A cooperative-relational approach to digital libraries

Copyright @ 2007 Springer-Verlag, Berlin HeidelbergThis paper presents a novel approach to model-driven development of Digital Library (DL) systems. The overall idea is to allow Digital Library systems designers (e.g. information architects, librarians, domain experts) to easily design such systems by using a visual language. We designed a Domain Specific Visual Language for such a purpose and developed a framework supporting it; this framework helps designers by automatically generating code for the defined Digital Library system, so that they do not have to get involved into technical issues concerning its deployment. In our approach, both Human-Computer Interaction and Computer Supported Collaborative Work techniques are exploited when generating interfaces and services for the specific Digital Library domain

A multi-layered Bayesian network model for structured document retrieval

New standards in document representation, like for example SGML, XML, and MPEG-7, compel Information Retrieval to design and implement models and tools to index, retrieve and present documents according to the given document structure. The paper presents the design of an Information Retrieval system for multimedia structured documents, like for example journal articles, e-books, and MPEG-7 videos. The system is based on Bayesian Networks, since this class of mathematical models enable to represent and quantify the relations between the structural components of the document. Some preliminary results on the system implementation are also presented

mRNA vaccination drives differential mucosal neutralizing antibody profiles in naïve and SARS-CoV-2 previously-infected individuals

Two doses of BNT162b2 mRNA vaccine induces a strong systemic SARS-CoV-2 specific humoral response. However, SARS-CoV-2 airborne transmission makes mucosal immune response a crucial first line of defense. Therefore, we characterized SARS-CoV-2-specific IgG responses induced by BNT162b2 vaccine, as well as IgG responses to other pathogenic and seasonal human coronaviruses in oral fluid and plasma from 200 UK healthcare workers who were naïve (N=62) or previously infected with SARS-CoV-2 (N=138) using a pan-coronavirus multiplex binding immunoassay (Meso Scale Discovery®). Additionally, we investigated the impact of historical SARS-CoV-2 infection on vaccine-induced IgG, IgA and neutralizing responses in selected oral fluid samples before vaccination, after a first and second dose of BNT162b2, as well as following a third dose of mRNA vaccine or breakthrough infections using the same immunoassay and an ACE2 inhibition assay. Prior to vaccination, we found that spike-specific IgG levels in oral fluid positively correlated with IgG levels in plasma from previously-infected individuals (Spearman r=0.6858, p<0.0001) demonstrating that oral fluid could be used as a proxy for the presence of plasma SARS-CoV-2 IgG. However, the sensitivity was lower in oral fluid (0.85, 95% CI 0.77-0.91) than in plasma (0.94, 95% CI 0.88-0.97). Similar kinetics of mucosal and systemic spike-specific IgG levels were observed following vaccination in naïve and previously-infected individuals, respectively. In addition, a significant enhancement of OC43 and HKU1 spike-specific IgG levels was observed in previously-infected individuals following one vaccine dose in oral fluid (OC43 S: p<0.0001; HKU1 S: p=0.0423) suggesting cross-reactive IgG responses to seasonal beta coronaviruses. Mucosal spike-specific IgA responses were induced by mRNA vaccination particularly in previously-infected individuals (71%) but less frequently in naïve participants (23%). Neutralizing responses to SARS-CoV-2 ancestral and variants of concerns were detected following vaccination in naïve and previously-infected participants, with likely contribution from both IgG and IgA in previously-infected individuals (correlations between neutralizing responses and IgG: Spearman r=0.5642, p<0.0001; IgA: Spearman r=0.4545, p=0.0001). We also observed that breakthrough infections or a third vaccine dose enhanced mucosal antibody levels and neutralizing responses. These data contribute to show that a previous SARS-CoV-2 infection tailors the mucosal antibody profile induced by vaccination

A multilayered Bayesian network model for structured document retrieval

Abstract. New standards in document representation, like for example SGML, XML, and MPEG-7, compel Information Retrieval to design and implement models and tools to index, retrieve and present documents according to the given document structure. The paper presents the design of an Information Retrieval system for multimedia structured documents, like for example journal articles, e-books, and MPEG-7 videos. The system is based on Bayesian Networks, since this class of mathematical models enable to represent and quantify the relations between the structural components of the document. Some preliminary results on the system implementation are also presented.

Improving Document Transformation Techniques with Collaborative Learned Term-based Concepts. In

Abstract. Document Transformation techniques have been studied for decades. In this paper, a new approach for a significant improvement is presented based on using a new query expansion method. In contrast to other methods, the regarded query is expanded by adding those terms that are most similar to the concept of individual query terms, rather than selecting terms that are similar to the complete query or that are directly similar to the query terms. Experiments have shown that Document Transformation techniques are significantly improved in the retrieval effectiveness when measuring the recall-precision.