Dual Dynamic Cross-Linked Epoxy Vitrimers Used for Strong, Detachable, and Reworkable Adhesives.

Novel reprocessable thermosetting adhesives (RTAs), which combine high adhesive strength, reusability, disassembly, and recyclability features, have attracted increasing attention. However, developing RTAs with a rapidly adhesive rate while ensuring high adhesive strength and self-healing ability is still a significant challenge. Here, we prepared a novel vitrimer called DA-DTSA, which can be used as an RTA.

Modulation of poly (acrylic acid) hydrogels with κ-carrageenan for high-performance quasi-solid Al-air batteries.

Primary quasi-solid Al-air batteries using hydrogels have attracted increasing research attention owing to their high energy density, good handling, safety and reliability. However, it is still difficult to develop hydrogel electrolytes with high ionic conductivity and water retention owing to limited capacity of single material hydrogels. Herein, we report a hydrogel electrolyte of poly (acrylic acid) (PAA) is modified by κ-carrageenan (KC) for solid-state Al-air batteries.

Annotating regulatory elements by heterogeneous network embedding.

Motivation: Regulatory elements (REs), such as enhancers and promoters, are known as regulatory sequences functional in a heterogeneous regulatory network to control gene expression by recruiting transcription regulators and carrying genetic variants in a context specific way. Annotating those REs relies on costly and labor-intensive next-generation sequencing and RNA-guided editing technologies in many cellular contexts.

Results: We propose a systematic Gene Ontology Annotation method for Regulatory Elements (RE-GOA) by leveraging the powerful word embedding in natural language processing.

Matching biomedical ontologies based on formal concept analysis.

Background: The goal of ontology matching is to identify correspondences between entities from different yet overlapping ontologies so as to facilitate semantic integration, reuse and interoperability. As a well developed mathematical model for analyzing individuals and structuring concepts, Formal Concept Analysis (FCA) has been applied to ontology matching (OM) tasks since the beginning of OM research, whereas ontological knowledge exploited in FCA-based methods is limited. This motivates the study in this paper, i.

Identifying Granularity Differences between Large Biomedical Ontologies through Rules.

The objective of this study is to identify the granularity differences as well as similarity between large biomedical ontologies through rules. Two anatomical ontologies were selected, and based on a set of concept mappings obtained through simple string matching techniques, we constructed rules to distinguish among different types of subclasses and classifications. 82% of the concept mappings have exactly the same classification in subclasses between the two ontologies.

Experience in Aligning Anatomical Ontologies.

An ontology is a formal representation of a domain modeling the entities in the domain and their relations. When a domain is represented by multiple ontologies, there is need for creating mappings among these ontologies in order to facilitate the integration of data annotated with these ontologies and reasoning across ontologies. The objective of this paper is to recapitulate our experience in aligning large anatomical ontologies and to reflect on some of the issues and challenges encountered along the way.

Identifying mismatches in alignments of large anatomical ontologies.

Unlabelled: The objective of this study is to propose a model of matching errors for identifying mismatches in alignments of large anatomical ontologies. Meth-ods: Three approaches to identifying mismatches are utilized: 1) lexical, based on the presence of modifiers in the names of the concepts aligned; 2) structural, identifying conflicting relations resulting from the alignment; and 3) semantic, based on disjoint top-level categories across ontologies.

Results: 83% of the potential mismatches identified by the HMatch system are identified by at least one of the approaches.

The foundational model of anatomy in OWL: Experience and perspectives.

We present the method developed for migrating the Foundational Model of Anatomy (FMA) from its representation with frames in Protégé to its logical representation in OWL and our experience in reasoning with it. Despite the extensive use of metaclasses in Protégé, it proved possible to convert the FMA from Protégé into OWL DL, while capturing most of its original features. The conversion relies on a set of translation and enrichment rules implemented with flexible options.

Lessons learned from cross-validating alignments between large anatomical ontologies.

Objectives: To compare the alignments of two large anatomical ontologies (the Foundational Model of Anatomy and GALEN) produced by three ontology alignment systems (AOAS, FALCON and PRIOR) in the framework of the Ontology Alignment Evaluation Initiative during its 2006 campaign.

Materials: Number of mappings identified by AOAS: 3,132, FALCON: 2,518 and PRIOR: 2,589.

Methods: Three approaches to analyzing and comparing the results were utilized: computing the overlap among result files, manual review of some 2,000 mappings and structural validation.

Comparing two approaches for aligning representations of anatomy.

Objective: To analyze the comparison, through their results, of two distinct approaches applied to aligning two representations of anatomy.

Materials: Both approaches use a combination of lexical and structural techniques. In addition, the first approach takes advantage of domain knowledge, while the second approach treats alignment as a special case of schema matching.

Comparing the representation of anatomy in the FMA and SNOMED CT.

Objective: This paper reports on the alignment between two large ontologies of anatomy: the Foundational Model of Anatomy (FMA) and the representation of anatomical structures in SNOMED CT. The objective of this study is to investigate the compatibility between a reference ontology of anatomy (the FMA, 75,019 concepts) and a representation of anatomy created for use in clinical applications (SNOMED CT, 30,933 anatomical concepts).

Methods: The alignment first identifies shared concepts lexically.

Experience in reasoning with the foundational model of anatomy in OWL DL.

The objective of this study is to compare description logics (DLs) and frames for representing large-scale biomedical ontologies and reasoning with them. The ontology under investigation is the Foundational Model of Anatomy (FMA). We converted it from its frame-based representation in Protégé into OWL DL.

Alignment of multiple ontologies of anatomy: deriving indirect mappings from direct mappings to a reference.

Objective: To investigate the indirect alignment of two anatomical ontologies through a reference ontology and to compare it to direct alignment between these two ontologies. The ontologies under investigation are the Adult Mouse Anatomical Dictionary (MA) and the NCI Thesaurus (NCI). The Foundational Model of Anatomy serves as reference ontology.

Of mice and men: aligning mouse and human anatomies.

This paper reports on the alignment between mouse and human anatomies, a critical resource for comparative science as diseases in mice are used as mod-els of human disease. The two ontologies under investigation are the NCI Thesaurus (human anatomy) and the Adult Mouse Anatomical Dictionary, each comprising about 2500 anatomical concepts. This study compares two approaches to aligning ontologies.

Law and order: assessing and enforcing compliance with ontological modeling principles in the Foundational Model of Anatomy.

The objective of this study is to provide an operational definition of principles with which well-formed ontologies should comply. We define 15 such principles, related to classification (e.g.

Comparing associative relationships among equivalent concepts across ontologies.

Methods for comparing associative relationships across ontologies often rely solely on lexical similarity between the names of the relationships, which may lead to missed matches and inaccurate matches. In this paper, we propose a novel method based on the analysis of paths between equivalent concepts across ontologies. Patterns of relationships are identified for each associative relationship.

Aligning representations of anatomy using lexical and structural methods.

Objective: The objective of this experiment is to develop methods for aligning two representations of anatomy (the Foundational Model of Anatomy and GALEN) at the lexical and structural level.

Methods: The alignment consists of the following four steps: 1)acquiring terms, 2) identifying anchors (i.e.