cssi/SciSciGPT-SciSciNet huggingface dataset:
Bioanalytical method development and validation of MES207, a neuropeptide FF receptor antagonist, and its application in preclinical pharmacokinetics.

Abstract The nonpeptide small molecule, MES207, exhibits 17-fold preferential binding to the neuropeptide FF receptor 1 (NPFFR1) over NPFFR2 and shows antagonist functionality at NPFF receptors. In order to further the development of MES207 as a NPFFR1 probe, an UPLC-MS/MS bioanalytical method was developed and validated to quantify MES207 in rat plasma for a linearity range of 3–200 ng/mL. The method was applied in the analysis of the plasma, brain, and urine samples collected during pharmacokinetic studies in healthy male and female Sprague Dawley rats. The animals were dosed through oral gavage (50 mg/kg) and intravenously (2.5 mg/kg). Test samples were analyzed using the validated bioanalytical method to generate plasma concentration-time profiles. The results were further subjected to non-compartmental analysis using Phoenix 6.4®. MES207 exhibits a large volume of distribution (1.2 ± 0.6 L), high clearance (0.8 ± 0.1 L/h), and a poor oral bioavailability (1.7 ± 0.4%). The compound also showed a multiple peak phenomenon with a very short absorption phase. It appears that gender does not significantly influence the differences in pharmacokinetic parameters of this NPFF probe.
Digital Messaging to Improve College Enrollment and Success

Abstract We investigate the efficacy of text messaging campaigns to support students with key steps in the college search, application, selection and transition process with concurrent cluster randomized control trials. Collaborating with national non-profit organizations, we implemented text-message based outreach to students in the high school graduating class of 2016 in over 700 high schools that primarily serve low-income students. Collaborating with several Texas school districts, we implemented a school-based version of the intervention. In contrast to the national version which produced null and negative effects, the school-based intervention yielded positive and significant impacts on several college-going steps but still only yielded significant impacts on college enrollment and second-year persistence for certain subgroups.
Use of Photovoice to engage stakeholders in planning for patient-centered outcomes research.

Research is needed to inform patient and provider decisions about how to best care for patients who go to the emergency department with complaints of chest pain when their symptoms are due to anxiety rather than a heart problem. However, this research may not be a high priority due, in part, to a lack of awareness for the severity of anxiety symptoms and the impact of anxiety on peoples’ daily lives. In this commentary article, we highlight the use of Photovoice as a unique method to share patients’ lived experience of anxiety with providers, researchers, and health system leaders. A brief background on Photovoice methods, the process of patient partner involvement in Photovoice, and the project’s Photovoice results (posters, photos and captions) is presented. Photovoice achieved its intended effects of increasing awareness of all stakeholders about the burden of anxiety in patients’ lives and the imperative of improving emergency department care for anxiety. This resulted in increased participation in a multi-stakeholder research partnership, critical health system support that included costs to the health system associated with implementing interventions to be tested, and submission of a patient-centered outcomes research proposal that is currently under review. In addition, Photovoice had positive benefits for participants including a therapeutic effect, may have increased group cohesion, and empowerment of patients as partners in the research process.
Implied Constraint Satisfaction in Power System optimization: The Impacts of Load Variations

In many power system optimization problems, we observe that only a small fraction of the line flow constraints ever become active at the optimal solution, despite variations in the load profile and generation costs. This observation has far-reaching implications not only for power system optimization, but also for practical applications such as long-term planning, operation, and control of the system.This paper presents a constraint screening approach to identify constraints whose satisfaction is implied by other constraints in the problem, and can therefore be safely disregarded. The approach is targeted at problems which involve DC power flow constraints, and involves two steps. The first step uses simple analytical relationships to remove redundant limits on parallel lines. The second step uses optimization to consider interactions among all of the problem constraints. In essence, we solve a (relaxed) optimization problem for each constraint to identify whether it is redundant. Different from existing methods that focus on constraint screening for a given daily load profile, we consider ranges of load that are wide enough to represent yearly variations in loading. The constraint screening results are thus valid for long periods of time, justifying the computational overhead required for the screening method. Numerical results for a wide variety of standard test cases show that even with load variations up to ±100% of nominal loading, we are able to eliminate a significant fraction of the transmission constraints. This large reduction in constraints may enable computational gains across a range of possible applications. As one illustrative example, we demonstrate the computational improvements for the unit commitment problem obtained as a result of the reduced number of constraints.
Excited states via coupled cluster theory without equation-of-motion methods: Seeking higher roots with application to doubly excited states and double core hole states

In this work, we revisited the idea of using the coupled-cluster (CC) ground state formalism to target excited states. Our main focus was targeting doubly excited states and double core hole states. Typical equation-of-motion (EOM) approaches for obtaining these states struggle without higher-order excitations than doubles. We showed that by using a non-Aufbau determinant optimized via the maximum overlap method, the CC ground state solver can target higher energy states. Furthermore, just with singles and doubles (i.e., CCSD), we demonstrated that the accuracy of ΔCCSD and ΔCCSD(T) (triples) far surpasses that of EOM-CCSD for doubly excited states. The accuracy of ΔCCSD(T) is nearly exact for doubly excited states considered in this work. For double core hole states, we used an improved ansatz for greater numerical stability by freezing core hole orbitals. The improved methods, core valence separation (CVS)-ΔCCSD and CVS-ΔCCSD(T), were applied to the calculation of the double ionization potential of small molecules. Even without relativistic corrections, we observed qualitatively accurate results with CVS-ΔCCSD and CVS-ΔCCSD(T). Remaining challenges in ΔCC include the description of open-shell singlet excited states with the single-reference CC ground state formalism as well as excited states with genuine multireference character. The tools and intuition developed in this work may serve as a stepping stone toward directly targeting arbitrary excited states using ground state CC methods.
A Study of the Residual Ionization in a Gas with Reference to Temperature Effects

A Study of the Residual Ionization in a Gas with Reference to Temperature Effects.---A form of electrometer was constructed which used the principle of the Wulf electrometer in separating the conduction of charge across the insulation from the conduction in the gas due to ionization. The new features of this apparatus were that it was possible (1) to make a quick and accurate test of the insulation properties under the same conditions as those under which the ionization tests were made, and (2) to subject the instrument to a wide range of temperatures.Ions generated per C.C. per Second.---The data experimentally determined show that the number of ions generated per c.c. per second within an air tight chamber is 8.22 in the basement of the Physical Laboratory and 4.15 over the Pacific Ocean.Residual Ionization not due to Thermal Impact.---The results of tests between -44.6\ifmmode^\circ\else\textdegree\fi{} C. and 92.5\ifmmode^\circ\else\textdegree\fi{} C. show no indications that the residual ionization is due in any part to a molecular impact of thermal agitation.Effect of Temperature on Insulation System.---Observations made of changes in temperature on the insulation system, would seem to account for the apparent daily and seasonal variations of the residual ionization as previously reported.Conclusions from Observations at Low Temperatures.---At temperatures from -30.5\ifmmode^\circ\else\textdegree\fi{} C. to -44.6\ifmmode^\circ\else\textdegree\fi{} C. an increase in conduction across the insulation system was noticed, which was comparable to the apparent increase in ionization as reported at high altitudes. It would therefore seem that it is not necessary to assume, as has been done by previous observers, that there is a highly radioactive cosmic layer in the upper atmosphere; or that the sun is a source of penetrating radiation sufficient to generate 90 ions per c.c. per second.
Scalable Decision-Theoretic Planning in Open and Typed Multiagent Systems.

In open agent systems, the set of agents that are cooperating or competing changes over time and in ways that are nontrivial to predict. For example, if collaborative robots were tasked with fighting wildfires, they may run out of suppressants and be temporarily unavailable to assist their peers. We consider the problem of planning in these contexts with the additional challenges that the agents are unable to communicate with each other and that there are many of them. Because an agent's optimal action depends on the actions of others, each agent must not only predict the actions of its peers, but, before that, reason whether they are even present to perform an action. Addressing openness thus requires agents to model each other's presence, which becomes computationally intractable with high numbers of agents. We present a novel, principled, and scalable method in this context that enables an agent to reason about others' presence in its shared environment and their actions. Our method extrapolates models of a few peers to the overall behavior of the many-agent system, and combines it with a generalization of Monte Carlo tree search to perform individual agent reasoning in many-agent open environments. Theoretical analyses establish the number of agents to model in order to achieve acceptable worst case bounds on extrapolation error, as well as regret bounds on the agent's utility from modeling only some neighbors. Simulations of multiagent wildfire suppression problems demonstrate our approach's efficacy compared with alternative baselines.
On the Inefficiency of Forward Markets in Leader–Follower Competition

The role of forward contracts in mitigating market power is an important and recurring theme in oligopolistic industries, such as electricity and gas. In “On the Inefficiency of Forward Markets in ...
The lipid elongation enzyme ELOVL2 is a molecular regulator of aging in the retina.

Methylation of the regulatory region of the elongation of very‐long‐chain fatty acids‐like 2 (ELOVL2) gene, an enzyme involved in elongation of long‐chain polyunsaturated fatty acids, is one of the most robust biomarkers of human age, but the critical question of whether ELOVL2 plays a functional role in molecular aging has not been resolved. Here, we report that Elovl2 regulates age‐associated functional and anatomical aging in vivo, focusing on mouse retina, with direct relevance to age‐related eye diseases. We show that an age‐related decrease in Elovl2 expression is associated with increased DNA methylation of its promoter. Reversal of Elovl2 promoter hypermethylation in vivo through intravitreal injection of 5‐Aza‐2’‐deoxycytidine (5‐Aza‐dc) leads to increased Elovl2 expression and rescue of age‐related decline in visual function. Mice carrying a point mutation C234W that disrupts Elovl2‐specific enzymatic activity show electrophysiological characteristics of premature visual decline, as well as early appearance of autofluorescent deposits, well‐established markers of aging in the mouse retina. Finally, we find deposits underneath the retinal pigment epithelium in Elovl2 mutant mice, containing components found in human drusen, a pathologic hallmark of age related macular degeneration. These findings indicate that ELOVL2 activity regulates aging in mouse retina, provide a molecular link between polyunsaturated fatty acids elongation and visual function, and suggest novel therapeutic strategies for the treatment of age‐related eye diseases.
Transparency in Structural Research

We propose a formal definition of transparency in empirical research and apply it to structural estimation in economics. We discuss how some existing practices can be understood as attempts to impr...
The α-synuclein hereditary mutation E46K unlocks a more stable, pathogenic fibril structure.

Aggregation of α-synuclein is a defining molecular feature of Parkinson's disease, Lewy body dementia, and multiple systems atrophy. Hereditary mutations in α-synuclein are linked to both Parkinson's disease and Lewy body dementia; in particular, patients bearing the E46K disease mutation manifest a clinical picture of parkinsonism and Lewy body dementia, and E46K creates more pathogenic fibrils in vitro. Understanding the effect of these hereditary mutations on α-synuclein fibril structure is fundamental to α-synuclein biology. We therefore determined the cryo-electron microscopy (cryo-EM) structure of α-synuclein fibrils containing the hereditary E46K mutation. The 2.5-A structure reveals a symmetric double protofilament in which the molecules adopt a vastly rearranged, lower energy fold compared to wild-type fibrils. We propose that the E46K misfolding pathway avoids electrostatic repulsion between K46 and K80, a residue pair which form the E46-K80 salt bridge in the wild-type fibril structure. We hypothesize that, under our conditions, the wild-type fold does not reach this deeper energy well of the E46K fold because the E46-K80 salt bridge diverts α-synuclein into a kinetic trap-a shallower, more accessible energy minimum. The E46K mutation apparently unlocks a more stable and pathogenic fibril structure.
Persistence of averages in financial Markov Switching models: A large deviations approach

Abstract The behavior of time averages, or functions of them, is important in quantitative research. Over an investment horizon, both the time-averaged number of loan defaults and the time-averaged log gross returns from securities investment, a.k.a. the continuously compounded cumulative rate of return (CROR), are important random variables affecting the performance of loan and securities portfolios, respectively. In ergodic models, the randomness in such averages is eliminated only asymptotically. The statistical theory of Large Deviations provides simply computed and useful tools for analyzing this persistence, and is developed and applied to Markov Switching models of loan defaults and securities portfolio choice.
Explicit modular forms from the divided beta family

Abstract We compute modular forms known to arise from the order 5 generators of the 5-local Adams-Novikov spectral sequence 2-line, generalizing and contextualizing previous computations of M. Behrens and G. Laures. We exhibit analogous computations at other primes and conjecture formulas for some of the modular forms arising in this way at arbitrary primes ≥5.
Optically enriched and guided dynamics of active skyrmions.

Light provides a powerful means of controlling physical behavior of materials but is rarely used to power and guide active matter systems. We demonstrate optical control of liquid crystalline topological solitons dubbed “skyrmions”, which recently emerged as highly reconfigurable inanimate active particles capable of exhibiting emergent collective behaviors like schooling. Because of a chiral nematic liquid crystal’s natural tendency to twist and its facile response to electric fields and light, it serves as a testbed for dynamic control of skyrmions and other active particles. Using ambient-intensity unstructured light, we demonstrate large-scale multifaceted reconfigurations and unjamming of collective skyrmion motions powered by oscillating electric fields and guided by optically-induced obstacles and patterned illumination.
Robust, Accurate, and Efficient: Quantum Embedding Using the Huzinaga Level-Shift Projection Operator for Complex Systems.

Using wave function (WF) in density functional theory (DFT) embedding methods provides a framework for performing localized, high-accuracy WF calculations on a system, while not incurring the full ...
Learning to Explore using Active Neural SLAM

This work presents a modular and hierarchical approach to learn policies for exploring 3D environments, called `Active Neural SLAM'. Our approach leverages the strengths of both classical and learning-based methods, by using analytical path planners with learned SLAM module, and global and local policies. The use of learning provides flexibility with respect to input modalities (in the SLAM module), leverages structural regularities of the world (in global policies), and provides robustness to errors in state estimation (in local policies). Such use of learning within each module retains its benefits, while at the same time, hierarchical decomposition and modular training allow us to sidestep the high sample complexities associated with training end-to-end policies. Our experiments in visually and physically realistic simulated 3D environments demonstrate the effectiveness of our approach over past learning and geometry-based approaches. The proposed model can also be easily transferred to the PointGoal task and was the winning entry of the CVPR 2019 Habitat PointGoal Navigation Challenge.
Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

Environmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear. To describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2471 genes) were significantly differentially expressed for the effect of diet, and 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, Padj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (FDR Padj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing many cellular and nuclear processes (Fisher exact test, Padj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5, Rheb, and Sirt2 showed significant elevation in expression, many key genes such as InR, chico, most insulin peptide genes, and the nutrient-sensing pathways were not observed. Our results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.
The Kraft–Russell Generic Equivalence Theorem and Its Application

We find some extensions of the Kraft–Russell generic equivalence theorem, and we improve a result of Dubouloz and Kishimoto.
Adolescent Depression and Adult Labor Market Outcomes

This article uses recently released data from a national longitudinal sample to present new evidence of the longer term effects of adolescent depression on labor market outcomes. Results suggest reductions in labor force attachment of approximately 5% and earnings reductions of approximately 15% for individuals with depressive symptoms as an adolescent. These effects are only partially reduced when controlling for channels operating through educational attainment, adult depressive symptoms, or co-occurring illnesses. Further, the unique structure of the data allows for high-school fixed effects as well as suggestive evidence using sibling comparisons, which allows controls for potentially important unobserved heterogeneity. Overall, the results suggest that the links between adolescent depression and labor market outcomes are quite robust and important in magnitude, suggesting the need for further investments in treatment options and opportunities during adolescence, which will likely result in long term returns.
Strength from Within: Internal Mobility and the Retention of High Performers

We develop and test a theoretically informed and generalizable empirical framework for evaluating the performance gap between internally and externally hired workers. First, human capital theory pr...
Globalization and Changing Patterns in the International Transmission of Shocks in Financial Markets

Abstract This paper compares the strength of, and patterns in the transmission of shocks, and currency crises during two periods of globalization—the pre-WWI classical gold standard era, 1880–1914, and the post-Bretton Woods era, 1975–2001. Our results suggest that financial market shocks were more globalized before 1914 compared to the present. We postulate that this difference in systemic stability between the two eras reflects factors such as strong cross-country interdependence fostered through links to gold, the growing financial maturity of advanced countries, and the widening of the center to include a more diverse group of countries spanning several regions.
Instability of nanometric fluid films on a thermally conductive substrate

The dynamics of a thin, incompressible viscous fluid, subject to both van der Waals and Marangoni forces, on a thermally conducting substrate, is theoretically considered in the regime where the temperature field of the film and of the substrate evolve on a comparable time scale. Calculations show that the Marangoni flows have a strong effect on the instability and that the evolution of the temperature field, coupled to the evolving film profile, qualitatively changes the instability.
An Implementation of Automatic Array Arithmetic by a Generalized Push-Down Stack

One of the most fundamental and useful notions of mathematical analysis is the concept of a continuous, single valued function of one independent variable. By y = f(x) we mean that for every x in the range of x, defined as α ≤ x ≤ β, the mapping f provides us with a value in the domain of the function yα ≤ y ≤ yβ, where yα = f(xα) and yβ = f(xβ). In a numerical computation we represent the part of the range of the independent variable, which is of interest to us, by a suitably chosen ordered set of n + 1 values (x0, x1, x2, . . ., xn), and a representation of any function over this range is then found by evaluating y = f(x) at these points, to obtain a corresponding ordered set of values (y0, y1, y2, . . ., yn). Because of the obvious analogy, these arrays of numbers representing continuous functions are often called vectors. However, a semantic problem arises when we discuss vectors of functions, such as the vector potential or the wind velocity patterns in the atmosphere. Therefore, I prefer to make a special case of the representations of continuous functions and refer to them as arrays rather than vectors.
Developmental programming: Transcriptional regulation of visceral and subcutaneous adipose by prenatal bisphenol-A in female sheep.

Abstract Background Bisphenol-A (BPA) exposure is widespread and early life exposure is associated with metabolic syndrome. While visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) are implicated in the development of metabolic syndrome, the adipose depot-specific effects of prenatal BPA treatment are poorly understood. Objective To determine the impact of prenatal BPA exposure on genome-wide gene expression of VAT and SAT depots. Methods RNA sequencing was performed on SAT and VAT from 21-month old control and prenatal BPA-treated female sheep. Gene expression and pathway differences between SAT and VAT depots with or without prenatal BPA-treatment and the effect of prenatal BPA treatment on each depot were tested. Results There were 179 differentially expressed genes (padjusted 2.5) between SAT and VAT. Development and immune response pathways were upregulated in SAT, while metabolic pathways were upregulated in VAT. These adipose depot-specific genes and pathways were consistent with prenatal BPA-treatment. In SAT, BPA-treatment resulted in differential expression of 108 genes (78% upregulated with BPA) and altered pathways (immune response downregulated, RNA processing upregulated). In contrast in VAT, BPA-treatment differentially expressed 4 genes and upregulated chromatin and RNA processing pathways. Conclusion Prenatal BPA-treatment induces adult depot-specific alterations in RNA expression in inflammation, RNA processing, and chromatin pathways, reflecting the diverse roles of SAT and VAT in regulating lipid storage and insulin sensitivity. These adipose tissue transcriptional dysregulations may contribute to the metabolic disorders observed in prenatal BPA-treated female sheep.
DNA origami and unknotted A-trails in torus graphs

Motivated by problem of determining the unknotted routes for the scaffolding strand in DNA origami self-assembly, we examine the existence and knottedness of A-trails in graphs embedded on the toru...
COVID-19 global pandemic planning: Decontamination and reuse processes for N95 respirators.

Coronavirus disease 2019 (COVID-19) is an illness caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease was first identified as a cluster of respi...
Two Computational Models for Analyzing Political Attention in Social Media

Understanding how political attention is divided and over what subjects is crucial for research on areas such as agenda setting, framing, and political rhetoric. Existing methods for measuring attention, such as manual labeling according to established codebooks, are expensive and can be restrictive. We describe two computational models that automatically distinguish topics in politicians' social media content. Our models—one supervised classifier and one unsupervised topic model—provide different benefits. The supervised classifier reduces the labor required to classify content according to pre-determined topic list. However, tweets do more than communicate policy positions. Our unsupervised model uncovers both political topics and other Twitter uses (e.g., constituent service). These models are effective, inexpensive computational tools for political communication and social media research. We demonstrate their utility and discuss the different analyses they afford by applying both models to the tweets posted by members of the 115th U.S. Congress.
Shallow Distance Dependence for Proton-Coupled Tyrosine Oxidation in Oligoproline Peptides

We have explored the kinetic effect of increasing electron transfer (ET) distance in a biomimetic, proton-coupled electron-transfer (PCET) system. Biological ET often occurs simultaneously with pro...
Radar Human Motion Recognition Using Motion States and Two-Way Classifications

We perform classification of Activities of Daily Living (ADL) using a Frequency-Modulated Continuous Waveform (FMCW) radar. In particular, we consider contiguous motions that are inseparable in time. Both the micro-Doppler signature and range-map are used to determine transitions from translation (walking) to in-place motions and vice versa, as well as to provide motion onset and offset times. The in-place motion classes post and prior to walking can be separately handled by forward and backward in time classifiers. The paper describes ADL in terms of motion states and transitioning motions or activities, and sets forward a framework to deal with time separable and inseparable activities. It is shown that limiting the classes of activities, which are physically possible and associated with the current state, improves the classification rates compared to incorporating all ADL for any given time.
AdvAug: Robust Adversarial Augmentation for Neural Machine Translation

In this paper, we propose a new adversarial augmentation method for Neural Machine Translation (NMT). The main idea is to minimize the vicinal risk over virtual sentences sampled from two vicinity distributions, in which the crucial one is a novel vicinity distribution for adversarial sentences that describes a smooth interpolated embedding space centered around observed training sentence pairs. We then discuss our approach, AdvAug, to train NMT models using the embeddings of virtual sentences in sequence-to-sequence learning. Experiments on Chinese-English, English-French, and English-German translation benchmarks show that AdvAug achieves significant improvements over theTransformer (up to 4.9 BLEU points), and substantially outperforms other data augmentation techniques (e.g.back-translation) without using extra corpora.
Faces under continuous flash suppression capture attention faster than objects, but without a face-evoked steady-state visual potential: Is curvilinearity responsible for the behavioral effect?

Abstract Face perception is a vital part of human social interactions. The social value of faces makes their efficient detection evolutionarily advantageous. It has been suggested that this might occur nonconsciously, but experimental results are equivocal thus far. Here, we probe nonconscious face perception using a novel combination of binocular rivalry with continuous flash suppression, and steady-state visually evoked potentials. In the first two experiments, participants viewed either non-face objects, neutral faces (Study 1), or fearful faces (Study 2). Consistent with the hypothesis that faces are processed nonconsciously, we found that faces broke through suppression faster than objects. We did not, however, observe a concomitant face-selective SSVEP. Study 3 was run to reconcile this paradox. We hypothesized that the faster breakthrough time was due to a mid-level visual feature, curvilinearity, rather than high-level category membership, which would explain the behavioral difference without neural evidence of face-selective processing. We tested this hypothesis by presenting participants with four different groups of stimuli outside of conscious awareness: rectilinear objects (e.g., chessboard), curvilinear objects (e.g., dartboard), faces, and objects that were not dominantly curvilinear or rectilinear. We found that faces and curvilinear objects broke through suppression faster than objects and rectilinear objects. Moreover, there was no difference between faces and curvilinear objects. These results support our hypothesis that the observed behavioral advantage for faces is due to their curvilinearity, rather than category membership. Highlights Faces presented outside of awareness do not evoke a steady-state visually evoked potential. This is true for both neutral and fearful faces. However, faces do breakthrough interocular suppression faster than objects. Curvilinear objects breakthrough interocular suppression faster than rectilinear objects. The breakthrough time advantage for faces over objects is due to their curvilinearity.
On Decoupling the Integrals of Cosmological Perturbation Theory

Author(s): Slepian, Zachary | Abstract: Perturbation theory (PT) is often used to model statistical observables capturing the translation and rotation-invariant information in cosmological density fields. PT produces higher-order corrections by integration over linear statistics of the density fields weighted by kernels resulting from recursive solution of the fluid equations. These integrals quickly become high-dimensional and naively require increasing computational resources the higher the order of the corrections. Here we show how to decouple the integrands that often produce this issue, enabling PT corrections to be computed as a sum of products of independent 1-D integrals. Our approach is related to a commonly used method for calculating multi-loop Feynman integrals in Quantum Field Theory, the Gegenbauer Polynomial $x$-Space Technique (GPxT). We explicitly reduce the three terms entering the 2-loop power spectrum, formally requiring 9-D integrations, to sums over successive 1-D radial integrals. These 1-D integrals can further be performed as convolutions, rendering the scaling of this method $N_{\rm g} \log N_{\rm g}$ with $N_{\rm g}$ the number of grid points used for each Fast Fourier Transform. This method should be highly enabling for upcoming large-scale structure redshift surveys where model predictions at an enormous number of cosmological parameter combinations will be required by Monte Carlo Markov Chain searches for the best-fit values.
Synthesis and characterization of optically transparent ceramic crystalline/amorphous and amorphous/amorphous multilayers

Abstract Optical nano multilayers (NMs) are promising candidates for durable transparent multifunctional coatings, where the contributions of interfaces and high transparency configurations have yet to be explored. To address this, high transparency NMs (%T380-1100nm≈94–99%) were synthesized by magnetron sputtering, and the effects of crystalline/amorphous (AlN/SiO2, AlN/Al2O3) and amorphous/amorphous (TiO2/SiO2) interfaces were characterized by spectrophotometry, transmission electron microscopy, and nanoindentation. We demonstrate that tuning layer configurations for improved transmittance resulted in substantial variations in microstructure and multifunctional film properties. Overall, this work presents a methodology for evaluating the structure-properties relationship in optical NMs in the context of interface character and layer microstructure.
Comparative American and Japanese tobacco smoke uptake parameters after overnight tobacco deprivation

Tyndale et al. (2002) reported that Japanese, among various ethnic groups, have a relatively high incidence of lower activity CYP2A6 genotypes and are associated with decreased risk for tobacco smoking. Furthermore, a very large percentage of male Japanese smoke. American and Japanese overnight deprived tobacco smokers were phenotyped with respect to expired CO, plasma nicotine and cotinine, and red cell COHb. The participants were 51 American and 55 Japanese cigarette smokers of mixed gender who met similar strict criteria. American and Japanese female smokers had similar tobacco uptake parameters. American and Japanese male smokers differed; the latter had higher plasma nicotine and lower cotinine levels as well as calculated 24 hr dose of nicotine and lower exhaled CO. Japanese females and males were similar in all tobacco smoke uptake parameters. When the two racial groups were compared, irrespective of gender, the only statistically significant differences were lower mean exhaled CO levels and percent COHb in the Japanese. It is concluded that Japanese males inhale cigarettes in moderation compared to Americans. Clinical Pharmacology & Therapeutics (2004) 75, P72–P72; doi: 10.1016/j.clpt.2003.11.272
Refinement of Novikov–Betti Numbers and of Novikov Homology Provided by an Angle Valued Map

To a pair (X, f), where X is a compact ANR and f : X → 𝕊1 is a continuous angle valued map, a field κ, and a nonnegative integer r, one assigns a finite configuration of complex numbers z with multiplicities δfr (z) and a finite configuration of free κ[t−1, t]-modules $$ {\hat{\delta}}_r^f $$ of rank $$ {\delta}_r^f $$ (z) indexed by the same numbers z. This is in analogy with the configuration of eigenvalues and of generalized eigenspaces of a linear operator in a finite-dimensional complex vector space. The configuration $$ {\delta}_r^f $$ refines the Novikov–Betti number in dimension r, and the configuration $$ {\hat{\delta}}_r^f $$ refines the Novikov homology in dimension r associated with the cohomology class defined by f. In the case of the field κ = C, the configuration $$ {\hat{\delta}}_r^f $$ provides by “von-Neumann completion” of a configuration $$ {\hat{\hat{\delta}}}_r^f $$ of mutually orthogonal closed Hilbert submodules of the L2-homology of the infinite cyclic cover of X determined by the map f, which is an L∞(𝕊1)-Hilbert module.
The ionization structure of planetary nebulae. V - NGC 3242

Spectrophotometric observations of emission line intensities over the spectral range 1400 A to 9600 A were made in five positions in the planetary nebula NGC 3242. In two of the positions, both the weakness of the 1548 A, 1550 A C IV resonance lines and the steepness of the Balmer decrement suggest the possibility of internal dust in the nebula. The measured electron temperature varies little from the average value of 11,100 K, which is in reasonably good agreement with the less accurate value of 12,900 K measured from the Balmer continuum. The 4267 A C II line implies a C(2+) abundance that is much higher than that determined from the 1906 A, 1908 A C III lines. This discrepancy decreases with increasing distance from the central star. Equations used to correct for the existence of elements in other than the optically-observable ionization stages give results that are consistent and in agreement with abundances calculated using ultraviolet lines. This discrepancy decreases with increasing distance from the central star. Equations used to correct for the existence of elements in other than the optically-observable ionization stages give results that are consistent and in agreement with abundances calculated using ultraviolet lines. The logarithmicmore » abundances are He = 10.96, O = 8.64, N = 7.96, Ne = 8.04, C = 8.41, Ar = 6.15, and S = 6.51. 22 references.« less
Common Baltic-Nordic Business Cycles : Correlation- versus Markov-switching Approaches

With strong historical ties, and economic linkages that have continued to grow after the fall of the Soviet Union, the Baltic and Nordic regions form a unique economic space. How interconnected are these regions, both to each other and to the rest of the world? Greater connections can help forecast future economic linkages—and also help assess the strength of the Euro as a common currency. This study applies two methods of business-cycle analysis (cross-correlations and Markov switching approaches) to seven countries in these regions. Both methods find evidence of a single Baltic common cycle for both output and consumption, while a Nordic cycle exists only for output, and there is no single common Baltic-Nordic cycle. Tests of correlation and concordance show there to be relatively strong connections with Germany, the U.S., and Russia—with Nordic-Baltic linkages also quire strong—but that the specific results vary by the method used
Evaluation of reproducible and transparent research practices in pulmonology.

Abstract Background Study reproducibility is valuable for validating or refuting results. Provision of reproducibility indicators, such as materials, protocols, and raw data in a study improve its potential for reproduction. Efforts to reproduce noteworthy studies in the biomedical sciences have resulted in an overwhelming majority of them being found to be unreplicable, causing concern for the integrity of research in other fields, including medical specialties. Here, we analyzed the reproducibility of studies in the field of pulmonology. Methods 500 pulmonology articles were randomly selected from an initial PubMed search for data extraction. Two authors scoured these articles for reproducibility indicators including materials, protocols, raw data, analysis scripts, inclusion in systematic reviews, and citations by replication studies as well as other factors of research transparency including open accessibility, funding source and competing interest disclosures, and study preregistration. Findings Few publications included statements regarding materials (10%), protocols (1%), data (15%), and analysis script (0%) availability. Less than 10% indicated preregistration. More than half of the publications analyzed failed to provide a funding statement. Conversely, 63% of the publications were open access and 73% included a conflict of interest statement. Interpretation Overall, our study indicates pulmonology research is currently lacking in efforts to increase replicability. Future studies should focus on providing sufficient information regarding materials, protocols, raw data, and analysis scripts, among other indicators, for the sake of clinical decisions that depend on replicable or refutable results from the primary literature.
CATASTROPHE AND RATIONAL POLICY: CASE OF NATIONAL SECURITY

Predicting catastrophes involves heavy‐tailed distributions with no mean, eluding proactive policy as expected cost‐benefit analysis fails. We study US government counterterrorism policy, given heightened risk of terrorism. But terrorism also involves human behavior. We synthesize the behavioral and statistical aspects in an adversary‐defender game. Calibration to extensive data shows that where a Weibull distribution is the best predictor, US counterterrorism policy is rational (and optimal). Here, we estimate the adversary's unobserved variables, e.g., difficulty of an attack. We also find cases where the best predictor is a Generalized‐Pareto with no finite mean and rational policy fails. Here, we offer “work‐arounds”. (JEL H56, D81, C46)
Phage-Antibiotic Synergy Is Driven by a Unique Combination of Antibacterial Mechanism of Action and Stoichiometry

The continued rise in antibiotic resistance is precipitating a medical crisis. Bacteriophage (phage) has been hailed as one possible therapeutic option to augment the efficacy of antibiotics. However, only a few studies have addressed the synergistic relationship between phage and antibiotics. Here, we report a comprehensive analysis of phage-antibiotic interaction that evaluates synergism, additivism, and antagonism for all classes of antibiotics across clinically achievable stoichiometries. We combined an optically based real-time microtiter plate readout with a matrix-like heat map of treatment potencies to measure phage and antibiotic synergy (PAS), a process we term synography. Phage-antibiotic synography was performed against a pandemic drug-resistant clonal group of extraintestinal pathogenic Escherichia coli (ExPEC) with antibiotic levels blanketing the MIC across seven orders of viral titers. Our results suggest that, under certain conditions, phages provide an adjuvating effect by lowering the MIC for drug-resistant strains. Furthermore, synergistic and antagonistic interactions are highly dependent on the mechanism of bacterial inhibition by the class of antibiotic paired to the phage, and when synergism is observed, it suppresses the emergence of resistant cells. Host conditions that simulate the infection environment, including serum and urine, suppress PAS in a bacterial growth-dependent manner. Lastly, two different related phages that differed in their burst sizes produced drastically different synograms. Collectively, these data suggest lytic phages can resuscitate an ineffective antibiotic for previously resistant bacteria while also synergizing with antibiotics in a class-dependent manner, processes that may be dampened by lower bacterial growth rates found in host environments.IMPORTANCE Bacteriophage (phage) therapy is a promising approach to combat the rise of multidrug-resistant bacteria. Currently, the preferred clinical modality is to pair phage with an antibiotic, a practice thought to improve efficacy. However, antagonism between phage and antibiotics has been reported, the choice of phage and antibiotic is not often empirically determined, and the effect of the host factors on the effectiveness is unknown. Here, we interrogate phage-antibiotic interactions across antibiotics with different mechanisms of action. Our results suggest that phage can lower the working MIC for bacterial strains already resistant to the antibiotic, is dependent on the antibiotic class and stoichiometry of the pairing, and is dramatically influenced by the host microenvironment.
Mental Distress and Mental Health Services Receipt in Foreign-Born Survivors of Cancer: a National Health Interview Survey Analysis.

e19001Background: There is a greater burden of mental illness, in survivors of cancer compared with the general population. Though mental health interventions may reduce mental distress and improve...
Concave Aspects of Submodular Functions

Submodular Functions are a special class of Set Functions, which generalize several Information Theoretic quantities such as Entropy and Mutual Information [1]. Submodular functions have subgradients and subdifferentials [2] and admit polynomial time algorithms for minimization, both of which are fundamental characteristics of convex functions. Submodular functions also show signs similar to concavity. Submodular function maximization, though NP hard, admits constant factor approximation guarantees and concave functions composed with modular functions are submodular. In this paper, we try to provide a more complete picture on the relationship between submodularity with concavity. We characterize the superdifferentials and polyhedra associated with upper bounds and provide optimality conditions for submodular maximization using the superdifferentials.
Molecular latent space simulators

Small integration time steps limit molecular dynamics (MD) simulations to millisecond time scales. Markov state models (MSMs) and equation-free approaches learn low-dimensional kinetic models from MD simulation data by performing configurational or dynamical coarse-graining of the state space. The learned kinetic models enable the efficient generation of dynamical trajectories over vastly longer time scales than are accessible by MD, but the discretization of configurational space and/or absence of a means to reconstruct molecular configurations precludes the generation of continuous atomistic molecular trajectories. We propose latent space simulators (LSS) to learn kinetic models for continuous atomistic simulation trajectories by training three deep learning networks to (i) learn the slow collective variables of the molecular system, (ii) propagate the system dynamics within this slow latent space, and (iii) generatively reconstruct molecular configurations. We demonstrate the approach in an application to Trp-cage miniprotein to produce novel ultra-long synthetic folding trajectories that accurately reproduce atomistic molecular structure, thermodynamics, and kinetics at six orders of magnitude lower cost than MD. The dramatically lower cost of trajectory generation enables greatly improved sampling and greatly reduced statistical uncertainties in estimated thermodynamic averages and kinetic rates.