Nitrogen fluxes from the landscape are controlled by net anthropogenic nitrogen inputs and by climate

The flux of nitrogen (N) to coastal marine ecosystems is strongly correlated with the “net anthropogenic nitrogen inputs” (NANI) to the landscape across 154 watersheds, ranging in size from 16 km2 to 279 000 km2, in the US and Europe. When NANI values are greater than 1070 kg N km−2 yr−1, an average of 25% of the NANI is exported from those watersheds in rivers. Our analysis suggests a possible threshold at lower NANI levels, with a smaller fraction exported when NANI values are below 1070 kg N km−2 yr−1. Synthetic fertilizer is the largest component of NANI in many watersheds, but other inputs also contribute substantially to the N fluxes; in some regions, atmospheric deposition of N is the major component. The flux of N to coastal areas is controlled in part by climate, and a higher percentage of NANI is exported in rivers, from watersheds that have higher freshwater discharge.

Planning for the reuse of redundant defence estate: disposal processes, policy frameworks and development impacts

This paper reviews recent research and other literature concerning the planning and development of redundant defence estate. It concentrates on UK sources but includes reference to material from Europe and the North America were it is relevant for comparative purposes. It introduces the topic by providing a brief review of the recent restructuring of the UK defence estate and then proceeds to examine the various planning policy issues generated by this process; the policy frameworks used to guide it; comparable approaches to surplus land disposal and the appraisal of impacts; and ending the main body of the review with an analyse of the economic, social and environmental impacts of military base closure and redevelopment. It concludes that there is a significant body of work focusing on the reuse and redevelopment of redundant defence estate in the UK and abroad, but that much of this work is based on limited research or on personal experience. One particular weakness of the current literature is that it does not fully reflect the institutional difficulties posed by the disposal process and the day-to-day pressures which MOD personnel have to deal with. In doing this, it also under-emphasises the embedded cultures of individuals and professional groups who are required to operationalise the policies, procedures and practices for planning and redeveloping redundant defence estate.

A continuum model of a fishing net

A working report for the Department of Agriculture and Fisheries, Scotland, Marine Laboratory Aberdeen

An elastic net orthogonal forward regression algorithm

In this paper we propose an efficient two-level model identification method for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level to carry out simultaneous model selection and elastic net parameter estimation. The two regularization parameters in the elastic net are optimized using a particle swarm optimization (PSO) algorithm at the upper level by minimizing the leave one out (LOO) mean square error (LOOMSE). Illustrative examples are included to demonstrate the effectiveness of the new approaches.

Do we need different frameworks to explain infant MNEs from developing countries?

I argue that the initial set of firm-specific assets (FSAs) act as an envelope for the early stages of internationalization of multinational enterprises (MNEs) (of whatever nationality) AND THAT there is a threshold LEVEL of FSAs that IT must possess for such international expansion to be SUCCESSFUL. I also argue that the initial FSAs of an MNE tend to be constrained by the location-specific (L) assets of the home country. However, beyond different initial conditions, there are few obvious reasons to insist that INFANT developing country MNEs are of unique character THAN ADVANCED ECONOMY MNEs, and I predict that as they evolve, the observable differences between the two groups will diminish. Successful firms will increasingly explore internationalization, but there is also no reason to believe that this is likely to happen disproportionately from the developing countries.

Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks

In order to gain knowledge from large databases, scalable data mining technologies are needed. Data are captured on a large scale and thus databases are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.

Reworking the NAFTA: departures from traditional frameworks

This paper reviews the treatment of intellectual property rights in the North American Free Trade Agreement (NAFTA) and considers the welfare-theoretic bases for innovation transfer between member and nonmember states. Specifically, we consider the effects of new technology development from within the union and question whether it is efficient (in a welfare sense) to transfer that new technology to nonmember states. When the new technology contains stochastic components, the important issue of information exchange arises and we consider this question in a simple oligopoly model with Bayesian updating. In this context, it is natural to ask the optimal price at which such information should be transferred. Some simple, natural conjugate examples are used to motivate the key parameters upon which the answer is dependent

Anion-directed template synthesis and hydrolysis of mono-condensed Schiff base of 1,3-pentanediamine ando-hydroxyacetophenone in NiII and CuII Complexes

Bis(o-hydroxyacetophenone)nickel(II) dihydrate, on reaction with 1,3-pentanediamine, yields a bis-chelate complex [NiL2]·2H2O (1) of mono-condensed tridentate Schiff baseligand HL {2-[1-(3-aminopentylimino)ethyl]phenol}. The Schiff base has been freed from the complex by precipitating the NiII as a dimethylglyoximato complex. HL reacts smoothly with Ni(SCN)2·4H2O furnishing the complex [NiL(NCS)] (2) and with CuCl2·2H2O in the presence of NaN3 or NH4SCN producing [CuL(N3)]2 (3) or [CuL(NCS)] (4). On the other hand, upon reaction with Cu(ClO4)2·6H2O and Cu(NO3)2·3H2O, the Schiff base undergoes hydrolysis to yield ternary complexes [Cu(hap)(pn)(H2O)]ClO4 (5) and [Cu(hap)(pn)(H2O)]NO3 (6), respectively (Hhap = o-hydroxyacetophenone and pn = 1,3-pentanediamine). The ligand HL undergoes hydrolysis also on reaction with Ni(ClO4)2·6H2O or Ni(NO3)2·6H2O to yield [Ni(hap)2] (7). The structures of the complexes 2, 3, 5, 6, and 7 have been confirmed by single-crystal X-ray analysis. In complex 2, NiII possesses square-planar geometry, being coordinated by the tridentate mono-negative Schiff base, L and the isothiocyanate group. The coordination environment around CuII in complex 3 is very similar to that in complex 2 but here two units are joined together by end-on, axial-equatorial azide bridges to result in a dimer in which the geometry around CuII is square pyramidal. In both 5 and 6, the CuII atoms display the square-pyramidal environment; the equatorial sites being coordinated by the two amine groups of 1,3-pentanediamine and two oxygen atoms of o-hydroxyacetophenone. The axial site is coordinated by a water molecule. Complex 7 is a square-planar complex with the Ni atom bonded to four oxygen atoms from two hap moieties. The mononuclear units of 2 and dinuclear units of 3 are linked by strong hydrogen bonds to form a one-dimensional network. The mononuclear units of 5 and 6 are joined together to form a dimer by very strong hydrogen bonds through the coordinated water molecule. These dimers are further involved in hydrogen bonding with the respective counteranions to form 2-D net-like open frameworks.

Replacing Norway spruce with European beech: a comparison of biomass and Net Primary Production patterns in young stands

An alteration of species composition in temperate forests – both managed and natural - is one of the expected effects of environmental change. Present forest tree species ranges will be altered by changing environmental conditions. By a combination of continuous and destructive sampling, we compared biomass stocks and annual NPP in naturally regenerated stands of Norway spruce and European beech. We purposely selected a site where future environmental conditions are predicted to favour beech over presently dominant spruce. We found no difference in overall productivity, but biomass allocation differed significantly between the two species. Beech allocated more assimilates to stem and roots than spruce. There was no significant difference between the species in NPP of the fast turnover biomass pool comprising foliage and fine roots. Maximum height growth occurred about a month earlier than in spruce, potentially changing the timing of carbon (C) flow into the soil pools. We show that the replacement of spruce by beech will result in changes in forest biomass allocation and in alterations of belowground C cycle. Such changes will affect forest ecosystem function by modifying the magnitude and timing of certain C fluxes, but also by potentially changing the species composition of forest biota dependent on them.

Elastic-net prefiltering for two-class classification

A two-stage linear-in-the-parameter model construction algorithm is proposed aimed at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage which constructs a sparse linear-in-the-parameter classifier. The prefiltering stage is a two-level process aimed at maximizing a model's generalization capability, in which a new elastic-net model identification algorithm using singular value decomposition is employed at the lower level, and then, two regularization parameters are optimized using a particle-swarm-optimization algorithm at the upper level by minimizing the leave-one-out (LOO) misclassification rate. It is shown that the LOO misclassification rate based on the resultant prefiltered signal can be analytically computed without splitting the data set, and the associated computational cost is minimal due to orthogonality. The second stage of sparse classifier construction is based on orthogonal forward regression with the D-optimality algorithm. Extensive simulations of this approach for noisy data sets illustrate the competitiveness of this approach to classification of noisy data problems.

Particle swarm optimisation assisted classification using elastic net prefiltering

A novel two-stage construction algorithm for linear-in-the-parameters classifier is proposed, aiming at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage to construct a sparse linear-in-the-parameters classifier. For the first stage learning of generating the prefiltered signal, a two-level algorithm is introduced to maximise the model's generalisation capability, in which an elastic net model identification algorithm using singular value decomposition is employed at the lower level while the two regularisation parameters are selected by maximising the Bayesian evidence using a particle swarm optimization algorithm. Analysis is provided to demonstrate how “Occam's razor” is embodied in this approach. The second stage of sparse classifier construction is based on an orthogonal forward regression with the D-optimality algorithm. Extensive experimental results demonstrate that the proposed approach is effective and yields competitive results for noisy data sets.