951 resultados para Barros, Manoel de 1916
Resumo:
In this paper, the productivities of Japanese airports over the period of 1987-2005 are analyzed using the Malmquist index, and technological bias is investigated. During this period, airports on average became less efficient and experienced technological regress. Our results indicate that the traditional growth accounting method, which assumes Hicks neutral technological change, is not appropriate for analyzing changes in productivity for Japanese airports.
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This paper investigates the productivity change of Japanese credit banks with a Malmquist index and the input technological bias during 2000-2006. Our results indicate that the traditional growth accounting method, which assumes Hicks neutral technological change, is not appropriate for analyzing changes in productivity. Our analysis unambiguously shows that management of Shinkin banks has to be improved. These must be based on the improvement of technical efficiency and/or technological change, emulating the procedures of the best-practice banks, i.e., those banks with Malmquist productivity scores higher than one and simultaneously with technical efficiency and technological change higher than one.
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This paper analyzes the change in productivity as a result of Angola oil policy from 2001 to 2007. Angola oil blocks are the main source of tax receipts and, therefore, strategically important for public finances. A Malmquist index with the input technological bias is applied to measure productivity change. Oil blocks on average became both more efficient and experienced technological progress. Our results indicate that the traditional growth accounting method, which assumes Hicks neutral technological change, is not appropriate for analyzing changes in productivity for Angola oil blocks. Policy implications are derived.
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In this paper, the random stochastic frontier model is used to estimate the technical efficiency of Japanese steam power generation companies taking into regulation and pollution. The companies are ranked according to their productivity for the period 1976-2003 and homogenous and heterogeneous variables in the cost function are disentangled. Policy implication is derived.
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The aim of this paper is to estimate the productivity change of Nigerian insurance companies and to rank the companies analysed in the sample according to their productivity score. This benchmark exercise provides the companies analysed with a view of how their relative productivity can be upgraded. For this purpose, the non-parametric Luenberger productivity model is used. For comparative purposes, the non-parametric Luenberger-Hicks-Moorsteen productivity indicator is also used. The companies are ranked according to their total productivity for the period 1994-2005, using both models, which produce variations in the respective results. Economic implications arising from the study are derived.
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In-memory databases have become a mainstay of enterprise computing offering significant performance and scalability boosts for online analytical and (to a lesser extent) transactional processing as well as improved prospects for integration across different applications through an efficient shared database layer. Significant research and development has been undertaken over several years concerning data management considerations of in-memory databases. However, limited insights are available on the impacts of applications and their supportive middleware platforms and how they need to evolve to fully function through, and leverage, in-memory database capabilities. This paper provides a first, comprehensive exposition into how in-memory databases impact Business Pro- cess Management, as a mission-critical and exemplary model-driven integration and orchestration middleware. Through it, we argue that in-memory databases will render some prevalent uses of legacy BPM middleware obsolete, but also open up exciting possibilities for tighter application integration, better process automation performance and some entirely new BPM capabilities such as process-based application customization. To validate the feasibility of an in-memory BPM, we develop a surprisingly simple BPM runtime embedded into SAP HANA and providing for BPMN-based process automation capabilities.
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Currently, there is a limited understanding of the sources of ambient fine particles that contribute to the exposure of children at urban schools. Since the size and chemical composition of airborne particle are key parameters for determining the source as well as toxicity, PM1 particles (mass concentration of particles with an aerodynamic diameter less than 1 µm) were collected at 24 urban schools in Brisbane, Australia and their elemental composition determined. Based on the elemental composition four main sources were identified; secondary sulphates, biomass burning, vehicle and industrial emissions. The largest contributing source was industrial emissions and this was considered as the main source of trace elements in the PM1 that children were exposed to at school. PM1 concentrations at the schools were compared to the elemental composition of the PM2.5 particles (mass concentration of particles with an aerodynamic diameter less than 2.5 µm) from a previous study conducted at a suburban and roadside site in Brisbane. This comparison revealed that the more toxic heavy metals (V, Cr, Ni, Cu, Zn and Pb), mostly from vehicle and industrial emissions, were predominantly in the PM1 fraction. Thus, the results from this study points to PM1 as a potentially better particle size fraction for investigating the health effects of airborne particles.
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The growth of APIs and Web services on the Internet, especially through larger enterprise systems increasingly being leveraged for Cloud and software-as-a-service opportunities, poses challenges for improving the efficiency of integration with these services. Interfaces of enterprise systems are typically larger, more complex and overloaded, with single operations having multiple data entities and parameter sets, supporting varying requests, and reflecting versioning across different system releases, compared to fine-grained operations of contemporary interfaces. We propose a technique to support the refactoring of service interfaces by deriving business entities and their relationships. In this paper, we focus on the behavioural aspects of service interfaces, aiming to discover the sequential dependencies of operations (otherwise known as protocol extraction) based on the entities and relationships derived. Specifically, we propose heuristics according to these relationships, and in turn, deriving permissible orders in which operations are invoked. As a result of this, service operations can be refactored on business entity CRUD lines, with explicit behavioural protocols as part of an interface definition. This supports flexible service discovery, composition and integration. A prototypical implementation and analysis of existing Web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms proposed through the paper.
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Mismatches between services needing to interoperate have been addressed through the adaptation of structural and behavioural interfaces of services, which in practice incur long lead time through manual, coding effort. We propose a framework, complementary to con- ventional service adaptation, to synthesise service interfaces in the open setting of business networks, allowing consumers to introspect service interfaces and formulate service invocations. The framework also allows evolved service requests, as new features of service capabilities are discov- ered, through interactions with other, similar services. Finally the frame- work fosters reuse of adaptation efforts through normalisation of struc- tural and behavioural interfaces of similar services. This paper provides a first exposition of the service interface synthesis framework, describing patterns containing novel requirements for unilateral service adaptation and detailing the interface synthesis technique. Complex examples of ser- vices drawn from commercial logistic systems are then used to validate the synthesis technique and identify open challenges and future research directions.
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The objective of this study is to examine technical efficiency and productivity growth in the Indian banking sector over the period from 2004 to 2011. We apply an innovative methodological approach introduced by Chen et al. (2011) and Barros et al. (2012), who use a weighted Russell directional distance model to measure technical inefficiency. We further modify and extend that model to measure TFP change with NPLs. We find that the inefficiency levels are significantly different among the three ownership structure of banks in India. Foreign banks have strong market position in India and they pull the production frontier in a more efficient direction. SPBs and domestic private banks show considerably higher inefficiency. We conclude that the restructuring policy applied in the late 1990s and early 2000s by the Indian government has not had a long-lasting effect.
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Nigerian electricity market is characterized by inadequate electricity generation framework, compounded by lack of timely routine maintenances. This results in significant deterioration in plant electricity output. This study analyzes the productivity changes in the Nigerian power sector. Productivity increased on average in the power sector by the adoption of new technologies from best-practice power plants. The assumption of Hicks neutral technological change is found not to be suitable for the Nigerian power sector. This study finds that the plants are not using their capacity meaningfully, instead, there is a tendency to use labor.
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Germline mutations in BRCA1 predispose carriers to a high incidence of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through critical roles in DNA repair, cell cycle arrest and transcriptional control. A major question has been why BRCA1 loss or mutation leads to tumors mainly in estrogen-regulated tissues, given that BRCA1 has essential functions in all cell types. Here we report that estrogen and estrogen metabolites can cause DNA double strand breaks (DSB) in estrogen receptor-α negative breast cells and that BRCA1 is required to repair these DSBs to prevent metabolite-induced genomic instability. We found that BRCA1 also regulates estrogen metabolism and metabolite-mediated DNA damage by repressing the transcription of estrogen-metabolising enzymes, such as CYP1A1, in breast cells. Lastly, we used a knock-in human cell model with a heterozygous BRCA1 pathogenic mutation to show how BRCA1 haploinsufficiency affects these processes. Our findings provide pivotal new insights into why BRCA1 mutation drives the formation of tumours in estrogen-regulated tissues, despite the general role of BRCA1 in DNA repair in all cell types.
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Mutations within BRCA1 predispose carriers to a high risk of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through the assembly of multiple protein complexes involved in DNA repair, cell-cycle arrest, and transcriptional regulation. Here, we report the identification of a DNA damage-induced BRCA1 protein complex containing BCLAF1 and other key components of the mRNA-splicing machinery. In response to DNA damage, this complex regulates pre-mRNA splicing of a number of genes involved in DNA damage signaling and repair, thereby promoting the stability of these transcripts/proteins. Further, we show that abrogation of this complex results in sensitivity to DNA damage, defective DNA repair, and genomic instability. Interestingly, mutations in a number of proteins found within this complex have been identified in numerous cancer types. These data suggest that regulation of splicing by the BRCA1-mRNA splicing complex plays an important role in the cellular response to DNA damage.
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The scale of environmental problems in China is clearly evident. This paper analyses foreign direct investment (FDI) in China with a finite mixture model, also known as latent class model to understand the relationship between FDI and several pollutions. This is used to regresses FDI as function covariates including pollutants. The results reveal that FDI is affected by pollutants. There are cases reducing pollution deters foreign investment in China.