Cerebral oximetry and return of spontaneous circulation after cardiac arrest: A systematic review and meta-analysis.

AIM: The prediction of return of spontaneous circulation (ROSC) during resuscitation of patients suffering of cardiac arrest (CA) is particularly challenging. Regional cerebral oxygen saturation (rSO2) monitoring through near-infrared spectrometry is feasible during CA and could provide guidance during resuscitation. METHODS: We conducted a systematic review and meta-analysis on the value of rSO2 in predicting ROSC both after in-hospital (IH) or out-of-hospital (OH) CA. Our search included MEDLINE (PubMed) and EMBASE, from inception until April 4th, 2015. We included studies reporting values of rSO2 at the beginning of and/or during resuscitation, according to the achievement of ROSC. RESULTS: A total of nine studies with 315 patients (119 achieving ROSC, 37.7%) were included in the meta-analysis. The majority of those patients had an OHCA (n=225, 71.5%; IHCA: n=90, 28.5%). There was a significant association between higher values of rSO2 and ROSC, both in the overall calculation (standardized mean difference, SMD -1.03; 95%CI -1.39,-0.67; p<0.001), and in the subgroups analyses (rSO2 at the beginning of resuscitation: SMD -0.79; 95%CI -1.29,-0.30; p=0.002; averaged rSO2 value during resuscitation: SMD -1.28; 95%CI -1.74,-0.83; p<0.001). CONCLUSIONS: Higher initial and average regional cerebral oxygen saturation values are both associated with greater chances of achieving ROSC in patients suffering of CA. A note of caution should be made in interpreting these results due to the small number of patients and the heterogeneity in study design: larger studies are needed to clinically validate cut-offs for guiding cardiopulmonary resuscitation.

Regional Science trends through the analysis of the main facts of the 51st ERSA Conference

The 51st ERSA Conference held in Barcelona in 2011 was one of the largest ever. By examining the characteristics of the conference, this paper identifies the main trends in Regional Science and draws on a broad array of sources of information: the delegates" demographic details, the conference program itself, a satisfaction survey conducted among delegates, a quality survey addressed to those chairing the sessions and, finally, a bibliometric database including each author signing a paper presented at the conference. We finally run a regression analysis from which we show that for ERSA delegates what matters most is quality, and this must be the direction that future conferences should move toward. Ultimately, ERSA conferences are comprehensive, all-embracing occasions, representing an ideal opportunity for regional scientists to present their work to each other and to network.

How to Model Heterogeneity in Costly Punishment: Insights from Responders' Response Times

We investigate what processes may underlie heterogeneity in social preferences. We address this question by examining participants' decisions and associated response times across 12 mini-ultimatum games. Using a finite mixture model and cross-validating its classification with a response time analysis, we identified four groups of responders: one group takes little to no account of the proposed split or the foregone allocation and swiftly accepts any positive offer; two groups process primarily the objective properties of the allocations (fairness and kindness) and need more time the more properties need to be examined; and a fourth group, which takes more time than the others, appears to take into account what they would have proposed had they been put in the role of the proposer. We discuss implications of this joint decision-response time analysis.

The composition of airborne and grain-dust fungal communities is shaped at regional scale by plant genotypes and farming practices

Chronic exposure to airborne fungi has been associated with different respiratory symptoms and pathologies in occupational populations, such as grain workers. However, the homogeneity in the fungal species composition of these bioaerosols on a large geographical scale and the different drivers that shape these fungal communities remain unclear. In this study, the diversity of fungi in grain dust and in the aerosols released during harvesting was determined across 96 sites at a geographical scale of 560 km(2) along an elevation gradient of 500 m by tag-encoded 454-pyrosequencing of the internal transcribed spacer (ITS) sequences. Associations between the structure of fungal communities in the grain dust and different abiotic (farming system, soil characteristics, geographic and climatic parameters) and biotic (wheat cultivar, previous crop culture) factors were explored. These analyses revealed a strong relationship between the airborne and grain dust fungal communities and showed the presence of allergenic and mycotoxigenic species in most samples, which highlights the potential contribution of these fungal species to work-related respiratory symptoms of grain workers. The farming system was the major driver of the alpha and beta phylogenetic diversity of fungal communities. In addition, elevation and soil CaCO3 concentrations shaped the alpha diversity whereas wheat cultivar, cropping history and the number of freezing days per year shaped the taxonomic beta diversity of these communities.

Predicted decrease in global climate suitability masks regional complexity of invasive fruit fly species response to climate change

Climate change affects the rate of insect invasions as well as the abundance, distribution and impacts of such invasions on a global scale. Among the principal analytical approaches to predicting and understanding future impacts of biological invasions are Species Distribution Models (SDMs), typically in the form of correlative Ecological Niche Models (ENMs). An underlying assumption of ENMs is that species-environment relationships remain preserved during extrapolations in space and time, although this is widely criticised. The semi-mechanistic modelling platform, CLIMEX, employs a top-down approach using species ecophysiological traits and is able to avoid some of the issues of extrapolation, making it highly applicable to investigating biological invasions in the context of climate change. The tephritid fruit flies (Diptera: Tephritidae) comprise some of the most successful invasive species and serious economic pests around the world. Here we project 12 tephritid species CLIMEX models into future climate scenarios to examine overall patterns of climate suitability and forecast potential distributional changes for this group. We further compare the aggregate response of the group against species-specific responses. We then consider additional drivers of biological invasions to examine how invasion potential is influenced by climate, fruit production and trade indices. Considering the group of tephritid species examined here, climate change is predicted to decrease global climate suitability and to shift the cumulative distribution poleward. However, when examining species-level patterns, the predominant directionality of range shifts for 11 of the 12 species is eastward. Most notably, management will need to consider regional changes in fruit fly species invasion potential where high fruit production, trade indices and predicted distributions of these flies overlap.

From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.

Human Capital Composition and Economic Growth at a Regional Level

With this paper we build a two-region model where both innovation and imitation are performed. In particular imitation takes the form of technological spillovers that lagging regions may exploit given certain human capital conditions. We show how the high skill content of each region’s workforce (rather than the average human capital stock) is crucial to determine convergence towards the income level of the leader region and to exploit the technological spillovers coming from the frontier. The same applies to bureaucratic/institutional quality which are conductive to higher growth in the long run. We test successfully our theoretical result over Spanish regions for the period between 1960 and 1997. We exploit system GMM estimators which allow us to correctly deal with endogeneity problems and small sample bias.

Regional economic growth and human capital: the role of overeducation

The paper analyses the link between human capital and regional economic growth in the European Union. Using different indicators of human capital calculated from census microdata, we conclude that the recent economic performance of European regions is associated to an increase in overeducation. In fact, measures of educational mismatch seem to have a stronger connection to regional economic performance than other traditional measures of human capital stocks.

Factors explaining urban transport systems in large European cities: A cross-sectional approach

The paper analyses the link between human capital and regional economic growth in the European Union. Using different indicat The importance of effective and efficient mobility in large cities is becoming essential for planners and citizens due to its impact in terms of social, economic and geographic development. The aim of this research is to determine factors explaining urban transport systems by estimating aggregate supply and demand equations for 45 large European cities. Supply and Demand equations are separately and jointly determined using OLS and SUR estimation models. On one hand, our findings suggest the importance of economic variables on the supply of public transport. On the other, we highlight the role of those factors influencing the generalized cost of transport as main drivers of demand for public transit. Additionally, regional variables are introduced to capture institutional heterogeneity in this service, and we find that regional patterns are powerful explanatory determinants of urban transportation systems in Europe.

Human Capital Spillovers Productivity and Regional Convergence in Spain

This paper analyses the differential impact of human capital, in terms of different levels of schooling, on regional productivity and convergence. The potential existence of geographical spillovers of human capital is also considered by applying spatial panel data techniques. The empirical analysis of Spanish provinces between 1980 and 2007 confirms the positive impact of human capital on regional productivity and convergence, but reveals no evidence of any positive geographical spillovers of human capital. In fact, in some specifications the spatial lag presented by tertiary studies has a negative effect on the variables under consideration.

The use of future-oriented knowledge in regional innovation processes: Research on knowledge generation, transfer and conversion

The importance of the regional level in research has risen in the last few decades and a vast literature in the fields of, for instance, evolutionary and institutional economics, network theories, innovations and learning systems, as well as sociology, has focused on regional level questions. Recently the policy makers and regional actors have also began to pay increasing attention to the knowledge economy and its needs, in general, and the connectivity and support structures of regional clusters in particular. Nowadays knowledge is generally considered as the most important source of competitive advantage, but even the most specialised forms of knowledge are becoming a short-lived resource for example due to the accelerating pace of technological change. This emphasizes the need of foresight activities in national, regional and organizational levels and the integration of foresight and innovation activities. In regional setting this development sets great challenges especially in those regions having no university and thus usually very limited resources for research activities. Also the research problem of this dissertation is related to the need to better incorporate the information produced by foresight process to facilitate and to be used in regional practice-based innovation processes. This dissertation is a constructive case study the case being Lahti region and a network facilitating innovation policy adopted in that region. Dissertation consists of a summary and five articles and during the research process a construct or a conceptual model for solving this real life problem has been developed. It is also being implemented as part of the network facilitating innovation policy in the Lahti region.

Formal Education, Mismatch and Wages After Transition: Assessing the Impact of Unobserved Heterogeneity using Matching Estimators

This paper studies the incidence and consequences of the mismatch between formal education and the educational requirements of jobs in Estonia during the years 1997-2003. We fi nd large wage penalties associated with the phenomenon of educational mismatch. Moreover, the incidence and wage penalty of mismatches increase with age. This suggests that structural educational mismatches can occur after fast transition periods. Our results are robust for various methodologies, and more importantly regarding departures from the exogeneity assumptions inherent in the matching estimators used in our analysis

Cross-national neighbouring effects on European regional specialization

In undertaking an analysis of neighbouring effects on European regional patterns of specialization, this paper makes two main contributions to the literature. First, we use a spatial weight matrix that takes into consideration membership of an EU cross-border regional association. We then compare our results with those obtained using a contiguity matrix and constitute an upper bound for our parameter of interest. In a further stage, we divide the CBR associations on the basis of their longstanding and the intensity of their cooperation to determine whether the association type has a significant impact. Second, we examine the sensitivity of our results to the use of alternative relative specialization indices.