Miracle-dz/UniFAR-FTUs huggingface dataset:
INFRARED AND KINEMATIC PROPERTIES OF THE SUBSTELLAR OBJECT G 196–3 B

We report unusual near- and mid-infrared photometric properties of G 196–3 B, the young substellar companion at 16″ from the active M2.5-type star G 196–3 A, using data taken with the IRAC and MIPS instruments onboard Spitzer. G 196–3 B shows markedly redder colors at all wavelengths from 1.6 up to 24 μm than expected for its spectral type, which is determined at L3 from optical and near-infrared spectra. We discuss various physical scenarios to account for its reddish nature and conclude that a low-gravity atmosphere with enshrouded upper atmospheric layers and/or a warm dusty disk/envelope provides the most likely explanations, the two of them consistent with an age in the interval 20–300 Myr. We also present new and accurate separate proper motion measurements for G 196–3 A and B confirming that both objects are gravitationally linked and share the same motion within a few mas yr−1. After integration of the combined spectrophotometric spectral energy distributions, we obtain the result that the difference in the bolometric magnitudes of G 196–3 A and B is 6.15 ± 0.10 mag. Kinematic consideration of the Galactic space motions of the system for distances in the interval 15–30 pc suggests that the pair is a likely member of the Local Association and that it lies near the past positions of young star clusters like α Persei less than 85 Myr ago, where the binary might have originated. At these young ages, the mass of G 196–3 B would be in the range 12–25 MJup, close to the frontier between planets and brown dwarfs.
Transfer Deep Learning for Remote Sensing Datasets: A Comparison Study

Remote sensing is also benefiting from the quick development of deep learning algorithms for image analysis and classification tasks. In this paper, we evaluate the classification performance of a well-known Convolutional Neural Network (CNN) models, such as ResNet50, using a transfer learning approach. We compare the performance when using vector-features acquired from general purpose data, such as the ImageNet [1], versus remote sensing data like BigEarthNet [2], UCMerced [3], RESISC45 [4] and So2Sat [5]. The results show that the model pre-trained on RESISC-45 data achieved the highest accuracy when classifying the Eurosat [6] testing dataset. This was followed by the model pre-trained on Imagenet with 95.94% and BigEarthNet with 95.93%. When presented with diverse remote sensing data, the classification improved in regards to large quantities of general-purpose data. The experiments carried out also show, that multi modal (co-registered synthetic aperture radar and multispectral) did not increase the classification rate with respect to using only multispectral data. The source codes of this work are available for reproducible research at https://github.com/itzahs/CNN-RS.
Subdomain Style Compensation Network for Remote Sensing Cross-Domain Scene Classification

High spatial resolution (HSR) imagery scene classification has been the subject of increased interest in recent years, and has great potential for many applications, such as urban planning and land cover classification. Deeping learning has been widely exploited in scene classification and achieved high classification accuracy. However, current the scene classification method based on deep learning depends on a large number of datasets for training, and the feature distribution of the default testing datasets is the same as that of the training datasets. In practical application, it is not only time-consuming and laborious to obtain a large number of training data, but also difficult to meet these needs due to the data shift between different domain. In addition, directly use of features extracted by the convolutional neural network (CNN) will lead to limited performance owing to the influence of domain migration. Therefore, how to effectively reduce the domain offset between the training data and the testing data, and discover discriminative information to scene classification is a challenging task. In this paper, the SSCN is proposed for HSR remote Sensing cross-domain scene classification. In SSCN, we introduce DSAN in which the local maximum mean discrepancy (LMMD) is first introduced for scene classification to capture the fine-grained information for each category and reduce the domain migration between training data and testing data. To extract more discriminative information from HSR images, a style normalization and restitution module (SNR) is developed, and an attention mechanism is added to the module to improve the performance of the model. The experimental results demonstrate that the proposed SSCN framework is superior to the state-of-the-art methods 1 and performs well for cross-domain scene classification.
CHARACTERIZING CO FOURTH POSITIVE EMISSION IN YOUNG CIRCUMSTELLAR DISKS

Carbon monoxide is a commonly used IR/submillimeter tracer of gas in protoplanetary disks. We present an analysis of ultraviolet CO emission in Hubble Space Telescope Cosmic Origins Spectrograph spectra for 12 Classical T Tauri stars (CTTSs). Several ro-vibrational bands of the CO A 1Π–X 1Σ+ (Fourth Positive) electronic transition system are spectrally resolved from emission of other atoms and H2. The CO A 1Π v′ = 14 state is populated by absorption of Lyα photons, created at the accretion column on the stellar surface. For targets with strong CO emission, we model the Lyα radiation field as an input for a simple fluorescence model to estimate CO rotational excitation temperatures and column densities. Typical column densities range from N CO = 1018 to 1019 cm−2. Our measured excitation temperatures are mostly below T CO = 600 K, cooler than typical M-band CO emission. These temperatures and the emission line widths imply that the UV emission originates in a different population of CO than that which is IR-emitting. We also find a significant correlation between CO emission and the disk accretion rate and age. Our analysis shows that ultraviolet CO emission can be a useful diagnostic of CTTS disk gas.
Robust stabilization of MIMO systems in finite/fixed time

The control design problem for finite‐time and fixed‐time stabilizations of linear multi‐input system with nonlinear uncertainties and disturbances is considered. The control design algorithm based on block decomposition and implicit Lyapunov function technique is developed. The robustness properties of the obtained control laws with respect to matched and unmatched uncertainties and disturbances are studied. Procedures for tuning of control parameters are presented in the form of linear matrix inequalities. Aspects of practical implementation of developed algorithms are discussed. Theoretical results are supported by numerical simulations. Copyright © 2015 John Wiley & Sons, Ltd.
HARMONICS AND WIND POWER INSTALLATIONS

The fact that wind-power installations influence the waveform distortion in and around these installations is generally known. The details and the challenges are less well known. This paper summarizes the results from four consecutive projects on this subject. The results are partly presented in the form of messages to different stakeholders. Generally speaking, the waveform distortion in and around wind-power installations are low, but high levels may occur due to a number of reasons. There is no need for strict emission limits, but instead the levels should be monitored continuously. The transfer-impedance method is presented as a useful tool for studying harmonic propagation; the method is a generalization of the distinction between primary and secondary emission. Next to (integer) harmonics, interharmonics and supraharmonics should be included in harmonic measurements and studies. Two major challenges remain: a measurement challenge and a modelling challenge.
Impact of Human Blockage on Dynamic Indoor Multipath Channels at 27 GHz

Human blockage and its dynamics are potential challenges for millimeter-wave mobile communication. This paper presents the results of wideband measurements at 27 GHz with one human blocker close by a dynamic mobile terminal, as well as one or multiple dynamic human blockers further away from a mobile terminal. The measured human blockage loss is largest when the direct path in a line-of-sight is blocked, but this loss is limited by other multipath components. For non line-of-sight channels, it is shown that human blockage loss is typically negligible. The presented measurement results show that human blockage loss in multipath channels is much smaller than is reported in diffraction- and measurement-based models, which neglect or minimize the contribution of all multipath components other than the direct path. This suggests that the multipath nature of the indoor wireless channel highly limits the impact of human blockage.
Observation of Magnetic Monopoles in Spin Ice

Excitations from a strongly frustrated system, the kagome ice state of the spin ice Dy 2 Ti 2 O 7 under magnetic fields along a [111] direction, have been studied. They are theoretically proposed to be regarded as magnetic monopoles. Neutron scattering measurements of spin correlations show that close to the critical point the monopoles are fluctuating between high- and low-density states, supporting that the magnetic Coulomb force acts between them. Specific heat measurements show that monopole-pair creation obeys an Arrhenius law, indicating that the density of monopoles can be controlled by temperature and magnetic field.
Resonances and poles in the second Riemann sheet

In this work we study basic properties of unstable particles and scalar hadronic resonances, respectively, within simple quantum mechanical and quantum field theoretical (effective) models. We start with the basic ideas of quantum field theory. In particular, we introduce the Feynman propagator for unstable scalar resonances and motivate the idea that this kind of correlation function should possess complex poles which parameterize the mass and decay width of the considered particle. We also briefly discuss the problematic scalar sector in particle physics, emphasizing that hadronic loop contributions dominate its dynamics. A whole chapter is dedicated to the method of analytic continuation of complex functions through branch cuts into the so called second Riemann sheet. This method is crucial in order to describe physics of scalar resonances because the Feynman propagator of interacting quantum field theories will have branch cuts in the complex energy plane and complex poles in the second Riemann sheet. We then apply these concepts to a simple non-relativistic Lee model and demonstrate the physical implications, i.e., the motion of the propagator poles and the behaviour of the spectral function. Besides that, we investigate the time evolution of a particle described by such a model. In the last chapter, we finally concentrate on a simple quantum field theoretical model which describes the decay of a scalar state into two (pseudo)scalar ones. It is investigated how the motion of the propagator poles is influenced by loop contributions of the two (pseudo)scalar particles. We perform a numerical study for a hadronic system involving a scalar seed state (alias the \sigma-meson) that couples to pions. The unexpected emergence of a putative stable state below the two-pion threshold is investigated and it is clarified under which conditions such a stable state appears.
High-velocity stars in the cores of globular clusters: the illustrative case of NGC 2808

Context. We report the detection of five high-velocity stars in the core of the globular cluster NGC 2808. The stars lie on the red giant branch and show total velocities between 40 and 45 kms(-1). For a core velocity dispersion sigma(c) = 13.4 kms(-1), this corresponds to up to 3.4 sigma(c). These velocities are close to the estimated escape velocity (similar to 50 km s(-1)) and suggest an ejection from the core. Two of these stars have been confirmed in our recent integral field spectroscopy data and we will discuss them in more detail here. These two red giants are located at a projected distance of similar to 0.3 pc from the center. According to their positions on the color magnitude diagram, both stars are cluster members.
MODELING COLLISIONAL CASCADES IN DEBRIS DISKS: STEEP DUST-SIZE DISTRIBUTIONS

We explore the evolution of the mass distribution of dust in collision-dominated debris disks, using the collisional code introduced in our previous paper. We analyze the equilibrium distribution and its dependence on model parameters by evolving over 100 models to 10 Gyr. With our numerical models, we confirm that systems reach collisional equilibrium with a mass distribution that is steeper than the traditional solution by Dohnanyi. Our model yields a quasi-steady-state slope of n(m) ∼ m−1.88 [n(a) ∼ a−3.65] as a robust solution for a wide range of possible model parameters. We also show that a simple power-law function can be an appropriate approximation for the mass distribution of particles in certain regimes. The steeper solution has observable effects in the submillimeter and millimeter wavelength regimes of the electromagnetic spectrum. We assemble data for nine debris disks that have been observed at these wavelengths and, using a simplified absorption efficiency model, show that the predicted slope of the particle-mass distribution generates spectral energy distributions that are in agreement with the observed ones.
CENTER-TO-LIMB OBSERVATIONS AND MODELING OF THE Ca i 4227 Å LINE

The observed center-to-limb variation (CLV) of the scattering polarization in different lines of the Second Solar Spectrum can be used to constrain the height variation of various atmospheric parameters, in particular the magnetic fields, via the Hanle effect. Here we attempt to model the nonmagnetic CLV observations of the Q/I profiles of the Ca i 4227 Å line recorded with the Zurich Imaging Polarimeter-3 at IRSOL. For modeling, we use the polarized radiative transfer with partial frequency redistribution with a number of realistic one-dimensional (1D) model atmospheres. We find that all the standard Fontenla–Avrett–Loeser (FAL) model atmospheres, which we used, fail to simultaneously fit the observed (I, Q/I) at all the limb distances (μ). However, an attempt is made to find a single model which can provide a fit to at least the CLV of the observed Q/I instead of a simultaneous fit to the (I, Q/I) at all μ. To this end we construct a new 1D model by combining two of the standard models after modifying their temperature structures in the appropriate height ranges. This new combined model closely reproduces the observed Q/I at all μ but fails to reproduce the observed rest intensity at different μ. Hence we find that no single 1D model atmosphere succeeds in providing a good representation of the real Sun. This failure of 1D models does not, however, cause an impediment to the magnetic field diagnostic potential of the Ca i 4227 Å line. To demonstrate this we deduce the field strength at various μ positions without invoking the use of radiative transfer.
A Novel SAR Image Registration Method Based on Target Attributed Scatter Center Feature

Synthetic Aperture Radar(SAR) image registration technology is widely used, but some problems are exhibited in the available technologies, such as feature extraction, loss of phase information, low computational complexity, and so on. To cope with these problems, in this paper, a method regards target Attributed Scatter Center (ASC) as the feature is proposed. ASC model highlights electromagnetic characteristics, which can better represent SAR images than optical characteristics. First, the parameter set of target ASC model is estimated by Iterative Shrinkage Thresholding Algorithm (ISTA), as a stable point feature registration descriptor of the image. Then, Nearest Neighbor Distance Ratio (NNDR) method is used to find the feature matching points of the reference image and the image to be registered. The matching accuracy is improved by the Random Sample Consensus (RANSAC) method. Finally, by transformation model and image offset, image registration and phase retention are realized. The simulation results demonstrate that the proposed method enables a better registration performance since the scattering characteristics are effectually utilized.
UAV Flight Configuration Impact on the Estimation of Dendrometric Parameters in Olive Trees

The estimation of dendrometric parameters of tree crops is crucial to decision making support for ecological and economic reasons. However, traditional methods for its measurement are time-consuming and laborious. Remote sensing data acquired from unmanned aerial vehicles (UAVs) combined with computer vision and Structure from Motion (SfM) algorithms can provide an easier and reliable solution to estimate those parameters. Nevertheless, various UAV flight settings can influence the quality of parameters derived from these data (e.g., flight height, imagery overlap). Thus, the main goal of this study is to assess the impact of different flight configurations on the detection of olive trees and on height and crown diameter estimation. The results showed that not only the configuration of the flight affects the dendrometric results, but also the topography of the terrain. Automatic tree detection revealed to be insensitive to the different flight configurations, whereas the tree height estimation was strongly affected. Among the analysed flights, the plan in double grid at 60 m of flight altitude and 90% of frontal overlap showed the best performance.
Semantic Segmentation Network with Band-Location Adaptive Selection Mechanism for Multispectral Remote Sensing Images

How to acquire effective information from multispectral remote sensing images is a challenging task in semantic segmentation of remote sensing images. In this paper, an end-to-end semantic segmentation network (BLASeNet) is proposed. The model adopts an encoder-decoder structure. In the encoder phase, to exploit the band correlation of multispectral remote sensing images, we propose an effective 3D Residual block to encode the spectral-spatial features of images. In order to extract more discriminative features from multispectral images, a band-location adaptive selection mechanism is proposed to adaptively learn the weights of different bands and different spatial locations within a single band, enhancing the expression of features. In the decoder phase, we introduce two trainable parameter matrices $\mathrm{W}_{\alpha}$ and Wβ in the skip connections, adaptively adjusting the fusion ratio of low-level detail features and high-level semantic features by network learning, improving the image segmentation accuracy. In addition, we extend the channel attention to 3D data, further refining the fused feature maps. Experimental results on ISPRS Potsdam and Qinghai datasets demonstrate the effectiveness of BLASeNet.
EFFECTS OF ROTATION ON STOCHASTICITY OF GRAVITATIONAL WAVES IN THE NONLINEAR PHASE OF CORE-COLLAPSE SUPERNOVAE

By performing three-dimensional (3D) simulations that demonstrate the neutrino-driven core-collapse supernovae aided by the standing accretion shock instability (SASI), we study how the spiral modes of the SASI can impact the properties of the gravitational-wave (GW) emission. To see the effects of rotation in the nonlinear postbounce phase, we give a uniform rotation on the flow advecting from the outer boundary of the iron core, the specific angular momentum of which is assumed to agree with recent stellar evolution models. We compute fifteen 3D models in which the initial angular momentum and the input neutrino luminosities from the protoneutron star are changed in a systematic manner. By performing a ray-tracing analysis, we accurately estimate the GW amplitudes generated by anisotropic neutrino emission. Our results show that the gravitational waveforms from neutrinos in models that include rotation exhibit a common feature; otherwise, they vary much more stochastically in the absence of rotation. The breaking of the stochasticity stems from the excess of the neutrino emission parallel to the spin axis. This is because the compression of matter is more enhanced in the vicinity of the equatorial plane due to the growth of the spiral SASI modes, leading to the formation of the spiral flows circulating around the spin axis with higher temperatures. We point out that recently proposed future space interferometers like Fabry–Perot-type DECIGO would permit the detection of these signals for a Galactic supernova.
Multi-camera scanning system for collecting and annotating 3D models of the head and neck

Obstructive sleep apnea is a respiratory syndrome that occurs in an increasing proportion of the population, including children. Diagnostics often consists of multiple examination steps what makes it difficult in many ways, such as time, labor, and price. As an additional method to the golden standard, which is polysomnography, we developed a supporting system that works with visual and spatial information of the patient's head and neck. In the first stage of research, we use the multi-camera scanning system for data collection. The collected data are annotated with a medical expert. The proposed annotation system is designed regarding preciseness, price, and accessibility. We also implemented the assistive algorithm, which helps to adjust the patient's head in a uniform position. We assume, that these data will be used in the future for developing the supportive tool which can give additional diagnostic information based on the craniofacial features. The relevance of such information will be the issue of future research and collaboration with experts in the field.
Group–galaxy correlations in redshift space as a probe of the growth of structure

We investigate the use of the cross-correlation between galaxies and galaxy groups to measure redshift-space distortions (RSD) and thus probe the growth rate of cosmological structure. This is compared to the classical approach based on using galaxy auto-correlation. We make use of realistic simulated galaxy catalogues that have been constructed by populating simulated dark matter haloes with galaxies through halo occupation prescriptions. We adapt the classical RSD dispersion model to the case of the group-galaxy cross-correlation function and estimate the RSD parameter $\beta$ by fitting both the full anisotropic correlation function $\xi(r_p,\pi)$ and its multipole moments. In addition, we define a modified version of the latter statistics by truncating the multipole moments to exclude strongly non-linear distortions at small transverse scales. We fit these three observable quantities in our set of simulated galaxy catalogues and estimate statistical and systematic errors on $\beta$ for the case of galaxy-galaxy, group-group, and group-galaxy correlation functions. When ignoring off-diagonal elements of the covariance matrix in the fitting, the truncated multipole moments of the group-galaxy cross-correlation function provide the most accurate estimate, with systematic errors below 3% when fitting transverse scales larger than $10Mpc/h$. Including the full data covariance enlarges statistical errors but keep unchanged the level of systematic error. Although statistical errors are generally larger for groups, the use of group-galaxy cross-correlation can potentially allow the reduction of systematics while using simple linear or dispersion models.