cssi/SciSciGPT-SciSciNet huggingface dataset:
A Putative Microcin Amplifies Shiga Toxin 2a Production of Escherichia coli O157:H7.

ABSTRACT Escherichia coli O157:H7 is a foodborne pathogen implicated in various multistate outbreaks. It encodes Shiga toxin on a prophage, and Shiga toxin production is linked to phage induction. An E. coli strain, designated 0.1229, that amplified Stx2a production when cocultured with E. coli O157:H7 strain PA2 was identified. Growth of PA2 in 0.1229 cell-free supernatants had a similar effect, even when supernatants were heated to 100°C for 10 min, but not after treatment with proteinase K. The secreted molecule was shown to use TolC for export and the TonB system for import. The genes sufficient for production of this molecule were localized to a 5.2-kb region of a 12.8-kb plasmid. This region was annotated, identifying hypothetical proteins, a predicted ABC transporter, and a cupin superfamily protein. These genes were identified and shown to be functional in two other E. coli strains, and bioinformatic analyses identified related gene clusters in similar and distinct bacterial species. These data collectively suggest that E. coli 0.1229 and other E. coli strains produce a microcin that induces the SOS response in target bacteria. Besides adding to the limited number of microcins known to be produced by E. coli, this study provides an additional mechanism by which stx2a expression is increased in response to the gut microflora. IMPORTANCE How the gut microflora influences the progression of bacterial infections is only beginning to be understood. Antibiotics are counterindicated for E. coli O157:H7 infections, limiting treatment options. An increased understanding of how the gut microflora directs O157:H7 virulence gene expression may lead to additional treatment options. This work identified E. coli strains that enhance the production of Shiga toxin by O157:H7 through the secretion of a proposed microcin. Microcins are natural antimicrobial peptides that target specific species, can act as alternatives to antibiotics, and mediate microbial competition. This work demonstrates another mechanism by which non-O157 E. coli strains may increase Shiga toxin production and adds to our understanding of microcins, a group of antimicrobials less well understood than colicins.
Meta-Analysis Reveals Consistent Bacterial Responses to Land Use Change Across the Tropics

Bacterial communities are a major component of global diversity and are intimately involved in most terrestrial biogeochemical processes. Despite their importance, we know far less about the response of bacteria to human-induced environmental change than we do about other organisms. Understanding the response of organisms to land use change is especially pressing for tropical rainforests, which are being altered at a higher rate than any other ecosystem. Here, we conduct a meta-analysis of studies performed in each of the major tropical rainforest regions to ask whether there are consistent responses of belowground bacterial communities to the conversion of tropical rainforest to agriculture. Remarkably, we find common responses despite wide variation across studies in the types of agriculture practiced and the research methodology used to study land use change. These responses include changes in the relative abundance of phyla, most notably decreases in Acidobacteria (-1.94±1.1 fold (average±95%CI)) and Proteobacteria (-1.38±1.0 fold) and increases in Actinobacteria (1.55±1.1 fold), Chloroflexi (3.47±1.2 fold) and Firmicutes (6.6±1.3 fold). We also find that alpha diversity (at the scale of single soil cores) consistently increases (1.17±1.0-fold) with ecosystem conversion. These consistent responses suggest that, while there is great diversity in agricultural practices across the tropics, common features such as the use of slash-and-burn tactics have the potential to alter bacterial community composition and diversity belowground.
Matching extension and the genus of a graph

Let G be a connected graph with p points having a perfect matching and suppose n is a positive integer with n ≤ (p−2)2. Then G is n-extendable if every matching in G containing n lines is a subset of a perfect matching. In this paper we obtain an upper bound on the n-extendability of a graph in terms of its genus.
Steady states and dynamics of a thin-film-type equation with non-conserved mass

We study the steady states and dynamics of a thin-film-type equation with non-conserved mass in one dimension. The evolution equation is a non-linear fourth-order degenerate parabolic partial differential equation (PDE) motivated by a model of volatile viscous fluid films allowing for condensation or evaporation. We show that by changing the sign of the non-conserved flux and breaking from a gradient flow structure, the problem can exhibit novel behaviours including having two distinct classes of co-existing steady-state solutions. Detailed analysis of the bifurcation structure for these steady states and their stability reveals several possibilities for the dynamics. For some parameter regimes, solutions can lead to finite-time rupture singularities. Interestingly, we also show that a finite-amplitude limit cycle can occur as a singular perturbation in the nearly conserved limit.
Affective Pavlovian motivation is enhanced in obesity susceptible populations: Implications for incentive motivation in obesity

Continually rising global obesity rates present a major challenge to human health. The contribution of Pavlovian motivational processes to overeating and obesity has become increasingly apparent. In humans, brain and behavioral reactivity to food-related stimuli positively correlates with subsequent weight gain. In concordance with this, selectively bred obesity-prone rats show stronger single-outcome Pavlovian-to-instrumental transfer (SO PIT) than obesity-resistant rats, providing support for the hypothesis that enhanced Pavlovian motivation is a pre-existing phenotype of obesity-susceptibility. However, whether obesity-susceptibility in outbred rats is associated with similar enhancements in PIT was unknown. Moreover, given that SO PIT does not distinguish between sensory specific and general affective motivational processes, it was unclear which of these was linked to obesity-susceptibility. Thus, here we determined whether obesity-susceptibility is associated with enhanced Sensory Specific (SS) PIT versus General PIT using both outbred and selectively bred populations. Rats were trained with two action-outcome and three stimulus-outcome associations; two of the Pavlovian and instrumental associations shared a common outcome. During PIT testing, the influence of the Pavlovian stimuli on the two instrumental responses were measured simultaneously. In outbred rats, expression of General PIT was positively correlated with subsequently determined obesity-susceptibility. In selectively bred rats, General PIT was stronger in obesity-prone versus obesity-resistant rats. Jointly, these data show that enhanced affective Pavlovian motivation is tightly linked to obesity vulnerability, supporting a role for phenotypic differences in incentive motivation in vulnerability to obesity. This has important implications for obesity prevention and for the specific neurocircuitry underlying enhanced food-seeking in vulnerable populations.
Automatic Quantification of Facial Asymmetry Using Facial Landmarks

One-sided facial paralysis causes uneven movements of facial muscles on the sides of the face. Physicians currently assess facial asymmetry in a subjective manner based on their clinical experience. This paper proposes a novel method to provide an objective and quantitative asymmetry score for frontal faces. Our metric has the potential to help physicians for diagnosis as well as monitoring the rehabilitation of patients with one-sided facial paralysis. A deep learning based landmark detection technique is used to estimate style invariant facial landmark points and dense optical flow is used to generate motion maps from a short sequence of frames. Six face regions are considered corresponding to the left and right parts of the forehead, eyes, and mouth. Motion is computed and compared between the left and the right parts of each region of interest to estimate the symmetry score. For testing, asymmetric sequences are synthetically generated from a facial expression dataset. A score equation is developed to quantify symmetry in both symmetric and asymmetric face sequences.
Cognitive Modeling Informs Interpretation of Go/No-Go Task-Related Neural Activations and Their Links to Externalizing Psychopathology.

Abstract Background Individuals with attention-deficit/hyperactivity disorder and other externalizing psychopathologies tend to display poor behavioral performance on the go/no-go task, which is thought to reflect deficits in inhibitory control. However, clinical neuroimaging studies using this task have yielded conflicting results, raising basic questions about what the task measures and which aspects of the task relate to clinical outcomes. We used computational modeling to provide a clearer understanding of how neural activations from this task relate to the cognitive mechanisms that underlie performance and to probe the implications of these relationships for clinical research. Methods A total of 143 young adults (8–21 years of age) performed the go/no-go task during functional magnetic resonance imaging scanning. We used the diffusion decision model (DDM), a cognitive modeling approach, to quantify distinct neurocognitive processes that underlie go/no-go performance. We then assessed correlations between DDM parameters and brain activation from standard go/no-go contrasts and assessed relationships of DDM parameters and associated neural measures with clinical ratings. Results Right-lateralized prefrontal activations on correct inhibition trials, which are generally assumed to isolate neural processes involved in inhibition, were unrelated to DDM parameters (and other performance indices). However, responses to failed inhibitions in brain regions associated with error monitoring were strongly related to more efficient task performance and correlated with externalizing behavior and attention-deficit/hyperactivity disorder symptoms. Conclusions Our findings cast doubt on conventional interpretations of go/no-go task-related activations as reflecting the neural basis of inhibitory functioning. We instead found evidence that error-related contrasts provide clinically relevant information about neural systems involved in monitoring and optimizing the efficiency of cognitive performance.
Commentary on the Liquid Metallic Hydrogen Model of the Sun: Insight Relative to Coronal Holes, Sunspots, and Solar Activity

While mankind will always remain unable to sample the interior of the Sun, the presence of sunspots and coronal holes can provide clues as to its subsurface structure. Insight relative to the solar body can also be gained by recognizing that the Sun must exist in the condensed state and support a discrete lattice structure, as required for the production of its continuous spectrum. In this regard, the layered liquid metallic hydrogen lattice advanced as a condensed model of the Sun (Robitaille P.M. Liquid Metallic Hydrogen: A Building Block for the Liquid Sun. Progr. Phys., 2011, v. 3, 60–74; Robitaille P.M. Liquid Metallic Hydrogen II: A Critical Assessment of Current and Primordial Helium Levels in Sun. Progr. Phys., 2013, v. 2, 35–47; Robitaille J.C. and Robitaille P.M. Liquid Metallic Hydrogen III. Intercalation and Lattice Exclusion Versus Gravitational Settling and Their Consequences Relative to Internal Structure, Surface Activity, and Solar Winds in the Sun. Progr. Phys., 2013, v. 2, in press) provides the ability to add structure to the solar interior. This constitutes a significant advantage over the gaseous solar models. In fact, a layered liquid metallic hydrogen lattice and the associated intercalation of non-hydrogen elements can help to account for the position of sunspots and coronal holes. At the same time, this model provides a greater understanding of the mechanisms which drive solar winds and activity. As the laws of a liquid are diff erent from those of a gas, a liquid star will behave diff erently from a gaseous star, and before we can predict the behaviour of a star we must know the state of the matter composing it. James Hopwood Jeans, 1928 [1]
Breakdown in the wetting transparency of graphene

We develop a theory to model the van der Waals interactions between liquid and graphene, including quantifying the wetting behavior of a graphene-coated surface. Molecular dynamics simulations and contact angle measurements were also carried out to test the theory. We show that graphene is only partially transparent to wetting and that the predicted highest attainable contact angle of water on a graphene-coated surface is 96°. Our findings reveal a more complex picture of wetting on graphene than what has been reported recently as complete "wetting transparency."
Improving Visual Feature Extraction in Glacial Environments

Glacial science could benefit tremendously from autonomous robots, but previous glacial robots have had perception issues in these colorless and featureless environments, specifically with visual feature extraction. This translates to failures in visual odometry and visual navigation. Glaciologists use near-infrared imagery to reveal the underlying heterogeneous spatial structure of snow and ice, and we theorize that this hidden near-infrared structure could produce more and higher quality features than available in visible light. We took a custom camera rig to Igloo Cave at Mt. St. Helens to test our theory. The camera rig contains two identical machine vision cameras, one which was outfitted with multiple filters to see only near-infrared light. We extracted features from short video clips taken inside Igloo Cave at Mt. St. Helens, using three popular feature extractors (FAST, SIFT, and SURF). We quantified the number of features and their quality for visual navigation by comparing the resulting orientation estimates to ground truth. Our main contribution is the use of NIR longpass filters to improve the quantity and quality of visual features in icy terrain, irrespective of the feature extractor used.
Dissimilarity Vectors of Trees are Contained in the Tropical Grassmannian

In this short writing, we prove that the set of $m$-dissimilarity vectors of phylogenetic $n$-trees is contained in the tropical Grassmannian ${\cal G}_{m,n}$, answering a question of Pachter and Speyer. We do this by proving an equivalent conjecture proposed by Cools.
Toward an Improved Method for Determining the Hamaker Constant of Solid Materials Using Atomic Force Microscopy. I. Quasi-Static Analysis for Arbitrary Surface Roughness

The initial development and preliminary validation of improvements to an existing approach-to-contact atomic force microscopy (AFM) method for determining the Hamaker constant, A, of solid material...
A fractional free boundary problem related to a plasma problem

We study a fractional analogue of a plasma problem arising from physics. Specifically, for a fixed bounded domain $\Omega$ we study solutions to the eigenfunction equation \[ (- \Delta)^s u = \lambda(u- \gamma)_+ \] with $u \equiv 0$ on $\partial \Omega$.
POLARIS: path of least action analysis on energy landscapes

Free-energy landscapes are a powerful tool for analyzing dynamical processes - capable of providing a complete mapping of a system’s configurations in state space while articulating its energetics ...
Clone Swarms: Learning to Predict and Control Multi-Robot Systems by Imitation

In this paper, we propose SwarmNet – a neural network architecture that can learn to predict and imitate the behavior of an observed swarm of agents in a centralized manner. Tested on artificially generated swarm motion data, the network achieves high levels of prediction accuracy and imitation authenticity. We compare our model to previous approaches for modelling interaction systems and show how modifying components of other models gradually approaches the performance of ours. Finally, we also discuss an extension of SwarmNet that can deal with nondeterministic, noisy, and uncertain environments, as often found in robotics applications.
Combining geomorphometry, feature extraction techniques and Earth-surface processes research: The way forward

Abstract In recent years, the wealth of technological development revolutionised our ability to collect data in geosciences. Due to the unprecedented level of detail of these datasets, geomorphologists are facing new challenges, giving more in-depth answers to a broad(er) range of fundamental questions across the full spectrum of the Earth's (and Planetary) processes. This contribution builds on the existing literature of geomorphometry (the science of quantitative land-surface analysis) and feature extraction (translate land surface parameters into extents of geomorphological elements). It provides evidence of critical themes as well as emerging fields of future research in the digital realm, supporting the likely effectiveness of geomorphometry and feature extractions as they are advancing the theoretical, empirical and applied dimension of geomorphology. The review further discusses the role of geomorphometric legacies, and scientific reproducibility, and how they can be implemented, in the hope that this will facilitate action towards improving the transparency, and efficiency of scientific research, and accelerate discoveries in geomorphology. In the current landscape, substantial changes in landforms, ecosystems, land use, hydrological routing, and direct anthropogenic modifications impact systems across the full spectrum of geomorphological processes. Although uncertainties in the precise nature and likelihood of changes exist, geomorphometry and feature extraction can aid exploring process regimes and landscape responses. Taken together, they can revolutionise geomorphology by opening the doors to improved investigations crossing space and time scales, blurring the boundaries between traditional approaches and computer modelling, and facilitating cross-disciplinary research. Ultimately, the exploitation of the available wealth of digital information can help to translate our understanding of geomorphic processes, which is often based on observations of past or current conditions, into the rapidly changing future.
The presence of a dedicated cardiac surgical intensive care service impacts clinical outcomes in adult cardiac surgery patients

Background Postoperative critical care management is an integral part of cardiac surgery that contributes directly to clinical outcomes. In the United States there remains considerable variability in the critical care infrastructure for cardiac surgical programs. There is little published data investigating the impact of a dedicated cardiac surgical intensive care service. Methods A retrospective study examining postoperative outcomes in cardiac surgical patients before and after the implementation of a dedicated cardiac surgical intensive care service at a single academic institution. An institutional Society of Thoracic Surgeons database was queried for study variables. Primary endpoints were the postoperative length of stay, intensive care unit length of stay, and mechanical ventilation time. Secondary endpoints included mortality, readmission rates, and postoperative complications. The effect on outcomes based on procedure type was also analyzed. Results A total of 1703 patients were included in this study-914 in the control group (before dedicated intensive care service) and 789 in the study group (after dedicated intensive care service). Baseline demographics were similar between groups. Length of stay, mechanical ventilation hours, and renal failure rate were significantly reduced in the study group. Coronary artery bypass grafting patients observed the greatest improvement in outcomes. Conclusions Implementation of a dedicated cardiac surgical intensive care service leads to significant improvements in clinical outcomes. The greatest benefit is seen in patients undergoing coronary artery bypass, the most common cardiac surgical operation in the United States. Thus, developing a cardiac surgical intensive care service may be a worthwhile initiative for any cardiac surgical program.
Comments on Ionization Cooling Channel Characteristics

Ionization cooling channels with a wide variety of characteristics and cooling properties are being developed. These channels can produce cooling performances that are largely consistent with the ionization cooling theory developed previously. In this paper we review ionization cooling theory, discuss its application to presently developing cooling channels, and discuss criteria for optimizing cooling.
MOCMC: Method of Characteristics Moment Closure, a Numerical Method for Covariant Radiation Magnetohydrodynamics

We present a conservative numerical method for radiation magnetohydrodynamics with frequency-dependent full transport in stationary spacetimes. This method is stable and accurate for both large and small optical depths and radiation pressures. The radiation stress-energy tensor is evolved in flux-conservative form, and closed with a swarm of samples that each transport a multigroup representation of the invariant specific intensity along a null geodesic. In each zone, the enclosed samples are used to efficiently construct a Delaunay triangulation of the unit sphere in the comoving frame, which in turn is used to calculate the Eddington tensor, average source terms, and adaptively refine the sample swarm. Radiation four-fources are evaluated in the moment sector in a semi-implicit fashion. The radiative transfer equation is solved in invariant form deterministically for each sample. Since each sample carries a discrete representation of the full spectrum, the cost of evaluating the transport operator is independent of the number of frequency groups, representing a significant reduction of algorithmic complexity for transport in frequency dependent problems. The major approximation we make in this work is performing scattering in an angle-averaged way, with Compton scattering further approximated by the Kompaneets equation. Local adaptivity in samples also makes this scheme more amenable to nonuniform meshes than a traditional Monte Carlo method. We describe the method and present results on a suite of test problems. We find that MOCMC converges at least as $\sim N^{-1}$, rather than the canonical Monte Carlo $N^{-1/2}$, where $N$ is the number of samples per zone. On several problems we demonstrate substantial improvement over Eddington and M1 closures and gray opacities.
Dynamic Stochastic Approximation for Multi-stage Stochastic Optimization

In this paper, we consider multi-stage stochastic optimization problems with convex objectives and conic constraints at each stage. We present a new stochastic first-order method, namely the dynamic stochastic approximation (DSA) algorithm, for solving these types of stochastic optimization problems. We show that DSA can achieve an optimal $${{\mathcal {O}}}(1/\epsilon ^4)$$ rate of convergence in terms of the total number of required scenarios when applied to a three-stage stochastic optimization problem. We further show that this rate of convergence can be improved to $${{\mathcal {O}}}(1/\epsilon ^2)$$ when the objective function is strongly convex. We also discuss variants of DSA for solving more general multi-stage stochastic optimization problems with the number of stages $$T > 3$$ . The developed DSA algorithms only need to go through the scenario tree once in order to compute an $$\epsilon $$ -solution of the multi-stage stochastic optimization problem. As a result, the memory required by DSA only grows linearly with respect to the number of stages. To the best of our knowledge, this is the first time that stochastic approximation type methods are generalized for multi-stage stochastic optimization with $$T \ge 3$$ .
Mosaic: A Sample-Based Database System for Open World Query Processing

Data scientists have relied on samples to analyze populations of interest for decades. Recently, with the increase in the number of public data repositories, sample data has become easier to access. It has not, however, become easier to analyze. This sample data is arbitrarily biased with an unknown sampling probability, meaning data scientists must manually debias the sample with custom techniques to avoid inaccurate results. In this vision paper, we propose Mosaic, a database system that treats samples as first-class citizens and allows users to ask questions over populations represented by these samples. Answering queries over biased samples is non-trivial as there is no existing, standard technique to answer population queries when the sampling probability is unknown. In this paper, we show how our envisioned system solves this problem by having a unique sample-based data model with extensions to the SQL language. We propose how to perform population query answering using biased samples and give preliminary results for one of our novel query answering techniques.
Initiation and Growth of Viscoelastic Fracture

Using an energy formulation including the work of viscous dissipation, fracture initiation and growth in linearly viscoelastic materials has been investigated. Assuming the viscoelastic character of the criterion is the same for all geometries as for the spherical cavity studied, the appropriate extension of the Griffith initiation criterion is believed established. Inasmuch as the threshold is time dependent, illustrative results are presented for four typical loading inputs, namely constant stress (strain), and constant stress rate (strain rate). If inertia effects are neglected, the formulation also permits a direct calculation of flaw size with time.
CPT-Violating Gravitational Orbital Perturbations

A model for spontaneous symmetry breaking using a specific form of the bumblebee model is analyzed in the context of a Schwarzschild background metric. The resulting back reaction of the symmetry-breaking field on the metric is computed to second order. Consistency with conventional (pseudo)Riemannian geometry is demonstrated. This background field is coupled to fermions via a spin-dependent CPT-violating coupling term of a type commonly considered in the Standard-Model Extension. The perturbations of various orbital trajectories are discussed. Specifically, a spin-dependent orbital velocity is found as well as a spin-dependent precession rate.
The catenoid estimate and its geometric applications

We prove a sharp area estimate for catenoids that allows us to rule out the phenomenon of multiplicity in min-max theory in several settings. We apply it to prove that i) the width of a three-manifold with positive Ricci curvature is realized by an orientable minimal surface ii) minimal genus Heegaard surfaces in such manifolds can be isotoped to be minimal and iii) the “doublings” of the Clifford torus by Kapouleas–Yang can be constructed variationally by an equivariant min-max procedure. In higher dimensions we also prove that the width of manifolds with positive Ricci curvature is achieved by an index $1$ orientable minimal hypersurface.
A note on species richness and the variance of epidemic severity

The commonly observed negative correlation between the number of species in an ecological community and disease risk, typically referred to as "the dilution effect", has received a substantial amount of attention over the past decade. Attempts to test this relationship experimentally have revealed that, in addition to the mean disease risk decreasing with species number, so too does the variance of disease risk. This is referred to as the "variance reduction effect", and has received relatively little attention in the disease-diversity literature. Here, we set out to clarify and quantify some of these relationships in an idealized model of a randomly assembled multi-species community undergoing an epidemic. We specifically investigate the variance of the community disease reproductive ratio, a multi-species extension of the basic reproductive ratio [Formula: see text], for a family of random-parameter community SIR models, and show how the variance of community [Formula: see text] varies depending on whether transmission is density or frequency-dependent. We finally outline areas of further research on how changes in variance affect transmission dynamics in other systems.
On the Physiology of Investment Biases: The Role of Cortisol and Testosterone

The underlying physiological mechanisms of biases are not well understood. As such, we examine the impact of testosterone and cortisol levels on several commonplace investment biases using realisti...
Efficient Parameter Sampling for Markov Jump Processes

Markov jump processes (MJPs) are continuous-time stochastic processes widely used in a variety of applied disciplines. Inference typically proceeds via Markov chain Monte Carlo (MCMC), the state-of...
5 – Population Systems

Publisher Summary Population systems can be described in terms of structural variables and processes that produce changes in population structure. These variables indicate population status and capacity for change in response to environmental heterogeneity. Structural variables include density, dispersion pattern of individuals and demes, age structure, sex ratio, and genetic composition. Density is the number of individuals per unit area. Dispersion is a measure of how populations are distributed in space. Regular dispersion occurs when organisms are spaced evenly among habitat or sampling units. The variables that determine the abundance and distribution of a population, in time and space, constitute a population system. The basic elements of this system are the individual members of the population, variables describing population size and structure, processes that affect population size and structure, and the environment. These elements of the population system largely determine the capacity of the population to maintain itself within a shifting landscape mosaic of habitable and unhabitable patches. This chapter summarizes these population variables and processes, their integration in life history strategies, and their contribution to change in population size and distribution.
The Bethesda System for Reporting Thyroid Cytopathology.

Objective To address terminology and other issues related to thyroid fine-needle aspiration (FNA), the National Cancer Institute (NCI) hosted The NCI Thyroid FNA State of the Science Conference. The conclusions regarding terminology and morphologic criteria from the NCI meeting led to the Bethesda Thyroid Atlas Project and form the framework for the Bethesda System for Reporting Thyroid Cytopathology. Design Participants of the Atlas Project were selected from among the committee members of the NCI FNA State of the Science Conference and other participants at the live conference. The terminology framework was based on a literature search of English language publications dating back to 1995 using PubMed as the search engine; online forum discussions ( http://thyroidfna.cancer.gov/forums/default.aspx ); and formal interdisciplinary discussions held on October 22 and 23, 2007, in Bethesda, MD. Main outcome For clarity of communication, the Bethesda System for Reporting Thyroid Cytopathology recommends that each report begin with one of the six general diagnostic categories. Each of the categories has an implied cancer risk that links it to an appropriate clinical management guideline. Conclusions The project participants hope that the adoption of this framework will facilitate communication among cytopathologists, endocrinologists, surgeons, and radiologists; facilitate cytologic-histologic correlation for thyroid diseases; facilitate research into the understanding of thyroid diseases; and allow easy and reliable sharing of data from different laboratories for national and international collaborative studies.
Learning, Termination, and Payout Policy in Dynamic Incentive Contracts

We study a principal–agent setting in which both sides learn about future profitability from output, and the project can be abandoned/terminated if profitability is too low. With learning, shirking by the agent both reduces output and lowers the principal’s estimate of future profitability. The agent can exploit this belief discrepancy and earn information rents, reducing his incentives to exert effort. The optimal contract controls information rents to improve incentives by distorting the termination decision. Our results capture the transition from a young, financially constrained firm to a mature firm that pays dividends. For young firms, poor performance permanently raises the termination threshold, as doing so lowers information rents. Mature firms pay smoothed dividends and have a fixed termination threshold. Dividend smoothing occurs because earnings surprises are used to adjust financial slack in line with profitability. When profitability only reflects the agent’s private ability, a simple equity contract is optimal.
Investor Sentiment, Misstatements, and Auditor Behavior

High investor sentiment has been linked with opportunistic managerial behavior in the face of more optimistic investors and analysts. We extend this line of work by documenting that the likelihood of misstatements is higher when sentiment is high. Although this would suggest elevated audit risk, we posit that a contemporaneous reduction in auditors' litigation cost could drive down audit fees and going concern opinion (GCO) reporting conservatism in order to please clientele. Consistent with this notion, we document that auditors charge lower fees and report GCOs less conservatively when sentiment is high. However, this reduction in reporting conservatism is unwarranted; results reveal that auditors are less likely to issue GCOs to clients which subsequently file for bankruptcy during high sentiment periods. We conduct additional tests to examine whether auditors' litigation costs indeed vary with sentiment and document that auditors are less likely to be sued and the market reacts less negatively to misstatement announcements when sentiment is high. Collectively, our findings suggest that, although misstatement risk is increasing with sentiment, auditors' litigation risk actually declines. Sentiment des investisseurs, inexactitudes et comportement de l'auditeur Un sentiment des investisseurs fort a ete associe a un comportement opportuniste de la part des gestionnaires lorsque les investisseurs et analystes se montrent plus optimistes. Nous elargissons l'examen de cette question en montrant que la probabilite d'inexactitudes est plus elevee lorsque le sentiment des investisseurs est fort. Bien que cela laisse entrevoir un risque d'audit eleve, nous postulons qu'une reduction concomitante des couts des litiges des auditeurs pourrait faire diminuer les frais d'audit et le caractere conservateur de l'opinion sur la continuite d'exploitation afin de plaire aux clients. Conformement a cette notion, nous montrons que les auditeurs demandent des honoraires moins eleves et emettent des opinions moins conservatrices sur la continuite d'exploitation lorsque le sentiment est fort. Toutefois, cette diminution du caractere conservateur de l'opinion n'est pas justifiee; nos resultats indiquent que, durant les periodes ou le sentiment est fort, les auditeurs sont moins susceptibles de fournir une opinion sur la continuite d'exploitation a des clients qui ulterieurement declarent faillite. Nous effectuons des analyses additionnelles pour decouvrir si les couts des litiges des auditeurs varient reellement en fonction du sentiment des investisseurs et nous constatons que les auditeurs sont moins susceptibles de faire l'objet de poursuites et que le marche reagit moins negativement aux annonces relatives aux inexactitudes lorsque le sentiment est fort. Pris dans leur ensemble, nos resultats donnent a penser que, bien que le risque d'inexactitudes augmente parallelement a la force du sentiment, le risque de litige des auditeurs diminue.
Effect of trospium chloride on somnolence and sleepiness in patients with overactive bladder

An objective of a large US phase-3 study was to determine the effects of trospium chloride 20-mg tablets versus placebo, administered twice daily, on central nervous system (CNS) adverse events (eg, somnolence) and on daytime sleepiness using the validated Stanford Sleepiness Scale. The impact of age groups also was assessed. Trospium chloride did not increase daytime sleepiness or appear to produce CNS adverse effects, as measured by the Stanford Sleepiness Scale and the incidence of CNS adverse events. Furthermore, there was no difference in these findings across age groups.
Non-indexability of the stochastic appointment scheduling problem

Abstract Consider a set of jobs with independent random service times to be scheduled on a single machine. The jobs can be surgeries in an operating room, patients’ appointments in outpatient clinics, etc. The challenge is to determine the optimal sequence and appointment times of jobs to minimize some function of the server idle time and service start-time delay. We introduce a generalized objective function of delay and idle time, and consider l 1 -type and l 2 -type cost functions as special cases of interest. Determining an index-based policy for the optimal sequence in which to schedule jobs has been an open problem for many years. For example, it was conjectured that ‘least variance first’ (LVF) policy is optimal for the l 1 -type objective. This is known to be true for the case of two jobs with specific distributions. A key result in this paper is that the optimal sequencing problem is non-indexable, i.e., neither the variance, nor any other such index can be used to determine the optimal sequence in which to schedule jobs for l 1 and l 2 -type objectives. We then show that given a sequence in which to schedule the jobs, sample average approximation yields a solution which is statistically consistent.
The Optimal Elasticity of Taxable Income

Abstract The strength of the behavioral response to a tax rate change depends on the environment individuals operate in, and may be manipulated by instruments controlled by the government. We first derive a measure of the social benefit to affecting this elasticity. The paper then examines this effect in the solution to the optimal income taxation problem when such an instrument is available, first in a general model and then in an example when the government chooses the income tax base.
Tumor Immune Microenvironment Clusters in Localized Prostate Adenocarcinoma: Prognostic Impact of Macrophage Enriched/Plasma Cell Non-Enriched Subtypes.

Background: Prostate cancer (PCa) is characterized by significant heterogeneity in its molecular, genomic, and immunologic characteristics. Methods: Whole transcriptome RNAseq data from The Cancer Genome Atlas of prostate adenocarcinomas (n = 492) was utilized. The immune microenvironment was characterized using the CIBERSORTX tool to identify immune cell type composition. Unsupervised hierarchical clustering was performed based on immune cell type content. Analyses of progression-free survival (PFS), distant metastases, and overall survival (OS) were performed using Kaplan–Meier estimates and Cox regression multivariable analyses. Results: Four immune clusters were identified, largely defined by plasma cell, CD4+ Memory Resting T Cells (CD4 MR), and M0 and M2 macrophage content (CD4 MRHighPlasma CellHighM0LowM2Mid, CD4 MRLowPlasma CellHighM0LowM2Low, CD4 MRHighPlasma CellLowM0HighM2Low, and CD4 MRHighPlasma CellLowM0LowM2High). The two macrophage-enriched/plasma cell non-enriched clusters (3 and 4) demonstrated worse PFS (HR 2.24, 95% CI 1.46–3.45, p = 0.0002) than the clusters 1 and 2. No metastatic events occurred in the plasma cell enriched, non-macrophage-enriched clusters. Comparing clusters 3 vs. 4, in patients treated by surgery alone, cluster 3 had zero progression events (p < 0.0001). However, cluster 3 patients had worse outcomes after post-operative radiotherapy (p = 0.018). Conclusion: Distinct tumor immune clusters with a macrophage-enriched, plasma cell non-enriched phenotype and reduced plasma cell enrichment independently characterize an aggressive phenotype in localized prostate cancer that may differentially respond to treatment.
Generation of 1 µJ and 40 fs pulses from a large mode area gain-managed nonlinear amplifier

We demonstrate numerically and experimentally a gain-managed nonlinear amplifier with a large mode area fiber. The amplifier delivers 1.2 µJ and sub-40 fs pulses with the spectrum spanning from ∼1000 to ∼1180nm. We show that longitudinal gain-loss evolution plays an essential role in pulse formation by comparing simulations with different gain models to the experimental results.
Foreign Exchange Risk, Hedging, and Tax‐Motivated Outbound Income Shifting

Although outbound income shifting to low‐tax jurisdictions provides tax savings, it is often accompanied by nontax costs. In this study, I examine whether foreign exchange (FX) risk constrains tax‐motivated outbound income shifting by U.S. multinational corporations. My findings indicate that exposure to greater currency volatility is associated with less outbound income shifting, and this effect is stronger for firms with foreign affiliates using foreign functional currencies. I also investigate whether hedging facilitates outbound income shifting. Consistent with hedging lowering costs associated with exchange rate volatility, I find that U.S. firms that use more currency derivatives tend to shift more income to low‐tax foreign jurisdictions. Overall, these findings suggest that FX risk is an important cost of outbound income shifting.
Degeneracy results for fully nonlinear integral operators

Abstract It is shown that integral operators of the fully nonlinear type K ( x ) ( t ) = ∫ Ω k ( t , s , x ( t ) , x ( s ) ) d s exhibit similar degeneracy phenomena in a large class of spaces as superposition operators F ( x ) ( t ) = f ( t , x ( t ) ) . In particular, K is Frechet differentiable in L p only if it is affine with respect to the “ x ( t ) ” argument. Similar degeneracy results hold if K satisfies a local Lipschitz or compactness condition. Also vector functions, infinite measure spaces, and a much richer class of function spaces than only L p are considered. As a side result, degeneracy assertions for superposition operators are obtained in this more general setting, complementing the known results for scalar functions. As a particular example, it is shown that the operators arising in continuous limits of coupled Kuramoto oscillators fail everywhere to be Frechet differentiable or locally compact.
Revealing 29 sets of independently modulated genes in Staphylococcus aureus, their regulators, and role in key physiological response

The ability of Staphylococcus aureus to infect many different tissue sites is enabled, in part, by its transcriptional regulatory network (TRN) that coordinates its gene expression to respond to different environments. We elucidated the organization and activity of this TRN by applying independent component analysis to a compendium of 108 RNA-sequencing expression profiles from two S. aureus clinical strains (TCH1516 and LAC). ICA decomposed the S. aureus transcriptome into 29 independently modulated sets of genes (i-modulons) that revealed: 1) High confidence associations between 21 i-modulons and known regulators; 2) an association between an i-modulon and σS, whose regulatory role was previously undefined; 3) the regulatory organization of 65 virulence factors in the form of three i-modulons associated with AgrR, SaeR, and Vim-3; 4) the roles of three key transcription factors (CodY, Fur, and CcpA) in coordinating the metabolic and regulatory networks; and 5) a low-dimensional representation, involving the function of few transcription factors of changes in gene expression between two laboratory media (RPMI, cation adjust Mueller Hinton broth) and two physiological media (blood and serum). This representation of the TRN covers 842 genes representing 76% of the variance in gene expression that provides a quantitative reconstruction of transcriptional modules in S. aureus, and a platform enabling its full elucidation.
Full-count PET recovery from low-count image using a dilated convolutional neural network

PURPOSE Positron emission tomography (PET) is an essential technique in many clinical applications that allows for quantitative imaging at the molecular level. This study aims to develop a denoising method using a novel dilated convolutional neural network (CNN) to recover full-count images from low-count images. METHODS We adopted similar hierarchical structures as the conventional U-Net and incorporated dilated kernels in each convolution to allow the network to observe larger, more robust features within the image without the requirement of downsampling and upsampling internal representations. Our dNet was trained alongside a U-Net for comparison. Both models were evaluated using a leave-one-out cross-validation procedure on a dataset of 35 subjects (~3500 slabs), which were obtained from an ongoing 18 F-Fluorodeoxyglucose (FDG) study. Low-count PET data (10% count) were generated by randomly selecting one-tenth of all events in the associated listmode file. Analysis was done on the static image from the last 10 minutes of emission data. Both low-count PET and full-count PET were reconstructed using ordered subset expectation maximization (OSEM). Objective image quality metrics, including mean absolute percent error (MAPE), peak signal-to-noise ratio (PSNR), and structural similarity index metric (SSIM), were used to analyze the deep learning methods. Both deep learning methods were further compared to a traditional Gaussian filtering method. Further, region of interest (ROI) quantitative analysis was also used to compare U-Net and dNet architectures. RESULTS Both the U-Net and our proposed network were successfully trained to synthesize full-count PET images from the generated low-count PET images. Compared to low-count PET and Gaussian filtering, both deep learning methods improved MAPE, PSNR, and SSIM. Our dNet also systematically outperformed U-Net on all three metrics (MAPE: 4.99 ± 0.68 vs 5.31 ± 0.76, P < 0.01; PSNR: 31.55 ± 1.31 dB vs 31.05 ± 1.39, P < 0.01; SSIM: 0.9513 ± 0.0154 vs 0.9447 ± 0.0178, P < 0.01). ROI quantification showed greater quantitative improvements using dNet over U-Net. CONCLUSION This study proposed a novel approach of using dilated convolutions for recovering full-count PET images from low-count PET images.
Complexity and the Limits of Revolution: What Will Happen to the Arab Spring?

The recent social unrest across the Middle East and North Africa has deposed dictators who had ruled for decades. While the events have been hailed as an “Arab Spring” by those who hope that repressive autocracies will be replaced by democracies, what sort of regimes will eventually emerge from the crisis remains far from certain. Here we provide a complex systems framework, validated by historical precedent, to help answer this question. We describe the dynamics of governmental change as an evolutionary process similar to biological evolution, in which complex organizations gradually arise by replication, variation, and competitive selection. Different kinds of governments, however, have differing levels of complexity. Democracies must be more systemically complex than autocracies because of their need to incorporate large numbers of people in decision-making. This difference has important implications for the relative robustness of democratic and autocratic governments after revolutions. Revolutions may disrupt existing evolved complexity, limiting the potential for building more complex structures quickly. Insofar as systemic complexity is reduced by revolution, democracy is harder to create in the wake of unrest than autocracy. Applying this analysis to the Middle East and North Africa, we infer that in the absence of stable institutions or external assistance, new governments are in danger of facing increasingly insurmountable challenges and reverting to autocracy.