Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase-shifting digital holography with vortex lens

Phase-shifting digital holography (PSDH) is considered as a promising imaging technique with wide application in optical storage, topography measurement and defect detection. The amplitude-only vortex lens is a kind of diffractive optical elements (DOEs) which can be used for focusing and imaging in a wide spectral region, such as coherent X-rays and terahertz wave. Here four-step PSDH with an amplitude-only vortex lens is proposed. Four frames of hologram can be recorded by rotating the vortex lens installed in the reference beam path. Both a 1951 U.S. air force resolution test target and a vortex focal spot are measured by four-step PSDH with vortex lens. The experimental results are in good agreement with the theoretical analysis and verify the validity of our proposed PSDH with vortex lens.
Distributed Computability

As today Computer Science is more and more (driven) consumed by its applications, it becomes more and more important to know what is and what is not computable. For a long time now, this has been relatively well understood in sequential computing. But today the computing world becomes more and more distributed, and consequently more and more applications are distributed. As a result, it becomes important, or even crucial, to understand what is distributed computing and which are its power and its limits. This article is a step in this direction from an agreement-oriented and fault-tolerance perspective.
Comprehensive Head Motion Correction For Functional Magnetic Resonance Imaging

Head motion artifacts are major confounds that limit use of functional magnetic resonance imaging (fMRI) in neuroscience research and clinical settings. Prospective motion correction is a promising candidate solution for head motion in fMRI that ideally allows the image plane to remain fixed with respect to the moving head (i.e., in the moving reference frame). Prospective motion correction has been shown to correct successfully for rigid body movement artifacts, but residual geometric distortion due to dynamic magnetic field nonuniformities and dynamic changes in receiver coil sensitivity profiles in the moving reference frame still remain a problem. This thesis focuses on three objectives. First, I investigated and corrected for the influence of respiratory effects on the performance of dynamic geometric correction using Phase Labeling for Additional Coordinate Encoding (PLACE). It was demonstrated that PLACE combined with the dynamic off-resonance in k-space (DORK) method, and temporal averaging substantially improved fMRI data quality in comparison to the results obtained by standard processing and static geometric distortion correction.
MAAIP

Simulating realistic interaction and motions for physics-based characters is of great interest for interactive applications, and automatic secondary character animation in the movie and video game industries. Recent works in reinforcement learning have proposed impressive results for single character simulation, especially the ones that use imitation learning based techniques. However, imitating multiple characters interactions and motions requires to also model their interactions. In this paper, we propose a novel Multi-Agent Generative Adversarial Imitation Learning based approach that generalizes the idea of motion imitation for one character to deal with both the interaction and the motions of the multiple physics-based characters. Two unstructured datasets are given as inputs: 1) a single-actor dataset containing motions of a single actor performing a set of motions linked to a specific application, and 2) an interaction dataset containing a few examples of interactions between multiple actors. Based on these datasets, our system trains control policies allowing each character to imitate the interactive skills associated with each actor, while preserving the intrinsic style. This approach has been tested on two different fighting styles, boxing and full-body martial art, to demonstrate the ability of the method to imitate different styles.
Solidarity and Resistance Meet Social Enterprise: The Social Logic of Alternative Cloudwork Platforms

Amid the popularity of global cloudwork platforms that connect vast numbers of clients and workers across geographic boundaries, local platforms have emerged. These alternative platforms, such as social enterprises, are established by platform workers and social entrepreneurs offering pro-worker platform-mediated work organization. Through two case studies, I situate the ambivalence of alternative platform formations within the social imaginaries and “entrepreneurial solidarities” underpinning cloudwork in the Philippines and the local sources of identification—spatial and local affinities and gender identities driving them. I then examine how these sources of identification shape the versions of fair and inclusive relations of production that they seek to embed in platform design. These represent an expression of agency aimed at improving platform conditions in ways that simultaneously embody and challenge the platforms’ business models. The article seeks to contribute to the enrichment of the debates in terms of the politics, nuances, and possibilities for solidarity and resistance in cloudwork in the Global South amid continuing technological development and platform reforms.
FAST AND DATA-EFFICIENT IMAGE SEGMENTATION by Daniil Pakhomov

Abundance and affordability of cameras has enabled scalable and affordable collection of image data. This has led to many research opportunities both in robot-assisted surgery and general computer vision domain related to image segmentation. In this thesis, we focus on image segmentation problem as it is a fundamental task which has many applications including pose estimation of surgical tools in robotic surgery and eye tracking in head mounted displays. As a result of our work we present a data-efficient method that does not require human annotation of data and exhibits real-time inference. First, we introduce the use of residual neural networks for surgical instrument segmentation for robotic surgery. We show state of the art results on multiple instrument segmentation datasets. Second, we introduce a neural architecture search method that is able to find a very efficient image segmentation model capable of realtime inference. Real-time inference is a crucial requirement for image segmentation methods for robotic surgery. Third, to reduce the amount of annotation required for our method, we introduce a semi-supervised approach which leverages unlabeled ii
The use of components’ weights improves the diagnostic accuracy of a health-related index

ABSTRACT This work aims to evaluate whether the use of specific weights in each component of a health-related index, is associated with its diagnostic accuracy. In addition, the impact of a composite health-related index's components multitude is examined in relation to its classification ability. An un-weighted and various weighted indices were constructed using different weighting methods. The indices’ diagnostic ability was evaluated by using true positive rate, true negative rate, true rate, positive predictive value, negative predictive value and the area under the receiver operating characteristic curve. Weights used in this study were obtained from linear discriminant analysis and binary logistic regression. These indices were applied in both simulated and actual data; and a variety of scenarios was applied based on the distribution's parameters of the component variables and on the number of components used. Results indicate that weighted indices’ evaluation measures were significantly higher compared to the un-weighted one; whereas area under receiver operating characteristic curve was positively associated with the number of components of each index that were correlated with the outcome. Weighting of index's components, as well as greater number of components related to the investigated outcome should be recommended for the construction of accurate indices.
Passive coherent discriminator using phase diversity for the simultaneous measurement of frequency noise and intensity noise of a continuous-wave laser

The frequency noise and intensity noise of a laser set the performance limits in many modern photonics applications and, consequently, must often be characterized. As lasers continue to improve, the measurement of these noises however becomes increasingly challenging. Current approaches for the characterization of very high-performance lasers often call for a second laser with equal or higher performance to the one that is to be measured, an incoherent interferometer having an extremely long delay-arm, or an interferometer that relies on an active device. These instrumental features can be impractical or problematic under certain experimental conditions. As an alternative, this paper presents an entirely passive coherent interferometer that employs an optical 90° hybrid coupler to perform in-phase and quadrature detection. We demonstrate the technique by measuring the frequency noise power spectral density of a highly-stable 192 THz (1560 nm) fiber laser over five frequency decades. Simultaneously, we are able to measure its relative intensity noise power spectral density and characterize the correlation between its amplitude noise and phase noise. We correct some common misconceptions through a detailed theoretical analysis and demonstrate the necessity to account for normal imperfections of the optical 90° hybrid coupler. We finally conclude that this passive coherent discriminator is suitable for reliable and simple noise characterization of highly-stable lasers, with bandwidth and dynamic range benefits but susceptibility to additive noise contamination.
Blockchain Games: What On and Off-chain factors affect the volatility, returns, and liquidity of Gaming Crypto Tokens

Blockchain games took the internet by storm as they offered a new way for users to play video games, own the assets in those games, and benefit monetarily from their efforts. Through Non-Fungible Tokens (NFTs) and cryptocurrencies, new, Web3 games ushered in a unique asset class for retail and institutional investors to diversify into and benefit from. This paper uses cross-sectional data from 30 blockchain gaming companies to identify on and off-chain factors that affect the company’s token volatility, returns, and liquidity. A multiple linear regression found the percentage of tokens dedicated to a company’s private sale and rewarding users, the length of a token’s vesting period, if the token has a fixed supply, and tokens based on the Solana or Polygon blockchains positively affect the volatility of that token. Conversely, the Monthly Active Users of the game, the token’s market capitalization, the amount of funds raised by the company, and the game genre negatively affect volatility. Funds raised, game genre, and Solana-based tokens were also significant in the returns model. Lastly, the number of faucets for the game and the percentage of tokens dedicated to rewards and the private sale showed significance in the liquidity model. This paper adds to the literature in the NFT, cryptocurrency, and blockchain gaming spaces. Table of
Les équations de Seiberg–Witten sur une surface complexe non Kählérienne

We consider the Seiberg-Witten invariants of non Kahler complex surfaces with b+2 > 0. They are all elliptic surfaces of nonnegative Kodaira dimension. We prove that they are simple type and we calculate the basic classes and the multiplicities. We deduce that non Kahler properly elliptic surfaces do not carry a symplectic structure.
Long-Living GHz Vibrations in Opal-Based Hypersonic Crystals

We report experiments in which high-quality silica opal film is used as a three-dimensional hypersonic crystal in the GHz frequency range. We inject into the sample a broadband elastic wave packet by means of optical excitation of metal hypersound transducer and study the temporal evolution of GHz coherent vibrations monitoring the modulation of film reflectivity. Measurements carried out at different incident angles of probe beam allow us to determine that only coherent surface vibrations contribute to the measured modulation of reflectivity. This conclusion is supported by the long lifetime of surface vibrational modes with the frequency that matches a phononic band gap.
Image Inpainting based on Block-based Linear Regression and Minimum Variance Convex Combinations

Estimation of missing entries in a multivariate data is one of classical problems in the field of statistical science. Linear regression with the EM algorithm is well known as one of popular approaches for this problem. When this approach is applied to block-based image inpainting problems, multiple candidates of estimate for a target lost pixel may be obtained. In our previous work, we proposed a denoising technique for multiple images using the convex combination which minimizes its variance of errors from a true image. In this paper, we propose a novel image inpainting method incorporating the application of the denoising technique to multiple estimates for a target pixel. We also show several results of numerical experiments in order to verify the efficacy of the proposed method.
The RNA binding proteins ZFP36L1 and ZFP36L2 are dysregulated in airway epithelium in human and a murine model of asthma

Asthma is the most common chronic inflammatory disease of the airways. The airway epithelium is a key driver of the disease, and numerous studies have established genome-wide differences in mRNA expression between health and asthma. However, the underlying molecular mechanisms for such differences remain poorly understood. We investigated the expression and possible role of the tristetraprolin (TTP) family of RNA binding proteins (RBPs), which are poorly understood in asthma. The human TTP family is comprised of ZFP36, ZFP36L1 and ZFP36L2, and has essential roles in immune regulation by determining the stability and translation of myriad mRNAs encoding for inflammatory mediators. We found ZFP36L1 and ZFP36L2 mRNA levels significantly downregulated in the airway epithelium of patients with very severe asthma in different cohorts (5 healthy vs 8 severe asthma; 36 moderate asthma vs 37 severe asthma on inhaled steroids vs 26 severe asthma on oral corticoids). Integrating several datasets allowed us to infer that mRNAs potentially targeted by these RBPs are increased in severe asthma. Zfp36l1 was downregulated in the lung of a mouse model of asthma, and immunostaining of ex vivo lung slices with a dual antibody demonstrated that Zfp36l1/l2 nuclear localization is increased in the airway epithelium of an acute asthma mouse model. Immunostaining of human bronchial biopsies showed that airway epithelial cell staining of ZFP36L1 was decreased in severe asthma as compared with mild, while ZFP36L2 was upregulated. We propose that the dysregulation of ZFP36L1/L2 levels as well as their subcellular mislocalization contributes to changes in mRNA expression and cytoplasmic fate in asthma.
Theoretical study of polarization dynamics in VCSEL-based optical frequency combs

A theoretical analysis of optical frequency combs associated with the main and suppressed linear polarization modes of a gain-switched long-wavelength VCSEL is performed. We have studied the VCSEL polarization-resolved dynamics by using an extension of the spin-flip model to include nonlinear carrier recombination. Our results show that two orthogonally polarized combs are generated that combine to produce a wider overall optical comb. The dependence of combs on the VCSEL parameters and on the amplitude and frequency of the modulation is analyzed. Bistability between the two orthogonally polarized combs is found.
Spatial kinetic energy spectra in the convection-permitting limited-area NWP model COSMO-DE

1 Kinetic energy spectra derived from commercial aircraft observations of horizontal wind 2 velocities exhibit a k−5/3 wavenumber dependence on the mesoscale that merges into a 3 k−3 dependence on the macroscale. In this study, spectral analysis is applied to evalu4 ate the mesoscale ensemble prediction system using the convection-permitting NWP model 5 COSMO-DE (COSMO-DE-EPS). One-dimensional wavenumber spectra of the kinetic en6 ergy are derived from zonal and meridional wind velocities, as well as from vertical velocities. 7 Besides a general evaluation, the model spectra reveal important information about spin-up 8 effects and effective resolution. 9 The COSMO-DE-EPS well reproduces the spectral k−5/3 dependence of the mesoscale 10 horizontal kinetic energy spectrum. Due to the assimilation of high-resolution meteorologi11 cal observations (mainly rain radar), there is no significant spin-up of the model simulations 12 within the first few hours after initialization. COSMO-DE-EPS features an effective reso13 lution of a factor of about 4 to 5 of the horizontal grid spacing. This is slightly higher in 14 comparison to other limited area models. Kinetic energy spectra derived from vertical ve15 locities exhibit a much flatter wavenumber dependence leading to relatively large spectral 16 energy on smaller scales. This is in good agreement with similar models and also suggested 17 by observations of temporal variance spectra of the vertical velocity. 18
A Constraint on Double Negation

We argue that (2) is not correct for two reasons. First, we show that the restriction in (1) is not only observed with morphological negation, but also with certain cases of syntactic negation. Second, we argue that it is no coincidence that certain negative markers are excluded with negative adjectives. We present a principled account for the data pattern in (1), which explains (1b) in terms of a ban on double negation. 2. Evidence. French and Dutch not only show the pattern in (1), but the same pattern with a case of syntactic negation, in particular with the negative Q-adjectives peu and weinig ‘little’. These can modify positive adjectives, but not negative ones, whether they be lexically negative or un-prefixed:
Superluminal and negative delay times in isotropic-anisotropic one-dimensional photonic crystal

In this work, we investigate the possibility of superluminal and negative delay times for electromagnetic wave propagation in a linear and passive periodic structure consisting of alternating isotropic and anisotropic media. This phenomenon is due to the birefringence of the anisotropic layers of the structure. By adjusting the orientations of these layers, the delay times of transmitted waves can be controlled from subluminality to superluminality and vice versa. Numerical results indicate that the apparent superluminal propagation of light occurs inside the photonic band-gaps when the principal axes of the anisotropic layers are parallel or perpendicular to the fixed axes. For other orientations of these layers, tunneling and superluminal regimes appear inside the photonic bandgaps and in the allowed bands for frequencies close to the transmission minima. The effect of the number of unit cells of the photonic crystal structure on the propagation of light with superluminal and negative delay times is als.
FOLIATIONS FORMED BY K-ORBITS OF MAXIMAL DIMENSION OF SOME MD5-GROUPS

In this paper we consider some MD5-groups and MD5-algebras, i.e., five-dimensional solvable Lie algebras and groups such that their orbits in the co-adjoint representation ( K-orbits ) are orbits of dimension zero or maximal dimension. We describe the geometry of K-orbits of MD5-groups. The foliations formed by K-orbits of maximal dimension of these MD5-groups and their measurability are also presented in the paper.
Finite-time attitude controller design via dual-loop control strategy

In this paper, a finite-time attitude control scheme based on the dual-loop framework is proposed for rigid spacecraft in the presence of inertia uncertainties, external disturbances, bounded angular velocity, and control input saturation. The control law was designed based on a dual-loop structure. First, a hyperbolic tangent function was used to design the virtual angular velocity command, which serves as the control input of the outer loop system to stabilize the attitude under angular velocity constraints. Second, a smooth function was used to approximate the saturation and an auxiliary system was constructed to compensate for the effects of actuator saturations. A finite-time control law was designed to track the limited command of the outer loop under the disturbance and control input constraints in the inner loop. The stability of the closed-loop system during saturation is thus guaranteed, and the tracking error converges to zero after controller parameters are selected appropriately. A numerical example illustrates the effectiveness of the proposed attitude controller.
Performances statistiques de méthodes à noyaux

Cette these se concentre sur le modele de classification binaire. Etant donne n couples de variables aleatoires independantes et identiquement distribuees (i. I. D. ) (Xi1, Yi), i = 1; : : : ; n de loi P, on cherche a predire la classe Y [appartient] {- 1, +1} d'une nouvelle entree X ou (X, Y ) est de loi P. La regle de Bayes, notee f*, minimise l'erreur de generalisation R(f) = P(f(X) [different de] Y ). Un algorithme de classification doit s'approcher de la regle de Bayes. Cette these suit deux axes : etablir des vitesses de convergence vers la regle de Bayes et proposer des procedures adaptatives. Les methodes de regularisation ont montre leurs interets pour resoudre des problemes de classification. L'algorithme des Machines a Vecteurs de Support (SVM) est aujourd'hui le representant le plus populaire. Dans un premier temps, cette these etudie les performances statistiques de cet algorithme, et considere le probleme d'adaptation a la marge et a la complexite. On etend ces resultats a une nouvelle procedure de minimisation de risque empirique penalisee sur les espaces de Besov. Enfin la derniere partie se concentre sur une nouvelle procedure de selection de modeles : la minimisation de l'enveloppe du risque (RHM). Introduite par L. Cavalier et Y. Golubev dans le cadre des problemes inverses, on cherche a l'appliquer au contexte de la classification.
A Method for Maximin Constrained Design of Experiments

This paper presents a new approach for generating a design of experiments in constrained and non-regular spaces. The methodology is based on the triangulation of the admissible space by Delaunay triangulation method. Then, a heuristic smoothing method for generating uniform finite element meshes within the triangulated space is applied to obtain uniformly spaced designs. Although not 100% reliable, the proposed method can produce superior designs compared with already known optimal solutions.
Dynamical Behaviors of Coupled Memristor-Based Oscillators with Identical and Different Nonlinearities

In this work, the interesting dynamics of coupled nonlinear memristor-based oscillators in ring configuration are explored. The mathematical models are derived to describe the possible cases of employing identical or different nonlinearities. Analytical and numerical techniques, involving perturbation methods, normal forms, phase portraits, and Lyapunov exponents are used to investigate various types of dynamical behaviors along with their stability regions in parameters space. The effects of time-delayed coupling on the proposed system are numerically studied. It is demonstrated that the coupled oscillators show rich dynamics including periodic orbits, quasiperiodicity, two-dimensional, and three-dimensional tori.