Perspectivization and modes of quoting in Hungarian

This paper examines modes of quoting with special regard to the organization of perspective. Due to the pragmatic interest of the study, our focus is on the functioning of two context-dependent vantage points, the subject of consciousness and the referential centre. Our key question about the former is to whom speaking as a sign of active consciousness is attributed and how this is linguistically marked. As regards the latter, the central issue is from where and how the spatio-temporal and interpersonal relations of the quoted discourse are represented.Further problems to be discussed include the questions of how and to what extent quoting is associated with pragmatic or metapragmatic awareness, and how various quoting modes may differ along this dimension.Although the paper is mostly concerned with a ‘universal pragmatic’ characterization of the functioning of perspective in quotations, it also highlights some language-particular features of Hungarian quoting strategies and touches on their evolution in the history of the language

Novel hybrid composites based on PVA/SeTiO2 nanoparticles and natural hydroxyapatite for orthopedic applications: Correlations between structural, morphological and biocompatibility properties

The properties of poly(vinyl alcohol) (PVA)-based composites recommend this material as a good candidate for the replacement of damaged cartilage, subchondral bone, meniscus, humeral joint and other orthopedic applications. The manufacturing process can be manipulated to generate the desired biomechanical properties. However, the main shortcomings of PVA hydrogels are related to poor strength and bioactivity. To overcome this situation, reinforcing elements are added to the PVA matrix. The aim of our work was to develop and characterize a novel composition based on PVA reinforced with Se-doped TiO2 nanoparticles and natural hydroxyapatite (HA), for possible orthopedic applications. The PVA/Se-doped TiO2 composites with and without HA were structurally investigated by FTIR and XRD, in order to confirm the incorporation of the inorganic phase in the polymeric structure, and by SEM and XRF, to evidence the ultrastructural details and dispersion of nanoparticles in the PVA matrix. Both the mechanical and structural properties of the composites demonstrated a synergic reinforcing effect of HA and Se-doped TiO2 nanoparticles. Moreover, the tailorable properties of the composites were proved by the viability and differentiation potential of the bone marrow mesenchymal stem cells (BMMSC) to osteogenic, chondrogenic and adipogenic lineages. The novel hybrid PVA composites show suitable structural, mechanical and biological features to be considered as a promising biomaterial for articular cartilage and subchondral bone repair

Critical assessment of protein intrinsic disorder prediction

Intrinsically disordered proteins, defying the traditional protein structure\u2013function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude

Critical assessment of protein intrinsic disorder prediction

Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude