Greek, Latin, and the Indian Civil Service

This is a slightly revised version of an article first published in the Cambridge Classical Journal, vol. 51 (2005), pp. 35-71.

Are the debates on water privatization missing the point? Experiences from Africa, Asia and Latin America

This paper has two principal aims: first, to unravel some of the arguments mobilized in the controversial privatization debate, and second, to review the scale and nature of private sector provision of water and sanitation in Africa, Asia and Latin America. Despite being vigorously promoted in the policy arena and having been implemented in several countries in the South in the 1990s, privatization has achieved neither the scale nor benefits anticipated. In particular, the paper is pessimistic about the role that privatization can play in achieving the Millennium Development Goals of halving the number of people without access to water and sanitation by 2015. This is not because of some inherent contradiction between private profits and the public good, but because neither publicly nor privately operated utilities are well suited to serving the majority of low-income households with inadequate water and sanitation, and because many of the barriers to service provision in poor settlements can persist whether water and sanitation utilities are publicly or privately operated. This is not to say that well-governed localities should not choose to involve private companies in water and sanitation provision, but it does imply that there is no justification for international agencies and agreements to actively promote greater private sector participation on the grounds that it can significantly reduce deficiencies in water and sanitation services in the South.

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

Effect of a methyl group on the spontaneous resolution of a square-pyramidal coordination compound: crystal packing and conglomerate formation

Reaction of [Cu(pic)2]·2H2O (where pic stands for 2-picolinato) with 2-({[2-(dimethylamino)ethyl]amino}methyl)phenol (HL1) produces the square-pyramidal complex [CuL1(pic)] (1), which crystallizes as a conglomerate (namely a mixture of optically pure crystals) in the Sohncke space group P212121. The use of the methylated ligand at the benzylic position, i.e. (±)-2-(1-{[2-(dimethylamino)ethyl]amino}ethyl)phenol (HL2), yields the analogous five-coordinate complex [CuL2(pic)] (2) that crystallizes as a true racemate (namely the crystals contain both enantiomers) in the centrosymmetric space group P21/c. Density functional theory (DFT) calculations indicate that the presence of the methyl group indeed leads to a distinct crystallization behaviour, not only by intramolecular steric effects, but also because its involvement in non-covalent C–H···π and hydrophobic intermolecular contacts appears to be an important factor contributing to the crystal-lattice (stabilizing) energy of 2

Alverata: Latin, Greek and Cyrillic typeface

Alverata: a typeface design for Europe This typeface is a response to the extraordinarily diverse forms of letters of the Latin alphabet in manuscripts and inscriptions in the Romanesque period (c. 1000–1200). While the Romanesque did provide inspiration for architectural lettering in the nineteenth century, these letterforms have not until now been systematically considered and redrawn as a working typeface. The defining characteristic of the Romanesque letterform is variety: within an individual inscription or written text, letters such as A, C, E and G might appear with different forms at each appearance. Some of these forms relate to earlier Roman inscriptional forms and are therefore familiar to us, but others are highly geometric and resemble insular and uncial forms. The research underlying the typeface involved the collection of a large number of references for lettering of this period, from library research and direct on-site ivestigation. This investigation traced the wide dispersal of the Romanesque lettering tradition across the whole of Europe. The variety of letter widths and weights encountered, as well as variant shapes for individual letters, offered both direct models and stylistic inspiration for the characters and for the widths and weight variants of the typeface. The ability of the OpenType format to handle multiple stylistic variants of any one character has been exploited to reflect the multiplicity of forms available to stonecutters and scribes of the period. To make a typeface that functions in a contemporary environment, a lower case has been added, and formal and informal variants supported. The pan-European nature of the Romanesque design tradition has inspired an pan-European approach to the character set of the typeface, allowing for text composition in all European languages, and the typeface has been extended into Greek and Cyrillic, so that the broadest representation of European languages can be achieved.

Sparse probability density function estimation using the minimum integrated square error

We develop a new sparse kernel density estimator using a forward constrained regression framework, within which the nonnegative and summing-to-unity constraints of the mixing weights can easily be satisfied. Our main contribution is to derive a recursive algorithm to select significant kernels one at time based on the minimum integrated square error (MISE) criterion for both the selection of kernels and the estimation of mixing weights. The proposed approach is simple to implement and the associated computational cost is very low. Specifically, the complexity of our algorithm is in the order of the number of training data N, which is much lower than the order of N2 offered by the best existing sparse kernel density estimators. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to those of the classical Parzen window estimate and other existing sparse kernel density estimators.

Pollen-based biome reconstructions for Latin America at 0, 6000 and 18000 radiocarbon years

The biomisation method is used to reconstruct Latin American vegetation at 6000±500 and 18 000±1000 radiocarbon years before present (14C yr BP) from pollen data. Tests using modern pollen data from 381 samples derived from 287 locations broadly reproduce potential natural vegetation. The strong temperature gradient associated with the Andes is recorded by a transition from high altitude cool grass/shrubland and cool mixed forest to mid-altitude cool temperate rain forest, to tropical dry, seasonal and rain forest at low altitudes. Reconstructed biomes from a number of sites do not match the potential vegetation due to local factors such as human impact, methodological artefacts and mechanisms of pollen representivity of the parent vegetation.