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Territories of rock-inhabiting fungi: Survival on and alteration of solid air-exposed surfaces
(2018)
Subaerial biofilms that are omnipresent at the interface between all solid substrates and the atmosphere are composed of a unique and widespread group of ascomycetes called rock-inhabiting fungi or microcolonial fungi (MCF), typically in communities with other microorganisms. While subaerial biofilms in toto have important roles in mineral weathering and biodeterioration of materials, methodological approaches to subaerial biofilm communities are diverse and frequently focussed on MCF. Here, we review the historical development of the research methods applied in the field and consider perspectives to increase our understanding of the biofilm-induced changes of solid substrate surfaces.
Emerging infectious diseases arise as a result of novel interactions between populations of hosts and pathogens, and can threaten the health and wellbeing of the entire spectrum of biodiversity. Bees andtheir viruses area case in point. However, detailed knowledge of the ecological factors and evolutionary forces that drive disease emergence in bees and other host–pathogen communities is surprisingly lacking. In this review, we build on the fundamental insight that viruses evolve and adapt over timescales that overlap with host ecology. At the same time, we integrate the role of host community ecology, including community structure and composition, biodiversity loss, and human driven disturbance, all of which represent significant factors in bee virus ecology. Both of these evolutionary and ecological perspectives represent major advances but, in most cases, it remains unclear how evolutionary forces actually operate across different biological scales (e.g., from cell to ecosystem). We present a molecule-to-ecology framework to help address these issues, emphasizing the role of molecular mechanisms as keybottom-up drivers of change at higher ecological scales. We consider the bee–virus system to be an ideal one in which to apply this framework. Unlike many other animal models, bees constitute a well characterized and accessible multispecies assemblage, whose populations and interspecific interactions can be experimentally manipulated and monitored in high resolution across space and time to provide robust tests of prevailing theory.
A combination of different complementary methods is employed to investigate scaling of the molecular dynamics of two different liquid crystals. Each method is sensitive to different kind of fluctuations and provides therefore a different window to look at the molecular dynamics. In detail, broadband dielectric spectroscopy is combined with specific heat spectroscopy and neutron scattering. As systems the nematic liquid crystal E7 and a discotic liquid crystalline pyrene are considered. First of all it was proven that both systems show all peculiarities which are characteristic for glassy dynamics and the glassy state. Especially for the nematic liquid crystal E7 it could be unambiguously shown by a combination of dielectric and specific heat spectroscopy that the tumbling mode is the underlying motional process responsible for glassy dynamics. Dielectric investigations on the discotic liquid crystalline pyrene reveal that at the phase transition from the plastic crystalline to the hexagonal columnar liquid crystalline phase the molecular dynamics changes from a more strong to fragile temperature dependence of the relaxation rates. Moreover a combination of results obtained by specific heat spectroscopy with structural methods allows an estimation of the length scale relevant for the glass transition.
Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification.
Intermediate level waste often contains residual water or other liquids. The liquids can be decomposed due to radiolysis and can also vaporize especially under fire impact. These pressure generating processes are described. One example for the pressure determination inside a closed cask is discussed using two different approaches: analytical and CFD
In present chapter, the potential usage of peroxy-fuels (usually known as organic peroxides) either in technically pure or in a blended form in engine combustion processes are explored. Although as additives (in small quantities <5% to conventional fuels, e.g., diesel, gasoline) peroxy-fuels are well known for many years their commercial applications as a main or primary fuel are not investigated in detail as such except a few. Their thermal instability and energy density demand great care during processing, which restricts their commercial exploitation. However, once the issues with safety are resolved they can be much more advantageously employed than conventional fuels. Some of these advantages are significant amount of fuel saving, reduction in amount of inducted air, or even the complete absence of air, i.e., anaerobic combustion, smaller volume of combustion (chamber), oxygenated fuel quality, and low emissions. An idea to develop the components of an engine operating solely on peroxy-fuels is also introduced. The engine concept is based on single and multiple injectors in a cylinder with special material coating to ensure a temperature-controlled processing.
Automatic vibration-based structural health monitoring has been recognized as a useful alternative or addition to visual inspections or local non-destructive testing performed manually. It is, in particular, suitable for mechanical and aeronautical structures as well as on civil structures, including cultural heritage sites. The main challenge is to provide a robust damage diagnosis from the recorded vibration measurements, for which statistical signal processing methods are required. In this chapter, a damage detection method is presented that compares vibration measurements from the current system to a reference state in a hypothesis test, where data9
related uncertainties are taken into account. The computation of the test statistic on new measurements is straightforward and does not require a separate modal identification. The performance of the method is firstly shown on a steel frame structure in a laboratory experiment. Secondly, the application on real measurements on S101 Bridge is shown during a progressive damage test, where damage was successfully detected for different damage scenarios.