Miracle-dz/UniFAR-FTUs huggingface dataset:
Scalable Evaluation and Improvement of Document Set Expansion via Neural Positive-Unlabeled Learning

We consider the situation in which a user has collected a small set of documents on a cohesive topic, and they want to retrieve additional documents on this topic from a large collection. Information Retrieval (IR) solutions treat the document set as a query, and look for similar documents in the collection. We propose to extend the IR approach by treating the problem as an instance of positive-unlabeled (PU) learning—i.e., learning binary classifiers from only positive (the query documents) and unlabeled (the results of the IR engine) data. Utilizing PU learning for text with big neural networks is a largely unexplored field. We discuss various challenges in applying PU learning to the setting, showing that the standard implementations of state-of-the-art PU solutions fail. We propose solutions for each of the challenges and empirically validate them with ablation tests. We demonstrate the effectiveness of the new method using a series of experiments of retrieving PubMed abstracts adhering to fine-grained topics, showing improvements over the common IR solution and other baselines.
Converged Deep Framework Assembling Principled Modules for CS-MRI

Compressed Sensing Magnetic Resonance Imaging (CS-MRI) significantly accelerates MR data acquisition at a sampling rate much lower than the Nyquist criterion. A major challenge for CS-MRI lies in solving the severely ill-posed inverse problem to reconstruct aliasing-free MR images from the sparse k-space data. Conventional methods typically optimize an energy function, producing reconstruction of high quality, but their iterative numerical solvers unavoidably bring extremely slow processing. Recent data-driven techniques are able to provide fast restoration by either learning direct prediction to final reconstruction or plugging learned modules into the energy optimizer. Nevertheless, these data-driven predictors cannot guarantee the reconstruction following constraints underlying the regularizers of conventional methods so that the reliability of their reconstruction results are questionable. In this paper, we propose a converged deep framework assembling principled modules for CS-MRI that fuses learning strategy with the iterative solver of a conventional reconstruction energy. This framework embeds an optimal condition checking mechanism, fostering \emph{efficient} and \emph{reliable} reconstruction. We also apply the framework to two practical tasks, \emph{i.e.}, parallel imaging and reconstruction with Rician noise. Extensive experiments on both benchmark and manufacturer-testing images demonstrate that the proposed method reliably converges to the optimal solution more efficiently and accurately than the state-of-the-art in various scenarios.
A Far-UV Variability Survey of the Globular Cluster M80

We have searched for variable sources in the core region of M80, using far ultra-violet data taken with the Advanced Camera for Surveys on board the Hubble Space Telescope. We found three sources that exhibit strong signs of variability in our data. Among these is source TDK1, which we believe to be an RR Lyrae star that reached maximum brightness during our observations. The light curve shows a >3 mag FUV brightening over the course of ~5 hours, with an estimated peak brightness of ~16.7 mag, followed by a decrease to ~20 mag. Archival optical data obtained with WFPC2 confirm that TDK1 is variable in all wavebands. TDK1's SED is reasonably fit by a star with temperature T(eff)=6700K and radius R=4.2R(sun), consistent with the suggestion that it is an RR Lyrae. Based on the photometric and variability characteristics of the other two variables, we suggest that TDK2 is likely to be an SX Phoenicis star with ~55 minutes period, and TDK3 is likely another RR Lyrae. Finally, we briefly discuss the FUV counterparts to two previously known variables in M80, the classical nova T Sco and the dwarf nova DN1.
Catastrophic Cooling in Superwinds: Line Emission and Non-equilibrium Ionization

Outflows are a pervasive feature of mechanical feedback from super star clusters (SSCs) in starburst galaxies, playing a fundamental role in galaxy evolution. Observations are now starting to confirm that outflows can undergo catastrophic cooling, suppressing adiabatic superwinds. Here we present a suite of one-dimensional, hydrodynamic simulations that study the ionization structure of these outflows and the resulting line emission generated by the cooling gas. We use the non-equilibrium atomic chemistry package within MAIHEM, our modified version of FLASH, which evolves the ionization state of the gas and computes the total cooling rate on an ion-by-ion basis. We find that catastrophically cooling models produce strong nebular line emission compared to adiabatic outflows. We also show that such models exhibit non-equilibrium conditions, thereby generating more highly ionized states than equivalent equilibrium models. When including photoionization from the parent SSC, catastrophically cooling models show strong C iv λ1549 and O vi λ1037 emission. For density-bounded photoionization, He ii λ1640, λ4686, C iii] λ1908, Si iv λ1206, and Si iii λ1400 are also strongly enhanced. These lines are seen in extreme starbursts where catastrophic cooling is likely to occur, suggesting that they may serve as diagnostics of such conditions. The higher ionization generated by these flows may help to explain line emission that cannot be attributed to SSC photoionization alone.
Results from the Robocademy ITN: Autonomy, Disturbance Rejection and Perception for Advanced Marine Robotics

Marine and Underwater resources are important part of the economy of many countries. This requires significant financial resources into their construction and maintentance. Robotics is expected to fill this void, by automating and/or removing humans from hostile environments in order to easily perform maintenance tasks. The Robocademy Marie Sklodowska-Curie Initial Training Network was funded by the European Union's FP7 research program in order to train 13 Fellows into world-leading researchers in Marine and Underwater Robotics. The fellows developed guided research into three areas of key importance: Autonomy, Disturbance Rejection, and Perception. This paper presents a summary of the fellows' research in the three action lines. 71 scientific publications were the primary result of this project, with many other publications currently in the pipeline. Most of the fellows have found employment in Europe, which shows the high demand for this kind of experts. We believe the results from this project are already having an impact in the marine robotics industry, as key technologies are being adopted already.
Mixup-breakdown: A Consistency Training Method for Improving Generalization of Speech Separation Models

Deep-learning based speech separation models confront poor generalization problem that even the state-of-the-art models could abruptly fail when evaluating them in mismatch conditions. To address this problem, we propose an easy-to-implement yet effective consistency based semi-supervised learning (SSL) approach, namely Mixup-Breakdown training (MBT). It learns a teacher model to "breakdown" unlabeled inputs, and the estimated separations are interpolated to produce more useful pseudo "mixup" input-output pairs, on which the consistency regularization could apply for learning a student model. In our experiment, we evaluate MBT under various conditions with ascending degrees of mismatch, including unseen interfering speech, noise, and music, and compare MBT’s generalization capability against state-of-the-art supervised learning and SSL approaches. The result indicates that MBT significantly outperforms several strong baselines with up to 13.77% relative SI-SNRi improvement. Moreover, MBT only adds negligible computational overhead to standard training schemes.
Notes on geometry of locomotion of 3-dimensional version of the Purcell's swimmer

We present a generalized, 3 dimensional version of the Purcell's swimmer which is a planar mechanism locomoting at low Reynlods number regime. We use Cox theory and resistive force theory to come up with the forces acting on the system. We finally come up with a purely kinematic form of the system's equations.
Distributed and consistent multi-image feature matching via QuickMatch

In this work, we consider the multi-image object matching problem in distributed networks of robots. Multi-image feature matching is a keystone of many applications, including Simultaneous Localization and Mapping, homography, object detection, and Structure from Motion. We first review the QuickMatch algorithm for multi-image feature matching. We then present NetMatch, an algorithm for distributing sets of features across computational units (agents) that largely preserves feature match quality and minimizes communication between agents (avoiding, in particular, the need to flood all data to all agents). Finally, we present an experimental application of both QuickMatch and NetMatch on an object matching test with low-quality images. The QuickMatch and NetMatch algorithms are compared with other standard matching algorithms in terms of preservation of match consistency. Our experiments show that QuickMatch and Netmatch can scale to larger numbers of images and features, and match more accurately than standard techniques.
C O ] 2 3 Ja n 20 08 Efficient l α Distance Approximation for High Dimensional Data Using α-Stable Projection

In recent years, large high-dimensional data sets have become commonplace in a wide range of applications in science and commerce. Techniques for dimension reduction are of primary concern in statistical analysis. Projection methods play an important role. We investigate the use of projection algorithms that exploit properties of the α-stable distributions. We show that lα distances and quasi-distances can be recovered from random projections with full statistical efficiency by L-estimation. The computational requirements of our algorithm are modest; after a once-and-for-all calculation to determine an array of length k, the algorithm runs in O(k) time for each distance, where k is the reduced dimension of the projection.
The Slowly Varying Corona. II. The Components of F10.7 and Their Use in EUV Proxies

Using four years of full-disk-integrated coronal differential emission measures calculated in Schonfeld et al. (2017), we investigate the relative contribution of bremsstrahlung and gyroresonance emission in observations of F10.7, the 10.7 cm (2.8 GHz) solar microwave spectral flux density and commonly used activity proxy. We determine that the majority of coronal F10.7 is produced by the bremsstrahlung mechanism, but the variability observed over individual solar rotations is often driven by gyroresonance sources rotating across the disk. Our analysis suggests that the chromosphere may contribute significantly to F10.7 variability and that coronal bremsstrahlung emission accounts for 14.2 ± 2.1 sfu (∼20%) of the observed solar minimum level. The bremsstrahlung emission has a power-law relationship to the total F10.7 at high activity levels, and this combined with the observed linearity during low activity yields a continuously differentiable piecewise fit for the bremsstrahlung component as a function of F10.7. We find that the bremsstrahlung component fit, along with the Mg ii index, correlates better with the observed 5–37 nm spectrum than the common 81 day averaged F10.7 proxy. The bremsstrahlung component of F10.7 is also well approximated by the moderate-strength photospheric magnetic field parameterization from Henney et al. (2012), suggesting that it could be forecast for use in both atmospheric research and operational models.
. 30 39 v 2 [ m at hph ] 1 1 N ov 2 00 8 PT-symmetric waveguides

We introduce a planar waveguide of constant width with non-Hermitian PT -symmetric Robin boundary conditions. We study the spectrum of this system in the regime when the boundary coupling function is a compactly supported perturbation of a homogeneous coupling. We prove that the essential spectrum is positive and independent of such perturbation, and that the residual spectrum is empty. Assuming that the perturbation is small in the supremum norm, we show that it gives rise to real weakly-coupled eigenvalues converging to the threshold of the essential spectrum. We derive sufficient conditions for these eigenvalues to exist or to be absent. Moreover, we construct the leading terms of the asymptotic expansions of these eigenvalues and the associated eigenfunctions. MSC2000: 35P15, 35J05, 47B44, 47B99.
Identifying Exo-Earth Candidates in Direct Imaging Data through Bayesian Classification

Future space telescopes may be able to directly image between approximately 10 and 100 planets with sizes and orbits consistent with habitable surface conditions (“exo-Earth candidates” or EECs), but observers will face difficulty in distinguishing these from the potentially hundreds of nonhabitable “false positives” which will also be detected. To maximize the efficiency of follow-up observations, a prioritization scheme must be developed to determine which planets are most likely to be EECs. In this paper, we present a Bayesian method for estimating the likelihood that any directly imaged extrasolar planet is a true EEC by interpreting the planet’s apparent magnitude and separation in the context of existing exoplanet statistics. As a specific application of this general framework, we use published estimates of the discovery yield of future space-based direct-imaging mission concepts to conduct “mock surveys” in which we compute the likelihood that each detected planet is an EEC. We find that it will be difficult to determine which planets are EECs with >50% confidence using single-band photometry immediately upon their detection. The best way to reduce this ambiguity would be to constrain the orbit of a given planet by revisiting the system multiple times or through a radial velocity precursor survey. Astrometric or radial velocity constraints on the mass of the planet would offer a lesser benefit. Finally, we show that a Bayesian approach to prioritizing targets would improve the follow-up efficiency of a direct imaging survey versus a blind approach using the same data. For example, the prioritized approach could reduce the amount of integration time required for the spectral detection (or rejection) of water absorption in most EECs by a factor of two.
MEMS Cantilever Based Frequency Doublers

Microelectromechanical system (MEMS) based on-chip resonators offer great potential for high frequency signal processing circuits like reference oscillators and filters. This is due to their exceptional features like small size, large frequency-quality factor product, integrability with CMOS ICs, low power consumption, low cost batch fabrication etc. A capacitively transduced cantilever beam resonator is one such popular MEMS resonator topology. In this letter, the inherent square-law nonlinearity of the voltage-to-force transfer function of a cantilever resonator’s capacitive transducer has been employed for the realization of frequency doubling effect. Using this concept, frequency doubling of input signals of 500 kHz to 1 MHz, and 227.5 kHz to 455 kHz has been experimentally demonstrated for two cantilever beams of length 51.75 μm and 76.75 μm respectively. The MEMS cantilevers have been fabricated with polysilicon using the PolyMUMPs surface micromachining process, and their testing has been performed using Laser Doppler Vibrometry. The test results obtained are in reasonable compliance with the analytical and CoventorWare finite-element simulation results. The high efficiency demonstrated by the cantilever frequency doubler makes it a promising choice for signal generation at high frequencies.
On the Mass Assembly History of the Local Group

In this work an ensemble of simulated Local Group analogues is used to constrain the properties of the mass assembly history of the Milky Way (MW) and Andromeda (M31) galaxies. These objects have been obtained using the constrained simulation technique, which ensures that simulated LGs live within a large scale environment akin to the observed one. Our results are compared against a standard Λ Cold Dark Matter (ΛCDM) series of simulations which use the same cosmological parameters. This allows us to single out the effects of the constraints on the results. We find that (a) the median constrained merging histories for M31 and MW live above the standard ones at the 1-σ level, (b) the median formation time takes place ≈0.5 Gyr earlier than unconstrained values, while the latest major merger happens on average 1.5 Gyr earlier and (c) the probability for both LG haloes to have experienced their last major merger in the first half of the history of the Universe is $\approx 50\%$ higher for the constrained pairs. These results have been estimated to be significant at the $99\%$ confidence level by means of a Kolmogorov-Simirnov test. These results suggest that the particular environment in which the Milky Way and Andromeda form plays a role in shaping their properties, and favours earlier formation and last major merger time values in agreement with other observational and theoretical considerations.
Compressive Partial Neuropathy of Axillary Nerve Resulting from Antero-Inferior Paralabral Cyst in an Adolescent Overhead Athlete

Paralabral cysts of the shoulder are rare, and there are few reports available that describe antero-inferior paralabral cysts arising from a detached antero-inferior glenoid labral tear without shoulder instability. We report an anteroinferior labral tear without shoulder instability in adolescent overhead athlete associated with paralabral cyst that leads to axillary nerve neurapraxia. Although nonoperative management of such labral lesions may provide symptoms of relief, it may not be enough for the athlete to return to the game. However, surgical treatment in this case provides successful recovery and rapid return to playing baseball play without having to worry about the progression of muscle denervation.
The effects of cryotherapy on proprioception, indices of muscle damage and on intramuscular, skin and core temperature

Cryotherapy, the therapeutic use of cold, has been used since the time of the ancient Greeks. In sport medicine, whole body cooling is used before and after athletic participation. Pre-cooling before exercise enables an individual to start exercise with a cooler body temperature, increase their heat storage capacity and perform more work before reaching a limiting core body temperature. Cryotherapy is also used after exercise in an attempt to alleviate the debilitating effects of exercise induced muscle damage. Cold Water Immersion (CWI) is one of the most commonly used modalities of cooling in sports medicine. CWI involves immersing an individual in cold water to the level of the waist or sternum. Whole Body Cryotherapy (WBC) is a relatively new modality of cooling that involves exposing an individual to extremely low temperatures for a short duration of time in a specially built cryogenic chamber. The physiological effects of whole body cooling, especially WBC, are poorly understood and the potential negative effects of pre-cooling on proprioceptive acuity have not been elucidated. Furthermore, the purported benefits of using WBC as a treatment for exercise induced muscle damage have not been evaluated. This thesis comprises 5 papers (2 reviews and 3 controlled studies) which investigate the physiological effects of whole body cooling. As it has been hypothesised that a reduction in Joint Position Sense (JPS) may reduce athletic performance or predispose injury, particular emphasis is paid to the effects of these modalities on JPS. Therefore, the primary aim was to explore the effects of CWI and WBC on proprioceptive acuity and to compare and contrast the ability of both cooling modalities to reduce muscle, skin and core temperature. A secondary aim of this thesis was to assess the effectiveness of WBC as a method of recovery following symptoms of exercise induced muscle damage. In summary the findings of this thesis suggest that knee JPS is not reduced following CWI or WBC. In addition WBC did not reduce muscle force (maximal voluntary isometric contraction of the knee extensors) or force proprioception. The cooling potential of CWI and WBC on muscle, skin and core temperature was investigated using a randomised crossover design. A comparable reduction in muscle and core temperature was observed, however skin temperature was lower immediately after WBC compared to CWI. Finally, when administered 24 hours after eccentric exercise, WBC appears to be ineffective in alleviating muscle soreness or enhancing muscle force recovery. The results and conclusions presented in this thesis may contribute to overall understanding of whole body cooling; inform clinicians and sports people and direct future research in the area.
CLL: a paradigm of tumor-associated immune dysfunction

Disorders of the immune system occur in a large range of malignancies. Whereas some of the abnormalities may affect different components of host defense against pathogens, others may contribute to the survival or even expansion of tumor cells. In B cell chronic lymphocytic leukemia (CLL) various immune disorders may be observed in the course of the disease. In CLL, an increased amount of regulatory T cells, skewing of the immune system towards Th2 and down modulation of costimulatory molecules combined with enhanced surface expression of CD200 by tumor cells may all serve as a protective mechanism against tumor-directed immune responses. Other coinciding immune disorders (like autoimmunity and hypogammaglobulinaemia) also have an effect on host immunity but offer no obvious advantage for the tumor cells. Strikingly, amidst all these impairments, immunity against chronic (herpes) viruses like cytomegalovirus (CMV) and Epstein Barr Virus (EBV) is conserved in CLL patients. Studying these unique T cell populations in CLL may provide new insights into the requirements for the maintenance of immunity against chronic (herpes) viruses. Moreover, these virus-specific T cells may also hand us a powerful tool for active immunotherapy for CLL if they can be redirected against tumor cells.