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opencc-by-4.0Apr 2020View details →

3D models for the ligaments of the Interosseous Membrane of 5 forearms with their biomechanical simulation scenes

This dataset contains a group of 15 ligaments corresponding to the five specimens (3 per forearm) modeled as 3D tetrahedral meshes. In addition, 15 simulation scenes written in SOFA framework (INRIA) are supplied to implement stretch experiments. Details about the study are provided in the technical report.

opencc-by-4.0Apr 2020View details →

Seagrass biomechanics and flow-seagrass interactions data

This data package provides post-processed data used in the manuscript “Temporal variability in biomechanics and within-plant heterogeneity regulate flow-seagrass interactions”authored by Davide Vettori and Timothy I. Marjoribanks. The data package contains data obtained from direct measurement of maximum quantum yield of fluorescence, morphological characteristics and mechanical properties of the seagrass species Zostera marina collected in the Rodsand lagoon (DK). Further, data of seagrass drag force, biomass height, and deflected height computed by using a numerical model of flow-seagrass interactions are provided. The numerical model was parameterized using data from direct measurements.

opencc-by-4.0Nov 2020View details →

Reinforcement Learning Control of a Biomechanical Model of the Upper Extremity

This dataset contains evaluation data of the paper "Reinforcement Learning Control of a Biomechanical Model of the Upper Extremity". Motivation We address the question whether the assumptions of signal-dependent and constant motor noise in a full skeletal model of the human upper body, together with the objective of movement time minimization, can predict reaching movements. For evaluation of the learned policy, two tasks are defined in the paper: a Fitts' Law type task and an elliptic via-point task. General description of the dataset <ul> <li>Fitts' Law Type Task <ul> <li>This dataset incorporates detailed information of all 6500 synthesized movements generated in the Fitts' Law type task (following the ISO 9241-9 standard).</li> <li> For each of the 10 task conditions differing in distance between targets ("dist<xxx>" in filename) and ID ('ID<xxx>' in filename), there are two .csv-files: - one with detailed trajectory information on a sample-to-sample basis ("ISO_SAMPLES" in filename), and - one with aggregated movement information on an episode basis ("ISO_METRICS" in filename). </li> <li> In addition, for each task condition and each of the 13 movement directions in the Fitts' Law type task, we include 6 figures: Position, Velocity, and Acceleration Profiles, as well as 3D movement path, Phasespace, and Hooke plots. Apart from the 3D plots, all figures use centroid projections of the respective trajectory onto the vector between initial and target position. The first integer in the file name denotes the movement direction number, starting with "0" for movements between the targets 1 and 2, "1" for movements between the targets 2 and 3 etc. The file "6_distance0.35_ID2_policy2100000_phasespace.png", e.g., shows velocity plotted againt position for all 50 movements between the targets 7 and 8 in the task condition with ID 2 and 35cm diameter of the target circle (see Fig 2 in Paper). </li> </ul> </li> <li> Elliptic Task <ul> <li> This dataset also contains two CSV-files with data of the trajectory generated by the final policy in the elliptic task: - one with detailed trajectory information on a sample-to-sample basis ("ELLIPSE_SAMPLES" in filename), and - one with aggregated movement information on an episode basis, where a new episode starts whenever the target on the ellipse given to the policy switches ("ELLIPSE_METRICS" in filename). </li> </ul> </li> </ul> Description of the .csv-files <ul> <li>SAMPLES Files <ul> <li>"time": time after reaching the initial target (target 1 in Fig 2) for the first time (in seconds)</li> <li>"elv_angle_pos" - "flexion_pos": angle of respective independent DOF (in radians) *</li> <li>"elv_angle_vel" - "flexion_vel": angular velocity of respective independent DOF (in radians/s) *</li> <li>"end-effector_xpos_x" - "end-effector_xpos_z": 3D position of end-effector in global coordinates (in meters) *</li> <li>"target_xpos_x" - "target_xpos_z": 3D position of target sphere in global coordinates (in meters) *</li> <li>"end-effector_xvelp_x" - "end-effector_xvelp_z": positional velocities of end-effector (in meters/s) *</li> <li>"target_xvelp_x" - "target_xvelp_z": positional velocities of target sphere (in meters/s) *</li> <li>"accsensor_end-effector_x" - "accsensor_end-effector_z": positional acceleration of end-effector (in meters/s^2) *</li> <li>"E_elv_angle" - "E_flexion": activation of respective independent DOF *</li> <li>"E_elv_angle_derivative" - "E_flexion_derivative": derivative of activation of respective independent DOF *</li> <li>"difference_vec_x" - "difference_vec_z": vector between the end-effector attached to the index finger and the target, pointing towards the target (in meters) *</li> <li>"centroid_vel_projection": projection of end-effector velocity towards target (in meters/s) *</li> <li>"target_width": radius (!) of the target sphere (in meters) *</li> <li>"A_elv_angle" - "A_flexion": action vector</li> <li>"thorax_tx_frc" - "wrist_hand_r3_frc": net external force at respective DOF (including dependent and fixed DOFs such as "thorax_tx" (thorax translation))</li> <li>"reward": reward obtained in this step</li> <li>"step_type": 0=initial step of episode, 1=intermediate step of episode, 2=terminal step of episode</li> <li>"target_switch": whether the target switched in this step</li> <li>"discount": internal value of tf-agents (does not correspond to the discount factor gamma, which is additionally applied!)</li> <li>"thorax_tx_pos" - "wrist_hand_r3_pos": angle of respective dependent DOF (in radians)</li> <li>"thorax_tx_vel" - "wrist_hand_r3_vel": angular velocity of respective dependent DOF (in radians)</li> </ul> </li> <li>METRICS Files <ul> <li>Index: episode ID</li> <li>"Init_X" - "Init_Z": initial position in global coordinates (in meters)</li> <li>"Init_X" - "Init_Z": target position in global coordinates (in meters)</li> <li>"Init_Distance": distance between last target (i.e., desired initial position) and current target (in meters)</li> <li>"Target_Width_Diameter": target width diameter (in meters)</li> <li>"Movement_ID": Index of Difficulty of current movement (using the Shannon Formulation) (in bits)</li> <li>"target_accuracy": 1 - (<remaining distance to target center at the end of the episode>/<target radius>) if end-effector is inside target, 0 else</li> <li>"movement_time": duration of the episode (in seconds)</li> <li>"episode_successful": whether episode terminated successfully within the permitted 1.5 seconds</li> <li>"dist2target": remaining distance to target center at the end of the episode (in meters)</li> </ul> </li> </ul> ------------------------------------- * included in state space

opencc-by-4.0Jun 2020View details →

Data of physiology, biomechanics and hydrodynamics of a freshwater macrophyte

This data package provides post-processed data used in the manuscript “Linking plant stress and hydrodynamics: evidence from freshwater macrophytes” submitted to Water Resources Research. The data package contains data obtained from direct measurements of maximum quantum yield of photosystem II, morphological characteristics and flexural rigidity of the freshwater macrophyte Potamogeton natans. Further, data of flow velocity, drag force, plant deflected height and plant centroid height obtained from flume experiments carried out with samples of P. natans are reported.

opencc-by-4.0Jan 2024View details →

FORCe step-down-and-pivot biomechanical dataset

Copyright (c) 2023 by La Trobe University  This work is licensed under CC BY 4.0. ---------------------------------------- Correspondence: Prasanna Sritharan, p.sritharan@latrobe.edu.au Biomechanical data for the step-down-and-pivot task underaken as part of the FORCe project at the La Trobe Sports & Exercise Medicine Research Centre, La Trobe University, Victoria, Australia. <ul> <li>Experimental joint angles and joint moment data for the step-down-and-pivot task. </li> <li>Relevant participant demographic data is provided.</li> <li>All valid participants and trials provided.</li> <li>All participants are fully de-identified.</li> <li>Joint angles are provided in degrees, and joint moments normalised to % of body weight * height.</li> <li>All trials resamples to 101 time steps, with a time vector provided.</li> </ul> Any use of this data must cite the following published work: Crossley K, Pandy MG, Majumdar S, Smith AJ, Semciw AI, Kemp JL, Heerey JJ, King MG, Lawrenson PR, Lin YC, Souza RB. Femoroacetabular impingement and hip OsteoaRthritis Cohort (FORCe): protocol for a prospective study. Journal of Physiotherapy. 2017 Jan 1. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jphys.2017.10.004" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jphys.2017.10.004</a>

opencc-zeroFeb 2024View details →

Data for: Biomechanical adaptations enable phoretic mite species to occupy distinct spatial niches on host burying beetles

Niche theory predicts that ecologically similar species coexist by minimising interspecific competition through niche partitioning. Therefore understanding the mechanisms of niche partitioning is essential for predicting interactions and coexistence between competing organisms. Here we study two phoretic mite species, Poecilochirus carabi, and Macrocheles nataliae that coexist on the same host-burying beetle Nicrophorus vespilloides and use it to 'hitchhike' between reproductive sites. Field observations revealed clear spatial partitioning between species in distinct host body parts. P. carabi preferred the ventral side of the thorax, whereas M. nataliae were exclusively found ventrally at the hairy base of the abdomen. Experimental manipulations of mite density showed that each species preferred these body parts, largely regardless of the density of the other mite species on the host beetle. Force measurements indicated that this spatial distribution is mediated by biomechanical adaptations, because each mite species required more force to be removed from their preferred location on the beetle. While P. carabi attached with large adhesive pads to the smooth thorax cuticle, M. nataliae gripped abdominal setae with their chelicerae. Our results show that specialist biomechanical adaptations for attachment can mediate spatial niche partitioning among species sharing the same host.

opencc-by-4.0Jun 2023View details →

I-Seed_DS1 – CHARACTERIZATION OF BIOMECHANICS AND MATERIALS OF NATURAL SEEDS MODEL

Dataset I-Seed_DS1 focus on bioengineering investigations of plant seed models, to define useful specifications for the design of the artificial systems in terms of multi-functional materials and morphological computation. Task 3.1. Erodium cicutarium seeds: from natural features to robotic specifics. Task 3.2. Samara seeds: from natural features to robotic specifics

opencc-zeroOct 2021View details →

Supplementary datasets, data analysis code, and R tutorials for: Phylogenetic analysis of adaptation in comparative physiology and biomechanics: overview and a case study of thermal physiology in treefrogs

Comparative phylogenetic studies of adaptation are uncommon in biomechanics and physiology. Such studies require collecting data from many species, a challenge when data collection is experimentally intensive. Moreover, researchers struggle to employ the most biologically appropriate phylogenetic tools for identifying adaptive evolution. Here, we detail an established but greatly underutilized phylogenetic comparative framework—the Ornstein-Uhlenbeck process—that explicitly models long-term adaptation. We discuss challenges in implementing and interpreting the model, and we outline potential solutions. We demonstrate use of the model through studying the evolution of thermal physiology in treefrogs. Frogs of the family Hylidae have twice colonized the temperate zone from the tropics, and such colonization likely involved a fundamental change in physiology due to colder and more seasonal temperatures. However, which traits changed to allow colonization is unclear. We measured cold-temperature tolerance and characterized thermal performance curves in jumping for twelve species of treefrogs distributed from the Neotropics to temperate North America. We then conducted phylogenetic comparative analyses to examine how tolerances and performance curves evolved and to test whether that evolution was adaptive. We found that tolerance to low temperatures increased with the transition to the temperate zone. In contrast, jumping well at colder temperatures was unrelated to biogeography and thus did not adapt during dispersal. Overall, our paper shows how comparative phylogenetic methods can be leveraged in biomechanics and physiology to test the evolutionary drivers of variation among species.

opencc-by-4.0Feb 2022View details →

Ultra high-resolution biomechanics suggest that substructures within insect mechanosensors affect their sensitivity

Accessible data for the Manuscript "Ultra high-resolution biomechanics suggest that substructures within insect mechanosensors decisively affect their sensitivity".

opencc-by-4.0Jul 2014View details →

Fig. 2 in Variability Of Structural And Biomechanical Parameters Of Pelophylax Esculentus (Amphibia, Anura) Limb Bones

Fig. 2. Coefficients of variation (CV) of morphometric and biomechanical parameters of P. esculentus limbs' long bones (1 — humeral; 2 — forearm bone; 3 — femoral; 4 — crural bone).

opencc-by-4.0Jul 2014View details →

Fig. 1 in Variability Of Structural And Biomechanical Parameters Of Pelophylax Esculentus (Amphibia, Anura) Limb Bones

Fig. 1. Shaft's cross-sectional shape of P. esculentus long bones: А — humeral; B — forearm; C — femoral; D — crural (d — dorsal mark; m — medial mark; Imax — maximum moment of inertia axis; Imin — minimum moment of inertia axis).

opencc-zeroJun 2022View details →

Dual spring force couples yield multifunctionality and ultrafast, precision rotation in tiny biomechanical systems

Small organisms use propulsive springs rather than muscles to repeatedly actuate high acceleration movements, even when constrained to tiny displacements and limited by inertial forces. Through integration of a large kinematic dataset, measurements of elastic recoil, energetic math modeling, and dynamic math modeling, we tested how trap-jaw ants (Odontomachus brunneus) utilize multiple elastic structures to develop ultrafast and precise mandible rotations at small scales. We found that O. brunneus develops torque on each mandible using an intriguing configuration of two springs: their elastic head capsule recoils to push and the recoiling muscle-apodeme unit tugs on each mandible. Mandibles achieved precise, planar, circular trajectories up to 49,100 radians/sec (470,000 rpm) when powered by spring propulsion. Once spring propulsion ended, the mandibles moved with unconstrained and oscillatory rotation. We term this mechanism "dual spring force couple" meaning that two springs deliver energy at two locations to develop torque. Dynamic modeling revealed that dual spring force couples reduce the need for joint constraints and thereby reduce dissipative joint losses, which is essential to the repeated use of ultrafast, small systems. Dual spring force couples enable multifunctionality: trap-jaw ants use the same mechanical system to produce ultrafast, planar strikes driven by propulsive springs and for generating slow, multi-degree of freedom mandible manipulations using muscles, rather than springs, to directly actuate the movement. Dual spring force couples are found in other systems and are likely widespread in biology. These principles can be incorporated into microrobotics to improve multifunctionality, precision, and longevity of ultrafast systems.

opencc-zeroJun 2024View details →

Data from: Biomechanical properties of non-flight vibrations produced by bees

Bees use thoracic vibrations produced by their indirect flight muscles for powering wingbeats in flight, but also during mating, pollination, defence, and nest building. Previous work on non-flight vibrations has mostly focused on acoustic (airborne vibrations) and spectral properties (frequency domain). However, mechanical properties such as the vibration's acceleration amplitude are important in some behaviours, e.g., during buzz pollination, where higher amplitude vibrations remove more pollen from flowers. Bee vibrations have been studied in only a handful of species and we know very little about how they vary among species. Here, we conduct the largest survey to date of the biomechanical properties of non-flight bee buzzes. We focus on defence buzzes as they can be induced experimentally and provide a common currency to compare among taxa. We analysed 15,000 buzzes produced by 306 individuals in 65 species and six families from Mexico, Scotland, and Australia. We found a strong association between body size and the acceleration amplitude of bee buzzes. Comparison of genera that buzz-pollinate and those that do not suggests that buzz-pollinating bees produce vibrations with higher acceleration amplitude. We found no relationship between bee size and the fundamental frequency of defence buzzes. Although our results suggest that body size is a major determinant of the amplitude of non-flight vibrations, we also observed considerable variation in vibration properties among bees of equivalent size and even within individuals. Both morphology and behaviour thus affect the biomechanical properties of non-flight buzzes.

Fig. 4 in Biomechanical analysis and new trophic hypothesis for Riojasuchus tenuisceps, a bizarre-snouted Late Triassic pseudosuchian from Argentina

Fig. 4. Biomechanical test of external force in the ornithosuchid pseudosuchian Riojasuchus tenuisceps Bonaparte, 1969. Lateral load force (A), tractive load force (B), and twist force (C). External force configuration for each test. The red arrows indicate the direction of the applied forces and the pink cylinder represents the bitten mass (A1–C1). For each test, we present the result of finite element analysis on anterolateral view of the skull (A2–C2), sections of the second and third right teeth of the dentary (A3–C3), and sections of right premaxillary teeth (A4–C4). Abbreviations: mAMP, musculus adductor mandibulae posterior; mAMEs/m/p, musculus adductor mandibulae externus superficialis/medialis/profundus; mPST, musculus pseudotemporalis; mIM, musculus intramandibularis; mPTv/d, musculus pterygoideus ventralis/dorsalis; mDM, musculus depressor mandibulae. The colorimetric scale shows the smooth effective stress distribution in the structure.

Fig. 3 in Biomechanical analysis and new trophic hypothesis for Riojasuchus tenuisceps, a bizarre-snouted Late Triassic pseudosuchian from Argentina

Fig. 3. Biomechanical test of bite force in the ornithosuchid pseudosuchian Riojasuchus tenuisceps Bonaparte, 1969. Skull model in lateral view (A) indicating the position of the bite force measurements (B–E), showing the respective results of finite element analysis for each bite force test. Abbreviations: mAMP, musculus adductor mandibulae posterior; mAMEs/m/p, musculus adductor mandibulae externus superficialis/medialis/profundus; mPST, musculus pseudotemporalis; mIM, musculus intramandibularis; mPTv/d, musculus pterygoideus ventralis/dorsalis; mDM, musculus depressor mandibulae. The colorimetric scale shows the smooth effective stress distribution in the structure.

Fig. 2 in Biomechanical analysis and new trophic hypothesis for Riojasuchus tenuisceps, a bizarre-snouted Late Triassic pseudosuchian from Argentina

Fig. 2. Analysis of mandibular occlusion in the ornithosuchid pseudosuchian Riojasuchus tenuisceps Bonaparte, 1969. A. Skull in lateral view (A1), marking the anterior (blue frame) and posterior (green frame) jaw; also indicated the closing angles for each section of the jaw. The bars show the tendency line of cranial teeth apex (yellow bar), the tendency line of mandibles teeth apex (orange bar), and middle of angle between both (pink bar); the light blue circle represent the captured prey. Arc formed by the anterior dentary teeth during the closing jaw (A2). B. Skulls comparison between Riojasuchus tenuisceps and living crocodiles, with teeth apexes plotted in dorsal view. The teeth apexes plot shows the separation between the cranial and mandibular dental rows on the same side. The blue and red dots correspond to the cranium and mandible teeth apexes, respectively. B not to scale.

Fig. 1 in Biomechanical analysis and new trophic hypothesis for Riojasuchus tenuisceps, a bizarre-snouted Late Triassic pseudosuchian from Argentina

Fig. 1. Skull of the ornithosuchid pseudosuchian Riojasuchus tenuisceps Bonaparte, 1969, from Los Colorados Formation, Late Triassic, La Rioja, Argentina. Photographs of the skull of PVL 3827 (A) and PVL 3828 (B). Reconstructions (C). Three-dimensional skull reconstruction (C1), with muscular reconstruction (C2), and model of muscular action bars (C3). Abbreviations: mAMP, musculus adductor mandibulae posterior; mA- MEs/m/p, musculus adductor mandibulae externus superficialis/medialis/ profundus; mPST, musculus pseudotemporalis; mIM, musculus intramandibularis; mPTv/d, musculus pterygoideus ventralis/dorsalis; mDM, musculus depressor mandibulae. The 3D views of reconstructions are available in the SOM (Supplementary Online Material available at http://app.pan.pl/ SOM/app68-Taborda_etal_SOM.pdf).