The Marangoni effect and translation of free non-deformable drops

A model is presented for flow caused by interface tension gradients, the so called Marangoni effect, on a free, nondeformable drop. A free drop, initially at rest, undergoes a translation motion upon the action of surface flow. The experiments carried out by injecting a drop with surfactants, which induce an interface tension gradient, are in good agreement with the theoretical model proposed

Low polarized emission from the core of coronal mass ejections

In white-light coronagraph images, cool prominence material is sometimes observed as bright patches in the core of coronal mass ejections (CMEs). If, as generally assumed, this emission is caused by Thomson-scattered light from the solar surface, it should be strongly polarised tangentially to the solar limb. However, the observations of a CME made with the SECCHI/STEREO coronagraphs on 31 August 2007 show that the emission from these bright core patches is exceptionally low polarised. We used the polarisation ratio method of Moran and Davila (2004) to localise the barycentre of the CME cloud. By analysing the data from both STEREO spacecraft we could resolve the plane-of-the-sky ambiguity this method usually suffers from. Stereoscopic triangulation was used to independently localise the low-polarisation patch relative to the cloud. We demonstrated for the first time that the bright core material is located close to the centre of the CME cloud. We show that the major part of the CME core emission, more than 85% in our case, is H$\alpha$ radiation and only a small fraction is Thomson-scattered light. Recent calculations also imply that the plasma density in the patch is 8 10$^8$ cm$^{-3}$ or more compared to 2.6 10$^6$ cm$^{-3}$ for the Thomson-scattering CME environment surrounding the core material.Comment: 5 pages, 3 figure

Machine learning in solar physics

The application of machine learning in solar physics has the potential to greatly enhance our understanding of the complex processes that take place in the atmosphere of the Sun. By using techniques such as deep learning, we are now in the position to analyze large amounts of data from solar observations and identify patterns and trends that may not have been apparent using traditional methods. This can help us improve our understanding of explosive events like solar flares, which can have a strong effect on the Earth environment. Predicting hazardous events on Earth becomes crucial for our technological society. Machine learning can also improve our understanding of the inner workings of the sun itself by allowing us to go deeper into the data and to propose more complex models to explain them. Additionally, the use of machine learning can help to automate the analysis of solar data, reducing the need for manual labor and increasing the efficiency of research in this field.Comment: 100 pages, 13 figures, 286 references, accepted for publication as a Living Review in Solar Physics (LRSP

Outcome of COVID-19 infections in patients with adrenal insufficiency and excess

Background: Information on clinical outcomes of coronavirus disease 19 (COVID-19) infection in patients with adrenal disorders is scarce. Methods: A collaboration between the European Society of Endocrinology (ESE) Rare Disease Committee and European Reference Network on Rare Endocrine Conditions via the European Registries for Rare Endocrine Conditions allowed the collection of data on 64 cases (57 adrenal insufficiency (AI), 7 Cushing's syndrome) that had been reported by 12 centres in 8 European countries between January 2020 and December 2021. Results: Of all 64 patients, 23 were males and 41 females (13 of those children) with a median age of 37 and 51 years. In 45/57 (95%) AI cases, COVID-19 infection was confirmed by testing. Primary insufficiency was present in 45/57 patients; 19 were affected by Addison's disease, 19 by congenital adrenal hyperplasia and 7 by primary AI (PAI) due to other causes. The most relevant comorbidities were hypertension (12%), obesity (n = 14%) and diabetes mellitus (9%). An increase by a median of 2.0 (IQR 1.4) times the daily replacement dose was reported in 42 (74%) patients. Two patients were administered i.m. injection of 100 mg hydrocortisone, and 11/64 were admitted to the hospital. Two patients had to be transferred to the intensive care unit, one with a fatal outcome. Four patients reported persistent SARS-CoV-2 infection, all others complete remission. Conclusion: This European multicentre questionnaire is the first to collect data on the outcome of COVID-19 infection in patients with adrenal gland disorders. It suggests good clinical outcomes in case of duly dose adjustments and emphasizes the importance of patient education on sick day rules.Metabolic health: pathophysiological trajectories and therap

Fixed point results for set-contractions on metric spaces with a directed graph

In this paper, we establish the existence of fixed points for set-valued mappings satisfying certain graph contractions with set-valued domain endowed with a graph. These results unify, generalize, and complement various known comparable results in the literature.King Fahd University of Petroleum and Minerals project IN 121023.http://link.springer.com/journal/11784hb201

Assessing the quality of models of the ambient solar wind

In this paper we present an assessment of the status of models of the global Solar Wind in the inner heliosphere. We limit our discussion to the class of models designed to provide solar wind forecasts, excluding those designed for the purpose of testing physical processes in idealized configurations. In addition, we limit our discussion to modeling of the ‘ambient’ wind in the absence of coronal mass ejections. In this assessment we cover use of the models both in forecast mode and as tools for scientific research. We present a brief history of the development of these models, discussing the range of physical approximations in use. We discuss the limitations of the data inputs available to these models and its impact on their quality. We also discuss current model development trends