Academic literature on the topic 'Peltarion'

A new species of Trichopeltarion A. Milne-Edwards, 1880, is described from off coast of Brazil, namely Trichopeltarion pezzutoi n. sp. The new species is compared to its Atlantic congeners, Trichopeltarion nobile A. Milne-Edwards, 1880, and Trichopeltarion intesi (Crosnier, 1981). The record of T. nobile from Brazil should actually be attributed to T. pezzutoi n. sp. The differences between the genera Trichopeltarion and Peltarion Jacquinot, 1847 are discussed.

In this paper are summarized the phytosociological characteristics of the white poplar dominated riparian forests (Senecioni sarracenici-Populetum albae) along the rába river in western Hungary. This community grows typically on alluvial soils developed over fluvial sand in the more elevated parts of the lower floodplain. Its species composition is clearly differ-ent from that of the oak-ash-elm forests growing in the higher floodplain, particularly in the higher proportion of Salicetea species, and the lower proportion of Fagetalia species. stands of this community host some local and regional rarities, such as Leucojum vernum, Galanthus nivalis, Omphalodes scorpi-oides, Peltaria alliacea, Scilla drunensis,Stellaria alsine. The community is classified in the „Populenion nigro-albae Kevey2008” suballiance.

Ruthenium tetroxide(RuO4) was first used as a stain in histology by Ranvier in 1887. Its use in TEM as a fixative or stain was reported by Gaylarde et al. However,the preservation of the cellular ultrastructure was very poor after RuO4 fixation alone, because RuO4 is a far more vigorous oxidant than osmium tetroxide. Peltari et al reported that a preceeding glutaraldehyde fixation helped to stabilize the ultrastructure, although the penetration of RuO4 into the tissue was poor.In the present study, RuO4 has been found to be a useful fixative and staining reagent with the prerequisite of using RuO4 as a postfixative after prefixation with tannic acid (TA)-glutaraldehyde(GL) for thin-section TEM(TA-RuO4 method) or after preceeding osmication followed by TA mordanting for non-coating SEM(OsO4-TA-RuO4 method).TA-RuO4 method for thin-section TEM

Models based around the transformer architecture have become one of the most prominent for solving a multitude of natural language processing (NLP)tasks since its introduction in 2017. However, much research related to the transformer model has focused primarily on achieving high performance and many problems remain unsolved. Two of the most prominent currently are the lack of high performing non-English pre-trained models, and the limited number of words most trained models can incorporate for their context. Solving these problems would make NLP models more suitable for real-world applications, improving information retrieval, reading comprehension, and more. All previous research has focused on incorporating long-context for English language models. This thesis investigates the cross-lingual transferability between languages when only training for long-context in English. Training long-context models in English only could make long-context in low-resource languages, such as Swedish, more accessible since it is hard to find such data in most languages and costly to train for each language. This could become an efficient method for creating long-context models in other languages without the need for such data in all languages or pre-training from scratch. We extend the models’ context using the training scheme of the Longformer architecture and fine-tune on a question-answering task in several languages. Our evaluation could not satisfactorily confirm nor deny if transferring long-term context is possible for low-resource languages. We believe that using datasets that require long-context reasoning, such as a multilingual TriviaQAdataset, could demonstrate our hypothesis’s validity.