cssi/SciSciGPT-SciSciNet huggingface dataset:
Nested Scale-Editing for Conditional Image Synthesis

We propose an image synthesis approach that provides stratified navigation in the latent code space. With a tiny amount of partial or very low-resolution image, our approach can consistently out-perform state-of-the-art counterparts in terms of generating the closest sampled image to the ground truth. We achieve this through scale-independent editing while expanding scale-specific diversity. Scale-independence is achieved with a nested scale disentanglement loss. Scale-specific diversity is created by incorporating a progressive diversification constraint. We introduce semantic persistency across the scales by sharing common latent codes. Together they provide better control of the image synthesis process. We evaluate the effectiveness of our proposed approach through various tasks, including image outpainting, image superresolution, and cross-domain image translation.
Time-of-day dependent effects of contractile activity on the phase of the skeletal muscle clock.

Key points Disruptions in circadian rhythms across an organism are associated with negative health outcomes, such as cardiometabolic and neurodegenerative diseases. Exercise has been proposed as a time cue for the circadian clock in rodents and humans In this study, we assessed the effect of a single bout of endurance exercise on the skeletal muscle clock in vivo and a bout of muscle contractions in vitro Timing of exercise or contractions influences the directional response of the muscle clock phase in vivo and in vitro Our findings demonstrate that muscle contractions, as a component of exercise, can directly modulate expression of muscle clock components in a time of day dependent manner. Abstract Exercise has been proposed to be a zeitgeber for the muscle circadian clock mechanism. However, this is not well defined and it is unknown if exercise timing induces directional shifts of the muscle clock. Our purpose herein was to assess the effect of one bout of treadmill exercise on skeletal muscle clock phase changes. We subjected PERIOD2::LUCIFERASE mice (n = 30F) to one 60-minute treadmill exercise bout at three times of day. Exercise at ZT5, 5 h after lights on, induced a phase advance (100.2 ± 25.8 min; p = 0.0002), whereas exercise at ZT11, 1 h before lights off, induced a phase delay (62.1 ± 21.1 min; p = 0.0003). Exercise at ZT17, middle of the dark phase, did not alter muscle clock phase. Exercise induces diverse systemic changes so we developed an in-vitro model system to examine effects of contractile activity on muscle clock phase. Contractions applied at peak or trough Bmal1 expression induced significant phase delays (applied at peak: 27.2 ± 10.2 min; p = 0.0017; applied at trough: 64.6 ± 6.5 min, p
Torch-Struct: Deep Structured Prediction Library

The literature on structured prediction for NLP describes a rich collection of distributions and algorithms over sequences, segmentations, alignments, and trees; however, these algorithms are difficult to utilize in deep learning frameworks. We introduce Torch-Struct, a library for structured prediction designed to take advantage of and integrate with vectorized, auto-differentiation based frameworks. Torch-Struct includes a broad collection of probabilistic structures accessed through a simple and flexible distribution-based API that connects to any deep learning model. The library utilizes batched, vectorized operations and exploits auto-differentiation to produce readable, fast, and testable code. Internally, we also include a number of general-purpose optimizations to provide cross-algorithm efficiency. Experiments show significant performance gains over fast baselines and case-studies demonstrate the benefits of the library. Torch-Struct is available at https://github.com/harvardnlp/pytorch-struct.
Redefining Accredited Investor: That’s One Small Step for the SEC, One Giant Leap for Our Economy

New ventures move our economy. Most of these ventures need additional capital to grow. They raise this capital through exempt offerings, and exempt offerings are essentially limited by the pool of accredited investors (AIs). Currently, individuals must meet either net worth or income thresholds to be considered AIs. Because of this, AIs make up only 13% of U.S. households, and only a small fraction of these households actually invest in exempt offerings. There is consensus that it is time to consider criteria besides net worth and income. Expanding the AI population by welcoming people who pass a relevant exam is a responsible way to increase the number of AIs. Even if no other securities laws or rules change, the AI exam would help ensure investor protection while generating more investment alternatives for individuals, additional capital for new ventures, and increased liquidity for the market.
Interracial contact at work: Does workplace diversity reduce bias?:

Research suggests that anti-Black bias among White Americans is persistent, pervasive, and has powerful negative effects on the lives of both Black and White Americans. Research also suggests that ...
Boomerang: Redundancy Improves Latency and Throughput in Payment-Channel Networks

In multi-path routing schemes for payment-channel networks, Alice transfers funds to Bob by splitting them into partial payments and routing them along multiple paths. Undisclosed channel balances and mismatched transaction fees cause delays and failures on some payment paths. For atomic transfer schemes, these straggling paths stall the whole transfer. We show that the latency of transfers reduces when redundant payment paths are added. This frees up liquidity in payment channels and hence increases the throughput of the network. We devise Boomerang, a generic technique to be used on top of multi-path routing schemes to construct redundant payment paths free of counterparty risk. In our experiments, applying Boomerang to a baseline routing scheme leads to 40% latency reduction and 2\({\times }\) throughput increase. We build on ideas from publicly verifiable secret sharing, such that Alice learns a secret of Bob iff Bob overdraws funds from the redundant paths. Funds are forwarded using Boomerang contracts, which allow Alice to revert the transfer iff she has learned Bob’s secret. We implement the Boomerang contract in Bitcoin Script.
Architecture Support for FPGA Multi-tenancy in the Cloud

Cloud deployments now increasingly provision FPGA accelerators as part of virtual instances. While FPGAs are still essentially single-tenant, the growing demand for hardware acceleration will inevitably lead to the need for methods and architectures supporting FPGA multi-tenancy. In this paper, we propose an architecture supporting space-sharing of FPGA devices among multiple tenants in the cloud. The proposed architecture implements a network-on-chip (NoC) designed for fast data movement and low hardware footprint. Prototyping the proposed architecture on a Xilinx Virtex Ultrascale + demonstrated near specification maximum frequency for on-chip data movement and high throughput in virtual instance access to hardware accelerators. We demonstrate similar performance compared to single-tenant deployment while increasing FPGA utilization (we achieved $6 \times$ higher FPGA utilization with our case study), which is one of the major goals of virtualization. Overall, our NoC interconnect achieved about $2 \times$ higher maximum frequency than the state-of-the-art and a bandwidth of 25.6 Gbps.
Structural insights into the Ca2+-dependent gating of the human mitochondrial calcium uniporter

Mitochondrial Ca2+ uptake is mediated by an inner mitochondrial membrane protein called the mitochondrial calcium uniporter. In humans, the uniporter functions as a holocomplex consisting of MCU, EMRE, MICU1 and MICU2, among which MCU and EMRE form a subcomplex and function as the conductive channel while MICU1 and MICU2 are EF-hand proteins that regulate the channel activity in a Ca2+-dependent manner. Here, we present the EM structures of the human mitochondrial calcium uniporter holocomplex (uniplex) in the presence and absence of Ca2+, revealing distinct Ca2+ dependent assembly of the uniplex. Our structural observations suggest that Ca2+ changes the dimerization interaction between MICU1 and MICU2, which in turn determines how the MICU1-MICU2 subcomplex interacts with the MCU-EMRE channel and, consequently, changes the distribution of the uniplex assemblies between the blocked and unblocked states.
Hobbesian causation and personal identity in the history of criminology

Hobbes is known for bridging natural and political philosophy, but less attention has been given to how this distinguishes the Hobbesian conception of the self from individualist strands of liberal...
A surface metric and software toolbox for EEG electrode grids in the macaque.

Abstract Background The past years have seen increased appreciation of electroencephalographic (EEG) recordings in non-human primates (NHP) as a tool for translational research. In humans, even large EEG electrode grids can easily and quickly be placed on standardized positions using commercially available EEG caps. In the NHP, the identification of standardized EEG electrode positions is more complicated and time-consuming. New method Here we introduce a surface metric and software package (NHP1020) that automates the planning of large, approximately evenly spaced electrode grids for EEG recordings in the NHP. Results Based on one CT and one MRI image as well as two intracranial markers, the NHP1020 software defines electrode positions on the brain surface using a surface-based spherical metric similar to the one used by the international 10-20 system. Standardized electrode grids can be shared, imported or defined with few high-level commands. Existing methods NHP EEG electrodes can be placed relative to extracranial markers and measurements or relative to underlying neural structures of interest. Both approaches are time-consuming and require manual intervention. Furthermore, the use of extracranial markers in this species may be more problematic than in humans, because cranial muscles and ridges are larger and keep maturing long into adulthood. Conclusion The presented surface metric and the NHP1020 toolbox provide fast and automated identification of entire electrode grids in the non-human primate based on a two-dimensional metric on the brain surface.
Infinite-fold enhancement in communications capacity using pre-shared entanglement

Pre-shared entanglement can significantly boost communication rates in the regime of high thermal noise, and a low-brightness transmitter. In this regime, the ratio between the entanglement-assisted capacity and the Holevo capacity, the maximum reliable-communication rate permitted by quantum mechanics without any pre-shared entanglement as a resource, is known to scale as $\log (1/{\bar N_S})$, where ${\bar N_{\text{S}}} \ll 1$ is the mean transmitted photon number per mode. This is especially promising in enabling a large boost to radio-frequency communications in the weak-transmit-power regime, by exploiting pre-shared optical-frequency entanglement, e.g., distributed by the quantum internet. In this paper, we propose a structured design of a quantum transmitter and receiver that leverages continuous-variable pre-shared entanglement from a downconversion source, which can harness this purported infinite-fold capacity enhancement— a problem that has been open for over a decade. Its implication to the breaking of the well-known square root law for covert communications, with entanglement assistance, is discussed.
Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels

We study the problem of estimation and testing in logistic regression with class-conditional noise in the observed labels, which has an important implication in the Positive-Unlabeled (PU) learning setting. With the key observation that the label noise problem belongs to a special sub-class of generalized linear models (GLM), we discuss convex and non-convex approaches that address this problem. A non-convex approach based on the maximum likelihood estimation produces an estimator with several optimal properties, but a convex approach has an obvious advantage in optimization. We demonstrate that in the low-dimensional setting, both estimators are consistent and asymptotically normal, where the asymptotic variance of the non-convex estimator is smaller than the convex counterpart. We also quantify the efficiency gap which provides insight into when the two methods are comparable. In the high-dimensional setting, we show that both estimation procedures achieve $\ell_2$-consistency at the minimax optimal $\sqrt{s\log p/n}$ rates under mild conditions. Finally, we propose an inference procedure using a de-biasing approach. We validate our theoretical findings through simulations and a real-data example.
Evaluation of Non-collocated Force Feedback Driven by Signal-independent Noise

Individuals living with paralysis or amputation can operate robotic prostheses using input signals based on their intent or attempt to move. Because sensory function is lost or diminished in these individuals, haptic feedback must be non-collocated. The intracortical brain computer interface (iBCI) has enabled a variety of neural prostheses for people with paralysis. An important attribute of the iBCI is that its input signal contains signal-independent noise. To understand the effects of signal-independent noise on a system with non-collocated haptic feedback and inform iBCI-based prostheses control strategies, we conducted an experiment with a conventional haptic interface as a proxy for the iBCI. Ablebodied users were tasked with locating an indentation within a virtual environment using input from their right hand. Non-collocated haptic feedback of the interaction forces in the virtual environment was augmented with noise of three different magnitudes and simultaneously rendered on users’ left hands. We found increases in distance error of the guess of the indentation location, mean time per trial, mean peak absolute displacement and speed of tool movements during localization for the highest noise level compared to the other two levels. The findings suggest that users have a threshold of disturbance rejection and that they attempt to increase their signal-to-noise ratio through their exploratory actions.
Control Synthesis from Linear Temporal Logic Specifications using Model-Free Reinforcement Learning

We present a reinforcement learning (RL) frame-work to synthesize a control policy from a given linear temporal logic (LTL) specification in an unknown stochastic environment that can be modeled as a Markov Decision Process (MDP). Specifically, we learn a policy that maximizes the probability of satisfying the LTL formula without learning the transition probabilities. We introduce a novel rewarding and discounting mechanism based on the LTL formula such that (i) an optimal policy maximizing the total discounted reward effectively maximizes the probabilities of satisfying LTL objectives, and (ii) a model-free RL algorithm using these rewards and discount factors is guaranteed to converge to such a policy. Finally, we illustrate the applicability of our RL-based synthesis approach on two motion planning case studies.
LSTM-TrajGAN: A Deep Learning Approach to Trajectory Privacy Protection

The prevalence of location-based services contributes to the explosive growth of individual-level trajectory data and raises public concerns about privacy issues. In this research, we propose a novel LSTM-TrajGAN approach, which is an end-to-end deep learning model to generate privacy-preserving synthetic trajectory data for data sharing and publication. We design a loss metric function TrajLoss to measure the trajectory similarity losses for model training and optimization. The model is evaluated on the trajectory-user-linking task on a real-world semantic trajectory dataset. Compared with other common geomasking methods, our model can better prevent users from being re-identified, and it also preserves essential spatial, temporal, and thematic characteristics of the real trajectory data. The model better balances the effectiveness of trajectory privacy protection and the utility for spatial and temporal analyses, which offers new insights into the GeoAI-powered privacy protection.
On card guessing game with one time riffle shuffle and complete feedback

Abstract This paper studies the game of guessing riffle-shuffled cards with complete feedback. A deck of n cards labeled 1 to n is riffle-shuffled once and placed on a table. A player tries to guess the cards from top and is given complete feedback after each guess. The goal is to find the guessing strategy with maximum reward (expected number of correct guesses). We give the optimal strategy for this game and prove that the maximum expected reward is n ∕ 2 + 2 ∕ π ⋅ n + O ( 1 ) , partially solving an open problem of Bayer and Diaconis (Bayer and Diaconis, 1992).
Microscopic Review of Nasopharyngeal Swabs as a Means of Benchside Quality Assurance.

Objective Nasopharyngeal swabs (NPS) are the collection modality of choice for reverse-transcription polymerase chain reaction (RT-PCR) multiplex array for respiratory viruses. NPS gather both extracellular material and human respiratory epithelial cells and, when used with RT-PCR, have reliable sensitivity for detection of viral infection. Goals At our institution, we identified a 1.7% re-order rate within 7-days for NPS destined for RT-PCR respiratory pathogen multiplex, which we hypothesize may be due in part to low confidence in adequate collection. We sought an inexpensive and accessible strategy for benchside quality assurance of NPS adequacy by observing microscopic content of viral transport media. Procedure For eight-hundred one NPS samples collected during routine clinical practice in November 2019, aliquots of viral transport media were air-dried and safranin-stained on glass slides under a fume hood. We then counted morphologically distinct ciliated columnar epithelial cells (CCEs), which are prevalent in the nasopharynx. Results Twenty percent of samples negative for respiratory pathogens by RT-PCR (BioFire FilmArray RP2, Cepheid GeneXpert) had no CCEs, while just seven percent of positive samples had no CCEs. Pearson's Chi-squared test was used to compare presence of CCEs between samples that were positive and negative for respiratory pathogens by RT-PCR (p=1.6×10-36). Conclusion We posit that samples without identifiable CCEs have a greater likelihood of inadequate collection. The basic, benchside protocol that we describe here demonstrates potential to reduce unnecessary re-testing when deployed to confirm negative tests despite high clinical suspicion: a strategy which may help conserve NPS reagents.
Simulation-Based Performance Prediction of HPC Applications: A Case Study of HPL

We propose a simulation-based approach for performance modeling of parallel applications on high-performance computing platforms. Our approach enables full-system performance modeling: (1) the hardware platform is represented by an abstract yet high-fidelity model; (2) the computation and communication components are simulated at a functional level, where the simulator allows the use of the components native interface; this results in a (3) fast and accurate simulation of full HPC applications with minimal modifications to the application source code. This hardware/software hybrid modeling methodology allows for low overhead, fast, and accurate exascale simulation and can be easily carried out on a standard client platform (desktop or laptop). We demonstrate the capability and scalability of our approach with High Performance LINPACK (HPL), the benchmark used to rank supercomputers in the TOP500 list. Our results show that our modeling approach can accurately and efficiently predict the performance of HPL at the scale of the TOP500 list supercomputers. For instance, the simulation of HPL on Frontera takes less than five hours with an error rate of four percent.
A k-NN METHOD TO CLASSIFY RARE ASTRONOMICAL SOURCES: PHOTOMETRIC SEARCH OF BROWN DWARFS WITH SPITZER/IRAC

We present a statistical method for the photometric search of rare astronomical sources based on the weighted k-Nearest Neighbors method. A metric is defined in a multidimensional color-magnitude space based only on the photometric properties of template sources and the photometric uncertainties of both templates and data, without the need to define ad hoc color and magnitude cuts which could bias the search. The metric is defined as a function of two parameters, the number of neighbors k and a threshold distance D th that can be optimized for maximum selection efficiency and completeness. We apply the method to the search of L and T dwarfs in the Spitzer Extragalactic First Look Survey and the Bootes field of the Spitzer Shallow Survey, as well as to the search of substellar mass companions around nearby stars. With high level of completeness, we confirm the absence of late-T dwarfs detected in at least two bands in the First Look Survey, and only one in the Shallow Survey (previously discovered by Stern et al.). This result is in agreement with the expected statistics for late-T dwarfs. One L/early-T candidate is found in the First Look Survey, and three in the Shallow Surveys, currently undergoing follow-up spectroscopic verification. Finally, we discuss the potential for brown dwarf searches with this method in the Spitzer warm mission Exploration Science programs.
Eulerian Method for Multiphase Interactions of Soft Solid Bodies in Fluids

We introduce an Eulerian approach for problems involving one or more soft solids immersed in a fluid, which permits mechanical interactions between all phases. The reference map variable is exploited to simulate finite-deformation constitutive relations in the solid(s) on the same fixed grid as the fluid phase, which greatly simplifies the coupling between phases. Our coupling procedure, a key contribution in the current work, is shown to be computationally faster and more stable than an earlier approach, and admits the ability to simulate both fluid--solid and solid--solid interaction between submerged bodies. The interface treatment is demonstrated with multiple examples involving a weakly compressible Navier--Stokes fluid interacting with a neo-Hookean solid, and we verify the method's convergence. The solid contact method, which exploits distance-measures already existing on the grid, is demonstrated with two examples. A new, general routine for cross-interface extrapolation is introduced and used as part of the new interfacial treatment.
Hydrodynamic Studies of the Evolution of Recurrent, Symbiotic and Dwarf Novae: the White Dwarf Components are Growing in Mass

Symbiotic binaries are systems containing white dwarfs (WDs) and red giants. Symbiotic novae are those systems in which thermonuclear eruptions occur on the WD components. These are to be distinguished from events driven by accretion disk instabilities analogous to dwarf novae eruptions in cataclysmic variable outbursts. Another class of symbiotic systems are those in which the WD is extremely luminous and it seems likely that quiescent nuclear burning is ongoing on the accreting WD. A fundamental question is the secular evolution of the WD. Do the repeated outbursts or quiescent burning in these accreting systems cause the WD to gain or lose mass? If it is gaining mass, can it eventually reach the Chandrasekhar Limit and become a supernova (a SN Ia if it can hide the hydrogen and helium in the system)? In order to better understand these systems, we have begun a new study of the evolution of Thermonuclear Runaways (TNRs) in the accreted envelopes of WDs using a variety of initial WD masses, luminosities and mass accretion rates. We use our 1-D hydro code, NOVA, which includes the new convective algorithm of Arnett, Meakin and Young, the Hix and Thielemann nuclear reaction solver, the Iliadis reaction rate library, the Timmes equation of state, and the OPAL opacities. We assume a solar composition (Lodders abundance distribution) and do not allow any mixing of accreted material with core material. This assumption strongly influences our results. We report here (1) that the WD grows in mass for all simulations so that canonical `steady burning' does not occur, and (2) that only a small fraction of the accreted matter is ejected in some (but not all) simulations. We also find that the accreting systems, before thermonuclear runaway, are too cool to be seen in X-ray searches for SN Ia progenitors.
Third-epoch Magellanic Cloud Proper Motions. II. The Large Magellanic Cloud Rotation Field in Three Dimensions

We present the first detailed assessment of the large-scale rotation of any galaxy based on full three-dimensional velocity measurements. We do this for the LMC by combining our Hubble Space Telescope average proper motion (PM) measurements for stars in 22 fields, with existing line-of-sight (LOS) velocity measurements for 6790 individual stars. We interpret these data with a model of circular rotation in a flat disk. The PM and LOS data paint a consistent picture of the LMC rotation, and their combination yields several new insights. The PM data imply a stellar dynamical center that coincides with the H I dynamical center, and a rotation curve amplitude consistent with that inferred from LOS velocity studies. The implied disk viewing angles agree with the range of values found in the literature, but continue to indicate variations with stellar population and/or radius. Young (red supergiant) stars rotate faster than old (red and asymptotic giant branch) stars due to asymmetric drift. Outside the central region, the circular velocity is approximately flat at V {sub circ} = 91.7 ± 18.8 km s{sup –1}. This is consistent with the baryonic Tully-Fisher relation and implies an enclosed mass M(8.7 kpc) = (1.7 ± 0.7) × 10{sup 10}more » M {sub ☉}. The virial mass is larger, depending on the full extent of the LMC's dark halo. The tidal radius is 22.3 ± 5.2 kpc (24.°0 ± 5.°6). Combination of the PM and LOS data yields kinematic distance estimates for the LMC, but these are not yet competitive with other methods.« less
Ternary mixed-anion semiconductors with tunable band gaps from machine-learning and crystal structure prediction

We report the computational investigation of a series of ternary ${X}_{4}{Y}_{2}Z$ and ${X}_{5}{Y}_{2}{Z}_{2}$ compounds with $X$=Mg, Ca, Sr, Ba; $Y$=P, As, Sb, Bi; and $Z$=S, Se, Te. The compositions for these materials were predicted through a search guided by machine learning, while the structures were resolved using the minima hopping crystal structure prediction method. Based on ab initio calculations, we predict that many of these phases are thermodynamically stable. In particular, 21 of the ${X}_{4}{Y}_{2}Z$ compounds crystallize in a tetragonal structure with $I\overline{4}2d$ symmetry, and exhibit band gaps in the range of 0.8 and 1.8 eV, well suited for various energy applications. We show that several candidates (in particular ${X}_{4}{Y}_{2}\mathrm{Te}$ and ${X}_{4}{\mathrm{Sb}}_{2}\mathrm{Se}$) exhibit good photo absorption in the visible range, while others (e.g., ${\mathrm{Ba}}_{4}{\mathrm{Sb}}_{2}\mathrm{Se}$) show excellent thermoelectric performance due to high power factors and extremely low lattice thermal conductivities.
Affine theory of gravitation

We propose a theory of gravitation, in which the affine connection is the only dynamical variable describing the gravitational field. We construct a simple dynamical Lagrangian density that is entirely composed from the connection, via its curvature and torsion, and is a polynomial function of its derivatives. It is given by the contraction of the Ricci tensor with a tensor which is inverse to the symmetric, contracted square of the torsion tensor, \(k_{\mu \nu }=S^\rho _{\lambda \mu }S^\lambda _{\rho \nu }\). We vary the total action for the gravitational field and matter with respect to the affine connection, assuming that the matter fields couple to the connection only through \(k_{\mu \nu }\). We derive the resulting field equations and show that they are identical with the Einstein equations of general relativity with a nonzero cosmological constant if the tensor \(k_{\mu \nu }\) is regarded as proportional to the metric tensor. The cosmological constant is simply a constant of proportionality between the two tensors, which together with \(c\) and \(G\) provides a natural system of units in gravitational physics. This theory therefore provides a physical construction of the metric as a polynomial function of the connection, and explains dark energy as an intrinsic property of spacetime.
The stability of noncommutative scalar solitons

We determine the stability conditions for a radially symmetric non-commutative scalar soliton at finite noncommutivity parameter θ. We find an intriguing relationship between the stability and existence conditions for all level-1 solutions, in that they all have nearly-vanishing stability eigenvalues at critical θm2. The stability or non-stability of the system may then be determined entirely by the 3 coefficient in the potential. For higher-level solutions we find an ambiguity in extrapolating solutions to finite θ which prevents us from making any general statements. For these stability may be determined by comparing the fluctuation eigenvalues to critical values which we calculate.
Perturbations of a stringy black hole

We extend the three-dimensional stringy black hole of Horne and Horowitz to four dimensions. After a brief discussion of the global properties of the metric, we discuss the stability of the background with respect to small perturbations, following the methods of Gilbert and of Chandrasekhar. The potential for axial perturbations is found to be positive definite.
Conditioning of Random Block Subdictionaries With Applications to Block-Sparse Recovery and Regression

The linear model, in which a set of observations is assumed to be given by a linear combination of columns of a matrix (often termed a dictionary), has long been the mainstay of the statistics and signal processing literature. One particular challenge for inference under linear models is understanding the conditions on the dictionary under which reliable inference is possible. This challenge has attracted renewed attention in recent years, since many modern inference problems (e.g., high-dimensional statistics and compressed sensing) deal with the underdetermined setting, in which the number of observations is much smaller than the number of columns in the dictionary. This paper makes several contributions for this setting when the set of observations is given by a linear combination of a small number of groups of columns of the dictionary, termed the block-sparse case. First, it specifies conditions on the dictionary under which most block submatrices of the dictionary (often termed block subdictionaries) are well conditioned. This result is fundamentally different from prior work on block-sparse inference because: 1) it provides conditions that can be explicitly computed in polynomial time; 2) the given conditions translate into near-optimal scaling of the number of columns of the block subdictionaries as a function of the number of observations for a large class of dictionaries; and 3) it suggests that the spectral norm, rather than the column/block coherences of the dictionary, fundamentally limits the scaling of dimensions of the well-conditioned block subdictionaries. Second, in order to help understand the significance of this result in the context of block-sparse inference, this paper investigates the problems of block-sparse recovery and block-sparse regression in underdetermined settings. In both of these problems, this paper utilizes its result concerning conditioning of block subdictionaries and establishes that near-optimal block-sparse recovery and block-sparse regression is possible for a large class of dictionaries as long as the dictionary satisfies easily computable conditions and the coefficients describing the linear combination of groups of columns can be modeled through a mild statistical prior. Third, the paper reports extensive numerical experiments that highlight the effects of different measures of the dictionary in block-sparse inference problems.
Is the magnitude of the Peccei–Quinn scale set by the landscape?

The value of the Higgs boson mass plus the lack of signal at LHC13 has led to a naturalness crisis for supersymmetric models. In contrast, rather general considerations of the string theory landscape imply a mild statistical draw towards large soft SUSY breaking terms tempered by the requirement of proper electroweak symmetry breaking where SUSY contributions to the weak scale are not too far from $$m_{weak}\sim 100$$ GeV. Such a picture leads to the prediction that $$m_h\simeq 125$$ GeV while most sparticles are beyond current LHC reach. Here we explore the possibility that the magnitude of the Peccei–Quinn (PQ) scale $$f_a$$ is also set by string landscape considerations within the framework of a compelling SUSY axion model. First, we examine the case where the PQ symmetry arises as an accidental approximate global symmetry from a more fundamental gravity-safe $$\mathbb {Z}_{24}^R$$ symmetry and where the SUSY $$\mu $$ parameter arises from a Kim-Nilles operator. The pull towards large soft terms then also pulls the PQ scale as large as possible. Unless this is tempered by rather severe (unknown) cosmological or anthropic bounds on the density of dark matter, then we would expect a far greater abundance of dark matter than is observed. This conclusion cannot be negated by adopting a tiny axion misalignment angle $$\theta _i$$ because WIMPs are also overproduced at large $$f_a$$. Hence, we conclude that setting the PQ scale via anthropics is highly unlikely. Instead, requiring soft SUSY breaking terms of order the gravity-mediation scale $$m_{3/2}\sim 10$$–100 TeV places the mixed axion–neutralino dark matter abundance into the intermediate scale sweet zone where $$f_a\sim 10^{11}$$–$$10^{12}$$ GeV. We compare our analysis to the more general case of a generic SUSY DFSZ axion model with uniform selection on $$\theta _i$$ but leading to the measured dark matter abundance: this approach leads to a preference for $$f_a\sim 10^{12}$$ GeV.
The Influence of T Cell Development on Pathogen Specificity and Autoreactivity

T cells orchestrate adaptive immune responses upon activation. T cell activation requires sufficiently strong binding of T cell receptors on their surface to short peptides derived from foreign proteins bound to protein products of the major histocompatibility (MHC) gene products, which are displayed on the surface of antigen presenting cells. T cells can also interact with peptide-MHC complexes, where the peptide is derived from host (self) proteins. A diverse repertoire of relatively self-tolerant T cell receptors is selected in the thymus. We study a model, computationally and analytically, to describe how thymic selection shapes the repertoire of T cell receptors, such that T cell receptor recognition of pathogenic peptides is both specific and degenerate. We also discuss the escape probability of autoimmune T cells from the thymus.
Universal Thermal Corrections to Entanglement Entropy for Conformal Field Theories on Spheres

We consider entanglement entropy of a cap-like region for a conformal field theory living on a sphere times a circle in d space-time dimensions. Assuming that the finite size of the system introduces a unique ground state with a nonzero mass gap, we calculate the leading correction to the entanglement entropy in a low temperature expansion. The correction has a universal form for any conformal field theory that depends only on the size of the mass gap, its degeneracy, and the angular size of the cap. We confirm our result by calculating the entanglement entropy of a conformally coupled scalar numerically. We argue that an apparent discrepancy for the scalar can be explained away through a careful treatment of boundary terms. In an appendix, to confirm the accuracy of the numerics, we study the mutual information of two cap-like regions at zero temperature.
Evidence for an Accelerating Wind as the Broad-Line Region in NGC 3516

Spectroscopic data in wavelengths 900-3000 A have been obtained in a low flux state of the nucleus of the Seyfert 1 galaxy NGC 3516. The line profiles show P Cygni characteristics, particularly in O VI λ1032, and are compared with data from an earlier and higher state. The profiles are suggestive of and consistent with an accelerating wind driven by a disk continuum source in which the ionization radii have changed. This scenario may apply to the formation of other broad emission lines in active galactic nuclei.
A regime of linear stability for the Einstein-scalar field system with applications to nonlinear Big Bang formation

We linearize the Einstein-scalar field equations, expressed relative to constant mean curvature (CMC)-transported spatial coordinates gauge, around members of the well-known family of Kasner solutions on (0,∞)×T. The Kasner solutions model a spatially uniform scalar field evolving in a (typically) spatially anisotropic spacetime that expands towards the future and that has a “Big Bang” singularity at {t = 0}. We place initial data for the linearized system along {t = 1} ≃ T and study the linear solution’s behavior in the collapsing direction t ↓ 0. Our main result is the identification of a new form of approximate L monotonicity for the linear solutions that holds whenever the background Kasner solution is sufficiently close to the Friedmann-Lemaitre-Robertson-Walker (FLRW) solution. Using the approximate monotonicity, we derive sharp information about the asymptotic behavior of the linear solution as t ↓ 0. In particular, we show that some of its time-rescaled components converge to regular functions defined along {t = 0}. In addition, we motivate the preferred direction of the approximate monotonicity by showing that the CMCtransported spatial coordinates gauge can be realized as a limiting version of a family of parabolic gauges for the lapse variable. An approximate L monotonicity inequality also holds in the parabolic gauges, but the corresponding parabolic PDEs are locally well-posed only in the direction t ↓ 0. In a companion article, we use the linear stability results to prove a stable singularity formation result for the nonlinear equations. Specifically, we show that the FLRW solution is globally nonlinearly stable in the collapsing direction t ↓ 0 under small perturbations of its data at {t = 1}.
Galois theory of iterated endomorphisms

Given an abelian algebraic group A over a global field F, � 2 A(F), and a prime `, the set of all preimages ofunder some iterate of (`) generates an extension of F that contains all `-power torsion points as well as a Kummer-type extension. We analyze the Galois group of this extension, and for several classes of A we give a simple characterization of when the Galois group is as large as possible up to constraints imposed by the endomorphism ring or the Weil pairing. This Galois group encodes information about the density of primes p in the ring of integers of F such that the order of (� mod p) is prime to `. We compute this density in the general case for several classes of A, including elliptic curves and one-dimensional tori. For example, if F is a number field, A=F is an elliptic curve with surjective 2-adic representation and � 2 A(F) with � 㘲 2A(F(A(4))), then the density of p with (� mod p) having odd order is 11=21.
A VLA SURVEY FOR FAINT COMPACT RADIO SOURCES IN THE ORION NEBULA CLUSTER

National Science Foundation Graduate Research Fellowship [2012115762]; NSF AAG [1311910]; NASA's Science Mission Directorate
Quasiclassical theory of electronic transport in mesoscopic systems: Luttinger liquids revisited

The method of the quasiclassical Green's function is used to determine the equilibrium properties of one-dimensional (1D) interacting Fermi systems, in particular, the bulk and the local (near a hard wall) density of states. While this is a novel approach to 1D systems, our findings do agree with standard results for Luttinger liquids obtained with the bosonization method. Analogies to the so-called P(E) theory of tunneling through ultrasmall junctions are pointed out and are exploited. Further applications of the Green's function method for ID systems are discussed.
Getting in shape and swimming: the role of cortical forces and membrane heterogeneity in eukaryotic cells.

Recent research has shown that motile cells can adapt their mode of propulsion to the mechanical properties of the environment in which they find themselves—crawling in some environments while swimming in others. The latter can involve movement by blebbing or other cyclic shape changes, and both highly-simplified and more realistic models of these modes have been studied previously. Herein we study swimming that is driven by membrane tension gradients that arise from flows in the actin cortex underlying the membrane, and does not involve imposed cyclic shape changes. Such gradients can lead to a number of different characteristic cell shapes, and our first objective is to understand how different distributions of membrane tension influence the shape of cells in an inviscid quiescent fluid. We then analyze the effects of spatial variation in other membrane properties, and how they interact with tension gradients to determine the shape. We also study the effect of fluid–cell interactions and show how tension leads to cell movement, how the balance between tension gradients and a variable bending modulus determine the shape and direction of movement, and how the efficiency of movement depends on the properties of the fluid and the distribution of tension and bending modulus in the membrane.
On a conjecture of Dobrinen and Simpson concerning almost everywhere domination

Dobrinen and Simpson [4] introduced the notions of almost everywhere domination and uniform almost everywhere domination to study recursion theoretic analogues of results in set theory concerning domination in generic extensions of transitive models of ZFC and to study regularity properties of the Lebesgue measure on 2 ω in reverse mathematics. In this article, we examine one of their conjectures concerning these notions. Throughout this article, ≤ T denotes Turing reducibility and μ denotes the Lebesgue (or “fair coin”) probability measure on 2 ω given by A property holds almost everywhere or for almost all X ∈ 2 ω if it holds on a set of measure 1. For f, g ∈ ω ω , f dominatesg if ∃ m ∀ n m (f( n ) > g ( n )). (Dobrinen, Simpson). A set A ∈ 2 ω is almost everywhere (a.e.) dominating if for almost all X ∈ 2 ω and all functions g ≤ T X , there is a function f ≤ T A such that f dominates g . A is uniformly almost everywhere (u.a.e.) dominating if there is a function f ≤ T A such that for almost all X ∈ 2 ω and all functions g ≤ T X, f dominates g . There are several trivial but useful observations to make about these definitions. First, although these properties are stated for sets, they are also properties of Turing degrees. That is, a set is (u.)a.e. dominating if and only if every other set of the same degree is (u.)a.e. dominating. Second, both properties are closed upwards in the Turing degrees. Third, u.a.e. domination implies a.e. domination. Finally, if A is u.a.e. dominating, then there is a function f ≤ T A which dominates every computable function.
Absolute Dimensions of the Eccentric Eclipsing Binary V541 Cygni

We report new spectroscopic and photometric observations of the main-sequence, detached, eccentric, double-lined eclipsing binary V541 Cyg (P = 15.34 days, e = 0.468). Using these observations together with existing measurements we determine the component masses and radii to better than 1% precision: M1 = 2.335 +0.017/-0.013 MSun, M2 = 2.260 +0.016/-0.013 MSun, R1 = 1.859 +0.012/-0.009 RSun, and R2 = 1.808 +0.015/-0.013 RSun. The nearly identical B9.5 stars have estimated temperatures of 10650 +/- 200 K and 10350 +/- 200 K. A comparison of these properties with current stellar evolution models shows excellent agreement at an age of about 190 Myr and [Fe/H] approximately -0.18. Both components are found to be rotating at the pseudo-synchronous rate. The system displays a slow periastron advance that is dominated by General Relativity (GR), and has previously been claimed to be slower than predicted by theory. Our new measurement, dw/dt = 0.859 +0.042/-0.017 deg/century, has an 88% contribution from GR and agrees with the expected rate within the uncertainties. We also clarify the use of the gravity darkening coefficients in the light-curve fitting program EBOP, a version of which we use here.
A MODERN INTRODUCTION TO QUARKONIUM THEORY

Recent advances in lattice and continuum QCD have given us new insights into quarkonium physics. These sets of lectures are intend for the uninitiated. We first give a physical picture of quarkonium and describe the hybrids states established in lattice QCD. Then we give an unorthodox presentation of Nonrelativistic QCD (NRQCD) including a novel method for the application of spin-symmetries. Finally we describe the prototypical application of NRQCD: cancellation of infrared divergences in decays of P wave quarkonia.
ATD: Anomalous Topic Discovery in High Dimensional Discrete Data

We propose an algorithm for detecting patterns exhibited by anomalous clusters in high dimensional discrete data. Unlike most anomaly detection (AD) methods, which detect individual anomalies, our proposed method detects groups ( clusters ) of anomalies; i.e., sets of points which collectively exhibit abnormal patterns. In many applications, this can lead to a better understanding of the nature of the atypical behavior and to identifying the sources of the anomalies. Moreover, we consider the case where the atypical patterns exhibit on only a small (salient) subset of the very high dimensional feature space. Individual AD techniques and techniques that detect anomalies using all the features typically fail to detect such anomalies, but our method can detect such instances collectively, discover the shared anomalous patterns exhibited by them, and identify the subsets of salient features. In this paper, we focus on detecting anomalous topics in a batch of text documents, developing our algorithm based on topic models. Results of our experiments show that our method can accurately detect anomalous topics and salient features (words) under each such topic in a synthetic data set and two real-world text corpora and achieves better performance compared to both standard group AD and individual AD techniques. All required code to reproduce our experiments is available from https://github.com/hsoleimani/ATD .
Normal amenable subgroups of the automorphism group of sofic shifts

Let be a transitive sofic shift and let denote its automorphism group. We generalize a result of Frisch, Schlank, and Tamuz to show that any normal amenable subgroup of must be contained in the subgroup generated by the shift. We also show that the result does not extend to higher dimensions by giving an example of a two-dimensional mixing shift of finite type due to Hochman whose automorphism group is amenable and not generated by the shift maps.