Impact of Mode-Area Dispersion on Nonlinear Pulse Propagation in Gas-Filled Anti-Resonant Hollow-Core Fiber

We numerically investigate the effect of mode-area dispersion in a tubular-type anti-resonant hollow-core fiber by using a modified generalized nonlinear Schrödinger equation that takes into account the wavelength-dependent mode area in its nonlinear term. The pulse evolution dynamics with and without the effect of mode-area dispersion are compared and analyzed. We show that strong dispersion of the mode area in the proximity of the cladding wall thickness-induced resonances has a significant impact on the soliton pulse propagation, resulting in considerable changes in the conversion efficiencies in nonlinear frequency mixing processes. The differences become more prominent when the pump has higher energy and is nearer to a resonance. Hence, the mode-area dispersion must be accounted for when modeling such a case.

Recursive State and Parameter Estimation of COVID-19 Circulating Variants Dynamics

COVID-19 pandemic response with non-pharmaceutical interventions is an intrinsic control problem. Governments balance social distancing policies to avoid overload on health system without major economic impact. A control strategy requires reliable predictions to be efficient on long-term. SARS-CoV-2 mutability, vaccination coverage and time-varying restrictive measures change virus evolution dynamics frequently. State and parameter estimations are an option do deal with these uncertainties. In this paper, a SIR-based model is proposed considering data available and feedback corrections over time. State and parameter estimations were done on state estimators with augmented states. Three observers were implemented: Constrained Extended Kalman Filter (CEKF), CEKF and Smoother (CEKF&S) and Moving Horizon Estimator (MHE). The parameters estimated therein are based on vaccine efficacy studies regarding transmissibility, severeness of disease and lethality. Social distancing is a measured disturbance calculated with Google mobility data. Six federative units from Brazil are used to evaluate proposed strategy: Amazonas, Mato Grosso do Sul, Rio Grande do Norte, Rio Grande do Sul, Rio de Janeiro and São Paulo. State and parameter estimations were realized from October 1 st 2020 to July 1 st 2021 during which Zeta and Gamma variants emerged. Results showed an efficient detection of circulating variants from proposed parameter estimation. In addition, it asserted dynamics related to virus mutations. Zeta mutations increase lethality between 19 and 45%, and increased transmissibility between 20 and 38%. Gamma mutations, on the other hand, increased lethality between 62 and 110% while increasing transmissibility between 52 and 107%. Furthermore, parameter estimation indicated existence and temporal change of subnotification on hospitalized and deceased individuals. Overall, dynamics estimated were within expectations and are applicable to control theory.

Application of principal component analysis on temporal evolution of COVID-19

The COVID-19 is one of the worst pandemics in modern history. We applied principal component analysis (PCA) to the daily time series of the COVID-19 death cases and confirmed cases for the top 25 countries from April of 2020 to February of 2021. We calculated the eigenvalues and eigenvectors of the cross-correlation matrix of the changes in daily accumulated data over monthly time windows. The largest eigenvalue describes the overall evolution dynamics of the COVID-19 and indicates that evolution was faster in April of 2020 than in any other period. By using the first two PC coefficients, we can identify the group dynamics of the COVID-19 evolution. We observed groups under critical states in the loading plot and found that American and European countries are represented by strong clusters in the loading plot. The first PC plays an important role and the correlations (C1) between the normalized logarithmic changes in deaths or confirmed cases and the first PCs may be used as indicators of different phases of the COVID-19. By varying C1 over time, we identified different phases of the COVID-19 in the analyzed countries over the target time period.

Investigation of propagation dynamics of material deformations caused by laser pulse action

The mechanoluminescent materials attract increasing attention of scientists due to their capability of visualizing the mechanical stresses and deformations experienced by them. The deformations of materials arising under the action of powerful laser pulses were studied. The composite mechanoluminescent materials based on the polymer and phosphor powder were used for visualization and registration of deformation evolution dynamics. The mechanoluminescent materials were deposited on the surface of the materials under study. It has been shown that the spatial distribution of glow intensity of the mechanoluminescent layer and the rate of its change make possible judging the value and rate of material deformation under laser pulses.

Analysis on Evolution Characteristics of Industry University Research Innovation Network in Guizhou Province Based on Patent

Based on the industry-university-research cooperation patent data of Guizhou Province from 1986 to 2020, this paper constructs Guizhou industry-university-research innovation network, and empirically explores the overall structural characteristics of Guizhou industry-university-research innovation network, such as network scale and network density, as well as the time evolution dynamics of nodes and cooperation intensity. It is found that the scale of industry-university-research innovation network in Guizhou Province is gradually expanding, the nodes are gradually increasing, and more cooperative groups have been formed, but the overall network is low density; Guizhou University and other universities and scientific research institutions have always occupied the central position of the network. Although enterprises are not in the core position, the intensity of cooperation with institutions is gradually increasing.

Asteroseismic fingerprints of stellar mergers

Stellar mergers are important processes in stellar evolution, dynamics, and transient science. However, it is difficult to identify merger remnant stars because they cannot easily be distinguished from single stars based on their surface properties. We demonstrate that merger remnants can potentially be identified through asteroseismology of red giant stars using measurements of the gravity mode period spacing together with the asteroseismic mass. For mergers that occur after the formation of a degenerate core, remnant stars have over-massive envelopes relative to their cores, which is manifested asteroseismically by a g mode period spacing smaller than expected for the star’s mass. Remnants of mergers which occur when the primary is still on the main sequence or whose total mass is less than ≈2 M⊙ are much harder to distinguish from single stars. Using the red giant asteroseismic catalogs of Vrard et al. (2016) and Yu et al. (2018), we identify 24 promising candidates for merger remnant stars. In some cases, merger remnants could also be detectable using only their temperature, luminosity, and asteroseismic mass, a technique that could be applied to a larger population of red giants without a reliable period spacing measurement.

Different Within-Host Viral Evolution Dynamics in Severely Immunosuppressed Cases with Persistent SARS-CoV-2

A successful Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variant, B.1.1.7, has recently been reported in the UK, causing global alarm. Most likely, the new variant emerged in a persistently infected patient, justifying a special focus on these cases. Our aim in this study was to explore certain clinical profiles involving severe immunosuppression that may help explain the prolonged persistence of viable viruses. We present three severely immunosuppressed cases (A, B, and C) with a history of lymphoma and prolonged SARS-CoV-2 shedding (2, 4, and 6 months), two of whom finally died. Whole-genome sequencing of 9 and 10 specimens from Cases A and B revealed extensive within-patient acquisition of diversity, 12 and 28 new single nucleotide polymorphisms, respectively, which suggests ongoing SARS-CoV-2 replication. This diversity was not observed for Case C after analysing 5 sequential nasopharyngeal specimens and one plasma specimen, and was only observed in one bronchoaspirate specimen, although viral viability was still considered based on constant low Ct values throughout the disease and recovery of the virus in cell cultures. The acquired viral diversity in Cases A and B followed different dynamics. For Case A, new single nucleotide polymorphisms were quickly fixed (13–15 days) after emerging as minority variants, while for Case B, higher diversity was observed at a slower emergence: fixation pace (1–2 months). Slower SARS-CoV-2 evolutionary pace was observed for Case A following the administration of hyperimmune plasma. This work adds knowledge on SARS-CoV-2 prolonged shedding in severely immunocompromised patients and demonstrates viral viability, noteworthy acquired intra-patient diversity, and different SARS-CoV-2 evolutionary dynamics in persistent cases.

Whole-genome microsynteny-based phylogeny of angiosperms

Plant genomes vary greatly in size, organization, and architecture. Such structural differences may be highly relevant for inference of genome evolution dynamics and phylogeny. Indeed, microsynteny—the conservation of local gene content and order—is recognized as a valuable source of phylogenetic information, but its use for the inference of large phylogenies has been limited. Here, by combining synteny network analysis, matrix representation, and maximum likelihood phylogenetic inference, we provide a way to reconstruct phylogenies based on microsynteny information. Both simulations and use of empirical data sets show our method to be accurate, consistent, and widely applicable. As an example, we focus on the analysis of a large-scale whole-genome data set for angiosperms, including more than 120 available high-quality genomes, representing more than 50 different plant families and 30 orders. Our ‘microsynteny-based’ tree is largely congruent with phylogenies proposed based on more traditional sequence alignment-based methods and current phylogenetic classifications but differs for some long-contested and controversial relationships. For instance, our synteny-based tree finds Vitales as early diverging eudicots, Saxifragales within superasterids, and magnoliids as sister to monocots. We discuss how synteny-based phylogenetic inference can complement traditional methods and could provide additional insights into some long-standing controversial phylogenetic relationships.