Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetic anisotropy and low-field magnetic phase diagram of the quasi-two-dimensional ferromagnet 
Cr2Ge2Te6

All known quasi-two-dimensional ferromagnets, such as $(X=\mathrm{Br},\mathrm{I})$ or ${\mathrm{Cr}}_{2}{(\mathrm{Ge},\mathrm{Si})}_{2}{\mathrm{Te}}_{6}$, exhibit a peculiar temperature dependence of the magnetization under small magnetic fields applied in the hard plane. Investigating the van der Waals layered ${\mathrm{Cr}}_{2}{\mathrm{Ge}}_{2}{\mathrm{Te}}_{6}$ by magnetization and specific-heat measurements under magnetic fields, we report the temperature dependence of the effective magnetic anisotropy as a plausible explanation for this unusual behavior. Magnetic temperature-field phase diagrams were measured for magnetic fields applied along the magnetic easy axis and in the hard plane up to 30 kOe and 150 K to obtain a detailed understanding of the magnetization behavior in the low-field region and especially below the magnetic saturation fields. From these magnetic phase diagrams the temperature dependence of the effective magnetocrystaline anisotropy constant is extracted and compared to the corresponding theory, unique for ${\mathrm{Cr}}_{2}{\mathrm{Ge}}_{2}{\mathrm{Te}}_{6}$ until now. Based on the thermal evolution of the effective magnetocrystalline anisotropy constant and the aforementioned magnetic phase diagrams, a qualitative scheme is developed explaining the changes of magnetization direction due to the influence of temperature, as well as strength and direction of external magnetic fields in ${\mathrm{Cr}}_{2}{\mathrm{Ge}}_{2}{\mathrm{Te}}_{6}$. Structural and magnetic similarities to other quasi-two-dimensional ferromagnets may allow this scheme to be generalized for the whole class of materials.
ALMA Unveils Widespread Molecular Gas Clumps in the Ram Pressure Stripped Tail of the Norma Jellyfish Galaxy

We present the first high-resolution map of the cold molecular gas distribution as traced by CO(2−1) emission with ALMA in a long ram pressure stripped tail. The Norma cluster galaxy ESO 137-001 is undergoing a strong interaction with the surrounding intracluster medium and is one of the nearest jellyfish galaxies with a long multiphase and multicomponent tail. We have mapped the full extent of the tail at 1″ (350 pc) angular resolution and found a rich distribution of mostly compact CO regions extending to nearly 60 kpc in length and 25 kpc in width. In total, about 109 M⊙ of molecular gas was detected with ALMA. From comparison with previous APEX observations, we also infer the presence of a substantial extended molecular component in the tail. The ALMA CO features are found predominantly at the heads of numerous small-scale (∼1.5 kpc) fireballs (i.e., star-forming clouds with linear streams of young stars extending toward the galaxy) but also large-scale (∼8 kpc) superfireballs and double-sided fireballs that have additional diffuse ionized gas tails extending in the direction opposite the stellar tails. The new data help to shed light on the origin of the molecular tail; CO filaments oriented in the direction of the tail are likely young molecular features formed in situ, whereas large CO features tilted with respect to the tail may have originated from dense gas complexes that were gradually pushed away from the disk.
Busemann functions and semi-infinite O’Connell–Yor polymers

We prove that given any fixed asymptotic velocity, the finite length O'Connell-Yor polymer has an infinite length limit satisfying the law of large numbers with this velocity. By a Markovian property of the quenched polymer this reduces to showing the existence of Busemann functions: almost sure limits of ratios of random point-to-point partition functions. The key ingredients are the Burke property of the O'Connell-Yor polymer and a comparison lemma for the ratios of partition functions. We also show the existence of infinite length limits in the Brownian last passage percolation model.
Protected cat states from kinetic driving of a boson gas

We investigate the behavior of a one-dimensional Bose-Hubbard gas in both a ring and a hard-wall box, whose kinetic energy is made to oscillate with zero time-average, which suppresses first-order particle hopping. For intermediate and large driving amplitudes the system in the ring has similarities to the Richardson model, but with a peculiar type of pairing and an attractive interaction in momentum space. This analogy permits an understanding of some key features of the interacting boson problem. The ground state is a macroscopic quantum superposition, or cat state, of two many-body states collectively occupying opposite momentum eigenstates. Interactions give rise to a reduction (or modified depletion) cloud that is common to both macroscopically distinct states. Symmetry arguments permit a precise identification of the two orthonormal macroscopic many-body branches which combine to yield the ground state. In the ring, the system is sensitive to variations of the effective flux but in such a way that the macroscopic superposition is preserved. We discuss other physical aspects that contribute to protect the cat-like nature of the ground state.
New preconditioners for Laplace and Helmholtz integral equations on open curves: II. Theoretical analysis

This paper is the second part of a work on Laplace and Helmholtz integral equations in 2 space dimensions on open curves. A new Galerkin method in weighted $L^2$ spaces together with new preconditioners for the weighted layer potentials are studied. This second part provides the theoretical analysis needed to establish the results announced in the first part. The main novelty is the introduction of a pseudo-differential calculus on open curves that allows to build parametrices for the weighted layer potentials. Contrarily to more classical approaches where the Mellin transform is used, this new approach is well-suited to the specific singularities that appear in the problem.
Explainability Techniques for Graph Convolutional Networks

Graph Networks are used to make decisions in potentially complex scenarios but it is usually not obvious how or why they made them. In this work, we study the explainability of Graph Network decisions using two main classes of techniques, gradient-based and decomposition-based, on a toy dataset and a chemistry task. Our study sets the ground for future development as well as application to real-world problems.
Neuropsychological changes in recovering men alcoholics.

indeed it exists, is a controversial phenomenon. Investigators have shown variously that neuropsychological cits do not exist in alcoholics, that they exist but are reversible, or that they are irreversible. These conflicting results are found from investigation to investigation and even within single studies and may be dependent, at least in part, on what measure of impairment is used. A minority of investigators (1-5) have found that alcoholics exhibit no impairments; however, most of these studies used measures that are not maximally sensitive to brain damage (e.g., Wechsler Adult Intelligence Scale, Bender Gestalt). Based on more sensitive measures, most of the research has shown that impairments do exist in alcoholics. The major research focus, thus, is not whether the deficits exist; it has more appropriately shifted to an examination of which areas are most likely to be affected and which deficits are reversible under what conditions (6). Of those studies which have identified impairments (7-17), some suggest reversibility with abstinence (11-17), while others indicate that some deficits are not reversible (14, 15). These conflicting results may be accounted for, at least in part, by which measures of impairment are used. A major step toward understanding the recovery process, if indeed it does exist, can be made only through research designed to eliminate the errors of previous research. The present investigation attempts to evaluate the existence of a recovery process in the intermediate stages of alcoholism by using measures which have demonstrated validity in discriminating between
Crowdsourcing and Validating Event-focused Emotion Corpora for German and English

Sentiment analysis has a range of corpora available across multiple languages. For emotion analysis, the situation is more limited, which hinders potential research on crosslingual modeling and the development of predictive models for other languages. In this paper, we fill this gap for German by constructing deISEAR, a corpus designed in analogy to the well-established English ISEAR emotion dataset. Motivated by Scherer’s appraisal theory, we implement a crowdsourcing experiment which consists of two steps. In step 1, participants create descriptions of emotional events for a given emotion. In step 2, five annotators assess the emotion expressed by the texts. We show that transferring an emotion classification model from the original English ISEAR to the German crowdsourced deISEAR via machine translation does not, on average, cause a performance drop.
Molecular analysis of hepatitis B virus associated with vaccine failure in infants and mothers: A case–control study in Thailand

Perinatal transmission of hepatitis B virus (HBV) has been controlled incompletely despite adequate immunoprophylaxis in infants. The aim of this study was to characterize virological factors of HBV associated with vaccine failure in Thailand. Sera of 14 infected infants (13 HBeAg‐positive and one HBeAg‐negative) with vaccine failure and their respective mothers (group M1) were tested quantitatively for HBV DNA by real‐time PCR, HBV genotypes and mutations were characterized by direct sequencing. Sera collected from 15 HBeAg‐positive (group M2) and 15 HBeAg‐negative (group M3) mothers whose infants had been vaccinated successfully served as controls. The results showed that group M1 and group M2 mothers had equal titers of HBV DNA but higher titers than group M3. All infected infants and their respective mothers had the same HBeAg status and HBV genotypes. DNA analysis in a pair of HBeAg‐negative infant and mother revealed that both were infected with an HBV precore mutant (G1896A). Escape mutants in the “a” determinant region (residues 144 and 145) were detected in two (14%) infected infants. The prevalence of BCP mutations/deletions in groups M2 and M3 was higher significantly than in group M1 (P = 0.022 and P < 0.001, respectively). In conclusion, instead of the HBeAg status, a high titer of HBV DNA in mothers was the major contributor to perinatal transmission of HBV. Escape mutants might be associated with vaccine failure in some infants. BCP mutations/deletions in mothers might contribute to the prevention of mother‐to‐infant transmission of HBV. J. Med. Virol. 84: 1177–1185, 2012. © 2012 Wiley Periodicals, Inc.
Evidence of charge density wave with anisotropic gap in a monolayer 
VTe2
 film

Angle-resolved photoemission spectroscopy measurements reveal the evidence of a charge density wave (CDW) and the underlying mechanism in a monolayer VTe${}_{2}$ film. The Fermi surface map is partially gapped and shows an arc shape. The CDW gap is found to be rather anisotropic and attributed to the imperfect nesting. First-principles calculations further indicate electron-phonon coupling at the corresponding wave vector. These observations suggest that both Fermi surface nesting and phonon instability contribute significantly to the CDW formation in this monolayer VTe${}_{2}$ film.
Implicit Regularization in Deep Matrix Factorization

Efforts to understand the generalization mystery in deep learning have led to the belief that gradient-based optimization induces a form of implicit regularization, a bias towards models of low "complexity. " We study the implicit regularization of gradient descent over deep linear neural networks for matrix completion and sensing, a model referred to as deep matrix factorization. Our first finding, supported by theory and experiments, is that adding depth to a matrix factorization enhances an implicit tendency towards low-rank solutions, oftentimes leading to more accurate recovery. Secondly, we present theoretical and empirical arguments questioning a nascent view by which implicit regularization in matrix factorization can be captured using simple mathematical norms. Our results point to the possibility that the language of standard regularizers may not be rich enough to fully encompass the implicit regularization brought forth by gradient-based optimization.
Maximizing Welfare in Social Networks under A Utility Driven Influence Diffusion model

Motivated by applications such as viral marketing, the problem of influence maximization (IM) has been extensively studied in the literature. The goal is to select a small number of users to adopt an item such that it results in a large cascade of adoptions by others. Existing works have three key limitations. (1) They do not account for economic considerations of a user in buying/adopting items. (2) Most studies on multiple items focus on competition, with complementary items receiving limited attention. (3) For the network owner, maximizing social welfare is important to ensure customer loyalty, which is not addressed in prior work in the IM literature. In this paper, we address all three limitations and propose a novel model called UIC that combines utility-driven item adoption with influence propagation over networks. Focusing on the mutually complementary setting, we formulate the problem of social welfare maximization in this novel setting. We show that while the objective function is neither submodular nor supermodular, surprisingly a simple greedy allocation algorithm achieves a factor of (1-1/e-ε) of the optimum expected social welfare. We develop bundleGRD, a scalable version of this approximation algorithm, and demonstrate, with comprehensive experiments on real and synthetic datasets, that it significantly outperforms all baselines.
Learning Equilibria of Simulation-Based Games

We tackle a fundamental problem in empirical game-theoretic analysis (EGTA), that of learning equilibria of simulation-based games. Such games cannot be described in analytical form; instead, a black-box simulator can be queried to obtain noisy samples of utilities. Our approach to EGTA is in the spirit of probably approximately correct learning. We design algorithms that learn so-called empirical games, which uniformly approximate the utilities of simulation-based games with finite-sample guarantees. These algorithms can be instantiated with various concentration inequalities. Building on earlier work, we first apply Hoeffding's bound, but as the size of the game grows, this bound eventually becomes statistically intractable; hence, we also use the Rademacher complexity. Our main results state: with high probability, all equilibria of the simulation-based game are approximate equilibria in the empirical game (perfect recall); and conversely, all approximate equilibria in the empirical game are approximate equilibria in the simulation-based game (approximately perfect precision). We evaluate our algorithms on several synthetic games, showing that they make frugal use of data, produce accurate estimates more often than the theory predicts, and are robust to different forms of noise.
Technical Debt in Data-Intensive Software Systems

The ever-increasing amount, variety as well as generation and processing speed of today's data pose a variety of new challenges for developing Data-Intensive Software Systems (DISS). As with developing other kinds of software systems, developing DISS is often done under severe pressure and strict schedules. Thus, developers of DISS often have to make technical compromises to meet business concerns. This position paper proposes a conceptual model that outlines where Technical Debt (TD) can emerge and proliferate within such data-centric systems by separating a DISS into three parts (Software Systems, Data Storage Systems and Data). Further, the paper illustrates the proliferation of Database Schema Smells as TD items within a relational database-centric software system based on two examples.
Photodesorption of Water Ice from Dust Grains and Thermal Desorption of Cometary Ices Studied by the INSIDE Experiment

A new experimental setup, INterStellar Ice-Dust Experiment (INSIDE), was designed for studying cosmic grain analogs represented by ice-coated carbon- and silicate-based dust grains. With the new instrument, we can simulate the physical and chemical conditions prevailing in interstellar and circumstellar environments. The setup combines ultrahigh vacuum and low-temperature conditions with infrared spectroscopy and mass spectrometry. Using INSIDE, we plan to investigate physical and chemical processes, such as adsorption, desorption, molecule formation, on the surface of dust/ice samples. First experiments on the photodesorption of water ice molecules from the surface of silicate and carbon grains by UV photons revealed a strong influence of the surface properties on the desorption yield, in particular in the monolayer regime. In the second experiment, the thermal desorption of cometary ice analogs composed of six molecular components was studied for the first time. Codesorption of CO2 and CH3OH with O2 indicates that at high O2 concentrations in cometary or interstellar ices, “heavy” ice molecules can be partly trapped in O2 and enter the gas phase much earlier than expected. This effect could explain astronomical detections of complex organic molecules in cold dense interstellar clouds.
Acupuncture Administration Improves Cognitive Functions and Alleviates Inflammation and Nuclear Damage by Regulating Phosphatidylinositol 3 Kinase (PI3K)/Phosphoinositol-Dependent Kinase 1 (PDK1)/Novel Protein Kinase C (nPKC)/Rac 1 Signaling Pathway in Senescence-Accelerated Prone 8 (SAM-P8) Mice

Background Alzheimer’s disease (AD) is an age-associated neurodegenerative disorder. This study aimed to investigate effects of acupuncture administration on cognitive function and associated mechanisms. Material/Methods Senescence-accelerated prone 8 (SAM-P8) mice were randomly divided into 3 groups: the SAM-P8 group (P8-CN), the SAM-P8 administrating with acupuncture (P8-Acup) group, and the SAM-P8 administrating without acupuncture (P8-Sham) group. Morris water maze test was conducted to evaluate cognitive functions (memory and learning ability). PDK1, nPKC, and Rac1 inhibitors were used to treat SAM-P8 mice. Transmission electron microscope analysis was used to examine nuclear damage hippocampal tissues. Hematoxylin and eosin (H&E) staining was employed to evaluate inflammation. Western blot was used to detect PI3K, PDK1, nPKC, and Rac 1 expression in hippocampal tissues. Results Acupuncture administration significantly reduced PI3K, PDK1, nPKC, and Rac 1 levels compared to P8-CN group (P<0.05). Both acupuncture and enzyme inhibitors (NSC23766, Rottlerin, OSU03012) significantly improved cognitive functions, reduced inflammation, and alleviated nuclear damages of SAM-P8 mice compared to P8-CN group (P<0.05). Acupuncture significantly enhanced effects of inhibitors on inflammation and nuclear damages compared to inhibitor treatment single (P<0.05). Acupuncture significantly enhanced down-regulative effects of OSU03012 on PI3K and PDK1 levels, increased down-regulative effects of Rottlerin on nPKC and Rac 1 levels and enhanced effects of Rottlerin on Rac 1 compared to P8-CN group (P<0.05). Conclusions Acupuncture administration improved cognitive functions and alleviated inflammatory response and nuclear damage of SAM-P8 mice, by downregulating PI3K/PDK1/nPKC/Rac 1 signaling pathway. This study could provide potential insight for treating cognitive dysfunction and aging of AD patients.
The eta invariant, analytic torsion, and a generalization via differential forms on spaces of operators and metrics

The central idea of this paper is to interpret certain spectral invariants as regularized integrals of closed differential forms on a space of elliptic operators or a space of metrics on a vector bundle. We apply this idea to the eta invariant and to the analytic torsion of a $\mathbb{Z}$-graded elliptic complex, explaining their dependence on the geometric data used to define them with a Stokes' theorem argument. We then introduce multi-torsion, a generalization of analytic torsion, in the context of manifolds with a certain local product structure; we prove that it is metric independent in a suitable sense.
Outcome of intramedullary interlocking SIGN nail in tibial diaphyseal fracture.

OBJECTIVE To determine the outcome of intramedullary interlocking surgical implant generation network (SIGN) nail in diaphyseal tibial fractures in terms of union and failure of implant (breakage of nail or interlocking screws). STUDY DESIGN Case series. PLACE AND DURATION OF STUDY Orthopaedics and Spinal Surgery, Ghurki Trust Teaching Hospital, Lahore Medical and Dental College, Lahore, from September 2008 to August 2009. METHODOLOGY Fifty patients aged 14 - 60 years, of either gender were included, who had closed and Gustilo type I and II open fractures reported in 2 weeks, whose closed reduction was not possible or was unsatisfactory and fracture was located 7 cm below knee joint to 7 cm above ankle joint. Fractures previously treated with external fixator, infected fractures and unfit patients were excluded. All fractures were fixed with intramedullary interlocking SIGN nail and were followed clinically and radiographically for union and for any implant failure. RESULTS Forty one (88%) patients had united fracture within 6 months, 5 (10%) patients had delayed union while 4 (8%) patients had non-union. Mean duration for achieving union was 163 + 30.6 days. Interlocking screws were broken in 2 patients while no nail was broken in any patient. CONCLUSION Intramedullary interlocking nailing is an effective measure in treating closed and grade I and II open tibial fractures. It provides a high rate of union less complications and early return to function.
Winds and feedback from supermassive black holes accreting at low rates: hydrodynamical treatment

Outflows produced by a supermassive black hole (SMBH) can have important feedback effects in its host galaxy. An unresolved question is the nature and properties of winds from SMBHs accreting at low rates in low-luminosity active galactic nuclei (LLAGNs). We performed two-dimensional numerical, hydrodynamical simulations of radiatively inefficient accretion flows on to non-spinning black holes. We explored a diversity of initial conditions in terms of rotation curves and viscous shear stress prescriptions, and evolved our models for very long durations of up to 8 × 105GM/c3. Our models resulted in powerful subrelativistic, thermally driven winds originated from the corona of the accretion flow at distances 10−100 GM/c2 from the SMBH. The winds reached velocities of up to 0.01c with kinetic powers corresponding to $0.1\! -\! 1 {\,{\rm per\, cent}}$ of the rest-mass energy associated with inflowing gas at large distances, in good agreement with models of the ‘radio mode’ of AGN feedback. The properties of our simulated outflows are in broad agreement with observations of winds in quiescent galaxies that host LLAGNs, which are capable of heating ambient gas and suppressing star formation.