Measurement Geometry Research Articles

Enhancing prediction of cancer therapy-related cardiomyopathy from surveillance echocardiograms: A Children’s Oncology Group (COG) report.

10012 Background: Many childhood cancer patients receive cardiotoxic therapies and need surveillance for therapy-related cardiomyopathy (CM). (Echo)cardiography is used to screen for cardiac dysfunction but has relatively poor discriminatory ability to predict who will develop CM. We sought to identify combinations of echo parameters that can better predict which patients subsequently develop CM. Methods: Longitudinal echos (obtained per routine care) of patients diagnosed with cancer < 21y who subsequently met CM criteria (left ventricular [LV] ejection fraction ≤50% / fractional shortening ≤28%, ≥2 times, with ≥1 time after completion of cancer therapy) plus clinical data were collated from COG sites. Echos and data from patients without CM were also collated. All echos were centrally remeasured for 42 routinely reported parameters in blinded fashion. We applied least absolute shrinkage and selection operator (LASSO) to fit logistic models to identify the most influential predictors for CM development within 2 and 5y of echo, plus age and sex. Data were randomly split into training (85%) and test (15%) sets with 10-fold cross validation. Prediction accuracy was calculated using area under the ROC curve (AUC), based on the model that provided the minimum mean cross-validated error. Results: Echos from 88 CM cases (248 echos predating CM) and 126 non-cases (518 echos) were available. Patients (n = 214) were diagnosed at mean age 7.7±5.2y with mean 9.5±4.0y follow-up. Mean doxorubicin equivalent doses for cases and non-cases were 350±188 and 272±199 mg/m2, respectively. For 2y CM prediction, models achieved training AUC 0.85 (95%CI 0.78-0.92; 261 echos) and test AUC 0.74 (95% CI 0.74-0.90; 46 echos). Factors selected included age, 2-dimensional (2D) measurements of LV geometry (LV systolic and end-systolic dimensions, and posterior wall thickness), systolic function (M-mode fractional shortening), diastolic function (mitral inflow E wave, septal E’, septal A’), and a measurement of combined systolic and diastolic function (myocardial performance index). For 5y CM prediction, models achieved training AUC 0.90 (95%CI 0.85-0.95; 175 echos) and test AUC 0.89 (95%CI 0.78-0.99; 30 echos). Age, LV end-systolic dimension (2D and M-mode), M-mode LV posterior wall thickness, 2D wall thickness-dimension ratio, mitral inflow E, septal E’, septal A’, and the myocardial performance index were selected. At both times 2D end-systolic dimension was the most influential parameter. Inclusion of anthracycline and chest radiotherapy dose did not meaningfully improve the AUCs. Conclusions: Prediction models that incorporate conventional echo data may be able to accurately identify childhood cancer patients at high risk of developing CM 2-5y prior to CM diagnosis. This may provide a window of opportunity to introduce interventions that may arrest or slow CM progression.

Phase Image Decoding Algorithm for Three-Dimensional Geometry Measurements of Dynamic Objects

Phase Image Decoding Algorithm for Three-Dimensional Geometry Measurements of Dynamic Objects

Performance and uncertainty of the all-wave net radiation space-time integrators by treetops

The quantification of electromagnetic energy exchanged between plants and their environment is important for ecophysiological studies. Measurement techniques have been developed for the determination of these changes in different spatial scales. In the literature are found some studies describing the use of devices carrying radiometers rotating around isolated trees. Otherwise, when it comes to plantations with spatial arrangement of trees in hedgerows, it is more convenient to use a notional cylindrical geometry of measurement. In this paper we described technical details of assembling devices moving along a stretch of the planting line, generating a notional cylindrical geometry for space-time integration of the all-wave radiation absorbed by the trees in hedgerow. Throughout the experiments it was verified the need for minor modifications which led to the improvement of mobile systems of measurement. Tests with the device free of plants indicated that the errors arising from the null deviation in this condition were sufficiently small. Analyses of measurements of each net radiometer over several days and, also comparison with measurement of daily latent heat calculated from sap flow in 24-hr period indicated that the proposed system gives accurate measurements, being reliable for testing the results of physical-mathematical models.

Predicting multiaxial fatigue life of FGH96 superalloy based on machine learning models by considering failure process and loading paths

Wide applications of powder metallurgy superalloys in mechanical engineering imply the great significance of studying their mechanical properties. Fatigue property of superalloys is complicated because of many influencing factors with variability. This means the difficulty to correctly predict a real-valued fatigue life due to the propagation of error. Specially, extreme dispersion of multiaxial fatigue life is an important challenge of fatigue life prediction for superalloys. In this paper, we focus on the difficulty and dispersion by developing machine learning (ML) models for predicting interval-valued fatigue life of FGH96 superalloy under multiaxial loadings. Some data extracted from fatigue failure process of FGH96 superalloy is used to develop ML methods such as back-propagation neural network (BP), support vector regression (SVR) and random forest (RF). Then considering the randomness in the data originating from multiaxial loading paths, measures of sample geometry and mechanical loading, testing system error and others, the low cycle fatigue life of FGH96 superalloy is predicted as an interval with a probability distribution. The obtained results are analyzed and compared with the fatigue experimental observations of FGH96 superalloy under six loading paths. It is found that the multiaxial fatigue failure behavior of FGH96 superalloy can be effectively described, and the developed ML models exhibit some advantages to tackle the difficulty and dispersion in predicting multiaxial fatigue life of alloys.

Programmable large-scale simulation of bosonic transport in optical synthetic frequency lattices

Photonic simulators using synthetic frequency dimensions have enabled flexible experimental analogues of condensed-matter systems. However, so far, such photonic simulators have been limited in scale, yielding results that suffer from finite-size effects. Here we present an analogue simulator capable of simulating large two-dimensional (2D) and 3D lattices, as well as lattices with non-planar connectivity. Our simulator takes advantage of the broad bandwidth achievable in photonics, allowing our experiment to realize programmable lattices with over 100,000 lattice sites. We showcase the scale of our simulator by demonstrating the extension of bandstructure spectroscopy from 1D to 2D and 3D lattices. We then report the direct observation of time-reversal symmetry-breaking in a triangular lattice in both momentum and real space, as well as site-resolved occupation measurements in a tree-like geometry that serves as a toy model in quantum gravity. Moreover, we demonstrate a method to excite arbitrary multisite states, which we use to study the response of a 2D lattice to both conventional and exotic input states. Our work highlights the scalability and flexibility of optical synthetic frequency dimensions. Future experiments building on our approach will be able to explore non-equilibrium phenomena in high-dimensional lattices and to simulate models with nonlocal higher-order interactions. Analogue photonic simulators have so far suffered from severe finite size effects and limited programmability. Now, a frequency-mode photonic simulator enables the simulation of large-scale models in two and three dimensions.

Chronological-hybrid optimization enabled deep learning for boundary segmentation and osteoporosis classification using femur bone

ABSTRACT This paper devises a technique for diagnosing and classifying osteoporosis using the femur bone’s X-ray images. The devised approach uses the following phases: image acquisition, pre-processing, segmentation of femur boundary, measurement of femoral geometry, feature mining, and osteoporosis categorization. Here, femur boundary segmentation is done using the Deep Contour Aware Network (DCAN), which is trained by the Chronological Artificial Ecosystem Optimization (CAEO) algorithm. Then, the femoral geometry is measured and the most relevant features in the image are identified. Further, osteoporosis is classified using the Convolutional Neural Network (CNN) with Transfer Learning (TL), where the CNN is employed with the hyperparameters of the pre-trained model, LeNet. Here, the Chronological Artificial Ecosystem Tasmanian Devil Optimization (CAETDO) algorithm optimizes the classification process. The CAETDO-CNN-TL is examined based on metrics and have the values of 0.910, 0.927, 0.928, and 0.904 for precision, True Negative Rate (TNR), True Positive Rate (TPR), and accuracy, correspondingly.

Five-probe method for finite samples - an enhancement of the van der Pauw method

A new five-point method for measuring the sheet resistance of finite samples of any shape is presented. The method is strict for point-size contacts and is a kind of extension of the van der Pauw method. Three contacts have to be located at the periphery of the sample while the other two can be at arbitrary positions. A particularly useful measurement geometry is keeping the three periphery contacts at constant positions and scanning the sample’s interior with the two other contacts with a constant separation between them. In this way, the local sheet resistance and thus homogeneity can be measured irrespectively of the location of the sample’s border. The results of experimental measurements are fully consistent with the presented theory and results of numerical simulations.

Individualized modeling for the peripheral optics of the human myopic eye.

Individualized optical modelling of the eye is a useful tool to estimate optical properties of the eye from a set of geometrical parameters. In the context of myopia research, it is important to understand not only the on-axis (foveal) optical quality, but also the peripheral profile. This work describes a method to extend on-axis individualized eye modeling to the peripheral retina. Using measurements of corneal geometry, axial distances, and central optical quality from a group of young adults, a crystalline lens model was built to help reproduce the peripheral optical quality of the eye. Subsequent individualized eye models were generated from each of the 25 participants. These models were used to predict the individual peripheral optical quality over the central 40 degrees. Outcomes of the final model were then compared to the actual measurements of peripheral optical quality in these participants, measured with a scanning aberrometer. A high agreement was found between the final model and measured optical quality for the relative spherical equivalent and J0 astigmatism.

Estimation of the trajectory and attitude of railway vehicles using inertial sensors with application to track geometry measurement

This paper describes a novel method for the estimation of the trajectory and orientation of a rigid body moving along a railway track. Compared to other recent developments in the literature, the presented approach has the significant advantage of using inertial sensors only, excluding global position and orientation sensors. The excluded sensors are compensated with an odometry system and previous knowledge of the design track geometry. The procedure is based on a kinematic model of the relative motion of the body with respect to the track, together with a Kalman filter algorithm. Two different approaches are used and compared for the estimation of the noise covariance matrices in the Kalman filter. One is based on the use of experimental results with a known output. The other one relies upon constrained maximum likelihood estimation. The calculated trajectory and orientation are applied in this research to the problem of track geometry measurement. A scale track is used for experimental validation, showing that results are sufficiently accurate for this application. The obtained results also reveal that the constrained maximum likelihood estimation performs similarly to the known-output method. This is very convenient because it allows a straightforward application of the algorithm in different scenarios.

Advanced Algorithm for Reliable Quantification of the Geometry and Printability of Printed Patterns.

In nanoparticle-based printed electronic devices, the printability of the patterns constituting the device are crucial factors. Although many studies have investigated the printability of patterns, only a few have analyzed and established international standards for measuring the dimensions and printability of shape patterns. This study introduces an advanced algorithm for accurate measurement of the geometry and printability of shape patterns to establish an international standard for pattern dimensions and printability. The algorithm involves three core concepts: extraction of edges of printed patterns and identification of pixel positions, identification of reference edges via the best-fitting of the shape pattern, and calculation of different pixel positions of edges related to reference edges. This method enables the measurement of the pattern geometry and printability, including edge waviness and widening, while considering all pixels comprising the edges of the patterns. The study results revealed that the rectangle and circle patterns exhibited an average widening of 3.55% and a maximum deviation of 1.58%, based on an average of 1662 data points. This indicates that the algorithm has potential applications in real-time pattern quality evaluation, process optimization using statistical or AI-based methods, and foundation of International Electrotechnical Commission standards for shape patterns.

Refined horoball counting and conformal measure for Kleinian group actions

Parabolic fixed points form a countable dense subset of the limit set of a non-elementary geometrically finite Kleinian group with at least one parabolic element. Given such a group, one may associate a standard set of pairwise disjoint horoballs, each tangent to the boundary at a parabolic fixed point. The diameter of such a horoball can be thought of as the 'inverse cost' of approximating an arbitrary point in the limit set by the associated parabolic point. A result of Stratmann and Velani allows one to count horoballs of a given size and, roughly speaking, for small \(r>0\) there are \(r^{-\delta}\) many horoballs of size approximately \(r\), where \(\delta\) is the Poincaré exponent of the group. We investigate localisations of this result, where we seek to count horoballs of size approximately \(r\) inside a given ball \(B(z,R)\). Roughly speaking, if \(r \lesssim R^2\), then we obtain an analogue of the Stratmann-Velani result (normalised by the Patterson-Sullivan measure of \(B(z,R)\)). However, for larger values of \(r\), the count depends in a subtle way on \(z\).
 
 Our counting results have several applications, especially to the geometry of conformal measures supported on the limit set. For example, we compute or estimate several 'fractal dimensions' of certain \(s\)-conformal measures for \(s>\delta\) and use this to examine continuity properties of \(s\)-conformal measures at \(s=\delta\).

A new method for sex estimation based on femoral cross-sectional geometry measurements and its validation using recent and ancient populations.

Estimating sex is a fundamental task in biological and forensic anthropology. This study aimed to develop new methods for sex estimation based on femoral cross-sectional geometry (CSG) variables and to test their applicability in recent and ancient assemblages. The sample was divided into a study group (living individuals, N = 124) for creating sex prediction equations and two test groups: living individuals (N = 31) and prehistoric individuals (N = 34). The prehistoric sample was divided into three subgroups according to subsistence strategy (hunter-gatherers, early farmers that also hunted, and farmers and herders). Femoral CSG variables (size, strength, and shape) were measured from CT images using dedicated software. Discriminant functions for sex estimation were calculated for various bone completeness scenarios and validated using the test groups. Size and strength parameters were sexually dimorphic, while shape was not. Discriminant functions for sex estimation produced success rates in the living sample between 83.9 and 93.5%; the distal shaft yielded the highest results. Success rates were lower among the prehistoric test sample, with better results (83.3%) for the mid-Holocene population (farmers and herders) than for earlier groups (e.g., hunter-gatherers; < 60%). These results were compared with those obtained using other methods for sex estimation based on various skeletal elements. This study provides new, reliable, and simple methods with high success rates for sex estimation based on femoral CSG variables obtained automatically from CT images. Discriminant functions were created for various conditions of femoral completeness. However, these functions should be used carefully in past populations from different settings.

Surveillance of the seashore using the KATERINA II geo-referenced detection system

In this work, the design and initial demonstration of the KATERINA II detection system for rapid mapping of radionuclides in areas near to seashore is presented. A new development has been realized by integrating a GPS module in KATERINA II detection system and synchronizing its data with the acquired spectra in real-time. The new system may be used in a backpack, for areas with low activity concentration, or can be installed in an unmanned vehicle, for observing and mapping the source(s) of radioactivity, e.g. at the seashore, in areas with high contamination. A quantitative solution is provided for natural and artificial radionuclides, taking into account the characteristics of the detector, the parameters of measurement geometry and a mean beach sand/sediment composition. This paper reports field results for site characterization issues through automated analysis of gamma-ray spectra including low-level and low-energy γ-emitters. Perspectives of the future application of the system in a worldwide basis are related to radionuclides mapping and the assessment of dose rates in seashore areas that may be contaminated due to the operation of nuclear power plants, desalination plants and NORM industries, and/or due to the decommissioning of nuclear installations.

Lengthwise regional mechanics of the human aneurysmal ascending thoracic aorta.

The prognosis of patients undergoing emergency endovascular repair of ascending thoracic aortic aneurysm (ATAA) depends on defect location, with root disease bearing worse outcomes than proximal or distal aortopathy. We speculate that a spatial gradient in aneurysmal tissue mechanics through the length of the ascending thoracic aorta may fuel noted survival discrepancies. To this end, we performed planar biaxial testing on 153 root, proximal, and distal segments of ATAA samples collected from 80 patients receiving elective open surgical repair. Following data averaging via surface fitting-based interpolation of strain-controlled protocols, we combined in-vitro and in-vivo measurements of loads and geometry to resolve inflation-extension kinematics and evaluate mechanical metrics of stress, stiffness, and energy at consistent deformation levels. Representative (averaged) experimental data and simulated in-vivo conditions revealed significantly larger biaxial stiffness at the root compared to either proximal or distal tissues, which persisted as the entire aorta stiffened during aging. Advancing age further reduced biaxial stretch and energy storage, a measure of aortic function, across all ATAA segments. Importantly, age emerged as a stronger predictor of tissue mechanics in ATAA disease than either bicuspid aortic valve or connective tissue disorders. Besides strengthening the general understanding of aneurysmal disease, our findings provide specifications to customize the design of stent-grafts for the treatment of ATAA disease. Optimization of deployment and interaction of novel endovascular devices with the local native environment is expected to carry significant potential for improving clinical outcomes. STATEMENT OF SIGNIFICANCE: Elucidating the lengthwise regional mechanics of ascending thoracic aortic aneurysms (ATAAs) is critical for the design of endovascular devices tailored to the ascending aorta. Stent-grafts provide a less invasive alternative to support the long-term survival of ATAA patients ineligible for open surgical repair. In this study, we developed a numerical framework that combines semi-inverse constitutive and forward modeling with in-vitro and in-vivo data to extract mechanical descriptors of ATAA tissue behavior at physiologically meaningful deformation. Moving distally from the aortic root to the first ascending aortic branch, we observed a progressive decline in biaxial stiffness. Furthermore, we showed that aging leads to reduced aortic function and is a stronger predictor of mechanics than either valve morphology or underlying syndromic disorder.

Behaviour of concrete-encased composite members under elevated temperatures

Elevated temperatures pose a significant threat to structures at any stage of the construction process. The purpose of this study is to investigate how various parameters, including geometry, detailing, temperature loading, and protective measures, affect the performance of steel composite components. The objective is to use the finite element software ABAQUS 6.10 to model composite members of beams and columns, and to examine the numerical investigation to achieve the stated goal.A structural damage index was developed to indicate structural temperature damage and demonstrate its applicability to assessing the damage and changes in material strength of steel–concrete composite members caused by high temperatures. Temperature significantly affects a material flexibility, heat conductivity, and specific heat. The same finite element mesh was used for both structural and thermal analysis, and the damage index evaluates the material strength loss of a structure due to temperature changes. This enables the analysis of the damage caused by temperature during and after exposure.The results of the analytical inquiry demonstrate the applicability of the developed indicator for assessing the severity of temperature damage to composite members. The research emphasizes the need for further investigation into the behaviour of composite columns and beams comprising entirely enclosed temperature steel sections. Although anticipated experiments were not conducted due to the pandemic, the findings provide valuable insights for designing and constructing structures that can withstand the hazards of elevated temperatures.

Measurements of ear-canal geometry from high-resolution CT scans of human adult ears

Description of the ear canal’s geometry is essential for describing peripheral sound flow, yet physical measurements of the canal’s geometry are lacking and recent measurements suggest that older-adult-canal areas are systematically larger than previously assumed. Methods to measure ear-canal geometry from multi-planar reconstructions of high-resolution CT images were developed and applied to 66 ears from 47 subjects, ages 18–90 years. The canal’s termination, central axis, entrance, and first bend were identified based on objective definitions, and the canal’s cross-sectional area was measured along its canal’s central axis in 1–2 mm increments. In general, left and right ears from a given subject were far more similar than measurements across subjects, where areas varied by factors of 2–3 at many locations. The canal areas varied systematically with age cohort at the first-bend location, where canal-based measurement probes likely sit; young adults (18–30 years) had an average area of 44mm2 whereas older adults (61–90 years) had a significantly larger average area of 69mm2. Across all subjects ages 18–90, measured means ± standard deviations included: canals termination area at the tympanic annulus 56±8mm2; area at the canal’s first bend 53±18mm2; area at the canal’s entrance 97±24mm2; and canal length 31.4±3.1mm2.

The Mechanical Properties of Thin-Walled Specimens Printed from a Bronze-Filled PLA-Based Composite Filament Using Fused Deposition Modelling.

This article focuses on the mechanical property analysis of important models omitted in many scientific papers (thin-walled specimens) printed from innovative material-such as PLA + bronze composite-using fused deposition modelling technology. It discusses the printing process, the measurement of the specimen geometry, the static tensile strength tests and the microscopic examinations conducted with a scanning electron microscope. The findings of this study could be used as an input to further research into the accuracy of filament deposition and the modification of base materials with bronze powder and for the optimization of the machine design, e.g., with the use of cell structures. The experimental results indicated that the thin-walled models fabricated using FDM showed substantial differences in tensile strength, depending on the specimen's thickness and the printing orientation. It was shown that it was not possible to test thin-walled models located on the building platform along the Z axis due to the lack of sufficient adhesion between the layers.

A Multi-objective approach for position alignment of track geometry measurements

This study aimed to develop a multi-objective approach for reducing the positional errors in geometry measurements of track as a linear asset. Accordingly, we evaluated and compared two alignment methods – recursive segment-wise peak alignment (RSPA) and modified correlation optimised warping (MCOW). Furthermore, a novel rule-based approach was introduced to avoid data loss while aligning the datasets of the measurements of linear assets. A case study was conducted to implement and assess the performance of these methods in reducing the positional errors in track geometry measurements. The results revealed that the rule-based method preserves all the single defects present in the datasets. Furthermore, RSPA outperforms MCOW when aligning peaks, whereas MCOW is more efficient when all the data points in the datasets have equal priority.

Distance Measures Based on Metric Information Matrix for Atanassov’s Intuitionistic Fuzzy Sets

The metric matrix theory is an important research object of metric measure geometry and it can be used to characterize the geometric structure of a set. For intuitionistic fuzzy sets (IFS), we defined metric information matrices (MIM) of IFS by using the metric matrix theory. We introduced the Gromov–Hausdorff metric to measure the distance between any two MIMs. We then constructed a kind of metric information matrix distance knowledge measure for IFS. The proposed distance measures have the ability to measure the distance between two incomplete intuitionistic fuzzy sets. In order to reduce the information confusion caused by the disorder of MIM, we defined a homogenous metric information matrix distance by rearranging MIM. Some theorems are given to show the properties of the constructed distance measures. At the end of the paper, some numerical experiments are given to show that the proposed distances can recognize different patterns represented by IFS.

Identification of shielded sources using a CZT detector and an unmanned ground vehicle

This work is dedicated to ability of a coplanar cadmium zinc telluride (CZT) detector to identify lost/orphan radioactive sources hidden inside soil layers. Considering point-like sources placed in soil and the CZT detector fixed on an unmanned ground vehicle (UGV), relevant measurement geometries were proposed. Full-energy peak efficiency (FEPE) calibrations of the CZT detector were prepared using the MCNP6.1 radiation transport code. In order to check the simulation set-up, control measurements were performed and compared with the Monte Carlo simulations.FEPEs obtained were used for estimations of minimum detectable activities (MDA) and their dependencies on the source depth in soil. Thereafter, field tests of the CZT detector were performed. Within field measurements, radioactive sources with known activities slightly above the MDA values were placed in upper layers of soil of a grassed meadow. The meadow surface was scanned by the CZT detector mounted on a mobile ground robotic platform remotely controlled by an operator. Results of the radiation mapping with the CZT detector were depicted as maps of count rates. On the basis of the maps created, positions of shielded sources were clearly revealed.