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opencc-by-4.0Aug 2017View details →

Ex-situ X-ray computed tomography data for a non-crimp fabric based fibre composite under fatigue loading

Ex-situ X-ray CT fatigue testing data sets published as a data in brief: "Ex-situ X-ray computed tomography data for a non-crimp fabric based fibre composite under fatigue loading", Data in brief, 2017, doi.org/10.1016/j.dib.2017.10.074. Together with the following article: K. M. Jespersen and L. P. Mikkelsen, “Three dimensional fatigue damage evolution in non-crimp glass fibre fabric based composites used for wind turbine blades,” Compos. Sci. Technol. (In press), 2017, 10.1016/j.compscitech.2017.10.004.

opencc-by-4.0Apr 2022View details →

Fig. 3. A in Data On The Reproductive Biology Of The Satanic Leaf-Tailed Gecko, Uroplatus Phantasticus (Squamata, Gekkonidae), At The Bion Terrarium Center As A Contribution To Ex Situ Offspring Programs

Fig. 3. A part of all fertile eggs laid by U. phantasticus females during 2020 breeding season; incubation boxes are filled with "Seramis" medium.

opencc-by-4.0Apr 2022View details →

Fig. 1 in Data On The Reproductive Biology Of The Satanic Leaf-Tailed Gecko, Uroplatus Phantasticus (Squamata, Gekkonidae), At The Bion Terrarium Center As A Contribution To Ex Situ Offspring Programs

Fig. 1. Laboratory for breeding stock of U. phantasticus (A) and individual breeze-like minimally equipped terrariums (B).

opencc-by-4.0Apr 2022View details →

Fig. 5. A in Data On The Reproductive Biology Of The Satanic Leaf-Tailed Gecko, Uroplatus Phantasticus (Squamata, Gekkonidae), At The Bion Terrarium Center As A Contribution To Ex Situ Offspring Programs

Fig. 5. A total number of eggs (pcs.) obtained from U. phantasticus females by dates during 2020 breeding season.

opencc-by-4.0Dec 2010View details →

Fig. 1 in Cruciata Glabra (L.) Ehrend. (Rubiaceae A. L. Juss.) In Lithuania: In Situ And Ex Situ

Fig. 1. Geobotanical districts in the area of Lithuania Red Data Book plants Juniperus communis L. The prevailing mosses under the lime (Tilia cordata Mill.) in the shady are Pleurozium schreberi (Brid.) Mitt., Ptilium place, in almost neutral soil (pH 7.26). It crista-castrensis (Hedw.) De Not., Hylocomium propagated by the vegetative way only, blew splendens (Hedw.) Schimp. and Dicranum not profusely. In the spring of 2007 Cruciata scoparium Hedw., there also grow some Calluna glabra (L.) was moved to the collection of rare vulgaris (L.) Hull., Vaccinium vitis-idaea L., plants in the Section of Plant Geography and Festuca ovina L., Milium effusum L., Systematics. Here place is sunny, the soil is a Melampyrum pratense L., Helianthemum little bit alkaline (pH 7.6). The plant adapted very nummularium (L.), Pulsatilla pratensis (L.) Mill. well (Fig. 3), blew profusely in May and June, and P. patens (L.) Mill., Chamerion procreated in vegetative way and nurtured seeds. angustifolium (L.) Holub, Scorzonera humilis Since 2007 information about Cruciata glabra L., Pyrola chlorantha Sw., Fragaria vesca L. growing in Botanical garden of Šiauliai University Next to the growing place on the dug up forest is included in Index Seminum publication square line grow Cerastium holosteoides Fr., designed for international interchange of seeds. Moehringia trinervia (L.) Clairv., Rumex acetosella L., Scleranthus annuus L., Spergula sp. Mentioned place plant names from literature CONCLUSIONS Z. Gudžinskas (1999). This growing place is the most northern natural place of this species in 1. Cruciata glabra (L.) Ehrend. species is Lithuania. The 13 geobotanical district (Fig. 1) particularly endagered by anthropogenic lies among Riga (1e) and Šiauliai (19 a). Possibility influence and spontaneous changes of to find this species growing in brighter woods forests. is very believable.

Figure 4 in Use of commercial biostimulator in the ex situ cultivation of a native medicinal plant of Cerrado: Campomanesia adamantium

Figure 4. Two-dimensional graphic of the production data, chemical attributes of substrate, macro and micronutrients of dry mass of aerial parts in different doses of biostimulator. PC1 and PC2 correspond to the Principal Components Leaf dry mass (LDM); Stem dry mass (SDM); Total dry mass (TDM); Leaf area (LA); Dickson quality index (DQI); Root length (RL); Potential of hydrogen (pH); Organic matter (OM); Sum of bases (SB); Cation exchange capacity (CEC); Base saturation (V%); Phosphorus of substrate (P); Calcium of substrate (Ca); Calcium of root (R Ca); Magnesium of substrate (Mg); Copper of substrate (Cu); Copper of shoot (AP Cu); Copper of root (R Cu); Manganese of substrate (Mn); Iron of substrate (Fe); Iron of shoot (AP Fe); Zinc of substrate (Zn); Zinc of shoot (AP Zn) and Zinc of root (R Zn).

Figure 1 in Use of commercial biostimulator in the ex situ cultivation of a native medicinal plant of Cerrado: Campomanesia adamantium

Figure 1. Two-dimensional graphic of the chemical and microbiological attributes in different doses of biostimulator. PC1 and PC2 correspond to the Principal Components Potential of hydrogen (pH); Organic matter (OM); Phosphorus (P); Calcium (Ca); Magnesium (Mg); Copper (Cu); Manganese (Mn); Iron (Fe); Zinc (Zn); Sum of bases (SB); Cation exchange capacity (CEC); Base saturation (V%); microbial biomass carbon (Cmic); Basal respiration (BSR); Metabolic quocient (qCO ).

Figure 3 in Use of commercial biostimulator in the ex situ cultivation of a native medicinal plant of Cerrado: Campomanesia adamantium

Figure 3. Number of leaves of 'guavira' plants according to doses of the biostimulator and epochs of evaluation, * indicates significant difference (p <0.05).

Figure 2 in Use of commercial biostimulator in the ex situ cultivation of a native medicinal plant of Cerrado: Campomanesia adamantium

Figure 2. Photosynthetic activity of 'guavira' plants. A. Photochemical efficiency of photosystem II (Fv/Fm); B. absorbed energy conversion efficiency (F v /F 0); C. chlorophyll index and D. chlorophyll b of 'guavira' plants grown on substrate with different doses of biostimulator, *indicates significant difference (p <0.05) between biostimulator.

Figure 5 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management

Figure 5. Illustration of the linear relationships between fetal age and growth measurements of biparietal diameter (BPD: top graph), thoracic diameter (TD: middle graph) and thoracic circumference (TC: bottom graph) in belugas.

Figure 4 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management

Figure 4. Comparisons of regression curves of TL growth during the first (●) and second half (○) of gestation (top graph) and the early (●), mid (○) and late (▲) pregnancy (bottom graph). The slopes of the regression lines for first half of gestation (F = 63.31, P <0.0001, df1 = 1, df2 = 33) and for early (F = 50.05, P <0.0001, df1 = 1, df2 = 37) and mid pregnancy (F = 135.04, P <0.0001, df1 = 1, df2 = 32) were different than those for the second half of gestation and late pregnancy, respectively. Note that the animals double in length during late pregnancy (315–473 d).

Figure 3 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management

Figure 3. Individual growth rate data from three animals (Animal 1, 2, 3). Regression line slopes during the first two-thirds of pregnancy (top graph) were similar (F = 0.48, P = 0.62, df1 = 2, df2 =18), while regression slopes where different (F = 15.13, P = 0.03, df1 = 2, df2 =3) from the second half to term. Animal 1 (▲) did not have any TL data beyond the first half of gestation so TL length data were used from the farthest in gestation and then again at term. Note that while growth rates were similar during the first two-thirds of pregnancy, fetuses were already different in size when initially detected.

Figure 2 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management

Figure 2. Fetal growth curve comparison illustrating different growth rates resulting in wide range in estimated gestation length as compared to known gestation length determined in this study. Data from Heide-Jørgensen and Teilmann (1994; dotted line) predicts a gestation length of 310 d for a 150 cm calf and similar to our study used a 2nd order polynomial regression to describe their data. Kleinenberg et al. ([1964] 1969: dashed line) developed a curve of the average monthly embryo/fetal growth. They did not provide the curve, only the predicted age at TL, which we then used to fit to a growth curve, which predicts 150 cm calf as 338 d.

Figure 1 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management

Figure 1. Ultrasonographic images of beluga fetuses. All images have yellow caliper lines used to measure dimensions. Biparietal diameter (A, B) at two different stages of gestation show the ovoid shaped skull and echo produced from falx (arrows) located midline between the parietal bones (arrowheads). The thoracic diameter (C) as measured between the yellow caliper marks (arrowheads) on the lateral side of the fetal thorax (d1 = 6.66 cm) at the level of the heart (white arrow) and thoracic circumference (c = 24.04 cm) determined by using the elliptical measurement caliper function to include the dorsal to ventral diameter (d2 = 8.67 cm). The total length of a fetus (D) which is bent in utero, thus requiring the addition of two separate measurements (arrowheads), 1) 8.38 cm from the cranial most aspect of the skull to mid abdomen and 2) 6.91 cm from mid abdomen to distal most portion of the peduncle for a total length of 15.29 cm.

opencc-by-4.0Feb 2018View details →

Three dimensional characterization of nickel coarsening in solid oxide cells via ex-situ ptychographic nano-tomography

Three-dimensional dataset of a solid oxide cell (SOC) fuel electrode microstructure. Data were acquired using ptychographic X-ray computed tomography (PXCT).

Fig. 3 in Captive breeding program for Scinax alcatraz (Anura: Hylidae): introducing amphibian ex situ conservation in Brazil

Fig. 3. Breeding of Scinax alcatraz at São Paulo Zoo. a) A pair in amplexus. b) Eggs deposited in the water. c) Maintanance of tadpoles in plastic pots with filtered water. d) Post-metamorph individuals (SVL x=12.49 mm). Photos by Cybele Lisboa.

Fig. 6 in Captive breeding program for Scinax alcatraz (Anura: Hylidae): introducing amphibian ex situ conservation in Brazil

Fig. 6. Range of environmental conditions (relative humidity and air temperature) most favorable for reproduction of Scinax alcatraz in captivity.

Fig. 5 in Captive breeding program for Scinax alcatraz (Anura: Hylidae): introducing amphibian ex situ conservation in Brazil

Fig. 5. Correlation between breeding events of Scinax alcatraz and environmental conditions (a) relative humidity and (b) air temperature from August 2013 to December 2017. Pearson product-moment Correlation Coefficient: r = 0.323; p <0.001; N = 732.

Fig. 2 in Captive breeding program for Scinax alcatraz (Anura: Hylidae): introducing amphibian ex situ conservation in Brazil

Fig. 2. Laboratory colony of Scinax alcatraz at Sao Paulo Zoo. a) Aquariums for maintanance of juveniles and adults. b) Plastic cups with filtered water and submerged plants for refuge. Photos by Cybele Lisboa.