Extension of geographical distribution of three common species of diurnal butterflies (Lepidoptera: Papilionoidea) from the Colombian Caribbean

En este documento se registran tres especies comunes de mariposas diurnas de la región Caribe colombiana (Aides dysoni, Calpodes ethlius y Anteos clorinde). Los especímenes fueron capturados con red entomológica en muestreos realizados en el municipio de Arjona (departamento de Bolívar) en el año de 2015 entre las 8:00 y 16:00 horas. Para cada una de ellas se proporcionan caracteres morfológicos útiles para su reconocimiento y se complementa su distribución en el Neotrópico.In this document we extend the geographical distribution for three common species of diurnal butterflies from the Colombian Caribbean region (Aides dysoni, Calpodes ethlius, and Anteos clorinde). The specimens were captured with an insect net in samplings conducted in the Arjona jurisdiction (Bolivar, Deparment) in 2015, between 8:00 and 16:00 hours. For each of them we provide important morphological characters for their recognition, and complement their distribution in the Neotropic

An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus

Hybrid models to detect dementia based on Machine Learning can provide accurate diagnoses in individuals with neurological disorders and cognitive complications caused by Human Immunodeficiency Virus (HIV) infection. This study proposes a hybrid approach, using Machine Learning algorithms associated with the multicriteria method of Verbal Decision Analysis (VDA). Dementia, which affects many HIV-infected individuals, refers to neurodevelopmental and mental disorders. Some manuals standardize the information used in the correct detection of neurological disorders with cognitive complications. Among the most common manuals used are the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th edition) of the American Psychiatric Association and the International Classification of Diseases, 10th edition (ICD-10)—both published byWorld Health Organization (WHO). The model is designed to explore the predictive of specific data. Furthermore, a well-defined database data set improves and optimizes the diagnostic models sought in the research.info:eu-repo/semantics/publishedVersio

Uso de bebederos artificiales por pequeños roedores en un bosque tropical seco en Oaxaca, México

The implementation of water developments for wildlife is a common management practice in regions with seasonal water shortages. The water developments are installed to benefit species of human interest, nevertheless, they can be used by other species. In this note we report observations of small rodents visiting the water developments in a locality in the Tehuacán-Cuicatlán Biosphere Reserve. The water developments were monitored using 12 camera traps during the 2018 dry season in the locality of San Gabriel Casa Blanca, Oaxaca. We calculate the visit rate of rodents and compared it between two types of water developments. We observe 154 visits of rodents of at least four genera: Peromyscus, Liomys, Sigmodon and Dipodomys. The mean visit rate for both types of water developments was 18.8 ± 37.7 visits/100 days. We don´t find significant differences in the visits among the water development types. Using camera-traps we demonstrate the visits and use of water developments by some species of cricetids. Likewise, we suggest that the lack of ramps or concave walls in the troughs represents a risk for small species. Other studies are necessary to evaluate the effect of the water developments on the biomass, survival, abundance of rodents in dry forests.La implementación de bebederos artificiales para fauna silvestre es una práctica de manejo común en regiones con escasez estacional de agua. Los bebederos se instalan para beneficiar a especies de interés humano, sin embargo, éstas pueden ser usadas por otras especies. En esta nota reportamos observaciones de pequeños roedores visitando los bebederos en una localidad en la Reserva de Biosfera Tehuacán-Cuicatlán. Se monitorearon los bebederos empleando 12 cámaras-trampa durante la temporada seca de 2018 en la localidad de San Gabriel Casa Blanca, Oaxaca. Se calculó la tasa de visita de roedores y se comparó entre dos tipos de bebederos. Se registraron 154 visitas de roedores de al menos cuatro géneros: Peromyscus, Liomys, Sigmodon y Dipodomys. La tasa de visita promedio en ambos tipos de bebederos fue de 18.8 ± 37.7 visitas/100 días. No se encontraron diferencias significativas en las visitas por tipo de bebedero. Empleando cámaras-trampa evidenciamos las visitas y uso de bebederos por algunas especies de cricétidos. Se sugiere que la falta de rampas o paredes cóncavas en los bebederos representa un riesgo para especies pequeñas. Son necesarios otros estudios para evaluar el posible efecto de los bebederos sobre la biomasa, supervivencia y abundancia de roedores en bosques secos

Thermal Transport and Rheological Properties of Hybrid Nanofluids Based on Vegetable Lubricants

Nanofluids based on vegetal oil with different wt.% of carbon nanotubes (CNT), hexagonal boron nitride (h-BN), and its hybrid (h-BN@CNT) were produced to investigate the effects of these nano-additives on the thermal conductivity and rheological properties of nanofluids. Stable suspensions of these oil/nanostructures were produced without the use of stabilizing agents. The dispersed nanostructures were investigated by SEM, EDS, XRD, and XPS, while the thermal conductivity and rheological characteristics were studied by a transient hot-wire method and steady-state flow tests, respectively. Increases in thermal conductivity of up to 39% were observed for fluids produced with 0.5 wt.% of the hybrid nanomaterials. As for the rheological properties, it was verified that both the base fluid and the h-BN suspensions exhibited Newtonian behavior, while the presence of CNT modified this tendency. This change in behavior is attributed to the hydrophobic character of both CNT and the base oil, while h-BN nanostructures have lip-lip “bonds”, giving it a partial ionic character. However, the combination of these nanostructures was fundamental for the synergistic effect on the increase of thermal conductivity with respect to their counterparts

Hybrid model for early identification post-Covid-19 sequelae

Artificial Intelligence techniques based on Machine Learning algorithms, Neural Networks and Naïve Bayes can optimise the diagnostic process of the SARS-CoV-2 or Covid-19. The most significant help of these techniques is analysing data recorded by health professionals when treating patients with this disease. Health professionals' more specific focus is due to the reduction in the number of observable signs and symptoms, ranging from an acute respiratory condition to severe pneumonia, showing an efficient form of attribute engineering. It is important to note that the clinical diagnosis can vary from asymptomatic to extremely harsh conditions. About 80% of patients with Covid-19 may be asymptomatic or have few symptoms. Approximately 20% of the detected cases require hospital care because they have difficulty breathing, of which about 5% may require ventilatory support in the Intensive Care Unit. Also, the present study proposes a hybrid approach model, structured in the composition of Artificial Intelligence techniques, using Machine Learning algorithms, associated with multicriteria methods of decision support based on the Verbal Decision Analysis methodology, aiming at the discovery of knowledge, as well as exploring the predictive power of specific data in this study, to optimise the diagnostic models of Covid-19. Thus, the model will provide greater accuracy to the diagnosis sought through clinical observation.info:eu-repo/semantics/publishedVersio

Enhancing spatial inference of air pollution using machine learning techniques with low-cost monitors in data-limited scenarios

Ensuring environmental justice necessitates equitable access to air quality data, particularly for vulnerable communities. However, traditional air quality data from reference monitors can be costly and challenging to interpret without in-depth knowledge of local meteorology. Low-cost monitors present an opportunity to enhance data availability in developing countries and enable the establishment of local monitoring networks. While machine learning models have shown promise in atmospheric dispersion modelling, many existing approaches rely on complementary data sources that are inaccessible in low-income areas, such as smartphone tracking and real-time traffic monitoring. This study addresses these limitations by introducing deep learning-based models for particulate matter dispersion at the neighbourhood scale. The models utilize data from low-cost monitors and widely available free datasets, delivering root mean square errors (RMSE) below 2.9 μg m−3 for PM1, PM2.5, and PM10. The sensitivity analysis shows that the most important inputs to the models were the nearby monitors' PM concentrations, boundary layer dissipation and height, and precipitation variables. The models presented different sensitivities to each road type, and an RMSE below the regional differences, evidencing the learning of the spatial dependencies. This breakthrough paves the way for applications in various vulnerable localities, significantly improving air pollution data accessibility and contributing to environmental justice. Moreover, this work sets the stage for future research endeavours in refining the models and expanding data accessibility using alternative sources

POTENCIAL AGRONÔMICO DE Eugenia candolleana D.C. EM ÁREA DE RESTINGA LITORÂNEA EM ARAQUARI-SC, BRASIL: RESULTADOS PARCIAIS

Eugenia candolleana D.C. (Myrtaceae) é uma espécie florestal frutífera endêmica da Mata Atlântica. Apesar da planta possuir propriedades medicinais e de seus frutos serem apreciados para o consumo in natura e na culinária, carece de informações técnicas no âmbito agronômico, principalmente para as condições do litoral nordeste de Santa Catarina. Este trabalho teve por objetivos verificar aspectos relativos ao potencial agronômico de E. candolleana D.C. em área de restinga litorânea. em Araquari-SC, Brasil. O estudo foi realizado em uma população plantas existentes na área do IFC-Campus Araquari (26°22'12'' S e 48°43' 19'' O), durante o período 01/08/2019 a 31/07/2020. Foram analisados: o período de colheita; a estimativa de produção de frutos, determinada pelo acumulado de colheita de todos os frutos maduros por planta; o comportamento pós-colheita, por meio da determinação do “tempo de vida de prateleira” de frutos frescos maduros e recém colhidos, mantidos a 10°C e 25°C, sendo determinadas a matéria fresca (g) e o teor total de sólidos solúveis (°Brix) aos 0, 2, 4, 6 e 8 dias após a colheita, bem como verificadas a ocorrência de alterações visuais nos frutos. Também foi observada a ocorrência de danos causados por pássaros, insetos ou doenças, obtida pela análise visual dos frutos durante a colheita e respectivo cálculo do percentual de frutos danificados. Os frutos foram acondicionados em bandejas plásticas. Da população de plantas observadas, foi possível realizar a colheita em apenas uma, possivelmente devido à juvenilidade das demais. O período de colheita de frutos foi de 29 dias, de 28/02/2020 à 28/03/2020, sendo realizadas ao todo 11 colheitas. Foi possível verificar duas etapas de produção, a primeira de 11 dias, referente à primeira florada e a outra de 14 dias de maior intensidade e produção. A produção total estimada foi 22,17 kg.planta-1 e o pesomédio dos frutos foi de 5,09g. Houveram danos decorrentes de pássaros e/ou queda natural em 21% dos frutos. O tempo de prateleira foi maior para frutos mantidos refrigerados, com redução de 12,06 para 11,24 °Brix e de 3% para matéria fresca aos 8 dias após a colheita. Frutos mantidos à 25°C reduziram de 12,5 para 11,42, 7,42 e 7,24 °Brix aos 4, 6 e 8 dias após a colheita, respectivamente, com cerca de 14% de redução de matéria fresca no final do período. Aos quatro dias após a colheita à 25°C, os frutos apresentaram odor desagradável, possivelmente devido a presença de larvas de insetos (mosca das frutas), sendo esta a principal causa de danos observada em frutos no final do tempo de prateleira. De acordo com as condições em que o trabalho foi desenvolvido pode-se concluir que: E. candolleana apresenta potencial agronômico quanto à produtividade de frutos; o reduzido tempo de prateleira demanda cuidados na comercialização de frutos frescos in natura e a refrigeração é uma alternativa na conservação da qualidade dos frutos em pós-colheita; Mosca das frutas é a principal praga encontrada, com potencial de dano econômico principalmente em pós-colheita