cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
On lamps, walls, and eyes: the spectral radiance field and the evaluation of light pollution indoors
Creators: name: Bará, Salvador
name: Escofet, Jaume
Publisher: name: arXiv
Year: 2017
Subjects: subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: Light plays a key role in the regulation of different physiological processes, through several visual and non-visual retinal phototransduction channels whose basic features are being unveiled by recent research. The growing body of evidence on the significance of these effects has sparked a renewed interest in the determination of the light field at the entrance pupil of the eye in indoor spaces. Since photic interactions are strongly wavelength-dependent, a significant effort is being devoted to assess the relative merits of the spectra of the different types of light sources available for use at home and in the workplace. The spectral content of the light reaching the observer eyes in indoor spaces, however, does not depend exclusively on the sources: it is partially modulated by the spectral reflectance of the walls and surrounding surfaces, through the multiple reflections of the light beams along all possible paths from the source to the observer. This modulation can modify significantly the non-visual photic inputs that would be produced by the lamps alone, and opens the way for controlling -to a certain extent- the subject's exposure to different regions of the optical spectrum. In this work we evaluate the expected magnitude of this effect and we show that, for factorizable sources, the spectral modulation can be conveniently described in terms of a set of effective filter-like functions that provide useful insights for lighting design and light pollution assessment. The radiance field also provides a suitable bridge between indoor and outdoor light pollution studies.
description: Accepted version, to be published in Journal of Quantitative Spectroscopy & Radiative Transfer
Similar temperature scale for valence changes in Kondo lattices with different Kondo temperatures
Creators: name: Kummer, K.
name: Geibel, C.
name: Krellner, C.
name: Zwicknagl, G.
name: Laubschat, C.
name: Brookes, N. B.
name: Vyalikh, D. V.
Publisher: name: arXiv
Year: 2016
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: The Kondo model predicts that both the valence at low temperatures and its temperature dependence scale with the characteristic energy T_K of the Kondo interaction. Here, we study the evolution of the 4f occupancy with temperature in a series of Yb Kondo lattices using resonant X-ray emission spectroscopy. In agreement with simple theoretical models, we observe a scaling between the valence at low temperature and T_K obtained from thermodynamic measurements. In contrast, the temperature scale T_v at which the valence increases with temperature is almost the same in all investigated materials while the Kondo temperatures differ by almost four orders of magnitude. This observation is in remarkable contradiction to both naive expectation and precise theoretical predictions of the Kondo model, asking for further theoretical work in order to explain our findings. Our data exclude the presence of a quantum critical valence transition in YbRh2Si2.
A Type of Unifying Relation in (A)dS Spacetime
Creators: name: Tao, Yi-Xiao
name: Chen, Qi
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: Unifying relations of amplitudes are elegant results in flat spacetime, but the research on these in (A)dS case is not very rich. In this paper, we discuss a type of unifying relations in (A)dS by using Berends-Giele currents. By taking the flat limit, we also get a semi-on-shell way to prove the unifying relations in the flat case. We also discuss the applications of our results in cosmology.
description: typos fixed
Faithful (meta-)encodings of programmable strategies into term rewriting systems
Creators: name: Cirstea, Horatiu
name: Lenglet, Serguei
name: Moreau, Pierre-Etienne
Publisher: name: arXiv
Year: 2017
Subjects: subject: Programming Languages (cs.PL)
subject: FOS: Computer and information sciences
subject: F.4

description: Rewriting is a formalism widely used in computer science and mathematical logic. When using rewriting as a programming or modeling paradigm, the rewrite rules describe the transformations one wants to operate and rewriting strategies are used to con- trol their application. The operational semantics of these strategies are generally accepted and approaches for analyzing the termination of specific strategies have been studied. We propose in this paper a generic encoding of classic control and traversal strategies used in rewrite based languages such as Maude, Stratego and Tom into a plain term rewriting system. The encoding is proven sound and complete and, as a direct consequence, estab- lished termination methods used for term rewriting systems can be applied to analyze the termination of strategy controlled term rewriting systems. We show that the encoding of strategies into term rewriting systems can be easily adapted to handle many-sorted signa- tures and we use a meta-level representation of terms to reduce the size of the encodings. The corresponding implementation in Tom generates term rewriting systems compatible with the syntax of termination tools such as AProVE and TTT2, tools which turned out to be very effective in (dis)proving the termination of the generated term rewriting systems. The approach can also be seen as a generic strategy compiler which can be integrated into languages providing pattern matching primitives; experiments in Tom show that applying our encoding leads to performances comparable to the native Tom strategies.
Using Supervised Deep-Learning to Model Edge-FBG Shape Sensors
Creators: name: Roodsari, Samaneh Manavi
name: Huck-Horvath, Antal
name: Freund, Sara
name: Zam, Azhar
name: Rauter, Georg
name: Schade, Wolfgang
name: Cattin, Philippe C.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Robotics (cs.RO)
subject: FOS: Computer and information sciences

description: Continuum robots in robot-assisted minimally invasive surgeries provide adequate access to target anatomies that are not directly reachable through small incisions. Achieving precise and reliable motion control of such snake-like manipulators necessitates an accurate navigation system that requires no line-of-sight and is immune to electromagnetic noises. Fiber Bragg Grating (FBG) shape sensors, particularly edge-FBGs, are promising tools for this task. However, in edge-FBG sensors, the intensity ratio between Bragg wavelengths carries the strain information that can be affected by undesired bending-related phenomena, making standard characterization techniques less suitable for these sensors. We showed in our previous work that a deep learning model has the potential to extract the strain information from the full edge-FBG spectrum and accurately predict the sensor's shape. In this paper, we conduct a more thorough investigation to find a suitable architectural design with lower prediction errors. We use the Hyperband algorithm to search for optimal hyperparameters in two steps. First, we limit the search space to layer settings, where the best-performing configuration gets selected. Then, we modify the search space for tuning the training and loss calculation hyperparameters. We also analyze various data transformations on the input and output variables, as data rescaling can directly influence the model's performance. Moreover, we performed discriminative training using Siamese network architecture that employs two CNNs with identical parameters to learn similarity metrics between the spectra of similar target values. The best-performing network architecture among all evaluated configurations can predict the sensor's shape with a median tip error of 3.11 mm.
description: 27 pages, 12 figures, preprint
The universal quantum invariant and colored ideal triangulations
Creators: name: Suzuki, Sakie
Publisher: name: arXiv
Year: 2016
Subjects: subject: Geometric Topology (math.GT)
subject: Quantum Algebra (math.QA)
subject: FOS: Mathematics
subject: 57M27, 81R50, 16T25

description: The Drinfeld double of a finite dimensional Hopf algebra is a quasi-triangular Hopf algebra with the canonical element as the universal $R$-matrix, and one can obtain a ribbon Hopf algebra by adding the ribbon element. The universal quantum invariant of framed links is constructed using a ribbon Hopf algebra. In that construction, a copy of the universal $R$-matrix is attached to each crossing, and invariance under the Reidemeister III move is shown by the quantum Yang-Baxter equation of the universal $R$-matrix. On the other hand, the Heisenberg double of a finite dimensional Hopf algebra has the canonical element (the $S$-tensor) satisfying the pentagon relation. In this paper we reconstruct the universal quantum invariant using the Heisenberg double, and extend it to an invariant of equivalence classes of colored ideal triangulations of $3$-manifolds up to colored moves. In this construction, a copy of the $S$-tensor is attached to each tetrahedron, and invariance under the colored Pachner $(2,3)$ moves is shown by the pentagon relation of the $S$-tensor.
Self-calibrating optical galaxy cluster selection bias using cluster, galaxy, and shear cross-correlations
Creators: name: Zeng, Chenxiao
name: Salcedo, Andrés N.
name: Wu, Hao-Yi
name: Hirata, Christopher M.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: FOS: Physical sciences

description: The clustering signals of galaxy clusters are known to be powerful tools for self-calibrating the mass-observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions -- cluster lensing, the cluster-galaxy cross-correlation function, and the galaxy auto-correlation function -- to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying Halo Occupation Distribution (HOD) models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition to the previously known small-scale boost in projected correlation functions, we find that the projection effects also significantly boost 3D correlation functions out to scales 100 $h^{-1} \mathrm{Mpc}$. We perform a likelihood analysis assuming survey conditions similar to that of the Dark Energy Survey (DES) and show that the selection bias can be self-consistently constrained at the 10% level. We discuss strategies for applying this approach to real data. We expect that expanding the analysis to smaller scales and using deeper lensing data would further improve the constraints on cluster selection bias.
description: 12 pages, 10 figures; replaced to match published version
Majorana Spin Liquids, Topology and Superconductivity in Ladders
Creators: name: Hur, Karyn Le
name: Soret, Ariane
name: Yang, Fan
Publisher: name: arXiv
Year: 2017
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Superconductivity (cond-mat.supr-con)
subject: High Energy Physics - Theory (hep-th)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We theoretically address spin chain analogs of the Kitaev quantum spin model on the honeycomb lattice. The emergent quantum spin liquid phases or Anderson resonating valence bond (RVB) states can be understood, as an effective model, in terms of p-wave superconductivity and Majorana fermions. We derive a generalized phase diagram for the two-leg ladder system with tunable interaction strengths between chains allowing us to vary the shape of the lattice (from square to honeycomb ribbon or brickwall ladder). We evaluate the winding number associated with possible emergent (topological) gapless modes at the edges. In the Az phase, as a result of the emergent Z2 gauge fields and pi-flux ground state, one may build spin-1/2 (loop) qubit operators by analogy to the toric code. In addition, we show how the intermediate gapless B phase evolves in the generalized ladder model. For the brickwall ladder, the $B$ phase is reduced to one line, which is analyzed through perturbation theory in a rung tensor product states representation and bosonization. Finally, we show that doping with a few holes can result in the formation of hole pairs and leads to a mapping with the Su-Schrieffer-Heeger model in polyacetylene; a superconducting-insulating quantum phase transition for these hole pairs is accessible, as well as related topological properties.
description: 25 pages, 10 figures, final version - to be published in PRB
Further results on Hilbert's Tenth Problem
Creators: name: Sun, Zhi-Wei
Publisher: name: arXiv
Year: 2017
Subjects: subject: Number Theory (math.NT)
subject: Logic (math.LO)
subject: FOS: Mathematics
subject: 11U05, 03D35, 03D25, 11D99, 11A41, 11B39

description: Hilbert's Tenth Problem (HTP) asks for an algorithm to test whether an arbitrary polynomial Diophantine equation with integer coefficients has solutions over the ring $\mathbb Z$ of the integers. This was finally solved by Matiyasevich negatively in 1970. In this paper we obtain some further results on HTP over $\mathbb Z$. We prove that there is no algorithm to determine for any $P(z_1,\ldots,z_9)\in\mathbb Z[z_1,\ldots,z_9]$ whether the equation $P(z_1,\ldots,z_9)=0$ has integral solutions with $z_9\ge0$. Consequently, there is no algorithm to test whether an arbitrary polynomial Diophantine equation $P(z_1,\ldots,z_{11})=0$ (with integer coefficients) in 11 unknowns has integral solutions, which provides the best record on the original HTP over $\mathbb Z$. We also prove that there is no algorithm to test for any $P(z_1,\ldots,z_{17})\in\mathbb Z[z_1,\ldots,z_{17}]$ whether $P(z_1^2,\ldots,z_{17}^2)=0$ has integral solutions, and that there is a polynomial $Q(z_1,\ldots,z_{20})\in\mathbb Z[z_1,\ldots,z_{20}]$ such that $$\{Q(z_1^2,\ldots,z_{20}^2):\ z_1,\ldots,z_{20}\in\mathbb Z\}\cap\{0,1,2,\ldots\}$$ coincides with the set of all primes.
description: 32 pages, final version
Prescribed $Q$-curvature flow on closed manifolds of even dimension
Creators: name: Ngô, Quôc Anh
name: Zhang, Hong
Publisher: name: arXiv
Year: 2017
Subjects: subject: Analysis of PDEs (math.AP)
subject: Differential Geometry (math.DG)
subject: FOS: Mathematics
subject: 35J30, 53C44

description: On a closed Riemannian manifold $(M,g_0)$ of even dimension $n \geqslant 4$, the well-known prescribed $Q$-curvature problem asks whether or not there is a metric $g$ comformal to $g_0$ such that its $Q$-curvature, associated with the GJMS operator $\mathbf P_g$, is equal to a given function $f$. Letting $g = e^{2u}g_0$, this problem is equivalent to solving \[ \mathbf P_{g_0} u+Q_{g_0} = f e^{nu}, \] where $Q_{g_0}$ denotes the $Q$-curvature of $g_0$. The primary objective of the paper is to introduce the following negative gradient flow of the time dependent metric $g(t)$ conformal to $g_0$, \[ \frac{\partial g (t)}{\partial t}= -2\Big(Q_{g (t)} - \frac{\int_M f Q_{g(t)} dμ_{g(t)} }{\int_M f^2 dμ_{g(t)} }f \Big)g(t) \quad \text{ for } t >0, \] to study the problem of prescribing $Q$-curvature. Since $\int_M Q_g dμ_g$ is conformally invariant, our analysis depends on the size of $\int_M Q_{g_0} dμ_{g_0}$, which is assumed to satisfy \[ \int_M Q_0 dμ_{g_0} \ne k (n-1)! \, {\rm vol}(\mathbb S^n) \quad \text{ for all } \; k = 2,3,... \] The paper is twofold. First, we identify suitable conditions on $f$ such that the gradient flow defined as above is defined to all time and convergent, as time goes to infinity, sequentially or uniformly. Second, we show that various existence theorems for prescribed $Q$-curvature problem can be derived from the convergence of the flow.
description: 53 pages, 0 figure
Counting Black Holes: The Cosmic Stellar Remnant Population and Implications for LIGO
Creators: name: Elbert, Oliver D.
name: Bullock, James S.
name: Kaplinghat, Manoj
Publisher: name: arXiv
Year: 2017
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: We present an empirical approach for interpreting gravitational wave signals of binary black hole mergers under the assumption that the underlying black hole population is sourced by remnants of stellar evolution. Using the observed relationship between galaxy mass and stellar metallicity, we predict the black hole count as a function of galaxy stellar mass. We show, for example, that a galaxy like the Milky Way should host millions of $\sim 30~M_\odot$ black holes and dwarf satellite galaxies like Draco should host $\sim 100$ such remnants, with weak dependence on the assumed IMF and stellar evolution model. Most low-mass black holes ($\sim10 M_\odot$) typically reside within massive galaxies ($M_\star \simeq 10^{11} M_\odot$) while massive black holes ($\sim 50~M_\odot$) typically reside within dwarf galaxies ($M_\odot \simeq 10^9 M_\odot$) today. If roughly $1\%$ of black holes are involved in a binary black hole merger, then the reported merger rate densities from Advanced LIGO can be accommodated for a range of merger timescales, and the detection of mergers with $> 50~M_\odot$ black holes should be expected within the next decade. Identifying the host galaxy population of the mergers provides a way to constrain both the binary neutron star or black hole formation efficiencies and the merger timescale distributions; these events would be primarily localized in dwarf galaxies if the merger timescale is short compared to the age of the universe and in massive galaxies otherwise. As more mergers are detected, the prospect of identifying the host galaxy population, either directly through the detection of electromagnetic counterparts of binary neutron star mergers or indirectly through the anisotropy of the events, will become a realistic possibility.
description: 10 pages, 8 figures. Accepted by MNRAS
Presentation: Single Sign on Model Using SAML and OAuth for Online Application of UPNYK
Creators: name: Akbar, Ahmad Taufiq
name: Prapcoyo, Hari
name: Rifki Indra Perwira
Publisher: name: Zenodo
Year: 2022

description: This material has presented on 1st International Conference on Advanced Research in Engineering and Technology. October 25, 2022
Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria
Creators: name: Bender, Theresa
name: Beinecke, Jacqueline Michelle
name: Krefting, Dagmar
name: Müller, Carolin
name: Dathe, Henning
name: Seidler, Tim
name: Spicher, Nicolai
name: Hauschild, Anne-Christin
Publisher: name: arXiv
Year: 2022
Subjects: subject: Signal Processing (eess.SP)
subject: Machine Learning (cs.LG)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: Despite their remarkable performance, deep neural networks remain unadopted in clinical practice, which is considered to be partially due to their lack in explainability. In this work, we apply attribution methods to a pre-trained deep neural network (DNN) for 12-lead electrocardiography classification to open this "black box" and understand the relationship between model prediction and learned features. We classify data from a public data set and the attribution methods assign a "relevance score" to each sample of the classified signals. This allows analyzing what the network learned during training, for which we propose quantitative methods: average relevance scores over a) classes, b) leads, and c) average beats. The analyses of relevance scores for atrial fibrillation (AF) and left bundle branch block (LBBB) compared to healthy controls show that their mean values a) increase with higher classification probability and correspond to false classifications when around zero, and b) correspond to clinical recommendations regarding which lead to consider. Furthermore, c) visible P-waves and concordant T-waves result in clearly negative relevance scores in AF and LBBB classification, respectively. In summary, our analysis suggests that the DNN learned features similar to cardiology textbook knowledge.
description: Accepted version including new experiments on additional database
Maximal Coherence and the Resource Theory of Purity
Creators: name: Streltsov, Alexander
name: Kampermann, Hermann
name: Wölk, Sabine
name: Gessner, Manuel
name: Bruß, Dagmar
Publisher: name: arXiv
Year: 2016
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: The resource theory of quantum coherence studies the off-diagonal elements of a density matrix in a distinguished basis, whereas the resource theory of purity studies all deviations from the maximally mixed state. We establish a direct connection between the two resource theories, by identifying purity as the maximal coherence which is achievable by unitary operations. The states that saturate this maximum identify a universal family of maximally coherent mixed states. These states are optimal resources under maximally incoherent operations, and thus independent of the way coherence is quantified. For all distance-based coherence quantifiers the maximal coherence can be evaluated exactly, and is shown to coincide with the corresponding distance-based purity quantifier. We further show that purity bounds the maximal amount of entanglement and discord that can be generated by unitary operations, thus demonstrating that purity is the most elementary resource for quantum information processing.
description: 8+3 pages, 2 figures, published version
The Illusion of Randomness: An Empirical Analysis of Address Space Layout Randomization Implementations
Creators: name: Binosi, Lorenzo
name: Barzasi, Gregorio
name: Carminati, Michele
name: Zanero, Stefano
name: Polino, Mario
Publisher: name: arXiv
Year: 2024
Subjects: subject: Cryptography and Security (cs.CR)
subject: FOS: Computer and information sciences

description: Address Space Layout Randomization (ASLR) is a crucial defense mechanism employed by modern operating systems to mitigate exploitation by randomizing processes' memory layouts. However, the stark reality is that real-world implementations of ASLR are imperfect and subject to weaknesses that attackers can exploit. This work evaluates the effectiveness of ASLR on major desktop platforms, including Linux, MacOS, and Windows, by examining the variability in the placement of memory objects across various processes, threads, and system restarts. In particular, we collect samples of memory object locations, conduct statistical analyses to measure the randomness of these placements and examine the memory layout to find any patterns among objects that could decrease this randomness. The results show that while some systems, like Linux distributions, provide robust randomization, others, like Windows and MacOS, often fail to adequately randomize key areas like executable code and libraries. Moreover, we find a significant entropy reduction in the entropy of libraries after the Linux 5.18 version and identify correlation paths that an attacker could leverage to reduce exploitation complexity significantly. Ultimately, we rank the identified weaknesses based on severity and validate our entropy estimates with a proof-of-concept attack. In brief, this paper provides the first comprehensive evaluation of ASLR effectiveness across different operating systems and highlights opportunities for Operating System (OS) vendors to strengthen ASLR implementations.
description: Extended version of the accepted paper at ACM CCS 2024
Influence of the geometric configuration of accretion flow on the black hole spin dependence of relativistic acoustic geometry
Creators: name: Tarafdar, Pratik
name: Das, Tapas Kumar
Publisher: name: arXiv
Year: 2017
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: FOS: Physical sciences

description: Linear perturbation of general relativistic accretion of low angular momentum hydrodynamic fluid onto a Kerr black hole leads to the formation of curved acoustic geometry embedded within the background flow. Characteristic features of such sonic geometry depend on the black hole spin. Such dependence can be probed by studying the correlation of the acoustic surface gravity $κ$ with the Kerr parameter $a$. The $κ- a$ relationship further gets influenced by the geometric configuration of the accretion flow structure. In this work, such influence has been studied for multitransonic shocked accretion where linear perturbation of general relativistic flow profile leads to the formation of two analogue black hole type horizons formed at the sonic points and one analogue white hole type horizon which is formed at the shock location producing divergent acoustic surface gravity. Dependence of the $κ- a$ relationship on the geometric configuration has also been studied for monotransonic accretion, over the entire span of the Kerr parameter including retrograde flow. For accreting astrophysical black holes, the present work thus investigates how the salient features of the embedded relativistic sonic geometry may be determined not only by the background space-time, but also by the flow configuration of the embedding matter.
description: 13 pages, 8 figures
Cracking Double-Blind Review: Authorship Attribution with Deep Learning
Creators: name: Bauersfeld, Leonard
name: Romero, Angel
name: Muglikar, Manasi
name: Scaramuzza, Davide
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computation and Language (cs.CL)
subject: FOS: Computer and information sciences

description: Double-blind peer review is considered a pillar of academic research because it is perceived to ensure a fair, unbiased, and fact-centered scientific discussion. Yet, experienced researchers can often correctly guess from which research group an anonymous submission originates, biasing the peer-review process. In this work, we present a transformer-based, neural-network architecture that only uses the text content and the author names in the bibliography to attribute an anonymous manuscript to an author. To train and evaluate our method, we created the largest authorship identification dataset to date. It leverages all research papers publicly available on arXiv amounting to over 2 million manuscripts. In arXiv-subsets with up to 2,000 different authors, our method achieves an unprecedented authorship attribution accuracy, where up to 73% of papers are attributed correctly. We present a scaling analysis to highlight the applicability of the proposed method to even larger datasets when sufficient compute capabilities are more widely available to the academic community. Furthermore, we analyze the attribution accuracy in settings where the goal is to identify all authors of an anonymous manuscript. Thanks to our method, we are not only able to predict the author of an anonymous work, but we also provide empirical evidence of the key aspects that make a paper attributable. We have open-sourced the necessary tools to reproduce our experiments.
description: 13 pages + 3 pages references
Entanglement masquerading in the CMB
Creators: name: Adil, Arsalan
name: Albrecht, Andreas
name: Baunach, Rose
name: Holman, R.
name: Ribeiro, Raquel H.
name: Richard, Benoit J.
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: The simplest single-field inflation models capture all the relevant contributions to the patterns in the Cosmic Microwave Background (CMB) observed today. A key assumption in these models is that the quantum inflationary fluctuations that source such patterns are generated by a particular quantum state -- the Bunch-Davies (BD) state. While this is a well-motivated choice from a theoretical perspective, the question arises of whether current data can rule out other, also well motivated, choices of states. In particular, as we previously demonstrated in arXiv:2104.13410 [hep-th], entanglement is naturally and inevitably dynamically generated during inflation given the presence of a "rolling" spectator scalar field -- and the resulting entangled state will yield a primordial power spectrum with potentially measurable deviations compared to the canonical BD result. For this work we developed a perturbative framework to allow a systematic exploration of constraints on (or detection of) entangled states with Planck CMB data using Monte Carlo techniques. We have found that most entangled states accessible with our framework are consistent with the data. One would have to expand the framework to allow a greater variety of entangled states in order to saturate the Planck constraints and more systematically explore any preferences the data may have among the different possibilities.
description: 37 pages, 12 figures, 3 appendices. V2: Final version accepted for publication in JCAP. Changes: References added and minor clarifications to the presentation. Our results and conclusions are unchanged
El NUESTROS PRIMEROS EDUCADORES
Creators: name: Reyes Serrano, Paola Andrea
Publisher: name: Revista de Investigación Transdisciplinaria en Educación, Empresa y Sociedad - ITEES
Year: 2020

description: En este artículo habla de la crianza y el cuidado de los niños de 0 a 6 años de edad que es la primera infancia se revela que los primeros educadores de los niños son sus padres a veces participan los abuelos en la crianza de los niños pero no es lo mismo asumir la obligación de la crianza que brindar un apoyo y atención en momentos puntuales también se habla que actualmente se les deja toda la responsabilidades de los niños y niñas a los educadores, pero se pueden hacer reuniones o actividades para que los padres se integren más con sus propios hijos y tengas más confianza y así ellos se involucran un poco más en el desarrollo inicial de sus propios hijo .
description: Revista de Investigación Transdisciplinaria en Educación, Empresa y Sociedad - ITEES, Vol. 1 Núm. 1 (2020): Revista de Investigación Transdisciplinaria en Educación, Empresa y Sociedad – ITEES - La educación Infantil como eje de transformación social
II Quintetti Pour Deux Violons Deux Alto et Basse : Œuvre XXI
Creators: name: Mozart, Wolfgang Amadeus
Publisher: name: Chez Sieber Musicien rue honore entre celle des Vieilles Etuve et Dorleans No. 85
Year: 1800

description: Stimmen: Violino I & II, Viola I & II, Vlc. (Basso)
description: III. Instrumentalmusik. 5. Streichquintette
description: Composé Par M.W. Mozart
description: Enthält [Nr. 1] g-moll = Klavierquartett g-moll, KV 478, als Streichquintett bearbeitet, und [Nr. 2] C-Dur = Klavierquartett C-Dur, KV 515, als Streichquintett bearbeitet
description: ReKat Juli 2022 UBS/1.7.2022/A100/rpf
description: Handschriftl. beschriebener Umschlag mit Incipits
ENTORNOS DIGITALES EN LA EDUCACION INFANTIL
Creators: name: Posada Forero, Lizeth Daniela
name: Arenas Joya, Lizeth Daniela
name: Ortiz Rey, Angy Daniela
Publisher: name: Revista de Investigación Transdisciplinaria en Educación, Empresa y Sociedad - ITEES
Year: 2020

description: El presente artículo abordo la temática de entornos digitales en la educación infantil, teniendo en cuenta los puntos positivos o a favor que esta tiene. Dicho artículo se generó a partir de una investigación descriptiva, con un enfoque cualitativo y a su vez estableció o se basó en unos referentes conceptuales y teóricos, que ayudaron a la observación y análisis de los puntos positivos que tienen hoy en día los entornos digitales en la educación infantil
description: Revista de Investigación Transdisciplinaria en Educación, Empresa y Sociedad - ITEES, Vol. 1 Núm. 1 (2020): Revista de Investigación Transdisciplinaria en Educación, Empresa y Sociedad – ITEES - La educación Infantil como eje de transformación social
title: Recovery of critical infrastructure networks: A methodology to identify significant recovery factors for planning and decision making
Creators: name: Syed, Yasir Imtiaz
name: Uma, S.R.
Publisher: name: GNS Science
Year: 2023

description: Critical infrastructure (CI) networks, such as electricity, transportation, potable water, natural gas and telecommunications, are required to provide essential services for the community to recover after a disruptive event. However, these networks are generally vulnerable to hazard events that can cause severe damage resulting in loss of functionality and lack of services. The recovery process of CI networks becomes complex when considering interdependencies and it is a challenging task for CI network providers and relevant decision-makers to plan and execute. To help recovery processes, high-level recommendations are available as guidelines by government sectors. However, for the process to be effective and efficient for a given CI network provider, we have presented a methodology to identify the factors that significantly influence the recovery outcomes. Our research methodology is based on an effective knowledge elicitation process that enabled us to build a knowledge base to understand the requirements, possibilities and constraints specific to a CI network. The identified significant recovery factors are essential components in developing computational recovery models that are useful to simulate multiple recovery scenarios for assisting efficient recovery planning and decision making.
High-Q trampoline resonators from strained crystalline InGaP for integrated free-space optomechanics
Creators: name: Manjeshwar, Sushanth Kini
name: Ciers, Anastasiia
name: Hellman, Fia
name: Bläsing, Jürgen
name: Strittmater, André
name: Wieczorek, Witlef
Publisher: name: arXiv
Year: 2022
Subjects: subject: Applied Physics (physics.app-ph)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Optics (physics.optics)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Tensile-strained materials have been used to fabricate nano- and micromechanical resonators with ultra-low mechanical dissipation in the kHz to MHz frequency range. These mechanical resonators are of particular interest for force sensing applications and quantum optomechanics at room temperature. Tensile-strained crystalline materials that are compatible with epitaxial growth of heterostructures would thereby allow realizing monolithic free-space optomechanical devices, which benefit from stability, ultra-small mode volumes, and scalability. In our work, we demonstrate string- and trampoline resonators made from tensile-strained InGaP, which is a crystalline material that can be epitaxially grown on an AlGaAs heterostructure. The strain of the InGaP layer is defined via its Ga content when grown on (Al,Ga)As. In our case, we realize devices with a stress of up to 470\,MPa along the $[1\,1\,0]$ crystal direction. We characterize the mechanical properties of the suspended InGaP devices, such as anisotropic stress, yield strength, and intrinsic quality factor. We find that the latter degrades over time. We reach mechanical quality factors surpassing $10^7$ at room temperature with a $Q\cdot f$-product as high as $7\cdot10^{11}\,$Hz with trampoline-shaped micromechanical resonators, which exploit strain engineering to dilute mechanical dissipation. The large area of the suspended trampoline resonator allows us to pattern a photonic crystal to engineer its out-of-plane reflectivity in the telecom band, which is desired for efficient signal transduction of mechanical motion to light. Stabilization of the intrinsic quality factor together with a further reduction of mechanical dissipation through hierarchical clamping or machine learning-based optimization methods paves the way for integrated free-space quantum optomechanics at room temperature in a crystalline material platform.
description: close to published version, added paragraph about future improvements in Appendix; 16 pages incl. appendix, 13 figures
Evaluating the Predictive Features of Person-Centric Knowledge Graph Embeddings: Unfolding Ablation Studies
Creators: name: Theodoropoulos, Christos
name: Mulligan, Natasha
name: Bettencourt-Silva, Joao
Publisher: name: arXiv
Year: 2024
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Developing novel predictive models with complex biomedical information is challenging due to various idiosyncrasies related to heterogeneity, standardization or sparseness of the data. We previously introduced a person-centric ontology to organize information about individual patients, and a representation learning framework to extract person-centric knowledge graphs (PKGs) and to train Graph Neural Networks (GNNs). In this paper, we propose a systematic approach to examine the results of GNN models trained with both structured and unstructured information from the MIMIC-III dataset. Through ablation studies on different clinical, demographic, and social data, we show the robustness of this approach in identifying predictive features in PKGs for the task of readmission prediction.
description: Published in the 34th Medical Informatics Europe Conference
title: Journal of Preventive Medicine and Hygiene, Vol. 63 No. 3 (2022): 2022633
title: 2022633
titleType: AlternativeTitle
Creators: name: Journal Of Preventive Medicine And Hygiene
Publisher: name: Journal of Preventive Medicine and Hygiene
Year: 2022

description: First wave of COVID-19 pandemic in Madrid: handling the unexpected in a tertiary hospital...E375 Reorganization of Intensive Care Units for the COVID-19 pandemic: effects on nursing sensitive outcomes ...E383 Covid-19: yesterday, today and tomorrow. The quality of Covid-19 management and the evaluation of the “Health” chapter of the Recovery Plan....E391 Exploring the effectiveness of the Green Pass Law as Public Health instrument to increase anti-COVID-19 vaccination in a sample of working-age adult population in the Palermo Metropolitan Area....E399 Monitoring influenza vaccination coverage among healthcare workers during Covid-19 pandemic: a three-year survey in a large University Hospital in North-West Italy...E405 Prevalence of cervical, oral and anal Human papillomavirus (HPV) infection in women...E415 Indirect hyperbilirubinemia and jaundice during chronic hepatitis C in an HIV-infected patient treated with glecaprevir/pibrentasvir (GLE/PIB) and antiretroviral therapy (ART). The first reported case in Italy...E420 Prediction of Hepatitis Disease Using Ensemble Learning Methods...E424 Assessment of the knowledge, attitude, and practice related to visceral leishmaniasis among residents of Al-Suwaira city, Wasit Governorate, Middle East of Iraq...E429 Evaluation of the Effects of Diabetes Self-Management Education based on 5A Model on the Quality of Life and Blood Glucose of Women with Gestational Diabetes Mellitus...E442 Relationship between dietary energy intake, nutritional status and cardiovascular risk in adults from the communes of Quellón and Chonchi, Chiloé, Chile...E435 How do undergraduate nursing students learn about the fundamentals of care? A pilot cross-sectional attitudinal study ...E448 Probability of Non-compliance to the Consumption of Iron Tablets in Pregnant Women in Indonesia...E456 THE HISTORY OF VACCINOLOGY AND HYGIENE THROUGH ACHILLE SCLAVO AND THE CULTURAL PATRIMONY CONSERVED IN THE ARCHIVES AND MUSEUMS: THE KEY ROLE OF MEDICAL MUSEOLOGY ...E476 The mediating effects of barriers to vaccination on the relationship between race/ethnicity and influenza vaccination status in a rural Southeastern Louisiana medical center. ...E482 Analisi delle segnalazioni di Incident Reporting inappropriate per categoria professionale: dove insistere con la formazione .....E492 The management of healthcare-related infections through lean methodology: systematic review and meta-analysis of observational studies. ...E464
Tailoring Capture-Recapture Methods to Estimate Registry-Based Case Counts Based on Error-Prone Diagnostic Signals
Creators: name: Ge, Lin
name: Zhang, Yuzi
name: Ward, Kevin C.
name: Lash, Timothy L.
name: Waller, Lance A.
name: Lyles, Robert H.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Methodology (stat.ME)
subject: FOS: Computer and information sciences

description: Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database.
GPT-3-driven pedagogical agents for training children's curious question-asking skills
Creators: name: Abdelghani, Rania
name: Wang, Yen-Hsiang
name: Yuan, Xingdi
name: Wang, Tong
name: Lucas, Pauline
name: Sauzéon, Hélène
name: Oudeyer, Pierre-Yves
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computation and Language (cs.CL)
subject: Human-Computer Interaction (cs.HC)
subject: FOS: Computer and information sciences

description: In order to train children's ability to ask curiosity-driven questions, previous research has explored designing specific exercises relying on providing semantic and linguistic cues to help formulate such questions. But despite showing pedagogical efficiency, this method is still limited as it relies on generating the said cues by hand, which can be a very costly process. In this context, we propose to leverage advances in the natural language processing field (NLP) and investigate the efficiency of using a large language model (LLM) for automating the production of the pedagogical content of a curious question-asking (QA) training. We study generating the said content using the "prompt-based" method that consists of explaining the task to the LLM in natural text. We evaluate the output using human experts annotations and comparisons with hand-generated content. Results suggested indeed the relevance and usefulness of this content. We also conduct a field study in primary school (75 children aged 9-10), where we evaluate children's QA performance when having this training. We compare 3 types of content : 1) hand-generated content that proposes "closed" cues leading to predefined questions; 2) GPT-3-generated content that proposes the same type of cues; 3) GPT-3-generated content that proposes "open" cues leading to several possible questions. We see a similar QA performance between the two "closed" trainings (showing the scalability of the approach using GPT-3), and a better one for participants with the "open" training. These results suggest the efficiency of using LLMs to support children in generating more curious questions, using a natural language prompting approach that affords usability by teachers and other users not specialists of AI techniques. Furthermore, results also show that open-ended content may be more suitable for training curious question-asking skills.
DART: Noise Injection for Robust Imitation Learning
Creators: name: Laskey, Michael
name: Lee, Jonathan
name: Fox, Roy
name: Dragan, Anca
name: Goldberg, Ken
Publisher: name: arXiv
Year: 2017
Subjects: subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: One approach to Imitation Learning is Behavior Cloning, in which a robot observes a supervisor and infers a control policy. A known problem with this "off-policy" approach is that the robot's errors compound when drifting away from the supervisor's demonstrations. On-policy, techniques alleviate this by iteratively collecting corrective actions for the current robot policy. However, these techniques can be tedious for human supervisors, add significant computation burden, and may visit dangerous states during training. We propose an off-policy approach that injects noise into the supervisor's policy while demonstrating. This forces the supervisor to demonstrate how to recover from errors. We propose a new algorithm, DART (Disturbances for Augmenting Robot Trajectories), that collects demonstrations with injected noise, and optimizes the noise level to approximate the error of the robot's trained policy during data collection. We compare DART with DAgger and Behavior Cloning in two domains: in simulation with an algorithmic supervisor on the MuJoCo tasks (Walker, Humanoid, Hopper, Half-Cheetah) and in physical experiments with human supervisors training a Toyota HSR robot to perform grasping in clutter. For high dimensional tasks like Humanoid, DART can be up to $3x$ faster in computation time and only decreases the supervisor's cumulative reward by $5\%$ during training, whereas DAgger executes policies that have $80\%$ less cumulative reward than the supervisor. On the grasping in clutter task, DART obtains on average a $62\%$ performance increase over Behavior Cloning.