Miracle-dz/UniFAR-FTUs huggingface dataset:
Regime crossover in Rayleigh–Bénard convection with mixed boundary conditions

Abstract We numerically simulate three-dimensional Rayleigh–Bénard convection, the flow in a fluid layer heated from below and cooled from above, with inhomogeneous temperature boundary conditions, to explore two distinct regimes described in recent literature. We fix the non-dimensional temperature difference, i.e. the Rayleigh number, to $Ra=10^8$, and vary the Prandtl number between $1$ and $100$. By introducing stripes of adiabatic boundary conditions on the top plate, and making the surface of the top plate only $50\,\%$ conducting, we modify the heat transfer, the average temperature profiles and the underlying flow properties. We find two regimes: when the pattern wavelength is small, the flow is barely affected by the stripes. The heat transfer is reduced, but remains a large fraction of that of the unmodified case, and the underlying flow is only slightly modified. When the pattern wavelength is large, the heat transfer saturates to approximately two-thirds of the value of the unmodified problem, the temperature in the bulk increases substantially, and velocity fluctuations in the directions normal to the stripes are enhanced. The transition between the two regimes happens at pattern wavelength around the distance between the two plates, with different quantities transitioning at slightly different wavelength values. This transition is approximately Prandtl-number-independent, even if the statistics in the long-wavelength regime slightly vary.
The VLA/ALMA Nascent Disk and Multiplicity (VANDAM) Survey of Orion Protostars. II. A Statistical Characterization of Class 0 and Class I Protostellar Disks

We have conducted a survey of 328 protostars in the Orion molecular clouds with the Atacama Large Millimeter/submillimeter Array at 0.87 mm at a resolution of ∼0. ″1 (40 au), including observations with the Very Large Array at 9 mm toward 148 protostars at a resolution of ∼0. ″08 (32 au). This is the largest multiwavelength survey of protostars at this resolution by an order of magnitude. We use the dust continuum emission at 0.87 and 9 mm to measure the dust disk radii and masses toward the Class 0, Class I, and flat-spectrum protostars, characterizing the evolution of these disk properties in the protostellar phase. The mean dust disk radii for the Class 0, Class I, and flat-spectrum protostars are , , and au, respectively, and the mean protostellar dust disk masses are 25.9 , , , respectively. The decrease in dust disk masses is expected from disk evolution and accretion, but the decrease in disk radii may point to the initial conditions of star formation not leading to the systematic growth of disk radii or that radial drift is keeping the dust disk sizes small. At least 146 protostellar disks (35% of 379 detected 0.87 mm continuum sources plus 42 nondetections) have disk radii greater than 50 au in our sample. These properties are not found to vary significantly between different regions within Orion. The protostellar dust disk mass distributions are systematically larger than those of Class II disks by a factor of >4, providing evidence that the cores of giant planets may need to at least begin their formation during the protostellar phase.
Spatial-Spectral Residual Network for Hyperspectral Image Super-Resolution

Deep learning-based hyperspectral image super-resolution (SR) methods have achieved great success recently. However, most existing models can not effectively explore spatial information and spectral information between bands simultaneously, obtaining relatively low performance. To address this issue, in this paper, we propose a novel spectral-spatial residual network for hyperspectral image super-resolution (SSRNet). Our method can effectively explore spatial-spectral information by using 3D convolution instead of 2D convolution, which enables the network to better extract potential information. Furthermore, we design a spectral-spatial residual module (SSRM) to adaptively learn more effective features from all the hierarchical features in units through local feature fusion, significantly improving the performance of the algorithm. In each unit, we employ spatial and temporal separable 3D convolution to extract spatial and spectral information, which not only reduces unaffordable memory usage and high computational cost, but also makes the network easier to train. Extensive evaluations and comparisons on three benchmark datasets demonstrate that the proposed approach achieves superior performance in comparison to existing state-of-the-art methods.
A Machine Condition Monitoring Framework Using Compressed Signal Processing

The vibration monitoring of ball bearings of a rotating machinery is a crucial aspect for smooth functioning and sustainability of plants. The wireless vibration monitoring using conventional Nyquist sampling techniques is costly in terms of power consumption, as it generates lots of data that need to be processed. To overcome this issue, compressive sensing (CS) can be employed, which directly acquires the signal in compressed form and hence reduces power consumption. The compressive measurements so generated can easily be transmitted to the base station and the original signal can be recovered there using CS reconstruction algorithms to diagnose the faults. However, the CS reconstruction is very costly in terms of computational time and power. Hence, this conventional CS framework is not suitable for diagnosing the machinery faults in real time. In this paper, a bearing condition monitoring framework is presented based on compressed signal processing (CSP). The CSP is a newer research area of CS, in which inference problems are solved without reconstructing the original signal back from compressive measurements. By omitting the reconstruction efforts, the proposed method significantly improves the time and power cost. This leads to faster processing of compressive measurements for solving the required inference problems for machinery condition monitoring. This gives a way to diagnose the machinery faults in real-time. A comparison of proposed scheme with the conventional method shows that the proposed scheme lowers the computational efforts while simultaneously achieving the comparable fault classification accuracy.
Cram\'er-Rao Lower Bounds Arising from Generalized Csisz\'ar Divergences

We study the geometry of probability distributions with respect to a generalized family of Csiszar $f$-divergences. A member of this family is the relative $\alpha$-entropy which is also a Renyi analog of relative entropy in information theory and known as logarithmic or projective power divergence in statistics. We apply Eguchi's theory to derive the Fisher information metric and the dual affine connections arising from these generalized divergence functions. This enables us to arrive at a more widely applicable version of the Cramer-Rao inequality, which provides a lower bound for the variance of an estimator for an escort of the underlying parametric probability distribution. We then extend the Amari-Nagaoka's dually flat structure of the exponential and mixer models to other distributions with respect to the aforementioned generalized metric. We show that these formulations lead us to find unbiased and efficient estimators for the escort model. Finally, we compare our work with prior results on generalized Cramer-Rao inequalities that were derived from non-information-geometric frameworks.
Observational Nonstationarity of AGN Variability: The Only Way to Go Is Down!

To gain insights into long-term active galactic nuclei (AGN) variability, we analyze an AGN sample from the Sloan Digital Sky Survey (SDSS) and compare their photometry with observations from the Hyper Suprime-Cam survey (HSC) observed yr after SDSS. On average, the AGN are fainter in HSC than SDSS. We demonstrate that the difference is not due to subtle differences in the SDSS versus HSC filters or photometry. The decrease in mean brightness is redshift dependent, consistent with expectations for a change that is a function of the rest-frame time separation between observations. At a given redshift, the mean decrease in brightness is stronger for more luminous AGN and for objects with longer time separation between measurements. We demonstrate that the dependence on redshift and luminosity of measured mean brightness decrease is consistent with simple models of Eddington ratio variability in AGN on long (Myr, Gyr) timescales. We show how our results can be used to constrain the variability and demographic properties of AGN populations.
On the Pilot Contamination Attack in Multi-Cell Multiuser Massive MIMO Networks

In this paper, we analyze pilot contamination (PC) attacks on a multi-cell massive multiple-input multiple-output (MIMO) network with correlated pilots. We obtain correlated pilots using a user capacity-achieving pilot sequence design. This design relies on an algorithm which designs correlated pilot sequences based on signal-to-interference-plus-noise ratio (SINR) requirements for all the legitimate users. The pilot design is capable of achieving the SINR requirements for all users even in the presence of PC. However, this design has some intrinsic limitations and vulnerabilities, such as a known pilot sequence and the non-zero cross-correlation among different pilot sequences. We reveal that such vulnerabilities may be exploited by an active attacker to increase PC in the network. Motivated by this, we analyze the correlated pilot design for vulnerabilities that can be exploited by an active attacker. Based on this analysis, we develop an effective active attack strategy in the massive MIMO network with correlated pilot sequences. Our examinations reveal that the user capacity region of the network is significantly reduced in the presence of the active attack. Importantly, the SINR requirements for the worst-affected users may not be satisfied even with an infinite number of antennas at the base station.
A spectroscopic survey of Abell 1703: is it a rare relaxed cluster hosting a radio halo or a usual merging system?

We present the study of the internal dynamics of the intriguing galaxy cluster Abell 1703, a system hosting a probable giant radio halo whose dynamical status is still controversial. Our analysis is based on unpublished spectroscopic data acquired at the Italian Telescopio Nazionale Galileo and data publicly available in the literature. We also use photometric data from the Sloan Digital Sky Survey. We select 147 cluster members and compute the cluster redshift $\left \sim 0.277$ and the global line-of-sight velocity dispersion $\sigma_{\rm v}\sim 1300$ km/s. We infer that Abell 1703 is a massive cluster: $M_{200}\sim 1-2\times 10^{15}$ $M_{\odot}$. The results of our study disagree with the picture of an unimodal, relaxed cluster as suggested by previous studies based on the gravitational lensing analysis and support the view of a perturbed dynamics proposed by recent works based on Chandra X-ray data. The first strong evidence of a dynamically disturbed cluster comes from the peculiarity of the BCG velocity with respect to the first moment of the velocity distribution of member galaxies. Moreover, several statistical tests employed to study the cluster galaxies kinematics find significant evidence of substructure, being Abell 1703 composed by at least two or three subclumps probably caught after the core-core passage. In this observational scenario, the suspected existence of a radio halo in the centre of this cluster is not surprising and well agrees with the theoretical models describing diffuse radio sources in clusters.
A Merged Search‐Coil and Fluxgate Magnetometer Data Product for Parker Solar Probe FIELDS

NASA's Parker Solar Probe (PSP) mission is currently investigating the local plasma environment of the inner heliosphere (<0.25 R⊙) using both in situ and remote sensing instrumentation. Connecting signatures of microphysical particle heating and acceleration processes to macroscale heliospheric structure requires sensitive measurements of electromagnetic fields over a large range of physical scales. The FIELDS instrument, which provides PSP with in situ measurements of electromagnetic fields of the inner heliosphere and corona, includes a set of three vector magnetometers: two fluxgate magnetometers (MAGs) and a single inductively coupled search‐coil magnetometer (SCM). Together, the three FIELDS magnetometers enable measurements of the local magnetic field with a bandwidth ranging from DC to 1 MHz. This manuscript reports on the development of a merged data set combining SCM and MAG (SCaM) measurements, enabling a high fidelity data product with an optimal signal‐to‐noise ratio. On‐ground characterization tests of complex instrumental responses and noise floors are discussed as well as application to the in‐flight calibration of FIELDS data. The algorithm used on PSP/FIELDS to merge waveform observations from multiple sensors with optimal signal‐to‐noise characteristics is presented. In‐flight analysis of calibrations and merging algorithm performance demonstrates a timing accuracy to well within the survey rate sample period of ∼340 μs.
GW190425 is inconsistent with being a binary neutron star born from a fast merging channel

The LIGO/Virgo Scientific Collaboration (LSC) recently announced the detection of a compact object binary merger, GW190425, with a total mass of $3.4^{+0.3}_{-0.1}$ M$_{\odot}$, and individual component masses in range of about 1.1 to 2.5 $M_{\odot}$. If the constituent compact objects are neutron stars, then the total mass is five standard deviations higher than the mean of $2.66\pm 0.12$ M$_{\odot}$ for Galactic binary neutron stars. The non-detection of such massive BNS systems in the Galaxy indicates a potential bias against their detection, which can arise if such massive BNS systems are born with short orbital periods and hence inspiral times of $\sim 10$ Myr. However, we show that the reported merger rate, $\mathcal{R}_{\rm GW190425}=460^{+1050}_{-390}$ yr$^{-1}$ Gpc$^{-3}$, requires extremely high formation efficiency for such systems of $\lambda_{\rm f,BNS}= 2\times10^{-4}-5\times10^{-3}$ M$_{\odot}^{-1}$, orders of magnitude larger than the formation efficiency of fast merging BNS systems from population synthesis models, $\lambda_{\rm f,BNS}\approx (2-5)\times10^{-6} M_{\odot}^{-1}$. Moreover, the comparable merger rates inferred from GW190425 and GW170817 is problematic for two reasons: (i) more massive systems are expected to have a lower formation rate, and (ii) fast merging channels should constitute $\lesssim 10\%$ of the total BNS systems if case BB unstable mass transfer is permitted to take place as a formation pathway. We argue that to account for the high merger rate of GW190425 as a BNS system requires: (i) a change in our understanding NS formation in supernova explosions, or (ii): that more massive NSs need to be preferentially born with weaker magnetic fields so that they would be undetectable in the radio surveys. Whether such an explanation is plausible would require detailed modeling of BNS population with careful treatment of their magnetic fields evolution.
$p$-Adic hypergeometric functions in the connections with certain twisted Kloosterman sheaf sum and modular forms

In this paper we establish certain identities connecting $p$-adic hypergeometric functions with 4-th twisted Kloosterman sheaf sum. To prove these identities we express certain character sum over finite field in terms of special values of $p$-adic hypergeometric functions. One conjecture of Evans behaves as a bridge to connect $p$-adic hypergeometric functions with Kloosterman sheaf sum. We also connect $p$-adic hypergeometric functions with Fourier coefficients of certain modular forms.
Formation of COMs through CO hydrogenation on interstellar grains

Context. Glycoaldehyde, ethylene glycol, and methyl formate are complex organic molecules that have been observed in dark molecular clouds. Because there is no efficient gas-phase route to produce these species, it is expected that a low-temperature surface route existst that does not require energetic processing. CO hydrogenation experiments at low temperatures showed that this is indeed the case. Glyoxal can form through recombination of two HCO radicals and is then further hydrogenated. Aims. Here we aim to constrain the methyl formate, glycolaldehyde, and ethylene glycol formation on the surface of interstellar dust grains through this cold and dark formation route. We also probe the dependence of the grain mantle composition on the initial gas-phase composition and the dust temperature. Methods. A full CO hydrogenation reaction network was built based on quantum chemical calculations for the rate constants and branching ratios. This network was used in combination with a microscopic kinetic Monte Carlo simulation to simulate ice chemistry, taking into account all positional information. After benchmarking the model against CO-hydrogenation experiments, simulations under molecular cloud conditions were performed. Results. Glycoaldehyde, ethylene glycol, and methyl formate are formed in all interstellar conditions we studied, even at temperatures as low as 8 K. This is because the HCO + HCO reaction can occur when HCO radicals are formed close to each other and do not require to diffuse. Relatively low abundances of methyl formate are formed. The final COM abundances depend more on the H-to-CO ratio and less on temperature. Only above 16 K, where CO build-up is less efficient, does temperature start to play a role. Molecular hydrogen is predominantly formed through abstraction reactions on the surface. The most important reaction leading to methanol is H2CO + CH3O → HCO + CH3OH. Our simulations are in agreement with observed COM ratios for mantles that have been formed at low temperatures.
Expression of Bcl-2 marker in premalignant lesions of cervical cancer

Background: Cervical cancer is one of the most common gynecological cancers in women of developing countries. HPV DNA testing is preferred cervical screening method for woman 30-65 years old as HPV is the proved causative agent of cervical carcinoma. Due to the high costs involved in doing HPV DNA test there is a need for a biomarker such as Bcl-2 which can indicate the initiation of carcinogenic process of HPV infection and thus can be used to identify those woman who will need more surveillance. Methods: Specimens of cervical biopsy retrieved from incident cases for routine histopathological evaluation from the Department of Obstetrics and gynecology, M.S. Ramaiah hospital, Bangalore, India from March 2013 to September 2015 formed the source of data for the study. Results: In this study total of 46 cases were studied which included 9 cases of CIN-1, 8 cases of CIN-2, 7 cases of CIN-3, 12 cases of squamous cell carcinoma and 10 cases of on specific cervicitis. Higher number of malignant lesions (75%) expressed Bcl-2 positivity as compared to premalignant lesions (62.5%). In case of CIN lesions, Bcl-2 positivity increased as the grade increased (CIN-1- 55.56%; CIN-2 - 62.5%; CIN-3 -71.43%). Conclusions: Bcl-2 which is an intracellular membrane protein which prevents apoptotic cell death can be used as a biomarker to know the severity of the CIN lesion and hence help in identifying the high risk CIN lesions which need further surveillance and treatment.
Amenability and functoriality of right-LCM semigroup C*-algebras

We prove a functoriality result for the full C*-algebras of right-LCM monoids with respect to monoid inclusions that are closed under factorization and preserve orthogonality, and use this to show that if a right-LCM monoid is amenable in the sense of Nica, then so are its submonoids. As applications, we complete the classification of Artin monoids with respect to Nica amenability by showing that only the right-angled ones are amenable in the sense of Nica and we show that the Nica amenability of a graph product of right-LCM semigroups is inherited by the factors.
Application of Convolutional Neural Networks to Identify Stellar Feedback Bubbles in CO Emission

We adopt the deep learning method called the Convolutional Approach to Shell Identification (casi) and extend it to 3D (casi-3d) to identify signatures of stellar feedback in molecular line spectra. We use magnetohydrodynamics simulations modeling the impact of stellar winds in a turbulent molecular cloud to generate synthetic 13CO (J = 1 − 0) observations. We train two casi-3d models: ME1 predicts only the position of feedback, while MF predicts the fraction of the mass coming from feedback in each voxel. We adopt 75% of the synthetic observations as the training set and assess the accuracy of the two models with the remaining data. Both models identify bubbles in simulated data within 5% error. We use bubbles previously visually identified in Taurus in 13CO to validate the models and show that both perform well on the highest confidence bubbles. Models ME1 and MF predict total feedback gas mass of 2894 M⊙ and 302 M⊙, respectively. After correcting for missing energy due to the limited velocity range, model ME1 predicts feedback kinetic energies of 4.0 × 1046 erg and 1.5 × 1047 erg with and without subtracting the cloud velocity gradient. Model MF predicts feedback kinetic energies of 9.6 × 1045 erg and 2.8 × 1046 erg with and without subtracting the cloud velocity gradient. Model ME1 predicts bubble locations and properties consistent with previous visual identifications. However, model MF demonstrates that feedback properties computed using visual identifications significantly overestimate feedback impact, due to line-of-sight confusion and contamination from background and foreground gas.
Ground-state phase diagram of the three-band Hubbard model in various parametrizations from density matrix embedding theory

\We compute the ground-state phase diagram of the three-band Hubbard model in various published parametrizations using density matrix embedding theory. We study the atomic-scale nature of the antiferromagnetic (AF) and superconducting (SC) orders, explicitly including the oxygen degrees of freedom. In the case of the AF order, as expected, the local magnetic moment localizes entirely at the copper sites and decays with doping, while in the SC phase we observe a local p_(x(y)) [or d_(xz(yz))]-symmetry modulation of the pair density on the Cu-O bonds within the larger scale d_(x²−y²)-wave SC pairing order between Cu-Cu and O-O. While all parametrizations of the model display AF and SC phases, the decay of AF order with doping is too slow compared to the experimental phase diagram, and further, coexistence of AF and SC orders occurs in all parameter sets. Our work highlights the importance of the oxygen degrees of freedom in the study of atomic-scale SC orders, as well as the necessity of re-evaluating current parametrizations of the three-band Hubbard model.
Cosets of monodromies and quantum representations

We use geometric methods to show that given any $3$-manifold $M$, and $g$ a sufficiently large integer, the mapping class group $\mathrm{Mod}(\Sigma_{g,1})$ contains a coset of an abelian subgroup of rank $\lfloor \frac{g}{2}\rfloor,$ consisting of pseudo-Anosov monodromies of open-book decompositions in $M. $ We prove a similar result for rank two free cosets of $\mathrm{Mod}(\Sigma_{g,1}). $ These results have applications to a conjecture of Andersen, Masbaum and Ueno about quantum representations of surface mapping class groups. For surfaces with boundary, and large enough genus, we construct cosets of abelian and free subgroups of their mapping class groups consisting of elements that satisfy the conjecture. The mapping tori of these elements are fibered 3-manifolds that satisfy a weak form of the Turaev-Viro invariants volume conjecture.