Temat: SELD - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Selenocysteine in Trypanosoma evansi: Identification of the Genes selb, selc, seld, pstk, seltryp and the Selenophosphate Synthetase Protein
Autorzy:: Tavares, Kaio Cesar Simiano
Dambrós, Maria Gabriela Casagrande
Antunes, André Saraiva Leão
Danziato, Pietro Martin
Stoco, Patricia Hermes
Schlindwein, Aline Daiane
Moreira, Renato Simões
Miletti, Luiz Claudio
Powiązania:: https://bibliotekanauki.pl/articles/2041954.pdf
Data publikacji:: 2021-08-05
Wydawca:: Uniwersytet Jagielloński. Wydawnictwo Uniwersytetu Jagiellońskiego
Tematy:: Trypanosoma evansi
selenocysteine
selB
selC
selD
PSTK
seltTRYP
Opis:: Selenoproteins have been described in all three domains of life and their function has been mainly associated with oxidative stress defense. Canonical elements required for selenoprotein production have been identified in members of the kinetoplastid group supporting the existence of a complete selenocysteine synthesis pathway in these organisms. Currently, nothing is known regarding the selenocysteine pathway in Trypanosoma evansi. In this study, we identified the expression of the elements selB, selC, selD, PSTK and selTRYP at the mRNA level in T. evansi. All translated proteins (selD, PSTK, selTRYP and selB) have the domains predicted and higher identity with Trypanosoma brucei. gambiense. The selenophosphate synthetase protein was localized in the cytoplasm. Our results support the existence of an active selenocysteine pathway in T. evansi.
Źródło:: Acta Protozoologica; 2021, 60; 21-29
1689-0027
Pojawia się w:: Acta Protozoologica
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Detection and Localization of Audio Event for Home Surveillance Using CRNN
Autorzy:: Suruthhi, V. S.
Smita, V.
Rolant Gini, J.
Ramachandran, K. I.
Powiązania:: https://bibliotekanauki.pl/articles/2055274.pdf
Data publikacji:: 2021
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: convolutional recurrent neural network
CRNN
gated recurrent unit
GRU
long short-term memory
LSTM
sound event localization and detection
SELD
Opis:: Safety and security have been a prime priority in people’s lives, and having a surveillance system at home keeps people and their property more secured. In this paper, an audio surveillance system has been proposed that does both the detection and localization of the audio or sound events. The combined task of detecting and localizing the audio events is known as Sound Event Localization and Detection (SELD). The SELD in this work is executed through Convolutional Recurrent Neural Network (CRNN) architecture. CRNN is a stacked layer of convolutional neural network (CNN), recurrent neural network (RNN) and fully connected neural network (FNN). The CRNN takes multichannel audio as input, extracts features and does the detection and localization of the input audio events in parallel. The SELD results obtained by CRNN with the gated recurrent unit (GRU) and with long short-term memory (LSTM) unit are compared and discussed in this paper. The SELD results of CRNN with LSTM unit gives 75% F1 score and 82.8% frame recall for one overlapping sound. Therefore, the proposed audio surveillance system that uses LSTM unit produces better detection and overall performance for one overlapping sound.
Źródło:: International Journal of Electronics and Telecommunications; 2021, 67, 4; 735--741
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

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