Three-dimensional Coordinates Research Articles

Filter-free lens-free polarimetric incoherent digital holography

I propose an incoherent digital holography (IDH) technique in which four-dimensional (4D, three-dimensional (3D) coordinates and polarization) information is simultaneously obtained using neither polarization filters nor lenses. A filter-free lens-free self-interference incoherent interferometer for 4D imaging is designed and developed. Four-dimensional (4D) information is multiplexed in recorded phase-shifted incoherent holograms and extracted by polarization-selective phase-shifting interferometry. The validity of the proposed holography for multiplexed 4D imaging is experimentally demonstrated by the constructed filter-free lens-free self-interference IDH system and a randomly polarized light-emitting diode.

Evaluation of the Reproducibility of Auricular Subunit Markers Based on Three-Dimensional Computed Tomography.

As a facial feature, the auricle plays an important role in the integrity and aesthetics of the whole face. Auricular subunits are associated with patient satisfaction in auricular reconstruction, but there are few studies on auricular subunits. We want to evaluate the reproducibility of auricular subunits by measuring the coordinates of the marker points of auricular subunits, accordingly provide a reference for the improvement of auricular reconstruction and the aesthetics of auricular injection. Mimics 19.0 was used to carry out three-dimensional (3D) reconstruction of the computed tomography (CT) scan data of patients' brains; measure the three-dimensional coordinates of the 13 auricular subunit markers, the morphological auricle length and width, and the physiological auricle length and width; and analyze the reproducibility as well as the differences between group. Reproducibility of auricle subunit markers: There are 1124 (58.82%) high reproducibility, 580 (30.35%) moderate reproducibility, and 207 (10.83%) low reproducibility. The superior tragus notch, tragus, and antitragus had the highest reproducibility. There was no significant difference between the groups in the marking points on the helix, and there were no statistically significant differences in the measurement values of the auricles on the two sides. The physiological ear length and width and the morphological ear length of males were larger than those of females. These showed significant differences between the age groups. Most auricular subunit markers have high reproducibility. The subunits with higher reproducibility are the structures that need to be optimized during auricle reconstruction surgery or auricle injection in the future. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Enabling three-dimensional real-space analysis of ionic colloidal crystallization.

Structures of molecular crystals are identified using scattering techniques because we cannot see inside them. Micrometre-sized colloidal particles enable the real-time observation of crystallization with optical microscopy, but in practice this is still hampered by a lack of 'X-ray vision'. Here we introduce a system of index-matched fluorescently labelled colloidal particles and demonstrate the robust formation of ionic crystals in aqueous solution, with structures that can be controlled by size ratio and salt concentration. Full three-dimensional coordinates of particles are distinguished through in situ confocal microscopy, and the crystal structures are identified via comparison of their simulated scattering pattern with known atomic arrangements. Finally, we leverage our ability to look inside colloidal crystals to observe the motion of defects and crystal melting in time and space and to reveal the origin of crystal twinning. Using this platform, the path to real-time analysis of ionic colloidal crystallization is now 'crystal clear'.

Research on a visual positioning method of paddy field weeding wheels based on laser rangefinder-camera calibration

The positioning of paddy field weeding wheels is of great significance for compensating the operation deviation between the weeding wheel and the seedling row in paddy field mechanical weeding. In this paper, a visual positioning method for determining the three-dimensional coordinates of weeding wheels in the camera coordinate system is proposed. By fixing the laser rangefinder with the weeding wheel, the proposed method converts the positioning of weeding wheels into solving the relative pose relationship between the laser rangefinder and the camera. Then, based on the constraints of the laser spots on the AprilTag calibration plane, a nonlinear optimization model is established to obtain the relative pose parameters. In the experiment, two evaluation indicators were proposed to evaluate the calibration accuracy. The experimental results showed that the proposed visual positioning method of the weeding wheel can reach a mean positioning error of 2.766 mm and a mean pixel error of 7.161 pixels.

Direct measurement on stretched wire to constrain the longitudinal network in CSNS

The elongated and non-closed structure of the longitudinal control network can lead to the accumulation of measurement errors from station to station, causing distortion and preventing the attainment of high-precision longitudinal control network coordinates. This fails to meet the high-precision alignment requirements of the accelerator components. In this study, the absolute scanner AS1 and Leica AT960 laser tracker were used to directly measure the 180-m long stretched wire in the CSNS LINAC tunnel and obtain its three-dimensional coordinates. The obtained data was used to constrain the transverse of the longitudinal control network, effectively improving its accuracy. The Helmert variance component estimation method was incorporated into the data adjustment algorithm, which reasonably allocated weights between horizontal distance, azimuth angle and offset. As a result, the transverse accuracy of the control network improved from 0.151 mm without wire constraint to 0.086 mm with wire constraint. In the future, we plan to apply this method to connect the control network on both sides of the lengthy sight-hole in CSNS-II.

Cartoon copyright recognition method based on character personality action

Aiming at the problem of cartoon piracy and plagiarism, this paper proposes a method of cartoon copyright recognition based on character personality actions. This method can be used to compare the original cartoon actions with the action characteristics of pirated or copied cartoons to identify whether there is piracy or plagiarism. Firstly, an image preprocessing scheme for character extraction is designed. GrabCut interactive image segmentation algorithm was used to obtain cartoon characters, and then binarization and morphological processing were performed on the results. Secondly, a feature extraction scheme based on character profile, moving character and character pose is designed. By extracting the perimeter and area of the character contour, the length-to-width ratio of the smallest rectangle and the inclination angle of the contour, the character contour features are obtained. The three-dimensional coordinates are established by the central point position of the cartoon character in the two-dimensional image and the change of the character's zoom in and out, and the character's motion angle characteristics are calculated. By skeletonizing a character to obtain the pose characteristics, and using deburring operation to remove redundant branches, then extract the skeleton joint angle information. Finally, feature fusion is performed on the extracted features. The experimental results show that the proposed method breaks the limitation of the conventional single feature based recognition, and can better extract the character features including contour feature, motion feature and pose feature through multi-feature based extraction, so as to protect the cartoon copyright.

Banana Bunch Weight Estimation and Stalk Central Point Localization in Banana Orchards Based on RGB-D Images

Precise detection and localization are prerequisites for intelligent harvesting, while fruit size and weight estimation are key to intelligent orchard management. In commercial banana orchards, it is necessary to manage the growth and weight of banana bunches so that they can be harvested in time and prepared for transportation according to their different maturity levels. In this study, in order to reduce management costs and labor dependence, and obtain non-destructive weight estimation, we propose a method for localizing and estimating banana bunches using RGB-D images. First, the color image is detected through the YOLO-Banana neural network to obtain two-dimensional information about the banana bunches and stalks. Then, the three-dimensional coordinates of the central point of the banana stalk are calculated according to the depth information, and the banana bunch size is obtained based on the depth information of the central point. Finally, the effective pixel ratio of the banana bunch is presented, and the banana bunch weight estimation model is statistically analyzed. Thus, the weight estimation of the banana bunch is obtained through the bunch size and the effective pixel ratio. The R2 value between the estimated weight and the actual measured value is 0.8947, the RMSE is 1.4102 kg, and the average localization error of the central point of the banana stalk is 22.875 mm. The results show that the proposed method can provide bunch size and weight estimation for the intelligent management of banana orchards, along with localization information for banana-harvesting robots.

Skating techniques of ladies' world-class long-distance speed skaters to shorten curved-section time during the official 3,000 m race

This study aimed to identify the factors contributing to expedited passage through curved sections in skating by analyzing centripetal acceleration and skating motions during curving in a 3,000 m race for ladies' world-class speed skating. It included 14 elite skaters participating in the ladies' 3,000 m race held during the World Cup. The recorded area consisted of the first inner curve lane. Skaters were recorded as they passed through the measurement range at the initial, middle, and final stages of the race. Three synchronized high-speed cameras were used to record skaters from the front, back, and side. From the images obtained by the high-speed camera, 21 body endpoints and 4 blade edges were digitized at 50 Hz using specialized digitizing software. Three-dimensional coordinates of the 25 points were obtained using a panning direct linear transformation technique. The stroke-averaged centripetal acceleration and kinematic parameters were calculated based on the three-dimensional coordinates of the body during the curve-skating motion. Centripetal acceleration had a significant effect on the curved-section time in all three race stages (initial: F = 17.19, middle: F = 23.30, final: F = 16.64) and significantly decreased as the race progressed (left: F = 9.42, right: F = 8.05). Throughout the race, the right and left shanks and the body's center of mass (CM) during the stroke were raised (shank angle: left: F = 13.62, right: F = 11.02, CM height: left: F = 21.15, right: F = 21.69). The body-tilt angle for both strokes and shank-tilt angle for the right stroke were significantly correlated with centripetal acceleration in all race stages (body-tilt: left: initial: r = 0.80, middle: r = 0.75, final: r = 0.89, right: initial: r = 0.78, middle: r = 0.84, final: r = 0.67, right shank-tilt initial: r = 0.80, middle: r = 0.77, final: r = 0.63). These results suggested that to reduce the skating time through curved sections, maintaining an inward body tilt and minimizing the decrease in centripetal acceleration even in the final race stage are crucial considerations. They also suggested that when leaning the body inward and maintaining centripetal acceleration, the right shank should be leaned inward for the right stroke and the left shank should be leaned inward for the left stroke, or the left blade should be positioned farther to the right of the CM.

An Image-Based Interactive Training Method of an Upper Limb Rehabilitation Robot

Aimed at the problem of human–machine interaction between patients and robots in the process of using rehabilitation robots for rehabilitation training, this paper proposes a human–machine interactive control method based on an independently developed upper limb rehabilitation robot. In this method, the camera is used as a sensor, the human skeleton model is used to analyse the moving image, and the key points of the human body are extracted. Then, the three-dimensional coordinates of the key points of the human arm are extracted by depth estimation and spatial geometry, and then the real-time motion data are obtained, and the control instructions of the robot are generated from it to realise the real-time interactive control of the robot. This method can not only improve the adaptability of the system to individual patient differences, but also improve the robustness of the system, which is less affected by environmental changes. The experimental results show that this method can realise real-time control of the rehabilitation robot, and that the robot assists the patient to complete the action with high accuracy. The results show that this control method is effective and can be applied to the fields of robot control and robot-assisted rehabilitation training.

Accuracy enhancement and joint calibration method of multi-station triangulation network based on absolute ranging

Precision measurement methods and technologies for large-scale three-dimensional coordinates are in high demand in advanced equipment manufacturing. The multi-station triangulation network represented by the rotary-laser scanning measurement system has the advantages of having high precision, having multitask parallel measurement capability, and having a high degree of automation. It is widely used in the docking of large components, quality control of key points, and collaborative positioning of production equipment. Nevertheless, due to the limitations in the measurement principle, the positioning accuracy along the depth direction is notably lower when compared to other directions. This difference becomes more pronounced with increasing distance. This paper proposes a method to address this issue by integrating a distance measurement station into the network. A novel, to the best of our knowledge, cooperative target, coupled with a high-dynamic beam guidance mechanism, is designed to achieve fast absolute distance measurement to the target. The weighted fusion of the distance and angle observations effectively enhances the measurement accuracy while preserving the advantages of highly automated measurement. Additionally, we introduce a joint calibration method for extrinsic parameters of multi-type stations. High-precision absolute distances are utilized to establish optical scale bars, complemented by the incorporation of physical scale bars, thereby obviating the necessity for using external reference instruments such as laser trackers. Finally, a series of experimental verifications demonstrate the effectiveness of calibration and measurement methods. The root mean square error of all measured points drop to 42.6% of that the triangulation method measures.

An innovative binocular vision-based method for displacement measurement in membrane structures

Abstract This article presents a new binocular vision method for accurate deformation measurements of flexible membrane structures. Using enhanced marker points on the membrane, the method identifies areas for displacement measurements, filtering out unwanted image features with scale-invariant feature transform and threshold correlation. It integrates Canny edge recognition and quadratic weighted averaging for precise positioning of measurement points. By comparing reference images and utilizing the principle of minimum distance between matching points, the method achieves fast matching and determines the three-dimensional coordinates of marker points, enhancing measurement efficiency and robustness. This approach has been empirically tested on membrane structures, providing new insights. The results highlight that our novel algorithm can achieve high-precision measurements down to millimeters, and its accuracy increases with the actual displacement of the membrane structure. Notably, this groundbreaking measurement method remains unaffected by the form of the membrane surface, addressing a long-standing challenge in the field.

Carrollian Amplitudes from Strings

Carrollian holography is supposed to describe gravity in four-dimensional asymptotically flat space-time by the three-dimensional Carrollian CFT living at null infinity. We transform superstring scattering amplitudes into the correlation functions of primary fields of Carrollian CFT depending on the three-dimensional coordinates of the celestial sphere and a retarded time coordinate. The power series in the inverse string tension is converted to a whole tower of both UV and IR finite descendants of the underlying field-theoretical Carrollian amplitude. We focus on four-point amplitudes involving gauge bosons and gravitons in type I open superstring theory and in closed heterotic superstring theory at the tree-level. We also discuss the limit of infinite retarded time coordinates, where the string world-sheet becomes celestial.

Application of a novel deep learning-based 3D videography workflow to bat flight.

Studying the detailed biomechanics of flying animals requires accurate three-dimensional coordinates for key anatomical landmarks. Traditionally, this relies on manually digitizing animal videos, a labor-intensive task that scales poorly with increasing framerates and numbers of cameras. Here, we present a workflow that combines deep learning-powered automatic digitization with filtering and correction of mislabeled points using quality metrics from deep learning and 3D reconstruction. We tested our workflow using a particularly challenging scenario: bat flight. First, we documented four bats flying steadily in a 2 m3 wind tunnel test section. Wing kinematic parameters resulting from manually digitizing bats with markers applied to anatomical landmarks were not significantly different from those resulting from applying our workflow to the same bats without markers for five out of six parameters. Second, we compared coordinates from manual digitization against those yielded via our workflow for bats flying freely in a 344 m3 enclosure. Average distance between coordinates from our workflow and those from manual digitization was less than a millimeter larger than the average human-to-human coordinate distance. The improved efficiency of our workflow has the potential to increase the scalability of studies on animal flight biomechanics.

Verification Test and Research on Fitting Curve of Shear and Tensile Synthesis Method

Based on the recommended curve of concrete compressive strength tested by shear and tensile composite method, this paper combined with concrete specimens of different strength grades, ages and batches produced by several test verification units, adopted the in vitro shear and tensile test method introduced by the regulations, and used basically the same test equipment to collect the single shear and tensile strength and the compressive strength of cube specimens under the same conditions. Each batch was divided into 15 or 30 specimens. Through the collected test data, the conversion strength of the single shear, pull-out and shear tensile composite methods were calculated respectively. The relative error of a single specimen was calculated based on the average strength of each batch of concrete. The error distribution types and errors of each company were systematically studied, and finally the relative error data of each company were summarized, and the probability distribution parameters of the error of the Shear and tensile synthesis method were understood through probability distribution analysis, and the relationship between the error of the shear and tensile synthesis method, the single shear method and the pull method, and the influence degree on the conversion strength of the shear and tensile synthesis method were shown by using three-dimensional coordinates. Using the test data of "shear and tensile synthesis method", "single shear method" and "pull-out method", the scatter plot is drawn, and the error size is compared to explore the direction of further improving the detection accuracy of "shear and tensile synthesis method".

Sex-related Differences in the Orbital Area of Bulgarians – a 3D Laser Scanning

The present study aimed to provide up-to-date information on normal sex-related dimensions of the orbital region in young Bulgarian adults, using a 3D laser scanner. The three-dimensional coordinates of several soft-tissue landmarks on the orbits and face were obtained using a hand-held laser scanner (FastSCAN Cobra, Polhemus Inc, Colchester VT) in 95 healthy individuals (46 males and 49 females) of Bulgarian origin aged 21–30 years. From the landmarks outer and intercanthal widths, length of eye fissure, and height of the orbit were calculated and averaged for sex. The data were analyzed using descriptive statistics and paired t-test. Statistically significant difference was found in outer canthal width, both eyes fissure length, and orbital height between sexes. The differences in the inner canthal width did not reach statistical significance (p > 0.05). The data of the present study could serve as a quantitative characteristic of human orbital morphology. Forensic applications, evaluations of traumas, craniofacial alterations, and facial reconstruction may also benefit from the data.

New computational method for calculating of water droplet–clay contact angles: Based on molecular dynamics

The measurement of the water contact angle (θ) on the surface of clay minerals poses a significant challenge due to their microscopic particle sizes ranging from micrometers to nanometers and their extensive specific surface areas. We introduce an advanced computational framework based on molecular dynamics simulations. This framework leverages the coordination number (CN) differences of the water molecules and effectively eliminates the gaseous water molecules in the droplet equilibrium system. Additionally, our framework uses an alpha-shaped probe ball to accurately determine the three-dimensional (3D) coordinates of the droplet interface and utilizes a feed-forward neural network (FFNN) to optimize the objective function of the 3D-interface; this ensures highly accurate characterization of the interface contour and an accurate computation of θ. Our approach exhibits outstanding performance in typical clay mineral surface-water wetting systems; it significantly overcomes the limitations of the transformed cylindrical coordinate system algorithm and accurately captures the wettability variations under complex environmental conditions. This new θ computational framework provides crucial assistance for the in-depth exploration of the wettability characteristics of clay minerals in complex environments.

An overview of Graph Convolutional Networks in skeleton-based action recognition

The field of research is currently focused on human activity recognition. Hence, numerous pertinent literature reviews have expounded upon the multifaceted nature of data, the process of selecting feature vectors, and the advantages and disadvantages of classification networks. Graph Convolutional Networks (GCNs) have demonstrated significant efficacy in the domain of human action recognition. In recent years, with the rapid development of 3D skeleton data collection, a plethora of studies in action recognition based on skeleton data have emerged. Skeleton data consists of three-dimensional coordinates of multiple spatiotemporal skeletal joints, making it an effective representation of kinematics. It can be easily acquired through low-cost depth sensors and also directly extracted from two-dimensional images using video-based pose estimation algorithms, attracting widespread attention. As relational networks continue to evolve, GCNs have been applied to various fields, including human action recognition. GCNs have demonstrated significant advantages in feature extraction from skeleton data. However, using GCNs alone may have various limitations. Therefore, in recent years, many enhancement measures for GCNs have emerged. This review aims to summarize the research achievements of Graph Convolutional Network improvements in the field of human action recognition in recent years. It intends to assist future researchers in quickly organizing their research ideas, facilitating the generation of new results.

Abstract 6272: Loss of SIRT6 diverts TGF-β signaling to promote liver cancer

Abstract Background: In the US, ~35% of individuals on the waitlist for a liver transplant who had hepatocellular cancer (HCC) also had metabolic dysfunction-associated steatohepatitis (MASH). Yet, key signaling mechanisms controlling cellular transformation in this obesity-driven HCC remain only partially understood. SIRT6 is NAD+-dependent protein deacetylases that limits the activity of the lipogenic transcription factors SREBP1/2. Reduced SIRT6 is associated with human fatty liver and cancer. However, SIRT6 also limits liver fibrosis by inhibiting TGF-β signaling through the deacetylation of SMAD2 and SMAD3. We found that Smad3 driven TGF-β signaling is modulated by βII-Spectrin (encoded by SPTBN1), and that a hot mutation in HCC- D1089Y encompasses the SPTBN1-SMAD3 binding site (Gastro 2018; 154:195-210). In stressed hepatocytes, βII-Spectrin promotes lipogenesis through interactions between caspase-cleaved forms of both SREBP1 and βII-Spectrin (Sci Transl Med 2021;13:624). Liver-specific knockout of βII-Spectrin (LSKO) blocks fatty liver and HCC. Here we explored the extent of βII-spectrin-D1089Y regulation of SIRT6 expression through SMAD3, and the combined roles of SIRT6 and SPTBN1 in human HCC. Methods: We generated a SPTBN1-D1089Y mutant mouse and examined SIRT6 in the SPTBN1-D1089Y mutant mouse liver tissues and MEFs. TGF-β/Smad3 pathway activity was analyzed in SPTBN1-D1089Y mutant MEFs via western blot and RNA-seq. SIRT6 expression was examined in mouse MAFLD/MASH (GSE156059). Structure-based molecular docking simulations using three-dimensional structural coordinates of human SIRT6 (ID: Q8N6T7) and β2SP (ID: Q01082) from the AlphaFold database, followed by interactions between SIRT6 and SPTBN1. Results: SIRT6 levels are decreased in SPTBN1-D1089Y mutant liver cancer cell line and mouse liver tissues. TGF-β/SMAD3 pathway activity was altered in SPTBN1-D1089Y mutant MEF cells with decreased phospho-SMAD3 levels. The structural model predicted specific interactions between human SPTBN1 and SIRT6. Overexpression of Flag-SIRT6 reduced βII-Spectrin acetylation in HepG2 cells. TGF-β induced SMAD3, βII-Spectrin coimmunoprecipitation with SIRT6. SIRT6 knockdown increases nSREBP1, SCD1 (encoded by a nSREBP1 target gene), and βII-Spectrin in HepG2 cells. SIRT6 RNA expression is significantly decreased in liver macrophages from mice with NAFLD/NASH. Conclusions: Our data indicated a SMAD dependent as well as a SMAD3 independent role of SPTBN1 in regulating SIRT6. βII-spectrin-D1089Y together with SIRT6 deficiency may increase the susceptibility to MASH/HCC via regulating the crosstalk between macrophage and hepatocytes or regulating MASH and HCC. Citation Format: Kazufumi Ohshiro, Xiyan Xiang, Xiaochun Yang, Krishanu Bhowmick, Mohammad I. Hassan, Taj Mohammad, Lopa Mishra. Loss of SIRT6 diverts TGF-β signaling to promote liver cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6272.

Innovative K-Means based machine learning method for determination of non-uniform image coordinate system in panoramic imaging: a case study with Ladybug2 camera.

Currently, the practical implementations of panoramic cameras range from vehicle navigation to space studies due to their 360-degree imaging capability in particular. In this variety of uses, it is possible to calculate three-dimensional coordinates from a panoramic image, especially using the Direct Linear Transformation (DLT) method. There are several types of omnidirectional cameras which can be classified mainly as central and non-central cameras for 360-degree imaging. The central omnidirectional cameras are those which satisfy the single-viewpoint characteristic. Multi-camera systems are usually developed for applications for which two-image stereo vision is not flexible enough to capture the environment surrounding a moving platform. Although the technology based on multi-view geometry is inexpensive, accessible, and highly customizable, multi-camera panoramic imaging systems pose a difficulty in obtaining a single projection center for the cameras. In this study, not only a defining method of the non-uniform image coordinate system is suggested by means of the K-Means algorithm for a single panoramic image, captured with a Ladybug2 panoramic camera in the panoramic calibration room but also the use of an elliptical panoramic projection coordinate system definition by Singular Value Decomposition (SVD) method in panoramic view. The results of the suggested method have been compared with the DLT algorithm for a single panoramic image which defined a conventional photogrammetric image coordinate system.

Muscle fibre size and myonuclear positioning in trained and aged humans.

Changes in myonuclear architecture and positioning are associated with exercise adaptations and ageing. However, data on the positioning and number of myonuclei following exercise are inconsistent. Additionally, whether myonuclear domains (MNDs; i.e., the theoretical volume of cytoplasm within which a myonucleus is responsible for transcribing DNA) and myonuclear positioning are altered with age remains unclear. The aim of this investigation was to investigate relationships between age and activity status and myonuclear domains and positioning. Vastus lateralis muscle biopsies from younger endurance-trained (YT) and older endurance-trained (OT) individuals were compared with age-matched untrained counterparts (YU and OU; OU samples were acquired during surgical operation). Serial, optical z-slices were acquired throughout isolated muscle fibres and analysed to give three-dimensional coordinates for myonuclei and muscle fibre dimensions. The mean cross-sectional area (CSA) of muscle fibres from OU individuals was 33%-53% smaller compared with the other groups. The number of nuclei relative to fibre CSA was 90% greater in OU compared with YU muscle fibres. Additionally, scaling of MND volume with fibre size was altered in older untrained individuals. The myonuclear arrangement, in contrast, was similar across groups. Fibre CSA and most myonuclear parameters were significantly associated with age in untrained individuals, but not in trained individuals. These data indicate that regular endurance exercise throughout the lifespan might better preserve the size of muscle fibres in older age and maintain the relationship between fibre size and MND volumes. Inactivity, however, might result in reduced muscle fibre size and altered myonuclear parameters.