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Vertical tanks are commonly used appliances for liquids, and its capacity is very important for quantitative liquid ratio and liquid trade. In order to measure the capacity of vertical tanks more conveniently, this paper proposes a vertical tank capacity measurement method based on Monte Carlo Method. The method arranges a plurality of sensor points on the inner surface of the tank, and then performs Monte Carlo tests by generating a large number of random sample points, and finally calculates the capacity by counting the sample points that meet the criterion. The criterion for whether a sample point is located in the tank, which is the core issue, is established with the coordinates of sensor points and the distance between different sensor points along the surface of the tank. The results show that the absolute error of the measurement results of the proposed method does not exceed ±0.0003[m3], and the absolute error of capacity per unit volume has a linear relationship with the height of the vertical tank, and has little effect with the radial size of the vertical tank.

Objectives Tape measurement is a commonly used method in the clinical assessment of lymphedema. However, few studies have assessed the precision and reliability of tape measurement in assessing head and neck lymphedema. This study aimed to evaluate the reliability and precision of using tape measurement, performed by different evaluators, for the assessment of head and neck lymphedema. Methods This study was conducted at a tertiary care cancer hospital. Between January and December 2019, 50 patients with head and neck cancers and 50 normal subjects were enrolled. Each subject was examined using tape measurements for 7 point-to-point distances of facial landmarks, 3 circumferences of the neck (upper, middle, and lower), and 2 circumferences of the face (vertical and oblique) by 3 random examiners. Test precision and reliability were assessed with the within-subject standard deviation (Sw) and intra-class correlation coefficient (ICC), respectively. Results Overall, the standard deviation of the tape measurements varied in the range of 4.6 mm to 18.3 mm. The measurement of distance between the tragus and mouth angle (Sw: 4.6 mm) yielded the highest precision, but the reliability (ICC: 0.66) was moderate. The reliabilities of neck circumference measurements (ICC: 0.90-0.95) were good to excellent, but the precisions (Sw: 8.3-12.3 mm) were lower than those of point-to-point facial measurements (Sw: 4.6-8.8 mm). Conclusions The different methods of tape measurements varied in precision and reliability. Thus, clinicians should not rely on a single measurement when evaluating head and neck lymphedema.

Ascertaining the accuracy of the pedicle screw (PS) trajectories is important as PS malpositioning can cause critical complications. We aimed to determine the angle range over which estimation is unreliable; build a low-cost PS placement support system that uses an inertial measurement unit (IMU) to enable the monitoring of surgical tools and PS trajectories, and determine the situations where IMU support would be most beneficial. In PS insertion experiments, we used cadaver samples that included lumbar porcine spines. Computed tomography images obtained before and after PS insertion were viewed. Offsets between the planned and implanted PS trajectories in the freehand and IMU-assisted groups were analyzed. The PS cortical bone breaches were classified according to the Gertzbein and Robbins criteria (GRC). Added head-down tilted sample experiments were repeated wherein we expected a decreased rostro-caudal rotational accuracy of the PS according to the angle estimation ability results. Evaluation of the PS trajectory accuracy revealed no significant advantage of IMU-assisted rostro-caudal rotational accuracy versus freehand accuracy. According to the GRC, IMU assistance significantly increased the rate of clinically acceptable PS positions (RoCA) than the freehand technique. In the head-down tilted sample experiments, IMU assist provided increased accuracies with both rostro-caudal and medial rotational techniques when compared with the freehand technique. In the freehand group, RoCA was significantly decreased in samples with rostral tilting relative to that in the samples without. However, In the IMU-assisted group, no significant difference in RoCA between the samples with and without head-down tilting was observed. Even when the planned PS medial and/or rostro-caudal rotational angle was relatively large and difficult to reproduce manually, IMU-support helped maintain the PS trajectory accuracy and positioning safety. IMU assist in PS placement was more beneficial, especially for larger rostro-caudal and/or medial rotational pedicle angles.

Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with these challenges. However, it is rather challenging to synergy these two kinds of techniques together to avoid the curse of dimensionality problem and to boost the performance of gene expression data clustering. In this paper, we employ a projective clustering ensemble (PCE) to integrate the advantages of projective clustering and ensemble clustering, and to avoid the dilemma of combining multiple projective clusterings. Our experimental results on publicly available cancer gene expression data show PCE can improve the quality of clustering gene expression data by at least 4.5% (on average) than other related techniques, including dimensionality reduction based single clustering and ensemble approaches. The empirical study demonstrates that, to further boost the performance of clustering cancer gene expression data, it is necessary and promising to synergy projective clustering with ensemble clustering. PCE can serve as an effective alternative technique for clustering gene expression data.

ImportanceThe PAWPER tape system is one of the three most accurate paediatric weight estimation systems in the world. The latest version of the tape, which does not rely on a subjective assessment of habitus, is the PAWPER XL-MAC method which uses length and mid-arm circumference (MAC) to estimate weight. It was derived and validated in a population in the USA and has not yet been fully validated in a population from a resource-limited setting.ObjectiveThe objective of this study was to evaluate the performance of the PAWPER XL-MAC tape weight estimation system in a large dataset sample of children from resource-limited settings.MethodsThis was a "virtual" study in which weight estimates were generated using the PAWPER XL-MAC tape and Broselow tape 2007B and 2011A editions in a very large open access dataset. The dataset contained anthropometric information of children aged 6 to 59 months from standardised nutritional surveys in 51 low- and middle-income countries. The performance of PAWPER XL-MAC method was compared with the Broselow tape and a new length- and habitus-based tape, the Ralston method.Main outcomes and measuresThe bias of the weight estimation methods was assessed using the mean percentage error (MPE) and precision using the 95% limits of agreement (LOA) of the MPE. The overall accuracy was denoted by the percentage of weight estimates falling within 10% and 20% of actual weight (abbreviated as p10 and p20 respectively).ResultsThe MPE (LOA) for the PAWPER XL-MAC tape, the Broselow 2007B and 2011A and Ralston method were 1.9 (-15.3, 19.2), 5.4 (-15.9, 26.7), 7.7 (-13.3, 30.5) and -0.7 (-20.2, 19.3) respectively. The p10 and p20 for each method were 79.3% and 96.9% for the PAWPER XL-MAC tape, 64.3% and 91.0% for the Broselow tape 2007B, 55.5% and 85.9% for the Broselow tape 2011A and 67.4 and 94.0% for the Ralston method respectively. The PAWPER XL-MAC system was statistically significantly more accurate than the Broselow tape 2011A, the Broselow tape 2007B and the Ralston method. The relative difference in accuracy (p10) was 43% (odds ratio 4.4 (4.4, 4.5), pConclusions and relevanceThe PAWPER XL-MAC tape performed well in this study and was statistically significantly more accurate than both the Broselow tape editions and the Ralston method. This difference was substantial and clinically important. The tape did not perform as well at extremes of habitus-type, however, and might benefit from recalibration.

While quite some research has focussed on the accuracy of haptic perception of distance, information on the precision of haptic perception of distance is still scarce, particularly regarding distances perceived by making arm movements. In this study, eight conditions were measured to answer four main questions, which are: what is the influence of reference distance, movement axis, perceptual mode (active or passive) and stimulus type on the precision of this kind of distance perception? A discrimination experiment was performed with twelve participants. The participants were presented with two distances, using either a haptic device or a real stimulus. Participants compared the distances by moving their hand from a start to an end position. They were then asked to judge which of the distances was the longer, from which the discrimination threshold was determined for each participant and condition. The precision was influenced by reference distance. No effect of movement axis was found. The precision was higher for active than for passive movements and it was a bit lower for real stimuli than for rendered stimuli, but it was not affected by adding cutaneous information. Overall, the Weber fraction for the active perception of a distance of 25 or 35 cm was about 11% for all cardinal axes. The recorded position data suggest that participants, in order to be able to judge which distance was the longer, tried to produce similar speed profiles in both movements. This knowledge could be useful in the design of haptic devices. © 2014 van Beek et al.

In recent years, several approaches to develop computer aided diagnosis (CAD) systems for dementia have been proposed. Some of these systems analyze neurological brain images by means of machine learning algorithms in order to find the patterns that characterize the disorder, and a few combine several imaging modalities to improve the diagnostic accuracy. However, they usually do not use neuropsychological testing data in that analysis. The purpose of this work is to measure the advantages of using not only neuroimages as data source in CAD systems for dementia but also neuropsychological scores. To this aim, we compared the accuracy rates achieved by systems that use neuropsychological scores beside the imaging data in the classification step and systems that use only one of these data sources. In order to address the small sample size problem and facilitate the data combination, a dimensionality reduction step (implemented using three different algorithms) was also applied on the imaging data. After each image is summarized in a reduced set of image features, the data sources were combined and classified using three different data combination approaches and a Support Vector Machine classifier. That way, by testing different dimensionality reduction methods and several data combination approaches, we aim not only highlighting the advantages of using neuropsychological scores in the classification, but also implementing the most accurate computer system for early dementia detention. The accuracy of the CAD systems were estimated using a database with records from 46 subjects, diagnosed with MCI or AD. A peak accuracy rate of 89% was obtained. In all cases the accuracy achieved using both, neuropsychological scores and imaging data, was substantially higher than the one obtained using only the imaging data., This work was supported by the University of Liege, the “Fonds de la Recherche Scientifique” (FRS-FNRS), the “Stichting Alzheimer Onderzoek/Fondation Recherche Alzheimer” (SAO-FRA), and the Inter University Attraction Pole P7/11.

Data indicated that dyslexic individuals exhibited difficulties on tasks involving Working Memory (WM). Previous studies have suggested that these deficits stem from impaired processing in the Phonological Loop (PL). The PL impairment was connected to poor phonological processing. However, recent data has pointed to the Central Executive (CE) system as another source of WM deficit in dyslexic readers. This opened a debate whether the WM deficit stems solely from PL or can also be seen as an outcome of poor CE processing. In an attempt to verify this question, the current study compared adult skilled and compensated dyslexic readers with no impairment of phonological skills. The participants' PL and CE processing were tested by using the fNIR device attached to the frontal lobe and measured the changes in brain oxygen values when performing N-back task. As it was previously suggested, the N = 0 represented PL and N = 1 to 3 represent CE processing. It was hypothesized that dyslexic readers who show non-impaired phonological skills will exhibit deficits mainly in the CE subsystem and to a lesser extent in the PL. Results indicated that the two reading level groups did not differ in their accuracy and reaction times in any of the N-Back conditions. However, the dyslexic readers demonstrated significant lower maximum oxyHb values in the upper left frontal lobe, mainly caused due to a significant lower activity under the N = 1 condition. Significant task effects were found in the medial left hemisphere, and the high medial right hemisphere. In addition, significant correlations between fNIR-features, reading performance and speed of processing were found. The higher oxyHb values, the better reading and speed of processing performance obtained. The results of the current study support the hypothesis that at least for the group of dyslexics with non-impaired PL, WM deficit stems from poor CE activity.

Introduction Current guidelines and consensus recommend arterial and venous samples as equally acceptable for blood glucose assessment in point-of-care devices, but there is limited evidence to support this recommendation. We evaluated the accuracy of two devices for bedside point-of-care blood glucose measurements using arterial, fingerstick and catheter venous blood samples in ICU patients, and assessed which factors could impair their accuracy. Methods 145 patients from a 41-bed adult mixed-ICU, in a tertiary care hospital were prospectively enrolled. Fingerstick, central venous (catheter) and arterial blood (indwelling catheter) samples were simultaneously collected, once per patient. Arterial measurements obtained with Precision PCx, and arterial, fingerstick and venous measurements obtained with Accu-chek Advantage II were compared to arterial central lab measurements. Agreement between point-of-care and laboratory measurements were evaluated with Bland-Altman, and multiple linear regression models were used to investigate interference of associated factors. Results Mean difference between Accu-chek arterial samples versus central lab was 10.7 mg/dL (95% LA -21.3 to 42.7 mg/dL), and between Precision PCx versus central lab was 18.6 mg/dL (95% LA -12.6 to 49.5 mg/dL). Accu-chek fingerstick versus central lab arterial samples presented a similar bias (10.0 mg/dL) but a wider 95% LA (-31.8 to 51.8 mg/dL). Agreement between venous samples with arterial central lab was the poorest (mean bias 15.1 mg/dL; 95% LA -51.7 to 81.9). Hyperglycemia, low hematocrit, and acidosis were associated with larger differences between arterial and venous blood measurements with the two glucometers and central lab. Vasopressor administration was associated with increased error for fingerstick measurements. Conclusions Sampling from central venous catheters should not be used for glycemic control in ICU patients. In addition, reliability of the two evaluated glucometers was insufficient. Error with Accu-chek Advantage II increases mostly with central venous samples. Hyperglycemia, lower hematocrit, acidosis, and vasopressor administration increase measurement error.

[Objectives](a) To assess the effects of computed tomography (CT) scanners, scanning conditions, airway size, and phantom composition on airway dimension measurement and (b) to investigate the limitations of accurate quantitative assessment of small airways using CT images. [Methods]An airway phantom, which was constructed using various types of material and with various tube sizes, was scanned using four CT scanner types under different conditions to calculate airway dimensions, luminal area (Ai), and the wall area percentage (WA%). To investigate the limitations of accurate airway dimension measurement, we then developed a second airway phantom with a thinner tube wall, and compared the clinical CT images of healthy subjects with the phantom images scanned using the same CT scanner. The study using clinical CT images was approved by the local ethics committee, and written informed consent was obtained from all subjects. Data were statistically analyzed using one-way ANOVA. [Results]Errors noted in airway dimension measurement were greater in the tube of small inner radius made of material with a high CT density and on images reconstructed by body algorithm (p

In dentistry, 3D intra-oral scanners are gaining increasing popularity essentially for the production of dental prostheses. However, there is no normalized procedure to evaluate their basic performance and enable comparisons among intra-oral scanners. The noise value highlights the trueness of a 3D intra-oral scanner and its capacity to plan prosthesis with efficient clinical precision. The aim of the present study is to develop a reproducible methodology for determining the noise of an intra-oral scanner. To this aim, and as a reference, an ultra-flat and ultra-smooth alu-mina wafer is used as a blank test. The roughness is calculated using an AFM (atomic force microscope) and interferometric microscope measurements to validate this ultra-flat characteristic. Then, two intra-oral scanners (Carestream CS3500 and Trios 3Shape) are used. The wafer is imaged by the two intra-oral scanners with three different angles and two different directions, 10 times for each parameter, given a total of 50 3D-meshes per intra-oral scanner. RMS (root mean square), representing the noise, is evaluated and compared for each angle/direction and each intra-oral scanner, for the whole mesh, and then in a central ROI (region of interest). In this study, we obtained RMS values ranging between 5.29 and 12.58 micrometers. No statistically significant differences were found between the mean RMS of the two intra-oral scanners, but significant differences in angulation and orientations were found between different 3D intra-oral scanners. This study shows that the evaluation of RMS can be an indicator of the value of the noise, which can be easily assessed by applying the present methodology.