Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent Developments and Applications in Tissue Mechanics and Tissue Engineering

The current clinical guidelines for the management of aortic abdominal aneurysms (AAAs) overlook the structural and mechanical heterogeneity of the aortic tissue and its role in the regional weakening that drives disease progression. This study is a comprehensive investigation of the structural and biomechanical heterogeneity of AAA tissue along the length and circumference of the aorta, by means of regional ex vivo and in vivo properties. Biaxial testing and histological analysis were performed on ex vivo human aortic specimens systematically collected during open repair surgery. Wall-shear stress and three-dimensional principal strain analysis were performed to allow for in vivo regional characterization of individual aortas. A marked effect of position along the aortic length was observed in both ex vivo and in vivo properties, with the central regions corresponding to the aneurysmal sac being significantly different from the adjacent regions. The heterogeneity along the circumference of the aorta was reflected in the ex vivo biaxial response at low strains and histological properties. Present findings uniquely show the importance of regional characterization for aortic assessment and the need to correlate heterogeneity at the tissue level with non-invasive measurements aimed at improving clinical outcomes.
KINEMATIC AND SPATIAL SUBSTRUCTURE IN NGC 2264

We present an expanded kinematic study of the young cluster NGC 2264 based upon optical radial velocities measured using multi-fiber echelle spectroscopy at the 6.5 m MMT and Magellan telescopes. We report radial velocities for 695 stars, of which approximately 407 stars are confirmed or very likely members. Our results more than double the number of members with radial velocities from Fűrész et al., resulting in a much better defined kinematic relationship between the stellar population and the associated molecular gas. In particular, we find that there is a significant subset of stars that are systematically blueshifted with respect to the molecular (13CO) gas. The detection of Lithium absorption and/or infrared excesses in this blueshifted population suggests that at least some of these stars are cluster members; we suggest some speculative scenarios to explain their kinematics. Our results also more clearly define the redshifted population of stars in the northern end of the cluster; we suggest that the stellar and gas kinematics of this region are the result of a bubble driven by the wind from O7 star S Mon. Our results emphasize the complexity of the spatial and kinematic structure of NGC 2264, important for eventually building up a comprehensive picture of cluster formation.
Comparison of Strong Gravitational Lens Model Software I. Time delay and mass calculations are sensitive to changes in redshift and are model dependent

Analysis of strong gravitational lensing depends on software analysis of observational data. The purpose of this study was to evaluate the behavior of strong gravitational lens modeling software with changes in redshift. Four dierent strong gravitational lens software modeling codes were directly compared (Lenstool / glac, two light traces mass codes, and GRALE / PixeLens, two non-light traces mass codes) in the analysis of model data as well as analysis of the giant gravitational quasar SDSSJ1004+4112. A generalized model for time delay calculation shows that calculated time delay is proportional to DdDs=Dds.The percent change in time delays calculated for each system at each redshift tested were compared with percent change in the value of DdDs=Dds. A simple point mass model was tested with each code. Five models were used with a constant zlens and a varying zsource, and ve models with a constant zsource and a varying zlens. The eects
Gain-switched laser diode seeded Yb-doped fiber amplifier delivering 11-ps pulses at repetition rates up to 40-MHz

Here, we demonstrate all-fiber direct amplification of 11 picosecond pulses from a gain-switched laser diode at 1063 nm. The diode was driven at a repetition rate of 40 MHz and delivered 13 μW of fiber-coupled average output power. For the low output pulse energy of 0.33 pJ we have designed a multi-stage core pumped preamplifier based on single clad Yb-doped fibers in order to keep the contribution of undesired amplified spontaneous emission as low as possible and to minimize temporal and spectral broadening. After the preamplifier we reduced the 40 MHz repetition rate to 1 MHz using a fiber coupled pulse-picker. The final amplification was done with a cladding pumped Yb-doped large mode area fiber and a subsequent Yb-doped rod-type fiber. With our setup we achieved amplification of 72 dBs to an output pulse energy of 5.7 μJ, pulse duration of 11 ps and peak power of >0.6 MW.
MONTE CARLO RADIATION-HYDRODYNAMICS WITH IMPLICIT METHODS

We explore the application of Monte Carlo transport methods to solving coupled radiation-hydrodynamics (RHD) problems. We use a time-dependent, frequency-dependent, three-dimensional radiation transport code that is special relativistic and includes some detailed microphysical interactions such as resonant line scattering. We couple the transport code to two different one-dimensional (non-relativistic) hydrodynamics solvers: a spherical Lagrangian scheme and a Eulerian Godunov solver. The gas–radiation energy coupling is treated implicitly, allowing us to take hydrodynamical time-steps that are much longer than the radiative cooling time. We validate the code and assess its performance using a suite of radiation hydrodynamical test problems, including ones in the radiation energy dominated regime. We also develop techniques that reduce the noise of the Monte Carlo estimated radiation force by using the spatial divergence of the radiation pressure tensor. The results suggest that Monte Carlo techniques hold promise for simulating the multi-dimensional RHD of astrophysical systems.
Tight Inapproximability for Graphical Games

We provide a complete characterization for the computational complexity of finding approximate equilibria in two-action graphical games. We consider the two most well-studied approximation notions: ε-Nash equilibria (ε-NE) and ε-well-supported Nash equilibria (ε-WSNE), where ε is in [0,1]. We prove that computing an ε-NE is PPAD-complete for any constant ε smaller than 1/2, while a very simple algorithm (namely, letting all players mix uniformly between their two actions) yields a 1/2-NE. On the other hand, we show that computing an ε-WSNE is PPAD-complete for any constant ε smaller than 1, while a 1-WSNE is trivial to achieve, because any strategy profile is a 1-WSNE. All of our lower bounds immediately also apply to graphical games with more than two actions per player.
Light yield of an undoped CsI crystal coupled directly to a photomultiplier tube at 77 Kelvin

A light yield of 20.4 ± 0.8 photoelectrons/keV was achieved with an undoped CsI crystal coupled directly to a photomultiplier tube at 77 Kelvin. This is by far the largest yield in the world achieved with CsI crystals. An energy threshold that is several times lower than the current dark matter experiments utilizing CsI(Tl) crystals may be achievable using this technique. Together with novel CsI crystal purification methods, the technique may be used to improve the sensitivities of dark matter and coherent elastic neutrino-nucleus scattering experiments. Also measured were the scintillation light decay constants of the undoped CsI crystal at both room temperature and 77 Kelvin. The results are consistent with those in the literature.
Gas and dust in a z= 2.8 obscured quasar★

We present new detections of the CO(5−4), CO(7−6), [CI] and [CI] molecular and atomic line transitions towards the unlensed, obscured quasar AMS12 (z= 2.7672), observed with the Institut de Radioastronomie Millimetrique (IRAM) Plateau de Bure Interferometer (PdBI). This is the first unlensed, high-redshift source to have both atomic carbon ([CI]) transitions detected. Continuum measurements between 70 m and 3 mm are used to constrain the far-infrared (FIR) spectral energy distribution (SED), and we find a best-fitting FIR luminosity of log10[LFIR/L⊙] = 13.5 ± 0.1, dust temperature TD= 88 ± 8 K and emissivity index β= 0.6 ± 0.1. The highly excited molecular gas probed by CO(3−2), (5−4) and (7−6) is modelled with large velocity gradient models. The gas kinetic temperature TG, density n(H2) and the characteristic size r0 are determined using the dust temperature from the FIR SED as a prior for the gas temperature. The best-fitting parameters are TG= 90 ±8 K, n(H2) = 103.9 ± 0.1 cm−3 and r0= 0.8 ± 0.04 kpc. The ratio of the [CI] lines gives a [CI] excitation temperature of 43 ± 10 K, indicating that the [CI] and the high-excitation CO are not in thermal equilibrium. The [CI] excitation temperature is below that of the dust temperature and the gas kinetic temperature of the high-excitation CO, perhaps because [CI] lies at a larger radius where there may also be a large reservoir of CO at a cooler temperature, perhaps detectable through the CO(1−0) line. Using the [CI] line we can estimate the strength of the CO(1−0) line and hence the gas mass. This suggests that a significant fraction (∼30 per cent) of the molecular gas is missed from the high-excitation line analysis, giving a gas mass higher than that inferred from the assumption that the high-excitation gas is a good tracer of the low-excitation gas. The stellar mass was estimated from the mid-/near-infrared SED to be M★∼ 3 × 1011 M⊙. The Eddington-limited black hole mass is found from the bolometric luminosity to be M•≳ 1.5 × 109 M⊙. These give a black hole–bulge mass ratio of M•/M★≳ 0.005. This is in agreement with studies on the evolution of the M•/M★ relationship at high redshifts, which find a departure from the local value of ∼0.002. We discuss the implications for the evolution of the black hole in AMS12 and its host galaxy.
Uniform convergence rates and automatic variable selection in nonparametric regression with functional and categorical covariates

In Selk and Gertheiss (2022) a nonparametric prediction method for models with multiple functional and categorical covariates is introduced. The dependent variable can be categorical (binary or multi-class) or continuous, thus both classification and regression problems are considered. In the paper at hand the asymptotic properties of this method are developed. A uniform rate of convergence for the regression / classification estimator is given. Further it is shown that, asymptotically, a data-driven least squares cross-validation method can automatically remove irrelevant, noise variables.
EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression

In this work we focus our attention on distributed optimization problems in the context where the communication time between the server and the workers is non-negligible. We obtain novel methods supporting bidirectional compression (both from the server to the workers and vice versa) that enjoy new state-of-the-art theoretical communication complexity for convex and nonconvex problems. Our bounds are the first that manage to decouple the variance/error coming from the workers-to-server and server-to-workers compression, transforming a multiplicative dependence to an additive one. Moreover, in the convex regime, we obtain the first bounds that match the theoretical communication complexity of gradient descent. Even in this convex regime, our algorithms work with biased gradient estimators, which is non-standard and requires new proof techniques that may be of independent interest. Finally, our theoretical results are corroborated through suitable experiments.
ContactNet: Online Multi-Contact Planning for Acyclic Legged Robot Locomotion

In legged logomotion, online trajectory optimization techniques generally depend on heuristic-based contact planners in order to have low computation times and achieve high replanning frequencies. In this work, we propose ContactNet, a fast acyclic contact planner based on a multi-output regression neural network. ContactNet ranks discretized stepping regions, allowing to quickly choose the best feasible solution, even in complex environments. The low computation time, in the order of 1 ms, makes possible the execution of the contact planner concurrently with a trajectory optimizer in a Model Predictive Control (MPC) fashion. We demonstrate the effectiveness of the approach in simulation in different complex scenarios with the quadruped robot Solo12.
Rapid scattering of radiation belt electrons by storm‐time EMIC waves

A storm main phase can produce a rapid depletion of electron fluxes in the Earth's outer radiation belt and the pitch‐angle scattering by the electromagnetic ion cyclotron (EMIC) waves is one mechanism that might account for the electron losses. To efficiently scatter the bulk of the electron population, below 1–2 MeV, the EMIC waves would need to have significant power very near a heavy ion gyrofrequency. We present a wave event at the storm main phase and carefully examine the wave spectrum to identify the energy range of electrons scattered by the waves. The EMIC waves exhibit power right below the He+ gyrofrequency and we estimate that they can interact with electrons having energies as low as 400 keV producing rapid scattering at almost all pitch‐angle values on the time scales of seconds. Our statistical analysis suggests that this event is not an exception; the majority of EMIC waves can scatter electrons with energies under 2 MeV. Our results show that EMIC waves can be one of the dominant radiation belt loss mechanisms during the storm main phase.
EMISSION MECHANISM OF “GREEN FUZZIES” IN HIGH-MASS STAR-FORMING REGIONS

The Infrared Array Camera (IRAC) on the Spitzer Space Telescope has revealed that a number of high-mass protostars are associated with extended mid-infrared emission, particularly prominent at 4.5 μm. These are called “Green Fuzzy” emission or “Extended Green Objects. ” We present color analysis of this emission toward six nearby (d = 2–3 kpc) well-studied high-mass protostars and three candidate high-mass protostars identified with the Spitzer GLIMPSE survey. In our color–color diagrams, most of the sources show a positive correlation between the [3.6]−[4.5] and [3.5]−[5.8] colors along the extinction vector in all or part of the region. We compare the colors with those of scattered continuum associated with the low-mass protostar L 1527, modeled scattered continuum in cavities, shocked emission associated with low-mass protostars, modeled H2 emission for thermal and fluorescent cases, and modeled polycyclic aromatic hydrocarbon (PAH) emission. Of the emission mechanisms discussed above, scattered continuum provides the simplest explanation for the observed linear correlation. In this case, the color variation within each object is attributed to different foreground extinctions at different positions. Alternative possible emission mechanisms to explain this correlation may be a combination of thermal and fluorescent H2 emission in shocks, and a combination of scattered continuum and thermal H2 emission, but detailed models or spectroscopic follow-up are required to investigate this possibility further. Our color–color diagrams also show possible contributions from PAHs in two objects. However, none of our samples show clear evidence for PAH emission directly associated with the high-mass protostars, several of which should be associated with ionizing radiation. This suggests that these protostars are heavily embedded even at mid-infrared wavelengths.
Visual Privacy Protection Based on Type-I Adversarial Attack

With the development of online artificial intelligence systems, many deep neural networks (DNNs) have been deployed in cloud environments. In practical applications, developers or users need to provide their private data to DNNs, such as faces. However, data transmitted and stored in the cloud is insecure and at risk of privacy leakage. In this work, inspired by Type-I adversarial attack, we propose an adversarial attack-based method to protect visual privacy of data. Specifically, the method encrypts the visual information of private data while maintaining them correctly predicted by DNNs, without modifying the model parameters. The empirical results on face recognition tasks show that the proposed method can deeply hide the visual information in face images and hardly affect the accuracy of the recognition models. In addition, we further extend the method to classification tasks and also achieve state-of-the-art performance.
Hektor - an exceptional D-type family among Jovian Trojans

In this work, we analyze Jovian Trojans in the space of suitable resonant elements and we identify clusters of possible collisional origin by two independent methods: the hierarchical clustering and a so-called "randombox". Compared to our previous work (Bro\v{z} and Rozehnal 2011), we study a twice larger sample. Apart from Eurybates, Ennomos and $1996\,\rm RJ$ families, we have found three more clusters --- namely families around asteroids (20961)~Arkesilaos, (624)~Hektor in the $L_4$ libration zone and (247341)~$2001\,\rm UV_{209}$ in $L_5$. The families fulfill our stringent criteria, i.e. a high statistical significance, an albedo homogeneity and a steeper size-frequency distribution than that of background. In order to understand their nature, we simulate their long term collisional evolution with the Boulder code (Morbidelli et al. 2009) and dynamical evolution using a modified SWIFT integrator (Levison and Duncan, 1994). Within the framework of our evolutionary model, we were able to constrain the the age of the Hektor family to be either 1 to 4 Gyr or, less likely, 0.1 to 2.5 Gyr, depending on initial impact geometry. Since (624) Hektor itself seems to be a bilobed--shape body with a satellite (Marchis et al. 2014), i.e. an exceptional object, we address its association with the D--type family and we demonstrate that the moon and family could be created during a single impact event. We simulated the cratering event using a Smoothed Particle Hydrodynamics (SPH, Benz and Asphaug, 1994). This is also the first case of a family associated with a D--type parent body.
Errata to "Quantum-mechanical scattering theory for short-range and coulomb interactions"

A rigorous account is given of time-dependent nonrelativistic quantum-mechanical scattering problems involving one or many particles. The discussion is carried out in the framework of Hilbert space. Results are given both for short-range and for Coulomb interactions. I. The description of particles in quantum mechanics. A nonrelativistic spinless quantum-mechanical particle of mass m is described by assigning to each real number £, — o° < t < °°, an element tyt of L(R3) such that \\tyt\\ = 1. \fßt is called the wave-function or sometimes the state of the particle at time t Introduce the Fourier transform fâ of i/ffby (1) ^ ( ^ ^ ^ ^ ^ W ^ '
The White Dwarf Binary Pathways Survey -- VIII: a post common envelope binary with a massive white dwarf and an active G-type secondary star

The white dwarf binary pathways survey is dedicated to studying the origin and evolution of binaries containing a white dwarf and an intermediate-mass secondary star of the spectral type A, F, G, or K (WD+AFGK). Here we present CPD-65 264, a new post common envelope binary with an orbital period of 1.37 days that contains a massive white dwarf ( 0 . 86 ± 0 . 06 M (cid:12) ) and an intermediate-mass (1 . 00 ± 0 . 05 M (cid:12) ) main-sequence secondary star. We characterized the secondary star and measured the orbital period using high-resolution optical spectroscopy. The white dwarf parameters are determined from HST spectroscopy. In addition, TESS observations revealed that up to 19 percent of the surface of the secondary is covered with starspots. Small period changes found in the light curve indicate that the secondary is the second example of a G-type secondary star in a post common envelope binary with latitudinal diﬀerential rotation. Given the relatively large mass of the white dwarf and the short orbital period, future mass transfer will be dynamically and thermally stable and the system will evolve into a cataclysmic variable. The formation of the system can be understood assuming common envelope evolution without contributions from energy sources besides orbital energy. CPD-65 264 is the seventh post common envelope binaries with intermediate-mass secondaries that can be understood assuming a small eﬃciency in the common envelope energy equation, in agreement with ﬁndings for post common envelope binaries with M-dwarf or sub-stellar companions.
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel

Explaining generalizations and preventing over-confident predictions are central goals of studies on the loss landscape of neural networks. Flatness, defined as loss invariability on perturbations of a pre-trained solution, is widely accepted as a predictor of generalization in this context. However, the problem that flatness and generalization bounds can be changed arbitrarily according to the scale of a parameter was pointed out, and previous studies partially solved the problem with restrictions: Counter-intuitively, their generalization bounds were still variant for the function-preserving parameter scaling transformation or limited only to an impractical network structure. As a more fundamental solution, we propose new prior and posterior distributions invariant to scaling transformations by \textit{decomposing} the scale and connectivity of parameters, thereby allowing the resulting generalization bound to describe the generalizability of a broad class of networks with the more practical class of transformations such as weight decay with batch normalization. We also show that the above issue adversely affects the uncertainty calibration of Laplace approximation and propose a solution using our invariant posterior. We empirically demonstrate our posterior provides effective flatness and calibration measures with low complexity in such a practical parameter transformation case, supporting its practical effectiveness in line with our rationale.
Generalizability of Adversarial Robustness Under Distribution Shifts

Recent progress in empirical and certified robustness promises to deliver reliable and deployable Deep Neural Networks (DNNs). Despite that success, most existing evaluations of DNN robustness have been done on images sampled from the same distribution on which the model was trained. However, in the real world, DNNs may be deployed in dynamic environments that exhibit significant distribution shifts. In this work, we take a first step towards thoroughly investigating the interplay between empirical and certified adversarial robustness on one hand and domain generalization on another. To do so, we train robust models on multiple domains and evaluate their accuracy and robustness on an unseen domain. We observe that: (1) both empirical and certified robustness generalize to unseen domains, and (2) the level of generalizability does not correlate well with input visual similarity, measured by the FID between source and target domains. We also extend our study to cover a real-world medical application, in which adversarial augmentation significantly boosts the generalization of robustness with minimal effect on clean data accuracy.