Miracle-dz/UniFAR-FTUs huggingface dataset:
Algebraic Analysis Of Goal-seeking Systems

This paper presents an approach to the algebraic analysis of learning paradigms. The technique is to map the learning paradigm into a learning automaton with certain convergence characteristics. Such automata have been studied by the authors and their algebraic structure analyzed. From this structure a lower bound can be assigned to the number of steps in a learning sequence. Using the mapping a similar lower bound can be deduced for the learning paradigm.
The magnetic field of the Crab Nebula and the nature of its jet

The results of multifrequency, polarimetric VLA observations of the Crab Nebula are presented, which make it possible to correct for Faraday rotation and map the projected magnetic field with 1.8 arcsec resolution. It is found that, along most of the periphery where high sensitivity detects the magnetic field orientation for the first time, the field is aligned radially with an apparent high degree of order. The observed Faraday rotation is constant over most of the Crab and has the same value over the jet, suggesting that, apart from certain filaments and other small areas, it is of interstellar origin. It is concluded that most likely the jet is the result of a high-velocity beam formed inside the nebula. 28 refs.
Diffuse X-Ray Scattering Study of Lead Magnesium Niobate Single Crystals

Single crystals of lead magnesium niobate, PbMg{sub 1/3} Nb{sub 2/3}O {sub 3} , were studied with x-ray scattering measurements at temperatures between 10 and 350 K. The diffuse scattering around odd-integer Bragg reflections (H+K+L=odd ) has a significant anisotropic component with ledges along {l_angle}110{r_angle} directions. We show that the transverse optic (ferro distortion) modes whose polarizations are along {l_angle}1{ovr 1}0{r_angle} directions are soft and responsible for the observed diffuse scattering. Upon cooling, these modes undergo a freezing process with q -dependent freezing temperatures. Below the lowest freezing temperature (T{approx_lt}190 K ) the diffuse scattering follows 1/q{sup 2} law, indicating an elastically distorted, static structure. {copyright} {ital 1997} {ital The American Physical Society}
The Taxonomy of Blue Amorphous Galaxies. I. Hα and UBVI Data

Dwarf galaxies play an important role in our understanding of galaxy formation and evolution. We have embarked on a systematic study of 12 nearby dwarf galaxies (most of which have been classified as amorphous) selected preferentially by their blue colors. The properties of the galaxies in the sample suggest that they are in a burst or postburst state. It seems likely that these amorphous galaxies are closely related to other “starburst” dwarfs such as blue compact dwarfs (BCDs) and H II galaxies but are considerably closer and therefore easier to study. If so, these galaxies may offer important insights into dwarf galaxy evolution. In an effort to clarify the role of starbursts in evolutionary scenarios for dwarf galaxies, we present Hα and UBVI data for our sample. Blue amorphous galaxies, like BCDs and H II galaxies, have surface brightness profiles that are exponential in the outer regions (r ≳ 1.5re) but have a predominantly blue central excess, which suggests a young burst in an older, redder galaxy. Seven of the galaxies have the bubble or filamentary Hα morphology and double-peaked emission lines that are the signature of superbubbles or superwind activity. These galaxies are typically the ones with the strongest central excesses. The underlying exponential galaxies are very similar to those found in BCDs and H II galaxies. How amorphous galaxies fit into the dwarf irregular-“starburst dwarf”-dwarf elliptical evolutionary debate is less clear. In this paper, we present our data and make some preliminary comparisons between amorphous galaxies and other classes of dwarf galaxies. In a future companion paper, we will compare this sample more quantitatively with other dwarf galaxy samples in an effort to determine if amorphous galaxies are a physically different class of object from other starburst dwarfs such as BCDs and H II galaxies and also investigate their place in dwarf galaxy evolution scenarios.
Mechanical Stress Influence on the Phase Transition in Low-Dimensional Ferroelastics

The temperatures of the phase transition in a thin ferroelastic film and ferroelastic rod with a square profile were calculated on the base of Landau thermodynamic theory with account of different contact theirs planes with environment at the external mechanical stress, variation chemical composition along a thickness. The dependences of critical sizes of a low-dimensional ferroelastics on a value of external mechanical stress and nonuniform of the sample chemical composition were calculated, and the size of sample was determined below that a phase transition in ferroelastic phase is impossible.
Multi-method-modeling of interacting galaxies I. A unique scenario for NGC 4449?

NGC 4449 is an active star-forming dwarf ga la xy of Magellanic type. From radio observations, van Woerden et al. ([CITE]) found an extended HI-halo around NGC 4449 which is at least a factor of 10 larger than the optical diameter $D_{\rm 25} \approx 5.6$ kpc. Recently, Hunter et al. ([CITE]) discerned details in the HI-halo: a disc-like feature around the center of NGC 4449 and a lopsided arm structure. We combined several N -body methods in order to investigate the interaction scenario between NGC 4449 and DDO 125, a close companion in projected space. In a first step fast restricted N -body models are used to confine a region in parameter space reproducing the main observational features. In a second step a genetic algorithm is applied for a uniqueness test of our preferred parameter set. We show that our genetic algorithm reliably recovers orbital parameters, provided that the data are sufficiently accurate, i.e. all the key features are included. In the third step the results of the restricted N -body models are compared with self-consistent N -body simulations. In the case of NGC 4449, the applicability of the simple restricted N -body calculations is demonstrated. Additionally, it is shown that the HI gas can be modeled here by a purely stellar dynamical approach. In a series of simulations, we demonstrate that the observed features of the extended HI disc can be explained by a gravitational interaction between NGC 4449 and DDO 125. According to these calculations the closest approach between both galaxies happened ~4-6 10 8 yr ago at a minimum distance of ~25 kpc on a parabolic or slightly elliptic orbit. In the case of an encounter scenario, the dynamical mass of DDO 125 should not be smaller than 10% of NGC 4449's mass. Before the encounter, the observed HI gas was arranged in a disc with a radius of 35-40 kpc around the center of NGC 4449. It had the same orientation as the central ellipsoidal HI structure. The origin of this disc is still unclear, but it might have been caused by a previous interaction.
Electro-convection in a dielectric liquid layer subjected to unipolar injection

The problem of electric charge convection in a dielectric liquid layer of high ionic purity, when subjected to unipolar injection, is in many ways analogous to that of thermal convection in a horizontal fluid layer heated from below, although no formal analogy can be established. The problem treated is intrinsically more nonlinear than the thermal problem. We consider two asymptotic states of convection: one where the whole motion is dominated by viscosity, and one where inertial effects dominate. In each state, two or three spatial regions are distinguished. From the approximate equations that hold in the different regions, information about the variation of the different quantities with distance from the injector is obtained, and further approximations permit us to establish the dependence of the current density ratio I/I0 (called the electric Nusselt number) on the stability parameter T = M2R = εϕ0/Kρν, and on 1/R = ν/Kϕ0, which is an equivalent Prandtl number (ε is the permittivity, ρ the fluid density, K the mobility, ν the kinematic viscosity, and ϕ0 the applied voltage). In the viscous state, the analysis gives I/I0 ∞ T½; in the inertial state the law I/I0 ∞ (T/R)1/4 = M½ is obtained. Since M is independent of the applied voltage, the latter law shows the saturation in the electric Nusselt number observed in earlier experiments. The transition in the states is associated with a transition number (MR)T [gap ] 30, which is an electric Reynolds number, related to an ordinary Reynolds number of about 10. The experimental results, obtained in liquids of very different viscosities and dielectric constants, verify these theoretical predictions; further, they yield more precise numerical coefficients. As for the transition criteria, the experiments confirm that the viscous and inertial effects are of the same order when Re [gap ] 10. It was also possible to determine roughly the limits of the viscous and inertial states. The viscous analysis remains valid up to a Reynolds number of about 1; the inertial state can be considered valid down to a Reynolds number of 60. Schlieren observations show that the motion has the structure of very stable hexagonal cells at applied voltages just above the critical voltage, which are transformed into unstable filaments when the voltage is increased further. At even higher voltages, the motion finally breaks down into turbulence. It may be of interest to point out that, when M < 3, the electric Nusselt number approaches 1, which is equivalent to the situation in thermal convection at low Prandtl numbers.
Pruning neural networks for inductive conformal prediction

Neural network pruning techniques are used to prune redundant parameters in overparam-eterized neural networks in order to compress the model size and reduce computational cost. The goal is to prune a neural network in such a way that it has the same, or nearly the same, predictive performance as the original. In this paper we study neural network pruning in the context of conformal prediction. In order to explore whether the neural network can be pruned while maintaining the predictive efficiency of conformal predictors, our work measures and compares the efficiency of the prediction sets provided by the inductive conformal predictor built with an underlying pruned neural network. We implement several existing pruning methods and propose a new pruning method based specifically on the conformal prediction framework. By evaluating with various neural network architectures and across several data sets, we find that the pruned network can maintain, or indeed improve, the efficiency of the conformal predictors up to a particular pruning ratio and this pruning ratio varies with different architectures and data sets. These results are instructive for deploying pruned neural network in real-work applications within the context of conformal predictors, where reliable predictions and reduced computational cost are relevant, e.g. in healthcare or safety-critical applications. This work is also relevant for further work applying continual learning techniques in the context of conformal predictors.
A linear conceptual subsurface storm flow model

A zero-dimensional (lumped), linear conceptual model of the subsurface storm flow from hillslopes has been developed by integrating, over the length of the hillslope, the linearized one-dimensional (Dupuit-Forchheimer approximation) discharge relationship for saturated flow over an inclined plane. The derived two-term storage function accounts for gravity- and gradient-driven flow. Coupled with the storage balance equation for the plane, the model allows direct, analytical computation of the outflow hydrograph at the foot of the hill in response to an infiltration step input. The model is the conceptual counterpart of the linear advection-diffusion (LAD) flow equation derived from the extended Boussinesq equation through linearization. In contrast to the kinematic wave approximation, the outflows normalized by their equilibrium values are properly given as functions of the infiltration rate. The outflow hydrographs computed by the conceptual LAD model approximate nonlinear behavior closely over a wide range of conditions encountered in field applications.
X-Ray Emission from the Magellanic Clouds Observed by UHURU

Description of three sources in the Large Magellanic Cloud and one in the Small Cloud which have been discovered by Uhuru. These sources each emit about 10 to the 38th erg/sec in the 2- to 7-keV band, and they account for more than 90% of the total emission from the Clouds. The source in the Small Cloud shows time variability on time scales of hours.
Exponentially weighted moving average plans for detecting unusual negative binomial counts

Exponentially Weighted Moving Average (EWMA) plans for negative binomial counts with a non-homogeneous (time-varying) mean are developed for monitoring disease counts. These plans are used to identify unusual disease outbreaks or unusual epidemics. Time-varying means are typical for disease counts. The recommended surveillance plan in this article differs from the traditional approach of using standardized forecast errors based on the normality assumption, which suffers assumption concerns. The article demonstrates that the proposed EWMA plan has efficient detection properties for signaling unusually large outbreaks. These plans may be a useful tool for epidemiologists.
Why are CMEs large-scale coronal events: nature or nurture?

Abstract. The apparent contradiction between small-scale source regions of, and large-scale coronal response to, coronal mass ejections (CMEs) has been a long-standing puzzle. For some, CMEs are considered to be inherently large-scale events – eruptions in which a number of flux systems participate in an unspecified manner, while others consider magnetic reconnection in special global topologies to be responsible for the large-scale response of the lower corona to CME events. Some of these ideas may indeed be correct in specific cases. However, what is the key element which makes CMEs large-scale? Observations show that the extent of the coronal disturbance matches the angular width of the CME – an important clue, which does not feature strongly in any of the above suggestions. We review observational evidence for the large-scale nature of CME source regions and find them lacking. Then we compare different ideas regarding how CMEs evolve to become large-scale. The large-scale magnetic topology plays an important role in this process. There is amounting evidence, however, that the key process is magnetic reconnection between the CME and other magnetic structures. We outline a CME evolution model, which is able to account for all the key observational signatures of large-scale CMEs and presents a clear picture how large portions of the Sun become constituents of the CME. In this model reconnection is driven by the expansion of the CME core resulting from an over-pressure relative to the pressure in the CME's surroundings. This implies that the extent of the lower coronal signatures match the final angular width of the CME.
The complete classification on a model of two species competition with an inhibitor

Hetzer and Shen [3] considered a system of a two-species Lotka-Volterra competition model with an inhibitor, investigated its long-term behavior and proposed two open questions: one is whether the system has a nontrivial periodic solution; the other is whether one of two positive equilibria is non-hyperbolic in the case that the system has exactly two positive equilibria. The goal of this paper is first to give these questions clear answers, then to present a complete classification for its dynamics in terms of coefficients. As a result, all solutions are convergent as $t$ goes to infinity.
Stability in geomechanics, experimental and numerical analyses

One of the main onsequences of the nonassociative character of plastic strains in geomaterials is the existence of failure states strictly inside the Mohr–Coulomb plastic limit surface. This point is first emphasized by considering proportional strain loading paths as generalizations of the classical undrained triaxial path. It is shown that the sign of the second‐order work is a proper criterion for analyzing these particular failure states. Then, experimental results and theoretical curves (obtained from an incrementally nonlinear constitutive relation) are compared for the case of proportional stress paths in axisymmetric conditions. Main features of the second‐order work criterion are identified, such as the existence of a bifurcation domain together with a number of instability cones inside the Mohr–Coulomb surface. Furthermore, decomposing the second‐order work into its isotropic and deviatoric parts makes it possible to compare each of the respective contributions to material instability. Finally, a heuristic boundary value problem is simulated via finite element modelling. A spectral analysis of the symmetric part of the stiffness matrix is conducted to extract the first vanishing eigenvalue and its associated eigenvector. It is found that the displacement field related to this eigenvector appears to be very close to the displacement computed just before global numerical breakdown signalling an effective failure. A plausible explanation is that, considering a material point, the flow rule at the boundary of the bifurcation domain almost coincides with the one describing the failure mechanism on the Mohr–Coulomb plastic limit surface. Copyright © 2010 John Wiley & Sons, Ltd.
Lam Huynh FROM 3 D SENSING TO DENSE PREDICTION

This thesis introduces novel learning-based approaches for improving 3D sensing and dense prediction. In recent years, deep neural networks (DNNs) have thrived on various vision tasks. Nonetheless, current developments indicate a compromise between accuracy, network size, and architectural engineering cost. This work proposes accurate and lightweight DNNs by exploiting prior knowledge, integrating self-attention, leveraging multi-scale 2D-3D representations fusion, and presenting efficient neural architecture search (NAS) strategies. Recent monocular depth estimation approaches exhibit impressive results. However, these are often achieved with bulky network architectures employing up to hundreds of millions of parameters and using massive training data. This thesis introduces architectures that exploit geometric constraints and non-local self-attention mechanisms to improve performance. Moreover, the methods achieve state-of-the-art results while using at least ten times less parameters than competing approaches. Depth completion aims to densify sparse input depth measurements. Best performing depth completion methods only work for cases with relatively high 3D point density. This work proposes a novel multi-scale framework that operates directly on both 2D and 3D feature spaces. Unlike previous approaches, the method performs well on extremely sparse and unevenly distributed 3D points. The proposed architecture is also very compact and works with an arbitrary source of the input 3D points. Dense prediction resolves mapping problems at the pixel level, comprising many sub-tasks such as depth estimation, semantic segmentation, optical flow prediction, and image restoration. Existing methods usually use human-engineering DNNs or focus on a single sub-task. This thesis presents a novel approach utilizing NAS towards more general dense prediction problems that enable holistic scene understanding.
Characterization of glass and high-power near-infrared cw laser beams using nonlinear optical techniques

Absorption coefficients of highly transparent optical materials (glass) have been measured using a z-scan technique. Absorption coefficients as low as 10−5 cm−1 and lower can be measured by scanning a substrate of a transparent optical material in the focal region of a lens. Glass substrates with relatively high absorption coefficients are used for calibration and for verifying the results of measurements. The sensitivity of this technique proves to be high enough to reveal differences between absorption coefficients of different substrates made of the same material (BK7). We have suggested and used a novel procedure, scanning nonlinear lens profiling, for characterization of homogeneity of glass substrates and other transparent optical materials. Optical nonlinearity of glass substrates allows fast and high-precision measurement of the power and power density of high-power near-IR laser beams without large temperature increases and related problems.
Spontaneous toroidal rotation driven by the off-diagonal term of momentum and heat transport in the plasma with the ion internal transport barrier in LHD

A spontaneous rotation in the co-direction is observed in plasmas with an ion internal transport barrier (ITB), where the ion temperature gradient is relatively large (∂Ti/∂r ∼ 5 keV m−1 and ) in LHD. Because of the large ion temperature gradients, the magnitude of the spontaneous toroidal flow, , becomes large enough to cancel the toroidal flows driven by tangential injected neutral beams and the net toroidal rotation velocity is almost zero at the outer half of the plasma minor radius even in the plasmas with counter-dominant NB injections. The effect of velocity pinch is excluded even if it exits because of zero rotation velocity. The spontaneous toroidal flow appears in the direction of co-rotation after the formation of the ITB, not during or before the ITB formation. The causality between the change in and ∂Ti/∂r observed in this experiment clearly shows that the spontaneous rotation is driven by the ion temperature gradient as the off-diagonal terms of momentum and heat transport.
Quantum tunnelling in magnetic particles, layers and multilayers

The time delayed reversal of the magnetization of magnetic system with distributions of energy barriers, is in general strongly dependent on temperature at high temperature. At low temperature it becomes independent of the temperature. This result is interpreted in terms of a crossover between a thermal regime, in which the irreversible rotation of the magnetization is thermally activated, and a quantum regime in which it proceeds by quantum tunnelling. In this paper we show some results obtained in nanoparticles, layers and multilayers. In particular an analogy with Josephson junction will be made for the case of the sandwiches (domain wall junction). The role of dissipation will be discussed.
MPC‐based approximate dual controller by information matrix maximization

This paper proposes a method to approximate a dual controller by a computationally feasible algorithm. Dual control that optimally solves the problem of simultaneous control and identification of a system with uncertain parameters is known to be both analytically and computationally unsolvable. This paper proposes a multiple‐step active control algorithm that gives a suboptimal but tractable solution to the original dual control problem. The algorithm is based on model predictive control (MPC) and approximates persistent system excitation in terms of the increase of the lowest eigenvalue of the parameter estimate information matrix.