271,158 research outputs found

    Transnational governance in global finance - the principles for stable capital flows and fair debt restructuring in emerging markets

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    This paper analyses and assesses the track record and effectiveness of the so-called “Principles for Stable Capital Flows and Fair Debt Restructuring in Emerging Markets”,which have emerged as an important instrument for crisis prevention and crisis resolution in the international financial system. The paper argues that, notwithstanding their low profile, the Principles which were jointly agreed between sovereign debtors and their private creditors in 2004 have proved to be an effective instrument in spite of their voluntary and nonbinding nature. Indeed, an increasing number of sovereign debtors and private creditors have adopted the Principles’ recommendations on transparency and the timely flow of information, close dialogue, “good faith” actions and fair treatment. Two elements have been critical to the success of the Principles: (i) their specific design feature as a soft mode of governance agreed by a transnational public-private partnership and (ii) the “hardening” after their launch in terms of precision and delegation, thus moving them somewhat along the continuum of soft law and hard law towards the latter. The paper also makes the case that the Principles and their design features can provide some lessons for the current international policy debate on codes of conduct in global financial regulation.. JEL Classification: F34, F51, F53, G15, G18.Crisis prevention, debt restructuring, sovereign default, soft law, transnational public-private partnership, global financial governance.

    Towards automatic classification within the ChEBI ontology

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    *Background*
Appearing in a wide variety of contexts, biochemical 'small molecules' are a core element of biomedical data. Chemical ontologies, which provide stable identifiers and a shared vocabulary for use in referring to such biochemical small molecules, are crucial to enable the interoperation of such data. One such chemical ontology is ChEBI (Chemical Entities of Biological Interest), a candidate member ontology of the OBO Foundry. ChEBI is a publicly available, manually annotated database of chemical entities and contains around 18000 annotated entities as of the last release (May 2009). ChEBI provides stable unique identifiers for chemical entities; a controlled vocabulary in the form of recommended names (which are unique and unambiguous), common synonyms, and systematic chemical names; cross-references to other databases; and a structural and role-based classification within the ontology. ChEBI is widely used for annotation of chemicals within biological databases, text-mining, and data integration. ChEBI can be accessed online at "http://www.ebi.ac.uk/chebi/":http://www.ebi.ac.uk/chebi/ and the full dataset is available for download in various formats including SDF and OBO.

*Automated Classification*
The selection of chemical entities for inclusion in the ChEBI database is user-driven. As the use of ChEBI has grown, so too has the backlog of user-requested entries. Inevitably, the annotation backlog creates a bottleneck, and to speed up the annotation process, ChEBI has recently released a submission tool which allows community submissions of chemical entities, groups, and classes. However, classification of chemical entities within the ontology is a difficult and niche activity, and it is unlikely that the community as a whole will be able or willing to correctly and consistently classify each submitted entity, creating required classes where they are missing. As a result, it is likely that while the size of the database grows, the ontological classification will become less sophisticated, unless the classification of new entities is assisted computationally. In addition, the ChEBI database is expecting substantial size growth in the next year, so automatic classification, which has up till now not been possible, is urgently required. Automatic classification would also enable the ChEBI ontology classes to be applied to other compound databases such as PubChem. 

*Description Logic Reasoning*
Description logic based reasoning technology is a prime candidate for development of such an automatic classification system as it allows the rules of the classification system to be encoded within the knowledgebase. Already at 18000 entities, ChEBI is a fair size for a real-world application of description logic reasoning technology, and as the ontology is enhanced with a richer density of asserted relationships, the classification will become more complex and challenging. We have successfully tested a description logic-based classification of chemical entities based on specified structural properties using the hypertableaux-based HermiT reasoner, and found it to be sufficiently efficient to be feasible for use in a production environment on a database of the size that ChEBI is now. However, much work still remains to enrich the ChEBI knowledgebase itself with the properties needed to provide the formal class definitions for use in the automated classification, and to assess the efficiency of the available description logic reasoning technology on a database the size of ChEBI's forecast future growth.

*Acknowledgements*
ChEBI is funded by the European Commission under SLING, grant agreement number 226073 (Integrating Activity) within Research Infrastructures of the FP7 Capacities Specific Programme, and by the BBSRC, grant agreement number BB/G022747/1 within the “Bioinformatics and biological resources” fund

    Elastic stable intramedullary nailing in pediatric diaphyseal forearm bone fracture

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    Background: Pediatric forearm bone fracture present significant challenges where most of them are managed with closed reduction and casting. Irreducible, unstable and open fracture usually requires operative stabilization. Intramedullary nailing is considered minimal invasive however it is not free of complication. The aim of this study is to analyze the outcome and complications after elastic stable intramedullary nailing in pediatric diaphyseal forearm fracture.Methods: A descriptive observational study was carried out for four years (2013-2016) in diaphyseal pediatric forearm fracture stabilized with titanium elastic stable intramedullary nailing. Final range of motion, complications and outcome were assessed using Clavien-Dindo classification modification appropriate for orthopedic surgery.Results: We report the outcome of 36 patients with complete medical records. Closed reduction and nailing was successful in 25 patients (69.4%) whereas eleven patients (30.6%) required open reduction (both radius and ulna in 6 patients 16.7%, ulna in 3 patients 8.3% and radius in 2 patients 5.6%). Radiological union was achieved at an average of 7.75±1.5 weeks (range 6 to 16 weeks). Forearm rotation was limited in 7 patients with average loss of 16° pronation and 18° supination. The overall rate of complication was 22.2%. According to Clavien-Dindo classification excellent results were noted in 29 patients (80.6%), good in 3 patients (8.3%) and fair in 4 patients (11.1%). Conclusions: Elastic intramedullary nailing in pediatric diaphyseal forearm bones fracture is minimally invasive with low rate of complication and the outcomes are fair to excellent

    The Effects of TARP on Fair Value Accounting

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    In the aftermath of the financial crisis of 2008, fair value accounting in banks has come under a great deal of criticism by some who believed bank managers were intentionally reclassifying assets to prevent write-downs, or who believed that banks were taking risks with fair value assets and liabilities that caused their distressed states. We analyzed banks’ use of fair value accounting by using the SEC’s EDGAR database to read and analyze the financial statements of public banks which received Troubled Asset Relief Program (TARP) funds and have since repaid them. We looked to see if banks classified more assets as level 3, the most subjective measurement, to avoid write-downs and/or if they held more or fewer fair value assets or liabilities in their portfolios when distressed. In determining whether or not a bank is distressed, we view a bank as distressed in the quarter prior to receiving TARP funds, and as no longer distressed in the quarter in which the final repayment of TARP funds took place. In our research, we used data such as the ratio of fair value assets to total assets, fair value liabilities to total liabilities, and the composition of fair value assets and liabilities by level (levels 1, 2, and 3) from both when the banks were distressed and when they had become stable again. We find weak evidence for the “classification effect,” or the idea that bank managers intentionally reclassified fair value assets when under distress, and strong evidence for the “portfolio effect,” or the idea that banks’ risk appetites significantly changed during the crisis. This suggests that while the banks’ risk appetites changed when they were distressed, they were not intentionally classifying more assets as level 3
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