Scalable Dynamic Mixture Model with Full Covariance for Probabilistic Traffic Forecasting

Deep learning-based multivariate and multistep-ahead traffic forecasting models are typically trained with the mean squared error (MSE) or mean absolute error (MAE) as the loss function in a sequence-to-sequence setting, simply assuming that the errors follow an independent and isotropic Gaussian or Laplacian distributions. However, such assumptions are often unrealistic for real-world traffic forecasting tasks, where the probabilistic distribution of spatiotemporal forecasting is very complex with strong concurrent correlations across both sensors and forecasting horizons in a time-varying manner. In this paper, we model the time-varying distribution for the matrix-variate error process as a dynamic mixture of zero-mean Gaussian distributions. To achieve efficiency, flexibility, and scalability, we parameterize each mixture component using a matrix normal distribution and allow the mixture weight to change and be predictable over time. The proposed method can be seamlessly integrated into existing deep-learning frameworks with only a few additional parameters to be learned. We evaluate the performance of the proposed method on a traffic speed forecasting task and find that our method not only improves model performance but also provides interpretable spatiotemporal correlation structures.Comment: 11 pages, 4 figures, 2 tabl

Le « national » et l’« international » dans les sciences sociales

M. Pierre-Yves Saunier est professeur agrégé au département des sciences historiques de l'Université Laval à Québec. Cet entretien a été réalisé par Vincent Houle, doctorant en histoire en cotutelle entre l'Université Paris 1 Panthéon-Sorbonne (SIRICE) et l'Université de Montréal, Solène Maillet, doctorante en histoire à l’Université de Montréal et à l’Institut national des langues et civilisations orientales (Inalco, Paris), et Guillemette Martin, titulaire d'un Doctorat en Histoire contemporaine obtenu en 2013 à l’IHEAL (Institut des Hautes Études de l’Amérique Latine- Université Paris III Sorbonne Nouvelle) et enseignante et chercheuse dans le Département d’Histoire de la Universidad Iberoamericana à Mexico. &nbsp

First Application of high resolution BRDF Algorithm (HABA) for reflectance normalization on a Fusion dataset from the Sen2Like Processor

Normalized Bidirectional Adjusted Reflectance (NBAR) is a key parameter for a consistent time series monitoring over non-lambertian surfaces. The Sen2like is a Virtual Constellation (VC) which harmonizes and fuses Landsat 8 / Landsat 9 & Sentinel 2 dataset giving out a higher spatial and temporal resolution surface reflectance. However, for adequate monitoring of land surface is necessary the correction of sun and sensor angle view across the VC acquisitions. In this context, the High resolution Adjusted BRDF Algorithm (HABA) provides up to 10m NBAR product retrieved from the disaggregation of the Bidirectional Reflectance Distribution Function (BRDF) parameters based on the VJB method applied to MODIS M{O,Y} D09 Climate Model Grid (CMG) at 1km resolution. HABA downscales this product to Sen2Like resolution inverting BRDF parameters (V & R) using the k-means unsupervised classification for each dataset. In order to compensate for the impact on images that do not present sufficient data representativeness due to cloud coverage, the disaggregated parameters are stabilized computing linear trends of time series of Normalized Difference Vegetation Index (NDVI) versus V & R. The model was evaluated on stable sites, such as Sahara Desert (Libya) and Amazonian Forest (Brazil) by comparing the impact of View Zenith Angle (VZA) and Solar Zenith Angle (SZA) of directional reflectance, a static NBAR model and HABA for Near InfraRed (NIR) and red spectrum. Also, the Sen2Like performance was assessed on dynamic sites with a mosaic of land covers across the Belgium tiles, calculating the absolute difference per tile in a 5-day window. The results of stable sites show a decline of linear dependency on the Amazon VZA from R² 0.57 (directional) to 0.37 (HABA) in NIR and R² 0.04 (directional) to 0.0 (HABA) in red. The Sahara Desert showed a correction of 4% of linear dependency of SZA versus reflectance. Finally, in Belgium, HABA corrected up to 12,74 % the directional effect on the time series. This work contributes to develop a dynamic and operationalization of NBAR correction method based on pixel scale for high resolution datasets

Sen2Like: Paving the Way towards Harmonization and Fusion of Optical Data

Satellite Earth Observation (EO) sensors are becoming a vital source of information for land surface monitoring. The concept of the Virtual Constellation (VC) is gaining interest within the science community owing to the increasing number of satellites/sensors in operation with similar characteristics. The establishment of a VC out of individual missions offers new possibilities for many application domains, in particular in the fields of land surface monitoring and change detection. In this context, this paper describes the Copernicus Sen2Like algorithms and software, a solution for harmonizing and fusing Landsat 8/Landsat 9 data with Sentinel-2 data. Developed under the European Union Copernicus Program, the Sen2Like software processes a large collection of Level 1/Level 2A products and generates high quality Level 2 Analysis Ready Data (ARD) as part of harmonized (Level 2H) and/or fused (Level 2F) products providing high temporal resolutions. For this purpose, we have re-used and developed a broad spectrum of data processing and analysis methodologies, including geometric and spectral co-registration, atmospheric and Bi-Directional Reflectance Distribution Function (BRDF) corrections and upscaling to 10 m for relevant Landsat bands. The Sen2Like software and the algorithms have been developed within a VC establishment framework, and the tool can conveniently be used to compare processing algorithms in combinations. It also has the potential to integrate new missions from spaceborne and airborne platforms including unmanned aerial vehicles. The validation activities show that the proposed approach improves the temporal consistency of the multi temporal data stack, and output products are interoperable with the subsequent thematic analysis processes

The genetic landscape and clinical spectrum of nephronophthisis and related ciliopathies

Nephronophthisis (NPH) is an autosomal-recessive ciliopathy representing one of the most frequent causes of kidney failure in childhood characterized by a broad clinical and genetic heterogeneity. Applied to one of the worldwide largest cohorts of patients with NPH, genetic analysis encompassing targeted and whole exome sequencing identified disease-causing variants in 600 patients from 496 families with a detection rate of 71%. Of 788 pathogenic variants, 40 known ciliopathy genes were identified. However, the majority of patients (53%) bore biallelic pathogenic variants in NPHP1. NPH-causing gene alterations affected all ciliary modules defined by structural and/or functional subdomains. Seventy six percent of these patients had progressed to kidney failure, of which 18% had an infantile form (under five years) and harbored variants affecting the Inversin compartment or intraflagellar transport complex A. Forty eight percent of patients showed a juvenile (5-15 years) and 34% a late-onset disease (over 15 years), the latter mostly carrying variants belonging to the Transition Zone module. Furthermore, while more than 85% of patients with an infantile form presented with extra-kidney manifestations, it only concerned half of juvenile and late onset cases. Eye involvement represented a predominant feature, followed by cerebellar hypoplasia and other brain abnormalities, liver and skeletal defects. The phenotypic variability was in a large part associated with mutation types, genes and corresponding ciliary modules with hypomorphic variants in ciliary genes playing a role in early steps of ciliogenesis associated with juvenile-to-late onset NPH forms. Thus, our data confirm a considerable proportion of late-onset NPH suggesting an underdiagnosis in adult chronic kidney disease

Estrogenic Plant Extracts Reverse Weight Gain and Fat Accumulation without Causing Mammary Gland or Uterine Proliferation

Long-term estrogen deficiency increases the risk of obesity, diabetes and metabolic syndrome in postmenopausal women. Menopausal hormone therapy containing estrogens might prevent these conditions, but its prolonged use increases the risk of breast cancer, as wells as endometrial cancer if used without progestins. Animal studies indicate that beneficial effects of estrogens in adipose tissue and adverse effects on mammary gland and uterus are mediated by estrogen receptor alpha (ERα). One strategy to improve the safety of estrogens to prevent/treat obesity, diabetes and metabolic syndrome is to develop estrogens that act as agonists in adipose tissue, but not in mammary gland and uterus. We considered plant extracts, which have been the source of many pharmaceuticals, as a source of tissue selective estrogens. Extracts from two plants, Glycyrrhiza uralensis (RG) and Pueraria montana var. lobata (RP) bound to ERα, activated ERα responsive reporters, and reversed weight gain and fat accumulation comparable to estradiol in ovariectomized obese mice maintained on a high fat diet. Unlike estradiol, RG and RP did not induce proliferative effects on mammary gland and uterus. Gene expression profiling demonstrated that RG and RP induced estradiol-like regulation of genes in abdominal fat, but not in mammary gland and uterus. The compounds in extracts from RG and RP might constitute a new class of tissue selective estrogens to reverse weight gain, fat accumulation and metabolic syndrome in postmenopausal women

Nord-Pas-de-Calais, Thérouanne, parcelle AB 232 : rapport de diagnostic

Ce nouveau diagnostic rue Saint-Jean offre un regard supplémentaire sur les vestiges archéologiques du secteur de la vieille ville. Les quatre fenêtres d'observations associés au trois sondages mécaniques ont permis de mettre en évidence une occupation médiévale stratifiée et d'observer en plusieurs endroits le niveau d'apparition des vestiges gallo-romains.Les niveaux antiques apparaissent à une profondeur comprise entre 2 m et 2,5 m. L’exiguïté des surfaces abordées n'a pas permis de caractériser précisément ces niveaux. On notera la présence d'un niveau de sol incendié, scellé par un remblai de démolition rubéfié. Les échantillons de céramique collectés dans ces sondages sont peu abondants et n'ont pas permis d'effectuer une datation précise de ces niveaux. Ces vestiges pourraient néanmoins être contemporains des niveaux incendiés du IIIe siècle de notre ère observés lors de précédentes interventions archéologiques sur des parcelles jouxtant la rue Saint-Jean.La période médiévale est caractérisée par la présence de vestiges datés par la céramique des XIVe et XVIe siècle. Les niveaux du XVIe siècle correspondent au dernier état de la ville avant la destruction de celle-ci par les troupes de Charles Quint en 1553. Il s'agit principalement de murs et de niveaux de sol. Ces derniers témoignent de la présence d'habitat domestique dans cette partie de la ville. Dans l'ensemble, les murs sont conservés au niveau de leur fondation. Le nombre important de maçonneries observé durant le diagnostic n'a toutefois pas permis de reconnaître un plan de bâtiment complet. Tous les murs contemporains de cette période sont orientés selon les mêmes axes. Ces orientations correspondent notamment à I'axe de la rue médiévale. Le sondage réalisé dans les niveaux de voirie révèle un bon état de conservation de celle-ci

Blooming of Irganox 3114® antioxidant onto a medical grade elastomer. Impact of the recrystallization conditions on the antioxidant polymorphism, on the film wettability and on the antioxidant leachability

No commentInternational audienceStudying the blooming and recrystallization of additives onto the surface of polymer medical devices is of a great interest because it can affect the biocompatibility of the material. The polymorphism of a phenolic antioxidant (Irganox 3114®) used as an additive in medical devices and pharmaceutical packaging was studied: two different polymorphs were characterized by differential scanning measurements, FTIR and X-ray diffraction analyses. Then, the behavior of the additive in medical grade polyurethane films was described: a recrystallization into the stable polymorphic form was observed onto the polymer surface after annealing at different temperatures. The morphology observed depends not only on the additive/polymer ratio but also on the whole amount of additive in the polymer film. Depending on the recrystallization morphology, the wettability with water could be lowered and the leachability of the additives into aqueous media could be favored. © 2012 Elsevier B.V. All rights reserved