Determining the contribution of volcanic ash and boundary layer aerosol in backscatter lidar returns: a three‐component atmosphere approach

A solution of the lidar equation is discussed, that permits combining backscatter and depolarization measurements to quantitatively distinguish two different aerosol types with different depolarization properties. The method has been successfully applied to simultaneous observations of volcanic ash and boundary layer aerosol obtained in Exeter, United Kingdom, on 16 and 18 April 2010, permitting the contribution of the two aerosols to be quantified separately. First a subset of the atmospheric profiles is used where the two aerosol types belong to clearly distinguished layers, for the purpose of characterizing the ash in terms of lidar ratio and depolarization. These quantities are then used in a three‐component atmosphere solution scheme of the lidar equation applied to the full data set, in order to compute the optical properties of both aerosol types separately. On 16 April a thin ash layer, 100–400 m deep, is observed (average and maximum estimated ash optical depth: 0.11 and 0.2); it descends from ∼2800 to ∼1400 m altitude over a 6‐hour period. On 18 April a double ash layer, ∼400 m deep, is observed just above the morning boundary layer (average and maximum estimated ash optical depth: 0.19 and 0.27). In the afternoon the ash is entrained into the boundary layer, and the latter reaches a depth of ∼1800 m (average and maximum estimated ash optical depth: 0.1 and 0.15). An additional ash layer, with a very small optical depth, was observed on 18 April at an altitude of 3500–4000 m. By converting the lidar optical measurements using estimates of volcanic ash specific extinction, derived from other works, the observations seem to suggest approximate peak ash concentrations of ∼1500 and ∼1000 mg/m3,respectively, on the two observations dates.

Epidemic K-Means clustering

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. This work proposes a fully decentralised algorithm (Epidemic K-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art distributed K-Means algorithms based on sampling methods. The experimental analysis confirms that the proposed algorithm is a practical and accurate distributed K-Means implementation for networked systems of very large and extreme scale.

Global trajectory optimisation: can we prune the solution space when considering deep space manoeuvres?

This document contains a report on the work done under the ESA/Ariadna study 06/4101 on the global optimization of space trajectories with multiple gravity assist (GA) and deep space manoeuvres (DSM). The study was performed by a joint team of scientists from the University of Reading and the University of Glasgow.

Fault tolerant decentralised K-Means clustering for asynchronous large-scale networks

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale.

A rare case of solution and solid state inter-conversion of two copper(II) dimers and a copper(II) chain

Three Cu(II)-azido complexes of formula [Cu2L2(N-3)(2)] (1), [Cu2L2(N-3)(2)]center dot H2O (2) and [CuL(N-3)](n) (3) have been synthesized using the same tridentate Schiff base ligand HL (2-[(3-methylaminopropylimino)-methyl]-phenol), the condensation product of N-methyl-1,3-propanediamine and salicyldehyde). Compounds 1 and 2 are basal-apical mu-1,1 double azido bridged dimers. The dimeric structure of 1 is centro-symmetric but that of 2 is non-centrommetric. Compound 3 is a mu-1,1 single azido bridged 1D chain. The three complexes interconvert in solution and can be obtained in pure form by carefully controlling the synthetic conditions. Compound 2 undergoes an irreversible transformation to 1 upon dehydration in the solid state. The magnetic properties of compounds 1 and 2 show the presence of weak antiferromagnetic exchange interactions mediated by the double 1,1-N-3 azido bridges (J = -2.59(4) and -0.10(1) cm-(1), respectively). The single 1,1-N-3 bridge in compound 3 mediates a negligible exchange interaction.

Homoleptic copper(II) and copper(I) complexes of 5,6-dihydro-5,6-epoxy-1,10-phenanthroline. Six-coordinate copper(I) in solution

Reaction of 5,6-dihydro-5,6-epoxy-1,10-phenanthroline (L) with Cu(ClO(4))(2)center dot 6H(2)O in methanol in 3:1 M ratio at room temperature yields light green [CuL(3)](ClO(4))(2)center dot H(2)O (1). The X-ray crystal structure of the hemi acetonitrile solvate [CuL(3)](ClO(4))(2)center dot 0.5CH(3)CN has been determined which shows Jahn-Teller distortion in the CuN(6) core present in the cation [CuL(3)](2+). Complex 1 gives an axial EPR spectrum in acetonitrile-toluene glass with g(parallel to) = 2.262 (A(parallel to) = 169 x 10 (4) cm (1)) and g(perpendicular to) = 2.069. The Cu(II/I) potential in 1 in CH(2)Cl(2) at a glassy carbon electrode is 0.32 V versus NHE. This potential does not change with the addition of extra L in the medium implicating generation of a six-coordinate copper(I) species [CuL(3)](+) in solution. B3LYP/LanL2DZ calculations show that the six Cu-N bond distances in [CuL(3)](+) are 2.33, 2.25, 2.32, 2.25, 2.28 and 2.25 angstrom while the ideal Cu(I)-N bond length in a symmetric Cu(I)N(6) moiety is estimated as 2.25 angstrom. Reaction of L with Cu(CH(3)CN)(4)ClO(4) in dehydrated methanol at room temperature even in 4:1 M proportion yields [CuL(2)]ClO(4) (2). Its (1)H NMR spectrum indicates that the metal in [CuL(2)](+) is tetrahedral. The Cu(II/I) potential in 2 is found to be 0.68 V versus NHE in CH(2)Cl(2) at a glassy carbon electrode. In presence of excess L, 2 yields the cyclic voltammogram of 1. From (1)H NMR titration, the free energy of binding of L to [CuL(2)](+) to produce [CuL(3)](+) in CD(2)Cl(2) at 298 K is estimated as -11.7 (+/-0.2) kJ mol (1).