cssi/SciSciGPT-SciSciNet huggingface dataset:
Geometry-aware domain adaptation for unsupervised alignment of word embeddings.

We propose a novel manifold based geometric approach for learning unsupervised alignment of word embeddings between the source and the target languages. Our approach formulates the alignment learning problem as a domain adaptation problem over the manifold of doubly stochastic matrices. This viewpoint arises from the aim to align the second order information of the two language spaces. The rich geometry of the doubly stochastic manifold allows to employ efficient Riemannian conjugate gradient algorithm for the proposed formulation. Empirically, the proposed approach outperforms state-of-the-art optimal transport based approach on the bilingual lexicon induction task across several language pairs. The performance improvement is more significant for distant language pairs.
Defending Against Model Stealing Attacks With Adaptive Misinformation

Deep Neural Networks (DNNs) are susceptible to model stealing attacks, which allows a data-limited adversary with no knowledge of the training dataset to clone the functionality of a target model, just by using black-box query access. Such attacks are typically carried out by querying the target model using inputs that are synthetically generated or sampled from a surrogate dataset to construct a labeled dataset. The adversary can use this labeled dataset to train a clone model, which achieves a classification accuracy comparable to that of the target model. We propose "Adaptive Misinformation" to defend against such model stealing attacks. We identify that all existing model stealing attacks invariably query the target model with Out-Of-Distribution (OOD) inputs. By selectively sending incorrect predictions for OOD queries, our defense substantially degrades the accuracy of the attacker's clone model (by up to 40%), while minimally impacting the accuracy (<0.5%) for benign users. Compared to existing defenses, our defense has a significantly better security vs accuracy trade-off and incurs minimal computational overhead.
Reward-Free Exploration for Reinforcement Learning

Exploration is widely regarded as one of the most challenging aspects of reinforcement learning (RL), with many naive approaches succumbing to exponential sample complexity. To isolate the challenges of exploration, we propose a new “reward-free RL” framework. In the exploration phase, the agent first collects trajectories from an MDP M without a pre-specified reward function. After exploration, it is tasked with computing near-optimal policies under for M for a collection of given reward functions. This framework is particularly suitable when there are many reward functions of interest, or when the reward function is shaped by an external agent to elicit desired behavior. We give an efficient algorithm that conducts O(S2Apoly(H)/ϵ2) episodes of exploration and returns ϵ-suboptimal policies for an arbitrary number of reward functions. We achieve this by finding exploratory policies that visit each “significant” state with probability proportional to its maximum visitation probability under any possible policy. Moreover, our planning procedure can be instantiated by any black-box approximate planner, such as value iteration or natural policy gradient. We also give a nearly-matching Ω(S2AH2/ϵ2) lower bound, demonstrating the near-optimality of our algorithm in this setting.
Total Positivity in Springer Fibres

Let u be a unipotent element in the totally positive part of a complex reductive group. We consider the intersection of the Springer fibre at u with the totally positive part of the flag manifold. We show that this intersection has a natural cell decomposition which is part of the cell decomposition (Rietsch) of the totally positive flag manifold.
Deep Transfer Learning For Plant Center Localization

Plant phenotyping focuses on the measurement of plant characteristics throughout the growing season, typically with the goal of evaluating genotypes for plant breeding. Estimating plant location is important for identifying genotypes which have low emergence, which is also related to the environment and management practices such as fertilizer applications. The goal of this paper is to investigate methods that estimate plant locations for a field-based crop using RGB aerial images captured using Unmanned Aerial Vehicles (UAVs). Deep learning approaches provide promising capability for locating plants observed in RGB images, but they require large quantities of labeled data (ground truth) for training. Using a deep learning architecture fine-tuned on a single field or a single type of crop on fields in other geographic areas or with other crops may not have good results. The problem of generating ground truth for each new field is labor-intensive and tedious. In this paper, we propose a method for estimating plant centers by transferring an existing model to a new scenario using limited ground truth data. We describe the use of transfer learning using a model fine-tuned for a single field or a single type of plant on a varied set of similar crops and fields. We show that transfer learning provides promising results for detecting plant locations.
The devil in the details: A tutorial review on some undervalued aspects of density functional theory calculations

Density functional theory, or DFT, has become ubiquitous for chemical applications in research and in education. The exact functional at the foundation of DFT is unfortunately unknown, and issues arise when choosing an approximation for a specific application. With this tutorial review, we tackle the selection problem and many related ones, such as the choices of a basis set and of an integration grid, that are often overlooked by occasional practitioners and by more experienced users as well. We offer a practical approach in the form of a commented notebook containing 12 experiments that can be run on a simple computer in just a few hours. We propose this review as a primary source for those who are willing to include DFT in their everyday research or teaching activities in a way that reflects the research advances of the field in the last couple of decades
Innovation, short-termism, and the cost of strong corporate governance

Research Summary Do the performance pressures of the capital market exacerbate short‐termism and stifle innovation? This longstanding question has doggedly eluded a conclusive answer due to conflicting empirical findings. We revisit two studies that have been central to rejecting short‐termism: Atanassov (2013) and its replication by Karpoff and Wittry (2018). After revising some of the empirical choices by Atanassov (2013), we find the opposite result: antitakeover laws that insulate managers from the market for corporate control enhance innovation, driven by firms with significant ownership by short‐term oriented investors. However, antitakeover laws do exacerbate the pursuit of value‐destroying acquisitions. Our findings highlight corporate governance as a strategic variable that imposes a tradeoff in disciplining different agency conflicts and weak governance as a necessary evil to stimulate innovation. Managerial Summary We present evidence that shareholder pressure indeed exacerbates short‐termism and stifles innovation, especially in firms with significant ownership by short‐term oriented investors. One key implication is that calls to reduce managerial entrenchment and hold managers more accountable to shareholders warrant careful consideration. While curbing other forms of agency conflict, such as managerial shirking and the pursuit of value‐destroying acquisitions, such reforms can exacerbate the myopic focus on short‐term profits and prevent long‐term value creation. Our findings warn that it is misleading to look for universally “good” governance. There are multiple forms of agency conflict that require diametric prescriptions, and designing corporate governance should carefully consider the tradeoffs based on a firm's ownership structure and the need for innovation.
Risk of Ischemic Stroke in Patients With Coronavirus Disease 2019 (COVID-19) vs Patients With Influenza.

Importance It is uncertain whether coronavirus disease 2019 (COVID-19) is associated with a higher risk of ischemic stroke than would be expected from a viral respiratory infection. Objective To compare the rate of ischemic stroke between patients with COVID-19 and patients with influenza, a respiratory viral illness previously associated with stroke. Design, Setting, and Participants This retrospective cohort study was conducted at 2 academic hospitals in New York City, New York, and included adult patients with emergency department visits or hospitalizations with COVID-19 from March 4, 2020, through May 2, 2020. The comparison cohort included adults with emergency department visits or hospitalizations with influenza A/B from January 1, 2016, through May 31, 2018 (spanning moderate and severe influenza seasons). Exposures COVID-19 infection confirmed by evidence of severe acute respiratory syndrome coronavirus 2 in the nasopharynx by polymerase chain reaction and laboratory-confirmed influenza A/B. Main Outcomes and Measures A panel of neurologists adjudicated the primary outcome of acute ischemic stroke and its clinical characteristics, mechanisms, and outcomes. We used logistic regression to compare the proportion of patients with COVID-19 with ischemic stroke vs the proportion among patients with influenza. Results Among 1916 patients with emergency department visits or hospitalizations with COVID-19, 31 (1.6%; 95% CI, 1.1%-2.3%) had an acute ischemic stroke. The median age of patients with stroke was 69 years (interquartile range, 66-78 years); 18 (58%) were men. Stroke was the reason for hospital presentation in 8 cases (26%). In comparison, 3 of 1486 patients with influenza (0.2%; 95% CI, 0.0%-0.6%) had an acute ischemic stroke. After adjustment for age, sex, and race, the likelihood of stroke was higher with COVID-19 infection than with influenza infection (odds ratio, 7.6; 95% CI, 2.3-25.2). The association persisted across sensitivity analyses adjusting for vascular risk factors, viral symptomatology, and intensive care unit admission. Conclusions and Relevance In this retrospective cohort study from 2 New York City academic hospitals, approximately 1.6% of adults with COVID-19 who visited the emergency department or were hospitalized experienced ischemic stroke, a higher rate of stroke compared with a cohort of patients with influenza. Additional studies are needed to confirm these findings and to investigate possible thrombotic mechanisms associated with COVID-19.
Facets of Fairness in Search and Recommendation

Several recent works have highlighted how search and recommender systems exhibit bias along different dimensions. Counteracting this bias and bringing a certain amount of fairness in search is crucial to not only creating a more balanced environment that considers relevance and diversity but also providing a more sustainable way forward for both content consumers and content producers. This short paper examines some of the recent works to define relevance, diversity, and related concepts. Then, it focuses on explaining the emerging concept of fairness in various recommendation settings. In doing so, this paper presents comparisons and highlights contracts among various measures, and gaps in our conceptual and evaluative frameworks.
An Introduction to Complex Systems Science and its Applications

The standard assumptions that underlie many conceptual and quantitative frameworks do not hold for many complex physical, biological, and social systems. Complex systems science clarifies when and why such assumptions fail and provides alternative frameworks for understanding the properties of complex systems. This review introduces some of the basic principles of complex systems science, including complexity profiles, the tradeoff between efficiency and adaptability, the necessity of matching the complexity of systems to that of their environments, multiscale analysis, and evolutionary processes. Our focus is on the general properties of systems as opposed to the modeling of specific dynamics; rather than provide a comprehensive review, we pedagogically describe a conceptual and analytic approach for understanding and interacting with the complex systems of our world. This paper assumes only a high school mathematical and scientific background so that it may be accessible to academics in all fields, decision-makers in industry, government, and philanthropy, and anyone who is interested in systems and society.
Learning Halfspaces with Massart Noise Under Structured Distributions

We study the problem of learning halfspaces with Massart noise in the distribution-specific PAC model. We give the first computationally efficient algorithm for this problem with respect to a broad family of distributions, including log-concave distributions. This resolves an open question posed in a number of prior works. Our approach is extremely simple: We identify a smooth non-convex surrogate loss with the property that any approximate stationary point of this loss defines a halfspace that is close to the target halfspace. Given this structural result, we can use SGD to solve the underlying learning problem.
Genome-Wide Mutagenesis Identifies Factors Involved in Enterococcus faecalis Vaginal Adherence and Persistence

ABSTRACT Enterococcus faecalis is a Gram-positive commensal bacterium native to the gastrointestinal tract and an opportunistic pathogen of increasing clinical concern. E. faecalis also colonizes the female reproductive tract, and reports suggest vaginal colonization increases following antibiotic treatment or in patients with aerobic vaginitis. Currently, little is known about specific factors that promote E. faecalis vaginal colonization and subsequent infection. We modified an established mouse vaginal colonization model to explore E. faecalis vaginal carriage and demonstrate that both vancomycin-resistant and -sensitive strains colonize the murine vaginal tract. Following vaginal colonization, we observed E. faecalis in vaginal, cervical, and uterine tissue. A mutant lacking endocarditis- and biofilm-associated pili (Ebp) exhibited a decreased ability to associate with human vaginal and cervical cells in vitro but did not contribute to colonization in vivo. Thus, we screened a low-complexity transposon (Tn) mutant library to identify novel genes important for E. faecalis colonization and persistence in the vaginal tract. This screen revealed 383 mutants that were underrepresented during vaginal colonization at 1, 5, and 8 days postinoculation compared to growth in culture medium. We confirmed that mutants deficient in ethanolamine catabolism or in the type VII secretion system were attenuated in persisting during vaginal colonization. These results reveal the complex nature of vaginal colonization and suggest that multiple factors contribute to E. faecalis persistence in the reproductive tract.
A Trimeric Autotransporter Enhances Biofilm Cohesiveness in Yersinia pseudotuberculosis but Not in Yersinia pestis.

ABSTRACT Cohesion of biofilms made by Yersinia pestis and Yersinia pseudotuberculosis has been attributed solely to an extracellular polysaccharide matrix encoded by the hms genes (Hms-dependent extracellular matrix [Hms-ECM]). However, mutations in the Y. pseudotuberculosis BarA/UvrY/CsrB regulatory cascade enhance biofilm stability without dramatically increasing Hms-ECM production. We found that treatment with proteinase K enzyme effectively destabilized Y. pseudotuberculosiscsrB mutant biofilms, suggesting that cell-cell interactions might be mediated by protein adhesins or extracellular matrix proteins. We identified an uncharacterized trimeric autotransporter lipoprotein (YPTB2394), repressed by csrB, which has been referred to as YadE. Biofilms made by a ΔyadE mutant strain were extremely sensitive to mechanical disruption. Overexpression of yadE in wild-type Y. pseudotuberculosis increased biofilm cohesion, similar to biofilms made by csrB or uvrY mutants. We found that the Rcs signaling cascade, which represses Hms-ECM production, activated expression of yadE. The yadE gene appears to be functional in Y. pseudotuberculosis but is a pseudogene in modern Y. pestis strains. Expression of functional yadE in Y. pestis KIM6+ weakened biofilms made by these bacteria. This suggests that although the YadE autotransporter protein increases Y. pseudotuberculosis biofilm stability, it may be incompatible with the Hms-ECM production that is essential for Y. pestis biofilm production in fleas. Inactivation of yadE in Y. pestis may be another instance of selective gene loss in the evolution of flea-borne transmission by this species. IMPORTANCE The evolution of Yersinia pestis from its Y. pseudotuberculosis ancestor involved gene acquisition and gene losses, leading to differences in biofilm production. Characterizing the unique biofilm features of both species may provide better understanding of how each adapts to its specific niches. This study identifies a trimeric autotransporter, YadE, that promotes biofilm stability of Y. pseudotuberculosis but which has been inactivated in Y. pestis, perhaps because it is not compatible with the Hms polysaccharide that is crucial for biofilms inside fleas. We also reveal that the Rcs signaling cascade, which represses Hms expression, activates YadE in Y. pseudotuberculosis. The ability of Y. pseudotuberculosis to use polysaccharide or YadE protein for cell-cell adhesion may help it produce biofilms in different environments.
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms

In several scientific and industrial applications, it is desirable to build compact, interpretable learning models where the output depends on a small number of input features. Recent work has show...
Throughput Maximization in Uncooperative Spectrum Sharing Networks

Throughput-optimal transmission scheduling in wireless networks has been a well considered problem in the literature, and the method for achieving optimality, MaxWeight scheduling, has been known for several decades. This algorithm achieves optimality by adaptively scheduling transmissions relative to each user’s stochastic traffic demands. To implement the method, users must report their queue backlogs to the network controller and must rapidly respond to the resulting resource allocations. However, many currently-deployed wireless systems are not able to perform these tasks and instead expect to occupy a fixed assignment of resources. To accommodate these limitations, adaptive scheduling algorithms need to interactively estimate these uncooperative users’ queue backlogs and make scheduling decisions to account for their predicted behavior. In this work, we address the problem of scheduling with uncooperative legacy systems by developing algorithms to accomplish these tasks. We begin by formulating the problem of inferring the uncooperative systems’ queue backlogs as a partially observable Markov decision process and proceed to show how our resulting learning algorithms can be successfully used in a queue-length-based scheduling policy. Our theoretical analysis characterizes the throughput-stability region of the network and is verified using simulation results.
Fundamental limits of distributed tracking

Consider the following communication scenario. An n-dlmensional source with memory is observed by K isolated encoders via parallel channels, who causally compress their observations to transmit to the decoder via noiseless rate-constrained links. At each time instant, the decoder receives K new codewords from the observers, combines them with the past received codewords, and produces a minimum- distortion estimate of the latest block of n source symbols. This scenario extends the classical one-shot CEO problem to multiple rounds of communication with communicators maintaining memory of the past.We prove a coding theorem showing that the minimum asymptotically (as n → ∞) achievable sum rate required to achieve a target distortion is equal to the directed mutual information from the observers to the decoder minimized subject to the distortion constraint and the separate encoding constraint. For the Gauss-Markov source observed via K parallel AWGN channels, we solve that minimal directed mutual information problem, thereby establishing the minimum asymptotically achievable sum rate. Finally, we explicitly bound the rate loss due to a lack of communication among the observers; that bound is attained with equality in the case of identical observation channels.The general coding theorem is proved via a new nonasymptotic bound that uses stochastic likelihood coders and whose asymptotic analysis yields an extension of the Berger-Tung inner bound to the causal setting. The analysis of the Gaussian case is facilitated by reversing the channels of the observers.
Thermodynamic costs of Turing machines

The authors analyze the minimal thermodynamic costs involved in performing computations using Turing machines. The resulting costs demonstrate the connections between statistical physics and algorithmic information theory.
Generalized Stability of Heisenberg Coefficients

Stembridge introduced the notion of stability for Kronecker triples, which generalizes Murnaghan’s classical stability result for Kronecker coefficients. Sam and Snowden proved a conjecture of Stembridge concerning stable Kronecker triples, and they also showed an analogous result for Littlewood–Richardson coefficients. Heisenberg coefficients are Schur structure constants of the Heisenberg product which generalize both Littlewood–Richardson coefficients and Kronecker coefficients. We show that any stable triple for Kronecker coefficients or Littlewood–Richardson coefficients also stabilizes Heisenberg coefficients, and we classify the triples stabilizing Heisenberg coefficients. We also follow Vallejo’s idea of using matrix additivity to generate Heisenberg stable triples.
Experiences and Lessons Learned Creating and Validating Concept Inventories for Cybersecurity

We reflect on our ongoing journey in the educational Cybersecurity Assessment Tools (CATS) Project to create two concept inventories for cybersecurity. We identify key steps in this journey and important questions we faced. We explain the decisions we made and discuss the consequences of those decisions, highlighting what worked well and what might have gone better.
The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing

Distance correlation and Hilbert-Schmidt independence criterion are widely used for independence testing, two-sample testing, and many inference tasks in statistics and machine learning. These two methods are tightly related, yet are treated as two different entities in the majority of existing literature. In this paper, we propose a simple and elegant bijection between metric and kernel. The bijective transformation better preserves the similarity structure, allows distance correlation and Hilbert-Schmidt independence criterion to be always the same for hypothesis testing, streamlines the code base for implementation, and enables a rich literature of distance-based and kernel-based methodologies to directly communicate with each other.
Divergence-Based Motivation for Online EM and Combining Hidden Variable Models.

Expectation-Maximization (EM) is a prominent approach for parameter estimation of hidden (aka latent) variable models. Given the full batch of data, EM forms an upper-bound of the negative log-likelihood of the model at each iteration and updates to the minimizer of this upper-bound. We first provide a "model level" interpretation of the EM upper-bound as sum of relative entropy divergences to a set of singleton models, induced by the set of observations. Our alternative motivation unifies the "observation level" and the "model level" view of the EM. As a result, we formulate an online version of the EM algorithm by adding an analogous inertia term which corresponds to the relative entropy divergence to the old model. Our motivation is more widely applicable than the previous approaches and leads to simple online updates for mixture of exponential distributions, hidden Markov models, and the first known online update for Kalman filters. Additionally, the finite sample form of the inertia term lets us derive online updates when there is no closed-form solution. Finally, we extend the analysis to the distributed setting where we motivate a systematic way of combining multiple hidden variable models. Experimentally, we validate the results on synthetic as well as real-world datasets.
Kinetic analysis of cellular internalization and expulsion of unstructured D-chirality cell penetrating peptides

Most cell penetrating peptides (CPPs) are unstructured and susceptible to proteolytic degradation. One alternative is to incorporate D-chirality amino acids into unstructured CPPs to allow for enhanced uptake and intracellular stability. This work investigates CPP internalization using a series of time, concentration, temperature, and energy dependent studies, resulting in a three-fold increase in uptake and 50-fold increase in stability of D-chirality peptides over L-chirality counterparts. CPP internalization occurred via a combination of direct penetration and endocytosis, with a percentage of internalized CPP expelling from cells in a time-dependent manner. Mechanistic studies identified that cells exported the intact internalized D-chirality CPPs via an exocytosis independent pathway, analogous to a direct penetration method out of the cells. These findings highlight the potential of D-chirality CPPs as bio-vectors in therapeutic and biosensing applications, but also identify a new expulsion method suggesting a relationship between uptake kinetics, intracellular stability, and export kinetics
Impact assessment of full and partial stay-at-home orders, face mask usage, and contact tracing: An agent-based simulation study of COVID-19 for an urban region.

Abstract Purpose Social intervention strategies to mitigate COVID-19 are examined using an agent-based simulation model. Outbreak in a large urban region, Miami-Dade County, Florida, USA is used as a case study. Results are intended to serve as a planning guide for decision makers. Methods The simulation model mimics daily social mixing behavior of the susceptible and infected generating the spread. Data representing demographics of the region, virus epidemiology, and social interventions shapes model behavior. Results include daily values of infected, reported, hospitalized, and dead. Results Results show that early implementation of complete stay-at-home order is effective in flattening and reversing the infection growth curve in a short period of time. Whereas, using Florida's Phase II plan alone could result in 75% infected and end of pandemic via herd immunity. Universal use of face masks reduced infected by 20%. A further reduction of 66% was achieved by adding contact tracing with a target of identifying 50% of the asymptomatic and pre-symptomatic. Conclusions In the absence of a vaccine, the strict stay-at-home order, though effective in curbing a pandemic outbreak, leaves a large proportion of the population susceptible. Hence, there should be a strong follow up plan of social distancing, use of face mask, contact tracing, testing, and isolation of infected to minimize the chances of large-scale resurgence of the disease. However, as the economic cost of the complete stay-at-home-order is very high, it can perhaps be used only as an emergency first response, and the authorities should be prepared to activate a strong follow up plan as soon as possible. The target level for contact tracing was shown to have a nonlinear impact on the reduction of the percentage of population infected. Increase in contact tracing target from 20% to 30% appeared to provide the largest incremental benefit.
The Great Inequality and the Dynamical Disintegration of the Outer Solar System

Using an ensemble of N-body simulations, this paper considers the fate of the outer gas giants (Jupiter, Saturn, Uranus, and Neptune) after the Sun leaves the main sequence and completes its stellar evolution. Due to solar mass loss—which is expected to remove roughly half of the star's mass—the orbits of the giant planets expand. This adiabatic process maintains the orbital period ratios, but the mutual interactions between planets and the width of mean-motion resonances (MMR) increase, leading to the capture of Jupiter and Saturn into a stable 5:2 resonant configuration. The expanded orbits, coupled with the large-amplitude librations of the critical MMR angle, make the system more susceptible to perturbations from stellar flyby interactions. Accordingly, within about 30 Gyr, stellar encounters perturb the planets onto the chaotic subdomain of the 5:2 resonance, triggering a large-scale instability, which culminates in the ejections of all but one planet over the subsequent ~10 Gyr. After an additional ~50 Gyr, a close stellar encounter (with a perihelion distance less than ~200 au) liberates the final planet. Through this sequence of events, the characteristic timescale over which the solar system will be completely dissolved is roughly 100 Gyr. Our analysis thus indicates that the expected dynamical lifetime of the solar system is much longer than the current age of the universe, but is significantly shorter than previous estimates.
Length spectra of flat metrics coming from q-differentials

When geometric structures on surfaces are determined by the lengths of curves, it is natural to ask: which curves' lengths do we really need to know? It is a result of Duchin--Leininger--Rafi that any flat metric induced by a unit-norm quadratic differential is determined by its marked simple length spectrum. We generalize the notion of simple curves to that of q-simple curves, for any positive integer q, and show that the lengths of q-simple curves suffice to determine a non-positively curved Euclidean cone metric induced by a q-differential.
METAL PRODUCTION IN GALAXY CLUSTERS: THE NON-GALACTIC COMPONENT

The metallicity in galaxy clusters is expected to originate from the stars in galaxies, with a population dominated by high-mass stars likely being the most important stellar component, especially in rich clusters. We examine the relationship between the metallicity and the prominence of galaxies as measured by the star-to-baryon ratio, M */M bary. Counter to expectations, we rule out a metallicity that is proportional to M */M bary, where the best fit has the gas-phase metallicity decreasing with M */M bary, or the metallicity of the gas plus the stars being independent of M */M bary. This implies that the population of stars responsible for the metals is largely proportional to the total baryonic mass of the cluster, not to the galaxy mass within the cluster. If generally applicable, most of the heavy elements in the universe were not produced within galaxies.
Neutrino oscillations in matter of varying density

We consider two-family neutrino oscillations in a medium of continuously varying density as a limit of the process in a series of constant-density layers. We find a form for the transition amplitudes that could provide new analytic solutions or could serve as numerical solutions. We test our approach with constructive analytic expressions for the conversion amplitude at high energies within a medium with a density profile that is piecewise linear. We also shed some light on effects that depend on the order of the material traversed by a neutrino beam.
Improved version of the PHOBOS Glauber Monte Carlo

“Glauber” models are used to calculate geometric quantities in the initial state of heavy ion collisions, such as impact parameter, number of participating nucleons and initial eccentricity. Experimental heavy-ion collaborations, in particular at RHIC and LHC, use Glauber Model calculations for various geometric observables for determination of the collision centrality. In this document, we describe the assumptions inherent to the approach, and provide an updated implementation (v2) of the Monte Carlo based Glauber Model calculation, which originally was used by the PHOBOS collaboration. The main improvement w.r.t. the earlier version (v1) (Alver et al. 2008) is the inclusion of Tritium, Helium-3, and Uranium, as well as the treatment of deformed nuclei and Glauber–Gribov fluctuations of the proton in p +A collisions. A users’ guide (updated to reflect changes in v2) is provided for running various calculations.
Did Fomalhaut, HR 8799, and HL Tauri Form Planets Via the Gravitational Instability? Placing Limits on the Required Disk Masses

Disk fragmentation resulting from the gravitational instability has been proposed as an efficient mechanism for forming giant planets. We use the planet Fomalhaut b, the triple-planetary system HR 8799, and the potential protoplanet associated with HL Tau to test the viability of this mechanism. We choose the above systems since they harbor planets with masses and orbital characteristics favored by the fragmentation mechanism. We do not claim that these planets must have formed as the result of fragmentation, rather the reverse: if planets can form from disk fragmentation, then these systems are consistent with what we should expect to see. We use the orbital characteristics of these recently discovered planets, along with a new technique to more accurately determine the disk cooling times, to place both lower and upper limits on the disk surface density—and thus mass—required to form these objects by disk fragmentation. Our cooling times are over an order of magnitude shorter than those of Rafikov, which makes disk fragmentation more feasible for these objects. We find that the required mass interior to the planet's orbital radius is ~0.1 M ☉ for Fomalhaut b, the protoplanet orbiting HL Tau, and the outermost planet of HR 8799. The two inner planets of HR 8799 probably could not have formed in situ by disk fragmentation.
DYSON-SCHWINGER EQUATIONS – ASPECTS OF THE PION

The contemporary use of Dyson-Schwinger equations in hadronic physics is exemplified via applications to the calculation of pseudoscalar meson masses, and inclusive deep inelastic scattering with a determination of the pion's valence-quark distribution function.
Hot Baryons and the Distribution of Metals in the Intergalactic Medium

We use the observed number and column density distributions of intergalactic O VI absorbers to constrain the distribution of metals in the low-redshift intergalactic medium (IGM). In this simple model, the metals in the O VI absorbers are assumed to be produced in and propagated from low-redshift galaxies drawn from a real sample, in this case the Sloan Digital Sky Survey. This model can explain the observed d/dz of metals borne by O VI absorbers if these metals are dispersed out to ~200 kpc by galaxies down to L ~ L. Massive galaxies (L ~ L) by themselves cannot provide the metals unless they can enrich volumes out to 0.5-1 Mpc. This model suggests that the turnover in d/dN dz below log N(O ) 13.5 (Wλ = 50 mA) is likely a real effect resulting from the apparently limited volumes over which galaxies can disperse metals, rather than a consequence of survey incompleteness. If so, it would indicate that metals are not as widespread throughout the IGM, as they are assumed to be in cosmological simulations of the warm-hot IGM. Alternatively, our model estimates the fraction of O VI absorbers directly caused by galaxies, such as the known populations of highly ionized high-velocity clouds surrounding the Milky Way, rather than the hot IGM.
New M, L, and T Dwarf Companions to Nearby Stars from the Wide-field Infrared Survey Explorer

We present 11 candidate late-type companions to nearby stars identified with data from the Wide-field Infrared Survey Explorer (WISE) and the Two Micron All Sky Survey (2MASS). Eight of the candidates are likely to be companions based on their common proper motions with the primaries. The remaining three objects are rejected as companions, one of which is a free-floating T7 dwarf. Spectral types are available for five of the companions, which consist of M2V, M8.5V, L5, T8, and T8. Based on their photometry, the unclassified companions are probably two mid-M dwarfs and one late-M/early-L dwarf. One of the T8 companions, WISE J142320.84+011638.0, has already been reported by Pinfield and coworkers. The other T8 companion, ULAS J095047.28+011734.3, was discovered by Burningham and coworkers through the United Kingdom Infrared Telescope Infrared Deep Sky Survey, but its companionship has not been previously recognized in the literature. The L5 companion, 2MASS J17430860+8526594, is a new member of a class of L dwarfs that exhibit unusually blue near-IR colors. Among the possible mechanisms that have been previously proposed for the peculiar colors of these L dwarfs, low metallicity does not appear to be a viable explanation for 2MASS J17430860+8526594 since our spectrum of the primary suggests that its metallicity is not significantly subsolar.
First-principles theory of doping in layered oxide electrode materials

Doping lithium-ion battery electrode materials $\mathrm{Li}M{\mathrm{O}}_{2}$ ($M=$ Co, Ni, Mn) with impurities has been shown to be an effective way to optimize their electrochemical properties. Here, we report a detailed first-principles study of layered oxides ${\mathrm{LiCoO}}_{2}$, ${\mathrm{LiNiO}}_{2}$, and ${\mathrm{LiMnO}}_{2}$ lightly doped with transition-metal (Fe, Co, Ni, Mn) and non-transition-metal (Mg, Al) impurities using hybrid-density-functional defect calculations. We find that the lattice site preference is dependent on both the dopant's charge and spin states, which are coupled strongly to the local lattice environment and can be affected by the presence of codopant(s), and the relative abundance of the host compound's constituting elements in the synthesis environment. On the basis of the structure and energetics of the impurities and their complexes with intrinsic point defects, we determine all possible low-energy impurity-related defect complexes, thus providing defect models for further analyses of the materials. From a materials modeling perspective, these lightly doped compounds also serve as model systems for understanding the more complex, mixed-metal, $\mathrm{Li}M{\mathrm{O}}_{2}$-based battery cathode materials.
Index-Energy Estimates for Yang–Mills Connections and Einstein Metrics

We prove a conformally invariant estimate for the index of Schrodinger operators acting on vector bundles over four-manifolds, related to the classical Cwikel–Lieb–Rozenblum estimate. Applied to Yang–Mills connections we obtain a bound for the index in terms of its energy which is conformally invariant, and captures the sharp growth rate. Furthermore we derive an index estimate for Einstein metrics in terms of the topology and the Einstein–Hilbert energy. Lastly we derive conformally invariant estimates for the Betti numbers of an oriented four-manifold with positive scalar curvature.
Cyclic competition of four species: Mean-field theory and stochastic evolution

Generalizing the cyclically competing three-species model (often referred to as the rock-paper-scissors game), we consider a simple system of population dynamics without spatial structures that involves four species. Unlike the previous model, the four form alliance pairs which resemble partnership in the game of Bridge. In a finite system with discrete stochastic dynamics, all but 4 of the absorbing states consist of coexistence of a partner-pair. From a master equation, we derive a set of mean-field equations of evolution. This approach predicts complex time dependence of the system and that the surviving partner-pair is the one with the larger product of their strengths (rates of consumption). Simulations typically confirm these scenarios. Beyond that, much richer behavior is revealed, including complicated extinction probabilities and non-trivial distributions of the population ratio in the surviving pair. These discoveries naturally raise a number of intriguing questions, which in turn suggests a variety of future avenues of research, especially for more realistic models of multispecies competition in nature.
Ruling polynomials and augmentations over finite fields

For any Legendrian link, L, in (\R^3, \ker(dz-y\,dx)) we define invariants, Aug_m(L,q), as normalized counts of augmentations from the Legendrian contact homology DGA of L into a finite field of order q where the parameter m is a divisor of twice the rotation number of L. Generalizing a result of Ng and Sabloff for the case q =2, we show the augmentation numbers, Aug_m(L,q), are determined by specializing the m-graded ruling polynomial, R^m_L(z), at z = q^{1/2}-q^{-1/2}. As a corollary, we deduce that the ruling polynomials are determined by the Legendrian contact homology DGA.
Polarized Emission from Interstellar Dust

Observations of far-infrared (FIR) and submillimeter (SMM) polarized emission are used to study magnetic fields and dust grains in dense regions on the interstellar medium (ISM). These observations place constraints on models of molecular clouds, star-formation, grain alignment mechanisms, and grain size, shape, and composition. The FIR/SMM polarization is strongly dependent on wavelength. We have attributed this wavelength dependence to sampling different grain populations at different temperatures. To date, most observations of polarized emission have been in the densest regions of the ISM. Extending these observations to regions of the diffuse ISM, and to microwave frequencies, will provide additional tests of grain and alignment models. An understanding of polarized microwave emission from dust is key to an accurate measurement of the polarization of the cosmic microwave background. The microwave polarization spectrum will put limits on the contributions to polarized emission from spinning dust and vibrating magnetic dust.
An enhanced isothermal amplification assay for viral detection

Rapid, inexpensive, robust diagnostics are essential to control the spread of infectious diseases. Current state of the art diagnostics are highly sensitive and specific, but slow, and require expensive equipment. Here we report the development of a molecular diagnostic test for SARS-CoV-2 based on an enhanced recombinase polymerase amplification (eRPA) reaction. eRPA has a detection limit on patient samples down to 5 viral copies, requires minimal instrumentation, and is highly scalable and inexpensive. eRPA does not cross-react with other common coronaviruses, does not require RNA purification, and takes ~45 min from sample collection to results. eRPA represents a first step toward at-home SARS-CoV-2 detection and can be adapted to future viruses within days of genomic sequence availability.
Wall to wall optimal transport

The calculus of variations is employed to find steady divergence-free velocity fields that maximize transport of a tracer between two parallel walls held at fixed concentration for one of two constraints on flow strength: a fixed value of the kinetic energy (mean square velocity) or a fixed value of the enstrophy (mean square vorticity). The optimizing flows consist of an array of (convection) cells of a particular aspect ratio . We solve the nonlinear Euler–Lagrange equations analytically for weak flows and numerically – as well as via matched asymptotic analysis in the fixed energy case – for strong flows. We report the results in terms of the Nusselt number , a dimensionless measure of the tracer transport, as a function of the Peclet number , a dimensionless measure of the strength of the flow. For both constraints, the maximum transport is realized in cells of decreasing aspect ratio as increases. For the fixed energy problem, and , while for the fixed enstrophy scenario, and . We interpret our results in the context of buoyancy-driven Rayleigh–Benard convection problems that satisfy the flow intensity constraints, enabling us to investigate how the transport scalings compare with upper bounds on expressed as a function of the Rayleigh number . For steady convection in porous media, corresponding to the fixed energy problem, we find and , while for steady convection in a pure fluid layer between stress-free isothermal walls, corresponding to fixed enstrophy transport, and .
Coupling to modes of a near-confocal optical resonator using a digital light modulator.

Digital micromirror devices (DMD) provide a robust platform with which to implement digital holography, in principle providing the means to rapidly generate propagating transverse electromagnetic fields with arbitrary mode profiles at visible and IR wavelengths. We use a DMD to probe a Fabry-Perot cavity in single-mode and near-degenerate confocal configurations. Pumping arbitrary modes of the cavity is possible with excellent specificity by virtue of the spatial overlap between the incident light field and the cavity mode.
Equivariant K-theory, groupoids and proper actions

In this paper we define complex equivariant K-theory for actions of Lie groupoids using finite-dimensional vector bundles. For a Bredon-compatible Lie groupoid , this defines a periodic cohomology theory on the category of finite -CW-complexes. We also establish an analogue of the completion theorem of Atiyah and Segal. Some examples are discussed.
Distributed Path Reconfiguration and Data Forwarding in Industrial IoT Networks

In today’s typical industrial environments, the computation of the data distribution schedules is highly centralised. Typically, a central entity configures the data forwarding paths so as to guarantee low delivery delays between data producers and consumers. However, these requirements might become impossible to meet later on, due to link or node failures, or excessive degradation of their performance. In this paper, we focus on maintaining the network functionality required by the applications after such events. We avoid continuously recomputing the configuration centrally, by designing an energy efficient local and distributed path reconfiguration method. Specifically, given the operational parameters required by the applications, we provide several algorithmic functions which locally reconfigure the data distribution paths, when a communication link or a network node fails. We compare our method through simulations to other state of the art methods and we demonstrate performance gains in terms of energy consumption and data delivery success rate as well as some emerging key insights which can lead to further performance gains.
Relativistic theory of the falling retroreflector gravimeter

We develop a relativistic treatment of interference between light reflected from a falling cube retroreflector in the vertical arm of an interferometer, and light in a reference beam in the horizontal arm. Coordinates that are nearly Minkowskian, attached to the falling cube, are used to describe the propagation of light within the cube. Relativistic effects such as the dependence of the coordinate speed of light on gravitational potential, propagation of light along null geodesics, relativity of simultaneity, and Lorentz contraction of the moving cube, are accounted for. The calculation is carried to first order in the gradient of the acceleration of gravity. Analysis of data from a falling cube gravimeter shows that the propagation time of light within the cube itself causes a significant reduction in the value of the acceleration of gravity obtained from measurements, compared to assuming reflection occurs at the face. An expression for the correction to the acceleration of gravity is derived and found to agree with experiment. Depending on the instrument, the correction can be several microgals, comparable to commonly applied corrections such as those due to polar motion and earth tides. The controversial "speed of light" correction is discussed.