Diferenças na infestação de Aphis gossypii em plantas de algodoeiro cultivar 'IAC-RM3' tratadas com reguladores de crescimento

We have studied the effect of application of growth regulators, (2-chloroethyl) trimethylammonium chloride (CCC), N,N-dimethylaminosuccinamic acid (SADH), gibberellic acid (GA3) and 3-indoleacetic acid (IAA) on cotton, Gossypium hirsutum L. cv. 'IAC-RM3', in relation to atack of Aphis gossypii Glover, 1876, under greenhouse conditions. Two determinations of infestation levels of the aphids showed differences in degree of infestation among treatments. CCC treated plants showed increasing in aphid colonization in relation to GA3 at 100 ppm treated plants. The application of SADH at 4000 ppm also showed a tendency of increasing aphid colonization in relation to treated plants with GA3 at 100 ppm. Probably growth retardants promote differences in the water status of hostplant; and the aphids preferences to that plants suggest that the increase in the osmotic potential promotes better rates of aphid feeding than GA3 treated plants. In treated plants with GA3 at 100 ppm the infestation decreased, there was water stress during the warmer time of the day and a probable decreasing in the osmotic potential.Estudou-se a influência da aplicação de reguladores de crescimento (CCC, SADH, GA3 e IAA) em algodoeiro, Gossypium hirsutum L. cv. 'IAC-RM3', na infestação de Aphis gossypii Glover, 1876; em condições de casa de vegetação. A realização de duas determinações no nível de infestação dos afídios, evidenciou que plantas tratadas com CCC mostram níveis superiores de infestação com relação às tratadas com GA3 a 100 ppm; sendo que a aplicação de SADH a 4000 ppm também promoveu uma tendência de maior infestação com relação ao GA3 a 100 ppm. Estes resultados parecem revelar que os retardadores de crescimento promovem um equilíbrio hídrico interno nas plantas mais favorável, mantendo o potencial osmótico mais elevado e possibilitando uma melhor alimentação do afídio. Plantas tratadas com GAg a 100 ppm parecem sofrer maiores déficits hídricos, não favorecendo o estabelecimento das colônias, nas condições estudadas

N-Beats as an EHG Signal Forecasting Method for Labour Prediction in Full Term Pregnancy

The early prediction of onset labour is critical for avoiding the risk of death due to pregnancy delay. Low-income countries often struggle to deliver timely service to pregnant women due to a lack of infrastructure and healthcare facilities, resulting in pregnancy complications and, eventually, death. In this regard, several artificial-intelligence-based methods have been proposed based on the detection of contractions using electrohysterogram (EHG) signals. However, the forecasting of pregnancy contractions based on real-time EHG signals is a challenging task. This study proposes a novel model based on neural basis expansion analysis for interpretable time series (N-BEATS) which predicts labour based on EHG forecasting and contraction classification over a given time horizon. The publicly available TPEHG database of Physiobank was exploited in order to train and test the model, where signals from full-term pregnant women and signals recorded after 26 weeks of gestation were collected. For these signals, the 30 most commonly used classification parameters in the literature were calculated, and principal component analysis (PCA) was utilized to select the 15 most representative parameters (all the domains combined). The results show that neural basis expansion analysis for interpretable time series (N-BEATS) forecasting can forecast EHG signals through training after few iterations. Similarly, the forecasting signal’s duration is determined by the length of the recordings. We then deployed XG-Boost, which achieved the classification accuracy of 99 percent, outperforming the state-of-the-art approaches using a number of classification features greater than or equal to 1