Late Vistulian and Holocene development of litho-morpho-pedogenic processes in the southern Baltic coastal zone: A case study from Dębina, northern Poland

Geoderma ◽  
2019 ◽  
Vol 348 ◽  
pp. 21-36 ◽  
Author(s):  
Jerzy Jonczak ◽  
Wacław Florek ◽  
Bogusława Kruczkowska ◽  
Joanna Gadziszewska ◽  
Monika Niska ◽  
...  
2020 ◽  
Vol 49 (3) ◽  
pp. 304-318
Author(s):  
Małgorzata Witak ◽  
Jarosław Pędziński ◽  
Sandra Oliwa ◽  
Dominika Hetko

AbstractThe paper presents the results of the analysis of diatoms from surface sediments (stones, sands) and macroflora (seagrass, macroalgae) collected at 16 sampling sites located along the inner coastal zone of Puck Bay (southern Baltic Sea) along the Hel Peninsula. The main diatom species of epilithon, epipsammon and epiphyton were characterized with respect to their autecological preferences (habitat, salinity, trophic status, saprobity). Three groups of diatoms were distinguished with respect to the type of substrate based on the results of benthic flora analysis: diatoms (i) of one type of substrate, (ii) of two types and (iii) those occurring on all types of substrates. Moreover, the distribution of benthic diatom communities indicates ecological differences in the study area. Marine and brackish-water species were observed in large numbers in the coastal zone of the Outer Puck Bay, whereas freshwater flora occurred with a higher frequency in the coastal zone of the Puck Lagoon. The content of polysaprobionts and of α-mesosaprobionts indicates that the region of the Hel Tip is highly eutrophicated and very polluted. The coast in the vicinity of Kuznica is less polluted, whereas the best environmental conditions are found in the Jurata–Jastarnia region, as evidenced by the frequency of diatoms that are β-mesosaprobionts.


2021 ◽  
Vol 11 (13) ◽  
pp. 5826
Author(s):  
Evangelos Axiotis ◽  
Andreas Kontogiannis ◽  
Eleftherios Kalpoutzakis ◽  
George Giannakopoulos

Ethnopharmacology experts face several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, and the different quality of language use across sources present some of what we call “big data” challenges in the analysis of this data. This study aims to understand if and how experts can be supported effectively through intelligent tools in the task of ethnopharmacological literature research. To this end, we utilize a real case study of ethnopharmacology research aimed at the southern Balkans and the coastal zone of Asia Minor. Thus, we propose a methodology for more efficient research in ethnopharmacology. Our work follows an “expert–apprentice” paradigm in an automatic URL extraction process, through crawling, where the apprentice is a machine learning (ML) algorithm, utilizing a combination of active learning (AL) and reinforcement learning (RL), and the expert is the human researcher. ML-powered research improved the effectiveness and efficiency of the domain expert by 3.1 and 5.14 times, respectively, fetching a total number of 420 relevant ethnopharmacological documents in only 7 h versus an estimated 36 h of human-expert effort. Therefore, utilizing artificial intelligence (AI) tools to support the researcher can boost the efficiency and effectiveness of the identification and retrieval of appropriate documents.


2013 ◽  
Vol 65 ◽  
pp. 672-677 ◽  
Author(s):  
Natalia Bugajny ◽  
Kazimierz Furmańczyk ◽  
Joanna Dudzińska-Nowak ◽  
Barbara Paplińska-Swerpel

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