A sequential model for disaggregating near-surface soil moisture observations using multi-resolution thermal sensors

A sequential model is developed to disaggregate microwave-derived soil moisture from 40 km to 4 km resolution using MODIS (Moderate Imaging Spectroradiometer) data and subsequently from 4 km to 500 m resolution using ASTER (Advanced Scanning Thermal Emission and Reflection Radiometer) data. The 1 km resolution airborne data collected during the three-week National Airborne Field Experiment 2006 (NAFE'06) are used to simulate the 40 km pixels, and a thermal-based disaggregation algorithm is applied using 1 km resolution MODIS and 100 m resolution ASTER data. The downscaled soil moisture data are subsequently evaluated using a combination of airborne and in situ soil moisture measurements. A key step in the procedure is to identify an optimal downscaling resolution in terms of disaggregation accuracy and sub-pixel soil moisture variability. Very consistent optimal downscaling resolutions are obtained for MODIS aboard Terra, MODIS aboard Aqua and ASTER, which are 4 to 5 times the thermal sensor resolution. The root mean square error between the 500 m resolution sequentially disaggregated and ground-measured soil moisture is 0.062 vol./vol. with a bias of − 0.045 vol./vol. and values ranging from 0.08 to 0.40 vol./vol.     

Model independent assertions for integration of heterogeneous schemas

Due to the proliferation of database applications, the integration of existing databases into a distributed or federated system is one of the major challenges in responding to enterprises' information requirements. Some proposed integration techniques aim at providing database administrators (DBAs) with a view definition language they can use to build the desired integrated schema. These techniques leave to the DBA the responsibility of appropriately restructuring schema elements from existing local schemas and of solving inter-schema conflicts. This paper investigates theassertion-based approach, in which the DBA's action is limited to pointing out corresponding elements in the schemas and to defining the nature of the correspondence in between. This methodology is capable of: ensuring better integration by taking into account additional semantic information (assertions about links); automatically solving structural conflicts; building the integrated schema without requiring conforming of initial schemas; applying integration rules to a variety of data models; and performing view as well as database integration. This paper presents the basic ideas underlying our approach and focuses on resolution of structural conflicts.     

Multi-month memory effects on early summer vegetative activity in semi-arid South Africa and their spatial heterogeneity

In semi-arid African regions (annual rainfall between 200 and 600 mm), variability of vegetative activity is mainly due to the rainfall of the current rainy season. In most of South Africa, the rainy season occurs from October to March. On average, vegetative activity lags rainfall by 1 to 2 months. The interannual variability in early summer (December to September) normalized difference vegetation index (NDVI) depends primarily on precipitation at the beginning (October to November) of the rainy season. However, once this primary control is removed, the residual interannual variability in NDVI highlights a double memory effect: a 1-year effect, referred to as Mem₁, and a 7- to 10-month effect, referred to as Mem₂. This article aims at better describing the influence of soil and vegetation characteristics on these two memory effects. The data sets used in this study are as follows: (1) a 19-year NDVI time series from National Oceanic and Atmospheric Administration (NOAA) satellites, (2) rainfall records from a network of 1160 rain-gauge stations compiled by the Water Research Commission (WRC), (3) vegetation types from Global Land Cover (GLC) 2000 and (4) soil characteristics from the soil and terrain database for Southern Africa (SOTERSAF). Results indicate that among 20–30% of NDVI variance that is not explained by the concurrent rainfall, one-third is explained by the two memory effects. Mem₁ is found to have maximum effect in the northwest of our study domain, near the Botswana boundary, in the South Kalahari. Associated conditions are open grasslands growing on Arenosols. Mem₁ is less important in the southeast, particularly in open grassland with shrubs growing on Cambisols. Thus, Mem₁ mainly depends on soil texture. Mem₂ is more widespread and its influence is the greatest in the centre, the south and the east of our domain. It is related to rainfall from January to April, which controls, beyond the intervening dry season, the interannual variations of NDVI (December to September) at the beginning of the next rainy season. Through these new findings, this article emphasizes again the high potential of remote-sensing techniques to monitor and understand the dynamics of semi-arid environments.     

A feasibility study on the use of anthropometric variables to make muscle–computer interface more practical

High classification accuracy has been achieved for muscle–computer interfaces (MCIs) based on surface electromyography (EMG) recognition in many recent works with an increasing number of discriminated movements. However, there are many limitations to use these interfaces in the real-world contexts. One of the major problems is compatibility. Designing and training the classification EMG system for a particular individual user is needed in order to reach high accuracy. If the system can calibrate itself automatically/semi-automatically, the development of standard interfaces that are compatible with almost any user could be possible. Twelve anthropometric variables, a measurement of body dimensions, have been proposed and used to calibrate the system in two different ways: a weighting factor for a classifier and a normalizing value for EMG features. The experimental results showed that a number of relationships between anthropometric variables and EMG time-domain features from upper-limb muscles and movements are statistically strong (average r=0.71?0.80) and significant (p<0.05). In this paper, the feasibility to use anthropometric variables to calibrate the EMG classification system is shown obviously and the proposed calibration technique is suggested to further improve the robustness and practical use of MCIs based on EMG pattern recognition.     

ARIANEXPERT: A knowledge based system to analyze ARIANE's mission data

The ARIANE launcher post mission analysis is done at ARIANESPACE. This activity is called the ‘level 0 post flight analysis’ (PFA) and is carried out after each launch by about 60 engineers who are working together under the leadership of ARIANESPACE.

The PFA is one of the most critical of ARIANE operations, for several reasons:

• - The launch rate (8 a year for ARIANE 4) leaves a very short time to carry out all the verification work. Moreover, the PFA is a mandatory step before authorizing the next launch.

• - The complexity of the ARIANE launcher results in a very high demand on the PFA engineers. Moreover, there are problems of availability of people with relevant expert knowledge (characterized by a substantial staff turn-over during the 10 year life duration of ARIANE 4) which could potentially result in errors or omissions.

It is very important to be able to take into account the experience of the preceding flights and to record the results and the knowledge accumulated for each launch.

• - The quality and the reliability of the PFA mainly depends on the accessibility of data and on the used methodology.

Because the PFA is still largely done manually, and does not benefit from improved methodologies and advanced technologies providing computerized support for data processing and diagnosis, ARIANESPACE has sponsored MATRA ESPACE for the development of a knowledge based system, called ARIANEXPERT, for supporting the PFA activity. This system combines AI techniques and numerical analysis techniques, together with advanced graphical capabilities.

A prototype has been delivered in April 1990 and has been used since 6 months by ARIANESPACE during real PFAs. Several lessons have been drawn from this operational experience and are described in this paper. They concern:

• - The utility and justification of the use of AI techniques mostly coming from the explanation capabilities and the stress put on capturing the expert knowledge.

• - The difficulties associated with the integration of such systems in the exploitation of ARIANE due to the introduction of very new tasks.

• - The user point of view which evolved from reluctant to convinced.

     

Experimental investigation of water droplet–air flow interaction in a non-reacting PEM fuel cell channel

It has been well documented that water production in PEM fuel cells occurs in discrete locations, resulting in the formation and growth of discrete droplets on the gas diffusion layer (GDL) surface within the gas flow channels (GFCs). This research uses a simulated fuel cell GFC with three transparent walls in conjunction with a high speed fluorescence photometry system to capture videos of dynamically deforming droplets. Such videos clearly show that the droplets undergo oscillatory deformation patterns. Although many authors have previously investigated the air flow induced droplet detachment, none of them have studied these oscillatory modes. The novelty of this work is to process and analyze the recorded videos to gather information on the droplets induced oscillation. Plots are formulated to indicate the dominant horizontal and vertical deformation frequency components over the range of sizes of droplets from formation to detachment. The system is also used to characterize droplet detachment size at a variety of channel air velocities. A simplified model to explain the droplet oscillation mechanism is provided as well.     

Synthesis and magnetic properties of an iron 1,2-bisthienyl perfluorocyclopentene photochromic coordination compound

The coordination compound Fe(BM-4-PTP)₂(NCS)₂⋅2MeOH (1) including the photoisomerizable ligand BM-4-PTP (1,2-bis(2′-methyl-5′-(pyrid-4″-yl)thien-3′-yl)perfluorocyclopentene) was obtained as an orange powder. The powder turns blue upon photocyclization of the 1,2-bisthienyl photochromic ligand induced by UV light irradiation at room temperature. Photocycloreversion is obtained by visible light irradiation of the material in the solid state. The orange and blue powders were investigated over the temperature range (5-293 K) and pressure range (1 bar-12 kbar) by magnetic susceptibility measurements and variable temperature ⁵⁷Fe Mössbauer spectroscopy. The photo-induced colour change is accompanied by a distinct magnetic variation at room temperature. Potentialities of this functional optical material for display and data recording are introduced.     

Study on the transformer equivalent circuit of eddy current nondestructive evaluation

The modeling of a practical configuration of nondestructive evaluation (NDE) by eddy currents (EC) generally requires extended analytical or numerical developments. This is a drawback to any understanding of the EC NDE principle and of its basic features. Nevertheless, it is possible to exploit a simple equivalent circuit based on an analogy with the operation of an electrical transformer. In this model the EC sensor constitutes the primary of the transformer whereas the evaluated conductive plate forms the transformer secondary and its electrical load. In this paper, thanks to the transformer analogy, the author obtains a simple analytical expression of the impedance of the EC sensor by using a distributed constant representation of the evaluated plate. This expression allows to exhibit some fundamental features of the EC NDE method.     

NX210c Peptide Promotes Glutamatergic Receptor-Mediated Synaptic Transmission and Signaling in the Mouse Central Nervous System

NX210c is a disease-modifying dodecapeptide derived from the subcommissural organ-spondin that is under preclinical and clinical development for the treatment of neurological disorders. Here, using whole-cell patch-clamp recordings, we demonstrate that NX210c increased α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)- and GluN2A-containing N-methyl-D-aspartate receptor (GluN2A-NMDAR)-mediated excitatory postsynaptic currents in the brain. Accordingly, using extracellular field excitatory postsynaptic potential recordings, an enhancement of synaptic transmission was shown in the presence of NX210c in two different neuronal circuits. Furthermore, the modulation of synaptic transmission and GluN2A-NMDAR-driven signaling by NX210c restored memory in mice chronically treated with the NMDAR antagonist phencyclidine. Overall, by promoting glutamatergic receptor-related neurotransmission and signaling, NX210c represents an innovative therapeutic opportunity for patients suffering from CNS disorders, injuries, and states with crippling synaptic dysfunctions.