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The control of Spodoptera frugiperda (J. E. Smith, 1797) (Lepidoptera: Noctuidae) in cotton (Gossypium hirsutum L.) has been limited by the rapid development of resistance to insecticides and Bt toxins. The fall armyworm has become increasingly present in cotton fields, becoming a major problem for growers. Therefore, the demand for new and more sustainable tools for managing this pest has increased in recent years. Ideally, the new tool should be compatible with other available control tactics, such as the use of Bt plants, and it should be implemented following IPM principles. In this study, we tested the efficacy of a liquid pheromone formulation for the Fall armyworm control in Bt and conventional cotton varieties in the Brazilian Midwest. Our results showed that the capture of insects in traps has been reduced by 85% in areas treated with pheromone compared to control suggesting high levels of mating suppression. Pheromone treatment also resulted in 70% less damage to cotton reproductive structures when compared to areas not treated with the pheromone in conventional cotton. Moreover, applying pheromone provided an additional benefit to Bt cotton, resulting in 85% damage reduction. Our results show the effectiveness and feasibility of mating disruption with pheromone as an important management tactic for Lepidopterans in cotton. However, no significant differences were found in yield in the conditions tested. These results represent a potential key step toward developing more sustainable tools for pest management in Brazil.

We provide a lower value for the volume of a unit vector field tangent to an antipodally punctured Euclidean sphere $\mathbb{S}^2$ depending on the length of an ellipse determined by the indexes of its singularities. We also exhibit minimizing vector fields $\vec{v}_k$ within each index class and show that they are the only ones that are sharp for the volume. These fields have areas given essentially by the length of ellipses depending just on the indexes in $N$ and $S$.

This study applied the Pearson correlation coefficient and principal component analysis as tools for unsupervised qualitative petroleum system evaluation techniques. A total of 252 oil samples (32 features per sample) representative of two Brazilian sedimentary basins (Recôncavo and Potiguar) were used to classify them according to their respective degrees of maturation and origin. The large initial set of variables comprises data on δ13C composition, saturate, aromatic, polar compound fractions, and the techniques reduced biomarkers to the most important variables, maintaining the global pattern of variance. The results were efficient in discriminating different petroleum systems from lacustrine, marine, and mixing sources, as observed in the studied accumulations from the Lower Cretaceous sediments of the Recôncavo and Potiguar basins. The methodology proved to be very useful to vene better characterize the petroleum systems. This methodology can be applied to analyze a large amount of oil samples, using simple software and spending relatively less time.

ObjectivesOver the past two decades, there has been tremendous growth in research regarding bipolar disorder (BD) among children and adolescents (ie, pediatric BD [PBD]). The primary purpose of this article is to distill the extant literature, dispel myths or exaggerated assertions in the field, and disseminate clinically relevant findings.MethodsAn international group of experts completed a selective review of the literature, emphasizing areas of consensus, identifying limitations and gaps in the literature, and highlighting future directions to mitigate these gaps.ResultsSubstantial, and increasingly international, research has accumulated regarding the phenomenology, differential diagnosis, course, treatment, and neurobiology of PBD. Prior division around the role of irritability and of screening tools in diagnosis has largely abated. Gold-standard pharmacologic trials inform treatment of manic/mixed episodes, whereas fewer data address bipolar depression and maintenance/continuation treatment. Adjunctive psychosocial treatment provides a forum for psychoeducation and targets primarily depressive symptoms. Numerous neurocognitive and neuroimaging studies, and increasing peripheral biomarker studies, largely converge with prior findings from adults with BD.ConclusionsAs data have accumulated and controversy has dissipated, the field has moved past existential questions about PBD toward defining and pursuing pressing clinical and scientific priorities that remain. The overall body of evidence supports the position that perceptions about marked international (US vs elsewhere) and developmental (pediatric vs adult) differences have been overstated, although additional research on these topics is warranted. Traction toward improved outcomes will be supported by continued emphasis on pathophysiology and novel therapeutics.

Objective: To investigate whether poor antidepressant tolerability is associated with functional brain changes in children and adolescents of parents with bipolar I disorder (at-risk youth). Methods: Seventy-three at-risk youth (ages 9-20 years old) who participated in a prospective study and had an available baseline functional magnetic resonance imaging (fMRI) scan were included. Research records were reviewed for the incidence of adverse reactions related to antidepressant exposure during follow-up. The sample was divided among at-risk youth without antidepressant exposure (n=21), at-risk youth with antidepressant exposure and no adverse reaction (n=12), at-risk youth with antidepressant-related adverse reaction (n=21), and healthy controls (n=20). The fMRI task was a continuous performance test with emotional distracters. Region-of-interest mean activation in brain areas of the fronto-limbic emotional circuit was compared among groups. Results: Right amygdala activation in response to emotional distracters significantly differed among groups (F3,66 = 3.1, p = 0.03). At-risk youth with an antidepressant-related adverse reaction had the lowest amygdala activation, while at-risk youth without antidepressant exposure had the highest activation (p = 0.004). Conclusions: Decreased right amygdala activation in response to emotional distracters is associated with experiencing an antidepressant-related adverse reaction in at-risk youth. Further studies to determine whether amygdala activation is a useful biomarker for antidepressant-related adverse events are needed.

Objectives: To prospectively investigate whether baseline clinical characteristics and medication exposure predict development of major depressive disorder or bipolar disorder in offspring of parents with bipolar disorder. Methods: Youth aged 9-20 years with at least one biological parent with bipolar disorder and no prior history of mood or psychotic episodes (n=93) were prospectively evaluated and treated naturalistically during the study. Participants were divided into two groups: converters, defined as those who met DSM-IV criteria for a mood episode during follow-up (n=19); or non-converters (n=74). Logistic regression models were used to investigate associations between baseline clinical variables and medication exposure during follow-up and risk of developing a first mood episode (conversion). Results: Multivariate regression analyses showed that baseline anxiety disorders and subsyndromal mood disorders were associated with increased risk of conversion during follow-up. Adding medication exposure to the multivariate model showed that exposure to antidepressants during follow-up was associated with increased risk of conversion. Conclusions: Caution should be used when treating bipolar offspring with anxiety and/or emerging depressive symptoms using antidepressant agents, given the increased risk of developing a major mood disorder.

Quantum gravity is expected to introduce quantum aspects into the description of reference frames. Here we begin exploring how quantum gravity induced deformations of classical symmetries could modify the transformation laws among reference frames in an effective regime. We invoke the quantum group SU q (2) as a description of deformed spatial rotations and interpret states of a representation of its algebra as describing the relative orientation between two reference frames. This leads to a quantization of one of the Euler angles and to an aspect of agency dependence : space is reconstructed as a collection of fuzzy points, exclusive to each agent, which depends on their choice of reference frame. Each agent can choose only one direction in which points can be sharp, while points in all other directions become fuzzy in a way that depends on this choice. Two agents making different choices will thus observe the same points with different degrees of fuzziness. [ABSTRACT FROM AUTHOR]

Bisphenol A (BPA) is an abundant raw material applied in the production of daily necessities, such as food cans, baby bottles, electronic and medical equipment. Phytotherapeutic use of plant preparations has long been known for multiple target medicinal uses. The species Bauhinia forficata is widely used as hypoglycemic, anti-inflammatory, antioxidant, diuretic and hypocholesterolemic agent. The aim of this study was to verify the effects of B. forficata extract in association with BPA exposure on serological parameters, hepatic antioxidant status and glycogen store capacity in Wistar rats. B. forficata was able to reduce BPA-induced glucose levels; it also prevented the early glucose elevation in control and BPA-exposed animals after the glucose provocative test. This effect was related to the hepatic glycogen content; while BPA reduced the hepatic glycogen deposits B. forficata treatment contributed to minimize it. BPA and B. forficata singly caused elevation in triacylglycerol and VLDL levels and reduction in cholesterol and LDL concentrations. BPA increased hepatic malondialdehyde levels and reduced catalase activity, thus inducing liver oxidative stress. Conversely, B. forficata treatment reduced malondialdehyde concentration without interfering with catalase activity; this antioxidant capacity is attributed to the flavonoids content (e.g., kaempferol and myricetin). Based on these results, we demonstrated that B. forficata commercial extract has hypoglycemic and antioxidant properties capable of minimizing the effects of BPA. However, it should be considered that the consumption of herbal commercial extract must be judicious to avoid deleterious health effects. Keywords: Bisphenol A, Bauhinia forficata, Hepatoprotection, Oxidative stress, Antioxidant capacity

This article aims at performing maritime target classification in SAR images using machine learning (ML) and deep learning (DL) techniques. In particular, the targets of interest are oil platforms and ships located in the Campos Basin, Brazil. Two convolutional neural networks (CNNs), VGG-16 and VGG-19, were used for attribute extraction. The logistic regression (LR), random forest (RF), support vector machine (SVM), k-nearest neighbours (kNN), decision tree (DT), naive Bayes (NB), neural networks (NET), and AdaBoost (ADBST) schemes were considered for classification. The target classification methods were evaluated using polarimetric images obtained from the C-band synthetic aperture radar (SAR) system Sentinel-1. Classifiers are assessed by the accuracy indicator. The LR, SVM, NET, and stacking results indicate better performance, with accuracy ranging from 84.1% to 85.5%. The Kruskal–Wallis test shows a significant difference with the tested classifier, indicating that some classifiers present different accuracy results. The optimizations provide results with more significant accuracy gains, making them competitive with those shown in the literature. There is no exact combination of methods for SAR image classification that will always guarantee the best accuracy. The optimizations performed in this article were for the specific data set of the Campos Basin, and results may change depending on the data set format and the number of images.

Purpose: This research examines the superiority of analysts over random walk models in forecasting the results of publicly-traded Brazilian companies in the short and long term. Originality/value: The literature indicates the uncontested superiority of market analysts because of their temporal and informational advantages. However, recent international studies call for a re-evaluation of this superiority, indicating that, for certain company characteristics, and primarily for long-term estimates, the superiority of analysts is not confirmed. Design/methodology/approach: This work evaluates the profit forecasting of analysts and simple and growth random walk models over the short and long term over 2010-2015 for publicly traded Brazilian companies, using the information available for the period with annual intervals. Findings: The results indicate: 1. the greater forecasting accuracy of simple random walk models compared to the growth random walk models; and 2. the greater forecasting accuracy of random walk models overall, with analyst forecasts only being superior for cases with three months of lag. The evidence suggests the forecasting superiority of the random walk models when compared to the market analysts' forecasts. The results suggest low efficiency of the forecasts of market analysts for the forecast of future results of publicly traded Brazilian companies in the analyzed period. / Objetivo: Esta pesquisa analisa a superioridade dos analistas com relação aos modelos random walk ao preverem os resultados de empresas brasileiras de capital aberto de curto e longo prazos. Originalidade/valor: A literatura indica superioridade irrestrita dos analistas de mercado devido às suas vantagens de tempo e informação. Entretanto, recentes estudos da literatura internacional apontam para a necessidade de uma reavaliação dessa superioridade, indicando que, para determinadas características da empresa, e principalmente para estimativas de longo prazo, a superioridade dos analistas não é confirmada. Design /metodologia/abordagem: Este trabalho avalia as previsões de lucro dos analistas e dos modelos random walk, simples e com crescimento, de curto e longo prazos, no período de 2010 a 2015 para as empresas brasileiras de capital aberto, utilizando dados com periodicidade anual. Resultados: Os resultados indicam: 1. maior acurácia de previsão para os modelos random walk simples quando comparados com os modelos de random walk com crescimento; 2. para a amostra total, nota-se maior acurácia da previsão dos modelos random walk, com superioridade dos analistas apenas para previsões com três meses de defasagem. A evidência sugere a superioridade de previsão dos modelos random walk quando comparados às previsões dos analistas de mercado. Os resultados sugerem baixa eficiência das previsões dos analistas de mercado para a previsão de resultado futuro das empresas brasileiras de capital aberto no período analisado.