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27 results for “hot-spots”
Figs 6–9. 6 in Deepor Beel - A Ramsar Site Of India: An Interesting Hot-Spot With Its Rich Rotifera Biodiversity
Figs 6–9. 6 = Brachionus dichotomus reductus KOSTE et SHIEL, dorsal view, 7 = Notommata spinata KOSTE et SHIEL, dorsal view, 8 = Keratella edmondsoni AHLSTROM, dorsal view, 9 = Lecane blachei BERZINS, dorsal view
Fig. 1. A in Deepor Beel - A Ramsar Site Of India: An Interesting Hot-Spot With Its Rich Rotifera Biodiversity
Fig. 1. A = map of indicating location Deepor Beel, B = map showing sampling sites (2002–2003 and 2008–2010)
Figs 2–5. 2 in Deepor Beel - A Ramsar Site Of India: An Interesting Hot-Spot With Its Rich Rotifera Biodiversity
Figs 2–5. 2 = Keratella tecta (GOSSE), dorsal view, 3 = Trichocerca bidens (LUCKS), lateral view, 4 = Trichocerca tigris (MÜLLER), lateral view, 5 = Lecane paxiana HAUER, dorsal view
A Google Earth Engine code to analyze e visualize land surface temperature and thermal hot-spot patterns: a Rome (Italy) case study
<p>Link to the <strong>Google Earth Engine </strong>(GEE) code: <strong>https://code.earthengine.google.com/cc3ea6593574e321acd7b68c975a9608</strong></p> <p>You can analyze and visualize the following spatial layers by accessing the GEE link: </p> <ol> <li><strong>Daytime summer land surface temperature</strong> (raster data, 30 m horizontal resolution, from Landsat-8 remote sensing data, years 2017-2022)</li> <li><strong>The surface thermal hot-spot pattern </strong>(raster data,30 m horizontal resolution) was obtained by using a statistical-spatial method based on the Getis-Ord Gi* approach through the ArcGIS tool. </li> </ol> <p>Here attached the .txt file from the <strong>GEE code</strong>. </p> <p> </p> <p><em>E-mail</em></p> <p>Giulia Guerri, CNR-IBE, giulia.guerri@ibe.cnr.it</p> <p>Marco Morabito, CNR-IBE, marco.morabito@cnr.it</p> <p>Alfonso Crisci, CNR-IBE, alfonso.crisci@ibe.cnr.it</p>
Fig. 3 in Urogenital schistosomiasis transmission on Unguja Island, Zanzibar: characterisation of persistent hot-spots
Fig. 3 Number of human-water contact sites in persistent hot-spot and low-prevalence shehias in Unguja
Fig. 2 in Urogenital schistosomiasis transmission on Unguja Island, Zanzibar: characterisation of persistent hot-spots
Fig. 2 Map of Unguja Island, Zanzibar, showing the location of selected persistent hot-spot and low-prevalence shehias
Fig. 1 in Urogenital schistosomiasis transmission on Unguja Island, Zanzibar: characterisation of persistent hot-spots
Fig. 1 Flowchart showing the inclusion procedure for persistent hot-spot and low-prevalence shehias in Unguja
Fig. 4 in Urogenital schistosomiasis transmission on Unguja Island, Zanzibar: characterisation of persistent hot-spots
Fig. 4 Number of B. globosus and B. globosus shedding S. haematobium cercariae per shehia in Unguja
Dataset used in the study "Urban microclimate simulations based on GIS data to mitigate thermal hot-spots: Tree design scenarios in an industrial area of Florence"
<p>This dataset repository includes input and output spatial data of urban microclimate simulations performed through QGIS and ENVI-met software used in the study "Urban microclimate simulations based on GIS data to mitigate thermal hot-spots: Tree design scenarios in an industrial area of Florence", published in the Building and Environment Journal, <a href="https://doi.org/10.1016/j.buildenv.2023.110854">https://doi.org/10.1016/j.buildenv.2023.110854</a>.</p>
Data from: Prevalence of afebrile malaria and development of risk-scores for gradation of villages: a study from a hot-spot in Odisha
Introduction: Malaria is a public health emergency in India and Odisha. The national malaria elimination programme aims to expedite early identification, treatment and follow-up of malaria cases in hot-spots through a robust health system, besides focusing on efficient vector control. This study, a result of mass screening conducted in a hot-spot in Odisha, aimed to assess prevalence, identify and estimate the risks and develop a management tool for malaria elimination. Methods: Through a cross-sectional study and using WHO recommended Rapid Diagnostic Test (RDT), 13221 individuals were screened. Information about age, gender, education and health practices were collected along with blood sample (5 µl) for malaria testing. Altitude, forestation, availability of a village health worker and distance from secondary health center were captured using panel technique. A multi-level poisson regression model was used to analyze association between risk factors and prevalence of malaria, and to estimate risk scores. Results: The prevalence of malaria was 5.8% and afebrile malaria accounted for 79 percent of all confirmed cases. Higher proportion of Pv infections were afebrile (81%). We found the prevalence to be 1.38 (1.1664 - 1.6457) times higher in villages where the Accredited Social Health Activist (ASHA) didn't stay; the risk increased by 1.38 (1.0428 - 1.8272) and 1.92 (1.4428 - 2.5764) times in mid- and high-altitude tertiles. With regard to forest coverage, villages falling under mid- and highest-tertiles were 2.01 times (1.6194 - 2.5129) and 2.03 times (1.5477 - 2.6809), respectively, more likely affected by malaria. Similarly, villages of mid tertile and lowest tertile of education had 1.73 times (1.3392 - 2.2586) and 2.50 times (2.009 - 3.1244) higher prevalence of malaria. Conclusion: Presence of ASHA worker in villages, altitude, forestation, and education emerged as principal predictors of malaria infection in the study area. An easy-to-use risk-scoring system for ranking villages based on these risk factors could facilitate resource prioritization for malaria elimination.
Data from: A multispecies approach reveals hot-spots and cold-spots of diversity and connectivity in invertebrate species with contrasting dispersal modes
Genetic diversity is crucial for species' maintenance and persistence, yet is often overlooked in conservation studies. Species diversity is more often reported due to practical constraints, but it is unknown if these measures of diversity are correlated. In marine invertebrates, adults are often sessile or sedentary and populations exchange genes via dispersal of gametes and larvae. Species with a larval period are expected to have more connected populations than those without larval dispersal. We assessed the relationship between measures of species and genetic diversity, and between dispersal ability and connectivity. We compiled data on genetic patterns and life history traits in nine species across five phyla. Sampling sites spanned 600 km in the northwest Mediterranean Sea and focused on a 50 km area near Marseilles, France. Comparative population genetic approaches yielded three main results. (1) Species without larvae showed higher levels of genetic structure than species with free-living larvae but the role of larval type (lecithotrophic or planktotrophic) was negligible. (2) A narrow area around Marseilles, subject to offshore advection, limited genetic connectivity in most species. (3) We identified sites with significant positive contributions to overall genetic diversity across all species, corresponding with areas near low human population densities. In contrast, high levels of human activity corresponded with a negative contribution to overall genetic diversity. Genetic diversity within species was positively and significantly linearly related with local species diversity. Our study suggests that local contribution to overall genetic diversity should be taken into account for future conservation strategies.
FIGURE 12. O. sibirica. A in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 12. O. sibirica. A) habit (fruiting specimens); B) leaves of sterile shoot from above (left) and below (right); C) lateral fruiting raceme; D) silicle in lateral, inner and outer view. Original drawing by L. Cecchi (based on the isotype of Alyssum suffrutescens var. epirotum BM000750156).
FIGURE 11. O. rigida. A in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 11. O. rigida. A) habit (fruiting specimen); B) leaf of sterile shoot, showing its upper (left) and lower surface (right); C) lateral fruiting raceme; D) silicle in lateral, inner and outer view. Original drawing by L. Cecchi (based on the neotype specimen, FI050434).
FIGURE 13. O. smolikana subsp. glabra. A in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 13. O. smolikana subsp. glabra. A) habit (fruiting specimen); B) leaf of sterile shoot, showing its upper (on the left) and lower surface (right); C) lateral fruiting raceme; D) flower in lateral view, with isolated sepal and petal; E) silicle in lateral, inner and outer view. Original drawing by L. Cecchi (based on FI050431 and FI050835).
FIGURE 9. O. decipiens. A in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 9. O. decipiens. A) habit (flowering specimen and fruiting shoot); B) leaf of sterile shoot, showing its upper (on the left) and lower surface (right); C) lateral fruiting racemes; D) closed and open silicles of different size and shape. Original drawing by L. Cecchi (based on FI050442 and FI052160).
FIGURE 10. O. moravensis. A in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 10. O. moravensis. A) habit (fruiting specimens); B) leaf of sterile shoot, showing its upper (left) and lower surface (right); C) lateral fruiting raceme; D) silicle in lateral, inner and outer view. Original drawing by L. Cecchi (based on the FI050441 and FI050828).
FIGURE 8. O in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 8. O. chalcidica: A, F) habit (flowering and fruiting specimens of different stature); B) cauline leaves of flowering (left) and sterile (right) shoots, showing their upper and lower surface on the left and on the right, respectively; C) lateral fruiting raceme; D) silicle in lateral, inner and outer view. Original drawing by L. Cecchi (based on FI050844 and FI050882).
FIGURE 6 in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 6. SEM micrographs of silicles of: A) O. albiflora (FI050840); B) O. chalcidica (neotype of A. markgrafii, FI050424); C) O. chalcidica (Greece, near Thessaloniki, isolectotype, FI010117); D) O. decipiens (FI050445); E) O. smolikana subsp. glabra (FI050433); F) O. moravensis (FI050441); G) O. muralis (Romania, Deva, type locality, FI050439); H) O. rigida (neotype, FI050434). Scale bar = 2mm.
FIGURE 4 in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 4. Phenological differences between taxa of Odontarrhena in Albania. Bars in light grey indicate the time interval between the decade in which at least 50% of the population is in flower and the decade when full flowering (100%) of the population occurs; bars in dark grey indicate the same interval for the fruiting process (50%-100% of the population with ripe fruits).
FIGURE 1 in The genus Odontarrhena (Brassicaceae) in Albania: Taxonomy and Nickel accumulation in a critical group of metallophytes from a major serpentine hot-spot
FIGURE 1. Distribution of Odontarrhena in Albania; the range of O. chalcidica is given as light grey area, the other taxa as symbols (in legend); major serpentine outcrops are represented as dark grey spots and numbered from the north to the south. 1: Tropoja, 2: Krrabi, 3: Gomsiqe, 4: Puke, 5: Kukesi, 6: Lure, 7: Skenderbeu, 8: Bulqize, 9: Shebenik, 10: Shpati, 11: Vallamara, 12: Devolli, 13: Voskopoja, 14: Morava (after Bani et. al. 2017, modified).
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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