Capital market expectations and the London office market

The analysis of office market dynamics has generally concentrated on the impact of underlying fundamental demand and supply variables. This paper takes a slightly different approach to many previous examinations of rental dynamics. Within a Vector-Error-Correction framework the empirical analysis concentrates upon the impact of economic and financial variables on rents in the City of London and West End of London office markets. The impulse response and variance decomposition reveal that while lagged rental values and key demand drivers play a highly important role in the dynamics of rents, financial variables are also influential. Stock market performance not only influences the City of London market but also the West End, whilst the default spread plays an important role in recent years. It is argued that both series incorporate expectations about future economic performance and that this is the basis of their influence upon rental values.

Construction of neurofuzzy models for imbalanced data classification

We propose a new class of neurofuzzy construction algorithms with the aim of maximizing generalization capability specifically for imbalanced data classification problems based on leave-one-out (LOO) cross validation. The algorithms are in two stages, first an initial rule base is constructed based on estimating the Gaussian mixture model with analysis of variance decomposition from input data; the second stage carries out the joint weighted least squares parameter estimation and rule selection using orthogonal forward subspace selection (OFSS)procedure. We show how different LOO based rule selection criteria can be incorporated with OFSS, and advocate either maximizing the leave-one-out area under curve of the receiver operating characteristics, or maximizing the leave-one-out Fmeasure if the data sets exhibit imbalanced class distribution. Extensive comparative simulations illustrate the effectiveness of the proposed algorithms.

A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

Adsorption, orientation and thermal decomposition of copper(II) hexafluoroacetylacetonate on rutile TiO2(110)

We have investigated the adsorption and thermal decomposition of copper hexafluoroacetylacetonate (Cu-11(hfaC)(2)) on single crystal rutile TiO2(110). Low energy electron diffraction shows that room temperature saturation coverage of the Cu-II(hfac)(2) adsorbate forms an ordered (2 x 1) over-layer. X-ray and ultra-violet photoemission spectroscopy of the saturated surface were recorded as the sample was annealed in a sequential manner to reveal decomposition pathways. The results show that the molecule dissociatively adsorbs by detachment of one of the two ligands to form hfac and Cu-1(hfac) which chemisorb to the substrate at 298 K. These ligands only begin to decompose once the surface temperature exceeds 473 K where Cu core level shifts indicate metallisation. This reduction from Cu(I) to Cu(0) takes place in the absence of an external reducing agent and without disproportionation and is accompanied by the onset of decomposition of the hfac ligands. Finally, C K-edge near edge X-ray absorption fine structure experiments indicate that both the ligands adsorb aligned in the < 001 > direction and we propose a model in which the hfac ligands adsorb on the 5-fold coordinated Ti atoms and the Cu-1(hfac) moiety attaches to the bridging O atoms in a square planar geometry. The calculated tilt angle for these combined geometries is approximately 10 degrees to the surface normal.

Decomposition in soil and chemical characteristics of pollen

The input to soils made by pollen and its subsequent mineralization has rarely been investigated from a soil microbiological point of view even though the small but significant quantities of C and N in pollen may make an important contribution to nutrient cycling. The relative resistance to decomposition of pollen exines (outer layers) has led to much of the focus of pollen in soil being on its preservation for archaeological and palaeo-ecological purposes. We have examined aspects of the chemical composition and decomposition of pollen from birch (Betula alba) and maize (Zea mays) in soil. The relatively large N contents, small C-to-N ratios and large water-soluble contents of pollen from both species indicated that they would be readily mineralized in soil. When added to soil and incubated at 16 degrees C an amount of C equivalent to 22-26% of the added pollen C was lost as CO2 within 22 days, with the Z. mays pollen decomposing faster. For B. alba pollen, the water-soluble fraction decomposed faster than the whole pollen and the insoluble fraction decomposed more slowly over 22 days. By contrast, there were no significant differences in the decomposition rates of the different fractions from Z. mays pollen. Solid-state C-13 nuclear magnetic resonance (NMR) revealed no gross chemical differences between the pollen of these two species, with strong resonances in the alkyl- and methyl-C region (0-45 p.p.m.) indicative of aliphatic compounds, the O-alkyl-C (60-90 p.p.m.) and the acetal- and ketal-C region (90-110 p.p.m.) indicative of polysaccharides, and the carbonyl-C region indicative of peptides and carboxylic acids. In addition, both pollens gave a small but distinct resonance at 55 p.p.m. attributed to N-alkyl-C. The resonances attributed to polysaccharides were lost completely or substantially reduced after decomposition.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Decomposition and phosphorus release from organic residues as affected by residue quality and added inorganic phosphorus

The combined use of organic residue and inorganic fertiliser-phosphorus (P) is appropriate in meeting both the short and long-term P requirement of crops. To assess the influence of added inorganic fertiliser-P on the processes of decomposition and P release from the residue and the relationships with quality, prunings of Gliricidia sepium, Leucaena leucocephela, Senna siamea, Acacia mangium and Paraserienthus falcataria were incubated without and with added inorganic fertiliser-P for 56 days. Soil was added only as inoculum. Decomposition rate and amounts of acid extractable-P (P release) were in the same order: G. sepium > S. siamea > L. leucocepheta > P falcataria > A. mangium. Unlike the other residues, A. mangium released no P despite the loss of half its mass during the 8 weeks of incubation. The residue P content correlated with P release. However, decomposition rate did not correlate with residue P content but with the lignin, polyphenol and cellulose content, and ratios to P. These ratios were negatively correlated with P release suggesting that lignin and polyphenol contents influence P release more when the residue-P content is low. Results suggest that rate of decomposition influences the release of P. The critical residue P content for P release was estimated to be 0.12% < P < 0.19%. Added P had no effect on decomposition and P release from the residues.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Decomposition in soil and chemical characteristics of pollen

The input to soils made by pollen and its subsequent mineralization has rarely been investigated from a soil microbiological point of view even though the small but significant quantities of C and N in pollen may make an important contribution to nutrient cycling. The relative resistance to decomposition of pollen exines (outer layers) has led to much of the focus of pollen in soil being on its preservation for archaeological and palaeo-ecological purposes. We have examined aspects of the chemical composition and decomposition of pollen from birch (Betula alba) and maize (Zea mays) in soil. The relatively large N contents, small C-to-N ratios and large water-soluble contents of pollen from both species indicated that they would be readily mineralized in soil. When added to soil and incubated at 16 degrees C an amount of C equivalent to 22-26% of the added pollen C was lost as CO2 within 22 days, with the Z. mays pollen decomposing faster. For B. alba pollen, the water-soluble fraction decomposed faster than the whole pollen and the insoluble fraction decomposed more slowly over 22 days. By contrast, there were no significant differences in the decomposition rates of the different fractions from Z. mays pollen. Solid-state C-13 nuclear magnetic resonance (NMR) revealed no gross chemical differences between the pollen of these two species, with strong resonances in the alkyl- and methyl-C region (0-45 p.p.m.) indicative of aliphatic compounds, the O-alkyl-C (60-90 p.p.m.) and the acetal- and ketal-C region (90-110 p.p.m.) indicative of polysaccharides, and the carbonyl-C region indicative of peptides and carboxylic acids. In addition, both pollens gave a small but distinct resonance at 55 p.p.m. attributed to N-alkyl-C. The resonances attributed to polysaccharides were lost completely or substantially reduced after decomposition.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Spin spaces and positive decomposition of linear maps on ordered Banach spaces

Spin factors and generalizations are used to revisit positive generation of B(E, F), where E and F are ordered Banach spaces. Interior points of B(E, F)+ are discussed and in many cases it is seen that positive generation of B(E, F) is controlled by spin structure in F when F is a JBW-algebra.

Multidecadal modulation of El Nino-Southern Oscillation (ENSO) variance by Atlantic Ocean sea surface temperatures

Observations suggest a possible link between the Atlantic Multidecadal Oscillation (AMO) and El Nino Southern Oscillation (ENSO) variability, with the warm AMO phase being related to weaker ENSO variability. A coupled ocean-atmosphere model is used to investigate this relationship and to elucidate mechanisms responsible for it. Anomalous sea surface temperatures (SSTs) associated with the positive AMO lead to change in the basic state in the tropical Pacific Ocean. This basic state change is associated with a deepened thermocline and reduced vertical stratification of the equatorial Pacific ocean, which in turn leads to weakened ENSO variability. We suggest a role for an atmospheric bridge that rapidly conveys the influence of the Atlantic Ocean to the tropical Pacific. The results suggest a non-local mechanism for changes in ENSO statistics and imply that anomalous Atlantic ocean SSTs can modulate both mean climate and climate variability over the Pacific.