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Institute
In-situ single particle analysis of ice particle residuals (IPR) and out-of-cloud aerosol particles was conducted by means of laser ablation mass spectrometry during the intensive INUIT-JFJ/CLACE campaign at the high alpine research station Jungfraujoch (3580 m a.s.l.) in January/February 2013. During the four week campaign more than 70000 out-of-cloud aerosol particles and 595 IPR were analyzed covering a particle size diameter range from 100 nm to 3 μm. The IPR were sampled during 273 hours while the station was covered by mixed-phase clouds at ambient temperatures between -27 °C and -6 °C. The identification of particle types is based on laboratory studies of different types of biological, mineral and anthropogenic aerosol particles. As outcome instrument specific marker peaks for the different investigated particle types were obtained and applied to the field data. The results show that the sampled IPR contain a larger relative amount of natural, primary aerosol, like soil dust (13 %) and minerals (11 %), in comparison to out-of-cloud aerosol particles (2 % and <1 %, respectively). Additionally, anthropogenic aerosol particles, like particles from industrial emissions and lead-containing particles, were found to be more abundant in the IPR than in the out-of-cloud aerosol. The out of-cloud aerosol contained a large fraction of aged particles (30 %, including organic material and secondary inorganics), whereas this particle type was much less abundant (3 %) in the IPR. In a selected subset of the data where a direct comparison between out-of-cloud aerosol particles and IPR in air masses with similar origin was possible, a pronounced enhancement of biological particles was found in the IPR.
Charts are used to measure relative success for a large variety of cultural items. Traditional music charts have been shown to follow self-organizing principles with regard to the distribution of item lifetimes, the on-chart residence times. Here we examine if this observation holds also for (a) music streaming charts (b) book best-seller lists and (c) for social network activity charts, such as Twitter hashtags and the number of comments Reddit postings receive. We find that charts based on the active production of items, like commenting, are more likely to be influenced by external factors, in particular by the 24 h day–night cycle. External factors are less important for consumption-based charts (sales, downloads), which can be explained by a generic theory of decision-making. In this view, humans aim to optimize the information content of the internal representation of the outside world, which is logarithmically compressed. Further support for information maximization is argued to arise from the comparison of hourly, daily and weekly charts, which allow to gauge the importance of decision times with respect to the chart compilation period.
Scores to identify patients at high risk of progression of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may become instrumental for clinical decision-making and patient management. We used patient data from the multicentre Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) and applied variable selection to develop a simplified scoring system to identify patients at increased risk of critical illness or death. A total of 1946 patients who tested positive for SARS-CoV-2 were included in the initial analysis and assigned to derivation and validation cohorts (n = 1297 and n = 649, respectively). Stability selection from over 100 baseline predictors for the combined endpoint of progression to the critical phase or COVID-19-related death enabled the development of a simplified score consisting of five predictors: C-reactive protein (CRP), age, clinical disease phase (uncomplicated vs. complicated), serum urea, and D-dimer (abbreviated as CAPS-D score). This score yielded an area under the curve (AUC) of 0.81 (95% confidence interval [CI]: 0.77–0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (95% CI: 0.77–0.85) during full follow-up. We used an additional prospective cohort of 682 patients, diagnosed largely after the “first wave” of the pandemic to validate the predictive accuracy of the score and observed similar results (AUC for the event within 7 days: 0.83 [95% CI: 0.78–0.87]; for full follow-up: 0.82 [95% CI: 0.78–0.86]). An easily applicable score to calculate the risk of COVID-19 progression to critical illness or death was thus established and validated.
In this study we show how size-resolved measurements of aerosol particles and cloud condensation nuclei (CCN) can be used to characterize the supersaturation of water vapor in a cloud. The method was developed and applied for the investigation of a cloud event during the ACRIDICON-Zugspitze campaign (17 September to 4 October 2012) at the high-alpine research station Schneefernerhaus (German Alps, 2650 m a.s.l.). Number size distributions of total and interstitial aerosol particles were measured with a scanning mobility particle sizer (SMPS), and size-resolved CCN efficiency spectra were recorded with a CCN counter system operated at different supersaturation levels.
During the evolution of a cloud, aerosol particles are exposed to different supersaturation levels. We outline and compare different estimates for the lower and upper bounds (Slow, Shigh) and the average value (Savg) of peak supersaturation encountered by the particles in the cloud. For the investigated cloud event, we derived Slow ≈ 0.19–0.25%, Shigh ≈ 0.90–1.64% and Savg ≈ 0.38–0.84%. Estimates of Slow, Shigh and Savg based on aerosol size distribution data require specific knowledge or assumptions of aerosol hygroscopicity, which are not required for the derivation of Slow and Savg from the size-resolved CCN efficiency spectra.
In this study we show how size-resolved measurements of aerosol particles and cloud condensation nuclei (CCN) can be used to characterize the supersaturation of water vapor in a cloud. The method was developed and applied during the ACRIDICON-Zugspitze campaign (17 September to 4 October 2012) at the high-Alpine research station Schneefernerhaus (German Alps, 2650 m a.s.l.). Number size distributions of total and interstitial aerosol particles were measured with a scanning mobility particle sizer (SMPS), and size-resolved CCN efficiency spectra were recorded with a CCN counter system operated at different supersaturation levels.
During the evolution of a cloud, aerosol particles are exposed to different supersaturation levels. We outline and compare different estimates for the lower and upper bounds (Slow, Shigh) and the average value (Savg) of peak supersaturation encountered by the particles in the cloud. A major advantage of the derivation of Slow and Savg from size-resolved CCN efficiency spectra is that it does not require the specific knowledge or assumptions about aerosol hygroscopicity that are needed to derive estimates of Slow, Shigh, and Savg from aerosol size distribution data. For the investigated cloud event, we derived Slow ≈ 0.07–0.25%, Shigh ≈ 0.86–1.31% and Savg ≈ 0.42–0.68%.
We investigate what statistical properties drive risk-taking in a large set of observational panel data on online poker games (n=4,450,585). Each observation refers to a choice between a safe 'insurance' option and a binary lottery of winning or losing the game. Our setting offers a real-world choice situation with substantial incentives where probability distributions are simple, transparent, and known to the individuals. We find that individuals reveal a strong and robust preference for skewness. The effect of skewness is most pronounced among experienced and losing players but remains highly significant for winning players, in contrast to the variance effect.
Investigation of the sympathetic regulation in delayed onset muscle soreness: results of an RCT
(2021)
Sports-related pain and injury is directly linked to tissue inflammation, thus involving the autonomic nervous system (ANS). In the present experimental study, we disable the sympathetic part of the ANS by applying a stellate ganglion block (SGB) in an experimental model of delayed onset muscle soreness (DOMS) of the biceps muscle. We included 45 healthy participants (female 11, male 34, age 24.16 ± 6.67 years [range 18–53], BMI 23.22 ± 2.09 kg/m2) who were equally randomized to receive either (i) an SGB prior to exercise-induced DOMS (preventive), (ii) sham intervention in addition to DOMS (control/sham), or (iii) SGB after the induction of DOMS (rehabilitative). The aim of the study was to determine whether and to what extent sympathetically maintained pain (SMP) is involved in DOMS processing. Focusing on the muscular area with the greatest eccentric load (biceps distal fifth), a significant time × group interaction on the pressure pain threshold was observed between preventive SGB and sham (p = 0.034). There was a significant effect on pain at motion (p = 0.048), with post hoc statistical difference at 48 h (preventive SGB Δ1.09 ± 0.82 cm VAS vs. sham Δ2.05 ± 1.51 cm VAS; p = 0.04). DOMS mediated an increase in venous cfDNA -as a potential molecular/inflammatory marker of DOMS- within the first 24 h after eccentric exercise (time effect p = 0.018), with a peak at 20 and 60 min. After 60 min, cfDNA levels were significantly decreased comparing preventive SGB to sham (unpaired t-test p = 0.008). At both times, 20 and 60 min, cfDNA significantly correlated with observed changes in PPT. The 20-min increase was more sensitive, as it tended toward significance at 48 h (r = 0.44; p = 0.1) and predicted the early decrease of PPT following preventive stellate blocks at 24 h (r = 0.53; p = 0.04). Our study reveals the broad impact of the ANS on DOMS and exercise-induced pain. For the first time, we have obtained insights into the sympathetic regulation of pain and inflammation following exercise overload. As this study is of a translational pilot character, further research is encouraged to confirm and specify our observations.
As part of the CLACE-6 campaign we performed size-resolved CCN measurements for a~supersaturation range of S = 0.079 % to 0.66% at the high-alpine research station Jungfraujoch, Switzerland, in March~2007. The derived effective hygroscopicity parameter κ describing the influence of particle composition on CCN activity was on average 0.23–0.30 for Aitken (50–100 nm) and 0.32–0.43 for accumulation mode particles (100–200 nm). The campaign average value of κ = 0.3 is similar to the average value of κ for other continental locations. When air masses came from southeasterly directions crossing the Po Valley in Italy, particles were much more hygroscopic (κ ≈ 0.42) due to large sulfate mass fractions. The κ values obtained at S = 0.079 % exhibited a good negative correlation with the organic mass fractions derived from PM1 aerosol mass spectrometer (AMS) measurements. Applying a simple mixing rule the organic and inorganic mass fractions observed by the AMS could be used to reproduce the temporal fluctuations of the hygroscopicity of accumulation mode particles quite well.
We show how during a cloud event the aerosol particles were activated as cloud droplets and then removed from the air by precipitation leaving behind only a small amount of accumulation mode particles consisting mainly of weakly CCN-active particles, most likely externally mixed unprocessed soot particles.
During the campaign we had the opportunity to directly compare two DMT CCN counters for a certain time. The total CCN concentration (NCCN,tot) obtained by the two instruments at equal supersaturations agreed well for both possible operating modes: detecting NCCN,tot directly by sampling the polydisperse aerosol with the CCNC, or indirectly by combining size-resolved measurements of the activated fraction with parallel measurements of the particle size distribution (e.g., by SMPS). However, some supersaturation setpoints differed between the two CCNCs by as much as 20% after applying the instrument calibrations, which resulted in differences of the corresponding NCCN,tot of up to 50%. This emphasizes that it is extremely important to carefully calibrate the supersaturation of the instrument, especially at low S.
During the measurement campaign FROST 2 (FReezing Of duST 2), the Leipzig Aerosol Cloud Interaction Simulator (LACIS) was used to investigate the influence of various surface modifications on the ice nucleating ability of Arizona Test Dust (ATD) particles in the immersion freezing mode. The dust particles were exposed to sulfuric acid vapor, to water vapor with and without the addition of ammonia gas, and heat using a thermodenuder operating at 250 °C. Size selected, quasi monodisperse particles with a mobility diameter of 300 nm were fed into LACIS and droplets grew on these particles such that each droplet contained a single particle. Temperature dependent frozen fractions of these droplets were determined in a temperature range between −40 °C ≤T≤−28 °C. The pure ATD particles nucleated ice over a broad temperature range with their freezing behavior being separated into two freezing branches characterized through different slopes in the frozen fraction vs. temperature curves. Coating the ATD particles with sulfuric acid resulted in the particles' IN potential significantly decreasing in the first freezing branch (T>−35 °C) and a slight increase in the second branch (T≤−35 °C). The addition of water vapor after the sulfuric acid coating caused the disappearance of the first freezing branch and a strong reduction of the IN ability in the second freezing branch. The presence of ammonia gas during water vapor exposure had a negligible effect on the particles' IN ability compared to the effect of water vapor. Heating in the thermodenuder led to a decreased IN ability of the sulfuric acid coated particles for both branches but the additional heat did not or only slightly change the IN ability of the pure ATD and the water vapor exposed sulfuric acid coated particles. In other words, the combination of both sulfuric acid and water vapor being present is a main cause for the ice active surface features of the ATD particles being destroyed. A possible explanation could be the chemical transformation of ice active metal silicates to metal sulfates. The strongly enhanced reaction between sulfuric acid and dust in the presence of water vapor and the resulting significant reductions in IN potential are of importance for atmospheric ice cloud formation. Our findings suggest that the IN concentration can decrease by up to one order of magnitude for the conditions investigated.