Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Mixture Structure on Multi-Source Time Series for Probabilistic Forecasting

In many data-driven applications, collecting data from different sources is increasingly desirable for enhancing performance. In this paper, we are interested in the problem of probabilistic forecasting with multi-source time series. We propose a neural mixture structure-based probability model for learning different predictive relations and their adaptive combinations from multi-source time series. We present the prediction and uncertainty quantification methods that apply to different distributions of target variables. Additionally, given the imbalanced and unstable behaviors observed during the direct training of the proposed mixture model, we develop a phased learning method and provide a theoretical analysis. In experimental evaluations, the mixture model trained by the phased learning exhibits competitive performance on both point and probabilistic prediction metrics. Meanwhile, the proposed uncertainty conditioned error suggests the potential of the mixture model's uncertainty score as a reliability indicator of predictions.
Sequential Monte Carlo p-values

SUMMARY The assessment of statistical significance by Monte Carlo simulation may be costly in computer time. This paper looks at a number of ways of calculating exact Monte Carlo p-values by sequential sampling. Such p-values are shown to have properties similar to those obtained by sampling with a fixed sample size. Both standard and generalized Monte Carlo procedures are discussed and, in particular, a sequential method is proposed for dealing with situations in which values can only be conveniently generated using a Markov chain, conditioned to pass through the observed data.
Fast-electron transport and induced heating in aluminum foils

Beams of fast electrons have been generated from the ultra-intense laser interaction (6×1019W cm−2, 40fs) with aluminum foil targets. The dynamics of fast-electron propagation as well as the level of induced in-depth heating have been investigated using the optical emission from the foil’s rear side. The dependence of the emitted signals spectrum and size on the target thickness allowed the identification of the coherent (coherent transition radiation) and incoherent (thermal radiation) mechanisms of the optical emission. We demonstrate a two-temperature energy distribution for the laser-generated fast-electron population: a divergent bulk component (θbulk=35°±5°) with ≈35% of the laser focal spot energy and a 400–600keV temperature, plus a relativistic tail highly collimated (θtail=7°±3°), with a 10MeV temperature and a periodic modulation in microbunches, representing less than 1% of the laser energy. Important yields of thermal emission, observed for targets thinner than 50μm, are consequence of a hot .
Density-functional-theory calculations of electronic band structure of single-crystal and single-layer WS 2

Electronic band structures of single-crystal and single-layer WS 2 are investigated by first-principles calculations based on local-density-functional theory using a plane-wave basis with ultrasoft pseudopotentials. The band structure calculated for the single crystal corresponds very well with experimental data and recent calculations using an augmented-spherical wave basis [A. Klein et al., Phys. Rev. B 64, 205416 (2001)]. The calculations for the single layer show that compared to the bulk case no significant structural relaxations of the atomic positions occur. This result is confirmed by the good agreement of our calculated band structures for the single layer with the data from angle-resolved photoemission measurements.
Removal of Glass Reflection Using TV-Retinex Model

The Retinex model is mainly used to removal of unfavorable illumination effects from images. In this paper, the Retinex model combined with the total variation regularization (TV-Retinex) is presented to removal of glass reflection that can be solved by a fast computational approach based on the split Bregman iteration. Experiments demonstrated that the proposed method can effectively reduce this kind of artifact as well as preserve the edge and detailed information.
Recent progress on x-ray and pulsed particle beam sources at the Advanced Laser Light Source (ALLS) facility

The 200TW laser system, (Ti:Sapphire CPA system) delivering 5J in 25fs pulse with a 10Hz repetition rate and a contrast ratio of 1:10^-11 at the fundamental 800nm frequency, is used at the Advanced Laser Light Source (ALLS) facility to develop new generation of x-ray and pulsed particle beam sources (electrons, protons, neutrons). Experimental results on the betatron emission and electron emission from high intensity (<10^19 W/cm2) interactions with gas jet targets (1cm long supersonic nozzle) and on proton generation during high intensity (10^20 W/cm2) laser interaction with thin foil (10nm) and thick (several µm) targets will be presented and discussed. With gas jet targets, very high-resolution single shot phase contrast imaging with 10-20 keV X-rays has been demonstrated, and electrons are currently generated in the GeV range. X-ray source characterization will be presented. With foil targets, the target expansion has been measured on both sides of the target as well as proton generation (15 MeV range) at these relativistic intensities with various diagnostics (folding wave interferometer, time of flight, Thomson parabola.) We will describe the progresses we are doing to move from the laboratory experiments system to the application levels with integrated systems and compact light sources, with a special emphasis on medical applications. We are exploring the use of these high power lasers as a basic tool to image in real time with X-rays (betatron emission) tumors during their irradiation by protons (accelerated by the same laser). + funded by NSERC, CIPI, CFI, FQRNT, MDEIE, INRS, CRC program.
Longitudinal Changes of Cardiorespiratory Fitness Performance in High School: Association with Individual and School-Based Variables

This study aimed to model adolescents’ cardiorespiratory fitness performance change trajectories longitudinally across high school years and its relation to school- and individual/student-level factors. We employed hierarchical linear modeling to examine longitudinal cardiorespiratory fitness performance changes, as measured by the progressive aerobic capacity endurance run (PACER), over the years, between sexes, and in association with the school-level variables. Participants were 76,227 adolescents from 80 high schools in the mid-Atlantic region of the United States. School-level academic performance (SAP), the percent of students eligible for free and reduced-price meals (FARM), and physical education student-faculty ratio were obtained with permission from the school districts. The number of laps completed in PACER test improved throughout the first three years of high school, however, proportions of those within the healthy fitness zone (HFZ) decreased overall from 9th to 11th grade. Furthermore, the number of laps completed by adolescents appeared to have plateaued at 11th grade, with a significant decline during the final year of high school. Sex-based discrepancies in performance in meeting HFZ were evident, where girls significantly outperformed boys during 9th and 10th grades, and boys significantly outperformed girls during 12th grade. Additionally, SAP and FARM were positively and negatively, respectively, significantly associated with PACER performance at the school level. The odds ratio of adolescents performing in the HFZ declined significantly over the years, even though the number of PACER laps improved in the first three years. Concerted efforts should be targeted at improving cardiorespiratory fitness in high school due to its positive relationship to academic achievement in schools, and negative association with cardiovascular disease, metabolic syndrome, obesity, and all-cause mortality in adulthood.
A Preliminary Investigation of the Diffuse Interstellar Line at 8621 Å

We have obtained high‐resolution spectra at the Dominion Astrophysical Observatory, the Calar Alto Observatory, and the European Southern Observatory of hot stars in the near‐infrared region to study the diffuse interstellar band (DIB) at 8621 Å. Field stars as well as selected members of the Perseus spiral arm, the ρ Ophiuchi complex, and the Cygnus OB2 association were observed and the equivalent widths of the band measured, as well as interstellar K i absorption at 7699 Å. In total we measure the equivalent width of the 8621 band in 64 stars. In a series of figures we show the correlations of the DIB with reddening, polarization, K i, and strengths of other DIBs at 5780, 5797, and 6613 Å. The quality of the correlations are discussed by means of the Spearman rank correlation test. Good correlations are found with reddening and, among the other DIBs, 8621 correlates best with 5780. By examining the three special regions mentioned above we confirm the weakness of the 8621 DIB in the hot stars of the ρ Oph star‐forming region. In the Perseus spiral arm region we find that the DIBs are formed largely in foreground clouds but not in the gas that appears to have been blown away from the young massive stars of the Perseus arm. In Cyg OB2 we find that the equivalent widths of the 8621 line lie above the linear correlation of equivalent width with E(B - V) and their strength does not vary as strongly with reddening. The heavily reddened Cyg OB2 star 12 is the most extreme example of the relative insensitivity of the 8621 equivalent width to reddening in the Cygnus OB2 region.
SMILE: Sample-to-feature Mixup for Efficient Transfer Learning

To improve the performance of deep learning, mixup has been proposed to force the neural networks favoring simple linear behaviors in-between training samples. Performing mixup for transfer learning with pre-trained models however is not that simple, a high capacity pre-trained model with a large fully-connected (FC) layer could easily overfit to the target dataset even with samples-to-labels mixed up. In this work, we propose SMILE — Sample-to-feature Mixup for EffIcient Transfer LEarning. With mixed images as inputs, SMILE regularizes the outputs of CNN feature extractors to learn from the mixed feature vectors of inputs, in addition to the mixed labels. SMILE incorporates a mean teacher to provide the surrogate "ground truth" for mixed feature vectors. Extensive experiments have been done to verify the performance improvement made by SMILE , in comparisons with a wide spectrum of transfer learning algorithms, including fine-tuning, L2-SP, DELTA, BSS, RIFLE, Co-Tuning and RegSL, even with mixup strategies combined.
Glassy dynamics and aging in a dense ferrofluid

X-ray Photon Correlation Spectroscopy is used here to probe for the first time a glass-forming dispersion of repulsive particles spherical and 10 nm sized. The highly concentrated colloidal system is based on the magnetic and charge-stabilized nanoparticles of a ferrofluid. Their out-of-equilibrium translational dynamics capture on nanoscale generic features usually observed on microscale: namely i) stretched exponential α relaxation with an exponent around 1.5 and ii) age-dependent characteristic time τ evolving from exponential at young ages to a slower behavior at large ages. τ is here scaling as Q−1 in the whole experimental Q-range, below, on and above the scale of the interparticle distance, the driving force for aging in this glass-forming nanosystem being associated to larger scale rearrangements.
Remarks on a generalized q-difference equation

In this paper, we establish one general q-exponential operator identity by solving one simple q-difference equation. Using this q-difference equation, we get some generalizations of Andrews–Askey and Askey–Roy integrals. In addition, we also study some properties of q-polynomials . We also derive two generalized transformation identities from q-Chu–Vandermonde summations with this method.
BOUNDARY CONDITIONS FOR THE WEAK FORMULATION OF THE MIXED (U, P) POROELASTICITY PROBLEM

This paper presents the boundary conditions that apply to the weak integral formulation of the Biot mixed (u_,p) poroelasticity equations. These boundary conditions are derived from the classical boundary conditions of the Biot displacement (u_,U_) poroelasticity equations. They are applied to the surface integrals of the associated weak form to account for exterior excitations, supports, and couplings with exterior elastic, acoustic, poroelastic media, and a septum. It will be shown that the derived boundary conditions for the (u_,p) formulation lead to simpler finite element equations compared to those obtained from the (u_,U_) formulation. Finally, two numerical examples are presented to validate the poroelastic-septum coupling condition, and to highlight the limitations of the free edge condition on a poroelastic medium.
A Novel Approach of Edge Detection Based on Gray Correlation Degree and Kirsch Operator

Image edge detection plays an important role in the process of image processing. This article classified the effect of various edge detection algorithms of digital images, mainly through the analysis of characteristics of the commonly used several kinds of classical edge detection operator in the time domain. For the actual image, the edge of the gray scale is sometimes not very clear, and the image also contains noise. A new algorithm of edge detection based on gray correlation degree and Kirsch operator is discussed in the paper. Kirsch operator is the reference sequence. Firstly, calculate the gray correlation degree of each pixel in the image and its neighbors formed eight action sequences and reference sequences, then determine the detection of edges based on gray correlation degree. The results show that this method can more accurately detect the useful information of the edge, and has a certain noise immunity. It is an effective and feasible new edge detection method.
A fast target detection and imaging method for compressive sensing Earth observation

The compressive sensing imaging technique, based on the realization of random measurement via active or passive devices (e.g., DMD), has attracted more and more attention. For imaging target of interest within large uniform scene (e.g., ships in the sea), high-resolution image was usually reconstructed and then used to detect targets, however the process is time-consuming, and moreover only part of the image consists of the targets of interest. In this paper, the stepwise multi-resolution fast target detection and imaging method through the combination of different numbers of DMD mirrors was explored. Low resolution image for larger area target searching and successively higher resolution image for smaller area containing the targets were reconstructed. Also, non-imaging fast target detection was realized based on the detector energy intensity, which includes the steps of rough target positioning by successively opening DMD blocks and accurate target positioning by adjusting the rough areas via intelligent search algorithm. Simulation experiments were carried out to compare the proposed method with traditional method. The result shows the area of the ships are accurately positioned without reconstructing the image by the proposed method and the multi-level scale imaging for suspect areas is realized. Compared with traditional target detection method from the reconstructed image, the proposed method not only highly enhances the measuring and reconstruction efficiency but also improves the positioning accuracy, which would be more significant for large area scene.
FINITE VOLUME APPROXIMATION FOR DEGENERATE DRIFT-DIFFUSION SYSTEM IN SEVERAL SPACE DIMENSIONS

This paper is devoted to a finite volume discretization for multidimensional nonlinear drift-diffusion system. Such system arises in semiconductors modelling and is composed of two degenerate parabolic equations and an elliptic one. We prove the convergence of the finite volume scheme and then the existence of solutions to the problem. Several numerical tests show the efficiency of the method.
Modeling of Seabed Logging Data for a Sand-shale Reservoir

a new rock-physics modeling tool was developed to describe the electric properties of a sand-shale reservoir. Four types of clay distribution models were implemented to describe possible sand-shale reservoirs including anisotropy. The corresponding algorithms gave as output an estimate of the e-cient-medium conductivity of the reservoir. The tool was interfaced to a 1.5- D EM-modeling program used to simulate Seabed logging data. The potential of this integrated modeling approach was demonstrated by calculating the variation in the EM response associated with a petroleum reservoir, due to difierent clay distributions as well as difierent brine salinities. DOI: 10.2529/PIERS060907053724
Optimal stabilization of modal control with variable structure

The paper shows that a control strategy based on the changing structure of a control system, ie, on controlled jump changes of the control system parameters, ensures more rapid stabilization than a control system with constant parameters. An algorithm of the time-optimal stabilization is designed in accordance with the Pontriagin's maximum principle in such a way that the resulting behaviour is non-periodic. The designed control algorithm divides the state space into segments in which the parameters take their limit values. The control problem is resolved for third-order and higher linear systems. Issues of system robustness are demonstrated by the example of stabilizing a variably loaded gantry crane.
Pseudo-spherical linearized radiative transfer model for trace gas profile retrieval

The Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) to be launched on ESA's environmental monitoring satellite ENVISAT-1 in November 2001, will measure the backscattered radiances in the UV, VIS and NIR of the solar spectrum. Apart from its nadir viewing mode, the instrument can also observe in limb viewing geometry. Such measurements will provide information about atmospheric trace gas distribution with high vertical resolution. A new generation of radiative transfer models is required in order to enable precise retrievals from UV and VIS limb observations. These models must (1) take scattering of light in a spherical shell atmosphere into account, and (2) be linearized with respect to the vertical trace gas distribution to be retrieved. As a first approach we present a linearized radiative transfer model in pseudo-spherical approximation, which employs the forward-adjoint perturbation theory. This method is based on two separate radiative transfer calculations: the usual forward and the adjoint formulation. The derivative of the radiance with respect to the trace gas concentration in a homogeneous model layer can easily be calculated, using the internal radiance field of both calculations. Thus, the proposed model carries out both the linearization with respect to changes in the vertical trace gas distribution and the modeling of backscattered radiances with reasonable numerical effort. Backscattered radiances are simulated with an accuracy better than 0.002 %. For the linearization the model achieves an accuracy better than 0.04 % in the derivatives.
Novel concept for flow-rate and flow-direction determination by means of pH-sensitive ISFETs

Sensor systems for multi-parameter detection in fluidics usually combine different sensors, which are designed to detect only one physical or (bio-)chemical parameter. In the present work, an ISFET (ion-sensitive field-effect transistor), which is well known as a (bio-)chemical sensor, is utilised for the flow velocity and flow direction measurement for the first time. The proposed flow sensor presents a chemical sensor-actuator system and consists of a H+-ion generator and a pH ISFET that detects the in-situ electrochemically generated H+ ions. By measuring the time of flight, the flow velocity can be determined. Since this measuring method represents a dynamic method, a calibration of the sensor usually is not required, because only relative changes in the sensor output signal are of interest. Moreover, sensor+s drift, temperature instability and sensitivity discrepancy between the various ISFETs are not relevant. The experimental results show good linearity between the measured flow velocity with the ISFET and the delivered flow rate of the pump. Due to the fast response of the ISFET (usually in the millisecond range), an ISFET-based flow sensor is suitable for the measurement of the flow velocity in a wide range. The results of the flow direction measurement with two ISFETs are presented, too.
Tunable alexandrite lasers: Development and performance

Some major recent developments in alexandrite laser research are reviewed. Emphasis is placed on key material characteristics, and their relationship to laser performance. Alexandrite's favorable thermomechanical properties and high capacity for energy storage have led to laser performance levels that, in certain areas, exceed those of established solid-state laser sources. Here we review performance achievements for a variety of pulsed and CW laser configurations including single-mode, multimode, and mode-locked resonators, high-power amplifiers, and zig-zag slabs. In these configurations, operating performance levels have been demonstrated that are comparable to those of older, more familiar solid-state laser technologies. Alexandrite's broad tunability offers additional advantages. Together with nonlinear frequency conversion processes, alexandrite lasers provide high-brightness output over most of the UV, visible, and near IR.
Accurate reconstruction of frequency-sparse signals from non-uniform samples

With the advent of a new sampling theory in recent years, compressed sensing (CS), it is possible to reconstruct signals from measurements far below the Nyquist rate. The CS theory assumes that signals are sparse and that measurement matrices satisfy certain conditions. Even though there have been many promising results, unfortunately there still exists a gap between the theory and actual real world applications. This is because of the fundamental problem that the CS formulation is discrete. We propose a sampling and reconstructing method for frequency-sparse signals that addresses this issue. The signals in our scenario are supported in a continuous sparsifying domain rather than discrete. This work focuses on a typical case in which the unknowns are frequencies and amplitudes. However, directly looking for the unknowns that best fit the measurements in the least-squares sense is a non-convex optimization problem, because sinusoids are oscillatory. Our approach extends the utility of CS to simplify this problem to a locally convex problem, hence making the solutions tractable. Direct measurements are taken from non-uniform time-samples, which is an extension of the CS problem with a subsampled Fourier matrix. The proposed reconstruction algorithm iteratively approximates the solutions using CS and then accurately solves for the frequencies with Newton's method and for the amplitudes with linear least squares solutions. Our simulations show success in accurate reconstruction of signals with arbitrary frequencies and significantly outperform current spectral compressed sensing methods in terms of reconstruction fidelity for both noise-free and noisy cases.