The Student Club as a Tool for Attracting Youth Audience to Museums

open access articleThe authors describe the possibility of using a differentiated approach based on vocational education in the field of art and culture as a new criterion for attracting youth audiences to museums in the digital era. A distinctive feature of the differentiated approach in the activities of museum student clubs is the targeted impact on various groups of young people, taking into account their age and level of art training in the development of museum programs. In order to assess the applicability of the differentiated approach to working with young people in museums, the members of student clubs of the two largest museums in Russia, i.e., the Hermitage and the Russian Museum, were surveyed. Expert interviews with the staff of the student clubs were also conducted. Based on the results of the analysis, the authors identified three groups of the young people, which were designated as “interested,” “advanced” and “proficient.” The criteria for dividing into the groups were differences in the educational level of the students in the field of art and culture. This division allowed to determine the forms of the most attractive museum events for the identified groups of students. The results of the study may be useful in working with the youth audience in other museums

Applying Machine Learning to the Phenomenological Flow Stress Modeling of TNM-B1

Data-driven or machine learning approaches are increasingly being used in material science and research. Specifically, machine learning has been implemented in the fields of materials discovery, prediction of phase diagrams and material modelling. In this work, the application of machine learning to the traditional phenomenological flow stress modelling of the titanium aluminide (TiAl) alloy TNM-B1 (Ti-43.5Al-4Nb-1Mo-0.1B) is investigated. Three model types were developed, analyzed and compared; a physics-based phenomenological model (PM) originally developed for steel by Cingara and McQueen, a purely data-driven machine learning model (MLM), and a hybrid model (HM), which uses characteristic points predicted by a learning algorithm as input for the phenomenological model. The same amount of data was used to both fit the PM and train the MLM and HM. The models were analyzed and compared based on the accuracy of their predictions, development and computing time, and their ability to predict on interpolated and extrapolated inputs. The results revealed that for the same amount of experimental data, the MLM was more accurate than the PM. In addition, the MLM was better able to capture the characteristic peak stress in the TNM-B1 the flow curves, and could be developed and computed faster. Furthermore, the MLM was able to make realistic predictions for inputs outside the experimental data used for training. The HM showed comparable accuracy to the PM for the experimental conditions. However, the HM was able to produce a better fit for input conditions outside the training data

Catheter ablation for atrial fibrillation after an unsuccessful surgical ablation and biological prosthetic mitral valve replacement: A pilot study

Background: Patients with mitral valve (MV) disease and atrial fibrillation (AF) undergo simultaneous prosthetic valve replacement and radiofrequency (RF) ablation procedure; however, this combinational procedure restores sinus rhythm (SR) in only 68–82% of the cases. In patients with ineffective surgical ablation, the use of a biological prosthetic valve might not only be a good choice to perform safe catheter ablation procedure in the left atrium (LA), but also provide a way to discontinue administration of oral anticoagulants. The objective of this study was to assess the efficacy of catheter ablation for AF after MV replacement with a biological prosthesis and an ineffective surgical ablation procedure. Methods: Ten consecutive patients aged 48 ± 7 years were enrolled in this study. All patients had long-persistent AF associated with a rheumatic valve disease, which was treated by MV replacement with a biological prosthesis and a surgical RF ablation procedure. In the late postoperative period, all the patients had recurrent hemodynamically significant AF, which required repeated cardioversions. From 1 year to 3 years after the surgery, catheter ablation was performed, including reisolation of pulmonary veins (PVs) with the ablation of ganglionic plexi or linear lesions on the roof of the LA and mitral isthmus. The efficacy was assessed at 3 months, 6 months, and 12 months after the procedure. Results: Restoration of SR during ablation was achieved in all of the cases. In 6–9 months, all the patients were free of arrhythmia. LA stunning manifested by the absence or decrease of the “A” wave in the transmitral flow and the retrograde wave in the PV flow was observed in nine patients with SR. In five of the patients, LA contractile function was restored in 1–6 months. Prosthetic valve dysfunction was not detected in any of the patients. Conclusion: Catheter ablation is an effective method for AF treatment following an ineffective surgical RF ablation procedure and biological prosthetic MV replacement. The use of bioprosthetic MVs allows for performing safe catheter ablation without subsequent prosthetic dysfunction