cssi/SciSciGPT-SciSciNet huggingface dataset:
Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts.

As pharmacogenomics data becomes increasingly integral to clinical treatment decisions, appropriate data storage and sharing protocols need to be adopted. One promising option for secure, high-integrity storage and sharing is Ethereum smart contracts. Ethereum is a blockchain platform, and smart contracts are immutable pieces of code running on virtual machines in this platform that can be invoked by a user or another contract (in the blockchain network). The 2019 iDASH (Integrating Data for Analysis, Anonymization, and Sharing) competition for Secure Genome Analysis challenged participants to develop time- and space-efficient Ethereum smart contracts for gene-drug relationship data. Here we design a specific smart contract to store and query gene-drug interactions in Ethereum using an index-based, multi-mapping approach. Our contract stores each pharmacogenomics observation, a gene-variant-drug triplet with outcome, in a mapping searchable by a unique identifier, allowing for time and space efficient storage and query. This solution ranked in the top three at the 2019 IDASH competition. We further improve our ”challenge solution” and develop an alternate ”fastQuery” smart contract, which combines together identical gene-variant-drug combinations into a single storage entry, leading to significantly better scalability and query efficiency. On a private, proof-of-authority network, both our challenge and fastQuery solutions exhibit approximately linear memory and time usage for inserting into and querying small databases (<1,000 entries). For larger databases (1000 to 10,000 entries), fastQuery maintains this scaling. Furthermore, both solutions can query by a single field (”0-AND”) or a combination of fields (”1- or 2-AND”). Specifically, the challenge solution can complete a 2-AND query from a small database (100 entries) in 35ms using 0.1 MB of memory. For the same query, fastQuery has a 2-fold improvement in time and a 10-fold improvement in memory. We show that pharmacogenomics data can be stored and queried efficiently using Ethereum blockchain. Our solutions could potentially be used to store a range of clinical data and extended to other fields requiring high-integrity data storage and efficient access.
Liquified protein vibrations, classification and cross-paradigm de novo image generation using deep neural networks

In recent work we reported the vibrational spectrum of more than 100,000 known protein structures, and a self-consistent sonification method to render the spectrum in the audible range of frequencies (Extreme Mechanics Letters, 2019). Here we present a method to transform these molecular vibrations into materialized vibrations of thin water films using acoustic actuators, leading to complex patterns of surface waves, and using the resulting macroscopic images in further processing using deep convolutional neural networks. Specifically, the patterns of water surface waves for each protein structure is used to build training sets for neural networks, aimed to classify and further process the patterns. Once trained, the neural network model is capable of discerning different proteins solely by analyzing the macroscopic surface wave patterns in the water film. Not only can the method distinguish different types of proteins (e.g. alpha-helix vs hybrids of alpha-helices and beta-sheets), but it is also capable of determining different folding states of the same protein, or the binding events of proteins to ligands. Using the DeepDream algorithm, instances of key features of the deep neural network can be made visible in a range of images, allowing us to explore the inner workings of protein surface wave patter neural networks, as well as the creation of new images by finding and highlighting features of protein molecular spectra in a range of photographic input. The integration of the water-focused realization of cymatics, combined with neural networks and especially generative methods, offer a new direction to realize materiomusical "Inceptionism" as a possible direction in nano-inspired art. The method could have applications for detecting different protein structures, the effect of mutations, or uses in medical imaging and diagnostics, with broad impact in nano-to-macro transitions.
Interactive Dynamic Literacy Model: An Integrative Theoretical Framework for Reading-Writing Relations.

I propose an integrative theoretical framework for reading and writing acquisition, called the interactive dynamic literacy model, after reviewing theoretical models of reading and writing, and recent efforts in integrating theoretical models within reading and writing, respectively. The central idea of the interactive dynamic literacy model is that reading and writing are inter-related, developing together, largely due to a shared constellation of skills and knowledge. Four core hypotheses of the interactive dynamic literacy model include (1) hierarchical structure of component skills with direct and indirect relations; (2) interactive relations between component skills, and between reading and writing; (3) co-morbidity of reading and writing difficulties; and (4) dynamic relations (relations change as a function of development, learner characteristics, and reading and writing measurement). Implications and future work are discussed.
Who should exert more effort? Risk aversion, downside risk aversion and optimal prevention

I provide new results on how risk preferences affect optimal prevention. I identify a comparative risk aversion and a comparative downside risk aversion effect and highlight those cases where both effects are aligned. Alignment depends on a probability threshold, which, in turn, only depends on the preferences of the benchmark agent. This allows to define an entire class of decision-makers who all share the same comparative static prediction relative to the reference agent. I relate my findings to different intensity measures of downside risk aversion and apply them to parametric preference changes and specific classes of utility functions.
Towards Equal Rights in the Global Game? FIFA's Strategy for Women’s Football as a Tightly Bounded Institutional Innovation

FIFA’s recent (rhetorical) embrace of human rights prominently includes commitments to address gender discrimination and promote gender equality both on and off the pitch. What promise does FIFA’s ‘first-ever global strategy for women’s football’ hold as a means of fulfilling such commitments? A feminist institutionalist approach to this question offers insights into the bounded model of change endorsed by the Women’s Football Strategy. It reveals that the Strategy’s three key objectives serve as ‘common carriers’ for both long-standing institutional interests (in power, profit, and prestige) and newer institutional interests (in women footballers, women’s football, and women in football governance). The assumption that these two sets of interests are mutually reinforcing is brought into question by exposing the ways in which FIFA’s mainline institutional priorities, combined with certain structural features of football governance, blunt the reformist potential of the Women’s Football Strategy. Bounded by old institutional features, the Strategy reflects a partial and incremental, rather than comprehensive and revolutionary, approach to addressing gender discrimination. FIFA’s commitment to human rights therefore remains unfulfilled vis-a-vis women in football.
Depths of Pluto's and Charon's craters, and their simple-to-complex transition

Abstract Impact craters form as point-like explosions on solar system bodies, excavating a cavity within the surface. Most information about the impactor itself is lost, save its energy, such that the target itself controls much of the final crater size and shape given the energy input. For this reason, impact craters are a useful probe of surface differences across a single body and between bodies. Two properties that are commonly used to compare craters from one body to another are the ratio between crater depth and diameter, and the diameter at which craters transition between simple, bowl-shaped morphologies to more complex morphologies that include flat floors, central peaks, wall terraces, and scalloped rims. Both metrics are important as input into theoretical models and for probing the strength of the surface material. In this work, we have measured these properties on Pluto and Charon and report on the results. However, the analysis is not entirely straightforward; a secondary goal of this work is to explore how to measure and quantify the two properties accurately (depth vs diameter and simple-to-complex transitions). We arrive at different results based on the method, and we report on that variation as a way to reasonably estimate the uncertainty in each quantity. For those reasons, it is difficult to place a single, exact value on each, but we do conclude that the morphology-based simple-to-complex transition occurs at approximately 11–12½ km on Pluto, and 13½–16 km on Charon. We also conclude that the existing, public topography data for at least Charon is likely too low in resolution to measure the simple crater depth vs diameter function accurately, such that a morphometry-based simple-to-complex transition diameter is not quantifiable at this time.
Algorithms for Subpath Convex Hull Queries and Ray-Shooting Among Segments

In this paper, we first consider the subpath convex hull query problem: Given a simple path $\pi$ of $n$ vertices, preprocess it so that the convex hull of any query subpath of $\pi$ can be quickly obtained. Previously, Guibas, Hershberger, and Snoeyink [SODA 90'] proposed a data structure of $O(n)$ space and $O(\log n\log\log n)$ query time; reducing the query time to $O(\log n)$ increases the space to $O(n\log\log n)$. We present an improved result that uses $O(n)$ space while achieving $O(\log n)$ query time. Like the previous work, our query algorithm returns a compact interval tree representing the convex hull so that standard binary-search-based queries on the hull can be performed in $O(\log n)$ time each. Our new result leads to improvements for several other problems. In particular, with the help of the above result, we present new algorithms for the ray-shooting problem among segments. Given a set of $n$ (possibly intersecting) line segments in the plane, preprocess it so that the first segment hit by a query ray can be quickly found. We give a data structure of $O(n\log n)$ space that can answer each query in $(\sqrt{n}\log n)$ time. If the segments are nonintersecting or if the segments are lines, then the space can be reduced to $O(n)$. All these are classical problems that have been studied extensively. Previously data structures of $\widetilde{O}(\sqrt{n})$ query time (the notation $\widetilde{O}$ suppresses a polylogarithmic factor) were known in early 1990s; nearly no progress has been made for over two decades. For all problems, our results provide improvements by reducing the space of the data structures by at least a logarithmic factor while the preprocessing and query times are the same as before or even better.
Health Literacy: An Essential Element of Health Care Professionalism and Resilience

This report discusses the importance of incorporating health literacy into health care professionalism and resilience. It defines health care management professionalism and its subcomponents. The report addresses the need for an improved definition of health care management professionalism. The inclusion of health literacy is not only important to the improved definition, but also to health care management education competencies. The report builds on the move towards competency-based education as a strategy to address health literacy in the areas of professionalism and ethics for healthcare professionals. This could lead to building healthcare systems with healthcare professionals who encompass high levels of professionalism as well as incorporating tools to combat burnout and increasing resilience.
Application of an analytical model to evaluate storage structures

Abstract The File Design Analyzer is a software package which evaluates well-known data base storage structures and access methods in terms of secondary storage processing time and storage overhead required to service a set of user applications. It implements a first-order analytical model to specifically evaluate sequential, indexed sequential, direct access, and inverted multilist storage structures. Interaction with the package is available in conversational mode, enabling the experienced analyst to conduct on-line sensitivity analysis. The paper describes three extensions which converted an abstract conceptual model into a practical tool for evaluation of existing or proposed data base designs: batched transactions, multi-access interference due to shared secondary storage, and analysis of variable record size. A case study from a real system illustrates the potential of the File Design Analyzer to provide insight regarding the optimal choice of physical parameters within a specified storage structure and to effectively compare alternative storage structures for a particular set of applications.
A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations

Single-cell RNA-sequencing (scRNA-seq) facilitates the unbiased reconstruction of multicellular tissue systems in health and disease. Here, we present a curated scRNA-seq dataset of human muscle samples from 10 adult donors with diverse anatomical locations. We integrated ~ 22,000 single-cell transcriptomes using Scanorama to account for technical and biological variation and resolved 16 distinct populations of muscle-resident cells using unsupervised clustering of the data compendium. These cell populations included muscle stem/progenitor cells (MuSCs), which bifurcated into discrete “quiescent” and “early-activated” MuSC subpopulations. Differential expression analysis identified transcriptional profiles altered in the activated MuSCs including genes associated with aging, obesity, diabetes, and impaired muscle regeneration, as well as long non-coding RNAs previously undescribed in human myogenic cells. Further, we modeled ligand-receptor cell-communication interactions and observed enrichment of the TWEAK-FN14 pathway in activated MuSCs, a characteristic signature of muscle wasting diseases. In contrast, the quiescent MuSCs have enhanced expression of the EGFR receptor, a recognized human MuSC marker. This work provides a new benchmark reference resource to examine human muscle tissue heterogeneity and identify potential targets in MuSC diversity and dysregulation in disease contexts.
Continuous Credit Networks and Layer 2 Blockchains: Monotonicity and Sampling

To improve transaction rates, many cryptocurrencies have implemented so-called "Layer-2" transaction protocols, where payments are routed across networks of private payment channels. However, for a given transaction, not every network state provides a feasible route to perform the payment; in this case, the transaction must be put on the public ledger. The payment channel network thus multiplies the transaction rate of the overall system; the less frequently it fails, the higher the multiplier. We build on earlier work on credit networks and show that this network liquidity problem is connected to the combinatorics of graphical matroids. Earlier work could only analyze the (unnatural) scenario where transactions had discrete sizes. In this work, we give an analytical framework that removes this assumption. This enables meaningful liquidity analysis for real-world parameter regimes. Superficially, it might seem like the continuous case would be harder to examine. However, removing this assumption lets us make progress in two important directions. First, we give a partial answer to the "monotonicity conjecture" that previous work left open. This conjecture asks that the network's performance not degrade as capacity on any edge increases. And second, we construct here a network state sampling procedure with much faster asymptotic performance than off-the-shelf Markov chains (O(|E| β(|E|)), where β(x) is the complexity of solving a linear program on x constraints.) We obtain our results by mapping the underlying graphs to convex bodies and then showing that the liquidity and sampling problems reduce to bounding and computing the volumes of these bodies. The transformation relies crucially on the combinatorial properties of the underlying graphic matroid, as do the proofs of monotonicity and fast sampling.
Orbit selection for the 1978 Pioneer Venus mission

The Pioneer Venus Orbiter will be launched by NASA in the spring of 1978. Selection of the orbit in July, 1975, resulted from scientific, mission, spacecraft, and operational considerations summarized by this paper. The orbit will be inclined 105 deg to the ecliptic, and its periapsis will lie between 16 and 28 deg north celestial latitude. Its periapsis altitude will be maintained between 150 and 260 km above the solid surface, and its period will be kept near 24 hr. This orbit and the spinning spacecraft's ecliptic-normal attitude permit the scientific coverage geometry of Venus, which also is summarized here.
Predator–prey interactions in the canopy

Small mammal abundances are frequently limited by resource availability, but predators can exert strong lethal (mortality) and nonlethal (e.g., nest abandonment) limitations. Artificially increasing resource availability for uncommon small mammals provides a unique opportunity to examine predator-prey interactions. We used remote cameras to monitor 168 nest platforms placed in the live tree canopy (n = 23 young forest stands), primarily for arboreal red tree voles (tree voles; Arborimus longicaudus), over 3 years (n = 15,510 monitoring-weeks). Tree voles frequently built nests and were detected 37% of monitoring-weeks, whereas flying squirrels (Glaucomys oregonensis) built nests infrequently but were detected 45% of monitoring-weeks. Most nest predators were detected infrequently (<1% of monitoring-weeks) and were positively correlated with tree vole presence. Weasels (Mustela spp.) were highly effective predators of tree voles (n = 8 mortalities; 10% of detections) compared to owls (n = 1), flying squirrels (n = 2), and Steller's jays (n = 1). Tree vole activity decreased from 84.1 (95% confidence interval [CI]: 56.2, 111.9) detections/week 1-week prior to a weasel detection to 4.7 detections/week (95% CI: 1.7, 7.8) 1-week postdetection and remained low for at least 12 weeks. Interpretations of predator-prey interactions were highly sensitive to how we binned continuously collected data and model results from our finest bin width were biologically counter-intuitive. Average annual survival of female tree voles was consistent with a previous study (0.14; 95% CI: -0.04 [0.01], 0.32) and high compared to many terrestrial voles. The relative infrequency of weasel detections and inefficiency of other predators did not provide strong support for the hypothesis that predation per se limited populations. Rather, predation pressure, by reducing occupancy of already scarce nest sites through mortality and nest abandonment, may contribute to long-term local instability of tree vole populations in young forests. Additional monitoring would be needed to assess this hypothesis.
Error Bounds and Guidelines for Privacy Calibration in Differentially Private Kalman Filtering.

Differential privacy has emerged as a formal framework for protecting sensitive information in control systems. One key feature is that it is immune to post-processing, which means that arbitrary post-hoc computations can be performed on privatized data without weakening differential privacy. It is therefore common to filter private data streams. To characterize this setup, in this paper we present error and entropy bounds for Kalman filtering differentially private state trajectories. We consider systems in which an output trajectory is privatized in order to protect the state trajectory that produced it. We provide bounds on a priori and a posteriori error and differential entropy of a Kalman filter which is processing the privatized output trajectories. Using the error bounds we develop, we then provide guidelines to calibrate privacy levels in order to keep filter error within pre-specified bounds. Simulation results are presented to demonstrate these developments.
Exploring aspects of similarity between spoken personal narratives by disentangling them into narrative clause types

Sharing personal narratives is a fundamental aspect of human social behavior as it helps share our life experiences. We can tell stories and rely on our background to understand their context, similarities, and differences. A substantial effort has been made towards developing storytelling machines or inferring characters’ features. However, we don’t usually find models that compare narratives. This task is remarkably challenging for machines since they, as sometimes we do, lack an understanding of what similarity means. To address this challenge, we first introduce a corpus of real-world spoken personal narratives comprising 10,296 narrative clauses from 594 video transcripts. Second, we ask non-narrative experts to annotate those clauses under Labov’s sociolinguistic model of personal narratives (i.e., action, orientation, and evaluation clause types) and train a classifier that reaches 84.7% F-score for the highest-agreed clauses. Finally, we match stories and explore whether people implicitly rely on Labov’s framework to compare narratives. We show that actions followed by the narrator’s evaluation of these are the aspects non-experts consider the most. Our approach is intended to help inform machine learning methods aimed at studying or representing personal narratives.
Human Languages in Source Code: Auto-Translation for Localized Instruction

Computer science education has promised open access around the world, but access is largely determined by what human language you speak. As younger students learn computer science it is less appropriate to assume that they should learn English beforehand. To that end, we present CodeInternational, the first tool to translate code between human languages. To develop a theory of non-English code, and inform our translation decisions, we conduct a study of public code repositories on GitHub. The study is to the best of our knowledge the first on human-language in code and covers 2.9 million Java repositories. To demonstrate CodeInternational's educational utility, we build an interactive version of the popular English-language Karel reader and translate it into 100 spoken languages. Our translations have already been used in classrooms around the world, and represent a first step in an important open CS-education problem.
Dynamic Deep Networks for Retinal Vessel Segmentation

Deep learning has recently yielded impressive gains in retinal vessel segmentation. However, state-of-the-art methods tend to be conservative, favoring precision over recall. Thus, they tend to under-segment faint vessels, underestimate the width of thicker vessels, or even miss entire vessels. To address this limitation, we propose a stochastic training scheme for deep neural networks that robustly balances precision and recall. First, we train our deep networks with dynamic class weights in the loss function that fluctuate during each training iteration. This stochastic approach--which we believe is applicable to many other machine learning problems--forces the network to learn a balanced classification. Second, we decouple the segmentation process into two steps. In the first half of our pipeline, we estimate the likelihood of every pixel and then use these likelihoods to segment pixels that are clearly vessel or background. In the latter part of our pipeline, we use a second network to classify the ambiguous regions in the image. Our proposed method obtained state-of-the-art results on five retinal datasets---DRIVE, STARE, CHASE-DB, AV-WIDE, and VEVIO---by learning a robust balance between false positive and false negative rates. Our novel training paradigm makes a neural network more robust to inter-sample differences in class ratios, which we believe will prove particularly effective for settings with sparse training data, such as medical image analysis. In addition, we are the first to report segmentation results on the AV-WIDE dataset, and we have made the ground-truth annotations for this dataset publicly available. An implementation of this work can be found at https://github.com/sraashis/deepdyn.
An example of liftings with different Hodge numbers

In this paper, we exhibit an example of a smooth proper variety in positive characteristic possessing two liftings with different Hodge numbers.
Ultimatum Bargaining with Rational Inattention

A seller bargains with a rationally inattentive buyer (Sims 2003) over a good of random quality. After observing quality, the seller makes a take-it-or-leave-it offer. The buyer pays attention to the seller's product and offer at a cost proportional to expected entropy reduction. Because attention is free off-path, multiple equilibria emerge, many of which are efficient. A trembling-hand-like refinement (Selten 1975) rules out efficiency, delivering complete disagreement when attention is expensive and a unique equilibrium with trade when attention is cheap. In this equilibrium, the buyer overpays for low-quality goods, underpays for high-quality goods, and earns a strictly positive payoff.
Improved outcomes of endovascular repair of thoracic aortic injuries at higher volume institutions.

Abstract Background The use of thoracic endovascular aortic repair (TEVAR) has significantly improved the ability to treat traumatic aortic injuries (tTEVAR). We sought to determine whether a greater center volume correlated with better outcomes. Methods Vascular Quality Initiative data of TEVAR (2011-2017) for trauma were used in the present analysis. Using the distribution of the annual case volume at the participating centers, the sample was stratified into three terciles. In-hospital mortality at high-volume centers (HVCs) and low-volume centers (LVCs) was compared after adjustment for risk factors established in our previous Vascular Quality Initiative-based risk model containing age, gender, renal impairment, left subclavian artery involvement, and select concomitant injuries. Results A total of 619 tTEVAR cases were studied across 74 centers. HVCs (n = 184 cases) had performed ≥4.9 cases annually and LVCs (n = 220 cases) had performed ≤2.4 cases annually. Both crude mortality (4.4% vs 8.6%; P = .22) and adjusted odds of mortality (odds ratio, 0.44; 95% confidence interval, 0.18-1.09; P = .08) showed a trend toward better outcomes for tTEVAR performed at HVCs than at LVCs. The addition of center volume to our previous multivariate model significantly improved its discriminative ability (C-statistic, 0.90 vs 0.88; P = .02). The overall TEVAR volume (for all indications) was not associated with increased odds of mortality for tTEVAR (odds ratio, 0.46; 95% confidence interval, 0.17-1.20; P = .11), nor did it improve the model's discriminative ability. Conclusions Higher volume centers showed improved perioperative mortality after tTEVAR. The thoracic aortic trauma volume was more predictive than the overall TEVAR volume, suggesting that technical expertise is not the driving factor. Stable patients might benefit from transfer to a higher volume center before repair.
LiSBOA: LiDAR Statistical Barnes Objective Analysis for optimal design of LiDAR scans and retrieval of wind statistics. Part II: Applications to synthetic and real LiDAR data of wind turbine wakes

Abstract. The LiDAR Statistical Barnes Objective Analysis (LiSBOA), presented in Letizia et al., is a procedure for the optimal design of LiDAR scans and calculation over a Cartesian grid of the statistical moments of the velocity field. The LiSBOA is applied to LiDAR data collected in the wake of wind turbines to reconstruct mean and turbulence intensity of the wind velocity field. The proposed procedure is firstly tested for a numerical dataset obtained by means of the virtual LiDAR technique applied to the data obtained from a large eddy simulation (LES). The optimal sampling parameters for a scanning Doppler pulsed wind LiDAR are retrieved from the LiSBOA, then the estimated statistics are calculated showing a maximum error of about 4 % for both the normalized mean velocity and the turbulence intensity. Subsequently, LiDAR data collected during a field campaign conducted at a wind farm in complex terrain are analyzed through the LiSBOA for two different configurations. In the first case, the wake velocity fields of four utility-scale turbines are reconstructed on a 3D grid, showing the capability of the LiSBOA to capture complex flow features, such as high-speed jet around the nacelle and the wake turbulent shear layers. For the second case, the statistics of the wakes generated by four interacting turbines are calculated over a 2D Cartesian grid and compared to the measurements provided by the nacelle-mounted anemometers. Maximum discrepancies as low as 3 % for the normalized mean velocity and turbulence intensity endorse the application of the LiSBOA for LiDAR-based wind resource assessment and diagnostic surveys for wind farms.
CLOUD PHOTOGRAMMETRY WITH GROUND-LOCATED K-17 AERIAL CAMERAS

Abstract A technique is presented in which a pair of ground-located K-17 aerial cameras is used on a 1.30-milebaseline to determine cloud ranges to 1-mi accuracy at 40 mi, and cloud-height measurements to within 500 feet at this range. Details of the power supply, vacuum supply, and camera-synchronization requirements are discussed, as well as methods used in analysis. In particular, a detailed discussion is given of the theoretical and practical errors encountered in such a photogrammetric technique.
Human capital divergence and the size distribution of cities: Is Gibrat’s law obsolete?:

This article studies how the changing geographic distribution of skilled workers in the US affects theoretical models that use Gibrat’s law to explain the size distribution of cities. In the empiri...
Knowledge of Evidence-Based Practices and Frequency of Selection Among School-Based Professionals of Students With Autism:

Autism Focused Intervention Resources and Modules (AFIRM) are a set of self-paced, online learning modules designed to disseminate information about the 27 evidence-based practices identified throu...
A General Model of the Behavioral Response to Taxation

This paper generalizes the standard model of how taxes affect the labor-leisure choice by allowing individuals to change both their labor supply and avoidance effort in response to tax changes. Doing so reveals that the income and substitution effect of taxes depend on both preferences and the avoidance technology. Econometric analysis will not in general allow one to separately identify the two influences, unless one can specify observable determinants of the cost of avoidance. The effective marginal tax rate on working must be modified by the addition of an avoidance-facilitating effect, which measures how the cost of avoidance changes with higher income. This model provides a conceptual structure for evaluating to what extent, and in what situations, the opportunities for tax avoidance mitigate the real substitution response to taxation.
Multidimensional Schinzel-type theorems for multiplicative functions near prime tuples

Abstract Assuming Dickson's conjecture, we obtain multidimensional analogues of recent results on the behavior of certain multiplicative arithmetic functions near twin-prime arguments. This is inspired by analogous unconditional theorems of Schinzel undertaken without primality assumptions.
Mucin-derived O-glycans supplemented to diet mitigate diverse microbiota perturbations.

Microbiota-accessible carbohydrates (MACs) are powerful modulators of microbiota composition and function. These substrates are often derived from diet, such as complex polysaccharides from plants or human milk oligosaccharides (HMOs) during breastfeeding. Host-derived mucus glycans on gut-secreted mucin proteins serve as a continuous endogenous source of MACs for resident microbes; here we investigate the potential role of purified, orally administered mucus glycans in maintaining a healthy microbial community. In this study, we liberated and purified O-linked glycans from porcine gastric mucin and assessed their efficacy in shaping the recovery of a perturbed microbiota in a mouse model. We found that porcine mucin glycans (PMGs) and HMOs enrich for taxonomically similar resident microbes. We demonstrate that PMGs aid recovery of the microbiota after antibiotic treatment, suppress Clostridium difficile abundance, delay the onset of diet-induced obesity, and increase the relative abundance of resident Akkermansia muciniphila. In silico analysis revealed that genes associated with mucus utilization are abundant and diverse in prevalent gut commensals and rare in enteric pathogens, consistent with these glycan-degrading capabilities being selected for during host development and throughout the evolution of the host–microbe relationship. Importantly, we identify mucus glycans as a novel class of prebiotic compounds that can be used to mitigate perturbations to the microbiota and provide benefits to host physiology.
At the intersection of scribal training and theological profundity chiasm as an editorial Technique in the Primeval History and Deuteronomy

Scribes in antiquity were well-trained in a wide range of technical devices associated with the composition, copying, transmission, editing, collation, revision, reworking, and interpretation of texts. Among the range of devices that have been attested and that are prevalent in the literature of the ancient Near East, including ancient Israel, are chiasm, Seidel’s Law, repetitive resumption (Wiederaufnahme), lemmatic citation and reformulation, textual voicing (including pseudepigraphy, theonymy, and the use of an omniscient narrator). This paper will focus on one of the most interesting of these devices, the literary chiasm, in which textual content is ordered in an ABCBʹAʹ chiastic or “x-shaped” pattern). In many cases, once this pattern is recognized within a chapter or literary unit, an ostensibly haphazard or difficult to follow textual sequence gains a sense of logical order or structure, as a logical structure emerges from the text. In this way, recognition of the structure of the chiasm provides an intellectual (and potentially spiritual) gain for the reader and a sense of pleasure. At the same time, it must equally be recognized that textual transmission in antiquity does not fit neatly into the modern world’s categories. Ancient scribes do not divide up easily into the prevailing distinction and bifurcation between “author” and “editor.” All too often, the phenomenon of chiasm has been caught up in modern scholarly debates regarding textual dating, textual coherence, original versus secondary material within a text, and so on. As a result, a number of scholars have muddied the waters by assuming that any evidence of a chiasm within a text provides unambiguous evidence of an “original” composition that has not undergone any subsequent editorial reworking. Sometimes the chiasm seems to have been used to make arguments against historical criticism or source criticism in ways that go beyond the evidence and seem to be used for apologetic purposes. Similarly, sometimes the methodological controls for identifying a chiasm appear to be insufficiently rigorous, shifting inconsistently from lexical criteria to topical or thematic correspondences. This article provides case studies from narrative and legal material within Genesis, Exodus, and Deuteronomy, to demonstrate both the pleasures and perils of chiasm. In itself, the literary structure of the chiasm is neutral. In itself, it does not have probative value for determining the “original” or “secondary” nature of a text. The device was used with equal elegance by authors and editors and helps point to the sophistication of ancient scribes in working with texts.
Evidence for fractional topological charge in SU(2) pure Yang-Mills theory

Abstract We investigate the spectral flows of the hermitian Wilson-Dirac operator in the fundamental and adjoint representations on two ensembles of pure SU(2) gauge field configurations at the same physical volume. We find several background gauge field configurations where the index of the hermitian Wilson-Dirac operator in the adjoint representation is not four times the index in the fundamental representation. This could imply a topological basis for the gluino condensate in supersymmetric Yang-Mills theories.
Development and evaluation of MADDIE: Method to Acquire Delivery Date Information from Electronic health records.

Abstract Objective To develop an algorithm that infers patient delivery dates (PDDs) and delivery-specific details from Electronic Health Records (EHRs) with high accuracy; enabling pregnancy-level outcome studies in women’s health. Materials and Methods We obtained EHR data from 1,060,100 female patients treated at Penn Medicine hospitals or outpatient clinics between 2010–2017. We developed an algorithm called MADDIE: Method to Acquire Delivery Date Information from Electronic Health Records that infers a PDD for distinct deliveries based on EHR encounter dates assigned a delivery code, the frequency of code usage, and the time differential between code assignments. We validated MADDIE's PDDs against a birth log independently maintained by the Department of Obstetrics and Gynecology. Results MADDIE identified 50,560 patients having 63,334 distinct deliveries. MADDIE was 98.6 % accurate (F1-score 92.1 %) when compared to the birth log. The PDD was on average 0.68 days earlier than the true delivery date for patients with only one delivery (± 1.43 days) and 0.52 days earlier for patients with more than one delivery episode (± 1.11 days). Discussion MADDIE is the first algorithm to successfully infer PDD information using only structured delivery codes and identify multiple deliveries per patient. MADDIE is also the first to validate the accuracy of the PDD using an external gold standard of known delivery dates as opposed to manual chart review of a sample. Conclusion MADDIE augments the EHR with delivery-specific details extracted with high accuracy and relies only on structured EHR elements while harnessing temporal information and the frequency of code usage to identify accurate PDDs.
DIVERSE PROPERTIES OF INTERSTELLAR MEDIUM EMBEDDING GAMMA-RAY BURSTS AT THE EPOCH OF REIONIZATION

Analysis is performed on ultra-high-resolution large-scale cosmological radiation-hydrodynamic simulations to quantify, for the first time, the physical environment of long-duration gamma-ray bursts (GRBs) at the epoch of reionization. We find that, on parsec scales, 13% of GRBs remain in high-density (≥104 cm–3) low-temperature star-forming regions, whereas 87% of GRBs occur in low-density (~10–2.5 cm–3) high-temperature regions heated by supernovae. More importantly, the spectral properties of GRB afterglows, such as the neutral hydrogen column density, total hydrogen column density, dust column density, gas temperature, and metallicity of intervening absorbers, vary strongly from sight line to sight line. Although our model explains extant limited observationally inferred values with respect to circumburst density, metallicity, column density, and dust properties, a substantially larger sample of high-z GRB afterglows would be required to facilitate a statistically solid test of the model. Our findings indicate that any attempt to infer the physical properties (such as metallicity) of the interstellar medium (ISM) of the host galaxy based on a very small number (usually one) of sight lines would be precarious. Utilizing high-z GRBs to probe the ISM and intergalactic medium should be undertaken properly, taking into consideration the physical diversities of the ISM.
Kinematics of a simple reciprocal model swimmer at intermediate Reynolds numbers

A study of the kinematics, power and recovery strokes, fluid flows, and efficiency of a reciprocal dumbbell swimmer with finite inertia finds that the swimmer's average flow field is dominated by the flow during its power stroke, and it switches from pullerlike to pusherlike depending on the (finite) Reynolds number.
Orthogonal Polynomials on the Unit Circle with Fibonacci Verblunsky Coefficients, II. Applications

We consider CMV matrices with Verblunsky coefficients determined in an appropriate way by the Fibonacci sequence and present two applications of the spectral theory of such matrices to problems in mathematical physics. In our first application we estimate the spreading rates of quantum walks on the line with time-independent coins following the Fibonacci sequence. The estimates we obtain are explicit in terms of the parameters of the system. In our second application, we establish a connection between the classical nearest neighbor Ising model on the one-dimensional lattice in the complex magnetic field regime, and CMV operators. In particular, given a sequence of nearest-neighbor interaction couplings, we construct a sequence of Verblunsky coefficients, such that the support of the Lee-Yang zeros of the partition function for the Ising model in the thermodynamic limit coincides with the essential spectrum of the CMV matrix with the constructed Verblunsky coefficients. Under certain technical conditions, we also show that the zeros distribution measure coincides with the density of states measure for the CMV matrix.
Symmetry in abstract elementary classes with amalgamation

This paper is part of a program initiated by Saharon Shelah to extend the model theory of first order logic to the non-elementary setting of abstract elementary classes (AECs). An abstract elementary class is a semantic generalization of the class of models of a complete first order theory with the elementary substructure relation. We examine the symmetry property of splitting (previously isolated by the first author) in AECs with amalgamation that satisfy a local definition of superstability. The key results are a downward transfer of symmetry and a deduction of symmetry from failure of the order property. These results are then used to prove several structural properties in categorical AECs, improving classical results of Shelah who focused on the special case of categoricity in a successor cardinal. We also study the interaction of symmetry with tameness, a locality property for Galois (orbital) types. We show that superstability and tameness together imply symmetry. This sharpens previous work of Boney and the second author.
Heegaard Floer homology of L-space links with two components

We compute different versions of link Floer homology $HFL^{-}$ and $\widehat{HFL}$ for any $L$-space link with two components. The main approach is to compute the $h$-function of the filtered chain complex which is determined by the Alexander polynomials of every sublink of the $L$-space link. As an application, Thurston polytope and Thurston norm of any 2-component $L$-space link are explicitly determined by Alexander polynomials of the link and the link components.
Matter-coupled de Sitter supergravity

The de Sitter supergravity describes the interaction of supergravity with general chiral and vector multiplets and also one nilpotent chiral multiplet. The extra universal positive term in the potential, generated by the nilpotent multiplet and corresponding to the anti-D3 brane in string theory, is responsible for the de Sitter vacuum stability in these supergravity models. In the flat-space limit, these supergravity models include the Volkov–Akulov model with a nonlinearly realized supersymmetry. We generalize the rules for constructing the pure de Sitter supergravity action to the case of models containing other matter multiplets. We describe a method for deriving the closed-form general supergravity action with a given potential K, superpotential W, and vectormatrix fAB interacting with a nilpotent chiral multiplet. It has the potential V = eK(|F2|+|DW|2-3|W|2), where F is the auxiliary field of the nilpotent multiplet and is necessarily nonzero. The de Sitter vacuums are present under the simple condition that |F2|-3|W|2 > 0. We present an explicit form of the complete action in the unitary gauge.
Quantum phase transitions of antiferromagnets and the cuprate superconductors

I begin with a proposed global phase diagram of the cuprate superconductors as a function of carrier concentration, magnetic field, and temperature, and highlight its connection to numerous recent experiments. The phase diagram is then used as a point of departure for a pedagogical review of various quantum phases and phase transitions of insulators, superconductors, and metals. The bond operator method is used to describe the transition of dimerized antiferromagnetic insulators between magnetically ordered states and spin-gap states. The Schwinger boson method is applied to frustrated square lattice antiferromagnets: phase diagrams containing collinear and spirally ordered magnetic states, \(Z_2\) spin liquids, and valence bond solids are presented, and described by an effective gauge theory of spinons. Insights from these theories of insulators are then applied to a variety of symmetry breaking transitions in d-wave superconductors. The latter systems also contain fermionic quasiparticles with a massless Dirac spectrum, and their influence on the order parameter fluctuations and quantum criticality is carefully discussed. I conclude with an introduction to strong coupling problems associated with symmetry breaking transitions in two-dimensional metals, where the order parameter fluctuations couple to a gapless line of fermionic excitations along the Fermi surface.
Stabilization of derivators revisited

We revisit and improve Alex Heller’s results on the stabilization of derivators in Heller (J Pure Appl Algebra 115(2):113–130, 1997), recovering his results entirely. Along the way we give some details of the localization theory of derivators and prove some new results in that vein.
EVIDENCE FOR STEADY HEATING: OBSERVATIONS OF AN ACTIVE REGION CORE WITH HINODE AND TRACE

The timescale for energy release is an important parameter for constraining the coronal heating mechanism. Observations of 'warm' coronal loops ({approx}1 MK) have indicated that the heating is impulsive and that coronal plasma is far from equilibrium. In contrast, observations at higher temperatures ({approx}3 MK) have generally been consistent with steady heating models. Previous observations, however, have not been able to exclude the possibility that the high temperature loops are actually composed of many small-scale threads that are in various stages of heating and cooling and only appear to be in equilibrium. With new observations from the EUV Imaging Spectrometer and X-ray Telescope (XRT) on Hinode we have the ability to investigate the properties of high temperature coronal plasma in extraordinary detail. We examine the emission in the core of an active region and find three independent lines of evidence for steady heating. We find that the emission observed in XRT is generally steady for hours, with a fluctuation level of approximately 15% in an individual pixel. Short-lived impulsive heating events are observed, but they appear to be unrelated to the steady emission that dominates the active region. Furthermore, we find no evidence for warm emission that is spatially correlatedmore » with the hot emission, as would be expected if the high temperature loops are the result of impulsive heating. Finally, we also find that intensities in the 'moss', the footpoints of high temperature loops, are consistent with steady heating models provided that we account for the local expansion of the loop from the base of the transition region to the corona. In combination, these results provide strong evidence that the heating in the core of an active region is effectively steady, that is, the time between heating events is short relative to the relevant radiative and conductive cooling times.« less