Oviposition Preference of Botanophila Flies (Diptera: Anthomyiidae) towards Stroma Size of Epichloë (Hypocreales: Clavicipitaceae) Hosts

Stromata of grass-infecting fungi from the genus Epichloë (Clavicipitaceae: Ascomycota) serve as a food source and egg-laying surface for flies of genus Botanophila (Diptera: Anthomyiidae). Larger stromata should make it possible for flies to lay more eggs and provide more food to offspring. This hypothesis was tested in four different grass-fungus associations that occur in central Poland. In two of these associations, Epichloë bromicola on Elymus repens and Epichloë typhina on Puccinellia distans, flies showed a preference for longer stromata, and egg density on these stromata was significantly higher than in the other two associations. A negative correlation between egg density and offspring success was observed in only one association, E. bromicola-El. repens. However, offspring success in this association did not differ significantly from offspring success in associations with lower egg density on the stromata, in which flies showed no preference for the stroma length. Long-term observations (2000-2010) of fly-fungus interaction in the E. typhina-P. distans association showed that fly preference toward stroma length may vary over time but with no clear tendency. No significant correlations were found between the larval density on a stroma and either larval weight or mortality. The results of the current study question our assumptions that egg laying depends on the stroma length and the fate of eggs laid (i.e., their hatching success and the condition, in terms of weight and survival, of the larvae) on egg density. It is possible that flies choose stromata based on attributes other than siz

Cell surface properties of Pseudomonas stutzeri in the process of diesel oil biodegradation

Pseudomonas stutzeri, isolated from crude oil-contaminated soil, was used to degrade diesel oil. Of three surfactants, 120 mg rhamnolipids 1−1 significantly increased degradation of diesel oil giving 88% loss after 14 days compared to 54% loss without the surfactant. The system with rhamnolipids was characterised by relatively high particle homogeneity. However, the addition of saponins to diesel oil caused the cells to aggregate (the polydispersity index: 0.542) and the biodegradation of diesel oil was only 46%. The cell yield was 0.22 g l−1

Uptake of Hydrocarbon by Pseudomonas fluorescens (P1) and Pseudomonas putida (K1) Strains in the Presence of Surfactants: A Cell Surface Modification

The objective of this research was the evaluation of the effects of exogenous added surfactants on hydrocarbon biodegradation and on cell surface properties. Crude oil hydrocarbons are often difficult to remove from the environment because of their insolubility in water. The addition of surfactants enhances the removal of hydrocarbons by raising the solubility of these compounds. These surfactants cause them to become more vulnerable to degradation, thereby facilitating transportation across the cell membrane. The obtained results showed that the microorganism consortia of bacteria are useful biological agents within environmental bioremediation. The most effective amongst all, as regards biodegradation, were the consortia of Pseudomonas spp. and Bacillus spp. strains. The results indicated that the natural surfactants (rhamnolipides and saponins) are more effective surfactants in hydrocarbon biodegradation as compared to Triton X-100. The addition of natural surfactants enhanced the removal of hydrocarbon and diesel oil from the environment. Very promising was the use of saponins as a surfactant in hydrocarbon biodegradation. This surfactant significantly increases the organic compound biodegradation. In the case of those surfactants that could be easily adsorbed on cells of strains (e.g., rhamnolipides), a change of hydrophobicity to ca. 30–40% was noted. As the final result, an increase in hydrocarbon biodegradation was observed

Modification of cell surface properties of Pseudomonas alcaligenes S22 during hydrocarbon biodegradation

Biodegradation of water insoluble hydrocarbons can be significantly increased by the addition of natural surfactants one. Very promising option is the use of saponins. The obtained results indicated that in this system, after 21 days, 92% biodegradation of diesel oil could be achieved using Pseudomonas alcaligenes. No positive effect on the biodegradation process was observed using synthetic surfactant Triton X-100. The kind of carbon source influences the cell surface properties of microorganisms. Modification of the surface cell could be observed by control of the sedimentation profile. This analytical method is a new approach in microbiological analysis

Design and construction of the MicroBooNE detector

This paper describes the design and construction of the MicroBooNE liquid argon time projection chamber and associated systems. MicroBooNE is the first phase of the Short Baseline Neutrino program, located at Fermilab, and will utilize the capabilities of liquid argon detectors to examine a rich assortment of physics topics. In this document details of design specifications, assembly procedures, and acceptance tests are reported

Oviposition preference of Botanophila flies (Diptera: Anthomyiidae) towards stroma size of Epichloë (Hypocreales: Clavicipitacea ) hosts

ISSN:0013-8746ISSN:1938-290

Generating Facial Expressions Associated with Text

How will you react to the next post that you are going to read? In this paper we propose a learning system that is able to artificially alter the picture of a face in order to generate the emotion that is associated with a given input text. The face generation procedure is function of further information about the considered person, either given (topics of interest) or automatically estimated from the provided picture (age, sex). In particular, two Convolutional Networks are trained to predict age and sex, while two other Recurrent Neural Network-based models predict the topic and the dominant emotion in the input text. First Order Logic (FOL)-based functions are introduced to mix the outcome of the four neural models and to decide which emotion to generate, following the theory of T-Norms. Finally, the same theory is exploited to build a neural generative model of facial expressions, that is used create the final face. Experimental results are performed to assess the quality of the information extraction process and to show the outcome of the generative network