Search Results (2)

Within the context of the Competence Centre for the Conservation of Cultural Heritage (4CH) project, the design and deployment of a platform-as-a-service cloud infrastructure for the first European competence centre of cultural heritage (CH) has begun, and some web services have been integrated into the platform. The first integrated service is the INFN-CHNet web application for FAIR storage of scientific analysis on CH: THESPIAN-Mask. It is based on CIDOC-CRM-compatible ontology and CRMhs, describing the scientific metadata. To ease the process of metadata generation and data injection, another web service has been developed: THESPIAN-NER. It is a tool based on a deep neural network for named entity recognition (NER), enabling users to upload their Italian-written report files and obtain labelled entities. Those entities are used as keywords either to serve as (semi)automatically custom queries for the database, or to fill (part of) the metadata form as a descriptor for the file to be uploaded. The services have been made freely available in the 4CH PaaS cloud platform. Full article

Despite their large size and striking markings, the identification of bumble bees (Bombus spp.) is surprisingly difficult. This is particularly true for three North American sympatric species in the subgenus Pyrobombus that are often misidentified: B. sandersoni Franklin, B. vagans Smith B. perplexus Cresson. Traditionally, the identification of these cryptic species was based on observations of differences in hair coloration and pattern and qualitative comparisons of morphological characters including malar length. Unfortunately, these characteristics do not reliably separate these species. We present quantitative morphometric methods to separate these species based on the malar length to width ratio (MRL) and the ratios of the malar length to flagellar segments 1 (MR1) and 3 (MR3) for queens and workers, and validated our determinations based on DNA barcoding. All three measurements discriminated queens of B. sandersoni and B. vagans with 100% accuracy. For workers, we achieved 99% accuracy by combining both MR1 and MR3 measurements, and 100% accuracy differentiating workers using MRL. Moreover, measurements were highly repeatable within and among both experienced and inexperienced observers. Our results, validated by genetic evidence, demonstrate that malar measurements provide accurate identifications of B. vagans and B. sandersoni. There was considerable overlap in the measurements between B. perplexus and B. sandersoni. However, these species can usually be reliably separated by combining malar ratio measurements with other morphological features like hair color. The ability to identify bumble bees is key to monitoring the status and trends of their populations, and the methods we present here advance these efforts. Full article