Differences In Shape Research Articles

Automated Grasp Labeling and Detection Framework with Pixel-Level Precision

Due to the differences in shape, material, and color of objects, the detection of planar grasps by robots remains challenging. Traditional methods rely on discrete grasp configurations for annotation, ignoring many possible grasp configurations. This leads to poor network generalization, making it challenging to handle a diverse range of grasped objects. Manual reannotation to continuous labels can effectively address this issue but comes with a significant cost. Therefore, this paper proposes a Pixel-level Grasp framework. Firstly, APGLG can automatically generate pixel-level grasp labels and discrete labels into continuous labels, effectively increasing the information content of individual data and improving the network generalization performance. Then, we propose the Max-Grasp-Net, built on the Multi-axis Vision Transformer and Dynamic Convolution Decomposition, to construct a U-shaped Network structure. A grasp decoder is incorporated, and deep supervision is applied to enhance network generalization. On the Cornell dataset, we achieve the best results, a grasping accuracy of 99.55%, an average success rate of 97.92% in single-object grasping, and 95.83% in multi-object grasping. We verified the effectiveness of our label generation algorithms and network innovation through actual grasp experiments.

Multi-damage detection of composite blades via the curvature modal shape approach in combination with surface interpolation and extreme learning machine

In recent years, there has been a rise in renewable energy, which has led to an increase in equipment maintenance. The damage detection technique for wind turbine blades (WTBs) can reduce maintenance costs. The majority are not immediately applicable to structures that are in an operating condition. Motivated by the current constraints, a novel two-stage multi-damage quantitative detection approach in WTBs during operation has been proposed. The multiple damage locations are first identified by calculating the curvature modal shape (CMS) difference for the WTBs after the interpolation of the operating deflection shape (ODS) using surface interpolation (SI). Then the relationship between the natural frequencies and damage severities for the WTBs is determined utilizing the finite element method (FEM). The established correlation provides a natural frequency database that can be utilized for identifying the corresponding damage severities through the application of the Extreme Learning Machine (ELM) method, upon measuring the natural frequencies of the damaged WTB. The efficacy of the suggested damage detection methodology has been confirmed through simulations conducted on WTBs featuring two or three instances of damage. Moreover, the ODS along with natural frequencies of the WTBs exhibiting two or three damages are experimentally assessed using a Scanning Laser Doppler Vibrometer. The simulation and experiment verify that the presented method has satisfactory effectiveness in damage detection.

HGLeNet DEEP LEARNING FOR SKIN CANCER DETECTION WITH SKIN LESION SEGMENTATION

Skin cancer is deemed to be the most dangerous type of cancer. It occurs due to the damage caused to the DNA and if left untreated can lead to death. Various methods have been devised over the last few years for skin cancer detection. However, their performance was affected by various challenges in image analysis, like color illumination variations, differences in shape, size, etc. Therefore, to tackle these issues the novel framework, deep learning (DL) technique for accurate skin cancer detection and lesion segmentation is developed. Primarily, the skin image is pre-processed by employing a weighted median filtering to eradicate the noises contained. Then, the segmentation of skin lesions is carried out by employing the efficient neural network (ENet). After that, augmentation is accomplished to avoid overfitting, and later, feature extraction is carried out. At last, skin cancer detection is effectuated with the help of hybrid GoogleNet-LeNet (HGLeNet), which is obtained by merging GoogleNet and LeNet, here layers are modified using the regression concept. Furthermore, the introduced framework is examined for its effectiveness through accuracy, sensitivity and specificity. Moreover, HGLeNet attained the highest accuracy of 0.922, sensitivity of 0.928, as well as specificity of 0.924.

RMCNet: A Liver Cancer Segmentation Network Based on 3D Multi-Scale Convolution, Attention, and Residual Path

Abdominal CT images are important clues for diagnosing liver cancer lesions. However, liver cancer presents challenges such as significant differences in tumor size, shape, and location, which can affect segmentation accuracy. To address these challenges, we propose an end-to-end 3D segmentation algorithm, RMCNet. In the shallow encoding part of RMCNet, we incorporated a 3D multiscale convolution (3D-Multiscale Convolution) module to more effectively extract tumors of varying sizes. Moreover, the convolutional block attention module (CBAM) is used in the encoding part to help the model focus on both the shape and location of tumors. Additionally, a residual path is introduced in each encoding layer to further enrich the extracted feature maps. Our method achieved DSC scores of 76.56% and 72.96%, JCC scores of 75.82% and 71.25%, HD values of 11.07 mm and 17.06 mm, and ASD values of 2.54 mm and 10.51 mm on the MICCAI 2017 Liver Tumor Segmentation public dataset and the 3Dircadb-01 public dataset, respectively. Compared to other methods, RMCNet demonstrates superior segmentation performance and stronger generalization capability.

Relationships between capnogram parameters by mainstream and sidestream techniques at different breathing frequencies

Capnography, routinely used in operating rooms and intensive care units, reveals essential information on lung ventilation and ventilation–perfusion matching. Mainstream capnography directly measures CO2 in the breathing circuit for accurate analysis and is considered a reference technique. Sidestream capnography, however, analyzes gas away from the patient leading to potentially less accurate measures. While these methodological differences impact the capnogram indices in mechanically ventilated patients, such assessments during spontaneous breathing are essentially lacking. Accordingly, we aimed to compare mainstream and sidestream capnography in spontaneously breathing subjects, focusing on differences in capnogram shape and dead space indices at various respiratory rates. Simultaneous mainstream and sidestream time and volumetric capnography were performed on spontaneously breathing adults (n = 35). Measurements were performed during controlled low (10/min), medium (12/min), and high (20/min) breathing rates as a challenge. Correlation and Bland–Altman analyses were used to assess trends and agreements between time and volumetric capnography indices obtained by the mainstream and sidestream techniques, including end-tidal CO2 (ETCO2), shape factors reflecting the slopes of phases 2 and 3, and anatomical and physiological dead space fractions. ETCO2 and physiological dead space measured by mainstream and sidestream techniques showed excellent correlations (r > 0.90, p < 0.001 for all breathing rates) and agreements. While strong correlations and moderate agreements were evidenced in the parameters reflecting the late phase of expiration (phase 3 slope and exhaled CO2 volume), these relationships were weaker for indices related to the early phase of expiration (phase 2 slope, anatomical dead space). Changing breathing frequency caused significant alterations in all capnography parameters, which were detectable by both mainstream and sidestream techniques. Sidestream capnography cannot substitute the more accurate mainstream technique for measuring the absolute values of shape factors and ventilation dead space fractions. However, sidestream capnography is also able to detect and track changes in uneven alveolar emptying, ventilation–perfusion matching and ventilation dead space fraction in spontaneously breathing subjects.

Temperature and Physicochemical Properties of Abnormal Heating Composite Insulators

Abnormal heating will reduce the insulation performance of composite insulators or even cause insulator fracture, and the abnormal heating phenomenon is more serious under high-humidity conditions. Therefore, in this paper, the voltage withstand test of abnormal heating composite insulators caused by aging and damp sheath, decay-like core rod, and contamination were carried out under different ambient humidity. The heating and discharge of composite insulators were observed by infrared thermal imager and ultraviolet imager, and its temperature characteristics were analyzed from the aspects of heating range, heating shape, and temperature difference. In addition, in order to study the abnormal heating mechanism of composite insulators, the micro-morphology, chemical groups and dielectric properties of the silicon rubber of composite insulators with aging and damp sheath and the decay-like core rod were also measured. It is found that the temperature characteristics of the three types of abnormal heating composite insulators are different, and the temperature difference increases with the increase of humidity. The deterioration of silicone rubber and core rod material is the internal reason for the abnormal heating of composite insulators, and high-humidity conditions will exacerbate the heating phenomenon.

Super-resolution reconstruction of time-resolved four-dimensional computed tomography (TR-4DCT) with multiple breathing cycles based on TR-4DMRI.

Respiratory motion irregularities in lung cancer patients are common and can be severe during multi-fractional (∼20 mins/fraction) radiotherapy. However, the current clinical standard of motion management is to use a single-breath respiratory-correlated four-dimension computed tomography (RC-4DCT or 4DCT) to estimate tumor motion to delineate the internal tumor volume (ITV), covering the trajectory of tumor motion, as a treatment target. To develop a novel multi-breath time-resolved (TR) 4DCT using the super-resolution reconstruction framework with TR 4D magnetic resonance imaging (TR-4DMRI) as guidance for patient-specific breathing irregularity assessment, overcoming the shortcomings of RC-4DCT, including binning artifacts and single-breath limitations. Six lung cancer patients participated in the IRB-approved protocol study to receive multiple T1w MRI scans, besides an RC-4DCT scan on the simulation day, including 80 low-resolution (lowR: 5×5×5mm3) free-breathing (FB) 3D cine MRFB images in 40s (2Hz) and a high-resolution (highR: 2×2×2mm3) 3D breath-hold (BH) MRBH image for each patient. A CT (1×1×3mm3) image was selected from 10-bin RC-4DCT with minimal binning artifacts and a close diaphragm match (<1cm) to the MRBH image. A mutual-information-based Freeform deformable image registration (DIR) was used to register the CT and MRBH via the opposite directions (namely F1: and F2: ) to establish CT-MR voxel correspondences. An intensity-based enhanced Demons DIR was then applied for , in which the original MRBH was used in D1: , while the deformed MRBH was used in D2: . The deformation vector fields (DVFs) obtained from each DIR were composed to apply to the deformed CT (D1) and original CT (D2) to reconstruct TR-4DCT images. A digital 4D-XCAT phantom at the end of inhalation (EOI) and end of exhalation (EOE) with 2.5cm diaphragmatic motion and three spherical targets (ϕ=2, 3, 4cm) were first tested to reconstruct TR-4DCT. For each of the six patients, TR-4DCT images at the EOI, middle (MID), and EOE were reconstructed with both D1 and D2 approaches. TR-4DCT image quality was evaluated with mean distance-to-agreement (MDA) at the diaphragm compared with MRFB, tumor volume ratio (TVR) referenced to MRBH, and tumor shape difference (DICE index) compared with the selected input CT. Additionally, differences in the tumor center of mass (|∆COMD1-D2|), together with TVR and DICE comparison, was assessed in the D1 and D2 reconstructed TR-4DCT images. In the phantom, TR-4DCT quality is assessed by MDA=2.0±0.8mm at the diaphragm, TVR=0.8±0.0 for all tumors, and DICE=0.83±0.01, 0.85±0.02, 0.88±0.01 for ϕ=2, 3, 4cm tumors, respectively. In six patients, the MDA in diaphragm match is -1.6±3.1mm (D1) and 1.0±3.9mm (D2) between the reconstructed TR-4DCT and lowR MRFB among 18 images (3 phases/patient). The tumor similarity is TVR=1.2±0.2 and DICE=0.70±0.07 for D1 and TVR=1.4±0.3 (D2) and DICE=0.73±0.07 for D2. The tumor position difference is |∆COMD1-D2|=1.2±0.8mm between D1 and D2 reconstructions. The feasibility of super-resolution reconstruction of multi-breathing-cycle TR-4DCT is demonstrated and image quality at the diaphragm and tumor is assessed in both the 4D-XCAT phantom and six lung cancer patients. The similarity of D1 and D2 reconstruction suggests consistent and reliable DIR results. Clinically, TR-4DCT has the potential for breathing irregularity assessment and dosimetry evaluation in radiotherapy.

Properties and Factors of CsxWO3 Slurry for Building Glass with High Visible Light Transmission and Outstanding Near-Infrared Insulation

This study is dedicated to the development of a new type of cesium tungsten bronze energy-saving laminated glass and explores its application in insulating glass combinations, offering innovative ideas and practical solutions for advancing energy-saving glass technology. Experimental results show that both CsxWO3 (CWO) dispersions exhibit good visible light transmittance and near-infrared shielding properties, with CWO1 demonstrating superior shielding in the 650–950 nm range, attributed to differences in shape and size distribution and verified by simulations using the Drude–Lorentz model and the finite element method.

Quantitative analysis of facial shape in children to support respirator design

The COVID-19 pandemic demonstrated the need for respiratory protection against airborne pathogens. Respirator options for children are limited, and existing designs do not consider differences in facial shape or size. We created a dataset of children's facial images from three cohorts, then used geometric morphometric analyses of dense and sparse facial landmark representations to quantify age, sex and ancestry-related variation in shape. We found facial shape and size in children vary significantly with age from ages 2 to 18, particularly in dimensions relevant to respirator design. Sex differences are small throughout most of the age range of our sample. Ancestry is associated with significant facial shape variation in dimensions that may affect respirator fit. We offer guidance on how to our results can be used for the appropriate design of devices such as respirators for pediatric populations. We also highlight the need to consider ancestry-related variation in facial morphology to promote equitable, inclusive products.

Unsupervised clustering of longitudinal clinical measurements in electronic health records.

Longitudinal electronic health records (EHR) can be utilized to identify patterns of disease development and progression in real-world settings. Unsupervised temporal matching algorithms are being repurposed to EHR from signal processing- and protein-sequence alignment tasks where they have shown immense promise for gaining insight into disease. The robustness of these algorithms for classifying EHR clinical data remains to be determined. Timeseries compiled from clinical measurements, such as blood pressure, have far more irregularity in sampling and missingness than the data for which these algorithms were developed, necessitating a systematic evaluation of these methods. We applied 30 state-of-the-art unsupervised machine learning algorithms to 6,912 systematically generated simulated clinical datasets across five parameters. These algorithms included eight temporal matching algorithms with fourteen partitional and eight fuzzy clustering methods. Nemenyi tests were used to determine differences in accuracy using the Adjusted Rand Index (ARI). Dynamic time warping and its lower-bound variants had the highest accuracies across all cohorts (median ARI>0.70). All 30 methods were better at discriminating classes with differences in magnitude compared to differences in trajectory shapes. Missingness impacted accuracies only when classes were different by trajectory shape. The method with the highest ARI was then used to cluster a large pediatric metabolic syndrome (MetS) cohort (N = 43,426). We identified three unique childhood BMI patterns with high average cluster consensus (>70%). The algorithm identified a cluster with consistently high BMI which had the greatest risk of MetS, consistent with prior literature (OR = 4.87, 95% CI: 3.93-6.12). While these algorithms have been shown to have similar accuracies for regular timeseries, their accuracies in clinical applications vary substantially in discriminating differences in shape and especially with moderate to high missingness (>10%). This systematic assessment also shows that the most robust algorithms tested here can derive meaningful insights from longitudinal clinical data.

Black shale high geological background potential toxic elements(PTEs) in middle reaches of the Yangtze River tributary basin water environment, China: Distribution, pollution sources, and risk assessment

As a typical high geological background area in the middle reaches of the Yangtze River tributary basin in China, the Loushao Basin in Hunan is covered with high mineral black shale, with an average element value 4.76–8.97 times higher than the world average rock level. The aim of this study is to analyze the water environment pollution in the middle reaches of the Yangtze River tributary basin under high geological background based on the spatial distribution differences of black shale concentration. PCA source analysis is used to track the source of pollution and highlight the differences in body shape to assess regional health risks. The research results show that Cd in water quality exceeds the background value by 7.5 times. There is a strong homology among Pb, Cd, Cr, As, and Hg elements in water bodies, mainly derived from the natural weathering, migration, and enrichment of rocks. Hg element is a pollution caused by human factors, and water pollution is more severe in areas close to high concentrations, with severe exceedance of Cr element in water quality. The main controlling factor for individual health risk differences is body shape, and men's health is more susceptible to threats.

Morphological variability of rosette leaves within Sempervivum ciliosum and S. ruthenicum complexes (Crassulaceae): The geometric morphometrics approach

The yellow-flowered Sempervivum species from the Balkan Peninsula, tentatively divided into Sempervivum ciliosum (S. ciliosum, S. galicicum, S. jakucsii, S. klepa, S. octopodes) and S. ruthenicum complexes (S. kindingeri, S. leucanthum, S. ruthenicum, S. zeleborii), are well known for their pronounced phenotypic plasticity, especially in the vegetative parts, resulting in exceedingly complicate infrageneric taxonomy. Extensive studies dealing with the variability of qualitative and quantitative traits, such as the shape and size of the rosette leaves, were not conducted in the past. This study aimed to analyse the extent of morphological variability of the rosette leaves regarding their shape and size and evaluate their potential to resolve taxonomic doubts. For this purpose, geometric morphometrics, as a tool for analysing minute shape variability, was used to discriminate mentioned species. The variability of the rosette leaves was statistically analysed within 15 populations using univariate (ANOVA) and multivariate statistical analysis (MANOVA, PCA, DA). Obtained results indicated highly statistically significant differences in rosette leaf shape and size between analysed complexes and species.

Understanding Standard Procedure in Auditory Brainstem Response: Importance of Normative Data

The auditory brainstem response (ABR) is a noninvasive test that measures neural activity in response to auditory stimuli. Racial differences in head shape have provided strong evidence for specific normative data and accurate device calibration. International standards emphasize the need for standardized procedures and references. This study aimed to outline the standard procedure and related normative ABR values. Standard procedures were performed according to International Electrotechnical Commission (IEC) standards. Five studies from two countries were included to compare the normative values of the ABR. The dataset from the National Standard Reference Data Center (NSRDC) was used as reference. Normative values were described in terms of stimuli, latency, and amplitude. For click stimuli, the latency of the ABR showed different patterns across populations, such as those from Korea and the USA. Although the latencies reported by the NSRDC and for Koreans were relatively short, those reported for USA populations were longer. Using clicks, it was shown that the USA population had the largest ABR amplitude compared to those reported for the other two datasets. For Wave V latency using tone bursts, a similar pattern was identified with click stimuli. Frequency-specific trends were also observed. Although there is a lack of ABR datasets, the information and insights of the present study could be utilized as standard guidelines in research on ABR.

Pottery evolution pattern discovery based on deep learning: case study of Miaozigou culture in China

Potteries, one of the tools widely used by early humans, encapsulates rich historical information. Deep neural networks have been applied to analyzing pottery digital images, bypassing the need for intricate handcrafted features. However, existing models focus solely on pottery shape comparison, neglecting the analysis of their evolution across different historical periods. In this work, we propose a method based on deep learning to assist experts in identifying the evolutionary patterns of a given pottery type within their specified chronological divisions. First we train a convolutional neural network for pottery classification, extracting low and high level features that represent different ages of pottery samples. Next, we employ clustering algorithms to identify representative potteries for each historical period based on high level features. To facilitate intuitive comparisons across different ages, we use shallow features and compute cosine similarities between potteries, visualizing shape and decoration differences. This approach enhances understanding of pottery evolution patterns directly through visual analysis. The effectiveness and efficiency of our proposed method are evaluated by validating it on three distinct era division cases using data from the Dabagou and Miaozigou archaeological sites, which represent the Miaozigou culture and exhibit clear evolutionary patterns. Our method identifies representative artifacts for each era and uncovers their evolutionary patterns effectively and efficiently, achieving conclusions comparable to those of experts while significantly reducing time compared to traditional manual methods.

Effect of Hydroxyapatite Nanoparticle Crystallinity and Colloidal Stability on Cytotoxicity.

Hydroxyapatite nanoparticles (nHA) have gained attention as potential intracellular drug delivery vehicles due to their high binding affinity for various biomolecules and pH-dependent solubility. Yet, the dependence of nHA cytocompatibility on their physicochemical properties remains unclear since numerous studies have revealed starkly contrasting results. These discrepancies may be attributed to differences in size, shape, crystallinity, and aggregation state of nHA, which complicates fundamental understanding of the factors driving nHA cytotoxicity. Here, we hypothesize that nHA cytotoxicity is primarily driven by intracellular calcium levels following the internalization of nHA nanoparticles. By investigating the cytotoxicity of spherical nHA with different crystallinity and dispersity, we find that both lower crystallinity and increased agglomeration of nHA raise cytotoxicity, with nanoparticle agglomeration being the more dominant factor. We show that the internalization of nHA enhances intracellular calcium levels and increases the production of reactive oxygen species (ROS). However, only subtle changes in intracellular calcium are observed, and their physiological relevance remains to be confirmed. In conclusion, we show that nHA agglomeration enhances ROS production and the associated cytotoxicity. These findings provide important guidelines for the future design of nHA-containing formulations for biomedical applications, implying that nHA crystallinity and especially agglomeration should be carefully controlled to optimize biocompatibility and therapeutic efficacy.

Study on noise barrier shape for reducing Shinkansen noise using scale model experiment

Since Shinkansen viaducts are aging, a large-scale renovation project has been planned. In this project, aged noise barriers of various shapes are scheduled to be removed and replaced. After replacing the noise barriers, further noise reduction is required. Therefore, it is desirable to verify the relationship between shapes of noise barriers and noise reduction effects. Against this background, the scale model experiments were conducted in anechoic chamber, focusing on the heights, the edge shapes of noise barrier and the differences in the area where sound absorbing materials were applied to the noise barrier. In these experiments, noise levels outside a viaduct were evaluated when the conditions of the noise barrier were changed. As one of the results, it is shown that applying sound absorbing material as large an area as possible is effective in reducing noise, regardless of the differences of edge shapes. Based on the experiments, it is thought that noise barriers with simple shape for easy maintenance can be realized by effective use of sound absorbing materials for replacing the aged noise barriers.

Associations of ocular anterior segment structures with sex and age: the Yamagata study (Funagata).

To investigate the associations of tomographic parameters in anterior segment optical coherence tomography (AS-OCT) with sex and age in a cohort study. A cohort design. AS-OCT data from 391 Japanese participants aged ≥ 35 years were obtained using swept-source OCT. In the cornea, the keratometric power at the flat (Kf) and steep (Ks) meridians, maximum keratometric power (Kmax), keratometric cylinder, spherical power, regular astigmatism, asymmetry, higher-order irregularity (HOI) from the anterior and posterior surfaces, and the central and thinnest corneal thicknesses were evaluated. Also, anterior chamber depth (ACD), lens thickness, crystalline lens rise (CLR), and nasal and temporal angle opening distances at 500μm from the scleral spur (AOD500) were assessed. Sex differences and age-related changes were analyzed. Women exhibited higher anterior Kf, Ks, and Kmax and lower posterior Kf, Ks, and Kmax than men. The ACD and nasal/temporal AOD500 were shorter in women than in men. The CLR was higher in women, whereas the lens thickness did not differ between the sexes, indicating a more anteriorly positioned lens in women. Age-related changes included increased anterior/posterior HOI, increased lens thickness and CLR resulting in decreased ACD and AOD500. This study reveals sex-related differences in corneal shape, anterior chamber conformation, and lens position, as well as age-related changes in tomographic parameters. ACD, CLR, nasal and temporal AOD500 showed significant sex differences in the 50-70s, whereas lens thickness showed no difference.

Heterogeneity in happiness: A latent profile analysis of single emerging adults.

Whether attending college, entering the workforce, or finding a romantic partner, single emerging adults navigate a pivotal stage of their lives. The present cross-sectional study sought to examine the heterogeneity in happiness of single emerging adults (N = 1,073) with a person-centered, group-differential approach. Using five predictors of life satisfaction (friendship satisfaction, family satisfaction, self-esteem, neuroticism, and extraversion) as indicators in latent profile analysis (LPA), we identified five distinct profiles (or groups) of young singles. The profiles, ordered from favorable to unfavorable indicator patterns, presented diverse shape and level differences that corresponded to varying happiness levels. Singles in Profile 1 with the most favorable indicator patterns (e.g., high friendship satisfaction, low neuroticism) were the happiest, while those in Profile 5 with the least favorable indicator patterns (e.g., low friendship satisfaction, high neuroticism) were the unhappiest. In the middle profiles, singles often offset disadvantages in one area (e.g., high neuroticism) with advantages in others (e.g., high friendship satisfaction) to achieve average to somewhat high levels of happiness. Importantly, friendship satisfaction emerged as a vital indicator, often distinguishing which singles were happy or not. Covariate analyses further validated the profiles and revealed additional profile differences (e.g., gender, anxiety, depression). Overall, our findings underscore the essential role of satisfying friendships in promoting the well-being of single emerging adults.

Survival strategies of microalgae in response to fluctuating brine environments in Saroma-ko Lagoon sea ice, Hokkaido, Japan.

This study investigated the changes in sea ice temperature, microalgae species distribution, shape changes, and photosynthetic activity observed in the first-year ice that forms in winter in Saroma-ko Lagoon, Hokkaido, Japan. Temperatures at the bottom of the ice remained constant at -1.7°C, near the freezing point, while they varied between -6 and -1°C with diel fluctuations at the surface layer. Carefully collected algal samples showed high photosynthetic quantum yield and acclimation to the light intensities of individual ice layers; this indicates that the algal photosynthetic activity responds to dynamic changes in the ice environment, such as variations in temperature, salinity, and brine space. The algal communities consisted of more than 95% diatoms. Smaller algal cells were distributed in the upper layer of the sea ice compared to the lower layers. Chaetoceros sp., the dominant small-cell species, was evenly distributed throughout the layers. In contrast, Detonula confervacea, the dominant large-cell species, was unevenly distributed in the lower layer, with smaller colony size and cell volume in the upper layer. The shape differences observed in this species were thought to be a response to the changing environment within the first-year sea ice.

Using two- and three-dimensional landmark data to examine the shape variation of Elliptio complanata from two heavily impounded rivers in northern New York (USA)

ABSTRACT Despite vast improvements in the quantification of shape variation with geometric morphometric methods, evaluating morphological variation in unionids has remained difficult due to the lack of measurable landmarks on shells and their overall morphological plasticity. In this study, we supplement traditional two-dimensional landmark data with three-dimensional landmark data. Using photogrammetry, we generate three-dimensional models that are landmarked. This approach adds a new, third dimension to capture shape changes, providing a more detailed understanding of the shell topography. With this method, we explore the differences in shell shape along river stretches of two heavily impounded rivers in northern New York (USA). We ask whether isolation by distance, presence of dams and/or difference in land use around sampling localities impact the shell morphologies of Elliptio complanata populations. Our data suggest that, although separated for almost a century, these unionid populations do not show a pattern of increased morphological difference with distance. But we find that broad, rounded morphs that are posteriorly extended occur more frequently in reservoir environments while unaltered river habitats have a higher number of slim and more elongated variants.