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Specialized documentation techniques have been developed to communicate key facts about machine-learning (ML) systems and the datasets and models they rely on. Techniques such as Datasheets, FactSheets, and Model Cards have taken a mainly descriptive approach, providing various details about the system components. Wh...
Prescriptive and Descriptive Approaches to Machine-Learning Transparency
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We study the direction-dependent drag acting on a cylindrical solid intruder with length $L$ and diameter $D$ as it moves in water-saturated granular beds at constant depth. Polysterene and hydrogel grains with diameter $d$ are used to investigate materials which have high contact friction and those which are nearly ...
Drag anisotropy of cylindrical solids in fluid-saturated granular beds
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The p-adic Simpson correspondence due to Faltings is a p-adic analogue of non-abelian Hodge theory. The following is the main result of this article: The correspondence for line bundles can be enhanced to a rigid analytic morphism of moduli spaces under certain smallness conditions. In the complex setting, Simpson sh...
Rigid analytic p-adic Simpson correspondence for line bundles
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This paper deals with ergodic theorems for particular time-inhomogeneous Markov processes, whose the time-inhomogeneity is asymptotically periodic. Under a Lyapunov/minorization condition, it is shown that, for any measurable bounded function $f$, the time average $\frac{1}{t} \int_0^t f(X_s)ds$ converges in $\mathbb...
An ergodic theorem for asymptotically periodic time-inhomogeneous Markov processes, with application to quasi-stationarity with moving boundaries
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A finite element model was developed to compute the fluid flow inside a sessile evaporating droplet on hydrophilic substrate in ambient conditions. The evaporation is assumed as quasi-steady and the flow is considered as axisymmetric with a pinned contact line. The Navier-Stokes equations in cylindrical coordinates w...
A finite-element model for computing fluid flow inside a sessile evaporating droplet on a solid surface
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The HoloLens (Microsoft Corp., Redmond, WA), a head-worn, optically see-through augmented reality display, is the main player in the recent boost in medical augmented reality research. In medical settings, the HoloLens enables the physician to obtain immediate insight into patient information, directly overlaid with ...
The HoloLens in Medicine: A systematic Review and Taxonomy
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We show that in cubic crystals with anisotropic impurity centers the sum of squares of the magnetic resonance (EPR) frequencies is invariant with respect to the magnetic field direction. The connection between such an invariant and the g-tensor components of the impurity is derived for different types of centers. The...
Invariants in the paramagnetic resonance spectra of impurity crystals
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Infant motion analysis is a topic with critical importance in early childhood development studies. However, while the applications of human pose estimation have become more and more broad, models trained on large-scale adult pose datasets are barely successful in estimating infant poses due to the significant differe...
Invariant Representation Learning for Infant Pose Estimation with Small Data
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This paper introduces a deep learning method for solving an elliptic hemivariational inequality (HVI). In this method, an expectation minimization problem is first formulated based on the variational principle of underlying HVI, which is solved by stochastic optimization algorithms using three different training stra...
Adaptive Learning on the Grids for Elliptic Hemivariational Inequalities
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Facially manipulated images and videos or DeepFakes can be used maliciously to fuel misinformation or defame individuals. Therefore, detecting DeepFakes is crucial to increase the credibility of social media platforms and other media sharing web sites. State-of-the art DeepFake detection techniques rely on neural net...
Adversarial Threats to DeepFake Detection: A Practical Perspective
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Many models in mathematical epidemiology are developed with the aim to provide a framework for parameter estimation and then prediction. It is well-known that parameters are not always uniquely identifiable. In this paper we consider network-based mean-field models and explore the problem of parameter identifiability...
On parameter identifiability in network-based epidemic models
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To date, few studies have focused on protostellar outflow feedback at scales larger than several parsecs. To address this paucity of research, we investigate the effects of feedback from CO outflow candidates on their parent clouds over $\sim$ 110 deg$^2$ toward the W3/4/5 complex and its surroundings. Our search ide...
CO Outflow Candidates Toward the W3/4/5 Complex II: Feedback from Candidate Outflows
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Machine learning models deployed as a service (MLaaS) are susceptible to model stealing attacks, where an adversary attempts to steal the model within a restricted access framework. While existing attacks demonstrate near-perfect clone-model performance using softmax predictions of the classification network, most of...
Towards Data-Free Model Stealing in a Hard Label Setting
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Manic episodes of bipolar disorder can lead to uncritical behaviour and delusional psychosis, often with destructive consequences for those affected and their surroundings. Early detection and intervention of a manic episode are crucial to prevent escalation, hospital admission and premature death. However, people wi...
Long-Short Ensemble Network for Bipolar Manic-Euthymic State Recognition Based on Wrist-worn Sensors
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The Ohmic spin diode (OSD) is a recent concept in spintronics, which is based on half-metallic magnets (HMMs) and spin-gapless semiconductors (SGSs). Quaternary Heusler compounds offer a unique platform to realize the OSD for room temperature applications as these materials possess very high Curie temperatures as wel...
First principles design of Ohmic spin diodes based on quaternary Heusler compounds
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Micro-bending is a well-known source of loss in optical waveguides. By treating the micro-bending as a stochastic process, the problem of loss mitigation can be modeled in terms of a Fokker-Planck equation. Given an initial refractive index profile, and taking micro-bending into account, we develop a formalism to der...
A Supersymmetric Approach to the Problem of Micro-bending Attenuation in Optical Waveguides
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Vision transformers have recently achieved competitive results across various vision tasks but still suffer from heavy computation costs when processing a large number of tokens. Many advanced approaches have been developed to reduce the total number of tokens in large-scale vision transformers, especially for image ...
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning
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The aim of this paper is introduce and give some constructions results and examples of n-BiHom-Lie color algebras. Next, we introduce the definition of BiHom-modules over n- BiHom-Lie color algebras and we provide some properties. Moreover we investigate generalized derivations of n-BiHom-Lie color algebras and their...
Constructions and generalised derivations of multiplicative n-BiHom-Lie color algebras
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Nonlinear optics is of crucial importance in several fields of science and technology with applications in frequency conversion, entangled-photon generation, self-referencing of frequency combs, crystal characterization, sensing, and ultra-short light pulse generation and characterization. In recent years, layered ma...
Parametric Nonlinear Optics with Layered Materials and Related Heterostructures
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Pedestrian detection in crowd scenes poses a challenging problem due to the heuristic defined mapping from anchors to pedestrians and the conflict between NMS and highly overlapped pedestrians. The recently proposed end-to-end detectors(ED), DETR and deformable DETR, replace hand designed components such as NMS and a...
DETR for Crowd Pedestrian Detection
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Skin lesion segmentation is one of the crucial steps for an efficient non-invasive computer-aided early diagnosis of melanoma. This paper investigates how color information, besides saliency, can be used to determine the pigmented lesion region automatically. Unlike most existing segmentation methods using only the s...
Saliency-based segmentation of dermoscopic images using color information
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Multi-modal machine learning (ML) models can process data in multiple modalities (e.g., video, audio, text) and are useful for video content analysis in a variety of problems (e.g., object detection, scene understanding, activity recognition). In this paper, we focus on the problem of video categorization using a mul...
Cross-modal Learning for Multi-modal Video Categorization
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Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and point of care applications; however, many challenges such as data privacy concerns impede its optimal utilization. Deep generative models, particularly, Generative Adversarial Networks (GANs) show great promise in generating syn...
A review of Generative Adversarial Networks for Electronic Health Records: applications, evaluation measures and data sources
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We obtain the quadratic term in Euler's asymptotic expansion of the nth harmonic number by a simple modification of Young's elementary determination of the linear term.
A Quadratic Harmonic Approximation
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Organizations often collect private data and release aggregate statistics for the public's benefit. If no steps toward preserving privacy are taken, adversaries may use released statistics to deduce unauthorized information about the individuals described in the private dataset. Differentially private algorithms addr...
Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases
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Smart grids (SGs) promise to deliver dramatic improvements compared to traditional power grids thanks primarily to the large amount of data being exchanged and processed within the grid, which enables the grid to be monitored more accurately and at a much faster pace. The smart meter (SM) is one of the key devices th...
Smart Meter Data Privacy
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Aims: We present the first measurements of the solar-wind angular-momentum (AM) flux recorded by the Solar Orbiter spacecraft. Our aim is the validation of these measurements to support future studies of the Sun's AM loss. Methods: We combine 60-minute averages of the proton bulk moments and the magnetic field measur...
The solar-wind angular-momentum flux observed during Solar Orbiter's first orbit
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An optical metasurface consists of a dense and usually non-uniform layer of scattering nanostructures behaving as a continuous and extremely thin optical component, with predefined phase and intensity transmission/reflection profiles. To date, various sorts of metasurfaces (metallic, dielectric, Huygens-like, Panchar...
Metasurface optical characterization using quadriwave lateral shearing interferometry
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We create a continuous series of daily and monthly hemispheric sunspot numbers (HSNs) from 1874 to 2020, which will be continuously expanded in the future with the HSNs provided by SILSO. Based on the available daily measurements of hemispheric sunspot areas from 1874 to 2016 from Greenwich Royal Observatory and NOAA...
Hemispheric sunspot numbers 1874--2020
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An L- sequence of a graph $G $ is a sequence of distinct vertices $S = \{v_1, ... , v_k\}$ such that $N[v_i] \setminus \cup_{j=1}^{i-1} N(v_j) \neq \emptyset$. The length of the longest L-sequence is called the L-Grundy domination number, denoted $\gamma_{gr}^L(G)$. In this paper, we prove $\gamma_{gr}^L(G) \leq n(G)...
On the length of L-Grundy sequences
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The separation between RR Lyrae (RRLs) and Type II Cepheid (T2Cs) variables based on their period is debated. Both types of variable stars are distance indicators and we aim to promote the use of T2Cs as distance indicators in synergy with RRLs. We adopted new and existing optical and Near-Infrared (NIR) photometry o...
On the separation between RR Lyrae and Type II Cepheids and their importance for distance determination: the case of $\omega$ Cen
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The collective absorption and emission of light by an ensemble of atoms is at the heart of many fundamental quantum optical effects and the basis for numerous applications. However, beyond weak excitation, both experiment and theory become increasingly challenging. Here, we explore the regimes from weak excitation to...
Collective excitation and decay of waveguide-coupled atoms: from timed Dicke states to inverted ensembles
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Cytoarchitecture describes the spatial organization of neuronal cells in the brain, including their arrangement into layers and columns with respect to cell density, orientation, or presence of certain cell types. It allows to segregate the brain into cortical areas and subcortical nuclei, links structure with connec...
2D histology meets 3D topology: Cytoarchitectonic brain mapping with Graph Neural Networks
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IoT devices trigger real-time applications by receiving data from their vicinity. Modeling these applications in the form of workflows enables automating their procedure, especially for the business and industry. Depending on the features of the applications, they can be modeled in different forms, including single w...
WIDESim: A toolkit for simulating resource management techniques of scientific Workflows In Distributed Environments with graph topology
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Case-based learning is a powerful pedagogical method of creating dialogue between theory and practice. CBL is particularly suited to executive learning as it instigates critical discussion and draws out relevant experiences. In this paper we used a real-world case to teach Information Security Management to students ...
Teaching Information Security Management Using an Incident of Intellectual Property Leakage
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We study the distribution of complex eigenvalues $z_1,\ldots, z_N$ of random Hermitian $N\times N$ block band matrices with a complex deformation of a finite rank. Assuming that the width of the band $W$ grows faster than $\sqrt{N}$, we proved that the limiting density of $\Im z_1,\ldots, \Im z_N$ in a sigma-model ap...
Finite-rank complex deformations of random band matrices: sigma-model approximation
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The theory of circuit quantum electrodynamics has successfully analyzed superconducting circuits on the basis of the classical Lagrangian, and the corresponding quantized Hamiltonian, describing these circuits. In many simplified versions of these networks, the modeling involves a Lagrangian that is singular, describ...
Consistent Quantization of Nearly Singular Superconducting Circuits
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In this paper, by incorporating the general delay to the reaction term in the memory-based diffusive system, we propose a diffusive system with memory delay and general delay (e.g., digestion, gestation, hunting, migration and maturation delays, etc.). We first derive an algorithm for calculating the normal form of H...
The spatially homogeneous Hopf bifurcation induced jointly by memory and general delays in a diffusive system
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Single channel blind source separation (SCBSS) refers to separate multiple sources from a mixed signal collected by a single sensor. The existing methods for SCBSS mainly focus on separating two sources and have weak generalization performance. To address these problems, an algorithm is proposed in this paper to sepa...
One to Multiple Mapping Dual Learning: Learning Multiple Sources from One Mixed Signal
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We discuss a hypothetical existential threat from a 10 km diameter bolide discovered 6 months prior to impact with one case being a comet and the other being an asteroid. We show that an extension of our work on bolide fragmentation using an array of penetrators but modified with small nuclear explosive devices (NED)...
Don't Forget To Look Up
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Quantum-logic techniques for state preparation, manipulation, and non-destructive interrogation are increasingly being adopted for experiments on single molecular ions confined in traps. The ability to control molecular ions on the quantum level via a co-trapped atomic ion offers intriguing possibilities for new expe...
Molecular-ion quantum technologies
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We show a classification method for finite groupoids and discuss the cardinality of cosets and its relation with the index. We prove a generalization of the Lagrange's Theorem and establish a Sylow theory for groupoids.
Generalizations of Lagrange and Sylow Theorems for Groupoids
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We report on a high-resolution spectroscopic survey of ${}^{6}\textrm{Li}{}^{40}\textrm{K}$ molecules near the $2\textrm{S}+4\textrm{P}$ dissociation threshold and produce a fully empirical representation for the $\textrm{B}^{1}\Pi$ potential by connecting available short- and long-range data. The purpose is to ident...
Empirical LiK excited state potentials: connecting short range and near dissociation expansions
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A class of axial decomposition algebras with Miyamoto group generated by two Miyamoto automorphisms and three eigenvalues $0,1$ and $\eta$ is introduced and classified in the case with $\eta\notin\{0,1,\frac{1}{2}\}$. This class includes specializations of 2-generated axial algebras of Majorana type $(\xi,\eta)$ to t...
On primitive axial decomposition algebras of Majorana type with degenerate eigenvalues
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Inducing latent tree structures from sequential data is an emerging trend in the NLP research landscape today, largely popularized by recent methods such as Gumbel LSTM and Ordered Neurons (ON-LSTM). This paper proposes FASTTREES, a new general purpose neural module for fast sequence encoding. Unlike most previous wo...
FastTrees: Parallel Latent Tree-Induction for Faster Sequence Encoding
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This paper investigates the use of the reconfigurable dual-functional surface to guarantee the full-space secure transmission in non-orthogonal multiple access (NOMA) networks. In the presence of eavesdroppers, the downlink communication from the base station to the legitimate users is safeguarded by the simultaneous...
Safeguarding NOMA Networks via Reconfigurable Dual-Functional Surface under Imperfect CSI
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Spectral camera based on ghost imaging via sparsity constraints (GISC spectral camera) obtains three-dimensional (3D) hyperspectral information with two-dimensional (2D) compressive measurements in a single shot, which has attracted much attention in recent years. However, its imaging quality and real-time performanc...
Hyperspectral image reconstruction for spectral camera based on ghost imaging via sparsity constraints using V-DUnet
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Quantum dot-based spin qubits are resilient towards charge noise and are affected by magnetic noise only. However, environmental interaction leads to decoherence in these qubit systems. The external control parameters are directly related to the magnitude of decoherence. This in turn limits the range of values of tho...
Impact of AC Magnetic Field on Decoherence of Quantum Dot based Single Spin Qubit System
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Temporal camera relocalization estimates the pose with respect to each video frame in sequence, as opposed to one-shot relocalization which focuses on a still image. Even though the time dependency has been taken into account, current temporal relocalization methods still generally underperform the state-of-the-art o...
KFNet: Learning Temporal Camera Relocalization using Kalman Filtering
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A classical method for partition generating functions is developed into a tool with wide applications. New expansions of well-known theorems are derived, and new results for partitions with n copies of n are presented.
Separable Integer Partition Classes
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Most recent few-shot learning (FSL) methods are based on meta-learning with episodic training. In each meta-training episode, a discriminative feature embedding and/or classifier are first constructed from a support set in an inner loop, and then evaluated in an outer loop using a query set for model updating. This q...
Contrastive Prototype Learning with Augmented Embeddings for Few-Shot Learning
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This paper details the Leibniz generalization of Lie-theoretic results from Peggy Batten's 1993 dissertation. We first show that the multiplier of a Leibniz algebra is characterized by its second cohomology group with coefficients in the field. We then establish criteria for when the center of a cover maps onto the c...
Multipliers and Unicentral Leibniz Algebras
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Thanks to the wide range of features offered by web browsers, modern websites include various types of content such as JavaScript and CSS in order to create interactive user interfaces. Browser vendors also provided extensions to enhance web browsers with additional useful capabilities that are not necessarily mainta...
Understanding and Mitigating the Security Risks of Content Inclusion in Web Browsers
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The growing advances in VLSI technology and design tools have exponentially expanded the application domain of digital signal processing over the past 10 years. This survey emphasises on the architectural and performance parameters of VLSI for DSP applications such as speech processing, wireless communication, analog...
VLSI Systems for signal processing and Communications
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We determine the limiting distribution of the family of values $\frac{L'}{L}(1/2+\epsilon,\chi_D)$ as $D$ varies over fundamental discriminants. Here, $0<\epsilon<\frac12$, and $\chi_D$ is the real character associated with $D$. Moreover, we also establish an upper bound for the rate of convergence of this family t...
The Distribution of Values of $\frac{L'}{L}(1/2+\epsilon,\chi_D)$
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We select 456 gas-star kinematically misaligned galaxies from the internal Product Launch-10 of MaNGA survey, including 74 star-forming (SF), 136 green-valley (GV) and 206 quiescent (QS) galaxies. We find that the distributions of difference between gas and star position angles for galaxies have three local peaks at ...
SDSS-IV MaNGA: Global Properties of Kinematically Misaligned Galaxies
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We show, that the theoretical expression for the dispersion of collective excitations reported in [Phys. Rev. B {\bf 103}, 099901 (2021)], at variance with what was claimed in the paper, does not account for the energy fluctuations and does not tend in the long-wavelegth limit to the correct hydrodynamic dispersion l...
Comment on "Erratum: Collective modes and gapped momentum states in liquid Ga:Experiment, theory, and simulation"
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Organic molecules are widely present in the dense interstellar medium, and many have been synthesized in the laboratory on Earth under the conditions typical for an interstellar environment. Until now, however, only relatively small molecules of biological interest have been demonstrated to form experimentally under ...
A pathway to peptides in space through the condensation of atomic carbon
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We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-and-extrude modeling operations. Our model utilizes distinct Transformer architectures to encode topological, geometric, and extrusion variations of construction sequences into disentan...
SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks
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Data privacy is a trending topic in the internet era. Given such importance, many challenges emerged in order to collect, manage, process, and publish data. In this sense, personal data have got attention, and many regulations emerged, such as GDPR in the European Union and LGPD in Brazil. This regulation model aims ...
Second layer data governance for permissioned blockchains: the privacy management challenge
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The tilt angle of sunspot groups is crucial in the BL type dynamo. Some studies have shown that the tilt coefficient is anti-correlated with the cycle strength. If the anti-correlation exists, it will be shown to act as an effective nonlinearity of the BL-type dynamo to modulate the solar cycle. However, some studies...
Sunspot tilt angles revisited: Dependence on the solar cycle strength
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We give an overview of some recent interactions between the geometry of K3 surfaces and their Ricci-flat Kahler metrics and the dynamical study of K3 automorphisms with positive entropy.
Ricci-flat metrics and dynamics on K3 surfaces
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This is the second and final article on the tutorial on manipulator differential kinematics. In Part 1, we described a method of modelling kinematics using the elementary transform sequence (ETS), before formulating forward kinematics and the manipulator Jacobian. We then described some basic applications of the mani...
Manipulator Differential Kinematics: Part 2: Acceleration and Advanced Applications
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Named entity linking (NEL) in news is a challenging endeavour due to the frequency of unseen and emerging entities, which necessitates the use of unsupervised or zero-shot methods. However, such methods tend to come with caveats, such as no integration of suitable knowledge bases (like Wikidata) for emerging entities...
Strong Heuristics for Named Entity Linking
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We derive the first order phase space dependence of spin-orbit motion of a particle in an accelerator by expanding the Thomas-BMT equation. Different forms can be found in the literature and we show how these are related, and care is taken to include fringe fields. The advantages of using certain forms is demonstrate...
Different forms of first order spin-orbit motion and their utility in spin matching in electron storage rings
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Sandstone mechanical stability is of key concern in projects involving injections of CO2 in sandstone geological reservoirs, for the purpose of long-term storage. We developed a method to measure nanometer-scale deformations of sandstones in real time. We demonstrate that Berea sandstone, when hydrated, changes dimen...
Nanometer-Scale Deformations of Berea Sandstone under Moisture Content Variations
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This paper presents an approach to provide strong assurance of the secure execution of distributed event-driven applications on shared infrastructures, while relying on a small Trusted Computing Base. We build upon and extend security primitives provided by Trusted Execution Environments (TEEs) to guarantee authentic...
End-to-End Security for Distributed Event-Driven Enclave Applications on Heterogeneous TEEs
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We present a computational method for the simulation of the solidification of multicomponent alloys in the sharp-interface limit. Contrary to the case of binary alloys where a fixed point iteration is adequate, we hereby propose a Newton-type approach to solve the non-linear system of coupled PDEs arising from the ti...
A Numerical Method for Sharp-Interface Simulations of Multicomponent Alloy Solidification
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We present weak lensing shear catalogues from the fourth data release of the Kilo-Degree Survey, KiDS-1000, spanning 1006 square degrees of deep and high-resolution imaging. Our `gold-sample' of galaxies, with well-calibrated photometric redshift distributions, consists of 21 million galaxies with an effective number...
KiDS-1000 catalogue: Weak gravitational lensing shear measurements
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This work introduces Guardian Angel, an Android App that assists visually impaired people to avoid danger in complex traffic environment. The system, consisting of object detection by pretrained YOLO model, distance estimation and moving direction estimation, provides information about surrounding vehicles and alarms...
Guardian Angel: A Novel Walking Aid for the Visually Impaired
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Linear sets on the projective line have attracted a lot of attention because of their link with blocking sets, KM-arcs and rank-metric codes. In this paper, we study linear sets having two points of complementary weight, that is with two points for which the sum of their weights equals the rank of the linear set. As ...
Linear sets on the projective line with complementary weights
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The weighted ancestor problem is a well-known generalization of the predecessor problem to trees. It is known to require $\Omega(\log\log n)$ time for queries provided $O(n\mathop{\mathrm{polylog}} n)$ space is available and weights are from $[0..n]$, where $n$ is the number of tree nodes. However, when applied to su...
Weighted Ancestors in Suffix Trees Revisited
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This paper considers the problem of establishing $L^p$-improving inequalities for Radon-like operators in intermediate dimensions (i.e., for averages overs submanifolds which are neither curves nor hypersurfaces). Due to limitations in existing approaches, previous results in this regime are comparatively sparse and ...
$L^p$-improving estimates for Radon-like operators and the Kakeya-Brascamp-Lieb inequality
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Event perception tasks such as recognizing and localizing actions in streaming videos are essential for scaling to real-world application contexts. We tackle the problem of learning actor-centered representations through the notion of continual hierarchical predictive learning to localize actions in streaming videos ...
Actor-centered Representations for Action Localization in Streaming Videos
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Magnetars, a population of isolated neutron stars with ultra-strong magnetic fields of $\sim 10^{14}-10^{15}$ G, have been increasingly accepted to explain a variety of astrophysical transients. A nascent millisecond-period magnetar can release its spin-down energy and power bright sources such as Gamma-ray Bursts (G...
A hyper flare of a weeks-old magnetar born from a binary-neutron-star merger
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We study experimentally and theoretically the in-plane magnetic field dependence of the coupling between dots forming a vertically stacked double dot molecule. The InAsP molecule is grown epitaxially in an InP nanowire and interrogated optically at millikelvin temperatures. The strength of interdot tunneling, leading...
Magnetic tuning of tunnel coupling between InAsP double quantum dots in InP nanowires
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Some links between Lorentz and Finsler geometries have been developed in the last years, with applications even to the Riemannian case. Our purpose is to give a brief description of them, which may serve as an introduction to recent references. As a motivating example, we start with Zermelo navigation problem, where ...
An account on links between Finsler and Lorentz Geometries for Riemannian Geometers
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Calvera (1RXS J141256.0+792204) is an isolated neutron star detected only through its thermal X-ray emission. Its location at high Galactic latitude ($b=+37^\circ$) is unusual if Calvera is a relatively young pulsar, as suggested by its spin period (59 ms) and period derivative ($3.2 \times 10^{-15}$ Hz s$^{-1}$). Us...
NICER study of pulsed thermal X-rays from Calvera: a neutron star born in the Galactic halo?
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In this letter, we study efficient channel estimation and passive beamforming designs for a double-intelligent reflecting surface (IRS) aided single-user communication system, where a user communicates with an access point (AP) via the cascaded user-IRS 1-IRS 2-AP double-reflection link. First, a general channel esti...
Wireless Communication via Double IRS: Channel Estimation and Passive Beamforming Designs
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We present a convergence result for the finite volume method applied to a particular phase field problem suitable for simulation of pure substance solidification. The model consists of the heat equation and the phase field equation with a general form of the reaction term which encompasses a variety of existing model...
Convergence of the Finite Volume Method on Unstructured Meshes for a 3D Phase Field Model of Solidification
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We construct Green's functions for second order parabolic operators of the form $Pu=\partial_t u-{\rm div}({\bf A} \nabla u+ \boldsymbol{b}u)+ \boldsymbol{c} \cdot \nabla u+du$ in $(-\infty, \infty) \times \Omega$, where $\Omega$ is an open connected set in $\mathbb{R}^n$. It is not necessary that $\Omega$ to be boun...
Green's function for second order parabolic equations with singular lower order coefficients
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Given a Markov decision process (MDP) $M$ and a formula $\Phi$, the strategy synthesis problem asks if there exists a strategy $\sigma$ s.t. the resulting Markov chain $M[\sigma]$ satisfies $\Phi$. This problem is known to be undecidable for the probabilistic temporal logic PCTL. We study a class of formulae that can...
Strategy Synthesis for Global Window PCTL
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Ghost imaging (GI) is an intriguing imaging technology which achieves the object images through intensity correlation between reference patterns and bucket signal. Here, we propose a probability model to explain the imaging mechanism of this modality, by assuming that the reference patterns fulfill an arbitrary ident...
Unified probability explanation for ghost imaging with thermal light
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Within the past two decades, Gaussian process regression has been increasingly used for modeling dynamical systems due to some beneficial properties such as the bias variance trade-off and the strong connection to Bayesian mathematics. As data-driven method, a Gaussian process is a powerful tool for nonlinear functio...
An Introduction to Gaussian Process Models
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Finite Difference methods (FD) are one of the oldest and simplest methods for solving partial differential equations (PDE). Block Finite Difference methods (BFD) are FD methods in which the domain is divided into blocks, or cells, containing two or more grid points, with a different scheme used for each grid point, u...
Error Inhibiting Methods for Finite Elements
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We study the localization properties and the Anderson transition in the 3D Lieb lattice $\mathcal{L}_3(1)$ and its extensions $\mathcal{L}_3(n)$ in the presence of disorder. We compute the positions of the flat bands, the disorder-broadened density of states and the energy-disorder phase diagrams for up to 4 differen...
Localization, phases and transitions in the three-dimensional extended Lieb lattices
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Goldstone Apple Valley Radio Telescope (GAVRT) is a science education partnership among NASA, the Jet Propulsion Laboratory (JPL), and the Lewis Center for Educational Research (LCER), offering unique opportunities for K -12 students and their teachers. As part of a long-term Jupiter synchrotron radiation (JSR) flux ...
Goldstone Apple Valley Radio Telescope Monitoring Flux Density of Jupiter's Synchrotron Radiation during the Juno Mission
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Two main methods have been proposed to derive the acoustical radiation force and torque applied by an arbitrary acoustic field on a particle: The first one relies on the plane wave angular spectrum decomposition of the incident field (see [Sapozhnikov and Bailey, J. Acoust. Soc. Am. 133, 661 (2013)] for the force and...
Equivalence between angular spectrum-based and multipole expansion-based formulas of the acoustic radiation force and torque
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Solar grade silicon (SoG-Si) is a key material for the development of crystalline silicon photovoltaics (PV), which is expected to reach the tera-watt level in the next years and around 50TW in 2050. Upgraded metallurgical grade silicon (UMG-Si) has already demonstrated to be a viable alternative to standard polysili...
Upgraded Metallurgical Grade Silicon for solar electricity production: a comparative Life Cycle Assessment
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We provide a new online learning algorithm which utilizes online passive-aggressive learning (PA) and total-error-rate minimization (TER) for binary classification. The PA learning establishes not only large margin training but also the capacity to handle non-separable data. The TER learning on the other hand minimiz...
Online Passive-Aggressive Total-Error-Rate Minimization
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We classify mutation-finite cluster algebras with arbitrary coefficients of geometric type.
Cluster algebras of finite mutation type with coefficients
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For "almost all" sufficiently large $N,$ satisfying necessary congruence conditions and $k\geq 2$, we show that there is an {\bf asymptotic formula} for the number of solutions of the equation \begin{align*} \begin{split} &N=p_{1}^{k}+p_{2}^{k}+\cdots+p_{s}^{k}, \\ &\left|p_{i}-( N/s)^{1/k}\right|\leq (N/s)^{\theta...
On sums of $k$-th powers with almost equal primes
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Heating to high-lying states strongly limits the experimental observation of driving induced non-equilibrium phenomena, particularly when the drive has a broad spectrum. Here we show that, for entire families of structured random drives known as random multipolar drives, particle excitation to higher bands can be wel...
Suppression of inter-band heating for random driving
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A $k$-uniform tight cycle is a $k$-uniform hypergraph with a cyclic ordering of its vertices such that its edges are all the sets of size $k$ formed by $k$ consecutive vertices in the ordering. We prove that every red-blue edge-coloured $K_n^{(4)}$ contains a red and a blue tight cycle that are vertex-disjoint and to...
Towards Lehel's conjecture for 4-uniform tight cycles
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We investigate possible quantifications of R. C. James' classical work on bases and reflexivity of Banach spaces. By introducing new quantities measuring how far a basic sequence is from being shrinking and/or boundedly complete, we prove quantitative versions of James' famous characterisations of reflexivity in term...
Quantifying shrinking and boundedly complete bases
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We provide novel dissipativity conditions for bounding the incremental L-1 gain of systems. Moreover, we adapt existing results on the L-infinity gain to the incremental setting and relate the incremental L-1 and L-infinity gain bounds through system adjoints. Building on work on optimization based approaches to cons...
Polyhedral Estimation of L-1 and L-infinity Incremental Gains of Nonlinear Systems
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In order to increase mental health equity among the most vulnerable and marginalized communities, it is important to increase access to high-quality therapists. One facet of addressing these needs, is to provide timely feedback to clinicians as they interact with their clients, in a way that is also contextualized to...
Local dynamic mode of Cognitive Behavioral Therapy
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We examine the fluid phase behaviour of the binary mixture of hard superellipses using the scaled particle theory The superellipse is a general two dimensional convex object which can be tuned between circular and rectangular shapes continuously at a given aspect ratio. We find that the shape of the particle affects ...
Demixing and tetratic ordering in some binary mixtures of hard superellipses
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In this paper, we propose and analyze a linear second-order numerical method for solving the Allen-Cahn equation with a general mobility. The proposed fully-discrete scheme is carefully constructed based on the combination of first and second-order backward differentiation formulas with nonuniform time steps for temp...
A linear second-order maximum bound principle-preserving BDF scheme for the Allen-Cahn equation with a general mobility
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Enormous advances have been made in the past 20 years in our understanding of the random-field Ising model, and there is now consensus on many aspects of its behavior at least in thermal equilibrium. In contrast, little is known about its generalization to the random-field Potts model which has wide-ranging applicati...
Critical behavior of the three-state random-field Potts model in three dimensions
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