Immune Response towards COVID-19

Background: As the world witnessed the outbreak of coronavirus illness 2019 (COVID-19), a disorder developed as a result of a novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), increasing genetics with healthcare evidence suggest a corresponding leadership to SARS as well as the Middle East Respiratory Syndrome (MERS). Aim: The aim of this review is to highlight Immune response of human body toward COVID-19. Materials and methods: This was a narrative review. A comprehensive literature search was done using PubMed, Google Scholar, Scopus, and EMBASE using the keywords, Immune Response; COVID-19; Vaccination; SARS-Cov-2; ACE2; Coronavirus; MERS. Results: A flow of viral components passes to the body by means of nostrils, mouth and eyes. SARS-CoV-2 is in a position to continue to become unnoticed extended than numerous influenza or coronaviruses. Its proteins can accomplish entry by unlocking the Angiotensin-Converting Enzyme 2 (ACE2) protein in the lung cells; viruses also possess antigens furthermore recognize that these are what cries the immunity into movement via making antibodies. Investigators demonstrate an extensive variety of immune cells respond to COVID-19 along with valuable source retrieval, discovering that might want to notify the manufacturing of a viable vaccination. Conclusion: The body's natural response to a viral infection is a non-invasive intrinsic response in which macrophages, neutrophils, and dendritic cells limit the virus's progression and may even prevent it by multiplying symptoms. This non-invasive solution is accompanied by an elastic response in which the body produces radicals that primarily adjust to the herpes virus.

De Digitale Charterbank Nederland

In de Nederlandse archieven worden tienduizenden oorkonden (ofwel charters) bewaard uit de middeleeuwen en de vroegmoderne tijd. Dit materiaal vormt een onschatbare bron van informatie over allerlei maatschappelijke aspecten. Toch worden deze oorkonden in het historisch onderzoek nog weinig gebruikt, vanwege de gecompliceerde heuristiek: de documenten zijn verspreid over tientallen archieven en honderden archieffondsen. De Digitale Charterbank Nederland (DCN) maakt het grootste deel van dit corpus nu toegankelijk in een geïntegreerde database, waarin alle stukken vindbaar zijn. Ons artikel bespreekt de opzet van DCN en de praktische consequenties daarvan voor de gebruiker. De database kent specifieke mogelijkheden maar ook bepaalde beperkingen, en dit artikel toont hoe DCN kan helpen bij zowel gedetailleerd onderzoek naar personen of plaatsen als bij brede studies over een lange periode. Tevens wordt ingegaan op de invloed van de nieuwe grootschalige digitale bronontsluitingen en de bijbehorende hulpmiddelen en technieken op het historisch onderzoek.The Dutch archives hold tens of thousands of charters from the Middle Ages and early modern period, providing an invaluable source of information on various societal aspects. Yet, this material is scarcely used in historical research mainly due to its complicated heuristics: the documents are spread across dozens of archives and hundreds of archival funds. The Digitale Charterbank Nederland (DCN) now makes most of this corpus accessible through an integrated database in which all documents can be found. Our article discusses the set-up of DCN and its practical consequences for the user. The database has specific possibilities but also certain limitations, and this article shows how DCN can help with both detailed research into persons or places, and with more broadly oriented research covering a long period of time. The article further includes a reflection on the impact of new large scale digital source retrieval systems and the associated tools and techniques on historical research.

Discovering Pesticides and their Transformation Products in Luxembourg Waters using Open Cheminformatics Approaches

The diversity of hundreds of thousands of potential organic pollutants and the lack of (publicly available) information about many of them is a huge challenge for environmental sciences, engineering, and regulation. Suspect screening based on high-resolution liquid chromatography-mass spectrometry (LC-HRMS) has enormous potential to help characterize the presence of these chemicals in our environment, enabling the detection of known and newly emerging pollutants, as well as their potential transformation products (TPs). Here, suspect list creation (focusing on pesticides relevant for Luxembourg, incorporating data sources in 4 languages) was coupled to an automated retrieval of related TPs from PubChem based on high confidence suspect hits, to screen for pesticides and their TPs in Luxembourgish river samples. A computational workflow was established to combine LC-HRMS analysis and pre-screening of the suspects (including automated quality control steps), with spectral annotation to determine which pesticides and, in a second step, their related TPs may be present in the samples. The data analysis with Shinyscreen (https://git-r3lab.uni.lu/eci/shinyscreen/), an open source software developed in house, coupled with custom-made scripts, revealed the presence of 162 potential pesticide masses and 135 potential TP masses in the samples. Further identification of these mass matches was performed using the open source MetFrag (https://msbi.ipb-halle.de/MetFrag/). Eventual target analysis of 36 suspects resulted in 31 pesticides and TPs confirmed at Level-1 (highest confidence), and five pesticides and TPs not confirmed due to different retention times. Spatio-temporal analysis of the results showed that TPs and pesticides followed similar trends, with a maximum number of potential detections in July. The highest detections were in the rivers Alzette and Mess and the lowest in the Sûre and Eisch. This study (a) added pesticides, classification information and related TPs into the open domain, (b) developed automated open source retrieval methods - both enhancing FAIRness (Findability, Accessibility, Interoperability and Reusability) of the data and methods; and (c) will directly support “L’Administration de la Gestion de l’Eau” on further monitoring steps in Luxembourg.

ANALISIS PENGARUH INFLASI DAN TINGKAT BUNGA INVESTASI DI INDONESIA

The purpose of this study was to find out and analyze the effect of inflation on investment and interest rates on investment in Indonesia from 2006 to 2015. This type of research is quantitative descriptive and data source retrieval with literature study techniques. The analytical method used in this study is regression time lag analysis. Based on the data analyzed in this study there are several conclusions as follows: 1) inflation has a significant effect on investment 2) interest rates have a significant effect on investment.

Evaluation of Fingerprint Selection Algorithms for Local Text Reuse Detection

Detection of local text reuse is central to a variety of applications, including plagiarism detection, origin detection, and information flow analysis. This paper evaluates and compares effectiveness of fingerprint selection algorithms for the source retrieval stage of local text reuse detection. In total, six algorithms are compared – Every p-th, 0 mod p, Winnowing, Hailstorm, Frequency-biased Winnowing (FBW), as well as the proposed modified version of FBW (MFBW).Most of the previously published studies in local text reuse detection are based on datasets having either artificially generated, long-sized, or unobfuscated text reuse. In this study, to evaluate performance of the algorithms, a new dataset has been built containing real text reuse cases from Bachelor and Master Theses (written in English in the field of computer science) where about half of the cases involve less than 1 % of document text while about two-thirds of the cases involve paraphrasing.In the performed experiments, the overall best detection quality is reached by Winnowing, 0 mod p, and MFBW. The proposed MFBW algorithm is a considerable improvement over FBW and becomes one of the best performing algorithms.The software developed for this study is freely available at the author’s website http://www.cs.rtu.lv/jekabsons/.

Retrieval of source documents in a text reuse system

The architecture of the text-reuse detection system consists of three main modules, i.e., source retrieval, text analysis, and knowledge-based postprocessing. Each module plays an important role in the accuracy rate of the detection outputs. Therefore, this research focuses on developing the source retrieval system in cases where the source documents have been obfuscated in different levels. Two steps of term weighting were applied to get such documents. The first was the local-word weighting, which has been applied to the test or reused documents to select query per text segments. The tf-idf term weighting was applied for indexing all documents in the corpus and as the basis for computing cosine similarity between the queries per segment and the documents in the corpus. A two-step filtering technique was applied to get the source document candidates. Using artificial cases of text reuse testing, the system achieves the same rates of precision and recall that are 0.967, while the recall rate for the simulated cases of reused text is 0.66.