cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
A Systematic Survey of Regularization and Normalization in GANs
Creators: name: Li, Ziqiang
name: Usman, Muhammad
name: Tao, Rentuo
name: Xia, Pengfei
name: Wang, Chaoyue
name: Chen, Huanhuan
name: Li, Bin
Publisher: name: arXiv
Year: 2020
Subjects: subject: Machine Learning (cs.LG)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Generative Adversarial Networks (GANs) have been widely applied in different scenarios thanks to the development of deep neural networks. The original GAN was proposed based on the non-parametric assumption of the infinite capacity of networks. However, it is still unknown whether GANs can fit the target distribution without any prior information. Due to the overconfident assumption, many issues remain unaddressed in GANs' training, such as non-convergence, mode collapses, gradient vanishing. Regularization and normalization are common methods of introducing prior information to stabilize training and improve discrimination. Although a handful number of regularization and normalization methods have been proposed for GANs, to the best of our knowledge, there exists no comprehensive survey that primarily focuses on objectives and development of these methods, apart from some in-comprehensive and limited scope studies. In this work, we conduct a comprehensive survey on the regularization and normalization techniques from different perspectives of GANs training. First, we systematically describe different perspectives of GANs training and thus obtain the different objectives of regularization and normalization. Based on these objectives, we propose a new taxonomy. Furthermore, we compare the performance of the mainstream methods on different datasets and investigate the applications of regularization and normalization techniques that have been frequently employed in state-of-the-art GANs. Finally, we highlight potential future directions of research in this domain. Code and studies related to the regularization and normalization of GANs in this work is summarized on https://github.com/iceli1007/GANs-Regularization-Review.
description: Accepted to Acm Computing Survey
Additional file 2 of Genomic prediction with epistasis models: on the marker-coding-dependent performance of the extended GBLUP and properties of the categorical epistasis model (CE)
Creators: name: Martini, Johannes
name: Gao, Ning
name: Diercles Cardoso
name: Wimmer, Valentin
name: Erbe, Malena
name: Cantet, Rodolfo
name: Simianer, Henner
Publisher: name: Figshare
Year: 2017
Subjects: subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Sociology
subject: FOS: Sociology
subject: 69999 Biological Sciences not elsewhere classified
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: 19999 Mathematical Sciences not elsewhere classified
subject: FOS: Mathematics
subject: Developmental Biology
subject: Computational Biology

description: The file presents mathematical arguments for the statements on the properties of the models, which have been made in the main text. (PDF 4034 kb)
TESS discovery of a super-Earth orbiting the M dwarf star TOI-1680
Creators: name: Ghachoui, M.
name: Soubkiou, A.
name: Wells, R. D.
name: Rackham, B. V.
name: Triaud, A. H. M. J.
name: Sebastian, D.
name: Giacalone, S.
name: Stassun, K. G.
name: Ciardi, D. R.
name: Collins, K. A.
name: Liu, A.
name: Chew, Y. Gómez Maqueo
name: Gillon, M.
name: Benkhaldoun, Z.
name: Delrez, L.
name: Eastman, J. D.
name: Demangeon, O.
name: Barkaoui, K.
name: Burdanov, A.
name: Demory, B. -O.
name: de Wit, J.
name: Dransfield, G.
name: Ducrot, E.
name: Garcia, L.
name: Gómez-Muñoz, M. A.
name: Hooton, M. J.
name: Jehin, E.
name: Murray, C. A.
name: Pedersen, P. P.
name: Pozuelos, F. J.
name: Queloz, D.
name: Sabin, L.
name: Schanche, N.
name: Timmermans, M.
name: Gonzales, E. J.
name: Dressing, C. D.
name: Aganze, C.
name: Burgasser, A. J.
name: Gerasimov, R.
name: Hsu, C.
name: Theissen, C. A.
name: Charbonneau, D.
name: Jenkins, J. M.
name: Latham, D. W.
name: Ricker, G.
name: Seager, S.
name: Shporer, A.
name: Twicken, J. D.
name: Vanderspek, R.
name: Winn, J. N.
name: Collins, K. I.
name: Fukui, A.
name: Gan, T.
name: Narita, N.
name: Schwarz, R. P.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Earth and Planetary Astrophysics (astro-ph.EP)
subject: FOS: Physical sciences

description: We report the discovery by the TESS mission of a super-Earth on a 4.8-d orbit around an inactive M4.5 dwarf (TOI-1680) validated by ground-based facilities. The host star is located 37.14 pc away, with a radius of 0.2100+/-0.0064 R_sun, mass of 0.1800+/-0.0044 M_sun and an effective temperature of 3211+/-100 K. We validated and characterized the planet using TESS data, ground-based multi-wavelength photometry from TRAPPIST, SPECULOOS, and LCO, as well as high-resolution AO observations from Keck/NIRC2 and Shane. Our analyses have determined the following parameters for the planet: a radius of 1.466+0.063/-0.049 R_earth and an equilibrium temperature of 404+/-14 K, assuming no albedo and perfect heat redistribution. Assuming a mass based on mass-radius relations, this planet is a promising target for atmospheric characterization with the James Webb Space Telescope (JWST).
description: Accepted in A&A
Classification and Unification of the Microscopic Deterministic Traffic Models with Identical Drivers
Creators: name: Yang, Bo
name: Monterola, Christopher
Publisher: name: arXiv
Year: 2015
Subjects: subject: Adaptation and Self-Organizing Systems (nlin.AO)
subject: Soft Condensed Matter (cond-mat.soft)
subject: FOS: Physical sciences

description: We show that all existing deterministic microscopic traffic models with identical drivers (including both two-phase and three-phase models) can be understood as special cases from a master model by expansion around well-defined ground states. This allows two traffic models to be compared in a well-defined way. The three-phase models are characterized by the vanishing of leading orders of expansion within a certain density range, and as an example the popular intelligent driver models (IDM) is shown to be equivalent to a generalized optimal velocity (OV) model. We also explore the diverse solutions of the generalized OV model that can be important both for understanding human driving behaviors and algorithms for autonomous driverless vehicles.
description: 4+ pages, 4 figs, minor changes updated for the accepted version
Information und/oder Infrastruktur - Transformation gestalten: Wünsche, Herausforderung, Realität
Creators: name: Stephan, Werner
Publisher: name: Kolloquium Wissensinfrastruktur
Year: 2012

description: Sondertermin zur Verabschiedung des ltd. Direktors der Universitätsbibliothek Bielefeld Dr. Michael Höppner
description: Kolloquium Wissensinfrastruktur, Wintersemester 2012/2013
Atomistic modeling of extreme near-field heat transport across nanogaps between two polar dielectric materials
Creators: name: Guo, Yangyu
name: Viloria, Mauricio Gómez
name: Messina, Riccardo
name: Ben-Abdallah, Philippe
name: Merabia, Samy
Publisher: name: arXiv
Year: 2023
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: The understanding of extreme near-field heat transport across vacuum nanogaps between polar dielectric materials remains an open question. In this work, we present a molecular dynamic simulation of heat transport across MgO-MgO nanogaps, together with a consistent comparison with the continuum fluctuational-electrodynamics theory using local dielectric properties. The dielectric function is computed by Green-Kubo molecular dynamics with the anharmonic damping properly included. As a result, the direct atomistic modeling shows significant deviation from the continuum theory even up to a gap size of few nanometers due to non-local dielectric response from acoustic and optical branches as well as phonon tunneling. The lattice anharmonicity is demonstrated to have a large impact on the energy transmission and thermal conductance, in contrast to its moderate effect reported for metallic vacuum nanogaps. The present work thus provides further insight into the physics of heat transport in the extreme near-field regime between polar materials, and put forward a methodology to account for anharmonic effects.
How to reduce the temporal yield variability of cropping systems by nutrient regimes? New insights for winter rye based on the Skierniewice long-term fertilization experiment (Poland). Supplementary materials
Creators: name: Studnicki, Marcin
name: Macholdt, Janna
name: Stępień, Wojciech
Publisher: name: Zenodo
Year: 2020

description: Supplementary materials for manuscript entitled "How to reduce the temporal yield variability of cropping systems by nutrient regimes? New insights for winter rye based on the Skierniewice long-term fertilization experiment (Poland)"
Abstracting the Traffic of Nonlinear Event-Triggered Control Systems
Creators: name: Delimpaltadakis, Giannis
name: Mazo, Manuel
Publisher: name: arXiv
Year: 2020
Subjects: subject: Systems and Control (eess.SY)
subject: Optimization and Control (math.OC)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Mathematics

description: Scheduling communication traffic in networks of event-triggered control (ETC) systems is challenging, as their sampling times are unknown, hindering application of ETC in networks. In previous work, finite-state abstractions were created, capturing the sampling behaviour of LTI ETC systems with quadratic triggering functions. Offering an infinite-horizon look to all sampling patterns of an ETC system, such abstractions can be used for scheduling of ETC traffic. Here we significantly extend this framework, by abstracting perturbed uncertain nonlinear ETC systems with general triggering functions. To construct an ETC system's abstraction: a) the state space is partitioned into regions, b) for each region an interval is determined, containing all intersampling times of points in the region, and c) the abstraction's transitions are determined through reachability analysis. To determine intervals and transitions, we devise algorithms based on reachability analysis. For partitioning, we propose an approach based on isochronous manifolds, resulting into tighter intervals and providing control over them, thus containing the abstraction's non-determinism. Simulations showcase our developments.
НОВАЯ ТЕХНОЛОГИЯ ПРОИЗВОДСТВА ШВЕЙНЫХ НИТЕЙ ИЗ НАТУРАЛЬНЫХ ТЕКСТИЛЬНЫХ ВОЛОКОН
Creators: name: Дадажонов, Ш.Д.
Publisher: name: Zenodo
Year: 2024

description: В данное статье приведены результаты исследований по разработке технологии производства швейных нитей из натуральных волокон, в частности, из комбинированной шелковой пряжи, получаемых из волокнистых отходов натурального шелка по кардогребенной системы шелкопрядения. Также приведены способы и технологии подготовки волокнистых отходов натурального шелка к чесанию. При производстве комбинированной прияжи в качестве нагонной нити использована комплексная полиэфирная нить линейной плотности 8,4 или 11,1 текс, а в качестве обвиваюшейся волокна две ровницы из шелковых волокон линейной плотности 143 текс.
No evidence for the blue-tilted power spectrum of relic gravitational waves
Creators: name: Huang, Qing-Guo
name: Wang, Sai
Publisher: name: arXiv
Year: 2015
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: In this paper, we constrain the tilt of the power spectrum of relic gravitational waves by combining the data from BICEP2/Keck array and Planck (BKP) and the Laser Interferometer Gravitational-Waves Observatory (LIGO). From the data of BKP B-modes, the constraint on the tensor tilt is $n_t=0.66^{+1.83}_{-1.44}$ at the $68%$ confidence level. By further adding the LIGO upper limit on the energy density of gravitational waves, the constraint becomes $n_t=-0.76^{+1.37}_{-0.52}$ at the $68%$ confidence level. We conclude that there is no evidence for a blue-tilted power spectrum of relic gravitational waves and either sign of the index of tensor power spectrum is compatible with the data.
description: 7 pages, 1 figure, 1 table
Additional file 1 of Genomic prediction with epistasis models: on the marker-coding-dependent performance of the extended GBLUP and properties of the categorical epistasis model (CE)
Creators: name: Martini, Johannes
name: Gao, Ning
name: Diercles Cardoso
name: Wimmer, Valentin
name: Erbe, Malena
name: Cantet, Rodolfo
name: Simianer, Henner
Publisher: name: Figshare
Year: 2017
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Pharmacology
subject: Evolutionary Biology
subject: 69999 Biological Sciences not elsewhere classified
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: 19999 Mathematical Sciences not elsewhere classified
subject: FOS: Mathematics
subject: Developmental Biology
subject: Marine Biology
subject: Cancer
subject: Plant Biology
subject: Computational Biology

description: Rdata-file with two lists. The list “Mouse_Data” contains a genotype matrix of 1298 individuals and 9265 markers as well as a matrix with records of 13 traits of the individuals. The list “Simulated_Data” offers the genotypes and phenotypes of the 20 simulations. Each entry of this list is a list of two elements representing genotypes and phenotypes of the respective simulation. Genotypes are given by a matrix of 1000 individuals with 9000 markers. Phenotypes are provided as a data.frame of the 1000 individuals and the 9 different phenotypes described in the Methods section. (DOC 82739 kb)
Additional file 1: of The transcriptome of the mosquito Aedes fluviatilis (Diptera: Culicidae), and transcriptional changes associated with its native Wolbachia infection
Creators: name: E. Caragata
name: F. Pais
name: L. Baton
name: J. Silva
name: M. Sorgine
name: L. Moreira
Publisher: name: Figshare
Year: 2017
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Genetics
subject: Evolutionary Biology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: Sociology
subject: FOS: Sociology
subject: 69999 Biological Sciences not elsewhere classified
subject: Infectious Diseases
subject: FOS: Health sciences

description: Divergence and phylogenetic analyses. Phylogenetic trees, and an estimate of the time of divergence for Aedes fluviatilis and other key mosquito species. (DOCX 1815 kb)
title: Dossier. Le ispirazioni del giurista. Storie, miti, favole, archetipi e altre dimensioni della narratività. Atti del IX Convegno Nazionale della ISLL - Campobasso, 30 giugno e 1° luglio 2022. Versione aggiornata
Creators: name: Vespaziani, Alberto
name: Mittica, Maria Paola
Publisher: name: Italian Society for Law and Literature (ISLL)
Year: 2023

description: ][The jurist's inspirations. Stories, myths, fables, archetypes, and other dimensions of narrativity. Proceedings of the IX National Conference of the ISLL]. On June 30 and July 1, 2022, the University of Molise at Campobasso hosted the 9th national convention of the Italian Society for Law and Literature (ISLL), titled “The jurist's inspirations. Stories, myths, fables, archetypes, and other dimensions of narrativity”. From Philosophy to the Sociology of Law, from Criminal Law to the History of Italian Law, from Constitutional Law to Comparative Law, from Medieval Philology to the Opera house, from Cinema to New Media, scholars of the literary culture of law have offered narratives and questions that agitate the conscience of the contemporary jurist. 
[Questa è la versione aggiornata del contributo, in cui è stato introdotto un nuovo codice ISBN: 9788854971929 e un nuovo DOI:10.6092/unibo/amsacta/8308. La versione precedente ha ISBN: 9788854971066 e DOI 10.6092/unibo/amsacta/7379
The VISCACHA survey -- VIII. Chemical evolution history of Small Magellanic Cloud West Halo cluster
Creators: name: Saroon, S.
name: Dias, B.
name: Tsujimotto, T.
name: Parisi, M. C.
name: Maia, F.
name: Kerber, L.
name: Bekki, K.
name: Minniti, D.
name: Oliveira, R. A. P.
name: Westera, P.
name: Santrich, O. J. K.
name: Bica, E.
name: Sanmartim, D.
name: Quint, B. C.
name: Fraga, L.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: The chemical evolution history of the Small Magellanic Cloud (SMC) has been a matter of debate for decades. The challenges in understanding the SMC chemical evolution are related to a very slow star formation rate (SFR) combined with bursts triggered by the multiple interactions between the SMC and the Large Magellanic Cloud, a significant (~0.5 dex) metallicity dispersion for the SMC cluster population younger than about 7.5 Gyr, and multiple chemical evolution models tracing very different paths through the observed age-metallicity relation of the SMC. There is no doubt that these processes were complex. Therefore, a step-by-step strategy is required in order to better understand the SMC chemical evolution. We adopted an existing framework to split the SMC into regions on the sky, and we focus on the west halo in this work, which contains the oldest and most metal-poor stellar populations and is moving away from the SMC, that is, in an opposite motion with respect to the Magellanic Bridge. We present a sample containing ~60% of all west halo clusters to represent the region well, and we identify a clear age-metallicity relation with a tight dispersion that exhibits a 0.5 dex metallicity dip about 6 Gyr ago. We ran chemical evolution models and discuss possible scenarios to explain this metallicity dip, the most likely being a major merger accelerating the SFR after the event. This merger should be combined with inefficient internal gas mixing within the SMC and different SFRs in different SMC regions because the same metallicity dip is not seen in the AMR of the SMC combining clusters from all regions. We try to explain the scenario to better understand the SMC chemo-dynamical history.
description: 16 pages, 8 figures, 3 tables, Accepted for publication in Astronomy & Astrophysics journals
The ultra-long GRB 220627A at z=3.08
Creators: name: de Wet, S.
name: Izzo, L.
name: Groot, P. J.
name: Bisero, S.
name: D'Elia, V.
name: De Pasquale, M.
name: Hartmann, D. H.
name: Heintz, K. E.
name: Jakobsson, P.
name: Laskar, T.
name: Levan, A.
name: Martin-Carrillo, A.
name: Melandri, A.
name: Guelbenzu, A. Nicuesa
name: Pugliese, G.
name: Rossi, A.
name: Saccardi, A.
name: Savaglio, S.
name: Schady, P.
name: Tanvir, N. R.
name: van Eerten, H.
name: Vergani, S.
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: FOS: Physical sciences

description: GRB 220627A is a rare burst with two distinct gamma-ray emission episodes separated by almost 1000 s that triggered the Fermi Gamma-ray Burst Monitor twice. High-energy GeV emission was detected by the Fermi Large Area Telescope coincident with the first emission episode but not the second. The discovery of the optical afterglow with MeerLICHT led to MUSE observations which secured the burst redshift to z=3.08, making this the most distant ultra-long gamma-ray burst (GRB) detected to date. The progenitors of some ultra-long GRBs have been suggested in the literature to be different to those of normal long GRBs. Our aim is to determine whether the afterglow and host properties of GRB 220627A agree with this interpretation. We performed empirical and theoretical modelling of the afterglow data within the external forward shock framework, and determined the metallicity of the GRB environment through modelling the absorption lines in the MUSE spectrum. Our optical data show evidence for a jet break in the light curve at ~1.2 days, while our theoretical modelling shows a preference for a homogeneous circumburst medium. Our forward shock parameters are typical for the wider GRB population, and we find that the environment of the burst is characterised by a sub-solar metallicity. Our observations and modelling of GRB 220627A do not suggest that a different progenitor compared to the progenitor of normal long GRBs is required. We find that more observations of ultra-long GRBs are needed to determine if they form a separate population with distinct prompt and afterglow features, and possibly distinct progenitors.
description: 17 pages, accepted for publication in A&A
EntropyRank: Unsupervised Keyphrase Extraction via Side-Information Optimization for Language Model-based Text Compression
Creators: name: Tsvetkov, Alexander
name: Kipnis, Alon
Publisher: name: arXiv
Year: 2023
Subjects: subject: Computation and Language (cs.CL)
subject: Information Theory (cs.IT)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: We propose an unsupervised method to extract keywords and keyphrases from texts based on a pre-trained language model (LM) and Shannon's information maximization. Specifically, our method extracts phrases having the highest conditional entropy under the LM. The resulting set of keyphrases turns out to solve a relevant information-theoretic problem: if provided as side information, it leads to the expected minimal binary code length in compressing the text using the LM and an entropy encoder. Alternately, the resulting set is an approximation via a causal LM to the set of phrases that minimize the entropy of the text when conditioned upon it. Empirically, the method provides results comparable to the most commonly used methods in various keyphrase extraction benchmark challenges.
Model predictive control strategy in waked wind farms for optimal fatigue loads
Creators: name: Zhong, Cheng
name: Ding, Yicheng
name: Wang, Husai
name: Chen, Jikai
name: Wang, Jian
name: Li, Yang
Publisher: name: arXiv
Year: 2023
Subjects: subject: Systems and Control (eess.SY)
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: With the rapid growth of wind power penetration, wind farms (WFs) are required to implement frequency regulation that active power control to track a given power reference. Due to the wake interaction of the wind turbines (WTs), there is more than one solution to distributing power reference among the operating WTs, which can be exploited as an optimization problem for the second goal, such as fatigue load alleviation. In this paper, a closed-loop model predictive controller is developed that minimizes the wind farm tracking errors, the dynamical fatigue load, and and the load equalization. The controller is evaluated in a mediumfidelity model. A 64 WTs simulation case study is used to demonstrate the control performance for different penalty factor settings. The results indicated the WF can alleviate dynamical fatigue load and have no significant impact on power tracking. However, the uneven load distribution in the wind turbine system poses challenges for maintenance. By adding a trade-off between the load equalization and dynamical fatigue load, the load differences between WTs are significantly reduced, while the dynamical fatigue load slightly increases when selecting a proper penalty factor.
description: Accepted by Electric Power Systems Research
Integral Kahler Invariants and the Bergman kernel asymptotics for line bundles
Creators: name: Alexakis, Spyros
name: Hirachi, Kengo
Publisher: name: arXiv
Year: 2015
Subjects: subject: Differential Geometry (math.DG)
subject: Complex Variables (math.CV)
subject: FOS: Mathematics
subject: 53B35

description: On a compact Kahler manifold, one can define global invariants by integrating local invariants of the metric. Assume that a global invariant thus obtained depends only on the Kahler class. Then we show that the integrand can be decomposed into a Chern polynomial (the integrand of a Chern number) and divergences of one forms, which do not contribute to the integral. We apply this decomposition formula to describe the asymptotic expansion of the Bergman kernel for positive line bundles and to show that the CR Q-curvature on a Sasakian manifold is a divergence.
description: 44 pages
Mixing it up: A general framework for Markovian statistics
Creators: name: Dexheimer, Niklas
name: Strauch, Claudia
name: Trottner, Lukas
Publisher: name: arXiv
Year: 2020
Subjects: subject: Statistics Theory (math.ST)
subject: Probability (math.PR)
subject: FOS: Mathematics
subject: 62M05, 62G20, 60G10, 60J25

description: Up to now, the nonparametric analysis of multidimensional continuous-time Markov processes has focussed strongly on specific model choices, mostly related to symmetry of the semigroup. While this approach allows to study the performance of estimators for the characteristics of the process in the minimax sense, it restricts the applicability of results to a rather constrained set of stochastic processes and in particular hardly allows incorporating jump structures. As a consequence, for many models of applied and theoretical interest, no statement can be made about the robustness of typical statistical procedures beyond the beautiful, but limited framework available in the literature. To close this gap, we identify $β$-mixing of the process and heat kernel bounds on the transition density as a suitable combination to obtain $\sup$-norm and $L^2$ kernel invariant density estimation rates matching the case of reversible multidimenisonal diffusion processes and outperforming density estimation based on discrete i.i.d. or weakly dependent data. Moreover, we demonstrate how up to $\log$-terms, optimal $\sup$-norm adaptive invariant density estimation can be achieved within our general framework based on tight uniform moment bounds and deviation inequalities for empirical processes associated to additive functionals of Markov processes. The underlying assumptions are verifiable with classical tools from stability theory of continuous time Markov processes and PDE techniques, which opens the door to evaluate statistical performance for a vast amount of Markov models. We highlight this point by showing how multidimensional jump SDEs with Lévy driven jump part under different coefficient assumptions can be seamlessly integrated into our framework, thus establishing novel adaptive $\sup$-norm estimation rates for this class of processes.
title: Graphical scaffolding for the learning of data wrangling APIs
Creators: name: Sundin, Lovisa
Publisher: name: University of Glasgow
Year: 2022

description: In order for students across the sciences to avail themselves of modern data streams, they must first know how to wrangle data: how to reshape ill-organised, tabular data into another format, and how to do this programmatically, in languages such as Python and R. Despite the cross-departmental demand and the ubiquity of data wrangling in analytical workflows, the research on how to optimise the instruction of it has been minimal. Although data wrangling as a programming domain presents distinctive challenges - characterised by on-the-fly syntax lookup and code example integration - it also presents opportunities. One such opportunity is how tabular data structures are easily visualised. To leverage the inherent visualisability of data wrangling, this dissertation evaluates three types of graphics that could be employed as scaffolding for novices: subgoal graphics, thumbnail graphics, and parameter graphics. Using a specially built e-learning platform, this dissertation documents a multi-institutional, randomised, and controlled experiment that investigates the pedagogical effects of these. Our results indicate that the graphics are well-received, that subgoal graphics boost the completion rate, and that thumbnail graphics improve navigability within a command menu. We also obtained several non-significant results, and indications that parameter graphics are counter-productive. We will discuss these findings in the context of general scaffolding dilemmas, and how they fit into a wider research programme on data wrangling instruction.
Reliable Off-policy Evaluation for Reinforcement Learning
Creators: name: Wang, Jie
name: Gao, Rui
name: Zha, Hongyuan
Publisher: name: arXiv
Year: 2020
Subjects: subject: Machine Learning (cs.LG)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences

description: In a sequential decision-making problem, off-policy evaluation estimates the expected cumulative reward of a target policy using logged trajectory data generated from a different behavior policy, without execution of the target policy. Reinforcement learning in high-stake environments, such as healthcare and education, is often limited to off-policy settings due to safety or ethical concerns, or inability of exploration. Hence it is imperative to quantify the uncertainty of the off-policy estimate before deployment of the target policy. In this paper, we propose a novel framework that provides robust and optimistic cumulative reward estimates using one or multiple logged trajectories data. Leveraging methodologies from distributionally robust optimization, we show that with proper selection of the size of the distributional uncertainty set, these estimates serve as confidence bounds with non-asymptotic and asymptotic guarantees under stochastic or adversarial environments. Our results are also generalized to batch reinforcement learning and are supported by empirical analysis.
description: 46 pages, 7 figures
Digital Modeling for Everyone: Exploring How Novices Approach Voice-Based 3D Modeling
Creators: name: Desolda, Giuseppe
name: Esposito, Andrea
name: Müller, Florian
name: Feger, Sebastian
Publisher: name: arXiv
Year: 2023
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences
subject: H.5.2; I.2.1

description: Manufacturing tools like 3D printers have become accessible to the wider society, making the promise of digital fabrication for everyone seemingly reachable. While the actual manufacturing process is largely automated today, users still require knowledge of complex design applications to produce ready-designed objects and adapt them to their needs or design new objects from scratch. To lower the barrier to the design and customization of personalized 3D models, we explored novice mental models in voice-based 3D modeling by conducting a high-fidelity Wizard of Oz study with 22 participants. We performed a thematic analysis of the collected data to understand how the mental model of novices translates into voice-based 3D modeling. We conclude with design implications for voice assistants. For example, they have to: deal with vague, incomplete and wrong commands; provide a set of straightforward commands to shape simple and composite objects; and offer different strategies to select 3D objects.
description: Presented at INTERACT 2023. This is a self-archival version: the version of record is available via Springer at https://doi.org/10.1007/978-3-031-42293-5_11
Hurricane Forecasting: A Novel Multimodal Machine Learning Framework
Creators: name: Boussioux, Léonard
name: Zeng, Cynthia
name: Guénais, Théo
name: Bertsimas, Dimitris
Publisher: name: arXiv
Year: 2020
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: Atmospheric and Oceanic Physics (physics.ao-ph)
subject: FOS: Computer and information sciences
subject: FOS: Physical sciences

description: This paper describes a novel machine learning (ML) framework for tropical cyclone intensity and track forecasting, combining multiple ML techniques and utilizing diverse data sources. Our multimodal framework, called Hurricast, efficiently combines spatial-temporal data with statistical data by extracting features with deep-learning encoder-decoder architectures and predicting with gradient-boosted trees. We evaluate our models in the North Atlantic and Eastern Pacific basins on 2016-2019 for 24-hour lead time track and intensity forecasts and show they achieve comparable mean absolute error and skill to current operational forecast models while computing in seconds. Furthermore, the inclusion of Hurricast into an operational forecast consensus model could improve over the National Hurricane Center's official forecast, thus highlighting the complementary properties with existing approaches. In summary, our work demonstrates that utilizing machine learning techniques to combine different data sources can lead to new opportunities in tropical cyclone forecasting.
description: Published by the AMS' Weather and Forecasting journal; Spotlight talk at NeurIPS 2021, Tackling Climate Change with AI ; https://journals.ametsoc.org/view/journals/wefo/37/6/WAF-D-21-0091.1.xml
Functorial Manifold Learning
Creators: name: Shiebler, Dan
Publisher: name: arXiv
Year: 2020
Subjects: subject: Machine Learning (cs.LG)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences

description: We adapt previous research on category theory and topological unsupervised learning to develop a functorial perspective on manifold learning, also known as nonlinear dimensionality reduction. We first characterize manifold learning algorithms as functors that map pseudometric spaces to optimization objectives and that factor through hierarchical clustering functors. We then use this characterization to prove refinement bounds on manifold learning loss functions and construct a hierarchy of manifold learning algorithms based on their equivariants. We express several popular manifold learning algorithms as functors at different levels of this hierarchy, including Metric Multidimensional Scaling, IsoMap, and UMAP. Next, we use interleaving distance to study the stability of a broad class of manifold learning algorithms. We present bounds on how closely the embeddings these algorithms produce from noisy data approximate the embeddings they would learn from noiseless data. Finally, we use our framework to derive a set of novel manifold learning algorithms, which we experimentally demonstrate are competitive with the state of the art.
description: In Proceedings ACT 2021, arXiv:2211.01102
Influence of Augmented Reality on Increasing Purchase Intention among Bangladeshi Consumers in the Retail Industry
Creators: name: Sakib Rahman, Dipto
Publisher: name: Emerald
Year: 2023
Subjects: AR
Bangladesh
Research
Technology
Purchase Intention
Influence of Augmented Reality

description: This research looks at how augmented reality (AR) is changing the retail industry in Bangladesh. It looks at how AR integration affects consumer behavior and how likely they are to buy. It also looks at what people think, feel, and want when it comes to AR-enabled shopping experiences. It's all about how AR can change the retail scene in Bangladesh. The research not only looks at how AR affects consumer behavior, but also what retailers and businesses can do to get more customers engaged and drive purchase intent with AR apps.
Theory of liquids: from excitations to thermodynamics
Creators: name: Trachenko, K.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Soft Condensed Matter (cond-mat.soft)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: Of the three basic states of matter, liquid is perhaps the most complex. While its flow properties are described by fluid mechanics, its thermodynamic properties are often neglected, and for many years it was widely believed that a general theory of liquid thermodynamics was unattainable. In recent decades that view has been challenged, as new advances have finally enabled us to understand and describe the thermodynamic properties of liquids. This book explains the recent developments in theory, experiment and modelling that have enabled us to understand the behaviour of excitations in liquids and the impact of this behaviour on heat capacity and other basic properties. Presented in plain language with a focus on real liquids and their experimental properties, this book is a useful reference text for researchers and graduate students in condensed matter physics and chemistry, as well as for advanced courses covering the theory of liquids.
description: 35 pages, 3 figures. Preface, Introduction and experimental section
Normal heat diffusion in many-body system via thermal photons
Creators: name: Luo, Minggang
name: Zhao, Junming
name: Liu, Linhua
Publisher: name: arXiv
Year: 2020
Subjects: subject: Applied Physics (physics.app-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: A normal-diffusion theory for heat transfer in many-body systems via carriers of thermal photons is developed. The thermal conductivity tensor is rigorously derived from fluctuational electrodynamics as a coefficient of diffusion term for the first time. In addition, a convection-like heat transfer behavior is revealed in systems of asymmetric distribution of particles, indicating violation of Fourier's law for such system. Considering the central role of thermal conductivity in heat transfer, this work paves a way for understanding, analysis and manipulation of heat transfer in nanoparticle system via thermal photons with many-body interactions.
description: 4 figures
Expressive power of complex-valued restricted Boltzmann machines for solving non-stoquastic Hamiltonians
Creators: name: Park, Chae-Yeun
name: Kastoryano, Michael J.
Publisher: name: arXiv
Year: 2020
Subjects: subject: Quantum Physics (quant-ph)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: Variational Monte Carlo with neural network quantum states has proven to be a promising avenue for evaluating the ground state energy of spin Hamiltonians. However, despite continuous efforts the performance of the method on frustrated Hamiltonians remains significantly worse than those on stoquastic Hamiltonians that are sign-free. We present a detailed and systematic study of restricted Boltzmann machine (RBM) based variational Monte Carlo for quantum spin chains, resolving how relevant stoquasticity is in this setting. We show that in most cases, when the Hamiltonian is phase connected with a stoquastic point, the complex RBM state can faithfully represent the ground state, and local quantities can be evaluated efficiently by sampling. On the other hand, we identify several new phases that are challenging for the RBM Ansatz, including non-topological robust non-stoquastic phases as well as stoquastic phases where sampling is nevertheless inefficient. Furthermore, we find that an accurate neural network representation of ground states in non-stoquastic phases is hindered not only by the sign structure but also by their amplitudes.
description: 14+10 pages, 20 Figures. Close to a version published in PRB
Why is there Socialism in the United States? Social Science and Industrial Society in Thorstein Veblen’s Line of Thought
Creators: name: Parisi, Clemente
Publisher: name: USAbroad – Journal of American History and Politics
Year: 2020
Subjects: Thorstein Veblen; United States; Social Sciences; Industrial Society; Technology

description: The article deals with Veblen’s vision of social conflict to critically reexamine his political thought. Retracing his intellectual biography, it focuses on three connected aspects: a twofold vision of social conflict that emerges from his reinvention of evolutionism; his reading of socialism in an industrial society; the relevance of an evolutionary concept of technology in order to understand new forms of conflict within the transition to a cooperative working process that is associated with scientific organization and planning. These elements are used to highlight Veblen’s stance towards Progressive Era social sciences and towards institutional and intellectual attempts to control the vagaries and conflicts of industrial capitalism.
description: USAbroad – Journal of American History and Politics, Vol 3 (2020)
Jellyfish galaxy candidates at low redshift
Creators: name: Poggianti, B. M.
name: Fasano, G.
name: Omizzolo, A.
name: Gullieuszik, M.
name: Bettoni, D.
name: Moretti, A.
name: Paccagnella, A.
name: Jaffe', Y. L.
name: Vulcani, B.
name: Fritz, J.
name: Couch, W.
name: D'Onofrio, M.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: Galaxies that are being stripped of their gas can sometimes be recognized from their optical appearance. Extreme examples of stripped galaxies are the so-called ``jellyfish galaxies'', that exhibit tentacles of debris material with a characteristic jellyfish morphology. We have conducted the first systematic search for galaxies that are being stripped of their gas at low-z (z=0.04-0.07) in different environments, selecting galaxies with varying degrees of morphological evidence for stripping. We have visually inspected B and V-band images and identified 344 candidates in 71 galaxy clusters of the OMEGAWINGS+WINGS sample and 75 candidates in groups and lower mass structures in the PM2GC sample. We present the atlas of stripping candidates and a first analysis of their environment and their basic properties, such as morphologies, star formation rates and galaxy stellar masses. Candidates are found in all clusters and at all clustercentric radii, and their number does not correlate with the cluster velocity dispersion sigma or X-ray luminosity L_X. Interestingly, convincing cases of candidates are also found in groups and lower mass haloes (10^{11}-10^{14} M_{sun}), although the physical mechanism at work needs to be securely identified. All the candidates are disky, have stellar masses ranging from log M/M_{sun} < 9 to > 11.5 and the majority of them form stars at a rate that is on average a factor of 2 higher (2.5 sigma) compared to non-stripped galaxies of similar mass. The few post-starburst and passive candidates have weak stripping evidence. We conclude that the stripping phenomenon is ubiquitous in clusters and could be present even in groups and low mass haloes. Further studies will reveal the physics of the gas stripping and clarify the mechanisms at work.
description: revised version including referee comments
Convexity constraints on linear background models for electron energy-loss spectra
Creators: name: Broek, Wouter Van den
name: Jannis, Daen
name: Verbeeck, Jo
Publisher: name: arXiv
Year: 2023
Subjects: subject: Data Analysis, Statistics and Probability (physics.data-an)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Computational Physics (physics.comp-ph)
subject: Instrumentation and Detectors (physics.ins-det)
subject: FOS: Physical sciences

description: In this paper convexity constraints are derived for a background model of electron energy loss spectra (EELS) that is linear in the fitting parameters. The model outperforms a power-law both on experimental and simulated backgrounds, especially for wide energy ranges, and thus improves elemental quantification results. Owing to the model's linearity, the constraints can be imposed through fitting by quadratic programming. This has important advantages over conventional nonlinear power-law fitting such as high speed and a guaranteed unique solution without need for initial parameters. As such, the need for user input is significantly reduced, which is essential for unsupervised treatment of large data sets. This is demonstrated on a demanding spectrum image of a semiconductor device sample with a high number of elements over a wide energy range.
description: Updated version
A generalized slip-flow theory for a slightly rarefied gas flow induced by discontinuous wall temperature
Creators: name: Taguchi, Satoshi
name: Tsuji, Tetsuro
Publisher: name: arXiv
Year: 2020
Subjects: subject: Fluid Dynamics (physics.flu-dyn)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences
subject: 82, 76

description: A system of fluid-dynamic-type equations and their boundary conditions derived from a system of the Boltzmann equation is of great importance in kinetic theory when we are concerned with the motion of a slightly rarefied gas. It offers an efficient alternative to solving the Boltzmann equation directly and, more importantly, provides a clear picture of the flow structure in the near-continuum regime. However, the applicability of the existing slip-flow theory is limited to the case where both the boundary shape and the kinetic boundary condition are smooth functions of the boundary coordinates, which precludes, for example, the case where the kinetic boundary condition has a jump discontinuity. In this paper, we discuss the motion of a slightly rarefied gas caused by a discontinuous wall temperature in a simple two-surface problem and illustrate how the existing theory can be extended. The discussion is based on our recent paper [Taguchi and Tsuji, J. Fluid Mech. 897, A16 (2020)] supported by some preliminary numerical results for the newly introduced kinetic boundary layer (the Knudsen zone), from which a source-sink condition for the flow velocity is derived.
description: 17 pages, 3 figures
title: Уголовно-правовая характеристика и проблемы квалификации налоговых преступлений
Creators: name: ELS IPR BOOKS
Publisher: name: Новосибирский государственный университет экономики и управления «НИНХ»
Year: 2022

description: Динамичность налогового и уголовного законодательства, новые разъяснения Верховного суда Российской Федерации и изменившаяся в связи с этим следственно-судебная практика обусловили потребность в переиздании учебного пособия, вышедшего в 2019 году. В обновленном издании, помимо уголовно-правовой характеристики налоговых и сопутствующих им преступлений, проводится анализ актуальной судебной практики и освещаются наиболее сложные вопросы правоприменения. Пособие предназначено для студентов, обучающихся по направлению «Юриспруденция», а также может представлять практический интерес для сотрудников правоохранительных органов, занимающихся расследованием преступлений в сфере экономической деятельности.
Figure S1 from Methylation of avpr1a in the cortex of wild prairie voles: effects of CpG position and polymorphism
Creators: name: M. Okhovat
name: S. M. Maguire
name: S.M. Phelps
Publisher: name: Figshare
Year: 2017
Subjects: subject: Molecular Biology
subject: Evolutionary Biology
subject: FOS: Biological sciences
subject: 60801 Animal Behaviour

description: CAGE data reveal the 5’ boundary of transcripts along the bis-seq target. A) Cap analysis gene expression (CAGE) sequencing reads from the FANTOM5 project (35) are viewed at the mouse (mm10) avpr1a (http://genome.ucsc.edu), within a region homologous to the vole bis-seq target. Significant CAGE peaks are marked by black bars on the bottom of track. B) Modified figures from Figure 2, show CpG density and methylation across bis-seq gene-features. Gene-feature borders are depicted by dashed lines.
The Grassmann algebra in arbitrary characteristic and generalized sign
Creators: name: Dor, Gal
name: Kanel-Belov, Alexei
name: Vishne, Uzi
Publisher: name: arXiv
Year: 2015
Subjects: subject: Rings and Algebras (math.RA)
subject: FOS: Mathematics
subject: Primary 16R10, Secondary 17A70, 16R30, 16R50

description: We define a generalization $\mathfrak{G}$ of the Grassmann algebra $G$ which is well-behaved over arbitrary commutative rings $C$, even when $2$ is not invertible. In particular, this enables us to define a notion of superalgebras that does not become degenerate in such a setting. Using this construction we are able to provide a basis of the non-graded multilinear identities of the free superalgebra with supertrace, valid over any ring. We also show that all identities of $\mathfrak{G}$ follow from the Grassmann identity, and explicitly give its co-modules, which turn out to be generalizations of the sign representation. In particular, we show that the co-module is a free $C$-module of rank $2^{n-1}$.
description: 25 pp