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  1. Article ; Online: Computational challenges for multimodal astrophysics.

    Cuoco, Elena / Patricelli, Barbara / Iess, Alberto / Morawski, Filip

    Nature computational science

    2022  Volume 2, Issue 8, Page(s) 479–485

    Abstract: In the coming decades, we will face major computational challenges, when the improved sensitivity of third-generation gravitational wave detectors will be such that they will be able to detect a high number (of the order of 7 × ... ...

    Abstract In the coming decades, we will face major computational challenges, when the improved sensitivity of third-generation gravitational wave detectors will be such that they will be able to detect a high number (of the order of 7 × 10
    MeSH term(s) Artificial Intelligence ; Gravitation ; Neutrons
    Language English
    Publishing date 2022-08-22
    Publishing country United States
    Document type Journal Article ; Review
    ISSN 2662-8457
    ISSN (online) 2662-8457
    DOI 10.1038/s43588-022-00288-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: LSTM and CNN application for core-collapse supernova search in gravitational wave real data

    Iess, Alberto / Cuoco, Elena / Morawski, Filip / Nicolaou, Constantina / Lahav, Ofer

    2023  

    Abstract: Context.$ Core-collapse supernovae (CCSNe) are expected to emit gravitational wave signals that could be detected by current and future generation interferometers within the Milky Way and nearby galaxies. The stochastic nature of the signal arising from ...

    Abstract $Context.$ Core-collapse supernovae (CCSNe) are expected to emit gravitational wave signals that could be detected by current and future generation interferometers within the Milky Way and nearby galaxies. The stochastic nature of the signal arising from CCSNe requires alternative detection methods to matched filtering. $Aims.$ We aim to show the potential of machine learning (ML) for multi-label classification of different CCSNe simulated signals and noise transients using real data. We compared the performance of 1D and 2D convolutional neural networks (CNNs) on single and multiple detector data. For the first time, we tested multi-label classification also with long short-term memory (LSTM) networks. $Methods.$ We applied a search and classification procedure for CCSNe signals, using an event trigger generator, the Wavelet Detection Filter (WDF), coupled with ML. We used time series and time-frequency representations of the data as inputs to the ML models. To compute classification accuracies, we simultaneously injected, at detectable distance of 1\,kpc, CCSN waveforms, obtained from recent hydrodynamical simulations of neutrino-driven core-collapse, onto interferometer noise from the O2 LIGO and Virgo science run. $Results.$ We compared the performance of the three models on single detector data. We then merged the output of the models for single detector classification of noise and astrophysical transients, obtaining overall accuracies for LIGO ($\sim99\%$) and ($\sim80\%$) for Virgo. We extended our analysis to the multi-detector case using triggers coincident among the three ITFs and achieved an accuracy of $\sim98\%$.

    Comment: 10 pages, 13 figures. Accepted by A&A journal
    Keywords Astrophysics - Instrumentation and Methods for Astrophysics ; Computer Science - Machine Learning ; General Relativity and Quantum Cosmology ; Physics - Data Analysis ; Statistics and Probability
    Subject code 006
    Publishing date 2023-01-23
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: A versatile 3D printed multi-electrode cell for determination of three COVID-19 biomarkers.

    de Matos Morawski, Franciele / Martins, Gustavo / Ramos, Maria Karolina / Zarbin, Aldo J G / Blanes, Lucas / Bergamini, Marcio F / Marcolino-Junior, Luiz Humberto

    Analytica chimica acta

    2023  Volume 1258, Page(s) 341169

    Abstract: 3D-printing has shown an outstanding performance for the production of versatile electrochemical devices. However, there is a lack of studies in the field of 3D-printed miniaturized settings for multiplex biosensing. In this work, we propose a fully 3D- ... ...

    Abstract 3D-printing has shown an outstanding performance for the production of versatile electrochemical devices. However, there is a lack of studies in the field of 3D-printed miniaturized settings for multiplex biosensing. In this work, we propose a fully 3D-printed micro-volume cell containing six working electrodes (WEs) that operates with 250 μL of sample. A polylactic acid/carbon black conductive filament (PLA/CB) was used to print the WEs and subsequently modified with graphene oxide (GO), to support protein binding. Cyclic voltammetry was employed to investigate the electrochemical behaviour of the novel multi-electrode cell. In the presence of K₃[Fe(CN)₆], PLA/CB/GO showed adequate peak resolution for subsequent label-free immunosensing. The innovative 3D-printed cell was applied for multiplex voltammetric detection of three COVID-19 biomarkers as a proof-of-concept. The multiple sensors showed a wide linear range with detection limits of 5, 1 and 1 pg mL
    MeSH term(s) Humans ; COVID-19/diagnosis ; Electrodes ; Microelectrodes ; Polyesters ; Printing, Three-Dimensional ; Biomarkers
    Chemical Substances graphene oxide ; Polyesters ; Biomarkers
    Language English
    Publishing date 2023-04-03
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1483436-4
    ISSN 1873-4324 ; 0003-2670
    ISSN (online) 1873-4324
    ISSN 0003-2670
    DOI 10.1016/j.aca.2023.341169
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  4. Book ; Online: Anomaly Detection in Gravitational Waves data using Convolutional AutoEncoders

    Morawski, Filip / Bejger, Michał / Cuoco, Elena / Petre, Luigia

    2021  

    Abstract: As of this moment, fifty gravitational waves (GW) detections have been announced, thanks to the observational efforts of the LIGO-Virgo Collaboration, working with the Advanced LIGO and the Advanced Virgo interferometers. The detection of signals is ... ...

    Abstract As of this moment, fifty gravitational waves (GW) detections have been announced, thanks to the observational efforts of the LIGO-Virgo Collaboration, working with the Advanced LIGO and the Advanced Virgo interferometers. The detection of signals is complicated by the noise-dominated nature of the data. Conventional approaches in GW detection procedures require either precise knowledge of the GW waveform in the context of matched filtering searches or coincident analysis of data from multiple detectors. Furthermore, the analysis is prone to contamination by instrumental or environmental artifacts called glitches which either mimic astrophysical signals or reduce the overall quality of data. In this paper, we propose an alternative generic method of studying GW data based on detecting anomalies. The anomalies we study are transient signals, different from the slow non-stationary noise of the detector. Presented in the manuscript anomalies are mostly based on the GW emitted by the mergers of binary black hole systems. However, the presented study of anomalies is not limited only to GW alone, but also includes glitches occurring in the real LIGO/Virgo dataset available at the Gravitational Waves Open Science Center.

    Comment: Submitted to the Machine Learning: Science and Technology; 29 pages, 18 figures
    Keywords Astrophysics - Instrumentation and Methods for Astrophysics ; General Relativity and Quantum Cosmology
    Subject code 551
    Publishing date 2021-03-13
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: Core-Collapse Supernova Gravitational-Wave Search and Deep Learning Classification

    Iess, Alberto / Cuoco, Elena / Morawski, Filip / Powell, Jade

    2020  

    Abstract: We describe a search and classification procedure for gravitational waves emitted by core-collapse supernova (CCSN) explosions, using a convolutional neural network (CNN) combined with an event trigger generator known as Wavelet Detection Filter (WDF). ... ...

    Abstract We describe a search and classification procedure for gravitational waves emitted by core-collapse supernova (CCSN) explosions, using a convolutional neural network (CNN) combined with an event trigger generator known as Wavelet Detection Filter (WDF). We employ both a 1-D CNN search using time series gravitational-wave data as input, and a 2-D CNN search with time-frequency representation of the data as input. To test the accuracies of our 1-D and 2-D CNN classification, we add CCSN waveforms from the most recent hydrodynamical simulations of neutrino-driven core-collapse to simulated Gaussian colored noise with the Virgo interferometer and the planned Einstein Telescope sensitivity curve. We find classification accuracies, for a single detector, of over 95% for both 1-D and 2-D CNN pipelines. For the first time in machine learning CCSN studies, we add short duration detector noise transients to our data to test the robustness of our method against false alarms created by detector noise artifacts. Further to this, we show that the CNN can distinguish between different types of CCSN waveform models.

    Comment: 19 pages, 8 figures
    Keywords General Relativity and Quantum Cosmology ; Astrophysics - Instrumentation and Methods for Astrophysics ; Computer Science - Machine Learning
    Subject code 006
    Publishing date 2020-01-01
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Book ; Online: Deep learning classification of the continuous gravitational-wave signal candidates from the time-domain F-statistic search

    Morawski, Filip / Bejger, Michał / Ciecieląg, Paweł

    2019  

    Abstract: Many potential sources of gravitational waves still await for detection. Among them, particular attention is given to a non-axisymmetric neutron star. The emitted, almost monochromatic signal, is expected to be detected in the near future by LIGO and ... ...

    Abstract Many potential sources of gravitational waves still await for detection. Among them, particular attention is given to a non-axisymmetric neutron star. The emitted, almost monochromatic signal, is expected to be detected in the near future by LIGO and Virgo detectors. Although the gravitational waves waveform is well known, its small amplitude makes it extremely hard to detect. The accepted approach in searching for continuous gravitational waves is a matched filter technique, known as the F-statistic method. The method consists in cross correlation of the collected data stream with signal templates in the frequency domain. Thus, for an all-sky search in which the parameters of the sources are not known, large number of templates have to be checked and therefore a large number of candidate gravitational-wave signals is produced and further analyzed. In this work, we propose deep learning as a fast method of classification for various types of candidates. We consider three types of signals: the Gaussian noise, the continuous gravitational wave, and the stationary line mimicking local artifacts in the detector. We demonstrate one and two-dimensional implementations of a convolutional neural network classifier. We present the limitations of our model with respect to the various signal-to-noise ratios and frequencies of the signal. The following work presents deep learning as a supporting method for the matched filtering detection pipeline.

    Comment: 10 pages, 11 figures, submitted to the PRD
    Keywords Astrophysics - Instrumentation and Methods for Astrophysics
    Subject code 551
    Publishing date 2019-07-16
    Publishing country us
    Document type Book ; Online
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  7. Article ; Online: Chitosan/genipin modified electrode for voltammetric determination of interleukin-6 as a biomarker of sepsis.

    de Matos Morawski, Franciele / Dias, Greicy Brisa Malaquias / Sousa, Kelline Alaide Pereira / Formiga, Rodrigo / Spiller, Fernando / Parize, Alexandre Luis / Báfica, André / Jost, Cristiane Luisa

    International journal of biological macromolecules

    2022  

    Abstract: Ultrasensitive electroanalytical monitoring of interleukin-6 levels in serum samples has emerged as a valuable tool for the early diagnosis of inflammatory diseases. Despite its advantages, there is a lack of strategies for the label-free voltammetric ... ...

    Abstract Ultrasensitive electroanalytical monitoring of interleukin-6 levels in serum samples has emerged as a valuable tool for the early diagnosis of inflammatory diseases. Despite its advantages, there is a lack of strategies for the label-free voltammetric determination of cytokines. Here, a novel chitosan/genipin modified fluorine tin oxide electrode was developed providing an in-situ hydrogel formation (FTO/CSG). This platform was applied for the detection of interleukin-6, a major pro-inflammatory cytokine. Transmission electron microscopy (TEM), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) indicated genipin serves as an efficient green cross-linker to build the immunosensing platform (FTO/CSG/anti-IL-6). EIS showed an increase in charge transfer resistance from 326 to 1360 kΩ after the immobilization of anti-IL-6 antibodies. By square wave voltammetry, this method achieved a detection limit of 0.03 pg mL
    Language English
    Publishing date 2022-10-29
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 282732-3
    ISSN 1879-0003 ; 0141-8130
    ISSN (online) 1879-0003
    ISSN 0141-8130
    DOI 10.1016/j.ijbiomac.2022.10.232
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    In stock of ZB MED Cologne/Königswinter

    Zs.B 2374: Show issues Location:
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  8. Article ; Online: A high-performance electrochemical sensor based on a mesoporous silica/titania material and cobalt(II) phthalocyanine for sensitive pentachlorophenol determination.

    de Barros, Marília Reginato / Winiarski, João Paulo / de Matos Morawski, Franciele / Marim, Renan Guilherme / Chaves, Eduardo Sidinei / Blacha-Grzechnik, Agata / Jost, Cristiane Luisa

    Mikrochimica acta

    2022  Volume 189, Issue 8, Page(s) 269

    Abstract: The synthesis and characterization of a novel titania/silica hybrid xerogel subsequently modified with 4-methylpyridine (4-Pic), named ... ...

    Abstract The synthesis and characterization of a novel titania/silica hybrid xerogel subsequently modified with 4-methylpyridine (4-Pic), named TiSi4Pic
    MeSH term(s) Cobalt/chemistry ; Electrodes ; Indoles ; Isoindoles ; Pentachlorophenol ; Silicon Dioxide ; Titanium
    Chemical Substances Indoles ; Isoindoles ; titanium dioxide (15FIX9V2JP) ; Cobalt (3G0H8C9362) ; Silicon Dioxide (7631-86-9) ; Titanium (D1JT611TNE) ; Pentachlorophenol (D9BSU0SE4T) ; phthalocyanine (V5PUF4VLGY)
    Language English
    Publishing date 2022-07-05
    Publishing country Austria
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 89-9
    ISSN 1436-5073 ; 0026-3672
    ISSN (online) 1436-5073
    ISSN 0026-3672
    DOI 10.1007/s00604-022-05360-z
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    In stock of ZB MED Bonn / Germany

    Z 56/171: Show issues
    Z 8.1: Show issues

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  9. Book: Secondary parasites of forest injurious insects

    Morawski, Franciszek

    superfamily Chalcidoidea = Pasożyty wtórne szkodników leśnych z nadrodziny Chalcidoidea

    1964  

    Author's details Franciszek Morawski ; translated from Polish
    Keywords Chalcididae. ; Insects/Parasites. ; Entomophagous insects.
    Language English ; Polish
    Size 11, [1] p., [3] leaves of plates :, ill. ;, 28 cm.
    Publisher Published for the Dept. of Agriculture and the National Science Foundation, Washington D. C. by Centralny Instytut Informacji Naukowo-Technicznej i Ekonomicznej
    Publishing place Warszawa
    Document type Book
    Note OTS 61-11342. ; Translated reprint of pamphlet published by the Main School of Rural Economy. ; Originally appeared: Wydawnictwa SZkoły Głównej Gospodarstwa Wiejskiego, v.1, 1934.
    Database NAL-Catalogue (AGRICOLA)

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  10. Article: ZASTOSOWANIE GAMMA GLOBULINY W CELU ZAPOBIEGANIA WIRUSOWEMU ZAPALENIU W ATROBY W SANATORIUM PRZECIWGRU'ZLICZYM DLA MLODZIEZY.

    OLAKOWSKI, T / TRZCINSKA, R / MORAWSKI, F / PESKA, S

    Przeglad epidemiologiczny

    1964  Volume 18, Page(s) 209–217

    Title translation USE OF GAMMA GLOBULIN IN PREVENTING VIRAL HEPATITIS IN A TUBERCULOSIS SANATORIUM FOR ADOLESCENTS.
    MeSH term(s) Adolescent ; Communicable Disease Control ; Communicable Diseases ; Hepatitis A ; Humans ; Poland ; Tuberculosis ; gamma-Globulins
    Chemical Substances gamma-Globulins
    Language Polish
    Publishing date 1964
    Publishing country Poland
    Document type Journal Article
    ZDB-ID 421782-2
    ISSN 0033-2100
    ISSN 0033-2100
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    In stock of ZB MED Cologne/Königswinter

    Zs.B 639: Show issues Location:
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