Schizophrenia is a severe mental illness that affects approximately 1% of the global population and presents significant challenges for patients, families, and healthcare professionals. Characterized by symptoms such as delusions, hallucinations, disorganized speech or behavior, and cognitive impairment, this condition has an early onset and chronic trajectory, making it a debilitating challenge. Schizophrenia also imposes a substantial burden on society, exacerbated by the stigma associated with mental disorders. Technological advancements, such as computerized semantic, linguistic, and acoustic analyses, are revolutionizing the understanding and assessment of communication alterations, a significant aspect in various severe mental illnesses. Early and accurate diagnosis is crucial for improving prognosis and implementing appropriate treatments. In this context, the advancement of Artificial Intelligence (AI) has provided new perspectives for the treatment of schizophrenia, with machine learning techniques and natural language processing allowing a more detailed analysis of clinical, neurological, and behavioral data sets. The present article aims to present a proposal for computational models for the identification of schizophrenic traits in texts.  The database used in this article was created with 139 excerpts of patients' speeches reported in the book “Memories of My Nervous Disease” by German judge Daniel Paul Schreber, classifying them into three categories: 1 - schizophrenic, 2 - with schizophrenic traits and 3 - without any relation to the disorder. Of these speeches, 104 were used for training the models and the others 35 for validation.Three classification models were implemented using features based on geometric properties of graphs (number of vertices, number of cycles, girth, vertex of maximum degree, maximum clique size) and text entropy. Promising results were observed in the classification, with the Decision Tree-based model [1] achieving 100% accuracy, the KNN- k-Nearest Neighbor model observed with 62.8% accuracy, and the 'centrality-based' model with 59% precision. The high precision rates, observed when geometric properties are incorporated into Artificial Intelligence Models, suggest that the models can be improved to the point of capturing the language deviation traits that are indicative of schizophrenic disorders. In summary, this study paves the way for significant advances in the use of geometric properties in the field of psychiatry, offering a new data-based approach to the understanding and therapy of schizophrenia

Características epidemiológicas de pacientes com Sepse e choque séptico

A sepse ocorre quando o sistema imunitário reage radicalmente a uma infecção. Febre alta, dificuldade respiratória, ritmo cardíaco acelerado e confusão são os principais sintomas. Para a prevenção de complicações que põem em risco a vida, é fundamental a atenção médica imediata. Este estudo teve como objetivo identificar características epidemiológicas de pacientes com sepse e choque séptico. Para isso, foi realizada uma revisão integrativa de literatura, utilizando-se LILACS e Medline como bases de pesquisa. A partir da análise qualitativa dos dados, concluiu-se que os principais fatores epidemiológicos se referem ao diagnóstico de sepse, o qual pode ser de difícil execução, realizado com atraso, de modo incorreto ou superdiagnosticado, e a inobservância das recomendações (práticas de enfermagem) para os cuidados com a sepse. Esses fatores contribuem para o agravamento da sepse, o atendimento de pacientes em unidades de terapia intensiva e o aumento dos níveis de mortalidade

High anti-SARS-CoV-2 antibody seroconversion rates before the second wave in Manaus, Brazil, and the protective effect of social behaviour measures: results from the prospective DETECTCoV-19 cohort

Background: The city of Manaus, Brazil, has seen two collapses of the health system due to the COVID-19 pandemic. We report anti-SARS-CoV-2 nucleocapsid IgG antibody seroconversion rates and associated risk factors in Manaus residents before the second wave of the epidemic in Brazil. Methods: A convenience sample of adult (aged ≥18 years) residents of Manaus was recruited through online and university website advertising into the DETECTCoV-19 study cohort. The current analysis of seroconversion included a subgroup of DETECTCoV-19 participants who had at least two serum sample collections separated by at least 4 weeks between Aug 19 and Oct 2, 2020 (visit 1), and Oct 19 and Nov 27, 2020 (visit 2). Those who reported (or had no data on) having a COVID-19 diagnosis before visit 1, and who were positive for anti-SARS-CoV-2 nucleocapsid IgG antibodies at visit 1 were excluded. Using an in-house ELISA, the reactivity index (RI; calculated as the optical density ratio of the sample to the negative control) for serum anti-SARS-CoV-2 nucleocapsid IgG antibodies was measured at both visits. We calculated the incidence of seroconversion (defined as RI values ≤1·5 at visit 1 and ≥1·5 at visit 2, and a ratio >2 between the visit 2 and visit 1 RI values) during the study period, as well as incidence rate ratios (IRRs) through cluster-corrected and adjusted Poisson regression models to analyse associations between seroconversion and variables related to sociodemographic characteristics, health access, comorbidities, COVID-19 exposure, protective behaviours, and symptoms. Findings: 2496 DETECTCoV-19 cohort participants returned for a follow-up visit between Oct 19 and Nov 27, 2020, of whom 204 reported having COVID-19 before the first visit and 24 had no data regarding previous disease status. 559 participants were seropositive for anti-SARS-CoV-2 nucleocapsid IgG antibodies at baseline. Of the remaining 1709 participants who were seronegative at baseline, 71 did not meet the criteria for seroconversion and were excluded from the analyses. Among the remaining 1638 participants who were seronegative at baseline, 214 showed seroconversion at visit 2. The seroconversion incidence was 13·06% (95% CI 11·52–14·79) overall and 6·78% (5·61–8·10) for symptomatic seroconversion, over a median follow-up period of 57 days (IQR 54–61). 48·1% of seroconversion events were estimated to be asymptomatic. The sample had higher proportions of affluent and higher-educated people than those reported for the Manaus city population. In the fully adjusted and corrected model, risk factors for seroconversion before visit 2 were having a COVID-19 case in the household (IRR 1·49 [95% CI 1·21–1·83]), not wearing a mask during contact with a person with COVID-19 (1·25 [1·09–1·45]), relaxation of physical distancing (1·31 [1·05–1·64]), and having flu-like symptoms (1·79 [1·23–2·59]) or a COVID-19 diagnosis (3·57 [2·27–5·63]) between the first and second visits, whereas working remotely was associated with lower incidence (0·74 [0·56–0·97]). Interpretation: An intense infection transmission period preceded the second wave of COVID-19 in Manaus. Several modifiable behaviours increased the risk of seroconversion, including non-compliance with non-pharmaceutical interventions measures such as not wearing a mask during contact, relaxation of protective measures, and non-remote working. Increased testing in high-transmission areas is needed to provide timely information about ongoing transmission and aid appropriate implementation of transmission mitigation measures. Funding: Ministry of Education, Brazil; Fundação de Amparo à Pesquisa do Estado do Amazonas; Pan American Health Organization (PAHO)/WHO.World Health OrganizationRevisión por pare

Análise da eficácia da Tirzepatida como agente terapêutico para perda de peso em pacientes com Obesidade

A obesidade e o diabetes são doenças crônicas que afetam milhões de pessoas em todo o mundo, sendo consideradas epidemias crescentes. O tratamento da obesidade envolve uma abordagem multifacetada, incluindo mudanças no estilo de vida e intervenções farmacológicas. Nesse contexto, a tirzepatida, uma terapia combinada de dois medicamentos que atuam em diferentes vias metabólicas para reduzir o apetite e promover a perda de peso em pacientes com obesidade, tem se destacado como uma opção terapêutica promissora. O objetivo deste estudo foi avaliar a eficácia e segurança da tirzepatida como agente terapêutico para perda de peso em pacientes com obesidade. Para isso, foram selecionados quatro artigos que avaliaram o uso da tirzepatida em pacientes com obesidade, publicados entre 2018 e 2023, nas bases de dados PubMed (Medline), Scientific Electronic Library Online (SciELO) e Cochrane Library. Os resultados indicam que a tirzepatida é uma terapia promissora e segura para perda de peso em pacientes com obesidade. Todos os estudos relataram perda de peso significativa em pacientes tratados com essa terapia, variando de 8,6% a 16,0% do peso corporal inicial. Além disso, a tirzepatida também apresentou efeitos benéficos em outros parâmetros metabólicos, como redução da glicemia e melhora da função hepática. Efeitos adversos foram relatados em menor frequência e gravidade em comparação com outras terapias para perda de peso. Em resumo, a tirzepatida é uma terapia combinada de dois medicamentos que tem demonstrado eficácia e segurança para a perda de peso em pacientes com obesidade, de acordo com os resultados de quatro estudos avaliados nesta pesquisa. Essa terapia pode ser uma opção terapêutica válida para pacientes com obesidade. No entanto, é importante destacar a necessidade de mais pesquisas para avaliar sua eficácia e segurança a longo prazo e sua aplicabilidade em diferentes populações. Portanto, é fundamental que o tratamento seja realizado com acompanhamento médico e que cada caso seja avaliado individualmente

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

Wood characterization of Eucalyptus paniculata Smith species

Eucalypts have not been well accepted for construction use by civil societies in different nations. For the elimination of these cultural barriers, there is the demand for better knowledge of the physical-mechanical properties of these silvicultural species. Thus, the research carried out a wide characterization of the Eucalyptus paniculata Smith wood species. Based on the Brazilian standard document ABNT NBR 7190, 14 mechanical properties and 2 physical properties were evaluated. Two moisture contents were adopted to compare the wood samples in different conditions: above the fiber saturation point and dried point. Results of properties were treated statistically with a t-test. In total, 1384 repeats were reached. Only two mechanical properties did not show changes in their resistance values to moisture reduction: tangential cleavage and modulus of rupture in the perpendicular tensile to grain. Further properties showed differences in the resistances from t-test for the studied moisture reduction