Miracle-dz/UniFAR-FTUs huggingface dataset:
Force distributions in two dimensional granular packs

In this article, the caustics method and holo-photoelasticity method are used to investigate the distribution of contact forces inside a pack of discrete square cells submitted to a compressive load. Our results demonstrate that the collective response of the pack contradicts the traditional elasticity theory predictions and supports a description by equations of the parabolic type. These results are significant to solve problems in soil mechanics.
Numerical Simulation of Supersonic Boundary Layer Stability with Applied Electromagnetic Field in a Weakly Ionized Flow

This paper investigates, by direct numerical simulation, the effect of an imposed electromagnetic field on a weakly ionized supersonic boundary layer in the range of 2.7 to 3.0 in a supersonic plasma wind tunnel, located at the non-equilibrium thermodynamics laboratory, under J. W. Rich and I. Adamovich, at the Ohio State University . The main emphasis of the study is on MHD effects on the supersonic boundary layer. The imposed magnetic field is generated by a magnet flush-mounted in the tunnel side wall and the electric field is generated in this supersonic flow, pre-ionized by the RF discharge, by applying a DC field using electrodes flush-mounted in the top and bottom walls, perpendicular both to the flow velocity and the magnetic field. The electrical conductivity of the flow varies between 0.1 and 0.5 mho/m. The magnetic Reynolds number of the flow is small so that the induced magnetic field is neglected. The governing equations of the MHD flow, which are the Navier-Stokes equations with the applied electromagnetic force terms, are computed by a third-order upwinded numerical scheme. A series of cases with different imposed magnetic fields, electric fields and electrical conductivity, for two different stagnation pressures at the nozzle entrance, have been investigated for the mean flow. Calculations on the second mode instability are planned. It is found that in the presence of electric fields and the absence of magnetic fields, i.e. joule heating, the flow at the centerline heats up strongly leading to retardation in the flow velocity. The boundary layer thickness also increases and the mean Mach number is brought down. In the presence of magnetic field only, it is observed that the boundary layer profile changes depending on the direction of the field and, also the effect on the boundary layer is less in magnitude compared to the effect of joule heating on the same. The magnetic field is limited in its ability to mitigate the effects of an imposed electric field on the flow field. Unsteady calculations are currently underway and comprehensive conclusions on effects of external electromagnetic fields are expected in future. We have also undertaken three dimensional calculations to understand the effects of the sidewall on the flow profile.
David Lewis Meets Hamilton and Jacobi

I commemorate David Lewis by discussing an aspect of modality within analytical mechanics, which is closely related to his work on counterfactuals. This concerns the way Hamilton‐Jacobi theory uses ensembles, i.e. sets of possible initial conditions. (A companion paper discusses other aspects of modality in analytical mechanics that are equally related to Lewis’s work.)
A methodology for constructing confldence regions with partially identifled models

We propose a methodology for constructing confldence regions with partially identifled models of general form. The region is obtained by inverting a test of internal consistency of the econometric structure. We develop a dilation bootstrap methodology to deal with sampling uncertainty without reference to the hypothesized economic structure, and apply a duality principle to reduce the dimensionality of the remaining deterministic problem. As a result, the confldence region becomes easily computable, and the methodology can be applied to the estimation of models with sample selection, censored observations and to games with multiple equilibria.
Enhancing Student Writing and Computer Programming with LATEX and MATLAB in Multivariable Calculus

Abstract Written communication and computer programming are foundational components of an undergraduate degree in the mathematical sciences. All lower-division mathematics courses at our institution are paired with computer-based writing, coding, and problem-solving activities. In multivariable calculus we utilize MATLAB and LATEX to have students explore mathematics visually, gain programming skills, and write technical reports on their findings. In this article we give a summary of the pedagogy, tools, and logistics of combining technical writing and computer programming with sophomore-level calculus content with the goals of improving student writing, coding, and mathematical understanding.
CONSTRUCTION OF TEST-CONTROL TREATMENT BLOCK DESIGNS WHEN v k >

Ting and Notz (1988) have only considered the construction of block designs for comparing test treatments with a control when the block size v k > , and have also given a catalogue of A optimal designs for such comparisons. In this paper, we have constructed such a type of designs using a new method called cyclic shifts or set(s) of shifts. The important feature of this method is that the properties of a design can be obtained from the off-diagonal elements of the concurrence matrix without constructing the actual blocks of the design. These newly proposed designs possess the property of A optimality for some specific values of v , b and block size k ) ( v
First Language Test Bias? Comparing French-Speaking and Polish-Speaking Participants’ Performance on the Peabody Picture Vocabulary Test

Cognates are known to facilitate second language acquisition and use, as learners tend to assign to a new L2 word the meaning of a similar L1word. Consequently, for L2 tests that rely largely on lexical items, performance may prove inflated for examinees whose L1 shares many cognates with the language being tested. This article examines the possibility of L1 bias on the Peabody Picture Vocabulary Test (PPVT), a well-established measure of receptive vocabulary knowledge in English. To investigate if performance on the PPVT is affected by cognates, we tested 293 speakers of French and 150 speakers of Polish, since those two languages differ markedly in the number of cognates they share with English. After demonstrating that both groups yield clearly distinct response patterns, descriptive and multivariate statistics confirmed that cognate items enhance test performance: the items with the highest score difference in favour of a language group overwhelmingly consist of cognates for that group only. Mantel-Haenszel and logistic regression show that items that are cognates for one of the two groups are more likely to show differential item functioning than the average items. The results suggest that scores on L2 vocabulary-based tests could be biased by the presence of cognates with the examinee’s first language.
Relating French Immersion Teacher Practices to Better Student Oral Production

This study examined seven Louisiana kindergarten immersion teachers’ practices to examine students’ oral target language production and compare the oral production elicited when different instructional practices were used over a single semester. Three rounds of three 20-minute observations in three different contexts – circle time, direct instruction, and centre time – were conducted in seven kindergarten teachers’ classrooms at the beginning, middle, and end of the semester. Using the Association canadienne des professeurs d’immersion (ACPI) accepted language proficiency levels, the researchers focused on students’ global capacity to communicate. Findings suggest that teacher practices influenced student oral language production and identify specific, practical suggestions for improving language immersion teaching practices and immersion teacher training.
Improved Bounds on the Elastic Properties of Porous Media with the Variational Equivalent Inclusion Method (VEIM)

The equivalent inclusion method (EIM) was initially proposed by Moschovidis and Mura [12] to find an approximate solution to the problem of two ellipsoidal inhomogeneities embedded in an infinite medium. More recently, it has been applied to large assemblies of inhomogeneities [7]. Although less accurate than traditional (e.g. finite elements) numerical techniques, the equivalent inclusion method is an attractive solution for numerical homogenization problems. Indeed, it leads to relatively small linear systems, and does not require time-consuming preliminaries (such as mesh creation). However, the standard EIM has some shortcomings which are mainly due to the fact that point collocation techniques are used to discretize the underlying integral equation [6, 12]. In contrast, the Variational Equivalent Inclusion Method (VEIM) introduced here uses Galerkin techniques to carry out this discretization. In this paper, we briefly recall the fundamentals of the standard EIM. We then present the VEIM and show that it can lead to rigorous bounds on the macroscopic properties. Finally, some illustrations of the method are presented.
Un théorème sur les zéros des matrices non négatives

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Sensitivity analysis for improving nanomechanical photonic transducers biosensors

The achievement of high sensitivity and highly integrated transducers is one of the main challenges in the development of high-throughput biosensors. The aim of this study is to improve the final sensitivity of an opto-mechanical device to be used as a reliable biosensor. We report the analysis of the mechanical and optical properties of optical waveguide microcantilever transducers, and their dependency on device design and dimensions. The selected layout (geometry) based on two butt-coupled misaligned waveguides displays better sensitivities than an aligned one. With this configuration, we find that an optimal microcantilever thickness range between 150 nm and 400 nm would increase both microcantilever bending during the biorecognition process and increase optical sensitivity to 4.8 × 10−2 nm−1, an order of magnitude higher than other similar opto-mechanical devices. Moreover, the analysis shows that a single mode behaviour of the propagating radiation is required to avoid modal interference that could misinterpret the readout signal.
Pragmatic solutions for syntactic problems: Understanding some L2 syntactic errors in terms of discourse-pragmatic deficits

Contemporary research in generative second language (L2) acquisition has attempted to address observable target-deviant aspects of L2 grammars within a UG-continuity framework (e.g. Lardiere 2000; Schwartz 2003; Sprouse 2004; Prevost & White 1999, 2000). With the aforementioned in mind, the independence of pragmatic and syntactic development, independently observed elsewhere (e.g. Grodzinsky & Reinhart 1993; Lust et al. 1986; Pacheco & Flynn 2005; Serratrice, Sorace & Paoli 2004), becomes particularly interesting. In what follows, I examine the resetting of the Null-Subject Parameter (NSP) for English learners of L2 Spanish. I argue that insensitivity to associated discoursepragmatic constraints on the discursive distribution of overt/null subjects accounts for what appear to be particular errors as a result of syntactic deficits. It is demonstrated that despite target-deviant performance, the majority must have native-like syntactic competence given their knowledge of the Overt Pronoun Constraint (Montalbetti 1984), a principle associated with the Spanish-type setting of the NSP.
Sensitive detection of millimeter wave electric field by driving trapped surface-state electrons

Sensitive detection of electromagnetic wave electric field plays an important role for electromagnetic communication and sensing. Here, we propose a quantum sensor to sensitively detect the electric field of the millimeter (mm) wave. The quantum sensor consists of many surface-state electrons trapped individually on liquid helium by a scalable electrode-network at the bottom of the helium film. On such a chip, each of the trapped electrons can be manipulated by the biased dc-current to deliver the strong spin-orbit couplings. The mm wave signal to be detected is applied to non-dispersively drive the orbital states of the trapped electrons, just resulting in the Stark shifts of the dressed spin-orbital states. As a consequence, the electric field of the applied mm wave could be detected sensitively by using the spin-echo interferometry of the long-lived spin states of the electrons trapped on liquid helium. The reasonable accuracy of the detection and also the feasibility of the proposal are discussed.
HRS-Bench: Holistic, Reliable and Scalable Benchmark for Text-to-Image Models

In recent years, Text-to-Image (T2I) models have been extensively studied, especially with the emergence of diffusion models that achieve state-of-the-art results on T2I synthesis tasks. However, existing benchmarks heavily rely on subjective human evaluation, limiting their ability to holistically assess the model’s capabilities. Furthermore, there is a significant gap between efforts in developing new T2I architectures and those in evaluation. To address this, we introduce HRS-Bench, a concrete evaluation benchmark for T2I models that is Holistic, Reliable, and Scalable. Unlike existing benchmarks that focus on limited aspects, HRS-Bench measures 13 skills that can be categorized into five major categories: accuracy, robustness, generalization, fairness, and bias. In addition, HRS-Bench covers 50 scenarios, including fashion, animals, transportation, food, and clothes. We evaluate nine recent large-scale T2I models using metrics that cover a wide range of skills. A human evaluation aligned with 95% of our evaluations on average was conducted to probe the effectiveness of HRS-Bench. Our experiments demonstrate that existing models often struggle to generate images with the desired count of objects, visual text, or grounded emotions. We hope that our benchmark help ease future text-to-image generation research. The code and data are available at https://eslambakr.github. io/hrsbench.github. io/.
Kasner-like description of spacelike singularities in spherically symmetric spacetimes with scalar matter

We study the properties of spacelike singularities in spherically symmetric spacetimes obeying the Einstein equations, in the presence of matter. We consider in particular matter described by a scalar field, both in the presence of an electromagnetic field and without. We prove that if a spacelike singularity obeying several reasonable assumptions is formed, then the Hawking mass, the Kretschmann scalar, and the matter fields have inverse polynomial blow-up rates near the singularity that may be described precisely. Furthermore, one may view the resulting spacetime in the context of the BKL heuristics regarding space-like singularities in relativistic cosmology. In particular, near any point $p$ on the singular boundary in our spherically symmetric spacetime, we obtain a leading order BKL-type expansion, including a description of Kasner exponents associated to $p$. This provides a rigorous description of a detailed correspondence between Kasner-like singularities most often associated to the cosmological setting, and the singularities observed in (spherically symmetric) gravitational collapse. Moreover, we outline a program concerning the study of the stability and instability of spacelike singularities in the latter picture, both outside of spherical symmetry and within (where the electromagnetic field acts as a proxy for angular momentum) - in particular we signify the importance of cosmological phenomena including subcritical regimes and Kasner bounces in the collapse setting.
Defrosting frozen stars: Spectrum of internal fluid modes

The frozen star model provides a classical description of a regularized black hole and is based upon the idea that regularizing the singularity requires deviations from the Schwarzschild geometry which extend over horizon-sized scales, as well as maximally negative radial pressure as an equation of state. The frozen star has also been shown to be ultra-stable against perturbations; a feature that can be attributed to the equation of state and corresponds to this model mimicking a black hole in the limit $\hbar\to 0$ or, equivalently, the limit of infinite Newton's constant. Here, we ``defrost'' the frozen star by allowing its radial pressure to be perturbatively less negative than maximal. This modification to the equation of state is implemented by appropriately deforming the background metric so as to allow the frozen star to mimic a quantum black hole at finite $\hbar$ and Newton's constant. As a consequence, the defrosted star acquires a non-trivial spectrum of oscillatory perturbations. To show this, we first use the Cowling approximation to obtain generic equations for the energy density and pressure perturbations of a static, spherically symmetric background with an anisotropic fluid. The particular setting of a deformed frozen star is then considered, for which the dispersion relation is obtained to leading order in terms of the deviation from maximal pressure. The current results compare favorably with those obtained earlier for the collapsed polymer model, whose strongly non-classical interior is argued to provide a microscopic description of the frozen and defrosted star geometries.
One-Shot High-Fidelity Talking-Head Synthesis with Deformable Neural Radiance Field

Talking head generation aims to generate faces that maintain the identity information of the source image and imitate the motion of the driving image. Most pioneering methods rely primarily on 2D representations and thus will inevitably suffer from face distortion when large head rotations are encountered. Recent works instead employ explicit 3D structural representations or implicit neural rendering to improve performance under large pose changes. Nevertheless, the fidelity of identity and expression is not so desirable, especially for novel-view synthesis. In this paper, we propose HiDe-NeRF, which achieves high-fidelity and free-view talking-head synthesis. Drawing on the recently proposed Deformable Neural Radiance Fields, HiDe-NeRF represents the 3D dynamic scene into a canonical appearance field and an implicit deformation field, where the former comprises the canonical source face and the latter models the driving pose and expression. In particular, we improve fidelity from two aspects: (i) to enhance identity expressiveness, we design a generalized appearance module that leverages multi-scale volume features to preserve face shape and details; (ii) to improve expression preciseness, we propose a lightweight deformation module that explicitly decouples the pose and expression to enable precise expression modeling. Extensive experiments demonstrate that our proposed approach can generate better results than previous works. Project page: https://www.waytron. net/hidenerf/
Correcting for bias due to mismeasured exposure in mediation analysis with a survival outcome

Mediation analysis is widely used in health science research to evaluate the extent to which an intermediate variable explains an observed exposure-outcome relationship. However, the validity of analysis can be compromised when the exposure is measured with error. Motivated by the Health Professionals Follow-up Study (HPFS), we investigate the impact of exposure measurement error on assessing mediation with a survival outcome, based on the Cox proportional hazards outcome model. When the outcome is rare and there is no exposure-mediator interaction, we show that the uncorrected estimators of the natural indirect and direct effects can be biased into either direction, but the uncorrected estimator of the mediation proportion is approximately unbiased as long as the measurement error is not large or the mediator-exposure association is not strong. We develop ordinary regression calibration and risk set regression calibration approaches to correct the exposure measurement error-induced bias when estimating mediation effects and allowing for an exposure-mediator interaction in the Cox outcome model. The proposed approaches require a validation study to characterize the measurement error process. We apply the proposed approaches to the HPFS (1986-2016) to evaluate extent to which reduced body mass index mediates the protective effect of vigorous physical activity on the risk of cardiovascular diseases, and compare the finite-sample properties of the proposed estimators via simulations.
Another Vertical View: A Hierarchical Network for Heterogeneous Trajectory Prediction via Spectrums

With the fast development of AI-related techniques, the applications of trajectory prediction are no longer limited to easier scenes and trajectories. More and more heterogeneous trajectories with different representation forms, such as 2D or 3D coordinates, 2D or 3D bounding boxes, and even high-dimensional human skeletons, need to be analyzed and forecasted. Among these heterogeneous trajectories, interactions between different elements within a frame of trajectory, which we call the ``Dimension-Wise Interactions'', would be more complex and challenging. However, most previous approaches focus mainly on a specific form of trajectories, which means these methods could not be used to forecast heterogeneous trajectories, not to mention the dimension-wise interaction. Besides, previous methods mostly treat trajectory prediction as a normal time sequence generation task, indicating that these methods may require more work to directly analyze agents' behaviors and social interactions at different temporal scales. In this paper, we bring a new ``view'' for trajectory prediction to model and forecast trajectories hierarchically according to different frequency portions from the spectral domain to learn to forecast trajectories by considering their frequency responses. Moreover, we try to expand the current trajectory prediction task by introducing the dimension $M$ from ``another view'', thus extending its application scenarios to heterogeneous trajectories vertically. Finally, we adopt the bilinear structure to fuse two factors, including the frequency response and the dimension-wise interaction, to forecast heterogeneous trajectories via spectrums hierarchically in a generic way. Experiments show that the proposed model outperforms most state-of-the-art methods on ETH-UCY, Stanford Drone Dataset and nuScenes with heterogeneous trajectories, including 2D coordinates, 2D and 3D bounding boxes.