Miracle-dz/UniFAR-FTUs huggingface dataset:
Less Confusion More Transferable: Minimum Class Confusion for Versatile Domain Adaptation

Domain Adaptation (DA) transfers a learning model from a labeled source domain to an unlabeled target domain which follows different distributions. There are a variety of DA scenarios subject to label sets and domain configurations, including closed-set and partial-set DA, as well as multi-source and multi-target DA. It is notable that existing DA methods are generally designed only for a specific scenario, and may underperform for scenarios they are not tailored to. Towards a versatile DA method, a more universal inductive bias other than the domain alignment should be explored. In this paper, we delve into a missing piece of existing methods: class confusion, the tendency that a classifier confuses the predictions between the correct and ambiguous classes for target examples. We unveil that less class confusion explicitly indicates more class discriminability and implicitly implies more domain transferability in all the above scenarios. Based on the more universal inductive bias, we propose a general loss function: Minimum Class Confusion (MCC). It can be characterized by (1) a non-adversarial DA method without explicitly deploying domain alignment, enjoying fast convergence speed (about 3x faster than mainstream adversarial methods); (2) a versatile approach that can handle Closed-Set, Partial-Set, Multi-Source, and Multi-Target DA, outperforming the state-of-the-art methods in these scenarios, especially on the largest and hardest dataset to date (7.25% on DomainNet). In addition, it can also be used as a general regularizer that is orthogonal and complementary to a variety of existing DA methods, accelerating convergence and pushing those readily competitive methods to a stronger level. We will release our code for reproducibility.
Does Interpretability of Neural Networks Imply Adversarial Robustness?

The success of deep neural networks is clouded by two issues: (1) a vulnerability to adversarial examples and (2) a tendency to be uninterpretable. Interestingly, recent empirical evidence in the literature as well as theoretical analysis on simple models suggest these two seemingly disparate issues are actually connected. In particular, robust models tend to be more interpretable than non-robust models. In this paper, we provide evidence for the claim that this relationship is bidirectional. Viz., models that are optimized to have interpretable gradients are more robust to adversarial examples than models trained in a standard manner. With further analysis and experiments on standard image classification datasets, we identify two factors behind this phenomenon---namely the suppression of the gradient's magnitude and the selective use of features guided by high-quality interpretations---which explain model behaviors under various regularization and target interpretation settings.
On Using Inspiraling Supermassive Binary Black Holes in the PTA Frequency Band as Standard Sirens to Constrain Dark Energy

Supermassive binary black holes (SMBBHs) in galactic centers may radiate gravitational waves (GW) in the nano-Hertz frequency band, which are expected to be detected by pulsar timing arrays (PTAs) in the near future. GW signals from individual SMBBHs at cosmic distances, if detected by PTAs, are potentially powerful standard sirens that can be used to independently measure distances and thus put constraints on cosmological parameters. In this paper, we investigate the constraint that may be obtained on the equation of state (w) of dark energy by using those SMBBHs, expected to be detected by the PTAs in the Square Kilometre Array (SKA) era. By considering both the currently available SMBBH candidates and mock SMBBHs in the universe resulting from a simple galaxy major merger model, we find that ∼200–3000 SMBBHs with chirp mass >109 M⊙ are expected to be detected with a signal-to-noise ratio >10 by SKA–PTA with conservative and optimistic settings and they can be used to put a constraint on w to an uncertainty of Δw ∼ 0.02–0.1. If further information on the mass and mass ratio of those SMBBHs can be provided by electromagnetic observations (e.g., chirp mass uncertainty ≲50%), the constraint may be further improved to a ≲0.01 level, as many more SMBBHs will be detected by SKA–PTA with relatively better distance measurements and can be used as the standard sirens.
Observations of solar chromospheric oscillations at 3 mm with ALMA

Aims. We aim to study spatially resolved chromospheric oscillations of the quiet Sun (QS) in the mm-domain at a resolution of a few arcsec, typically 2.4″ × 4.5″. Methods. We used Atacama Large millimeter and submillimeter Array (ALMA) time series of interferometric observations of the QS obtained at 3 mm with a 2-s cadence and a spatial resolution of a few arcsec. The observations were performed on March 16, 2017 and seven 80″ × 80″ fields of view (FoV) going from disk center to limb were covered, each one observed for 10 min, therefore limiting the frequency resolution of the power spectra to 1.7 mHz. For each FoV, masks for cell and network were derived, and the averaged power spectral densities (PSDs) for the entire FoV, cell, and network were computed. The resulting power spectra were fit with an analytical function in order to derive the frequency and the root-mean-square (rms) power associated with the peaks. The same analysis, over the same FoVs and for the same intervals, was performed for simultaneous Atmospheric Imaging Assembly (AIA) image sequences in 1600 Å. Results. Spatially resolved chromospheric oscillations at 3 mm, with frequencies of 4.2 ± 1.7 mHz are observed in the QS, in both cell and network. The coherence length-scale of the oscillations is commensurate with the spatial resolution of our ALMA observations. Brightness-temperature fluctuations in individual pixels could reach up to a few hundred K, while the spatially averaged PSDs yield rms in the range ≈55–75 K, i.e., up to ≈1% of the averaged brightness temperatures and exhibit a moderate increase towards the limb. For AIA 1600 Å, the oscillation frequency is 3.7 ± 1.7 mHz. The relative rms is up to 6% of the background intensity, with a weak increase towards the disk center (cell, average). ALMA 3 mm time-series lag AIA 1600 Å by ≈100 s, which corresponds to a formation-height difference of ≈1200 km, representing a novel determination of this important parameter. Conclusions. The ALMA oscillations that we detected exhibit higher amplitudes than those derived from previous lower (≈10″) resolution observations at 3.5 mm by the Berkeley-Illinois-Maryland Array. Chromospheric oscillations are, therefore, not fully resolved at the length-scale of the chromospheric network, and possibly not even at the spatial resolution of our ALMA observations. Any study of transient brightenings in the mm-domain should take into account the oscillations.
Constraining the masses of planets in protoplanetary discs from the presence or absence of vortices – comparison with ALMA observations

A massive planet in a protoplanetary disc will open a gap in the disc material. A steep gap edge can be hydrodynamically unstable, which results in the formation of vortices that can act as tracers for the presence of planets in observational results. However, in a viscous disc, the potential formation of these vortices is dependent on the time-scale over which the massive planet accretes mass and with a sufficiently long time-scale it is possible for no vortices to form. Hence, there is a connection between the presence of vortices and the growth time-scale of the planet and it may therefore be possible to exclude a planetary interpretation of observed structure from the absence of vortices. We have investigated the effect of the planet growth time-scale on vortex formation for a range of planet masses and viscosities and have found an approximate relation between the planet mass, viscosity and planet growth time-scale for which vortices are not formed within the disc. We then interpret these results in the light of recent observations. We have also found that planets do not need to be close to a Jupiter mass to form vortices in the disc if these discs have low viscosity, as these can be caused by planets as small as a few Neptune masses.
Online vector balancing and geometric discrepancy

We consider an online vector balancing question where T vectors, chosen from an arbitrary distribution over [−1,1] n , arrive one-by-one and must be immediately given a ± sign. The goal is to keep the discrepancy—the ℓ∞-norm of any signed prefix-sum—as small as possible. A concrete example of this question is the online interval discrepancy problem where T points are sampled one-by-one uniformly in the unit interval [0,1], and the goal is to immediately color them ± such that every sub-interval remains always nearly balanced. As random coloring incurs Ω(T 1/2) discrepancy, while the worst-case offline bounds are Θ(√n log(T/n)) for vector balancing and 1 for interval balancing, a natural question is whether one can (nearly) match the offline bounds in the online setting for these problems. One must utilize the stochasticity as in the worst-case scenario it is known that discrepancy is Ω(T 1/2) for any online algorithm. In a special case of online vector balancing, Bansal and Spencer [BS19] recently show an O(√nlogT) bound when each coordinate is independently chosen. When there are dependencies among the coordinates, as in the interval discrepancy problem, the problem becomes much more challenging, as evidenced by a recent work of Jiang, Kulkarni, and Singla [JKS19] that gives a non-trivial O(T 1/loglogT ) bound for online interval discrepancy. Although this beats random coloring, it is still far from the offline bound. In this work, we introduce a new framework that allows us to handle online vector balancing even when the input distribution has dependencies across coordinates. In particular, this lets us obtain a poly(n, logT) bound for online vector balancing under arbitrary input distributions, and a polylog (T) bound for online interval discrepancy. Our framework is powerful enough to capture other well-studied geometric discrepancy problems; e.g., we obtain a poly(log d (T)) bound for the online d-dimensional Tusnády’s problem. All our bounds are tight up to polynomial factors. A key new technical ingredient in our work is an anti-concentration inequality for sums of pairwise uncorrelated random variables, which might also be of independent interest.
Hydration Mimicry by Membrane Ion Channels.

Ions transiting biomembranes might pass readily from water through ion-specific membrane proteins if these protein channels provide environments similar to the aqueous solution hydration environment. Indeed, bulk aqueous solution is an important reference condition for the ion permeation process. Assessment of this hydration mimicry concept depends on understanding the hydration structure and free energies of metal ions in water in order to provide a comparison for the membrane channel environment. To refine these considerations, we review local hydration structures of ions in bulk water and the molecular quasi-chemical theory that provides hydration free energies. In doing so, we note some current views of ion binding to membrane channels and suggest new physical chemical calculations and experiments that might further clarify the hydration mimicry concept. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 71 is April 20, 2020. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Dissecting the Graphcore IPU Architecture via Microbenchmarking

This report focuses on the architecture and performance of the Intelligence Processing Unit (IPU), a novel, massively parallel platform recently introduced by Graphcore and aimed at Artificial Intelligence/Machine Learning (AI/ML) workloads. We dissect the IPU's performance behavior using microbenchmarks that we crafted for the purpose. We study the IPU's memory organization and performance. We study the latency and bandwidth that the on-chip and off-chip interconnects offer, both in point-to-point transfers and in a spectrum of collective operations, under diverse loads. We evaluate the IPU's compute power over matrix multiplication, convolution, and AI/ML primitives. We discuss actual performance in comparison with its theoretical limits. Our findings reveal how the IPU's architectural design affects its performance. Moreover, they offer simple mental models to predict an application's performance on the IPU, on the basis of the computation and communication steps it involves. This report is the natural extension to a novel architecture of a continuing effort of ours that focuses on the microbenchmark-based discovery of massively parallel architectures.
Developing Patient Education Questionnaire in Iranian Population

Introduction: Patient education is a key component for effective self-management and monitoring required with many acute and chronic conditions. The objective of the study was to develop an instrument to measure patient education content. Materials and Methods: First of all, literature searches were undertaken to determine current national and international patient education questionnaires. Then a forty five item questionnaire was developed. The questioner was filled by 396 patients of medical surgical wards of Kerman hospitals. Reliability of the questionnaire was assessed by Cronbach's alpha. Factor analysis in conjunction with Principal Component Analysis (PCA) was applied to assess the construct validity of the instrument. Results: The result regarding reliability of the scale showed that The alpha coefficient of the scale was 0.95. Using PCA, a five-factor solution was selected as the most appropriate model, which accounted for nearly 70% of the total variance; disease information, disease complication, drug information, general information, and miscellaneous.
Face beautification: Beyond makeup transfer

Facial appearance plays an important role in our social lives. Subjective perception of women's beauty depends on various face-related (e.g., skin, shape, hair) and environmental (e.g., makeup, lighting, angle) factors. Similarly to cosmetic surgery in the physical world, virtual face beautification is an emerging field with many open issues to be addressed. Inspired by the latest advances in style-based synthesis and face beauty prediction, we propose a novel framework for face beautification. For a given reference face with a high beauty score, our GAN-based architecture is capable of translating an inquiry face into a sequence of beautified face images with the referenced beauty style and the target beauty score values. To achieve this objective, we propose to integrate both style-based beauty representation (extracted from the reference face) and beauty score prediction (trained on the SCUT-FBP database) into the beautification process. Unlike makeup transfer, our approach targets many-to-many (instead of one-to-one) translation, where multiple outputs can be defined by different references with various beauty scores. Extensive experimental results are reported to demonstrate the effectiveness and flexibility of the proposed face beautification framework. To support reproducible research, the source codes accompanying this work will be made publicly available on GitHub.
JAX, M.D.: End-to-End Differentiable, Hardware Accelerated, Molecular Dynamics in Pure Python

A large fraction of computational science involves simulating the dynamics of particles that interact via pairwise or many-body interactions. These simulations, called Molecular Dynamics (MD), span a vast range of subjects from physics and materials science to biochemistry and drug discovery. Most MD software involves significant use of handwritten derivatives and code reuse across C++, FORTRAN, and CUDA. This is reminiscent of the state of machine learning before automatic differentiation became popular. In this work we bring the substantial advances in software that have taken place in machine learning to MD with JAX, M.D. (JAX MD). JAX MD is an end-to-end differentiable MD package written entirely in Python that can be just-in-time compiled to CPU, GPU, or TPU. JAX MD allows researchers to iterate extremely quickly and lets researchers easily incorporate machine learning models into their workflows. Finally, since all of the simulation code is written in Python, researchers can have unprecedented flexibility in setting up experiments without having to edit any low-level C++ or CUDA code. In addition to making existing workloads easier, JAX MD allows researchers to take derivatives through whole-simulations as well as seamlessly incorporate neural networks into simulations. This paper explores the architecture of JAX MD and its capabilities through several vignettes. Code is available at this http URL. We also provide an interactive Colab notebook that goes through all of the experiments discussed in the paper.
6-DOF Grasping for Target-driven Object Manipulation in Clutter

Grasping in cluttered environments is a fundamental but challenging robotic skill. It requires both reasoning about unseen object parts and potential collisions with the manipulator. Most existing data-driven approaches avoid this problem by limiting themselves to top-down planar grasps which is insufficient for many real-world scenarios and greatly limits possible grasps. We present a method that plans 6-DOF grasps for any desired object in a cluttered scene from partial point cloud observations. Our method achieves a grasp success of 80.3%, outperforming baseline approaches by 17.6% and clearing 9 cluttered table scenes (which contain 23 unknown objects and 51 picks in total) on a real robotic platform. By using our learned collision checking module, we can even reason about effective grasp sequences to retrieve objects that are not immediately accessible. Supplementary video can be found here.
Constraining Properties of the Next Nearby Core-collapse Supernova with Multimessenger Signals

With the advent of modern neutrino and gravitational wave (GW) detectors, the promise of multimessenger detections of the next galactic core-collapse supernova (CCSN) has become very real. Such detections will give insight into the CCSN mechanism and the structure of the progenitor star, and may resolve longstanding questions in fundamental physics. In order to properly interpret these detections, a thorough understanding of the landscape of possible CCSN events, and their multimessenger signals, is needed. We present detailed predictions of neutrino and GW signals from 1D simulations of stellar core collapse, spanning the landscape of core-collapse progenitors from 9 to 120 M⊙. In order to achieve explosions in 1D, we use the Supernova Turbulence In Reduced-dimensionality model, which includes the effects of turbulence and convection in 1D supernova simulations to mimic the 3D explosion mechanism. We study the GW emission from the 1D simulations using an astroseismology analysis of the protoneutron star. We find that the neutrino and GW signals are strongly correlated with the structure of the progenitor star and remnant compact object. Using these correlations, future detections of the first few seconds of neutrino and GW emission from a galactic CCSN may be able to provide constraints on stellar evolution independent of preexplosion imaging and the mass of the compact object remnant prior to fallback accretion.
Associated Brain Parenchymal Abnormalities in Developmental Venous Anomalies: Evaluation with Susceptibility-weighted MR Imaging

Developmental venous anomalies (DVAs) of the brain are frequently encountered on contrast-enhanced (CE) CT or MR imaging. They are regarded as normal variants of the cerebral venous development and are usually asymptomatic (1-4). However, it has been reported that MR signal abnormalities in the adjacent brain parenchyma could be This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Received: July 12, 2015 Revised: August 15, 2015 Accepted: August 18, 2015
Effect of Mirror Therapy on Hand Functions in Children with Hemiplegic Cerebral Palsy: A Case Study

Introduction: Cerebral Palsy describes “group of disorders of the development of movement and posture, causing activity limitation that are attributed to non-progressive disturbances that occurred in the developing fetal or infant brain”. Children with hemiplegic cerebral palsy learn strategies [4] and techniques leading to learnt non-use of the affected hand. Purpose of Study: Out of total population of children with cerebral palsy, about 18% children [1] are diagnosed cases of hemiplegic cerebral palsy as per the statistical data available in the Indian Journal of Paediatrics. G. Cioni [15] in his study have shown that upper extremity involvement is more severe and the residual effects are prolonged. Hence, easy and suitable treatment technique is necessary that will help the patients in better recovery and early functional use of hand. Aim of study: To study the effect of mirror therapy on hand functions in children with hemiplegic cerebral palsy. Methodology: A 5year old female patient diagnosed as hemiplegic cerebral palsy was assessed for the QUEST [Quality of Upper Extremity Skills Test] and Box and Block test. Mirror therapy was taken for 30 minutes per day for 6 days a week for 3 weeks. Activities performed by the right hand included-Grasps of cylindrical, spherical and hook pattern, Gripping activities with theraputty of green colour, Arrangement of peg board, Peg link activities, Transfer of objects. Conclusion: the pre-treatment and post treatment scores showed significant changes suggesting that mirror therapy has an effect incorporating use of affected hand for daily activities.
Visceral and Nonvisceral Angiosarcomas: Imaging Features and Clinical Correlation

Angiosarcomas are highly malignant neoplasms of vascular origin. They most commonly arise from the skin and subcutaneous soft tissue of the head and neck, with only a small percentage of tumors from the viscera. In this article, we evaluated the clinical and imaging features of angiosarcomas and compared visceral angiosarcomas with nonvisceral angiosarcomas. A comparison between angiosarcomas and hemangiopericytomas was performed as well. This study included 14 patients (7 men, 7 women, averaging 53 years) with pathologically confirmed angiosarcomas during a period of 14 years. All clinical data and images, including computed tomography (CT) images in 10 patients and magnetic resonance images (MRI) in two, were reviewed. The clinical data of angiosarcomas in the present study were also compared with those of hemangiopericytomas from our previously reported study. Visceral and nonvisceral each comprised 50% of all angiosarcomas in the study. Visceral angiosarcomas were larger at the time of diagnosis than nonvisceral angiosceral angiosarcomas. The metastatic rate was much higher for patients with visceral angiosarcomas than for those with nonvisceral angiosarcomas. The overall 2-year and 5-year survival rates were lower for patients with visceral angiosarcomas than for those with nonvisceral angiosarcomas. Most lesions were ill defined, heterogeneous, and had variable degrees and patterns of enhancement on contrast-enhanced CT images. The overall two-year survival rate for the patients with angiosarcomas and those with previously reported hemangiopericytomas were 43% and 61% respectively. Angiosarcomas were heterogeneously hypointense on T1-weighted MR images and hyperintense on T2-weighted MR images. In our report, visceral angiosarcomas were more common, had higher metastatic rates, and poorer prognosis than nonvisceral angiosarcomas. Imaging features were nonspecific to angiosarcomas but were characteristic for hypervascular tumors. The prognosis for patients with hemangiopericytomas was poorer than for those with nonvisceral angiosarcomas, but better than for those with visceral angiosarcomas.