Connaissances géospatiales dans les annonces immobilières : détection et extraction d’information spatiale à partir du texte

International audienceWe proposed a workflow to extract geospatial knowledge from text applied to Real Estate advertisements. We first extracted geographic and spatial entities using a model based on a BiLSTM-CRF architecture with a concatenation of se-veral text representations. Secondly, we performed relations extraction, particularly spatial relations extraction, to build a structured Geospatial knowledge base that we stored in a RDF Knowledge Graph.Nous avons proposé un modèle d’extraction de connaissances géospatiales à parir du texte appliqué au cas des annonces immobilières. La première étape consiste à extraire les entités géographiques et spatiales à l’aide d’un modèlebasé sur une architecture BiLSTM-CRF et la concaténation de plusieurs embeddings. Ensuite, nous avons réalisé l’extraction de relations, notamment spatiales, pour créer une base de connaissance géospatiale structurée stockéedans un graphe de connaissance RDF

Impact of a catch-up strategy of DT-IPV vaccination during hospitalization on vaccination coverage among people over 65 years of age in france: The HOSPIVAC study (Vaccination during hospitalization)

In France, diphtheria tetanus and inactivated polio vaccine (DT-IPV) coverage and immunization are insufficient in the elderly and decrease with age. The principal objective of this study was to assess the impact of a strategy of catch-up DT-IPV vaccination during hospitalization in people over the age of 65 years in central France (the Sarthe region). We performed a prospective, single-center, cluster-randomized study (four hospital wards). We included patients aged ≥65 years, without mental impairment, contraindication and who accepted to participate, hospitalized in the internal medicine wards in Le Mans Hospital from 28 May 2018 to 27 May 2019. The DT-IPV vaccination status of the patients was determined at inclusion and the wards were randomized (intervention and control). In the intervention group, vaccination was up-dated during hospitalization. In case of temporary contraindication, vaccination was prescribed at hospital discharge. Patients hospitalized in the control wards received oral information only. Final immunization status was determined by calling the patient’s general practitioner two months after hospital discharge. One hundred and fifty seven patients were included: 73 in the intervention and 84 in the control arm. Baseline immunization coverage was 46.5%. Vaccination coverage increased from 56.2% to 80.8% in the intervention group and from 38.1% to 40.5% in the control group (p < 0.001). Having received sufficient information from the general practitioner was the only factor associated with vaccination being up-to-date in uni- and multivariate analysis: OR = 5.07 [2.45–10.51]. In a setting of low vaccination coverage DT-IPV vaccination during hospitalization is an effective catch-up strategy

Loss of ATF2 Function Leads to Cranial Motoneuron Degeneration during Embryonic Mouse Development

The AP-1 family transcription factor ATF2 is essential for development and tissue maintenance in mammals. In particular, ATF2 is highly expressed and activated in the brain and previous studies using mouse knockouts have confirmed its requirement in the cerebellum as well as in vestibular sense organs. Here we present the analysis of the requirement for ATF2 in CNS development in mouse embryos, specifically in the brainstem. We discovered that neuron-specific inactivation of ATF2 leads to significant loss of motoneurons of the hypoglossal, abducens and facial nuclei. While the generation of ATF2 mutant motoneurons appears normal during early development, they undergo caspase-dependent and independent cell death during later embryonic and foetal stages. The loss of these motoneurons correlates with increased levels of stress activated MAP kinases, JNK and p38, as well as aberrant accumulation of phosphorylated neurofilament proteins, NF-H and NF-M, known substrates for these kinases. This, together with other neuropathological phenotypes, including aberrant vacuolisation and lipid accumulation, indicates that deficiency in ATF2 leads to neurodegeneration of subsets of somatic and visceral motoneurons of the brainstem. It also confirms that ATF2 has a critical role in limiting the activities of stress kinases JNK and p38 which are potent inducers of cell death in the CNS

Rapamycin and the transcription factor C/EBPβ as a switch in osteoclast differentiation: implications for lytic bone diseases

Lytic bone diseases and in particular osteoporosis are common age-related diseases characterized by enhanced bone fragility due to loss of bone density. Increasingly, osteoporosis poses a major global health-care problem due to the growth of the elderly population. Recently, it was found that the gene regulatory transcription factor CCAAT/enhancer binding protein beta (C/EBPβ) is involved in bone metabolism. C/EBPβ occurs as different protein isoforms of variable amino terminal length, and regulation of the C/EBPβ isoform ratio balance was found to represent an important factor in osteoclast differentiation and bone homeostasis. Interestingly, adjustment of the C/EBPβ isoform ratio by the process of translational control is downstream of the mammalian target of rapamycin kinase (mTOR), a sensor of the nutritional status and a target of immunosuppressive and anticancer drugs. The findings imply that modulating the process of translational control of C/EBPβ isoform expression could represent a novel therapeutic approach in osteolytic bone diseases, including cancer and infection-induced bone loss

Post-disaster social recovery: disaster governance lessons learnt from Tropical Cyclone Yasi

Post-disaster social recovery remains the least understood of the disaster phases despite increased risks of extreme events leading to disasters due to climate change. This paper contributes to advance this knowledge by focusing on the disaster recovery process of the Australian coastal town of Cardwell which was affected by category 4/5 Tropical Cyclone Yasi in 2011. Drawing on empirical data collected through semi-structured interviews with Cardwell residents post-Yasi, it examines issues related to social recovery in the first year of the disaster and 2 years later. Key findings discuss the role played by community members, volunteers and state actors in Cardwell’s post-disaster social recovery, especially with respect to how current disaster risk management trends based on self-reliance and shared responsibility unfolded in the recovery phase. Lessons learnt concerning disaster recovery governance are then extracted to inform policy implementation for disaster risk management to support social recovery and enhance disaster resilience in the light of climate change

Connaissances géospatiales dans les annonces immobilières : détection et extraction d’information spatiale à partir du texte

International audienceWe proposed a workflow to extract geospatial knowledge from text applied to Real Estate advertisements. We first extracted geographic and spatial entities using a model based on a BiLSTM-CRF architecture with a concatenation of se-veral text representations. Secondly, we performed relations extraction, particularly spatial relations extraction, to build a structured Geospatial knowledge base that we stored in a RDF Knowledge Graph.Nous avons proposé un modèle d’extraction de connaissances géospatiales à parir du texte appliqué au cas des annonces immobilières. La première étape consiste à extraire les entités géographiques et spatiales à l’aide d’un modèlebasé sur une architecture BiLSTM-CRF et la concaténation de plusieurs embeddings. Ensuite, nous avons réalisé l’extraction de relations, notamment spatiales, pour créer une base de connaissance géospatiale structurée stockéedans un graphe de connaissance RDF

Geospatial Knowledge in Housing Advertisements: Capturing and Extracting Spatial Information from Text

International audienceInformation of the geographical and spatial type is found in numerous text documents and constitutes a very challenging target for extraction. Geoparsing applications have been developed to extract geographic terms. However, off-the-shelf Named Entity Recognition (NER) models are mainly designed for Toponym recognition and are very sensitive to language specificity. In this paper, we propose a workflow to first extract geographic and spatial entities based on a BiLSTM-CRF architecture with a concatenation of several text representations. We also propose a Relation Extraction module, particularly aimed at spatial relationships extraction, to build a structured Geospatial knowledge base. We demonstrate our pipeline by applying it to the case of French housing advertisements, which generally provide information about a property's location and neighbourhood. Our results show that the workflow tackles French language and the variability and irregularity of housing advertisements, generalizes Geoparsing to all geographic and spatial terms, and successfully retrieves most of the relationships between entities from the text

Perception of the communities exposed to forest fires

Peer reviewe