Holcus bacterial spot of Zea mays and Holcus species

A bacterial leaf spot disease on corn (Z ea mays L.) has been under observation in Iowa since 1916. In the fall\u27 of 1924, it was quite prevalent on Zea mays, and on volunteer sorghum (Holcus sorghum L.) growing together near Ames, Iowa. Further examination revealed the presence of a somewhat similar leaf spot on Holcus sorghum, sudan grass [H. s01\u27ghurn val\u27. sudanensis (Piper) Hitchc.]\u27 Johnson grass (H. halepensis L.) and pearl millet [Pennisetum glancttm (L.) R.Br.]. \u27fhese observations led to a cultural study of the causal agents and a survey of the literature on bacterial diseases of these hosts

Metabolic consequences of gestational cannabinoid exposure

Up to 20% of pregnant women ages 18–24 consume cannabis during pregnancy. Moreover, clinical studies indicate that cannabis consumption during pregnancy leads to fetal growth restriction (FGR), which is associated with an increased risk of obesity, type II diabetes (T2D), and cardiovascular disease in the offspring. This is of great concern considering that the concentration of D9- tetrahydrocannabinol (D9-THC), a major psychoactive component of cannabis, has doubled over the last decade and can readily cross the placenta and enter fetal circulation, with the potential to negatively impact fetal development via the endocannabinoid (eCB) system. Cannabis exposure in utero could also lead to FGR via placental insufficiency. In this review, we aim to examine current pre-clinical and clinical findings on the direct effects of exposure to cannabis and its constituents on fetal development as well as indirect effects, namely placental insufficiency, on postnatal metabolic diseases

Two Notions Of Safety

Timothy Williamson (1992, 224–5) and Ernest Sosa (1996) have ar- gued that knowledge requires one to be safe from error. Something is said to be safe from happening iff it does not happen at “close” worlds. I expand here on a puzzle noted by John Hawthorne (2004, 56n) that suggests the need for two notions of closeness. Counterfac- tual closeness is a matter of what could in fact have happened, given the specific circumstances at hand. The notion is involved in the semantics for counterfactuals and is the one epistemologists have typically assumed. Normalized closeness is rather a matter of what could typically have happened, that is, what would go on in a class of normal alternatives to actuality, irrespectively of whether or not they could have happened in the circumstances at hand

Change point detection in social networksCritical review with experiments

© 2018 Elsevier Inc. Change point detection in social networks is an important element in developing the understanding of dynamic systems. This complex and growing area of research has no clear guidelines on what methods to use or in which circumstances. This paper critically discusses several possible network metrics to be used for a change point detection problem and conducts an experimental, comparative analysis using the Enron and MIT networks. Bayesian change point detection analysis is conducted on different global graph metrics (Size, Density, Average Clustering Coefficient, Average Shortest Path) as well as metrics derived from the Hierarchical and Block models (Entropy, Edge Probability, No. of Communities, Hierarchy Level Membership). The results produced the posterior probability of a change point at weekly time intervals that were analysed against ground truth change points using precision and recall measures. Results suggest that computationally heavy generative models offer only slightly better results compared to some of the global graph metrics. The simplest metrics used in the experiments, i.e. nodes and links numbers, are the recommended choice for detecting overall structural changes

Fast track children's hearing pilot: final report of the evaluation of the pilot

This report presents key findings of the evaluation of the Fast Track children’s hearings pilot in Scotland1. The research was undertaken by staff at the Universities of Glasgow, Stirling and Strathclyde between February 2003 and January 2005

Exposure to Δ9-tetrahydrocannabinol during rat pregnancy leads to impaired cardiac dysfunction in postnatal life

Background: Cannabis use in pregnancy leads to fetal growth restriction (FGR), but the long-term effects on cardiac function in the offspring are unknown, despite the fact that fetal growth deficits are associated with an increased risk of developing postnatal cardiovascular disease. We hypothesize that maternal exposure to Δ9-tetrahydrocannabinol (Δ9-THC) during pregnancy will impair fetal development, leading to cardiac dysfunction in the offspring. Methods: Pregnant Wistar rats were randomly selected and administered 3 mg/kg of Δ9-THC or saline as a vehicle daily via intraperitoneal injection from gestational days 6 to 22, followed by echocardiogram analysis of cardiac function on offspring at postnatal days 1 and 21. Heart tissue was harvested from the offspring at 3 weeks for molecular analysis of cardiac remodelling. Results: Exposure to Δ9-THC during pregnancy led to FGR with a significant decrease in heart-to-body weight ratios at birth. By 3 weeks, pups exhibited catch-up growth associated with significantly greater left ventricle anterior wall thickness with a decrease in cardiac output. Moreover, these Δ9-THC-exposed offsprings exhibited increased expression of collagen I and III, decreased matrix metallopeptidase-2 expression, and increased inactivation of glycogen synthase kinase-3β, all associated with cardiac remodelling. Conclusions: Collectively, these data suggest that Δ9-THC-exposed FGR offspring undergo postnatal catch-up growth concomitant with cardiac remodelling and impaired cardiac function early in life. Impact: To date, the long-term effects of perinatal Δ9-THC (the main psychoactive component) exposure on the cardiac function in the offspring remain unknown.We demonstrated, for the first time, that exposure to Δ9-THC alone during rat pregnancy results in significantly smaller hearts relative to body weight.These Δ9-THC-exposed offsprings exhibited postnatal catch-up growth concomitant with cardiac remodelling and impaired cardiac function.Given the increased popularity of cannabis use in pregnancy along with rising Δ9-THC concentrations, this study, for the first time, identifies the risk of perinatal Δ9-THC exposure on early postnatal cardiovascular health

Dermoscopic dark corner artifacts removal: Friend or foe?

Background and Objectives: One of the more significant obstacles in classification of skin cancer is the presence of artifacts. This paper investigates the effect of dark corner artifacts, which result from the use of dermoscopes, on the performance of a deep learning binary classification task. Previous research attempted to remove and inpaint dark corner artifacts, with the intention of creating an ideal condition for models. However, such research has been shown to be inconclusive due to a lack of available datasets with corresponding labels for dark corner artifact cases. Methods: To address these issues, we label 10,250 skin lesion images from publicly available datasets and introduce a balanced dataset with an equal number of melanoma and non-melanoma cases. The training set comprises 6126 images without artifacts, and the testing set comprises 4124 images with dark corner artifacts. We conduct three experiments to provide new understanding on the effects of dark corner artifacts, including inpainted and synthetically generated examples, on a deep learning method. Results: Our results suggest that introducing synthetic dark corner artifacts which have been superimposed onto the training set improved model performance, particularly in terms of the true negative rate. This indicates that deep learning learnt to ignore dark corner artifacts, rather than treating it as melanoma, when dark corner artifacts were introduced into the training set. Further, we propose a new approach to quantifying heatmaps indicating network focus using a root mean square measure of the brightness intensity in the different regions of the heatmaps. Conclusions: The proposed artifact methods can be used in future experiments to help alleviate possible impacts on model performance. Additionally, the newly proposed heatmap quantification analysis will help to better understand the relationships between heatmap results and other model performance metrics

The effects of pseudo magnetic fields in molecular spectra and scattering

Pseudo magnetic fields appear in the Born-Oppenheimer method for molecules when conical intersections or electronic angular momenta are taken into account. These fields are not real magnetic fields but they have the same mathematical properties and can lead to real observable effects in the dynamics of molecules. A general vector potential (gauge theory) approach for including these field effects in the Born-Oppenheimer method is introduced and applied to H + O{sub 2} scattering and the vibrational spectrum of Na{sub 3}(X) for zero total angular momentum (J = 0). The scattering results for HO{sub 2} show significant shifts in the resonance energies and lifetimes due to a magnetic solenoid type field originating from the C{sub 2v} conical intersection in HO{sub 2}. Significant changes in the state-to-state transition probabilities are also observed. The non-degenerate A{sub 1} and A{sub 2} vibrational spectra of Na{sub 3}(X) show significant shifts in the energy levels due to a magnetic solenoid type field originating from the D{sub 3h} conical intersection in Na{sub 3}. These two examples show that the effects of pseudo magnetic fields can be significant and in many cases they must be included in order to obtain agreement between theory and experiment. The newly developed gauge theory techniques for treating pseudo magnetic fields are also relevant for including the effects of real magnetic fields