cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
PUBH992_Final Group Paper_16Apr2020
Creators: name: Li, Hong
name: Polaskey, Kathryn
name: Fulbright, Elizabeth
name: Lyall, Taylor
name: Dove, Justice Arielle
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2020

description: Social determinants of health (SDoH) are structural and social factors that affect an individual's health. These factors could include but are not limited to housing insecurity, food insecurity, transportation, and interpersonal safety/toxic stress. Furthermore, the interesting and colorful aspect about SDoH is that all of the SDoH factors are interconnected. Successfully addressing SDoH not only helps public health leaders look at public health issues from an upstream and broader perspective but can also help decrease health inequities and disparities. Hence, in order to effectively address public health issues in Robeson County, we must look at their unmet needs with an SDoH lens.
The housing system in Lumberton, North Carolina is a system that impacts low-income families due to inability to pay rent, paying more than 30% of income on rent, constant moving, poor living conditions, and homelessness. This social determinant of health impacts the physical and mental well-being of these families through low-quality, unstable living conditions and chronic and toxic stress to afford rent.
We are proposing the formation of Lumberton Cares, an accountable care community (ACC) created to advocate for these families and create solutions to reduce the cost burden in the community. The Housing Authority of the City of Lumberton (HACL) is working together with key partnering organizations to achieve this goal. Our key partners include local policy makers, the NC Landlords Association, the NC Council of Churches, Smithfield Foods Company, and State Farm Insurance Agency. The ACC will incorporate the feedback from various community stakeholders to assess needs and assets within the community in relation to the housing system. We will coordinate and facilitate partners’ continuous collaboration to advance policy and support aligned activities to reach our shared vision.
The ACC proposes developing activities for policy advocacy, policy development, and policy adoption in the community. These activities will be based upon a thorough assessment of stakeholders and resources in the community to ensure our initiatives align with the needs of the community. The organization will also rely on the key partners to form an effective coalition towards a common goal. Stakeholder engagement will be key to the success of our organization as we strive to reduce the burden of housing insecurity in the Lumberton community.
 
Keywords: proposal, Robeson County, North Carolina, Lumberton, housing, housing insecurity, affordable, community, low-income families, poverty, stability, stakeholders, ACC, policy, health, disparities, social determinants of health
Deep learning reconstruction of the large scale structure of the Universe from luminosity distance observations
Creators: name: García, Cristhian
name: Santa, Camilo
name: Romano, Antonio Enea
Publisher: name: arXiv
Year: 2021
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: Astrophysics of Galaxies (astro-ph.GA)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: Supernovae Ia (SNe) can provide a unique window on the large scale structure (LSS) of the Universe at redshifts where few other observations are available, by solving the inversion problem (IP) consisting in reconstructing the LSS from its effects on the observed luminosity distance. So far the IP was solved assuming some restrictions about space-time, such as spherical symmetry for example, while we obtain for the first time solutions of the IP problem for arbitrary space-time geometries using deep learning. The method is based on the use of convolutional neural networks (CNN) trained on simulated data. The training data set is obtained by first generating random density and velocity fields, and then computing their effects on the luminosity distance. The CNN, based on an appriately modified version of U-Net to account for the tridimensionality of the data, is then trained to reconstruct the density and velocity fields from the luminosity distance. We find that the velocity field inversion is more accurate than the density field, because the effects of the velocity on the luminosity distance only depend on the source velocity, while in the case of the density it is an integrated effect along the line of sight, giving rise to more degeneracy in the solution of the IP. Improved versions of these neural networks, modified to accommodate the non uniform distribution of the SNe, can be applied to observational data to reconstruct the large scale structure of the Universe at redshifts at which few other observations are available.
description: Version Accepted by MNRAS
Distribution of ripples in graphene membrane
Creators: name: Yu, Jin
name: Katsnelson, Mikhail I.
name: Yuan, Shengjun
Publisher: name: arXiv
Year: 2021
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: Intrinsic ripples with various configurations and sizes were reported to affect the physical and chemical properties of 2D materials. By performing molecular dynamics simulations and theoretical analysis, we use two geometric models of the ripple shape to explore numerically the distribution of ripples in graphene membrane. We focus on the ratio of ripple height to its diameter (t/D) which was recently shown to be the most relevant for chemical activity of graphene membranes. Our result demonstrates that the ripple density decreases as the coefficient t/D increases, in a qualitative agreement with the Boltzmann distribution derived analytically from the bending energy of the membrane. Our theoretical study provides also specific quantitative information on the ripple distribution in graphene and gives new insights applicable to other 2D materials.
Willingness and Ability of Older Adults in the Emergency Department to Provide Clinical Information Using a Tablet Computer
Creators: name: Braz, Valerie A.
name: Platts-Mills, Timothy F.
name: Brahmandam, Sruti
name: Mangipudi, Sowmya A.
name: Holland, Wesley C.
name: Hunold, Katherine M.
name: Medlin, Richard P.
name: Jones, Christopher W.
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2016

description: To estimate the proportion of older adults in the emergency department (ED) who are willing and able to use a tablet computer to answer questions.
Wide and Deep Graph Neural Network with Distributed Online Learning
Creators: name: Gao, Zhan
name: Gama, Fernando
name: Ribeiro, Alejandro
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Signal Processing (eess.SP)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Graph neural networks (GNNs) are naturally distributed architectures for learning representations from network data. This renders them suitable candidates for decentralized tasks. In these scenarios, the underlying graph often changes with time due to link failures or topology variations, creating a mismatch between the graphs on which GNNs were trained and the ones on which they are tested. Online learning can be leveraged to retrain GNNs at testing time to overcome this issue. However, most online algorithms are centralized and usually offer guarantees only on convex problems, which GNNs rarely lead to. This paper develops the Wide and Deep GNN (WD-GNN), a novel architecture that can be updated with distributed online learning mechanisms. The WD-GNN consists of two components: the wide part is a linear graph filter and the deep part is a nonlinear GNN. At training time, the joint wide and deep architecture learns nonlinear representations from data. At testing time, the wide, linear part is retrained, while the deep, nonlinear one remains fixed. This often leads to a convex formulation. We further propose a distributed online learning algorithm that can be implemented in a decentralized setting. We also show the stability of the WD-GNN to changes of the underlying graph and analyze the convergence of the proposed online learning procedure. Experiments on movie recommendation, source localization and robot swarm control corroborate theoretical findings and show the potential of the WD-GNN for distributed online learning.
description: arXiv admin note: text overlap with arXiv:2006.06376
Rational points on fibrations with few non-split fibres
Creators: name: Harpaz, Yonatan
name: Wei, Dasheng
name: Wittenberg, Olivier
Publisher: name: arXiv
Year: 2021
Subjects: subject: Number Theory (math.NT)
subject: Algebraic Geometry (math.AG)
subject: FOS: Mathematics

description: We revisit the abstract framework underlying the fibration method for producing rational points on the total space of fibrations over the projective line. By fine-tuning its dependence on external arithmetic conjectures, we render the method unconditional when the degree of the non-split locus is $\leq 2$, as well as in various instances where it is $3$. We are also able to obtain improved results in the regime that is conditionally accessible under Schinzel's hypothesis, by incorporating into it, for the first time, a technique due to Harari for controlling the Brauer--Manin obstruction in families.
description: 46 pages; v2: exposition improved
On the rapidity dependence of the average transverse momentum in hadronic collisions
Creators: name: Durães, F. O.
name: Giannini, A. V.
name: Goncalves, V. P.
name: Navarra, F. S.
Publisher: name: arXiv
Year: 2015
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Experiment (hep-ex)
subject: Nuclear Experiment (nucl-ex)
subject: Nuclear Theory (nucl-th)
subject: FOS: Physical sciences

description: The energy and rapidity dependence of the average transverse momentum $\langle p_T \rangle$ in $pp$ and $pA$ collisions at RHIC and LHC energies are estimated using the Colour Glass Condensate (CGC) formalism. We update previous predictions for the $p_T$ - spectra using the hybrid formalism of the CGC approach and two phenomenological models for the dipole - target scattering amplitude. We demonstrate that these models are able to describe the RHIC and LHC data for the hadron production in $pp$, $dAu$ and $pPb$ collisions at $p_T \le 20$ GeV. Moreover, we present our predictions for $\langle p_T \rangle$ and demonstrate that the ratio $\langle p_{T}(y)\rangle / \langle p_{T}(y = 0)\rangle$ decreases with the rapidity and has a behaviour similar to that predicted by hydrodynamical calculations.
description: 11 pages, 7 figures; revised version: new results for the average transverse momentum at partonic level added in fig. 4; Results and Discussion section has been improved and enlarged
Helical Liquids in Semiconductors
Creators: name: Hsu, Chen-Hsuan
name: Stano, Peter
name: Klinovaja, Jelena
name: Loss, Daniel
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: One-dimensional helical liquids can appear at boundaries of certain condensed matter systems. Two prime examples are the edge of a quantum spin Hall insulator and the hinge of a three-dimensional second-order topological insulator. For these materials, the presence of a helical state at the boundary serves as a signature of their nontrivial electronic bulk topology. Additionally, these boundary states are of interest themselves, as a novel class of strongly correlated low-dimensional systems with interesting potential applications. Here, we review existing results on such helical liquids in semiconductors. Our focus is on the theory, though we confront it with existing experiments. We discuss various aspects of the helical liquids, such as their realization, topological protection and stability, or possible experimental characterization. We lay emphasis on the hallmark of these states, being the prediction of a quantized electrical conductance. Since so far reaching a well-quantized conductance has remained challenging experimentally, a large part of the review is a discussion of various backscattering mechanisms which have been invoked to explain this discrepancy. Finally, we include topics related to proximity-induced topological superconductivity in helical states, as an exciting application towards topological quantum computation with the resulting Majorana bound states.
description: 47 pages, 19 figures, revised version accepted for publication at https://doi.org/10.1088/1361-6641/ac2c27
Assessment of Dentally Related Function in Individuals with Cognitive Impairment: The Dental Activities Test
Creators: name: Zimmerman, Sheryl
name: Sloane, Philip D.
name: Reed, David
name: Potter, Guy G.
name: Chen, Xi
name: Cohen, Lauren W.
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2017

description: To develop and validate the Dental Activities Test (DAT), a clinical tool for measuring dentally-related function in cognitively-impaired older adults.
Learning Robot Structure and Motion Embeddings using Graph Neural Networks
Creators: name: Kim, J. Taery
name: Park, Jeongeun
name: Choi, Sungjoon
name: Ha, Sehoon
Publisher: name: arXiv
Year: 2021
Subjects: subject: Robotics (cs.RO)
subject: FOS: Computer and information sciences

description: We propose a learning framework to find the representation of a robot's kinematic structure and motion embedding spaces using graph neural networks (GNN). Finding a compact and low-dimensional embedding space for complex phenomena is a key for understanding its behaviors, which may lead to a better learning performance, as we observed in other domains of images or languages. However, although numerous robotics applications deal with various types of data, the embedding of the generated data has been relatively less studied by roboticists. To this end, our work aims to learn embeddings for two types of robotic data: the robot's design structure, such as links, joints, and their relationships, and the motion data, such as kinematic joint positions. Our method exploits the tree structure of the robot to train appropriate embeddings to the given robot data. To avoid overfitting, we formulate multi-task learning to find a general representation of the embedding spaces. We evaluate the proposed learning method on a robot with a simple linear structure and visualize the learned embeddings using t-SNE. We also study a few design choices of the learning framework, such as network architectures and message passing schemes.
description: 7 pages, 9 figures
The Far Ultraviolet Background
Creators: name: Kulkarni, S. R.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: The diffuse far-ultraviolet (FUV) background has received considerable attention from astronomers since the 1970's. The initial impetus came from the hope of detecting UV radiation from the hot intergalactic medium. The central importance of the FUV background to the physics (heating and ionization) of the diffuse atomic phases motivated the next generation of experiments. The consensus view is that the diffuse FUV emission at high latitudes has three components: stellar FUV reflected by dust grains (diffuse Galactic light or DGL), FUV from other galaxies and the intergalactic medium (extra-galactic background light or EBL) and a component of unknown origin (and referred to as the "offset" component). During the1980's, there was some discussion that decaying dark matter particles produced FUV radiation. In this paper I investigate production of FUV photons by conventional sources: line emission from Galactic Hot Ionized Medium, two-photon emission from the Galactic Warm Ionized Medium and low-velocity shocks, and Lyman-beta fluorescence of hydrogen at several locales in the Solar System (the interplanetary medium, the exosphere and the thermosphere of Earth). I conclude that two thirds and arguably all of the offset component can be explained by the sum of the radiation from the processes listed above.
description: Accepted by PASP (20 April 2022). Twenty one pages, 16 Figures and 3 Tables
Emergent new symmetry from the Higgs shadow
Creators: name: Abdallah, Waleed
name: Barik, Anjan Kumar
name: Rai, Santosh Kumar
name: Samui, Tousik
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: We show in this Letter how a new hidden gauge symmetry responsible for neutrino mass as well as dark matter (DM) in the Universe can be discovered through scalar mediators responsible for breaking the new symmetry. The new force mediator ($Z'$) may be lighter than the Standard Model (SM) gauge bosons but cannot be observed in traditional searches for new gauge bosons. We highlight a novel way of discovering such a symmetry at the Large Hadron Collider (LHC) by incorporating an existing ATLAS analysis on four lepton final states which include the Higgs resonance. In addition, we show that the hidden sector also introduces flavor violation in the lepton sector which can become a significant channel of discovery for the new force.
description: 8 pages, 4 figures, 4 tables
Diagnosis of Elder Abuse in U.S. Emergency Departments
Creators: name: Hunold, Katherine M.
name: Platts-Mills, Timothy F.
name: Rosen, Tony
name: Evans, Christopher S.
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2017

description: To estimate the proportion of visits to United States emergency departments (EDs) receiving a diagnosis of elder abuse using two nationally representative datasets.
Narrow optical transitions in erbium-implanted silicon waveguides
Creators: name: Gritsch, Andreas
name: Weiss, Lorenz
name: Früh, Johannes
name: Rinner, Stephan
name: Reiserer, Andreas
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: Other Condensed Matter (cond-mat.other)
subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: The realization of a scalable architecture for quantum information processing is a major challenge for quantum science. A promising approach is based on emitters in nanostructures that are coupled by light. Here, we show that erbium dopants can be reproducibly integrated at well-defined lattice sites by implantation into pure silicon. We thus achieve a narrow inhomogeneous broadening, less than 1 GHz, strong optical transitions, and an outstanding optical coherence even at temperatures of 8 K, with an upper bound to the homogeneous linewidth of around 10 kHz. Our study thus introduces a promising materials platform for the implementation of on-chip quantum memories, microwave-to-optical conversion, and distributed quantum information processing.
A Dynamic Programming Algorithm for Finding an Optimal Sequence of Informative Measurements
Creators: name: Loxley, Peter N.
name: Cheung, Ka-Wai
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: Robotics (cs.RO)
subject: Optimization and Control (math.OC)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics

description: An informative measurement is the most efficient way to gain information about an unknown state. We present a first-principles derivation of a general-purpose dynamic programming algorithm that returns an optimal sequence of informative measurements by sequentially maximizing the entropy of possible measurement outcomes. This algorithm can be used by an autonomous agent or robot to decide where best to measure next, planning a path corresponding to an optimal sequence of informative measurements. The algorithm is applicable to states and controls that are either continuous or discrete, and agent dynamics that is either stochastic or deterministic; including Markov decision processes and Gaussian processes. Recent results from the fields of approximate dynamic programming and reinforcement learning, including on-line approximations such as rollout and Monte Carlo tree search, allow the measurement task to be solved in real time. The resulting solutions include non-myopic paths and measurement sequences that can generally outperform, sometimes substantially, commonly used greedy approaches. This is demonstrated for a global search task, where on-line planning for a sequence of local searches is found to reduce the number of measurements in the search by approximately half. A variant of the algorithm is derived for Gaussian processes for active sensing.
The zeros of the partition function of the pinning model
Creators: name: Giacomin, Giambattista
name: Greenblatt, Rafael L.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mathematical Physics (math-ph)
subject: Probability (math.PR)
subject: FOS: Physical sciences
subject: FOS: Mathematics
subject: 82B27, 30C15, 31B05, 60E10, 82B44, 60K35

description: We aim at understanding for which (complex) values of the potential the pinning partition function vanishes. The pinning model is a Gibbs measure based on discrete renewal processes with power law inter-arrival distributions. We obtain some results for rather general inter-arrival laws, but we achieve a substantially more complete understanding for a specific one parameter family of inter-arrivals. We show, for such a specific family, that the zeros asymptotically lie on (and densely fill) a closed curve that, unsurprisingly, touches the real axis only in one point (the critical point of the model). We also perform a sharper analysis of the zeros close to the critical point and we exploit this analysis to approach the challenging problem of Griffiths singularities for the disordered pinning model. The techniques we exploit are both probabilistic and analytical. Regarding the first, a central role is played by limit theorems for heavy tail random variables. As for the second, potential theory and singularity analysis of generating functions, along with their interplay, will be at the heart of several of our arguments.
description: 42 pages, 6 figures. Accepted for publication on "Mathematical Physics, Analysis and Geometry"
Measurement of Bell-type inequalities and quantum entanglement from $Λ$-hyperon spin correlations at high energy colliders
Creators: name: Gong, Wenjie
name: Parida, Ganesh
name: Tu, Zhoudunming
name: Venugopalan, Raju
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: Nuclear Experiment (nucl-ex)
subject: Nuclear Theory (nucl-th)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Spin correlations of $Λ$-hyperons embedded in the QCD strings formed in high energy collider experiments provide unique insight into their locality and entanglement features. We show from general considerations that while the Clauser-Horne-Shimony-Holt inequality is less stringent for such states, they provide a benchmark for quantum-to-classical transitions induced by varying i) the associated hadron multiplicity, ii) the spin of nucleons, iii) the separation in rapidity between pairs, and iv) the kinematic regimes accessed. These studies also enable the extraction of quantitative measures of quantum entanglement. We first explore such questions within a simple model of a QCD string composed of singlets of two partial distinguishable fermion flavors and compare analytical results to those obtained on quantum hardware. We further discuss a class of spin Hamiltonians that model the dynamics of $Λ$ spin correlations. Prospects for extracting quantum features of QCD strings from hyperon measurements at current and future colliders are outlined.
description: Final version accepted by PRD Letter
Genetics of murine craniofacial morphology: diallel analysis of the eight founders of the Collaborative Cross
Creators: name: Percival, Christopher J.
name: Spritz, Richard
name: Pardo-Manuel de Villena, Fernando
name: Marcucio, Ralph
name: Liberton, Denise K.
name: Hallgrímsson, Benedikt
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2016

description: Using eight inbred founder strains of the mouse Collaborative Cross (CC) project and their reciprocal F1 hybrids, we quantified variation in craniofacial morphology across mouse strains, explored genetic contributions to craniofacial variation that distinguish the founder strains, and tested whether specific or summary measures of craniofacial shape display stronger additive genetic contributions. This study thus provides critical information about phenotypic diversity among CC founder strains and about the genetic contributions to this phenotypic diversity, which is relevant to understanding the basis of variation in standard laboratory strains and natural populations. Craniofacial shape was quantified as a series of size-adjusted linear dimensions (RDs) and by principal components (PC) analysis of morphological landmarks captured from computed tomography images from 62 out of the 64 reciprocal crosses of the CC founder strains. We first identified aspects of skull morphology that vary between these phenotypically ‘normal’ founder strains and that are defining characteristics of these strains. We estimated the contributions of additive and various non-additive genetic factors to phenotypic variation using diallel analyses of a subset of these strongly differing RDs and the first 8 PCs of skull shape variation. We find little difference in the genetic contributions to RD measures and PC scores, suggesting fundamental similarities in the magnitude of genetic contributions to both specific and summary measures of craniofacial phenotypes. Our results indicate that there are stronger additive genetic effects associated with defining phenotypic characteristics of specific founder strains, suggesting these distinguishing measures are good candidates for use in genotype-phenotype association studies of CC mice. Our results add significantly to understanding of genotype-phenotype associations in the skull, which serve as a foundation for modeling the origins of medically and evolutionarily relevant variation.
title: Building capacity and self-efficacy in teaching Scripture to early years learners
Creators: name: Nolen, Elizabeth
Publisher: name: University of Southern Queensland
Year: 2023
Subjects: classificationCode: 390302
subject: Early childhood education
classificationCode: 390307
subject: Teacher education and professional development of educators

description: This thesis reports on a major and minor study involving a team of religious education leaders and teachers of preparatory to year three learners from Catholic schools in southeast Queensland. This inquiry used the approach of design-based research to collaboratively work with practitioners to discover what learning environments support the meaningful teaching of Scripture to young children. This inquiry also explored factors, processes, and strategies that enabled professional learning about Scripture with the goal to transform professional practice. Both teams met multiple times over a year to investigate needs and design interventions for teachers to trial and provide feedback for analysis and explore the research questions. Thematic analysis supported the identification of key themes and findings from the data, with multiple insights discovered. Two precursors emerged of teachers needing to achieve readiness to teach the text and build skills for informed pedagogical decision-making before teaching Scripture. Twelve pedagogies and seven teacher capacities emerged to create meaningful Scripture learning environments. The data also revealed that teachers value professional learning that responds to three core needs, as well as identifying that building social capital, creating a strong culture for learning and embedding effective monitoring practices all significantly contribute to enabling professional learning to transform practice. Due to the limited research in this area, the findings have relevance for all early years teachers and religious education leaders in Catholic schools, universities, or education systems who seek to build capacity for the meaningful teaching of Scripture to early years learners and the broader application of these insights. This research resulted in the construction of several seminal models and frameworks for others working in similar contexts. The major contribution is a multi-layered framework constructed from theory and practice insights, for building capacity to teach Scripture.
Observation of universal strong orbital-dependent correlation effects in iron chalcogenides
Creators: name: Yi, Ming
name: Liu, Zhongkai
name: Zhang, Yan
name: Yu, Rong
name: Zhu, Jianxin
name: Lee, James
name: Moore, Rob
name: Schmitt, Felix
name: Li, Wei
name: Riggs, Scott
name: Chu, Jiun-Haw
name: Lv, Bing
name: Hu, Jin
name: Hashimoto, Makoto
name: Mo, Sung-Kwan
name: Hussain, Zahid
name: Mao, Zhiqiang
name: Chu, Ching-Wu
name: Fisher, Ian
name: Si, Qimiao
name: Shen, Zhi-Xun
name: Lu, Donghui
Publisher: name: arXiv
Year: 2015
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: FOS: Physical sciences

description: Establishing the appropriate theoretical framework for unconventional superconductivity in the iron-based materials requires correct understanding of both the electron correlation strength and the role of Fermi surfaces. This fundamental issue becomes especially relevant with the discovery of the iron chalcogenide (FeCh) superconductors, the only iron-based family in proximity to an insulating phase. Here, we use angle-resolved photoemission spectroscopy (ARPES) to measure three representative FeCh superconductors, FeTe0.56Se0.44, K0.76Fe1.72Se2, and monolayer FeSe film grown on SrTiO3. We show that, these FeChs are all in a strongly correlated regime at low temperatures, with an orbital-selective strong renormalization in the dxy bands despite having drastically different Fermi-surface topologies. Furthermore, raising temperature brings all three compounds from a metallic superconducting state to a phase where the dxy orbital loses all spectral weight while other orbitals remain itinerant. These observations establish that FeChs display universal orbital-selective strong correlation behaviors that are insensitive to the Fermi surface topology, and are close to an orbital-selective Mott phase (OSMP), hence placing strong constraints for theoretical understanding of iron-based superconductors.
description: published version
A minimal phase-coupling model for intermittency in turbulent systems
Creators: name: Arguedas-Leiva, José-Agustín
name: Carroll, Enda
name: Biferale, Luca
name: Wilczek, Michael
name: Bustamante, Miguel D.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Fluid Dynamics (physics.flu-dyn)
subject: Chaotic Dynamics (nlin.CD)
subject: FOS: Physical sciences

description: Turbulent systems exhibit a remarkable multi-scale complexity, in which spatial structures induce scale-dependent statistics with strong departures from Gaussianity. In Fourier space, this is reflected by pronounced phase synchronization. A quantitative relation between real-space structure, statistics, and phase synchronization is currently missing. Here, we address this problem in the framework of a minimal phase-coupling model, which enables a detailed investigation by means of dynamical systems theory and multi-scale high-resolution simulations. We identify the spectral power-law steepness, which controls the phase coupling, as the control parameter for tuning the non-Gaussian properties of the system. Whereas both very steep and very shallow spectra exhibit close-to-Gaussian statistics, the strongest departures are observed for intermediate slopes comparable to the ones in hydrodynamic and Burgers turbulence. We show that the non-Gaussian regime of the model coincides with a collapse of the dynamical system to a lower-dimensional attractor and the emergence of phase synchronization, thereby establishing a dynamical-systems perspective on turbulent intermittency.
description: 6 pages, 3 figures. Main changes: Improved introduction and model discussion to emphasize the deterministic system that supports a turbulent attractor. Improved figures and text to introduce a time-dependent order parameter
Coronilla vaginalis Lam., Encycl.
Creators: name: Peruzzi, Lorenzo
name: Galasso, Gabriele
name: Domina, Gianniantonio
name: Bartolucci, Fabrizio
name: Santangelo, Annalisa
name: Alessandrini, Alessandro
name: Astuti, Giovanni
name: D'Antraccoli, Marco
name: Roma-Marzio, Francesco
name: Ardenghi, Nicola M. G.
name: Barberis, Giuseppina
name: Conti, Fabio
name: Bernardo, Liliana
name: Peccenini, Simonetta
name: Stinca, Adriano
name: Wagensommer, Robert P.
name: Bonari, Gianmaria
name: Iamonico, Duilio
name: Iberite, Mauro
name: Viciani, Daniele
name: Guacchio, Emanuele Del
name: Galdo, Gianpietro Giusso Del
name: Lastrucci, Lorenzo
name: Villani, Mariacristina
name: Brunu, Antonello
name: Magrini, Sara
name: Pistarino, Annalaura
name: Brullo, Salvatore
name: Salmeri, Cristina
Publisher: name: Zenodo
Year: 2019
Subjects: Biodiversity
Taxonomy
Plantae
Tracheophyta
Magnoliopsida
Fabales
Fabaceae
Coronilla
Coronilla vaginalis

description: Coronilla vaginalis Lam., Encycl. 2(1): 121. 1786. [16 October 1786]
 Ind. Loc.:—“observée dans l’Italie”. ITA
 Type:—Not designated.
 Compiled by:— R. Di Pietro
description: Published as part of Peruzzi, Lorenzo, Galasso, Gabriele, Domina, Gianniantonio, Bartolucci, Fabrizio, Santangelo, Annalisa, Alessandrini, Alessandro, Astuti, Giovanni, D'Antraccoli, Marco, Roma-Marzio, Francesco, Ardenghi, Nicola M. G., Barberis, Giuseppina, Conti, Fabio, Bernardo, Liliana, Peccenini, Simonetta, Stinca, Adriano, Wagensommer, Robert P., Bonari, Gianmaria, Iamonico, Duilio, Iberite, Mauro, Viciani, Daniele, Guacchio, Emanuele Del, Galdo, Gianpietro Giusso Del, Lastrucci, Lorenzo, Villani, Mariacristina, Brunu, Antonello, Magrini, Sara, Pistarino, Annalaura, Brullo, Salvatore & Salmeri, Cristina, 2019, An inventory of the names of native, non-endemic vascular plants described from Italy, their loci classici and types, pp. 1-215 in Phytotaxa 410 (1) on page 50, DOI: 10.11646/phytotaxa.410.1.1, http://zenodo.org/record/13716045
Thickness Dependent OER Electrocatalysis of Epitaxial LaFeO$_{3}$ Thin Films
Creators: name: Burton, Andricus R.
name: Paudel, Rajendra
name: Matthews, Bethany
name: Sassi, Michel
name: Spurgeon, Steven R.
name: Farnum, Byron H.
name: Comes, Ryan B.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: Transition metal oxides have long been an area of interest for water electrocatalysis through the oxygen evolution and oxygen reduction reactions. Iron oxides, such as LaFeO$_{3}$, are particularly promising due to the favorable energy alignment of the valence and conduction bands comprised of Fe$^{3+}$ cations and the visible light band gap of such materials. In this work, we examine the role of band alignment on the electrocatalytic oxygen evolution reaction (OER) in the intrinsic semiconductor LaFeO$_{3}$ by growing epitaxial films of varying thicknesses on Nb-doped SrTiO$_{3}$. Using cyclic voltammetry and electrochemical impedance spectroscopy, we find that there is a strong thickness dependence on the efficiency of electrocatalysis for OER. These measurements are understood based on interfacial band alignment in the system as confirmed by layer-resolved electron energy loss spectroscopy and electrochemical Mott-Schottky measurements. Our results demonstrate the importance of band engineering for the rational design of thin film electrocatalysts for renewable energy sources.
description: 19 pages, 6 figures; authors Burton and Paudel contributed equally; supplement: 11 pages, 7 figures
Non-linear diffusion with stochastic resetting
Creators: name: Chelminiak, Przemyslaw
Publisher: name: arXiv
Year: 2021
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: Resetting or restart, when applied to a stochastic process, usually brings its dynamics to a time-independent stationary state. In turn, the optimal resetting rate makes the mean time to reach a target to be the shortest one. These and other intriguing problems have been intensively studied in the case of ordinary diffusive processes over the last decade. In this paper we consider the influence of stochastic resetting on a diffusive motion modeled in terms of the non-linear differential equation. The reason for its non-linearity is the power-law dependence of the diffusion coefficient on the probability density function or, in another context, the concentration of particles. We briefly outline this issue at first to prepare the foundations for our further considerations. Then, we derive an exact formula for the mean squared displacement and demonstrate how it attains the steady-state value under the influence of exponential resetting. This mechanism brings also about that the spatial support of the probability density function, which for the free non-linear diffusion is confined to the set of a finite measure, tends to span the entire domain of real numbers. In addition, we explore the first-passage properties for the non-linear diffusion intermittent by the exponential resetting and find analytical expressions for the mean first-passage time and determine numerically the optimal resetting rate which minimizes the mean time needed for a particle to reach a pre-determined target. Finally, we test and confirm the universal property that the relative fluctuation in the mean first-passage time of optimally restarted non-linear diffusion is equal to unity.
description: 22 pages, 11 figures, The current paper is the essential modification of the previous version. The manuscript captures new results, especially for the mean hitting time where the absorbing boundary condition for the probability density function has been rejected. As we will show in a separate paper, it can not be used in the case of the non-linear diffusion equation
Hyperparameter selection for Discrete Mumford-Shah
Creators: name: Lucas, Charles-Gérard
name: Pascal, Barbara
name: Pustelnik, Nelly
name: Abry, Patrice
Publisher: name: arXiv
Year: 2021
Subjects: subject: Image and Video Processing (eess.IV)
subject: Optimization and Control (math.OC)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Mathematics

description: This work focuses on a parameter-free joint piecewise smooth image denoising and contour detection. Formulated as the minimization of a discrete Mumford-Shah functional and estimated via a theoretically grounded alternating minimization scheme, the bottleneck of such a variational approach lies in the need to fine-tune their hyperparameters, while not having access to ground truth data. To that aim, a Stein-like strategy providing optimal hyperparameters is designed, based on the minimization of an unbiased estimate of the quadratic risk. Efficient and automated minimization of the estimate of the risk crucially relies on an unbiased estimate of the gradient of the risk with respect to hyperparameters. Its practical implementation is performed using a forward differentiation of the alternating scheme minimizing the Mumford-Shah functional, requiring exact differentiation of the proximity operators involved. Intensive numerical experiments are performed on synthetic images with different geometry and noise levels, assessing the accuracy and the robustness of the proposed procedure. The resulting parameter-free piecewise-smooth estimation and contour detection procedure, not requiring prior image processing expertise nor annotated data, can then be applied to real-world images.
Forward Heavy Quarkonium Productions at the LHC
Creators: name: Watanabe, Kazuhiro
name: Xiao, Bo-Wen
Publisher: name: arXiv
Year: 2015
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: Nuclear Theory (nucl-th)
subject: FOS: Physical sciences

description: We investigate the low transverse momentum heavy quarkonium ($J/ψ$, $Υ$) productions in the forward rapidity region of $pp$ and $pA$ collisions at the LHC as an important probe to the transverse momentum tomography of the gluons in hadrons in the Color Glass Condensate (CGC) framework. By implementing the Sudakov resummation consistently in the CGC formalism, we achieve an excellent agreement between the improved CGC calculations and the LHC data. We show that both the small-$x$ and the Sudakov effects are essential for a complete description of heavy quarkonium productions in the low transverse momentum region. This provides a solid foundation to study the small-$x$ gluon saturation in a big nucleus with the future $pA$ programs at the LHC.
description: 5 pages, 3 figures; some corrections
Progenitor cell niches in the human pancreatic duct system and associated pancreatic duct glands: an anatomical and immunophenotyping study
Creators: name: Onori, Paolo
name: Carpino, Guido
name: Renzi, Anastasia
name: Reid, Lola M.
name: Overi, Diletta
name: Rossi, Massimo
name: Franchitto, Antonio
name: Alvaro, Domenico
name: Cardinale, Vincenzo
name: Berloco, Pasquale Bartolomeo
name: Gaudio, Eugenio
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2016

description: Abstract Pancreatic duct glands (PDGs) are tubule‐alveolar glands associated with the pancreatic duct system and can be considered the anatomical counterpart of peribiliary glands (PBGs) found within the biliary tree. Recently, we demonstrated that endodermal precursor niches exist fetally and postnatally and are composed functionally of stem cells and progenitors within PBGs and of committed progenitors within PDGs. Here we have characterized more extensively the anatomy of human PDGs as novel niches containing cells with multiple phenotypes of committed progenitors. Human pancreata (n = 15) were obtained from cadaveric adult donors. Specimens were processed for histology, immunohistochemistry and immunofluorescence. PDGs were found in the walls of larger pancreatic ducts (diameters > 300 μm) and constituted nearly 4% of the duct wall area. All of the cells identified were negative for nuclear expression of Oct4, a pluripotency gene, and so are presumably committed progenitors and not stem cells. In the main pancreatic duct and in large interlobular ducts, Sox9+ cells represented 5–30% of the cells within PDGs and were located primarily at the bottom of PDGs, whereas rare and scattered Sox9+ cells were present within the surface epithelium. The expression of PCNA, a marker of cell proliferation, paralleled the distribution of Sox9 expression. Sox9+PDG cells proved to be Pdx1+/Ngn3+/–/Oct4A−. Nearly 10% of PDG cells were positive for insulin or glucagon. Intercalated ducts contained Sox9+/Pdx1+/Ngn3+ cells, a phenotype that is presumptive of committed endocrine progenitors. Some intercalated ducts appeared in continuity with clusters of insulin‐positive cells organized in small pancreatic islet‐like structures. In summary, PDGs represent niches of a population of Sox9+ cells exhibiting a pattern of phenotypic traits implicating a radial axis of maturation from the bottoms of the PDGs to the surface of pancreatic ducts. Our results complete the anatomical background that links biliary and pancreatic tracts and could have important implications for the common patho‐physiology of biliary tract and pancreas.
Quantum random number generation
Creators: name: Ma, Xiongfeng
name: Yuan, Xiao
name: Cao, Zhu
name: Qi, Bing
name: Zhang, Zhen
Publisher: name: arXiv
Year: 2015
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness --- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at a high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.
description: 32 pages, 5 figures
Faint CO Line Wings in Four Star-Forming (Ultra)luminous Infrared Galaxies
Creators: name: Leroy, Adam K.
name: Walter, Fabian
name: Decarli, Roberto
name: Bolatto, Alberto
name: Zschaechner, Laura
name: Weiss, Axel
Publisher: name: arXiv
Year: 2015
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: We report the results of a search for large velocity width, low-intensity line wings - a commonly used signature of molecular outflows - in four low redshift (ultra)luminous infrared galaxies (U/LIRGs) that appear to be dominated by star formation. The targets were drawn from a sample of fourteen such galaxies presented in Chung et al. (2011), who showed the stacked CO spectrum of the sample to exhibit 1000 km/s-wide line wings. We obtained sensitive, wide bandwidth imaging of our targets using the IRAM Plateau de Bure Interferometer. We detect each target at very high significance but do not find the claimed line wings in these four targets. Instead, we constrain the flux in the line wings to be only a few percent. Casting our results as mass outflow rates following Cicone et al. (2014) we show them to be consistent with a picture in which very high mass loading factors preferentially occur in systems with high AGN contributions to their bolometric luminosity. We identify one of our targets, IRAS05083 (VII Zw 31), as a candidate molecular outflow.
description: 9 pages, 5 figures, 1 appendix; accepted for publication in the Astrophysical Journal
Analytic Gaussian Covariance Matrices for Galaxy $N$-Point Correlation Functions
Creators: name: Hou, Jiamin
name: Cahn, Robert N.
name: Philcox, Oliver H. E.
name: Slepian, Zachary
Publisher: name: arXiv
Year: 2021
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: FOS: Physical sciences

description: We derive analytic covariance matrices for the $N$-Point Correlation Functions (NPCFs) of galaxies in the Gaussian limit. Our results are given for arbitrary $N$ and projected onto the isotropic basis functions of Cahn & Slepian (2020), recently shown to facilitate efficient NPCF estimation. A numerical implementation of the 4PCF covariance is compared to the sample covariance obtained from a set of lognormal simulations, Quijote dark matter halo catalogues, and MultiDark-Patchy galaxy mocks, with the latter including realistic survey geometry. The analytic formalism gives reasonable predictions for the covariances estimated from mock simulations with a periodic-box geometry. Furthermore, fitting for an effective volume and number density by maximizing a likelihood based on Kullback-Leibler divergence is shown to partially compensate for the effects of a non-uniform window function.
description: 31 pages, 17 figures