Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolving power: A general approach to compare the discriminating capacity of threshold-free evaluation metrics

This paper introduces the concept of resolving power to describe the capacity of an evaluation metric to discriminate between models of similar quality. This capacity depends on two attributes: 1. The metric’s response to improvements in model quality (its signal), and 2. The metric’s sampling variability (its noise). The paper deﬁnes resolving power as a metric’s sampling uncertainty scaled by its signal. Resolving power’s primary application is to compare the discriminating capacity of threshold-free evaluation metrics, such as the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). A simulation study compares the AUROC and the AUPRC in a variety of contexts. The analysis suggests that the AUROC generally has greater resolving power, but that the AUPRC is superior in some conditions, such as those where high-quality models are applied to low prevalence outcomes. The paper concludes by proposing an empirical method to estimate resolving power that can be applied to any dataset and any initial classiﬁcation model.
Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation

Stabilizer simulation can efficiently simulate an important class of quantum circuits consisting exclusively of Clifford gates. However, all existing extensions of this simulation to arbitrary quantum circuits including non-Clifford gates suffer from an exponential runtime.To address this challenge, we present a novel approach for efficient stabilizer simulation on arbitrary quantum circuits, at the cost of lost precision. Our key idea is to compress an exponential sum representation of the quantum state into a single abstract summand covering (at least) all occurring summands. This allows us to introduce an abstract stabilizer simulator that efficiently manipulates abstract summands by over−approximating the effect of circuit operations including Clifford gates, non-Clifford gates, and (internal) measurements.We implemented our abstract simulator in a tool called Abstraqt and experimentally demonstrate that Abstraqt can establish circuit properties intractable for existing techniques.
Flux-resolved Spectropolarimetric Evolution of the X-Ray Pulsar Hercules X-1 Using IXPE

We conduct a spectropolarimetric study of the accreting X-ray pulsar Hercules X-1 using observations with the Imaging X-ray Polarimetry Explorer (IXPE). IXPE monitored the source in three different epochs, sampling two “Main-on” and one “Short-on” state of the well-known super-orbital period of the source. We find that the 2–7 keV polarization fraction increases significantly from ∼7% to 9% in the Main-on state to ∼15%–19% in the Short-on state, while the polarization angle remains more or less constant or changes slightly, ∼47°–59°, in all three epochs. The polarization degree and polarization angle are consistent with being energy independent for all three epochs. We propose that in the Short-on state, when the neutron star is partially blocked by the disk warp, the increase in the polarization fraction can be explained as a result of the preferential obstruction of one of the magnetic poles of the neutron star.
The Rado Multiplicity Problem in Vector Spaces over Finite Fields

We study an analogue of the Ramsey multiplicity problem for additive structures, establishing the minimum number of monochromatic $3$-APs in $3$-colorings of $\mathbb{F}_3^n$ and obtaining the first non-trivial lower bound for the minimum number of monochromatic $4$-APs in $2$-colorings of $\mathbb{F}_5^n$. The former parallels results by Cumings et al.~\cite{CummingsEtAl_2013} in extremal graph theory and the latter improves upon results of Saad and Wolf~\cite{SaadWolf_2017}. Lower bounds are notably obtained by extending the flag algebra calculus of Razborov~\cite{razborov2007flag}.
The Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web Archives

The Archive Query Log (AQL) is a previously unused, comprehensive query log collected at the Internet Archive over the last 25 years. Its first version includes 356 million queries, 137 million search result pages, and 1.4 billion search results across 550 search providers. Although many query logs have been studied in the literature, the search providers that own them generally do not publish their logs to protect user privacy and vital business data. Of the few query logs publicly available, none combines size, scope, and diversity. The AQL is the first to do so, enabling research on new retrieval models and (diachronic) search engine analyses. Provided in a privacy-preserving manner, it promotes open research as well as more transparency and accountability in the search industry.
Oscillatory flows in compliant conduits at arbitrary Womersley number

We develop a theory of fluid--structure interaction (FSI) between an oscillatory Newtonian fluid flow and a compliant conduit. We consider the canonical geometries of a 2D channel with a deformable top wall and an axisymmetric deformable tube. Focusing on the hydrodynamics, we employ a linear relationship between wall displacement and hydrodynamic pressure, which has been shown to be suitable for a leading-order-in-slenderness theory. The slenderness assumption also allows the use of lubrication theory, and the flow rate is related to the pressure gradient (and the tube/wall deformation) via the classical solutions for oscillatory flow in a channel and in a tube (attributed to Womersley). Then, by two-way coupling the oscillatory flow and the wall deformation via the continuity equation, a one-dimensional nonlinear partial differential equation (PDE) governing the instantaneous pressure distribution along the conduit, without \textit{a priori} assumptions on the magnitude of the oscillation frequency (\textit{i.e.}, at arbitrary Womersley number). We find that the cycle-averaged pressure (for harmonic pressure-controlled conditions) deviates from the expected steady pressure distribution, suggesting the presence of a streaming flow. An analytical perturbative solution for a weakly deformable conduit is obtained to rationalize how FSI induces such streaming. In the case of a compliant tube, the results obtained from the proposed reduced-order PDE and its perturbative solutions are validated against three-dimensional, two-way-coupled direct numerical simulations. We find good agreement between theory and simulations for a range of dimensionless parameters characterizing the oscillatory flow and the FSI, demonstrating the validity of the proposed theory of oscillatory flows in compliant conduits at arbitrary Womersley number.
A paradigm for well-balanced schemes for traveling waves emerging in parabolic biological models

We propose a methodology for designing well-balanced numerical schemes to investigate traveling waves in parabolic models from mathematical biology. We combine well-balanced techniques for parabolic models known in the literature with the so-called LeVeque-Yee formula as a dynamic estimate for the spreading speed. This latter formula is used to consider the evolution problem in a moving frame at each time step, where the equations admit stationary solutions, for which well-balanced techniques are suitable. Then, the solution is shifted back to the stationary frame in a well-balanced manner. We illustrate this methodology on parabolic reaction-diffusion equations, such as the Fisher/Kolmogorov-Petrovsky-Piskunov Equation, and a class of equations with a cubic reaction term that exhibit a transition from pulled to pushed waves. We show that the numerical schemes capture in a consistent way simultaneously the wave speed and, to an extent, the so-called Bramson delay.
Comparison results for Hessian equations via symmetrization

where the λ’s are the eigenvalues of the Hessian matrix D2u of u and Sk is the kth elementary symmetric function. For example, for k = 1, S1(Du) = 1u, while, for k = n, Sn(D 2u) = detD2u. Equations involving these operators, and some more general equations of the form F(λ1, . . . , λn) = f in , (1.2) have been widely studied by many authors, who restrict their considerations to convenient cones of solutions with respect to which the operator in (1.2) is elliptic. Following [25] we define the cone 0k of ellipticity for (1.1) to be the connected component containing the positive cone 0 = {λ ∈ R : λi > 0 ∀i = 1, . , n} of the set where Sk is positive. Thus 0k is an open, convex, symmetric cone with vertex at the origin and ∂Sk ∂λi (λ) > 0 on 0k, ∀i = 1, . , n.
Fast Convergence of Random Reshuffling under Over-Parameterization and the Polyak-Łojasiewicz Condition

Modern machine learning models are often over-parameterized and as a result they can interpolate the training data. Under such a scenario, we study the convergence properties of a sampling-without-replacement variant of stochastic gradient descent (SGD) known as random reshuffling (RR). Unlike SGD that samples data with replacement at every iteration, RR chooses a random permutation of data at the beginning of each epoch and each iteration chooses the next sample from the permutation. For under-parameterized models, it has been shown RR can converge faster than SGD under certain assumptions. However, previous works do not show that RR outperforms SGD in over-parameterized settings except in some highly-restrictive scenarios. For the class of Polyak-\L ojasiewicz (PL) functions, we show that RR can outperform SGD in over-parameterized settings when either one of the following holds: (i) the number of samples ($n$) is less than the product of the condition number ($\kappa$) and the parameter ($\alpha$) of a weak growth condition (WGC), or (ii) $n$ is less than the parameter ($\rho$) of a strong growth condition (SGC).
Thermodynamic Cucker-Smale ensemble with unit speed and its sufficient framework for collision avoidance

We investigate a Cucker-Smale-type flocking model for multi-agent systems that move with constant speed. The model incorporates both kinematic observables and internal energy (temperatures) in the agents' interactions. Traditionally, collision avoidance in the absence of speed limitation is achieved by introducing singularities into the communication rule. However, when a unit speed constraint is applied, the mechanism of collision avoidance can differ, and the singularity may not necessarily prevent collisions. In this paper, we propose a framework that generates collision avoidance, asymptotic flocking, thermal equilibrium, and strict spacing between agents, subject to sufficient conditions expressed by the initial condition, system parameters, and degree of singularity.
Polytuplet Loss: A Reverse Approach to Training Reading Comprehension and Logical Reasoning Models

Throughout schooling, students are tested on reading comprehension and logical reasoning. Students have developed various strategies for completing such exams, some of which are generally thought to outperform others. One such strategy involves emphasizing relative accuracy over absolute accuracy and can theoretically produce the correct answer without full knowledge of the information required to solve the question. This paper examines the effectiveness of applying such a strategy to train transfer learning models to solve reading comprehension and logical reasoning questions. The models were evaluated on the ReClor dataset, a challenging reading comprehension and logical reasoning benchmark. While previous studies targeted logical reasoning skills, we focus on a general training method and model architecture. We propose the polytuplet loss function, an extension of the triplet loss function, to ensure prioritization of learning the relative correctness of answer choices over learning the true accuracy of each choice. Our results indicate that models employing polytuplet loss outperform existing baseline models. Although polytuplet loss is a promising alternative to other contrastive loss functions, further research is required to quantify the benefits it may present. 1
Miniature insect flight

Approximately half of the existing winged-insect species are of very small size (wing length about 0.3-4 mm); they are referred to as miniature insects. Yet until recently, much of what we know about the mechanics of insect flight was derived from studies on relatively large insects, such as hoverflies, honey bees and hawkmoths. Because of their very small size, many miniature insects fly at a Reynolds number (Re) on the order of 10 or less. At such a low Re, the viscous effect of the air is very large: A miniature insect moves through the air as would a bumble bee move through mineral oil. Miniature insects must use new flapping mode and new aerodynamic mechanisms to fly. Over the past decade, much work has been done in the study of the mechanics of flight in miniature insects: novel flapping modes have been discovered and new mechanisms of aerodynamic force generation have been revealed; progress has also been made on the fluid-mechanics related flight problems, such as flight power requirements and flight dynamic stability. This article reviews these developments and discusses potential future directions.
Assessing stellar yields in Galaxy chemical evolution: Observational stellar abundance patterns

One-zone Galactic Chemical Evolution (GCE) models have provided useful insights on a great wealth of average abundance patterns in many environments, especially for the Milky Way and its satellites. However, the scatter of such abundance patterns is still a challenging aspect to reproduce. The leading hypothesis is that dynamics is a likely major source of the dispersion. In this work we test another hypothesis, namely that different assumptions on yield modeling may be at play simultaneously. We compare whether the abundance patterns spanned by the models are consistent with those observed in Galactic data. First, we test the performance of recent yield tabulations, and we show which of these tabulations best fit Galactic stellar abundances. We then group the models and test if yield combinations match data scatter and standard deviation. On a fixed Milky-Way-like parametrization of NuPyCEE, we test a selection of yields for the three dominant yield sets: low-to-intermediate mass stars, massive stars, and Type Ia supernovae. We also include the production of r-process elements by neutron star mergers. We explore the statistical properties spanned by such yields. We identify the differences and commonalities among yield sets. We define criteria that estimate whether an element is in agreement with the data, or if the model overestimates or underestimates it in various redshift bins. While it is true that yields are a major source of uncertainty in GCE models, the scatter of abundances in stellar spectra cannot be explained by a simple averaging of runs across yield prescriptions.
The Hausdorff Measure and Upper Convex Density of a Class of Self-Similar Sets on the Plane

This paper deals with the exact computation of Hausdbrff measure of a class of self-similar sets on the plane. Under some conditions, we get the natural covering is the best one, and the Hausdorff measure of those sets are equal to (2s)~/(1/2), where s is its Hausdorff dimension.
Two-layer adaptive trajectory tracking controller for quadruped robots on slippery terrains

Quadruped robots are commonly employed in challenging and unpredictable environments where their stability and controllability could be compromised during locomotion. During task execution, the robot might face non-controllable conditions or loss of balance either due to dynamic contact events or aggressive control efforts, e.g. during trajectory tracking. In this work, we propose a robust adaptive trajectory tracking controller that consists of two prioritized layers of adaptation aimed at maintaining stability during dynamic (possibly unstable) contact of one or more supporting legs. The aforementioned key-feature can serve as the basis for avoiding slippage during dynamic locomotion. The proposed method is a novel lightweight analytical solution that assumes no prior knowledge of the friction properties of the surface. This is accomplished by considering the slippage probability as extracted by our previous work on contact state estimation in order to avoid non-controllable conditions. We evaluate our approach through simulations and validate it with real experiments, demonstrating robustness in multiple scenarios.
Equivalence of Additive and Multiplicative Coupling in Spiking Neural Networks

Spiking neural network models characterize the emergent collective dynamics of circuits of biological neurons and help engineer neuro-inspired solutions across fields. Most dynamical systems’ models of spiking neural networks typically exhibit one of two major types of interactions: First, the response of a neuron’s state variable to incoming pulse signals (spikes) may be additive and independent of its current state. Second, the response may depend on the current neuron’s state and multiply a function of the state variable. Here we reveal that deterministic spiking neural network models with additive coupling are equivalent to models with multiplicative coupling for simultaneously modified intrinsic neuron time evolution. As a consequence, the same collective dynamics can be attained by state-dependent multiplicative and constant (state-independent) additive coupling. Such a mapping enables the transfer of theoretical results between spiking neural network models with different types of interaction mechanisms and at the same time extends the option space for hardware implementation or modeling. By allowing to choose the coupling type or neuron type that is the simplest one to implement in a given practical situation where a specific dynamic or functionality is required, it potentially allows simpler or more effective engineering applications.
Analysis of polarization anisotropy along the c axis in the photoluminescence of wurtzite GaN

The polarization of photoluminescence (PL) was investigated on (1100) GaN grown by metalorganic vapor phase epitaxy. We found that the PL intensity and wavelength have polarization dependence parallel and perpendicular to the c axis. We quantitatively analyzed the dependence and found that, since the crystal field of wurtzite GaN along the c axis is strong enough to fix the |z〉 axis of p functions at the c axis, the difference in symmetry between three valence bands appears as the polarization anisotropy in radiative emission, even in bulk GaN.
In search of a sustainable alternative for meat production: understanding the purchase intention of meat from transhumance origin

Abstract In recent years, meat production and consumption has become a topic of intense debate for environmental, animal welfare and health reasons. Research on more sustainable alternatives to meat production has increased. Our goal is to gain insight into the purchase of meat from transhumance livestock and to explore the main factors driving this process. This type of meat is more respectful towards the environment and animal welfare, provides financial stability for many rural families and helps preserve an activity that is part of the cultural heritage in rural areas. From a methodological point of view, we have adopted the theoretical alphabet theory model proposed by Zepeda and Deal in 2009 to explain sustainable purchase behavior. For this purpose, we created two different models, one for lamb meat and one for beef meat. The data come from an online survey of Spanish meat consumers. We applied a structural equation modeling technique to test the suggested model and hypothesis. The results allow us to conclude that the alphabet theory is a suitable theory for our data. The level of knowledge on transhumance and contextual factors, such as the content of fat or the type of meat, impact the creation of attitudes towards this type of livestock farming, but demographic variables do not. In both models, buying meat with a designation of origin and buying meat at specialty retailers are habits that positively influence purchase intention. Our results are highly relevant to help meat of transhumant origin reach the markets and to differentiate it from other products.
Promoting female physician-scientists: Perspectives from a unique learning environment

© The Author(s), 2023. Published by Cambridge University Press on behalf of The Association for Clinical and Translational Science. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. Promoting female physician-scientists: Perspectives from a unique learning environment
Group presentation, $p$-adic analytic groups and lattices in $\mathrm{SL}_2(\mathbf{C})$

groups by using their pro-p completions. This method is based on the observation that if (X; R) is a presentation of the finitely generated (f.g.) group F, then (X; R), considered as a presentation for a pro-p group is actually a presentation for T,;, the pro-p completion of F. First we prove a generalization of a theorem of Golod and Shafarevich (cf. [H]). THEOREM. Let G be a p-adic analytic pro-p group different from Zp (= the p-adic integers). If (X; R) is a minimal presentation of G then 1X;2 IRI? 2
Graph-Optimizer: Towards Predictable Large-Scale Graph Processing Workloads

Graph and hardware-specific optimisations lead to orders of magnitude improvements in performance, energy, and cost over conventional graph processing methods. Typical big data platforms, such as Apache MapReduce and Apache Spark, rely on generic primitives, exhibiting poor performance and high financial and environmental costs. Even optimised basic graph operations (BGOs) lack the tools to combine them towards real-world applications. Furthermore, graph topology and dynamics (i.e., changing the number and content of vertices and edges) lead to high variability in computational needs. Primitive predictive models demonstrate they can enable algorithm selection and advanced auto-scaling techniques to ensure better performance, but no such models exist for energy consumption. In this work, we present the Graph-Optimizer tool. Graph-Optimizer uses optimised BGOs and composition rules to capture and model the workload. It combines the workload model with hardware and infrastructure models, predicting performance and energy consumption. Combined with design space exploration, such predictions select codesigned workload implementations to fit a requested performance objective and guarantee their performance bounds during execution.
From UML/MARTE Specifications to ESL HW/SW Co-Design: Early Functional Verification and Timing Validation

The continuous adoption of embedded systems in the most diverse application domains contributes to the increasing complexity of their development. Hardware/Software Co-Design methodologies are usually employed to tackle the challenges deriving from even more stringent functional and non-functional requirements. Using these methodologies, several validation and verification steps can be carried out early in the design process using a unified, technology-independent system model. This work investigates the possibility of integrating formal functional verification and timing validation in a Hardware/Software Co-Design flow at the system-level of abstraction. Specifically, we introduce Co-V&V, namely an additional step that consists of two phases: (i) a transformation from UML/MARTE to UPPAAL Timed Automata, and (ii) a preliminary functional verification and timing validation that exploits the UPPAAL verifier. We describe the Co-V&V step through a case study characterized by a component-based architecture and reactive behavior. The verification and validation conducted with UPPAAL indicate that our approach is particularly effective in discovering design flaws located in the communication protocol as well as those arising from the internal behavior of components.