Miracle-dz/UniFAR-FTUs huggingface dataset:
Deficits in facial emotional valence processing in older people with subjective memory complaints: Behavioral and electrophysiological evidence.

Subjective memory complaints (SMCs), which occur in the absence of clinical memory deficits, may precede mild cognitive impairment (MCI) or Alzheimer's disease (AD). Some studies have reported a deficit in facial emotion processing in people with MCI or AD. However, it is unclear whether this deficit is also present in older people with SMCs. The present study used behavioral measurements and event-related potentials (ERPs) to investigate the facial emotion processing of 41 older people with SMCs and 38 without SMCs. The task contained 204 images displaying facial emotions (positive, negative, and neutral). In terms of behavior, our results showed that participants with SMCs were slower and less accurate than controls. In terms of ERPs, the N170 latency was longer in men with SMCs than in controls, whereas no differences were observed between groups in the P300 and late positive potential (LPP) latencies or amplitudes. Moreover, in participants with SMCs, higher P300 and LPP amplitudes were related to better performance on working memory, psychomotor speed, and attention. Additionally, women were faster and more accurate than men on the facial emotion-processing task. In sum, these results suggest that older people with SMCs may have deficits in the processing of facial expressions of emotion. However, this deficit seems to affect the structural encoding of faces, rather than the late stages of processing.
Streaming Based Bicriteria Approximation Algorithms for Submodular Optimization

This paper proposes the optimization problem Non-Monotone Submodular Cover (SC), which is to minimize the cost required to ensure that a non-monotone submodular beneﬁt function exceeds a given threshold. Two algorithms are presented for SC that both give a ((1 + (cid:15) )(4 /(cid:15) 2 + 1) , 1 / 2(1 − (cid:15) )) bicriteria approximation guarantee to the problem. Both algorithms process the ground set in a stream, one in multiple passes. Further, a (1 / 2(1 − (cid:15) ) , (1 + (cid:15) )(4 /(cid:15) 2 + 1)) bicriteria approximation guarantee is given for the related optimization problem Submodular Knapsack (SK).
Determining the Hubble constant without the sound horizon: Perspectives with future galaxy surveys

$H_0$ constraints from galaxy surveys are sourced by the geometric properties of two standardisable rulers: the sound horizon scale, $r_s$, and the matter-radiation equality scale, $k_{\rm eq}$. While most analyses over the last decade have focused on the first scale, recent work has emphasised that the second can provide an independent source of information about the expansion rate of the universe. Recent approaches to obtain a sound-horizon-independent measurement of $H_0$ from the equality scale have avoided $r_s$-based information by removing the sound-horizon-calibrating prior on the baryon density. We present a new method to marginalise over $r_s$; this allows baryon information to be retained enabling tighter parameter constraints. For a Euclid-like spectroscopic survey, we forecast sound-horizon-independent $H_0$ constraints of $\sigma_{H_0} = 0.7\rm{\ km\ s^{-1}\ Mpc^{-1}}$ for our method using the equality scale, compared with $\sigma_{H_0} = 0.5\rm{\ km\ s^{-1}\ Mpc^{-1}}$ from the sound horizon. Upcoming equality scale $H_0$ measurements thus can be highly competitive, although we caution that the impact of observational systematics on such measurements still needs to be investigated in detail. Applying our new approach to the BOSS power spectrum gives $H_0 = 69.5^{+3.0}_{-3.5}\rm{\ km\ s^{-1}\ Mpc^{-1}}$ from equality alone, somewhat tighter than previous constraints. Consistency of $r_s$- and $k_{\rm eq}$-based $H_0$ measurements can provide a valuable internal consistency test of the cosmological model; as an example, we consider the change in $H_0$ created by early dark energy. Assuming the \textit{Planck}+SH0ES best-fit EDE model we find a $2.6\sigma$ shift ($\Delta H_0 = 2.6\rm{\ km\ s^{-1}\ Mpc^{-1}}$) between the two measurements for Euclid; if we instead assume the ACT best-fit model, this increases to $9.0\sigma$ ($\Delta H_0 = 7.8\rm{\ km\ s^{-1}\ Mpc^{-1}}$).
Two-photon IR pumped UV–Vis transient absorption spectroscopy of Dirac fermions in the topological insulator Bi2Se3

It is often taken for granted that in pump-probe experiments on the topological insulator (TI) Bi2Se3 using IR pumping with a commercial Ti:sapphire laser [∼800 nm (1.55 eV photon energy)], the electrons are excited in the one-photon absorption regime, even when pumped with absorbed fluences in the mJ cm−2 range. Here, using UV–Vis transient absorption (TA) spectroscopy, we show that even at low-power Infrared (IR) pumping with absorbed fluences in the μJ cm−2 range, the TA spectra of the TI Bi2Se3 extend across a part of the UV and the entire visible region. This observation suggests unambiguously that the two-photon pumping regime accompanies the usual one-photon pumping regime even at low laser powers applied. We attribute the high efficiency of two-photon pumping to the giant nonlinearity of Dirac fermions in the Dirac surface states (SS). On the contrary, one-photon pumping is associated with the excitation of bound valence electrons in the bulk into the conduction band. Two mechanisms of absorption bleaching were also revealed since they manifest themselves in different spectral regions of probing and cause the appearance of three different relaxation dynamics. These two mechanisms were attributed to the filling of the phase-space in the Dirac SS and bulk states, followed by the corresponding Pauli blocking.
FSpGEMM: An OpenCL-based HPC Framework for Accelerating General Sparse Matrix-Matrix Multiplication on FPGAs

General sparse matrix-matrix multiplication (SpGEMM) is an integral part of many scientific computing, high-performance computing (HPC), and graph analytic applications. This paper presents a new compressed sparse vector (CSV) format for representing sparse matrices and FSpGEMM, an OpenCL-based HPC framework for accelerating general sparse matrix-matrix multiplication on FPGAs. The proposed FSpGEMM framework includes an FPGA kernel implementing a throughput-optimized hardware architecture based on Gustavson's algorithm and a host program implementing pre-processing functions for converting input matrices to the CSV format tailored for the proposed architecture. FSpGEMM utilizes a new buffering scheme tailored to Gustavson's algorithm. We compare FSpGEMM implemented on an Intel Arria 10 GX FPGA development board with Intel Math Kernel Library (MKL) implemented on an Intel Xeon E5-2637 CPU and cuSPARSE on an NVIDIA GTX TITAN X GPU, respectively, for multiplying a set of sparse matrices selected from SuiteSparse Matrix Collection. The experiment results show that the proposed FSpGEMM solution achieves on average 4.9x and 1.7x higher performance with 31.9x and 13.1x lower energy consumption per SpGEMM computation than the CPU and GPU implementations, respectively.
Gravitational lensing in the charged NUT–de Sitter spacetime

It is a long-standing open question if a gravitomagnetic charge, the gravitational analogon to a hypothetical magnetic charge in electrodynamics, exists in nature. It naturally occurs in certain exact solutions to Einstein's electrovacuum-field equations with cosmological constant. The charged NUT-de Sitter metric is such a solution. It describes a black hole with electric and gravitomagnetic charges and a cosmological constant. In this paper we will address the question how we can observe the gravitomagnetic charge using gravitational lensing. For this purpose we first solve the equations of motion for lightlike geodesics using Legendre's canonical forms of the elliptic integrals and Jacobi's elliptic functions. We fix a stationary observer in the domain of outer communication and introduce an orthonormal tetrad. The orthonormal tetrad relates the direction under which the observer detects a light ray to its latitude-longitude coordinates on the observer's celestial sphere. In this parametrization we rederive the angular radius of the shadow, formulate a lens map, discuss the redshift, and the travel time. We also discuss relevant differences with respect to spherically symmetric and static spacetimes and how we can use them to determine if an astrophysical black hole has a gravitomagnetic charge.
Adversarially Robust Stability Certificates can be Sample-Efficient

Motivated by bridging the simulation to reality gap in the context of safety-critical systems, we consider learning adversarially robust stability certificates for unknown nonlinear dynamical systems. In line with approaches from robust control, we consider additive and Lipschitz bounded adversaries that perturb the system dynamics. We show that under suitable assumptions of incremental stability on the underlying system, the statistical cost of learning an adversarial stability certificate is equivalent, up to constant factors, to that of learning a nominal stability certificate. Our results hinge on novel bounds for the Rademacher complexity of the resulting adversarial loss class, which may be of independent interest. To the best of our knowledge, this is the first characterization of sample-complexity bounds when performing adversarial learning over data generated by a dynamical system. We further provide a practical algorithm for approximating the adversarial training algorithm, and validate our findings on a damped pendulum example.
Fragmentation functions for gluon into B c or B ∗ c meson

: In the paper, we calculate the fragmentation functions for g → B c and g → B ∗ c . The ultraviolet divergences in the calculation are removed through the renormalization of the operator deﬁnition of the fragmentation functions under the modiﬁed minimal subtraction scheme. We then obtain the fragmentation functions D g → B c ( z, µ F ) and D g → B ∗ c ( z, µ F ) , which are presented as ﬁgures and ﬁtting functions. The obtained fragmentation functions are complementary to the previous work on the next-to-leading order fragmentation functions for ¯ b → B c ( B ∗ c ) and c → B c ( B ∗ c ) .
Transmission backlash of precise cable drive system

Precise cable drive has been developed as an alternative transmission element to gears, belts and pulleys, chains and sprockets in electro-optical tracking system. The analytical method is developed to predict the transmission backlash of precise cable drive to enable designers to better assess the precision performance in the design study phase. Slip angle of precise cable drive is studied, and the effect of the rotational velocity and inertia of cable on the force equilibrium of contact region is considered. The deformation of cable in slip region and free region is calculated respectively and theoretical formulation of transmission backlash for precise cable drive system is carried out. Parametric sensitivity is investigated to evaluate the relationship between the transmission backlash and precise cable drive parameters including preload tension, load tension, friction coefficient, center distance and output drum radius. Experimental setup is built and the transmission backlash is tested. Effect of preload tension on the transmission backlash is tested. Results show that the experimental value and the theoretical curve of the transmission backlash fit well, which validates the theoretical method developed in this article.
Multi-passband Observations of a Solar Flare over the He i 10830 Å line

This study presents a C3.0 flare observed by the Big Bear Solar Observatory/Goode Solar Telescope (GST) and Interface Region Imaging Spectrograph (IRIS) on 2018 May 28 around 17:10 UT. The Near-Infrared Imaging Spectropolarimeter of GST was set to spectral imaging mode to scan five spectral positions at ±0.8, ±0.4 Å and line center of He i 10830 Å. At the flare ribbon’s leading edge, the line is observed to undergo enhanced absorption, while the rest of the ribbon is observed to be in emission. When in emission, the contrast compared to the preflare ranges from about 30% to nearly 100% at different spectral positions. Two types of spectra, “convex” shape with higher intensity at line core and “concave” shape with higher emission in the line wings, are found at the trailing and peak flaring areas, respectively. On the ribbon front, negative contrasts, or enhanced absorption, of about ∼10%–20% appear in all five wavelengths. This observation strongly suggests that the negative flares observed in He i 10830 Å with mono-filtergram previously were not caused by pure Doppler shifts of this spectral line. Instead, the enhanced absorption appears to be a consequence of flare-energy injection, namely nonthermal collisional ionization of helium caused by the precipitation of high-energy electrons, as found in our recent numerical modeling results. In addition, though not strictly simultaneous, observations of Mg ii from the IRIS spacecraft, show an obvious central reversal pattern at the locations where enhanced absorption of He i 10830 Å is seen, which is consistent with previous observations.
Community detection and reciprocity in networks by jointly modeling pairs of edges

To unravel the driving patterns of networks, the most popular models rely on community detection algorithms. However, these approaches are generally unable to reproduce the structural features of the network. Therefore, attempts are always made to develop models that incorporate these network properties beside the community structure. In this article, we present a probabilistic generative model and an efficient algorithm to both perform community detection and capture reciprocity in networks. Our approach jointly models pairs of edges with exact two-edge joint distributions. In addition, it provides closed-form analytical expressions for both marginal and conditional distributions. We validate our model on synthetic data in recovering communities, edge prediction tasks and generating synthetic networks that replicate the reciprocity values observed in real networks. We also highlight these findings on two real datasets that are relevant for social scientists and behavioural ecologists. Our method overcomes the limitations of both standard algorithms and recent models that incorporate reciprocity through a pseudo-likelihood approximation. The inference of the model parameters is implemented by the efficient and scalable expectation–maximization algorithm, as it exploits the sparsity of the dataset. We provide an open-source implementation of the code online.
Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units

This paper proposes a safe reinforcement learning algorithm for generation bidding decisions and unit maintenance scheduling in a competitive electricity market environment. In this problem, each unit aims to find a bidding strategy that maximizes its revenue while concurrently retaining its reliability by scheduling preventive maintenance. The maintenance scheduling provides some safety constraints which should be satisfied at all times. Satisfying the critical safety and reliability constraints while the generation units have an incomplete information of each others' bidding strategy is a challenging problem. Bi-level optimization and reinforcement learning are state of the art approaches for solving this type of problems. However, neither bi-level optimization nor reinforcement learning can handle the challenges of incomplete information and critical safety constraints. To tackle these challenges, we propose the safe deep deterministic policy gradient reinforcement learning algorithm which is based on a combination of reinforcement learning and a predicted safety filter. The case study demonstrates that the proposed approach can achieve a higher profit compared to other state of the art methods while concurrently satisfying the system safety constraints.
Fermi acceleration in rotating drums

Consider hard balls in a bounded rotating drum. If there is no gravitation, then there is no Fermi acceleration, i.e., the energy of the balls remains bounded forever. If there is gravitation, Fermi acceleration may arise. A number of explicit formulas for the system without gravitation are given. Some of these are based on an explicit realization, which we derive, of the well-known microcanonical ensemble measure.
Vehicle and Labor Requirements for Yard Waste Collection

Curbside collection of yard waste material is costly because the amounts collected per residence are small compared to the total waste stream and time is wasted driving by non-setting-out residences. In this paper, mathematical models are presented capable of estimating route time based on the distribution and amount of materials collected, and route and collection method characteristics. A method is presented that uses route time, set-out rate, and average set-out amount to estimate vehicle and labor requirements for compost curbside collection programs. The effect of collection practice on vehicle and labor needs is also explored. © 1997 ISWA
Competition between replication potential and predictable secondary structure formation sets the alphabet size of RNA

The simplest possible informational heteropolymer requires just two alphabets to be able to store information. The evolutionary choice of four monomers in the informational biomolecules DNA and RNA is intriguing, given the inherent difficulties in the simultaneous and localized prebiotic synthesis of all four monomers of progenitors of DNA from common precursors on early Earth. Excluding the scenario where a binary-alphabet genome eventually expanded to include two more alphabets to code for more amino acids on teleological grounds, we show that an evolutionarily successful heteropolymer sequence in the RNA-world needed to be composed of at least four alphabets in order to predictably fold into a secondary structure. Using a model that we previously used to demonstrate the evolutionary advantages of unidirectional replication and anti-parallel strand orientation of duplex DNA, we show that the dual constraints of maximum replicative potential and predictable secondary structure formation can be simultaneously satisfied only by RNA sequences composed of a minimum of four alphabets, within the premise of the presence of sequence-dependent asymmetric cooperativity in RNA. We illustrate this conflict between replicative potential and predictable secondary structure formation, the latter being a metric of information stored in primordial self-replicators, using tRNA, a possible remnant of the RNA world.
Long-time behavior of solutions to the M1 model with boundray effect

In this paper, we are concerned with the asymptotic behavior of solutions of M1 model on quadrant (x, t) ∈ R+ × R+. From this model, combined with damped compressible Euler equations, a more general system is introduced. We show that the solutions to the initial boundary value problem of this system globally exist and tend time-asymptotically to the corresponding nonlinear parabolic equation governed by the related Darcy’s law. Compared with previous results on compressible Euler equations with damping obtained by Nishihara and Yang in [24], and Marcati, Mei and Rubino in [16], the better convergence rates are obtained. The approach adopted is based on the technical time-weighted energy estimates together with the Green’s function method.
Mathematics of internal waves in a 2D aquarium

Following theoretical and experimental work of Maas et al we consider a linearized model for internal waves in effectively two dimensional aquaria. We provide a precise description of singular profiles appearing in long time wave evolution and associate them to classical attractors. That is done by microlocal analysis of the spectral Poincar\'e problem, leading in particular to a limiting absorption principle. Some aspects of the paper (for instance Section 6) can be considered as a natural microlocal continuation of the work of John on the Dirichlet problem for hyperbolic equations in two dimensions.
From Robot Self-Localization to Global-Localization: An RSSI Based Approach

Localization is a crucial task for autonomous mobile robots in order to successfully move to goal locations in their environment. Usually, this is done in a robot-centric manner, where the robot maintains a map with its body in the center. In swarm robotics applications, where a group of robots needs to coordinate in order to achieve their common goals, robot-centric localization will not suffice as each member of the swarm has its own frame of reference. One way to deal with this problem is to create, maintain and share a common map (global coordinate system), among the members of the swarm. This paper presents an approach to global localization for a group of robots in unknown, GPS and landmark free environments that extends the localization scheme of the LadyBug algorithm. The main idea relies on members of the swarm staying still and acting as beacons, emitting electromagnetic signals. These stationary robots form a global frame of reference and the rest of the group localize themselves in it using the Received Signal Strength Indicator (RSSI). The proposed method is evaluated, and the results obtained from the experiments are promising.
3D Instance Segmentation of MVS Buildings

We present a novel 3D instance segmentation framework for Multi-View Stereo (MVS) buildings in urban scenes. Unlike existing works focusing on semantic segmentation of urban scenes, the emphasis of this work lies in detecting and segmenting 3D building instances even if they are attached and embedded in a large and imprecise 3D surface model. Multi-view RGB images are first enhanced to RGBH images by adding a heightmap and are segmented to obtain all roof instances using a fine-tuned 2D instance segmentation neural network. Instance masks from different multi-view images are then clustered into global masks. Our mask clustering accounts for spatial occlusion and overlapping, which can eliminate segmentation ambiguities among multi-view images. Based on these global masks, 3D roof instances are segmented out by mask back-projections and extended to the entire building instances through a Markov random field optimization. A new dataset that contains instance-level annotation for both 3D urban scenes (roofs and buildings) and drone images (roofs) is provided. To the best of our knowledge, it is the first outdoor dataset dedicated for 3D instance segmentation with much more annotations of attached 3D buildings than existing datasets1. Quantitative evaluations and ablation studies have shown the effectiveness of all major steps and the advantages of our multi-view framework over the orthophoto-based method.