Using climatology to predict the first major summer corn earworm (Lepidoptera: Noctuidae) catch in north central Illinois

One of the largest food production companies in the United States, with sales in the billions of dollars, must closely monitor anything that may affect their vegetable crops. This includes harmful insects, such as the corn earworm (CEW) (Helicoverpa zea), that can reduce sweet corn yields and cause losses of approximately 12 million dollars annually in the Midwest. For this study, a major sweet corn production area located in north central Illinois was used to evaluate CEW moth flight characteristics. The initial major CEW catch (i.e. when 10 or more CEWs were caught in a field trap within a 24 h period) occurs on average around 20 August. However, during the period from 1960 to 2005 the first major catch occurred between 1 August and 16 September. If climatological information can be used to anticipate the initial major CEW arrival, then pest management strategies can be better implemented and field losses reduced. Seven of 13 years with an early first major CEW arrival (1 to 15 August) occurred when accumulated growing degree days (GDDs with a base of 10 °C) were >917 and the number of warm nights (minimum temperatures ≥18.3 °C) was above average (>21 days) from 1 May to 31 July, while 7 of 13 years with a late first major CEW arrival (24 August to 16 September) occurred when accumulated GDDs <853, the number of warm nights was <18 days, and the number of days with an average air flow from the south was <30 between 1 May and 31 July

Production de poussée d'une plaque bidimensionnelle en mouvement de tangage

La présente étude s'inscrit dans le contexte de la propulsion marine instationnaire. Elle relève de l'analyse numérique et expérimentale des conditions de propulsion d'une plaque en mouvement de tangage. L'étude est réalisée à un nombre de Reynolds de 2000 calculé sur la base de la longueur de la plaque et de la vitesse d'entrée de l'écoulement. La plaque oscille sinusoïdalement autour de son axe au tiers de sa longueur. La fréquence réduite d'oscillation considérée comme un paramètre important du problème varie entre 1 et 5. Une procédure de résolution multi-domaine par différences finies des équations de Navier-Stockes est utilisée pour résoudre numériquement le problème. La vitesse est obtenue expérimentalement grâce aux mesures de Vélocimétrie par Images de Particules (PIV) du champ d'écoulement autour d'une plaque de carbone en tangage montée au sein du tunnel hydrodynamique de l'IRENav. L'objet de l'étude est de caractériser le sillage derrière la plaque et d'évaluer la fréquence réduite seuil en vue de quantifier la transition vers un régime marqué par une production de poussée. Les résultats montrent une bonne concordance entre le numérique et l'expérience. L'apparition d'une fréquence réduite d'oscillation seuil au-delà de laquelle le sillage présente le motif d'une allée inversée de Von Kàrmàn est notée. Au-dessus de cette fréquence, les profils moyens de vitesse dans le sillage présentent une transformation. De profils usuels de type sillage avec un déficit de vitesse, on passe en profils de type « jet » avec un excès de vitesse qui sont généralement considérés comme l'empreinte de la production de poussée. Les forces exercées sur la plaque sont extraites des résultats de simulation numérique et on montre que des prévisions fiables pour une éventuelle production de poussée peuvent être déduites d'une analyse expérimentale classique basée sur le théorème de quantité de mouvement, uniquement lorsqu'en plus de la vitesse moyenne, les fluctuations de vitesse et la pression sont prises en compte

Association Between Advanced Maternal Age and Maternal and Neonatal Morbidity: A Cross-Sectional Study on a Spanish Population

Background and objective: Over recent decades, a progressive increase in the maternal age at childbirth has been observed in developed countries, posing a health risk for both women and infants. The aim of this study was to analyze the association between advanced maternal age (AMA) and maternal and neonatal morbidity. Material and methods: A cross-sectional study of 3,315 births was conducted in the north of Spain in 2014. We compared childbirth between women aged 35 years or older, with a reference group of women aged between 24 and 27 years. AMA was categorized based on ordinal ranking into 35-38 years, 39-42 years, and >42 years to estimate a dose-response pattern (the older the age, the greater the risk). As an association measure, crude and adjusted Odds Ratios (OR) were estimated by non-conditional logistic regression and 95% Confidence Intervals (95%CI) were calculated. Results: Repeated abortions were more common among women of AMA in comparison to pregnant women aged 24-27 years (reference group): adjusted OR = 2.68; 95%CI (1.52-4.73). A higher prevalence of gestational diabetes was also observed among women of AMA, reaching statistical significance when restricted to first time mothers: adjusted OR = 8.55; 95%CI (1.12-65.43). In addition, the possibility of an instrumental delivery was multiplied by 1.6 and the possibility of a cesarean by 1.5 among women of AMA, with these results reaching statistical significance, and observing a dose-response pattern. Lastly, there were associations between preeclampsia, preterm birth (<37 weeks) and low birthweight, however without reaching statistical significance. Conclusion: Our results support the association between AMA and suffering repeated abortions. Likewise, being of AMA was associated with a greater risk of suffering from gestational diabetes, especially among primiparous women, as well as being associated with both instrumental deliveries and cesareans among both primiparous and multiparous women

Forces on a pitching plate: An experimental and numerical study

International audienc

Identification of psychiatric disorder subtypes from functional connectivity patterns in resting-state electroencephalography

The understanding and treatment of psychiatric disorders, which are known to be neurobiologically and clinically heterogeneous, could benefit from the data-driven identification of disease subtypes. Here, we report the identification of two clinically relevant subtypes of post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) on the basis of robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the default mode network. We identified the disease subtypes by analysing, via unsupervised and supervised machine learning, the power-envelope-based connectivity of signals reconstructed from high-density resting-state electroencephalography in four datasets of patients with PTSD and MDD, and show that the subtypes are transferable across independent datasets recorded under different conditions. The subtype whose functional connectivity differed most from those of healthy controls was less responsive to psychotherapy treatment for PTSD and failed to respond to an antidepressant medication for MDD. By contrast, both subtypes responded equally well to two different forms of repetitive transcranial magnetic stimulation therapy for MDD. Our data-driven approach may constitute a generalizable solution for connectome-based diagnosis