EXECUTABLE ARCHIVES: Software integrity for data readability and validation of archived studies

© 2021 author(s). The text of this paper is published under a CC-BY license (https://creativecommons.org/licenses/by/4.0/)This paper presents practices and processes for managing software integrity to support data archiving for long term use in response to the regulatory requirements. Through a case study of a scientific software decommissioning, we revisit the issues of archived data readability. Established software lifecycle management processes are extended with archiving and data integrity requirements for retention of data and revalidation of data analyses. That includes the software transition from operational to archival use within the Executable Archive model that extends the traditional data archive with computing environments with software installations required to reproduce study results from the archived records. The content use requirements are an integral part of both data access and the software management considerations, assuring that data integrity is fully supported by the software integrityPeer reviewe

Contextual Knowledge Learning For Dialogue Generation

Incorporating conversational context and knowledge into dialogue generation models has been essential for improving the quality of the generated responses. The context, comprising utterances from previous dialogue exchanges, is used as a source of content for response generation and as a means of selecting external knowledge. However, to avoid introducing irrelevant content, it is key to enable fine-grained scoring of context and knowledge. In this paper, we present a novel approach to context and knowledge weighting as an integral part of model training. We guide the model training through a Contextual Knowledge Learning (CKL) process which involves Latent Vectors for context and knowledge, respectively. CKL Latent Vectors capture the relationship between context, knowledge, and responses through weak supervision and enable differential weighting of context utterances and knowledge sentences during the training process. Experiments with two standard datasets and human evaluation demonstrate that CKL leads to a significant improvement compared with the performance of six strong baseline models and shows robustness with regard to reduced sizes of training sets.Comment: 9 pages, 4 figures, 6 tables. Accepted as a full paper in the main conference by ACL 202

Impaired Insulin sensitivity and Insulin secretion in Haemodialysis patients with and without Secondary Hyperparathyroidism

The aim of our study was to investigate insulin sensitivity and beta cell function in hemodialysis (HD) patients without diabetes. We hypothesized that parathyroid gland function was a determinant of insulin sensitivity and/or beta cell function. The study was a randomized, cross-sectional one and patients were divided into two groups (total 27 patients), Gp.1 being those with relative hypoparathyroidism (iPTH<200 pg/ml) ­ 9 (33.3%), Gp.2 those with hyperparathyroidism (iPTH200 pg/ml) ­ 18 (66.6%) with Gp.3 (consisting of 43 healthy subjects acting as controls). Insulin resistance and insulin secretion were calculated from fasting serum insulin and glucose concentrations by the Homeostatic Model Assessment score (HOMA IR and HOMA BETA). The value of HOMA IR (3.28±1.3 for Gp.1, 4.80±2.4 for Gp.2, 1.70±0.8 for Gp.3) as well as the glucose level (5.0±1.0mmol/l in Gp.1, 5.2±0.8mmol/ l in Gp.2, 4.6±0.4mmol/l in Gp.3) was significantly higher in HD patients than in control subjects. Excessive insulin secretion was present in HD patients (as assessed by HOMA BETA) significantly higher only in Gp.1 (p=0.02).peer-reviewe