A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning

Knowledge Graph Embedding (KGE) has proven to be an effective approach to solving the Knowledge Graph Completion (KGC) task. Relational patterns which refer to relations with specific semantics exhibiting graph patterns are an important factor in the performance of KGE models. Though KGE models' capabilities are analyzed over different relational patterns in theory and a rough connection between better relational patterns modeling and better performance of KGC has been built, a comprehensive quantitative analysis on KGE models over relational patterns remains absent so it is uncertain how the theoretical support of KGE to a relational pattern contributes to the performance of triples associated to such a relational pattern. To address this challenge, we evaluate the performance of 7 KGE models over 4 common relational patterns on 2 benchmarks, then conduct an analysis in theory, entity frequency, and part-to-whole three aspects and get some counterintuitive conclusions. Finally, we introduce a training-free method Score-based Patterns Adaptation (SPA) to enhance KGE models' performance over various relational patterns. This approach is simple yet effective and can be applied to KGE models without additional training. Our experimental results demonstrate that our method generally enhances performance over specific relational patterns. Our source code is available from GitHub at https://github.com/zjukg/Comprehensive-Study-over-Relational-Patterns.Comment: This paper is accepted by ISWC 202

Finite Element Analysis of Composite Frames in Wheelchair under Upward Loading

The finite element analysis is adopted in this primary study. Using the Tsai-Wu criterion and delamination criterion, the stacking sequence [45/04/-454/904]s is the final optimal design for the wheelchair frame. On the contrary, the uni-directional laminates, i.e. [9013]s, [4513]s and [-4513]s, are bad designs due to the higher failure indexes

Telomere Recombination Accelerates Cellular Aging in Saccharomyces cerevisiae

Telomeres are nucleoprotein structures located at the linear ends of eukaryotic chromosomes. Telomere integrity is required for cell proliferation and survival. Although the vast majority of eukaryotic species use telomerase as a primary means for telomere maintenance, a few species can use recombination or retrotransposon-mediated maintenance pathways. Since Saccharomyces cerevisiae can use both telomerase and recombination to replicate telomeres, budding yeast provides a useful system with which to examine the evolutionary advantages of telomerase and recombination in preserving an organism or cell under natural selection. In this study, we examined the life span in telomerase-null, post-senescent type II survivors that have employed homologous recombination to replicate their telomeres. Type II recombination survivors stably maintained chromosomal integrity but exhibited a significantly reduced replicative life span. Normal patterns of cell morphology at the end of a replicative life span and aging-dependent sterility were observed in telomerase-null type II survivors, suggesting the type II survivors aged prematurely in a manner that is phenotypically consistent with that of wild-type senescent cells. The shortened life span of type II survivors was extended by calorie restriction or TOR1 deletion, but not by Fob1p inactivation or Sir2p over-expression. Intriguingly, rDNA recombination was decreased in type II survivors, indicating that the premature aging of type II survivors was not caused by an increase in extra-chromosomal rDNA circle accumulation. Reintroduction of telomerase activity immediately restored the replicative life span of type II survivors despite their heterogeneous telomeres. These results suggest that telomere recombination accelerates cellular aging in telomerase-null type II survivors and that telomerase is likely a superior telomere maintenance pathway in sustaining yeast replicative life span