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Grain piles embody the complex mechanics and kinematics of disordered granular materials, including solid-like and fluid-like behaviours, complex kinematics, and preparation history-dependent stress variation. It is widely believed that the bulk of a growing pile is static and flow is confined to a thin layer at the surface, but very few studies have investigated the subsurface kinematics. Here we study the flow within conical grain piles by flow imaging experiments and particle dynamics simulations. We provide direct evidence of continuous plastic flow deep within piles as grains are poured from above, and show that the direction of flow varies smoothly from vertical at the symmetry axis to parallel to the surface at the periphery. Our findings provide new insight into the kinematics and rheology of granular media, including the nature of creep in seemingly solid-like regions, and have important implications for geophysical phenomena such as landslides and industrial processes.

Screening classifiers are increasingly used to identify qualified candidates in a variety of selection processes. In this context, it has been recently shown that, if a classifier is calibrated, one can identify the smallest set of candidates which contains, in expectation, a desired number of qualified candidates using a threshold decision rule. This lends support to focusing on calibration as the only requirement for screening classifiers. In this paper, we argue that screening policies that use calibrated classifiers may suffer from an understudied type of within-group unfairness -- they may unfairly treat qualified members within demographic groups of interest. Further, we argue that this type of unfairness can be avoided if classifiers satisfy within-group monotonicity, a natural monotonicity property within each of the groups. Then, we introduce an efficient post-processing algorithm based on dynamic programming to minimally modify a given calibrated classifier so that its probability estimates satisfy within-group monotonicity. We validate our algorithm using US Census survey data and show that within-group monotonicity can be often achieved at a small cost in terms of predi

We demonstrate that higgsino dark matter (DM) could be discovered within the next few years using the Cherenkov Telescope Array Observatory's soon-to-be-operational northern site (CTAO-North). A 1.1 TeV thermal higgsino is a highly motivated yet untested model of DM. Despite its strong theoretical motivation in supersymmetry and beyond, the higgsino is notoriously difficult to detect; it lies deep within the neutrino fog of direct detection experiments and could pose a challenge even for a future muon collider. We show that, in contrast, higgsino detection could be possible within this decade with CTAO-North in La Palma, Spain. The Galactic Center is the region where the dominant DM annihilation signature emerges, but it only barely rises above the horizon at the CTAO-North site. However, we project that this challenge can be overcome with large-zenith-angle observations at the northern site, enabling the conclusive detection of a higgsino signal by 2030 for a range of DM density profiles in the inner Galaxy.

Numerical galaxy formation simulations are sensitive to numerical methods and sub-grid physics models, making code comparison projects essential for quantifying uncertainties. Here, we evaluate GADGET4-OSAKA within the AGORA project framework by conducting a systematic comparison with its predecessor. We perform an isolated disk galaxy and a cosmological zoom-in run of a Milky Way-mass halo, following the multi-step AGORA calibration procedure. By systematically deconstructing the updated stellar feedback model, we demonstrate that mechanical momentum injection is necessary to suppress unphysical gas fragmentation and regulate star formation, yielding agreement with the Kennicutt-Schmidt relation. Meanwhile, stochastic thermal heating is essential for driving a hot, metal-enriched gaseous halo, thereby creating a multiphase circumgalactic medium that is absent in the predecessor code. In the cosmological context, we calibrate the simulation to match the stellar mass growth history targeted by the AGORA collaboration. The validated GADGET4-OSAKA simulation has been contributed to the AGORA CosmoRun suite, providing a new data point for understanding the impact of numerical and physi

Sustainability-driven computing research - encompassing equity, diversity, climate change, and social justice - is increasingly dismissed as woke or even dangerous in many sociopolitical contexts. As misinformation, ideological polarisation, deliberate ignorance and reactionary narratives gain ground, how can sustainability research in computing continue to exist and make an impact? This paper explores these tensions through Fictomorphosis, a creative story retelling method that reframes contested topics through different genres and perspectives. By engaging computing researchers in structured narrative transformations, we investigate how sustainability-oriented computing research is perceived, contested, and can adapt in a post-truth world.

Fingerspelling poses challenges for sign language processing due to its high-frequency motion and use for open-vocabulary terms. While prior work has studied fingerspelling recognition, there has been little attention to evaluating how well sign language translation models understand fingerspelling in the context of entire sentences -- and improving this capability. We manually annotate instances of fingerspelling within FLEURS-ASL and use them to evaluate the effect of two simple measures to improve fingerspelling recognition within American Sign Language to English translation: 1) use a model family (ByT5) with character- rather than subword-level tokenization, and 2) mix fingerspelling recognition data into the translation training mixture. We find that 1) substantially improves understanding of fingerspelling (and therefore translation quality overall), but the effect of 2) is mixed.

Social network analysis is pivotal for organizations aiming to leverage the vast amounts of data generated from user interactions on social media and other digital platforms. These interactions often reveal complex social structures, such as tightly-knit groups based on common interests, which are crucial for enhancing service personalization or fraud detection. Traditional methods like community detection and graph matching, while useful, often fall short of accurately identifying specific groups of users. This paper introduces a novel framework specifically designed to identify groups of users within transactional graphs by focusing on the contextual and structural nuances that define these groups.

We compute the tensor meson pole contributions to the Hadronic Light-by-Light piece of $a_μ$ in the purely hadronic region, using Resonance Chiral Theory. Given the differences between the dispersive and holographic groups determinations, we consider timely to present an alternative evaluation. In our approach, the lightest tensor meson nonet and two vector meson resonance nonets are considered in the chiral limit. Disregarding operators with derivatives, only the form factor $\mathcal{F}_1^T$ is non-vanishing, as assumed in the dispersive study. All parameters are determined by imposing a set of short-distance QCD constraints, and the radiative decay widths. In this case, we obtain (in units of $10^{-11}$): $ a_2$-pole: $-\left(1.02(10)_{\rm stat}(^{+0.00}_{-0.12})_{\rm syst}\right)$, $f_2$-pole: $-\left(3.2(3)_{\rm stat}(^{+0.0}_{-0.4})_{\rm syst}\right)$ and $f_2^\prime$-pole: $-\left(0.042(13)_{\rm stat}\right)$, which add up to $a_μ^{a_2+f_2+f_2^\prime \rm -pole}=-\left(4.3^{+0.3}_{-0.5}\right)$, in close agreement with the holographic result when truncated to $\mathcal F_1^T$ only. However, with an ad-hoc extended Lagrangian, that also generates $\mathcal F_3^T$, as in the ho

Facial recognition is one of the most academically studied and industrially developed areas within computer vision where we readily find associated applications deployed globally. This widespread adoption has uncovered significant performance variation across subjects of different racial profiles leading to focused research attention on racial bias within face recognition spanning both current causation and future potential solutions. In support, this study provides an extensive taxonomic review of research on racial bias within face recognition exploring every aspect and stage of the face recognition processing pipeline. Firstly, we discuss the problem definition of racial bias, starting with race definition, grouping strategies, and the societal implications of using race or race-related groupings. Secondly, we divide the common face recognition processing pipeline into four stages: image acquisition, face localisation, face representation, face verification and identification, and review the relevant corresponding literature associated with each stage. The overall aim is to provide comprehensive coverage of the racial bias problem with respect to each and every stage of the face

The origin and evolution of planetary rings and moons remains an active area of study, particularly as they relate to the impact history and volatile inventory of the outer solar system. The Uranian system contains a complex system of rings that are coplanar with the highly inclined planetary equator relative to the orbital plane. Uranus also harbors five primary regular moons that play an important role in the distribution of material that surrounds the planet. Here we present the results of a dynamical simulation suite for the Uranian system, intended to explore the interaction between the five primary regular moons and particles within the system. We identify regions of extreme mass loss within 40 planetary radii of Uranus, including eccentricity excitation of particle orbits at resonance locations that can promote moonlet formation within the rings. We calculate a total dynamical particle mass loss rate of 35\% within $0.5 \times 10^6$ years, and 40\% mass loss within $10^7$ years. We discuss the implications for post-impact material, including dynamical truncation of stable ring locations, and/or locations of moon formation promoted by dynamical excitation of ring material.

Crossing multiple planetary boundaries places us in a zone of uncertainty that is characterized by considerable fluctuations in climatic events. The situation is exacerbated by the relentless use of resources and energy required to develop digital infrastructures that have become pervasive and ubiquitous. We are bound to these infrastructures, dead technologies and negative commons, just as much as they bind us. Although their growth threatens the necessary reduction of our impact, we have a responsibility to maintain them until we can do without them. In university setting, as well as in any public organization, urban mines per se, we propose an IT architecture based on the exclusive use of unreliable waste from electrical and electronic equipment (WEEE) as a frugal alternative to the incessant replacement of devices. Powered by renewable energy, autonomous, robust, adaptable, and built on battle-tested open-source software, we envision this solution for a situation where use is bound to decline eventually, to close this damaging technological chapter. Digital technology, the idol of modern times, is to meet its twilight if we do not want to irrevocably alter the critical zone.

Although numerous investigations reveal the gas physisorption characteristics of porous materials and a variety of theories have also established to describe gas physisorption during the past century, the essence of physisorption behavior of gas within nanoscale space is still indistinct. We find that the physisorption behavior of complex molecular system of methane and carbon dioxide within nanoporous materials exhibits a quantum effect. Based on this quantum effect, we established a physisorption equation from the perspective of quantum mechanics to re-understand the basic principles of gas physisorption within nanopores. Energy level transition triggers gas physisorption, and non-uniform spatial distribution of energy-quantized molecules within nanopores dominates the gas physisorption behavior. The spatial distribution of gas molecules can be adjusted by temperature, pressure and potential energy field. This result contributes to understand and predict the physisorption behavior of CH4 and CO2 within nanoporous materials.

We generalize the model of Gallice and Monzon (2019) to incorporate a public goods game with groups, position uncertainty, and observational learning. Contributions are simultaneous within groups, but groups play sequentially based on their observation of an incomplete sample of past contributions. We show that full cooperation between and within groups is possible with self-interested players on a fixed horizon. Position uncertainty implies the existence of an equilibrium where groups of players conditionally cooperate in the hope of influencing further groups. Conditional cooperation implies that each group member is pivotal, so that efficient simultaneous provision within groups is an equilibrium.

We examine the properties of dark matter halos within a rich galaxy cluster using a high resolution simulation that captures the cosmological context of a cold dark matter universe. The mass and force resolution permit the resolution of 150 halos with circular velocities larger than 80 kms within the cluster's virial radius of 2 Mpc. This enables an unprecedented study of the statistical properties of a large sample of dark matter halos evolving in a dense environment. The cumulative fraction of mass attached to these halos varies from 0% at 200 kpc, to 13% at the virial radius. Even at this resolution the overmerging problem persists; halos that pass within 200 kpc of the cluster center are tidally disrupted. Additional substructure is lost at earlier epochs within the massive progenitor halos. The median ratio of apocentric to pericentric radii is 6:1; the orbital distribution is close to isotropic, circular orbits are rare, radial orbits are common. The orbits of halos are unbiased with respect to both position within the cluster and with the orbits of the smooth dark matter background and no velocity bias is detected. The tidal radii of surviving halos are generally well-fit us

Analysis of interstellar absorption lines observed in high-resolution {\em HST} spectra of nearby stars provides temperatures, turbulent velocities, and kinetic properties of warm interstellar clouds. Previous studies identified 15 warm partially ionized clouds within about 10~pc of the Sun and measured their mean thermal and kinematic properties. A new analysis of 100 interstellar velocity components reveals a wide range of temperatures and turbulent velocities within the Local Interstellar Cloud (LIC) and other nearby clouds. These variations appear to be random with Gaussian distributions. We find no trends of these properties with stellar distance, angle from the Galactic Center, the main source of EUV radiation (the star $ε$~CMa), the center of the LIC, or the direction of inflowing interstellar matter into the heliosphere. The spatial scale for temperature variations in the LIC is likely smaller than 5,100~au, a distance that the Sun will traverse in 1,000 years. Essentially all velocity components align with known warm clouds. We find that within 4~pc of the Sun, space is completely filled with partially ionized clouds, but at larger distances space is only partially filled

Probing the transport of fluids within confined domains is important in many areas including material science, catalysis, food science, and cell biology. The diffusion propagator fully characterizes the diffusion process, which is highly sensitive to the confining boundaries as well as the structure within enclosed pores. While magnetic resonance has been used extensively to observe various features of the diffusion process, its full characterization has been elusive. Here, we address this challenge by employing a special sequence of magnetic field gradient pulses for measuring the diffusion propagator, which allows for `listening to the drum' and determining not only the pore's shape but also diffusive dynamics within it.

We develop a method for constructing the Heavy Baryon Chiral Perturbation Theory Lagrangian (L_{HBChPT}), to a given chiral order, within HBChPT. We work within SU(2) theory, with only the pion field interacting with the nucleon. The main difficulties, which are solved, are to develop techniques for implementing charge conjugation invariance, and for taking the nucleon on shell, both within the nonrelativistic formalism. We obtain complete lists of independent terms in L_{HBChPT} through O(q^3) for off- shell nucleons. Then, eliminating equation-of-motion (eom) terms at the relativistic and nonrelativistic level (both within HBChPT), we obtain L_{HBCHPT} for on-shell nucleons, through O(q^3). The extension of the method (to obtain on-shell L_{HBChPT} within HBChPT) to higher orders is also discussed.

We address the problem of load shaping within a network of coupled microgrids (MGs) in a bilevel optimisation framework. To this end, we consider the charging/discharging rates of residential energy storage devices within each MG on the lower level and the power exchange among neighbouring MGs on the upper level as optimisation variables. We improve a previously developed model such that the maximal amount of exchanged power does not depend on the power demand, thus, increasing the flexibility within the network, and adapt the corresponding bidirectional optimisation scheme accordingly. For efficiency, standard distributed optimisation routines are used for the optimisation on the lower level; the power exchange problem on the upper level is replaced by parallelisable small-scale quadratic programmings. We prove global convergence of the optimisation scheme and illustrate the potential of the approach in a numerical case study based on real-world data.

In this work, we find the light front densities for momentum and forces, including pressure and shear forces, within hadrons. This is achieved by deriving relativistically correct expressions relating these densities to the gravitational form factors $A(t)$ and $D(t)$ associated with the energy momentum tensor. The derivation begins from the fundamental definition of density in a quantum field theory, namely the expectation value of a local operator within a spatially-localized state. We find that it is necessary to use the light front formalism to define a density that corresponds to internal hadron structure. When using the instant form formalism, it is impossible to remove the spatial extent of the hadron wave function from any density, and -- even within instant form dynamics -- one does not obtain a Breit frame Fourier transform for a properly defined density. Within the front formalism, we derive new expressions for various mechanical properties of hadrons, including the mechanical radius, as well as for stability conditions. The multipole ansatz for the form factors is used as an example to illustrate all of these findings.