Wrocław University of Technology

About: Wrocław University of Technology is a education organization based out in Wrocław, Poland. It is known for research contribution in the topics: Laser & Fuzzy logic. The organization has 13115 authors who have published 31279 publications receiving 338694 citations.

Re-ranking method based on inter-document distances

Abstract: Lately there has been intensive research into the possibilities of using additional information about documents (such as hyperlinks) to improve retrieval effectiveness. It is called data fusion, based on the intuitive principle that different document and query representations or different methods lead to a better estimation of the documents' relevance scores.In this paper we propose a new method of document re-ranking that enables us to improve document scores using inter-document relationships. These relationships are expressed by distances and can be obtained from the text, hyperlinks or other information. The method formalizes the intuition that strongly related documents should not be assigned very different weights.

Activity profiling of SARS-CoV-2-PLpro protease provides structural framework for anti-COVID-19 drug design

Abstract: In December 2019, the first cases of a novel coronavirus infection causing COVID-19 were diagnosed in Wuhan, China. Viral Papain-Like cysteine protease (PLpro, NSP3) is essential for SARS-CoV-2 replication and represents a promising target for the development of antiviral drugs which would be facilitated by an understanding of its substrate specificity. Here, we used a combinatorial substrate library containing natural and a wide variety of nonproteinogenic amino acids and performed comprehensive activity profiling of SARS-CoV-2-PLpro. We found that the P2 site of SARS-CoV-2-PLpro is highly specific for Gly, the P3 site exhibits a high degree of promiscuity, and the P4 site exhibits a preference for amino acids with hydrophobic side chains. We also demonstrate that SARS-CoV-2-PLpro harbors deubiquitinating activity. Both the substrate binding profile and deubiquitinating activity are shared with the highly related SARS-CoV-PLpro which harbors near identical S4-S2 binding pockets. On the scaffold of best hits from positional scanning we have designed optimal fluorogenic substrates and irreversible inhibitors with a high degree of selectivity for SARS PLpro variants versus other proteases. Altogether this work has revealed the molecular rules governing PLpro substrate specificity and provides a framework for development of inhibitors with potential therapeutic value or drug repositioning.

Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark

Abstract: Mining massive and high-speed data streams among the main contemporary challenges in machine learning. This calls for methods displaying a high computational efficacy, with ability to continuously update their structure and handle ever-arriving big number of instances. In this paper, we present a new incremental and distributed classifier based on the popular nearest neighbor algorithm, adapted to such a demanding scenario. This method, implemented in Apache Spark, includes a distributed metric-space ordering to perform faster searches. Additionally, we propose an efficient incremental instance selection method for massive data streams that continuously update and remove outdated examples from the case-base. This alleviates the high computational requirements of the original classifier, thus making it suitable for the considered problem. Experimental study conducted on a set of real-life massive data streams proves the usefulness of the proposed solution and shows that we are able to provide the first efficient nearest neighbor solution for high-speed big and streaming data.