Miracle-dz/UniFAR-FTUs huggingface dataset:
Fractional transconductance via nonadiabatic topological Cooper pair pumping

Many robust physical phenomena in quantum physics are based on topological invariants arising due to intriguing geometrical properties of quantum states. Prime examples are the integer and fractional quantum Hall effects that demonstrate quantized Hall conductances, associated with topology both in the single particle and the strongly correlated many-body limit. Interestingly, the topology of the integer effect can be realized in superconducting multiterminal systems, but a proposal for the more complex fractional counterpart is lacking. In this work, we theoretically demonstrate how to achieve fractional quantized transconductance in an engineered chain of Josephson junctions. Crucially, similar to the stabilization of the conductance plateaus in Hall systems by disorder, we obtain stable transconductance plateaus as a result of non-adiabatic Landau-Zener transitions. We furthermore show that the fractional plateaus are robust to disorder and study the optimal operation regime to observe these effects. Our proposal paves the way for quantum simulation of exotic many-body out-of-equilibrium states in Josephson junction systems.
A Non-linear MPC Local Planner for Tractor-Trailer Vehicles in Forward and Backward Maneuvering

Designing a local planner to control tractor-trailer vehicles in forward and backward maneuvering is a challenging control problem in the research community of autonomous driving systems. Considering a critical situation in the stability of tractor-trailer systems, a practical and novel approach is presented to design a non-linear MPC(NMPC) local planner for tractor-trailer autonomous vehicles in both forward and backward maneuvering. The tractor velocity and steering angle are considered to be control variables. The proposed NMPC local planner is designed to handle jackknife situations, avoiding multiple static obstacles, and path following in both forward and backward maneuvering. The challenges mentioned above are converted into a constrained problem that can be handled simultaneously by the proposed NMPC local planner. The direct multiple shooting approach is used to convert the optimal control problem(OCP) into a non-linear programming problem(NLP) that IPOPT solvers can solve in CasADi. The controller performance is evaluated through different backup and forward maneuvering scenarios in the Gazebo simulation environment in real-time. It achieves asymptotic stability in avoiding static obstacles and accurate tracking performance while respecting path constraints. Finally, the proposed NMPC local planner is integrated with an open-source autonomous driving software stack called AutowareAi.
DYST (Did You See That?): An Amplified Covert Channel That Points To Previously Seen Data

Covert channels are unforeseen and stealthy communication channels that enable manifold adversary scenarios. However, they can also allow the exchange of confidential information by journalists. All covert channels described until now therefore need to craft seemingly legitimate information flows for their information exchange, mimicking unsuspicious behavior. In this paper, we present DYST, which represents a new class of covert channels we call history covert channels jointly with the new paradigm of covert channel amplification. History covert channels can communicate almost exclusively by pointing to unaltered legitimate traffic created by regular network nodes. Only a negligible fraction of the covert communication process requires the transfer of actual covert channel information by the covert channel's sender. This allows, for the first time, an amplification of the covert channel's message size, i.e., minimizing the fraction of actually transferred secret data by a covert channel's sender in relation to the overall secret data being exchanged. We extend the current taxonomy for covert channels to show how history channels can be categorized. We describe multiple scenarios in which history covert channels can be realized, theoretically analyze the characteristics of these channels and show how their configuration can be optimized for different implementations. We further evaluate the robustness and detectability of history covert channels.
Dispersion relation and wave equation for attenuative elliptically anisotropic media

The P-wave slowness and group-velocity surfaces in elliptically anisotropic media are ellipsoids. Elliptical anisotropy is convenient to use as the reference medium in perturbation methods designed to solve P-wave wave-propagation problems for transverse isotropy (TI). Here, we make the elliptically anisotropic TI model attenuative and discuss the corresponding P-wave dispersion relation and the wave equation. Our analysis leads to two conditions in terms of the Thomsen-type parameters, which guarantee that the P-wave slowness surface and the dispersion relation satisfy elliptical equations. We also obtain the viscoacoustic wave equation for such elliptically anisotropic media and solve it for point-source radiation using the correspondence principle. Numerical examples validate the proposed elliptical conditions and illustrate the behavior of the P-wavefield in attenuative elliptical TI models.
Adiabatic preparation of fractional Chern insulators from an effective thin-torus limit

We explore the quasi one-dimensional (thin torus, or TT) limit of fractional Chern insulators (FCIs) as a starting point for their adiabatic preparation in quantum simulators. Our approach is based on tuning the hopping amplitude in one direction as an experimentally amenable knob to dynamically change the effective aspect ratio of the system. Similar to the TT limit of fractional quantum Hall (FQH) systems in the continuum, we find that the hopping-induced TT limit adiabatically connects the FCI state to a trivial charge density wave (CDW) ground state. This adiabatic path may be harnessed for state preparation schemes relying on the initialization of a CDW state followed by the adiabatic decrease of a hopping anisotropy. Our findings are based on the calculation of the excitation gap in a number of FCI models, both on a lattice and consisting of coupled wires. By analytical calculation of the gap in the limit of strongly anisotropic hopping, we show that its scaling is compatible with the preparation of large size FCIs for sufficiently large hopping anisotropy. Our numerical simulations in the framework of exact diagonalization explore the full anisotropy range to corroborate these results.
Structure of Charge Density Waves in La$_{1.875}$Ba$_{0.125}$CuO$_4$

Although charge-density wave (CDW) correlations exist in several families of cuprate supercon-ductors, they exhibit substantial variation in CDW wavevector and correlation length, indicating a key role for CDW-lattice interactions. We investigated this interaction in La$_{1.875}$Ba$_{0.125}$CuO$_4$ using single crystal x-ray diffraction to collect a large number of CDW peak intensities, and determined the Cu and La/Ba atomic distortions induced by the formation of CDW order. Within the CuO$_2$ planes, the distortions involve a periodic modulation of the Cu-Cu spacing along the direction of the ordering wave vector. The charge ordering within the copper-oxygen layer induces an out-of-plane breathing modulation of the surrounding lanthanum layers, which leads to a related distortion on the adjacent copper-oxygen layer. Our result implies that the CDW-related structural distortions do not remain confined to a single layer but rather propagate an appreciable distance through the crystal. This leads to overlapping structural modulations, in which CuO$_2$ planes exhibit distortions arising from the orthogonal CDWs in adjacent layers as well as distortions from the CDW within the layer itself. We attribute this striking effect to the weak c-axis charge screening in cuprates and suggest this effect could help couple the CDW between adjacent planes in the crystal.
Automatically Annotating Indoor Images with CAD Models via RGB-D Scans

We present an automatic method for annotating images of indoor scenes with the CAD models of the objects by relying on RGB-D scans. Through a visual evaluation by 3D experts, we show that our method retrieves annotations that are at least as accurate as manual annotations, and can thus be used as ground truth without the burden of manually annotating 3D data. We do this using an analysis-by-synthesis approach, which compares renderings of the CAD models with the captured scene. We introduce a ’cloning procedure’ that identifies objects that have the same geometry, to annotate these objects with the same CAD models. This allows us to obtain complete annotations for the Scan-Net dataset and the recent ARKitScenes dataset. We will release these annotations publicly, as we believe they will be very useful for the computer vision community.
Nonreciprocal magnetoacoustic waves in synthetic antiferromagnets with Dzyaloshinskii-Moriya interaction

The interaction between surface acoustic waves (SAWs) and spin waves (SWs) in a piezoelectric/magnetic thin film heterostructure yields potential for the realization of novel microwave devices and applications in magnonics. In the present work, we investigate the SAW-SW interaction in a Pt/Co(2 nm)/Ru(0.85 nm)/Co(4 nm)/Pt synthetic antiferromagnet (SAF) composed of two ferromagnetic layers with different thicknesses separated by a thin nonmagnetic Ru spacer layer. Because of the combined presence of interfacial Dzyaloshinskii--Moriya interaction (iDMI) and interlayer dipolar coupling fields, the optical SW mode shows a large nondegenerate dispersion relation for oppositely propagating SWs. Due to SAW-SW interaction, we observe nonreciprocal SAW transmission in the piezoelectric/SAF hybrid device. The equilibrium magnetization directions of both Co layers are manipulated by an external magnetic field to set a ferromagnetic, canted, or antiferromagnetic configuration. This has a strong impact on the SW dispersion, its nonreciprocity, and SAW-SW interaction. The experimental results are in agreement with a phenomenological SAW-SW interaction model, which considers the interlayer exchange coupling, iDMI, and interlayer dipolar coupling fields of the SWs.
The analytic theory of linear resonant absorption

The analytic theory of resonant absorption developed by Piliya (1966) is reviewed to resolve the discrepancy with numerical calculations. The equivalence of this approach with an alternative one by Hirsch and Shmoys (1965) is demonstrated. It is shown by numerical evaluation that provided exact solutions of the complementary functions are used, the analytic theory yields results in excellent agreement with numerical calculations.
NarrativeTime: Dense Temporal Annotation on a Timeline

For the past decade, temporal annotation has been sparse: only a small portion of event pairs in a text was annotated. We present NarrativeTime, the first timeline-based annotation framework that achieves full coverage of all possible TLinks. To compare with the previous SOTA in dense temporal annotation, we perform full re-annotation of TimeBankDense corpus, which shows comparable agreement with a significant increase in density. We contribute TimeBankNT corpus (with each text fully annotated by two expert annotators), extensive annotation guidelines, open-source tools for annotation and conversion to TimeML format, baseline results, as well as quantitative and qualitative analysis of inter-annotator agreement.
Sparsely-gated MoE Layers for CNN Interpretability

Sparsely-gated Mixture of Expert (MoE) layers have been recently successfully applied for scaling large trans-formers, especially for language modeling tasks. An in-triguing side effect of sparse MoE layers is that they convey inherent interpretability to a model via natural expert specialization. In this work, we apply sparse MoE layers to CNNs for computer vision tasks and analyze the resulting effect on model interpretability. To stabilize MoE training, we present both soft and hard constraint-based approaches. With hard constraints, the weights of certain experts are allowed to become zero, while soft constraints balance the contribution of experts with an additional auxiliary loss. As a result, soft constraints handle expert utilization better and support the expert specialization process, while hard constraints maintain more generalized experts and increase overall model performance. Our ﬁndings demonstrate that experts can implicitly focus on individual sub-domains of the input space. For example, experts trained for CIFAR-100 image classiﬁcation specialize in recognizing different domains such as ﬂowers or animals without previous data clustering. Experiments with RetinaNet and the COCO dataset further indicate that object detection experts can also specialize in detecting objects of distinct sizes.
A Multiple-View Geometric Model for Specularity Prediction on General Curved Surfaces

Specularity prediction is essential to many computer vision applications, giving important visual cues usable in Augmented Reality (AR), Simultaneous Localisation and Mapping (SLAM), 3D reconstruction and material modeling. However, it is a challenging task requiring numerous information from the scene including the camera pose, the geometry of the scene, the light sources and the material properties. Our previous work addressed this task by creating an explicit model using an ellipsoid whose projection fits the specularity image contours for a given camera pose. These ellipsoid-based approaches belong to a family of models called JOint-LIght MAterial Specularity (JOLIMAS), which we have gradually improved by removing assumptions on the scene geometry. However, our most recent approach is still limited to uniformly curved surfaces. This paper generalises JOLIMAS to any surface geometry while improving the quality of specularity prediction, without sacrificing computation performances. The proposed method establishes a link between surface curvature and specularity shape in order to lift the geometric assumptions made in previous work. Contrary to previous work, our new model is built from a physics-based local illumination model namely Torrance-Sparrow, providing an improved reconstruction. Specularity prediction using our new model is tested against the most recent JOLIMAS version on both synthetic and real sequences with objects of various general shapes. Our method outperforms previous approaches in specularity prediction, including the real-time setup, as shown in the supplementary videos.
Traducteurs dans la société de l’information : Évolutions et interdépendances

Les nouvelles missions du traducteur dans les domaines de l’audiovisuel et du multimedia se conjuguent avec une evolution de son metier, sous des contraintes d’efficacite et d’efficience accrues. Une etude de cas multiples revele les interdependances entre trois poles d’evolution du metier de traducteur. La transformation des aptitudes a traduire et la maitrise de nouveaux outils techniques entretiennent une dynamique contradictoire d’attenuation et de renforcement des frontieres de la specialisation. L’interaction entre les nouveaux modes d’organisation du travail de traduction et les aptitudes a traduire conduit a une specialisation des traducteurs independants et a une polyvalence des personnels permanents. Enfin, la maitrise de nouveaux outils techniques et les nouveaux modes d’organisation se renforcent mutuellement.
Simulation of the A–X and B–X transition emission spectra of the InBr molecule for diagnostics in low-pressure plasmas

Inductively coupled low-pressure discharges containing InBr have been investigated spectroscopically. In order to obtain plasma parameters such as the vibrational and rotational temperature of the InBr molecule, the emission spectra of the and the transitions have been simulated. The program is based on the molecular constants and takes into account vibrational states up to v = 24. The required Franck–Condon factors and vibrationally resolved transition probabilities have been computed solving the Schrödinger equation using the Born–Oppenheimer approximation. The ground state density of the InBr molecule in the plasma has been determined from absorption spectra using effective transition probabilities for the A–X and B–X transition according to the vibrational population. The obtained densities agree well with densities derived from an Arrhenius type vapour pressure equation.
Ulva L. biodiversity in the central Mediterranean Sea: cryptic species and new records

ABSTRACT Ulva L. species are problematic to identify since they have cryptic morphologies with few distinctive features, as well as significant intraspecific variation. In this study, we report two new records for the Maltese islands: the heterokont benthic multicellular algae Ulva torta (Mertens) Trevisan and Ulva californica Wille, which were isolated and grown in culture from incubated natural substrata. This study includes an integrative systematics approach using both morphology and barcode sequencing of the nuclear internal transcribed spacer (ITS) region (ITS1-5.8S-ITS2), the chloroplast RUBISCO LSU (rbcL) gene and the elongation factor Tu (tufA). Subsequent phylogenetic analyses, supported the separation of these two species from other closely-related congeners that have previously been reported from the Maltese islands. RÉSUMÉ Biodiversité des Ulva L. en Méditerranée centrale: espèces cryptiques et signalements nouveaux. Certaines espèces d'Ulva L. sont difficiles à identifier car elles sont cryptiques, soit par manque de caractères distinctifs, soit en raison de variation phénotypique intraspécifique. Cette étude documente deux nouvelles espèces pour les îles maltaises: les algues multicellulaires benthiques hétérokontes Ulva torta (Mertens) Trevisan et Ulva californica Wille, qui ont été isolées et cultivées en culture à partir de substrats naturels incubés. Cette étude comprend une approche intégrative utilisant la morphologie aussi bien que le séquençage d'ADN de la région de l'espaceur transcrit interne nucléaire (ITS) (ITS1-5.8S-ITS2), du gène chloroplastique RUBISCO LSU (rbcL) et du facteur d'élongation Tu (tufA). Ces deux espèces ont été séparées de leurs proches congénères des îles maltaises grâce aux analyses phylogénétiques.
A review of disparities in peripheral artery disease and diabetes–related amputations during the COVID-19 pandemic

The Coronavirus Disease 2019 (COVID-19) pandemic has profoundly affected healthcare delivery. In addition to the significant morbidity and mortality associated with acute illness from COVID-19, the indirect impact has been far-reaching, including significant disruptions in chronic disease care. As a result of pandemic disruptions in healthcare, vulnerable populations and minorities have faced health inequalities. The aim of this review is to investigate how the COVID-19 pandemic has impacted vulnerable populations with limb-threatening peripheral artery disease and diabetic foot infections.
Automatic Recognition of Density and Weave Pattern of Yarn-Dyed Fabric

Abstract Under the production mode of small-batch and multi-item, the recognition of yarn-dyed fabric patterns is a crucial task in the textile industry. In this article, an automatic recognition system based on pixel-level features is proposed to recognize the density, the weave pattern, and the color pattern. In this system, the fabric images are captured by a scanner. First, a method based on the Hough transform is used to correct the skew of the yarns, including warp and weft. Second, the yarns and nodes are located in the enhanced images with a brightness-projection method. The density can be calculated by using the results. Then, the type of each node is identified based on the boundary information. We can obtain the weave pattern after knowing the type of each node. Finally, the fuzzy C-means algorithm is used to determine the color of each node, and thus we obtain the color pattern of the yarn-dyed fabric. Experimental results demonstrate that the proposed recognition system is effective for detecting the structural parameters of yarn-dyed fabric.
The progress and prospect for sustainable development of waste wool resources

With the growth of the world population and the improvement of living standards, the demand for global textiles has been increasing rapidly. Although natural fibers are affected by the development of synthetic fibers, wool still occupies a certain share in the textile industry and is one of the most indispensable materials. However, many postindustrial and post-consumer waste wool textiles will be produced. The conventional treatment method is landfill or incineration, which is not conducive to economic, environmental, and social development. To counter this problem, many measures and methods have been adapted for the reuse of waste resources. This article provides a review on waste wool recycling and summarizes two main directions for reuse. Waste wool can be used for thermal and sound insulation materials, reinforced composite materials, or adsorbent materials to purify contaminated water which rely on fiber properties. Keratin extracted from waste wool can be applied for the production of high-value products such as functional finishing agents, organic fertilizers, regenerated protein films/fibers, or smart wearable electronic devices. Meanwhile, future development trends and the demand of waste wool recycling are also discussed. Continuous research and exploration are still needed for effective management of waste wool resources and to turn them into useful and valuable materials or products.
A Method for Inverse Aerofoil and Cascade Design by Surface Vorticity

Surface vorticity theory, normally considered as an analysis tool, has been modified to operate as a design tool whereby the shapes of components may be found to produce a prescribed surface velocity in incompressible flow. The basis of the method is presented and checked against classical solutions for cylindrical and diamond shaped struts with fully attached flow. A procedure for turbomachine blade or aerofoil design is outlined and illustrated with back checks via Martensen’s method. The method allows specification of velocity distribution on either or both surfaces of the body. If only one surface of an aerofoil or blade is prescribed, the user is allowed to specify profile thickness also.Copyright © 1982 by ASME
Nonparametric models and methods for nonlinear analysis of covariance

SUMMARY A fully nonparametric model for nonlinear analysis of covariance is proposed. The term nonlinear means that the covariate influences the response in a possibly nonlinear and nonpolynomial fashion, while the term fully nonparametric implies that the distributions for each factor level combination and covariate value are not restricted to comply with any parametric or semiparametric model. The possibility of different shapes of covariate effect in different factor level combinations is also allowed. This generality is useful whenever modelling assumptions such as proportional odds, or linearity and homoscedasticity appear suspect. In the context of this nonparametric model hypotheses, of no main effect, no interaction and no simple effect, which adjust for the covariate values are defined and test statistics are developed. Both the response and the covariate are allowed to be ordinal. The test statistics are based on averages over the covariate values of certain NadarayaWatson-type nonparametric regression quantities and asymptotically they have, under their respective null hypotheses, a central Z2-distribution. Simulation results show that the statistics have good power properties. The procedures are demonstrated on two real datasets.