Miracle-dz/UniFAR-FTUs huggingface dataset:
Canonical Dual K -g-Bessel Sequences and K -g-Frame Sequences

The classical canonical dual for a K -g-frame is absent since the frame operator may not be invertible. We introduce the concept of canonical dual K -g-Bessel sequences, which have some properties similar to classical canonical dual, to investigate the duality of K -g-frames. We obtain the exact form of the canonical dual K -g-Bessel sequences for Parseval K -g-frames and some other related results. We also introduce the concept of K -g-frame sequences to explore the properties of local K -g-frames. We present a necessary and suﬃcient condition under which a K -g-frame sequence is a K -g-frame, and necessary and suﬃcient conditions for a sequence of bounded operators to be a K -g-frame sequence. We end the paper by examining the relationship between K -g-frame sequences and g-frames for closed subspaces, and the relationship between two K -g-frame sequences and the ranges of the involved operators.
Holonomy braidings, biquandles and quantum invariants of links with flat connections

R. Kashaev and N. Reshetikhin introduced the notion of holonomy braiding extending V. Turaev’s homotopy braiding to describe the behavior of cyclic representations of the unrestricted quantum groupUqsl(2) at root of unity. In this paper, using quandles and biquandles we develop a general theory for Reshetikhin–Turaev ribbon type functor for tangles with quandle representations. This theory applies to the unrestricted quantum group Uqsl(2) and produces an invariant of links with a gauge class of quandle representations. Mathematics Subject Classification Primary 57M27; Secondary 81R50 · 17B37
Energy Crisis in the Superbubble DEM L192 (N51D)

Superbubbles surrounding OB associations provide ideal laboratories in which to study the stellar energy feedback problem, because the stellar energy input can be estimated from the observed stellar content of the OB associations, and the interstellar thermal and kinetic energies of superbubbles are well defined and easy to observe. We have used DEM L192, also known as N51D, to carry out a detailed case study of the energy budget in a superbubble, and we find that the expected amount of stellar mechanical energy injected into the interstellar medium, (18 ± 5) × 1051 ergs, exceeds the amount of thermal and kinetic energies stored in the superbubble, (6 ± 2) × 1051 ergs. Clearly, a significant fraction of the stellar mechanical energy must have been converted into other forms of energy. The X-ray spectrum of the diffuse emission from DEM L192 requires a power-law component to explain the featureless emission at 1.0-3.0 keV. The origin of this power-law component is unclear, but it may be responsible for the discrepancy between the stellar energy input and the observed interstellar energy in DEM L192.
Mixture models : inference and applications to clustering

General Introduction Introduction History of Mixture Models Background to the General Classification Problem Mixture Likelihood Approach to Clustering Identifiability Likelihood Estimation for Mixture Models via EM Algorithm Start Values for EMm Algorithm Properties of Likelihood Estimators for Mixture Models Information Matrix for Mixture Models Tests for the Number of Components in a Mixture Partial Classification of the Data Classification Likelihood Approach to Clustering Mixture Models with Normal Components Likelihood Estimation for a Mixture of Normal Distribution Normal Homoscedastic Components Asymptotic Relative Efficiency of the Mixture Likelihood Approach Expected and Observed Information Matrices Assessment of Normality for Component Distributions: Partially Classified Data Assessment of Typicality: Partially Classified Data Assessment of Normality and Typicality: Unclassified Data Robust Estimation for Mixture Models Applications of Mixture Models to Two-Way Data Sets Introduction Clustering of Hemophilia Data Outliers in Darwin's Data Clustering of Rare Events Latent Classes of Teaching Styles Estimation of Mixing Proportions Introduction Likelihood Estimation Discriminant Analysis Estimator Asymptotic Relative Efficiency of Discriminant Analysis Estimator Moment Estimators Minimum Distance Estimators Case Study Homogeneity of Mixing Proportions Assessing the Performance of the Mixture Likelihood Approach to Clustering Introduction Estimators of the Allocation Rates Bias Correction of the Estimated Allocation Rates Estimated Allocation Rates of Hemophilia Data Estimated Allocation Rates for Simulated Data Other Methods of Bias Corrections Bias Correction for Estimated Posterior Probabilities Partitioning of Treatment Means in ANOVA Introduction Clustering of Treatment Means by the Mixture Likelihood Approach Fitting of a Normal Mixture Model to a RCBD with Random Block Effects Some Other Methods of Partitioning Treatment Means Example 1 Example 2 Example 3 Example 4 Mixture Likelihood Approach to the Clustering of Three-Way Data Introduction Fitting a Normal Mixture Model to Three-Way Data Clustering of Soybean Data Multidimensional Scaling Approach to the Analysis of Soybean Data References Appendix
A localised dynamic closure model for Euler turbulence

ABSTRACT In this work, we present a localised form of the dynamic eddy viscosity model for computationally efficient and accurate simulation of the turbulent flows governed by Euler equations. In our framework, we determine the dynamic model coefficient locally using the information from neighbouring grid points through a test filtering process. We then develop an optimised Gaussian filtering kernel, using a consistent definition with respect to the test filtering ratio, which gives full attenuation at the grid cut-off wave number. A systematic a-posteriori analysis of our model is performed by solving two 3D test problems: (i) incompressible Taylor–Green vortex flow and (ii) compressible shear layer turbulence induced by Kelvin–Helmholtz instability to show the wide range of applicability of the proposed localised dynamic model. We demonstrate that the proposed dynamic model is robust and provides a better estimation of the inertial range turbulence dynamics than other numerical models tested in this study.
Long range dynamical coupling between magnetic adatoms mediated by a 2D topological insulator

We study the spin excitation spectra and the dynamical exchange coupling between iron adatoms on a Bi bilayer nanoribbon. We show that the topological character of the edge states is preserved in the presence of the magnetic adatoms. Nevertheless, they couple significantly to the edge spin currents, as witnessed by the large and long-ranged dynamical coupling we obtain in our calcula- tions. The large effective magnetocrystalline anisotropy of the magnetic adatoms combined with the transport properties of the topologically protected edge states make this system a strong candidate for implementation of spintronics devices and quantum information and/or computation protocols.
Coding random self-similar river networks and calculating geometric distances: 1. General methodology / Codage de réseaux hydrographiques auto-similaires aléatoires et calcul de distances géométriques: 1. Méthodologie générale

Abstract This study proposes a preliminary method for coding random self-similar river networks as a series of numbers, and investigates the corresponding algorithm that calculates the geometric distances from the code series. The coding method, generating random self-similar patterns with various probabilities of particular pattern links, and transferring the pattern into numerical code series, is proposed, based on the wide range of stochastic characteristics of natural patterns. The heredity of self-similarity and the connecting relationships inside the generated pattern are discussed. Finally, the algorithm to calculate the geometric distances of the generated pattern are developed.
Poincar´e polynomial and SL (2 , C ) SL (2 , C ) SL (2 , C ) -representation on K¨ahler manifolds

The cohomology ring of any compact K¨ahler manifold gives rise to an SL (2 , C )-representation. In this short note, we show that the character of this representation essentially is the Poincar´e polynomial of this K¨ahler manifold, which gives a natural interpretation of the Poincar´e polynomial for K¨ahler manifolds. Our result is an analogue to an interpretation of the χ y genus for holomorphic symplectic manifolds due to George Thompson.
Analytic automorphisms of C 2 generated by polynomial vector

We give the classiﬁcation of the transcendental automorphisms of C 2 of the form ( x, y ) → ( P e Q , R e S ) with P, Q, R , S ∈ C [ x, y ]. Mathematics Subject Classiﬁcation. Primary 32M17; Secondary 32M25.
Classiﬁcation of large partial plane spreads in PG(6 , 2) and related combinatorial objects

The partial plane spreads in PG(6 , 2) of maximum possible size 17 and of size 16 are classiﬁed. Based on this result, we obtain the classiﬁcation of the following closely related combinatorial objects: vector space partitions of PG(6 , 2) of type (3 16 4 1 ), binary 3 × 4 MRD codes of minimum rank distance 3, and subspace codes with the optimal parameters (7 , 17 , 6) 2 and (7 , 34 , 5) 2 .
Key comparison BIPM.RI(I)-K2 of the air-kerma standards of the ARPANSA, Australia, and the BIPM in low-energy x-rays

A key comparison has been made between the air-kerma standards of the ARPANSA, Australia, and the BIPM in the low-energy x ray range. The results show the standards to agree at the level of the expanded uncertainty of the comparison of 9 parts in 103 (22 parts in 103 at 10 kV). The results are analysed and presented in terms of degrees of equivalence, suitable for entry in the BIPM key comparison database. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm. org/kcdb/. The final report has been peer-reviewed and approved for publication by the CCRI, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Organ Finder a new AI-based organ segmentation tool for CT

Background: Automated organ segmentation in computed tomography (CT) is a vital component in many artificial intelligence-based tools in medical imaging. This study presents a new organ segmentation tool called Organ Finder 2.0. In contrast to most existing methods, Organ Finder was trained and evaluated on a rich multi-origin dataset with both contrast and non-contrast studies from different vendors and patient populations. Approach: A total of 1,171 CT studies from seven different publicly available CT databases were retrospectively included. Twenty CT studies were used as test set and the remaining 1,151 were used to train a convolutional neural network. Twenty-two different organs were studied. Professional annotators segmented a total of 5,826 organs and segmentation quality was assured manually for each of these organs. Results: Organ Finder showed high agreement with manual segmentations in the test set. The average Dice index over all organs was 0.93 and the same high performance was found for four different subgroups of the test set based on the presence or absence of intravenous and oral contrast. Conclusions: An AI-based tool can be used to accurately segment organs in both contrast and non-contrast CT studies. The results indicate that a large training set and high-quality manual segmentations should be used to handle common variations in the appearance of clinical CT studies.
Efficacy of the wild-type/Omicron BA.1 bivalent vaccine as the second booster dose against Omicron BA.2 and BA.5

Introduction In addition to the original monovalent vaccines available for SARS-CoV-2, bivalent vaccines covering wild-type (WT) and Omicron BA.1 are also available. However, there is a lack of real-world data on the effectiveness of bivalent vaccines as second boosters on the dominant Omicron sublineages, including BA.2 and BA.5. Methods This prospective longitudinal cohort study was conducted at Toyama University Hospital, a tertiary medical center in Japan. Participants (n = 565) who received the first booster vaccination were followed up until 2 weeks after the second booster dose of the monovalent mRNA-1273 (WT group, n = 168) and bivalent BNT162b2 (WT+BA.1 group, n = 23) vaccines. Participants with previous SARS-CoV-2 infections were excluded from the study. Anti-receptor-binding domain (RBD) antibody levels and neutralizing activity were measured. Vaccine-related symptoms were also assessed using a questionnaire after the second booster dose. Results The anti-RBD antibody levels after the second booster dose in the WT and WT+BA.1 group were similar (median [inter quartile], 26262.0 [16951.0-38137.0] U/mL vs. 24840.0 [14828.0-41460.0] U/mL, respectively). Although the neutralization activity of the pooled sera of the WT+BA.1 group was the lowest against BA.5, the activities against BA.2 and BA.5 were higher than those of the WT group in both pseudotyped and live virus assays. Vaccine-related symptoms, including systemic and local symptoms, were strongly correlated with anti-RBD antibody levels and neutralizing titers with significant differences. Conclusion The second booster dose of the bivalent (WT/Omicron BA.1) vaccine induced higher neutralizing activity against BA.2 and BA.5 than that of the original monovalent vaccine.
Maternal synapsin autoantibodies are associated with neurodevelopmental delay

Maternal autoantibodies can be transmitted diaplacentally, with potentially deleterious effects on neurodevelopment. Synapsin 1 (SYN1) is a neuronal protein that is important for synaptic communication and neuronal plasticity. While monoallelic loss of function (LoF) variants in the SYN1 gene result in X-linked intellectual disability (ID), learning disabilities, epilepsy, behavioral problems, and macrocephaly, the effect of SYN1 autoantibodies on neurodevelopment remains unclear. We recruited a clinical cohort of 208 mothers and their children with neurologic abnormalities and analyzed the role of maternal SYN1 autoantibodies. We identified seropositivity in 9.6% of mothers, and seropositivity was associated with an increased risk for ID and behavioral problems. Furthermore, children more frequently had epilepsy, macrocephaly, and developmental delay, in line with the SYN1 LoF phenotype. Whether SYN1 autoantibodies have a direct pathogenic effect on neurodevelopment or serve as biomarkers requires functional experiments.
Gas flow above an alpha disk

The flow of particles and of gas above an alpha disk is studied by solving the equations of their motion when acted upon by the radiation pressure from the disk and by the gravitational attraction of its central object. When the disk luminosity is 0.4 times the Eddington luminosity, almost all material is ultimately accepted by the central object. Between Eddington numbers 0.4 and 1.2, some gas streams away along the rotation axis of the disk. When 1.2
Inter-Rater Agreement for the Annotation of Neurologic Concepts in Electronic Health Records

The extraction of patient signs and symptoms recorded as free text in electronic health records is critical for precision medicine. Once extracted, signs and symptoms can be made computable by mapping to clinical concepts in an ontology. Extracting clinical concepts from free text is tedious and time-consuming. Prior studies have suggested that inter-rater agreement for clinical concept extraction is low. We have examined inter-rater agreement for annotating neurologic concepts in clinical notes from electronic health records. After training on the annotation process, the annotation tool, and the supporting neuro-ontology, three raters annotated 15 clinical notes in three rounds. Inter-rater agreement between the three annotators was high for text span and category label. A machine annotator based on a convolutional neural network had a high level of agreement with the human annotators, but one that was lower than human inter-rater agreement. We conclude that high levels of agreement between human annotators are possible with appropriate training and annotation tools. Furthermore, more training examples combined with improvements in neural networks and natural language processing should make machine annotators capable of high throughput automated clinical concept extraction with high levels of agreement with human annotators.
Comparing pre- and post-diagnosis presentations of multiple sclerosis and other inflammatory diseases in primary care: an agnostic study of French and British health records.

Importance The identification of a prodrome in multiple sclerosis (MS) is the key to early prevention and the targeting of new interventions. Objective To assess the associations between health conditions diagnosed in primary care and the risk of incident MS relative to other autoimmune inflammatory diseases. Design A case-control study in the UK and France was conducted from Jan 1, 1996 to March 28, 2022 in the UK and from Jan 4, 1998 to March 28, 2022 in France. Setting Data were obtained from electronic health records from the Health Improvement Network database. Participants We included all individuals with at least two years of history in the database and a recorded diagnosis of either MS, lupus or Crohn's disease. Three controls matched for sex, age at index date and year at index date were randomly assigned to each individual with a diagnosis of MS. Main outcome measures We agnostically tested the associations between 113 different diagnoses and multiple sclerosis diagnosis during the five years before or the five years after the diagnosis of MS. Unadjusted odds ratios (ORs) and 95% CIs were estimated, and p values were corrected for multiple comparisons. We also stratified for sex, age at diagnosis, and year of diagnosis. A logistic regression analysis (adjusted for sex and age at diagnosis) was performed to compare MS patients with lupus and Crohn's disease patients. Results The study population consisted of patients with MS (UK: 15,808; and France: 4,366), Crohn's disease (UK: 20,872; and France: 9,605) or lupus (UK: 5,296; and France: 2,041). We identified twelve health conditions as significantly positively associated with the risk of MS. After considering health conditions suggestive of demyelinating events as the first diagnosis of MS, five health conditions remained significantly associated with MS: depression (UK OR 1.22 [95%CI 1.11-1.34]), sexual dysfunction (1.47 [1.11-1.95]), constipation (1.5 [1.27-1.78]), cystitis (1.21 [1.05-1.39]), and urinary tract infections (1.38 [1.18-1.61]). However, none of these conditions was selectively associated with MS in comparisons with both lupus and Crohn's disease. During the five years after MS diagnosis, all five health conditions identified here were still associated with MS. Conclusion and relevance The identified symptoms may be considered to be not only prodromal, but also early-stage symptoms, albeit not specific to MS.
Bayes' theorem and quantum retrodiction

Abstract We derive on the basis of Bayes' theorem a simple but general expression for the retrodicted premeasurement state associated with the result of any measurement. The retrodictive density operator is the normalized probability operator measure element associated with the result. We examine applications to quantum optical cryptography and to the optical beam splitter.
Implications of cosmic strings with time-varying tension on the CMB and large scale structure

We investigate cosmological evolution and implications of cosmic strings with time-dependent tension. We derive basic equations of time development of the correlation length and the velocity of such strings, based on the one-scale model. Then, we find that, in the case where the tension depends on some power of the cosmic time, cosmic strings with time-dependent tension goes into the scaling solution if the power is lower than a critical value. We also discuss cosmic microwave background anisotropy and matter power spectra produced by these strings. The constraints on their tensions from the Wilkinson microwave anisotropy probe (WMAP) 3 yr data and Sloan digital sky survey (SDSS) data are also given.
Ongoing star formation at the outskirts of Sextans A: Spectroscopic detection of early-O type stars.

With both nebular- and stellar-derived abundances of $\lesssim$ 1/10 Zsun and low foreground extinction, Sextans A is a prime candidate to replace the Small Magellanic Cloud as reservoir of metal-poor massive stars and reference to study the metal-poor Universe. We report the discovery of two early-O type stars in Sextans A, the earliest O-stars with metallicity < 1/7 Zsun known to date, and two additional O9 stars. Colour-excess estimates towards individual targets, enabled by spectral typing, manifest that internal reddening is neither uniform nor negligible. The four targets define a new region of star formation far from the optically-brightest centre of the galaxy and from its conspicuous HII shells, but not devoid of neutral hydrogen. In fact, we detect a spatial correlation between OB-stars and HI in Sextans A and other dIrr's that leads us to propose that the neutral phase may be fundamental to star formation in low-density environments. According to the existing evidence at least two of the targets formed in isolation, thus suggestive of an stochastic sampling of the initial mass function that would enable low-mass galaxies like Sextans A to form very massive stars. The discovery of these four stars provide spatially-resolved, spectroscopic confirmation of recent findings suggesting that dwarf galaxies can sustain star formation despite the low density of the gas phase.
Imaging and microscopy in linear and nonlinear media using digital holography

Keywords: nonlinear optics ; imaging ; optical Kerr effect ; filamentation ; self-focusing ; digital holography ; confocal microscopy ; optical phase tomography These Ecole polytechnique federale de Lausanne EPFL, n° 5617 (2013)Programme doctoral PhotoniqueFaculte des sciences et techniques de l'ingenieurInstitut de microtechniqueLaboratoire d'optiqueJury: C. Moser (president), J. Fleischer, O. Martin, C. Yang Public defense: 2013-1-25 Reference doi:10.5075/epfl-thesis-5617Print copy in library catalog Record created on 2013-01-21, modified on 2017-05-10
Temperature rise in shear bands in a simulated metallic glass

Temperature rise ($\mathrm{\ensuremath{\Delta}}T$) associated with shear banding of metallic glasses is of great importance for their performance. However, experimental measurement of $\mathrm{\ensuremath{\Delta}}T$ is difficult due to temporal and spatial localization of shear bands and, as a result, our understanding of the mechanism of $\mathrm{\ensuremath{\Delta}}T$ is limited. Here, based on molecular dynamics simulations, we observe a spectrum of $\mathrm{\ensuremath{\Delta}}T$, which depends on both sample size and strain rate, in the shear bands of CuZr metallic glass under tension. More importantly, we find that the maximum sliding velocity of the shear bands correlates linearly with the corresponding $\mathrm{\ensuremath{\Delta}}T$, ranging from $\ensuremath{\sim}25$ K up to near the melting point for the samples studied. Taking heat diffusion into account, we expect $\mathrm{\ensuremath{\Delta}}T$ to be lower than 25 K for the lower end of sliding velocity. At high temperature, shear band bifurcation and/or multiplication can occur as a negative feedback mechanism that prevents temperature rising well above the melting point.