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1,029 results for “altitude”
Thermoregulatory behavior varies with altitude and season in the sceloporine Mesquite lizard.
<p>In ectothermic vertebrates, body temperature is the factor that most affects physiology and behavior. Most ectotherms show limited physiological control of body temperature, so they use behavioral strategies to regulate and maintain a constant temperature within a range. The variation of environmental temperature due to altitude and seasonality could have a great impact on the regulation of body temperature in lizards, even more so in elevation gradients, in which environmental temperature decreases with elevation.</p> <p>We chose three populations of the lizard Sceloporus grammicus that inhabit along an altitudinal gradient at 2500, 3400, and 4100 m and compared some seasonal (spring, summer, and autumn) thermal traits:</p> <p>1. Body temperature in the field when the lizards were active<br> 2. The relationship between body, air, and substrate temperatures where they were first observed<br> 3. The temperature that they selected in a thermal gradient in laboratory conditions<br> 4. The precision of thermoregulation, the thermal quality of the environment, the effectiveness of thermoregulation, and the Blouin-Demers index<br> 5. The ambient temperatures available during the period of activity (Operative temperature)</p> <p>Thus, our data suggest that the thermal quality of the environment is low at higher altitudes and in summer, while lizards are capable of modifying their body temperature when they are active in the field and the temperature they select in the laboratory due to the effect of altitude and of the season, according to the requirements they have in each part of the year.</p>
Data for the manuscript named 'Altitude-dependence response near cusp region after solar wind variations'
<p>Data for the manuscript named 'Altitude-dependence response near cusp region after solar wind variations</p> <p>1) cluster data, observation from cluster mission</p> <p>2) MAD6400_2001-10-12_tau1a_59.4@vhfa_041292, EISCAT radar data</p> <p>3) OMNI: solar wind and IMF data</p> <p>4) p_shell_5.7Re_011012 is thermal pressure at 5.7 Re-shell, which was carried out in real-time solar wind conditions during 08:30-10:00UT (real-time-density run)</p> <p>5) p_shell_5.7Re_011012cd is thermal pressure at 5.7 Re-shell, which was carried out in real-time solar wind conditions except for solar wind density during 08:30-10:00UT (no-density-increasing run) </p> <p>“1_5.7Rshell_out.txt”time_latitude_out</p> <p>“1P_shell_5.7Re.csv”time_shell_5.7Re</p> <p>data range: MLT 08:00~16:00, latitude -90°~ -30°</p>
Data from: Sensitivity analysis of collision risk at wind turbines based on flight altitude of migratory waterbirds
<p>This dataset contains information on the distribution of geese and swans and the three-dimensional flight trajectories. The former was obtained through vehicle field surveys, interviews, and a literature review. The latter was obtained using ornithodolites.</p>
Multi-Altitude Aerial Vehicles Dataset
<p><strong>Custom Multi-Altitude Aerial Vehicles Dataset:</strong></p> <p>Created for publishing results for ICUAS 2023 paper "<em>How High can you Detect? Improved accuracy and efficiency at varying altitudes for Aerial Vehicle Detection</em>", following the abstract of the paper.</p> <p><strong>Abstract</strong>—Object detection in aerial images is a challenging task mainly because of two factors, the objects of interest being really small, e.g. people or vehicles, making them indistinguishable from the background; and the features of objects being quite different at various altitudes. Especially, when utilizing Unmanned Aerial Vehicles (UAVs) to capture footage, the need for increased altitude to capture a larger field of view is quite high. In this paper, we investigate how to find the best solution for detecting vehicles in various altitudes, while utilizing a single CNN model. The conditions for choosing the best solution are the following; higher accuracy for most of the altitudes and real-time processing ( > 20 Frames per second (FPS) ) on an Nvidia Jetson Xavier NX embedded device. We collected footage of moving vehicles from altitudes of 50-500 meters with a 50-meter interval, including a roundabout and rooftop objects as noise for high altitude challenges. Then, a YoloV7 model was trained on each dataset of each altitude along with a dataset including all the images from all the altitudes. Finally, by conducting several training and evaluation experiments and image resizes we have chosen the best method of training objects on multiple altitudes to be the mixup dataset with all the altitudes, trained on a higher image size resolution, and then performing the detection using a smaller image resize to reduce the inference performance. The main results</p> <p>The creation of a custom dataset was necessary for altitude evaluation as no other datasets were available. To fulfill the requirements, the footage was captured using a small UAV hovering above a roundabout near the University of Cyprus campus, where several structures and buildings with solar panels and water tanks were visible at varying altitudes. The data were captured during a sunny day, ensuring bright and shadowless images. Images were extracted from the footage, and all data were annotated with a single class labeled as 'Car'. The dataset covered altitudes ranging from 50 to 500 meters with a 50-meter step, and all images were kept at their original high resolution of 3840x2160, presenting challenges for object detection. The data were split into 3 sets for training, validation, and testing, with the number of vehicles increasing as altitude increased, which was expected due to the larger field of view of the camera. Each folder consists of an aerial vehicle dataset captured at the corresponding altitude. For each altitude, the dataset annotations are generated in YOLO, COCO, and VOC formats. The dataset consists of the following images and detection objects:</p> <table> <tbody> <tr> <td><strong>Data</strong></td> <td><strong>Subset</strong></td> <td><strong>Images</strong></td> <td><strong>Cars</strong></td> </tr> <tr> <td>50m</td> <td>Train</td> <td>130</td> <td>269</td> </tr> <tr> <td>50m</td> <td>Test</td> <td>32</td> <td>66</td> </tr> <tr> <td>50m</td> <td>Valid</td> <td>33</td> <td>73</td> </tr> <tr> <td>100m</td> <td>Train</td> <td>246</td> <td>937</td> </tr> <tr> <td>100m</td> <td>Test</td> <td>61</td> <td>226</td> </tr> <tr> <td>100m</td> <td>Valid</td> <td>62</td> <td>250</td> </tr> <tr> <td>150m</td> <td>Train</td> <td>244</td> <td>1691</td> </tr> <tr> <td>150m</td> <td>Test</td> <td>61</td> <td>453</td> </tr> <tr> <td>150m</td> <td>Valid</td> <td>61</td> <td>426</td> </tr> <tr> <td>200m</td> <td>Train</td> <td>246</td> <td>1753</td> </tr> <tr> <td>200m</td> <td>Test</td> <td>61</td> <td>445</td> </tr> <tr> <td>200m</td> <td>Valid</td> <td>62</td> <td>424</td> </tr> <tr> <td>250m</td> <td>Train</td> <td>245</td> <td>3326</td> </tr> <tr> <td>250m</td> <td>Test</td> <td>61</td> <td>821</td> </tr> <tr> <td>250m</td> <td>Valid</td> <td>61</td> <td>823</td> </tr> <tr> <td>300m</td> <td>Train</td> <td>246</td> <td>6250</td> </tr> <tr> <td>300m</td> <td>Test</td> <td>61</td> <td>1553</td> </tr> <tr> <td>300m</td> <td>Valid</td> <td>62</td> <td>1585</td> </tr> <tr> <td>350m</td> <td>Train</td> <td>246</td> <td>10741</td> </tr> <tr> <td>350m</td> <td>Test</td> <td>61</td> <td>2591</td> </tr> <tr> <td>350m</td> <td>Valid</td> <td>62</td> <td>2687</td> </tr> <tr> <td>400m</td> <td>Train</td> <td>245</td> <td>20072</td> </tr> <tr> <td>400m</td> <td>Test</td> <td>61</td> <td>4974</td> </tr> <tr> <td>400m</td> <td>Valid</td> <td>61</td> <td>4924</td> </tr> <tr> <td>450m</td> <td>Train</td> <td>246</td> <td>31794</td> </tr> <tr> <td>450m</td> <td>Test</td> <td>61</td> <td>7887</td> </tr> <tr> <td>450m</td> <td>Valid</td> <td>61</td> <td>7880</td> </tr> <tr> <td>500m</td> <td>Train</td> <td>270</td> <td>49782</td> </tr> <tr> <td>500m</td> <td>Test</td> <td>67</td> <td>12426</td> </tr> <tr> <td>500m</td> <td>Valid</td> <td>68</td> <td>12541</td> </tr> <tr> <td>mix_alt</td> <td>Train</td> <td>2364</td> <td>126615</td> </tr> <tr> <td>mix_alt</td> <td>Test</td> <td>587</td> <td>31442</td> </tr> <tr> <td>mix_alt</td> <td>Valid</td> <td>593</td> <td>31613</td> </tr> </tbody> </table> <p>It is advised to further enhance the dataset so that random augmentations are probabilistically applied to each image prior to adding it to the batch for training. Specifically, there are a number of possible transformations such as geometric (rotations, translations, horizontal axis mirroring, cropping, and zooming), as well as image manipulations (illumination changes, color shifting, blurring, sharpening, and shadowing).</p>
Data from: Diversification processes in Gerp's mouse lemur demonstrate the importance of rivers and altitude as biogeographic barriers in Madagascar's humid rainforests
<p><span>Madagascar exhibits exceptionally high levels of biodiversity and endemism. Models to explain the diversification and distribution of species in Madagascar stress the importance of historical variability in climate conditions which may have led to the formation of geographic barriers by changing water and habitat availability. The relative importance of these models for the diversification of the various forest-adapted taxa of Madagascar has yet to be understood. Here, we reconstructed the phylogeographic history of Gerp's mouse lemur (<em>Microcebus gerpi</em>) to identify relevant mechanisms and drivers of diversification in Madagascar's humid rainforests. We used restriction site associated DNA (RAD) markers and applied population genomic and coalescent-based techniques to estimate genetic diversity, population structure, gene flow and divergence times among <em>M. gerpi</em> populations and its two sister species <em>M. jollyae</em> and <em>M. marohita</em>. Genomic results were complemented with ecological niche models to better understand the relative barrier function of rivers and altitude. We show that <em>M. gerpi</em> diversified during the late Pleistocene. The inferred ecological niche, patterns of gene flow and genetic differentiation in <em>M. gerpi</em> suggest that the potential for rivers to act as biogeographic barriers depended on both size and elevation of headwaters. Populations on opposite sides of the largest river in the area with headwaters that extend far into the highlands show particularly high genetic differentiation, whereas rivers with lower elevation headwaters have weaker barrier functions, indicated by higher migration rates and admixture. We conclude that<em> M. gerpi</em> likely diversified through repeated cycles of dispersal punctuated by isolation to refugia as a result of paleoclimatic fluctuations during the Pleistocene. We argue that this diversification scenario serves as a model of diversification for other rainforest taxa that are similarly limited by geographic factors. In addition, we highlight conservation implications for this critically endangered species, which faces extreme habitat loss and fragmentation. </span></p>
Psycho-physio-neurological correlates of qualitative attention, emotion and flow experiences in a close-to-real-life extreme sports situation: low- and high-altitude slackline walking
<p>It has been indicated that extreme sport activities, despite providing fear, stress and anxiety, also result in a highly rewarding experience. Studies have related this experience to the concept of flow, a positive feeling that individuals undergo when they are completely immersed in an activity. However, little is known about the exact nature of these experiences, and, there are still no empirical results to characterize the brain dynamics during extreme sport practice. This work aimed at investigating changes in psychological responses while recording physiological (heart rate – HR, and breathing rate – BR) and neural (electroencephalographic – EEG) data of eight volunteers, during outdoors slackline walking in a mountainous environment at two different altitude conditions (1 m – low-walk – and 45 m – high-walk – from the ground). Low-walk showed a higher score on flow scale, while high-walk displayed a higher score in the negative affect aspects, which together point to some level of flow restriction during high-walk. The order of task performance was shown to be relevant for the physiological and neural variables. The brain behavior during flow, mainly considering attention networks, displayed the stimulus-driven ventral attention network – VAN, regionally prevailing (mainly at the frontal lobe), over the goal-directed dorsal attention network – DAN. Therefore, we suggest an interpretation of flow experiences as an opened attention to more changing details in the surroundings, i.e., configured as a ‘task-constantly-opened-to-subtle-information experience’, rather than a ‘task-focused experience’.</p>
Psycho-physio-neurological correlates of qualitative attention, emotion and flow experiences in a close-to-real-life extreme sports situation: low- and high-altitude slackline walking
<p>It has been indicated that extreme sport activities, despite providing fear, stress and anxiety, also result in a highly rewarding experience. Studies have related this experience to the concept of flow, a positive feeling that individuals undergo when they are completely immersed in an activity. However, little is known about the exact nature of these experiences, and, there are still no empirical results to characterize the brain dynamics during extreme sport practice. This work aimed at investigating changes in psychological responses while recording physiological (heart rate – HR, and breathing rate – BR) and neural (electroencephalographic – EEG) data of eight volunteers, during outdoors slackline walking in a mountainous environment at two different altitude conditions (1 m – low-walk – and 45 m – high-walk – from the ground). Low-walk showed a higher score on flow scale, while high-walk displayed a higher score in the negative affect aspects, which together point to some level of flow restriction during high-walk. The order of task performance was shown to be relevant for the physiological and neural variables. The brain behavior during flow, mainly considering attention networks, displayed the stimulus-driven ventral attention network – VAN, regionally prevailing (mainly at the frontal lobe), over the goal-directed dorsal attention network – DAN. Therefore, we suggest an interpretation of flow experiences as an opened attention to more changing details in the surroundings, i.e., configured as a ‘task-constantly-opened-to-subtle-information experience’, rather than a ‘task-focused experience’.</p>
Age Structure and Body Size of The Tibetan Toad (Bufo tibetanus) Populations from Two Different Altitudes in China
<p>Knowledge about the altitudinal patterns in age and body size helps to highlight the evolution of life history parameters in animals. In this study, we investigated the demographic traits of the Tibetan toad (<em>Bufo tibetanus</em>) between populations from low and high altitude habitats (2650 <em>vs</em> 3930m) using skeletochronology. We found 1) the mean age and body size of females were significantly greater than those of males in either population; 2) both sexes of toads from the higher altitude tended to be significantly older in age and larger in body size; 3) a significant positive relationship between age and body size within each sex of the toad at both altitudes; 4) growth rates varied between the two populations, with the higher rate observed in the low-altitude population, and lower in the high-altitude population. Our results suggest that factors other than age can influence altitudinal patterns in body size, such as altitude-associated temperature. Future research should pay attention to these factors and evaluate their influences on the growth patterns of animals.Knowledge about the altitudinal patterns in age and body size helps to highlight the evolution of life history parameters in animals. In this study, we investigated the demographic traits of the Tibetan toad (<em>Bufo tibetanus</em>) between populations from low and high altitude habitats (2650 <em>vs</em> 3930m) using skeletochronology. We found 1) the mean age and body size of females were significantly greater than those of males in either population; 2) both sexes of toads from the higher altitude tended to be significantly older in age and larger in body size; 3) a significant positive relationship between age and body size within each sex of the toad at both altitudes; 4) growth rates varied between the two populations, with the higher rate observed in the low-altitude population, and lower in the high-altitude population. Our results suggest that factors other than age can influence altitudinal patterns in body size, such as altitude-associated temperature. Future research should pay attention to these factors and evaluate their influences on the growth patterns of animals.</p>
Data from: Divergent mechanisms of reduced growth performance in Betula ermanii saplings from high-altitude and low-latitude range edges
<p><span>The reduced growth performance of individuals from range edges is a common phenomenon in various taxa, and considered to be an evolutionary factor that limits the species' range. However, most studies did not distinguish between two mechanisms that can lead to this reduction: genetic load and adaptive selection to harsh conditions. This study investigated the climatic and genetic factors underlying the growth performance of <em>Betula ermanii</em> saplings transplanted from 11 populations including high-altitude edge and low-latitude edge population using RAD-seq analysis.</span></p> <p>For 11 B. ermanii populations in wide-latitude range of Japan, we estimated gene diversity, nucleotide diversity, <span>the coefficients of linkage disequilibrium, genetic differentiation between populations, population structure as well as the relatedness coefficient from SNPs. As a result, the low-latitude edge population exhibited a high level of linkage disequilibrium, low genetic diversity, a distinct genetic composition from the other populations, and a high relatedness coefficient.</span></p> <p><span>This data contains two SNPs datas (vcf files) used in these analysis. We analyzed SNPs data separately for 8 planting sites. Then each tarball contains 8 separate vcf files. One tarball named "vcfAfterFiltering" contains vcf files after SNP filtering steps used for the calculation of the coefficients of linkage disequilibrium. Another tarball named "vcfAfterLDPruning" contains vcf files after SNP filtering and before LD-based pruning used for the calculation of other genetic parameters.</span></p>
HYPHOP: a tool for high-altitude, long-range monitoring of hydrogen peroxide and higher organic peroxides in the atmosphere
<p>We provide here the supporting dataset for our study on measurement performance of the HYPHOP monitor during the CAFE-Brazil aircraft campaign in 2022/23. </p>
High Altitude Balloon by Julián Fernández RF recording 2019-05-19
<p>This is a recording of an Amateur high altitude balloon released by Julián Fernández EA4HCD on 2019-05-19. The balloon carried a LoRa and RTTY transmitter on 434.5MHz and a LoRa transmitter on 868MHz. The balloon was released near Madrid (Spain) and reached and altitude of 24km and distance of 180km. This recording was done from shortly after release until 15 minutes before burst.</p> <p>Amateur radio callsign: EA4GPZ</p> <p>Station location: 40.620697,-3.6936182, in Tres Cantos, near Madrid.</p> <p>Antenna: 7 element 435MHz yagi from Arrow Antennas, vertical polarization, roughly aimed to the balloon location, 3m above ground level.</p> <p>Receiver: FUNcube Dongle Pro+, LNA and mixer gain enabled.</p> <p>Frequency: 434.5MHz at the start of the recording, changed later to 434.502MHz without interruption of the recording.</p> <p>Sample rate: 192ksps.</p> <p>Recording start: 2019-05-19 15:37:19 UTC</p> <p>Format: Linrad raw format: 41 byte header followed by little-endian int16 IQ data.</p>
Efficacy Study of Riociguat and Its Effects on Exercise Performance and Pulmonary Artery Pressure at High Altitude
ClinicalTrials.gov study NCT02024386. IPD Sharing: Not stated. Countries: 1. Publications: 31.
Rapid Acclimatization to Hypoxia at Altitude
ClinicalTrials.gov study NCT01702025. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Prevention of Altitude Illness With Non-steroidal Anti-inflammatory Study (PAINS)
ClinicalTrials.gov study NCT01171794. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Study Looking at End Expiratory Pressure for Altitude Illness Decrease (SLEEP-AID)
ClinicalTrials.gov study NCT01842906. IPD Sharing: NO. Countries: 1. Publications: 1.
Effects of Nebivolol Versus Carvedilol on Cardiopulmonary Function at High Altitude in Healthy Subjects.
ClinicalTrials.gov study NCT00924833. IPD Sharing: Not stated. Countries: 1. Publications: 8.
The Psychophysiological Effect of Simulated and Terrestrial Altitude
ClinicalTrials.gov study NCT04075565. IPD Sharing: NO. Countries: 1. Publications: 0.
Altitude Sickness Prevention and Efficacy of Comparative Treatments
ClinicalTrials.gov study NCT02604173. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Influences of ski-runs, meadow management and climate on the occupancy of reptiles and amphibians in a high-altitude environment of Italy
Open the record for dataset details and reuse information.
Low migratory flight altitudes may explain increased collision risk for Scolopax minor (American Woodcock)
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International Brain Laboratory public data
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OpenNeuro
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