cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Biocompatible surface functionalization architecture for a diamond quantum sensor
Creators: name: Xie, Mouzhe
name: Yu, Xiaofei
name: Rodgers, Lila V. H.
name: Xu, Daohong
name: Chi-Duran, Ignacio
name: Toros, Adrien
name: Quack, Niels
name: de Leon, Nathalie P.
name: Maurer, Peter C.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: Biological Physics (physics.bio-ph)
subject: FOS: Physical sciences

description: Quantum metrology enables some of the most precise measurements. In the life sciences, diamond-based quantum sensing has enabled a new class of biophysical sensors and diagnostic devices that are being investigated as a platform for cancer screening and ultra-sensitive immunoassays. However, a broader application in the life sciences based on nanoscale nuclear magnetic resonance spectroscopy has been hampered by the need to interface highly sensitive quantum bit (qubit) sensors with their biological targets. Here, we demonstrate a new approach that combines quantum engineering with single-molecule biophysics to immobilize individual proteins and DNA molecules on the surface of a bulk diamond crystal that hosts coherent nitrogen vacancy qubit sensors. Our thin (sub-5 nm) functionalization architecture provides precise control over protein adsorption density and results in near-surface qubit coherence approaching 100 μs. The developed architecture remains chemically stable under physiological conditions for over five days, making our technique compatible with most biophysical and biomedical applications.
Grad DFT: a software library for machine learning enhanced density functional theory
Creators: name: Casares, Pablo A. M.
name: Baker, Jack S.
name: Medvidovic, Matija
name: Reis, Roberto dos
name: Arrazola, Juan Miguel
Publisher: name: arXiv
Year: 2023
Subjects: subject: Chemical Physics (physics.chem-ph)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Machine Learning (cs.LG)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT; an endeavor with many open questions and technical challenges. In this work, we present Grad DFT: a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange-correlation energy functionals. Grad DFT employs a pioneering parametrization of exchange-correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, Grad DFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.
description: 22 pages, 10 figures. The following article has been submitted to the Journal of Chemical Physics. After it is published, it will be found at https://publishing.aip.org/resources/librarians/products/journals/
Adiabatic theorem for classical stochastic processes
Creators: name: Takahashi, Kazutaka
Publisher: name: arXiv
Year: 2023
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: We apply adiabatic theorems developed for quantum mechanics to stochastic annealing processes described by the classical master equation with a time-dependent generator. When the instantaneous stationary state is unique and the minimum decay rate g is nonzero, the time-evolved state is basically relaxed to the instantaneous stationary state. By formulating an asymptotic expansion rigorously, we derive conditions for the annealing time T that the state is close to the instantaneous stationary state. Depending on the time dependence of the generator, typical conditions are written as T> const/g^a with 1const|ln g|/g^2.
description: 18 pages, 7 figures
Cucurbit[8]uril-improved recognition using a fluorescent sensor for different metal cations
Creators: name: Deng, Xin Yu
name: Xu, Wei Tao
name: Liu, Ming
name: Yang, Mei Xiang
name: Zhu, Qian Jiang
name: Lü, Bin
name: Tao, Zhu
Publisher: name: Taylor & Francis
Year: 2019
Subjects: subject: Biophysics
subject: Space Science
subject: Molecular Biology
subject: Evolutionary Biology
subject: FOS: Biological sciences
subject: Environmental Sciences not elsewhere classified
subject: Chemical Sciences not elsewhere classified
subject: Astronomical and Space Sciences not elsewhere classified
subject: Cancer

description: Metal cations in aqueous solutions at different pHs (1.5, 4.5 and7.2) can be detected using the known inclusion complex H33258@Q8 as a fluorescent probe. Indeed, the fluorescence intensity of H33258 increases rapidly upon increasing the amount of Q[8] up to a Q[8]:H33258 ratio of 2:1, even at pH 1.5. The experimental results reveal that the probe not only exhibited selective recognition of metal cations at different pH but also showed different recognition for metal cations at different pHs. At pH 7.2, the probe responded to quite a variety metal cations, including one of the third main group elements, Al3+, four transition metal cations, Hg2+, Fe3+, Fe2+, and Cr3+ and three lanthanide cations Eu3+, Tm3+ and Yb3+; At pH 4.5, the probe responded to only two transition metal cations, Hg2+ and Fe3+. Unexpectedly, the probe lost its recognition properties at pH 1.5.
Spin Drude weight for the integrable XXZ chain with arbitrary spin
Creators: name: Ae, Shinya
name: Sakai, Kazumitsu
Publisher: name: arXiv
Year: 2023
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Mathematical Physics (math-ph)
subject: Exactly Solvable and Integrable Systems (nlin.SI)
subject: FOS: Physical sciences

description: Using generalized hydrodynamics (GHD), we exactly evaluate the finite-temperature spin Drude weight at zero magnetic field for the integrable XXZ chain with arbitrary spin and easy-plane anisotropy. First, we construct the fusion hierarchy of the quantum transfer matrices ($T$-functions) and derive functional relations ($T$- and $Y$-systems) satisfied by the $T$-functions and certain combinations of them ($Y$-functions). Through analytical arguments, the $Y$-system is reduced to a set of non-linear integral equations, equivalent to the thermodynamic Bethe ansatz (TBA) equations. Then, employing GHD, we calculate the spin Drude weight at arbitrary finite temperatures. As a result, a characteristic fractal-like structure of the Drude weight is observed at arbitrary spin, similar to the spin-1/2 case. In our approach, the solutions to the TBA equations (i.e., the $Y$-functions) can be explicitly written in terms of the $T$-functions, thus allowing for a systematic calculation of the high-temperature limit of the Drude weight.
description: 45 pages; typos fixed; presentation improved; references added
Glioma subtype classification from histopathological images using in-domain and out-of-domain transfer learning: An experimental study
Creators: name: Despotovic, Vladimir
name: Kim, Sang-Yoon
name: Hau, Ann-Christin
name: Kakoichankava, Aliaksandra
name: Klamminger, Gilbert Georg
name: Borgmann, Felix Bruno Kleine
name: Frauenknecht, Katrin B. M.
name: Mittelbronn, Michel
name: Nazarov, Petr V.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Image and Video Processing (eess.IV)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: We provide in this paper a comprehensive comparison of various transfer learning strategies and deep learning architectures for computer-aided classification of adult-type diffuse gliomas. We evaluate the generalizability of out-of-domain ImageNet representations for a target domain of histopathological images, and study the impact of in-domain adaptation using self-supervised and multi-task learning approaches for pretraining the models using the medium-to-large scale datasets of histopathological images. A semi-supervised learning approach is furthermore proposed, where the fine-tuned models are utilized to predict the labels of unannotated regions of the whole slide images (WSI). The models are subsequently retrained using the ground-truth labels and weak labels determined in the previous step, providing superior performance in comparison to standard in-domain transfer learning with balanced accuracy of 96.91% and F1-score 97.07%, and minimizing the pathologist's efforts for annotation. Finally, we provide a visualization tool working at WSI level which generates heatmaps that highlight tumor areas; thus, providing insights to pathologists concerning the most informative parts of the WSI.
Universal and shape dependent features of surface superconductivity
Creators: name: Correggi, Michele
name: Devanarayanan, Bharathiganesh
name: Rougerie, Nicolas
Publisher: name: arXiv
Year: 2017
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: Mathematical Physics (math-ph)
subject: Analysis of PDEs (math.AP)
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: We analyze the response of a type II superconducting wire to an external magnetic field parallel to it in the framework of Ginzburg-Landau theory. We focus on the surface superconductivity regime of applied field between the second and third critical values, where the superconducting state survives only close to the sample's boundary. Our first finding is that, in first approximation, the shape of the boundary plays no role in determining the density of superconducting electrons. A second order term is however isolated, directly proportional to the mean curvature of the boundary. This demonstrates that points of higher boundary curvature (counted inwards) attract superconducting electrons.
Stability and convergence of Strang splitting. Part I: Scalar Allen-Cahn equation
Creators: name: Li, Dong
name: Quan, Chaoyu
name: Xu, Jiao
Publisher: name: arXiv
Year: 2021
Subjects: subject: Numerical Analysis (math.NA)
subject: Analysis of PDEs (math.AP)
subject: FOS: Mathematics

description: We consider a class of second-order Strang splitting methods for Allen-Cahn equations with polynomial or logarithmic nonlinearities. For the polynomial case both the linear and the nonlinear propagators are computed explicitly. We show that this type of Strang splitting scheme is unconditionally stable regardless of the time step. Moreover we establish strict energy dissipation for a judiciously modified energy which coincides with the classical energy up to $\mathcal O(τ)$ where $τ$ is the time step. For the logarithmic potential case, since the continuous-time nonlinear propagator no longer enjoys explicit analytic treatments, we employ a second order in time two-stage implicit Runge--Kutta (RK) nonlinear propagator together with an efficient Newton iterative solver. We prove a maximum principle which ensures phase separation and establish energy dissipation law under mild restrictions on the time step. These appear to be the first rigorous results on the energy dissipation of Strang-type splitting methods for Allen-Cahn equations.
description: 22 pages, to appear in JCP
Additional file 2: of Effectiveness, efficiency and adverse effects of using direct or indirect bonding technique in orthodontic patients: a systematic review and meta-analysis
Creators: name: Li, Yanxi
name: Mei, Li
name: Wei, Jieya
name: Yan, Xinyu
name: Zhang, Xu
name: Zheng, Wei
name: Li, Yu
Publisher: name: figshare
Year: 2019
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Pharmacology
subject: Biological Sciences not elsewhere classified
subject: Science Policy

description: Figure S2. Forest plot of sensitivity analyses. (PDF 218 kb)
Efficient simulation of DC-DC switch-mode power converters by multirate partial differential equations
Creators: name: Pels, Andreas
name: Gyselinck, Johan
name: Sabariego, Ruth V.
name: Schöps, Sebastian
Publisher: name: arXiv
Year: 2017
Subjects: subject: Computational Engineering, Finance, and Science (cs.CE)
subject: Numerical Analysis (math.NA)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics
subject: G.1.7; G.1.8; J.2
subject: 65L05, 65L80, 65M60

description: In this paper, Multirate Partial Differential Equations (MPDEs) are used for the efficient simulation of problems with 2-level pulsed excitations as they often occur in power electronics, e.g., DC-DC switch-mode converters. The differential equations describing the problem are reformulated as MPDEs which are solved by a Galerkin approach and time discretization. For the solution expansion two types of basis functions are proposed, namely classical Finite Element (FE) nodal functions and the recently introduced excitation-specific pulse width modulation (PWM) basis functions. The new method is applied to the example of a buck converter. Convergence, accuracy of the solution and computational efficiency of the method are numerically analyzed.
Dark Matter from Axion Strings with Adaptive Mesh Refinement
Creators: name: Buschmann, Malte
name: Foster, Joshua W.
name: Hook, Anson
name: Peterson, Adam
name: Willcox, Don E.
name: Zhang, Weiqun
name: Safdi, Benjamin R.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: Axions are hypothetical particles that may explain the observed dark matter (DM) density and the non-observation of a neutron electric dipole moment. An increasing number of axion laboratory searches are underway worldwide, but these efforts are made difficult by the fact that the axion mass is largely unconstrained. If the axion is generated after inflation there is a unique mass that gives rise to the observed DM abundance; due to nonlinearities and topological defects known as strings, computing this mass accurately has been a challenge for four decades. Recent works, making use of large static lattice simulations, have led to largely disparate predictions for the axion mass, spanning the range from 25 microelectronvolts to over 500 microelectronvolts. In this work we show that adaptive mesh refinement (AMR) simulations are better suited for axion cosmology than the previously-used static lattice simulations because only the string cores require high spatial resolution. Using dedicated AMR simulations we obtain an over three order of magnitude leap in dynamic range and provide evidence that axion strings radiate their energy with a scale-invariant spectrum, to within $\sim$5% precision, leading to a mass prediction in the range (40,180) microelectronvolts.
description: 7+11 pages, 4 + 10 figures, Supplementary Animations at https://bit.ly/amr_axion
Analysis of Current Practice in CeOS Uptake in Higher Education Curricula and Teaching Practice in Library Studies in SE Europe
Creators: name: Karaiskou, Theodora
name: Tsakonas, Giannis
Publisher: name: Zenodo
Year: 2024

description: This document focuses on Citizen Science and its involvement in curricula of Higher Education Institutions in Southeastern Europe. It provides an analysis of the current practices in Library and Information Science studies, using data from a landscape research and a survey involving students from various parts of Europe.
Additional file 1: of Test-retest repeatability of child’s respiratory symptoms and perceived indoor air quality – comparing self- and parent-administered questionnaires
Creators: name: Lampi, Jussi
name: Ung-Lanki, Sari
name: Santalahti, Päivi
name: Pekkanen, Juha
Publisher: name: figshare
Year: 2018
Subjects: subject: Medicine
subject: Physiology
subject: FOS: Biological sciences
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Sociology
subject: FOS: Sociology
subject: 69999 Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Science Policy

description: Test-retest repeatability of child's respiratory symptoms and perceived indoor air quality - Additional file. (PDF 200 kb)
title: ADCO, Cartulaire général de Cîteaux, dit de Jean de Cirey, (XVe siècle), tome VI, Cart. 190 (11 H 75), 316 folios, f. 0061r
Creators: name: de la Côte d'Or, Archives départementales
name: Archives Départementales De La Côte-D'Or
name: Petot, Frédérique
name: Projet CBMA
name: CG21/F.PETOT/2012
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020
Subjects: subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris
subject: cartulaire
subject: Corpus Burgundiae Medii Aevi
subject: Chartes de la Bourgogne du Moyen Âge

description: Cartulaire général de Cîteaux, dit de Jean de Cirey, (XVe siècle), tome VI, Archives départementales de la Côte-d'Or, Cart. 190 (11 H 75), 316 folios, f. 0061r, Numérisation en mode image.
description: Relation: http://www.cbma-project.eu/
description: Bibliographic citation: Cartulaire général de Cîteaux, dit de Jean de Cirey, (XVe siècle), tome VI, Archives départementales de la Côte-d'Or, Cart. 190 (11 H 75), 316 folios, f. 0061r, in Projet CBMA - Corpus Burgundiae Medii Aevi [Ressource en ligne], https:// manuscrits.cbma-project.eu/
description: Provenance: abbaye de Cîteaux
description: Provenance: http://www.wikidata.org/entity/Q843261
description: Provenance: https://www.geonames.org/3024876
description: Provenance: http://www.idref.fr/030974844/id
description: Provenance: https://catalogue.bnf.fr/ark:/12148/cb12228351v
f(R) Gravity in an Ellipsoidal Universe
Creators: name: Deliduman, Cemsinan
name: Kasikci, Oguzhan
name: Tugyanoglu, Vildan Keles
Publisher: name: arXiv
Year: 2023
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: FOS: Physical sciences

description: We propose a new model of cosmology based on an anisotropic background and a specific $f(R)$ theory of gravity. It is shown that field equations of $f(R)$ gravity in a Bianchi type I background give rise to a modified Friedmann equation. This model contains two important parameters: $γ$ and $δ$. We, thus, simply call our model $γδ$CDM. It is distinguished in two important aspects from the $Λ$CDM model: firstly, the contribution of different energy densities to the Hubble parameter are weighted with different weights, and then, dependence of energy densities to redshift is modified as well. This unorthodox relation of energy content to Hubble parameter brings forth a new way of interpreting the cosmological history. This solution does not allow the existence of a cosmological constant component, however, a dark energy contribution with dependence on redshift is possible. We tested observational relevance of the new solution by best fitting to different data sets. We found that our model could accommodate the idea of cosmological coupling of black holes.
description: 20 pages, 4 figures, 2 tables. v2: Prior choices are explained. New references added. v3: New references and further comments added. v4: Data analysis is repeated with larger data sets. Conclusions are unchanged. New references added. Final version
Weak antilocalization effect due to topological surface states in Bi$_2$Se$_{2.1}$Te$_{0.9}$
Creators: name: Shrestha, K.
name: Graf, D.
name: Marinova, V.
name: Lorenz, B.
name: Chu, C. W.
Publisher: name: arXiv
Year: 2017
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We have investigated the weak antilocalization (WAL) effect in the p-type Bi$_2$Se$_{2.1}$Te$_{0.9}$ topological system. The magnetoconductance shows a cusp-like feature at low magnetic fields, indicating the presence of the WAL effect. The WAL curves measured at different tilt angles merge together when they are plotted as a function of the normal field components, showing that surface states dominate the magnetoconductance in the Bi$_2$Se$_{2.1}$Te$_{0.9}$ crystal. We have calculated magnetoconductance per conduction channel and applied the Hikami-Larkin-Nagaoka formula to determine the physical parameters that characterize the WAL effect. The number of conduction channels and the phase coherence length do not change with temperature up to T=5 K. In addition, the sample shows a large positive magnetoresistance that reaches 1900% under a magnetic field of 35 T at T=0.33K with no sign of saturation. The magnetoresistance value decreases with both increasing temperature and tilt angle of the sample surface with respect to the magnetic field. The large magnetoresistance of topological insulators can be utilized in future technology such as sensors and memory devices.
description: 5 pages, 4 figures
Coherent Perfect Absorption in Tavis-Cummings Models
Creators: name: Wang, Zibo
name: Khatiwada, Pawan
name: Wang, Dan
name: Mirza, Imran M.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We theoretically study the conditions under which two laser fields can undergo Coherent Perfect Absorption (CPA) when shined on a single-mode bi-directional optical cavity coupled with two two- level quantum emitters (natural atoms, artificial atoms, quantum dots, qubits, etc.). In addition to being indirectly coupled through the cavity-mediated field, in our Tavis-Cummings model the two quantum emitters (QEs) are allowed to interact directly via the dipole-dipole interaction (DDI). Under the mean-field approximation and low-excitation assumption, in this work, we particularly focus on the impact of DDI on the existence of CPA in the presence of decoherence mechanisms (spontaneous emission from the QEs and the leakage of photons from the cavity walls). We also present a dressed-state analysis of the problem to discuss the underlying physics related to the allowed polariton state transitions in the Jaynes-Tavis-Cummings ladder. As a key result, we find that in the strong-coupling regime of cavity quantum electrodynamics, the strong DDI and the emitter-cavity detuning can act together to achieve the CPA at two laser frequencies tunable by the inter-atomic separation which are not possible to attain with a single QE in the presence of detuning. Our CPA results are potentially applicable in building quantum memories that are an essential component in long-distance quantum networking.
description: 14 pages, 7 figures
Conformal Bootstrap Analysis for Yang-Lee Edge Singularity
Creators: name: Hikami, S.
Publisher: name: arXiv
Year: 2017
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: Mathematical Physics (math-ph)
subject: FOS: Physical sciences

description: The Yang-Lee edge singularity is investigated by the determinant method of the conformal field theory. The critical dimension Dc, for which the scale dimension of scalar Delta_phi is vanishing, is discussed by this determinant method. The result is incorporated in the Pade analysis of epsilon expansion, which leads to an estimation of the value Delta_phi between three and six dimensions. The structure of the minors is viewed from the fixed points.
description: 15 page, 8 figures
Data and Script
Creators: name: Sedlmeier, Peter
name: Matko, Karin
Publisher: name: OSF
Year: 2020
Subjects: differential effects
mechanisms
meditation
meditation techniques
motivation
person-technique fit
personality
single-case research

description: Contains data and scripts to replicate the findings of the article "Which meditation technique for whom? An experimental single-case study comparing concentrative, humming, observing-thoughts, and walking meditation"
End-to-End Chess Recognition
Creators: name: Masouris, Athanasios
name: van Gemert, Jan
Publisher: name: arXiv
Year: 2023
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: Chess recognition is the task of extracting the chess piece configuration from a chessboard image. Current approaches use a pipeline of separate, independent, modules such as chessboard detection, square localization, and piece classification. Instead, we follow the deep learning philosophy and explore an end-to-end approach to directly predict the configuration from the image, thus avoiding the error accumulation of the sequential approaches and eliminating the need for intermediate annotations. Furthermore, we introduce a new dataset, Chess Recognition Dataset (ChessReD), that consists of 10,800 real photographs and their corresponding annotations. In contrast to existing datasets that are synthetically rendered and have only limited angles, ChessReD has photographs captured from various angles using smartphone cameras; a sensor choice made to ensure real-world applicability. Our approach in chess recognition on the introduced challenging benchmark dataset outperforms related approaches, successfully recognizing the chess pieces' configuration in 15.26% of ChessReD's test images. This accuracy may seem low, but it is ~7x better than the current state-of-the-art and reflects the difficulty of the problem. The code and data are available through: https://github.com/ThanosM97/end-to-end-chess-recognition.
description: 12 pages, 7 figures
Entanglement Spectrum in General Free Fermionic Systems
Creators: name: Bettelheim, Eldad
name: Banerjee, Aditya
name: Plenio, Martin B.
name: Huelga, Susana F.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: Mathematical Physics (math-ph)
subject: FOS: Physical sciences

description: The statistical mechanics characterization of a finite subsystem embedded in an infinite system is a fundamental question of quantum physics. Nevertheless, a full closed form { for all required entropic measures} does not exist in the general case even for free systems when the finite system in question is composed of several disjoint intervals. Here we develop a mathematical framework based on the Riemann-Hilbert approach to treat this problem in the one-dimensional case where the finite system is composed of two disjoint intervals and in the thermodynamic limit (both intervals and the space between them contains an infinite number of lattice sites and the result is given as a thermodynamic expansion). To demonstrate the usefulness of our method, we compute the change in the entanglement and negativity namely the spectrum of eigenvalues of the reduced density matrix with our without time reversal of one of the intervals. We do this in the case that the distance between the intervals is much larger than their size. The method we use can be easily applied to compute any power in an expansion in the ratio of the distance between the intervals to their size. {We expect these results to provide the necessary mathematical apparatus to address relevant questions in concrete physical scenarios, namely the structure and extent of quantum correlations in fermionic systems subject to local environment.
SN 2020zbf: A fast-rising hydrogen-poor superluminous supernova with strong carbon lines
Creators: name: Gkini, A.
name: Lunnan, R.
name: Schulze, S.
name: Dessart, L.
name: Brennan, S. J.
name: Sollerman, J.
name: Pessi, P. J.
name: Nichol, M.
name: Yan, L.
name: Omand, C. M. B.
name: Kangas, T.
name: Moore, T.
name: Anderson, J. P.
name: Chen, T. -W.
name: Gonzalez, E. P.
name: Gromadzki, M.
name: Gutiérrez, Claudia P.
name: Hiramatsu, D.
name: Howell, D. A.
name: Ihanec, N.
name: Inserra, C.
name: McCully, C.
name: Müller-Bravo, T. E.
name: Pellegrino, C.
name: Pignata, G.
name: Pursiainen, M.
name: Young, D. R.
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: SN\,2020zbf is a hydrogen-poor superluminous supernova (SLSN) at $z = 0.1947$ that shows conspicuous \ion{C}{II} features at early times, in contrast to the majority of H-poor SLSNe. Its peak magnitude is $M_{\rm g}$ = $-21.2$~mag and its rise time ($\lesssim 26.4$ days from first light) places SN\,2020zbf among the fastest rising type I SLSNe. We used spectra taken from ultraviolet (UV) to near-infrared wavelengths to identify spectral features. We paid particular attention to the \ion{C}{II} lines as they present distinctive characteristics when compared to other events. We also analyzed UV and optical photometric data and modeled the light curves considering three different powering mechanisms: radioactive decay of $^{56}$Ni, magnetar spin-down, and circumstellar medium (CSM) interaction. The spectra of SN\,2020zbf match the model spectra of a C-rich low-mass magnetar-powered supernova model well. This is consistent with our light curve modeling, which supports a magnetar-powered event with an ejecta mass $M_{\rm ej}$ = 1.5~$\rm M_\odot$. However, we cannot discard the CSM-interaction model as it may also reproduce the observed features. The interaction with H-poor, carbon-oxygen CSM near peak light could explain the presence of \ion{C}{II} emission lines. A short plateau in the light curve around 35 -- 45 days after peak, in combination with the presence of an emission line at 6580~Å,\ can also be interpreted as being due to a late interaction with an extended H-rich CSM. Both the magnetar and CSM-interaction models of SN\,2020zbf indicate that the progenitor mass at the time of explosion is between 2 and 5~$\rm M_\odot$. Modeling the spectral energy distribution of the host galaxy reveals a host mass of 10$^{8.7}$~$\rm M_\odot$, a star formation rate of 0.24$^{+0.41}_{-0.12}$~$\rm M_\odot$~yr$^{-1}$, and a metallicity of $\sim$ 0.4~$\rm Z_\odot$.
description: Accepted in A&A. 26 pages, 22 figures
A programmable two-qubit quantum processor in silicon
Creators: name: Watson, T. F.
name: Philips, S. G. J.
name: Kawakami, E.
name: Ward, D. R.
name: Scarlino, P.
name: Veldhorst, M.
name: Savage, D. E.
name: Lagally, M. G.
name: Friesen, Mark
name: Coppersmith, S. N.
name: Eriksson, M. A.
name: Vandersypen, L. M. K.
Publisher: name: arXiv
Year: 2017
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: With qubit measurement and control fidelities above the threshold of fault-tolerance, much attention is moving towards the daunting task of scaling up the number of physical qubits to the large numbers needed for fault tolerant quantum computing. Here, quantum dot based spin qubits may offer significant advantages due to their potential for high densities, all-electrical operation, and integration onto an industrial platform. In this system, the initialisation, readout, single- and two-qubit gates have been demonstrated in various qubit representations. However, as seen with other small scale quantum computer demonstrations, combining these elements leads to new challenges involving qubit crosstalk, state leakage, calibration, and control hardware which provide invaluable insight towards scaling up. Here we address these challenges and demonstrate a programmable two-qubit quantum processor in silicon by performing both the Deutsch-Josza and the Grover search algorithms. In addition, we characterise the entanglement in our processor through quantum state tomography of Bell states measuring state fidelities between 85-89% and concurrences between 73-80%. These results pave the way for larger scale quantum computers using spins confined to quantum dots.
Additional file 3: of Candidate SNP markers of reproductive potential are predicted by a significant change in the affinity of TATA-binding protein for human gene promoters
Creators: name: Chadaeva, Irina
name: Ponomarenko, Petr
name: Rasskazov, Dmitry
name: Sharypova, Ekaterina
name: Kashina, Elena
name: Zhechev, Dmitry
name: Drachkova, Irina
name: Arkova, Olga
name: Savinkova, Ludmila
name: Ponomarenko, Mikhail
name: Kolchanov, Nikolay
name: Osadchuk, Ludmila
name: Osadchuk, Alexandr
Publisher: name: figshare
Year: 2018
Subjects: subject: Biochemistry
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Pharmacology
subject: 69999 Biological Sciences not elsewhere classified
subject: 110309 Infectious Diseases
subject: FOS: Health sciences

description: Table S1. Clinically known dependences between reproductive potential and hereditary diseases whose SNP markers were predicted in this work. (PDF 198 kb)
Spatiotemporally Controlled Room Temperature Exciton Transport under Dynamic Pressure
Creators: name: Datta, Kanak
name: Lyu, Zhengyang
name: Li, Zidong
name: Taniguchi, Takashi
name: Watanabe, Kenji
name: Deotare, Parag B.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Applied Physics (physics.app-ph)
subject: FOS: Physical sciences

description: Two-dimensional transition metal dichalcogenides (TMDs) provide an attractive platform for studying strain dependent exciton transport at room temperature due to large exciton binding energy and strong bandgap sensitivity to mechanical stimuli. Here, we use Rayleigh type surface acoustic wave (SAW) to demonstrate controlled and directional exciton transport under weak coupling regime at room temperature. We screen the in-plane piezoelectric field using photogenerated carriers to study transport under type-I bandgap modulation and measure a maximum exciton drift velocity of 600 m/s. Furthermore, we demonstrate precise steering of exciton flux by controlling the relative phase between the input RF excitation and exciton photogeneration. The results provide important insight into the weak coupling regime between dynamic strain wave and room temperature excitons in a 2D semiconductor system and pave way to exciting applications of excitonic devices in data communication and processing, sensing and energy conversion.
Invariant vacuum
Creators: name: Robles-Perez, Salvador
Publisher: name: arXiv
Year: 2017
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: We apply the Lewis-Riesenfeld invariant method for the harmonic oscillator with time dependent mass and frequency to the modes of a charged scalar field that propagates in a curved, homogeneous and isotropic spacetime. We recover the Bunch-Davies vacuum in the case of a flat DeSitter spacetime, the equivalent one in the case of a closed DeSitter spacetime and the invariant vacuum in a curved spacetime that evolves adiabatically. In the three cases, it is computed the thermodynamical magnitudes of entanglement between the modes of the particles and antiparticles of the invariant vacuum, and the modification of the Friedmann equation caused by the existence of the energy density of entanglement. The amplitude of the vacuum fluctuations are also computed.
description: 10 pages. Revised version. Accepted in PLB
ChatGPT for Computational Topology
Creators: name: Liu, Jian
name: Shen, Li
name: Wei, Guo-Wei
Publisher: name: arXiv
Year: 2023
Subjects: subject: Algebraic Topology (math.AT)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Mathematics
subject: FOS: Computer and information sciences

description: ChatGPT represents a significant milestone in the field of artificial intelligence (AI), finding widespread applications across diverse domains. However, its effectiveness in mathematical contexts has been somewhat constrained by its susceptibility to conceptual errors. Concurrently, topological data analysis (TDA), a relatively new discipline, has garnered substantial interest in recent years. Nonetheless, the advancement of TDA is impeded by the limited understanding of computational algorithms and coding proficiency among theoreticians. This work endeavors to bridge the gap between theoretical topological concepts and their practical implementation in computational topology through the utilization of ChatGPT. We showcase how a pure theoretician, devoid of computational experience and coding skills, can effectively transform mathematical formulations and concepts into functional code for computational topology with the assistance of ChatGPT. Our strategy outlines a productive process wherein a mathematician trains ChatGPT on pure mathematical concepts, steers ChatGPT towards generating computational topology code, and subsequently validates the generated code using established examples. Our specific case studies encompass the computation of Betti numbers, Laplacian matrices, and Dirac matrices for simplicial complexes, as well as the persistence of various homologies and Laplacians. Furthermore, we explore the application of ChatGPT in computing recently developed topological theories for hypergraphs and digraphs. This work serves as an initial step towards effectively transforming pure mathematical theories into practical computational tools, with the ultimate goal of enabling real applications across diverse fields.
MOESM2 of Endoplasmic reticulum stress activation in adipose tissue induces metabolic syndrome in individuals with familial partial lipodystrophy of the Dunnigan type
Creators: name: Foss-Freitas, Maria
name: Ferraz, Rafael
name: Monteiro, Luciana
name: Gomes, Patricia
name: Iwakura, Ricardo
name: Luiz Freitas
name: Foss, Milton
Publisher: name: figshare
Year: 2018
Subjects: subject: Biochemistry
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Physiology
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: 111714 Mental Health
subject: FOS: Health sciences
subject: Computational Biology

description: Additional file 2: Figure S1. Human Unfolded Protein Response PCR-Array Layout in adipose tissue in individuals with FPLD. Regulation of genes expression in adipose tissue in response FPLD. (A) Heatmap representing the quantitation of 84 genes of ERS expressed in the subcutaneous adipose tissue of control group and FPLD group. (B) Quantitation of 84 genes (Fold-Change) in subcutaneous fat. ERS important genes are over-expressed in adipocytes of individuals with FPLD. Total RNA from adipose tissue were isolated from control group (n = 4) and FPLD group (n = 5) as described in the Experimental Procedures.
Speaker-independent Speech Separation with Deep Attractor Network
Creators: name: Luo, Yi
name: Chen, Zhuo
name: Mesgarani, Nima
Publisher: name: arXiv
Year: 2017
Subjects: subject: Sound (cs.SD)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Despite the recent success of deep learning for many speech processing tasks, single-microphone, speaker-independent speech separation remains challenging for two main reasons. The first reason is the arbitrary order of the target and masker speakers in the mixture permutation problem, and the second is the unknown number of speakers in the mixture output dimension problem. We propose a novel deep learning framework for speech separation that addresses both of these issues. We use a neural network to project the time-frequency representation of the mixture signal into a high-dimensional embedding space. A reference point attractor is created in the embedding space to represent each speaker which is defined as the centroid of the speaker in the embedding space. The time-frequency embeddings of each speaker are then forced to cluster around the corresponding attractor point which is used to determine the time-frequency assignment of the speaker. We propose three methods for finding the attractors for each source in the embedding space and compare their advantages and limitations. The objective function for the network is standard signal reconstruction error which enables end-to-end operation during both training and test phases. We evaluated our system using the Wall Street Journal dataset WSJ0 on two and three speaker mixtures and report comparable or better performance than other state-of-the-art deep learning methods for speech separation.
description: IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), Volume 26 Issue 4, April 2018, Page 787-796
Multi-Slice Dense-Sparse Learning for Efficient Liver and Tumor Segmentation
Creators: name: Zhao, Ziyuan
name: Ma, Zeyu
name: Liu, Yanjie
name: Zeng, Zeng
name: Chow, Pierce KH
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Artificial Intelligence (cs.AI)
subject: Machine Learning (cs.LG)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Accurate automatic liver and tumor segmentation plays a vital role in treatment planning and disease monitoring. Recently, deep convolutional neural network (DCNNs) has obtained tremendous success in 2D and 3D medical image segmentation. However, 2D DCNNs cannot fully leverage the inter-slice information, while 3D DCNNs are computationally expensive and memory intensive. To address these issues, we first propose a novel dense-sparse training flow from a data perspective, in which, densely adjacent slices and sparsely adjacent slices are extracted as inputs for regularizing DCNNs, thereby improving the model performance. Moreover, we design a 2.5D light-weight nnU-Net from a network perspective, in which, depthwise separable convolutions are adopted to improve the efficiency. Extensive experiments on the LiTS dataset have demonstrated the superiority of the proposed method.
description: Accepted in 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE EMBC 2021
Search for direct production of electroweakinos in final states with one lepton, jets and missing transverse momentum in pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector
Creators: name: ATLAS Collaboration
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: Searches for electroweak production of chargino pairs, $\tildeχ^{+}_{1}\tildeχ^{-}_{1}$, and of chargino and next-to-lightest neutralino, $\tildeχ^{\pm}_{1}\tildeχ^{0}_{2}$, are presented. The models explored assume that the charginos decay into a $W$ boson and the lightest neutralino, $\tildeχ^{\pm}_1 \rightarrow W^{\pm} \tildeχ^{0}_{1}$. The next-to-lightest neutralinos are degenerate in mass with the chargino and decay to $\tildeχ^{0}_{1}$ and either a $Z$ or a Higgs boson, $\tildeχ^{0}_{2} \rightarrow Z \tildeχ^{0}_{1}$ or $h \tildeχ^{0}_{1}$. The searches exploit the presence of a single isolated lepton and missing transverse momentum from the $W$ boson decay products and the lightest neutralinos, and the presence of jets from hadronically decaying $Z$ or $W$ bosons or from the Higgs boson decaying into a pair of $b$-quarks. The searches use 139 fb$^{-1}$ of $\sqrt{s}= 13$ TeV proton-proton collisions data collected by the ATLAS detector at the Large Hadron Collider between 2015 and 2018. No deviations from the Standard Model expectations are found, and 95% confidence level exclusion limits are set. Chargino masses ranging from 260 to 520 GeV are excluded for a massless $\tildeχ^{0}_{1}$ in chargino pair production models. Degenerate chargino and next-to-lightest neutralino masses ranging from 260 to 420 GeV are excluded for a massless $\tildeχ^{0}_{1}$ for $\tildeχ^{0}_{2} \rightarrow Z \tildeχ^{0}_{1}$. For decays through an on-shell Higgs boson and for mass-splitting between $\tildeχ^{\pm}_{1} / \tildeχ^{0}_{2}$ and $\tildeχ^{0}_{1}$ as small as the Higgs boson mass, mass limits are improved by up to 40 GeV in the range of 200-260 GeV and 280-470 GeV compared to previous ATLAS constraints.
description: 60 pages in total, authorlist starting on page 43, 10 figures, 12 tables, published in JHEP12(2023)167. All figures including auxiliary figures are available at http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2023-01
Two Eyes Are Better Than One: Exploiting Binocular Correlation for Diabetic Retinopathy Severity Grading
Creators: name: Qian, Peisheng
name: Zhao, Ziyuan
name: Chen, Cong
name: Zeng, Zeng
name: Li, Xiaoli
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Artificial Intelligence (cs.AI)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Diabetic retinopathy (DR) is one of the most common eye conditions among diabetic patients. However, vision loss occurs primarily in the late stages of DR, and the symptoms of visual impairment, ranging from mild to severe, can vary greatly, adding to the burden of diagnosis and treatment in clinical practice. Deep learning methods based on retinal images have achieved remarkable success in automatic DR grading, but most of them neglect that the presence of diabetes usually affects both eyes, and ophthalmologists usually compare both eyes concurrently for DR diagnosis, leaving correlations between left and right eyes unexploited. In this study, simulating the diagnostic process, we propose a two-stream binocular network to capture the subtle correlations between left and right eyes, in which, paired images of eyes are fed into two identical subnetworks separately during training. We design a contrastive grading loss to learn binocular correlation for five-class DR detection, which maximizes inter-class dissimilarity while minimizing the intra-class difference. Experimental results on the EyePACS dataset show the superiority of the proposed binocular model, outperforming monocular methods by a large margin.
description: Accepted in 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE EMBC 2021