Peru’s Experience in Sovereign Debt Management and Litigation: Some Lessons for the Legal Approach to Sovereign Indebtedness

The paper sheds light upon a specific issue: carbon leakage. Leakage can be understood as an unanticipated net carbon loss or gain, attributable to a climate policy, or reduction activities. Benign leakage effects are harmless. Unsettling are the ones that pose a threat to project’s environmental integrity. The Clean Development Mechanism (CDM) is no exception to such risk. In order to investigate leakage and the corresponding leakage calculation methods addressed in the CDM projects, a qualitative content analysis is conducted on 203 methodologies. Methodology documents serve as ideal textual data for examining CDM related leakage because the development of any new project must be based on methodologies. In relation to the research question, the content analysis synthesizes 11 types of leakage sources. Excluding the case where no leakage is considered, 10 type of leakage sources are then broadly classified as Activity Shift, Market Effects and Life Cycle Leakage. Their corresponding leakage calculation methods are described and reviewed in terms of their geographic reach, and leakage characteristics. A percentage pattern is presented in relation to each sector. The findings are that the vast majority of the CDM leakage calculation methods address primary leakage specific to each individual project at a localized scale, among which, methods addressing Life Cycle Leakage are in the predominant majority. Market Effects as secondary sources are acknowledged as a potential threat to the overall benefit, but the CDM methodologies offer no quantitative method

Water Pipeline Leakage Detection Based on Machine Learning and Wireless Sensor Networks

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and intelligence of leakage detection, we propose a leakage identification method that employs the intrinsic mode function, approximate entropy, and principal component analysis to construct a signal feature set and that uses a support vector machine (SVM) as a classifier to perform leakage detection. Simulation analysis and experimental results indicate that the proposed leakage identification method can effectively identify the water pipeline leakage and has lower energy consumption than the networking methods used in conventional wireless sensor networks

Asymmetric gate induced drain leakage and body leakage in vertical MOSFETs with reduced parasitic capacitance

Vertical MOSFETs, unlike conventional planar MOSFETs, do not have identical structures at the source and drain, but have very different gate overlaps and geometric configurations. This paper investigates the effect of the asymmetric source and drain geometries of surround-gate vertical MOSFETs on the drain leakage currents in the OFF-state region of operation. Measurements of gate-induced drain leakage (GIDL) and body leakage are carried out as a function of temperature for transistors connected in the drain-on-top and drain-on-bottom configurations. Asymmetric leakage currents are seen when the source and drain terminals are interchanged, with the GIDL being higher in the drain-on-bottom configuration and the body leakage being higher in the drain-on-top configuration. Band-to-band tunneling is identified as the dominant leakage mechanism for both the GIDL and body leakage from electrical measurements at temperatures ranging from ?50 to 200?C. The asymmetric body leakage is explained by a difference in body doping concentration at the top and bottom drain–body junctions due to the use of a p-well ion implantation. The asymmetric GIDL is explained by the difference in gate oxide thickness on the vertical (110) pillar sidewalls and the horizontal (100) wafer surface

The Influence of Swirl Brakes on the Rotordynamic Forces Generated by Discharge-to-Suction Leakage Flows in Centrifugal Pumps

Increasing interest has been give to swirl brakes as a means of reducing destabilizing rotordynamic forces due to leakage flows in new high speed rocket turbopumps. Although swirl brakes have been used successfully in practice (such as with the Space Shuttle HPOTP), no experimental test until now have been performed to demonstrate their beneficial effect over a range of leakage flow rates. The present study investigates the effect of swirl brakes on rotordynamic forces generated by discharge-to-suction leakage flows in the annulus of shrouded centrifugal pumps over a range of subsynchronous whirl ratios and various leakage flow rates. In addition, the effectiveness of swirl brakes in the presence of leakage inlet (pump discharge) swirl is also demonstrated. The experimental data demonstrates that with the addition of swirl brakes a significant reduction in the destabilizing tangential force for lower flow rates is achieved. At higher flow rates, the brakes are detrimental. In the presence of leakage inlet swirl, brakes were effective over all leakage flow rates tested in reducing the range of whirl frequency ratio for which the tangential force is destabilizing

Prediction of gas leakage of environmental control systems

Mathematical models of leakage configurations and various flow theories are presented with the substantive experimental test data to provide background material for future design and failure analysis. Normal-rate leakage and emergency, high-rate leakage are considered