Current Measurement Techniques Research Articles

Mass scaling relations for dark halos from an analytic universal outer density profile

Context. The average matter density within the turnaround scale, which demarcates where galaxies shift from clustering around a structure to joining the expansion of the Universe, is an important cosmological probe. However, a measurement of the mass enclosed by the turnaround radius is difficult. Analyses of the turnaround scale in simulated galaxy clusters place the turnaround radius at about three times the virial radius in a ΛCDM universe and at a (present-day) density contrast with the background matter density of the Universe of δ ~ 11. Assessing the mass at such extended distances from a cluster’s center is a challenge for current mass measurement techniques. Consequently, there is a need to develop and validate new mass-scaling relations, to connect observable masses at cluster interiors with masses at greater distances. Aims. Our research aims to establish an analytical framework for the most probable mass profile of galaxy clusters, leading to novel mass scaling relations, allowing us to estimate masses at larger scales. We derive such analytical mass profiles and compare them with those from cosmological simulations. Methods. We used excursion set theory, which provides a statistical framework for the density and local environment of dark matter halos, and complement it with the spherical collapse model to follow the non-linear growth of these halos. Results. The profile we developed analytically showed good agreement (better than 30%, and dependent on halo mass) with the mass profiles of simulated galaxy clusters. Mass scaling relations were obtained from the analytical profile with offset better than 15% from the simulated ones. This level of precision highlights the potential of our model for probing structure formation dynamics at the outskirts of galaxy clusters.

Active elimination of DC bias current of a SiC based dual active bridge by controlling the dead time period

AbstractDual active bridge (DAB) is an isolated DC‐DC converter gaining wider attention in power electronics applications. The high frequency (HF) transformer is an integral part of the DAB which is prone to saturation. Silicon carbide (SiC) based DAB are generally preferred for highly efficient power conversions, calling for an extremely low DC resistance of the transformer. This aggravates the DC bias issue significantly. The DC bias current generally flows due to the mismatch in static and transient switching of active devices, leading to eventual saturation of the transformer. This paper proposes an active method to precisely control the dead time of the devices (8–100 ns) without sacrificing the voltage utilization of the converter. This method does not require a sophisticated DC offset current measurement technique. The field programmable gate array (FPGA) based control platform on the gate driver side executes the proposed algorithm. The proposed control is experimentally verified in a 5 kW SiC based converter. The control implementation methodology is discussed with the support of necessary experimental results.

Comparative Analysis of Total Pressure Measurement Techniques in Rotating Detonation Combustors

Abstract Current total pressure measurement techniques in RDCs are based on different assumptions and therefore show different applicability for specific RDC operating conditions, and few studies have directly compared these techniques. Therefore, this study comprehensively tested three total pressure measurement techniques: the direct Kiel probe method, the Mach-corrected CTAP method, and the equivalent available pressure (EAP) method under different RDC geometries and mass flow rates, and compared them with their corresponding uncertainties considered. The results show that for all tests in this study, the EAP method shows the largest uncertainty range up to 24%, which is mainly contributed by the load cell calibration process, while the direct Kiel probe method has the lowest uncertainty range, which is consistently below 7%. These uncertainties were incorporated into the comparison between the three techniques via Gaussian process regression, showing that the direct Kiel probe method and the Mach-corrected CTAP method can present EAP-like total pressure. In particular, the total pressure of the SWCC and L modes measured by the three techniques is very comparable. This work shows that the comparability of total pressure techniques depends on the specific RDC environment, and provides the possibility to evaluate the RDC performance with the simplest implementation.

Bicharacteristic probability of detection of crack under multi-factor influences using alternating current field measurement technique

Alternating Current Field Measurement (ACFM) technique has been widely used in various fields such as oil & gas, aerospace areas. However, during the detection process, the probability of detection (POD) is influenced by multi-factors such as lift-off height, scanning angle and detection speed. In this paper, a bicharacteristic probability of detection (BPOD) model is developed for quantifying the crack detection reliability using integrated Bx and Bz signals in the ACFM technique. A multidimensional BPOD model is established to study the influence of multiple factors on the detection probability of cracks using ACFM technique. A Bayesian network-based method is proposed to reverse the hierarchical impact weights of influence factors on the BPOD of the ACFM technique. The results show that the BPOD model considering both Bx and Bz response signals can evaluate smaller defects than the conventional POD model. The multiple influencing factors can substantially decrease the BPOD of cracks. The hierarchical impact weights on BPOD for cracks are ranked as follows: lift-off height, detection speed, personnel involved in the detection process and scanning angle. This approach can retrospectively find the potential contributors to the missed detections based on the BPOD.

MV-SSRP: Machine Vision Approach for Stress–Strain Measurement in Rice Plants

Rice plants’ ability to develop lodging resistance is essential for their proper growth and development, and understanding the stress–strain relationship is crucial for a comprehensive analysis of this resilience. Nevertheless, significant data variability, inefficiency, and substantial observational inaccuracies hinder current measurement and analysis techniques. Therefore, this study proposes a machine vision-based stress–strain measurement method for rice plants to address these limitations. The technique primarily involves the implementation of the proposed MV-SSRP rotating target detection network, which enhances the model’s ability to predict the strain of rice stalks accurately when subjected to bending forces through the integration of the spatial channel reorganization convolution (ScConv) and Squeeze-and-Excitation (SE) attention mechanism. A stress–strain dynamic relationship model was also developed by incorporating real-time stress data obtained from a mechanical testing device. The experimental findings demonstrated that MV-SSRP attained precision, recall, and mean average precision (mAP) rates of 93.4%, 92.6%, and 97.6%, respectively, in the context of target detection. These metrics represented improvements of 4.8%, 3.8%, and 5.1%, respectively, over the performance of the YOLOv8sOBB model. This investigation contributes a theoretical framework and technical underpinning for examining rice lodging resistance.

Lagrangian particle tracking in the atmospheric surface layer

Abstract Field measurements in the atmospheric surface layer (ASL) are key to understanding turbulent exchanges in the atmosphere, such as fluxes of mass, water vapor, and momentum. However, current field measurement techniques are limited to single-point time series or large-scale flow field scans. Extending image-based laboratory measurement techniques to field-relevant scales is a promising route to more detailed atmospheric flow measurements, but this requires significant increases in the attainable measurement volume while keeping the spatiotemporal resolution high. Here, we present an adaptable particle tracking system using helium-filled soap bubbles, mirrorless cameras, and high-power LEDs enabling volumetric ASL field measurements. We conduct analyses pertinent to image-based field measurement systems and develop general guidelines for their design. We validate the particle tracking system in a field experiment. Single-point Eulerian velocity statistics are presented and compared to data from concurrently operated sonic anemometers. Lagrangian displacement statistics are also presented with a comparison to Taylor’s theory of dispersion. The system improves the state-of-the-art in field measurements in the lower atmosphere and enables unprecedented insights into flow in the ASL.

D'or: deep orienter of protein-protein interaction networks.

Protein-protein interactions (PPIs) provide the skeleton for signal transduction in the cell. Current PPI measurement techniques do not provide information on their directionality which is critical for elucidating signaling pathways. To date, there are hundreds of thousands of known PPIs in public databases, yet only a small fraction of them have an assigned direction. This information gap calls for computational approaches for inferring the directionality of PPIs, aka network orientation. In this work, we propose a novel deep learning approach for PPI network orientation. Our method first generates a set of proximity scores between a protein interaction and sets of cause and effect proteins using a network propagation procedure. Each of these score sets is fed, one at a time, to a deep set encoder whose outputs are used as features for predicting the interaction's orientation. On a comprehensive dataset of oriented PPIs taken from five different sources, we achieve an area under the precision-recall curve of 0.89-0.92, outperforming previous methods. We further demonstrate the utility of the oriented network in prioritizing cancer driver genes and disease genes. D'or is implemented in Python and is publicly available at https://github.com/pirakd/DeepOrienter.

3D visual reconstruction of corrosion in underwater structure using alternating current field measurement technique

Corrosion is a common damage form in various underwater structures. However, the corrosions are usually covered by the coatings and attachments in the underwater environment. In this paper, the 3D visual reconstruction methods for evaluating the corrosion defect using the alternating current field measurement (ACFM) technique are presented. The FEM model is set up with corrosion and pitting defects to analyze the disturbed current field and the distorted magnetic field. A gradient imaging algorithm based on the Bz signal is proposed to reconstruct the surface morphology of the corrosion and the pitting defect. The inner contour of the corrosion defect is reconstructed using the Bx signal sensitive characteristics of probe lift-off. The calibration method is proposed to measure the depth of the pitting defect. The testing system is built, and the experiments are carried out to verify the 3D visual reconstruction methods. The maximum error of the surface area reconstruction is 8.13%. The maximum error of the corrosion inner reconstruction is 10%. The maximum error of the pitting depth is 3.25%.

Selective Detection of Dynamics-Complete Set of Correlations via Quantum Channels.

Correlations of fluctuations are essential to understanding many-body systems and key information for advancing quantum technologies. To fully describe the dynamics of a physical system, all time-ordered correlations (TOCs), i.e., the dynamics-complete set of correlations are needed. The current measurement techniques can only access a limited set of TOCs, and there has been no systematic and feasible solution for extracting the dynamic-complete set of correlations hitherto. Here we propose a platform-universal protocol to selectively detect arbitrary types of TOCs via quantum channels. In our method, the quantum channels are synthesized with various controls, and engineer the evolution of a sensor-target system along a specific path that corresponds to a desired correlation. Using nuclear magnetic resonance, we experimentally demonstrate this protocol by detecting a specific type of fourth-order TOC that has never been accessed previously. We also show that the knowledge of the TOCs can be used to significantly improve the precision of quantum optimal control. Our method provides a new toolbox for characterizing the quantum many-body states and quantum noise, and hence for advancing the fields of quantum sensing and quantum computing.

Dichotomous dynamics of magnetic monopole fluids

A recent advance in the study of emergent magnetic monopoles was the discovery that monopole motion is restricted to dynamical fractal trajectories [J. N. Hallén et al., Science 378, 1218 (2022)], thus explaining the characteristics of magnetic monopole noise spectra [R. Dusad et al., Nature 571, 234 (2019); A. M. Samarakoon et al., Proc. Natl. Acad. Sci. U.S.A. 119, e2117453119 (2022)]. Here, we apply this novel theory to explore the dynamics of field-driven monopole currents, finding them composed of two quite distinct transport processes: initially swift fractal rearrangements of local monopole configurations followed by conventional monopole diffusion. This theory also predicts a characteristic frequency dependence of the dissipative loss angle for AC field-driven currents. To explore these novel perspectives on monopole transport, we introduce simultaneous monopole current control and measurement techniques using SQUID-based monopole current sensors. For the canonical material Dy2Ti2O7, we measure [Formula: see text], the time dependence of magnetic flux threading the sample when a net monopole current [Formula: see text] is generated by applying an external magnetic field [Formula: see text] These experiments find a sharp dichotomy of monopole currents, separated by their distinct relaxation time constants before and after t ~[Formula: see text] from monopole current initiation. Application of sinusoidal magnetic fields [Formula: see text] generates oscillating monopole currents whose loss angle [Formula: see text] exhibits a characteristic transition at frequency [Formula: see text] over the same temperature range. Finally, the magnetic noise power is also dichotomic, diminishing sharply after t ~[Formula: see text]. This complex phenomenology represents an unprecedented form of dynamical heterogeneity generated by the interplay of fractionalization and local spin configurational symmetry.

Integrated monitoring method of flood free surface and surface velocity in a laboratory compound channel

River flooding can pose a significant threat to people's lives and properties on the floodplain. Due to the difficulty and potential danger of monitoring field river floods, laboratory experiments have become the main and key method for exploring flood propagation and evaluating potential flood risks. However, the complex three-dimensional flow state of floods in the compound channel makes current measurement techniques inadequate for meeting monitoring requirements. To this end, a new technique is developed in this study that can simultaneously monitor the flood free surface and the surface velocity in the laboratory compound channel. The developed measurement technique combines stereoscopy and the particle tracking velocimetry (PTV) method through the pixel coordinate fitting method, so that the coordinates of the tracer particles can be reconstructed in the three-dimensional state. This method can not only increase the basic data in the free surface construction but can also capture the complex three-dimensional flood flow behavior. The proposed technology was applied to measure the free surface of flood propagation in a laboratory compound channel. Water level, flow velocity, wave velocity, and wave height were simultaneously measured. The measurement accuracy was verified using wave probes, spatial planes, and fringe projection techniques. The results indicate that the water level measurement error is approximately 1.6 mm, and the flow velocity measurement error is around 3 %. The developed measurement system is simpler than previous methods based on light reflection or absorption. Most importantly, it can simultaneously measure both the flood free surface and surface velocity by only sowing tracer particles on the water surface. The current measurement technology offers a new tool for studying flood propagation in a laboratory compound channel.

A novel transition frequency for identification and evaluation of subsurface cracks based on alternating current field measurement technique

Subsurface cracks are more challenging to detect and evaluate compared to surface cracks. This paper introduces a novel transition frequency to identify and evaluate subsurface cracks using alternating current field measurement (ACFM) technique. A theoretical model is proposed to explore current disturbance mechanism for subsurface cracks under different frequencies. A 3D simulation model is established to validate the proposed theoretical model and investigate the effects of crack length, shape and specimen thickness on transition frequency. The ACFM testing system is used to detect subsurface cracks with different burial depths and explore the effect of lift-off on transition frequency. The results demonstrate that, with increasing frequency, the shape of Bx signal for subsurface cracks transitions from a trough to a peak, which can be utilized for identifying subsurface cracks. The burial depth can be accurately assessed by transition frequencies. The transition frequency is hardly affected by crack length, shape and lift-off.

Monitoring the venous circulation: novel techniques and applications.

Venous pressure is an often-unrecognized cause of patient morbidity. However, bedside assessment of PV is challenging. We review the clinical significance of venous pressure measurement, existing techniques, and introduce the Venous Excess Ultrasound (VExUS) Score as a novel approach using doppler ultrasound to assess venous pressure. Studies show clear associations between elevated venous pressure and adverse outcomes in critically ill patients. Current venous pressure measurement techniques include physical examination, right heart catheterization (RHC), two-dimensional ultrasound, and a variety of labor-intensive research-focused physiological maneuvers. Each of these techniques have specific shortcomings, limiting their clinical utility. To address these gaps, Beaubien-Souligny et al. introduced the VExUS Score, a novel doppler ultrasound-based method that integrates IVC diameter with doppler measurements of the hepatic, portal, and renal veins to generate a venous congestion assesment. Studies show strong correlations between VExUS score and RHC measurements, and well as an association between VExUS score and improvement in cardiorenal acute kidney injury, diuretic response, and fluid status shifts. However, studies in noncardiac populations have been small, heterogenous, and inconclusive. Early studies evaluating the use of doppler ultrasound to assess venous congestion show promise, but further research is needed in diverse patient populations and clinical settings.

Advances in exercise-induced vascular adaptation: mechanisms, models, and methods.

Insufficient physical activity poses a significant risk factor for cardiovascular diseases. Exercise plays a crucial role in influencing the vascular system and is essential for maintaining vascular health. Hemodynamic stimuli generated by exercise, such as shear stress and circumferential stress, directly impact vascular structure and function, resulting in adaptive changes. In clinical settings, incorporating appropriate exercise interventions has become a powerful supplementary approach for treating and rehabilitating various cardiovascular conditions. However, existing models for studying exercise-induced vascular adaptation primarily rely on in vivo animal and in vitro cellular models, each with its inherent limitations. In contrast, human research faces challenges in conducting mechanistic analyses due to ethics issues. Therefore, it is imperative to develop highly biomimetic in vitro/ex vivo vascular models that can replicate exercise stimuli in human systems. Utilizing various vascular assessment techniques is also crucial to comprehensively evaluate the effects of exercise on the vasculature and uncover the molecular mechanisms that promote vascular health. This article reviews the hemodynamic mechanisms that underlie exercise-induced vascular adaptation. It explores the advancements in current vascular models and measurement techniques, while addressing their future development and challenges. The overarching goal is to unravel the molecular mechanisms that drive the positive effects of exercise on the cardiovascular system. By providing a scientific rationale and offering novel perspectives, the aim is to contribute to the formulation of precise cardiovascular rehabilitation exercise prescriptions.

Absorption and scattering limits of silicon nitride integrated photonics in the visible spectrum.

Visible-light photonic integrated circuits (PICs) promise scalability for technologies such as quantum information, biosensing, and scanning displays, yet extending large-scale silicon photonics to shorter wavelengths has been challenging due to the higher losses. Silicon nitride (SiN) has stood out as the leading platform for visible photonics, but the propagation losses strongly depend on the film's deposition and fabrication processes. Current loss measurement techniques cannot accurately distinguish between absorption and surface scattering, making it difficult to identify the dominant loss source and reach the platform's fundamental limit. Here we demonstrate an ultra-low loss, high-confinement SiN platform that approaches the limits of absorption and scattering across the visible spectrum. Leveraging the sensitivity of microresonators to loss, we probe and discriminate each loss contribution with unparalleled sensitivity, and derive their fundamental limits and scaling laws as a function of wavelength, film properties and waveguide parameters. Through the design of the waveguide cross-section, we show how to approach the absorption limit of the platform, and demonstrate the lowest propagation losses in high-confinement SiN to date across the visible spectrum. We envision that our techniques for loss characterization and minimization will contribute to the development of large-scale, dense PICs that redefine the loss limits of integrated platforms across the electromagnetic spectrum.

TEST PLATFORM PARADIGM FOR UNDERWATER DYNAMICS MEASUREMENTS

This paper presents a test platform paradigm for underwater dynamics measurement. The platform aims to ad- dress the limitations of current measurement techniques and provide a comprehensive understanding of underwater dynamics. The proposed platform incorporates advanced control systems and compensation techniques to improve the accuracy and reliability of measurements. The effectiveness of the platform is demonstrated through experimental results, showing improved performance compared to existing methods. The test platform paradigm offers a promising approach for underwater dynamics measurement in various applications.

Investigation of Interfacial Behavior of Ni-Rich NCM Cathode Particles in Sulfide-Based Solid-State Electrolyte

All-solid-state batteries (ASSBs) are currently investigated as a future battery technology with conventional layered cathode materials because they can offer benefits in the gravimetric and volumetric energy densities compared to flammable liquid electrolyte lithium-ion batteries with graphite intercalation anode. The solid electrolyte is believed to suppress dendritic growth and low Coulombic efficiency on the lithium metal anode side, which are the key issues for the use of a lithium metal electrode in conventional batteries with liquid electrolyte. Moreover, layered transition metal oxides such as LiNixCoyMnzO2 (NCM, 0 < x, y, z < 1) are one of the most promising positive electrode active material candidates being developed to increase the energy density. In particular, recent studies have shown a tendency to decrease the cobalt content and increase the nickel content to increase energy density and price competitiveness, so high-nickel NCM can be the optimal material suitable for this purpose. However, the remaining interfacial challenges of the cathode / solid electrolyte interface still need to be solved.Herein, we investigated the kinetics such as charge transfer resistance at the interface between high nickel (Ni0.94) NCM particles and argyrodite (Li6PS5Cl) solid electrolytes using the microcavity electrode with the negative and positive pulsed current measurement technique and compared with liquid electrolytes using the same manner measurement technique. The cavity-electrode system is adopted to analyze the electrochemical properties of active particles and electrolytes confined in the cavity to exclude the effects of surrounding interfaces, barriers, and side reactions caused by battery components around the electrodes and the impact of loading and current collectors of the composite electrode. Therefore, understanding the electrode-electrolyte interface between cathode active particles and solid electrolytes is crucial for theoretical studies on the interfacial phenomenon in solid electrolyte batteries.

The use of finite element models for backface deformation and body armour design: a systematic review

While injuries sustained from body armour backface deformation (BFD) have not been well-documented in military injury trauma registries, data from US law enforcement officers, animal tests and currently available data pertaining to military combatants has shown that BFD can not only cause minor injuries, but also result in serious trauma. However, the nature and severity of injuries sustained depends on a multitude of factors including the projectile type, the impact location and velocity, and the specific type of body armour worn. The difficulties involved in current measurement techniques for ballistic testing has led researchers to seek alternative techniques to evaluate the level of protection from body armour, such as the finite element (FE) method. In the current study, a systematic review of the open literature was undertaken using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology. The aim was to summarise the literature pertaining to the development and application of FE models to investigate body armour BFD and behind armour blunt trauma (BABT), and included FE models representing the projectile, clay-based mediums, ballistic gelatine and the human torso. Using the keywords ‘behind armour*’, ‘ballistic blunt trauma’, ‘BABT’, ‘backface signature’, ‘backface deformation’, ‘BFS’, ‘BFD’, ‘wound ballistic’, ‘ballistic impact testing’, ‘body armour’, ‘bullet proof vest’, ‘ballistic vest’, ‘Finite Element*’ and ‘FE’, an electronic database search of EBSCOhost, Google Scholar, ProQuest, Scopus, Standards, Web of Science and PubMed was conducted, and included peer-reviewed journal articles, review papers, research reports, conference papers, and MSc or PhD theses. While this research demonstrates the potential of FE analysis for recreating realistic blunt impact scenarios and enhancing the current understanding of BABT mechanisms, a common limitation in most studies is the lack of validation. Thus, in order to address this issue, it is proposed that injury predictions from FE models be correlated with trauma data from soldiers who have sustained BABT. Consequently, pressure and energy distributions within the organs can be used to interpret the effects of non-penetrating ballistic impacts on the human torso. Bridging the gap between simulation and real-world data is essential in order to validate FE models and enhance their utility in optimising body armour design and employing injury mitigation strategies.

Nanoscale Surface Photovoltage Spectroscopy

AbstractUnderstanding electron and ion dynamics is an important task for improving modern energy materials, such as photovoltaic perovskites. These materials usually have delicate nano‐ and microstructures that influence the device parameters. To resolve detailed structure–function relationships on the relevant micro‐ and nanometer length scales, the current macroscopic and microscopic measurement techniques are often not sufficient. Here, nanoscale surface photovoltage spectroscopy (nano‐SPV) and nanoscale ideality factor mapping (nano‐IFM) via time‐resolved Kelvin probe force microscopy are introduced. These methods can map nanoscale variations in charge carrier recombination, ion migration, and defects. To show the potential of nano‐SPV and nano‐IFM, these methods are applied to perovskite samples with different morphologies. The results clearly show an improved uniformity of the SPV and SPV decay distribution within the perovskite films upon passivation and increasing the grain size. Nevertheless, nano‐SPV and nano‐IFM can still detect local variations in the defect density on these optimized samples, guiding the way for further optimization.

Hydrogel-based molecular tension fluorescence microscopy for investigating receptor-mediated rigidity sensing.

Extracellular matrix (ECM) rigidity serves as a crucial mechanical cue impacting diverse biological processes. However, understanding the molecular mechanisms of rigidity sensing has been limited by the spatial resolution and force sensitivity of current cellular force measurement techniques. Here we developed a method to functionalize DNA tension probes on soft hydrogel surfaces in a controllable and reliable manner, enabling molecular tension fluorescence microscopy for rigidity sensing studies. Our findings showed that fibroblasts respond to substrate rigidity by recruiting more force-bearing integrins and modulating integrin sampling frequency of the ECM, rather than simply overloading the existing integrin-ligand bonds, to promote focal adhesion maturation. We also demonstrated that ECM rigidity positively regulates the pN force of T cell receptor-ligand bond and T cell receptor mechanical sampling frequency, promoting T cell activation. Thus, hydrogel-based molecular tension fluorescence microscopy implemented on a standard confocal microscope provides a simple and effective means to explore detailed molecular force information for rigidity-dependent biological processes.