EU biofuels sustainability standards and certification systems - how to seek WTO-compatibility

Biofuels are increasingly being produced and consumed as a partial substitute to fossil-fuel based transport fuels in the fight against climate change. Sustainability criteria have been introduced recently by some countries to help ensure biofuels perform better than fossil fuels environmentally. Concerns have been expressed from various quarters that such criteria could represent World Trade Organisation (WTO)-incompatible barriers to trade. The present paper addresses two specific issues. First, it argues that biofuels can be expected to be treated like any other traded product under WTO law. Thus an importing country could not impose different trade measures dependent on whether the biofuel complied with its sustainability criteria. Second, the Technical Barriers to Trade Agreement (TBTA) provides guidance on how to draw up criteria to help ensure WTO compatibility. This cannot guarantee compatibility, but it can help reduce significantly the chances of WTO Members bringing actions against a fellow Member’s biofuels sustainability criteria. There is little direct case law to draw upon but it is argued that, if the TBT guidance is followed, in the long term the absence of case law can be taken as an indication that the sustainability criteria established are WTO-compatible

State Transfer and Spin Measurement

We present a Hamiltonian that can be used for amplifying the signal from a quantum state, enabling the measurement of a macroscopic observable to determine the state of a single spin. We prove a general mapping between this Hamiltonian and an exchange Hamiltonian for arbitrary coupling strengths and local magnetic fields. This facilitates the use of existing schemes for perfect state transfer to give perfect amplification. We further prove a link between the evolution of this fixed Hamiltonian and classical Cellular Automata, thereby unifying previous approaches to this amplification task. Finally, we show how to use the new Hamiltonian for perfect state transfer in the, to date, unique scenario where total spin is not conserved during the evolution, and demonstrate that this yields a significantly different response in the presence of decoherence.Comment: 4 pages, 2 figure

Using a smartphone app to identify signs of pre-eclampsia and/or worsening blood pressure

Background Hypertensive disorders of pregnancy complicate 10% of pregnancies and can have serious consequences. Aims To explore the experiences of pregnant women with a history of hypertension using an innovative home blood pressure monitoring device. Methods A qualitative study using a grounded theory approach was undertaken. Data were collected through semi-structured interviews. Women were given a blood pressure machine to monitor their blood pressure daily. They inserted their blood pressure results on a smartphone app and answered questions for signs of pre-eclampsia. Participants were followed up every 2 weeks. Findings The results suggested that women wanted a holistic care pathway for the management of hypertension in pregnancy. Three subcategories (‘empowerment’, ‘comparison of care pathways’ and ‘continuity of care’) were also identified. Conclusions The traditional management of hypertension in pregnancy is not holistic. The home blood pressure service was accepted by women and incorporated elements of holistic care but more is required to meet the standard of care that women need

Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach.

Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain-computer interface models. However, the absence of standardized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the difficulty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a "containerized" approach and freely available tools we have developed to facilitate the process of annotating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-)analysis. The EEG Study Schema (ESS) comprises three data "Levels," each with its own XML-document schema and file/folder convention, plus a standardized (PREP) pipeline to move raw (Data Level 1) data to a basic preprocessed state (Data Level 2) suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are increasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at www.eegstudy.org and a central catalog of over 850 GB of existing data in ESS format is available at studycatalog.org. These tools and resources are part of a larger effort to enable data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org)