Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Bi-Hemispheric Discrepancy Model for EEG Emotion Recognition

Neuroscience study has revealed the discrepancy of emotion expression between the left and right hemispheres of human brain. Inspired by this study, in this article, we propose a novel bi-hemispheric discrepancy model (BiHDM) to learn this discrepancy information between the two hemispheres to improve electroencephalograph (EEG) emotion recognition. Concretely, we first employ four directed recurrent neural networks (RNNs) based on two spatial orientations to traverse electrode signals on two separate brain regions. This enables the proposed model to obtain the deep representations of all the EEG electrodes’ signals that keep their intrinsic spatial dependence. Upon this representation, a pairwise subnetwork is designed to explicitly capture the discrepancy information between the two hemispheres and extract higher level features for final classification. Furthermore, considering the presence of the domain shift between training and testing data, we incorporate a domain discriminator that adversarially induces the overall feature learning module to generate emotion related but domain-invariant feature representation so as to further promote EEG emotion recognition. Experiments are conducted on three public EEG emotional data sets, in which we evaluate the performance of the proposed BiHDM as well as investigated the important brain areas in emotion expression and explore to use less electrodes to achieve comparable results. These experimental results jointly demonstrate the effectiveness and advantage of the proposed BiHDM model in solving the EEG emotion recognition problem.
Two-photon quantum interference and entanglement at 2.1 μm

Our results show a viable route to free-space quantum-secured communication in an unexplored atmospheric transparency window. Quantum-enhanced optical systems operating within the 2- to 2.5-μm spectral region have the potential to revolutionize emerging applications in communications, sensing, and metrology. However, to date, sources of entangled photons have been realized mainly in the near-infrared 700- to 1550-nm spectral window. Here, using custom-designed lithium niobate crystals for spontaneous parametric down-conversion and tailored superconducting nanowire single-photon detectors, we demonstrate two-photon interference and polarization-entangled photon pairs at 2090 nm. These results open the 2- to 2.5-μm mid-infrared window for the development of optical quantum technologies such as quantum key distribution in next-generation mid-infrared fiber communication systems and future Earth-to-satellite communications.
Probabilistic hypergraph grammars for efficient molecular optimization

We present an approach to make molecular optimization more efficient. We infer a hypergraph replacement grammar from the ChEMBL database, count the frequencies of particular rules being used to expand particular nonterminals in other rules, and use these as conditional priors for the policy model. Simulating random molecules from the resulting probabilistic grammar, we show that conditional priors result in a molecular distribution closer to the training set than using equal rule probabilities or unconditional priors. We then treat molecular optimization as a reinforcement learning problem, using a novel modification of the policy gradient algorithm - batch-advantage: using individual rewards minus the batch average reward to weight the log probability loss. The reinforcement learning agent is tasked with building molecules using this grammar, with the goal of maximizing benchmark scores available from the literature. To do so, the agent has policies both to choose the next node in the graph to expand and to select the next grammar rule to apply. The policies are implemented using the Transformer architecture with the partially expanded graph as the input at each step. We show that using the empirical priors as the starting point for a policy eliminates the need for pre-training, and allows us to reach optima faster. We achieve competitive performance on common benchmarks from the literature, such as penalized logP and QED, with only hundreds of training steps on a budget GPU instance.
Small Planets in the Galactic Context: Host Star Kinematics, Iron, and Alpha-element Enhancement

We explored the occurrence rate of small close-in planets among Kepler target stars as a function of the iron abundance and the stellar total velocity . We estimated the occurrence rate of those planets by combining information from the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) and the California-Kepler Survey and found that iron-poor stars exhibit an increase in the occurrence with from f < 0.2 planets per star at < 30 to f ∼ 1.2 at > 90 . We suggest this planetary profusion may be a result of a higher abundance of α elements associated with iron-poor, high-velocity stars. Furthermore, we have identified an increase in small-planet occurrence with iron abundance, particularly for the slower stars ( < 30 ), where the occurrence increased to f ∼ 1.1 planets per star in the iron-rich domain. Our results suggest there are two regions in the ([Fe/H], [α/Fe]) plane in which stars tend to form and maintain small planets. We argue that analysis of the effect of overall metal content on planet occurrence is incomplete without including information on both iron and α-element enhancement.
Galactic radial abundance gradients: cepheids and photoionized nebulae.

Radial abundance gradients are observed in the Galaxy and other galaxies as well, and include several chemical elements in different stellar systems. Possibly the most accurate gradients in the Galaxy are those determined from chepheid variable stars. These objects have very accurate abundances for many elements and are generally considered as standard candles, so that their galactocentric distances are very well determined. These stars are relatively young, with ages between the main types of photoionized nebulae, namely the younger HII regions and the older planetary nebulae. In this paper we consider the O/H and Fe/H gradients based on a large sample of galactic cepheids, and compare the results with recent determinations from photoionized nebulae.
The Evolution of the Interstellar Medium in Post-starburst Galaxies

We derive dust masses (Mdust) from the spectral energy distributions of 58 post-starburst galaxies (PSBs). There is an anticorrelation between specific dust mass (Mdust/M⋆) and the time elapsed since the starburst ended, indicating that dust was either destroyed, expelled, or rendered undetectable over the ∼1 Gyr after the burst. The Mdust/M⋆ depletion timescale, , is consistent with that of the CO-traced , suggesting that dust and gas are altered via the same process. Extrapolating these trends leads to the Mdust/M⋆ and values of early-type galaxies (ETGs) within 1–2 Gyr, a timescale consistent with the evolution of other PSB properties into ETGs. Comparing Mdust and for PSBs yields a calibration, log , that allows us to place 33 PSBs on the Kennicutt–Schmidt (KS) plane, . Over the first ∼200–300 Myr, the PSBs evolve down and off of the KS relation, as their star formation rate (SFR) decreases more rapidly than . Afterwards, continues to decline whereas the SFR levels off. These trends suggest that the star formation efficiency bottoms out at 10−11 yr−1 and will rise to ETG levels within 0.5–1.1 Gyr afterwards. The SFR decline after the burst is likely due to the absence of gas denser than the CO-traced H2. The mechanism of the Mdust/M⋆ and decline, whose timescale suggests active galactic nucleus/low-ionization nuclear emission-line region feedback, may also be preventing the large CO-traced molecular gas reservoirs from collapsing and forming denser star-forming clouds.
On the Energy of a Non-Singular Black Hole Solution Satisfying the Weak Energy Condition

The energy-momentum localization for a new four-dimensional and spherically symmetric, charged black hole solution that through a coupling of general relativity with non-linear electrodynamics is everywhere non-singular while it satisfies the weak energy condition, is investigated. The Einstein and Møller energy-momentum complexes have been employed in order to calculate the energy distribution and the momenta for the aforesaid solution. It is found that the energy distribution depends explicitly on the mass and the charge of the black hole, on two parameters arising from the space-time geometry considered, and on the radial coordinate. Further, in both prescriptions all the momenta vanish. In addition, a comparison of the results obtained by the two energy-momentum complexes is made, whereby some limiting and particular cases are pointed out.
A Survey of Behavior Learning Applications in Robotics - State of the Art and Perspectives

Recent success of machine learning in many domains has been overwhelming, which often leads to false expectations regarding the capabilities of behavior learning in robotics. In this survey, we analyze the current state of machine learning for robotic behaviors. We will give a broad overview of behaviors that have been learned and used on real robots. Our focus is on kinematically or sensorially complex robots. That includes humanoid robots or parts of humanoid robots, for example, legged robots or robotic arms. We will classify presented behaviors according to various categories and we will draw conclusions about what can be learned and what should be learned. Furthermore, we will give an outlook on problems that are challenging today but might be solved by machine learning in the future and argue that classical robotics and other approaches from artificial intelligence should be integrated more with machine learning to form complete, autonomous systems.
THE UTILIZATION OF SODIUM TAUROCHOLATE IN EXCYSTATION OF CRYPTOSPORIDIUM PARVUM AND INFECTION OF TISSUE CULTURE

The present work deals with optimization of excystation of Cryptosporidium parvum oocysts and the infection process of tissue culture cells by the parasite. It was shown that presence of the bile salt sodium taurocholate in the incubation medium expedited excystation of the tested GCH1 isolate and enhanced it, as compared with bleaching of the oocysts. This bile salt had no effect on the viability of tissue culture cell lines MDBK and HCT-8 at the tested concentration of 0.375% for up to 2 hr of coincubation. Infection studies conducted on tissue culture cells showed higher infection rates in the presence of sodium taurocholate than with bleached oocysts in the absence of this bile salt. It may be concluded that, at least as regards the GCH1 strain of C. parvum, the whole infection process can be performed in the presence of sodium taurocholate, and does not require separation and cleaning of the excysted sporozoites before their application to tissue culture cells.
Neural Legal Judgment Prediction in English

Legal judgment prediction is the task of automatically predicting the outcome of a court case, given a text describing the case’s facts. Previous work on using neural models for this task has focused on Chinese; only feature-based models (e.g., using bags of words and topics) have been considered in English. We release a new English legal judgment prediction dataset, containing cases from the European Court of Human Rights. We evaluate a broad variety of neural models on the new dataset, establishing strong baselines that surpass previous feature-based models in three tasks: (1) binary violation classification; (2) multi-label classification; (3) case importance prediction. We also explore if models are biased towards demographic information via data anonymization. As a side-product, we propose a hierarchical version of BERT, which bypasses BERT’s length limitation.
Flexible stability and nonsoficity

<p>A sofic group <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3. org/1998/Math/MathML" alttext="upper G"> <mml:semantics> <mml:mi>G</mml:mi> <mml:annotation encoding="application/x-tex">G</mml:annotation> </mml:semantics> </mml:math> </inline-formula> is said to be flexibly stable if every sofic approximation to <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3. org/1998/Math/MathML" alttext="upper G"> <mml:semantics> <mml:mi>G</mml:mi> <mml:annotation encoding="application/x-tex">G</mml:annotation> </mml:semantics> </mml:math> </inline-formula> can be converted to a sequence of disjoint unions of Schreier graphs by modifying an asymptotically vanishing proportion of edges. We establish that if <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3. org/1998/Math/MathML" alttext="normal upper P normal upper S normal upper L Subscript d Baseline left-parenthesis double-struck upper Z right-parenthesis"> <mml:semantics> <mml:mrow> <mml:msub> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">P</mml:mi> <mml:mi mathvariant="normal">S</mml:mi> <mml:mi mathvariant="normal">L</mml:mi> </mml:mrow> <mml:mi>d</mml:mi> </mml:msub> <mml:mo stretchy="false">(</mml:mo> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="double-struck">Z</mml:mi> </mml:mrow> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> <mml:annotation encoding="application/x-tex">\mathrm {PSL}_d(\mathbb {Z})</mml:annotation> </mml:semantics> </mml:math> </inline-formula> is flexibly stable for some <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3. org/1998/Math/MathML" alttext="d greater-than-or-equal-to 5"> <mml:semantics> <mml:mrow> <mml:mi>d</mml:mi> <mml:mo>≥<! -- ≥ --></mml:mo> <mml:mn>5</mml:mn> </mml:mrow> <mml:annotation encoding="application/x-tex">d \geq 5</mml:annotation> </mml:semantics> </mml:math> </inline-formula>, then there exists a group which is not sofic. </p>
Colors of Trans-Neptunian Contact Binaries

The g′r′i′ colors of seven likely and potential contact binaries in the Kuiper Belt were acquired with the Magellan-Baade telescope and combined with colors from the literature to understand contact binary surfaces. The likely and potential contact binaries discovered in the dynamically cold classical population display very red/ultra-red colors. Such colors are common in this sub-population and imply that the cold classical contact binaries were formed in situ. The likely contact binaries found in several mean motion resonances with Neptune have colors from moderately to ultra-red, suggesting different formation regions. Among the nine contact binaries discovered in resonances, five have very red/ultra-red colors and four have moderately red surfaces. Based on the very red/ultra-red colors and low to moderate inclinations of the contact binaries in resonances, these contact binaries are possibly escaped dynamically cold classicals that are now trapped in resonances. Moderately red surfaces are common in diverse sub-populations of the Kuiper Belt, thus pinpointing their origin is difficult though they are most likely captured objects that formed in the giant planet area. Finally, for the contact binary population we report an anti-correlation between inclination and g′–r′, as noticed in the rest of this belt. We also find hints of trends between eccentricity, perihelion distance, rotational period, and g′–r′, but as we are still dealing with a limited sample, additional data are required to confirm them.
Going deep: models for continuous-time within-play valuation of game outcomes in American football with tracking data

Abstract Continuous-time assessments of game outcomes in sports have become increasingly common in the last decade. In American football, only discrete-time estimates of play value were possible, since the most advanced public football datasets were recorded at the play-by-play level. While measures such as expected points and win probability are useful for evaluating football plays and game situations, there has been no research into how these values change throughout the course of a play. In this work, we make two main contributions: First, we introduce a general framework for continuous-time within-play valuation in the National Football League using player-tracking data. Our modular framework incorporates several modular sub-models, to easily incorporate recent work involving player tracking data in football. Second, we use a long short-term memory recurrent neural network to construct a ball-carrier model to estimate how many yards the ball-carrier is expected to gain from their current position, conditional on the locations and trajectories of the ball-carrier, their teammates and opponents. Additionally, we demonstrate an extension with conditional density estimation so that the expectation of any measure of play value can be calculated in continuous-time, which was never before possible at such a granular level.
hp-Version discontinuous Galerkin methods on essentially arbitrarily-shaped elements

We extend the applicability of the popular interior-penalty discontinuous Galerkin (dG) method discretizing advection-diffusion-reaction problems to meshes comprising extremely general, essentially arbitrarily-shaped element shapes. In particular, our analysis allows for \emph{curved} element shapes, without the use of (iso-)parametric elemental maps. The feasibility of the method relies on the definition of a suitable choice of the discontinuity-penal-ization parameter, which turns out to be essentially independent on the particular element shape. A priori error bounds for the resulting method are given under very mild structural assumptions restricting the magnitude of the local curvature of element boundaries. Numerical experiments are also presented, indicating the practicality of the proposed approach.
Revisiting Shared Data Protection Against Key Exposure

This paper puts a new light on computational secret sharing with a view towards distributed storage environments. It starts with revisiting the security model for encrypted data protection against key exposure. The goal of this revisiting is to take advantage of the characteristics of distributed storage in order to design faster key leakage resisting schemes, with the same security properties as the existing ones in this context of distributed storage. We then introduce two novel schemes that match our ---all storage places or nothing--- security level of secret sharing under key exposure. The first one is based on standard block cipher encryption. The second one fits both in the random oracle model (e.g. Keccak) or in the idealized blockcipher model with twice larger key than the security parameter (e.g. an idealized AES256 would achieve 128 bits security). The first one reduces by half the amount of the processing required to be done in addition to data encryption with regard to the fastest state-of-the-art solution, whereas the second one completely eradicates additional processing. We confirm the complexity results by presenting a performance evaluation. A non-negligible part of our contribution lies in the provided security analysis. In addition to giving security proofs for our schemes, we revisit the ones of previous work and point out structural weaknesses in a context of key exposure.
The evolution of the UV luminosity function of globular clusters in the E-MOSAICS simulations

We present the evolution of the rest-frame ultraviolet (UV) properties of the globular cluster (GC) populations and their host galaxies formed in the E-MOSAICS suite of cosmological hydrodynamical simulations. We compute the luminosities of all clusters associated with 25 simulated Milky-Way-mass galaxies, discussed in previous works, in the rest-frame UV and optical bands by combining instantaneous cluster properties (age, mass, metallicity) with simple stellar population models, from redshifts z = 0 to 10. Due to the rapid fading of young stellar populations in the UV, most of the simulated galaxies do not host GCs bright enough to be individually identified in deep Hubble Space Telescope observations, even in highly magnified systems. The median age of the most UV-luminous GCs is 2 is typically MUV ∼ −16, consistent with the luminosities of observed compact high-redshift sources.
The Role of Energy Diffusion in the Deposition of Energetic Electron Energy in Solar and Stellar Flares

During solar flares, a large fraction of the released magnetic energy is carried by energetic electrons that transfer and deposit energy in the Sun’s atmosphere. Electron transport is often approximated by a cold thick-target model, assuming that electron energy is much larger than the temperature of the ambient plasma, and electron energy evolution is modeled as a systematic loss. Using kinetic modeling of electrons, we reevaluate the transport and deposition of flare energy. Using a full collisional warm-target model (WTM), we account for electron thermalization and for the properties of the ambient coronal plasma such as its number density, temperature and spatial extent. We show that the deposition of nonthermal electron energy in the lower atmosphere is highly dependent on the properties of the flaring coronal plasma. In general, thermalization and a reduced WTM energy loss rate leads to an increase of nonthermal energy transferred to the chromosphere, and the deposition of nonthermal energy at greater depths. The simulations show that energy is deposited in the lower atmosphere initially by high-energy nonthermal electrons, and later by lower energy nonthermal electrons that partially or fully thermalize in the corona, over timescales of seconds, unaccounted for in previous studies. This delayed heating may act as a diagnostic of both the injected nonthermal electron distribution and the coronal plasma, vital for constraining flare energetics.
Galaxy simulation with the evolution of grain size distribution

We compute the evolution of interstellar dust in a hydrodynamic simulation of an isolated disc galaxy. We newly implement the evolution of full grain size distribution by sampling 32 grid points on the axis of the grain radius. We solve it consistently with the chemical enrichment and hydrodynamic evolution of the galaxy. This enables us to theoretically investigate spatially resolved evolution of grain size distribution in a galaxy. The grain size distribution evolves from a large-grain-dominated ($\gtrsim 0.1\,\rm{\mu m}$) phase to a small-grain production phase, eventually converging to a power-law-like grain size distribution similar to the so-called MRN distribution. We find that the small-grain abundance is higher in the dense ISM in the early epoch (t ≲ 1 Gyr) because of efficient dust growth by accretion, while coagulation makes the small-grain abundance less enhanced in the dense ISM later. This leads to steeper extinction curves in the dense ISM than in the diffuse ISM in the early phase, while they show the opposite trend later. The radial trend of extinction curves is described by faster evolution in the inner part. We also confirm that the simulation reproduces the observed relation between dust-to-gas ratio and metallicity, and the radial gradients of dust-to-gas ratio and dust-to-metal ratio in nearby galaxies. Since the above change in the grain size distribution occurs in t ∼ 1 Gyr, the age and density dependence of grain size distribution has a significant impact on the extinction curves even at high redshift.