On the magnetohydrodynamics mechanism of solar activity

Magnetohydrodynamic mechanism of solar activit

Sur les rapports existants entre les chronologies des inversions géomagnétiques, des extinctions biologiques et des glaciations

Les époques des inversions paléomagnétiques et des glaciations montrent une corrélation et présentent un décalage d'une demi-période par rapport à une oscillation de l'activité solaire de 200 000 ans

Note sur la liaison continentale Amérique du Sud-Antarctique

L'étude comparée des Antilles boréales et australes montre que l'isthme volcanique reliant, au Tertiaire, les Terres de Feu et de Graham, a été érodé par la glaciation quaternaire

Une confirmation de la doctrine de la permanence

La forme hexagonale du Pacifique et la position de l’équateur primitif permettent la reconstitution, — avant les actions glaciaires et les subsidences volcaniques, — d'un continent unique primitif ayant permis un facile peuplement du Globe, dans le cadre de la permanence des aires continentales et des fosses océaniques

Towards Outdoor Localization Using GIS, Vision System andStochastic Error Propagation

voir basilic : http://emotion.inrialpes.fr/bibemotion/2004/KDDML04/ address: Palmerston North (NZ)International audienceThe paper presents a method for robot localization (the position and attitude of the robot with respect to a model) when a robot is on the move and does not necessarily have good gps coverage. The robot discussed in the paper is a remote controlled vehicle with a GIS database and an onboard camera. The method developed starts with an initial vehicle configuration (steering wheel angle, speed) and an initial point in the GIS mapped to an initial point in the camera's image. Then, for each small displacement of the vehicle, the linear and angular velocities are calculated and a formula developed in the paper for error adjustment is applied if there is a good gps reading. The result of the calculation is used to determine the uncertainty of the location and can be used along with the 3D GIS data to project areas of uncertainty for features of interest onto the camera image. For example, say the GIS data contains fire hydrants and the calculations show that there is a high degree of location uncertainty then the camera image will have an overlay of large ellipses around the fire hydrants whereas a small degree of uncertainty would have smaller ellipses around the fire hydrants. An experiment testing the method is discussed in the paper and there is also a good review of prior work on localization techniques

Functional importance of cardiac enhancer-associated noncoding RNAs in heart development and disease.

The key information processing units within gene regulatory networks are enhancers. Enhancer activity is associated with the production of tissue-specific noncoding RNAs, yet the existence of such transcripts during cardiac development has not been established. Using an integrated genomic approach, we demonstrate that fetal cardiac enhancers generate long noncoding RNAs (lncRNAs) during cardiac differentiation and morphogenesis. Enhancer expression correlates with the emergence of active enhancer chromatin states, the initiation of RNA polymerase II at enhancer loci and expression of target genes. Orthologous human sequences are also transcribed in fetal human hearts and cardiac progenitor cells. Through a systematic bioinformatic analysis, we identified and characterized, for the first time, a catalog of lncRNAs that are expressed during embryonic stem cell differentiation into cardiomyocytes and associated with active cardiac enhancer sequences. RNA-sequencing demonstrates that many of these transcripts are polyadenylated, multi-exonic long noncoding RNAs. Moreover, knockdown of two enhancer-associated lncRNAs resulted in the specific downregulation of their predicted target genes. Interestingly, the reactivation of the fetal gene program, a hallmark of the stress response in the adult heart, is accompanied by increased expression of fetal cardiac enhancer transcripts. Altogether, these findings demonstrate that the activity of cardiac enhancers and expression of their target genes are associated with the production of enhancer-derived lncRNAs

Genome-wide profiling of the cardiac transcriptome after myocardial infarction identifies novel heart-specific long non-coding RNAs

Aim Heart disease is recognized as a consequence of dysregulation of cardiac gene regulatory networks. Previously, unappreciated components of such networks are the long non-coding RNAs (lncRNAs). Their roles in the heart remain to be elucidated. Thus, this study aimed to systematically characterize the cardiac long non-coding transcriptome post-myocardial infarction and to elucidate their potential roles in cardiac homoeostasis. Methods and results We annotated the mouse transcriptome after myocardial infarction via RNA sequencing and ab initio transcript reconstruction, and integrated genome-wide approaches to associate specific lncRNAs with developmental processes and physiological parameters. Expression of specific lncRNAs strongly correlated with defined parameters of cardiac dimensions and function. Using chromatin maps to infer lncRNA function, we identified many with potential roles in cardiogenesis and pathological remodelling. The vast majority was associated with active cardiac-specific enhancers. Importantly, oligonucleotide-mediated knockdown implicated novel lncRNAs in controlling expression of key regulatory proteins involved in cardiogenesis. Finally, we identified hundreds of human orthologues and demonstrate that particular candidates were differentially modulated in human heart disease. Conclusion These findings reveal hundreds of novel heart-specific lncRNAs with unique regulatory and functional characteristics relevant to maladaptive remodelling, cardiac function and possibly cardiac regeneration. This new class of molecules represents potential therapeutic targets for cardiac disease. Furthermore, their exquisite correlation with cardiac physiology renders them attractive candidate biomarkers to be used in the clini

HENA, heterogeneous network-based data set for Alzheimer's disease.

Alzheimer's disease and other types of dementia are the top cause for disabilities in later life and various types of experiments have been performed to understand the underlying mechanisms of the disease with the aim of coming up with potential drug targets. These experiments have been carried out by scientists working in different domains such as proteomics, molecular biology, clinical diagnostics and genomics. The results of such experiments are stored in the databases designed for collecting data of similar types. However, in order to get a systematic view of the disease from these independent but complementary data sets, it is necessary to combine them. In this study we describe a heterogeneous network-based data set for Alzheimer's disease (HENA). Additionally, we demonstrate the application of state-of-the-art graph convolutional networks, i.e. deep learning methods for the analysis of such large heterogeneous biological data sets. We expect HENA to allow scientists to explore and analyze their own results in the broader context of Alzheimer's disease research