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Climate models exhibit an approximately invariant surface warming pattern in typical end-of-century projections. This observation has been used extensively in climate impact assessments for fast calculations of local temperature anomalies, with a linear procedure known as pattern scaling. At the same time, emerging research has also shown that time-varying warming patterns are necessary to explain the time evolution of effective climate sensitivity in coupled models, a mechanism that is known as the pattern effect and that seemingly challenges the pattern scaling understanding. Here we present a simple theory based on local energy balance arguments to reconcile this apparent contradiction. Specifically, we show that the pattern invariance is an inherent feature of exponential forcing, linear feedbacks, a constant forcing pattern and diffusive dynamics. These conditions are approximately met in most CMIP6 Shared Socioeconomic Pathways (SSP), except in the Arctic where nonlinear feedbacks are important and in regions where aerosols considerably alter the forcing pattern. In idealized experiments where concentrations of CO2 are abruptly increased, such as those used to study the pattern effect, the warming pattern can change considerably over time because of spatially inhomogeneous ocean heat uptake, even in the absence of nonlinear feedbacks. Our results illustrate why typical future projections are amenable to pattern scaling, and provide a plausible explanation of why more complicated approaches, such as nonlinear emulators, have only shown marginal improvements in accuracy over simple linear calculations., Comment: To be submitted to J Clim

We introduce the LUNA neutron detector array developed for the investigation of the 13C(a,n)16O reaction towards its astrophysical s-process Gamow peak in the low-background environment of the Laboratori Nazionali del Gran Sasso (LNGS). Eighteen 3He counters are arranged in two different configurations (in a vertical and a horizontal orientation) to optimize neutron detection effciency, target handling and target cooling over the investigated energy range Ea;lab = 300 - 400 keV (En = 2.2 - 2.6 MeV in emitted neutron energy). As a result of the deep underground location, the passive shielding of the setup and active background suppression using pulse shape discrimination, we reached a total background rate of 1.23 +- 0.12 counts/hour. This resulted in an improvement of two orders of magnitude over the state of the art allowing a direct measurement of the 13C(a,n)16O cross-section down to Ea;lab = 300 keV. The absolute neutron detection efficiency of the setup was determined using the 51V(p,n)51Cr reaction and an AmBe radioactive source, and completed with a Geant4 simulation. We determined a (34+-3) % and (38+-3) % detection efficiency for the vertical and horizontal configurations, respectively, for En = 2.4 MeV neutrons., Comment: 8 pages, 5 figures, to be published in NIMA

Wildfire frequency is increasing as the climate changes, and the resulting air pollution poses health risks. Just as people routinely use weather forecasts to plan their activities around precipitation, reliable air quality forecasts could help individuals reduce their exposure to air pollution. In the present work, we evaluate several existing forecasts of fine particular matter (PM2.5) within the continental United States in the context of individual decision-making. Our comparison suggests there is meaningful room for improvement in air pollution forecasting, which might be realized by incorporating more data sources and using machine learning tools. To facilitate future machine learning development and benchmarking, we set up a framework to evaluate and compare air pollution forecasts for individual decision making. We introduce a new loss to capture decisions about when to use mitigation measures. We highlight the importance of visualizations when comparing forecasts. Finally, we provide code to download and compare archived forecast predictions., Comment: 22 pages, 3 figures

The $\mathrm{^{20}Ne(p, \gamma)^{21}Na}$ reaction is the slowest in the NeNa cycle and directly affects the abundances of the Ne and Na isotopes in a variety of astrophysical sites. Here we report the measurement of its direct capture contribution, for the first time below $E\rm_{cm} = 352$~keV, and of the contribution from the $E^{\rm }_{cm} = 368$~keV resonance, which dominates the reaction rate at $T=0.03-1.00$~GK. The experiment was performed deep underground at the Laboratory for Underground Nuclear Astrophysics, using a high-intensity proton beam and a windowless neon gas target. Prompt $\gamma$ rays from the reaction were detected with two high-purity germanium detectors. We obtain a resonance strength $\omega \gamma~=~(0.112 \pm 0.002_{\rm stat}~\pm~0.005_{\rm sys})$~meV, with an uncertainty a factor of $3$ smaller than previous values. Our revised reaction rate is 20\% lower than previously adopted at $T < 0.1$~GK and agrees with previous estimates at temperatures $T \geq 0.1$~GK. Initial astrophysical implications are presented., Comment: 8 pages, 4 figures, accepted to PRC (letter)

In stars, the fusion of $^{22}$Ne and $^4$He may produce either $^{25}$Mg, with the emission of a neutron, or $^{26}$Mg and a $\gamma$ ray. At high temperature, the ($\alpha,n$) channel dominates, while at low temperature, it is energetically hampered. The rate of its competitor, the $^{22}$Ne($\alpha$,$\gamma$)$^{26}$Mg reaction, and, hence, the minimum temperature for the ($\alpha,n$) dominance, are controlled by many nuclear resonances. The strengths of these resonances have hitherto been studied only indirectly. The present work aims to directly measure the total strength of the resonance at $E$_{r}$\,=\,$334$\,$keV (corresponding to $E$_{x}$\,=\,$10949$\,$keV in $^{26}$Mg). The data reported here have been obtained using high intensity $^4$He$^+$ beam from the INFN LUNA 400 kV underground accelerator, a windowless, recirculating, 99.9% isotopically enriched $^{22}$Ne gas target, and a 4$\pi$ bismuth germanate summing $\gamma$-ray detector. The ultra-low background rate of less than 0.5 counts/day was determined using 67 days of no-beam data and 7 days of $^4$He$^+$ beam on an inert argon target. The new high-sensitivity setup allowed to determine the first direct upper limit of 4.0$\,\times\,$10$^{-11}$ eV (at 90% confidence level) for the resonance strength. Finally, the sensitivity of this setup paves the way to study further $^{22}$Ne($\alpha$,$\gamma$)$^{26}$Mg resonances at higher energy., Comment: Submitted to Eur. Phys. J. A

What science does, what science could do, and how to make science work? If we want to know the answers to these questions, we need to be able to uncover the mechanisms of science, going beyond metrics that are easily collectible and quantifiable. In this perspective piece, we link metrics to mechanisms by demonstrating how emerging metrics of science not only offer complementaries to existing ones, but also shed light on the hidden structure and mechanisms of science. Based on fundamental properties of science, we classify existing theories and findings into: hot and cold science referring to attention shift between scientific fields, fast and slow science reflecting productivity of scientists and teams, soft and hard science revealing reproducibility of scientific research. We suggest that interest about mechanisms of science since Derek J. de Solla Price, Robert K. Merton, Eugene Garfield, and many others complement the zeitgeist in pursuing new, complex metrics without understanding the underlying processes. We propose that understanding and modeling the mechanisms of science condition effective development and application of metrics., Comment: 20 pages, 1 figure

It is widely understood that diffusion of and simultaneous interactions between narratives -- defined here as persistent point-of-view messaging -- significantly contributes to the shaping of political discourse and public opinion. In this work, we propose a methodology based on Multi-Variate Hawkes Processes and our newly-introduced Process Influence Measures for quantifying and assessing how such narratives influence (Granger-cause) each other. Such an approach may aid social scientists enhance their understanding of socio-geopolitical phenomena as they manifest themselves and evolve in the realm of social media. In order to show its merits, we apply our methodology on Twitter narratives during the 2019 Venezuelan presidential crisis. Our analysis indicates a nuanced, evolving influence structure between 8 distinct narratives, part of which could be explained by landmark historical events., Comment: This document has 11 pages and 4 figures

Our goal is to understand the characteristics of high-performing teams on GitHub. Towards this end, we collect data from software repositories and evaluate teams by examining differences in productivity. Our study focuses on the team formation phase, the first six months after repository creation. To better understand team activity, we clustered repositories based on the proportion of their work activities and discovered three work styles in teams: toilers, communicators, and collaborators. Based on our results, we contend that early activities in software development repositories on GitHub establish coordination processes that enable effective collaborations over time.

Among the reactions involved in the production and destruction of deuterium during Big Bang Nucleosynthesis, the deuterium-burning D(p,gamma)3He reaction has the largest uncertainty and limits the precision of theoretical estimates of primordial deuterium abundance. Here we report the results of a careful commissioning of the experimental setup used to measure the cross-section of the D(p,gamma)3He reaction at the Laboratory for Underground Nuclear Astrophysics of the Gran Sasso Laboratory (Italy). The commissioning was aimed at minimising all sources of systematic uncertainty in the measured cross sections. The overall systematic error achieved (< 3 %) will enable improved predictions of BBN deuterium abundance., Comment: 11 pages, 11 figures

This paper explains the design of a social network analysis framework, developed under DARPA's SocialSim program, with novel architecture that models human emotional, cognitive and social factors. Our framework is both theory and data-driven, and utilizes domain expertise. Our simulation effort helps in understanding how information flows and evolves in social media platforms. We focused on modeling three information domains: cryptocurrencies, cyber threats, and software vulnerabilities for the three interrelated social environments: GitHub, Reddit, and Twitter. We participated in the SocialSim DARPA Challenge in December 2018, in which our models were subjected to extensive performance evaluation for accuracy, generalizability, explainability, and experimental power. This paper reports the main concepts and models, utilized in our social media modeling effort in developing a multi-resolution simulation at the user, community, population, and content levels., Comment: 16 pages

Direct measurements of reaction cross-sections at astrophysical energies often require the use of solid targets able to withstand high ion beam currents for extended periods of time. Thus, monitoring target thickness, isotopic composition, and target stoichiometry during data taking is critical to account for possible target modifications and to reduce uncertainties in the final cross-section results. A common technique used for these purposes is the Nuclear Resonant Reaction Analysis (NRRA), which however requires that a narrow resonance be available inside the dynamic range of the accelerator used. In cases when this is not possible, as for example the 13C(alpha,n)16O reaction recently studied at low energies at the Laboratory for Underground Nuclear Astrophysics (LUNA) in Italy, alternative approaches must be found. Here, we present a new application of the shape analysis of primary gamma rays emitted by the 13C(p,g)14N radiative capture reaction. This approach was used to monitor 13C target degradation {\em in situ} during the 13C(alpha,n)16O data taking campaign. The results obtained are in agreement with evaluations subsequently performed at Atomki (Hungary) using the NRRA method. A preliminary application for the extraction of the 13C(alpha,n)16O reaction cross-section at one beam energy is also reported., Comment: 10 pages, 6 figures, to be published in EPJ A

The $^{22}$Ne($p,\gamma$)$^{23}$Na reaction, part of the neon-sodium cycle of hydrogen burning, may explain the observed anticorrelation between sodium and oxygen abundances in globular cluster stars. Its rate is controlled by a number of low-energy resonances and a slowly varying non-resonant component. Three new resonances at $E_p$ = 156.2, 189.5, and 259.7 keV have recently been observed and confirmed. However, significant uncertainty on the reaction rate remains due to the non-resonant process and to two suggested resonances at $E_p$ = 71 and 105 keV. Here, new $^{22}$Ne($p,\gamma$)$^{23}$Na data with high statistics and low background are reported. Stringent upper limits of 6$\times$10$^{-11}$ and 7$\times$10$^{-11}$\,eV (90\% confidence level), respectively, are placed on the two suggested resonances. In addition, the off-resonant S-factor has been measured at unprecedented low energy, constraining the contributions from a subthreshold resonance and the direct capture process. As a result, at a temperature of 0.1 GK the error bar of the $^{22}$Ne($p,\gamma$)$^{23}$Na rate is now reduced by three orders of magnitude., Comment: Submitted to Phys. Rev. Lett

The settling of colloidal particles with short-ranged attractions is investigated via highly resolved immersed boundary simulations. At modest volume fractions, we show that inter-colloid attractions lead to clustering that reduces the hinderance to settling imposed by fluid back flow. For sufficient attraction strength, increasing the particle concentration grows the particle clusters, which further increases the mean settling rate in a physical mode termed promoted settling. The immersed boundary simulations are compared to recent experimental measurements of the settling rate in nanoparticle dispersions for which particles are driven to aggregate by short-ranged depletion attractions. The simulations are able to quantitatively reproduce the experimental results. We show that a simple, empirical model for the settling rate of adhesive hard sphere dispersions can be derived from a combination of the experimental and computational data as well as analytical results valid in certain asymptotic limits of the concentration and attraction strength. This model naturally extends the Richardson-Zaki formalism used to describe hindered settling of hard, repulsive spheres. Experimental measurements of the collective diffusion coefficient in concentrated solutions of globular proteins are used to illustrate inference of effective interaction parameters for sticky, globular macromolecules using this new empirical model. Finally, application of the simulation methods and empirical model to other colloidal systems are discussed.

The experimental study of nuclear reactions of astrophysical interest is greatly facilitated by a low-background, high-luminosity setup. The Laboratory for Underground Nuclear Astrophysics (LUNA) 400 kV accelerator offers ultra-low cosmic-ray induced background due to its location deep underground in the Gran Sasso National Laboratory (INFN-LNGS), Italy, and high intensity, 250-500 $\mu$A, proton and $\alpha$ ion beams. In order to fully exploit these features, a high-purity, recirculating gas target system for isotopically enriched gases is coupled to a high-efficiency, six-fold optically segmented bismuth germanate (BGO) $\gamma$-ray detector. The beam intensity is measured with a beam calorimeter with constant temperature gradient. Pressure and temperature measurements have been carried out at several positions along the beam path, and the resultant gas density profile has been determined. Calibrated $\gamma$-intensity standards and the well-known $E_p$ = 278 keV $\mathrm{^{14}N(p,\gamma)^{15}O}$ resonance were used to determine the $\gamma$-ray detection efficiency and to validate the simulation of the target and detector setup. As an example, the recently measured resonance at $E_p$ = 189.5 keV in the $^{22}$Ne(p,$\gamma$)$^{23}$Na reaction has been investigated with high statistics, and the $\gamma$-decay branching ratios of the resonance have been determined., Comment: 11 pages, 11 figures, accepted in Eur. Phys. Journal A

We describe a computational model of social norms based on identifying values that a certain culture finds desirable such as dignity, generosity and politeness. The model quantifies these values in the form of Culture-Sanctioned Social Metrics (CSSMs) and treats social norms as the requirement to maximize these metrics from the perspective of the self, peers and public. This model can be used to create realistic social simulations, to explain or predict human behavior in specific scenarios, or as a component of robots or agents that need to interact with humans in specific social-cultural settings. We validate the model by using it to represent a complex deception scenario and showing that it can yield non-trivial insights such as the explanation of apparently irrational human behavior.

Brownian Dynamics simulations are an important tool for modeling the dynamics of soft matter. However, accurate and rapid computations of the hydrodynamic interactions between suspended, microscopic components in a soft material is a significant computational challenge. Here, we present a new method for Brownian Dynamics simulations of suspended colloidal scale particles subject to an important class of hydrodynamic constraints with practically linear scaling of the computational cost with the number of particles modeled. Specifically, we consider the "stresslet" constraint for which suspended particles resist local deformation. The presented method is an extension of the recently reported positively-split formulation for Ewald summation of the Rotne-Prager-Yamakawa (RPY) mobility tensor to higher order (dipole) terms in the hydrodynamic scattering series [Andrew M. Fiore et al. The Journal of Chemical Physics, 146(12):124116, 2017]. The hydrodynamic mobility tensor, which is proportional to the covariance of particle Brownian displacements, is constructed as an Ewald sum in a novel way that guarantees the real-space and wave-space sums are independently positive-definite for all possible particle configurations. This property is leveraged to rapidly sample the Brownian displacements from a superposition of statistically independent processes with the wave-space and real-space contributions as respective covariances. The cost of computing the Brownian displacements in this way is comparable to the cost of computing the deterministic displacements. Addition of a stresslet constraint to the over-damped particle equations of motion leads to a stochastic differential algebraic equation (SDAE) of index 1, which is integrated in time using a mid-point integration scheme that implicitly produces displacements consistent with the fluctuation-dissipation theorem for the constrained system.

Understanding the correlation between structure and rheology in colloidal suspensions is important as these suspensions are crucial in industrial applications. Moreover, colloids exhibit a wide range of structures under confinement that could considerably alter the viscosity. Here, we use a combination of experiments and simulations to elucidate how confinement induced structures alter the relative contributions of hydrodynamic and repulsive forces to produce up to a ten fold change in the viscosity. We use a custom built confocal rheoscope to image the particle configurations of a colloidal suspension while simultaneously measuring the viscosity. We find a non-monotonic trend to the viscosity under confinement that is strongly correlated with the microstructure. As the gap decreases below 15 particle diameters, the viscosity first decreases from its bulk value, shows fluctuations with the gap, and then sharply increases for gaps below three particle diameters. Further, we compare our experimental results to two simulations techniques that enables us to determine the relative contributions of hydrodynamic and short range repulsive stresses. The first method uses the lubrication approximation to find the hydrodynamic stress and includes a short range repulsive force between the particles and the second is a Stokesian dynamics simulation that calculates the full hydrodynamic stress in the suspension. We find that the decrease in the viscosity at moderate confinements has a significant contribution from both the hydrodynamic and repulsive forces whereas the increase in viscosity at gaps less than three particle diameters arises primarily from short range repulsive forces. These results provide new insights to the unique rheological behavior of confined suspensions and further enable us to tune the viscosity by changing properties such as the gap, polydispersity, and the volume fraction., Comment: 15 pages, 10 figures