Inaccurate Measurements Research Articles

Comparison of Aerodynamic Effects on the Commonwealth Advisory Aeronautical Research Council (CAARC) Tall Building Model Tested in Two Wind Tunnel Laboratories

Wind tunnel test results can be influenced by various factors such as the blockage ratio and scaling ratio. These factors may introduce errors in the experimental outcomes, impacting the accuracy and reliability of the data obtained. This study quantitatively assesses consistency and identifies uncertainty sources to enhance result uniformity across various wind tunnel laboratories. This study conducted a systematic comparison between different wind tunnels in terms of rigid model pressure measurement wind tunnel experiments on the same Commonwealth Advisory Aeronautical Research Council (CAARC) standard tall building model. The study analyzes and discusses the results of mean and root-mean-square (RMS) wind pressure coefficients, peak factors, extreme wind pressure coefficients, probability density distributions, and base overturning force coefficients. The results indicated that in the open-circuit wind tunnel laboratory, the mean wind pressure coefficient is underestimated in the positive pressure region and overestimated in the negative pressure region. This is due to the static pressure which significantly decreases the streamwise direction within the test section, and the difference in static pressure is logarithmically proportional to the mean wind speed. Additionally, dynamic pressure is uniformly distributed along the test section axis. The inaccurate measurement of static pressure leads to these results. To address this issue, an indirect measurement method was employed to correct the static pressure results and reduce the error in the mean wind pressure coefficient to within 10%. Furthermore, differences in turbulence integral scale result in an error of up to 16% in the RMS wind pressure coefficient. Therefore, when conducting rigid model pressure measurement wind tunnel experiments, especially in open-circuit wind tunnel laboratories, careful consideration should be given to the influence of static pressure drop and integral length scale of turbulence.

Long-range trajectory reconstructions using the point mass model.

In shooting incident reconstructions, forensic examiners usually deal with scenes involving short-range trajectories, typically ≤30 m. Insituations such as this, a linear trajectory reconstruction model is appropriate. However, a forensic expert can also be asked to estimate a shooter's position by reconstructing a long-range trajectory where the bullet's path becomes arced as a result of gravity and the greater time in flight. In this study, the point mass model (PMM) was used, because it is accessible and considered sufficiently accurate. A computer program using PMM can perform long-range trajectory reconstructions starting from an impact point. The reconstruction results in an area where the shot is expected to be fired from, not a single location. This is caused by varying the input parameters of the PMM. The aim of this study is to assess the accuracy of the method and discuss the influence of the most relevant parameters. The model has been validated by comparing its performance with 20 handgun bullet trajectories that were determined using Doppler radar measurements over long ranges, i.e. from 500 m to 1800 m. Comparison between the area calculated using the model and the actual shooter position demonstrates the limits of these reconstructions, particularly at high incident angles. The differences between the reconstructed deflections and the deflections measured by the tracking radar are rather large. This phenomenon is caused by either measurement errors in the cross wind as a function of height or inaccuracy of the radar's deflection measurements.

The effects of surface tension on spherical oscillatory indentation of viscoelastic materials

Abstract The oscillatory indentation has become an attractive approach to characterizing the viscoelastic properties of soft biological solids. However, the influences of surface tension on oscillatory responses are ignored, which might lead to an inaccurate measurement of mechanical properties. In this work, the influences of surface tension on spherical oscillatory indentation for viscoelastic materials are investigated through the finite element method. The viscoelasticity of solids is characterized by the standard linear solid model and a sinusoidal displacement is applied as the excitation signal. During an entire cycle at the steady state of oscillation, both the average value of contact radius and the dissipated energy decrease due to the presence of surface tension. For the oscillatory responses at various frequencies, the existence of surface tension results in an increase of average force but a decrease of phase angle. The force amplitude at low frequencies becomes higher when surface tension is considered. For the evaluation of the complex modulus, neglecting the surface tension would lead to a significant overestimation of storage modulus at low frequencies and an obvious underestimation of loss modulus when the normalized frequency approaches 1. Our results provide a comprehensive understanding of the effects of surface tension on the mechanical responses of oscillation and the determination of viscoelastic properties through oscillatory indentation.

Next-generation methods for precise pH detection in ocular chemical burns: a review of recent analytical advancements.

Ocular burns due to accidental chemical spillage pose an immediate threat, representing over 20% of emergency ocular traumas. Early detection of the ocular pH is imperative in managing ocular chemical burns. Alkaline chemical burns are more detrimental than acidic chemical burns. Current practices utilize litmus, nitrazine strips, bromothymol blue, fluorescent dyes, and micro-combination glass probes to detect ocular pH. However, these methods have inherent drawbacks, leading to inaccurate pH measurements, less sensitivity, photodegradation, limited pH range, and longer response time. Hence, there is a tremendous necessity for developing relatively simple, accurate, precise ocular pH detection methods. The current review aims to provide comprehensive coverage of the conventional practices of ocular pH measurement during accidental chemical burns, highlighting their strengths and weaknesses. Besides, it delves into cutting-edge technologies, including pH-sensing contact lenses, microfluidic contact lenses, fluorescent scleral contact lenses, fiber optic pH technology, and pH-sensitive thin films. The study meticulously examines the reported work since 2000. The collected data have also helped propose future directions, and the research gap needs to be filled to provide a more rapid, sensitive, and accurate measurement of ocular pH in eye clinics. For the first time, this review consolidates current techniques and recent advancements in ocular pH detection, offering a strategic overview to propel ophthalmic-related research forward and enhance ocular burn management during a chemical spillage.

ANALYSIS OF THE STRUCTURE OF INTERFERENCE COATINGS FOR THE OPTIMIZATION OF THE PARAMETERS OF NARROWBAND OPTICAL FILTERS

To monitor the parameters of semiconductor layers deposited from solid solutions of A3B5 compounds during the epitaxy, optical control methods are used. The choice of optical monitoring methods is determined by the reactor design, which requires non-contact, fast, and precise measuring of wafer surface parameters. During the growth of epitaxial layers, the deposition of semiconductor compounds causes changes in the optical parameters of the wafer surface. To ensure precise measurements, it is essential to monitor these parameters within a narrow spectral range. In electro-optical monitoring systems, narrowband interference filters are used to select the desired spectrum. However, this type of filters is sensitive to several factors, such as environmental conditions, aging of the coating, and the angle of incidence. As a result, the manufacturing of narrowband optical filters with stable and precisely controlled optical characteristics presents a complex challenge. This article analyzes the impact of various factors on the optical characteristics of interference coatings. Quantitative analysis of these shows that shift of the selected spectral band with central wavelength λmax can approach or even exceed the full width at half maximum (FWHM). These changes in the optical characteristics of narrowband filters lead to a decrease in the accuracy required for optical monitoring during epitaxial processes, which leads to inaccuracies in measurements. The results of this analysis will guide the optimization of thin-film structures used in narrowband optical filters. The study of the shift in the selected band also enables, within certain limits, controlled changes to λmax or the compensation of its shift its shift during regular factor variations. Ultimately, it enables to take these changes into account when designing electro-optical systems for monitoring the epitaxial growth of semiconductor heterostructures, which increases the accuracy and stability of optical measurements in the required accuracy range.

Renovation of JGC-30 Coal Feeding Belt in Thermal Power Plant

The coal feeder of our company's pulverizing system adopts JGC-30 weighing metering coal feeder. The raw coal in the raw coal hopper falls onto the coal feeder belt through the coal drop port by its own gravity. The existing design of high belt skirt on both sides is 40mm. A small amount of coal blocks falls off on both sides of the belt during the falling process. Due to the wind force of the coal feeder sealing wind and the operation of the belt, a small amount of coal blocks are scattered and stuck at the coal feeder weighing device. The inaccurate coal quantity measurement leads to large fluctuations in the coal feeding quantity of the pulverizing system, that will makes inducing abnormal vibration of the coal mill, insufficient coal powder output, large amount of slag discharge from the coal mill and other problems, which seriously affect the safe and stable operation of the pulverizing system. In this regard, the coal feeding belt was modified, and the skirts on both sides of the coal feeder were increased to 60mm. After the modification, it can be ensured that the raw coal does not fall from the skirts on both sides during the operation of the coal feeder, thereby solving the problem of inaccurate coal quantity measurement caused by coal blocks stuck in the weighing device. This study aims to address the problem by modifying the coal feeder belt, namely by increasing the skirt height on both sides of the belt from 40mm to 60mm. The method applied was to adjust the belt skirt design directly on the operating coal feeder, followed by operational testing to evaluate the effectiveness of the modification in preventing coal falling from the belt side. Results show that after increasing the height of the skirt belt, there is no more coal falling during coal feeder operation. Coal measurement became more accurate, which had a positive impact on coal feeding stability, reduced vibration in the coal mill, as well as increased fine coal output and reduced the amount of slag produced.

Suitability of the DSM-5 social anxiety disorder severity scale for autistic adults.

Mental health measures used with autistic adults are often only evaluated for use with non-autistic adults, which may cause inaccurate measurement. This is important when measuring social anxiety disorder as some features overlap with social characteristics of autism. This study evaluated one self-report questionnaire measure of social anxiety disorder, the Severity Measure for Social Anxiety Disorder. The Severity Measure for Social Anxiety Disorder is based upon criteria for diagnosis of social anxiety disorder, and we aimed to understand its suitability for autistic adults. The Severity Measure for Social Anxiety Disorder was completed by 284 autistic adults and 80 non-autistic adults who were then asked five follow-up questions about ambiguous questions on the Severity Measure for Social Anxiety Disorder. We found that over half our sample of autistic adults, on at least one question, attributed their answer to something other than anxiety. Furthermore, in autistic adults, one underlying construct of social anxiety did not link their answers on the Severity Measure for Social Anxiety Disorder together, suggesting the Severity Measure for Social Anxiety Disorder might not be suited to capturing social anxiety disorder in autistic adults. To improve measurement, we rescored answers where participants said their response was due to something other than social anxiety, however, the rescored Severity Measure for Social Anxiety Disorder did not only capture social anxiety in autistic adults either. Finally, we analysed the reasons other than social anxiety autistic adults said influenced their answers. We grouped their responses into 10 categories, for example, 'fatigue', 'sensory overwhelm', and 'masking'. Overall, our findings suggest caution when using the Severity Measure for Social Anxiety Disorder with autistic adults, and the categories identified may suggest how to measure social anxiety more accurately in autistic adults.

Inaccuracy of temporal thermometer measurement by age and race.

Rapid vital sign assessment, including temperature measurement, is critical among pediatric patients presenting to the emergency department (ED). While error rates in temporal thermometry are well documented, the potential for differential error rates by demographics are not well established. Our objective was to evaluate error rates of temporal thermometers by demographic variables, specifically race and age, among pediatric patients in the ED. Pediatric patients (≤18 years old) identified as either Black or White in the medical record presenting to the ED between January 2020 and December 2022 who received at least one paired temperature measurement (temporal and oral/rectal temperature within 30 minutes) were included. Rates of discordance by demographic characteristics were then evaluated. Secondarily, we explored characteristics of patients who received temporal thermometry only. The final population included 1,526 paired temperatures (1,412 patients). Among all paired measurements, 26% had discordant measurements (25% in Black patients vs. 26% in White patients). In the final adjusted model, children age ≤12 years old were found to have 2-3 times higher odds of discordance than children >12 years old. Black patients were statistically significantly more likely to receive a temporal thermometer measurement only (aOR 1.27, 95%CI: 1.22, 1.33), even when controlling for fever-related chief complaints. Age ≤12 years old was associated with increased odds of missed fever by temporal thermometry. In our secondary analysis, Black patients were found to be more likely to receive temporal thermometry only. These findings highlight the need for consistent, accurate measurement protocols among pediatric patients.

Ground Calibration with Orthogonality Correction for Tri-Axis Fluxgate Magnetometer for CAS500-3

This paper presents ground calibration and orthogonality correction methods for the tri-axis fluxgate magnetometer (FGM), named as adaptive in-phase magnetometer (AIMAG), aboard the CAS500-3 satellite. The orthogonality errors of the FGM among the axes can lead to significant inaccuracies in magnetic field measurements. In this study, we employed Helmholtz coils and an autocollimator to apply controlled magnetic fields and adjust the magnetometer’s alignment. By deriving the correction matrix, we could transfer the sensor axes to the ideal orthogonal coordinate system. We validated the correction method by analyzing the sensor’s output under various magnetic field conditions. This correction method is expected to enhance the in-flight magnetic field measurements of the CAS500-3 satellite.

Analysis and Decoupling Study of the Coupling Effects on Projectile Acceleration Parameters

Abstract Internal ballistic parameter testing is crucial for evaluating artillery performance and design, with projectile acceleration being a core parameter. During the firing process, projectile acceleration parameters can easily be coupled with the projectile’s modal effects and the transverse effects of triaxial accelerometers, leading to inaccurate measurements. Therefore, this paper innovatively proposes a data decoupling method to improve the accuracy of acceleration measurements. Firstly, the internal ballistic firing mechanism and the transverse effects of triaxial accelerometers are analyzed. Secondly, a simulation analysis of the projectile modal is conducted, combined with the projectile’s motion state within the barrel, to determine the modal orders and frequencies under axial stretching and compression vibration modes. Thirdly, shock tests are performed on triaxial accelerometers using a shock table to establish the relationships between triaxial acceleration signals. Finally, the projectile modal, Empirical Mode Decomposition (EMD), and the transverse effects of triaxial accelerometers are combined to decouple the acceleration signals. A comparison between the decoupled acceleration signals and theoretical data shows that the error is reduced from 8.1% to 3.2%, significantly improving the accuracy of the acceleration signals.

Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations.

Middle-Aged and Elderly people today face a variety of health problems as a result of their modern lifestyle, which includes increased work stress, less physical activity, and altered food habits. Because of Complications arising, diabetes has become one of the most frequent, severe, and fatal illnesses around the world. Therefore, inaccurate measurements of blood glucose levels can seriously damage vital organs. Several strategies for long-term glucose prediction have been proposed in the literature. Unfortunately, these methods require the patient to identify their daily activities, which can be error-prone, such as meal intake, insulin injection, and emotional aspects. This paper suggests using continuous glucose monitoring (CGM) of 14733 patients, with three assistance factors to predict blood glucose levels independently of other parameters, hence reducing the burden on the patients. To support this an Artificial Neural Network (ANN), Binary Decision Tree (BDT), Linear Regression (LR), Boosting Regression Tree Ensemble (BSTE), Linear Regression with Stochastic Gradient Descent (LRSGD), Stepwise (SW), Support Vector Machine (SVM), and Gaussian process regression (GPR) were investigated. The result indicated that The highest classification accuracy of (92.58%) has been achieved by BDT followed by BSTE (92.04%) and GPR (88.59%). The obtained average of root means square error (MSE) was 1.64, 1.67, 1.69, mg/dL for prediction horizon (PH) respectively to GPR, BSTE, and ANN.

Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks

Abstract An extendable, efficient and explainable Machine Learning approach is proposed to represent cyclic plasticity and replace conventional material models based on the Radial Return Mapping algorithm. High accuracy and stability by means of a limited amount of training data is achieved by implementing physics-informed regularizations and the back stress information. The off-loading of the neural network (NN) is applied to the maximal extent. The proposed model architecture is simpler and more efficient compared to existing solutions from the literature using approximately only half the amount of NN parameters, while representing a complete three-dimensional material model. The validation of the approach is carried out by means of results obtained with the Armstrong–Frederick kinematic hardening model. The mean squared error is assumed as the loss function which stipulates several restrictions: deviatoric character of internal variables, compliance with the flow rule, the differentiation of elastic and plastic steps and the associativity of the flow rule. The latter, however, has a minor impact on the accuracy, which implies the generalizability of the model for a broad spectrum of evolution laws for internal variables. Numerical tests simulating several load cases are presented in detail. The validation shows cyclic stability and deviations in normal directions of less than 2% at peak values which is comparable to the order of measurement inaccuracies.

Examining the self-regulated learning scale using the Rasch model approach

Self-regulated learning is a crucial aspect of the learning process for students. This ability is often overlooked due to the challenges of inaccurate measurement. This study aims to evaluate the quality of a self-regulated learning scale developed through an analysis of respondent responses. The research employed a descriptive quantitative approach using the Rasch Model as the analytical method. The instrument used consisted of 30 statement items. The study sample included 59 mathematics education students selected through cluster random sampling from two universities in different districts. The analysis results indicated that, after three calibration processes, the self-regulated learning scale was refined to 28 items with excellent quality. Furthermore, the responses of 58 students demonstrated a high level of consistency. Thus, self-regulated learning scale has good validity and reliability, making it a dependable tool for measuring self-regulated learning abilities. The implications of this study include the provision of a practical and reliable instrument for researchers and educators to support further studies and serve as an evaluation tool in learning development.

How to take and record a manual blood pressure measurement.

Accurate measurement of a patient's blood pressure (BP) is essential to identify hypotension or hypertension and to inform subsequent management and treatment decisions. The auscultatory, or manual, method remains the gold standard for non-invasive BP measurement, so it is vital that nurses are able to undertake this procedure accurately. This article explains how to take and record a manual BP measurement using an aneroid sphygmomanometer and a stethoscope. Nurses and nursing students undertaking this procedure must be equipped with the knowledge and skills to do so proficiently and work within their scope of practice. • BP measurement comprises two pressure readings, systolic and diastolic, which are measured in millimetres of mercury (mmHg) and expressed in documentation as a 'fraction'. • Inaccurate BP measurement, whether overestimation or underestimation, can result in diagnostic errors and incorrect risk assessment and decision-making. • Various factors can influence the accuracy of BP measurement, including patient positioning, cuff size, arm position and correct use of the stethoscope. • It is vital to ensure regular maintenance and recalibration of BP measuring equipment, in accordance with the manufacturer's instructions, to ensure accuracy of readings. REFLECTIVE ACTIVITY: 'How to' articles can help to update your practice and ensure it remains evidence based. Apply this article to your practice. Reflect on and write a short account of: • How this article might improve your practice when taking a manual BP measurement. • How you could use this information to educate nursing students or your colleagues on the appropriate steps when taking and recording a manual BP measurement.

On the Parasitic Surface Adsorption of Pyrrolidinium and Phosphonium-Based Ionic Liquid Preventing Accurate Differential Capacitance Measurements

Ionic Liquids (ILs) have received a substantial interest from the scientific community over the past few decades1, in particular, because of their possible use as electrolytes for battery technology. This wide excitement stems from their known thermal stability and non-volatile nature2 (as opposed to more traditional organic carbonate-based electrolytes) which has led the study of IL to fall under the category of green chemistry3.In a similar fashion to aqueous-based electrolytes, whose bulk properties are fundamentally different from their properties near charged interfaces (giving rise to an Electrical Double Layer, EDL), ILs and IL-based electrolytes also exhibit a distinct interfacial structuring near charged surfaces consisting of alternating layers of cations and anions4 extending into the liquid over several nanometers5. This interfacial structuring (i.e., EDL) initially formed at the electrode/electrolyte interface defines the charge transfer mechanism6. It is also believed to play a critical role in the formation of the Solid Electrolyte Interphase (SEI)7,8. The latter, via its morphological, mechanical and chemical properties directly governs the performance of the battery9.Electrochemical Impedance Spectroscopy (EIS) is an attractive technique for the indirect study of the EDL at charged interfaces, via the so-called differential capacitance measurement. The latter giving an indication of the ionic density near the interface10. Differential capacitance measurements are, however, difficult to interpret and compare, because there is no real consensus as to how the measurement needs to be performed. To add to the difficulty, some ionic liquids are known to display a hysteresis process, inducing measurement variabilities.In this study, we propose to investigate the structure of the EDL of pure IL (trimethyl isobutyl phosphonium bis(fluorosulfonyl)imide, P111i4FSI and N-methyl-N-propylpyrrolidinium bis(fluorosulfonyl)imide, C3mpyrFSI) as well as IL-based electrolytes composed of 42mol% of NaFSI in C3mpyrFSI and/or P111i4FSI using both a differential capacitance and AFM approach. Using a well-established method for the measurement of the differential capacitance in IL and IL-based electrolytes, we show that all the studied systems display important hysteresis properties (in particular, the pyrrolidinium-based ones). Via a series of differential capacitance as well as AFM experiments, we further demonstrate that the hysteresis is a result of adsorption processes on the surface of the electrode. This parasitic adsorption leads inaccuracies in traditional differential capacitance measurements. We therefore propose an alternative method for the measurement of the differential capacitance which allows to minimize the impact of adsorption.This new understanding of differential capacitance measurements has important methodological implications. By providing guidelines for accurately probing the differential capacitance of ILs and IL-based electrolytes, in particular, pyrrolidinium and phosphonium-based ones via a single, reliable method, this report may well help pave the way to easier comparisons and interpretations. J.P. Hallett et al., Chem. Rev. 2011, 111, 3508-3576.S. Zhang et al., ACS Appl. Mater. Interfaces 2021, 13, 53904-53914.K. Paduszynski et al., J. Chem. Inf. Model. 2014, 54, 1311-1324.J.M. Black et al., ACS Appl. Mater. Interfaces 2017, 9, 40949-40958.R. Hayes et al., Chem. Rev. 2015, 115, 6357-6426.D. Rakov et al., Chem. Mater. 2021, 34, 165-177.Q. Wu et al., J. Am. Chem. Soc. 2023, 145, 2473-2484.D.S. Silvester et al., J. Phys. Chem. C 2021, 125, 13707-13720.Y. Zhou et al., Nat. Nanotechnol. 2020, 15, 224-230.J.M. Klein et al., Phys. Chem. Chem. Phys. 2019, 21, 3712-3720. Figure 1

The INS/GPS integrated navigation based on autonomous underwater vehicle using modified extended Kalman filter

Ensuring highhtab accuracy and robustness remains a paramount concern in the realm of underwater positioning and navigation research. This paper proposes a filtering algorithm grounded in Inertial Measurement Unit/Global Positioning System (INS/GPS) integrated navigation to effectively address the challenges posed by non-Gaussian noise, stemming from outliers and measurement inaccuracies. Currently, most filtering algorithms are developed based on the criteria of minimum mean square error (MMSE) or maximum entropy criteria (MCC). To address the challenge of handling complex non-Gaussian noises, this paper uses the Minimum Error Entropy Criterion (MEE) and Extended Kalman Filter (EKF) with Kernel Risk-Sensitive Loss (KRSL) instead of MMSE or MCC to develop an online filtering algorithm with a recursive process, and adjusts the kernel size of MEE within a reasonable range by constructing an adaptive factor to deal with outliers generated during measurement and excessive convergence caused by the inapplicability of the kernel size. Through extensive target tracking simulations and surface Autonomous Underwater Vehicle (AUV) localization experiments, results demonstrate the efficacy of the proposed algorithm. Notably, the algorithm optimizes kernel sizes for different types of noises, ensuring robust state estimation and rapid convergence without compromising filtering accuracy.

Oil pipeline multiple leakage detection and localization based on sensor fusion

Oil pipeline simultaneous leak localization solely using pressure and flow rate measurements at its boundaries is inherently challenging. Localizing simultaneous leaks in a long-distance oil pipeline solely using pressure and flow rate measurements at its boundaries presents significant challenges. This difficulty is attributed to the presence of noisy measurements and the interdependence of two equations that incorporate variables associated with leaks, leading to inherent uncertainty. Additionally, existing leak detection methodologies predominantly utilize a single sensor, which contributes to a high incidence of false alarms, particularly in complex operational environments. Developing nonlinear equations based on momentum and continuity principles is proposed as a comprehensive solution for estimating multiple leak locations in oil pipelines. In this study, multiple leaks in long-distance oil pipelines are estimated using a two-stage decision-making scheme. Arrays of sensors are proposed for improving the reliability and accuracy of simultaneous leak estimations, replacing the traditional reliance on single sensors along pipelines. The Fisher fusion technique combines inaccurate measurements to improve estimation accuracy. This method integrates sensor measurements even when noise is present, demonstrating its effectiveness. Comprehensive simulationsare conductedusing OLGA multiphase flow simulation software to evaluate the robustness and practicality of the proposed approach under various real-time conditions found in long-distance oil pipelines. The system’s state convergence and precision in simultaneous leak estimations highlight the effectiveness of the proposed strategy in oil pipeline control. Across various scenarios, the leak detector showed a 28 % improvement for a 50 Km oil pipeline.

Abstract A016: Early pancreatic cancer detection using extracellular vesicle DNA methylation signatures in blood

Abstract In 2020, there were 495,773 new cases and 466,003 deaths for pancreatic cancer worldwide. Furthermore, pancreatic cancer is emerging to be the leading cause of cancer related deaths in the U.S. by the year 2030, surpassing lung and colon cancer. The majority of pancreatic cancer patients (∼80%) are diagnosed at the most advanced (metastatic) stage, for which the 5-year survival is 3%. Dramatically, studies show that if it can be detected at an early stage when surgical removal is feasible, the 5-year survival rate significantly increased to 37%. This data highlights the crucial importance of early detection for pancreatic cancer treatment with curative intent. Unfortunately, currently there are no reliable techniques for routine screening to identify pancreatic cancer at early stages. In this Abstract, we developed and validated the performance of those DNA methylation markers to detect pancreatic cancer in a cohort of pancreatic cancer patients. Firstly, we collected a large amount of genome-wide methylation microarray data (targeting over 450,000 methylation sites) of tissue samples from several publicly available databases, including samples of solid pancreatic tumors (n = 384), noncancerous pancreatic tissues (n = 126) and healthy whole blood (n = 453). The raw microarray data were preprocessed using a pipeline implemented in R, which removes inaccurate measurements and corrects for bias caused by technical issues. A two-stage feature selection procedure was designed and implemented in Python, which makes use of various filters and a multivariate embedded method, support vector machine recursive feature elimination (SVM-RFE). The features were evaluated using two metrics, classification performance and stability, based on a tradeoff of which we selected a set of differentially methylated loci for discriminating the samples. The set of prospective markers includes 129 hypermethylated and 142 hypomethylated tumor-specific loci, 8 hypermethylated and 8 hypomethylated pancreatic tissue specific loci. To validate the performance of those pancreatic cancer-specific methylation markers, as a feasibility study, we isolated extracellular vesicles from cancer cells and plasma of cancer patients using lipid nanoprobe (LNP). Extracellular vesicles (EVs) are lipid-bilayer-enclosed vesicles of sub- micrometer size that are secreted by virtually all cell types. In a pilot study encompassing 11 pancreatic cancer patients (Stage I-IV) and age-matched 10 healthy donors (HD), we employed quantitative methylation-specific polymerase chain reaction assays (qMSP) to examine the promoter methylation status of the genes within plasma EV DNA. The receiver operating characteristic (ROC) curves were employed to assess the performance of a combined promoter methylation signature in EV DNA for the detection of pancreatic cancer. Our findings indicate that the promoter methylation of genes can be specific to pancreatic cancer, suggesting the efficient packaging of methylation information from genomic DNA into EVs. Citation Format: Hongzhang He, Siyang Zheng. Early pancreatic cancer detection using extracellular vesicle DNA methylation signatures in blood [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A016.

Capacitance-based mass flow rate measurement of two-phase hydrogen in a 0.5 in. tube

Mass flow rate is a critical measurement parameter when designing cryogenic hydrogen fluid systems. It is important in custody transfer applications for calculating financial obligations, fundamental fluid property research/modeling, and fluid system design applications to optimize chill down performance, maintain thermal equilibriums, and provide feedback control for pumps and valves. However, due to the large temperature differential between cryogenic fluids and the environment, there is often multiphase flow during system chilldown and steady state operation. Current available cryogenic flow measurement techniques are not equipped to deal with the complex multiphase flow inherent in cryogenic fluid systems, resulting in significant measurement errors. This mass flow measurement inaccuracy can cause financial loss, system instability, and even component failure, resulting in a strong market demand for a multiphase cryogenic mass flow meter to optimize and control sophisticated and costly cryogenic systems. This paper presents a solution in the form of a novel capacitance-based technique for measuring the multiphase mass flow rate of cryogenic hydrogen in a terrestrial environment. The device was calibrated and tested on a ½” tube multiphase hydrogen flow loop at a cryogenic hydrogen test facility. An error of ± 2 % full scale was achieved across a range of flow conditions, including transient and steady states.

Enhancing accuracy of alignment measurement in lithography using two-dimensional desirable sidelobe convolution window

Suppressing spectral leakage is crucial for achieving high-precision measurements using fringe images. However, existing classical windows are not effective in suppressing spectral leakage owing to their inadequate performance, leading to inaccurate measurements. To enhance the accuracy of alignment measurement for lithography by suppressing the spectral leakage associated with phase extraction of Moiré fringes, we introduce a novel two-dimensional desirable sidelobe convolution window (2D-DSCW), constructed using the maximum sidelobe attenuation window as the basis, followed by multiple self-convolutions. The 2D-DSCW with a reasonable order exhibits outstanding sidelobe behaviors, with the peak sidelobe level and sidelobe attenuation rate proportional to the convolution order. Based on this window, an improved windowed fast Fourier transform algorithm is established. Simulation and experimental results reveal that compared with classical windows, the proposed approach can more effectively suppress spectral leakage, enhancing phase extraction accuracy, and thus enabling lithography alignment with an accuracy of sub-1-nm (0.91 nm).