Variation In Shape Research Articles

Assessing brain neuroplasticity: Surface morphometric analysis of cortical changes induced by Quadrato motor training.

Morphological markers for brain plasticity are still lacking and their findings are challenged by the extreme variability of cortical brain surface. Trying to overcome the "correspondence problem," we applied a landmark-free method (the generalized procrustes surface analysis (GPSA)) for investigating the shape variation of cortical surface in a group of 40 healthy volunteers (i.e., the practice group) subjected to daily motor training known as Quadrato motor training (QMT). QMT is a sensorimotor walking meditation that aims at balancing body, cognition, and emotion. More specifically, QMT requires coordination and attention and consists of moving in one of three possible directions on corners of a 50 × 50 cm2. Brain magnetic resonance images (MRIs) of practice group (acquired at baseline, as well as after 6 and 12 weeks of QMT), were 3D reconstructed and here compared with brain MRIs of six more volunteers never practicing the QMT (naïve group). Cortical regions mostly affected by morphological variations were visualized on a 3D average color-scaled brain surface indicating from higher (red) to lower (blue) levels of variation. Cortical regions interested in most of the shape variations were as follows: (1) the supplementary motor cortex; (2) the inferior frontal gyrus (pars opercolaris) and the anterior insula; (3) the visual cortex; (4) the inferior parietal lobule (supramarginal gyrus and angular gyrus). Our results show that surface morphometric analysis (i.e., GPSA) can be applied to assess brain neuroplasticity processes, such as those stimulated by QMT.

When to Go Against the Flow: Examining Patterns of Performance Over Multiday Migration Events in the Hawaiian Stream Fish, 'O'opu Nōpili (Sicyopterus stimpsoni).

Many animals migrate across regions of their geographic range as part of extended events, with groups of individuals proceeding through areas of travel on several successive days. Early migrating individuals may have an advantage over late migrating individuals by gaining early access to the resources at the eventual destination. For situations where early access to resources would provide an advantage, specific sets of locomotor traits might be found among individuals that are earlier migrators. We tested for associations between migration timing and traits related to escape responses, climbing, and morphology in the amphidromous Hawaiian stream goby, 'o'opu nōpili (Sicyopterus stimpsoni). In this species, juvenile fish migrate in pulses over several days immediately following flash floods. We collected daily measurements of escape responses and waterfall climbing from juvenile fish arriving at streams from the ocean. We found that escape performance showed mainly stochastic variation across migrating individuals tested on successive days. In contrast, some metrics of climbing performance decrease over successive pulses during a migration event. We also found more variation in body shape among fish from early pulses during migration events compared to later in pulses. These results could have implications for guiding conservation efforts, identifying critical time windows for protection as periods with the greatest likelihood of successful migrants.

Identifying Morphs of the Yellow-Legged Hornet (Vespa velutina) and Other Pests of Quarantine Importance with Geometric Morphometrics

We assess the accuracy of geometric morphometrics (GMM) for determining the origin of insects of quarantine importance using the Asian hornet (Vespa velutina Lep.1836) as a case study. This species is highly variable, has an extensive natural distribution, and has been transported to many regions of the world. Forewing landmarks were applied to a large sample of regionally specific color morphs (previously considered “subspecies”) from across the species’ native Asian range. We reconfirm that GMM can statistically distinguish geographic variants independent of the color patterns that have heretofore been used for provenance, but which have been suspected of being unreliable. Almost all morphs in our analyses were statistically different except the centrally located V. v. variana, whose range lies between the continental V. v. auraria Smith, 1852, and V. v. nigrithorax du Buysson, 1905 morphs, and the Malaysian and Indonesian morphs. Even with moderate-sized training samples, discriminant function analysis (DFA) was able to classify geographic morphos with about 90% accuracy (ranging from 60% to 100%). We apply these results to determine the origin of a dead wasp recently intercepted in a mail parcel in Utah. Both DFA and continuous-trait maximum-likelihood clustering suggest that the Utah specimen belongs to the nigrithorax morph, which is native to southern China but now invasive in Europe, Japan, and Korea. These results are also supported by DNA barcode analysis, which groups the Utah individual with nigrithorax populations in South Korea and Japan. The relationship between variation in wing shape and genetic differentiation deserves further study, but molecular data are consistent with the GMM results suggesting that morphometric comparisons may be able to identify and provenance intercepted specimens quickly and inexpensively when molecular sequences and taxonomic specialists are unavailable.

Studies on Genetic Divergence in Cabbage Genotypes in the Mid Hills of Solan District, Himachal Pradesh, India

Cabbage (Brassica oleracea var. capitata L.) is one of the most important vegetables of the family Brassicaceae and is grown under temperate to tropical climatic conditions for its head in more than ninety countries throughout the world. The diversity in cabbage is immense due to the presence of variation in shape, size, weight and maturity of heads. The greater the variability in the available germplasm, more would be the chances for selecting superior genotypes for use in breeding programmes or direct use as cultivars. Twenty three genotypes of cabbage including check variety, Golden Acre were evaluated in a Randomized Complete Block Design (RCBD) with three replications. The results concluded that twenty-three diverse genotypes of cabbage were grouped into four clusters. The resultant four clusters showed genetic diversity and maximum number of genotypes were accommodated in cluster I (12) followed by II (7), IV (3) and III (1). The maximum inter cluster distance was recorded between cluster II and III, therefore, the hybridization between the genotypes of cluster II and III can be performed to get superior hybrids or recombinants in segregating populations for further breeding programmes. Based on the mean performance, genetic distance and clustering pattern, inter-varietal crosses can be made which may be advantageous in creating wider variability for better heterotic combinations and transgressive segregants in cabbage.

Identifying Street Environmental Factors That Attract Public Attention from the Jogger’s Perspective: A Multiscale Spatial Exploration

Improving street jogging environments can promote urban health and sustainability, especially within urban built-up areas. Public attention to the environment during jogging has not been sufficiently studied, and the recommended route data from the fitness app offers an opportunity for multiscale spatial exploration. Initially, by analyzing the recommendation reason text, the study identified 22 environmental factors and proposed the Environmental Factor Public Attention Intensity (EFPAI) for quantification, with subsequent comparisons to expert opinions. Further, by analyzing five types of data from the recommended routes, the relationships between EFPAI and jogging frequency, route shape, spatial distribution, and seasonal variations were uncovered. The study revealed: (1) discrepancies between expert opinions and public attention, with experts more likely to overlook factors such as slope, visual quality, width, and acoustic quality; (2) the public tends to notice factors like pedestrians, green spaces, waterfront spaces, landscapes, culture, sports facilities, and accessibility on routes with high jogging frequency; (3) EFPAI for traffic infrastructure, waterfront spaces, landscapes, residential areas, and campuses is associated with route shape; (4) EFPAI of certain environmental factors is influenced by urban geographical spatial factors, and substantial differences exist between different cities. Specific recommendations were provided from three different scales—site scale, street block scale, and urban scale—to guide the resolution of issues in planning and decision-making processes for urban renewal.

Exploring the Impact of Noise and Image Quality on Deep Learning Performance in DXA Images.

Segmentation of the femur in Dual-Energy X-ray (DXA) images poses challenges due to reduced contrast, noise, bone shape variations, and inconsistent X-ray beam penetration. In this study, we investigate the relationship between noise and certain deep learning (DL) techniques for semantic segmentation of the femur to enhance segmentation and bone mineral density (BMD) accuracy by incorporating noise reduction methods into DL models. Convolutional neural network (CNN)-based models were employed to segment femurs in DXA images and evaluate the effects of noise reduction filters on segmentation accuracy and their effect on BMD calculation. Various noise reduction techniques were integrated into DL-based models to enhance image quality before training. We assessed the performance of the fully convolutional neural network (FCNN) in comparison to noise reduction algorithms and manual segmentation methods. Our study demonstrated that the FCNN outperformed noise reduction algorithms in enhancing segmentation accuracy and enabling precise calculation of BMD. The FCNN-based segmentation approach achieved a segmentation accuracy of 98.84% and a correlation coefficient of 0.9928 for BMD measurements, indicating its effectiveness in the clinical diagnosis of osteoporosis. In conclusion, integrating noise reduction techniques into DL-based models significantly improves femur segmentation accuracy in DXA images. The FCNN model, in particular, shows promising results in enhancing BMD calculation and clinical diagnosis of osteoporosis. These findings highlight the potential of DL techniques in addressing segmentation challenges and improving diagnostic accuracy in medical imaging.

Permian tectonic evolution of the proto-Japan and East Asia: Insights from detrital zircon geochronology and crystal morphology

Combination analyses of detrital zircon ages and morphology from Permian sandstones in Japan provide evidence of orogenic evolution caused by collision in East Asia and reveal their paleogeographic setting. This study compares published and newly measured data from Permian fore-arc accretionary complexes (Akiyoshi Belt) and back-arc basin deposits (Maizuru Belt) in the Inner Zone of Southwest Japan. The fore-arc deposits and lower part of the back-arc deposits consist mainly of approximately 300–250 Ma zircon grains that are close to the depositional ages and are generally angular to subangular. These sediments formed around the Late Paleozoic volcanic arc isolated from the older continental crust, and their source rocks were exposed immediately prior to their erosion and transport and were transported directly to the depositional site in a relatively short time. In contrast, upper part of the back-arc deposits generally contains approximately 2,700–1,800 and 500–250 Ma zircon grains, which are commonly older than their depositional ages and are rounded. These grains were supplied from multiple sources, such as the Paleozoic volcanic arc and Precambrian continental block, and were affected by long-distance transport and a strong abrasion effect during transport. Comprehensive detrital zircon data emphasize that the oceanic arc–back-arc basin–continental margin system formed along the eastern margin of East Asia, and that the volcanic arc collided with the eastern margin of the Sino-Korean Block during the Permian. The variation in detrital zircon ages and shapes of back-arc deposits provides a constraint for modeling the East Asian Permian collision. Detritus derived from continental crust was captured by a back-arc basin and blocked by the uplift zone of the volcanic arc. However, a small amount of detritus originating from the continental crust was supplied to the fore-arc.

Virtual reconstruction of orbital defects using Gaussian process morphable models.

The conventional method to reconstruct the bone level for orbital defects, which is based on mirroring and manual adaptation, is time-consuming and the accuracy highly depends on the expertise of the clinical engineer. The aim of this study is to propose and evaluate an automated reconstruction method utilizing a Gaussian process morphable model (GPMM). Sixty-five Computed Tomography (CT) scans of healthy midfaces were used to create a GPMM that can model shape variations of the orbital region. Parameter optimization was performed by evaluating several quantitative metrics inspired on the shape modeling literature, e.g. generalization and specificity. The reconstruction error was estimated by reconstructing artificial defects created in orbits from fifteen CT scans that were not included in the GPMM. The developed algorithms utilize the existing framework of Gaussian process morphable models, as implemented in the Scalismo software. By evaluating the proposed quality metrics, adequate parameters are chosen for non-rigid registration and reconstruction. The resulting median reconstruction error using the GPMM was lower (0.35 ± 0.16mm) compared to the mirroring method (0.52 ± 0.18mm). In addition, the GPMM-based reconstruction is automated and can be applied to large bilateral defects with a median reconstruction error of 0.39 ± 0.11mm. The GPMM-based reconstruction proves to be less time-consuming and more accurate than reconstruction by mirroring. Further validation through clinical studies on patients with orbital defects is warranted. Nevertheless, the results underscore the potential of GPMM-based reconstruction as a promising alternative for designing patient-specific implants.

Linear measurements and shape analysis in the calcaneus of selected dog breeds.

The vast array of dog breeds showcases a remarkable diversity that extends to osteological differences. Exploring these morphological distinctions and establishing reference data for various dog breeds are essential steps in comprehending the evolutionary changes that dogs have undergone. In this study, we conducted linear measurements of the calcaneus and performed shape analyses on selected dog breeds to elucidate distinctive characteristics among them. X-ray images of the calcaneus from six different dog breeds-Maltese Terrier, Toy Poodle, Pomeranian, Cavalier King Charles Spaniel, French Bulldog and Golden Retriever-were utilized for this investigation. Radiological images were obtained from a medio-lateral exposure, positioned 30 cm away from the x-ray device. From these images, four linear length measurements and two angle values were extracted. Additionally, a 2D geometric morphometric analysis was conducted using 32 semi landmarks placed on the radiological images. Linear measurements were assessed using ANOVA, while principal component analysis was employed to examine shape variations across all individuals. Shape differences between species were further elucidated through canonical variates analysis. The results revealed that the Golden Retriever exhibited the highest values for linear measurements, while the Pomeranian showed the lowest. Maltese Terriers displayed the highest dorsal calcaneal angle value. Notably, there were significant differences in calcaneal body length among all breeds, except for the Toy Poodle and Cavalier King Charles Spaniel. Moreover, Maltese Terriers exhibited statistically distinct angular measurements compared to other breeds. Principal component analysis unveiled that the first principal component explained 32.69% of the total variation, with the cranial edge of the calcaneal body being closer to the body in individuals with higher values. Shape variations also indicated that Golden Retrievers displayed a broader range of shapes compared to French Bulldogs, which exhibited a more conservative distribution. While there was no clear breed-specific distinction according to the first principal component, Cavalier King Charles Spaniels generally showed lower values. In canonical variates analysis, distinctions in calcaneal shape between species were apparent, with Golden Retrievers, Cavalier King Charles Spaniels and French Bulldogs displaying positive values for the first canonical variates. The highest Procrustes distance was observed between Maltese Terriers and Cavalier King Charles Spaniels. Notably, allometry was found to be statistically insignificant. This comprehensive study utilized both linear and geometric morphometric analyses based on x-ray images, yielding promising results. The integration of imaging systems in veterinary anatomy research presents numerous opportunities for studying animal welfare and health, utilizing various materials such as bones and cadavers. These advancements hold the potential for further enhancing our understanding of animal morphology and well-being.

Role of Shape Deformation of DNA-Binding Sites in Regulating the Efficiency and Specificity in Their Recognition by DNA-Binding Proteins.

Accurate transcription of genetic information is crucial, involving precise recognition of the binding motifs by DNA-binding proteins. While some proteins rely on short-range hydrophobic and hydrogen bonding interactions at binding sites, others employ a DNA shape readout mechanism for specific recognition. In this mechanism, variations in DNA shape at the binding motif resulted from either inherent flexibility or binding of proteins at adjacent sites are sensed and capitalized by the searching proteins to locate them specifically. Through extensive computer simulations, we investigate both scenarios to uncover the underlying mechanism and origin of specificity in the DNA shape readout mechanism. Our findings reveal that deformation in shape at the binding motif creates an entropy funnel, allowing information about altered shapes to manifest as fluctuations in minor groove widths. This signal enhances the efficiency of nonspecific search of nearby proteins by directing their movement toward the binding site, primarily driven by a gain in entropy. We propose this as a generic mechanism for DNA shape readout, where specificity arises from the alignment between the molecular frustration of the searching protein and the ruggedness of the entropic funnel governed by molecular features of the protein and arrangement of the DNA bases at the binding site, respectively.

Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility.

The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.e., anisokaryosis and/or shape) using a segmentation model. Its performance was evaluated on 46 cPC cases with comprehensive follow-up data regarding its accuracy in nuclear segmentation and its prognostic ability. Its assessment of NP was compared to manual morphometry and established prognostic tests (pathologists' NP estimates (n = 11), mitotic count, histological grading, and TNM-stage). The standard deviation (SD) of the nuclear area, indicative of anisokaryosis, exhibited good discriminatory ability for tumor-specific survival, with an area under the curve (AUC) of 0.80 and a hazard ratio (HR) of 3.38. The algorithm achieved values comparable to manual morphometry. In contrast, the pathologists' estimates of anisokaryosis resulted in HR values ranging from 0.86 to 34.8, with slight inter-observer reproducibility (k = 0.204). Other conventional tests had no significant prognostic value in our study cohort. Fully automated morphometry promises a time-efficient and reproducible assessment of NP with a high prognostic value. Further refinement of the algorithm, particularly to address undersegmentation, and application to a larger study population are required.

Bridging Formal Shape Models and Deep Learning: A Novel Fusion for Understanding 3D Objects

This article describes a novel fusion of a generative formal model for three-dimensional (3D) shapes with deep learning (DL) methods to understand the geometric structure of 3D objects and the relationships between their components, given a collection of unorganized point cloud measurements. Formal 3D shape models are implemented as shape grammar programs written in Procedural Shape Modeling Language (PSML). Users write PSML programs to describe complex objects, and DL networks estimate the configured free parameters of the program to generate 3D shapes. Users write PSML programs to enforce fundamental rules that define an object class and encode object attributes, including shapes, components, size, position, etc., into a parametric representation of objects. This fusion of the generative model with DL offers artificial intelligence (AI) models an opportunity to better understand the geometric organization of objects in terms of their components and their relationships to other objects. This approach allows human-in-the-loop control over DL estimates by specifying lists of candidate objects, the shape variations that each object can exhibit, and the level of detail or, equivalently, dimension of the latent representation of the shape. The results demonstrate the advantages of the proposed method over competing approaches.

From slenderness to robustness: Understanding long bone shape in sigmodontine rodents.

The morphological evolution of the appendicular skeleton may reflect the selective pressures specific to different environments, phylogenetic inheritance, or allometry. Covariation in bone shapes enhances morphological integration in response to ecological specializations. In contrast to previous multivariate studies using classical linear morphometry, we use a geometric morphometric approach to explore the morphological diversity of long bones and examine relationships between ecological categories and morphological characters in a species-rich and ecomorphologically diverse group of rodents. We examined the humerus, ulna, femur, and tibiofibula of 19 sigmodontine species with different locomotor types (ambulatory, quadrupedal-saltatorial, natatorial, semifossorial and scansorial) to investigate the influence of locomotor type and phylogeny on limb bone shape and morphological integration of the appendicular skeleton. This study represents the most detailed examination of the morphological diversity of long bones in sigmodontines, employing geometric morphometrics within an ecomorphological framework. Our results indicate that functional demands and evolutionary history jointly influence the shape of forelimb and hindlimb bones. The main variation in bone shape is associated with a slenderness-robustness gradient observed across all ecological categories. Quadrupedal-saltatorial species, with their need for agility, possess slender and elongated limbs, while natatorial and semifossorial species exhibit shorter and more robust bone shapes, suited for their respective environments. This gradient also influences bone covariation within limbs, demonstrating interconnectedness between elements. We found functional covariation between the ulna-tibiofibula and humerus-tibiofibula, likely important for propulsion, and anatomical covariation between the humerus-ulna and femur-tibiofibula, potentially reflecting overall limb structure. This study demonstrates that the versatile morphology of long bones in sigmodontines plays a critical role in their remarkable ecological and phylogenetic diversification.

Principles of miRNA/miRNA* function in plant MIRNA processing.

MicroRNAs (miRNAs) are essential regulators of gene expression, defined by their unique biogenesis, which requires the precise excision of the small RNA from an imperfect fold-back precursor. Unlike their animal counterparts, plant miRNA precursors exhibit variations in sizes and shapes. Plant MIRNAs can undergo processing in a base-to-loop or loop-to-base direction, with DICER-LIKE1 (DCL1) releasing the miRNA after two cuts (two-step MIRNAs) or more (sequential MIRNAs). In this study, we demonstrate the critical role of the miRNA/miRNA* duplex region in the processing of miRNA precursors. We observed that endogenous MIRNAs frequently experience suboptimal processing in vivo due to mismatches in the miRNA/miRNA* duplex, a key region that fine-tunes miRNA levels. Enhancing the interaction energy of the miRNA/miRNA* duplex in two-step MIRNAs results in a substantial increase in miRNA levels. Conversely, sequential MIRNAs display distinct and specific requirements for the miRNA/miRNA* duplexes along their foldback structure. Our work establishes a connection between the miRNA/miRNA* structure and precursor processing mechanisms. Furthermore, we reveal a link between the biological function of miRNAs and the processing mechanism of their precursors with the evolution of plant miRNA/miRNA* duplex structures.

Geologically constrained geometry inversion and null-space navigation to explore alternative geological scenarios: a case study in the Western Pyrenees

SUMMARY Reducing the gap between geophysical inversion and geological interpretation can be achieved by integrating geological modelling into geophysical inversion. For this, we use a generalized, iterative level-set gravity inversion scheme in which geological units are deformed automatically. During the inversion process, a regularization term is defined using automated geological modelling to account for geological data and principles. This provides model-dependent geological constraints and encourages geological realism throughout inversion. To alleviate the dependence on the starting model and consider the possibility of features unseen by direct observations, an automated geophysical data-driven method is proposed to insert new rock units in the model. Uncertainty quantification is achieved through the null-space shuttle algorithm, which is used to generate a series of alternative models that are consistent with geophysical data. This methodology is applied to assess the uncertainties of a pre-existing 3-D crustal-scale geological model of the Western Pyrenean orogeny (France, Spain). The area is characterized by a positive gravity anomaly generally attributed to the presence of a shallow mantle body. The impact of variations in shape and density of key crustal and mantle features is investigated. Different scenarios are explored in 3-D space to produce a range of viable, relatively simple crustal-scale models of the area. This application demonstrates the capability and potential of this approach to evaluate alternative interpretations of geophysical data. The results show the plausibility of scenarios with a shorter subducted Iberian lower crust and a denser Axial Zone than in the pre-existing model.

Ultra-Flexible microwave absorber of PEDOT:PSS/Melamine composite film with wide tunable frequency controlled by Self-Strain sensing

The exploration of smart microwave (MW) absorption materials with excellent mechanical properties and wide frequency tuning ability is challenging work. Herein, an ultra-flexible MW absorber with wide frequency modulation by itself strain sensing has been successfully constructed, which is realized by introducing doped conductive poly (3,4-ethylenedioxythiophene)-poly (styrenesulfonate) (PEDOT:PSS) with dimethyl sulfoxide (DMSO) into three-dimensional melamine foam (MF) network. The formed MF/P-D20 composite itself is a piezoresistive sensor with a high sensitivity. Most importantly, it is found that the absorption frequency band of the MF/P-D20 composite film can be controllably and reversibly modulated in a wide frequency range from S to Ku bands by changing the compression strain monitored by the value of ΔR/R0. Furthermore, theoretical simulations and experimental findings confirm that the variations of pore shape and size after compression serve as a crucial factor responsible for shifting the enhanced electron flux density and MW loss to higher frequency, which consequently induces the shift of impedance matching and sequent MW absorption to higher frequency. The MW absorber also shows excellent properties of mechanical robustness, thermal insulation, electro-thermal conversion and retardant. This study provides insights into the smart and reversible control of MW absorption properties and paves the way for tuning MW absorption frequency in wide frequency.

Shape variation in cranium, mandible and teeth in selected mouse strains.

There are different strains of laboratory mouse used in many different fields. These strains differ anatomically. In order to determine these anatomical differences, shape analysis was conducted according to species. CD-1, C57bl/6 and Balb-c strains were preferred to study these differences. Forty-eight adult mouse strains belonging to these strains were utilized. The bones were photographed and geometric morphometry was applied to these photographs. Principal Component Analysis was applied to determine shape variations. In Principal component 1 for cranium, CD-1 and C57bl/6 strain groups showed different shape variations, while Balb-c strain group showed similar shape variations to the other strain groups. Principal Component 1 for the mandible separated the CD-1 and C57bl/6 strain groups in terms of shape variation. Principal Component 2 explained most of the variation between the C57bl/6 and CD-1 lineage groups. In PC1 for molars, the CD-1 group showed a different shape variation from the other groups. Mahalanobis distances and Procrustes distances were measured using Canonical variance analysis to explain the differences between the lineage groups. These measurements were statistically significant. For cranium, in canonical variate 1, CD-1 group of mouse and Balb-c group of mouse were separated from each other. In canonical variate 2, C57bl/6 group of mouse were separated from the other groups. For mandible, Balb-c group of mouse in canonical variate 1 and CD-1 group of mouse in canonical variate 2 were separated from the other groups. For molars, CD-1 group of mouse in canonical variate 1 and Balb-c group of mouse in canonical variate 2 were separated from the other groups. It was thought that these anatomical differences could be caused by genotypic factors as well as dietary differences and many different habits that would affect the way their muscles work.

Stress-induced changes in magnetite: insights from a numerical analysis of the Verwey transition

SUMMARY Magnetic susceptibility behaviour around the Verwey transition of magnetite (≈125 K) is known to be sensitive to stress, composition and oxidation. From the isotropic point (≈130 K) to room temperature, decreasing magnetic susceptibility indicates an increase in magnetocrystalline anisotropy. In this study, we present a model which numerically analyses low-temperature magnetic susceptibility curves (80–280 K) of an experimentally shocked (up to 30 GPa) and later heated (973 K) magnetite ore. To quantify variations of the transition shape caused by both shock and heating, the model statistically describes local variations in the Verwey transition temperature within bulk magnetite. For the description, Voigt profiles are used, which indicate variations between a Gaussian and a Lorentzian character. These changes are generally interpreted as variations in the degree of correlation between observed events, that is between local transition temperatures in the model. Shock pressures exceeding the Hugoniot elastic limit of magnetite ($ \ge $5 GPa) cause an increase in transition width and Verwey transition temperature, which is partially recovered by heat treatment. Above the Verwey transition temperature, susceptibility variations related to the magnetocrystalline anisotropy are described with an exponential approach. The room temperature magnetic susceptibility relative to the maximum near the isotropic point is reduced after shock, which is related to grain size reduction. Since significant oxidation and cation substitution can be excluded for the studied samples, variations are only attributed to changes in elastic strain associated with shock-induced deformation and annealing due to heat treatment. The shocked magnetite shows a high correlation between local transition temperatures which is reduced by heat treatment. The model allows a quantitative description of low-temperature magnetic susceptibility curves of experimentally shocked and subsequently heat-treated polycrystalline magnetite around the Verwey transition temperature. The curves are accurately reproduced within the experimental uncertainties. Further applications for analysing magnetite-bearing rocks seem possible if model parameters, such as for oxidation are included into the model.

DFT Atomic‐Scale Insight into Pt/Cu Single Atom Alloy Clusters Supported on γ‐Al2O3: The Effect of Hydrogen Environment

Single atom alloy (SAA) clusters formed by anchoring single atoms in small supported host clusters are emerging as catalysts with high performance. In this work, density functional theory (DFT) calculations and ab‐initio molecular dynamics (AIMD) simulations are performed to study the stability and the structure evolution of γ‐alumina‐supported platinum/copper SAA clusters of sub‐nanometer size in hydrogen environment. Due to the strong dynamic nature of both Cu cluster and anchored Pt single atom and their evolving interaction with the support, different isomers with different geometric and energetic properties are predicted. Extensive sampling through AIMD simulations reveals strong effect of hydrogen on the location of Pt single atom and strong variation of the cluster shape, evolving from 3D to concave and planar shapes wetting the alumina support. Interfacial site location of Pt single atom is found to be hydrogen coverage dependent. When the hydrogen coverage increases, the Pt single atom located preferentially at the interfacial site is pulled up by hydrogen atoms toward the upper surface Cu layers. The interaction of Pt/Cu cluster with alumina is predicted to decrease with increasing hydrogen coverage. Finally, electronic structure analysis reveals dramatic effect of hydrogen on the metallic nature of the catalysts.

Analysis of knee-bending motion through three-dimensional scanning for advanced brace design

Knee braces have been increasing in popularity as a means to support joint stability and promote the healing process. In order to enhance the fit, comfort, and design of knee braces, this study investigates knee shape deformations across four knee-bending angles from 0° to 90°. Using three-dimensional (3D) scanning technology, the knee contours of 50 Asian males aged between 22 and 33 were examined. The reliability of the 3D measurements was validated through comparisons with tape measurements on the actual body. The analysis revealed a stretch of the skin covering the patella bone with a notable vertical strain of 19% and horizontal stretching of 7%. The circumference along the muscle belly at the thigh (15 cm above the center of the patella) and at the calf (7.5 cm below the center of the patella) showed no significant changes with different bending angles, and can be used as an indicator for sizing of knee braces. However, at the patella bone level, the bending of the knee from 0° to 90° increased the knee circumference by 6.4%. The results from sectional analysis showed the asymmetry and the lateral shifting of the knee joint during bending. The findings offer guidelines for the design and optimization of knee braces to address knee deformations and individual body shape variations.