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Water Vapor Vertical Profiles on Mars in Dust Storms Observed by TGO/NOMAD
It has been suggested that dust storms efficiently transport water vapor from the near‐surface to the middle atmosphere on Mars. Knowledge of the water vapor vertical profile during dust storms is important to understand water escape. During Martian Year 34, two dust storms occurred on Mars: a global dust storm (June to mid‐September 2018) and a regional storm (January 2019). Here we present water vapor vertical profiles in the periods of the two dust storms (Ls = 162–260° and Ls = 298–345°) from the solar occultation measurements by Nadir and Occultation for Mars Discovery (NOMAD) onboard ExoMars Trace Gas Orbiter (TGO). We show a significant increase of water vapor abundance in the middle atmosphere (40–100 km) during the global dust storm. The water enhancement rapidly occurs following the onset of the storm (Ls~190°) and has a peak at the most active period (Ls~200°). Water vapor reaches very high altitudes (up to 100 km) with a volume mixing ratio of ~50 ppm. The water vapor abundance in the middle atmosphere shows high values consistently at 60°S‐60°N at the growth phase of the dust storm (Ls = 195°–220°), and peaks at latitudes greater than 60°S at the decay phase (Ls = 220°–260°). This is explained by the seasonal change of meridional circulation: from equinoctial Hadley circulation (two cells) to the solstitial one (a single pole‐to‐pole cell). We also find a conspicuous increase of water vapor density in the middle atmosphere at the period of the regional dust storm (Ls = 322–327°), in particular at latitudes greater than 60°S
Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.
BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362
Can Social Learning Increase Learning Speed, Performance or Both?
Social learning enables multiple robots to share learned experiences while completing a task. The literature offers contradicting examples of its benefits; robots trained with social learning reach a higher performance, an increased learning speed, or both, compared to their individual learning counterparts. No general explanation has been advanced for the difference in observations, which make the results highly dependent on the particular system and parameter setting. In this research, we show that even within one system, the observed advantages of social learning can vary between parameter settings. Using Evolutionary Robotics, we train robots individually in a foraging task. We compare the performance of 50 parameter instances of the evolutionary algorithm obtained by a definitive screening design. We apply social learning in groups of two and four robots to the parameter settings that lead to the best and median performance. Our results show that the observed advantages of social learning differ highly between parameter settings but in general, median quality parameter settings experience more benefit from social learning. These results serve as a reminder that tuning of the parameters should not be left as an afterthought because they can drastically impact the conclusions on the advantages of social learning. Additionally, these results suggest that social learning reduces the sensitivity of the learning process to the choice of parameters
The dialogical self as a society of mind. Introduction
Item does not contain fulltextThe dialogical self works as a society with oppositions, conflicts, negotiations, cooperation and coalitions between positions. As society becomes more heterogeneous, more relatively autonomous spatial domains emerge in the self. Like a society, the self is based on two principles: intersubjective exchange and social domination. The article briefly discusses the different contributions in the light of the developing theory