Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

The study investigated the understanding and perception of ecosystem services among high school and undergraduate students the field of Biological Sciences in the state of São Paulo. A semi-structured questionnaire was applied, and statistical analyses revealed significant differences in perception between the two groups and attributed to formal education and cultural experiences. The results demonstrated the need for specific educational strategies to increase awareness of ecosystem services, especially in high school. Early inclusion of these topics in the curriculum and practical activities is recommended to enhance understanding and appreciation of these concepts. Environmental education is essential for developing individuals who are conscious and capable of building more sustainable and environmentally responsible societies.

The National High School Exam – ENEM, instituted in 1998, is a large-scale assessment that has become a way of access to Higher Education, exerting a strong influence on the Brazilian education system and on teaching practice. To provide support to teachers and to evaluate the possible distancing of this assessment in relation to social issues, the research aimed to investigate the presence of aspects of Scientific Literacy in Biology questions of the ENEM 2019, through the Content Analysis, proposed by Laurence Bardin. The results showed that the questions have a greater relationship with the individual dimension, and social dimension in the functionalist perspective of Scientific Literacy. Interdisciplinarity was little represented.

With the aim of analyzing teacher training, an experience is presented involving 20 undergraduate students and a Technical School in the interior of the State of São Paulo. There was a great distance between University and School, both in relation to curricular content and professional perspectives. Activities in the area of ​​science teaching were planned and carried out, under supervision, with records in a field diary and production of reports, later analyzed. It provided experience with issues of teaching practice such as didactic planning, selection of themes and methodologies, forms of assessment, teacher-student relationship, and others. Programs of this type constitute an important path for learning and teaching, reducing the distance between the University and the School, the places of teacher training.

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A deterioração da qualidade ambiental das águas do Açude Grande agravou a disponibilidade hídrica na cidade de Cajazeiras (estado da Paraíba, Brasil) em períodos de estiagem. Assim, o presente trabalho buscou avaliar a clarificação seguida de filtração para tratamento das águas do Açude Grande. A pesquisa é inovadora na aplicação de métodos de otimização em técnicas convencionais para o tratamento de mananciais considerados impróprios para o consumo humano, em localidades com recursos hídricos limitados e restrições econômicas e operacionais. Desse modo, as variáveis de concentração de sulfato de alumínio e pH foram otimizadas em função da remoção de turbidez e cor aparente na etapa de clarificação (coagulação, floculação e decantação), utilizando o planejamento fatorial do tipo delineamento composto central rotacional associado à metodologia de superfície de resposta. Posteriormente, a etapa de filtração, composta por uma camada de areia e brita, foi simulada em escala de bancada. Os resultados demonstraram que a dosagem do coagulante de 60,0 mg.L-1 e pH de 6 alcançaram a melhor remoção de turbidez (67,3%) e de cor aparente (78,1%), enquadrando o parâmetro turbidez nos limites da Portaria do Ministério da Saúde GM/MS n° 888/2021. Quanto ao processo de filtração, este apresentou uma boa eficiência na remoção dos parâmetros de turbidez (>77,0%), de cor aparente (>70,0%) e de demanda bioquímica de oxigênio (>46,0%) em comparação à amostra pós-clarificação. Conclui-se que o tratamento convencional tem potencial para adequar os parâmetros investigados aos padrões organolépticos de potabilidade, sendo sugerida a pré-oxidação para aumentar a remoção de matéria orgânica.

Microplastics are present all around the globe, and they are a major threat to the environment because of the challenges they pose. Their sampling, isolation, and analysis processes are laborious and difficult due to their size, shape, and spreading dynamics. Furthermore, the lack of standardized protocols in microplastic research makes it difficult to compare results and unify the progress of the field. In this context, this work proposes and evaluates a model architecture based on deep learning to classify microplastic images using a dataset of real microplastics sampled from a freshwater reservoir, with convolutional neural network and transfer learning. Moreover, the model identifies diatom algae frustules, which can persist in the hydrogen peroxide degradation during the process of microplastic isolation due to their biosilica composition. The model was developed in Python using the Google Colab environment. A total of 1,140 images were used, and to ensure a robust and generalized evaluation, 5-fold cross-validation was applied. The model achieved 93% accuracy, with a recall of 97, 95, 92, and 90% for algae, microplastic filaments, fragments, and pellets, respectively. Overall, the accuracy of the model is encouraging considering the dataset size and all the challenges that involve the automatic identification of microplastics, with all their shape variations and nuances; thus the results are promising. To our knowledge, this is the first work addressing diatom presence after one of the most common microplastic isolation techniques and their automated classification among microplastics as well.

Both pharmaceuticals and personal care products (PPCPs) contaminate river water in Brazil. To determine the extent of such contamination in the rivers and tributaries of important basins in the state of Mato Grosso do Sul, Brazilian Midwest, this study aimed to examine the distribution of PPCPs in these waterways and then perform an ecological risk assessment (ERA). To accomplish this, water samples were collected from four river basins and their sub-basins, all of which are located in the southern part of the Brazilian state of Mato Grosso do Sul. PPCP concentrations were quantified, along with assessments of the in situ physicochemical characteristics of the water. ERA was evaluated as a risk quotient (RQ) based on the maximum measured concentration of PPCPs in the samples. The relationship among the concentrations of PPCPs in aqueous samples was examined to assessthe distribution of these substances in the environment. Thehighest concentrations of PPCPs involved caffeine, particularly during the dry season, indicating an intense route of contamination at sampled sites. Among other compounds, pharmaceutical compounds such as diclofenac, ibuprofen, and naproxen were prevalent, especially during the dry season, albeit in slightly lower concentrations. RQ results showed that most compounds investigated represent moderate to high toxicological risk to the aquatic ecosystem. These results suggest that PPCPs are widely distributed in the studied area and provide a benchmark for comparison, or starting point, for future monitoring and environmental recovery programs, as well as encouraging revisions to current legislation.

A simplified atmospheric transmittance model based on the Beer-Lambert law was utilized to analyze surface solar radiation (SSR) variability based on different sources of cloud cover datasets (CMIP6, ERA5, NCEP, ISCCP, and EUMETSAT). This study evaluated the performance of various modeled SSR datasets against observed data from the Brazilian Daily Weather Gridded Data (BR-DWGD) over the period from 1983 to 2009. Contour plots of annual average SSR from the five modeled datasets were compared with BR-DWGD observations, revealing spatial agreements and discrepancies. The highest SSR values were consistently observed in the Brazilian semi-arid Northeast, while the Amazon region exhibited the lowest values. In the analysis of annual averages, the International Satellite Cloud Climatology Project (ISCCP) demonstrated the closest agreement with BR-DWGD, while the National Center for Environmental Prediction (NCEP) showed the most significant deviations. Root mean square error (RMSE) analysis highlighted seasonal variability in model performance, with the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) performing best during equinoxes, and ISCCP showing the lowest annual RMSE (16.9 Wm⁻²). Hierarchical clustering further grouped EUMETSAT and CMIP6 as the most similar and accurate datasets, while NCEP remained the least consistent. Global horizontal irradiance maps corroborated SSR patterns, with higher values in the Northeast and lower values in the Amazon and Southern regions. These findings underscored the importance of dataset selection for accurate SSR modeling in Brazil, with ISCCP, EUMETSAT, and CMIP6 emerging as the most reliable options.

A estimativa da geração de resíduos da construção civil (RCC) é essencial para o planejamento sustentável e a gestão eficaz de resíduos em canteiros de obras. No entanto, os métodos convencionais frequentemente não atendem às demandas práticas do setor. Este estudo investigou o uso de redes neurais artificiais (RNA) como ferramenta preditiva para a quantificação de RCC. Foram realizadas simulações com amostras de 5.000 dados (A) e 10.000 dados (B), seguidas da validação com amostra de 360 dados (R) coletados em canteiros de obras em Curitiba, estado do Paraná, Brasil. Essa abordagem permitiu uma avaliação abrangente da acurácia preditiva e da aplicabilidade prática da RNA. O melhor desempenho foi obtido com a amostra B, utilizando uma RNA configurada com duas variáveis de entrada, dez neurônios na camada oculta e três ciclos de treinamento. Nas simulações, o modelo apresentou coeficiente de determinação (R²) de 1,00, raiz do erro quadrático médio (RMSE, root mean squared error) de 6,55 kg e erro percentual absoluto médio (MAPE, mean absolute percentagem error) de 0,00013%. Na validação, obteve-se R² de 0,83, RMSE de 4.337,69 m³ e estimativas precisas em mais de 60% dos casos (MAPE). Os resultados demonstraram a viabilidade do uso de RNA para aprimorar a estimativa de RCC, contribuindo para a tomada de decisão e para o desenvolvimento de estratégias mais eficientes de redução de resíduos na construção civil.

Considering that gram-positive contaminant bacteria may compromise the alcoholic fermentation process for ethanol production, natural biocides are sought for use in controlling such microorganisms. In this sense, neem (Azadirachta indica), known for its biological properties, emerges as a solution for controlling these contaminations. This study aimed to evaluate the antimicrobial activity of neem leaf, bark, and seed extracts, correlating them to the presence of secondary metabolites, thus determining their biocide potential. The extracts were obtained by maceration in ethanol and phytochemically analyzed through thin-layer chromatography (TLC) and Fourier transform infrared spectroscopy (FTIR), with the quantification of total phenolics, total flavonoids, total tannins, and antioxidant activity. The antimicrobial activity was evaluated through disk diffusion tests and the minimum inhibitory concentration (MIC) determination, using L. fermentumand L. mesenteroides as bacterial models. The tests showed that the leaf and bark extracts inhibited bacterial growth without affecting the yeast S. cerevisiae, with an efficacy of 50 and 30 mg/mL, respectively. A phytochemical analysis revealed the predominance of flavonoids in the leaves and a more significant concentration of tannins in the bark, both of which are recognized for their antimicrobial properties. The extracts also presented high levels of phenolic compounds, reinforcing their bacterial efficacy, while the antioxidant activity of the bark suggests a complementary role of action of the extract. The seed extract did not show antimicrobial activity. Hence, the neem leaf and bark extracts have biocide potential to be used in alcoholic fermentation.