Similar Precision Research Articles

A Novel Prediction Algorithm of Pedestrian Activity Region for Intelligent Vehicle Collision Avoidance System

With the development of intelligent vehicle technology, pedestrian trajectory prediction techniques play a key role in collision avoidance systems. Activity regions are commonly adopted to cover the uncertainty of predicted trajectories. However, setting a rational region size for each pedestrian is a challenging issue. Excessive region size may lead to over-reactions of vehicles and limit the degree of freedom of the path planning while insufficient region size may fail to cover the uncertainty. This work proposes a novel dynamic activity region (DAR) prediction algorithm and a relevant collision risk evaluation method. In the prediction module, the proposed method predicts a rational activity region for each pedestrian based on the historical trajectory in contrast to the conventional methods which adopt preset static activity regions (SAR) for all pedestrians. The comparative study shows that the proposed method reduces the sizes of pedestrian activity regions by 10.5% on average with similar precision. In the cases where the trajectory is highly nonlinear, the region size reduction can reach 12.1%. In the collision risk evaluation module, the risk statuses of pedestrians are classified based on the relationship between their DARs and the future trajectory of the vehicle. This method can produce a more detailed classification. The effectiveness and improvement of the proposed method are validated by experiments and simulations.

Clinical Accuracy and Precision of 3 Multifrequency Electronic Apex Locators Assessed through Micro–Computed Tomographic Imaging

IntroductionThis study aimed to compare the in vivo accuracy and precision of 3 electronic apex locators (EALs) in determining the position of the major foramen using micro–computed tomographic (micro-CT) technology. MethodsAfter access preparation of 23 necrotic or vital teeth from 5 patients, canals were negotiated, and hand files were used to determine the position of the foramen with 3 EALs: Propex Pixi (Dentsply Maillefer, Ballaigues, Switzerland), Woodpex III (Woodpecker Medical Instrument Co, Guilin, China), and Root ZX II (J Morita, Tokyo, Japan). After fixing the silicon stop to the file, teeth were extracted and scanned in a micro-CT device with and without the instrument inserted into the canal. Data sets were coregistered, and the accuracy and precision of the EALs were determined at a tolerance level of ±0.5 mm by measuring the distance from the tip of the instruments to a tangential line crossing the margins of the foramen. Statistical comparisons were performed using Friedman with post hoc related samples sign and Spearman tests (α = 5%). ResultsA significant difference was detected comparing the accuracy of Root ZX II (100%), Woodpex III (86.96%), and Propex Pixi (52.17%) (P < .05). There was a lack of significance in the relationship between the pulp status and the accuracy of the tested EALs (P > .05). Propex Pixi was significantly less precise than Root ZX II (P < .05), whereas no difference was found between Woodpex III and Root ZX II or Propex Pixi (P > .05). ConclusionsEALs presented similar precision, but Woodpex III and Root ZX II showed better accuracy to determine the position of the apical major foramen than Propex Pixi.

THE ACCURACY AND PRECISION OF SMALL-SIZED MODERN WOOD SAMPLES ANALYZED AT THE CHRONOS 14CARBON-CYCLE FACILITY

ABSTRACTTree-ring series offer considerable potential for the development of environment-sensitive proxy records. However, with traditional increment cores, only small amounts of wood are often available from annual tree-ring sequences. For this reason, it is important to understand the reliability (and reproducibility) of radiocarbon measurements obtained from small-sized samples. Here we report the F14C results from the Chronos 14Carbon-Cycle Facility of modern tropical Australian tree samples over a range of four graphite target sizes from the same rings. Our study shows that similar precision can be obtained from full-sized, half-sized, as well as small-sized graphite targets using standard pretreatment and analysis procedures. However, with a decline in sample size, there was an increase seen in the associated variance of the ages and the smallest target weights started showing a systematic bias. Wiggle-matching accuracy tests, comparing the Southern Hemisphere post-bomb atmospheric calibration curve to the different sample weight sequences, were all significant except for the 200 μgC graphite targets. Our results indicate that samples smaller than 350 μgC have limited accuracy and precision. Overall, reliable measurements of F14C sequences from tree-ring records across a range of sample sizes, with best results found using graphitized samples &gt;350 μgC.

A microservice regression testing selection approach based on belief propagation

Regression testing is required to assure the quality of each iteration of microservice systems. Test case selection is one of main techniques to optimize regression testing. Existing techniques mainly involve artifacts acquisition, processing and maintenance, thus hard to apply in microservice regression testing since it is difficult to obtain and process required artifacts from multiple development teams, which is normal in cases of microservice systems. This paper proposes a novel approach, namely MRTS-BP, which takes API gateway logs instead of artifacts as inputs. By mining service dependencies from API gateway logs, MRTS-BP analyzes service change impacts based on a propagation calculation, and selects test cases affected by changes based on impact degree values. To evaluate the effectiveness of MRTS-BP, empirical studies based on four real deployed systems are presented. Retest-all strategy and a regression testing selection approach based on control flow graphs called RTS-CFG are compared with MRTS-BP. The results show that, MRTS-BP can significantly reduce both the number of test cases and overall time cost while maintaining the fault detection capability of selected test suite, and that MRTS-BP can save more time cost than RTS-CFG with the similar safety and precision.

Automatic segmentation of inferior alveolar canal with ambiguity classification in panoramic images using deep learning

BackgroundManual segmentation of the inferior alveolar canal (IAC) in panoramic images requires considerable time and labor even for dental experts having extensive experience. The objective of this study was to evaluate the performance of automatic segmentation of IAC with ambiguity classification in panoramic images using a deep learning method. MethodsAmong 1366 panoramic images, 1000 were selected as the training dataset and the remaining 336 were assigned to the testing dataset. The radiologists divided the testing dataset into four groups according to the quality of the visible segments of IAC. The segmentation time, dice similarity coefficient (DSC), precision, and recall rate were calculated to evaluate the efficiency and segmentation performance of deep learning-based automatic segmentation. ResultsAutomatic segmentation achieved a DSC of 85.7% (95% confidence interval [CI] 75.4%–90.3%), precision of 84.1% (95% CI 78.4%–89.3%), and recall of 87.7% (95% CI 77.7%–93.4%). Compared with manual annotation (5.9s per image), automatic segmentation significantly increased the efficiency of IAC segmentation (33 ms per image). The DSC and precision values of group 4 (most visible) were significantly better than those of group 1 (least visible). The recall values of groups 3 and 4 were significantly better than those of group 1. ConclusionsThe deep learning-based method achieved high performance for IAC segmentation in panoramic images under different visibilities and was positively correlated with IAC image clarity.

Super-resolution paint imaging with molecular beacon.

DNA-PAINT offers simple super-resolution imaging through the transient binding of fluorescently-labelled DNA imagers to target molecules. It has many advantages, including super-multiplexing capability and robustness against photobleaching. However, the unbound fluorescent imagers in the solution can cause high fluorescence background and place constraints on the imaging conditions that limit the technique's potential, such as low imager concentration, thin TIRF illumination, and long exposure time. In this study, we developed a new strategy to improve PAINT imaging using a fluorogenic molecular beacon (MB) as the imager. MB-PAINT eliminates false localizations from nonspecific surface adsorption and fluorescence background at concentrations far exceeding conventional linear imagers. Furthermore, MB-PAINT achieves similar nanometer localization precision to conventional DNA-PAINT. Lastly, we demonstrate that MB-PAINT is ideally suited for super-resolution tension imaging in living cells even at high frame rates, suppressing the potential of artifacts from free-diffusing and spontaneous binding of imagers at the cell-substrate interface.

Super-resolution microscopy reveals the number and distribution of topoisomerase IIα and CENH3 molecules within barley metaphase chromosomes

Topoisomerase IIα (Topo IIα) and the centromere-specific histone H3 variant CENH3 are key proteins involved in chromatin condensation and centromere determination, respectively. Consequently, they are required for proper chromosome segregation during cell divisions. We combined two super-resolution techniques, structured illumination microscopy (SIM) to co-localize Topo IIα and CENH3, and photoactivated localization microscopy (PALM) to determine their molecule numbers in barley metaphase chromosomes. We detected a dispersed Topo IIα distribution along chromosome arms but an accumulation at centromeres, telomeres, and nucleolus-organizing regions. With a precision of 10-50 nm, we counted ~ 20,000-40,000 Topo IIα molecules per chromosome, 28% of them within the (peri)centromere. With similar precision, we identified ~13,500 CENH3 molecules per centromere where Topo IIα proteins and CENH3-containing chromatin intermingle. In short, we demonstrate PALM as a useful method to count and localize single molecules with high precision within chromosomes. The ultrastructural distribution and the detected amount of Topo IIα and CENH3 are instrumental for a better understanding of their functions during chromatin condensation and centromere determination.

A versatile approach for the preparation of matrix-matched standards for LA-ICP-MS analysis – Standard addition by the spraying of liquid standards

In the last years, LA-ICP-MS has become an attractive technique for analyzing solid samples from various research fields. However, application in material science is often hampered by the limited availability of appropriate certified reference materials, which are a precondition for accurate quantification. Thus, frequently in-house prepared standards are used, which match the sample's composition and include all elements of interest at the required concentration levels. However, preparing and characterizing such standards is often labor-intensive and time-consuming.This work proposes a new approach for the fabrication of matrix-matched standards based on the concept of standard addition. In the first step, the analytes of interest are homogeneously deposited onto the sample surface using liquid standards and a spraying device. For analysis, the generated thin layer is ablated simultaneously with the underlying sample. Thereby deviations in the ablation process and particle transport can be avoided. It could be shown that the developed method is highly versatile and could be easily adapted to the actual needs. Using silicon, silicon carbide, copper, aluminum, and glass as a matrix, excellent linear correlations between observed signal intensities and deposited amounts were found for the elements Zn, Ag, In, and Pb (R2 - values greater than 0.99).The method was applied to determine the content of sulfur, zinc, silver, indium, and lead in a commercial Kapton® polyimide film. The obtained results could be verified based on the homogeneously distributed sulfur by conventional liquid ICP-MS analysis after sample digestion, showing similar precision and accuracy. Lead was found to show a very inhomogeneous distribution in the Kapton® film, with concentration below the LOD at most measured locations and irregularly occurring spots with significantly higher concentrations. Finally, a quantitative depth profile of sulfur in a Kapton® film has been measured to assess the uptake of SO2 after a weathering experiment.

Effect of computer-aided design and computer-aided manufacturing technique on the accuracy of fixed partial denture patterns used for casting or pressing

ObjectivesTo evaluate the effect of additive and subtractive manufacturing on the accuracy (trueness and precision) of fixed partial denture patterns (FPDPs) used for casting or pressing. Materials and MethodsA 3-unit complete coverage FPD on mandibular right first premolar and first molar teeth was virtually designed. Using the design data, FPD patterns were fabricated from an additively manufactured resin (PR, ProArt Print Wax) and 2 CAD-CAM wax discs (YW, ProArt CAD Wax Yellow and BW, ProArt CAD Wax Blue) (n = 10). Each pattern was then digitized with a scanner (CEREC Primescan) and evaluated for 3D surface deviation at 4 different surfaces (overall, external, marginal, and intaglio surfaces) by using a 3D analysis software (Medit Link). Root mean square (RMS) values were automatically calculated. Data were analyzed by using Kruskal-Wallis and Dunn's post hoc tests for trueness and precision (α= 0.05). ResultsSignificant differences were found among the RMS values for overall (P<.001) and each surface (P≤.040) evaluated. PR had the highest overall (P≤.011) and intaglio surface (P≤.01) deviations, while the difference between YW and BW was not significant (P≥.199). PR had the highest (P≤.027) and BW had the lowest (P≤.042) external surface mean RMS values. BW had higher mean marginal RMS value than YW (P=.047). For precision, significant differences were observed among test groups only for marginal RMS values (P=.002). PR had lower precision than BW (P=.002). ConclusionsBW and YW FPDPs mostly had higher trueness compared with PR FPDPs. However, considering relatively smaller deviations at marginal and intaglio surfaces and the fact that patterns mostly had similar precision, clinical fit of FPDs fabricated by using tested patterns may be similar. Clinical SignificanceDefinitive 3-unit fixed partial dentures fabricated by using tested patterns may be similar. However, FPDs fabricated with tested additively manufactured resin patterns might result in more chairside adjustments than those fabricated with tested subtractively manufactured wax patterns.

Signatures of Life Detected in Images of Rocks Using Neural Network Analysis Demonstrate New Potential for Searching for Biosignatures on the Surface of Mars.

Microorganisms play a role in the construction or modulation of various types of landforms. They are especially notable for forming microbially induced sedimentary structures (MISS). Such microbial structures have been considered to be among the most likely biosignatures that might be encountered on the martian surface. Twenty-nine algorithms have been tested with images taken during a laboratory experiment for testing their performance in discriminating mat cracks (MISS) from abiotic mud cracks. Among the algorithms, neural network types produced excellent predictions with similar precision of 0.99. Following that step, a convolutional neural network (CNN) approach has been tested to see whether it can conclusively detect MISS in images of rocks and sediment surfaces taken at different natural sites where present and ancient (fossil) microbial mat cracks and abiotic desiccation cracks were observed. The CNN approach showed excellent prediction of biotic and abiotic structures from the images (global precision, sensitivity, and specificity, respectively, 0.99, 0.99, and 0.97). The key areas of interest of the machine matched well with human expertise for distinguishing biotic and abiotic forms (in their geomorphological meaning). The images indicated clear differences between the abiotic and biotic situations expressed at three embedded scales: texture (size, shape, and arrangement of the grains constituting the surface of one form), form (outer shape of one form), and pattern of form arrangement (arrangement of the forms over a few square meters). The most discriminative components for biogenicity were the border of the mat cracks with their tortuous enlarged and blistered morphology more or less curved upward, sometimes with thin laminations. To apply this innovative biogeomorphological approach to the images obtained by rovers on Mars, the main physical and biological sources of variation in abiotic and biotic outcomes must now be further considered.

GFR estimated with creatinine rather than cystatin C is more reflective of the true risk of adverse outcomes with low GFR in kidney transplant recipients.

Serum cystatin C-based estimated glomerular filtration rate (eGFRcys) generally associates with clinical outcomes better than serum creatinine-based eGFR (eGFRcr) despite similar precision in estimating measured GFR (mGFR). We sought to determine whether the risk of adverse outcomes with eGFRcr or eGFRcys was via GFR alone or also via non-GFR determinants among kidney transplant recipients. Consecutive adult kidney transplant recipients underwent a standardized GFR assessment during a routine follow-up clinic visit between 2011 and 2013. Patients were followed for graft failure or the composite outcome of cardiovascular (CV) events or mortality through 2020. The risk of these events by baseline mGFR, eGFRcr and eGFRcys was assessed unadjusted, adjusted for mGFR and adjusted for CV risk factors. There were 1135 recipients with a mean baseline mGFR of 55.6, eGFRcr of 54.8 and eGFRcys of 46.8ml/min/1.73m2 and a median follow-up of 6years. Each 10ml/min/1.73m2 decrease in mGFR, eGFRcr or eGFRcys associated with graft failure [hazard ratio (HR) 1.79, 1.68 and 2.07, respectively; P<.001 for all) and CV events or mortality outcome (HR 1.28, 1.19 and 1.43, respectively; P<.001 for all). After adjusting for mGFR, eGFRcys associated with graft failure (HR 1.57, P<.001) and CV events or mortality (HR 1.49, P<.001), but eGFRcr did not associate with either. After further adjusting for CV risk factors, risk of these outcomes with lower eGFRcys was attenuated. eGFRcr better represents the true relationship between GFR and outcomes after kidney transplantation because it has less non-GFR residual association. Cystatin C is better interpreted as a nonspecific prognostic biomarker than is eGFR in the kidney transplant setting.

In Vitro Trueness and Precision of Intraoral Scanners in a Four-Implant Complete-Arch Model

(1) Background: New intraoral (IOS) and laboratory scanners appear in the market and their trueness and precision have not been compared. (2) Methods: Seven IOS and two laboratory scanners were used to scan a mandibular edentulous model with four parallel internal hexagon implant analogues and PEEK scan bodies. Digital models in Standard Tessellation Language (STL) were created. The master model with the scan bodies was scanned (×10) with a computerized numerical control 3D Coordinate Measuring Machine (CMM). The short (distances of adjacent scan posts) and long distances (distances of the scan posts with non-adjacent sites in the arch) among the centroids of the four analogues were calculated using CMM special software. Trueness (comparisons with the master model) and precision (intragroup comparisons) were statistically compared with ANOVA, chi-square and Tukey tests. (3) Results: Laboratory scanners had the best trueness and precision compared to all IOSs for long distances. Only iTero (Align Technologies Inc., Milpitas, CA, USA) had comparable trueness with one laboratory scanner in short and long distances. For short distances, CS3600 (Carestream Health, Inc., Rochester, NY, USA), Omnicam, Primescan (Sirona Dental Sys-tems GmbH, Bens-heim, Germany) and TRIOS 4 (3Shape A/S, Copen-hagen, Denmark) had similar trueness to one laboratory scanner. From those, only Omnicam and Primescan had similar precision as the same laboratory scanner. Most IOSs seem to work better for smaller distances and are less precise in cross-arch distances. (4) Conclusions: The laboratory scanners showed significantly higher trueness and precision than all IOSs tested for the long-distance group; for the short distance, some IOSs were not different in trueness and precision than the laboratory scanners.

An Intelligent Auxiliary Framework for Bone Malignant Tumor Lesion Segmentation in Medical Image Analysis.

Bone malignant tumors are metastatic and aggressive, with poor treatment outcomes and prognosis. Rapid and accurate diagnosis is crucial for limb salvage and increasing the survival rate. There is a lack of research on deep learning to segment bone malignant tumor lesions in medical images with complex backgrounds and blurred boundaries. Therefore, we propose a new intelligent auxiliary framework for the medical image segmentation of bone malignant tumor lesions, which consists of a supervised edge-attention guidance segmentation network (SEAGNET). We design a boundary key points selection module to supervise the learning of edge attention in the model to retain fine-grained edge feature information. We precisely locate malignant tumors by instance segmentation networks while extracting feature maps of tumor lesions in medical images. The rich contextual-dependent information in the feature map is captured by mixed attention to better understand the uncertainty and ambiguity of the boundary, and edge attention learning is used to guide the segmentation network to focus on the fuzzy boundary of the tumor region. We implement extensive experiments on real-world medical data to validate our model. It validates the superiority of our method over the latest segmentation methods, achieving the best performance in terms of the Dice similarity coefficient (0.967), precision (0.968), and accuracy (0.996). The results prove the important contribution of the framework in assisting doctors to improve the accuracy of diagnosis and clinical efficiency.

Epigenetic gestational age and the relationship with developmental milestones in early childhood.

Shorter gestational age (GA) is a risk factor of developmental delay. GA is usually estimated clinically from last menstrual period and ultrasound. DNA methylation (DNAm) estimates GA using sets of cytosine-guanine-sites coupled with a clock algorithm. Therefore, DNAm-estimated GA may better reflect biological maturation. A DNAm GA greater than clinical GA, known as gestational age acceleration (GAA), may indicate epigenetic maturity and holds potential as an early biomarker for developmental delay risk. We used data from the Upstate KIDS Study to examine associations of DNAm GA and developmental delay within the first 3years based on the Ages & Stages Questionnaire® (n = 1010). We estimated DNAm GA using two clocks specific to the Illumina Methylation EPIC 850K, the Haftorn clock and one developed from the Effects of Aspirin in Gestation and Reproduction study, in which women were followed to detect pregnancy at the earliest time possible. Among singletons, each week increase in DNAm GA was protective for overall delay (odds ratio:0.74; 95% confidence interval:0.61-0.90) and delay in all domains except for problem-solving skills. Among twins, we observed similar point estimates but lower precision. Results were similar for clinical GA. GAA was largely not associated with developmental delays. In summary, either DNAm GA or clinical GA at birth, but not epigenetic maturity (i.e. GAA), was associated with decreased odds of developmental delay in early childhood. Our study does not support using DNAm GA or GAA as separate risk factors for future risk of developmental delay within the first 3years of age.

Predicting microbial crude protein synthesis in cattle from intakes of dietary energy and crude protein.

Accurate predictions of microbial crude protein (MCP) synthesis are needed to predict metabolizable protein supply in ruminants. Since 1996, the National Academies of Sciences, Engineering, and Medicine series on beef cattle nutrient requirements has used the intake of total digestible nutrients (TDN) to predict ruminal MCP synthesis. Because various tabular energy values for feeds are highly correlated, our objective was to determine whether intakes of digestible energy (DE), metabolizable energy (ME), and net energy for maintenance (NEm) could be used as predictors of MCP synthesis in beef cattle. A published database of 285 treatment means from experiments that evaluated MCP synthesis was updated with 50 additional treatment mean observations. When intakes of TDN, fat-free TDN, DE, ME, NEm, dry matter, organic matter, crude protein (CP), ether extract, neutral detergent fiber, and starch were used in a stepwise regression analysis to predict MCP, only intakes of DE and CP met the P < 0.10 criterion for entry into the model. Mixed-model regression analyses were used to adjust for random intercept and slope effects of citations to evaluate intake of DE alone or in combination with CP intake as predictors of MCP synthesis, and the intakes of TDN, ME, and NEm as alternatives to DE intake. Similar precisions in predicting MCP synthesis were obtained with all measures of energy intake (CV = root mean square error [RMSE] as a percentage of the overall mean MCP varied from 9% to 9.67%), and adding CP intake to statistical models increased precision (CV ranged from 8.43% to 9.39%). Resampling analyses were used to evaluate observed vs. predicted values for the various energy intake models with or without CP intake, as well as the TDN-based equation used in the current beef cattle nutrient requirements calculations. The coefficient of determination, concordance correlation coefficient, and RMSE of prediction as a percentage of the mean averaged 0.595%, 0.730%, and 28.6% for the four measures of energy intake, with average values of 0.630%, 0.757%, and 27.4%, respectively, for equations that included CP intake. The TDN equation adopted by the 2016 beef cattle nutrient requirements system yielded similar results to newly developed equations but had a slightly greater mean bias. We concluded that any of the measures of energy intake we evaluated can be used to predict MCP synthesis by beef cattle and that adding CP intake improves model precision.

Computational Predictions of Nonclinical Pharmacokinetics at the Drug Design Stage.

Although computational predictions of pharmacokinetics (PK) are desirable at the drug design stage, existing approaches are often limited by prediction accuracy and human interpretability. Using a discovery data set of mouse and rat PK studies at Roche (9,685 unique compounds), we performed a proof-of-concept study to predict key PK properties from chemical structure alone, including plasma clearance (CLp), volume of distribution at steady-state (Vss), and oral bioavailability (F). Ten machine learning (ML) models were evaluated, including Single-Task, Multitask, and transfer learning approaches (i.e., pretraining with in vitro data). In addition to prediction accuracy, we emphasized human interpretability of outcomes, especially the quantification of uncertainty, applicability domains, and explanations of predictions in terms of molecular features. Results show that intravenous (IV) PK properties (CLp and Vss) can be predicted with good precision (average absolute fold error, AAFE of 1.96-2.84 depending on data split) and low bias (average fold error, AFE of 0.98-1.36), with AutoGluon, Gaussian Process Regressor (GP), and ChemProp displaying the best performance. Driven by higher complexity of oral PK studies, predictions of F were more challenging, with the best AAFE values of 2.35-2.60 and higher overprediction bias (AFE of 1.45-1.62). Multi-Task approaches and pretraining of ChemProp neural networks with in vitro data showed similar precision to Single-Task models but helped reduce the bias and increase correlations between observations and predictions. A combination of GP-computed prediction variance, molecular clustering, and dimensionality-reduction provided valuable quantitative insights into prediction uncertainty and applicability domains. SHAPley Additive exPlanations (SHAPs) highlighted molecular features contributing to prediction outcomes of Vss, providing explanations that could aid drug design. Combined results show that computational predictions of PK are feasible at the drug design stage, with several ML technologies converging to successfully leverage historical PK data sets. Further studies are needed to unlock the full potential of this approach, especially with respect to data set sizes and quality, transfer learning between in vitro and in vivo data sets, model-independent quantification of uncertainty, and explainability of predictions.

Reply to the 'Comment on "Perturbation theory of scattering for grazing-incidence fast-atom diffraction"' by G. A. Bocan, H. Breiss, S. Szilasi, A. Momeni, E. M. S. Casagrande, E. A. Sánchez, M. S. Gravielle and H. Khemliche, Phys. Chem. Chem. Phys., 2023, 25, DOI: 10.1039/D3CP02486E.

In this Reply, we show that criticisms of perturbation theory for grazing-incidence fast-atom diffraction (GIFAD) are ill-founded. We show explicitly that our formulation (W. Allison, S. Miret-Artés and E. Pollak, Phys. Chem. Chem. Phys., 2022, 24, 15851) provides a similar precision in describing the observed phenomena as ab initio potentials. Since that is the main criterion to distinguish between methods, it seems reasonable to conclude that the perturbation approach using a Morse-type potential reproduces the essential aspects of the dynamics correctly. In addition we expand on the historical context and summarize the physical insights provided by our methods.

The impact of 3D stereoscopic visualisation on performance in electron skin apposition techniques using VERT

Abstract Introduction: The Virtual Environment for Radiotherapy Training (VERT) is a simulator used to train radiotherapy students cost-effectively with limited risk. VERT is available as a two-dimensional (2D) and a more costly three-dimensional (3D) stereoscopic resource. This study aimed to identify the specific benefits afforded by stereoscopic visualisation for student training in skin apposition techniques. Method: Eight participants completed six electron skin apposition setups in both 2D and 3D views of VERT using a 7 cm × 10 cm rectangular applicator setup to 100 cm focus skin distance (FSD). The standard deviation (SD) of the mean distance from each corner of the applicator to the virtual patient’s skin surface [which we define as apposition precision (AP)] was measured along with the time taken to achieve each setup. Participants then completed a four-question Likert-style questionnaire concerning their preferences and perceptions of the 2D and 3D views. Results: There was little difference in mean setup times with 218·43 seconds for 2D and 211·29 seconds for 3D (3·3% difference). There was a similarly small difference in AP with a mean SD of 5·61 mm for 2D and 5·79 mm for 3D (3·2% difference) between views. The questionnaire results showed no preference for the 3D view over the 2D. Conclusion: These findings suggest that the 2D and 3D views result in similar setup times and precision, with no user preference for the 3D view. It is recommended that the 2D version of VERT could be utilised in similar situations with a reduced logistical and financial impact.

Automatic segmentation of human supraclavicular adipose tissue using high-resolution T2-weighted magnetic resonance imaging.

To achieve efficient segmentation of human supraclavicular adipose tissue (sclavAT) using high-resolution T2-weighted magnetic resonance images. High-resolution 1.0mm isotropic 3D T2-weighted images covering human supraclavicular area were acquired in transverse or coronary plane from 29 volunteers using a 3.0T MRI scanner. There were typically 144/288 slices for the transverse/coronary scans for each subject, which amounts to a total of 6816 images in 29 volunteers. A U-NET network was trained to segment the supraclavicular adipose tissue (sclavAT). The performance of the automatic segmentation method was evaluated by comparing the output results with the manual labels using the quantitative indices of dice similarity coefficient (DSC), precision rate (PR), and recall rate (RR). The auto-segmented images were used to calculate the sclavAT volumes and registered to the MR fat fraction (FF) images to quantify the fat component of the sclavAT area. The relationship between body mass index (BMI), the volume and FF of sclavAT area was evaluated for all subjects. The DSC, PR and RR of the automatic sclavAT segmentation method on the testing datasets were 0.920 ± 0.048, 0.915 ± 0.070 and 0.930 ± 0.058. The volume and the mean FF of sclavAT were both found to be strongly correlated to BMI, with the correlation coefficient of 0.703 and 0.625 (p < 0.05), respectively. The averaged computation time of the automatic segmentation method was approximately 0.06s per slice, compared to more than 5min for manual labeling. The present study demonstrates that the proposed automatic segmentation method using U-Net network is able to identify human sclavAT efficiently and accurately.

Flexural behaviour and ultimate bending capacity of high-volume fly ash reinforced concrete beams

Large number of studies analyzed physical and mechanical properties of high-volume fly ash concrete, but only a few discussed its structural behavior. Material properties are an important input parameter for structural analysis, but they are insufficient for reliable conclusions to be made. This study analyses flexural behavior of reinforced concrete beams made with 63% of low-calcium class F fly ash in total cementitious materials mass, using experimental method and analyzing current code predictions (EN 1992-1-1). The analysis was done by comparing beams made with two longitudinal reinforcement ratios, made with traditional cement concrete (OPC) and high-volume fly ash concrete (HVFAC), both corresponding to concrete class C30/37. Beams were tested in a four-point bending test measuring vertical displacement, crack development, concrete strains and longitudinal reinforcement strains. According to this research, the flexural performance of HVFAC beams is similar to flexural performance of corresponding OPC beams in terms of ultimate bending capacity. The significant difference was noticed regarding cracking extent that was higher in HVFAC beams. Available ultimate bending moments code predictions can be applied on HVFAC beams with similar precision and variation of results, like for OPC beams. However, this cannot be concluded for parameters depending on the cracking behaviour, like cracking moments or deflections. Results and analysis presented in this study indicate that HVFAC can be used in structural elements subjected dominantly to bending, like beams and slabs. More research regarding structural behavior of HVFAC using full-scale long-term tests is needed to develop larger database for reliability analysis.