42 research outputs found
Simplified high-order Volterra series transfer function for optical transmission links
We develop a simplified high-order multi-span Volterra series transfer function (SHMS-
VSTF), basing our derivation on the well-known third-order Volterra series transfer function
(VSTF). We notice that when applying an approach based on a recursive method and considering
the phased-array factor, the order of the expression for the transfer function grows as 3 raised to
the number of considered spans. By imposing a frequency-flat approximation to the higher-order
terms that are usually neglected in the commonly used VSTF approach, we are able to reduce
the overall expression order to the typical third-order plus a complex correction factor. We carry
on performance comparisons between the purposed SH-MS-VSTF, the well-known split-step
Fourier method (SSFM), and the third-order VSTF. The SH-MS-VSTF exhibits a uniform
improvement of about two orders of magnitude in the normalized mean squared deviation with
respect to the other methods. This can be translated in a reduction of the overall number of steps
required to fully analyze the transmission link up to 99.75% with respect to the SSFM, and
98.75% with respect to the third-order VSTF, respectively, for the same numerical accuracy
Joint Carrier-Phase Estimation for Digital Subcarrier Multiplexing Systems With Symbol-Rate Optimization
Digital subcarrier multiplexing (SCM) has recently emerged as a promising solution for next-generation ultra-high-baudrate coherent optical communication systems. Among its distinctive advantages over traditional single-carrier modulation, SCM enables the exploitation of symbol-rate optimization (SRO), which has been shown to enable the passive mitigation of the nonlinear interference noise (NLIN) that is generated during propagation over dispersion-unmanaged optical fiber systems. However, the full exploitation of SRO-based NLIN mitigation is severely hindered by the uncompensated distortion caused by laser phase noise (LPN) and non-linear phase noise (NLPN), whose impact is magnified by the use of low-baudrate subcarriers. Resorting to low-complexity carrier phase estimation (CPE) algorithms, in this paper we experimentally demonstrate that it is possible to overcome the hurdles posed by LPN and NLPN in SCM systems, provided that adequate joint-subcarrier CPE processing is employed. A dual-stage joint-processing approach composed of a pilot-based CPE optionally followed by a blind phase search (BPS)-based estimator is implemented and experimentally assessed, enabling to effectively optimize the symbol-rate per subcarrier down to 3 GBaud, in accordance with the theoretical SRO predictions for the system under test. In addition, we demonstrate that signal-to-noise ratio (SNR) gains of more than 1 dB can be achieved through joint-subcarrier CPE processing in shorter-reach links, while this gain tends to progressively reduce with increasing propagation distance, down to about 0.5 dB gain after 3000 km propagation
Digital signal processing for fiber nonlinearities [Invited]
This paper reviews digital signal processing techniques that compensate, mitigate, and exploit fiber nonlinearities in coherent optical fiber transmission systems
400G Frequency-Hybrid Superchannel for the 62.5 GHz Slot
We experimentally demonstrate a PM-16QAM/64QAM triple-carrier 400G superchannel compatible with the 62.5 GHz grid. The optimum power ratio between carriers is analytically determined using the EGN model, enabling a maximum reach of 1700 km
Real-Time Demonstration of Low-Complexity Time-Domain Chromatic Dispersion Equalization
We demonstrate real-time CD equalization (CDE) for coherent optical transmission systems using a low complexity
time-domain (TD) multiplierless finite-impulse response (FIR)-based equalizer, based on a field-programmable gate
array (FPGA) implementation. The real-time operation is performed for a single-channel 2.5 Gb/s QPSK optical
signal with a performance penalty of only 0.15 dB with respect to the maximum performance. The hardware
complexity is also evaluated in terms of occupation in a Virtex-6 FPGA-XC6VLX240T, revealing the high efficiency
of the proposed CDE algorithm
Strontium hexaferrite platelets: a comprehensive soft X-ray absorption and Mössbauer spectroscopy study
IBERMÖSS-2019, Bilbao, 30-31 may 2019. --https://www.ehu.eus/es/web/ibermossmeetingStrontium ferrite (SFO, SrFe12O19) is a ferrite
employed for permanent magnets due to its high
magnetocrystalline anisotropy. Since its discovery
in the mid-20th century, this hexagonal ferrite has
become an increasingly important material both
commercially and technologically, finding a variety
of uses and applications. Its structure can be
considered a sequence of alternating spinel (S) and
rocksalt (R) blocks. All the iron cations are in the
Fe3+ oxidation state and it has a ferrimagnetic
configuration with five different cationic
environments for the iron (three octahedral sites, a
tetraedrical site and a bipiramidal site)[1,2].
We have studied the properties of SrFe 12O19 in the
shape of platelets, up to several micrometers in
width, and tens of nanometers thick, synthesized by
a hydrothermal method. We have characterized the
structural and magnetic properties of these platelets
by Mössbauer spectroscopy, x-ray transmission
microscopy (TMX), transmission electron
microscopy (TEM), x-ray diffraction (XRD),
vibrating-sample magnetometry (VSM), x-ray
absorption spectroscopy (XAS), x-ray circular
magnetic dichroism (XMCD) and photoemission
electron microscopy (PEEM). To the best of our
knowledge this is the first time that the x-ray
absorption spectra at the Fe L 2,3 edges of this
material in its pure form have been reported. The
Mössbauer results recorded from these platelets
both in the electron detection and transmission
modes have helped to understand the iron magnetic
moments determined by XMCD (Fig.1). The
experimental results have been complemented with
multiplet calculations aimed at reproducing the
observed XAS and XMCD spectra at the Fe L 2,3
absorption edge, and by density functional theory
(DFT) calculations to reproduce the oxygen K-
absorption edge. Finally the domain pattern
measured in remanence is in good agreement with
micromagnetic simulations [3]
HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity
The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis
The Human Phenotype Ontology in 2024: phenotypes around the world.
The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs
SARS-CoV-2 introductions and early dynamics of the epidemic in Portugal
Genomic surveillance of SARS-CoV-2 in Portugal was rapidly implemented by
the National Institute of Health in the early stages of the COVID-19 epidemic, in collaboration
with more than 50 laboratories distributed nationwide.
Methods By applying recent phylodynamic models that allow integration of individual-based
travel history, we reconstructed and characterized the spatio-temporal dynamics of SARSCoV-2 introductions and early dissemination in Portugal.
Results We detected at least 277 independent SARS-CoV-2 introductions, mostly from
European countries (namely the United Kingdom, Spain, France, Italy, and Switzerland),
which were consistent with the countries with the highest connectivity with Portugal.
Although most introductions were estimated to have occurred during early March 2020, it is
likely that SARS-CoV-2 was silently circulating in Portugal throughout February, before the
first cases were confirmed.
Conclusions Here we conclude that the earlier implementation of measures could have
minimized the number of introductions and subsequent virus expansion in Portugal. This
study lays the foundation for genomic epidemiology of SARS-CoV-2 in Portugal, and highlights the need for systematic and geographically-representative genomic surveillance.We gratefully acknowledge to Sara Hill and Nuno Faria (University of Oxford) and
Joshua Quick and Nick Loman (University of Birmingham) for kindly providing us with
the initial sets of Artic Network primers for NGS; Rafael Mamede (MRamirez team,
IMM, Lisbon) for developing and sharing a bioinformatics script for sequence curation
(https://github.com/rfm-targa/BioinfUtils); Philippe Lemey (KU Leuven) for providing
guidance on the implementation of the phylodynamic models; Joshua L. Cherry
(National Center for Biotechnology Information, National Library of Medicine, National
Institutes of Health) for providing guidance with the subsampling strategies; and all
authors, originating and submitting laboratories who have contributed genome data on
GISAID (https://www.gisaid.org/) on which part of this research is based. The opinions
expressed in this article are those of the authors and do not reflect the view of the
National Institutes of Health, the Department of Health and Human Services, or the
United States government. This study is co-funded by Fundação para a Ciência e Tecnologia
and Agência de Investigação Clínica e Inovação Biomédica (234_596874175) on
behalf of the Research 4 COVID-19 call. Some infrastructural resources used in this study
come from the GenomePT project (POCI-01-0145-FEDER-022184), supported by
COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation
(POCI), Lisboa Portugal Regional Operational Programme (Lisboa2020), Algarve Portugal
Regional Operational Programme (CRESC Algarve2020), under the PORTUGAL
2020 Partnership Agreement, through the European Regional Development Fund
(ERDF), and by Fundação para a Ciência e a Tecnologia (FCT).info:eu-repo/semantics/publishedVersio
The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts
Biodiversity continues to decline in the face of increasing anthropogenic pressures
such as habitat destruction, exploitation, pollution and introduction of
alien species. Existing global databases of species’ threat status or population
time series are dominated by charismatic species. The collation of datasets with
broad taxonomic and biogeographic extents, and that support computation of
a range of biodiversity indicators, is necessary to enable better understanding of
historical declines and to project – and avert – future declines. We describe and
assess a new database of more than 1.6 million samples from 78 countries representing
over 28,000 species, collated from existing spatial comparisons of
local-scale biodiversity exposed to different intensities and types of anthropogenic
pressures, from terrestrial sites around the world. The database contains
measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35)
biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains
more than 1% of the total number of all species described, and more than
1% of the described species within many taxonomic groups – including flowering
plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans
and hymenopterans. The dataset, which is still being added to, is
therefore already considerably larger and more representative than those used
by previous quantitative models of biodiversity trends and responses. The database
is being assembled as part of the PREDICTS project (Projecting Responses
of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk).
We make site-level summary data available alongside this article. The full database
will be publicly available in 2015