Shape Space Research Articles

Shaping spaces: governance and climate-related mobility in Ethiopia

ABSTRACT Migration is often approached as being a consequence of climate change with a significant degree of causality invoked. The role of government and other institutions, particularly in the local space where households take decisions as they face the effects of slow-onset climate change tends not to be studied. The paper seeks to address the role of these institutions in the local space in which households operate and how they contribute to shaping the context for households’ agency with regard to their mobility practices. The paper draws on data collected in Ethiopia as part of a research programme on climate-related mobility. 1 It argues for a more nuanced approach to mobility practices in which the role of government and other institutions, formal and informal, can point to ways for understanding migration and mobility generally as not being a problem, but as a practice to be managed and incorporated into policies for climate change adaptation. In so doing, the paper challenges the approach of many international organizations and NGOs for whom climate change is seen as the cause of migration.

BOSS: Bones, organs and skin shape model

A virtual anatomical model of a patient can be a valuable tool for enhancing clinical tasks such as workflow automation, patient-specific X-ray dose optimization, markerless tracking, positioning, and navigation assistance in image-guided interventions. For these tasks, it is highly desirable that the patient’s surface and internal organs are of high quality for any pose and shape estimate. At present, the majority of statistical shape models (SSMs) are restricted to a small number of organs or bones or do not adequately represent the general population. To address this, we propose a deformable human shape and pose model that combines skin, internal organs, and bones, learned from CT images. By modeling the statistical variations in a pose-normalized space using probabilistic PCA while also preserving joint kinematics, our approach offers a holistic representation of the body that can be beneficial for automation in various medical applications. In an interventional setup, our model could, for example, facilitate automatic system/patient positioning, organ-specific iso-centering, automated collimation or collision prediction. We assessed our model’s performance on a registered dataset, utilizing the unified shape space, and noted an average error of 3.6 mm for bones and 8.8 mm for organs. By utilizing solely skin surface data or patient metadata like height and weight, we find that the overall combined error for bone-organ measurement is 8.68 mm and 8.11 mm, respectively. To further verify our findings, we conducted additional tests on publicly available datasets with multi-part segmentations, which confirmed the effectiveness of our model. In the diverse TotalSegmentator dataset, the errors for bones and organs are observed to be 5.10mm and 8.72mm, respectively. Our work shows that anatomically parameterized statistical shape models can be created accurately and in a computationally efficient manner. The proposed approach enables the construction of shape models that can be directly integrated into to various medical applications.

A Gaussian kernel for Kendall’s space of [formula omitted]-D shapes

In this paper, we develop an approach to exploit kernel methods with data lying on the m-D Kendall shape space. When data arise in a finite-dimensional curved Riemannian manifold, as in this case, the usual Euclidean computer vision and machine learning algorithms must be treated carefully. A good approach is to use positive definite kernels on manifolds to embed the manifold with its corresponding metric in a high-dimensional reproducing kernel Hilbert space, where it is possible to utilize algorithms developed for linear spaces. Different Gaussian kernels can be found in the literature on the 2-D Kendall shape space to perform this embedding. The main novelty of this work is to provide a Gaussian kernel for the m-D Kendall shape space. This new Kernel coincides in the case m=2 with the Gaussian kernels most widely used in the Kendall planar shape space and allows to define an embedding of the m-D Kendall shape space into a reproducible kernel Hilbert space. As far as we know, the complexity of the m-D Kendall shape space has meant that this embedding has not been addressed in the literature until now. This methodology will be tested on a machine learning problem with a simulated and a real data set.

Preserving the positivity of the deformation gradient determinant in intergrid interpolation by combining RBFs and SVD: Application to cardiac electromechanics

The accurate, robust and efficient transfer of the deformation gradient tensor between meshes of different resolution is crucial in cardiac electromechanics simulations. This paper presents a novel method that combines rescaled localized Radial Basis Function (RBF) interpolation with Singular Value Decomposition (SVD) to preserve the positivity of the determinant of the deformation gradient tensor. The method involves decomposing the evaluations of the tensor at the quadrature nodes of the source mesh into rotation matrices and diagonal matrices of singular values; computing the RBF interpolation of the quaternion representation of rotation matrices and the singular value logarithms; reassembling the deformation gradient tensors at quadrature nodes of the destination mesh, to be used in the assembly of the electrophysiology model equations. The proposed method overcomes limitations of existing interpolation methods, including nested intergrid interpolation and RBF interpolation of the displacement field, that may lead to the loss of physical meaningfulness of the mathematical formulation and then to solver failures at the algebraic level, due to negative determinant values. Furthermore, the proposed method enables the transfer of solution variables between finite element spaces of different degrees and shapes and without stringent conformity requirements between different meshes, thus enhancing the flexibility and accuracy of electromechanical simulations. We show numerical results confirming that the proposed method enables the transfer of the deformation gradient tensor, allowing to successfully run simulations in cases where existing methods fail. This work provides an efficient and robust method for the intergrid transfer of the deformation gradient tensor, thus enabling independent tailoring of mesh discretizations to the particular characteristics of the individual physical components concurring to the of the multiphysics model.

Optimizing contact patterns for robot locomotion via geometric mechanics

Contact planning is crucial to the locomotion performance of robots: to properly self-propel forward, it is not only important to determine the sequence of internal shape changes (e.g., body bending and limb shoulder joint oscillation) but also the sequence by which contact is made and broken between the mechanism and its environment. Prior work observed that properly coupling contact patterns and shape changes allows for computationally tractable gait design and efficient gait performance. The state of the art, however, made assumptions, albeit motivated by biological observation, as to how contact and shape changes can be coupled. In this paper, we extend the geometric mechanics (GM) framework to design contact patterns. Specifically, we introduce the concept of “contact space” to the GM framework. By establishing the connection between velocities in shape and position spaces, we can estimate the benefits of each contact pattern change and therefore optimize the sequence of contact patterns. In doing so, we can also analyze how a contact pattern sequence will respond to perturbations. We apply our framework to sidewinding robots and enable (1) effective locomotion direction control and (2) robust locomotion performance as the spatial resolution decreases. We also apply our framework to a hexapod robot with two back-bending joints and show that we can simplify existing hexapod gaits by properly reducing the number of contact state switches (during a gait cycle) without significant loss of locomotion speed. We test our designed gaits with robophysical experiments, and we obtain good agreement between theory and experiments.

Intrinsic Shape Analysis in Archaeology: A Case Study on Ancient Sundials

The fact that the physical shapes of man-made objects are subject to overlapping influences—such as technological, economic, geographic, and stylistic progressions—holds great information potential. On the other hand, it is also a major analytical challenge to uncover these overlapping trends and to disentagle them in an unbiased way. This article explores a novel mathematical approach to extract archaeological insights from ensembles of similar artifact shapes. We show that by considering all shape information in a find collection , it is possible to identify shape patterns that would be difficult to discern by considering the artifacts individually or by classifying shapes into predefined archaeological types and analyzing the associated distinguishing characteristics. Recently, a series of high-resolution digital representations of artifacts have become available. Such datasets enable the application of extremely sensitive and flexible methods of shape analysis. We explore this potential on a set of 3D models of ancient Greek and Roman sundials, with the aim of providing alternatives to the traditional archaeological method of “trend extraction by ordination” (typology). In the proposed approach, each 3D shape is represented as a point in a shape space —a high-dimensional, curved, non-Euclidean space. Proper consideration of its mathematical properties reduces bias in data analysis and thus improves analytical power. By performing regression in shape space, we find that for Roman sundials, the bend of the shadow-receiving surface of the sundials changes with the latitude of the location. This suggests that, apart from the inscribed hour lines, also a sundial’s shape was adjusted to the place of installation. As an example of more advanced inference, we use the identified trend to infer the latitude at which a sundial, whose location of installation is unknown, was placed. We also derive a novel method for differentiated morphological trend assertion, building upon and extending the theory of geometric statistics and shape analysis. Specifically, we present a regression-based method for statistical normalization of shapes that serves as a means of disentangling parameter-dependent effects (trends) and unexplained variability . In addition, we show that this approach is robust to noise in the digital reconstructions of the artifact shapes.

DeepPortraitDrawing: Generating human body images from freehand sketches

Various methods for generating realistic images of objects and human faces from freehand sketches have been explored. However, generating realistic human body images from sketches is still a challenging problem. It is, first because of the sensitivity to human shapes, second because of the complexity of human images caused by body shape and pose changes, and third because of the domain gap between realistic images and freehand sketches. In this work, we present DeepPortraitDrawing, a deep generative framework for converting roughly drawn sketches to realistic human body images. To encode complicated body shapes under various poses, we take a local-to-global approach. Locally, we employ semantic part auto-encoders to construct part-level shape spaces, which are useful for refining the geometry of an input pre-segmented hand-drawn sketch. Globally, we employ a cascaded spatial transformer network to refine the structure of body parts by adjusting their spatial locations and relative proportions. Finally, we use a style-based generator as the global synthesis network for the sketch-to-image translation task which is modulated by segmentation maps for semantic preservation. Extensive experiments have shown that given roughly sketched human portraits, our method produces more realistic images than the state-of-the-art sketch-to-image synthesis techniques.

From Feynman's ratchet to time crystalline molecular motors.

Cats have an instinctive ability to use the connection governing parallel transport in the space of shapes to land safely on their feet. Here, we argue that the concept of connection, which is extensively used in general relativity and other parts of theoretical physics, also explains the impressive performance of molecular motors by enabling molecules to evade the conclusions of Feynman's ratchet-and-pawl analysis. First, we demonstrate the emergence of directed rotational motion from shape changes, which is independent of angular momentum. Then, we computationally design knotted polyalanine molecules and demonstrate the organization of individual atom thermal vibrations into collective rotational motion, which is independent of angular momentum. The motion occurs effortlessly even in ambient water and can be further enhanced through spontaneous symmetry breaking, rendering the molecule an effective theory time crystal. Our findings can be experimentally verified via nuclear magnetic resonance measurements and hold practical potential for molecular motor design and engineering.

Mapping triangles and breads in shape spaces: a big-data approach to estimating category distributions

Mapping triangles and breads in shape spaces: a big-data approach to estimating category distributions

Synthesis of uniformly ordered single-crystalline TiO2 nanorods on flexible Ti substrate

With high conductivity and ionic mobility, one-dimensional (1D) titanium dioxide (TiO2) nanoarrays have attracted great interest in the photoanode of solar cells and the cathode of lithium-ion/sodium-ion batteries. However, the synthesis of TiO2 nanoarrays often requires highly toxic or corrosive solution circumstances. Meanwhile, the case that most TiO2 nanoarrays are grown on rigid conductive substrate can’t satisfy the demand for application in the space of complex shape. In this work, we developed a simple method to prepare highly ordered single crystalline rutile TiO2 nanorod arrays with high density on flexible metal Ti substrate in relatively weak acid solution, and the orientation of the nanorods were more uniform than those by other means ever before. Based on detailed analysis, an ion-assisted and concentration-limited epitaxial growth mechanism by H+ and is proposed for this uniformly ordered rutile TiO2 nanorod array. This work can promote the research and application of flexible solar cells and lithium-ion batteries, especially their integration.

HACK: Learning a Parametric Head and Neck Model for High-fidelity Animation

Significant advancements have been made in developing parametric models for digital humans, with various approaches concentrating on parts such as the human body, hand, or face. Nevertheless, connectors such as the neck have been overlooked in these models, with rich anatomical priors often unutilized. In this paper, we introduce HACK (Head-And-neCK), a novel parametric model for constructing the head and cervical region of digital humans. Our model seeks to disentangle the full spectrum of neck and larynx motions, facial expressions, and appearance variations, providing personalized and anatomically consistent controls, particularly for the neck regions. To build our HACK model, we acquire a comprehensive multi-modal dataset of the head and neck under various facial expressions. We employ a 3D ultrasound imaging scheme to extract the inner biomechanical structures, namely the precise 3D rotation information of the seven vertebrae of the cervical spine. We then adopt a multi-view photometric approach to capture the geometry and physically-based textures of diverse subjects, who exhibit a diverse range of static expressions as well as sequential head-and-neck movements. Using the multi-modal dataset, we train the parametric HACK model by separating the 3D head and neck depiction into various shape, pose, expression, and larynx blendshapes from the neutral expression and the rest skeletal pose. We adopt an anatomically-consistent skeletal design for the cervical region, and the expression is linked to facial action units for artist-friendly controls. We also propose to optimize the mapping from the identical shape space to the PCA spaces of personalized blendshapes to augment the pose and expression blendshapes, providing personalized properties within the framework of the generic model. Furthermore, we use larynx blendshapes to accurately control the larynx deformation and force the larynx slicing motions along the vertical direction in the UV-space for precise modeling of the larynx beneath the neck skin. HACK addresses the head and neck as a unified entity, offering more accurate and expressive controls, with a new level of realism, particularly for the neck regions. This approach has significant benefits for numerous applications, including geometric fitting and animation, and enables inter-correlation analysis between head and neck for fine-grained motion synthesis and transfer.

Deployable strip structures

We introduce the new concept of C-mesh to capture kinetic structures that can be deployed from a collapsed state. Quadrilateral C-meshes enjoy rich geometry and surprising relations with differential geometry: A structure that collapses onto a flat and straight strip corresponds to a Chebyshev net of curves on a surface of constant Gaussian curvature, while structures collapsing onto a circular strip follow surfaces which enjoy the linear-Weingarten property. Interestingly, allowing more general collapses actually leads to a smaller class of shapes. Hexagonal C-meshes have more degrees of freedom, but a local analysis suggests that there is no such direct relation to smooth surfaces. Besides theory, this paper provides tools for exploring the shape space of C-meshes and for their design. We also present an application for freeform architectural skins, namely paneling with spherical panels of constant radius, which is an important fabrication-related constraint.

Anatomical characteristics of the leaning stem in Pinus merkusii seedling

Abstract. Safitri NM, Prastiwi FW, Salsabila S, Feriawan Y, Brilianto A, Nugroho WD. 2023. Anatomical characteristics of the leaning stem in Pinus merkusii seedling. Biodiversitas 24: 3796-3802. Pinus merkusii Jungh. & de Vriese is one of the tropical conifer species. The species formed reaction wood called compression wood (CW) when the stem grows in an abnormal position. CW in stem wood is frequently found to cause several problems for utilization in the use of its products. However, there are few studies on the anatomical characteristics of reaction wood in tropical conifer. This study aimed to observe the differences in anatomical characteristics between compression (CW) and opposite (OW) woods in leaning the stem of P. merkusii seedlings and their anatomical differences compared to normal wood (NW). Approx. 1-year-old P. merkusii seedlings from a nursery in Trenggalek, East Java, Indonesia, that were naturally bent or tilted were used in the study. Anatomical characteristics of wood, namely the dimension of tracheids, rays, resin canals, and the proportion of cells were observed in the study. The results showed that CW of P. merkusii seedlings formed a rounded tracheid shape and intercellular space. The differences between CW and OW in P. merkusii seedlings were significant in terms of height of ray cells, tracheid proportion, and resin canal proportion. However, tracheid length, tracheid diameter, tracheid wall thickness, resin canal diameter and frequency, rays frequency, and ray proportion were not significantly different compared to OW and NW.

Crystal structure, Hirshfeld surface analysis, and computational study of tin (IV) complex: Insights from spectroscopic, anticancer and cytotoxic properties

The complex di(p-methylbenzyl) (dibromo)(4,7-diphenyl-1,10-phenanthroline) tin (IV) complex (B1) was synthesized and characterized. For the theoretical investigation, we used DFT. With the help of the Multiwfn software package, topological analysis and RDG were calculated. A very low energy gap (2.3 eV) was observed in the HOMO-LUMO analysis. Nucleophilic and electrophilic attacking sites are confirmed using the MEP study. In a single crystal, analysis confirmed the octahedral shape and monoclinic space group. The intramolecular hydrogen was formed through the C—H—Br. The tin atom is in a uniform octahedral shape, which can be seen in the XRD of the complex B1. The Vero and Hela cell lines are used for anticancer and cytotoxic activities. Our synthesized complex shows better activity against Vero and Hela cell lines when compared to cisplatin.

Automated body composition estimation from device-agnostic 3D optical scans in pediatric populations

Excess adiposity in children is strongly correlated with obesity-related metabolic disease in adulthood, including diabetes, cardiovascular disease, and 13 types of cancer. Despite the many long-term health risks of childhood obesity, body mass index (BMI) Z-score is typically the only adiposity marker used in pediatric studies and clinical applications. The effects of regional adiposity are not captured in a single scalar measurement, and their effects on short- and long-term metabolic health are largely unknown. However, clinicians and researchers rarely deploy gold-standard methods for measuring compartmental fat such as magnetic resonance imaging (MRI) and dual X-ray absorptiometry (DXA) on children and adolescents due to cost or radiation concerns. Three-dimensional optical (3DO) scans are relatively inexpensive to obtain and use non-invasive and radiation-free imaging techniques to capture the external surface geometry of a patient's body. This 3D shape contains cues about the body composition that can be learned from a structured correlation between 3D body shape parameters and reference DXA scans obtained on a sample population. This study seeks to introduce a radiation-free, automated 3D optical imaging solution for monitoring body shape and composition in children aged 5-17. We introduce an automated, linear learning method to predict total and regional body composition of children aged 5-17 from 3DO scans. We collected 145 male and 206 female 3DO scans on children between the ages of 5 and 17 with three scanners from independent manufacturers. We used an automated shape templating method first introduced on an adult population to fit a topologically consistent 60,000 vertex (60k) mesh to 3DO scans of arbitrary scanning source and mesh topology. We constructed a parameterized body shape space using principal component analysis (PCA) and estimated a regression matrix between the shape parameters and their associated DXA measurements. We automatically fit scans of 30 male and 38 female participants from a held-out test set and predicted 12 body composition measurements. The coefficient of determination (R2) between 3DO predicted body composition and DXA measurements was at least 0.85 for all measurements with the exception of visceral fat on 3D scan predictions. Precision error was 1-4 times larger than that of DXA. No predicted variable was significantly different from DXA measurement except for male trunk lean mass. Optical imaging can quickly, safely, and inexpensively estimate regional body composition in children aged 5-17. Frequent repeat measurements can be taken to chart changes in body adiposity over time without risk of radiation overexposure.

Sparse Dynamic Deep Neural Network in Marginal Shape Space for Accurate COVID-19 Lung Tissue Segmentation from Chest CT Images

Sparse Dynamic Deep Neural Network in Marginal Shape Space for Accurate COVID-19 Lung Tissue Segmentation from Chest CT Images

Editorial

The Interactive Film and Media Journal advances scholarly and creative discourse on the intersection of interactivity and various media forms. This issue features contributions from the IV International Interactive Film and Media Conference (2022), coordinated by a diverse group of academics. The conference theme, Interactive Epistemology, Listening, and Ecomedia, facilitated an exploration of knowledge-building, listening, and ecological consciousness within interactivity. Emphasizing the importance of listening as a mode of knowledge production, the issue promotes a holistic understanding of interactivity across different research areas. The contributions address the role of interactivity in media, such as books, films, games, and real-time streaming, along with virtual and augmented reality. They provoke thought on interactivity's embodied and affective aspects and explore interactive technologies' influence on power relations and ecological concerns. The papers in this issue converge on themes like empathy and responsibility, illuminating the power of interactive digital media to reshape the understanding of social issues. For instance, interactive narratives, VR and games employ participatory elements to bring nuanced portrayals of migration experiences to the forefront. This approach encourages critical reflection and social responsibility. This issue also explores the transformative potential of interactive documentaries in varied contexts, highlighting their effectiveness in altering perceptions of history, socio-political phenomena, and power dynamics. These documentaries foster inclusivity and dialectical reflection, urging viewers to engage in complex narratives embedded in various landscapes. Some papers explore the impact of digital and artistic mediums on shaping space, narrative, and community engagement. The issue showcases how machine learning and public art can address mimetic trauma and discrimination and how digital comics and web-based artworks can redefine concepts of spatial interactions and narrative structures. A particular emphasis is placed on immersive technologies like VR and immersive journalism in civic engagement, underlining the power of these mediums in addressing social and environmental concerns. Exploring art and interactive documentary, specifically in the context of historical violence and colonial legacies, adds a significant dimension to the issue. This second set of papers from the 2022 Interactive Film and Media Conference highlights the transformative power of interactivity in reshaping narratives, promoting critical reflection, and fostering social responsibility. It emphasizes the crucial role of interactive media in fostering a more inclusive, empathetic, and informed society.

New genomic insights into the conformation of Lipizzan horses

Conformation traits are important selection criteria in equine breeding, as they describe the exterior aspects of the horse (height, joint angles, shape). However, the genetic architecture of conformation is not well understood, as data of these traits mainly consist of subjective evaluation scores. Here, we performed genome-wide association studies on two-dimensional shape data of Lipizzan horses. Based on this data, we identified significant quantitative trait loci (QTL) associated with cresty neck on equine chromosome (ECA)16 within the MAGI1 gene, and with type, hereby differentiating heavy from light horses on ECA5 within the POU2F1 gene. Both genes were previously described to affect growth, muscling and fatty deposits in sheep, cattle and pigs. Furthermore, we pin-pointed another suggestive QTL on ECA21, near the PTGER4 gene, associated with human ankylosing spondylitis, for shape differences in the back and pelvis (roach back vs sway back). Further differences in the shape of the back and abdomen were suggestively associated with the RYR1 gene, involved in core muscle weakness in humans. Therefore, we demonstrated that horse shape space data enhance the genomic investigations of horse conformation.

The Pedagogy of Gear Touchers: Unearthing Modes of Teaching Within and Through DIY Venues

Background: Within the body of literature on do-it-yourself (DIY) music scenes, researchers have routinely placed an emphasis on the role of material space in shaping the sociocultural and musical practices of punk music and other related genres. Scholars have also examined the teaching and learning processes of these musical subcultures under the banner of “punk pedagogy” scholarship. However, investigations into the intersection between these two strands of research need to occur because theories of punk pedagogy have largely overlooked the role of physical space within the educative practices of DIY music. Research into the thematically related space of the maker movement amplifies this need, because maker education scholars have repeatedly shown the multiple ways that materials and space shape how individuals learn through DIY production. Research Questions: I use this paper to attend to the following questions: How do DIY music venues shape the pedagogical practices of DIY music scenes? And in what ways do those pedagogies align with the ideological and ethical aims of these communities? By focusing on learning within DIY venues, I consider multiple forms of musical production outside of the context of a specific genre (i.e., punk). This study therefore provides insight into the mechanisms through which individuals learn and how those mechanisms relate to the physical affordances of these spaces. Research Design: To address these questions, I conducted a year-long comparative case study into two intertwined music series centered on noise music (an experimental subgenre within DIY music’s broad umbrella) and located in two separate DIY venues. Although each of the 13 events in this series included both a workshop and a concert, I focus my analysis on the concert portion of the series to explore a common site of interaction within DIY scenes. Through open and iterative qualitative analyses of field notes generated from observations of concerts in the series and interviews with featured artists and audience members, I provide a nuanced understanding of learning within DIY music venues and the role that both material space and technologies play in shaping that process. Conclusions: Drawing on this analysis, I contend that the stageless design of DIY venues provides a physical affordance that allows “gear toucher conversations” to occur. These conversations involve audience members engaging performers in discussions about the music technologies they use mere seconds after they finish performing, thus linking this pedagogical moment to the material attributes of the venue. However, these conversations reinscribe masculine notions of technology and undermine DIY music’s egalitarian politics, a finding that mirrors critical research into maker education. This work therefore calls on both researchers and practitioners to contend with the pedagogies of place and the educative processes that emerge out of situated technologies to further the liberatory praxes that DIY production can produce.

Response of Prolyl 4 Hydroxylases, Arabinogalactan Proteins and Homogalacturonans in Four Olive Cultivars under Long-Term Salinity Stress in Relation to Physiological and Morphological Changes.

Olive (Olea europeae L.) salinity stress induces responses at morphological, physiological and molecular levels, affecting plant productivity. Four olive cultivars with differential tolerance to salt were grown under saline conditions in long barrels for regular root growth to mimic field conditions. Arvanitolia and Lefkolia were previously reported as tolerant to salinity, and Koroneiki and Gaidourelia were characterized as sensitive, exhibiting a decrease in leaf length and leaf area index after 90 days of salinity. Prolyl 4-hydroxylases (P4Hs) hydroxylate cell wall glycoproteins such as arabinogalactan proteins (AGPs). The expression patterns of P4Hs and AGPs under saline conditions showed cultivar-dependent differences in leaves and roots. In the tolerant cultivars, no changes in OeP4H and OeAGP mRNAs were observed, while in the sensitive cultivars, the majority of OeP4Hs and OeAGPs were upregulated in leaves. Immunodetection showed that the AGP signal intensity and the cortical cell size, shape and intercellular spaces under saline conditions were similar to the control in Arvanitolia, while in Koroneiki, a weak AGP signal was associated with irregular cells and intercellular spaces, leading to aerenchyma formation after 45 days of NaCl treatment. Moreover, the acceleration of endodermal development and the formation of exodermal and cortical cells with thickened cell walls were observed, and an overall decrease in the abundance of cell wall homogalacturonans was detected in salt-treated roots. In conclusion, Arvanitolia and Lefkolia exhibited the highest adaptive capacity to salinity, indicating that their use as rootstocks might provide increased tolerance to irrigation with saline water.