Designer buildings: an evaluation of the price impacts of signature architects

This study investigates whether commercial offices designed by signature architects in the United States achieve rental premiums compared to commercial offices designed by nonsignature architects. Focusing on buildings designed by winners of the Prizker Prize and the Gold Medal awarded by the American Institute of Architects, we create a sample of commercial office buildings designed by signature architects drawing on CoStar's national database. We use a combination of hedonic regression model and a logit model to estimate the various rent determinants. While the first stage measures the typical rental price differential above the typical building in a particular sub-market over a specific timeframe, the second stage identifies a potential price differential over a set of buildings closely matched on important characteristics (such as age, size, location etc.). We find that in both stages offices design by signature architects exhibit a premium. However these results are preliminary. The premium could be indeed an effect of the name of the architect, but others factors such as micro-market conditions might be the cause. Further tests are needed to confirm the validity of our results.

The dynamics of asset prices and transaction activity in illiquid markets: the case of private commercial real estate

This paper investigates the relationship between capital flows, turnover and returns for the UK private real estate market. We examine a number of possible implication of capital flows and turnover on capital returns testing for evidence of a price pressure effect, ‘return chasing’ behaviour and information revelation. The main tool of analysis is a panel vector autoregressive (VAR) regression model in which institutional capital flows, turnover and returns are specified as endogenous variables in a two equation system in which we also control for macro-economic variables. Data on flows, turnover and returns are obtained for the 10 market segments covering the main UK commercial real estate sectors. Our results do not support the widely-held belief among practitioners that capital flows have a ‘price pressure’ effect. Although there is some evidence of return chasing behaviour, the short timescales involved suggest this finding may be due to delayed recording of flows relative to returns given the difficulties of market entry. We find a significant positive relationship between lagged turnover and contemporaneous capital returns, suggesting that asset turnover provides pricing information.

Dietary, lifestyle and clinico-pathological factors associated with APC mutations and promoter methylation in colorectal cancers from the EPIC-Norfolk Study

The tumour suppressor APC is the most commonly altered gene in colorectal cancer (CRC). Genetic and epigenetic alterations of APC may therefore be associated with dietary and lifestyle risk factors for CRC. Analysis of APC mutations in the extended mutation cluster region (codons 1276-1556) and APC promoter 1A methylation was performed on 185 archival CRC samples collected from participants of the European Prospective Investigation into Cancer (EPIC)-Norfolk Study, with the aim of relating these to high quality seven-day dietary and lifestyle data collected prospectively. Truncating APC mutations (APC+) and promoter 1A methylation (PM+) were identified in 43% and 23% of CRCs analysed, respectively. Distal CRCs were more likely than proximal CRCs to be APC+ or PM+ (P = 0.04). APC+ CRCs were more likely to be moderately/well differentiated and microsatellite stable than APC- CRCs (P = 0.05 and 0.03). APC+ CRC cases consumed more alcohol than their counterparts (P = 0.01) and PM+ CRC cases consumed lower levels of folate and fibre (P = 0.01 and 0.004). APC+ or PM+ CRC cases consumedhigher levels of processed meat and iron from red meat and red meat products (P=0.007 and 0.006). Specifically, CRC cases harbouring GC to AT transition mutations consumed higher levels of processed meat (35 versus 24 g/day, P = 0.04) and iron from red meat and red meat products (0.8 versus 0.6 mg/day, P = 0.05). In a logistic regression model adjusted for age, sex and cigarette smoking status, each 19g/day (1SD) increment increase in processed meat consumption was associated with cases with GC to AT mutations (OR 1.68, 95% CI 1.03-2.75). In conclusion, APC+ and PM+ CRCs may be influenced by diet and GC to AT mutations in APC are associated with processed meat consumption, suggesting a mechanistic link with dietary alkylating agents, such as N-nitroso compounds.

A neurofuzzy classifier for two class problems

A neurofuzzy classifier identification algorithm is introduced for two class problems. The initial fuzzy base construction is based on fuzzy clustering utilizing a Gaussian mixture model (GMM) and the analysis of covariance (ANOVA) decomposition. The expectation maximization (EM) algorithm is applied to determine the parameters of the fuzzy membership functions. Then neurofuzzy model is identified via the supervised subspace orthogonal least square (OLS) algorithm. Finally a logistic regression model is applied to produce the class probability. The effectiveness of the proposed neurofuzzy classifier has been demonstrated using a real data set.

Risk assessment of UK skylark populations using life-history and individual-based landscape models

Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

Crossbred cow adoption and milk market participation in a multivariate count data framework

Cross-bred cow adoption is an important and potent policy variable precipitating subsistence household entry into emerging milk markets. This paper focuses on the problem of designing policies that encourage and sustain milkmarket expansion among a sample of subsistence households in the Ethiopian highlands. In this context it is desirable to measure households’ ‘proximity’ to market in terms of the level of deficiency of essential inputs. This problem is compounded by four factors. One is the existence of cross-bred cow numbers (count data) as an important, endogenous decision by the household; second is the lack of a multivariate generalization of the Poisson regression model; third is the censored nature of the milk sales data (sales from non-participating households are, essentially, censored at zero); and fourth is an important simultaneity that exists between the decision to adopt a cross-bred cow, the decision about how much milk to produce, the decision about how much milk to consume and the decision to market that milk which is produced but not consumed internally by the household. Routine application of Gibbs sampling and data augmentation overcome these problems in a relatively straightforward manner. We model the count data from two sites close to Addis Ababa in a latent, categorical-variable setting with known bin boundaries. The single-equation model is then extended to a multivariate system that accommodates the covariance between crossbred-cow adoption, milk-output, and milk-sales equations. The latent-variable procedure proves tractable in extension to the multivariate setting and provides important information for policy formation in emerging-market settings

Ozone database in support of CMIP5 simulations: results and corresponding radiative forcing

A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multimodel mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISSPUCCINI)and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23Wm−2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of −0.08Wm−2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of −0.05Wm−2, but which is within the stated range of −0.15 to +0.05Wm−2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1Wm−2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/).

Centennial-scale climate change in Ireland during the Holocene

We examine mid- to late Holocene centennial-scale climate variability in Ireland using proxy data from peatlands, lakes and a speleothem. A high degree of between-record variability is apparent in the proxy data and significant chronological uncertainties are present. However, tephra layers provide a robust tool for correlation and improve the chronological precision of the records. Although we can find no statistically significant coherence in the dataset as a whole, a selection of high-quality peatland water table reconstructions co-vary more than would be expected by chance alone. A locally weighted regression model with bootstrapping can be used to construct a ‘best-estimate’ palaeoclimatic reconstruction from these datasets. Visual comparison and cross-wavelet analysis of peatland water table compilations from Ireland and Northern Britain show that there are some periods of coherence between these records. Some terrestrial palaeoclimatic changes in Ireland appear to coincide with changes in the North Atlantic thermohaline circulation and solar activity. However, these relationships are inconsistent and may be obscured by chronological uncertainties. We conclude by suggesting an agenda for future Holocene climate research in Ireland.

MEGAPOLI: concept of multi-scale modelling of megacity impact on air quality and climate

The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes.

Variation in genes related to hepatic lipid metabolism and changes in waist circumference and body weight.

We analysed single nucleotide polymorphisms (SNPs) tagging the genetic variability of six candidate genes (ATF6, FABP1, LPIN2, LPIN3, MLXIPL and MTTP) involved in the regulation of hepatic lipid metabolism, an important regulatory site of energy balance for associations with body mass index (BMI) and changes in weight and waist circumference. We also investigated effect modification by sex and dietary intake. Data of 6,287 individuals participating in the European prospective investigation into cancer and nutrition were included in the analyses. Data on weight and waist circumference were followed up for 6.9 ± 2.5 years. Association of 69 tagSNPs with baseline BMI and annual changes in weight as well as waist circumference were investigated using linear regression analysis. Interactions with sex, GI and intake of carbohydrates, fat as well as saturated, monounsaturated and polyunsaturated fatty acids were examined by including multiplicative SNP-covariate terms into the regression model. Neither baseline BMI nor annual weight or waist circumference changes were significantly associated with variation in the selected genes in the entire study population after correction for multiple testing. One SNP (rs1164) in LPIN2 appeared to be significantly interacting with sex (p = 0.0003) and was associated with greater annual weight gain in men (56.8 ± 23.7 g/year per allele, p = 0.02) than in women (-25.5 ± 19.8 g/year per allele, p = 0.2). With respect to gene-nutrient interaction, we could not detect any significant interactions when accounting for multiple testing. Therefore, out of our six candidate genes, LPIN2 may be considered as a candidate for further studies.

Bank integration and co-movements across housing markets

This paper investigates whether bank integration measured by cross-border bank flows can capture the co-movements across housing markets in developed countries by using a spatial dynamic panel model. The transmission can occur through a global banking channel in which global banks intermediate wholesale funding to local banks. Changes in financial conditions are passed across borders through the banks’ balance-sheet exposure to credit, currency, maturity, and funding risks resulting in house price spillovers. While controlling for country-level and global factors, we find significant co-movement across housing markets of countries with proportionally high bank integration. Bank integration can better capture house price co-movements than other measures of economic integration. Once we account for bank exposure, other spatial linkages traditionally used to account for return co-movements across region – such as trade, foreign direct investment, portfolio investment, geographic proximity, etc. – become insignificant. Moreover, we find that the co-movement across housing markets decreases for countries with less developed mortgage markets characterized by fixed mortgage rate contracts, low limits of loan-to-value ratios and no mortgage equity withdrawal.

Training on the use of a bespoke continuing professional development framework improves the quality of CPD records

BACKGROUND: Using continuing professional development (CPD) as part of the revalidation of pharmacy professionals has been proposed in the UK but not implemented. We developed a CPD Outcomes Framework (‘the framework’) for scoring CPD records, where the score range was -100 to +150 based on demonstrable relevance and impact of the CPD on practice. OBJECTIVE: This exploratory study aimed to test the outcome of training people to use the framework, through distance-learning material (active intervention), by comparing CPD scores before and after training. SETTING: Pharmacy professionals were recruited in the UK in Reading, Banbury, Southampton, Kingston-upon-Thames and Guildford in 2009. METHOD: We conducted a randomised, double-blinded, parallel-group, before and after study. The control group simply received information on new CPD requirements through the post; the active intervention group also received the framework and associated training. Altogether 48 participants (25 control, 23 active) completed the study. All participants submitted CPD records to the research team before and after receiving the posted resources. The records (n=226) were scored blindly by the researchers using the framework. A subgroup of CPD records (n=96) submitted first (before-stage) and rewritten (after-stage) were analysed separately. MAIN OUTCOME MEASURE: Scores for CPD records received before and after distributing group-dependent material through the post. RESULTS: Using a linear-regression model both analyses found an increase in CPD scores in favour of the active intervention group. For the complete set of records, the effect was a mean difference of 9.9 (95% CI = 0.4 to 19.3), p-value = 0.04. For the subgroup of rewritten records, the effect was a mean difference of 17.3 (95% CI = 5.6 to 28.9), p-value = 0.0048. CONCLUSION: The intervention improved participants’ CPD behaviour. Training pharmacy professionals to use the framework resulted in better CPD activities and CPD records, potentially helpful for revalidation of pharmacy professionals. IMPACT: • Using a bespoke Continuing Professional Development outcomes framework improves the value of pharmacy professionals’ CPD activities and CPD records, with the potential to improve patient care. • The CPD outcomes framework could be helpful to pharmacy professionals internationally who want to improve the quality of their CPD activities and CPD records. • Regulators and officials across Europe and beyond can assess the suitability of the CPD outcomes framework for use in pharmacy CPD and revalidation in their own setting.

Interaction between FTO gene variants and lifestyle factors on metabolic traits in an Asian Indian population

Background Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). Methods The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. Results There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5). Conclusions This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.

The influence of maternal factors on the concentration of vitamin A in mature breast milk

Background & aims: This study evaluated the relationship between vitamin A concentration in maternal milk and the characteristics of the donors of a Brazilian human milk bank. Material and methods: A total of 136 donors were selected in 2003-2004 for micronutrient determinations in breast milk and blood, anthropometric measurements and investigation of obstetric, socioeconomic-demographic factors, and life style. Maternal serum/milk samples were obtained for vitamin A, iron, copper, and zinc determinations. Vitamin A concentrations in breast milk and blood were assessed by high-performance liquid chromatography. Copper, zinc and iron concentrations in breast milk, and copper and zinc concentrations in blood were detected by atomic emission spectrophotometry. Serum ceruloplasmin and serum iron were determined, respectively, by nephelometry and colorimetry. A linear regression model assessed the associations between milk concentrations of vitamin A and maternal factors. Results: Vitamin A in milk presented positive associations with iron in milk (p < 0.001), serum retinol (p = 0.03), maternal work (p = 0.02), maternal age (p = 0.02). and oral contraceptive use (p = 0.01), and a negative association with % body fat (p = 0.01) (R(2) = 0.47). Conclusion: These results suggest that some nutritional, obstetric, and socioeconomic-demographic factors may have an effect on mature breast milk concentrations of vitamin A in apparently healthy Brazilian mothers. (C) 2009 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Assessment of inbreeding depression in a Guzerat dairy herd: Effects of individual increase in inbreeding coefficients on production and reproduction

Influences of inbreeding on daily milk yield (DMY), age at first calving (AFC), and calving intervals (CI) were determined on a highly inbred zebu dairy subpopulation of the Guzerat breed. Variance components were estimated using animal models in single-trait analyses. Two approaches were employed to estimate inbreeding depression: using individual increase in inbreeding coefficients or using inbreeding coefficients as possible covariates included in the statistical models. The pedigree file included 9,915 animals, of which 9,055 were inbred, with an average inbreeding coefficient of 15.2%. The maximum inbreeding coefficient observed was 49.45%, and the average inbreeding for the females still in the herd during the analysis was 26.42%. Heritability estimates were 0.27 for DMY and 0.38 for AFC. The genetic variance ratio estimated with the random regression model for CI ranged around 0.10. Increased inbreeding caused poorer performance in DMY, AFC, and CI. However, some of the cows with the highest milk yield were among the highly inbred animals in this subpopulation. Individual increase in inbreeding used as a covariate in the statistical models accounted for inbreeding depression while avoiding overestimation that may result when fitting inbreeding coefficients.