Europium Underneath Graphene on Ir(111): Intercalation Mechanism, Magnetism, and Band Structure

The intercalation of Eu underneath Gr on Ir(111) is comprehensively investigated by microscopic, magnetic, and spectroscopic measurements, as well as by density functional theory. Depending on the coverage, the intercalated Eu atoms form either a $(2 \times 2)$ or a $(\sqrt{3} \times \sqrt{3})$R$30^{\circ}$ superstructure with respect to Gr. We investigate the mechanisms of Eu penetration through a nominally closed Gr sheet and measure the electronic structures and magnetic properties of the two intercalation systems. Their electronic structures are rather similar. Compared to Gr on Ir(111), the Gr bands in both systems are essentially rigidly shifted to larger binding energies resulting in n-doping. The hybridization of the Ir surface state $S_1$ with Gr states is lifted, and the moire superperiodic potential is strongly reduced. In contrast, the magnetic behavior of the two intercalation systems differs substantially as found by X-ray magnetic circular dichroism. The $(2 \times 2)$ Eu structure displays plain paramagnetic behavior, whereas for the $(\sqrt{3} \times \sqrt{3})$R$30^{\circ}$ structure the large zero-field susceptibility indicates ferromagnetic coupling, despite the absence of hysteresis at 10 K. For the latter structure, a considerable easy-plane magnetic anisotropy is observed and interpreted as shape anisotropy.Comment: 18 pages with 14 figures, including Supplemental Materia

Association between exercise frequency with renal and cardiovascular outcomes in diabetic and non-diabetic individuals at high cardiovascular risk

Background: Guidelines recommend physical activity to reduce cardiovascular (CV) events. The association between physical activity and progression of chronic kidney disease (CKD) with and without diabetes is unknown. We assessed the association of self-reported physical activity with renal and CV outcomes in high-risk patients aged≥55 years over a median follow-up of 56 months in post-hoc analysis of a previously randomized trial program. Methods: Analyses were done with Cox regression analysis, mixed models for repeated measures, ANOVA and χ2 - test. 31,312 patients, among them 19,664 with and 11,648 without diabetes were analyzed. Results: Physical activity was inversely associated with renal outcomes (doubling of creatinine, end-stage kidney disease (ESRD)) and CV outcomes (CV death, myocardial infarction, stroke, heart failure hospitalization). Moderate activity (at least 2 times/week to every day) was associated with lower risk of renal outcomes and lower incidence of new albuminuria (p<0.0001 for both) compared to lower exercise levels. Similar results were observed for those with and without diabetes without interaction for renal outcomes (p=0.097–0.27). Physical activity was associated with reduced eGFR decline with a moderate association between activity and diabetes status (p=0.05). Conclusions: Moderate physical activity was associated with improved kidney outcomes with a threshold at two sessions per week. The association of physical activity with renal outcomes did not meaningfully difer with or without diabetes but absolute beneft of activity was even greater in people with diabetes. Thus, risks were similar between those with diabetes undertaking high physical activity and those without diabetes but low physical activity. Clinical trial registration: http://clinicaltrials.gov.uniqueidentifer:NCT00153101

Association between exercise frequency with renal and cardiovascular outcomes in diabetic and non-diabetic individuals at high cardiovascular risk

Background: Guidelines recommend physical activity to reduce cardiovascular (CV) events. The association between physical activity and progression of chronic kidney disease (CKD) with and without diabetes is unknown. We assessed the association of self-reported physical activity with renal and CV outcomes in high-risk patients aged ≥ 55 years over a median follow-up of 56 months in post-hoc analysis of a previously randomized trial program. Methods Analyses were done with Cox regression analysis, mixed models for repeated measures, ANOVA and χ2-test. 31,312 patients, among them 19,664 with and 11,648 without diabetes were analyzed. Results Physical activity was inversely associated with renal outcomes (doubling of creatinine, end-stage kidney disease (ESRD)) and CV outcomes (CV death, myocardial infarction, stroke, heart failure hospitalization). Moderate activity (at least 2 times/week to every day) was associated with lower risk of renal outcomes and lower incidence of new albuminuria (p < 0.0001 for both) compared to lower exercise levels. Similar results were observed for those with and without diabetes without interaction for renal outcomes (p = 0.097–0.27). Physical activity was associated with reduced eGFR decline with a moderate association between activity and diabetes status (p = 0.05). Conclusions Moderate physical activity was associated with improved kidney outcomes with a threshold at two sessions per week. The association of physical activity with renal outcomes did not meaningfully differ with or without diabetes but absolute benefit of activity was even greater in people with diabetes. Thus, risks were similar between those with diabetes undertaking high physical activity and those without diabetes but low physical activity. Clinical trial registration: http://clinicaltrials.gov.uniqueidentifier :NCT00153101

Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection

As several countries gradually release social distancing measures, rapid detection of new localized COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (automatic selection of models and outlier detection for epidemics), a new tool for detecting sudden changes in COVID-19 incidence. Our approach relies on automatically selecting the best (fitting or predicting) model from a range of user-defined time series models, excluding the most recent data points, to characterize the main trend in an incidence. We then derive prediction intervals and classify data points outside this interval as outliers, which provides an objective criterion for identifying departures from previous trends. We also provide a method for selecting the optimal breakpoints, used to define how many recent data points are to be excluded from the trend fitting procedure. The analysis of simulated COVID-19 outbreaks suggests ASMODEE compares favourably with a state-of-art outbreak-detection algorithm while being simpler and more flexible. As such, our method could be of wider use for infectious disease surveillance. We illustrate ASMODEE using publicly available data of National Health Service (NHS) Pathways reporting potential COVID-19 cases in England at a fine spatial scale, showing that the method would have enabled the early detection of the flare-ups in Leicester and Blackburn with Darwen, two to three weeks before their respective lockdown. ASMODEE is implemented in the free R package trendbreaker. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -- corrected for geometrical effects -- is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO

Single-nanoparticle phase transitions visualized by four-dimensional electron microscopy

The advancement of techniques that can probe the behaviour of individual nanoscopic objects is of paramount importance in various disciplines, including photonics and electronics. As it provides images with a spatiotemporal resolution, four-dimensional electron microscopy, in principle, should enable the visualization of single-nanoparticle structural dynamics in real and reciprocal space. Here, we demonstrate the selectivity and sensitivity of the technique by visualizing the spin crossover dynamics of single, isolated metal–organic framework nanocrystals. By introducing a small aperture in the microscope, it was possible to follow the phase transition and the associated structural dynamics within a single particle. Its behaviour was observed to be distinct from that imaged by averaging over ensembles of heterogeneous nanoparticles. The approach reported here has potential applications in other nanosystems and those that undergo (bio)chemical transformations

Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy

We measure the energy emitted by extensive air showers in the form of radio emission in the frequency range from 30 to 80 MHz. Exploiting the accurate energy scale of the Pierre Auger Observatory, we obtain a radiation energy of 15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV arriving perpendicularly to a geomagnetic field of 0.24 G, scaling quadratically with the cosmic-ray energy. A comparison with predictions from state-of-the-art first-principle calculations shows agreement with our measurement. The radiation energy provides direct access to the calorimetric energy in the electromagnetic cascade of extensive air showers. Comparison with our result thus allows the direct calibration of any cosmic-ray radio detector against the well-established energy scale of the Pierre Auger Observatory.Comment: Replaced with published version. Added journal reference and DOI. Supplemental material in the ancillary file