Time Signal Research Articles

Real-time in-situ ultrasound monitoring of soft hydrogel 3D printing with subwavelength resolution

3D bioprinting has excellent potential in tissue engineering, regenerative medicine, and drug delivery systems due to the ability to fabricate intricate structures that are challenging to make with conventional manufacturing methods. However, the complexity of parametric combinations and lack of product quality control have restricted soft hydrogel bioprinting from practical applications. Here we show an in-situ ultrasound monitoring system that reveals the alginate-gelatin hydrogel’s additive manufacturing process. We use this technique to understand the parameters that influenced transient printing behaviors and material properties in approximately real-time. This unique monitoring process can facilitate the detection of minor errors/flaws during the printing. By analyzing the ultrasonic reflected signals in both time and frequency domains, transient printing information can be obtained from 3D printed soft hydrogels during the processes with a depth subwavelength resolution approaching 0.78λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}. This in-situ technique monitors the printing behaviors regarding the constructed film, interlayer bonding, transient effective elastic constant, layer-wise surface roughness (elastic or plastic), nozzle indentation/scratching, and gravitational spreading. The simulation-verified experimental methods monitored fully infilled printing and gridded pattern printing conditions. Furthermore, the proposed ultrasound system also experimentally monitored the post-crosslinking process of alginate-gelatin hydrogel in CaCl2 solution. The results can optimize crosslinking time by balancing the hydrogel’s stiffness enhancement and geometrical distortion.

MKIDGen3: Energy-resolving, single-photon-counting microwave kinetic inductance detector readout on a radio frequency system-on-chip

Microwave Kinetic Inductance Detectors (MKIDs) are superconducting detectors capable of single-photon counting with energy resolution across the ultraviolet, optical, and infrared (UVOIR) spectrum with microsecond timing precision. MKIDs are also multiplexable, providing a feasible way to create large-format, cryogenic arrays for sensitive imaging applications in biology, astronomy, and quantum information. Building large, cryogenic MKID arrays requires processing highly multiplexed, wideband readout signals in real time; this task has previously required large, heavy, and power-intensive custom electronics. In this work, we present the third-generation UVOIR MKID readout system (Gen3), which is capable of reading out twice as many detectors with an order of magnitude lower power, weight, volume, and cost-per-pixel as compared to the previous system. Gen3 leverages the Xilinx RFSoC4x2 platform to read out 2048, 1 MHz MKID channels per board. The system takes a modern approach to FPGA design using Vitis High-Level Synthesis to specify signal processing blocks in C/C++, Vivado ML intelligent design runs to inform implementation strategy and close timing, and Python productivity for Zynq to simplify interacting with and programming the FPGA using Python. This design suite and tool flow allows general users to contribute to and maintain the design and positions Gen3 to rapidly migrate to future platforms as they become available. In this work, we describe the system requirements, design, and implementation. We also provide performance characterization details and show that the system achieves detector-limited resolving power in the case of few readout tones and minimal degradation with all 2048 tones. Planned upgrades and future work are also discussed. The Gen3 MKID readout system is fully open-source and is expected to facilitate future array scaling to megapixel-sized formats and increase the feasibility of deploying UVOIR MKIDs in space.

Research and Design of BPM Shortwave Time Signal Modulation Technology Based on Chirp

The shortwave time service system is a vital land-based wireless time service solution, serving as a supplement and backup to the global navigation satellite system. It ensures that time users can access reliable timings, especially in extreme situations. However, the current BPM shortwave time service signal in China faces issues such as insufficient anti-interference reception capabilities and poor timing accuracy. This paper capitalizes on the advantages of Chirp signals and explores a new modulation technology for BPM shortwave time signals that is compatible with the existing modulation system. A Dual Chirp Time-Division Combined Modulation (DCTDCM) scheme is proposed for broadcasting two time signals: Coordinated Universal Time (UTC) and Universal Time 1 (UT1). Furthermore, an in-depth study of the receiving method for this scheme is conducted, with detailed design of its parameters. The designed DCTDCM signals offer a spread spectrum gain of 24 dB and a multipath resolution capability of at least 125 μs, significantly enhancing the anti-interference reception and anti-multipath attenuation capabilities of shortwave time signals. As a result, the availability and timing accuracy of shortwave time signals are substantially improved. Finally, extensive comparative experiments on reception performance validate the effectiveness of this approach.

Galectin-3 zebrafish model: identification and pharmacological modulation of arrhythmogenic cardiomyopathy-related phenotypes

Abstract Background Arrhythmogenic Cardiomyopathy (ACM) is rare hereditary cardiac condition characterized by the substitution of ventricular myocardium with fibro-fatty tissue leading to high risk of life-threatening arrhythmias and sudden cardiac death, particularly among young individuals and athletes. Based on genotype-phenotype correlation, the spectrum of the ACM phenotype was shown to be broader than previously believed. Approximately 40% of ACM patients carry one or more putative pathogenic variants in genes encoding desmosomal proteins. Recently LGALS3 gene involvement in ACM early pathogenesis has been advocated. Aim To achieve a comprehensive understanding of LGALS3 role in the pathogenesis of AC. Methods This stable mutant line was generated by CRISPR/Cas9 strategy and then deeply characterized. Phenotyping included heart activity characterization using a recently published software specific for zebrafish, the pyHeart4Fish. Gene expression analysis was carried out by using RNAseq, Real Time PCR and signaling pathway reporter zebrafish lines. Immunofluorescence analysis were performed using and antibody against L-plastin, a leukocyte marker for the detection of inflammatory cells and Acridine Orange/Ethidium Bromide staining to check the possible presence of apoptotic and necrotic events. Results Morphological investigation revealed notable structural abnormalities such as pericardial effusion and/or hemopericardium. The heart activity analysis detected a diminished ventricle contractility and ejection fraction, with bradycardia and occurrence of arrhythmia events. Rna analysis highlighted the dysregulation of Wnt/β-catenin signaling pathway. Moreover, the L-plastin inflammatory marker revealed a significant infiltration of inflammatory cells in the heart as well as an elevated number of apoptotic and necrotic cells (figure 1). The pharmacological treatment, partially rescued a subset of AC-related cardiac phenotypes observed, including heart contractility, bradycardia and arrhythmia. Conclusion Our findings strongly validate our lgals3a zebrafish mutant as an effective model to elucidate its role in ACM related phenotype. This model accurately replicates the cardiac abnormalities and dysregulation in cell signaling that are characteristic of ACM. Further, observed cell death and inflammation and the partial recovery of cardiac phenotypes through pharmacological intervention, underscores the potential of targeting the Wnt/β-catenin signaling pathway as future perspective for ACM.Figure 1

Highly accurate absolute optical transfer delay measurement over a long distance assisted by the pulse time signal

In this paper, an absolute optical transfer delay measurement method based on pulse time signal, pseudo-random code phase, and microwave phase is proposed. By employing two-stage integer ambiguity resolution, not only can a measurement range of several hundred kilometers be achieved, but sub-picosecond level measurement accuracy can also be attained. A test system was built in the laboratory and experimentally verified on a fiber optic link. The experimental results verify an accuracy of ±0.1 ps in measuring an ultrahigh-accuracy optical delay line. In addition, long fiber is also tested, which proves that a measurement range of at least 100 km can be achieved. The refresh rate of the measurement results can reach 100 ms each time.

Methods in fluctuation (noise) spectroscopy and continuous analysis for high-throughput measurements

Abstract Fluctuation (noise) spectroscopy is widely used to investigate the low-frequency dynamics of charge carriers in condensed-matter systems, aiming to (i) improve the performance of micro- and nanoscale electronic devices and sensors, and (ii) use ‘noise as a signal’ in order to fundamentally investigate the microscopic motion and transitions of charge carriers coupled to the low-lying excitations in solids. Here, we focus on measurements of the ubiquitous 1 / f -type fluctuations, often composed by a superposition of (independent or correlated) two-level systems each giving rise to a Lorentzian spectrum, denoted random telegraph noise in the time domain. We briefly review the basic concepts of noise and fluctuations and give a comprehensive overview of state-of-the-art measuring techniques, using both commercially available signal analyzers and custom software in order to perform the spectral analysis of the recorded time signals, and critically evaluate their advantages and drawbacks. We describe how to use fast data acquisition devices in a cross-correlation setup providing additional quantitative information on the magnitude of uncorrelated instrument noise, and demonstrate the mathematical intricacies of extracting the noise spectra. We introduce a new method for high-throughput measurements by automated spectral analysis based on the concept of Continuous Analysis. We demonstrate the potential of this technique, working towards a FAIR data workflow, by measurements of magnetic flux noise within the hysteresis loop of ferromagnetic nanostructures.

Time–frequency ridge characterisation of sleep stage transitions: Towards improving electroencephalogram annotations using an advanced visualisation technique

Manual sleep stage scoring of polysomnography recordings is an expensive and time-consuming process, further complicated by inconsistent sleep stage agreement among sleep experts (clinicians and sleep technologists). Hence, development of automated sleep scoring algorithms are an emerging topic of interest. Automation typically mimics the clinical decision path by implementing a series of predefined rules, such as the American Academy of Sleep Medicine’s (AASM) scoring manual. Recently, data driven methods have emerged using machine or deep learning. Both manual and automated methods of scoring have known limitations; primarily, unacceptable variation in agreement between different scorers and algorithms. Within the literature, electroencephalogram (EEG) frequency is an important feature considered by both sleep experts and automated approaches for classifying sleep stages.This study presents a novel approach to sleep stage analysis, by developing a methodology to precisely determine the temporal location of sleep stage transitions. The current gold standard fails to identify such transitional changes, which leads to poor inter-scorer reliability. Therefore, development and implementation of such methodologies is a crucial, but overlooked, step in improving the consistency of scoring within sleep studies. In this work, EEG time–frequency ridge analysis was used to characterise the dominant frequency component of EEG signals in time, at the point of sleep stage transition. An in-depth analysis of N3 → N2 and N2 → N3 transitions in the 2018 PhysioNet challenge “You Snooze, You Win” and the Wisconsin Sleep Cohort (WSC) datasets (n = 994, n = 742; approximately 13,888 h of sleep data) showed consistent time–frequency patterns at the point of transition, from one sleep stage to another. This methodology allows simple and ‘interpretable’ features to be generated in future work, to precisely identify the temporal location of sleep stage transitions with the aim of improving inter-scorer reliability.

Multiple-Access Time and Frequency Transfer over Fiber and Free-Space Link Based on Optical Frequency Comb

We have demonstrated a multiple-access transfer of time and frequency signal over a fiber and free-space link based on an optical frequency comb (OFC). With this transfer technique, two time–frequency signals were disseminated separately from a master site to two slave sites over a 3.9 km fiber and 100 m free-space link for 10,000 s. The timing fluctuations and instabilities of the time and frequency transfer were measured, estimated, and discussed. The experimental results show that the total root-mean-square (RMS) timing fluctuation of the transfer from site A to B is about 119 ps, with a fractional frequency instability on the order of 3.3 × 10−11 at 1 s and 2.8 × 10−14 at 2000 s. The RMS timing fluctuation of the transfer from site A to C is about 59.5 ps, with a fractional frequency instability on the order of 3.0 × 10−11 at 1 s and 2.6 × 10−14 at 2000 s. These results indicate that the multiple-access transfer technique proposed in this paper can provide important support for the application of a large-scale time–frequency synchronization network.

Continuous Signal Convolution Using FFT with Overlap for Transportation Robot Coordinate Determination

The paper discusses the development of a continuous discrete signal convolution algorithm using fast Fourier transform (FFT) with overlap for more accurate determination of the coordinates of a transportation robot. Two methods for determining the coordinates of a transportation robot in two-dimensional space are presented, where the convolution operation is used and where this algorithm can be applied. The algorithm is based on a method that allows the FFT to be performed on multiple computational units in parallel, such as on a TMS320F28377D digital signal processor, where three computational units are available that operate independently in parallel. The use of a FFT with overlap allows signal processing without data loss, which is critical for continuous signal processing.The study of the influence of the FFT window offset value on the frequency of obtaining the spectrum of the signal has been carried out, and as it was found that reducing the FFT window offset leads to an increase in the frequency of obtaining the spectrum of the signal, which, in turn, allows you to more accurately restore the amplitude of the original signal, that is, there is less loss of spectrum data. As results, the paper provides illustrations of the study in the form of three-dimensional graphs, where the spectra of the signal in time during the FFT with overlap, where as the initial signal is used a sinusoidal signal, which over time increases its frequency. Comparison of the results of the algorithm without overlap and with overlap at different offset values showed that the method with overlap provides significantly more accurate and frequent acquisition of spectrum data, avoiding data loss.The presented results are useful in robotics when it is required to accurately determine the coordinates of a transportation robot.

Concept study of a storage ring-based gravitational wave observatory: Gravitational wave strain and synchrotron radiation noise

This work for the first time addresses the feasibility of measuring millihertz gravitational waves (mHz GWs) with a storage ring-based detector. While this overall challenge consists of several partial problems, here we focus solely on quantifying design limitations imposed by the kinetic energy and radiated power of circulating ions at relativistic velocities. We propose an experiment based on the measurement of the time-of-flight signal of an ion chain. One of the dominant noise sources inherent to the measurement principle for such a GW detector is the shot noise of the emitted synchrotron radiation. We compute the noise amplitude of arrival time signals obtained by analytical estimates and simulations of ions with different masses and velocities circulating in a storage ring with the circumference of the Large Hadron Collider. Thereby, we show that our experiment design could reduce the noise amplitude due to the synchrotron radiation in the frequency range 10−4–10−2 Hz to one or two orders of magnitude below the expected GW signals from of astrophysical sources, such as supermassive binary black holes or extreme mass-ratio inspirals. Other key requirements for building a working storage ring-based GW detector include the generation and acceleration of heavy ion chains with the required energy resolution, their injection and continued storage, as well as the detection method to be used for the determination of the particle arrival time. However, these are not the focus of the work presented here, in which we instead concentrate on the definition of a working principle in terms of ion type, kinetic energy, and ring design, which will later serve as a starting point when addressing a more complete experimental setup. Published by the American Physical Society 2024

Intensity- and time-based strategies for micro/nano-sizing via single-particle ICP-mass spectrometry: A comparative assessment using Au and SiO2 as model particles

BackgroundSingle-particle ICP-mass spectrometry (SP-ICP-MS) is a powerful method for micro/nano-particle (MNP) sizing. Despite the outstanding evolution of the technique in the last decade, most studies still rely on traditional approaches based on (1) the use of integrated intensity as the analytical signal and (2) the calculation of the transport efficiency (TE). However, the increasing availability of MNP standards and advancements in hardware and software have unveiled new venues for MNP sizing, including TE-independent and time-based approaches. This work systematically examines these different methodologies to identify and summarize their strengths and weaknesses, thus helping to determine their preferred application areas. ResultsDifferent SP-ICP-MS methods for MNP sizing were assessed using AuNPs (20–70 nm) and SiO2MNPs (100–1000 nm). Among TE-dependent approaches, the particle frequency method was characterized by larger uncertainties than the particle size method. The results of the latter were dependent on the appropriate selection of the reference MNP, making the use of multiple reference MNPs recommended. TE-independent methods were based on external (linear and polynomial) calibrations and a relative approach. These methods exhibited the lowest uncertainties of all the strategies evaluated. External calibrations benefited from simpler calculations, but their application could be hindered by a lack of reference MNPs within the desired size range or by the need for interpolations outside the calibration range. Finally, transit time signals are directly proportional to the MNP size rather than its mass. The time-based method demonstrated adequate performance for sizing AuNPs but failed when sizing the largest SiO2MNPs (1000 nm). Significance and noveltyThis work provides further insights into the application of different SP-ICP-MS methodologies for MNP sizing. Both TE-independent approaches and the monitoring of the transit time as the analytical signal are underused strategies; in this context, a Python script was developed for accurate transit time measurement. After 20 years of development, a quantitative comparison of the different methodologies, including the most novel approaches, is deemed necessary for further growth on solid theoretical ground.

Prediction of composite pressure vessels’ burst strength through machine learning

In Hydrogen Fuel Cell Electric Vehicles, hydrogen is stored as compressed gas in tanks made from carbon fiber composite. Tanks are designed to withstand 2.25 times the nominal working pressure. If low variability in tank strength can be demonstrated, this margin of safety could be reduced. This requires accurate prediction of the strength of the vessel and quantification of its uncertainty. In this work, several composite pressure vessels are manufactured using filament winding, and the parameters that control the winding and curing recorded as time signals. Process parameters include fiber tension, winding speed, liner pressure, fiber volume fraction, winding time and curing pressure. The vessels are tested for burst pressure. Several configurations are defined, where each manufacturing parameter is changed. The recorded manufacturing data are fed to machine learning(ML) algorithms and trained to predict the vessel’s burst pressure. These ML algorithms include neural networks, Gaussian process regression GPR, Kernel Principal Component Analysis-Lasso (kPCA-Lasso), and an Ensemble regressor. The KPCA-Lasso and GPR models show good correlation. The Ensemble regressor yields better results by combining the KPCA-Lasso and GPR models. The study demonstrates the potential of ML algorithms in predicting the burst pressure of carbon fiber vessels from the monitored manufacturing data.

An auralisation approach for tyre/road noise

Tyre/road noise is one of the main sources of traffic noise. Over the years, different approaches have been made to study the influence of road and tyre design on the noise generation and to reduce the negative impact of rolling noise on health and wellbeing. The study of human perception of tyre/road noise requires time signals of rolling noise for listening tests. Recorded signals could be used for this purpose, however, this only allows to investigate existing tyres and roads. Alternatively, simulated signals could be used. This paper presents a methodology to rolling noise signals based on physical modelling of the tyre/road contact. The Chalmers tyre/road interaction model has been extended to allow for calculating sufficiently long time signals in the form of CPX signals and/or pass-by signals. The approach is demonstrated by considering a surface with a contraction joint. The results indicate that the model might be suitable for listening tests or psychoacoustic evaluation.

Characterization of the scattered pressure from a cylindrical shell close to a free surface and understanding of the depth-dependent phenomenon

The characterization of the scattered pressure field of a submerged cylindrical target is of interest for underwater acoustics applications. The aim of this work is to study the vibroacoustic behavior of an immersed cylindrical shell excited by a plane wave, particularly in close proximity to a free surface. To achieve this goad, finite element simulation and experimental investigation are carried out on a mock-up. The effect of the free surface is highlighted by comparing results to those obtained in a free field situation, in both time and frequency domains. Additional echoes are observed on the time signals due to the presence of the free surface. In fact, after being scattered by the target, these echoes reflect on the surface, implying a time shift between echoes directly from the target and those that have travelled a longer path. The spectrum is also impacted as the form function shows additional oscillations. These observations are depth-dependent. To determine wave trajectories, a study based on flight time and ray theory is conducted.

The use of gold and magnetite-gold composite nanoparticles for the enhanced detection of Salmonella LT2 cells under photoacoustic flow cytometry

Photoacoustic flow cytometry (PAFC) is an emerging technology that has generated significant interest in several research fields, particularly in bacteremia. The application of functionalised nanoparticles like gold and iron oxide-gold complex (Fe3O4-Au) has been realised to enhance the photoacoustic (PA) detection of bacteria cells under PAFC systems. Inclusively, the bacteria cell concentrations are statistically quantified through the number of time-signal detection counts. This study uses a similar technique by using gold (Au) and magnetite-gold complex (Fe3O4-Au) nanoparticles in the PAFC system to improve the detection of Salmonella LT2 (SLT2) cells under 532 nm laser irradiation, resulting in over a 200 % increase. However, this study’s contribution comes from the post-processing and analysis of PA time signals after exposing various concentrations of SLT2 cells. Upon fast Fourier transform (FFT) analysis of time signals, a distinct peak frequency at 2.75 MHz was significantly attributed to SLT2 as its likely acoustic frequency fingerprint, even at its lowest concentrations (10 CFU/ml). Furthermore, an electromagnetic wave simulation (optical scattering and heat transfer in fluids) was employed to distinguish the PA and Photothermal contributions of the nanoparticles in the system. The resulting data consolidates the continuous wave transform (CWT) of the time signal, where 22.5 – 30 µs was strongly affiliated with PA, and 32–40 µs was that of the photo-thermal-acoustic effect—indicating that both signals can be used to detect and potentially confirm the eradication of SLT2 cells. Overall, magnetised Fe3O4-Au nanoparticles yielded more efficiency through its reproducible PA time signals with 0.84 standard deviations, and its 2.75 MHz frequency peak area matches most accurately with the SLT2 cell concentration by 97.3 %.

Experimental study of type-I crack propagation in rock monitored by fiber Bragg grating

The occurrence of rock mass engineering disasters can be reduced significantly by obtaining the key information in the process of rock internal fracture accumulation and evolution through advanced monitoring means and taking certain preventive measures. Through fiber Bragg grating monitoring tests of the type-I crack propagation in rock, the spectral characteristics of the fiber Bragg grating in the process of rock failure were analyzed, the bandwidth expansion was extracted to characterize the local tensile strain during the crack propagation process, and the damage variable based on the bandwidth expansion was calculated to describe the type-I crack propagation process. The research results showed the following: (1) The fiber Bragg grating generated a non-uniform local tensile strain during type-I crack propagation. The bandwidth expansion of the wave spectrum was positively correlated with the local tensile strain. The change in the characteristics of the wave spectrum could provide the local real strain in the process of crack propagation. (2) During the steady propagation of the type-I crack, the bandwidth increased obviously, while the number of acoustic emission events was relatively small, and most of them were in the process zone. The gentle increase in the bandwidth corresponded to the unstable growth stage of the type-I crack, which could be used as a precursor of rock sample instability. During loading, the maximum tensile strain of the type-I crack was 6 %, while the maximum shear strain reached 1.8 %, primarily attributed to tensile failure. The average value of fracture toughness KIC, based on the equivalent linear elastic fracture mechanics model, was determined to be 1.21 MPa·m1/2, and the average value of fracture energy Gf was calculated as 57.7 N/m. The variation of peak reflectivity in fiber Bragg grating was associated with the closure of pre-existing defects and the propagation of microcracks in rocks, resulting in unstable shear strain at crack extension sites. (3) The damage variable D defined by the bandwidth broadening began to become concentrated and accumulated in the crack steady growth stage, and it increased slowly in the crack intensification and evolution stage. The grating was sensitive to changes when it was pasted to the surface at 90°, but it could easily fracture or become unable to capture spectral signals in time. Based on a comprehensive comparison, the monitoring effect was the best when the grating was pasted at 60° relative to the crack.

Extreme Space Weather Impacts on GNSS Timing Signals for Electricity Grid Management

AbstractExtreme space weather events can have serious impacts on critical infrastructure, including Global Navigation Satellite Systems (GNSS). The use of GNSS, particularly as sources of accurate timing signals, is becoming more widespread, with one example being the measurement of electricity grid frequency and phase information to aid grid management and stability. Understanding the likelihood of extreme space weather impacts on GNSS timing signals is therefore becoming vital to maintain national electricity grid resilience. This study determines critical intensity thresholds above which the complete failure of a GNSS based timing system may occur. Solar radio bursts are identified as a simple example to investigate in more detail. The probability of occurrence of an extreme space weather event with an intensity equal to or greater than the critical intensity is estimated. Both a power law and extreme value theory were used to evaluate recurrence probabilities based on historical event frequencies. The probability was estimated to be between 3%–12% per decade to cause the complete failure of any GNSS‐based timing system.

Optimising the acquisition conditions of high information quality low-field NMR signals based on a cutting-edge approach applying information theory and Taguchi's experimental designs – Virgin olive oil as an application example

BackgroundDeveloping a new spectrometric analytical method based on a fingerprinting approach requires optimization of the experimental stage, particularly with novel instruments like benchtop low-field NMR spectrometers. To ensure high-quality LF-NMR spectra before developing the multivariate model, an experimental design to optimize instrument conditions is essential. However, difficult-to-control factors may be critical for optimization. Taguchi methodology addresses these factors to obtain a system robust to variation. This study uses the Taguchi methodology to optimize instrument settings for acquiring high-quality 1H and 13C LF-NMR signals in a short time from virgin olive oil (VOO). ResultsTwo experimental trials (for 1H and 13C signals, respectively) were carried out and analysed to find an optimal and robust combination of instrument settings against changes in two difficult-to-control factors: ambient temperature and small deviations of the NMR tube volume (700 ± 50 μL). The responses to be optimised, run time and spectral information quality, were analysed separately and jointly, as some factors showed opposite behaviour in the effect on the responses. Multiple response analysis based on suitable desirability functions yielded a combination of factors resulting in desirability values above 0.8 for 1H LF-NMR signals and almost 1.0 for 13C LF-NMR signals.In addition, a novel approach to assess the information quality of an analytical signal was proposed, addressing a major challenge in analytical chemistry. By applying information theory and calculating information entropy, this approach demonstrated its potential for selecting the highest quality (i.e. most informative) analytical signals. SignificanceThe acquisition instrument conditions of LF-NMR were successfully optimised using Taguchi methodology to acquire highly informative 1H and 13C spectra in a minimum run time. The importance lies in the future development of non-targeted analytical applications for VOO quality control. In addition, the innovative use of information entropy to a priori assess the signal quality represents a significant advance and proposes a solution to a long-standing challenge in analytical chemistry.

The Discovery of Three Pulsars in the Globular Cluster M15 with FAST

We present the discovery of three pulsars in the globular cluster (GC) M15 (NGC 7078) by the Five-hundred-meter Aperture Spherical Radio Telescope. PSR J2129+1210J (M15J) is a millisecond pulsar with a spin period of 11.84 ms and a dispersion measure of 66.68 pc cm−3. Both PSR J2129+1210K and L (M15K and L) are long-period pulsars with spin periods of 1928 ms and 3961 ms, respectively. M15L is the GC pulsar with the longest spin period known. We update the timing solutions of M15A to M15H. As predicted by A. Ridolfi et al., the flux density of M15C keeps decreasing, and the latest detection in our data set was on 2022 December 20. We have also detected M15I’s signal for the first time since its discovery. Current timing suggests that it is an isolated pulsar.

Comprehensive monitoring system for high voltage cables based on the ground current signal of the cable metal sheath

Abstract This paper has presented a comprehensive monitoring system for high voltage cables based on the ground current signal of the cable metal sheath. The system can collect and process the power frequency AC current and three high-frequency partial discharge signals in real time synchronously, which realize the synchronous detection of leakage current, relative dielectric loss, harmonic, partial discharge, and improve the integration of the hardware system.