cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
title: ADCO, Abbaye de Cîteaux, Tablettes de cire, comptes du boursier, 1321-1325, 11 H 1165, f. 0005274
Creators: name: de la Côte d'Or, Archives départementales
name: Archives Départementales De La Côte-D'Or
name: Petot, Frédérique
name: Projet CBMA
name: CG21/F.PETOT/2012
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020
Subjects: subject: comptes
subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris
subject: Chartes de la Bourgogne du Moyen Âge
subject: Corpus Burgundiae Medii Aevi

description: Abbaye de Cîteaux, Tablettes de cire, comptes du boursier, 1321-1325, Archives départementales de la Côte-d'Or, 11 H 1165, f. 0005274, Numérisation en mode image.
description: Relation: http://www.cbma-project.eu/
description: Bibliographic citation: Abbaye de Cîteaux, Tablettes de cire, comptes du boursier, 1321-1325, Archives départementales de la Côte-d'Or, 11 H 1165, f. 0005274, in Projet CBMA - Corpus Burgundiae Medii Aevi [Ressource en ligne], https://manuscrits.cbma-project.eu/
description: Provenance: https://www.geonames.org/3024876
description: Provenance: http://www.idref.fr/030974844/id
description: Provenance: https://catalogue.bnf.fr/ark:/12148/cb12228351v
description: Provenance: abbaye de Cîteaux
description: Provenance: http://www.wikidata.org/entity/Q843261
Deterministic distribution of orbital angular momentum multiplexed continuous-variable entanglement and quantum steering
Creators: name: Zeng, Li
name: Ma, Rong
name: Wen, Hong
name: Wang, Meihong
name: Liu, Jun
name: Qin, Zhongzhong
name: Su, Xiaolong
Publisher: name: arXiv
Year: 2022
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Orbital angular momentum (OAM) multiplexing provides an efficient method to improve data-carrying capacity in various quantum communication protocols. It is a precondition to distribute OAM multiplexed quantum resources in quantum channels for implementing quantum communication. However, quantum steering of OAM multiplexed optical fields and the effect of channel noise on OAM multiplexed quantum resources remain unclear. Here, we generate OAM multiplexed continuous-variable (CV) entangled states and distribute them in lossy or noisy channels. We show that the decoherence property of entanglement and quantum steering of the OAM multiplexed states carrying topological charges $l=1$ and $l=2$ are the same as that of the Gaussian mode with $l=0$ in lossy and noisy channels. The sudden death of entanglement and quantum steering of high-order OAM multiplexed states is observed in the presence of excess noise. Our results demonstrate the feasibility to realize high data-carrying capacity quantum information processing by utilizing OAM multiplexed CV entangled states.
description: 9 pages, 7 figures. Comments are welcome
A First Look at Duplicate and Near-duplicate Self-admitted Technical Debt Comments
Creators: name: Yasmin, Jerin
name: Sheikhaei, Mohammad Sadegh
name: Tian, Yuan
Publisher: name: arXiv
Year: 2022
Subjects: subject: Software Engineering (cs.SE)
subject: FOS: Computer and information sciences

description: Self-admitted technical debt (SATD) refers to technical debt that is intentionally introduced by developers and explicitly documented in code comments or other software artifacts (e.g., issue reports) to annotate sub-optimal decisions made by developers in the software development process. In this work, we take the first look at the existence and characteristics of duplicate and near-duplicate SATD comments in five popular Apache OSS projects, i.e., JSPWiki, Helix, Jackrabbit, Archiva, and SystemML. We design a method to automatically identify groups of duplicate and near-duplicate SATD comments and track their evolution in the software system by mining the commit history of a software project. Leveraging the proposed method, we identified 3,520 duplicate and near-duplicate SATD comments from the target projects, which belong to 1,141 groups. We manually analyze the content and context of a sample of 1,505 SATD comments (by sampling 100 groups for each project) and identify if they annotate the same root cause. We also investigate whether duplicate SATD comments exist in code clones, whether they co-exist in the same file, and whether they are introduced and removed simultaneously. Our preliminary study reveals several surprising findings that would shed light on future studies aiming to improve the management of duplicate SATD comments. For instance, only 48.5% duplicate SATD comment groups with the same root cause exist in regular code clones, and only 33.9% of the duplicate SATD comment pairs are introduced in the same commit.
description: 4 +1 pages
Framework for Learning and Control in the Classical and Quantum Domains
Creators: name: Vedaie, Seyed Shakib
name: Dalal, Archismita
name: Páez, Eduardo J.
name: Sanders, Barry C.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Control and learning are key to technological advancement, both in the classical and quantum domains, yet their interrelationship is insufficiently clear in the literature, especially between classical and quantum definitions of control and learning. We construct a framework that formally relates learning and control, both classical and quantum, to each other, with this formalism showing how learning can aid control. Furthermore, our framework helps to identify interesting unsolved problems in the nexus of classical and quantum control and learning and help in choosing tools to solve problems. As a use case, we cast the well-studied problem of adaptive quantum-enhanced interferometric-phase estimation as a supervised learning problem for devising feasible control policies. Our unification of these fields relies on diagrammatically representing the state of knowledge, which elegantly summarizes existing knowledge and exposes knowledge gaps.
description: 28 pages, 11 figures, 1 table
Additional file 2 of Enlightening the taxonomy darkness of human gut microbiomes with a cultured biobank
Creators: name: Liu, Chang
name: Du, Meng-Xuan
name: Abuduaini, Rexiding
name: Yu, Hai-Ying
name: Li, Dan-Hua
name: Wang, Yu-Jing
name: Zhou, Nan
name: Jiang, Min-Zhi
name: Niu, Peng-Xia
name: Han, Shan-Shan
name: Chen, Hong-He
name: Shi, Wen-Yu
name: Wu, Linhuan
name: Xin, Yu-Hua
name: Ma, Juncai
name: Zhou, Yuguang
name: Jiang, Cheng-Ying
name: Liu, Hong-Wei
name: Liu, Shuang-Jiang
Publisher: name: figshare
Year: 2021
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Genetics

description: Additional file 1: Figure S1. The phylogenetic tree of 108 novel taxon candidates. The phylogenetic tree was constructed with the 16S rRNA gene sequences of each strain using MEGA7 [80] under the neighbor-joining method. The bootstrap value is 1000. The ANIs between adjacent taxa on the tree was calculated using OrthoANI OTA solfware [80] and list in the panel (red color). The names of 102 novel-taxon candidates that were later identified to represent novel taxa were colored in blue, while the 6 candidates that were later determined to be new strains of known species were colored in grey and the 16S rRNA gene identity to the known species were listed in the brackets.
Base drag reduction for squareback road vehicles
Creators: name: Varney, Max
Publisher: name: Loughborough University
Year: 2020
Subjects: subject: 99999 Engineering not elsewhere classified
subject: FOS: Other engineering and technologies

description: As we are in the throes of a climate crisis, we need to scrutinise how our everyday activity impacts it. A significant portion of the global CO 2 emissions are a result of passenger vehicles (16%) with a significant portion of these being sports utility vehicle geometries (37.5%). The squareback nature of sports utility vehicles is desired by some manufacturers to maintain brand identity, but these geometries are not typically aerodynamic. On top of this, the emissions regulations do not take into account realistic conditions that a vehicle will operate in, resulting in an underestimation of their impact on the global CO2 emissions.
This thesis implements cavities and small trailing edge side edge tapers on a quarter scale Windsor model (with and without wheels) at more realistic flow conditions to generalise drag reduction techniques. These generalisations focus on the base of the model as this region generates a significant portion of the overall drag. As the geometries are unlikely to be implemented on a full-scale vehicle, the generalisations provide a goal for a lower drag vehicle which can be applied to any baseline geometry.
Irrespective of the device used it was found that a way to reduce drag generally was to force the wake into a balanced, symmetric condition. The lateral symmetry is shown to reduce the instantaneous base drag at yaw on the baseline geometry, but also the mean base drag with a cavity or side edge tapering at yaw. The vertical symmetry is shown to improve the mean base drag on the Windsor model with wheels, both with a cavity and with the side edge tapering at all yaw angles tested.
A symmetric, balanced wake was shown not to be the only route to low drag. The cavities showed a reduction in base drag due to the reduced flow velocity in the wake with flow field measurements inside the cavity, while presenting an asymmetric wake. The tapering generated base drag reductions with slower velocities parallel to the base, higher velocities perpendicular to the base and shorter wakes that were upwash or downwash dominated.
title: Commission d'Instruction de la Cour de justice de la République, "Arrêt portant renvoi devant la Cour de justice de la République : Prononcé au siège de la Cour de justice de la République le 17 juillet 1998"
Creators: name: Leibowitch, Jacques
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020

description: Première partie.
description: Source: http://www.calames.abes.fr/pub/ms/Calames-20193111233429215
MANAJEMEN PENILAIAN AKREDITASI JURNAL
Creators: name: M. Ibraar Ayatullah
Publisher: name: Zenodo
Year: 2022
Subjects: Akreditasi Jurnal
Re-Akreditasi Jurnal
Jurnal
Arjuna

description: Kegiatan ini merupakan kegiatan Pelatihan Persiapan Akreditasi dan Re-akreditasi E-Jurnal di Lingkungan Poltekkes Kemenkes Surabaya.
Spatial distribution of HOCN around Sagittarius B2
Creators: name: Zheng, Siqi
name: Li, Juan
name: Wang, Junzhi
name: Gao, Feng
name: Wu, Yajun
name: liu, Shu
name: Li, Shanghuo
Publisher: name: arXiv
Year: 2022
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: HOCN and HNCO abundance ratio in molecular gas can tell us the information of their formation mechanism. We performed high-sensitivity mapping observations of HOCN, HNCO, and HNC$^{18}$O lines around Sagittarius B2 (Sgr B2) with IRAM 30m telescope at 3-mm wavelength. HNCO 4$_{04}$-3$_{03}$ and HOCN 4$_{04}$-3$_{03}$ are used to obtain the abundance ratio of HNCO to HOCN. The ratio of HNCO 4$_{04}$-3$_{03}$ to HNC$^{18}$O 4$_{04}$-3$_{03}$ is used to calculate the optical depth of HNCO 4$_{04}$-3$_{03}$. The abundance ratio of HOCN and HNCO is observed to range from 0.4% to 0.7% toward most positions, which agrees well with the gas-grain model. However, the relative abundance of HOCN is observed to be enhanced toward the direction of Sgr B2 (S), with HOCN to HNCO abundance ratio of $\sim$ 0.9%. The reason for that still needs further investigation.Based on the intensity ratio of HNCO and HNC$^{18}$O lines, we updated the isotopic ratio of $^{16}$O/$^{18}$O to be 296 $\pm$ 54 in Sgr B2.
Natural Disasters and Preferences for the Environment: Evidence from the Impressionable Years
Creators: name: FALCO, CHIARA
name: Corbi, R.
Publisher: name: Dipartimento di Economia Marco Biagi - Universit� di Modena e Reggio Emilia
Year: 2022

description: Do generations a?ected by natural disasters during the critical years of adolescence and early adulthood form di?erent preferences towards the environment than generations who are not? Consistent with the theories of social psychology, we show that an environmental shock experienced during the impressionable years (18-25 years old) help shape positive environmental preferences. Individuals tend not to change beliefs in response to natural disasters experienced in other age ranges. Using information from the General Social Survey and World Values Survey, we exploit yearly natural disasters variation both within the US and across countries to identify these effects.
title: ADCO, Cartulaire général de Cîteaux, dit de Jean de Cirey, (XVe siècle), tome VI, Cart. 190 (11 H 75), 316 folios, f. 0229v
Creators: name: de la Côte d'Or, Archives départementales
name: Archives Départementales De La Côte-D'Or
name: Petot, Frédérique
name: Projet CBMA
name: CG21/F.PETOT/2012
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020
Subjects: subject: cartulaire
subject: Corpus Burgundiae Medii Aevi
subject: Chartes de la Bourgogne du Moyen Âge
subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris

description: Cartulaire général de Cîteaux, dit de Jean de Cirey, (XVe siècle), tome VI, Archives départementales de la Côte-d'Or, Cart. 190 (11 H 75), 316 folios, f. 0229v, Numérisation en mode image.
description: Relation: http://www.cbma-project.eu/
description: Bibliographic citation: Cartulaire général de Cîteaux, dit de Jean de Cirey, (XVe siècle), tome VI, Archives départementales de la Côte-d'Or, Cart. 190 (11 H 75), 316 folios, f. 0229v, in Projet CBMA - Corpus Burgundiae Medii Aevi [Ressource en ligne], https:// manuscrits.cbma-project.eu/
description: Provenance: https://www.geonames.org/3024876
description: Provenance: http://www.idref.fr/030974844/id
description: Provenance: https://catalogue.bnf.fr/ark:/12148/cb12228351v
description: Provenance: abbaye de Cîteaux
description: Provenance: http://www.wikidata.org/entity/Q843261
title: ADCO, Cartulaire de Cîteaux pour les possessions de Chaugey et Maison-Dieu (Fin XVe siècle), Cart. 180 (11 H 755), 83 folios, f. 0156
Creators: name: de la Côte d'Or, Archives départementales
name: Archives Départementales De La Côte-D'Or
name: Petot, Frédérique
name: Projet CBMA
name: CG21/F.PETOT/2017
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020
Subjects: subject: Chartes de la Bourgogne du Moyen Âge
subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris
subject: cartulaire
subject: Corpus Burgundiae Medii Aevi

description: Cartulaire de Cîteaux pour les possessions de Chaugey et Maison-Dieu (Fin XVe siècle), Archives départementales de la Côte-d'Or, Cart. 180 (11 H 755), 83 folios, f. 0156, Numérisation en mode image.
description: Relation: http://www.cbma-project.eu/
description: Bibliographic citation: Cartulaire de Cîteaux pour les possessions de Chaugey et Maison-Dieu (Fin XVe siècle), Archives départementales de la Côte-d'Or, Cart. 180 (11 H 755), 83 folios, f. 0156, in Projet CBMA - Corpus Burgundiae Medii Aevi [Ressource en ligne], https:// manuscrits.cbma-project.eu/
description: Provenance: https://www.geonames.org/3024876
description: Provenance: http://www.idref.fr/030974844/id
description: Provenance: https://catalogue.bnf.fr/ark:/12148/cb12228351v
description: Provenance: abbaye de Cîteaux
description: Provenance: http://www.wikidata.org/entity/Q843261
Additional file 17 of Enlightening the taxonomy darkness of human gut microbiomes with a cultured biobank
Creators: name: Liu, Chang
name: Du, Meng-Xuan
name: Abuduaini, Rexiding
name: Yu, Hai-Ying
name: Li, Dan-Hua
name: Wang, Yu-Jing
name: Zhou, Nan
name: Jiang, Min-Zhi
name: Niu, Peng-Xia
name: Han, Shan-Shan
name: Chen, Hong-He
name: Shi, Wen-Yu
name: Wu, Linhuan
name: Xin, Yu-Hua
name: Ma, Juncai
name: Zhou, Yuguang
name: Jiang, Cheng-Ying
name: Liu, Hong-Wei
name: Liu, Shuang-Jiang
Publisher: name: figshare
Year: 2021
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Genetics

description: Additional file 16: Supplementary Methods. The documentation of detailed recipes and references of basic media used in this study.
Radiation fluxes of gravitational, electromagnetic, and scalar perturbations in type-D black holes: an exact approach
Creators: name: Chen, Changkai
name: Jing, Jiliang
Publisher: name: arXiv
Year: 2023
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: We present a novel method that solves Teukolsky equations with the source to calculate radiation fluxes at infinity and event horizon for any perturbation fields of type-D black holes. For the first time, we use the confluent Heun function to obtain the exact solutions of ingoing and outgoing waves for the Teukolsky equation. This benefits from our derivation of the asymptotic analytic expression of the confluent Heun function at infinity. It is interesting to note that these exact solutions are not subject to any constraints, such as low-frequency and weak-field. To illustrate the correctness, we apply these exact solutions to calculate the gravitational, electromagnetic, and scalar radiations of the Schwarzschild black hole. Numerical results show that the proposed exact solution appreciably improves the computational accuracy and efficiency compared with the 23rd post-Newtonian order expansion and the Mano-Suzuki-Takasugi method.
description: 23 pages, 5 figures, and 6 tables
title: Histoires de l'éducation spécialisée (1827-1970)
title: Les arcanes du placement institutionnel
titleType: Subtitle
title: Histoires de l'éducation spécialisée (1827-1970)
titleType: AlternativeTitle
Creators: name: Avvanzino, Pierre
name: Valsesia, Charles-Antoine
Publisher: name: Editions EESP
Year: 1993

description: Également sur la page de titre : De l'enfant abandonné à l'enfant inadapté de l'Asile rural à la Maison d'éducation. Étude historique vue à travers un analyseur: l’École Pestalozzi à Échichens.
Generalised Amit-Roginsky model from perturbations of 3d quantum gravity
Creators: name: Nador, Victor
name: Oriti, Daniele
name: Pang, Xiankai
name: Tanasa, Adrian
name: Wang, Yi-Li
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: Mathematical Physics (math-ph)
subject: FOS: Physical sciences

description: A generalised Amit-Roginsky vector model in flat space is obtained as the effective dynamics of pertubations around a classical solution of the Boulatov group field theory for 3d euclidean quantum gravity, extended to include additional matter degrees of freedom. By further restricting the type of perturbations, the original Amit-Roginsky model can be obtained. This result suggests a general link (and possibly a unified framework) between two types of tensorial quantum field theories: quantum geometric group field theories and tensorial models for random geometry, on one hand, and melonic-dominated vector and tensorial models in flat space, such as the Amit-Roginsky model (and the SYK model), on the other hand.
description: 30 pages
Additional file 18 of Enlightening the taxonomy darkness of human gut microbiomes with a cultured biobank
Creators: name: Liu, Chang
name: Du, Meng-Xuan
name: Abuduaini, Rexiding
name: Yu, Hai-Ying
name: Li, Dan-Hua
name: Wang, Yu-Jing
name: Zhou, Nan
name: Jiang, Min-Zhi
name: Niu, Peng-Xia
name: Han, Shan-Shan
name: Chen, Hong-He
name: Shi, Wen-Yu
name: Wu, Linhuan
name: Xin, Yu-Hua
name: Ma, Juncai
name: Zhou, Yuguang
name: Jiang, Cheng-Ying
name: Liu, Hong-Wei
name: Liu, Shuang-Jiang
Publisher: name: figshare
Year: 2021
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Genetics

description: Additional file 17: Supplementary Data 1. The detailed taxonomic descriptions of novel taxa in hGMB.
Plasmoids formation during simulations of coaxial helicity injection in the National Spherical Torus Experiment
Creators: name: Ebrahimi, F.
name: Raman, R.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Plasma Physics (physics.plasm-ph)
subject: Space Physics (physics.space-ph)
subject: FOS: Physical sciences

description: Formation of an elongated Sweet-Parker current sheet and a transition to plasmoid instability has for the first time been predicted by simulations in a large-scale toroidal fusion plasma in the absence of any pre-existing instability. Plasmoid instability is demonstrated through resistive MHD simulations of transient Coaxial Helicity Injection (CHI) experiments in the National Spherical Torus Experiment (NSTX).Consistent with the theory, fundamental characteristics of the plasmoid instability, including fast reconnection rate, have been observed in these realistic simulations. Motivated by the simulations, experimental camera images have been revisited and suggest the existence of reconnecting plasmoids in NSTX. Global, system-size plasmoid formation observed here should also have strong implications for astrophysical reconnection, such as rapid eruptive solar events.
description: 5 pages, 5 figures
Updated global fit of the aligned two-Higgs-doublet model with heavy scalars
Creators: name: Karan, Anirban
name: Miralles, Víctor
name: Pich, Antonio
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: An updated global fit on the parameter-space of the Aligned Two-Higgs-Doublet model has been performed with the help of the open-source package HEPfit, assuming the Standard-Model Higgs to be the lightest scalar. No new sources of CP violation, other than the phase in the CKM matrix of the Standard Model, have been considered. A similar global fit was previously performed in Ref. [JHEP 05 (2021) 005] with a slightly different set of parameters. Our updated fit incorporates improved analyses of the theoretical constraints required for perturbative unitarity and boundedness of the scalar potential from below, additional flavour observables and updated data on direct searches of heavy scalars at the LHC, Higgs signal strengths and electroweak precision observables. Although not included in the main fit, the implications of the CDF measurement of the $W^\pm$ mass are also discussed.
description: 38 pages, 15 figures
Is public information really public? The role of newspapers.
Creators: name: FERRETTI, Riccardo
name: PATTARIN, Francesco
Publisher: name: Dipartimento di Economia Marco Biagi - Universit� di Modena e Reggio Emilia
Year: 2008

description: Our paper offers evidence that printed media can affect stock prices by covering public news (nonevents) even without resorting to spin or emphasis. However, the price reaction is limited to small caps, suggesting that small investors still obtain public information mainly through newspapers. The absence of spin or emphasis is the core element that differentiates our study from existing evidence, making it unique, to the best of our knowledge, in the financial literature on the media and asset pricing.
title: ADCO, Cartulaire de Fontenay, premier fragment (XIIIe siècle), Cart. 201 (15 H 9), 175 folios, f. 017v
Creators: name: de la Côte d'Or, Archives départementales
name: Petot, Frédéric
name: Archives Départementales De La Côte-D'Or
name: Petot, Frédérique
name: Projet CBMA
name: CG21/F.PETOT/2009
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020
Subjects: subject: Chartes de la Bourgogne du Moyen Âge
subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris
subject: cartulaire
subject: Corpus Burgundiae Medii Aevi

description: Cartulaire de Fontenay, premier fragment (XIIIe siècle), Archives départementales de la Côte-d'Or, Cart. 201 (15 H 9), 175 folios. Numérisation en mode image.
description: Relation: http://www.cbma-project.eu/
description: Bibliographic citation: Cartulaire de Fontenay, premier fragment (XIIIe siècle), Archives départementales de la Côte-d'Or, Cart. 201 (15 H 9), 175 folios, f. 017v, in Projet CBMA - Corpus Burgundiae Medii Aevi [Ressource en ligne], https:// manuscrits.cbma-project.eu/
description: Provenance: abbaye de Fontenay
description: Provenance: http://www.wikidata.org/entity/Q464918
description: Provenance: https://catalogue.bnf.fr/ark:/12148/cb119679755
description: Provenance: https://www.geonames.org/7874015
description: Provenance: http://www.idref.fr/027691802/id
Fully $1\times1$ Convolutional Network for Lightweight Image Super-Resolution
Creators: name: Wu, Gang
name: Jiang, Junjun
name: Jiang, Kui
name: Liu, Xianming
Publisher: name: arXiv
Year: 2023
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Deep models have achieved significant process on single image super-resolution (SISR) tasks, in particular large models with large kernel ($3\times3$ or more). However, the heavy computational footprint of such models prevents their deployment in real-time, resource-constrained environments. Conversely, $1\times1$ convolutions bring substantial computational efficiency, but struggle with aggregating local spatial representations, an essential capability to SISR models. In response to this dichotomy, we propose to harmonize the merits of both $3\times3$ and $1\times1$ kernels, and exploit a great potential for lightweight SISR tasks. Specifically, we propose a simple yet effective fully $1\times1$ convolutional network, named Shift-Conv-based Network (SCNet). By incorporating a parameter-free spatial-shift operation, it equips the fully $1\times1$ convolutional network with powerful representation capability while impressive computational efficiency. Extensive experiments demonstrate that SCNets, despite its fully $1\times1$ convolutional structure, consistently matches or even surpasses the performance of existing lightweight SR models that employ regular convolutions. The code and pre-trained models can be found at https://github.com/Aitical/SCNet.
description: Accepted by Machine Intelligence Research, DOI: 10.1007/s11633-024-1401-z
An Iterative Co-Training Transductive Framework for Zero Shot Learning
Creators: name: Liu, Bo
name: Hu, Lihua
name: Dong, Qiulei
name: Hu, Zhanyi
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: In zero-shot learning (ZSL) community, it is generally recognized that transductive learning performs better than inductive one as the unseen-class samples are also used in its training stage. How to generate pseudo labels for unseen-class samples and how to use such usually noisy pseudo labels are two critical issues in transductive learning. In this work, we introduce an iterative co-training framework which contains two different base ZSL models and an exchanging module. At each iteration, the two different ZSL models are co-trained to separately predict pseudo labels for the unseen-class samples, and the exchanging module exchanges the predicted pseudo labels, then the exchanged pseudo-labeled samples are added into the training sets for the next iteration. By such, our framework can gradually boost the ZSL performance by fully exploiting the potential complementarity of the two models' classification capabilities. In addition, our co-training framework is also applied to the generalized ZSL (GZSL), in which a semantic-guided OOD detector is proposed to pick out the most likely unseen-class samples before class-level classification to alleviate the bias problem in GZSL. Extensive experiments on three benchmarks show that our proposed methods could significantly outperform about $31$ state-of-the-art ones.
description: 15 pages, 7 figures
Remote Co-teaching in Rural Classroom: Current Practices, Impacts, and Challenges
Creators: name: Guo, Siling
name: Sun, Tianchen
name: Gong, Jiangtao
name: Lu, Zhicong
name: Zhang, Liuxin
name: Wang, Qianying
Publisher: name: arXiv
Year: 2022
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: FOS: Computer and information sciences
subject: J.4
subject: 91C99

description: The shortage of high-quality teachers is one of the biggest educational problems faced by underdeveloped areas. With the development of information and communication technologies (ICTs), China has begun a remote co-teaching intervention program using ICTs for rural classes, forming a unique co-teaching classroom. We conducted semi-structured interviews with nine remote urban teachers and twelve local rural teachers. We identified the remote co-teaching classes standard practices and co-teachers collaborative work process. We also found that remote teachers high-quality class directly impacted local teachers and students. Furthermore, interestingly, local teachers were also actively involved in making indirect impacts on their students by deeply coordinating with remote teachers and adapting the resources offered by the remote teachers. We conclude by summarizing and discussing the challenges faced by teachers, lessons learned from the current program, and related design implications to achieve a more adaptive and sustainable ICT4D program design.
description: 16 pages, 6 figures, SIGCHI 2022
CERT Releases 2 Tools to Assess Insider Risk
Creators: name: Black, Roger
Publisher: name: Carnegie Mellon University
Year: 2024
Subjects: Software Engineering

description: According to a 2023 Ponemon study, the number of reported insider risk incidents and the costs associated with them continues to rise. With more than 7,000 reported cases in 2023, the average insider risk incident cost organizations over $600,000. To help organizations assess their insider risk programs and identify potential vulnerabilities that could result in insider threats, the SEI CERT Division has released two tools available for download on its website. Previously available only to licensed partners, the Insider Threat Vulnerability Assessment (ITVA) and Insider Threat Program Evaluation (ITPE) toolkits provide practical methods to assess your organization’s  ability to manage insider risk. This post describes the purpose and use of the toolkits, with a focus on the workbook components of the toolkits that are the primary methods of program assessment.
MOESM1 of Tissue of origin dictates GOT1 dependence and confers synthetic lethality to radiotherapy
Creators: name: Nelson, Barbara
name: Lin, Lin
name: Kremer, Daniel
name: Sousa, CristovÃ£o
name: Cotta-Ramusino, Cecilia
name: Myers, Amy
name: Ramos, Johanna
name: Gao, Tina
name: Kovalenko, Ilya
name: Wilder-Romans, Kari
name: Dresser, Joseph
name: Davis, Mary
name: Lee, Ho-Joon
name: Nwosu, Zeribe
name: Campit, Scott
name: Mashadova, Oksana
name: Nicolay, Brandon
name: Tolstyka, Zachary
name: Halbrook, Christopher
name: Chandrasekaran, Sriram
name: Asara, John
name: Crawford, Howard
name: Cantley, Lewis
name: Kimmelman, Alec
name: Wahl, Daniel
name: Lyssiotis, Costas
Publisher: name: figshare
Year: 2020
Subjects: subject: Physiology
subject: FOS: Biological sciences
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Developmental Biology

description: Additional file 1. Supplementary figures.
Mapping tissue microstructure of brain white matter in vivo in health and disease using diffusion MRI
Creators: name: Liao, Ying
name: Coelho, Santiago
name: Chen, Jenny
name: Ades-Aron, Benjamin
name: Pang, Michelle
name: Osorio, Ricardo
name: Shepherd, Timothy
name: Lui, Yvonne W.
name: Novikov, Dmitry S.
name: Fieremans, Els
Publisher: name: arXiv
Year: 2023
Subjects: subject: Medical Physics (physics.med-ph)
subject: FOS: Physical sciences

description: Diffusion magnetic resonance imaging offers unique in vivo sensitivity to tissue microstructure in brain white matter, which undergoes significant changes during development and is compromised in virtually every neurological disorder. Yet, the challenge is to develop biomarkers that are specific to micrometer-scale cellular features in a human MRI scan of a few minutes. Here we quantify the sensitivity and specificity of a multicompartment diffusion modeling framework to the density, orientation and integrity of axons. We demonstrate that using a machine learning based estimator, our biophysical model captures the morphological changes of axons in early development, acute ischemia and multiple sclerosis (total N=821). The methodology of microstructure mapping is widely applicable in clinical settings and in large imaging consortium data to study development, aging and pathology.
description: 4 figures, 5 supplementary figures, 1 supplementary table
Probabilistic Parameter Estimation Using a Gaussian Mixture Density Network: Application to X-ray Reflectivity Data Curve Fitting
Creators: name: Kim, Kook Tae
name: Lee, Dong Ryeol
Publisher: name: arXiv
Year: 2022
Subjects: subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: X-ray reflectivity (XRR) is widely used for thin-film structure analysis, and XRR data analysis involves minimizing the difference between an XRR curve calculated from model parameters describing the thin-film structure. This analysis takes a certain amount of time because it involves many unavoidable iterations. However, the recently introduced artificial neural network (ANN) method can dramatically reduce the analysis time in the case of repeated analyses of similar samples. Here, we demonstrate the analysis of XRR data using a mixture density network (MDN), which enables probabilistic prediction while maintaining the advantages of an ANN. First, under the assumption of a unimodal probability distribution of the output parameter, the trained MDN can estimate the best-fit parameter and, at the same time, estimate the confidence interval (CI) corresponding to the error bar of the best-fit parameter. The CI obtained in this manner is similar to that obtained using the Neumann process, a well-known statistical method. Next, the MDN method provides several possible solutions for each parameter in the case of a multimodal distribution of the output parameters. An unsupervised machine learning method is used to cluster possible parameter sets in order of high probability. Determining the true value by examining the candidates of the parameter sets obtained in this manner can help solve the inherent inverse problem associated with scattering data.
Spectral Density Classification For Environment Spectroscopy
Creators: name: Barr, Jessica
name: Zicari, Giorgio
name: Ferraro, Alessandro
name: Paternostro, Mauro
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Physics (quant-ph)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: Spectral densities encode the relevant information characterising the system-environment interaction in an open-quantum system problem. Such information is key to determining the system's dynamics. In this work, we leverage the potential of machine learning techniques to reconstruct the features of the environment. Specifically, we show that the time evolution of a system observable can be used by an artificial neural network to infer the main features of the spectral density. In particular, for relevant examples of spin-boson models, we can classify with high accuracy the Ohmicity parameter of the environment as either Ohmic, sub-Ohmic or super-Ohmic, thereby distinguishing between different forms of dissipation.
description: 11+2 pages, 9 figures, RevTeX4-2 Close to the published version in Mach. Learn.: Sci. Technol
Supplementary Material from Tanning of the tarsal and mandibular cuticle in adult anax imperator (insecta: odonata) during the emergence sequence
Creators: name: Preuss, Anika
name: Appel, Esther
name: Gorb, Stanislav N.
name: Büsse, Sebastian
Publisher: name: The Royal Society
Year: 2024
Subjects: classificationCode: 320203
subject: Clinical microbiology
classificationCode: 400302
subject: Biomaterials

description: Figures S1 - S11 including captions
An Efficient Anchor-free Universal Lesion Detection in CT-scans
Creators: name: Sheoran, Manu
name: Dani, Meghal
name: Sharma, Monika
name: Vig, Lovekesh
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: Existing universal lesion detection (ULD) methods utilize compute-intensive anchor-based architectures which rely on predefined anchor boxes, resulting in unsatisfactory detection performance, especially in small and mid-sized lesions. Further, these default fixed anchor-sizes and ratios do not generalize well to different datasets. Therefore, we propose a robust one-stage anchor-free lesion detection network that can perform well across varying lesions sizes by exploiting the fact that the box predictions can be sorted for relevance based on their center rather than their overlap with the object. Furthermore, we demonstrate that the ULD can be improved by explicitly providing it the domain-specific information in the form of multi-intensity images generated using multiple HU windows, followed by self-attention based feature-fusion and backbone initialization using weights learned via self-supervision over CT-scans. We obtain comparable results to the state-of-the-art methods, achieving an overall sensitivity of 86.05% on the DeepLesion dataset, which comprises of approximately 32K CT-scans with lesions annotated across various body organs.
description: 4 Pages, 2 figures, 2 tables. Paper accepted at IEEE International Symposium on Biomedical Imaging (ISBI'22)
‘Cold spots’ of Urban Infrastructure
Creators: name: Moss, Timothy
Publisher: name: Humboldt-Universität zu Berlin
Year: 2008
Subjects: subject: 300 Sozialwissenschaften

description: This paper explores the unfamiliar, but increasingly prevalent problem of overcapacity in urban infrastructure systems in regions subject to dramatic socio-economic restructuring. Taking the case of water supply and wastewater disposal systems in Eastern Germany as an example, it examines firstly how infrastructure overcapacities have emerged since reunification in 1990, resulting from sharply declining water consumption in the wake of ‘shrinking’ processes but also from infrastructure expansion. Secondly, the paper analyses what impact chronic overcapacity is having on the governance of water infrastructure systems. This empirical analysis is framed conceptually in terms of the current debate on the changing relationship between infrastructures and the localities they serve. It assesses specifically how far and in what ways the phenomenon of overcapacity in technical networks resonates with the ‘splintering urbanism’ thesis developed by Stephen Graham and Simon Marvin. It argues that the serious technical and economic problems posed by overcapacity are intensifying spatial disparities in service quality and price and – more fundamentally –are challenging the supply-driven ‘modern infrastructural ideal’ of universal and equitable water services.
Continual Normalization: Rethinking Batch Normalization for Online Continual Learning
Creators: name: Pham, Quang
name: Liu, Chenghao
name: Hoi, Steven
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Existing continual learning methods use Batch Normalization (BN) to facilitate training and improve generalization across tasks. However, the non-i.i.d and non-stationary nature of continual learning data, especially in the online setting, amplify the discrepancy between training and testing in BN and hinder the performance of older tasks. In this work, we study the cross-task normalization effect of BN in online continual learning where BN normalizes the testing data using moments biased towards the current task, resulting in higher catastrophic forgetting. This limitation motivates us to propose a simple yet effective method that we call Continual Normalization (CN) to facilitate training similar to BN while mitigating its negative effect. Extensive experiments on different continual learning algorithms and online scenarios show that CN is a direct replacement for BN and can provide substantial performance improvements. Our implementation is available at \url{https://github.com/phquang/Continual-Normalization}.
Deep Learning for Steganalysis of Diverse Data Types: A review of methods, taxonomy, challenges and future directions
Creators: name: Kheddar, Hamza
name: Hemis, Mustapha
name: Himeur, Yassine
name: Megías, David
name: Amira, Abbes
Publisher: name: arXiv
Year: 2023
Subjects: subject: Cryptography and Security (cs.CR)
subject: Artificial Intelligence (cs.AI)
subject: Machine Learning (cs.LG)
subject: Multimedia (cs.MM)
subject: Sound (cs.SD)
subject: Audio and Speech Processing (eess.AS)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Steganography and steganalysis are two interrelated aspects of the field of information security. Steganography seeks to conceal communications, whereas steganalysis is aimed to either find them or even, if possible, recover the data they contain. Steganography and steganalysis have attracted a great deal of interest, particularly from law enforcement. Steganography is often used by cybercriminals and even terrorists to avoid being captured while in possession of incriminating evidence, even encrypted, since cryptography is prohibited or restricted in many countries. Therefore, knowledge of cutting-edge techniques to uncover concealed information is crucial in exposing illegal acts. Over the last few years, a number of strong and reliable steganography and steganalysis techniques have been introduced in the literature. This review paper provides a comprehensive overview of deep learning-based steganalysis techniques used to detect hidden information within digital media. The paper covers all types of cover in steganalysis, including image, audio, and video, and discusses the most commonly used deep learning techniques. In addition, the paper explores the use of more advanced deep learning techniques, such as deep transfer learning (DTL) and deep reinforcement learning (DRL), to enhance the performance of steganalysis systems. The paper provides a systematic review of recent research in the field, including data sets and evaluation metrics used in recent studies. It also presents a detailed analysis of DTL-based steganalysis approaches and their performance on different data sets. The review concludes with a discussion on the current state of deep learning-based steganalysis, challenges, and future research directions.
Directional fault classification for correlated High-Dimensional data streams using hidden Markov models
Creators: name: He, Yan
name: Kang, Yicheng
name: Tsung, Fugee
name: Xiang, Dongdong
Publisher: name: Taylor & Francis
Year: 2023
Subjects: Neuroscience
Biotechnology
Mathematical Sciences not elsewhere classified

description: Modern manufacturing systems are often installed with sensor networks which generate high-dimensional data at high velocity. These data streams offer valuable information about the industrial system’s real-time performance. If a shift occurs in the manufacturing process, fault diagnosis based on the data streams becomes a fundamental task as it identifies the affected data streams and provides insights into the root cause. Existing fault diagnostic methods either ignore the correlation between different streams or fail to determine the shift directions. In this paper, we propose a directional fault classification procedure that incorporates the between-stream correlations. We suggest a three-state hidden Markov model that captures the correlation structure and enables inference about the shift direction. We show that our procedure is optimal in the sense that it minimizes the expected number of false discoveries while controlling the proportion of missed signals at a desired level. We also propose a deconvolution-expectation-maximization (DEM) algorithm for estimating the model parameters and establish the asymptotic optimality for the data-driven version of our procedure. Numerical comparisons with an existing approach and an application to a semiconductor production study show that the proposed procedure works well in practice.
Additional file 1 of Genetic diversity analysis of Chinese Leishmania isolates and development of L. donovani complex-specific markers by RAPD
Creators: name: Yuan, Dongmei
name: Qin, Hanxiao
name: Chen, Dali
name: Chen, Jianping
Publisher: name: figshare
Year: 2021
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 1: Table S1. Genetic similarity matrix among the 17 Leishmania strains by NTSYS.
Rigid Transformations for Stabilized Lower Dimensional Space to Support Subsurface Uncertainty Quantification and Interpretation
Creators: name: Mabadeje, Ademide O.
name: Pyrcz, Michael J.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Subsurface datasets inherently possess big data characteristics such as vast volume, diverse features, and high sampling speeds, further compounded by the curse of dimensionality from various physical, engineering, and geological inputs. Among the existing dimensionality reduction (DR) methods, nonlinear dimensionality reduction (NDR) methods, especially Metric-multidimensional scaling (MDS), are preferred for subsurface datasets due to their inherent complexity. While MDS retains intrinsic data structure and quantifies uncertainty, its limitations include unstabilized unique solutions invariant to Euclidean transformations and an absence of out-of-sample points (OOSP) extension. To enhance subsurface inferential and machine learning workflows, datasets must be transformed into stable, reduced-dimension representations that accommodate OOSP.
 Our solution employs rigid transformations for a stabilized Euclidean invariant representation for LDS. By computing an MDS input dissimilarity matrix, and applying rigid transformations on multiple realizations, we ensure transformation invariance and integrate OOSP. This process leverages a convex hull algorithm and incorporates loss function and normalized stress for distortion quantification. We validate our approach with synthetic data, varying distance metrics, and real-world wells from the Duvernay Formation. Results confirm our method's efficacy in achieving consistent LDS representations. Furthermore, our proposed "stress ratio" (SR) metric provides insight into uncertainty, beneficial for model adjustments and inferential analysis. Consequently, our workflow promises enhanced repeatability and comparability in NDR for subsurface energy resource engineering and associated big data workflows.
description: 30 pages, 17 figures
Contribution of the Temperature of the Objects to the Problem of Thermal Imaging Focusing
Creators: name: Espinosa-Duró, Virginia
name: Faundez-Zanuy, Marcos
name: Mekyska, Jiri
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: When focusing an image, depth of field, aperture and distance from the camera to the object, must be taking into account, both, in visible and in infrared spectrum. Our experiments reveal that in addition, the focusing problem in thermal spectrum is also hardly dependent of the temperature of the object itself (and/or the scene).
description: 5 pages, published in 2012 IEEE International Carnahan Conference on Security Technology (ICCST), 15-18 Oct. 2012 Boston (MA) USA. arXiv admin note: text overlap with arXiv:2203.08513