Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
313
datasets available to search
ShareScore release 0.9.0
Dataset results
313 results for “locomotion”
Hunslet 204HP Diesel Locomotive D10
Built: 1957 Leeds Hunslet No. 5152 Type: 0-6-0 Diesel Locomotive Caroni No.10 Caroni Asset No. 39123 Status Extant: Brechin Castle Information and footage provided by Glen Beadon Trinidad Lost Railways: https://www.youtube.com/watch?v=Vt8RMr0Wj-Q Source: Objaverse 1.0 / Sketchfab
Evaluation of tracking performance and robustness for a hybrid locomotion controller
<p>Legged locomotion is a complex control problem that requires both accuracy and robustness to cope with real-world challenges. Legged systems have traditionally been controlled using trajectory optimization with inverse dynamics. Such hierarchical model-based methods are appealing due to intuitive cost function tuning, accurate planning, generalization, and most importantly, the insightful understanding gained from more than one decade of extensive research. However, model mismatch and violation of assumptions are common sources of faulty operation. Simulation-based reinforcement learning, on the other hand, results in locomotion policies with unprecedented robustness and recovery skills.<br>Yet, all learning algorithms struggle with sparse rewards emerging from environments where valid footholds are rare, such as gaps or stepping stones. In this work, we propose a hybrid control architecture that combines the advantages of both worlds to simultaneously achieve greater robustness, foot-placement accuracy, and terrain generalization. Our approach utilizes a model-based planner to roll out a reference motion during training. A deep neural network policy is trained in simulation, aiming to track the optimized footholds. We evaluate the accuracy of our locomotion pipeline on sparse terrains, where pure data-driven methods are prone to fail. Furthermore, we demonstrate superior robustness in the presence of slippery or deformable ground when compared to model-based counterparts. Finally, we show that our proposed tracking controller generalizes across different trajectory optimization methods not seen during training. In conclusion, our work unites the predictive capabilities and optimality guarantees of online planning with the inherent robustness attributed to offline learning.</p>
Locomotive Headlamp
This object from the collection of the [Museum of The Scottish Railways and the Bo'ness and Kinneil Railway](http://www.bkrailway.co.uk/) is a locomotive headlamp which was used by the London and North Eastern Railway Company between 1923 and 1947. In the Steam and early Diesel era, where these lamps were placed told the signal men what kind of a train it was, for example if it was an ordinary passenger train or carrying livestock. It also indicated the train's likely running speed as well as its line priority. The 3D model was created as a part of Scanning The Horizon project lead by the Scottish Maritime Museum, which is a partnering institution in Industrial Museums Scotland ([Go Industrial](http://www.goindustrial.co.uk/)). Source: Objaverse 1.0 / Sketchfab
Effects of ingesting large prey on the kinematics of rectilinear locomotion in Boa constrictor
<p>Large and stout snakes commonly consume large prey and use rectilinear crawling, yet, whether body wall distention after feeding impairs rectilinear locomotion is poorly understood. After eating large prey (30-37% body mass), all <em>Boa constrictor</em> tested could perform rectilinear locomotion in the region with the food bolus despite a greatly increased distance between the ribs and the ventral skin that likely lengthens muscles relevant to propulsion. Unexpectedly, out of eleven kinematic variables, only two changed significantly (P<0.05) after feeding: cyclic changes in snake height increased by more than 1.5x and the longitudinal movements of ventral skin relative to the skeleton decreased by more than 25%. Additionally, cyclic changes in snake width suggest that the ribs are active and mobile during rectilinear locomotion particularly in fed snakes, but also in unfed snakes. These kinematic changes suggest that rectilinear actuators reorient more vertically and undergo smaller longitudinal excursions following large prey ingestion, both of which likely act to reduce elongation of these muscles that may otherwise experience substantial strain.</p>
Dynamics of Centipede Locomotion Revealed by Large-Scale Traction Force Microscopy (J. Roy Soc INTERFACE, to be published, march 2024)
<p>data and matlab code from paper "Dynamics of Centipede Locomotion Revealed by Large-Scale Traction Force Microscopy" (paper submitted to J. Roy Soc INTERFACE, to be published, march 2024)</p> <p><strong><span>Dynamics of Centipede Locomotion Revealed by Large-Scale Traction Force Microscopy</span></strong></p> <p><span> </span><span>J.P. Rieu</span><sup><span>1, *</span></sup><span>, H. Delanoë-Ayari</span><sup><span>1</span></sup><span>, C. Barentin</span><sup><span>1</span></sup><span>, T. Nakagaki</span><sup><span>2</span></sup><span> and S. Kuroda</span><sup><span>3</span></sup><sup><span> ,*</span></sup></p> <p><sup><span>1</span></sup><span> </span><span>Institut Lumière Matière, University of Lyon, Université Claude Bernard Lyon 1, CNRS, F-69622, Villeurbanne, France</span></p> <p><sup><span>2</span></sup><span> Research Institute for Electronic Science, Hokkaido University, N20W10 Kita-ku, Sapporo Hokkaido 001-0020, Japan</span></p> <p><sup><span>3 </span></sup><span>Faculty of Software and Information Technology, Aomori University, Koubata 2-3-1, Aomori, 030-0943, Japan</span></p> <p><span>* Authors for correspondence:<span> </span>Jean-Paul Rieu (e-mail: jean-paul.rieu@univ-lyon1.fr) and Shigeru Kuroda (shigeru-kuroda@aomori-u.ac.jp)</span></p> <p> </p> <p><strong><span>Abstract</span></strong></p> <p><span>We present a novel approach to traction force microscopy (TFM) for studying the locomotion of 10cm-long walking centipedes on soft substrates.</span><span> Leveraging the </span><span>remarkable</span><span> elasticity and ductility of kudzu starch gels, we utilize them as a deformable gel substrate, providing resilience against the centipedes' sharp leg tips. </span><span>Through optimizing fiducial marker size and density and fine-tuning imaging conditions, we enhance measurement accuracy. Our TFM investigation reveals traction forces along the centipede's longitudinal axis that effectively counterbalance inertial forces within the 0-10mN range, providing the first report of non-vanishing inertia forces in TFM studies. Interestingly, we observe waves of forces propagating from the head to the tail of the centipede, corresponding to its locomotion speed. Furthermore, we discover a characteristic cycle of leg clusters engaging with the substrate: forward force (friction) upon leg tip contact, backward force (traction) as the leg pulls the substrate while stationary, and subsequent forward force as the leg tip detaches to reposition itself in the anterior direction. </span><span>This work </span><span>opens perspectives for TFM applications in ethology, tribology, and robotics</span><span>.</span></p>
Anatomical insights into fish terrestrial locomotion: a study of barred mudskipper (Periophthalmus argentilineatus) fins based on μCT 3D reconstructions
<p>Mudskippers are a group of extant ray-finned fishes with an amphibious lifestyle and serve as exemplars for understanding the evolution of amphibious capabilities in teleosts. A comprehensive anatomical profile of both the soft and hard tissues within their propulsive fins is essential for advancing our understanding of terrestrial locomotor adaptations in fish. Despite the ecological significance of mudskippers, detailed data on their musculoskeletal anatomy remains limited. In the present research, we utilized contrast-enhanced high-resolution micro-computed tomography (μCT) imaging to investigate the barred mudskipper, <em>Periophthalmus argentilineatus</em>. This technique enabled detailed reconstruction and quantification of the morphological details of the pectoral, pelvic, and caudal fins of this terrestrial mudskipper, facilitating comparison with its aquatic relatives. Our findings reveal that <em>P. argentilineatus</em> has undergone complex musculoskeletal adaptations for terrestrial movement, including an increase in muscle complexity and muscle volume, as well as the development of specialized structures like aponeuroses for pectoral fin extension. Skeletal modifications are also evident, with features such as a reinforced shoulder-pelvic joint and thickened fin rays. These evolutionary modifications suggest biomechanically advanced fins capable of overcoming the gravitational challenges of terrestrial habitats, indicating a strong selective advantage for these features in land-based environments. The unique musculoskeletal modifications in the fins of mudskippers like <em>P. argentilineatus</em>, compared to their aquatic counterparts, mark a critical evolutionary shift toward terrestrial adaptations. This study not only sheds light on the specific anatomical changes facilitating this transition but also offers broader insights into the early evolutionary mechanisms of terrestrial locomotion, potentially mirroring the transformative journey from aquatic to terrestrial life in the lineage leading to tetrapods.</p>
Kinematics of sea star legged locomotion
Sea stars have slower crawling and faster bouncing gaits. Both speed and oscillation amplitude increase during the transition from crawling to oscillating. In the bouncy gait, vertical velocities precede horizontal velocities by 98&[deg], as reflected by clockwise circular hodographs. Potential energy precedes horizontal energy by 16&[deg] and so are nearly in phase. These phase relationships resemble terrestrial running gaits, except that podia are always on the ground. Kinetic and potential energy scale as mass<sup>1.1</sup>, with the change in kinetic energy consistently two orders of magnitude less, indicating that efficient exchange is not feasible. Frequency of the bouncy gait scales with mass<sup>-0.14</sup>, which is similar to continuously running vertebrates and indicates that gravitational forces are important. This scaling differs from the Hill model, in which scaling of muscle forces determine frequency. We propose a simple torque stabilized inverted pendulum (TS-IP) model to conceptualize the dynamics of this gait. The TS-IP model incorporates mathematics equivalent to an angular spring, but implemented by a nearly constant upward force generated by the podia in each step. That upward force is just larger than the force required to sustain the underwater weight of the sea star. Even though the bouncy gait is the rapid gait for these sea stars, the pace of movement is still very slow. In fact, the observed Froude numbers (10<sup>-2</sup> to 10<sup>-3</sup>) are much lower than those typical of vertebrate locomotion and are as low or lower than those reported for slow walking fruit flies, which are the lowest values for pedestrian Froude numbers of which we are aware. --
Leg length and bristle density both necessary for water surface locomotion are genetically correlated in water striders
<p class="MsoNormal"><span>Access to hitherto unexploited ecological opportunities is associated with phenotypic evolution and often results in significant lineage diversification. Yet, our understanding of the mechanisms underlying such adaptive traits remains limited. Water striders have been able to exploit the water-air interface, primarily facilitated by changes in the density of hydrophobic bristles and a significant increase in leg length. These two traits are functionally correlated and are both necessary for generating efficient locomotion on the water surface. Whether bristle density and leg length have any cellular or developmental genetic mechanisms in common is unknown. Here, we combine comparative genomics and transcriptomics with functional RNAi assays to examine the developmental genetic and cellular mechanisms underlying the patterning of the bristles and the legs in <em>Gerris buenoi</em> and <em>Mesovelia mulsanti,</em> two species of water striders. We found that two gene duplication events in the genes <em>beadex </em>and <em>taxi </em>led to a functional expansion of the paralogs to affect bristle density and leg length. We also identified genes for which no function in bristle development has been previously described in other insects. Interestingly, most of these genes play a dual role in regulating bristle development and leg length. In addition, these genes play a role in regulating cell division. This result suggests that cell division may be a common mechanism through which these genes can simultaneously regulate leg length and bristle density. We propose that pleiotropy, by which gene function affects the development of multiple traits, may play a prominent role in facilitating access to unexploited ecological opportunities and species diversification.</span></p> <p> </p>
VR Locomotion Taxonomies
<p>Publication of JSON-modelled VR locomotion taxonomies and sources for the extracted locomotion taxonomies (see references).</p> <p> </p> <p> </p>
Comprehensive Kinetic and EMG Dataset of Daily Locomotion with 6 types of Sensors
<p> </p> <p><strong><a href="https://www.cambridge.org/core/journals/wearable-technologies/article/wearable-realtime-kinetic-measurement-sensor-setup-for-human-locomotion/488C21B7706FFDFA7FFAB387FD0A1A64?utm_campaign=shareaholic&utm_medium=copy_link&utm_source=bookmark">The paper</a> is now published in the recent Wearable Technology Journal, more detailed information on this dataset can be found there!</strong></p> <p>A human movement experiment with 12 young adults performing 13 daily movement trials (6 walking trials (speed: 0.9, 1.8, 2.7, 3.6, 4.5, 5.4 km/ h; 3 running trials (speed: 6.3, 8.8, 9.9 km/h); and four non-locomotion trials (vertical jump, squat, lunge, and single leg landing) was conducted with the ethic approved by the University of Twente (ET/A.21.19298, reference number 2021.57). </p> <p>Six types of measurement devices were used to capture different information of participants’ movements. They can be divided into two systems: the wearable system and the conventional non-wearable system. In the wearable measurement system, eight IMUs (Xsens Link, Enschede, The Netherlands) were used to measure the kinematic movements of lower limbs and trunk. A pair of pressure insoles (Moticon, Munich, Germany) was used to measure the vertical GRF and CoPs. In the conventional system, an optical motion capture system (OMC) containing 8 infrared light cameras (6+ series, Qualisys, Gothenburg, Sweden) was used to measure body kinematics data using reflective markers. A split-belt instrumented treadmill (Motek-Forcelink B.V, Culemborg, The Netherlands) was used to measure the GRFs under each foot. Two video cameras were also included inside the conventional system to capture the RGB images of participants’ body postures at the sagittal and frontal planes (<a href="https://doi.org/10.5281/zenodo.6644593">https://doi.org/10.5281/zenodo.6644593</a>). In addition, nine electromyography sensors (EMGs) (Delsys Trigno, Delsys, USA) were included to record the activations of nine major muscles in the dominant leg ("soleus", "medial gastrocnemius", "lateral gastrocnemius", "tibialis anterior", " semimembranosus", " biceps femoris long head", "vastus lateral", "rectus femoris", "vastus medial").</p> <p>In this shared data repository, both raw data (to be uploaded) and processed data (Processed_data.zip) are provided. The data processing pipeline can be found in this public GitHub repository: <a href="https://github.com/HuaweiWang/BioMechPro-WearableSystemVaildation">https://github.com/ET-BE/BioMechPro/tree/study/WearableSystemValidation</a>. Guidelines for creating the same wearable system in the corresponding comparison study are shared in this GitHub repo: <a href="https://github.com/HuaweiWang/WearableMeasurementSystem">https://github.com/HuaweiWang/WearableMeasurementSystem</a>.</p> <p><strong>[Note!]</strong> If you have unstable network that not able to download the huge data files, please check this version of dataset with small file sizes(2GB each)</p> <ul> <li>Raw data: <a href="https://doi.org/10.5281/zenodo.7422043">https://doi.org/10.5281/zenodo.7422043</a></li> <li>Processed data: <a href="https://doi.org/10.5281/zenodo.7422031">https://doi.org/10.5281/zenodo.7422031</a> </li> </ul> <p> </p> <p>Dataset structure descriptions:</p> <p><a href="https://zenodo.org/api/files/871df791-82f9-495a-ac56-eafd195c56ad/Raw_data.rar?versionId=41a0df36-b9b2-4e48-a50e-a6e81b23609b">Raw_data.rar</a>: Raw dataset</p> <ul> <li><em>Subjxx</em>: subject folder <ul> <li><em>Qualisys</em>: Qualisys project folder of the recordings</li> <li><em>Xsens</em>: Xsens project folder of the recordings</li> <li><em>Insoles</em>: Pressure insole project folder of the recordings</li> </ul> </li> </ul> <p><a href="https://zenodo.org/api/files/871df791-82f9-495a-ac56-eafd195c56ad/Processed_data.rar?versionId=d035b581-a334-48bb-88e1-3c655943b5cc">Processed_data.rar</a>: Processed dataset.</p> <ul> <li><em>allAverage.mat</em>: the overall summarization data of all subject at all movement trials. </li> <li><em>dataValidation.m</em>: the Matlab code to plot the summarization data by loading the allAverage.mat.</li> <li><em>subjs_info.txt</em>: general information of all participants. </li> <li><em>ComparisonPlots</em>: folder that contains the comparison plots between the laboratory-based system and the wearable measurement systems.</li> <li><strong><em>Subjxx</em></strong>: processed data for participants xx <ul> <li><em>dynMVCvalue.mat</em>: the dynamic Maximal Voluntary Contraction of measured muscles (highest value among all recorded movements)</li> <li><em>MVCvalue.mat</em>: the Maximal Voluntary Contraction of measured muscles (highest value in MVC recording trial only)</li> <li><em>Subjxx_xxxx_xx.mat</em>: the processed data (generated by the above mentioned processing pipeline) of current subject at specific movement trial.</li> <li><em>Qualisys</em>: The exported mat files from the Qualisys recordings, including markers, EMGs, GRFs.</li> <li><em>Xsens</em>: The exported .mvnx files from the Xsens MVN software reprocessing. This file can be directly loaded by Matlab without requiring the Xsens license.</li> <li><em>Insole</em>: Insole recorded data, parsed from the Moticon endpoint SDK output.</li> <li><em>OS</em>: The folder that contains the scaled OpenSim model and corresponding .xml and data files for IK and ID processing. Majority content in this folder is automatically generated by the processing pipeline</li> <li><em>Figures</em>: plots of the processed data, including joint angles, GRFs, joint torques, and EMGs. They are all generated in the last module of the processing pipeline.</li> </ul> </li> </ul> <p>Structure of the <strong>Subjxx_xxxx_xx.mat</strong>:</p> <p><em><strong>Subjxx_xxxx_xx</strong>.</em><em><strong>mat:</strong></em></p> <ul> <li><em>Info</em>: the general information of the participant and corresponding processing steps.</li> <li><em>Marker</em>: Marker data from Qualisys</li> <li><em>Force</em>: GRFs data from Qualisys</li> <li><em>EMG</em>: EMG data from Qualisys</li> <li><em>IMU</em>: Motion data from Xsens IMU system (from .mvnx)</li> <li><em>Insole</em>: The recorded pressure insole data</li> <li><strong>Resample</strong>: This data structure that contains the resampled data of the above mentioned sensor data <ul> <li><em>FrameRate</em>: the sampling rate for all resampled sensor data</li> <li><em>Marker</em>: Resampled marker data</li> <li><em>Force</em>: resampled force data</li> <li><em>EMG</em>: resampled EMG data</li> <li><em>IMU</em>: resampled IMU data</li> <li><em>Insole</em>: resampled Insole data</li> <li><em>CoM</em>: resampled center of mass data from Xsens IMU system</li> <li><strong>Sych</strong>: this data structure contains the IK & ID data of two measurement systems. They are also synchronized by calculate the highest correlation coefficient. <ul> <li><em>DeltaT</em>: the time differences between the laboratory-based system and the wearable measurement system.</li> <li><em>IKAngData</em>: the joint angle data from marker data inverse kinematics</li> <li><em>ForcePlateGFRData</em>: the ground reaction force data from instrumented treadmill</li> <li><em>IDTrqData</em>: the joint torque data from laboratory measurement system (optical + treadmill)</li> <li><em>IMUAngData</em>: the joint angle data from Xsens MVN software</li> <li><em>InsoleGRFData</em>: the ground reaction force data from pressure insoles</li> <li><em>IDTrqData_portable</em>: the joint torque data from the wearable system inverse dynamics</li> <li><em>EMG</em>: synchronized EMG data</li> <li><em>CoM</em>: synchronized CoM data</li> <li><em>xxxxxLabel</em>: the labels of each data column of corresponding data matrix</li> <li><strong>Average</strong>: this data structure contains the averaged gait/moment cycles <ul> <li><em>hsMatrix_right</em>: The heel strike data points of the right leg</li> <li><em>hsMatrix_left</em>: the heel strike data points of the left leg</li> <li><em>EMGAvedynNorFlag</em>: whether dynamic MVC normalization is applied on EMG.</li> <li><em>EMGAveNorFlag</em>: whether MVC normalization is applied on EMG.</li> <li><em>xxxx</em>: The averaged data of corresponding variables</li> <li><em>ForcePlateGRFDataInCalCn</em>: transferred treadmill GRF data from the treadmill global coordinate to the local Calcaneus coordinate of the scaled OpenSim model. </li> </ul> </li> </ul> </li> </ul> </li> </ul>
Understanding muscle function during perturbed in vivo locomotion using a muscle avatar approach
<p>To investigate in vivo mechanics of the guinea fowl lateral gastrocnemius (LG) muscle during obstacle negotiation while running on a treadmill, we used mouse extensor digitorum longus (EDL) muscles in ex vivo experiments with in vivo strain inputs from perturbed and steady strides obtained in a previous study. In vivo strain trajectories from a stride down from obstacle to treadmill, two strides up from treadmill to obstacle, and a level stride with no obstacle, as well as a sinusoidal strain trajectory at the same amplitude and frequency, were used as inputs in work loop experiments. With five strain trajectories and three activation patterns, each muscle was used in a total of 15 work loop experiments. EDL forces produced using in vivo strain trajectories were more similar to in vivo LG forces (<em>R<sup>2</sup></em> = 0.58 – 0.94) than to forces produced using the sinusoidal trajectory (average <em>R<sup>2</sup></em> = 0.045). Given the same activation, in vivo strain trajectories produced consistent work loops that showed a shift in muscle function from more positive work during strides up from treadmill to obstacle to less positive work in strides down from obstacle to treadmill. Activation, strain trajectory, and activation*strain trajectory interaction had significant effects on all work loop variables, with the interaction having the largest effect on peak force and work per cycle. These results support the hypothesis that muscle is an active material whose viscoelastic properties are tuned by activation, and which produces forces in response to deformations of length associated with time-varying loads.</p>
Information board of the Fablok steam locomotive
The first Locomotive Factory in Poland "Fablok" S.A. – manufactory Time and place of creation: 1928, Chrzanów, Poland Inventory number: Mch-S/3506 Museum: Irena and Mieczysław Mazaraki Museum in Chrzanów https://muzea.malopolska.pl/pl/lista-obiektow/2717 Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
Supporting data and code for Nakov, Beaulieu, Alverson: Accelerated diversification is related to life history and locomotion in a hyperdiverse lineage of microbial eukaryotes (Diatoms, Bacillariophyta)
<p>This archive includes:</p> <p>1. Character and species richness datasets</p> <p>2. Phylogenies and time-calibration files</p> <p>3. R scripts</p>
Supporting material for "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test"
<p>The data were uploaded to support the manuscript "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test" for the submission to Journal of Pharmacological and Toxicological Methods.</p>
Data for Improving propulsive efficiency using bio-inspired intermittent locomotion
<p>Raw and processed data for the manuscript: Improving propulsive efficiency using bio-inspired intermittent locomotion</p> <p>Contains both static and free propulsion measurements</p>
Light quantity controls locomotion in photosymbiotic Aiptasia
<p>Many cnidarians engage in endosymbiotic relationships with photosynthetic microalgae in the family Symbiodiniaceae. This symbiosis is deeply integrated into the physiology of the host. Although positive phototaxis and phototropism have been reported for symbiotic cnidarians, it is currently unknown whether light quantity influences phototactic behavior. Here we tested behavior of aposymbiotic (without Symbiodiniaceae) and symbiotic (with Symbiodiniaceae) Aiptasia in a light gradient to assess presence and effect of phototactic behavior. </p> <p> </p>
The relationship between sternum variation and mode of locomotion in birds
<p>Background: </p><p>The origin of powered avian flight was a locomotor innovation that expanded the ecological potential of maniraptoran dinosaurs, leading to remarkable variation in modern birds (Neornithes). The avian sternum is the anchor for the major flight muscles and, despite varying widely in morphology, has not been extensively studied from evolutionary or functional perspectives. We quantify sternal variation across a broad phylogenetic scope of birds using 3D geometric morphometrics methods. Using this comprehensive dataset, we apply phylogenetically informed regression approaches to test hypotheses of sternum size allometry and the correlation of sternal shape with both size and locomotory capabilities, including flightlessness and the highly varying flight and swimming styles of Neornithes.</p> <p></p> <p>Results: </p><p>We find evidence for isometry of sternal size relative to body mass and document significant allometry of sternal shape alongside important correlations with locomotory capability, reflecting the effects of both body shape and musculoskeletal variation. Among these, we show that a large sternum with a deep or cranially projected sternal keel is necessary for powered flight in modern birds, that deeper sternal keels are correlated with slower but stronger flight, robust caudal sternal borders are associated with faster flapping styles, and that narrower sterna are associated with running abilities. Correlations between shape and locomotion are significant but show weak explanatory power, indicating that although sternal shape is broadly associated with locomotory ecology, other unexplored factors are also important.</p> <p></p> <p>Conclusions: </p><p>These results display the ecological importance of the avian sternum for flight and locomotion by providing a novel understanding of sternum form and function in Neornithes. Our study lays the groundwork for estimating the locomotory abilities of paravian dinosaurs, the ancestors to Neornithes, by highlighting the importance of this critical element for avian flight, and will be useful for future work on the origin of flight along the dinosaur-bird lineage.</p> <p></p>
Data for: Telomere dynamics in relation to experimentally increased locomotion costs and fitness in great tits
<p>Evidence that telomere length (TL) and dynamics can be interpreted as proxy for 'life stress' experienced by individuals stems largely from correlational studies. We tested for effects of an experimental increase of workload on telomere dynamics by equipping male great tits (Parus major) with a 0.9 gram backpack for a full year. In addition, we analysed associations between natural life-history variation, TL and TL dynamics. Carrying 5% extra weight for a year did not significantly accelerate telomere attrition. This agrees with our earlier finding that this experiment did not affect survival or future reproduction. Apparently, great tit males were able to compensate behaviourally or physiologically for the increase in locomotion costs we imposed. We found no cross-sectional association between reproductive success and TL, but individuals with higher reproductive success (number of recruits) lost fewer telomere base pairs in the subsequent year. We used the TRF method to measure TL, which method yields a TL distribution for each sample, and the association between reproductive success and telomere loss was more pronounced in the higher percentiles of the telomere distribution, in agreement with the higher impact of ageing on longer telomeres within individuals. Individuals with longer telomeres and less telomere shortening were more likely to survive to the next breeding season, but these patterns did not reach statistical significance. Whether successful individuals are characterized by losing fewer or more base pairs from their telomeres varies between species, and we discuss aspects of ecology and social organisation that may explain this variation.</p>
Lifelong exposure to artificial light at night impacts stridulation and locomotion activity patterns in the cricket Gryllus bimaculatus
<p>This dataset contains data from a laboratory experiments described in the paper: "<span>Levy, K., Wegrzyn, Y., Efronny, R., Barnea, A., & Ayali, A. 2021 Lifelong exposure to artificial light at night impacts stridulation and locomotion activity patterns in the cricket <i>Gryllus bimaculatus.</i> Proc. R. Soc. B 20211626. <a href="https://doi.org/10.1098/rspb.2021.1626">https://doi.org/10.1098/rspb.2021.162</a></span>". </p> <p>Artificial light at night (ALAN) is increasing worldwide,with most of the world population living under light-polluted skies. Growing awareness of the harmful effects of ALAN calls for more comprehensive understanding of these effects. <span>The stridulation and locomotion patterns of adult male crickets reared under different lifelong ALAN intensities were monitored simultaneously for five consecutive days in custom-made anechoic chambers. Activity periods and acrophases were compared between the experimental groups. </span></p> <p><span>Control crickets exhibited a robust rhythm, stridulating at night and demonstrating locomotor activity during the day. In contrast, ALAN affected both the relative level and timing of the crickets' nocturnal and diurnal activity. ALAN induced free-running patterns, manifested in significant changes in the median and variance of the activity periods, and even arrhythmic behavior. The magnitude of disruption was light intensity dependent, revealing an increase in the difference between the activity periods calculated for stridulation and locomotion in the same individual. </span></p> <p><span>Our results demonstrate that ecologically-relevant ALAN intensities affect crickets' behavioral patterns, and may lead to decoupling of locomotion and stridulation behaviors at the individual level, and to loss of synchronization at the population level. </span></p>
Energetics of human locomotion near the walk-run transition speed.
<p><strong>Energetics of human locomotion near the walk-run transition speed.</strong></p> <p> </p> <p>This dataset includes the raw metabolic and mechanical data of 28 young subjects during locomotion at variable speed, walking and running on a treadmill at different speeds and gaits.</p> <p>Characteristics of the experimental group:</p> <p>- Sex: 28 Males - Age: 32. 53 (10.99SD)- height: 175.0 cm (0.008 SD)- weight: 72.96 kg (9.51 SD)</p> <p>Equipment:</p> <p>- Cosmed K5 portable metabolic analyzer- Cosmed Omnia Software v.1.6.5</p> <p>- Vicon Nexus 2.14 (Vicon Motion Systems Ltd, Oxford, UK)</p> <p>Experimental Design: The walking stroke transition speed (W-R Ts) was determined experimentally. Each subject was asked to perform 3 trials on a treadmill (GE T2100, General Electric, USA), with an escalating speed ladder protocol. The ramp was designed to start with a comfortable ride (3.0 km h-1), and to increase speed by 0.5 km.h-1 every 15 s. When the subject began to run, the ramp stopped and the speed was marked on a worksheet. The mean or modal transition speed was taken as the T of the subject. All treadmill tests were performed at the Biomechanics and Motion Analysis Research Laboratory (LIBiAM) of the University of the Republic in Paysandú (Uruguay), at a controlled temperature of 25ºC.</p> <p>The theoretical transition velocity tTs was calculated according to the Froude number equation (Alexander. 1976): v = (nFr g LL) 0.5, where v is the theoretical velocity, g is gravity, LL is the leg length, and nFr the Froude number, which was set to the constant value of 0.5, corresponding to the W-R transition (Alexander & Jayes, 1983; Alejandro, 2003; Bona et al., 2019).</p> <p>Experimental speed ramp:</p> <p>-A custom ascending and descending speed ramp was designed, focused on the transition speed and varied from (Ts = Transition Speed) Ts-20% to Ts+20%, each step with a duration of 5 s. Each ramp cycle lasted 50 s, and was repeated 5 times, for a total test time of 250 s. The trial was repeated twice.</p> <p> </p> <p><em>Mechanical Work (Mechanical cost of transport)</em></p> <p>The time course of the trajectory by <em>BcoM</em> was used to infer changes in the mechanical energies (potential and kinetics) involved. The horizontal work (<em>W<sub>h</sub></em>) was defined as the sum of the increments of the kinetic energy of the <em>BcoM</em> along the forward and mediolateral axes; the vertical work (<em>W<sub>v</sub></em>) was determined by the sum of the increments of gravitational potential energy and kinetic energy along the vertical axis; the external work (<em>W</em><sub>ext</sub> ), the mechanical work done to lift and accelerate the <em>BcoM</em>, was computed as the sum of the increments of the total mechanical energy of the <em>BcoM</em> (potential plus kinetic) (Cavagna et al., 1976; Willems et al., 1995). The internal work (<em>W</em><sub>int</sub>), the work necessary to accelerate the body segments with respects to the <em>BcoM</em>, was estimated with the methodology proposed by Cavagna & Kaneko (1977). <em>W</em><sub>int</sub> and <em>W</em><sub>ext</sub> were summed to give the total mechanical work (<em>W<sub>tot</sub></em>) (Cavagna & Kaneko, 1977; Willems et al., 1995). </p> <p>During locomotion cycles, especially in W, part of the potential energy of the <em>BcoM</em> is converted into kinetic energy, and vice versa, so that the sum of <em>W<sub>h</sub></em> and <em>W<sub>v</sub></em> is greater than the actual work done (<em>W<sub>ext</sub></em>). The difference, expressed as percentage, corresponds to the energy recovery R% (Cavagna et al., 1976), which formula is:</p> <p>R% = (<em>W</em><sub>h</sub> +<em> Wv</em> -<em> W</em><sub>ext</sub>) (<em>W</em><sub>h</sub> + <em>Wv</em>)</p> <p><em> Cost of transport (Metabolic transport cost)</em></p> <p>Oxygen uptake and respiratory quotient were measured breath-by-breath by a portable metabolimeter (K5, Cosmed, Italy). Reference resting values were measured during 5 min in orthostatic quiet position. Each trial was started when the metabolic parameters were near the reference resting values.</p> <p>The <sub>2</sub> (mlO<sub>2</sub>.kg<sup>-1</sup>.min<sup>-1</sup>) and RQ of the last 50 s of each recorded trial, corresponding to the last complete ramp, were averaged. The reference resting <sub>2</sub> was subtracted to the measured one to obtain the net oxygen uptake. VO<sub>2NET</sub> was then converted to mass-specific metabolic rate (W kg<sup>-1</sup>) using a RQ based energetic equivalent(P. E. Di Prampero et al., 2015). The C (J kg<sup>-1</sup> m<sup>-1</sup>) was finally obtained by dividing the metabolic rate for the average speed: </p> <p> </p> <p> (2)</p> <p> </p> <p><em>Apparent Mechanical Efficiency (AE)</em></p> <p>The AE was calculated as proposed by Cavagna and Kaneko, ie,</p> <p>AE = <em>W</em><sub>to</sub> C</p> <p>where <em>W</em><sub>tot</sub> is the total mechanical work and C the cost of transport (G. A. Cavagna & Kaneko, 1977).</p> <p> </p> <p><em>Data processing and calculation</em></p> <p>Image preprocessing was performed in Vicon Nexus 2.14 (Vicon Motion Systems Ltd, Oxford, UK), kinematic variable calculation performed with Python 2.7 and ProCalc 1.6 (Vicon Motion Systems Ltd, Oxford, UK), the calculation of mechanical variables was implemented in MatLab (The MathWorks, Inc., California, USA). The calculation of C was performed in Microsoft Excel (Microsoft Office 365).</p> <p> </p> <p>Note: Not all subjects performed the entire protocol. In particular, some data lack follow-up.</p> <p>Analysis of the cost of transportation:</p> <p>All participants signed an informed consent. The protocol was approved by the University's Ethics Committee (#311170-000921-19).<br> </p> <p>The legend of the dataset.</p> <p>There are 3 excel sheets where each row is associated with subjects from 1 to 28.</p> <p>Energy sheet:</p> <p>Subject: Subject</p> <p>Age</p> <p>Weigth</p> <p>Heigth(m)</p> <p>IMC</p> <p>Km x week: kilometers per week</p> <p>Background: history of injuries</p> <p>INT1 km/h: attempt 1</p> <p>INT2 km/h: attempt 2</p> <p>INT3 km/h: Attempt 3</p> <p>Average transition (km/h): average walk-race transition speed</p> <p>Froude estimated PST(m/s)</p> <p>Froude Estimated PST(km/h)</p> <p>Basal Vo2: Basal oxygen consumption in orthostasis</p> <p>VO2/kg/min: Oxygen consumption in the test</p> <p>RQ: RQ in the test</p> <p>VO2 Net VO2kg/min): VO2 net in the test</p> <p>VO2/kg/s</p> <p>J/kg/s = W/kg</p> <p>C (J/kg/m): transport cost obtained in the test</p> <p> </p> <p>Test: test performed</p> <p>Gait: type of gait that has been evaluated</p> <p>ASC/DESC: place on the ramp (ascending or descending)</p> <p>Stride: stride identification for each type of gait</p> <p>Duty Factor_tr: duty factor</p> <p>Stride Frequency_tr: stride frequency</p> <p>Stride Time_tr: stride time</p> <p>Time: time in the stride</p> <p>Speed in treadmill : speed that occurs in treadmill</p> <p>Distance: distance traveled by the stride</p> <p>Step frequency: frequency of passage</p> <p>Wext: External Work</p> <p>Rec: recovery</p> <p>Wv: trabajo vertical</p> <p>Wh: horizontal work</p> <p>WintTOT: Total internal work</p> <p> </p> <p> </p>
ScienceDex guides
Understand access before you commit
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.