Introducing sufficiency in the building sector in net-zero scenarios for France

International audienceIn France, the building sector (residential and commercial) represented 16% of carbon emissions in 2015 (use-phase). The building sector therefore has a major role to play in the carbon transition by acting on all available levers: sufficiency, efficiency, decarbonised energy and carbon sinks. How much can the sector contribute to the overall goal of carbon neutrality by 2050? The article presents findings from Transition(s) 2050, a set of scenarios developed for the whole economy by ADEME, the French Environmental Transition Agency. It focuses on sufficiency: which role can it play in the decarbonation of the building sector, both in the use-phase and beyond? What would enabling conditions be?Sufficiency can contribute to achieve further energy savings compared to “efficiency-only” scenarios in areas such as domestic electrical appliances or space cooling, hence easing the wider decarbonation effort. Furthermore, sufficiency has systemic implications beyond the use-phase. It contributes to decreasing energy consumption in the industrial sector, as building less has direct impact on the demand for construction material. It also has impact on other resources such as land. Land take and building waste are significantly lower in the most sufficient scenarios. However, implementing sufficiency requires profound changes both in policies for the building sector and the way these policies are designed

Can real time molecular analyses change the paradigm of dog sarcoma diagnosis and classification?

International audienc

Real-Time Molecular Diagnosis of Tumors Using Water-Assisted Laser Desorption/Ionization Mass Spectrometry Technology

International audienceHistopathological diagnosis of biopsy samples and margin assessment of surgical specimens are challenging aspects in sarcoma. Using dog patient tissues, we assessed the performance of a recently developed technology for fast ex vivo molecular lipid-based diagnosis of sarcomas. The instrument is based on mass spectrometry (MS) molecular analysis through a laser microprobe operating under ambient conditions using excitation of endogenous water molecules. Classification models based on cancer/normal/necrotic, tumor grade, and subtypes showed a minimum of 97.63% correct classification. Specific markers of normal, cancer, and necrotic regions were identified by tandem MS and validated by MS imaging. Real-time detection capabilities were demonstrated by ex vivo analysis with direct interrogation of classification models

Linked Open Data Validity -- A Technical Report from ISWS 2018

Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied by a URI and accessible via HTTP. LOD encodes globalscale knowledge potentially available to any human as well as artificial intelligence that may want to benefit from it as background knowledge for supporting their tasks. LOD has emerged as the backbone of applications in diverse fields such as Natural Language Processing, Information Retrieval, Computer Vision, Speech Recognition, and many more. Nevertheless, regardless of the specific tasks that LOD-based tools aim to address, the reuse of such knowledge may be challenging for diverse reasons, e.g. semantic heterogeneity, provenance, and data quality. As aptly stated by Heath et al. Linked Data might be outdated, imprecise, or simply wrong": there arouses a necessity to investigate the problem of linked data validity. This work reports a collaborative effort performed by nine teams of students, guided by an equal number of senior researchers, attending the International Semantic Web Research School (ISWS 2018) towards addressing such investigation from different perspectives coupled with different approaches to tackle the issue

Linked Open Data Validity -- A Technical Report from ISWS 2018

Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied by a URI and accessible via HTTP. LOD encodes globalscale knowledge potentially available to any human as well as artificial intelligence that may want to benefit from it as background knowledge for supporting their tasks. LOD has emerged as the backbone of applications in diverse fields such as Natural Language Processing, Information Retrieval, Computer Vision, Speech Recognition, and many more. Nevertheless, regardless of the specific tasks that LOD-based tools aim to address, the reuse of such knowledge may be challenging for diverse reasons, e.g. semantic heterogeneity, provenance, and data quality. As aptly stated by Heath et al. Linked Data might be outdated, imprecise, or simply wrong": there arouses a necessity to investigate the problem of linked data validity. This work reports a collaborative effort performed by nine teams of students, guided by an equal number of senior researchers, attending the International Semantic Web Research School (ISWS 2018) towards addressing such investigation from different perspectives coupled with different approaches to tackle the issue