This paper presents new records and noteworthy data on the following taxa in SE Europe and adjacent regions: red algae Lemanea rigida and Paralemanea torulosa, mycorrhizal fungi Amanita simulans and Terfezia pseudoleptoderma, parasitic fungus Microbotryum vinosum, saprotrophic fungus Sarcoscypha jurana, stonewort Chara tenuispina, mosses Brachytheciastrum collinum and Meesia longiseta, monocots Dactylorhiza romana and Neotinea maculata and dicots Adenophora liliifolia, Ambrosia artemisiifolia and Tanacetum corymbosum subsp. cinereum are given within SE Europe and adjacent regions.

This paper presents new records and noteworthy data on the following taxa in SE Europe and adjacent regions: red algae Lemanea fucina and Paralemanea annulata, parasitic fungus Anthracoidea pratensis, saprotrophic fungi Cyathus olla, Massaria campestris, and Xylaria sicula, stonewort Chara canescens, liverworts Gymnomitrion commutatum and Porella baueri, moss Acaulon triquetrum, monocots Anacamptis laxiflora, Cephalanthera damasonium, and Himantoglossum robertianum and dicot Jacobaea othonnae are given within SE Europe and adjacent regions.

Changes in the market, caused by globalization, have led to the fact that many companies needed to adapt their operations. In response to these changes, the concept of supply chain was developed to help companies from procurement to sales of products. This paper examines the effects of supply chains on competitiveness using the example of agro-food companies from the Republic of Croatia. The research was conducted through a questionnaire which included 188 agribusiness companies. The responses were systematized and statistically processed using descriptive statistics, correlation analysis and multivariate regression analysis. The results showed that the effects of supply chains play a major role in determining the competitiveness of agro-food companies. Therefore, it is necessary to improve the effects of the supply chain in these companies in order to improve competitiveness and achieve better results of these companies on the market.

The aim of the research in the paper is to evaluate the state of rural settlements in Brčko District with regard to the development of rural tourism. Together with the Tourism Department of the Brčko District, five experts from the field of tourism were selected and they evaluated the current state of rural settlements in this part of Bosnia and Herzegovina. The evaluations were processed using the fuzzy approach with the SWARA (Stepwise Weight Assessment Ratio Analysis) multi-criteria decision-making method. Using this method, the weights of the used criteria were determined, representing the degree of development of conditions in rural settlements. The results showed that "rural facilities and services" are the best developed in rural settlements, while the criteria related to feelings and experiences are the least developed. Based on this research, it is possible to implement measures to strengthen certain criteria that have not been adequately developed in order to further improve rural tourism in Brčko District.

The purpose of this paper is to examine the current state of rural tourism in Republic of Srpska as well as to provide guidance and recommendations for the development of this form of tourism. The used model approach expert opinion and, on this occasion, the DEX method of multicriteria decision-making was used. With this model, an assessment of rural tourist capacities is carried out on a random sample of four tourist facilities. The reason for the results obtained in this way is that the observed facilities have adequately used the natural resources available to Republic of Srpska. In addition, recommendations and guidelines are given in order to further develop this type of tourism in Republic of Srpska. The presented model offers an innovative approach in the assessment of current and potential tourist facilities. For this reason, it should be used in future research.

We present an open-source web tool for quality control of distributed imaging studies. To minimize the amount of human time and attention spent reviewing the images, we created a neural network to provide an automatic assessment. This steers reviewers’ attention to potentially problematic cases, reducing the likelihood of missing image quality issues. We test our approach using 5-fold cross validation on a set of 5217 magnetic resonance images.