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FIG. 3. — A in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 3. — A detail of the chromatographic plate TLC nr 1903 developed in solvent system C presenting C. chicitae (W.L. Culb.) W.L. Culb. & C.F. Culb. specimens under UV 254 nm (A), UV 366 nm (B) and sprayed with anisaldehyde/sulphuric acid (C). Specimens in positions 3-9 are: 3, from Page County, Virginia, United States (BP 75822); 4, from the Bükk Mts, Hungary (BP 71276); 5, from the Zemplén Mts, Hungary (BP 49905); 6, from Pocahontas County, West Virginia, United States (BP 91365); 7, from Ukraine (BP 44999); 8, from Romania (BP 85320); 9, from Poland (BP 21508). Abbreviations of LSMs are according to Table 2.
Daily soil water content under different tillage techniques in Józsefmajor Experimental and Training Farm, Hungary
<p>Continous soil water content monitoring of a Central European chernozem type soil under mouldboard ploughing (MP) and no-tillage (NT) treatments</p> <p>Measurement frequency was 10 minutes, aggragated daily mean data are presented.</p> <p>Sampling depths: 5-10, 15-20, 30-35, 40-45 cm</p> <p><strong>Site description:</strong> Józsefmajor Experimental and Training Farm's long-term tillage experiment (Hungary, 47.688, 19.605).</p> <p>crop rotation, adaptable fertilization, Haplic Kastanozem (Aric, Pantoloamic, Pachic, Bathycalcic) soil type,</p> <p> </p>
FIG. 15 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 15. — Cladonia novochlorophaea (Sipman) Brodo & Ahti: A, habit (BP[BP 9314]); B, spots of lichen secondary metabolites on chromatographic plates; C, distribution in Hungary. Abbreviations: H, homosekiaic acid; F, fumarprotocetraric acid; Z, zeorin; N, norstictic acid. Scale bar: A, 2 mm.
FIG. 8 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 8. — The mean diameter of soredia (µm) measured on podetia (n = 10). Abbreviations: asa, C. asahinae (n = 22); chlo, C. chlorophaea (n = 55); cry, C. cryptochlorophaea (n = 53); gra, C. grayi (n = 17); mero, C. merochlorophaea (n = 70); novo, C. novochlorophaea (n = 10). The lines represent the minimum and maximum values, the box represents the 25% and 75% of the data, the thick line represents the median. Means with the same letter are not significantly different at 95% confidence.
FIG. 5 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 5. — Height of cup (mm) in different species. Abbreviations: asa, C. asahinae (n = 22); chlo, C. chlorophaea (n = 55); cry, C. cryptochlorophaea (n = 53); gra, C. grayi (n = 17); mero, C. merochlorophaea (n = 70); novo, C. novochlorophaea (n = 10). The lines represent the minimum and maximum values, the box represents the 25% and 75% of the data, the thick line represents the median. Means with the same letter are not significantly different at 95% confidence.
FIG. 9 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 9. — Conditional inference tree presenting the five most important morphological variables separating species: CH, height of cup; CW, width of cup; PH, height of podetium; SW, width of podetium stalk. The order of the species at the end of the nodes is as follows: a, C. asahinae; c, C. chlorophaea; cr, C. cryptochlorophaea; g, C. grayi; m, C. merochlorophaea; n, C. novochlorophaea. Boxes represent the highest probability of a species occurrence on the tree node. A level of p <0.05 was considered for a significant difference.
FIG. 12 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 12. — Cladonia cryptochlorophaea Asahina: A, habit (BP[BP 48938]); B, spots of lichen secondary metabolites on chromatographic plates; C, distribution in Hungary. Abbreviations: c, cryptochlorophaeic acid; nR, norrangiformic acid; F, fumarprotocetraric acid; Z, zeorin; N, norstictic acid. Scale bar: A, 2 mm.
FIG. 7 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 7. — Width of podetium stalk (mm) in different species. Abbreviations: asa, C. asahinae (n = 22); chlo, C. chlorophaea (n = 55); cry, C. cryptochlorophaea (n = 53); gra, C. grayi (n = 17); mero, C. merochlorophaea (n = 70); novo, C. novochlorophaea (n = 10). The lines represent the minimum and maximum values, the box represents the 25% and 75% of the data, the thick line represents the median. Means with the same letter are not significantly different at 95% confidence.
FIG. 11 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 11. — Cladonia chlorophaea (FlÖrke ex Sommerf.) Spreng.: A, habit (BP[BP 49014]); B, spots of lichen secondary metabolites on chromatographic plates; C, distribution in Hungary. Abbreviations: F, fumarprotocetraric acid; Z, zeorin; N, norstictic acid. Scale bar: A, 2 mm.
FIG. 6 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 6. — Width of cup (mm) in different species. Abbreviations: asa, C. asahinae (n = 22); chlo, C. chlorophaea (n = 55); cry, C. cryptochlorophaea (n = 53); gra, C. grayi (n = 17); mero, C. merochlorophaea (n = 70); novo, C. novochlorophaea (n = 10). The lines represent the minimum and maximum values, the box represents the 25% and 75% of the data, the thick line represents the median. Means with the same letter are not significantly different at 95% confidence.
FIG. 10. — Cladonia asahinae J.W in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 10. — Cladonia asahinae J.W.Thomson: A, habit (BP[BP 9421]); B, spots of lichen secondary metabolites on chromatographic plates; C, distribution in Hungary. Abbrevations: R, rangiformic acid; nR, norrangiformic acid; F, fumarprotocetraric acid; Z, zeorin; N, norstictic acid. Scale bar: A, 2 mm.
FIG. 3 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 3. — Conditional inference tree presenting the presence of the three most abundant lichen secondary metabolites occurring in more than one species of the C. chlorophaea species group. A level of p <0.05 was considered for a significant difference. Abbreviations: cch, cryptochlorophaeic acid; ran, rangiformic acid; tha, thamnolic acid; a, C. asahinae; ch, C. chlorophaea; cr, C. cryptochlorophaea; g, C. grayi; me, C. merochlorophaea; no, C. novochlorophaea. Boxes represent the highest probability of a species occurrence on the tree node.
FIG. 4 in Analysis of lichen secondary metabolites and morphometrics in the Cladonia chlorophaea species group (Cladoniaceae, lichenized Ascomycota) in Hungary
FIG. 4. — Height of podetia (mm) of the different species. Abbreviations: asa, C. asahinae (n = 22); chlo, C. chlorophaea (n = 55); cry, C. cryptochlorophaea (n = 53); gra, C. grayi (n = 17); mero, C. merochlorophaea (n = 70); novo, C. novochlorophaea (n = 10). The lines represent the minimum and maximum values, the box represents the 25% and 75% of the data, the thick line represents the median. Means with the same letter are not significantly different at 95% confidence.
Figure 3 in Three new species and a new record of tenuipalpid mites (Acari: Tenuipalpidae) from Hungary
Figure 3. (Continued).
Figure 1 in Three new species and a new record of tenuipalpid mites (Acari: Tenuipalpidae) from Hungary
Figure 1. (Continued).
Survey of Local Organisations and Economic Development in the Czech Republic, Hungary and Poland (2007).
This survey, undertaken in 2007, covers 1,200 local organisations in the Czech Republic, Hungary and Poland. Data cover two regions per country - one above and one below the average level of countrywide economic development (GDP, unemployment rate, rate of agriculture in GDP). 400 organisations per country (200 per region) are surveyed. Organisations include firms, NGOs, municipalities and universities.
Laboratory data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - Hungary
<p>This dataset contains ASF laboratory analytical results in wild boar.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_HU - National Food Chain Safety Office (NFCSO)</li> <li>ASF2023_HU - National Food Chain Safety Office (NFCSO)</li> <li>ASF2022_HU - National Food Chain Safety Office (NFCSO)*</li> <li>ASF2022_HU - National Food Chain Safety Office (NFCSO)</li> </ul> <p> </p> <p> </p> <p>*This version of the ASF laboratory data has been republished with the subunit identification code (sampUnitIds.subUnitId) column empty due to data protection reasons</p>
Hungary
[Hungary](https://en.wikipedia.org/wiki/Hungary) is a landlocked country in Central Europe. Spanning 93,030 square kilometres (35,920 sq mi) of the Carpathian Basin, it is bordered by Slovakia to the north, Ukraine to the northeast, Romania to the east and southeast, Serbia to the south, Croatia and Slovenia to the southwest and Austria to the west. Hungary has a population of nearly 10 million, mostly ethnic Hungarians and a significant Romani minority. Hungarian, the official language, is the world's most widely spoken Uralic language and among the few non-Indo-European languages widely spoken in Europe. Budapest is the country's capital and largest city; other major urban areas include Debrecen, Szeged, Miskolc, Pécs and Győr. Source: Objaverse 1.0 / Sketchfab
Managing competition between legacy television services and video streaming platforms in Hungary in the early 2020s – A case study [Secondary documentary sources]
<p>Secondary documentary sources used in the paper entitled "Managing competition between legacy television services and video streaming platforms in Hungary in the early 2020s – A case study"</p>
Bias-corrected EURO-CORDEX daily temperature and precipitation dataset for Hungary
<p>These datasets contain bias-corrected regional climate model outputs for daily precipitation, near surface mean-, minimum- and maximum temperature for the historical period 1993-2005 on a regular 0.11°x0.11° lon/lat grid (between latitudes 45.6825°N and 48.6525°N, and longitudes 15.9075°E and 22.9475°E).</p> <p> </p> <p>The datasets contain daily outputs of the following high-resolution (0.11°) regional climate models from the framework of EURO-CORDEX (Jacob et al., 2014):</p> <p>-CCLM</p> <p>-HIRHAM</p> <p>-RACMO</p> <p>-RCA</p> <p>-REMO</p> <p> </p> <p>The reference dataset is HUCLIM, which covers Hungary for the period 1971-2022 (downloaded in 2023) produced by the HungaroMet Hungarian Meteorological Service.</p> <p>File format: NetCDF</p> <p>All bias-corrected data produced by the use of HUCLIM have been created following the work of Mezghani et al. (2017).</p> <p> </p> <p>References:</p> <p>Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O.B., Bouwer, L.M., Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevel, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B. and Yiou, P. (2014) EURO-CORDEX New high resolution climate change projections for European impact research. Reg. Environ. Change, 14, 563–578. <a href="https://doi.org/10.1007/s10113-013-0499-2" target="_blank" rel="noopener">https://doi.org/10.1007/s10113-013-0499-2</a></p> <p>Mezghani, A., Dobler, A., Haugen, J.E., Benestad, R.E., Parding, K.M., Piniewski, M., Kardel, I. and Kundzewicz, Z.W. (2017) CHASE-PL Climate Projection dataset over Poland – bias adjustment of EURO-CORDEX simulations. Earth Syst. Sci. Data, 9, 905–925. <a href="https://doi.org/10.5194/essd-9-905-2017" target="_blank" rel="noopener">https://doi.org/10.5194/essd-9-905-2017</a></p> <p> </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.