Modelling the fate of persistent organic pollutants (POPs) in the North Sea system

The environmental fate of selected persistent organic pollutants (POPs) in the North Sea system is modelled with a high resolution Fate and Transport Ocean Model (FANTOM) that uses hydrodynamic model output from the Hamburg Shelf Ocean Model (HAMSOM). Large amounts of POPs enter the North Sea from the surrounding highly populated, industrialised and agricultural countries. Major pathways to the North Sea are atmospheric deposition and river inputs, with additional contributions coming from bottom sediments and adjacent seas. The model domain covers the entire North Sea region, extending northward as far as the Shetland Islands, and includes adjacent basins such as the Skagerrak, Kattegat, and the westernmost part of the Baltic Sea. Model resolution (for both models) is 1.5’ latitude x 2.5’ longitude (approximately 3 km horizontal resolution) with 30 vertical levels. The POP model also has 20 sediment layers. Important model processes controlling the fate of POPs in the North Sea system are discussed. Results focus on Lindane gamma- HCH or gamma-hexachlorocyclohexane) and PCB 153.

Evidence reasoning for event inference in smart transport video surveillance

In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.

Battery modelling methods for electric vehicles - a review

Electric vehicles (EVs) and hybrid electric vehicles (HEVs) are rapidly gaining popularity as a means of de-carbonization in the transport sector in tackling sustainable energy supply and environment pollution problems. To build a proper battery model is essential in predicting battery behaviour under various operating conditions for avoiding unsafe battery operations and developing proper controlling algorithms and maintenance strategies. This paper presents a comprehensive review of battery modelling methods. In particular, the mechanism and characteristics of Li-ion batteries are presented, and different modelling methods are discussed. Considering that equivalent electric circuit models (EECMs) are the most widely used, a detailed analysis of the modelling procedure is presented.

An R-matrix approach for plasma modelling and the interpretation of astrophysical observation

Over the last decade an Auburn-Rollins-Strathclyde consortium has developed several suites of parallel R-matrix codes [1, 2, 3] that can meet the fundamental data needs required for the interpretation of astrophysical observation and/or plasma experiments. Traditionally our collisional work on light fusion-related atoms has been focused towards spectroscopy and impurity transport for magnetically confined fusion devices. Our approach has been to provide a comprehensive data set for the excitation/ionization for every ion stage of a particular element. As we progress towards a burning fusion plasma, there is a demand for the collisional processes involving tungsten, which has required a revitalization of the relativistic R-matrix approach. The implementation of these codes on massively parallel supercomputers has facilitated the progression to models involving thousands of levels in the close-coupling expansion required by the open d and f sub-shell systems of mid Z tungsten. This work also complements the electron-impact excitation of Fe-Peak elements required by astrophysics, in particular the near neutral species, which offer similar atomic structure challenges. Although electron-impact excitation work is our primary focus in terms of fusion application, the single photon photoionisation codes are also being developed in tandem, and benefit greatly from this ongoing work.

Insight into determinants of substrate binding and transport in a multidrug efflux protein

Multidrug resistance arising from the activity of integral membrane transporter proteins presents a global public health threat. In bacteria such as Escherichia coli, transporter proteins belonging to the major facilitator superfamily make a considerable contribution to multidrug resistance by catalysing efflux of myriad structurally and chemically different antimicrobial compounds. Despite their clinical relevance, questions pertaining to mechanistic details of how these promiscuous proteins function remain outstanding, and the role(s) played by individual amino acid residues in recognition, binding and subsequent transport of different antimicrobial substrates by multidrug efflux members of the major facilitator superfamily requires illumination. Using in silico homology modelling, molecular docking and mutagenesis studies in combination with substrate binding and transport assays, we identified several amino acid residues that play important roles in antimicrobial substrate recognition, binding and transport by Escherichia coli MdtM, a representative multidrug efflux protein of the major facilitator superfamily. Furthermore, our studies suggested that 'aromatic clamps' formed by tyrosine and phenylalanine residues located within the substrate binding pocket of MdtM may be important for antimicrobial substrate recognition and transport by the protein. Such 'clamps' may be a structurally and functionally important feature of all major facilitator multidrug efflux proteins.