The Experts below are selected from a list of 160701 Experts worldwide ranked by ideXlab platform

Pere Rafols - One of the best experts on this subject based on the ideXlab platform.

  • rmsicleanup an open source tool for matrix related peak annotation in mass spectrometry imaging and its application to silver assisted laser desorption ionization
    Journal of Cheminformatics, 2020
    Co-Authors: Gerard Baquer, Lluc Semente, Maria Garciaaltares, Young Jin Lee, Pierre Chaurand, X Correig, Pere Rafols
    Abstract:

    Mass spectrometry imaging (MSI) has become a mature, widespread analytical technique to perform non-targeted spatial metabolomics. However, the compounds used to promote desorption and ionization of the analyte during acquisition cause spectral interferences in the low mass range that hinder Downstream Data processing in metabolomics applications. Thus, it is advisable to annotate and remove matrix-related peaks to reduce the number of redundant and non-biologically-relevant variables in the Dataset. We have developed rMSIcleanup, an open-source R package to annotate and remove signals from the matrix, according to the matrix chemical composition and the spatial distribution of its ions. To validate the annotation method, rMSIcleanup was challenged with several images acquired using silver-assisted laser desorption ionization MSI (AgLDI MSI). The algorithm was able to correctly classify m/z signals related to silver clusters. Visual exploration of the Data using Principal Component Analysis (PCA) demonstrated that annotation and removal of matrix-related signals improved spectral Data post-processing. The results highlight the need for including matrix-related peak annotation tools such as rMSIcleanup in MSI workflows.

  • rmsicleanup an open source tool for matrix related peak annotation in mass spectrometry imaging and its application to silver assisted laser desorption ionization
    bioRxiv, 2019
    Co-Authors: Gerard Baquer, Lluc Semente, Maria Garciaaltares, Young Jin Lee, Pierre Chaurand, X Correig, Pere Rafols
    Abstract:

    Abstract Mass spectrometry imaging (MSI) has become a mature, widespread analytical technique to perform non-targeted spatial metabolomics. However, the compounds used to promote desorption and ionization of the analyte during acquisition cause spectral interferences in the low mass range that hinder Downstream Data processing in metabolomics applications. Thus, it is advisable to annotate and remove matrix-related peaks to reduce the number of redundant and non-biologically-relevant variables in the Dataset. We have developed rMSIcleanup, an open-source R package to annotate and remove matrix-related signals based on its chemical formula and the spatial distribution of its ions. To validate the annotation method, rMSIcleanup was challenged with several images acquired using silver-assisted laser desorption ionization MSI (AgLDI MSI). The algorithm was able to correctly classify m/z signals related to silver clusters. Visual exploration of the Data using Principal Component Analysis (PCA) demonstrated that annotation and removal of matrix-related signals improved spectral Data post-processing. The results highlight the need for including matrix-related peak annotation tools such as rMSIcleanup in MSI workflows. Resources availability The R package presented in this publication is freely available under the terms of the GNU General Public License v3.0 at https://github.com/gbaquer/rMSIcleanup. The Datasets used in the experiments can be accessed upon request to the corresponding author.

Rabah Attia - One of the best experts on this subject based on the ideXlab platform.

  • bidirectional long reach wdm pon delivering Downstream Data 20 gbps and upstream Data 10 gbps using mode locked laser and rsoa
    Optical and Quantum Electronics, 2015
    Co-Authors: Laxman Tawade, Sofien Mhatli, Rabah Attia
    Abstract:

    This paper presents long reach wavelength division multiplexing passive optical network (WDM-PON) system capable of delivering Downstream 20 Gbit/s Data and upstream 10 Gbit/s Data on a single wavelength. The optical source for Downstream Data and upstream Data is mode locked laser at central office and reflective semiconductor optical amplifier (RSOA) at each optical network unit. We use two RSOAs at each optical network unit for the 10-Gb/s upstream transmission. The operating wavelengths of these RSOAs are separated by the free-spectral range of the cyclic arrayed waveguide gratings used at the central office and remote node (RN) for (de)multiplexing the WDM channels. We extend the maximum reach of this WDM PON to be 45 km by using Erbium-doped fiber amplifiers at the RN.The hybrid amplifier is designed to enhance the signal power and compensated the fiber dispersion over a wide wavelength range. Optical Equalization technique is used before the receiver to improve modulation bandwidth of an RSOA based colorless optical network unit. Optical Equalization technique helps to improve downlink and uplink performance. Author also investigates analysis of backscattered optical signal for upstream Data and Downstream Data simultaneously. Bit error rate, backscattered optical signal power were measured to demonstrate the proposed scheme. In this paper Long reach and large Data service aspects of a WDM-PON is presented.

  • long reach ofdm wdm pon delivering 100 gb s of Data Downstream and 2 gb s of Data upstream using a continuous wave laser and a reflective semiconductor optical amplifier
    Optics Letters, 2014
    Co-Authors: Sofien Mhatli, Laxman Tawade, Mohammad Ghanbarisabagh, Bechir Nsiri, Mutsam A Jarajreh, Malak Channoufi, Rabah Attia
    Abstract:

    This paper presents a long-reach orthogonal frequency division multiplexing wavelength division multiplexing passive optical network (OFDM WDM–PON), a system capable of delivering 100  Gb/s of Data Downstream and 2  Gb/s of Data upstream on a single wavelength. The optical sources for Downstream Data and upstream Data are a continuous-wave laser at a central office and a reflective semiconductor optical amplifier (RSOA) at each optical network unit.

Gerard Baquer - One of the best experts on this subject based on the ideXlab platform.

  • rmsicleanup an open source tool for matrix related peak annotation in mass spectrometry imaging and its application to silver assisted laser desorption ionization
    Journal of Cheminformatics, 2020
    Co-Authors: Gerard Baquer, Lluc Semente, Maria Garciaaltares, Young Jin Lee, Pierre Chaurand, X Correig, Pere Rafols
    Abstract:

    Mass spectrometry imaging (MSI) has become a mature, widespread analytical technique to perform non-targeted spatial metabolomics. However, the compounds used to promote desorption and ionization of the analyte during acquisition cause spectral interferences in the low mass range that hinder Downstream Data processing in metabolomics applications. Thus, it is advisable to annotate and remove matrix-related peaks to reduce the number of redundant and non-biologically-relevant variables in the Dataset. We have developed rMSIcleanup, an open-source R package to annotate and remove signals from the matrix, according to the matrix chemical composition and the spatial distribution of its ions. To validate the annotation method, rMSIcleanup was challenged with several images acquired using silver-assisted laser desorption ionization MSI (AgLDI MSI). The algorithm was able to correctly classify m/z signals related to silver clusters. Visual exploration of the Data using Principal Component Analysis (PCA) demonstrated that annotation and removal of matrix-related signals improved spectral Data post-processing. The results highlight the need for including matrix-related peak annotation tools such as rMSIcleanup in MSI workflows.

  • rmsicleanup an open source tool for matrix related peak annotation in mass spectrometry imaging and its application to silver assisted laser desorption ionization
    bioRxiv, 2019
    Co-Authors: Gerard Baquer, Lluc Semente, Maria Garciaaltares, Young Jin Lee, Pierre Chaurand, X Correig, Pere Rafols
    Abstract:

    Abstract Mass spectrometry imaging (MSI) has become a mature, widespread analytical technique to perform non-targeted spatial metabolomics. However, the compounds used to promote desorption and ionization of the analyte during acquisition cause spectral interferences in the low mass range that hinder Downstream Data processing in metabolomics applications. Thus, it is advisable to annotate and remove matrix-related peaks to reduce the number of redundant and non-biologically-relevant variables in the Dataset. We have developed rMSIcleanup, an open-source R package to annotate and remove matrix-related signals based on its chemical formula and the spatial distribution of its ions. To validate the annotation method, rMSIcleanup was challenged with several images acquired using silver-assisted laser desorption ionization MSI (AgLDI MSI). The algorithm was able to correctly classify m/z signals related to silver clusters. Visual exploration of the Data using Principal Component Analysis (PCA) demonstrated that annotation and removal of matrix-related signals improved spectral Data post-processing. The results highlight the need for including matrix-related peak annotation tools such as rMSIcleanup in MSI workflows. Resources availability The R package presented in this publication is freely available under the terms of the GNU General Public License v3.0 at https://github.com/gbaquer/rMSIcleanup. The Datasets used in the experiments can be accessed upon request to the corresponding author.

Leonid G. Kazovsky - One of the best experts on this subject based on the ideXlab platform.

  • success a next generation hybrid wdm tdm optical access network architecture
    Journal of Lightwave Technology, 2004
    Co-Authors: Futai An, E S Hu, David Gutierrez, K Shrikhande, Leonid G. Kazovsky
    Abstract:

    In this paper, the authors propose a next-generation hybrid WDM/TDM optical access network architecture called Stanford University aCCESS or SUCCESS. This architecture provides practical migration steps from current-generation time-division multiplexing (TDM)-passive optical network (PONs) to future WDM optical access networks. The architecture is backward compatible for users on existing TDM-PONs, while simultaneously capable of providing upgraded high-bandwidth services to new users on DWDM-PONs through advanced WDM techniques. The SUCCESS architecture is based on a collector ring and several distribution stars connecting the CO and the users. A semipassive configuration of the Remote Nodes (RNs) enables protection and restoration, making the network resilient to power failures. A novel design of the OLT and DWDM-PON ONUs minimizes the system cost considerably: 1) tunable lasers and receivers at the OLT are shared by all ONUs on the network to reduce the transceiver count and 2) the fast tunable lasers not only generate Downstream Data traffic but also provide DWDM-PON ONUs with optical CW bursts for their upstream Data transmission. Results from an experimental system testbed support the feasibility of the proposed SUCCESS architecture. Also, simulation results of the first SUCCESS DWDM-PON MAC protocol verify that it can efficiently provide bidirectional transmission between the OLT and ONUs over multiple wavelengths with a small number of tunable transmitters and receivers.

Liankuan Chen - One of the best experts on this subject based on the ideXlab platform.