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This article focuses on developing an expert system applicable to the area of neurocognitive rehabilitation. The benefit of this interdisciplinary research is to propose an expert system that has been adapted based on real patients' results from the Addenbrooke's cognitive examination (ACE-R). One of this research's main results is a unique proposal to transfer the ACE-R result to the CHC (Cattell–Horn–Carroll) intelligence model. This unique approach enables transforming the CHC model domains according to the modified ACE-R factor analysis, which has never been used before. The expert system inference results allow the automated optimized design of a neurorehabilitation plan to train patients' cognitive functions according to the CHC model. A set of tasks in 6 difficulty levels (Level 1–Level 6) was proposed for each of the nine CHC model domains. For each patient, the ACE-R results helped determine specific CHC domains to be rehabilitated as well as the starting game level for the rehabilitation within each domain. The proposed expert system has been verified on real data of 705 patients and achieved an average error of 5.94% for all CHC model domains. The proposed system is to be included in the outcomes of the research project of the Technology Agency of the Czech Republic as a verified procedure for healthcare providers. [ABSTRACT FROM AUTHOR]

Aim: To describe the classification approach and protocols that were used in the project Vegetation of the Czech Republic and relate them to the comparative framework for broad-scale plot-based vegetation classification proposed by De Cáceres et al. (2015). This description should facilitate comparison of this national vegetation classification with vegetation classifications in other countries. Location: Czech Republic. Methods: The project Vegetation of the Czech Republic, realized from 1997 to 2013, was based on the analyses of vegetationplot records from the Czech National Phytosociological Database. Associations were defined as the basic hierarchical level using formal definitions created with the Cocktail method. These formal definitions were included in a computer expert system for automatic identification of associations. Evaluation and characterization of associations were based on the groups of plot records assigned to the particular associations by the expert system. Higher classification levels were classified by type-based grouping of associations. A novel statistical method for determining diagnostic species of vegetation types was developed within the project. All the analytical procedures used and developed for the project were included in the JUICE program. Results: The national vegetation classification system was published in a four-volume monograph from 2007 to 2013. It consists of five hierarchical levels with nested vegetation types, including 9 formations, 39 classes, 138 alliances, 496 associations and for some associations also variants. At the same time the project infrastructure, including the expert system and the JUICE program, was published online. Conclusions: The national vegetation classification of the Czech Republic provided novel classification approach and protocols. Several elements of these protocols have been subsequently applied in other countries. At the national level, the classification has found various applications both in nature conservation and in basic research. [ABSTRACT FROM AUTHOR]

Abstract: Flood prevention and nature conservation are often considered not to be compatible. This publication presents a method by which different land use scenarios can be developed and interdisciplinarily evaluated from both the flood prevention and nature conservation perspective. The method was designed and tested using a small subcatchment area in the Eastern Erzgebirge (Saxony, Germany) as an example. Based on guidelines four scenarios were developed. Main measures are transformation of arable fields into extensively used grasslands, afforestation and ecological transformation of forests. The ecological assessment was based on an analysis of biotope types and closely linked to an evaluation of landscape structure. To asses the hydrological situation and to identify risk areas in the catchment, the expert system WBS-FLAB was used. The assessment procedures were designed to enable a comparison of various scenarios with each other. Finally the evaluation results of both assessment procedures were related to each other. A comparison with the actual situation shows that all four developed land use scenarios can improve the situation from both the perspective of flood prevention as well as of nature conservation. In practice, the presented method can be a valuable interdisciplinary decision support for decision-makers and landscape planners. [Copyright &y& Elsevier]