Modeling of the control logic of a UASS based on coefficient of variation spraying distribution analysis in an indoor flight simulator

Introduction

In the past decade, unmanned aerial spraying systems (UASS) have emerged as an effective crop treatment platform option, competing with other ground vehicle treatments. The development of this platform has provided an effective spraying system that can be used on all crop types and in all weather conditions. However, related research has not been able to develop a UASS that can be operated in windy conditions with a low drift percentage.

Methods

In this research, spraying was simulated in an indoor flight simulator by considering flight speed, altitude, wind speed, wind direction, rotor rotation, interval, spraying pattern, and nozzle type, which were used as the parameters affecting the output value of the coefficient of variation (CV) of spraying. These parameters were referenced as properties that occur in the field, and using machine learning methods, the CV value was used as a dataset to develop a model that can execute pump opening by controlling the flow rate. There are four machine learning methods used, i.e. random forest regression, gradient boosting, ada boost, and automatic relevance determination regression which are compared with simple linear regression and ridge regression as linear regression.

Results

The results revealed that the random forest regression model was the most accurate, with R2 of 0.96 and root mean square error (RMSE) of 0.04%. The developed model was used to simulate spraying with pump opening A, which connects two nozzles in front, and pump opening AB, which connects all four nozzles.

Discussion

Using the logic based on CV value and pesticide quantity, the model can execute the pump opening against the environment and UASS operation.

The water extract of Samultang protects the lipopolysaccharide (LPS)/phorbol 12-myristate 13-acetate (PMA)-induced damage and nitric oxide production of C6 glial cells via down-regulation of NF-kappaB

Samultang has been traditionally used for treatment of ischemic heart and brain diseases in oriental medicine. However, little is known about the mechanism by which Samultang rescues the myocardial and neuronal cells from ischemic damage. This study was designed to evaluate whether the water extract of Samultang may modulate the production of nitric oxide (NO) in LPS and PMA treated-C6 glial cells to protect the cells from NO-induced cytotoxicity. C6 glial cells treated with both LPS and PMA significantly produced a large amount of NO compared to untreated, PMA, or LPS-treated cells. In parallel with NO production, cotreatment of LPS and PMA induced the severe apoptotic death of C6 glial cells. However, Samultang significantly reduced both cell death and NO production by LPS/PMA in a dose-dependent manner. In addition, the modulatory effects of Samultang on LPS/PMA-induced cytotoxicity and NO production could be mimicked by exogenous treatments of N(G)MMA, a nitric oxide synthase (NOS) inhibitor, and pyrrolidine dithiocarbamate (PDTC), a strong NF-kappaB inhibitor. Treatment of C6-glial cells with LPS/PMA induced the transcriptional activation of NF-kappaB, which was markedly inhibited by Samultang. Taken together, we suggest that the protective effects of Samultang against LPS/PMA-induced cytotoxicity may be mediated by the suppression of NO synthesis via down-regulation of NF-kappaB activation.