Hemispheric competence for auditory spatial representation.

Sound localization relies on the analysis of interaural time and intensity differences, as well as attenuation patterns by the outer ear. We investigated the relative contributions of interaural time and intensity difference cues to sound localization by testing 60 healthy subjects: 25 with focal left and 25 with focal right hemispheric brain damage. Group and single-case behavioural analyses, as well as anatomo-clinical correlations, confirmed that deficits were more frequent and much more severe after right than left hemispheric lesions and for the processing of interaural time than intensity difference cues. For spatial processing based on interaural time difference cues, different error types were evident in the individual data. Deficits in discriminating between neighbouring positions occurred in both hemispaces after focal right hemispheric brain damage, but were restricted to the contralesional hemispace after focal left hemispheric brain damage. Alloacusis (perceptual shifts across the midline) occurred only after focal right hemispheric brain damage and was associated with minor or severe deficits in position discrimination. During spatial processing based on interaural intensity cues, deficits were less severe in the right hemispheric brain damage than left hemispheric brain damage group and no alloacusis occurred. These results, matched to anatomical data, suggest the existence of a binaural sound localization system predominantly based on interaural time difference cues and primarily supported by the right hemisphere. More generally, our data suggest that two distinct mechanisms contribute to: (i) the precise computation of spatial coordinates allowing spatial comparison within the contralateral hemispace for the left hemisphere and the whole space for the right hemisphere; and (ii) the building up of global auditory spatial representations in right temporo-parietal cortices.

Where is the economics in spatial econometrics?

Spatial econometrics has been criticized by some economists because some model specifications have been driven by data-analytic considerations rather than having a firm foundation in economic theory. In particular this applies to the so-called W matrix, which is integral to the structure of endogenous and exogenous spatial lags, and to spatial error processes, and which are almost the sine qua non of spatial econometrics. Moreover it has been suggested that the significance of a spatially lagged dependent variable involving W may be misleading, since it may be simply picking up the effects of omitted spatially dependent variables, incorrectly suggesting the existence of a spillover mechanism. In this paper we review the theoretical and empirical rationale for network dependence and spatial externalities as embodied in spatially lagged variables, arguing that failing to acknowledge their presence at least leads to biased inference, can be a cause of inconsistent estimation, and leads to an incorrect understanding of true causal processes.

Regional productivity variation and the impact of public capital stock: an analysis with spatial interaction, with reference to Spain

In this paper we examine whether variations in the level of public capital across Spain‟s Provinces affected productivity levels over the period 1996-2005. The analysis is motivated by contemporary urban economics theory, involving a production function for the competitive sector of the economy („industry‟) which includes the level of composite services derived from „service‟ firms under monopolistic competition. The outcome is potentially increasing returns to scale resulting from pecuniary externalities deriving from internal increasing returns in the monopolistic competition sector. We extend the production function by also making (log) labour efficiency a function of (log) total public capital stock and (log) human capital stock, leading to a simple and empirically tractable reduced form linking productivity level to density of employment, human capital and public capital stock. The model is further extended to include technological externalities or spillovers across provinces. Using panel data methodology, we find significant elasticities for total capital stock and for human capital stock, and a significant impact for employment density. The finding that the effect of public capital is significantly different from zero, indicating that it has a direct effect even after controlling for employment density, is contrary to some of the earlier research findings which leave the question of the impact of public capital unresolved.

Multilevel Modelling with Spatial Effects

In multilevel modelling, interest in modeling the nested structure of hierarchical data has been accompanied by increasing attention to different forms of spatial interactions across different levels of the hierarchy. Neglecting such interactions is likely to create problems of inference, which typically assumes independence. In this paper we review approaches to multilevel modelling with spatial effects, and attempt to connect the two literatures, discussing the advantages and limitations of various approaches.

Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal

Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales.

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

The endodermis--development and differentiation of the plant's inner skin.

Controlling external compound entrance is essential for plant survival. To set up an efficient and selective sorting of nutrients, free diffusion via the apoplast in vascular plants is blocked at the level of the endodermis. Although we have learned a lot about endodermal specification in the last years, information regarding its differentiation is still very limited. A differentiated endodermal cell can be defined by the presence of the "Casparian strip" (CS), a cell wall modification described first by Robert Caspary in 1865. While the anatomical description of CS in many vascular plants has been very detailed, we still lack molecular information about the establishment of the Casparian strips and their actual function in roots. The recent isolation of a novel protein family, the CASPs, that localizes precisely to a domain of the plasma membrane underneath the CS represents an excellent point of entry to explore CS function and formation. In addition, it has been shown that the endodermis contains transporters that are localized to either the central (stele-facing) or peripheral (soil-facing) plasma membranes. These features suggest that the endodermis functions as a polar plant epithelium.

A bayesian spatial individual effects probit model of the 2010 UK general election

The Conservative Party emerged from the 2010 United Kingdom General Election as the largest single party, but their support was not geographically uniform. In this paper, we estimate a hierarchical Bayesian spatial probit model that tests for the presence of regional voting effects. This model allows for the estimation of individual region-specic effects on the probability of Conservative Party success, incorporating information on the spatial relationships between the regions of the mainland United Kingdom. After controlling for a range of important covariates, we find that these spatial relationships are significant and that our individual region-specic effects estimates provide additional evidence of North-South variations in Conservative Party support.

Roles of aldehyde dehydrogenase (ALDH) isoforms and retinoic acids in the growth and differentiation potential of human adult cardiac progenitor cells

Aim: We have studied human adult cardiac progenitor cells (CPCs) based on high aldehyde dehydrogenase activity (ALDH-hi), a property shared by many stem cells across tissues and organs. However, the role of ALDH in stem cell function is poorly known. In humans, there are 19 ALDH isoforms with different biological activities. The isoforms responsible for the ALDH-hi phenotype of stem cells are not well known but they may include ALDH1A1 and ALDH1A3 isoforms, which function in all-trans retinoic acid (RA) cell signaling. ALDH activity has been shown to regulate hematopoietic stem cell function via RA. We aimed to analyze ALDH isoform expression and the role of RA in human CPC function. Methods: Human adult CPCs were isolated from atrial appendage samples from patients who underwent heart surgery for coronary artery or valve disease. Atrial samples were either cultured as primary explants or enzymatically digested and sorted for ALDH activity by FACS. ALDH isoforms were determined by qRT-PCR. Cells were cultured in the presence or absence of the specific ALDH inhibitor DEAB, with or without RA. Induction of cardiac-specific genes in cells cultured in differentiation medium was measured by qRT-PCR. Results: While ALDH-hi CPCs grew in culture and could be expanded, ALDH-low cells grew poorly. CPC isolated as primary explant outgrowths expressed high levels of ALDH1A3 but not of other isoforms. CPCs isolated from cardiospheres expressed relatively high levels of all the 11 isoforms tested. In contrast, expanded CPCs and cardiosphere-derived cells expressed low levels of all ALDH isoforms. DEAB inhibited CPC growth in a dose-dependent manner, whereas RA rescued CPC growth in the presence of DEAB. In differentiation medium, ALDH-hi CPCs expressed approximately 300-fold higher levels of cardiac troponin T compared with their ALDH-low counterparts. Conclusions: High ALDH activity identifies human adult cardiac cells with high growth and cardiomyogenic potential. ALDH1A3 and, possibly, ALDH1A1 isoforms account for high ALDH activity and RA-mediated regulation of CPC growth.

Personal Indebtedness, Spatial Effects and Crime

There is a long and detailed history of attempts to understand what causes crime. One of the most prominent strands of this literature has sought to better understand the relationship between economic conditions and crime. Following Becker (1968), the economic argument is that in an attempt to maintain consumption in the face of unemployment, people may resort to sources of illicit income. In a similar manner, we might expect ex–ante, that increases in the level of personal indebtedness would be likely to provide similar incentives to engage in criminality. In this paper we seek to understand the spatial pattern of property and theft crimes using a range of socioeconomic variables, including data on the level of personal indebtedness.

On the transition of genetic differentiation from isolation to panmixia: What we can learn from GST and D.

Population genetic differentiation characterizes the repartition of alleles among populations. It is commonly thought that genetic differentiation measures, such as GST and D, should be near zero when allele frequencies are close to their expected value in panmictic populations, and close to one when they are close to their expected value in isolated populations. To analyse those properties, we first derive analytically a reference function f of known parameters that describes how important features of genetic differentiation (e.g. gene diversity, proportion of private alleles, frequency of the most common allele) are close to their expected panmictic and isolation value. We find that the behaviour of function f differs according to three distinct mutation regimes defined by the scaled mutation rate and the number of populations. Then, we compare GST and D to f, and demonstrate that their signal of differentiation strongly depends on the mutation regime. In particular, we show that D captures well the variations of genetic diversity when mutation is weak, otherwise it overestimates it when panmixia is not met. GST detects population differentiation when mutation is intermediate but has a low sensitivity to the variations of genetic diversity when mutation is weak. When mutation is strong the domain of sensitivity of both measures are altered. Finally, we also point out the importance of the number of populations on genetic differentiation measures, and provide recommendations for the use of GST and D.

Personal Indebtedness, Spatial Effects and Crime

There is a long and detailed history of attempts to understand what causes crime. One of the most prominent strands of this literature has sought to better understand the relationship between economic conditions and crime. Following Becker (1968), the economic argument is that in an attempt to maintain consumption in the face of unemployment, people may resort to sources of illicit income. In a similar manner, we might expect ex–ante, that increases in the level of personal indebtedness would be likely to provide similar incentives to engage in criminality. In this paper we seek to understand the spatial pattern of property and theft crimes using a range of socioeconomic variables, including data on the level of personal indebtedness.

Personal indebtedness, community characteristics and theft crimes

Becker (1968) and Stigler (1970) provide the germinal works for an economic analysis of crime, and their approach has been utilised to consider the response of crime rates to a range of economic, criminal and socioeconomic factors. Until recently however this did not extend to a consideration of the role of personal indebtedness in explaining the observed pattern of crime. This paper uses the Becker (1968) and Stigler (1970) framework, and extends to a fuller consideration of the relationship between economic hardship and theft crimes in an urban setting. The increase in personal debt in the past decade has been significant, which combined with the recent global recession, has led to a spike in personal insolvencies. In the context of the recent recession it is important to understand how increases in personal indebtedness may spillover into increases in social problems like crime. This paper uses data available at the neighbourhood level for London, UK on county court judgments (CCJ's) granted against residents in that neighbourhood, this is our measure of personal indebtedness, and examines the relationship between a range of community characteristics (economic, socio-economic, etc), including the number of CCJ's granted against residents, and the observed pattern of theft crimes for three successive years using spatial econometric methods. Our results confirm that theft crimes in London follow a spatial process, that personal indebtedness is positively associated with theft crimes in London, and that the covariates we have chosen are important in explaining the spatial variation in theft crimes. We identify a number of interesting results, for instance that there is variation in the impact of covariates across crime types, and that the covariates which are important in explaining the pattern of each crime type are largely stable across the three periods considered in this analysis.

Spatial Takeoff in the First Industrial Revolution

Using the framework of Desmet and Rossi-Hansberg (forthcoming), we present a model of spatial takeoff that is calibrated using spatially-disaggregated occupational data for England in c.1710. The model predicts changes in the spatial distribution of agricultural and manufacturing employment which match data for c.1817 and 1861. The model also matches a number of aggregate changes that characterise the first industrial revolution. Using counterfactual geographical distributions, we show that the initial concentration of productivity can matter for whether and when an industrial takeoff occurs. Subsidies to innovation in either sector can bring forward the date of takeoff while subsidies to the use of land by manufacturing firms can significantly delay a takeoff because it decreases spatial concentration of activity.