STUDY QUESTION How did coronavirus disease 2019 (COVID-19) impact on medically assisted reproduction (MAR) services in Europe during the COVID-19 pandemic (March to May 2020)? SUMMARY ANSWER MAR services, and hence treatments for infertile couples, were stopped in most European countries for a mean of 7 weeks. WHAT IS KNOWN ALREADY With the outbreak of COVID-19 in Europe, non-urgent medical care was reduced by local authorities to preserve health resources and maintain social distancing. Furthermore, ESHRE and other societies recommended to postpone ART pregnancies as of 14 March 2020. STUDY DESIGN, SIZE, DURATION A structured questionnaire was distributed in April among the ESHRE Committee of National Representatives, followed by further information collection through email. PARTICIPANTS/MATERIALS, SETTING, METHODS The information was collected through the questionnaire and afterwards summarised and aligned with data from the European Centre for Disease Control on the number of COVID-19 cases per country. MAIN RESULTS AND THE ROLE OF CHANCE By aligning the data for each country with respective epidemiological data, we show a large variation in the time and the phase in the epidemic in the curve when MAR/ART treatments were suspended and restarted. Similarly, the duration of interruption varied. Fertility preservation treatments and patient supportive care for patients remained available during the pandemic. LARGE SCALE DATA N/A LIMITATIONS, REASONS FOR CAUTION Data collection was prone to misinterpretation of the questions and replies, and required further follow-up to check the accuracy. Some representatives reported that they, themselves, were not always aware of the situation throughout the country or reported difficulties with providing single generalised replies, for instance when there were regional differences within their country. WIDER IMPLICATIONS OF THE FINDINGS The current article provides a basis for further research of the different strategies developed in response to the COVID-19 crisis. Such conclusions will be invaluable for health authorities and healthcare professionals with respect to future similar situations. STUDY FUNDING/COMPETING INTEREST(S) There was no funding for the study, apart from technical support from ESHRE. The authors had no COI to disclose.

Human Merkel cells (MCs) were first described by Friedrich S. Merkel in 1875 and named “Tastzellen” (touch cells). Merkel cells are primarily localized in the basal layer of the epidermis and concentrated in touch-sensitive areas. In our previous work, we reported on the distribution of MCs in the human esophagus, so therefore we chose other parts of the human body to study them. We selected the human vagina, because it has a similar epithelium as the esophagus and plays very important roles in reproduction and sexual pleasure. Due to the fact that there are very few research studies focusing on the innervation of this region, we decided to investigate the occurrence of MCs in the anterior wall of the vagina. The aim of our research was to identify MCs in the stratified squamous non-keratinized epithelium of the human vagina in 20 patients. For the identification of Merkel cells by light microscopy, we used antibodies against simple-epithelial cytokeratins (especially anti-cytokeratin 20). We also tried to identify them using transmission electron microscopy. Our investigation confirmed that 10 (50 %) of 20 patients had increased number of predominantly intraepithelial CK20 positive “Merkel-like” cells (MLCs) in the human vaginal epithelium. Subepithelial CK20 positive MLCs were observed in only one patient (5%). We tried to identify them also using transmission electron microscopy. Our investigation detected some unique cells that may be MCs. The purpose of vaginal innervation is still unclear. There are no data available concerning the distribution of MCs in the human vagina, so it would be interesting to study the role of MCs in the vaginal epithelium, in the context of innervation and epithelial biology.

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We introduce KaraMIR, a musical project dedicated to karaoke song analysis. Within KaraMIR, we define Kara1k, a dataset composed of 1000 cover songs provided by Recisio Karafun application, and the corresponding 1000 songs by the original artists. Kara1k is mainly dedicated toward cover song identification and singing voice analysis. For both tasks, Kara1k offers novel approaches, as each cover song is a studio-recorded song with the same arrangement as the original recording, but with different singers and musicians. Essentia, harmony-analyser, Marsyas, Vamp plugins and YAAFE have been used to extract audio features for each track in Kara1k. We provide metadata such as the title, genre, original artist, year, International Standard Recording Code and the ground truths for the singer’s gender, backing vocals, duets, and lyrics’ language. KaraMIR project focuses on defining new problems and describing features and tools to solve them. We thus provide a comparison of traditional and new features for a cover song identification task using statistical methods, as well as the dynamic time warping method on chroma, MFCC, chords, keys, and chord distance features. A supporting experiment on the singer gender classification task is also proposed. The KaraMIR project website facilitates the continuous research.

Part 3: Data Analysis and Information RetrievalInternational audienceCover song identification has been a popular task within music information retrieval in the 20th century. The task is to identify a different version or performance of a previously recorded song. Unlike audio search for an exact matching song, this task has not yet been popularized among users, due to an ambiguous definition of a cover song and the complexity of the problem. With a great variety of methods proposed on the benchmarking challenges, it is increasingly difficult to compare advantages and disadvantages of the features and algorithms. We provide a comparison of three levels of feature extraction (chroma features, chroma vector distances, chord distances) and show how each level affects the results. We further distinguish five scores for dynamic time warping method, to find the best performance in conjunction with the features. Results were evaluated on covers80 and SecondHandSongs datasets and compared to the state-of-the-art