Enhance Measurement Precision Research Articles

Searches for exotic spin-dependent interactions with spin sensors.

Numerous theories have postulated the existence of exotic spin-dependent interactions beyond the Standard Model of particle physics. Spin-based quantum sensors, which utilize the quantum properties of spins to enhance measurement precision, emerge as powerful tools for probing these
exotic interactions. These sensors encompass a wide range of technologies, such as optically pumped magnetometers, atomic comagnetometers, spin masers, nuclear magnetic resonance, spin amplifiers, and nitrogen-vacancy centers. These technologies stand out for their ultrahigh sensitivity, compact tabletop design, and cost-effectiveness, offering complementary approaches to the large-scale particle colliders and astrophysical observations. This article reviews the underlying physical principles of various spin sensors and highlights the recent theoretical and experimental progress in the searches for exotic spin-dependent interactions with these quantum sensors. Investigations covered include the exotic interactions of spins with ultralight dark matter, exotic spin-dependent forces, electric dipole moment, spin-gravity interactions, and among others. Ongoing and forthcoming experiments using advanced spin-based sensors to investigate exotic spin-dependent interactions are discussed.

Enhancing the Precision of the Self-Compassion Scale Short Form (SCS-SF) with Rasch Methodology

Abstract Objectives Precise measurement of self-compassion is essential for informing well-being–related policies. Traditional assessment methods have led to inconsistencies in the factor structure of self-compassion scales. We used Rasch methodology to enhance measurement precision and assess the psychometric properties of the Self-Compassion Scale Short Form (SCS-SF), including its invariance across Ghana, Germany, India, and New Zealand. Method We employed the Partial Credit Rasch model to analyse responses obtained from 1000 individuals randomly selected (i.e. 250 from each country) from a total convenience sample of 1822 recruited from the general populations of Germany, Ghana, India, and New Zealand. Results The initial identification of local dependency among certain items led to a significant misfitting of the SCS-SF to the Rasch model (χ2 (108) = 260.26, p < 0.001). We addressed this issue by merging locally dependent items, using testlets. The solution with three testlets resulted in optimal fit of the SCS-SF to the Rasch model (χ2 (27) = 23.84, p = 0.64), showing evidence of unidimensionality, strong sample targeting (M = 0.20; SD = 0.72), and good reliability (Person Separation Index = 0.71), including invariance across sociodemographic factors. We then developed ordinal-to-interval conversion tables based on the Rasch model’s person estimates. The SCS-SF showed positive correlations with measures of compassion towards others, optimism, and positive affect, alongside negative associations with psychological distress and negative affect. Conclusions The current study supports the reliability, as well as the structural, convergent, and external validity of the SCS-SF. By employing the ordinal-to-interval conversion tables published here, the precision of the measure is significantly enhanced, offering a robust tool for investigating self-compassion across different cultures.

Comparative analysis of optical gating time characterization methods for ultrafast gated image intensifiers with sub-nanosecond temporal resolution

Ultrafast gated image intensifiers are crucial for capturing high-resolution images with sub-nanosecond temporal resolution. This study compares two methods for characterizing optical gating time in these intensifiers: Method I, involving a “laser pulse walkthrough,” and Method II, utilizing a fiber optic delay array. Both methods were applied to the same intensifier, with results analyzed for consistency and discrepancies. The findings indicate that both methods yield consistent optical gating times within their standard deviations range, though Method II exhibited greater dispersion at the photocathode edges due to spatial non-uniformity. The study further reveals that while the optical gating time distribution across the photocathode is uniformly consistent, a constant delay exists between different regions. To enhance measurement precision it is recommended to subdivide the photocathode for individual calibration of gating time and delay. These insights are pivotal for improving the precision and reliability of optical gating time measurements in applications requiring sub-nanosecond or even picosecond temporal resolution.

A calibration method for a wireless real-time CMOS pixel medical dosimeter

This study introduces and validates a novel calibration function for wireless wearable dosimeters, crucial for real-time dosimetry in interventional radiology. Focusing on enhancing accuracy and safety, it compares data from threshold-based wireless dosimeters with a full-data-read detector. The research involves a central detector and four lateral wireless dosimeters, each equipped with an identically-typed CMOS Image Sensor (CIS), subjected to various photon dose rates and doses from a certified beam. Two key calibration functions were developed: one that correlates the pixel count over a threshold with the dose rate, and the other that links the cumulative pixel value above the threshold to the total absorbed dose. These functions are essential in converting raw CIS data into precise dosimetric information.The study findings reveal that the single-pixel sensitivity of wireless prototypes is approximately 8.5 ± 0.8 ADC/nGy. Following the application of calibration functions, the responses of these prototypes align consistently with the TLD dosimeter measurements. In particular, for three of the prototypes, this calibration ensures that the measurement uncertainty remains within 6% for the dose rate and within 8% for the dose.This research confirms the effectiveness and feasibility of pixel-based wireless dosimeters in interventional radiology, highlighting the importance of integrating offline data processing for enhanced measurement precision.

Harnessing graph state resources for robust quantum magnetometry under noise

Precise measurement of magnetic fields is essential for various applications, such as fundamental physics, space exploration, and biophysics. Although recent progress in quantum engineering has assisted in creating advanced quantum magnetometers, there are still ongoing challenges in improving their efficiency and noise resistance. This study focuses on using symmetric graph state resources for quantum magnetometry to enhance measurement precision by analyzing the estimation theory under time-homogeneous and time-inhomogeneous noise models. The results show a significant improvement in estimating both single and multiple Larmor frequencies. In single Larmor frequency estimation, the quantum Fisher information spans a spectrum from the standard quantum limit to the Heisenberg limit within a periodic range of the Larmor frequency, and in the case of multiple Larmor frequencies, it can exceed the standard quantum limit for both noisy cases. This study highlights the potential of graph state-based methods for improving magnetic field measurements under noisy environments.

Precision Calibration and Linearity Assessment of Thin Film Force-Sensing Resistors

In this study, we thoroughly analyzed the linearity and repeatability of force-sensing resistor (FSR) sensors through static load tests to ensure their reliability. The novelty of this research lies in its comprehensive evaluation and direct comparison of two widely used FSR sensors, i.e., Flexiforce A201-1 and Interlink FSR-402, under various loading conditions by employing a robust calibration methodology. This study provides detailed insights into the sensors’ performances, offering practical calibration equations that enhance measurement precision and reliability, which have not been extensively documented in previous studies. Our results demonstrate that the linearity of thin film FSR sensors is highly accurate, closely resembling a straight line. We employed M1 Class weights, applying loads ranging from 20 g to 300 g. The resistance of the FSR sensors, which varies with the applied load, was measured using a voltage divider circuit and an analog-to-digital converter of a microcontroller. MATLAB was used to calculate the average output voltage for each applied load and fixed resistance. Additionally, we examined the relationships among load, FSR sensor resistance, and conductivity. Our research indicates that with precise calibration, thin film FSR sensors can be highly reliable for force measurement applications.

Accuracy compensation method with the combined dissimilar measurement devices for enhanced measurement quality: a digital aircraft assembly technology

PurposeThe pivotal aspect of aircraft assembly lies in precise measurement accuracy. While a solitary digital measuring tool suffices for analytical and small surfaces, it falls short for extensive synthetic surfaces like aircraft fuselage panels and wing spars. The purpose of this study is to develop a “combined measurement method” (CMM) that enhances measurement quality and expands the evaluative scope, addressing the limitations posed by singular digital devices in meeting measurement requirements across various aircraft components.Design/methodology/approachThe study illustrated the utilization of the CMM by combining a laser tracker and a portable arm-measuring machine. This innovative approach is tailored to address the intricate nature and substantial dimensions of aircraft fuselage panels. The portable arm-measuring machine performs precise scans of panel components, while common points recorded by the laser tracker undergo coordinate conversion to reconstruct the fuselage panel’s shape. The research outlines the CMM’s measurement procedure and scrutinizes the data processing technique. Ultimately, the investigation yields a deviation vector matrix and chromatogram deviation distribution, pivotal in achieving enhanced measurement precision for the novel CMM device.FindingsThe use of CMM noticeably enhances fuselage panel assembly accuracy, concurrently reducing assembly time and enhancing efficiency compared to conventional measurement systems.Practical implicationsThe research’s practical implication lies in revolutionizing aircraft assembly by mitigating accuracy issues through the innovative digital CMM for aircraft synthetic structure type product (aircraft fuselage panel). This ensures safer flights, reduces rework and enhances overall efficiency in the aerospace industry.Originality/valueIntroducing a new aircraft assembly accuracy compensation method through digital combined measurement, pioneering improved assembly precision. Also, it enhances aerospace assembly quality, safety and efficiency, offering innovative insights for optimized aviation manufacturing processes.

Entanglement-enhanced quantum metrology: From standard quantum limit to Heisenberg limit

Entanglement-enhanced quantum metrology explores the utilization of quantum entanglement to enhance measurement precision. When particles in a probe are prepared into a suitable quantum entangled state, they may collectively accumulate information about the physical quantity to be measured, leading to an improvement in measurement precision beyond the standard quantum limit and approaching the Heisenberg limit. The rapid advancement of techniques for quantum manipulation and detection has enabled the generation, manipulation, and detection of multi-particle entangled states in synthetic quantum systems such as cold atoms and trapped ions. This article aims to review and illustrate the fundamental principles and experimental progresses that demonstrate multi-particle entanglement for quantum metrology, as well as discuss the potential applications of entanglement-enhanced quantum sensors.

Comparison between NodeMCU ESP8266 and Uno R3 for Software Development using Ubidots

The Internet of Things (IoT) refers to devices with the capability to collect, analyze, and communicate sensed data to users. This technology streamlines user observation and control of water quality, aiming to enhance measurement precision and overall water conditions through the integration of Ubidots. The motivation behind this project is to monitor water quality, comparing the effectiveness of the NodeMCU ESP8266 and Uno R3 systems. This project was into hardware and software development. In the hardware development, first part the sensor such as Total Dissolved Oxygen (TDS) value attached with Uno R3 and second part TDS sensor attached with NodeMCU ESP8266 was integrated. For software development, Arduino IDE programming is used to program the operation of water quality monitoring system. Furthermore, Ubidots software to ensure the real-time update of data collection from water quality monitoring system (WQMS). Finally, the recorded data will be uploaded simultaneously to be an analyzed and compared on the IoT platform. The result shows that the WQMS can fully function in different conditions of water and software development using Ubidots.

Wideband Measurement Approach for EIS of Lithium-Ion Batteries Using Low-Frequency Concentrated Disturbance

Precise and rapid measurement for electrochemical impedance spectroscopy (EIS) is conducive to the working state monitoring and fault diagnosis of lithium-ion batteries (LIBs). Although using a wideband signal can effectively reduce measurement time, it will deteriorate the measurement precision due to the insufficient Signal-to-Noise Ratio. Considering this issue, this paper proposes a wideband measurement approach using low-frequency concentrated disturbance for the EIS of LIBs. This approach can obtain high measurement accuracy and a wide measurement bandwidth under a small current disturbance. Besides, it effectively reduces the measurement time. First, LIBs are stimulated by a low-frequency concentrated binary sequence signal to enhance measurement precision in a low-frequency region. Then, in the entire frequency region, an accurate EIS can be obtained by a fast Morlet wavelet transform and covariance-based impedance calculation. Finally, the effectiveness of the proposed approach is verified on a buck-boost converter-based EIS measurement platform, and comparative analyses with literature methods are conducted. The experimental results illustrate that the maximum Normalized Root Square Error of the two types of LIBs at different state-of-charge is 0.37% under the response voltage amplitude of less than 10mV. Moreover, this approach is approximately 20 times faster than commercial electrochemical workstations in measurement time.

Motor proficiency in young children with Prader-Willi syndrome: a preliminary report

BACKGROUND: Systematic documentation of motor characteristics in young children with Prader-Willi syndrome (PWS) is vital as access to treatments improves. AIM: To characterize motor proficiency (MP) in young children with PWS. METHOD: Participants included 6 children (3 male and 3 female) with PWS and 13 children with neurotypical development (NT), (9 male and 4 female) ages 4-6 years. Five out of six children with PWS had been on growth hormone replacement therapy (GHRT) for >3 years. Some children with PWS exhibited cognitive delays and others performed within the average range (Intellectual quotient mean± standard deviation = 65.3 ± 7.62, range = 47 – 94). MP was measured using the Short Form of the Bruininks-Oseretsky Test of Motor Proficiency-Second Edition (BOT-2-SF). RESULTS: Children with PWS scored lower than children with NT in all areas of MP except for fine motor integration. All children with PWS scored well-below average for total MP; children with NT scored average (n=10) or above-average (n=3) for total MP, respectively. CONCLUSION: At this young age children with PWS universally exhibited poor MP despite most of them being on GHRT and some exhibited intellectual functioning in the average range. Evidence of BOT-2-SF floor effects underscores the need to refine assessment procedures and enhance measurement precision for this population.

A Method for Measuring Shaft Diameter Based on Light Stripe Image Enhancement.

When the workpiece surface exhibits strong reflectivity, it becomes challenging to obtain accurate key measurements using non-contact, visual measurement techniques due to poor image quality. In this paper, we propose a high-precision measurement method shaft diameter based on an enhanced quality stripe image. By capturing two stripe images with different exposure times, we leverage their different characteristics. The results extracted from the low-exposure image are used to perform grayscale correction on the high-exposure image, improving the distribution of stripe grayscale and resulting in more accurate extraction results for the center points. The incorporation of different measurement positions and angles further enhanced measurement precision and robustness. Additionally, ellipse fitting is employed to derive shaft diameter. This method was applied to the profiles of different cross-sections and angles within the same shaft segment. To reduce the shape error of the shaft measurement, the average of these measurements was taken as the estimate of the average diameter for the shaft segment. In the experiments, the average shaft diameters determined by averaging elliptical estimations were compared with shaft diameters obtained using a coordinate measuring machine (CMM) the maximum error and the minimum error were respectively 18 μm and 7 μm; the average error was 11 μm; and the root mean squared error of the multiple measurement results was 10.98 μm. The measurement accuracy achieved is six times higher than that obtained from the unprocessed stripe images.

Enhanced measurement precision with continuous interrogation during dynamical decoupling

Dynamical decoupling (DD) is normally ineffective when applied to DC measurement. In its straightforward implementation, DD nulls out DC signal as well while suppressing noise. This work proposes a phase relay method that is capable of continuously interrogating the DC signal over many DD cycles. We illustrate its efficacy when applied to the measurement of a weak DC magnetic field with an atomic spinor Bose–Einstein condensate. Sensitivities approaching standard quantum limit or Heisenberg limit are potentially realizable for a coherent spin state or a squeezed spin state of 10000 atoms, respectively, while ambient laboratory level noise is suppressed by DD. Our work offers a practical approach to mitigate the limitations of DD to DC measurement and would find other applications for resorting coherence in quantum sensing and quantum information processing research.

Assessment of Lifecourse Social Exposome in Brain Bank Decedents

AbstractBackgroundThere is increasing evidence that the social exposome impacts the development of Alzheimer’s disease and related dementias (ADRD). The social exposome includes factors such as neighborhood disadvantage, and is thought to impact brain health across the lifecourse, particularly during sensitive life stages such as early childhood. Residential histories are required to assess dosage and timing of exposures, yet are rarely categorized and linked to brain bank cohorts. Our objective was to characterize the lifecourse neighborhood disadvantage across two Alzheimer’s Disease Research Center (ADRC) brain banks.MethodAfter abstracting publicly available residential data, we constructed residential histories using validated metrics of neighborhood disadvantage, nationwide Area Deprivation percentile rankings (ADI), constructed for each census timeframe from 1910‐present, to measure lifecourse social exposome time‐concordantly aligned to participant life‐year. ADIs were linked for all available years between birth and death, ranging from age 0 to 103. Greater ADI values denote living in higher neighborhood disadvantage. These ADIs were linked to the residential histories for each decedent and used to calculate two sensitive life stages: ages 0‐19 and 40‐60. A repeated measures one‐way ANOVA determined variance in ADI both within and between these sensitive life stages.ResultThis sample contained 1309 decedents from two brain. To date, 1230 decedents have been linked to at least one ADI timepoint, with an average of 81% (71‐88%) of all life‐course years accounted for via ADI linkage. The mean ADI for the 0‐19 period was 23.5 (SD = 22.3, 5.0‐36.9), while the 40‐60 period was 22.0 (21.6, 5.0‐34.0). A repeated measures one‐way ANOVA found a statistically significant difference in ADI between the two windows of time.ConclusionTissue banked samples are not typically characterized on social determinants of health. Here we show that determining lifecourse social exposomes are feasible using publicly available data. To our knowledge, this is the first time such characterization has been successfully performed. Efforts to link decedents to ADI timepoints are still ongoing, which will reduce missingness, enhance measurement precision, and allow for comparison between all life stages. This work provides a unique methodology for assessing the social exposome in relation to ADRD brain pathology.

DATA FUSION OF ULTRASONIC SENSORS FOR DISTANCE MEASUREMENT

Distance measurement plays a fundamental role in contemporary technology, exerting a significant influence on applications across a myriad of sectors, ranging from autonomous navigation and industrial automation to robotics. Ultrasonic sensors, celebrated for their simplicity, cost-efficiency, and adaptability, have grown into essential instruments for gauging distances. Nevertheless, individual ultrasonic sensors are not exempt from constraints, which encompass inaccuracies stemming from environmental conditions, sensor noise, and measurement errors. This article delves into the advanced practice of data fusion, a method that entails amalgamating data from multiple ultrasonic sensors, bolstered by intricate algorithms like artificial intelligence (AI) and statistical techniques. The fusion of ultrasonic sensor data surpasses mere amalgamation; it harnesses the potency of AI to refine data integration. Consequently, this doesn't only enhance measurement precision but also equips systems to function dependably in dynamic and demanding environments. The article explores the importance of ultrasonic sensors, the necessity for data fusion, procedures for data preprocessing, the extraction of relevant features, the application of fusion algorithms, and the handling of uncertainties. It investigates the utilization of ultrasonic sensor data fusion in diverse domains such as autonomous vehicles, robotics, industrial automation, healthcare, and environmental monitoring. Moreover, it confronts issues associated with data quality, environmental variations, privacy concerns, and ethical deliberations. The article concludes by shedding light on the encouraging avenues that lie ahead in the field, which include the development of advanced algorithms, the seamless integration of different sensor types, real-time data processing, and a strong emphasis on safety-critical applications. Data fusion from ultrasonic sensors signifies an evolving and transformative technology with profound consequences for various sectors. The responsible advancement and deployment of this technology are of paramount importance to ensure the realization of its full potential, while maintaining the principles of safety, ethics, and reliability in a continuously evolving technological landscape. Keywords: Complex measurement, Multi-sensor distance measurement, Ultrasonic sensors, Data fusion, Measurement accuracy.

Science Students’ Attitudes Towards the Use of Indigenous Language in Understanding Visual Representations

This study aimed to investigate the attitudes of science students toward the utilization of their indigenous language in comprehending visual representations. A mixed-methods approach was employed to delve into students' perspectives, preferences, and beliefs regarding the medium of instruction in science education, with a specific emphasis on the role played by indigenous languages in the interpretation of visual representations. The study utilized a sequential explanatory research design, initially collecting and analyzing quantitative data, followed by qualitative data to augment the comprehension of the quantitative findings. The findings indicated a marked preference among students for employing English as the medium of instruction in science education, driven by its perceived global significance and potential advantages in accessing scientific resources and opportunities. Furthermore, students who had not been exposed to science education in their indigenous language exhibited negative attitudes toward its utilization. They also repudiated the notion that acquiring science knowledge in their indigenous language would enhance their ability to interpret visual representations effectively. These findings bear implications for the indigenization of curricula and underscore the significance of taking into account students' language preferences and attitudes in the context of science education. Future research should delve further into language choices in various educational settings and refine research instruments to enhance measurement precision. Educators and policymakers would be well-advised to consider students' language preferences to create inclusive and culturally responsive learning environments. This approach provides support to students in enhancing their proficiency in the selected language of instruction.

Nonlinear Interferometry for Quantum-Enhanced Measurements of Multiphoton Absorption.

Multiphoton absorption is of vital importance in many spectroscopic, microscopic, or lithographic applications. However, given that it is an inherently weak process, the detection of multiphoton absorption signals typically requires large field intensities, hindering its applicability in many practical situations. In this Letter, we show that placing a multiphoton absorbent inside an imbalanced nonlinear interferometer can enhance the precision of multiphoton cross section estimation with respect to strategies based on photon-number measurements using coherent or even squeezed light directly transmitted through the medium. In particular, the power scaling of the sensitivity with photon flux can be increased by 1 order compared with transmission measurements of the sample with coherent light, such that the measurement precision at any given intensity can be greatly enhanced. Furthermore, we show that this enhanced measurement precision is robust against experimental imperfections leading to photon losses, which usually tend to degrade the detection sensitivity. We trace the origin of this enhancement to an optimal degree of squeezing which has to be generated in a nonlinear SU(1,1) interferometer.

Design and Optimization of Multi-Stage TMR Sensors for Power Equipment AC/DC Leakage Current Detection

Tunnel magnetoresistance (TMR) can measure weak magnetic fields and has significant advantages for use in alternating current/direct current (AC/DC ) leakage current sensors for power equipment; however, TMR current sensors are easily perturbed by external magnetic fields, and their measurement accuracy and measurement stability are limited in complex engineering application environments. To enhance the TMR sensor measurement performance, this paper proposes a new multi-stage TMR weak AC/DC sensor structure with high measurement sensitivity and anti-magnetic interference capability. The front-end magnetic measurement characteristics and interference immunity of the multi-stage TMR sensor are found to be closely related to the multi-stage ring size design via finite element simulation. The optimal size of the multipole magnetic ring is determined using an improved non-dominated ranking genetic algorithm (ACGWO-BP-NSGA-II) to derive the optimal sensor structure. Experimental results demonstrate that the newly designed multi-stage TMR current sensor has a measurement range of 60 mA, a fitting nonlinearity error of less than 1%, a measurement bandwidth of 0–80 kHz, a minimum AC measurement value of 85 μA and a minimum DC measurement value of 50 μA, as well as a strong external electromagnetic interference. The TMR sensor can effectively enhance measurement precision and stability in the presence of intense external electromagnetic interference.

Quantification of Chemical Composition Distribution of Polyolefin Materials for Improved Accuracy and Speed

Crystallization-based separation techniques are widely used for chemical composition distribution (CCD, also often referred as short chain branching distribution SCBD) measurement in the polyolefin industry, in which CCD is among the most critical structural parameters to define their properties and applications. The desire to improve the sample throughput rate by shortening the analysis time in the current CCD techniques would normally sacrifice measurement accuracy due to the cocrystallization phenomena, in which the polymer chains with similar molecular architectures will cocrystallize or coelute enigmatically in the CCD analysis. Herein, we reported the investigation by exploring various separation packing materials on the cocrystallization phenomena. In comparison with the commercially available Crystallization Elution Fractionation (CEF) technique, an improved technique for CCD measurement (iCCD) was developed using the columns packed with gold-coated nickel substrate or spherical gold particles with or without the dynamic cooling process. With iCCD, it was observed with equivalent cocrystallization degree to the industrial gold standard benchmark Wild-TREF method but with over 70+ times improved sample throughput rate (62 vs 4500 min). The experimental CCD chromatogram for a polyolefin blend similarly assembled to the mathematically constructed result further demonstrated the minimized cocrystallization and measurement accuracy in the iCCD method. In addition, the superior mechanical properties of gold-coated nickel particles enabled the long-term robustness and enhanced measurement precision of the iCCD technique during the repeated thermal treatment cycles and pressure variations.

Measuring engagement among older adults using a multidimensional approach to communication.

Characterizing older adult engagement is important to determine the effectiveness of interventions. Engagement refers to the occupying of oneself in external stimuli and is observable across multiple dimensions of behavior. Engagement of older adults is commonly investigated using a single behavioral dimension. There is a dearth of analytical methods that can simultaneously quantify both verbal and non-verbal forms of communication as proxies for engagement. In this article, we present a multidimensional technique to measure engagement of older adults using techniques appropriate for people with varying degrees of dementia. The new analytical approach measures facial movement, lexical use, and prosodic patterns of speech as indices of affective and behavioral outcomes of engagement. Contexts for engagement included a dyadic reminiscence therapy interview and a 12-week technology-driven group reminiscence therapy. Illustrative examples of the technique are described by two participants from two different groups in a naturalistic setting. Application of these analytical techniques can enhance measurement precision and further develop the science and evidence base, especially for, but not confined to, non-pharmacological interventions.