Magnetoencephalography as a putative biomarker for Alzheimer's disease.

Alzheimer’s Disease (AD) is the most common dementia in the elderly and is estimated to affect tens of millions of people worldwide. AD is believed to have a prodromal stage lasting ten or more years. While amyloid deposits, tau filaments, and loss of brain cells are characteristics of the disease, the loss of dendritic spines and of synapses predate such changes. Popular preclinical detection strategies mainly involve cerebrospinal fluid biomarkers, magnetic resonance imaging, metabolic PET scans, and amyloid imaging. One strategy missing from this list involves neurophysiological measures, which might be more sensitive to detect alterations in brain function. The Magnetoencephalography International Consortium of Alzheimer’s Disease arose out of the need to advance the use of Magnetoencephalography (MEG), as a tool in AD and pre-AD research. This paper presents a framework for using MEG in dementia research, and for short-term research priorities

Estimation of nitrogen budgets for contrasting catchments at the landscape scale.

A comprehensive assessment of nitrogen (N) flows at the landscape scale is fundamental to understand spatial interactions in the N cascade and to inform the development of locally optimised N management strategies. To explore these interactions, complete N budgets were estimated for two contrasting hydrological catchments (dominated by agricultural grassland vs. semi-natural peat-dominated moorland), forming part of an intensively studied landscape in southern Scotland. Local scale atmospheric dispersion modelling and detailed farm and field inventories provided high resolution estimations of input fluxes. Direct agricultural inputs (i.e. grazing excreta, N2 fixation, organic and synthetic fertiliser) accounted for most of the catchment N inputs, representing 82% in the grassland and 62% in the moorland catchment, while atmospheric deposition made a significant contribution, particularly in the moorland catchment, contributing 38% of the N inputs. The estimated catchment N budgets highlighted areas of key uncertainty, particularly N2 exchange and stream N export. The resulting N balances suggest that the study catchments have a limited capacity to store N within soils, vegetation and groundwater. The "catchment N retention", i.e. the amount of N which is either stored within the catchment or lost through atmospheric emissions, was estimated to be 13% of the net anthropogenic input in the moorland and 61% in the grassland catchment. These values contrast with regional scale estimates: Catchment retentions of net anthropogenic input estimated within Europe at the regional scale range from 50% to 90%, with an average of 82% (Billen et al., 2011). This study emphasises the need for detailed budget analyses to identify the N status of European landscapes.

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes.

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

Monolithic master oscillator power amplifier at 1.58 µm for lidar measurements

Nowadays the interest in high power semiconductor devices is growing for applications such as telemetry, lidar system or free space communications. Indeed semiconductor devices can be an alternative to solid state lasers because they are more compact and less power consuming. These characteristics are very important for constrained and/or low power supply environment such as airplanes or satellites. Lots of work has been done in the 800-1200 nm range for integrated and free space Master Oscillator Power Amplifier (MOPA) [1]-[3]. At 1.5 ?m, the only commercially available MOPA is from QPC [4]: the fibred output power is about 700 mW and the optical linewidth is 500 kHz. In this paper, we first report on the simulations we have done to determine the appropriate vertical structure and architecture for a good MOPA at 1.58 ?m (section II). Then we describe the fabrication of the devices (section III). Finally we report on the optical and electrical measurements we have done for various devices (section IV).

High brightness semiconductor lasers as transmitters for space lidar systems

High brightness semiconductor lasers are potential transmitters for future space lidar systems. In the framework of the European Project BRITESPACE, we propose an all-semiconductor laser source for an Integrated Path Differential Absorption lidar system for column-averaged measurements of atmospheric CO2 in future satellite missions. The complete system architecture has to be adapted to the particular emission properties of these devices using a Random Modulated Continuous Wave approach. We present the initial experimental results of the InGaAsP/InP monolithic Master Oscillator Power Amplifiers, providing the ON and OFF wavelengths close to the selected absorption line around 1572 nm.

Random-modulation cw lidar system for space-borne carbon dioxide remote sensing based on a high-brightness semiconductor laser

In this paper, we report on the progresses of the BRITESPACE Consortium in order to achieve space-borne LIDAR measurements of atmospheric carbon dioxide concentration based on an all semiconductor laser source at 1.57 ?m. The complete design of the proposed RM-CW IPDA LIDAR has been presented and described in detail. Complete descriptions of the laser module and the FSU have been presented. Two bended MOPAs, emitting at the sounding frequency of the on- and off- IPDA channels, have been proposed as the transmitter optical sources with the required high brightness. Experimental results on the bended MOPAs have been presented showing a high spectral purity and promising expectations on the high output power requirements. Finally, the RM-CW approach has been modelled and an estimation of the expected SNR for the entire system is presented. Preliminary results indicate that a CO2 retrieval precision of 1.5 ppm could be achieved with an average output power of 2 W for each channel.