Miracle-dz/UniFAR-FTUs huggingface dataset:
Recoil momentum of an atom absorbing light in a gaseous medium and the Abraham-Minkowski debate

We discuss a fundamental question regarding the Abraham-Minkowski debate about the momentum of light in a medium: If an atom in a gas absorbs a photon, what is the momentum transferred to it? We consider a classical model for the internal degrees of freedom of the absorbing atom, computing the absorbed energy and momentum using the Lorentz force law due to the microscopic electromagnetic fields. Each non-absorbing atom from the gas is treated as a dielectric sphere, with the set of atoms forming a linear, dielectric, non-magnetic, and non-absorbing medium with a refractive index $n$ close to one. Our numerical results indicate that if the atoms are classically localized, the average absorbed momentum increases with $n$, but is smaller than Minkowski's momentum $np_0$, $p_0$ being the photon momentum in vacuum. However, experiments performed with Bose-Einstein condensates [Phys. Rev. Lett. $\mathbf{94}$, 170403 (2005)] are consistent with the atom absorbing Minkowski's momentum. We argue that there is no contradiction between these results since, in a Bose-Einstein condensate, the atoms are in a quantum state spatially superposed in a relatively large volume, forming a ``continuous'' medium. In this sense, the experimental verification of an atomic momentum recoil compatible with Minkowski's momentum would be a quantum signature of the medium state.
The Runge-Kutta discontinuous Galerkin method with compact stencils for hyperbolic conservation laws

In this paper, we develop a new type of Runge--Kutta (RK) discontinuous Galerkin (DG) method for solving hyperbolic conservation laws. Compared with the original RKDG method, the new method features improved compactness and allows simple boundary treatment. The key idea is to hybridize two different spatial operators in an explicit RK scheme, utilizing local projected derivatives for inner RK stages and the usual DG spatial discretization for the final stage only. Limiters are applied only at the final stage for the control of spurious oscillations. We also explore the connections between our method and Lax--Wendroff DG schemes and ADER-DG schemes. Numerical examples are given to confirm that the new RKDG method is as accurate as the original RKDG method, while being more compact, for problems including two-dimensional Euler equations for compressible gas dynamics.
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer

Generative adversarial networks (GANs) learn a target probability distribution by optimizing a generator and a discriminator with minimax objectives. This paper addresses the question of whether such optimization actually provides the generator with gradients that make its distribution close to the target distribution. We derive metrizable conditions, sufficient conditions for the discriminator to serve as the distance between the distributions by connecting the GAN formulation with the concept of sliced optimal transport. Furthermore, by leveraging these theoretical results, we propose a novel GAN training scheme, called slicing adversarial network (SAN). With only simple modifications, a broad class of existing GANs can be converted to SANs. Experiments on synthetic and image datasets support our theoretical results and the SAN's effectiveness as compared to usual GANs. Furthermore, we also apply SAN to StyleGAN-XL, which leads to state-of-the-art FID score amongst GANs for class conditional generation on ImageNet 256$\times$256.
The Hamiltonian Structure and Euler-Poincare Formulation of the Valsov-Maxwell and Gyrokinetic System

We present a new variational principle for the gyrokinetic system, similar to the Maxwell-Vlasov action presented in Ref. 1. The variational principle is in the Eulerian frame and based on constrained variations of the phase space fluid velocity and particle distribution function. Using a Legendre transform, we explicitly derive the field theoretic Hamiltonian structure of the system. This is carried out with the Dirac theory of constraints, which is used to construct meaningful brackets from those obtained directly from Euler-Poincare theory. Possible applications of these formulations include continuum geometric integration techniques, large-eddy simulation models and Casimir type stability methods. __________________________________________________
Learning fixed points of recurrent neural networks by reparameterizing the network model

In computational neuroscience, fixed points of recurrent neural networks are commonly used to model neural responses to static or slowly changing stimuli. These applications raise the question of how to train the weights in a recurrent neural network to minimize a loss function evaluated on fixed points. A natural approach is to use gradient descent on the Euclidean space of synaptic weights. We show that this approach can lead to poor learning performance due, in part, to singularities that arise in the loss surface. We use a reparameterization of the recurrent network model to derive two alternative learning rules that produces more robust learning dynamics. We show that these learning rules can be interpreted as steepest descent and gradient descent, respectively, under a non-Euclidean metric on the space of recurrent weights. Our results question the common, implicit assumption that learning in the brain should be expected to follow the negative Euclidean gradient of synaptic weights.
Enhancing Reliability in Federated mmWave Networks: A Practical and Scalable Solution using Radar-Aided Dynamic Blockage Recognition

This article introduces a new method to improve the dependability of millimeter-wave (mmWave) and terahertz (THz) network services in dynamic outdoor environments. In these settings, line-of-sight (LoS) connections are easily interrupted by moving obstacles like humans and vehicles. The proposed approach, coined as Radar-aided Dynamic blockage Recognition (RaDaR), leverages radar measurements and federated learning (FL) to train a dual-output neural network (NN) model capable of simultaneously predicting blockage status and time. This enables determining the optimal point for proactive handover (PHO) or beam switching, thereby reducing the latency introduced by 5G new radio procedures and ensuring high quality of experience (QoE). The framework employs radar sensors to monitor and track objects movement, generating range-angle and range-velocity maps that are useful for scene analysis and predictions. Moreover, FL provides additional benefits such as privacy protection, scalability, and knowledge sharing. The framework is assessed using an extensive real-world dataset comprising mmWave channel information and radar data. The evaluation results show that RaDaR substantially enhances network reliability, achieving an average success rate of 94% for PHO compared to existing reactive HO procedures that lack proactive blockage prediction. Additionally, RaDaR maintains a superior QoE by ensuring sustained high throughput levels and minimising PHO latency.
Calibration strategy and status of tritium purity monitoring for KATRIN

We acknowledge the support of Helmholtz Association (HGF), Ministry for Education and Research BMBF (05A17PM3, 05A17PX3, 05A17VK2, and 05A17WO3), Helmholtz Alliance for Astroparticle Physics (HAP), and Helmholtz Young Investigator Group (VH-NG-1055) in Germany; Ministry of Education, Youth and Sport (CANAM-LM2011019), cooperation with the JINR Dubna (3+3 grants) 2017–2019 in the Czech Republic; and the Department of Energy through grants DEFG0297ER41020, DE-FG02-94ER40818, DE-SC0004036, DE-FG0297ER41033, DE-FG02-97ER41041, DE-AC02-05CH11231, and DE-SC0011091 in the United States. Motivation
New calibration estimator in stratified sampling

ABSTRACT This paper develops the theory of calibration estimation and proposes calibration approach alternative to existing calibration estimators for estimating population mean of the study variable using auxiliary variable in stratified sampling. The theory of new calibration estimation is given and optimum weights are derived. A simulation study is carried out to performance of the proposed calibration estimator with other existing calibration estimators. The results reveal that the proposed calibration estimators are more efficient than Tracy et al., Singh et al., Singh calibration estimators of the population mean.
Greedy coordinate descent from the view of $\ell_1$-norm gradient descent

In optimization community, coordinate descent algorithms are often viewed as some coordinate-wise variants of $\ell_2$-norm gradient descent. In this paper, we improve coordinate descent algorithms from another view that greedy coordinate descent (GCD) is equivalent to finding the solution with the least coordinate update of $\ell_1$-norm gradient descent. Then from the perspective of solving an $\ell_1$-regularized $\ell_1$-norm gradient descent ($\ell_1$-$\ell_1$-GD) problem, GCD is generalized to solve $\ell_1$-regularized convex problems. It is nontrivial to solve the $\ell_1$-$\ell_1$-GD problem and thus an efficient greedy algorithm called \emph{$\ell_1$-greedy} is proposed, which is proved to \emph{exactly} solve it. Meanwhile, by combing $\ell_1$-greedy and a specific mirror descent step as well as Katyusha framework, we \emph{accelerate} and \emph{randomize} GCD to obtain the optimal convergence rate $O(1/\sqrt{\epsilon})$ and reduce the complexity of greedy selection by a factor up to $n$. When the regularization parameter is relatively large and the samples are high-dimensional and dense, the proposed AGCD and BASGCD algorithms are better than the state of the art algorithms for $\ell_1$-regularized empirical risk minimization.
Argument inheritance and left periphery in Hungarian infinitival constructions

Hungarian infinitival constructions have both mono-clausal and bi-clausal properties at the same time. The arguments of the infinitive behave the same way as the arguments of the finite verb do, but the non-finite verb has its own left periphery. After discussing the general description of Hungarian sentence structure and presenting an HPSG analysis for it – including a description of the connection between word order and scope order in the Hungarian left periphery – this paper presents an analysis for Hungarian infinitival constructions. The analysis lexically distinguishes the left peripheral arguments of the infinitive from its complements, and allows the infinitive and its left peripheral arguments to form constituents, while the complements of the infinitive are inherited to the finite verb.
RESEARCH AND EDUCATION IN THE AIR FORCE – AFASES 2017 393 REGARDING A CONTINUOUSLY DIFFERENTIABLE FRICTION MODEL USED FOR CONTROL OF DYNAMIC SYSTEMS DESIGN

This paper analyzes several models that have been useful to characterize friction in motion control systems, where for high-performance of different engineering systems, modelbased controllers are required to accommodate for the system nonlinearities. Unfortunately, according to the dynamical systems theory, developing accurate models for friction has been historically challenging, because typical models were either discontinuous or only piecewise continuous. Motivated by the fact that discontinuous and piecewise continuous friction models are problematic for the development of high-performance continuous controllers, a new model for friction is considered and analysed in this paper. This simple continuously differentiable friction model represents a foundation that captures the major effects existed in the friction modeling area of applied mathematics and physics.
On the Hamiltonian formalism of the tetrad-connection gravity

We present a detailed analysis of the Hamiltonian constraints of the d-dimensional tetrad-connection gravity where the non-dynamic part of the spatial connection is fixed to zero by an adequate gauge transformation. This new action leads to a coherent Hamiltonian formalism where the Lorentz, scalar and vectorial first-class constraints obey a closed algebra in terms of Poisson brackets. This algebra closes with structure constants instead of structure functions resulting from the Hamiltonian formalisms based on the A.D.M. decomposition. The same algebra of the reduced first-class constraints, where the second-class constraints are eliminated as strong equalities, is obtained in terms of Dirac brackets. These first-class constraints lead to the same physical degrees of freedom of the general relativity.
Retrospective: Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU

The original paper published in ISCA 2010 investigated multiple performance claims showing 1-2 orders of magnitude performance difference in favor of GPU over CPU running various throughput computing kernels. Our paper sought to dig deeper into these performance claims in terms of their various architectural, micro-architectural and algorithmic components. We proposed a systematic framework for analyzing the performance delta across the two parallel processors, enumerating key attributes of CPU and GPU architectures and related performance optimizations. Critical optimizations identified for CPU included multi-threading, cache blocking, and reorganization of memory accesses for SIMD-ification. Optimizations for GPU included minimizing global synchronization and using local shared buffers. Our paper also identified some fairness concerns regarding the large performance deltas such as using single thread/single core scalar code as an optimized proxy for a multi-core CPU, or comparing a highend GPU to a mobile CPU, etc. Putting it all to practice, the paper showed how most of the CPU performance gap with respect to GPU could be recovered using properly conducted algorithm-architecture co-design, no different from what was needed and undertaken for the GPU. In summary, our paper highlighted the importance of algorithm-architecture co-design in the emerging multi/many-core era. This co-design benefits both GPUs and CPUs, and when it is leveraged to get optimal performance on GPUs, it should not be ignored for the CPU baseline.
Pulmonary Fibrosis: Unveiling the Pathogenesis, Exploring Therapeutic Targets, and Advancements in Drug Delivery Strategies

Idiopathic pulmonary fibrosis (IPF) is an ailment with no cure and a very high rate of progression that ultimately leads to death. The exact reason for this disease is still not acknowledged. Many underlying mechanisms of wound healing and various types of stimuli that trigger the pathogenesis of IPF continue to be intensively explored. The exact therapy for the reversal of this disease is not yet known and is constantly in progress. Existing treatments only slow down the process or mitigate the symptoms to enhance the patient’s healthcare system. The only two Food and Drug Administration-approved oral medications include pirfenidone and nintedanib whose high dose and systemic circulation can have side effects to a greater extent. Further research on restorative and extra-curative therapies for IPF is necessary due to the absence of viable therapeutic choices. To assure minimum off-targeted site delivery and longer duration of action, techniques that offer a sustainable release of the drug, better bioavailability, and patient compliance can be used. The work is an overview of the main therapeutic targets and pertinent developing therapies for the management of IPF. This study is an attempt to focus on various drug delivery systems that are responsible for showing effectiveness in defense mechanisms against IPF.
Performance improvement of an active vibration absorber subsystem for an aircraft model using a bees algorithm based on multi-objective intelligent optimization

ABSTRACT This study develops a mathematical model to investigate the behaviour of adaptable shock absorber dynamics for the six-degree-of-freedom aircraft model in the taxiing phase. The purpose of this research is to design a proportional-integral-derivative technique for control of an active vibration absorber system using a hydraulic nonlinear actuator based on the bees algorithm. This optimization algorithm is inspired by the natural intelligent foraging behaviour of honey bees. The neighbourhood search strategy is used to find better solutions around the previous one. The parameters of the controller are adjusted by minimizing the aircraft’s acceleration and impact force as the multi-objective function. The major advantages of this algorithm over other optimization algorithms are its simplicity, flexibility and robustness. The results of the numerical simulation indicate that the active suspension increases the comfort of the ride for passengers and the fatigue life of the structure. This is achieved by decreasing the impact force, displacement and acceleration significantly.
Understanding the dependence of mean precipitation on convective treatment in tropical aquachannel experiments

The intertropical convergence zone (ITCZ) is a key circulation and precipitation feature in the tropics. There has been a large spread in the representation of the ITCZ in global weather and climate models for a long time, the reasons for which remain unclear. This manuscript presents a novel approach with which we disentangle different physical processes responsible for the changeable behavior of the ITCZ in numerical models. The diagnostic tool is based on a conceptual framework developed by Emanuel (2019) and allows for physically consistent estimates of convective mass ﬂux and precipitation efﬁciency for 5 simulations with explicit and parameterized convection. We apply our diagnostics to a set of tropical aquachannel experiments using the ICOsahedral Nonhydrostatic (ICON) model with horizontal grid resolution of 13 km and with various representations of deep and shallow convection. The channel length corresponds to the Earth’s circumference and has rigid walls at 30 °N/S. Zonally symmetric sea surface temperatures are prescribed.
Implementa on of the “Unplugged” School-based Preven on Programme in Nigeria: Results of Process Evalua on

Department of Transla onal Medicine, University of Eastern Piedmont, Novara, Italy 2 Piedmont Centre for Drug Addic on Epidemiology, ASL TO3, Grugliasco (Torino), Italy Department of Public Health and Pediatrics, University of Torino, Italy 4 Department of Neuroscience 'Rita Levi Montalcini', University of Turin, Turin, Italy United Na ons Office on Drugs and Crime, Project Office, Lagos, Nigeria 6 University of Jos, Nigeria Faculty for Educa on, Health and Social Work, University College Ghent, Ghent, Belgium
On Dephasing and Exciton Transfer in Light-Harvesting Complexes

Photosynthesis is the main energy source in plants, algae and different types of bacteria, such as purple and green sulphur bacteria. The primary step in photosynthesis is represented by the photo excitation of the light harvesting (LH) pigment present in the organism. Subsequently, the excitation delocalizes among the pigments due to the electronic couplings between them. The excitation energy is then transferred to neighboring LH systems and finally to the reaction center (RC) where charge separation occurs. During the last decades many studies have been carried out in order to understand the optical and the exciton transfer properties of the LH complexes. Nevertheless, a full understanding has not yet been achieved. In particular, the experimentally-observed long-lived coherences as well as dephasing processes have attracted the attention of the scientific community in recent years. The present thesis aims at contributing to the understanding of these processes. To this end, different methods have been employed, such as molecular dynamics simulations, quantum-chemistry methods and wave packet dynamics calculations. The combination of these methods allows a more detailed theoretical description of the studied LH systems. The dephasing phenomenon is discussed in the first half of the thesis. In this work, an analytic and a numerical methodology has been developed to relate it to the energy gap fluctuation. This formalism has been applied to the case of both single pigments and whole complexes. It can be concluded that a universal relation exists between these two entities, independently from the system and from the method used to obtain such quantities. The second half of this thesis consists of combined molecular dynamics and quantum approaches applied to different systems. Three different LH systems are discussed and compared in detail and the photo-active part of a bio-inspired solar cell is studied.
Stirring across the Antarctic Circumpolar Current’s Southern Boundary at the Greenwich Meridian, Weddell Sea

At the Southern Boundary of the Antarctic Circumpolar Current (ACC), relatively warm ACC waters encounter the colder waters surrounding Antarctica. Strong density gradients across the Southern Boundary indicate the presence of a frontal jet and are thought to modulate the southward heat transport across the front. In this study, the Southern Boundary in the Weddell Sea sector at the Greenwich Meridian is surveyed for the first time in high resolution over an entire austral summer with underwater gliders transecting the front on 5 occasions. The 5 transects show that the frontal structure (i.e., 5 hydrography, velocities and lateral density gradients) varies temporally. The results demonstrate significant, quite rapid (a few weeks) variability of the Southern Boundary and its frontal jet in location, strength and width. A mesoscale cold-core eddy is identified to disrupt the Southern Boundary’s frontal structure and strengthen lateral density gradients across the front. The front’s barrier properties are assessed using mixing length scales and potential vorticity to establish the cross-frontal exchange of properties between the Southern Boundary and the Weddell Gyre. The results show that stronger lateral density gradients 10 caused by the mesoscale eddy strengthen the barrier-like properties of the front through reduced mixing length scales and pronounced gradients of potential vorticity. In contrast, the barrier-like properties of the Southern Boundary are reduced when no mesoscale eddy is influencing the density gradients across the front. Using altimetry, we further demonstrate that the barrier properties over the past decade have strengthened as a result of increased meridional gradients of absolute dynamic topography and increased frontal jet speeds in comparison to previous decades. Our results emphasize that locally and rapidly changing