Nitrogen use efficiency in modern agriculture is very low. It means that a lot of synthetic chemicals are wasted rather than utilized by crops. This can cause more problems where the soil surface is thin and rocky like Jeju Island in the Republic of Korea. This is because overly used nitrogen fertilizer can be washed into the underground water and pollute it. Thus, it would be important to monitor the nitrogen deficiency of crops in the field to provide the right amount of nitrogen in a timely manner so that nitrogen waste can be limited. To achieve this, the normalized difference vegetation index (NDVI) was used to monitor chlorophyll content, which is tightly associated with nitrogen content in the buckwheat field. The NDVI was calculated with the data obtained by a low-resolution camera mounted on an unmanned aerial vehicle. The results showed that the NDVI can estimate the chlorophyll content of buckwheat. These simple but clear results imply that precision agriculture could be achieved even with a low-resolution camera in a cost-effective manner to reduce the pollution of underground water.

Kenaf (Hibiscus cannabinus L.) is widely used as an important industrial crop. It has the potential to act as a sustainable energy provider in the future, and contains beneficial compounds for medical and therapeutic use. However, there are no clear breeding strategies to increase its biomass or leaf volume. Thus, to attain an increase in these parameters, we examined potential key traits such as stem diameter, plant height, and number of nodes to determine the relationship among them. We hypothesized that it would be easier to reduce the amount of time and labor required for breeding if correlations among these parameters are identified. In this study, we found a strong positive correlation between height and number of nodes (Spearman’s Rho = 0.67, p < 0.001) and number of nodes and stem diameter (Spearman’s Rho = 0.65, p < 0.001), but a relatively low correlation (Spearman’s Rho = 0.34, p < 0.01) between height and stem diameter in the later stages of kenaf growth. We suggest that an efficient breeding strategy could be devised according to the breeding purpose, considering the correlations between various individual traits of kenaf.

A leishmaniose tegumentar é uma doença infecciosa com padrões epidemiológicos de transmissão relacionados a alterações significativas na paisagem, decorrentes principalmente de atividades econômicas. O objetivo deste trabalho foi analisar a disseminação dos casos de leishmaniose tegumentar no estado de Goiás entre os anos de 2001 e de 2020, buscando evidências de formação de agrupamentos regionais. Foram utilizados dados públicos disponíveis no Sistema de Informações de Agravos de Notificação (SINAN) e bases cartográficas disponíveis nas bases do Instituto Brasileiro de Geografia e Estatística (IBGE). Para a avaliação da tendência temporal, a técnica estatística de regressão por joinpoint foi aplicada às taxas estaduais. A fim de reduzir possíveis flutuações aleatórias nas taxas de prevalência em nível municipal, recorreu-se à análise bayesiana global. As taxas ajustadas foram posteriormente aplicadas à equação de Moran, para avaliação de formações dos agrupamentos regionais. A análise de tendência temporal em nível estadual indicou redução de casos no período analisado, com variação percentual anual de -2,8 casos a cada 100.000 habitantes. Os resultados dos índices de Moran evidenciaram a formação de agrupamentos regionais. Tais regiões apresentam grupos de municípios com significativa vulnerabilidade social e exploração econômica voltada a atividades agrícolas e de mineração

The outbreak of COVID 19 has been provoking several problems to the health system around the world. One of the concerning is the crash of the health system due to the increasing demand suddenly. To avoid it, knowing the total number and daily new cases is crucial. In this study, we fitted curves growth models using a Bayesian approach. We extracted information obtained from some countries to build the prior distribution of the model. The total number of cases of the COVID 19 in the state of Goias was analyzed. Results from analysis indicated that the date of the outbreak peak is between 51 and 68 days after the beginning. Moreover, the total number of cases is around 3180 cases. The analysis did not take into consideration possibles changes in government control measures. We hope this study can provide some valuable information to public health management.

The rapid expansion of Uber Technologies, Inc.’s ride-sharing, courier service, and food delivery system and e-hailing applications has been transforming the logistics network and urban mobility around the world. We aimed to evaluate the impact of the Uber system on traffic injury (TI) mortality during its implementation in Brazilian capital cities. A quasiexperimental design of interrupted time series was used. The monthly mortality rates for TI standardized by age were analyzed. The date of availability of the Uber app, specific to each capital, was considered the start date. Data from the Brazilian Mortality Information System and the Brazilian Institute of Geography and Statistics were used. For the data analysis, from an interrupted time-series design, autoregressive integrated moving average (ARIMA) models with a transfer function were fitted. In 92.6% (n = 25) of Brazilian capitals, there was no impact of Uber system implementation, 12 months after the start of its activities, on TI mortality. A reduction in mortality from this cause was observed after the system was implemented in Belo Horizonte and Rio de Janeiro. The impact on TI mortality was progressive and continuous in both. More studies are needed to establish the factors associated with the inequalities observed in the impact of Uber system implementation between different locations and the heterogeneity of effects.