Applying semantic web services to enterprise web

Enterprise Web provides a convenient, extendable, integrated platform for information sharing and knowledge management. However, it still has many drawbacks due to complexity and increasing information glut, as well as the heterogeneity of the information processed. Research in the field of Semantic Web Services has shown the possibility of adding higher level of semantic functionality onto the top of current Enterprise Web, enhancing usability and usefulness of resource, enabling decision support and automation. This paper aims to explore the use of Semantic Web Services in Enterprise Web and discuss the Semantic Web Services (SWS) approach for designing Enterprise Web applications. A Semantic Web Service oriented model is presented, in which resources and services are described by ontology, and processed through Semantic Web Service, allowing integrated administration, interoperability and automated reasoning

Levenshtein Distance Embedding with Poisson Regression for DNA Storage

Efficient computation or approximation of Levenshtein distance, a widely-used metric for evaluating sequence similarity, has attracted significant attention with the emergence of DNA storage and other biological applications. Sequence embedding, which maps Levenshtein distance to a conventional distance between embedding vectors, has emerged as a promising solution. In this paper, a novel neural network-based sequence embedding technique using Poisson regression is proposed. We first provide a theoretical analysis of the impact of embedding dimension on model performance and present a criterion for selecting an appropriate embedding dimension. Under this embedding dimension, the Poisson regression is introduced by assuming the Levenshtein distance between sequences of fixed length following a Poisson distribution, which naturally aligns with the definition of Levenshtein distance. Moreover, from the perspective of the distribution of embedding distances, Poisson regression approximates the negative log likelihood of the chi-squared distribution and offers advancements in removing the skewness. Through comprehensive experiments on real DNA storage data, we demonstrate the superior performance of the proposed method compared to state-of-the-art approaches

The Tensor Current Divergence Equation in U(1) Gauge Theories is Free of Anomalies

The possible anomaly of the tensor current divergence equation in U(1) gauge theories is calculated by means of perturbative method. It is found that the tensor current divergence equation is free of anomalies.Comment: Revtex4, 7 pages, 2 figure

Cost-effectiveness of unselected multigene germline and somatic genetic testing for epithelial ovarian cancer

Background : Parallel panel germline and somatic genetic testing of all patients with ovarian cancer (OC) can identify more pathogenic variants (PVs) that would benefit from PARP inhibitor (PARPi) therapy, and allow for precision prevention in unaffected relatives with PVs. In this study, we estimate the cost-effectiveness and population impact of parallel panel germline and somatic BRCA testing of all patients with OC incorporating PARPi therapy in the United Kingdom and the United States compared with clinical criteria/family history (FH)–based germline BRCA testing. We also evaluate the cost-effectiveness of multigene panel germline testing alone. Methods: Microsimulation cost-effectiveness modeling using data from 2,391 (UK: n=1,483; US: n=908) unselected, population-based patients with OC was used to compare lifetime costs and effects of panel germline and somatic BRCA testing of all OC cases (with PARPi therapy) (strategy A) versus clinical criteria/FH-based germline BRCA testing (strategy B). Unaffected relatives with germline BRCA1/BRCA2/RAD51C/RAD51D/BRIP1 PVs identified through cascade testing underwent appropriate OC and breast cancer (BC) risk-reduction interventions. We also compared the cost-effectiveness of multigene panel germline testing alone (without PARPi therapy) versus strategy B. Unaffected relatives with PVs could undergo risk-reducing interventions. Lifetime horizon with payer/societal perspectives, along with probabilistic/one-way sensitivity analyses, are presented. Incremental cost-effectiveness ratio (ICER) and incremental cost per quality-adjusted life year (QALY) gained were compared with £30,000/QALY (UK) and $100,000/QALY (US) thresholds. OC incidence, BC incidence, and prevented deaths were estimated. Results: Compared with clinical criteria/FH-based BRCA testing, BRCA1/BRCA2/RAD51C/RAD51D/BRIP1 germline testing and BRCA1/BRCA2 somatic testing of all patients with OC incorporating PARPi therapy had a UK ICER of £51,175/QALY (payer perspective) and £50,202/QALY (societal perspective) and a US ICER of$175,232/QALY (payer perspective) and $174,667/QALY (societal perspective), above UK/NICE and US cost-effectiveness thresholds in the base case. However, strategy A becomes cost-effective if PARPi costs decrease by 45$68,808/QALY and societal-perspective ICERs of £6,923/QALY or $65,786/QALY. One year’s testing could prevent 209 UK BC/OC cases and 192 deaths, and 560 US BC/OC cases and 460 deaths. Conclusions: Unselected panel germline and somatic BRCA testing can become cost-effective, with a 45% to 46% reduction in PARPi costs. Regarding germline testing, unselected panel germline testing is highly cost-effective and should replace BRCA testing alone

Neuromyelitis optica spectrum disorder in three generations of a Chinese family

© 2019 Neuromyelitis optica spectrum disorder is an inflammatory demyelinating disease that is largely sporadic. Familial disease has been reported in one or two generations, although its basis remains unknown. We report here three subjects meeting diagnostic criteria for NMOSD in one family: a father and son, and the maternal aunt of the father. Anticipation, of 27 years, was apparent in transmission from father to son. Aquaporin-4 antibodies were observed in the aunt but not the father and son, nor in other family members. A putative pathogenic mutation in the NECL2 gene was not found in this pedigree. This first report of NMOSD in three generations of one family underlines the heterogeneity of familial NMOSD

DoDo-Code: a Deep Levenshtein Distance Embedding-based Code for IDS Channel and DNA Storage

Recently, DNA storage has emerged as a promising data storage solution, offering significant advantages in storage density, maintenance cost efficiency, and parallel replication capability. Mathematically, the DNA storage pipeline can be viewed as an insertion, deletion, and substitution (IDS) channel. Because of the mathematical terra incognita of the Levenshtein distance, designing an IDS-correcting code is still a challenge. In this paper, we propose an innovative approach that utilizes deep Levenshtein distance embedding to bypass these mathematical challenges. By representing the Levenshtein distance between two sequences as a conventional distance between their corresponding embedding vectors, the inherent structural property of Levenshtein distance is revealed in the friendly embedding space. Leveraging this embedding space, we introduce the DoDo-Code, an IDS-correcting code that incorporates deep embedding of Levenshtein distance, deep embedding-based codeword search, and deep embedding-based segment correcting. To address the requirements of DNA storage, we also present a preliminary algorithm for long sequence decoding. As far as we know, the DoDo-Code is the first IDS-correcting code designed using plausible deep learning methodologies, potentially paving the way for a new direction in error-correcting code research. It is also the first IDS code that exhibits characteristics of being `optimal' in terms of redundancy, significantly outperforming the mainstream IDS-correcting codes of the Varshamov-Tenengolts code family in code rate