Biodiversity surveys of grassland and coastal habitats in 2021 as a documentation of pre-war status in southern Ukraine

Background This paper presents two sampling-event datasets with occurrences of vascular plants, bryophytes and lichens collected in May-June 2021 in southern Ukraine. We aimed to collect high-quality biodiversity data in an understudied region and contribute it to international databases and networks. The study was carried out during the 15th Eurasian Dry Grassland Group (EDGG) Field Workshop in southern Ukraine and the Dark Diversity Network (DarkDivNet) sampling in the Kamianska Sich National Nature Park. By chance, these datasets were collected shortly before the major escalation of the Russian invasion in Ukraine. Surveyed areas in Kherson and Mykolaiv Regions, including established monitoring plots, were severely affected by military actions in 2022. Therefore, collected data are of significant value in the context of biodiversity documentation. The knowledge about the biodiversity of this area will help to assess the environmental impact of the war and plan restoration of the damaged or destroyed habitats. The first preliminary analysis of collected data demonstrates the biodiversity richness and conservation value of studied grassland habitats. New information We provide sampling-event datasets with 7467 occurrences, which represent 708 taxa (vascular plants, bryophytes and lichens) collected in 275 vegetation relevés. Amongst them, vascular plants are represented by 6665 occurrences (610 taxa), lichens - 420 (46) and bryophytes - 381 (51). Several new species were reported for the first time at the national or regional level. In particular, one vascular plant species (Torilis pseudonodosa) and two lichen species (Cladonia conista, Endocarpon loscosii) were new to Ukraine. One vascular plant (Stipa tirsa), two species of bryophytes (Rhynchostegium megapolitanum, Ptychostomum torquescens) and three species of lichens (Cladonia cervicornis, C. symphycarpa, Involucropyrenium breussi) were recorded for the first time for the Kherson Region. Additionally, these datasets contain occurrences of taxa with narrow distribution, specialists of rare habitat types and, therefore, represented by a low number of occurrences in relevant biodiversity databases and particularly in GBIF. This publication highlights the diversity of natural vegetation and its flora in southern Ukraine and raises conservation concerns

The feature selection problem in computer-assisted cytology

Modern cancer diagnostics is based heavily on cytological examinations. Unfortunately, visual inspection of cytological preparations under the microscope is a tedious and time-consuming process. Moreover, intra- and inter-observer variations in cytological diagnosis are substantial. Cytological diagnostics can be facilitated and objectified by using automatic image analysis and machine learning methods. Computerized systems usually preprocess cytological images, segment and detect nuclei, extract and select features, and finally classify the sample. In spite of the fact that a lot of different computerized methods and systems have already been proposed for cytology, they are still not routinely used because there is a need for improvement in their accuracy. This contribution focuses on computerized breast cancer classification. The task at hand is to classify cellular samples coming from fine-needle biopsy as either benign or malignant. For this purpose, we compare 5 methods of nuclei segmentation and detection, 4 methods of feature selection and 4 methods of classification. Nuclei detection and segmentation methods are compared with respect to recall and the F1 score based on the Jaccard index. Feature selection and classification methods are compared with respect to classification accuracy. Nevertheless, the main contribution of our study is to determine which features of nuclei indicate reliably the type of cancer. We also check whether the quality of nuclei segmentation/detection significantly affects the accuracy of cancer classification. It is verified using the test set that the average accuracy of cancer classification is around 76%. Spearman’s correlation and chi-square test allow us to determine significantly better features than the feature forward selection method

Torilis pseudonodosa Bianca (Apiaceae) – new species for the flora of Ukraine

We report the first record of Torilis pseudonodosa Bianca (Apiaceae) from Ukraine. It was found on 28th of May 2021 in the “Potiivska” section of the Black Sea Biosphere Reserve near the village of Zaliznyi Port (Southern Ukraine). Torilis pseudonodosa previously was known from various countries in the Mediterranean Basin and Western Asia, but not from Ukraine nor elsewhere in Eastern Europe. We discovered a hitherto unknown population of Torilis pseudonodosa during the 15th EDGG Field Workshop, an international expedition of the Eurasian Dry Grassland Group (EDGG) taking place in Southern Ukraine, from 23 May to 2 June 2021. We present the taxon, its morphology and general distribution, describe its first Ukrainian site ecologically and coenologically and provide photos of the site and the species. The species occurred in a saline steppe, close to the Black Sea coast. The vegetation was dominated by Agropyron pectinatum and Halimione verrucifera, with Artemisia santonica, Festuca callieri agg., Milium vernale and Vicia hirsuta as subdominants. The classification of the saline steppe of the “Potiivska” section of the Black Sea Biosphere Reserve near is problematic, because species composition represents a mixture of steppic and halophytic plants. A definitive decision would require comprehensive phytosociological analyses. Since there was no indication of anthropogenic influence at the site, we assume that Torilis pseudonodosa reached it as a result of natural migration of its propagules (e.g. with birds). Thus, the species can be considered as nonsynathropic in the flora of Ukraine

Curriculum Cardiology 2nd updated Edition

The updated second edition of the Curriculum cardiology, first edition 2013, aims to show which competences a cardiologist should nowadays master. It is very pleasing that in this second edition representatives of the Young German Cardiac Society (Young DGK) have contributed as authors. The increasing specialization within cardiology should, however, only represent one side of the coin: there must also still be a common foundation of cardiology, embedded in the discipline internal medicine. This foundation includes the basis of theoretical knowledge, practical skills (competence levels I-III) and an occupational and professional attitude of the (prospective) cardiologist. New additions to the advanced training since the first edition of the curriculum in 2013 are, for example a chapter on digital cardiology, the further training in psychocardiology, which was newly introduced into the model further training regulations and finally also the explicit formulation of shared decision making in the interests of cardiac patients. The curriculum should give the prospective cardiologist the possibility to structure the further training as efficiently as possible and ultimately to retain and expand that which has been learned in the sense of a professional lifelong qualification. The curriculum also aims to reach the trainers and the Medical Councils and demonstrate which contents and skills should be mediated in the further training to become a cardiologist from the perspective of the German Cardiac Society (DGK)