Extending Seqenv: a taxa-centric approach to environmental annotations of 16S rDNA sequences

Understanding how the environment selects a given taxon and the diversity patterns that emerge as a result of environmental filtering can dramatically improve our ability to analyse any environment in depth as well as advancing our knowledge on how the response of different taxa can impact each other and ecosystem functions. Most of the work investigating microbial biogeography has been site-specific, and logical environmental factors, rather than geographical location, may be more influential on microbial diversity. SEQenv, a novel pipeline aiming to provide environmental annotations of sequences emerged to provide a consistent description of the environmental niches using the ENVO ontology. While the pipeline provides a list of environmental terms on the basis of sample datasets and, therefore, the annotations obtained are at the dataset level, it lacks a taxa centric approach to environmental annotation. The work here describes an extension developed to enhance the SEQenv pipeline, which provided the means to directly generate environmental annotations for taxa under different contexts. 16S rDNA amplicon datasets belonging to distinct biomes were selected to illustrate the applicability of the extended SEQenv pipeline. A literature survey of the results demonstrates the immense importance of sequence level environmental annotations by illustrating the distribution of both taxa across environments as well as the various environmental sources of a specific taxon. Significantly enhancing the SEQenv pipeline in the process, this information would be valuable to any biologist seeking to understand the various taxa present in the habitat and the environment they originated from, enabling a more thorough analysis of which lineages are abundant in certain habitats and the recovery of patterns in taxon distribution across different habitats and environmental gradients

Measurement and Prediction of the Viscosity of Hydrocarbon Mixtures and Crude Oils

Crude oil is a complex mixture of hydrocarbons whose physical properties vary significantly with its composition, temperature and pressure. Viscosity is a particularly important property influencing the flow of oil in hydrocarbon reservoirs and its displacement by water and other fluids during production processes. The modelling and optimisation of such processes would be greatly aided by models which predict the viscosity of crude oils at (high) reservoir temperatures and pressures (HTHP), ideally from a knowledge of the oil composition. This research has involved making accurate HTHP viscosity measurements on a range of hydrocarbon systems and using these to evaluate the ability of an effective hard-sphere model to predict the data with minimal calibration. In the first phase, the viscosity and density of a range of pure hydrocarbons, representative of those found in crude oils, and their mixtures, were measured at temperatures and pressures covering typical reservoir conditions (up to 448.15 K and 135 MPa). The vibrating wire technique was used for viscosity in conjunction with a vibrating U-tube densimeter. The ability of the Dymond-Assael (DA) effective hard-sphere model to correlate and predict the viscosity of both the pure components and the complex mixtures was investigated. Agreement for pure components was within ± 5 % whereas for the mixtures this ranged from ± 5% to ± 25 % depending on the complexity. The same thermophysical properties were determined for two North Sea crude oil samples at temperatures ranging from (298.15 to 448.15) K and pressures up to 135 MPa. The effect of adding an alkane mixture diluent was also investigated. It was found that by treating the crude oils as effective single hydrocarbon components, the Dymond-Assael model could correlate their viscosity to within the experimental uncertainty and that of the diluted crudes to within ±10%. The overall study gives encouragement that a limited number of calibration viscosity/density measurements on a crude oil should enable prediction of its viscosity over a wide range of temperatures and pressures and enable viscosity changes to be predicted when crude oils are mixed with components whose DA parameters are known

Performance Enhancement of Multiuser Time Reversal UWB Communication System

UWB communication is a recent research area for indoor propagation channels. Time Reversal (TR) communication in UWB has shown promising results for improving the system performance. In multiuser environment, the system performance is significantly degraded due to the interference among different users. TR reduces the interference caused by multiusers due to its spatial focusing property. The performance of a multiuser TR communication system is further improved if the TR filter is modified. In this paper, multiuser TR in UWB communication is investigated using simple TR filter and a modified TR filter with circular shift operation. The concept of circular shift in TR is analytically studied. Thereafter, the channel impulse responses (CIR) of a typical indoor laboratory environment are measured. The measured CIRs are used to analyze the received signal peak power and signal to interference ratio (SIR) with and without performing the circular shift operation in a multiuser environment