Accuracy Of Volume Measurements Research Articles

Late intervention for type II endoleak is not determined by early sac diameter or volume changes after EVAR.

To compare the diagnostic accuracy and predictive value of aneurysm sac volume measurement versus maximum diameter measurement of abdominal aortic aneurysm sac after endovascular aneurysm repair (EVAR) in patients with type II endoleak. Retrospective study on a cohort of 103 patients who presented with a type II endoleak after EVAR for infrarenal abdominal aortic aneurysm. Maximum diameter and volumetric measurements were calculated on computed tomography follow-up scans at 3 months and 1 year after index surgery. Pearson correlation coefficient was used to determine linear association between diameter and volume; Mann-Whitney U test was used to compare patients with and without later intervention for type II endoleak with regard to diameter and volume change. The correlation between diameter and volume measurement was high (Rho: 0.890-0.980 with P < 0.0001). In 38 out of 103 patients (37%) with type II endoleak, a later intervention for endoleak management was performed; early diameter (P = 0.097), or volume (P = 0.387) change could not predict risk for later intervention. Both diameter and volume measurements can be used in the imaging follow-up of patients with endoleak type II after EVAR; however early changes in diameter or volume of the aneurysm sac cannot predict late intervention for type II endoleak.

Microstructural Evaluation of Dental Implant Success Using Micro-CT: A Comprehensive Review

Micro-computed tomography (micro-CT) is an invaluable tool for the evaluation of dental implant success, whereby the assessment of bone microstructure is conducted. This review examines the role of micro-CT in evaluating bone microstructure in dental implants. A review of the current literature reveals that micro-CT enables the accurate measurement of bone volume, trabecular morphology, and connectivity density, all of which play a crucial role in implant stability. The high-resolution three-dimensional visualization capabilities of micro-CT are also beneficial for the analysis of osseointegration and the evaluation of bone augmentation biomaterials. Despite the existence of challenges such as imaging artifacts and limitations in in vivo applications, advancements in sub-micron resolution and artificial intelligence integration offer promise for improving diagnostic capabilities. Micro-CT provides valuable insights into bone microarchitecture and osseointegration dynamics, which have the potential to enhance pre-operative planning and clinical outcomes in dental implantology. Future research should prioritize the standardization of micro-CT analysis protocols and the exploration of direct clinical applications of this technology.

Evaluating the effectiveness of AI-powered UrologiQ's in accurately measuring kidney stone volume in urolithiasis patients.

Kidney stones and urolithiasis are kidney diseases that have a significant impact on health and well-being, and their incidence is increasing annually owing to factors such as age, sex, ethnicity, and geographical location. Accurate identification and volume measurement of kidney stones are critical for determining the appropriate surgical approach, as timely and precise treatment is essential to prevent complications and ensure successful outcomes. Larger stones often require more invasive procedures, and precise volume measurements are essential for effective surgical planning and patient outcomes. This study aimed to compare the ability of artificial intelligence (AI) to detect and measure kidney stone volume via CT-KUB images. CT KUB imaging data were analyzed to determine the effectiveness of AI in identifying the volume of kidney stones. The results were compared with measurements taken by radiologists. Compared with radiologists, the AI had greater accuracy, efficiency, and consistency in measuring kidney stone volume. The AI calculates the volume of kidney stones with an average difference of 80% compared with the volumes calculated by radiologists, highlighting a significant discrepancy that is critical for accurate surgical planning. The results suggest that artificial intelligence (AI) outperforms radiologists' manual calculations in measuring kidney stone volume. By integrating AI with kidney stone detection and treatment, there is potential for greater diagnostic precision and treatment effectiveness, which could ultimately improve patient outcomes.

Log Volume Measurement and Counting Based on Improved Cascade Mask R-CNN and Deep SORT

Logs require multiple verifications to ensure accurate volume and quantity measurements. Log end detection is a crucial step in measuring log volume and counting logs. Currently, this task primarily relies on the Mask R-CNN instance segmentation model. However, the Feature Pyramid Network (FPN) in Mask R-CNN may compromise accuracy due to feature redundancy during multi-scale fusion, particularly with small objects. Moreover, counting logs in a single image is challenging due to their large size and stacking. To address the above issues, we propose an improved log segmentation model based on Cascade Mask R-CNN. This method uses ResNet for multi-scale feature extraction and integrates a hierarchical Convolutional Block Attention Module (CBAM) to refine feature weights and enhance object emphasis. Then, a Region Proposal Network (RPN) is employed to generate log segmentation proposals. Finally, combined with Deep SORT, the model tracks log ends in video streams and counts the number of logs in the stack. Experiments demonstrate the effectiveness of our method, achieving an average precision (AP) of 82.3, APs of 75.3 for small, APm of 70.9 for medium, and APl of 86.2 for large objects. These results represent improvements of 1.8%, 3.7%, 2.6%, and 1.4% over Mask R-CNN, respectively. The detection rate reached 98.6%, with a counting accuracy of 95%. Compared to manually measured volumes, our method shows a low error rate of 4.07%.

"Navigating the complexities of low-Grade glioma treatment: insights into SBT I-125 and novel assessment tools".

Central nervous system tumors, classified by the WHO into four grades based on their aggressiveness, present significant challenges in treatment, particularly low-grade gliomas (LGGs) which, despite their slower growth, can progress to high-grade gliomas. Lucca B. Palavani and colleagues evaluated the efficacy and safety of SBT I-125 brachytherapy for LGMs in a systematic review and meta-analysis of 20 studies involving 988 patients. The analysis revealed an overall complication rate of 10%, with headaches and cyst formation being the most frequent issues. The five-year progression-free survival (PFS) rate was 66%, while the ten-year PFS rate was 30%, and the rate of malignant transformation was 26%. The mortality rate was 33%. Despite these findings, significant limitations were noted, including data insufficiencies, study heterogeneity, lack of randomized controlled trials, and potential publication bias. Inconsistencies in follow-up durations further hindered the evaluation of long-term efficacy and safety. Recent advancements in automated tumor assessment, such as Cheng et al.'s deep learning-based pipeline, are revolutionizing glioma management by enhancing the accuracy and consistency of tumor volume and RANO measurements. These innovations facilitate improved glioma grading, genetic mutation prediction, surgical planning, real-time intraoperative guidance, and histopathological analysis. Integrating such advanced tools into clinical practice can significantly enhance the precision and efficiency of glioma management. In conclusion, while SBT I-125 brachytherapy shows promise, concerns regarding safety and efficacy underscore the need for further research with standardized methodologies. Incorporating advanced automated assessment tools could improve treatment evaluation and patient outcomes.

The impact of real-time feedback on ventilation quality during out-of-hospital cardiac arrest: A before-and-after study

IntroductionVentilations are a critical component of cardiopulmonary resuscitation (CPR). There is conflicting evidence, however, on the most appropriate method of ventilation during cardiac arrest management. Recent evidence has suggested that regardless of the optimal ventilation strategy, ventilations are often not delivered compliant with guideline recommendations. Recent technological advancements have allowed for accurate measurement and real-time feedback of ventilation rate and volume during resuscitation. Simulation studies have found significant improvements in ventilations with the use of real-time feedback during simulated cardiac arrest. The use of feedback has not been studied in clinical practice.The objective of this study was to determine whether the use of real-time feedback improves compliance with pre-defined targets for ventilation rate and volume during out-of-hospital cardiac resuscitation. MethodsThis was a before-and-after study with four paramedic services in Ontario, Canada. We enrolled adult, out-of-hospital cardiac arrest (OHCA) patients where the ZOLL Accuvent® device was utilized to measure ventilation rate and volume. In the before phase (without feedback), the Accuvent® was used to measure ventilations, however, providers were blinded to the real-time feedback. In the after phase (with feedback), the feedback dashboard was activated and providers used the real-time feedback to guide their ventilations. All other aspects of resuscitation remained consistent throughout the study. The main objective of the study was to compare the proportion of each case that was compliant with pre-defined ventilation targets with real-time feedback and without real-time feedback. We also examined the use of advanced airways on ventilation quality and examined for associations between ventilation parameters and return of circulation. ResultsWe enrolled 412 patients in the study (191 in the before phase without feedback and 221 in the after phase with feedback). Overall, we found significant improvements in both ventilation rate and volume in the after phase (with real-time feedback) compared to the before phase (without real-time feedback). We did not find any differences in ventilation compliance with or without advanced airways, or intra-arrest or post-cardiac arrest. ConclusionThe use of real-time feedback was associated with an increased proportion of ventilations that were compliant with pre-defined targets during cardiac resuscitation. Further work is required to improve the use of real-time ventilation feedback, and to determine the impact of ventilations on patient outcomes.

3D reconstruction and volume measurement of irregular objects based on RGB-D camera

Abstract To address the challenge of measuring volumes of irregular objects, this paper proposes a volume measurement method based on 3D point cloud reconstruction. The point clouds of the object with multiple angles are obtained from an RGB-D camera mounted on a robotic arm, and then are reconstructed to form a whole complete point cloud to calculate the volume of the object. Firstly, the robotic arm is controlled to move to four angles for capturing the original point clouds of the target. Then, by using the rotation and translation matrices obtained from the calibration block pre-registration, the point clouds data from the four angles are fused and reconstructed. Subsequently, the issue of missing bottom point cloud data is addressed using a bottom-filling algorithm. Following this, the efficiency of the point cloud volume calculation algorithm is enhanced through the application of AABB filtering. Finally, the reconstructed point cloud volume is calculated using a slicing algorithm that integrates 2D point cloud segmentation and point cloud sorting. Experimental results show that this method achieves a volume measurement accuracy of over 95% for irregular objects and exhibits good robustness.

An accurate measurement method of irregular coal gangue volume based on adaptive image restoration and error compensation

To improve the accuracy of volume measurement for irregularly shaped coal gangue, defects in the depth image and various errors in volume measurement are analyzed. The gray difference similarity (Gds) is proposed for pre-classifying defects, and the depth and RGB information are used interactively for adaptive repair. To minimize the impact of abnormal gray distribution and irrelevant information on the repair process, the areas to be repaired are divided into abnormal regions or layers based on gray and distance weights. Taking into account parameters like geometric morphology (GeMo), volume (Ve), and GeMo × Ve, the influence of wrong imaging and gaps is fully considered. The reverse compensation of errors is achieved by applying the principles of mathematical statistics and the nonlinear surface fitting algorithm. The results show that compared with other algorithms, the proposed algorithm has the smallest measurement error of 6.614 % and is not easily affected by external factors.

Volumetric Assessment of Traumatic Intracranial Hematomas: Is ABC/2 Reliable?

Accurate measurement of traumatic intracranial hematoma volume is important for assessing disease progression and prognosis, as well as for serving as an important end-point in clinical trials aimed at preventing hematoma expansion. While the ABC/2 formula has traditionally been used for volume estimation in spontaneous intracerebral hemorrhage, its adaptation to traumatic hematomas lacks validation. This study aimed to compare the accuracy of ABC/2 with computer-assisted volumetric analysis (CAVA) in estimating the volumes of traumatic intracranial hematomas. We performed a dual-center observational study that included adult patients with moderate-to-severe traumatic brain injury. Volumes of intracerebral, subdural (SDHs), and epidural hematomas from admission computed tomography scans were measured using ABC/2 and CAVA, and compared using the Wilcoxon signed-rank test, Spearman's rank correlation, Lin's concordance correlation coefficient (CCC), and Bland-Altman plots. Prognostic significance for outcomes was evaluated through logistic and linear regression models. In total, 1,179 patients with 1,543 hematomas were included. Despite a high correlation (Spearman coefficients between 0.95 and 0.98) and excellent concordance (Lin's CCC from 0.89 to 0.96) between ABC/2 and CAVA, ABC/2 overestimated hematoma volumes compared with CAVA, in some instances exceeding 50 ml. Bland-Altman analysis highlighted wide limits of agreement, especially in SDH. While both methods demonstrated comparable accuracy in predicting outcomes, CAVA was slightly better at predicting craniotomies and midline shift. We conclude that while ABC/2 provides a generally reliable volumetric assessment suitable for descriptive purposes and as baseline variables in studies, CAVA should be the gold standard in clinical situations and studies requiring more precise volume estimations, such as those using hematoma expansion as an outcome.

High-Throughput and Accurate 3D Scanning of Cattle Using Time-of-Flight Sensors and Deep Learning.

We introduce a high-throughput 3D scanning system designed to accurately measure cattle phenotypes. This scanner employs an array of depth sensors, i.e., time-of-flight (ToF) sensors, each controlled by dedicated embedded devices. The sensors generate high-fidelity 3D point clouds, which are automatically stitched using a point could segmentation approach through deep learning. The deep learner combines raw RGB and depth data to identify correspondences between the multiple 3D point clouds, thus creating a single and accurate mesh that reconstructs the cattle geometry on the fly. In order to evaluate the performance of our system, we implemented a two-fold validation process. Initially, we quantitatively tested the scanner for its ability to determine accurate volume and surface area measurements in a controlled environment featuring known objects. Next, we explored the impact and need for multi-device synchronization when scanning moving targets (cattle). Finally, we performed qualitative and quantitative measurements on cattle. The experimental results demonstrate that the proposed system is capable of producing high-quality meshes of untamed cattle with accurate volume and surface area measurements for livestock studies.

An experimental test of endfire synthetic aperture sonar for sediment characterisation

AbstractThe validation of seafloor scattering models used for seabed characterisation requires quantifying the contributions from the sediment interface and volume to the total acoustic returns. At low‐frequencies, direct measurements of sediment volume scattering have rarely been made, due to the bias in interface roughness scattering caused by large beamwidths of low‐frequency sonars. Endfire Synthetic Aperture Sonar (EF‐SAS) can achieve narrower beamwidths by forming a vertically oriented synthetic array as a transmitter and/or receiver and moving it through the water column. The narrower beamwidths achieved by EF‐SAS allow for more accurate measurements of volume scattering by reducing interface scattering bias in acoustic returns. The application of EF‐SAS for sediment characterisation is explored for the first time. The authors demonstrate that EF‐SAS can be used to construct the angular response curve for both interface and volume scattering as well as to estimate the attenuation and reflection coefficients, which can be inverted for grain size.

The effect of imaging programs and segmentation methods on the accuracy of volume measurements of teeth

ObjectiveThis study investigated whether there are differences between software programs, voxel sizes, segmentation techniques, and intraoral scanners in terms of volume measurement in incisor teeth. Study DesignThirty extracted teeth were scanned using a 3D intraoral scanner. Physical volumes were measured using the water displacement method (WDM) as the gold standard. Cone Beam Computed Tomography (CBCT) images were taken in two voxel sizes (0.3- 0.4 voxel). The volumes of the teeth were calculated using the manual segmentation technique in the 3D Doctor and ImageJ (Fiji) Program, manual and automatic segmentation methods in the ITK-Snap program, and automatic segmentation methods in the 3D Slicer program. The data were analyzed using the Statistical Package for Social Sciences (SPSS, v 20.0). ResultsThere is a significant difference between WDM and 3D Doctor volume measurements at the voxel size of 0.4 (p <0.05). The 3D Doctor program showed more than 13% difference compared to the WDM. There is no significant difference between WDM, intraoral scanner, ITK-Snap, ImageJ (Fiji), 3D Slicer, and 3D-Doctor volume measurements at the voxel size of 0.3. ConclusionMeasurements with manual segmentation in ITK-Snap and ImageJ programs give the closest results to the physical volume measurements of the teeth. The automatic segmentation method in ITK-Snap and 3D Slicer programs may be preferred due to its ease of use and less time consuming. In the 3D Doctor software, volume measurements tend to increase with larger voxel size. Statement of Clinical RelevanceDifferent software programs, voxel size, and segmentation techniques used in CBCT images affect the measurement results of tooth volumes. Very close to physical volume was obtained with the intraoral scanner. Measurements obtained through manual segmentation yield more accurate results.

Accuracy and reliability for estimating jaw functional range of motion

BackgroundThree dimensional (3D) kinematic analysis based on motion capture can study synchronized data from the integrated jaw and neck motor system. Jaw function is commonly estimated on linear outcome variables of motion range. By combining jaw border movements in three planes the functional range of motion could be described by movement area and volume measures. Research questionCan we ensure the accuracy, test-retest reliability, and intra-individual variability with 3D kinematic analysis for estimating jaw functional range of motion (ROM), including jaw movement area and volume and jaw and head linear measures? MethodsAccuracy was estimated by applying the method to a set of beakers with known volume, based on the percentage deviation and Pearson correlation coefficient between target and estimated values. Test-retest reliability was then analysed on maximum jaw movements performed in a pre-determined movement sequence by 17 pain-free participants (25.4 years ± 2.4) to estimate jaw functional ROM. Intraclass correlation coefficients (ICC) were calculated, and Bland-Altman plots were constructed. Coefficient of variation (CV) tested the within session reliability. ResultsThe accuracy in volume and area measurements were high with a percentage deviation (0.03±0.59) and (1.2±0.45), respectively, with a strong linear relationship (R2=0.99) between target and estimated values. The test-retest reliability showed moderate to excellent reliability, and Bland-Altman plots showed good agreement. Overall, CVs showed high repeatability, but jaw movements in horizontal directions were less reliable and presented higher variability. SignificanceThe study with 3D kinematic analysis of jaw functional ROM, provides a methodological basis for accurate and reliable measurements. The study presents a new way to estimate jaw functional ROM measures, useful for evaluation in clinical intervention, for instance in pain and jaw dysfunction. Moreover, the natural biological movement variability and the complexity of the interplay of jaw-head movement will be emphasised.

Effects of different ground segmentation methods on the accuracy of UAV-based canopy volume measurements.

The nonuniform distribution of fruit tree canopies in space poses a challenge for precision management. In recent years, with the development of Structure from Motion (SFM) technology, unmanned aerial vehicle (UAV) remote sensing has been widely used to measure canopy features in orchards to balance efficiency and accuracy. A pipeline of canopy volume measurement based on UAV remote sensing was developed, in which RGB and digital surface model (DSM) orthophotos were constructed from captured RGB images, and then the canopy was segmented using U-Net, OTSU, and RANSAC methods, and the volume was calculated. The accuracy of the segmentation and the canopy volume measurement were compared. The results show that the U-Net trained with RGB and DSM achieves the best accuracy in the segmentation task, with mean intersection of concatenation (MIoU) of 84.75% and mean pixel accuracy (MPA) of 92.58%. However, in the canopy volume estimation task, the U-Net trained with DSM only achieved the best accuracy with Root mean square error (RMSE) of 0.410 m3, relative root mean square error (rRMSE) of 6.40%, and mean absolute percentage error (MAPE) of 4.74%. The deep learning-based segmentation method achieved higher accuracy in both the segmentation task and the canopy volume measurement task. For canopy volumes up to 7.50 m3, OTSU and RANSAC achieve an RMSE of 0.521 m3 and 0.580 m3, respectively. Therefore, in the case of manually labeled datasets, the use of U-Net to segment the canopy region can achieve higher accuracy of canopy volume measurement. If it is difficult to cover the cost of data labeling, ground segmentation using partitioned OTSU can yield more accurate canopy volumes than RANSAC.

Intra- and Interobserver Variability in Ultrasound Measurement of Testicular Volumes in Pubertal Boys

Accurate measurement of testicular volume (TV) in boys is an important tool in clinical practice, e.g., in varicocele treatment. This study aims to assess the degree of intra- and interobserver variability of testicular volume measurements. In a prospective study, boys between 11 and 17 years of age without testicular pathology were enrolled. Testicular ultrasound was performed by three investigators (A: pediatric radiologist; B: pediatric surgery/urology resident; C: pediatric urologist). Intraobserver variability was calculated in investigators B and C and interobserver variability between all three investigators. A total of 30 boys were enrolled. Mean intraobserver variability in both observers was +0.3% with a range of −39.6 to 51.5%. The proportion of measurements with a difference &gt;20% was 18.6%. The mean interobserver variability was −1.0% (range: −74.1% to 62.8%). The overall proportion of measurements with a difference &gt;20% was 35%. A lower testicular size of &lt; 4 mL showed a significantly higher rate of &gt;20% difference in both the intraobserver group (31.1% vs. 14.4%; p = 0.035) and the interobserver group (63.2% vs. 26.2%; p = 0.000031). Furthermore, the rate of &gt;20% difference was significantly lower in obese compared to non-obese patients in both the intraobserver (2.8% vs. 22.4%; p = 0.0084) and the interobserver group (24% vs. 40.8%, p = 0.0427). Both intraobserver and interobserver variability in ultrasound-based TV measurements in pubertal boys contain a relevant degree of uncertainty that renders them unsuitable for individualized follow-up care. At the cohort level, however, mean differences in ultrasound-based TV measurements are low enough to make ultrasound comparisons reasonable.

The Impact of Nasal Septum Deviation on Paranasal Sinus Volumes

Objective: This study examined the impact of nasal septum deviation on the volumes of four pairs of paranasal sinuses: sinus frontalis, sinus maxillaris, sinus sphenoidalis, and cellulae ethmoidales. These cavities are formed by the invagination of the nasal mucosa into bones and vary greatly in shape and size. Their location is crucial in the pathogenesis of regional diseases, and anatomical variations are frequently observed in humans. Computed Tomography imaging provides excellent soft tissue differentiation, which is essential for diagnosing sinonasal disorders. Cavalieri’s principle enables rapid and accurate measurement of sinus volumes using sectional images. The aim of our study was to retrospectively examine the impact of nasal septum deviation on paranasal sinus volumes in relation to age and gender. Material and Method: The study reviewed computed tomography images of participants who visited Tokat Gaziosmanpaşa University Hospital using The Picture Archiving and Communication System. A total of 281 participants, comprising 151 women and 130 men, were included in the study. The participants were divided into four age groups: 0–17, 18–45, 46–65, and over 65. The computed tomography images related to the paranasal sinuses were listed, and the interior of the volume to be measured was colored using ImageJ software. The volume of each sinus was calculated using Cavalieri’s principle. Results: Upon examination of all sinuses, it was observed that men had larger sinus volumes than women (p0.05). Conclusion: Quantitatively measuring the volumes of paranasal sinuses in a short period and determining their relationship with nasal septum deviation will facilitate surgical planning in the future. It may provide some advantages for surgeons.

Pediatric blood cultures—turning up the volume: a before and after intervention study

The major determinant of blood culture (BC) diagnostic performance is blood volume, and pediatric sample volumes are frequently low. We aimed to assess BC volumes in our institution, design an intervention to increase volumes, and assess its impact. All pediatric BCs submitted over a 7-month period to the microbiology laboratory in a university hospital (including emergency department, pediatric ward, and neonatal unit) were included. A pre-intervention period assessed current practice. A multi-faceted intervention (education, guideline introduction, active feedback strategies) was collaboratively designed by all stakeholders. Impact was assessed in a post-intervention period. The main outcome measures included the percentage of samples adequately filled using three measures of sample adequacy (1) manufacturer-recommended minimum validated volume—> 0.5 ml, (2) manufacturer-recommended optimal minimum volume—> 1.0 ml, (3) newly introduced age-specific recommendations. Three hundred ninety-eight pre-intervention and 388 post-intervention samples were included. Initial volumes were low but increased significantly post-intervention (median 0.77 ml vs. 1.52 ml), with multivariable regression analysis estimating volumes increased 89% post-intervention. There were significant increases in all measures of volume adequacy, including an increase in age-appropriate filling (20.4–53.1%), with less improvement in those aged > 3 years. Overall, 68.4% of pathogens were from adequately filled cultures, while 76% of contaminants were from inadequately filled cultures. A pathogen was detected in a higher proportion of adequately filled than inadequately filled cultures (9.4% vs. 2.2%, p < 0.001). Conclusion: Blood volume impacts BC sensitivity, with lower volumes yielding fewer pathogens and more contaminants. Focused intervention can significantly improve volumes to improve diagnostic performance.What is Known:• Blood volume is the major determinant of blood culture positivity, and yet pediatric blood culture volumes are frequently low, resulting in missed pathogens and increased contamination.What is New:• Adequately filled (for age) blood cultures have a pathogen detection rate three times higher than inadequately filled blood cultures.• This interventional study shows that collaboratively designed multi-modal interventions including focus on accurate volume measurement can lead to significant increases in blood volumes and improve blood culture diagnostic performance.

Volume Determination Challenges in Waste Sorting Facilities: Observations and Strategies.

In this case study on volume determination in waste sorting facilities, we evaluate the effectiveness of ultrasonic sensors and address waste-material-specific challenges. Although ultrasonic sensors offer a cost-effective automation solution, their accuracy is affected by irregular waste shapes, varied compositions, and environmental factors. Notable inconsistencies in volume measurements between storage bunkers and conveyor belts underscore the need for a comprehensive approach to standardize bale production. With prediction reliability being constrained by limited datasets, undocumented modifications to machine settings, and sensor failures, this task renders a challenging application area for machine learning. We explore related research and present dataset analyses from three distinct waste sorting facilities in Europe, addressing issues such as sensor usability, data quality, and material specifics. Our analysis suggests promising strategies and future directions for enhancing waste volume measurement accuracy, ultimately aiming to advance sustainable waste management.

A study of membrane correction accounting for both curvature and tension in DEM simulations of triaxial tests of sand and ballast with two alternative flexible membrane models

In DEM simulations of triaxial tests, modelling a flexible lateral membrane is crucial and challenging. It is essential for the correct application of a uniform lateral pressure and for an accurate measurement of sample volume. Here, we introduce a membrane made of triangular facets, and model it as a continuum; we then compare this approach with a well-established method that uses a layer of bonded spheres. With either method, it is also possible to assess the additional stress applied by the membrane as it deforms, i.e. the difference between the stress applied at the boundary and the actual stress within the sample. It is shown that this difference has two origins: the tension developed in the membrane, as it deforms; and the curvature of the membrane, since this causes a vertical component of the confining pressure which can be significant. These findings may be used to inform and improve the membrane correction commonly used in experiments, where similar effects occur.Graphic abstract

Techniques for Measuring the Fluctuation of Residual Lower Limb Volume in Clinical Practices: A Systematic Review of the Past Four Decades

Increased pressure and shear stress distributions at the limb–socket interface are hypothesised to result from changes in the residual limb shape and volume, which can cause socket fit difficulties. Accurate residual limb volume measurements may aid clinicians in developing strategies to accommodate volume fluctuations. This review primarily aims to analyse the techniques available for measuring the residual lower limb volume that may be used in clinical settings, as documented in the works published over the previous four decades. A comprehensive search of articles in PubMed, ScienceDirect, Web of Science, and Google Scholar identified 904 articles, and further analysis resulted in only 39 articles being chosen to be analysed. Based on the findings, there are nine techniques available to measure the residual limb volume: water displacement, anthropometric measurement, contact probes, optical scanning, spiral X-ray computed tomography (SXCT), magnetic resonance imaging (MRI), ultrasound, laser scanning, and bioimpedance. Considering the variety of techniques for determining residual limb volume, it is critical to choose the ones that best suit clinicians’ objectives, and each technique has potential sources of error that should be avoided by taking precautionary action. A comprehensive study of the measurement techniques is needed since researchers have developed and extensively utilised many new measuring devices, especially handheld 3D laser scanners.