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A look at how the Wright Brothers became the first celebrities of the twentieth century through their 1909 public flying exhibitions in New York City and Germany.

US surface O3 responds to varying global-to-regional precursor emissions, climate, and extreme weather, with implications for designing effective air quality control policies. We examine these conjoined processes with observations and global chemistry-climate model (GFDL-AM3) hindcasts over 1980–2014. The model captures the salient features of observed trends in daily maximum 8 h average O3: (1) increases over East Asia (up to 2 ppb yr−1), (2) springtime increases at western US (WUS) rural sites (0.2–0.5 ppb yr−1) with a baseline sampling approach, and (3) summertime decreases, largest at the 95th percentile, and wintertime increases in the 50th to 5th percentiles over the eastern US (EUS). Asian NOx emissions have tripled since 1990, contributing as much as 65 % to modeled springtime background O3 increases (0.3–0.5 ppb yr−1) over the WUS, outpacing O3 decreases attained via 50 % US NOx emission controls. Methane increases over this period contribute only 15 % of the WUS background O3 increase. Springtime O3 observed in Denver has increased at a rate similar to remote rural sites. During summer, increasing Asian emissions approximately offset the benefits of US emission reductions, leading to weak or insignificant observed O3 trends at WUS rural sites. Mean springtime WUS O3 is projected to increase by  ∼  10 ppb from 2010 to 2030 under the RCP8.5 global change scenario. While historical wildfire emissions can enhance summertime monthly mean O3 at individual sites by 2–8 ppb, high temperatures and the associated buildup of O3 produced from regional anthropogenic emissions contribute most to elevating observed summertime O3 throughout the USA. GFDL-AM3 captures the observed interannual variability of summertime EUS O3. However, O3 deposition sink to vegetation must be reduced by 35 % for the model to accurately simulate observed high-O3 anomalies during the severe drought of 1988. Regional NOx reductions alleviated the O3 buildup during the recent heat waves of 2011 and 2012 relative to earlier heat waves (e.g., 1988, 1999). The O3 decreases driven by NOx controls were more pronounced in the southeastern US, where the seasonal onset of biogenic isoprene emissions and NOx-sensitive O3 production occurs earlier than in the northeast. Without emission controls, the 95th percentile summertime O3 in the EUS would have increased by 0.2–0.4 ppb yr−1 over 1988–2014 due to more frequent hot extremes and rising biogenic isoprene emissions.

Light elements were produced in the first few minutes of the Universe through a sequence of nuclear reactions known as Big Bang nucleosynthesis (BBN) 1 , 2 . Among the light elements produced during BBN 1 , 2 , deuterium is an excellent indicator of cosmological parameters because its abundance is highly sensitive to the primordial baryon density and also depends on the number of neutrino species permeating the early Universe. Although astronomical observations of primordial deuterium abundance have reached percent accuracy 3 , theoretical predictions 4 – 6 based on BBN are hampered by large uncertainties on the cross-section of the deuterium burning D( p , γ ) 3 He reaction. Here we show that our improved cross-sections of this reaction lead to BBN estimates of the baryon density at the 1.6 percent level, in excellent agreement with a recent analysis of the cosmic microwave background 7 . Improved cross-section data were obtained by exploiting the negligible cosmic-ray background deep underground at the Laboratory for Underground Nuclear Astrophysics (LUNA) of the Laboratori Nazionali del Gran Sasso (Italy) 8 , 9 . We bombarded a high-purity deuterium gas target 10 with an intense proton beam from the LUNA 400-kilovolt accelerator 11 and detected the γ-rays from the nuclear reaction under study with a high-purity germanium detector. Our experimental results settle the most uncertain nuclear physics input to BBN calculations and substantially improve the reliability of using primordial abundances to probe the physics of the early Universe. High-precision cross-sections of the nuclear reaction that burns deuterium to create helium-3 are used to produce theoretical estimates of the primordial baryon density that are in agreement with recent astronomical observations.

The 2030 Agenda has among its key objectives the poverty eradication through increasing the level of education. A good level of education and investment in culture of a country is in fact necessary to guarantee a sustainable economy, in which coexists satisfactory levels of quality of life and an equitable distribution of income. There is a lack of studies in particular on the relations between some significant dimensions, such as education, culture and poverty, considering time lags for the measurement of impacts. Therefore, this study aims to fill this gap by focusing on the relationship between education, culture and poverty based on a panel of data from 34 European countries, over a 5-year period, 2015–2019. For this purpose, after applying principal component analysis to avoid multicollinearity problems, the authors applied three different approaches: pooled-ordinary least squares model, fixed effect model and random effect model. Fixed-effects estimator was selected as the optimal and most appropriate model. The results highlight that increasing education and culture levels in these countries reduce poverty. This opens space to new research paths and policy strategies that can start from this connection to implement concrete actions aimed at widening and improving educational and cultural offer.

Collaborative problem solving (CPS) has been receiving increasing international attention because much of the complex work in the modern world is performed by teams. However, systematic education and training on CPS is lacking for those entering and participating in the workforce. In 2015, the Programme for International Student Assessment (PISA), a global test of educational progress, documented the low levels of proficiency in CPS. This result not only underscores a significant societal need but also presents an important opportunity for psychological scientists to develop, adopt, and implement theory and empirical research on CPS and to work with educators and policy experts to improve training in CPS. This article offers some directions for psychological science to participate in the growing attention to CPS throughout the world. First, it identifies the existing theoretical frameworks and empirical research that focus on CPS. Second, it provides examples of how recent technologies can automate analyses of CPS processes and assessments so that substantially larger data sets can be analyzed and so students can receive immediate feedback on their CPS performance. Third, it identifies some challenges, debates, and uncertainties in creating an infrastructure for research, education, and training in CPS. CPS education and assessment are expected to improve when supported by larger data sets and theoretical frameworks that are informed by psychological science. This will require interdisciplinary efforts that include expertise in psychological science, education, assessment, intelligent digital technologies, and policy.

We describe an approach aimed at helping artificial intelligence develop theory of mind of their human teammates to support team interactions. We show how this can be supported through the provision of quantifiable, machine-readable, a priori information about the human team members to an agent. We first show how our profiling approach can capture individual team member characteristic profiles that can be constructed from sparse data and provided to agents to support the development of artificial theory of mind. We then show how it captures features of team composition that may influence team performance. We document this through an experiment examining factors influencing the performance of ad-hoc teams executing a complex team coordination task when paired with an artificial social intelligence (ASI) teammate. We report the relationship between the individual and team characteristics and measures related to task performance and self-reported perceptions of the ASI. The results show that individual and emergent team profiles were able to characterize features of the team that predicted behavior and explain differences in perceptions of ASI. Further, the features of these profiles may interact differently when teams work with human versus ASI advisors. Most strikingly, our analyses showed that ASI advisors had a strong positive impact on low potential teams such that they improved the performance of those teams across mission outcome measures. We discuss these findings in the context of developing intelligent technologies capable of social cognition and engage in collaborative behaviors that improve team effectiveness.

Given the worldwide prevalence of NAFLD and NASH, there is a need to develop treatments to slow or reverse disease progression. GR-MD-02 (galactoarabino-rhamnogalaturonate) has been shown to reduce hepatic fibrosis in animal studies, and lower serum biomarkers of NASH fibrogenesis in humans. The primary aim of this study was to determine the difference between four-months of treatment with GR-MD-02 or placebo in liver inflammation and fibrosis as measured by iron-corrected T1 (cT1) mapping, a non-invasive magnetic resonance imaging (MRI) biomarker that correlates with the extent of hepatic fibro-inflammatory disease. The secondary aims were to determine change in liver stiffness as measured by magnetic resonance elastography (MRE) and shear-wave ultrasonic elastography (LSM), and to explore test-retest repeatability of the three biomarkers. Thirty subjects (13 females, 46-71 years) with NASH and advanced fibrosis were recruited. Subjects were randomized to receive 8 mg.kg-1 GR-MD-02 (via IV infusion) or placebo, administered biweekly over a 16-week period. Therapeutic efficacy was examined using cT1, MRE, and LSM. Statistical analyses on group differences in the biomarkers were performed using robust ANCOVA models adjusting for baseline measurement and additional covariates. There was no significant difference in cT1 (p = 0.16) between GR-MD-02 and placebo groups following a 16-week intervention. There was also no significant difference in liver stiffness, measured by MRE (p = 0.80) or LSM (p = 0.63), between groups. Examination of repeatability of the cT1, MRE and LSM revealed coefficient of variations of 3.1%, 11% and 40% respectively. 8 mg.kg-1 of GR-MD-02 had no significant effect on non-invasive biomarkers of liver inflammation or fibrosis over a 4-month period. Histological confirmation was not available in this study. The high reproducibility of the primary outcome measure suggests that cT1 could be utilized for monitoring longitudinal change in patients with NASH.

The hydroxyl radical (OH) sets the oxidative capacity of the atmosphere and, thus, profoundly affects the removal rate of pollutants and reactive greenhouse gases. While observationally derived constraints exist for global annual mean present-day OH abundances and interannual variability, OH estimates for past and future periods rely primarily on global atmospheric chemistry models. These models disagree ± 30% in mean OH and in its changes from the preindustrial to late 21st century, even when forced with identical anthropogenic emissions. A simple steady-state relationship that accounts for ozone photolysis frequencies, water vapor, and the ratio of reactive nitrogen to carbon emissions explains temporal variability within most models, but not intermodel differences. Here, we show that departure from the expected relationship reflects the treatment of reactive oxidized nitrogen species (NO y ) and the fraction of emitted carbon that reacts within each chemical mechanism, which remain poorly known due to a lack of observational data. Our findings imply a need for additional observational constraints on NO y partitioning and lifetime, especially in the remote free troposphere, as well as the fate of carbon-containing reaction intermediates to test models, thereby reducing uncertainties in projections of OH and, hence, lifetimes of pollutants and greenhouse gases.

The published literature debates the extent to which naturally occurring stratospheric ozone intrusions reach the surface and contribute to exceedances of the U.S. National Ambient Air Quality Standard (NAAQS) for ground‐level ozone (75 ppbv implemented in 2008). Analysis of ozonesondes, lidar, and surface measurements over the western U.S. from April to June 2010 show that a global high‐resolution (∼50 × 50 km2) chemistry‐climate model (GFDL AM3) captures the observed layered features and sharp ozone gradients of deep stratospheric intrusions, representing a major improvement over previous chemical transport models. Thirteen intrusions enhanced total daily maximum 8‐h average (MDA8) ozone to ∼70–86 ppbv at surface sites. With a stratospheric ozone tracer defined relative to a dynamically varying tropopause, we find that stratospheric intrusions can episodically increase surface MDA8 ozone by 20–40 ppbv (all model estimates are bias corrected), including on days when observed ozone exceeds the NAAQS threshold. These stratospheric intrusions elevated background ozone concentrations (estimated by turning off North American anthropogenic emissions in the model) to MDA8 values of 60–75 ppbv. At high‐elevation western U.S. sites, the 25th–75th percentile of the stratospheric contribution is 15–25 ppbv when observed MDA8 ozone is 60–70 ppbv, and increases to ∼17–40 ppbv for the 70–85 ppbv range. These estimates, up to 2–3 times greater than previously reported, indicate a major role for stratospheric intrusions in contributing to springtime high‐O3events over the high‐altitude western U.S., posing a challenge for staying below the ozone NAAQS threshold, particularly if a value in the 60–70 ppbv range were to be adopted. Key Points Stratospheric intrusions can episodically increase surface ozone by 20‐40 ppbv These intrusion events can push ground‐level ozone over the health‐based limit Global high‐res model, satellite and in situ observations yield process insights