cssi/SciSciGPT-SciSciNet huggingface dataset:
A weak form of beyond endoscopic decomposition for the stable trace formula of odd orthogonal groups

We show that the cuspidal component of the stable trace formula of a split special odd orthogonal group over a number field, satisfies a weak form of beyond endoscopic decomposition. We also study the $r$-stable trace formula, when $r$ is the standard or the second fundamental representation of the dual group, and show that they satisfy a similar kind of beyond endoscopic decomposition. The results are consequences of Arthurs works (2013) on endoscopic classification of automorphic representations, together with known results concerning a class of Langlands $L$-functions for special odd orthogonal groups.
A matrix of linear forms which is annihilated by a vector of indeterminates

Abstract Let R = k [ T 1 , … , T f ] be a standard graded polynomial ring over the field k and Ψ be an f × g matrix of linear forms from R, where 1 ≤ g f . Assume [ T 1 ⋯ T f ] Ψ is 0 and that grade I g ( Ψ ) is exactly one short of the maximum possible grade. We resolve R ‾ = R / I g ( Ψ ) , prove that R ‾ has a g -linear resolution, record explicit formulas for the h-vector and multiplicity of R ‾ , and prove that if f − g is even, then the ideal I g ( Ψ ) is unmixed. Furthermore, if f − g is odd, then we identify an explicit generating set for the unmixed part, I g ( Ψ ) unm , of I g ( Ψ ) , resolve R / I g ( Ψ ) unm , and record explicit formulas for the h-vector of R / I g ( Ψ ) unm . (The rings R / I g ( Ψ ) and R / I g ( Ψ ) unm automatically have the same multiplicity.) These results have applications to the study of the blow-up algebras associated to linearly presented grade three Gorenstein ideals.
Eliciting Knowledge from Experts: Automatic Transcript Parsing for Cognitive Task Analysis.

Cognitive task analysis (CTA) is a type of analysis in applied psychology aimed at eliciting and representing the knowledge and thought processes of domain experts. In CTA, often heavy human labor is involved to parse the interview transcript into structured knowledge (e.g., flowchart for different actions). To reduce human efforts and scale the process, automated CTA transcript parsing is desirable. However, this task has unique challenges as (1) it requires the understanding of long-range context information in conversational text; and (2) the amount of labeled data is limited and indirect—i.e., context-aware, noisy, and low-resource. In this paper, we propose a weakly-supervised information extraction framework for automated CTA transcript parsing. We partition the parsing process into a sequence labeling task and a text span-pair relation extraction task, with distant supervision from human-curated protocol files. To model long-range context information for extracting sentence relations, neighbor sentences are involved as a part of input. Different types of models for capturing context dependency are then applied. We manually annotate real-world CTA transcripts to facilitate the evaluation of the parsing tasks.
Asymptotic behavior of the dimension of the Chow variety

Abstract First, we calculate the dimension of the Chow variety of degree d cycles on projective space. We show that the component of maximal dimension usually parametrizes degenerate cycles, confirming a conjecture of Eisenbud and Harris. Second, for a numerical class α on an arbitrary variety, we study how the dimension of the components of the Chow variety parametrizing cycles of class mα grows as we increase m. We show that when the maximal growth rate is achieved, α is represented by cycles that are “degenerate” in a precise sense.
Full-Speed Fuzzing: Reducing Fuzzing Overhead through Coverage-Guided Tracing

Coverage-guided fuzzing is one of the most successful approaches for discovering software bugs and security vulnerabilities. Of its three main components: (1) test case generation, (2) code coverage tracing, and (3) crash triage, code coverage tracing is a dominant source of overhead. Coverage-guided fuzzers trace every test case's code coverage through either static or dynamic binary instrumentation, or more recently, using hardware support. Unfortunately, tracing all test cases incurs significant performance penalties–-even when the overwhelming majority of test cases and their coverage information are discarded because they do not increase code coverage. To eliminate needless tracing by coverage-guided fuzzers, we introduce the notion of coverage-guided tracing. Coverage-guided tracing leverages two observations: (1) only a fraction of generated test cases increase coverage, and thus require tracing; and (2) coverage-increasing test cases become less frequent over time. Coverage-guided tracing encodes the current frontier of coverage in the target binary so that it self-reports when a test case produces new coverage–-without tracing. This acts as a filter for tracing; restricting the expense of tracing to only coverage-increasing test cases. Thus, coverage-guided tracing trades increased time handling coverage-increasing test cases for decreased time handling non-coverage-increasing test cases. To show the potential of coverage-guided tracing, we create an implementation based on the static binary instrumentor Dyninst called UnTracer. We evaluate UnTracer using eight real-world binaries commonly used by the fuzzing community. Experiments show that after only an hour of fuzzing, UnTracer's average overhead is below 1%, and after 24-hours of fuzzing, UnTracer approaches 0% overhead, while tracing every test case with popular white- and black-box-binary tracers AFL-Clang, AFL-QEMU, and AFL-Dyninst incurs overheads of 36%, 612%, and 518%, respectively. We further integrate UnTracer with the state-of-the-art hybrid fuzzer QSYM and show that in 24-hours of fuzzing, QSYM-UnTracer executes 79% and 616% more test cases than QSYM-Clang and QSYM-QEMU, respectively.
Total Equitable List Coloring

An equitable coloring is a proper coloring of a graph such that the sizes of the color classes differ by at most one. A graph G is equitably k-colorable if there exists an equitable coloring of G which uses k colors, each one appearing on either $$\lfloor |V(G)|/k \rfloor $$ or $$\lceil |V(G)|/k \rceil $$ vertices of G. In 1994, Fu conjectured that for any simple graph G, the total graph of G, T(G), is equitably k-colorable whenever $$k \ge \max \{\chi (T(G)), \Delta (G)+2\}$$ where $$\chi (T(G))$$ is the chromatic number of the total graph of G and $$\Delta (G)$$ is the maximum degree of G. We investigate the list coloring analogue. List coloring requires each vertex v to be colored from a specified list L(v) of colors. A graph is k-choosable if it has a proper list coloring whenever vertices have lists of size k. A graph is equitably k-choosable if it has a proper list coloring whenever vertices have lists of size k, where each color is used on at most $$\lceil |V(G)|/k \rceil $$ vertices. In the spirit of Fu’s conjecture, we conjecture that for any simple graph G, T(G) is equitably k-choosable whenever $$k \ge \max \{\chi _l(T(G)), \Delta (G)+2\}$$ where $$\chi _l(T(G))$$ is the list chromatic number of T(G). We prove this conjecture for all graphs satisfying $$\Delta (G) \le 2$$ while also studying the related question of the equitable choosability of powers of paths and cycles.
R-Matrix Theory for Nanoscale Phonon Thermal Transport across Devices and Interfaces

We have adapted R-matrix theory to calculate phonon scattering across systems of molecular to mesoscopic scale. The key novelty of this work is that the only required information about the scattering region is its normal modes, which are evaluated only once for a system. Thus, R-matrix theory is a computationally efficient and simple approach to calculate phonon scattering in larger systems. To validate and to demonstrate the applicability of the theory, we apply it to two systems: a one-dimensional chain of atoms and a graphene nanoribbon. In both cases, we discuss the effect of mass impurities on thermal transport.
Homogenization of randomly deformed conductivity resistant membranes

We study the homogenization of a stationary conductivity problem in a random heterogeneous medium with highly oscillating conductivity coefficients and an ensemble of simply closed conductivity resistant membranes. This medium is randomly deformed and then rescaled from a periodic one with periodic membranes, in a manner similar to the random medium proposed by Blanc, Le Bris and Lions \cite{BLBL06}. Across the membranes, the flux is continuous but the potential field itself undergoes a jump of Robin type. We prove that, for almost all realizations of the random deformation, as the small scale of variations of the medium goes to zero, the random conductivity problem is well approximated by that on an effective medium which has deterministic and constant coefficients and contains no membrane. The effective coefficients are explicitly represented. One of our main contributions is to provide a solution to the associated auxiliary problem that is posed on the whole domain with infinitely many interfaces, in a setting that is neither periodic nor stationary ergodic in the usual sense.
On normal subgroups of the braided Thompson groups

We inspect the normal subgroup structure of the braided Thompson groups Vbr and Fbr. We prove that every proper normal subgroup of Vbr lies in the kernel of the natural quotient Vbr \onto V, and we exhibit some families of interesting such normal subgroups. For Fbr, we prove that for any normal subgroup N of Fbr, either N is contained in the kernel of Fbr \onto F, or else N contains [Fbr,Fbr]. We also compute the Bieri-Neumann-Strebel invariant Sigma^1(Fbr), which is a useful tool for understanding normal subgroups containing the commutator subgroup.
An improved composite hypothesis test for Markov models with applications in network anomaly detection

Recent work has proposed the use of a composite hypothesis Hoeffding test for statistical anomaly detection. Setting an appropriate threshold for the test given a desired false alarm probability involves approximating the false alarm probability. To that end, a large deviations asymptotic is typically used which, however, often results in an inaccurate setting of the threshold, especially for relatively small sample sizes. This, in turn, results in an anomaly detection test that does not control well for false alarms. In this paper, we develop a tighter approximation using the Central Limit Theorem (CLT) under Markovian assumptions. We apply our result to a network anomaly detection application and demonstrate its advantages over earlier work.
Almost continuous extension for taut foliations

A taut foliation of a hyperbolic 3-manifold has the continuous extension property for leaves in almost every direction; that is, for each leaf of the universal cover of the foliation and almost every geodesic ray in the leaf, the limit of the ray in the universal cover of the 3-manifold is a well-defined point in the ideal boundary.
The Isometry Degree of a Computable Copy of $$\ell ^p$$

Suppose p is a computable real so that \(p \ge 1\). We define the isometry degree of a computable presentation of \(\ell ^p\) to be the least powerful Turing degree \(\mathbf {d}\) by which it is \(\mathbf {d}\)-computably isometrically isomorphic to the standard presentation of \(\ell ^p\). We show that this degree always exists and that when \(p \ne 2\) these degrees are precisely the c.e. degrees.
Markov determinantal point processes

A determinantal point process (DPP) is a random process useful for modeling the combinatorial problem of subset selection. In particular, DPPs encourage a random subset Y to contain a diverse set of items selected from a base set Y. For example, we might use a DPP to display a set of news headlines that are relevant to a user's interests while covering a variety of topics. Suppose, however, that we are asked to sequentially select multiple diverse sets of items, for example, displaying new headlines day-by-day. We might want these sets to be diverse not just individually but also through time, offering headlines today that are unlike the ones shown yesterday. In this paper, we construct a Markov DPP (M-DPP) that models a sequence of random sets {Yt}. The proposed M-DPP defines a stationary process that maintains DPP margins. Crucially, the induced union process Zt ≡ Yt ⋃ Yt-1 is also marginally DPP-distributed. Jointly, these properties imply that the sequence of random sets are encouraged to be diverse both at a given time step as well as across time steps. We describe an exact, efficient sampling procedure, and a method for incrementally learning a quality measure over items in the base set Y based on external preferences. We apply the M-DPP to the task of sequentially displaying diverse and relevant news articles to a user with topic preferences.
Kevlar: A Mapping-Free Framework for Accurate Discovery of De Novo Variants

De novo genetic variants are an important source of causative variation in complex genetic disorders. Many methods for variant discovery rely on mapping reads to a reference genome, detecting numerous inherited variants irrelevant to the phenotype of interest. To distinguish between inherited and de novo variation, sequencing of families (parents and siblings) is commonly pursued. However, standard mapping-based approaches tend to have a high false-discovery rate for de novo variant prediction. Kevlar is a mapping-free method for de novo variant discovery, based on direct comparison of sequences between related individuals. Kevlar identifies high-abundance k-mers unique to the individual of interest. Reads containing these k-mers are partitioned into disjoint sets by shared k-mer content for variant calling, and preliminary variant predictions are sorted using a probabilistic score. We evaluated Kevlar on simulated and real datasets, demonstrating its ability to detect both de novo single-nucleotide variants and indels with high accuracy.
On the design of efficient CSMA algorithms for wireless networks

Recently, it has been shown that CSMA algorithms which use queue length-based link weights can achieve throughput optimality in wireless networks. In particular, a key result by Rajagopalan, Shah, and Shin (2009) shows that, if the link weights are chosen to be of the form log log(q) (where q is the queue-length), then throughput optimality is achieved. In this paper, we tighten their result by showing that throughput optimality is preserved even with weight functions of the form log(q)/g(q), where g(q) can be a function that increases arbitrarily slowly. The significance of the result is due to the fact that weight functions of the form log(q)/g(q) seem to achieve the best delay performance in practice.
A comparison theorem for Gromov-Witten invariants in the symplectic category

Abstract We exploit the geometric approach to the virtual fundamental class, due to Fukaya–Ono and Li–Tian, to compare Gromov–Witten invariants of a symplectic manifold and a symplectic submanifold whenever all constrained stable maps to the former are contained in the latter to first order. Various special cases of the comparison theorem in this paper have long been used in the algebraic category; some of them have also appeared in the symplectic setting. Combined with the inherent flexibility of the symplectic category, the main theorem leads to a confirmation of Pandharipandeʼs Gopakumar–Vafa prediction for GW-invariants of Fano classes in 6-dimensional symplectic manifolds. The proof of the main theorem uses deformations of the Cauchy–Riemann equation that respect the submanifold and Carleman Similarity Principle for solutions of perturbed Cauchy–Riemann equations. In a forthcoming paper, we apply a similar approach to relative Gromov–Witten invariants and the absolute/relative correspondence in genus 0.
Fourier integral operators with open umbrellas and seismic inversion for cusp caustics

In general the composition of Fourier integral operators (FIOs) need not be an FIO. Motivated by the problem of linearized seismic inversion in the presence of cusp caustics for the background sound speed, we consider FIOs whose canonical relations have certain two-sided cusp degeneracies, and show that the resulting compositions have wave-front relations in the union of the diagonal and an open umbrella, the simplest type of singular Lagrangian manifold.
Topology Estimation Using Graphical Models in Multi-Phase Power Distribution Grids

Power distribution grids are structurally operated radially, such that energized lines form a collection of trees with a substation at the root of each tree. The operational topology may change from time to time; however, tracking these changes, even though important for the distribution grid operation and control, is hindered by limited real-time monitoring. This paper develops a learning framework to reconstruct the radial operational structure of the distribution grid from synchronized voltage measurements. To detect operational lines, our learning algorithm uses conditional independence tests for continuous random variables that is applicable to a wide class of probability distributions, and in particular Gaussian, for injections. We validate the algorithm through extensive experiments on ac three-phase IEEE distribution grid test cases.
MULTICOMPLEXES AND SPECTRAL SEQUENCES

In this note, we present some algebraic examples of multicomplexes whose differentials differ from those in the spectral sequences associated to the multicomplexes. The motivation for constructing examples showing the algebraic distinction between a multicomplex and its associated spectral sequence comes from the author's work on Morse–Bott homology with A. Banyaga [A. Banyaga and D. E. Hurtubise, Morse–Bott homology, Trans. Amer. Math. Soc. (to appear), arXiv:math/0612316v2].
Subgraph centrality and walk-regularity

Abstract Matrix-based centrality measures have enjoyed significant popularity in network analysis, in no small part due to our ability to rigorously analyze their behavior as parameters vary. Recent work has considered the relationship between subgraph centrality, which is defined using the matrix exponential f ( x ) = exp ⁡ ( x ) , and the walk structure of a network. In a walk-regular graph, the number of closed walks of each length must be the same for all nodes, implying uniform f-subgraph centralities for any f (or maximum f-walk entropy). We consider when non-walk-regular graphs can achieve maximum entropy, calling such graphs entropic. For parameterized measures, we are also interested in which values of the parameter witness this uniformity. To date, only one entropic graph has been identified, with only two witnessing parameter values, raising the question of how many such graphs and parameters exist. We resolve these questions by constructing infinite families of entropic graphs, as well as a family of witnessing parameters with a limit point at zero.
Initiation of droxidopa during hospital admission for management of refractory neurogenic orthostatic hypotension in severely ill patients.

Orthostatic hypotension (OH) is a common cause of hospitalization, particularly in the elderly. Hospitalized patients with OH are often severely ill, with complex medical comorbidities and high rates of disability. Droxidopa is a norepinephrine precursor approved for the treatment of neurogenic OH (nOH) associated with autonomic failure that is commonly used in the outpatient setting, but there are currently no data regarding the safety and efficacy of droxidopa initiation in medically complex patients. We performed a retrospective review of patients started on droxidopa for refractory nOH while hospitalized at Vanderbilt University Medical Center between October 2014 and May 2017. Primary outcome measures were safety, change in physician global impression of illness severity from admission to discharge, and persistence on medication after 180-day follow-up. A total of 20 patients were identified through chart review. Patients were medically complex with high rates of cardiovascular comorbidities and a diverse array of underlying autonomic diagnoses. Rapid titration of droxidopa was safe and well tolerated in this cohort, with no cardiovascular events or new onset arrhythmias. Supine hypertension requiring treatment occurred in four patients. One death occurred during hospital admission due to organ failure associated with end-stage amyloidosis. Treating physicians noted improvements in presyncopal symptoms in 80% of patients. After 6 months, 13 patients (65%) continued on droxidopa therapy. In a retrospective cohort of hospitalized, severely ill patients with refractory nOH, supervised rapid titration of droxidopa was safe and effective. Treatment persistence was high, suggesting that symptomatic benefit extended beyond acute intervention.
Experimental Realization of Acoustic Bianisotropic Gratings

Bianisotropic gratings offer superior control of airborne sound via asymmetric wave transmission and reflection at an arbitrarily designed angle, leading to better technology in acoustic lensing, noise control, and high-intensity focused ultrasound therapies. Traditional bianisotropic materials depend on the resonance of deeply subwavelength particles, with intrinsic loss that limits grating efficiency. This study designs bianisotropic elements using a finite-element method to maximize scattering efficiency, and spatial Fourier analysis for verification. The result is a systematic process for designing gratings with 100% efficiency for an arbitrary scattering angle.
ATTACK2VEC: leveraging temporal word embeddings to understand the evolution of cyberattacks

Despite the fact that cyberattacks are constantly growing in complexity, the research community still lacks effective tools to easily monitor and understand them. In particular, there is a need for techniques that are able to not only track how prominently certain malicious actions, such as the exploitation of specific vulnerabilities, are exploited in the wild, but also (and more importantly) how these malicious actions factor in as attack steps in more complex cyberattacks. In this paper we present ATTACK2VEC, a system that uses temporal word embeddings to model how attack steps are exploited in the wild, and track how they evolve. We test ATTACK2VEC on a dataset of billions of security events collected from the customers of a commercial Intrusion Prevention System over a period of two years, and show that our approach is effective in monitoring the emergence of new attack strategies in the wild and in flagging which attack steps are often used together by attackers (e.g., vulnerabilities that are frequently exploited together). ATTACK2VEC provides a useful tool for researchers and practitioners to better understand cyberattacks and their evolution, and use this knowledge to improve situational awareness and develop proactive defenses.
Velocity saturation in La-doped BaSnO3 thin films

BaSnO3, a high mobility perovskite oxide, is an attractive material for oxide-based electronic devices. However, in addition to low-field mobility, high-field transport properties such as the saturation velocity of carriers play a major role in determining the device performance. We report on the experimental measurement of the electron saturation velocity in La-doped BaSnO3 thin films for a range of doping densities. The predicted saturation velocities based on a simple LO-phonon emission mode, using an effective LO phonon energy of 120 meV show good agreement with the measurements of velocity saturation in La-doped BaSnO3 films. Density-dependent saturation velocity in the range of 1.8 × 107 cm/s reducing to 2 × 106 cm/s is predicted for δ-doped BaSnO3 channels with carrier densities ranging from 1013 cm−2 to 2 × 1014 cm−2, respectively. These results are expected to aid the informed design of BaSnO3 as an active material for high-charge density electronic transistors.
Comparing Convective Self-Aggregation in Idealized Models to Observed Moist Static Energy Variability Near the Equator

Idealized convection-permitting simulations of radiative-convective equilibrium (RCE) have become a popular tool for understanding the physical processes leading to horizontal variability of tropical water vapor and rainfall. However, the applicability of idealized simulations to nature is still unclear given that important processes are typically neglected, such as lateral vapor advection by extratropical intrusions, or interactive ocean coupling. Here, we exploit spectral analysis to compactly summarize the multi-scale processes supporting convective aggregation. By applying this framework to high-resolution reanalysis data and satellite observations in addition to idealized simulations, we compare convective-aggregation processes across horizontal scales and data sets. The results affirm the validity of the RCE simulations as an analogy to the real world. Column moist static energy tendencies share similar signs and scale-selectivity in convection-permitting models and observations: Radiation increases variance at wavelengths above 1,000km, while advection damps variance across wavelengths, and surface fluxes mostly reduce variance between 1,000km and 10,000km.
A mixed-methods evaluation using effectiveness perception surveys, social network analysis, and county-level health statistics: A pilot study of eight rural Indiana community health coalitions.

Abstract Community health coalitions (CHCs) are a promising approach for addressing disparities in rural health statistics. However, their effectiveness has been variable, and evaluation methods have been insufficient and inconsistent. Thus, we propose a mixed-methods evaluation framework and discuss pilot study findings. CHCs in our pilot study partnered with Purdue Extension. Extension links communities and land grant universities, providing programming and support for community-engaged research. We conducted social network analysis and effectiveness perception surveys in CHCs in 8 rural Indiana counties during summer 2017 and accessed county-level health statistics from 2015-16. We compared calculated variables (i.e., effectiveness survey k-means clusters, network measures, health status/outcomes) using Pearson’s correlations. CHC members’ positive perceptions of their leadership and functioning correlated with interconnectedness in their partnership networks, while more centralized partnership networks correlated with CHC members reporting problems in their coalitions. CHCs with highly rated leadership and functioning developed in counties with poor infant/maternal health and opioid outcomes. Likewise, CHCs reporting fewer problems for participation developed in counties with poor infant/maternal health, poor opioid outcomes, and more people without healthcare coverage. This pilot study provides a framework for iterative CHC evaluation. As the evidence grows, we will make recommendations for best practices that optimize CHC partnerships to improve local health in rural areas.
Coded Caching With Distributed Storage

Content delivery networks store information distributed across multiple servers, so as to balance the load and avoid unrecoverable losses in case of node or disk failures. Coded caching has been shown to be a useful technique which can reduce peak traffic rates by pre-fetching popular content at the end users and encoding transmissions so that different users can extract different information from the same packet. On one hand, distributed storage limits the capability of combining content from different servers into a single message, causing performance losses in coded caching schemes. But, on the other hand, the inherent redundancy existing in distributed storage systems can be used to improve the performance of those schemes through parallelism. This paper designs coded caching and delivery schemes tailored towards systems where the library is distributed across multiple servers, possibly with some redundancy in the form of maximum distance separable (MDS) erasure codes. Different schemes are proposed based on the capacity of the users’ caches, as well as the number of parity servers. The main focus is on scenarios with one (RAID-4) or two (RAID-6) parity servers, but the paper also includes simple extensions for cases with more than two or no parity servers at all. The proposed schemes are shown to reduce the worst case latency, or equivalently the peak transmission rate from any server, below that of state-of-the-art algorithms.
The covariant Gromov–Hausdorff propinquity

We extend the Gromov-Hausdorff propinquity to a metric on Lipschitz dynamical systems, which are given by strongly continuous actions of proper monoids on quantum compact metric spaces via Lipschitz morphisms. We prove that our resulting metric is zero between two Lipschitz dynamical systems if and only if there exists an equivariant full quantum isometry between. We also present sufficient conditions for Cauchy sequences to converge for our new metric, thus exhibiting certain complete classes of Lipschitz dynamical systems. We apply our work to convergence of the dual actions on fuzzy tori to the dual actions on quantum tori. Our framework is general enough to also allow for the study of the convergence of continuous semigroups of positive linear maps and other actions of proper monoids.
Generalized Gaffney inequality and discrete compactness for discrete differential forms

We prove generalized Gaffney inequalities and the discrete compactness for finite element differential forms on s-regular domains, including general Lipschitz domains. In computational electromagnetism, special cases of these results have been established for edge elements with weakly imposed divergence-free conditions and used in the analysis of nonlinear and eigenvalue problems. In this paper, we generalize these results to discrete differential forms, not necessarily with strongly or weakly imposed constraints. The analysis relies on a new Hodge mapping and its approximation property. As an application, we show $$L^{p}$$ estimates for several finite element approximations of the scalar and vector Laplacian problems.
Nutraceuticals: An Alternative Strategy for the Use of Antimicrobials

Livestock industries strive to improve the health of their animals and, in the future, they are going to be required to do this with a continued reduction in antimicrobial use. Nutraceuticals represent a group of compounds that may help fill that void because they exert some health benefits when supplemented to livestock. This review is focused on the mechanisms of action, specifically related to the immune responses and health of ruminants. The nutraceutical classes discussed include probiotics, prebiotics, phytonutrients (essential oils and spices), and polyunsaturated fatty acids.
Optimizing Phylogenomics with Rapidly Evolving Long Exons: Comparison with Anchored Hybrid Enrichment and Ultraconserved Elements

Marker selection has emerged as an important component of phylogenomic study design due to rising concerns of the effects of gene tree estimation error, model misspecification, and data-type differences. Researchers must balance various trade-offs associated with locus length and evolutionary rate among other factors. The most commonly used reduced representation data sets for phylogenomics are ultraconserved elements (UCEs) and Anchored Hybrid Enrichment (AHE). Here, we introduce Rapidly Evolving Long Exon Capture (RELEC), a new set of loci that targets single exons that are both rapidly evolving (evolutionary rate faster than RAG1) and relatively long in length (>1,500 bp), while at the same time avoiding paralogy issues across amniotes. We compare the RELEC data set to UCEs and AHE in squamate reptiles by aligning and analyzing orthologous sequences from 17 squamate genomes, composed of 10 snakes and 7 lizards. The RELEC data set (179 loci) outperforms AHE and UCEs by maximizing per-locus genetic variation while maintaining presence and orthology across a range of evolutionary scales. RELEC markers show higher phylogenetic informativeness than UCE and AHE loci, and RELEC gene trees show greater similarity to the species tree than AHE or UCE gene trees. Furthermore, with fewer loci, RELEC remains computationally tractable for full Bayesian coalescent species tree analyses. We contrast RELEC to and discuss important aspects of comparable methods, and demonstrate how RELEC may be the most effective set of loci for resolving difficult nodes and rapid radiations. We provide several resources for capturing or extracting RELEC loci from other amniote groups.
Multi-label Multi-task Deep Learning for Behavioral Coding

We propose a methodology for estimating human behaviors in psychotherapy sessions using multi-label and multi-task learning paradigms. We discuss the problem of behavioral coding in which data of human interactions are annotated with labels to describe relevant human behaviors of interest. We describe two related, yet distinct, corpora consisting of therapist-client interactions in psychotherapy sessions. We experimentally compare the proposed learning approaches for estimating behaviors of interest in these datasets. Specifically, we compare single and multiple label learning approaches, single and multiple task learning approaches, and evaluate the performance of these approaches when incorporating turn context. We demonstrate that the best multi-label, multi-task learning model with turn context achieves 18.9% and 19.5% absolute improvements with respect to a logistic regression classifier (for each behavioral coding task respectively) and 6.4% and 6.1% absolute improvements with respect to the best single-label, single-task deep neural network models. Lastly, we discuss the insights these modeling paradigms provide into these complex interactions including key commonalities and differences of behaviors within and between the two prevalent psychotherapy approaches-Motivational Interviewing and Cognitive Behavioral Therapy-considered.
Threshold-Secure Coding with Shared Key

Cryptographic protocols are often implemented at upper layers of communication networks, while error-correcting codes are employed at the physical layer. In this paper, we consider utilizing readily-available physical layer functions, such as encoders and decoders, together with shared keys to provide a threshold-type security scheme. To this end, the effect of physical layer communication is abstracted out and the channels between the legitimate parties, Alice and Bob, and the eaves-dropper Eve are assumed to be noiseless. We introduce a model for threshold-secure coding, where Alice and Bob communicate using a shared key in such a way that Eve does not get any information, in an information-theoretic sense, about the key as well as about any subset of the input symbols of size up to a certain threshold. Then, a framework is provided for constructing threshold-secure codes form linear block codes while characterizing the requirements to satisfy the reliability and security conditions. Moreover, we propose a threshold-secure coding scheme, based on Reed-Muller (RM) codes, that meets security and reliability conditions. Furthermore, it is shown that the encoder and the decoder of the scheme can be implemented efficiently with quasi-linear time complexity. In particular, a low-complexity successive cancellation decoder is shown for the RM-based scheme. Also, the scheme is flexible and can be adapted given any key length.
Is There a Risk-Return Tradeoff in the Corporate Bond Market? Time-Series and Cross-Sectional Evidence

Abstract We provide time-series and cross-sectional evidence on the significance of a risk-return tradeoff in the bond and equity markets. We find a significantly positive intertemporal relation between expected return and risk in the bond market. We also propose novel measures of systematic and idiosyncratic risk for individual corporate bonds and find a significantly positive cross-sectional relation between systematic risk and expected bond returns, whereas there is no significant link between idiosyncratic risk and future bond returns. We provide an explanation for the significance of systematic (idiosyncratic) risk based on different investor preferences and informational frictions in the bond (equity) market.
Hydrodynamic Profiles for the Totally Asymmetric Exclusion Process with a Slow Bond

We study a totally asymmetric simple exclusion process where jumps happen at rate one, except at the origin where the rate is lower. We prove a hydrodynamic scaling limit to a macroscopic profile described by a variational formula. The limit is valid for all values of the slow rate. The only assumption required is that a law of large numbers holds for the initial particle distribution. This allows also deterministic initial configurations. The hydrodynamic description contains as an unknown parameter the macroscopic rate at the origin, which is strictly larger than the microscopic slow rate. The limit is proved by the variational coupling method.
MimickNet, Matching Clinical Post-Processing Under Realistic Black-Box Constraints

Image post-processing is used in clinical-grade ultrasound scanners to improve image quality (e.g., reduce speckle noise and enhance contrast). These post-processing techniques vary across manufacturers and are generally kept proprietary, which presents a challenge for researchers looking to match current clinical-grade workflows. We introduce a deep learning framework, MimickNet, that transforms conventional delay-and-summed (DAS) beamformed images into the approximate post-processed images found on clinical-grade scanners. Training MimickNet only requires post-processed image samples from a scanner of interest without the need for explicit pairing to DAS data. Unpaired image flexibility allows MimckNet to hypothetically approximate any manufacturer’s post-processing without hacking into commercial machines for pre-processed data. MimickNet generates images with an average similarity index measurement (SSIM) of 0.930±0.0892 on a 300 cineloop test set, and it generalizes to cardiac cineloops achieving an SSIM of 0.967±0.002 despite using no cardiac data in the training process. To our knowledge, this is the first work to approximate current clinical-grade ultrasound post-processing under realistic black-box constraints where before and after post-processing data is unavailable. MimickNet can be used out of the box or retrained to serve as a clinical post-processing baseline to compare against for future works in ultrasound image formation. To this end, we have made the MimickNet software open source at https://github.com/ouwen/mimicknet.
AN OPTION THEORETIC APPROACH TO MARKET EFFICIENCY

I use five separate measures of deviation from Put-Call Parity of options on a stock without splits or dividends as separate negative measures for market efficiency. I rely upon the theory of tradi...
Communication, Distortion, and Randomness in Metric Voting

In distortion-based analysis of social choice rules over metric spaces, voters and candidates are jointly embedded in a metric space. Voters rank candidates by non-decreasing distance. The mechanism, receiving only this ordinal (comparison) information, must select a candidate approximately minimizing the sum of distances from all voters to the chosen candidate. It is known that while the Copeland rule and related rules guarantee distortion at most 5, the distortion of many other standard voting rules, such as Plurality, Veto, or k-approval, grows unboundedly in the number n of candidates.An advantage of Plurality, Veto, or k-approval with small k is that they require less communication from the voters; all deterministic social choice rules known to achieve constant distortion require voters to transmit their complete rankings of all candidates. This motivates our study of the tradeoff between the distortion and the amount of communication in deterministic social choice rules.We show that any one-round deterministic voting mechanism in which each voter communicates only the candidates she ranks in a given set of k positions must have distortion at least 2n-k/k; we give a mechanism achieving an upper bound of O(n/k), which matches the lower bound up to a constant. For more general communication-bounded voting mechanisms, in which each voter communicates b bits of information about her ranking, we show a slightly weaker lower bound of Ω(n/b) on the distortion.For randomized mechanisms, Random Dictatorship achieves expected distortion strictly smaller than 3, almost matching a lower bound of 3 − 2/n for any randomized mechanism that only receives each voter's top choice. We close this gap, by giving a simple randomized social choice rule which only uses each voter's first choice, and achieves expected distortion 3 − 2/n.
Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time Series

Detecting repeating patterns of different lengths in time series, also called variable-length motifs, has received a great amount of attention by researchers and practitioners. Despite the significant progress that has been made in recent single dimensional variable-length motif discovery work, detecting variable-length sub dimensional motifs —patterns that are simultaneously occurring only in a subset of dimensions in multivariate time series—remains a difficult task. The main challenge is scalability. On the one hand, the brute-force enumeration solution, which searches for motifs of all possible lengths, is very time consuming even in single dimensional time series. On the other hand, previous work show that index-based fixed-length approximate motif discovery algorithms such as random projection are not suitable for detecting variable-length motifs due to memory requirement. In this paper, we introduce an approximate variable-length subdimensional motif discovery algorithm called Collaborative HIerarchy based Motif Enumeration (CHIME) to efficiently detect variable-length subdimensional motifs given a minimum motif length in large-scale multivariate time series. We show that the memory cost of the approach is significantly smaller than that of random projection. Moreover, the speed of the proposed algorithm is significantly faster than that of the state-of-the-art algorithms. We demonstrate that CHIME can efficiently detect meaningful variable-length subdimensional motifs in large real world multivariate time series datasets.
Do low-income parents who receive unemployment insurance pay more child support?

Abstract This paper investigates the relationship between receipt of unemployment insurance (UI) benefits and formal child support payments and compliance among low-income parents experiencing employment difficulties. In theory, receipt of UI benefits may help noncustodial parents experiencing employment difficulties continue to meet their child support obligations. Under federal law, child support agencies can collect child support from unemployment insurance benefits received by noncustodial parents on IV-D cases. In practice, take-up of UI is quite low, particularly among low-income workers. In order to learn more about the relationship between unemployment insurance and child support payments, this paper uses survey and administrative data from a federally funded eight-state intervention for noncustodial parents. Findings from individual-level fixed effect models indicate that UI receipt is associated with increases in child support payments and compliance. These findings suggest that UI can be an important source of economic support for children living apart from the parent receiving benefits. These findings also highlight the potential for service connections between child support and UI agencies to support noncustodial parents in meeting their child support obligations and the continued importance of expanding economically disadvantaged workers’ access to the UI program.
Searches for decays of new particles in the DUNE Multi-Purpose near Detector

One proposed component of the upcoming Deep Underground Neutrino Experiment (DUNE) near detector complex is a multi-purpose, magnetized, gaseous argon time projection chamber: the Multi-Purpose Detector (MPD). We explore the new-physics potential of the MPD, focusing on scenarios in which the MPD is significantly more sensitive to new physics than a liquid argon detector, specifically searches for semi-long-lived particles that are produced in/near the beam target and decay in the MPD. The specific physics possibilities studied are searches for dark vector bosons mixing kinetically with the Standard Model hypercharge group, leptophilic vector bosons, dark scalars mixing with the Standard Model Higgs boson, and heavy neutral leptons that mix with the Standard Model neutrinos. We demonstrate that the MPD can extend existing bounds in most of these scenarios. We illustrate how the ability of the MPD to measure the momentum and charge of the final state particles leads to these bounds.
SECNVs: A Simulator of Copy Number Variants and Whole-Exome Sequences From Reference Genomes.

Copy number variants are duplications and deletions of the genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested SECNVs (Simulator of Exome Copy Number Variants), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs.
Establishment of chromatin accessibility by the conserved transcription factor Grainy head is developmentally regulated.

ABSTRACT The dramatic changes in gene expression required for development necessitate the establishment of cis-regulatory modules defined by regions of accessible chromatin. Pioneer transcription factors have the unique property of binding closed chromatin and facilitating the establishment of these accessible regions. Nonetheless, much of how pioneer transcription factors coordinate changes in chromatin accessibility during development remains unknown. To determine whether pioneer-factor function is intrinsic to the protein or whether pioneering activity is developmentally modulated, we studied the highly conserved, essential transcription factor Grainy head (Grh). Prior work established that Grh is expressed throughout Drosophila development and is a pioneer factor in the larva. We demonstrated that Grh remains bound to mitotic chromosomes, a property shared with other pioneer factors. By assaying chromatin accessibility in embryos lacking maternal and/or zygotic Grh at three stages of development, we discovered that Grh is not required for chromatin accessibility in early embryogenesis, in contrast to its essential functions later in development. Our data reveal that the pioneering activity of Grh is temporally regulated and likely influenced by additional factors expressed at a given developmental stage.
The Role of Lunar Astronomy in the Exploration and Development of the Moon

Lunar astronomical facilities can be robotically emplaced or form an adjunct to a human base. Connected facilities are a means to increase science-per-dollar. Near-Earth and Centaur asteroids may also serve as venues for astronomy.