cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases
Creators: name: Daniel, Thomas
name: Casenave, Fabien
name: Akkari, Nissrine
name: Ketata, Ali
name: Ryckelynck, David
Publisher: name: arXiv
Year: 2021
Subjects: subject: Numerical Analysis (math.NA)
subject: FOS: Mathematics

description: Nonlinear model order reduction has opened the door to parameter optimization and uncertainty quantification in complex physics problems governed by nonlinear equations. In particular, the computational cost of solving these equations can be reduced by means of local reduced-order bases. This article examines the benefits of a physics-informed cluster analysis for the construction of cluster-specific reduced-order bases. We illustrate that the choice of the dissimilarity measure for clustering is fundamental and highly affects the performances of the local reduced-order bases. It is shown that clustering with an angle-based dissimilarity on simulation data efficiently decreases the intra-cluster Kolmogorov $N$-width. Additionally, an a priori efficiency criterion is introduced to assess the relevance of a ROM-net, a methodology for the reduction of nonlinear physics problems introduced in our previous work in [T. Daniel, F. Casenave, N. Akkari, D. Ryckelynck, Model order reduction assisted by deep neural networks (ROM-net), Advanced Modeling and Simulation in Engineering Sciences 7 (16), 2020]. This criterion also provides engineers with a very practical method for ROM-nets' hyperparameters calibration under constrained computational costs for the training phase. On five different physics problems, our physics-informed clustering strategy significantly outperforms classic strategies for the construction of local reduced-order bases in terms of projection errors.
Active learning and element embedding approach in neural networks for infinite-layer versus perovskite oxides
Creators: name: Sahinovic, Armin
name: Geisler, Benjamin
Publisher: name: arXiv
Year: 2021
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: Combining density functional theory simulations and active learning of neural networks, we explore formation energies of oxygen vacancy layers, lattice parameters, and their correlations in infinite-layer versus perovskite oxides across the periodic table, and place the superconducting nickelate and cuprate families in a comprehensive statistical context. We show that neural networks predict these observables with high precision, using only 30-50% of the data for training. Element embedding autonomously identifies concepts of chemical similarity between the individual elements in line with human knowledge. Based on the fundamental concepts of entropy and information, active learning composes the training set by an optimal strategy without a priori knowledge and provides systematic control over the prediction accuracy. This offers key ingredients to considerably accelerate scans of large parameter spaces and exemplifies how artificial intelligence may assist on the quantum scale in finding novel materials with optimized properties.
description: 4 pages, 5 figures
Doubled Moiré Flat Bands in Double-twisted Few Layer Graphite
Creators: name: Ma, Zhen
name: Li, Shuai
name: Lu, Ming
name: Xu, Dong-Hui
name: Gao, Jin-Hua
name: Xie, X. C.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We study the electronic structure of a double-twisted few layer graphite (DTFLG), which consists of three few layer graphite (FLG), i.e. ABA-stacked graphene multilayer, stacked with two twist angles. We consider two categories of DTFLG, alternately twisted case and chirally twisted one, according to the rotation direction of the two twist angles. We show that, once the middle FLG of DTFLG is not thinner than trilayer, both kinds of DTFLG can remarkably host two pairs of degenerate moiré flat bands (MFBs) at $E_f$, twice that of the magic angle twisted bilayer graphene (TBG). The doubled MFBs of DTFLG lead to doubled DOS at $E_f$, which implies much stronger correlation effects than the TBG. The degeneracy of MFBs can be lifted by a perpendicular electric field, and the isolated MFBs have nonzero valley Chern number. We also reveal the peculiar wave function patterns of the MFBs in the DTFLG. Our results establish a new family of moiré systems that have the much larger DOS at $E_f$, and thus possible much stronger correlation effects.
description: 6 pages, 4 figures
Automated Olfactory Bulb Segmentation on High Resolutional T2-Weighted MRI
Creators: name: Estrada, Santiago
name: Lu, Ran
name: Diers, Kersten
name: Zeng, Weiyi
name: Ehses, Philipp
name: Stöcker, Tony
name: Breteler, Monique M. B
name: Reuter, Martin
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: The neuroimage analysis community has neglected the automated segmentation of the olfactory bulb (OB) despite its crucial role in olfactory function. The lack of an automatic processing method for the OB can be explained by its challenging properties. Nonetheless, recent advances in MRI acquisition techniques and resolution have allowed raters to generate more reliable manual annotations. Furthermore, the high accuracy of deep learning methods for solving semantic segmentation problems provides us with an option to reliably assess even small structures. In this work, we introduce a novel, fast, and fully automated deep learning pipeline to accurately segment OB tissue on sub-millimeter T2-weighted (T2w) whole-brain MR images. To this end, we designed a three-stage pipeline: (1) Localization of a region containing both OBs using FastSurferCNN, (2) Segmentation of OB tissue within the localized region through four independent AttFastSurferCNN - a novel deep learning architecture with a self-attention mechanism to improve modeling of contextual information, and (3) Ensemble of the predicted label maps. The OB pipeline exhibits high performance in terms of boundary delineation, OB localization, and volume estimation across a wide range of ages in 203 participants of the Rhineland Study. Moreover, it also generalizes to scans of an independent dataset never encountered during training, the Human Connectome Project (HCP), with different acquisition parameters and demographics, evaluated in 30 cases at the native 0.7mm HCP resolution, and the default 0.8mm pipeline resolution. We extensively validated our pipeline not only with respect to segmentation accuracy but also to known OB volume effects, where it can sensitively replicate age effects.
title: Transitional Justice and Civilian Conflict Transformation
Creators: name: Schell-Faucon, Stephanie
name: Kayser-Whande, Undine
Publisher: name: Philipps-Universität Marburg
Year: 2008
Subjects: subject: Political science
subject: FOS: Political science
subject: Politik

description: This study looks at the current state of transitional justice literature, research and practice, with a special focus on the non-judicial interventions in the field. The authors explore potential future research questions from a practice perspective and based on their own insights as practitioners. Using experiences from development and conflict transformation/ peacebuilding work they seek to embed transitional justice interventions in a holistic view of social transformation processes after violent conflict. In particular the paper offers a sharpened focus on the so-called ‘soft issues’ of transitioning - the social, cultural and psycho-emotional phenomena often seen as peripheral but, in fact, central to making or breaking the success of transitional justice interventions. Starting with a brief history and overview of the aims and definitions of transitional justice, the authors outline the conventionally mentioned non-judicial instruments of transitional justice such as truth commissions, reparations, restoration and social repair as well as institutional reform. They expand in some more depth on insights from critical trauma work, memory work and dialogue/encounter work making links to the long-term German experiences of dealing with the past. The study further explores a range of crosscutting issues - conflict contexts and the conditions of peace processes; global norms and local agency; the role of local resources, neo-traditional approaches and questions of identity, subjectivity and gender - thus tracing potential synergies between the fields of civilian conflict transformation and transitional justice.
title: Combined Use of High-field static MRI and weight bearing low-field dynamic MRI in the pre-surgical assessment of meniscofemoral instability in professional athletes.
Creators: name: Giannini, Silvana
Publisher: name: European Society of Muscoskeletal Radiology
Year: 2016
Subjects: subject: Musculoskeletal system
subject: MR
subject: Diagnostic procedure
subject: Athletic injuries

description: Purpose Methods and Materials Results Conclusion References Personal Information
description: Purpose: We have tried to show the use of a weight bearing dynamic exam in the assessment of meniscal dislocation and meniscofemoral discontinuity after a sport trauma, to evaluate the possible surgical...
Community effectiveness of indoor spraying as a dengue vector control method: A systematic review
Creators: name: Runge-Ranzinger, Silvia
name: Ward, Tara
name: Manrique, Pablo
name: Boyce, Ross
name: Maoz, Dorit
name: Toledo, Joao
name: Samuel, Moody
name: Horstick, Olaf
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2017

description: The prevention and control of dengue rely mainly on vector control methods, including indoor residual spraying (IRS) and indoor space spraying (ISS). This study aimed to systematically review the available evidence on community effectiveness of indoor spraying.
Discrete Boltzmann Modeling of Plasma Shock Wave
Creators: name: Liu, Zhipeng
name: Song, Jiahui
name: Xu, Aiguo
name: Zhang, Yudong
name: Xie, Kan
Publisher: name: arXiv
Year: 2021
Subjects: subject: Plasma Physics (physics.plasm-ph)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Computational Physics (physics.comp-ph)
subject: Fluid Dynamics (physics.flu-dyn)
subject: FOS: Physical sciences

description: Plasma shock waves widely exist and play an important role in high-energy-density environment, especially in the inertial confinement fusion. Due to the large gradient of macroscopic physical quantities and the coupled thermal, electrical, magnetic and optical phenomena, there exist not only hydrodynamic non-equilibrium (HNE) effects, but also strong thermodynamic non-equilibrium (TNE) effects around the wavefront. In this work, a two-dimensional single-fluid discrete Boltzmann model is proposed to investigate the physical structure of ion shock. The electron is assumed inertialess and always in thermodynamic equilibrium. The Rankine-Hugoniot relations for single fluid theory of plasma shock wave is derived. It is found that the physical structure of shock wave in plasma is significantly different from that in normal fluid and somewhat similar to that of detonation wave from the sense that a peak appears in the front. The non-equilibrium effects around the shock front become stronger with increasing Mach number. The charge of electricity deviates oppositely from neutrality in upstream and downstream of the shock wave. The large inertia of the ions causes them to lag behind, so the wave front charge is negative and the wave rear charge is positive. The variations of HNE and TNE with Mach number are numerically investigated. The characteristics of TNE can be used to distinguish plasma shock wave from detonation wave.
description: Accepted by Part C: Journal of Mechanical Engineering Science
Additional file 1 of Soil pH enhancement and alterations in nutrient and Bacterial Community profiles following Pleioblastus amarus expansion in tea plantations
Creators: name: Fan, Lili
name: Chen, Shuanglin
name: Guo, Ziwu
name: Hu, Ruicai
name: Yao, Liangjin
Publisher: name: figshare
Year: 2024
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Ecology

description: Supplementary Material 1
OpenQASM 3: A broader and deeper quantum assembly language
Creators: name: Cross, Andrew W.
name: Javadi-Abhari, Ali
name: Alexander, Thomas
name: de Beaudrap, Niel
name: Bishop, Lev S.
name: Heidel, Steven
name: Ryan, Colm A.
name: Sivarajah, Prasahnt
name: Smolin, John
name: Gambetta, Jay M.
name: Johnson, Blake R.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Quantum assembly languages are machine-independent languages that traditionally describe quantum computation in the circuit model. Open quantum assembly language (OpenQASM 2) was proposed as an imperative programming language for quantum circuits based on earlier QASM dialects. In principle, any quantum computation could be described using OpenQASM 2, but there is a need to describe a broader set of circuits beyond the language of qubits and gates. By examining interactive use cases, we recognize two different timescales of quantum-classical interactions: real-time classical computations that must be performed within the coherence times of the qubits, and near-time computations with less stringent timing. Since the near-time domain is adequately described by existing programming frameworks, we choose in OpenQASM 3 to focus on the real-time domain, which must be more tightly coupled to the execution of quantum operations. We add support for arbitrary control flow as well as calling external classical functions. In addition, we recognize the need to describe circuits at multiple levels of specificity, and therefore we extend the language to include timing, pulse control, and gate modifiers. These new language features create a multi-level intermediate representation for circuit development and optimization, as well as control sequence implementation for calibration, characterization, and error mitigation.
description: 60 pages, 17 figures
title: Ultrasound evaluation of knee trauma
Creators: name: Vasilevska Nikodinovska, Violeta
Publisher: name: European Society of Muscoskeletal Radiology
Year: 2016
Subjects: subject: Athletic injuries
subject: Trauma
subject: Education
subject: Diagnostic procedure
subject: Ultrasound
subject: Musculoskeletal soft tissue
subject: Musculoskeletal joint
subject: Musculoskeletal bone

description: Learning objectives Background Imaging findings OR Procedure Details Conclusion References Personal Information
description: Learning objectives: To describe the normal ultrasound anatomy of the visible knee structures. To show the most common acute traumatic changes and chronic microtrauma-overuse syndromes of the knee structures. To identify the advantages of the...
Scaled lattice rules for integration on $\mathbb{R}^d$ achieving higher-order convergence with error analysis in terms of orthogonal projections onto periodic spaces
Creators: name: Nuyens, Dirk
name: Suzuki, Yuya
Publisher: name: arXiv
Year: 2021
Subjects: subject: Numerical Analysis (math.NA)
subject: FOS: Mathematics
subject: 65D30, 65D32, 65Y20

description: We introduce a new method to approximate integrals $\int_{\mathbb{R}^d} f(\boldsymbol{x}) \, \mathrm{d} \boldsymbol{x}$ which simply scales lattice rules from the unit cube $[0,1]^d$ to properly sized boxes on $\mathbb{R}^d$, hereby achieving higher-order convergence that matches the smoothness of the integrand function $f$ in a certain Sobolev space of dominating mixed smoothness. Our method only assumes that we can evaluate the integrand function $f$ and does not assume a particular density nor the ability to sample from it. In particular, for the theoretical analysis we show a new result that the method of adding Bernoulli polynomials to a function to make it "periodic" on a box without changing its integral value over the box, is equivalent to an orthogonal projection from a well chosen Sobolev space of dominating mixed smoothness to an associated periodic Sobolev space of the same dominating mixed smoothness, which we call a Korobov space. We note that the Bernoulli polynomial method is often not used because of its excessive computational complexity and also here we only make use of it in our theoretical analysis. We show that our new method of applying scaled lattice rules to increasing boxes can be interpreted as orthogonal projections with decreasing projection error. Such a method would not work on the unit cube since then the committed error caused by non-periodicity of the integrand would be constant, but for integration on the Euclidean space we can use the certain decay towards zero when the boxes grow. Hence we can bound the truncation error as well as the projection error and show higher-order convergence in applying scaled lattice rules for integration on Euclidean space. We illustrate our theoretical analysis by numerical experiments which confirm our findings.
description: 40 pages, 5 figures
Remarkable enhancement in catechol sensing by the decoration of selective transition metals in biphenylene sheet: A systematic first-principles study
Creators: name: Mahamiya, Vikram
name: Dewangan, Juhee
name: Shukla, Alok
name: Chakraborty, Brahmananda
Publisher: name: arXiv
Year: 2022
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Chemical Physics (physics.chem-ph)
subject: FOS: Physical sciences

description: Motivated by the recent successful synthesis of biphenylene structure [Science 372, (2021), 852], we have explored the sensing properties of this material towards the catechol biomolecule by performing the first-principles density functional theory and molecular dynamics simulations. Pristine biphenylene sheet adsorbs catechol molecule with a binding energy of -0.35 eV, which can be systematically improved by decorating the transition metals (Ag, Au, Pd, and Ti) at various possible sites of biphenylene. It is observed that the catechol molecule is adsorbed on Pd and Ti-decorated biphenylene sheets with strong adsorption energies of -1.00 eV and -2.54 eV, respectively. The interaction of the catechol molecule with biphenylene and metal-decorated biphenylene is due to the charge transfer from the O-2p orbitals of the catechol molecule to the C-2p orbitals of biphenylene and d-orbitals of metals in metal-decorated biphenylene, respectively. From the Bader charge calculation, we found that 0.05e amount of charge is transferred from the catechol molecule to pristine biphenylene, which gets almost double (~0.1e) for the Ti-decorated biphenylene sheet. The diffusion energy barrier for the clustering of the Pd and Ti atoms comes out to be 2.39 eV and 4.29 eV, computed by performing the climbing-image nudged elastic band calculations. We found that the catechol molecule gets desorbed from the pristine biphenylene sheet even at 100 K but remains attached to metal (Pd, Ti) decorated biphenylene sheets at room temperature by performing the ab-initio molecular dynamics simulations. The Ti-decorated biphenylene sheet has more sensitivity toward catechol adsorption while the Pd-decorated biphenylene sheet has a suitable recovery time at 500 K. The results suggest that the Pd and Ti-decorated biphenylene sheets are promising materials for catechol detection.
description: main article 29 pages, 10 figures (included); supporting information 5 pages, 5 figures (included), J. Phys. D (in press)
Clonal diversity and zoonotic potential of MDR Escherichia coli isolated from poultry at different age intervals
Creators: name: Anjum, F.
name: Maherchandani, S.
name: Gahlot, K.
name: Purva, M.
Publisher: name: Taylor & Francis
Year: 2023
Subjects: subject: Biochemistry
subject: Microbiology
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Biotechnology
subject: Evolutionary Biology
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Infectious Diseases
subject: FOS: Health sciences

description: 1. A pool of 480 E. coli isolates of poultry (broilers and ducks) representing different time intervals (0, 10, 20 and 30 days) was selected for ribotyping and used to determine polymorphism of 16-23S ribosomal RNA intergenic space. All the isolates were multidrug-resistant (MDR). 2. Out of these, 10 isolates were tested for MLST (MultiLocus Sequence Typing) among which novel allelic combinations and therefore new sequence types were identified in seven isolates. 3. This work showed the changes in E. coli strains structure at farm level and individual bird level in host species raised on organised farms with similar parental lineage and environmental housing. The statistical results showed that the structure of variation is very different by farm, supporting a strong effect of location, which confirms the temporal clustering. 4. There were significant differences between E. coli strains in chickens and ducks, indicating host specificity of the E. coli strains. 5. Some of the pathogenic E. coli strains found using MLST belonged to ST735, ST2796 and a pandemic clone ST752 of ST10 clonal complex. The results strongly suggested the clonal expansion and establishment of specific MDR clones that have zoonotic relevance.
Switching off: the phenotypic transition to the uninduced state of the lactose uptake pathway
Creators: name: Bhogale, Prasanna M.
name: Sorg, Robin A.
name: Veening, Jan-Willem
name: Berg, Johannes
Publisher: name: arXiv
Year: 2021
Subjects: subject: Molecular Networks (q-bio.MN)
subject: FOS: Biological sciences

description: The lactose uptake-pathway of E. coli is a paradigmatic example of multistability in gene-regulatory circuits. In the induced state of the lac-pathway, the genes comprising the lac-operon are transcribed, leading to the production of proteins which import and metabolize lactose. In the uninduced state, a stable repressor-DNA loop frequently blocks the transcription of the lac-genes. Transitions from one phenotypic state to the other are driven by fluctuations, which arise from the random timing of the binding of ligands and proteins. This stochasticity affects transcription and translation, and ultimately molecular copy numbers. Our aim is to understand the transition from the induced to the uninduced state of the lac-operon. We use a detailed computational model to show that repressor-operator binding/unbinding, fluctuations in the total number of repressors, and inducer-repressor binding/unbinding all play a role in this transition. Based on the timescales on which these processes operate, we construct a minimal model of the transition to the uninduced state and compare the results with simulations and experimental observations. The induced state turns out to be very stable, with a transition rate to the uninduced state lower than $2 \times 10^{-9}$ per minute. In contrast to the transition to the induced state, the transition to the uninduced state is well described in terms of a 2D diffusive system crossing a barrier, with the diffusion rates emerging from a model of repressor unbinding.
description: 10 pages, 6 figures. For SI contact corresponding author
title: Pearls and pitfalls of odontoid peg fractures in paediatric patients
Creators: name: Kumar, Raekha
Publisher: name: European Society of Muscoskeletal Radiology
Year: 2016
Subjects: subject: Musculoskeletal spine
subject: Paediatric
subject: Plain radiographic studies
subject: CT
subject: Education
subject: Education and training

description: Learning objectives Background Imaging findings OR Procedure Details Conclusion References Personal Information
description: Learning objectives: Understand the anatomy and development of the odontoid peg, including normal variants. Recognise the common types of PEG fractures and their associated ligamentous...
title: Primary Rosai-Dorfman Disease of the Bone – A Rare Presentation of a Rare Disease
Creators: name: Pawley, Christopher
Publisher: name: European Society of Muscoskeletal Radiology
Year: 2016
Subjects: subject: Haematologic diseases
subject: Radiation therapy / Oncology
subject: Biopsy
subject: Plain radiographic studies
subject: PET-CT
subject: MR
subject: Musculoskeletal bone
subject: Haematologic
subject: Bones

description: Learning objectives Background Imaging findings OR Procedure Details Conclusion References Personal Information
description: Learning objectives: Introduce histiocystic disorders. Outline Rosai-Dorfman Disease (RDD). Present a rare manifestation of primary osseous RDD of the navicular...
Community effectiveness of pyriproxyfen as a dengue vector control method: A systematic review
Creators: name: Velayudhan, Raman
name: Toledo, Joao
name: Runge-Ranzinger, Silvia
name: Boyce, Ross
name: Horstick, Olaf
name: Müller, Pie
name: Samuel, Moody
name: Ward, Tara
name: Maoz, Dorit
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2017

description: Vector control is the only widely utilised method for primary prevention and control of dengue. The use of pyriproxyfen may be promising, and autodissemination approach may reach hard to reach breeding places. It offers a unique mode of action (juvenile hormone mimic) and as an additional tool for the management of insecticide resistance among Aedes vectors. However, evidence of efficacy and community effectiveness (CE) remains limited.
Biomarker discovery and authentication of cold-slaughtered chicken through classical analytical procedures and mass spectrometry based proteomic approaches
Creators: name: Belore, B. M.
name: Maheswarappa, N. B.
name: Kulkarni, V. V.
name: Banerjee, R.
name: Hazarika, P.
name: Dasoju, S.
name: Mishra, B. P.
name: Govindaiah, P. M.
Publisher: name: Taylor & Francis
Year: 2023
Subjects: subject: Biochemistry
subject: Medicine
subject: Biotechnology
subject: Environmental Sciences not elsewhere classified
subject: Chemical Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Mathematical Sciences not elsewhere classified
subject: Cancer
subject: Science Policy
subject: Infectious Diseases
subject: FOS: Health sciences

description: 1. This study evaluated the suitability of routine analytical procedures and used mass spectrometry based proteomic approaches to distinguish meat from dead chicken/ cold slaughtered birds (CS), electrically stunned and slaughtered birds, as per standard protocols (ES), and birds slaughtered according to halal guidelines (HS). 2. Meat from CS birds had lower (P < 0.05) pH, water holding capacity and higher (P < 0.05) lipid oxidation, haem iron content, residual blood and total viable counts relative to ES and HS meat indicating poor quality. 3. The results demonstrated the presence of unique protein bands on SDS-PAGE only in CS meat that can be used for routine screening. 4. Protein analysis using MALDI-TOF mass spectrometry has identified haemoglobin subunit alpha-A and alpha-D; Adenylate kinase isoenzyme 1 as reliable and stable marker proteins for authentication of dead chicken meat under raw and cooked conditions and halal slaughtered chicken, respectively. 5. The methods used may be employed by the food safety and regulatory agencies for regular screening of meat quality and to authenticate CS or HS chicken.
Testing non-associative quantum mechanics
Creators: name: Bojowald, Martin
name: Brahma, Suddhasattwa
name: Buyukcam, Umut
Publisher: name: arXiv
Year: 2015
Subjects: subject: Quantum Physics (quant-ph)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: The familiar concepts of state vectors and operators in quantum mechanics rely on associative products of observables. However, these notions do not apply to some exotic systems such as magnetic monopoles, which have long been known to lead to non-associative algebras. Their quantum physics has remained obscure. This letter presents the first derivation of potentially testable physical results in non-associative quantum mechanics, based on effective potentials. They imply new effects which cannot be mimicked in usual quantum mechanics with standard magnetic fields.
description: 5 pages; v2: new references, extended discussion; v3: erratum included
title: Lumbar CT-guided steroid infiltration on the refractory back pain.
Creators: name: Diez Renovales, Fernando
Publisher: name: European Society of Muscoskeletal Radiology
Year: 2016
Subjects: subject: Hernia
subject: Puncture
subject: CT
subject: Musculoskeletal spine
subject: Interventional non-vascular

description: Purpose Methods and Materials Results Conclusion References Personal Information
description: Purpose: Low back pain of mechanical origin is a major cause of disability and surgical intervention ( IQ ) . Lumbar steroid injection can accelerate the recovery process and sometimes Avoid IQ. Our purpose in the present study is: -To describe the procedure...
Washington Post/Kaiser Family Foundation Poll: Survey on Political Rallygoing and Activism
Creators: name: Kaiser Family Foundation
name: Washington Post
Publisher: name: Roper Center for Public Opinion Research
Year: 2019

description: Political rally or protest attendance in past two years (2); following government and public affairs (1); considers self activist (1); causes or issues for which respondent has attended protest or rally (27); most important issue for respondent (1); rallies or protests attended focused mostly on local/national issues (1); amount of involvement in political activities in past two years vs. over two years ago (1); age of first political event attendance (1); reasons for not attending any protests or rallies (6); has/has not done various political activities in past two years (7); political activity on social media (4); believe they can make more difference on local/national issues (1); protesters today vs. protesters 50 years ago, in late 1960s (4); protesting rights (1); appropriateness of various protest activities (4); people should/should not have right to peacefully protest in support of Nazis, white supremacy (1); oppose/support various issues (10); increasing racial and ethnic diversity is threatening/enriching American culture (1); political party preference (3); hopeful/fearful about America’s future (1); confidence in people holding or running for public office (1); trust in men vs. women as public officials (1); trust in American people to make judgments under democratic system (1); trust in mass media (1); public officials do/do not care about what people like respondent think (1); preferred political party’s representation of respondent's views and interests (2); influence of conservative activists on Republican party (1); influence of liberal activists on Democratic party (1); prefers elected officials who compromise to get things done/stick to positions even if it means gridlock (1); tone of various groups' political discussions (3); amount of political involvement next year (1); working or volunteering for political party or candidate's campaign ahead of 2018 congressional election (2); President Donald Trump job performance (1); Republicans in Congress should follow Trump's leadership/lead party in different direction (1); registered to vote (1); voting frequency (1); voting in congressional election (3); vote in last presidential election (2).
Learning through structure: towards deep neuromorphic knowledge graph embeddings
Creators: name: Chian, Victor Caceres
name: Hildebrandt, Marcel
name: Runkler, Thomas
name: Dold, Dominik
Publisher: name: arXiv
Year: 2021
Subjects: subject: Neural and Evolutionary Computing (cs.NE)
subject: Artificial Intelligence (cs.AI)
subject: Machine Learning (cs.LG)
subject: Neurons and Cognition (q-bio.NC)
subject: FOS: Computer and information sciences
subject: FOS: Biological sciences

description: Computing latent representations for graph-structured data is an ubiquitous learning task in many industrial and academic applications ranging from molecule synthetization to social network analysis and recommender systems. Knowledge graphs are among the most popular and widely used data representations related to the Semantic Web. Next to structuring factual knowledge in a machine-readable format, knowledge graphs serve as the backbone of many artificial intelligence applications and allow the ingestion of context information into various learning algorithms. Graph neural networks attempt to encode graph structures in low-dimensional vector spaces via a message passing heuristic between neighboring nodes. Over the recent years, a multitude of different graph neural network architectures demonstrated ground-breaking performances in many learning tasks. In this work, we propose a strategy to map deep graph learning architectures for knowledge graph reasoning to neuromorphic architectures. Based on the insight that randomly initialized and untrained (i.e., frozen) graph neural networks are able to preserve local graph structures, we compose a frozen neural network with shallow knowledge graph embedding models. We experimentally show that already on conventional computing hardware, this leads to a significant speedup and memory reduction while maintaining a competitive performance level. Moreover, we extend the frozen architecture to spiking neural networks, introducing a novel, event-based and highly sparse knowledge graph embedding algorithm that is suitable for implementation in neuromorphic hardware.
description: Accepted for publication at the International Conference on Neuromorphic Computing (ICNC 2021)
Hybridization of filter and wrapper approaches for the dimensionality reduction and classification of hyperspectral images
Creators: name: Elmaizi, Asma
name: Merzouqi, Maria
name: Sarhrouni, Elkebir
name: hammouch, Ahmed
name: Nacir, Chafik
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: The high dimensionality of hyperspectral images often imposes a heavy computational burden for image processing. Therefore, dimensionality reduction is often an essential step in order to remove the irrelevant, noisy and redundant bands. And consequently, increase the classification accuracy. However, identification of useful bands from hundreds or even thousands of related bands is a nontrivial task. This paper aims at identifying a small set of bands, for improving computational speed and prediction accuracy. Hence, we have proposed a hybrid algorithm through band selection for dimensionality reduction of hyperspectral images. The proposed approach combines mutual information gain (MIG), Minimum Redundancy Maximum Relevance (mRMR) and Error probability of Fano with Support Vector Machine Bands Elimination (SVM-PF). The proposed approach is compared to an effective reproduced filters approach based on mutual information. Experimental results on HSI AVIRIS 92AV3C have shown that the proposed approach outperforms the reproduced filters. Keywords - Hyperspectral images, Classification, band Selection, filter, wrapper, mutual information, information gain.
An energy-based model for neuro-symbolic reasoning on knowledge graphs
Creators: name: Dold, Dominik
name: Garrido, Josep Soler
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: Cryptography and Security (cs.CR)
subject: FOS: Computer and information sciences

description: Machine learning on graph-structured data has recently become a major topic in industry and research, finding many exciting applications such as recommender systems and automated theorem proving. We propose an energy-based graph embedding algorithm to characterize industrial automation systems, integrating knowledge from different domains like industrial automation, communications and cybersecurity. By combining knowledge from multiple domains, the learned model is capable of making context-aware predictions regarding novel system events and can be used to evaluate the severity of anomalies that might be indicative of, e.g., cybersecurity breaches. The presented model is mappable to a biologically-inspired neural architecture, serving as a first bridge between graph embedding methods and neuromorphic computing - uncovering a promising edge application for this upcoming technology.
description: Accepted for publication at the 20th IEEE International Conference on Machine Learning and Applications (ICMLA 2021)
Personal Dosimetry in Direct Pulsed Photon Fields with the Dosepix Detector
Creators: name: Haag, Dennis
name: Schmidt, Sebastian
name: Hufschmidt, Patrick
name: Anton, Gisela
name: Ballabriga, Rafael
name: Behrens, Rolf
name: Campbell, Michael
name: Eberle, Franziska
name: Fuhg, Christian
name: Hupe, Oliver
name: Llopart, Xavier
name: Roth, Jürgen
name: Tlustos, Lukas
name: Wong, Winnie
name: Zutz, Hayo
name: Michel, Thilo
Publisher: name: arXiv
Year: 2021
Subjects: subject: Medical Physics (physics.med-ph)
subject: Instrumentation and Detectors (physics.ins-det)
subject: FOS: Physical sciences

description: First investigations regarding dosimetric properties of the hybrid, pixelated, photon-counting Dosepix detector in the direct beam of a pulsed photon field (RQR8) for the personal dose equivalent $H\mathrm{_p(10)}$ are presented. The influence quantities such as pulse duration and dose rate were varied, and their responses were compared to the legal limits provided in PTB-A 23.2. The variation of pulse duration at a nearly constant dose rate of about 3.7$\,$Sv/h shows a flat response around 1.0 from 3.6$\,$s down to 2$\,$ms. A response close to 1.0 is achieved for dose rates from 0.07$\,$Sv/h to 35$\,$Sv/h for both pixel sizes. Above this dose rate, the large pixels (220$\,μ$m edge length) are below the lower limit. The small pixels (55$\,μ$m edge length) stay within limits up to 704$\,$Sv/h. The count rate linearity is compared to previous results, confirming the saturating count rate for high dose rates.
description: 6 pages, 4 figures. This work was accepted for publication in IEEE Transactions on Nuclear Science
Levels of algebraicity in stable homotopy theories
Creators: name: Ishak, Jocelyne
name: Roitzheim, Constanze
name: Williamson, Jordan
Publisher: name: arXiv
Year: 2021
Subjects: subject: Algebraic Topology (math.AT)
subject: Category Theory (math.CT)
subject: FOS: Mathematics
subject: 55P42, 55U35

description: We study several different notions of algebraicity in use in stable homotopy theory and prove implications between them. The relationships between the different meanings of algebraic are unexpectedly subtle, and we illustrate this with several interesting examples arising from chromatic homotopy theory.
description: 30 pages, to appear in Journal of the LMS
Scale and electroweak first-order phase transitions
Creators: name: Kubo, Jisuke
name: Yamada, Masatoshi
Publisher: name: arXiv
Year: 2015
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: We consider phase transitions in the standard model (SM) without the Higgs mass term, which is coupled through a Higgs portal term to an SM singlet, classically scale-invariant gauge sector with SM singlet scalar fields. At lower energies the gauge-invariant scalar bilinear in the hidden sector forms a condensate, dynamically creating a robust energy scale, which is transmitted through the Higgs portal term to the SM sector. A scale phase transition is a transition between phases with zero and nonzero condensates. An interplay between the EW and scale phase transitions is therefore expected. We find that in a certain parameter space both the electroweak (EW) and scale phase transitions can be a strong first-order phase transition. The result is obtained by means of an effective theory for the condensation of scalar bilinear in the mean field approximation.
description: 21 pages, 6 figures, published version, arXiv admin note: text overlap with arXiv:1505.05971
On the use of galaxies as clocks and the universal expansion
Creators: name: Kjerrgren, Anders Ahlstrom
name: Mortsell, Edvard
Publisher: name: arXiv
Year: 2021
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: We set out to rederive the 8 Hubble parameter values obtained from estimated relative galaxy ages by Simon et al. [Physical Review D, 71, 123001 (2005)]. We find that to obtain the level of precision claimed in $H(z)$, unrealistically small galaxy age uncertainties have to be assumed. Also, some parameter values will be correlated. In our analysis we find that the uncertainties in the Hubble parameter values are significantly larger when 8 independent $H(z)$ are obtained using Monte Carlo sampling. Smaller uncertainties can be obtained using Gaussian processes, but at the cost of strongly correlated results. We do not obtain any useful constraints on the Hubble parameter from the galaxy data employed.
description: 8 pages, 10 figures. Matches version published in MNRAS
title: MR imaging features of facet joint septic arthritis and correlation with evidence of systemic and synchronous spinal infection
Creators: name: Peachey, Thomas
Publisher: name: European Society of Muscoskeletal Radiology
Year: 2016
Subjects: subject: Infection
subject: Abscess
subject: Biopsy
subject: MR
subject: Musculoskeletal system
subject: Musculoskeletal spine

description: Purpose Methods and Materials Results Conclusion References Personal Information
description: Purpose: Facet joint septic arthritis is an uncommon manifestation of spinal infection. Failure to recognise the diagnosis can lead to prolonged back pain and potentially progressive spinal sepsis. Small case series, mainly describing lumbar facet joint...
Dissecting the human serum antibody response to secondary dengue virus infections
Creators: name: Miley, Michael J.
name: Patel, Bhumi
name: de Silva, Aravinda M.
name: Montoya, Magelda
name: Harris, Eva
name: Longo, Patti
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2017

description: Dengue viruses (DENVs) are mosquito-borne flaviviruses and the causative agents of dengue fever and dengue hemorrhagic fever. As there are four serotypes of DENV (DENV1-4), people can be infected multiple times, each time with a new serotype. Primary infections stimulate antibodies that mainly neutralize the serotype of infection (type-specific), whereas secondary infections stimulate responses that cross-neutralize 2 or more serotypes. Previous studies have demonstrated that neutralizing antibodies induced by primary infections recognize tertiary and quaternary structure epitopes on the viral envelope (E) protein that are unique to each serotype. The goal of the current study was to determine the properties of neutralizing antibodies induced after secondary infection with a different (heterotypic) DENV serotypes. We evaluated whether polyclonal neutralizing antibody responses after secondary infections consist of distinct populations of type-specific antibodies to each serotype encountered or a new population of broadly cross-neutralizing antibodies. We observed two types of responses: in some individuals exposed to secondary infections, DENV neutralization was dominated by cross-reactive antibodies, whereas in other individuals both type-specific and cross-reactive antibodies contributed to neutralization. To better understand the origins of type-specific and cross-reactive neutralizing antibodies, we analyzed sera from individuals with well-documented sequential infections with two DENV serotypes only. These individuals had both type-specific and cross-reactive neutralizing antibodies to the 2 serotypes responsible for infection and only cross-reactive neutralizing antibodies to other serotypes. Collectively, the results demonstrate that the quality of neutralizing (and presumably protective) antibodies are different in individuals depending on the number of previous exposures to different DENV serotypes. We propose a model in which low affinity, cross-reactive antibody secreting B-cell clones induced by primary exposure evolve during each secondary infection to secrete higher affinity and more broadly neutralizing antibodies.
Electron paramagnetic resonance of the $\mathrm{N_{2}V^{-}}$ defect in $\mathrm{^{15}N}$-doped synthetic diamond
Creators: name: Green, Ben L.
name: Dale, Matthew W.
name: Newton, Mark E.
name: Fisher, David
Publisher: name: arXiv
Year: 2015
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: Nitrogen is the dominant impurity in the majority of natural and synthetic diamonds, and the family of nitrogen vacancy-type ($\mathrm{N_{n}V}$) defects are crucial in our understanding of defect dynamics in these diamonds. A significant gap is the lack of positive identification of $\mathrm{N_{2}V}^{-}$, the dominant charge state of $\mathrm{N_{2}V}$, in diamond that contains a significant concentration of electron donors. In this paper we employ isotopically-enriched diamond to identify the EPR spectrum associated with $^{15}\mathrm{N_{2}V}^{-}$ and use the derived spin Hamiltonian parameters to identify $^{14}\mathrm{N_{2}V}^{-}$ in a natural isotopic abundance sample. The electronic wavefunction of the $\mathrm{N_{2}V^{-}}$ ground state and previous lack of identification is discussed. The $\mathrm{N_{2}V}^{-}$ EPR spectrum intensity is shown to correlate with H2 optical absorption over an order of magnitude in concentration.
Tensor networks for unsupervised machine learning
Creators: name: Liu, Jing
name: Li, Sujie
name: Zhang, Jiang
name: Zhang, Pan
Publisher: name: arXiv
Year: 2021
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Machine Learning (cs.LG)
subject: Quantum Physics (quant-ph)
subject: Machine Learning (stat.ML)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: Modeling the joint distribution of high-dimensional data is a central task in unsupervised machine learning. In recent years, many interests have been attracted to developing learning models based on tensor networks, which have the advantages of a principle understanding of the expressive power using entanglement properties, and as a bridge connecting classical computation and quantum computation. Despite the great potential, however, existing tensor network models for unsupervised machine learning only work as a proof of principle, as their performance is much worse than the standard models such as restricted Boltzmann machines and neural networks. In this Letter, we present autoregressive matrix product states (AMPS), a tensor network model combining matrix product states from quantum many-body physics and autoregressive modeling from machine learning. Our model enjoys the exact calculation of normalized probability and unbiased sampling. We demonstrate the performance of our model using two applications, generative modeling on synthetic and real-world data, and reinforcement learning in statistical physics. Using extensive numerical experiments, we show that the proposed model significantly outperforms the existing tensor network models and the restricted Boltzmann machines, and is competitive with state-of-the-art neural network models.
description: v2