Shape Variables Research Articles

The influence of invariant horizontal projection area constraint on shape optimization of free-form surface structure with openings

Free-form curved surface shell roof is favored by architects, but the openings for daylighting will decline its mechanical properties. In the shell shape optimization under the vertical load, when the outer contour of the openings or the shell changes, the total load of the structure also changes with the changes in its horizontal projection area. This contradicts the premise of structural optimization, that is, to maintain the principle of unchanging total loads. To solve this problem, the invariant horizontal projection area of the shell was taken as constraints in the shell shape optimization in which the objective function was structural strain energy and optimization design variables were internal and external boundary points of the curved surfaces with openings, and the key points on the curved surface which were design variables of the overall shape of the curved surface. The numerical examples verified the validity of the method, and the influence of the invariant horizontal projection area constraint of the curved surface with openings on the optimization results of the minimum strain energy, optimization with the frequency constraint, and the initial surface with the different support distribution were discussed. The results of the numerical examples showed that the invariant horizontal projection area constraint has a greater impact on the results of the curved surface with opening optimization, and its influence should be considered in the engineering design.

Physical modeling of the effect of shape, blockage, and flow variability on scour in culvert outlets

Physical modeling of the effect of shape, blockage, and flow variability on scour in culvert outlets

Using shell shape analysis based on landmarks to trace the geographical origin of the common cockle (Cerastoderma edule)

Determining the geographical origin of seafood is crucial for regulators and fishing industries who seek to prevent commercial fraud, enforce food safety regulations, and encourage high standards in sustainable fisheries management. The cockle, Cerastoderma edule (Linnaeus 1768), is a key species in estuarine ecosystems and is harvested all over Europe. Therefore, traceability tools using quick and inexpensive techniques to identify the origin of this bivalve are of paramount importance to support law enforcement. In this work, we explore the potential of using Geometric Morphometric (GM) methods to identify the geographical origin of cockle specimens. This method is based on landmarks identified in the shell to trace the origin of specimens obtained in nearby aquatic systems (from <35 km to <250 km distance). Specimens were collected in five aquatic systems (Ria de Aveiro, the Tagus and Sado estuaries, and the Albufeira and Óbidos coastal lagoons) in Portugal. Shells were digitalized and 16 landmarks were identified in each right valve and analyzed using Generalized Procrustes Superimposition. The discriminating power for traceability of 12 statistical and machine learning methods was assessed based on the corresponding shape variables, using R and Python (Linear Discriminant Analysis (LDA), Canonical Variable Analysis (CVA), Principal Component Analysis (PCA), Between-Group PCA (bgPCA), Partial Least Squares Discriminant (PLSD), Classification Regression Tree (CRT), Logistic Regression (LR), Random Forest (RF), Gradient Boosting (GB), K Nearest Neighbors (KNN), Support Vector Machines (SVM), Extending Gradient Boosting (XGBoost) and Neural Networks (NNET). LDA, CVA, SVM, and NNET demonstrated greater accuracy and a F1-score >80%, even with a small and unbalanced sample size. The highest percentage of correctly assigned individuals was obtained in the Tagus estuary (mean 89%) and in the Albufeira lagoon (mean 93%), which were also the systems with more specimens measured (174 and 59 respectively), whereas the worst results were obtained in the Sado estuary (50%, 56 specimens). In the Albufeira coastal lagoon, the best classification methods reached 100% correct classifications. It further highlights the importance of establishing statistical standards, such as the ones developed in the current work, to evaluate different methods, as small changes in the procedure may cause substantial differences in the results and conclusions. The revision of previous works (presented as a table) showed often >90% of correct classification in both bivalves and gastropods, highlighting the potential of the techniques for other mollusks. Our results support the use of GM based on landmarks as a reliable tool for bivalve's traceability, since it is a quick, simple and inexpensive approach. Further research should extend these findings to other species and other shape analysis techniques.

Size and shape of the neurocranium of laying chicken breeds

The neurocranium in birds provides valuable insights into their morphological diversity, including adaptations related to brain size, facial shaping, and environmental factors. This study analyzes the neurocranial shape characteristics and size of chickens with similar genetic backgrounds. By examining the neurocranial shape variation in chickens of the same age and sex, the study aims to understand the factors contributing to morphological diversity within this specific group. 3D geometric morphometrics was used to analyze 235 neurocrania from four chicken breeds. The analysis revealed significant differences in centroid size among the chicken breeds. The largest neurocranium centroid size was found in Sasso chickens., which were statistically separated from Atak-S. Additionally, centroid size effectively differentiates between Lohmann Brown and Lohmann Sandy chicken breeds.The most significant shape variation concerned the width of the rostral part of the frontal bone. However, according to the PC1 value, the shape variation was observed within rather than between groups. Lohmann Sandy chickens exhibited higher variability in neurocranial shape, suggesting greater shape diversity within this breed than others. As for shape analysis, the breeds showed closer similarity to each other. Lohmann Sandy chickens are characterized by positive PC1 value, with the rostral end of the frontal region inclined more ventrally, and a more extensive basioccipital region. Sasso chickens have a more dome-shaped middle part of the frontal region than other breeds. The study also identified the most significant shape variation among the study samples, observed at the rostral part of the frontal bone. These findings contribute to understanding the genetic and environmental influences shaping neurocranial morphology in chickens. Similar studies in different bird species and subspecies offer valuable insights into avian biology and adaptation.

The Apparent Shape and Functional Variables and their Repercussions on the Aesthetic Response to the Industrial Product

The Apparent Shape and Functional Variables and their Repercussions on the Aesthetic Response to the Industrial Product

Transpension: The Right Adjoint to the Pi-type

Presheaf models of dependent type theory have been successfully applied to model HoTT, parametricity, and directed, guarded and nominal type theory. There has been considerable interest in internalizing aspects of these presheaf models, either to make the resulting language more expressive, or in order to carry out further reasoning internally, allowing greater abstraction and sometimes automated verification. While the constructions of presheaf models largely follow a common pattern, approaches towards internalization do not. Throughout the literature, various internal presheaf operators ($\surd$, $\Phi/\mathsf{extent}$, $\Psi/\mathsf{Gel}$, $\mathsf{Glue}$, $\mathsf{Weld}$, $\mathsf{mill}$, the strictness axiom and locally fresh names) can be found and little is known about their relative expressivenes. Moreover, some of these require that variables whose type is a shape (representable presheaf, e.g. an interval) be used affinely. We propose a novel type former, the transpension type, which is right adjoint to universal quantification over a shape. Its structure resembles a dependent version of the suspension type in HoTT. We give general typing rules and a presheaf semantics in terms of base category functors dubbed multipliers. Structural rules for shape variables and certain aspects of the transpension type depend on characteristics of the multiplier. We demonstrate how the transpension type and the strictness axiom can be combined to implement all and improve some of the aforementioned internalization operators (without formal claim in the case of locally fresh names).

IMG-23. AN MRI-BASED RADIOMIC SIGNATURE TO PREDICT LONG-TERM SURVIVAL IN PATIENTS WITH DIFFUSE INTRINSIC PONTINE GLIOMAS

Abstract BACKGROUND Diffuse intrinsic pontine gliomas are characterized by a short life expectancy after diagnosis, with a mean overall survival of less than 12 months. To stratify patients and possibly better adapt therapy, we are proposing a radiomic signature that predicts, at the time of diagnosis, which patients might survive beyond 2 years. METHODS A retrospective database comprising 80 patients who had undergone 3D multimodal MRI at the time of diagnosis was compiled. All images were acquired at a single center, and the protocol included T1-weighted images acquired before and after contrast injection, T2-weighted and FLAIR images. Depending on the patient, some modalities were missing (around 10% per modality). After manual tumor delineation, a dedicated radiomic pipeline extracted 79 features (first-order statistics and texture parameters) per imaging modality. In addition, gender, age and 14 tumor shape features were collected without missing data. After feature selection (maximum of 4 features per model), five logistic regression models were defined, one per modality and another for clinical and shape variables. Each patient was eligible for 2 to 5 models, with an average score calculated over these models. RESULTS Based on a leave-one-out approach, the multi-model was able to define patients who survive more than 2 years correctly, (sensitivity=100%, specificity =79%). A prediction could be made for each patient despite missing MR modalities. Defining a radiomic signature based on the multi-model score (cut-off=0.5), Kaplan-Meier analysis shows a good separation of the two groups (p-value&amp;lt;0.001). This result is superior to that obtained with the TP53 mutation (available for 61 patients, with p-value&amp;lt;0.01). CONCLUSIONS We have demonstrated the value of multimodal 3D MRI in predicting which DIPG patients might survive beyond 2 years. The robustness of this radiomic signature has yet to be tested using multicentric images.

Optimized landslide susceptibility prediction based on SBAS-InSAR: case study of the Jiuzhaigou Ms7.0 earthquake

Earthquake-induced landslides can cause severe surface damage and casualties, posing a serious threat to the overall ecological environment and social stability. Traditional landslide susceptibility prediction (LSP) techniques often suffer from low effectiveness and precision, necessitating the exploration of remote sensing technology. However, this research in this area is limited, and the development of high-performance prediction models remains a pressing scientific issue. This study focuses on the Ms7.0 earthquake in Jiuzhaigou on 8 August 2017. To investigate the optimal integration of remote sensing technology with traditional LSP techniques, the study applies collaborative factor analysis and contingency matrix methods to create four new coupling models (SVM-I, SVM-II, RF-I, RF-II), followed by a comprehensive performance evaluation of these models. The results indicate that the integration of SAR-derived surface deformation data significantly enhances the accuracy of Landslide Susceptibility Mapping (LSM). Comparing the model performance with the receiver operating characteristic curve and landslide density, the reliability and prediction performance of the RF-I model are outstanding, reflecting that the improved method based on the InSAR collaborative machine learning model with shape variables along the slope direction can optimize the accuracy of the LSM, and has better performance and robustness in earthquake landslide susceptibility evaluation.

Otolith shape reveals the population structure of 'Malabar Labeo’, Labeo dussumieri (Valenciennes, 1842), in the four west-flowing rivers of India

Otolith shape variation in Labeo dussumieri from the four west-flowing rivers of India was analyzed using Wavelet coefficients and elliptic Fourier descriptors in the ShapeR package. The mean otolith shape of L. dussumieri varied significantly among sampling locations, with the posterior margin of the otolith showing the maximum variation. Otolith shape analysis also revealed variations between regions of different latitudes, with the northern (Narmada and Kundalika River) and southern populations (Achankovil and Chalakudy River) forming two distinct clusters. This variability in otolith shape might be attributed to the variation in environmental conditions prevailing in the sampling locations. The linear discriminant analysis based on elliptic Fourier descriptors and Wavelet coefficients showed an overall classification success of 89.03 % and 89.20 %, respectively. The present study validated that the lapillar otoliths are ideal for investigating the population structure of cyprinid fishes like L. dussumieri. The present study provided the first comprehensive information on the otolith shape analysis of L. dussumieri from the four west-flowing rivers of India.

Effect of pre-heat treatment and carbonization temperature on comprehensive properties of melamine-derived carbon foam

Carbon foams (CFs), which can be manufactured from melamine foam (MF) via direct carbonization, are promising spacecraft thermal insulation material due to their excellent performance of sound absorption, low density, high porosity and heat resistance. Carbonization temperature, heating rate and carbonization time are three key elements during the melamine carbon foam process. As an improvement, this study simultaneously researches the impacts of pre-heat treatment on the microstructure, structure parameter, mechanical properties and heat-shielding performance of the melamine-derived carbon foam (MDCF), aiming to explore the best process of MDCF production. The results showed that the cross-linking degree and defects of MF samples were directly improved by pre-heat treatment. Additionally, all MDCF samples retained the three-dimensional mesh open-cell skeleton structure. The MDCF samples obtained by carbonization at 900 °C had the smallest average pore size structure, which performed the compressive stress of 16.8 kPa at 10 % strain and lowest thermal conductivity of 0.0252 W m−1 K−1. To further study the mechanical property and thermal conductivity performance of MDCF samples, the mechanics relationships of the buckling strength and shape variables, as well as thermal conductivity and pore size structure were researched.

Procrustes analysis of a shape of pediatric supracondylar humerus fractures

Shape of supracondylar fracture of the humeral of pediatric patients is analysed with Procrustes method. XR-images of fractures are considered both in anterio-posterior (AP) view and in a lateral (L) view. Applying Procrustes method for both views mean images are constructed and compared. Variability of shapes is quantified with a shape principal component analysis. Possibility of predictions of typical shape of humeral fracture and its variability using statistical shape analysis offers additional information on injury characteristics important in preoperative planning. Non-parametric tests (permutational and bootstrap) do not indicate statistical difference between Procrustes mean shapes in anterio-posterior and lateral projections. It is shown, however, that AP and L shapes of humeral fractures differ in their variability quantified by shape principal components.

A new online detection method of tobacco impurities for tobacco robot.

In the tobacco industry, impurity detection is an important prerequisite for ensuring the quality of tobacco. However, in the actual production process, the complex background environment and the variability of impurity shapes can affect the accuracy of impurity detection by tobacco robots, which leads to a decrease in product quality and an increase in health risks. To address this problem, we propose a new online detection method of tobacco impurities for tobacco robot. Firstly, a BCFormer attention mechanism module is designed to effectively mitigate the interference of irrelevant information in the image and improve the network's ability to identify regions of interest. Secondly, a Dual Feature Aggregation (DFA) module is designed and added to Neck to improve the accuracy of tobacco impurities detection by augmenting the fused feature maps with deep semantic and surface location data. Finally, to address the problem that the traditional loss function cannot accurately reflect the distance between two bounding boxes, this paper proposes an optimized loss function to more accurately assess the quality of the bounding boxes. To evaluate the effectiveness of the algorithm, this paper creates a dataset specifically designed to detect tobacco impurities. Experimental results show that the algorithm performs well in identifying tobacco impurities. Our algorithm improved the mAP value by about 3.01% compared to the traditional YOLOX method. The real-time processing efficiency of the model is as high as 41 frames per second, which makes it ideal for automated inspection of tobacco production lines and effectively solves the problem of tobacco impurity detection.

Geometrical characterization of healthy red blood cells using digital holographic microscopy and parametric shape models for biophysical studies and diagnostic applications

Modeling of the red blood cell (RBC) shape is an integral part of the experimental and computer simulation investigations of light scattering by these cells for fundamental studies as well as diagnostic applications in techniques like cytometry and quantitative phase imaging. In the present work, a comprehensive study of the geometrical characterization of healthy human RBCs using digital holographic microscopy (DHM) and six frequently employed parametric shape models is reported. It is shown that the comparison of the optical phase profiles, and the thickness profiles given by the models with the DHM results gives a better judgment of the appropriateness of the parametric shape models. It is also shown that the RBC parametric models offer a simpler solution to the refractive index-thickness decoupling problem in QPI methods. Results of geometrical characterization of 500 healthy RBCs in terms of volume, surface area (SA), and sphericity index (SI) led to the classification of the parametric models in two categories based on the nature of variation of these quantities with the cell diameter. In light of the variability of the healthy RBC shapes, our findings suggest that the parametric models exhibiting a negative correlation between the SI and the cell diameter would provide more reliable estimates of the RBC parameters in diagnostic applications. Statistical distributions and descriptive statistics of the RBC volume, SA and SI serve as a guide for the assessment of the capability of the studied parametric models to give a reliable account of the variability of the healthy RBC shape and size.

MONET: The Minor Body Generator Tool at DART Lab.

Minor bodies exhibit considerable variability in shape and surface morphology, posing challenges for spacecraft operations, which are further compounded by highly non-linear dynamics and limited communication windows with Earth. Additionally, uncertainties persist in the shape and surface morphology of minor bodies due to errors in ground-based estimation techniques. The growing need for autonomy underscores the importance of robust image processing and visual-based navigation methods. To address this demand, it is essential to conduct tests on a variety of body shapes and with different surface morphological features. This work introduces the procedural Minor bOdy geNErator Tool (MONET), implemented using an open-source 3D computer graphics software. The starting point of MONET is the three-dimensional mesh of a generic minor body, which is procedurally modified by introducing craters, boulders, and surface roughness, resulting in a photorealistic model. MONET offers the flexibility to generate a diverse range of shapes and surface morphological features, aiding in the recreation of various minor bodies. Users can fine-tune relevant parameters to create the desired conditions based on the specific application requirements. The tool offers the capability to generate two default families of models: rubble-pile, characterized by numerous different-sized boulders, and comet-like, reflecting the typical morphology of comets. MONET serves as a valuable resource for researchers and engineers involved in minor body exploration missions and related projects, providing insights into the adaptability and effectiveness of guidance and navigation techniques across a wide range of morphological scenarios.

The pronotum shape of scelimenine grasshoppers (Orthoptera: Tetrigidae) likely represents an exaptation for heterogeneous niche colonization

Abstract Insects are suitable model organisms for functional morphology research, especially in the context of exaptation, when the same morphological trait represents an advantage in disparate niches. Phylogenetically distant groups of pygmy grasshoppers (Orthoptera: Tetrigidae) have various pronotal projections defining their general appearance and body shape. However, body shape has never been related to niche occupation in these insects, thus the aim of this study is to investigate the relationship between pronotum shape and macrohabitat adaptation in Scelimeninae, a group of Asian and Papuan tetrigids encompassing amphibious and corticolous (bark-dwelling) representatives. With the use of geometric morphometrics and phylogenetic comparative methods, two morphological and functional groups were distinguished, with the body shape exhibiting a significant phylogenetic signal. The first group consists of elongated amphibious taxa (Scelimenini tribe) with highly uniform pronotum morphology, likely due to a strong selection for streamlined body shape. Stouter corticolous taxa (Discotettigini tribe) exhibit more conspicuous body shape variability, possibly increasing camouflage efficiency in tree bark habitats. Ecological divergence associated with macrohabitat adaptation may thus have been the primary driver of speciation in this insect group, but the evolutionary constraints leading to this divergence are still to be identified.

Inspecting PGC 165324 and PGC 977941 Galaxies Using a Combination ofPhotometric and Spectroscopic Methods

Photometric and spectroscopic approaches were utilized to examine the two galaxies, PGC 165324 and PGC 977941. Data releases (DR7 and DR17) from "The Sloan Digital Sky Survey (SDSS)” were employed to acquire the observed data. Then, ellipsoids were fitted via employing the Image Reduction and Analysis Facility (IRAF) with utilising STSDAS Library, the ELLIPS task. Along with the astrometric characteristics, the surfaces’ brightness of the galaxies PGC 165324 and PGC 977941, as well as their magnitudes, cumulative flux, central axis position angles, ellipticities, vertical and horizontal shifts, isophotal shape variables (B4), and also the star-forming rates (SFRs), were analysed and evaluated. It was indicated that the two galaxies, are members of a close pair galaxy system; in addition, they are considered a physical system; the PGC 165324 galaxy was a merging galaxy with a higher SFR. It was likely that the PGC 977941 had separated itself from the galaxy collision and drifted away.

The sex of organ geometry

Organs have a distinctive yet often overlooked spatial arrangement in the body1–5. We propose that there is a logic to the shape of an organ and its proximity to its neighbours. Here, by using volumetric scans of many Drosophila melanogaster flies, we develop methods to quantify three-dimensional features of organ shape, position and interindividual variability. We find that both the shapes of organs and their relative arrangement are consistent yet differ between the sexes, and identify unexpected interorgan adjacencies and left–right organ asymmetries. Focusing on the intestine, which traverses the entire body, we investigate how sex differences in three-dimensional organ geometry arise. The configuration of the adult intestine is only partially determined by physical constraints imposed by adjacent organs; its sex-specific shape is actively maintained by mechanochemical crosstalk between gut muscles and vascular-like trachea. Indeed, sex-biased expression of a muscle-derived fibroblast growth factor-like ligand renders trachea sexually dimorphic. In turn, tracheal branches hold gut loops together into a male or female shape, with physiological consequences. Interorgan geometry represents a previously unrecognized level of biological complexity which might enable or confine communication across organs and could help explain sex or species differences in organ function.

Shape analysis of the nasal complex among South African groups from CBCT scans

Three-dimensional (3D) anatomical extraction techniques could help the forensic anthropologist in a precise and inclusive assessment of biological phenotypes for the development of facial reconstruction methods. In this research, the nose morphology and the underlying hard tissue of two South African populations were studied. To this end, a 3D computer-assisted approach based on an automated landmarking workflow was used to generate relevant 3D anatomical components, and shape discrepancies were investigated using a data set of 200 cone-beam computer tomography (CBCT) scans. The anatomical landmarks were placed on the external nose and the mid-facial skeleton (the nasal bones, the anterior nasal aperture, the zygoma, and the maxilla). Shape differences related to population affinity, sex, age, and size were statistically evaluated and visualised using geometric morphometric methods. Population affinity, sexual dimorphism, age, and size affect the nasal complex morphology. Shape variation in the mid-facial region was significantly influenced by population affinity, emphasising that shape variability was specific to the two population groups, along with the expression of sexual dimorphism and the effect of ageing. In addition, nasal complex shape and correlations vary greatly between white and black South Africans, highlighting a need for reliable population-specific 3D statistical nose prediction algorithms.

OPTIMIZATION-DRIVEN STATISTICAL MODELS OF ANATOMIES USING RADIAL BASIS FUNCTION SHAPE REPRESENTATION.

Particle-based shape modeling (PSM) is a popular approach to automatically quantify shape variability in populations of anatomies. The PSM family of methods employs optimization to automatically populate a dense set of corresponding particles (as pseudo landmarks) on 3D surfaces to allow subsequent shape analysis. A recent deep learning approach leverages implicit radial basis function representations of shapes to better adapt to the underlying complex geometry of anatomies. Here, we propose an adaptation of this method using a traditional optimization approach that allows more precise control over the desired characteristics of models by leveraging both an eigenshape and a correspondence loss. Furthermore, the proposed approach avoids using a black-box model and allows more freedom for particles to navigate the underlying surfaces, yielding more informative statistical models. We demonstrate the efficacy of the proposed approach to state-of-the-art methods on two real datasets and justify our choice of losses empirically.

Performance of different modeling techniques in testing the impact of environmental variables on eel landing in Ichkeul Lake, a RAMSAR Wetland and UNESCO biosphere reserve

Advanced modeling techniques, including Random Forest (RF) and Cubist model (CB), were used to assess the relationship between environmental factors and European eels (Anguilla anguilla) abundance and to provide insights into the lake's ecological status while considering climate change and anthropogenic influences. A comprehensive dataset, attained through extensive environmental and biological monitoring for the period 2010–2020, was employed. The performance of the models is carried out using key metrics including the root mean square error (RMSE), coefficient of determination (R²), and mean estimation error (MAE). In addition, a sensitivity analysis was conducted to ascertain the relative significance of the thirteen input variables in shaping the predictions of the models. The precision of the CB and RF models in predicting eel landings surpassed that of Multiple Regression. In the training dataset, the CB model achieved R2=0.55, RMSE=7.68 tons, and MSE=6.20 tons, and the RF model achieved R2=0.56, RMSE=7.20 tons, and MSE=5.56 tons. High accuracy was maintained on the testing dataset, with CB achieving R2=0.73, RMSE=5.13 tons, and MSE=5.89 tons, and RF achieving R2=0.73, RMSE=5.81 tons, and MSE=4.67 tons. The scatter plot between predicted and measured eel landings indicated that the RF model tends to overestimate lower values and underestimate higher values of eel landings, while the CB model gave better performance in this context. Further, the carried sensitivity analysis using the CB model unequivocally identified three pivotal factors – water level, salinity, and turbidity level – as the most influential determinants governing the landing of eels in this ecosystem. Thus, the CB model is considered to be more promising for interpreting the relationship between environmental parameters and eel landings, which could be used by managers for an effective lake management strategy.