Актуальні проблеми застосування державних соціальних стандартів та гарантій в Україні

The 16.4Ma old Bogács Ignimbrite, located south of the Bükk Mountains, northern Hungary, was formed during a silicic ignimbrite flare-up in the Pannonian Basin that occurred from 20Ma to 13Ma. It comprises two main units, a lower, variably welded pumiceous and an upper, scoriaceous pyroclastic flow unit. Bulk chemistry of the juvenile clasts indicates a gradual change of geochemical character with an upward decreasing SiO 2 content through the stratigraphic section. A detailed in-situ major and trace element investigation of the main mineral phases and glasses combined with petrogenetic model calculations reveals complex magma reservoir processes. Based on the major and trace element variability, six juvenile clast types were distinguished and each contain fresh glass fractions with distinct compositions. The mineral assemblage consists of plagioclase, orthopyroxene, biotite with minor and variable amounts of quartz, amphibole, ilmenite, zircon and allanite. The anorthite content of the plagioclases varies from 20 to 90mol%, whilst the Enstatite content of orthopyroxenes covers also a wide range from 40 to 90mol%. This large compositional variation can be detected even in single crystals. This extreme geochemical variability can be explained by mixing of crystal mush bodies evolved from both basaltic and more silicic magmas. The calcic plagioclases (An=80-90mol%) and magnesian orthopyroxenes (En=70-90mol%) clearly indicate the role of primitive mafic magmas in the growth of the silicic magma reservoir, even though no basaltic volcanic activity was associated with the Miocene silicic volcanism in the Pannonian basin. The prolonged crystallization in the mushy sills resulted in compositionally different residual melt fractions that moved upwards and accumulated in separated melt pods at the roof of the magma reservoir. Intermittent intrusions of mafic and intermediate magmas into this silicic magma system could have resulted in thorough stirring of the crystal mush bodies and the melt pods, leading to eruptive products having compositionally heterogeneous glass and mineral assemblage

Assessment of anthropogenic, seasonal and aquatic vegetation effects on the contamination level of oxbows

The contamination level of oxbows depends on both natural and anthropogenic effects. The aim of our study was to identify those abiotic and biotic factors that determine the contamination level of oxbows. The effect of anthropogenic activities, seasonality, and vegetation types was studied on the contamination level of surface water of oxbows. The following chemical variables were measured: suspended solid, ammonium, nitrate, chlorophyll-a, Al, Ba, Fe, Mn, Pb, Sr and Zn from eight oxbows from 2013 summer to 2014 autumn in the Upper Tisza region in Eastern Hungary. Three of the studied oxbows were protected, four oxbows were used for fishing and one oxbow was contaminated with wastewater. Our findings revealed that anthropogenic activities had remarkable effect on the contamination level of oxbows. Seasonality also influenced the contamination level, except the concentration of suspended solid, chlorophyll-a and manganese. Significant differences were found among vegetation types for the concentration of suspended solids, aluminium, iron, manganese and lead. The high level of iron concentration was not explained by the anthropogenic activities, suggesting that the quality of oxbows depends on both natural and anthropogenic effects

Deep Learning-based Approach for the Semantic Segmentation of Bright Retinal Damage

Regular screening for the development of diabetic retinopathy is imperative for an early diagnosis and a timely treatment, thus preventing further progression of the disease. The conventional screening techniques based on manual observation by qualified physicians can be very time consuming and prone to error. In this paper, a novel automated screening model based on deep learning for the semantic segmentation of exudates in color fundus images is proposed with the implementation of an end-to-end convolutional neural network built upon UNet architecture. This encoder-decoder network is characterized by the combination of a contracting path and a symmetrical expansive path to obtain precise localization with the use of context information. The proposed method was validated on E-OPHTHA and DIARETDB1 public databases achieving promising results compared to current state-of-theart methods.This paper was supported by the European Union’s Horizon 2020 research and innovation programme under the Project GALAHAD [H2020-ICT2016-2017, 732613]. The work of Adri´an Colomer has been supported by the Spanish Government under a FPI Grant [BES-2014-067889]. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.Silva, C.; Colomer, A.; Naranjo Ornedo, V. (2018). Deep Learning-based Approach for the Semantic Segmentation of Bright Retinal Damage. En Intelligent Data Engineering and Automated Learning – IDEAL 2018. Springer. 164-173. https://doi.org/10.1007/978-3-030-03493-1_18S164173World Health Organization: Diabetes fact sheet. Sci. Total Environ. 20, 1–88 (2011)Verma, L., Prakash, G., Tewari, H.K.: Diabetic retinopathy: time for action. No complacency please! Bull. World Health Organ. 80(5), 419–419 (2002)Sopharak, A.: Machine learning approach to automatic exudate detection in retinal images from diabetic patients. J. Mod. Opt. 57(2), 124–135 (2010)Imani, E., Pourreza, H.R.: A novel method for retinal exudate segmentation using signal separation algorithm. Comput. Methods Programs Biomed. 133, 195–205 (2016)Haloi, M., Dandapat, S., Sinha, R.: A Gaussian scale space approach for exudates detection, classification and severity prediction. arXiv preprint arXiv:1505.00737 (2015)Welfer, D., Scharcanski, J., Marinho, D.R.: A coarse-to-fine strategy for automatically detecting exudates in color eye fundus images. Comput. Med. Imaging Graph. 34(3), 228–235 (2010)Harangi, B., Hajdu, A.: Automatic exudate detection by fusing multiple active contours and regionwise classification. Comput. Biol. Med. 54, 156–171 (2014)Sopharak, A., Uyyanonvara, B., Barman, S.: Automatic exudate detection from non-dilated diabetic retinopathy retinal images using fuzzy C-means clustering. Sensors 9(3), 2148–2161 (2009)Havaei, M., Davy, A., Warde-Farley, D.: Brain tumor segmentation with deep neural networks. Med. Image Anal. 35, 18–31 (2017)Liskowski, P., Krawiec, K.: Segmenting retinal blood vessels with deep neural networks. IEEE Trans. Med. Imag. 35(11), 2369–2380 (2016)Pratt, H., Coenen, F., Broadbent, D.M., Harding, S.P.: Convolutional neural networks for diabetic retinopathy. Procedia Comput. Sci. 90, 200–205 (2016)Gulshan, V., Peng, L., Coram, M.: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 316(22), 2402–2410 (2016)Prentašić, P., Lončarić, S.: Detection of exudates in fundus photographs using deep neural networks and anatomical landmark detection fusion. Comput. Methods Programs Biomed. 137, 281–292 (2016)Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234–241. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24574-4_28Garcia-Garcia, A., Orts-Escolano, S., Oprea, S., Villena-Martinez, V., Garcia-Rodriguez, J.: A review on deep learning techniques applied to semantic segmentation, pp. 1–23. arXiv preprint arXiv:1704.06857 (2017)Deng, Z., Fan, H., Xie, F., Cui, Y., Liu, J.: Segmentation of dermoscopy images based on fully convolutional neural network. In: IEEE International Conference on Image Processing (ICIP 2017), pp. 1732–1736. IEEE (2017)Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431–3440. IEEE (2014)Li, W., Qian, X., Ji, J.: Noise-tolerant deep learning for histopathological image segmentation, vol. 510 (2017)Chen, H., Qi, X., Yu, L.: DCAN: deep contour-aware networks for object instance segmentation from histology images. Med. Image Anal. 36, 135–146 (2017)Walter, T., Klein, J.C., Massin, P., Erginay, A.: A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina. IEEE Trans. Med. Imaging 21(10), 1236–1243 (2002)Morales, S., Naranjo, V., Angulo, U., Alcaniz, M.: Automatic detection of optic disc based on PCA and mathematical morphology. IEEE Trans. Med. Imaging 32(4), 786–796 (2013)Zhang, X., Thibault, G., Decencière, E.: Exudate detection in color retinal images for mass screening of diabetic retinopathy. Med. Image Anal. 18(7), 1026–1043 (2014

A unique Valanginian paleoenvironment at an iron ore deposit near Zengővárkony (Mecsek Mts, South Hungary), and a possible genetic model

Abstract The spatially restricted Early Valanginian iron ore (limonite) and manganese deposit at Zengõvárkony (Mecsek Mts, southern Hungary) contains a rich, strongly limonitized, remarkably large-sized (specimens are 30–70% larger than those at their type localities) brachiopod-dominated (mainly Lacunosella and Nucleata) megafauna and a diverse crustacean microfauna, which indicates a shallow, nutrient-rich environment possibly linked to an uplifted block, and/or a hydrothermal vent

Origin and ascent history of unusually crystal-rich alkaline basaltic magmas from the western Pannonian Basin

The last eruptions of the monogenetic Bakony-Balaton Highland Volcanic Field (western Pannonian Basin, Hungary) produced unusually crystal- and xenolith-rich alkaline basalts which are unique among the alkaline basalts of the Carpathian- Pannonian Region. Similar alkaline basalts are only rarely known in other volcanic fields of the world. These special basaltic magmas fed the eruptions of two closely located volcanic centres: the Bondoró-hegy and the Füzes-tó scoria cone. Their uncommon enrichment in diverse crystals produced unique rock textures and modified original magma compositions (13.1-14.2 wt.% MgO, 459-657 ppm Cr, 455-564 ppm Ni contents). Detailed mineral-scale textural and chemical analyses revealed that the Bondoró-hegy and Füzes-tó alkaline basaltic magmas have a complex ascent history, and that most of their minerals (~30 vol.% of the rocks) represent foreign crystals derived from different levels of the underlying lithosphere. The most abundant xenocrysts, olivine, orthopyroxene, clinopyroxene and spinel, were incorporated from different regions and rock types of the subcontinental lithospheric mantle. Megacrysts of clinopyroxene and spinel could have originated from pegmatitic veins / sills which probably represent magmas crystallized near the crust-mantle boundary. Green clinopyroxene xenocrysts could have been derived from lower crustal mafic granulites. Minerals that crystallized in situ from the alkaline basaltic melts (olivine with Cr-spinel inclusions, clinopyroxene, plagioclase, Fe-Ti oxides) are only represented by microphenocrysts and overgrowths on the foreign crystals. The vast amount of peridotitic (most common) and mafic granulitic materials indicates a highly effective interaction between the ascending magmas and wall rocks at lithospheric mantle and lower crustal levels. However, fragments from the middle and upper crust are absent from the studied basalts, suggesting a change in the style (and possibly rate) of magma ascent in the crust. These xenocryst- and xenolith-rich basalts yield divers tools for estimating magma ascent rate that is important for hazard forecasting in monogenetic volcanic fields. According to the estimated ascent rates, the Bondoró-hegy and Füzes-tó alkaline basaltic magmas could have reached the surface within hours to few days, similarly to the estimates for other eruptive centres in the Pannonian Basin which were fed by "normal" (crystal- and xenolith-poor) alkaline basalts

Investigating International Time Trends in the Incidence and Prevalence of Atopic Eczema 1990-2010: A Systematic Review of Epidemiological Studies

The prevalence of atopic eczema has been found to have increased greatly in some parts of the world. Building on a systematic review of global disease trends in asthma, our objective was to study trends in incidence and prevalence of atopic eczema. Disease trends are important for health service planning and for generating hypotheses regarding the aetiology of chronic disorders. We conducted a systematic search for high quality reports of cohort, repeated cross-sectional and routine healthcare database-based studies in seven electronic databases. Studies were required to report on at least two measures of the incidence and/or prevalence of atopic eczema between 1990 and 2010 and needed to use comparable methods at all assessment points. We retrieved 2,464 citations, from which we included 69 reports. Assessing global trends was complicated by the use of a range of outcome measures across studies and possible changes in diagnostic criteria over time. Notwithstanding these difficulties, there was evidence suggesting that the prevalence of atopic eczema was increasing in Africa, eastern Asia, western Europe and parts of northern Europe (i.e. the UK). No clear trends were identified in other regions. There was inadequate study coverage worldwide, particularly for repeated measures of atopic eczema incidence. Further epidemiological work is needed to investigate trends in what is now one of the most common long-term disorders globally. A range of relevant measures of incidence and prevalence, careful use of definitions and description of diagnostic criteria, improved study design, more comprehensive reporting and appropriate interpretation of these data are all essential to ensure that this important field of epidemiological enquiry progresses in a scientifically robust manner

Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8–13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05–6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50–75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life. Funding Pfizer, Amgen, Merck Sharp & Dohme, Sanofi–Aventis, Daiichi Sankyo, and Regeneron

Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life