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1,416 results for “Evidence Base”
FIGURE 2 in Huchimingia, a new genus segregated from Millettia (Leguminosae, Millettieae) based on morphological and molecular evidence
FIGURE 2. Morphology of Huchimingia ichthyochtona (Drake) Z.Q. Song. A habit B leafy branch C ungerminated bud D germinating bud, showing ciliate scales E part of leaflets, showing the asymmetric base and no stipel F pseudoraceme, showing the indistinct brachyblasts with two flowers, scale bar = 4 cm G flowering branches H bract subtending the indistinct brachyblast I floral bracts J undissected and dissected flowers, scale bar = 1 cm K pod and seeds, scale bar = 4 cm. Photograph by Zhu-Qiu Song.
FIGURE 1 in Huchimingia, a new genus segregated from Millettia (Leguminosae, Millettieae) based on morphological and molecular evidence
FIGURE 1. Maximum likelihood phylogeny of the tribe Millettieae and close relatives based on the concatenated plastid matK and nuclear ITS sequences. The blue fonts indicate samples of Millettia species. The grey cover shows the representative of the new genus Huchimingia and its sister taxa Antheroporum and Ohashia (green fonts). SH-aLRT (SH) and ultrafast bootstrap (BS) support values from maximum likelihood analyses, and posterior probabilities (PP) from Bayesian inference are displayed near the branches (SH/BS/PP).
FIGURE 4 in Huchimingia, a new genus segregated from Millettia (Leguminosae, Millettieae) based on morphological and molecular evidence
FIGURE 4. Seedling of Huchimingia ichthyochtona (Drake) Z.Q. Song. A 10-day old seedling, showing epigeal and phanerocotylar cotylendons B 14-day old seedling, showing the first two eophylls with 7–9 leaflets C–E 10-day old seedling, showing the stipules and leaflets with dense appressed hairs F–H 28-day old seedling, showing position of dropped cotylendons (red arrow), dropped stiuples (G), and no stipels (H). Scale bars = 8 cm. Photograph by Zhu-Qiu Song.
FIGURE 3 in Huchimingia, a new genus segregated from Millettia (Leguminosae, Millettieae) based on morphological and molecular evidence
FIGURE 3. Morphology of Huchimingia podocarpa (Dunn) Z.Q. Song (A–C) and H. weizhii (Z.Q. Song) Z.Q. Song (D–F). A fruiting branches B ungerminated bud C unopened and opened pods, showing the position of seeds (red arrows) D leafy branch E germinating bud, showing ciliate scales F stipitate pods. Scale bars = 4 cm. Photograph by Zhu-Qiu Song.
FIGURE 5 in Huchimingia, a new genus segregated from Millettia (Leguminosae, Millettieae) based on morphological and molecular evidence
FIGURE 5. Morphology of sister taxa of Huchimingia Z.Q. Song & Shi J. Li. A–C Antheroporum glaucum Z.Wei A flowering branch B part of inflorescence, showing the indistinct brachyblast with two flowers and ebracteolate calyx C undissected and dissected flowers D–E Antheroporum pierrei Gagnep. D tree bearing inflated pods E inflated, vacuous, stipitate pods F–I Ohashia yunnanensis (Chun & F.C. How) X.Y. Zhu & R.P. Zhang F part of inflorescence, showing the distinct and thick brachyblast with 7–10 flowers and calyx with bracteoles G undissected and dissected flowers H fruiting branch I flat and estipitate pod. Scale bar = 1 cm. Photograph by Zhu-Qiu Song (A–C, E), Shi-Jin Li (D), Ming-Song Wu (F, G, I), and Kai-Wen Luo (H).
FIGURE 1 in Athyrium aberrans (Athyriaceae), a new species of the lady ferns from southeastern Xizang, China, based on morphological and molecular evidence
FIGURE 1. Maximum likelihood phylogeny of Athyrium based on five plastid markers (rbcL, rps4, rps4-trnS, trnL, and trnL-F). Maximum likelihood bootstrap support (MLBS) and Bayesian inference posterior probability (BIPP) are given above and below the branches, respectively. The asterisk indicates MLBS = 100, BIPP = 1.00. The new species (in red) belongs to the A. otophorum clade (Wei et al. 2018b).
Rapid increase in China's industrial ammonia emissions: evidence from unit-based mapping
<p>Ammonia (NH<sub>3</sub>) is an important precursor of secondary inorganic aerosols and greatly impacts nitrogen deposition and acid rain. Previous studies have mainly focused on the agricultural NH<sub>3</sub> emissions, while recent research has noted that industrial sources could be significant in China. However, detailed estimates of NH<sub>3</sub> emitted from industrial sectors in China are lacking. Here we established an unprecedented high-spatial-resolution dataset of China's industrial NH<sub>3</sub> emissions using up-to-date measurements of NH<sub>3</sub> and point source-level information covering eight major industries and 27 subdivided process categories. We found that China emitted 798 (90% confidence interval: 668–933) gigagrams of industrial NH<sub>3</sub> to the atmosphere in 2019, equivalent to 44±20% of the industrial emissions worldwide; this flux is three-fold larger than that in 1998 and has fluctuated since 2014. Furthermore, although fertilizer production is responsible for approximately half of the emissions in China, the emissions from cement production and coal-fired power plants increased dramatically from near zero to 164 and 41 gigagrams, respectively, in the past two decades, primarily due to the NH<sub>3</sub> escape caused by the large-scale application of the denitration process. Our results reveal that, unlike other major air pollutants, China's industrial NH<sub>3</sub> emission control is still in a critical period, and stricter NH<sub>3</sub> emission standards and innovation in pollution control technologies are highly desirable.</p>
FIGURE 3 in Combination of Chloranthus flavus into C. nervosus based on morphological and molecular evidence
FIGURE 3. Inflorescence and floral diversity of Chloranthus nervosus from different places. A Xilin, Guangxi, China; B, E Debao, Guangxi, China; C Xishuangbanna, Yunnan, China; D Lingyun, Guangxi, China. Photographs taken by Yong-Bin Lu (A–D) and Ying Qin (E).
FIGURE 1 in Combination of Chloranthus flavus into C. nervosus based on morphological and molecular evidence
FIGURE 1. The best maximum likelihood phylogenetic trees based on the ITS (A) and concatenated plastid data (B). ML bootstrap support values and Bayesian posterior probability are indicated along nodes. The newly sequenced samples are mapped with the collection locations and the type locality of C. flavus is highlighted in bold. The serial numbers beginning with a capital "C" are given after the species names to distinguish each of individuals, and I-XIII represent different populations.
FIGURE 2 in Combination of Chloranthus flavus into C. nervosus based on morphological and molecular evidence
FIGURE 2. Chloranthus flavus (A–F), Chloranthus nervosus (G–L). A, G Plants in cultivation; B,H Infructescences; C, I Stems; D, J Scale-like leaves; E, K Stamen connectives; F, L Fruits. Photographs taken by Yong-Bin Lu.
FIGURE 33 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 33. Ponticola syrman. ZM-CBSU S065.2-1, 183.2 mm SL, off Neka, Mazandaran Province, Iran (Zarei et al. 2022a).
FIGURE 28 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 28. Ponticola goebelii. ZM-CBSU S014-1, female, 55.4 mm SL, off Anzali, Gilan Province, Iran.
FIGURE 27 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 27. Distributions of (A) Ponticola hircaniaensis, Ponticola iranicus, Ponticola patimari, and Ponticola cyrius, (B) Ponticola gorlap, (C) Ponticola goebelii, (D) Ponticola syrman, and (E) Proterorhinus nasalis in the Caspian Sea basin.
FIGURE 6 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 6. Species richness of gobiid genera in the South Caspian waters (i.e., marine and freshwaters) of three countries.
FIGURE 15 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 15. Hyrcanogobius bergi. From top: ZM-CBSU S017-1, 29.5 mm SL; ZM-CBSU S017-12, 23.6 mm SL, off Astara, southern Caspian Sea, Gilan Province, Iran.
FIGURE 11 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 11. Distribution of (A) Benthophilus granulosus, Benthophilus leptorhynchus, Benthophilus grimmi and Benthophilus svetovidovi, (B) Benthophilus leobergius, Benthophilus microcephalus and Benthophilus kessleri and (C) Benthophilus mahmudbejovi, Benthophilus ragimovi and Benthophilus spinosus.
FIGURE 18 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 18. Knipowitschia iljini. From top: ZM-CBSU S104-2, 19.6 mm SL; ZM-CBSU S104-4, 20.1 mm SL, off Anzali, Gilan Province, Iran.
FIGURE 5 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 5. IUCN red list status of gobiids known from the South Caspian Sea sub-basin (global assessments). Rhinogobius sp. was excluded.
FIGURE 17 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 17. Knipowitschia caucasica. ZM-CBSU S039-5, 26.8 mm SL, Anzali Wetland, Gilan Province, Iran.
FIGURE 22 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 22. Distribution of (A) Neogobius bathybius, (B) Neogobius caspius, (C) Neogobius melanostomus, and (D) Neogobius pallasi.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.