Earthworm community characteristics during afforestation of abandoned chalk grasslands (Upper Normandy, France)

La biomasse, la densité et la composition spécifique des vers de terre a été évaluée dans différents stades d'une succession secondaire après l'abandon d'une pelouse calcicole pâturée. La biomasse et la densité des populations de vers de terre sont très élevées (51,2 à 130,2 g/m2 et 175,8 à 522,6 ind/m2 en moyenne) dans toutes les parcelles échantillonnées. L'abandon du pâturage conduit à un rapide développement des communautés de vers. La biomase et la densité atteignent leur maximum dans une pelouse récemment mise en exclos, puis diminue dans une pelouse abandonnée depuis 50 ans. La densité croit ensuite, alors que la biomasse diminue légèrement pendant l'installation du bois de feuillus. La densité et la biomasse sont minimales sous pinède. La richesse taxonomique (nombre d'unités taxonomiques) ne change pas pendant la succession, mais la composition spécifique varie de façon nette. La dynamique des communautés de vers de terre semblent être sous l'influence de deux facteurs environnementaux prépondérants, eux-même étroitement liés à deux paramètres de la végétation : la structure verticale de la végétation (importance de la couverture du sol par la végétation herbacée, la litière, les mousses, présence d'arbres) et la qualité des litières restituées, liées à la nature de la végétation (herbacée, conifères ou feuillus). (Résumé d'auteur

Factors influencing soil macrofaunal communities in post-pastoral successions of western France

The soil macrofaunal communities (Lumbricidae, Formicidae, Coleoptera, Chilopoda, Diplopoda, Isopoda, Arachnida, Gastropoda) were studied in six plots representing different stages in theoretical post-pastoral succession chalk grassland. Macrofaunal biomass was high in all the plots (70.2-140.3 g/m2). The macroinvertebrate communities along successional gradients respond to two major environmental factors : the structure of the vegetation, which determines the diversity of microhabitats and life conditions for macroinvertebrates ; and the quality of above-ground litter production, which depends on the nature of vegetation and the presence of domestic herbivores. (Résumé d'auteur

MRI in multiple myeloma : a pictorial review of diagnostic and post-treatment findings

Magnetic resonance imaging (MRI) is increasingly being used in the diagnostic work-up of patients with multiple myeloma. Since 2014, MRI findings are included in the new diagnostic criteria proposed by the International Myeloma Working Group. Patients with smouldering myeloma presenting with more than one unequivocal focal lesion in the bone marrow on MRI are considered having symptomatic myeloma requiring treatment, regardless of the presence of lytic bone lesions. However, bone marrow evaluation with MRI offers more than only morphological information regarding the detection of focal lesions in patients with MM. The overall performance of MRI is enhanced by applying dynamic contrast-enhanced MRI and diffusion weighted imaging sequences, providing additional functional information on bone marrow vascularization and cellularity. This pictorial review provides an overview of the most important imaging findings in patients with monoclonal gammopathy of undetermined significance, smouldering myeloma and multiple myeloma, by performing a 'total' MRI investigation with implications for the diagnosis, staging and response assessment. Main message aEuro cent Conventional MRI diagnoses multiple myeloma by assessing the infiltration pattern. aEuro cent Dynamic contrast-enhanced MRI diagnoses multiple myeloma by assessing vascularization and perfusion. aEuro cent Diffusion weighted imaging evaluates bone marrow composition and cellularity in multiple myeloma. aEuro cent Combined morphological and functional MRI provides optimal bone marrow assessment for staging. aEuro cent Combined morphological and functional MRI is of considerable value in treatment follow-up

From spinal central pattern generators to cortical network: integrated BCI for walking rehabilitation

Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy

Development of the ECOSAR P-Band Synthetic Aperture Radar

This paper describes objectives and recent progress on the development of the EcoSAR, a new P-band airborne radar instrument being developed at the NASA/ Goddard Space Flight Center (GSFC) for the polarimetric and interferometric measurements of ecosystem structure and biomass. These measurements support science requirements for the study of the carbon cycle and its relationship to climate change. The instrument is scheduled to be completed and flight tested in 2013. Index Terms SAR, Digital Beamforming, Interferometry

Primitive computations in speech processing

Previous research suggests that artificial-language learners exposed to quasi-continuous speech can learn that the first and the last syllables of words have to belong to distinct classes (e.g., Endress & Bonatti, 2007; Peña, Bonatti, Nespor, & Mehler, 2002). The mechanisms of these generalizations, however, are debated. Here we show that participants learn such generalizations only when the crucial syllables are in edge positions (i.e., the first and the last), but not when they are in medial positions (i.e., the second and the fourth in pentasyllabic items). In contrast to the generalizations, participants readily perform statistical analyses also in word middles. In analogy to sequential memory, we suggest that participants extract the generalizations using a simple but specific mechanism that encodes the positions of syllables that occur in edges. Simultaneously, they use another mechanism to track the syllable distribution in the speech streams. In contrast to previous accounts, this model explains why the generalizations are faster than the statistical computations, require additional cues, and break down under different conditions, and why they can be performed at all. We also show that that similar edge-based mechanisms may explain many results in artificial-grammar learning and also various linguistic observations