A Stepwise Efficiency Improvement DEA Model for Airport Operations with Fixed Production Factors

In the spirit of the deregulation movement, Japan is also faced with an ÃgAsia Open SkyÃh agreement which favours aviation liberalization in international services. This means an end to Japan's aviation policy of isolation. In association with this policy change, also environmental concerns grew increasingly severe for small and local regional airports. Consequently, there is a need for an objective analysis of the efficiency of airport operations in Japan. A standard tool to judge the efficiency of such activities is Data Envelopment Analysis (DEA). In the past years, much progress has been made to extend this approach in various directions. Interesting examples are the Distance Friction Minimization (DFM) model and the Context-Dependent (CD) model. The DFM model is based on a generalized distance friction function and serves to improve the performance of a Decision Making Unit (DMU) by identifying the most appropriate movement towards the efficiency frontier surface. Standard DEA models use a uniform input reduction in the improvement projections, but the DFM approach aims to enhance efficiency strategies by introducing a weighted projection function. This approach may address both input reduction and output increase as a strategy of a DMU. Likewise, the CD model yields efficient frontiers at different levels, while it is based on a level-by-level improvement projection. The Stepwise DFM model is an integration of the DFM and the CD model in order to design a stepwise efficiency-improving projection model for a conventional DEA. In general, a DEA model – and neither the mix of the DFM-CD model – doesnÃft take into account a fixed factor. Such a non-controllable of fixed factor may refer to a production factor that cannot be flexibly adjusted in the short run. In our study the newly integrated Stepwise DFM-CD model will be extended with a fixed factor model in order to adapt the DEA model to realistic circumstances in an efficiency improvement projection. The above-mentioned stepwise fixed factor projection model is illustrated on the basis of an application to the efficiency analysis of airport operations in Japan in light of the above mentioned contextual changes in aviation policy.

Effective Clusters as Territorial Performance Engines in a Regional Development Strategy - A Triple-Layer DEA Assessment of the Aviation Valley in Poland

Regional development policy aims to cope with the challenge of spatial disparities. It is based on a smart combination of various critical capital assets in a region which functionally and spatially interact and which yield synergetic economic opportunities and promising challenges for innovation and progress. The present study regards sustainable territorial performance – as a manifestation of regional development – as the overarching principle for competitive advantages and economic growth in a system of regions, which is particularly induced by territorial capital, comprising human capital, infrastructural capital and social capital. In the long-standing tradition of regional development policy a wide variety of effective facilitators or drivers of accelerated spatial growth has been distinguished, for instance, industrial districts, growth poles, growth centers, industrial complexes, special economic zones, communication axes, and so forth. In the past decades, a new concept has been introduced, viz. economic-technological clusters. An avalanche of literature has been published on the conceptual, operational and policy foundation and relevance of this concept, especially in relation to previously developed regional growth concepts. In this paper, clusters will be regarded as the spatial foci of sustainable territorial performance strategies and synergetic actions by both public and private actors. The present paper aims to address the relevance of cluster concepts for an effective regional development policy, based on the above notion of territorial capital. It does so by introducing a new concept, viz. effective cluster, in which spatial-economic synergy, local/regional concentration of industry, and the supporting role of territorial capital are regarded as the main determinants of a highly performing cluster in a given territory. The effective cluster concept will be tested on the basis of a field study on the aviation and aerospace cluster ‘Dolina Lotnicza’ in the Podkarpackie region in South-East Poland. This is one of the most vibrant high-tech clusters in the country. A new approach based on a triple-layer architecture will be adopted here, viz.: a quantitative comparative analysis of the 16 Polish ‘voivodships’ (main administrative regions in the country, at a NUTS-2 level), a benchmark analysis of the 25 counties (‘powiats’) within the Podkarpackie voivodship (at a NUTS-4 level), and an effective industrial cluster analysis on the basis of the individual aviation firms located in the Podkarpackie region. In each step an extended Data Envelopment Analysis (DEA), characterised by a merger of a Slack-Based Measure (SMB) and a super-efficiency (SE) DEA, will be used in order to achieve an unambiguous ranking of the various regions or Decision Making Units (DMUs). The study will employ an extensive database on individual actors in the cluster, in combination with a broadly composed territorial-capital database for the areas under study. The paper will be concluded with some strategic policy lessons

Mechanistic species distribution modeling reveals a niche shift during invasion

Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern-origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual populations. Ignoring such effects could substantially underestimate the extent and impact of invasions

Targeting miR-223 in neutrophils enhances the clearance of Staphylococcus aureus in infected wounds

Abstract Argonaute 2 bound mature microRNA (Ago2‐miRNA) complexes are key regulators of the wound inflammatory response and function in the translational processing of target mRNAs. In this study, we identified four wound inflammation‐related Ago2‐miRNAs (miR‐139‐5p, miR‐142‐3p, miR‐142‐5p, and miR‐223) and show that miR‐223 is critical for infection control. miR‐223Y/− mice exhibited delayed sterile healing with prolonged neutrophil activation and interleukin‐6 expression, and markedly improved repair of Staphylococcus aureus‐infected wounds. We also showed that the expression of miR‐223 was regulated by CCAAT/enhancer binding protein alpha in human neutrophils after exposure to S. aureus peptides. Treatment with miR‐223Y/−‐derived neutrophils, or miR‐223 antisense oligodeoxynucleotides in S. aureus‐infected wild‐type wounds markedly improved the healing of these otherwise chronic, slow healing wounds. This study reveals how miR‐223 regulates the bactericidal capacity of neutrophils at wound sites and indicates that targeting miR‐223 might be of therapeutic benefit for infected wounds in the clinic