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Recent 15N R1ρ-relaxation studies have shown that proteins in the solid state undergo slow, low amplitude global motion in the sub-millisecond time range. This range is at the edge of the time window for R1ρ experiments and, therefore, the motional parameters obtained by this method are not precise or reliable. In this paper, we present a 2H stimulated echo study of this type of molecular dynamics. The 2H stimulated echo experiments on a static sample allow for direct measurement of the correlation function in the time range of 10−6–10−1 s, making them well suited to study this type of molecular mobility. We have conducted a detailed analytical and numerical comparison of the correlation functions obtained from the relaxation and stimulated echo experiments, which are generally different. We have identified conditions and algorithms that enable a direct comparison of the relaxation and stimulated echo experimental results. Using the protein GB1 in the form of a lyophilized powder, we have demonstrated that 15N R1ρ-relaxation and 2H stimulated echo experiments yield essentially the same slow-motion correlation function. Surprisingly, this type of motion is observed not only in the protein sample but also in the tripeptide and single amino acid solid samples. The comparison of data measured in these three samples at different temperatures led us to conclude that this slow motion is, in fact, ultrasonic phonons, which seem to be inherent to all rigid biological solids. [ABSTRACT FROM AUTHOR]

Measurement of coating–substrate interface stiffness can indirectly characterize interface bonding quality. This paper proposes a noval quantitative inversion coating–substrate interface stiffness method based on the multi-resonance frequencies of a constructed ultrasonic echo phase derivative spectrum (UEPDS). The theoretical relationship between UEPDS resonance frequencies and interface stiffness is derived. The detection frequency and high-sensitivity interface stiffness range are optimized based on the sensitivity analyzed. Numerical simulation and experiment are implemented on a 0.48 mm aluminum layer/carbon steel substrate specimen to prove the validity of the proposed ultrasonic method. The simulation results show that the maximal relative error between the inversion and the preset interface stiffnesses is reduced from 23% to 8% compared with the traditional ultrasonic reflection coefficient amplitude spectrum-based (URCAS-based) method. The experiment results indicate that the UEPDS-based inversion interface stiffnesses have the same trend as the nominal contact pressures between the coating–substrate interface. [ABSTRACT FROM AUTHOR]

PURPOSE OF REVIEW: Environmental chemical exposures may disrupt child development, with long-lasting health impacts. To date, U.S. studies of early environmental exposures have been limited in size and diversity, hindering power and generalizability. With harmonized data from over 60,000 participants representing 69 pregnancy cohorts, the National Institutes of Healths Environmental influences on Child Health Outcomes (ECHO) Program is the largest study of U.S. childrens health. Here, we: (1) review ECHO-wide studies of chemical exposures and maternal-child health; and (2) outline opportunities for future research using ECHO data. RECENT FINDINGS: As of early 2024, in addition to over 200 single-cohort (or award) papers on chemical exposures supported by ECHO, ten collaborative multi-cohort papers have been made possible by ECHO data harmonization and new data collection. Multi-cohort papers have examined prenatal exposure to per- and polyfluoroalkyl substances (PFAS), phthalates, phenols and parabens, organophosphate esters (OPEs), metals, melamine and aromatic amines, and emerging contaminants. They have primarily focused on describing patterns of maternal exposure or examining associations with maternal and infant outcomes; fewer studies have examined later child outcomes (e.g., autism) although follow up of enrolled ECHO children continues. The NICHDs Data and Specimen Hub (DASH) database houses extensive ECHO data including over 470,000 chemical assay results and complementary data on priority outcome areas (pre, peri-, and postnatal, airway, obesity, neurodevelopment, and positive health), making it a rich resource for future analyses. ECHOs extensive data repository, including biomarkers of chemical exposures, can be used to advance our understanding of environmental influences on childrens health. Although few published studies have capitalized on these unique harmonized data to date, many analyses are underway with data now widely available.

We have observed that Variational Mode Decomposition (VMD) exhibits instability in the denoising and separation of noisy multitone signals. Specifically, minor changes in factors such as signal-to-noise ratio, frequency spacing, sampling rate, and probability distribution can significantly impact the decomposition results. To address this issue, we have developed the Dual-VMD-correlation algorithm. This algorithm effectively mitigates the impact of beat effects when harmonics of closely spaced frequencies are superimposed, enabling stable denoising of noisy multitone signals and the separation of each individual tone signal. The algorithm holds promise for applications in frequency-modulated continuous wave laser detection. It can address challenges related to denoising laser echo signals interfered with by aerosols and the difficulty in separating backscatter interference from the target reflected signal spectrum. [ABSTRACT FROM AUTHOR]

As one of the most successful platforms of quantum control, trapped ions can be modulated by sequential microwave pulses to realize high-fidelity quantum logic gates, and dephasing noise may lead to invalidation of phase locking. In this work, we utilize the Dirac–Frenkel time-dependent variational approach with Davydov ansatz to simulate spin echo dynamics in the framework of spin-boson model. As the essential modulation parameters, pulse duration and waiting time have been comprehensively investigated to optimize the phase gates by two microwave pulses. We find that, as spin orientation undergoes periodic changes, the phase difference by acting one and two pulses exhibits spontaneous locking following time evolution, which indicates the robustness of the quantum phase gates. Spectrum of the environmental noise that is appropriate for the phase locking is also determined. [ABSTRACT FROM AUTHOR]

A new scheme for ultrasonic non-destructive evaluation of wire-to-terminal joints was developed in this study. A finite element simulation model of 2D porous media based on X-CT images of an NG sample was proposed to analyse acoustic scattering. The simulation signal features were extracted in the time domain, frequency domain, and time-frequency domain, and entropy analysis was conducted to explore the relationship between different characteristic values and porosity, thereby revealing prominent trends in these features. By controlling parameters, 28 welding samples labelled OK and NG were produced, and their echoes were acquired by an ultrasonic Full Matrix Capture (FMC) system. Features of the full matrix signals were extracted, and the combined XGBoost machine learning was used to classify the quality and order the attribution of features. The result highlighted the significance of the waveform factor, margin factor, and kurtosis which are consistent with simulation results. The accuracy of weld quality identification can reach 84%. The three factors may be performance criteria for ultrasonically welded wire-to-terminal joints. [ABSTRACT FROM AUTHOR]

Objective: To demonstrate the potential of a double angle stimulated echo (DA-STE) method for fast and accurate "full" homogeneous Helmholtz-based electrical properties tomography using a simultaneous B 1 + magnitude and transceive phase measurement. Methods: The combination of a spin and stimulated echo can be used to yield an estimate of both B 1 + magnitude and transceive phase and thus provides the means for "full" EPT reconstruction. An interleaved 2D acquisition scheme is used for rapid acquisition. The method was validated in a saline phantom and compared to a double angle method based on two single gradient echo acquisitions (GRE-DAM). The method was evaluated in the brain of a healthy volunteer. Results: The B 1 + magnitude obtained with DA-STE showed excellent agreement with the GRE-DAM method. Conductivity values based on the "full" EPT reconstruction also agreed well with the expectations in the saline phantom. In the brain, the method delivered conductivity values close to literature values. Discussion: The method allows the use of the "full" Helmholtz-based EPT reconstruction without the need for additional measurements. As a result, quantitative conductivity values are improved compared to phase-based EPT reconstructions. DA-STE is a fast complex- B 1 + mapping technique that could render EPT clinically relevant at 3 T. [ABSTRACT FROM AUTHOR]

There is a long history of using VHF radar systems to detect ionospheric irregularities based on the theory of coherent scattering. According to previous work, there is a high occurrence of field-aligned irregularities (FAIs) in the ionospheric E-region over Kunming, China. In this paper, the VHF coherent scattering radar at Kunming is used to study the FAIs in the ionospheric E-region. Different arrangement of VHF radar antenna arrays, interferometry, and FAI echo parameter inversion methods are designed and tested. The measurement results show that the temporal and spatial characteristics of the irregularities can be obtained using these methods, as well as more refined spatial three-dimensional structure information. It is indicated that the new arrangement of the VHF radar antenna array is feasible to operate interferometry detection of E-region FAIs with the Kunming VHF radar. [ABSTRACT FROM AUTHOR]

The study of the ultrasonic acoustic response of materials is of increasing interest for the characterisation of high-frequency applications. In this work, some elastic properties (acoustic velocity and acoustic attenuation) and some physical properties (thickness and density), together with the phase shift of the transducer, are estimated via one method. Scanning acoustic microscopy was performed via an innovative and different method using a high-frequency (50 MHz) planar wave transducer. In addition, the Debye series model (DSM) was used to model the acoustic response of the bilayer structure of the glass substrate and the resin‒epoxy sample. The inverse problem of estimating the acoustic parameters that results in a DSM reflected echo that matches the experimental signal is solved by proposing an innovative step-by-step curve fitting algorithm. The algorithm for solving the inverse problem is then optimised via relative mean square error (RMSE) curves, resulting in a robust method for assessing the uniqueness of the multiparameter solution. [ABSTRACT FROM AUTHOR]

It is demonstrated that the time evolution of the electron-nuclear polarization transfer process during pulsed dynamic nuclear polarization (DNP) can be reversed on a microsecond timescale, leading to the observation of DNP echoes. The DNP echoes are induced by consecutive application of two pulse trains that produce effective Hamiltonians that differ only in the sign of the effective hyperfine coupling. The experiments have been performed on a frozen solution of trityl radicals in water/glycerol on a homebuilt X-band electron paramagnetic resonance/DNP spectrometer at 80 kelvins. We envisage that DNP echoes will play an important role in future development of pulsed DNP for sensitivity-enhanced nuclear magnetic resonance, hyperfine spectroscopy, and quantum sensing. [ABSTRACT FROM AUTHOR]

In shipborne high-frequency surface wave radar (HFSWR), the change of platform speed or heading will cause variations in the extension of the Doppler spectrum for vessel targets located in different directions, subsequently resulting in alterations to the signal-to-noise ratio (SNR). These alterations in vessel target echo present challenges for manual parameter adjustments in traditional constant false alarm rate (CFAR) methods for shipborne HFSWR, thereby hindering the maintenance of stable target detection capabilities. In this paper, a self-attention-convolutional neural network (SA-CNN)-based CFAR detector is proposed, which transforms the detection problem into signal structure classification. First, the extension characteristics of vessel target echoes resulting from changes in speed or heading of the shipborne platform are quantitatively analysed, thereby guiding the selection of an optimal sliding window and constructing input vectors for the neural network. Subsequently, the SA-CNN is designed to efficiently extract the structural features of the signal and accurately predict the probability of target presence. Finally, the Monte Carlo method is used to control the false alarm rate effectively. Simulation and real dataset verification demonstrate that the proposed method exhibits superior detection performance compared to traditional methods in shipborne HFSWR, especially for detecting extended targets. [ABSTRACT FROM AUTHOR]

This study analyses the interference effect in a visible light‐non‐orthogonal multiple access (VL‐NOMA) network that considers the signal power parameters performance for near and far users. The light‐emitting diode (LED) as a carrier transmits signals, and we investigate the interference effect. The interference effect challenge is a result of unaligned signal power parameters, thereby producing noise or echo during the signal transmission. The signal power parameters are successfully aligned, and NOMA techniques are deployed, which improves the signal performance in terms of bit‐error rate (BER), achieved data rate, and signal‐to‐interference plus noise ratio (SINR). Furthermore, the deployed NOMA techniques, such as power allocations (PA) to assign the signals appropriately, then superposition coding (SC) encodes the entire signal, and successive interference cancellation (SIC) cancels the interference within the signals. The signal behavior of the aligned and the unaligned signal power parameters performance are used to investigate the interference effect. We observed that unaligned signal power parameters reduce the signal performance of achieved data rate, BER, and SINR. Further, the aligned signal power parameter with NOMA techniques improves the signal performance. Moreover, in the aligned signal power scenario of NOMA, the near user performed better than the far user. [ABSTRACT FROM AUTHOR]

The classification and recognition of underwater targets by an active sonar system remain challenging and complex. Traditional methods have limited classification performance in time and spatially varying ocean channels. An active sonar target recognition method is proposed based on multi‐domain transformations and an attention‐based fusion network. Initially, the active target echo undergoes time‐frequency analysis, auditory signal processing, and matched filtering to represent target attributes in joint spatial‐time‐frequency domains. Subsequently, multiple attention‐based fusion models fuse the multi‐domain transformations either early or late in the processing stages. An attention module further enhances significant feature channels through adaptive weight assignment. Experiment results demonstrate that the recognition accuracy of active sonar echoes using multi‐domain transformations improves significantly compared to that of single‐domain methods, with an increase of up to 10.5%. The incorporation of multiple transformation domains provides complementary information about the target, thereby enhancing the network's representation ability, especially with limited data samples. Furthermore, the findings indicate that feature fusion of multiple transformations in a high‐level feature space yields more informative and effective results for active sonar echoes compared to low‐level feature spaces. [ABSTRACT FROM AUTHOR]

We conduct simulations of Spin Echo Small Angle Neutron Scattering (SESANS) by employing Monte Carlo methods to a setup using four magnetic Wollaston prisms. Our primary focus involves the validation of these models, encompassing monochromatic scenarios across various neutron wavelengths to ascertain the reliability of the simulations. Subsequently, we extend this validation to encompass simulations in time-of-flight mode. Our model consistently and precisely predicts the scattering patterns emanating from dilute spheres in both monochromatic and time-of-flight modes. Notably, it also accurately reproduces the intricate encoding associated with scattering occurring between the third and fourth magnetic Wollaston prism, which provides us with another approach to increase the solid angle coverage of a SESANS instrument. This validation process conclusively demonstrates the efficacy of our simulation methods. Importantly, it paves the way for simulating more intricate and realistic instrumental configurations, broadening the horizons for future research endeavours. [ABSTRACT FROM AUTHOR]

The article "Echo" by Amit Pinchevski, published in 2022, explores the concept of echo as a medium that connects and maintains separation, challenging the idea of echo as a simple repetition. Pinchevski draws on a wide range of disciplines, from literature to technology, to illustrate the creative possibilities of echo across nature and culture. While the book covers a broad interdisciplinary ground, some aspects of the analysis, particularly gendered analysis, could benefit from further development. Overall, Pinchevski's work offers a valuable new lens for understanding echoes in various fields, inviting readers to rethink the relationship between theoretical lenses and their objects. [Extracted from the article]

The Manila Amendment 2010 to the STCW International Convention has made clear requirements for seafarers to use the navigation simulation system for training. A shipborne echo sounder is an important navigation aid equipment necessary for a ship's bridge. Proper use of this equipment can effectively prevent ship grounding accidents. Given the lack of research on simulating different seabed substrate echoes within echo sounder simulations, this paper proposes an algorithm for generating echoes and clutter from various seabed substrates, based on the Jackson model and noise model. Using the seabed echo generation algorithm, the bathymetric data and seabed echo under the influence of ship rolling are generated, the seabed echo simulation of the sounder under the influence of four different grazing angles and six different substrates is realized. Clutter images, including random noise, bubble interference, co-frequency interference, and fish school interference, are also simulated. A typical ship echo sounder simulator is designed and developed. The echo sounder simulator developed in this paper has high realism in seabed echoes and clutter simulation, complete functions, and friendly human–computer interaction. The system has been used by college students and crews, with satisfactory results, which can effectively meet the needs of actual training of seafarers. [ABSTRACT FROM AUTHOR]

Abstract The classification and recognition of underwater targets by an active sonar system remain challenging and complex. Traditional methods have limited classification performance in time and spatially varying ocean channels. An active sonar target recognition method is proposed based on multi‐domain transformations and an attention‐based fusion network. Initially, the active target echo undergoes time‐frequency analysis, auditory signal processing, and matched filtering to represent target attributes in joint spatial‐time‐frequency domains. Subsequently, multiple attention‐based fusion models fuse the multi‐domain transformations either early or late in the processing stages. An attention module further enhances significant feature channels through adaptive weight assignment. Experiment results demonstrate that the recognition accuracy of active sonar echoes using multi‐domain transformations improves significantly compared to that of single‐domain methods, with an increase of up to 10.5%. The incorporation of multiple transformation domains provides complementary information about the target, thereby enhancing the network's representation ability, especially with limited data samples. Furthermore, the findings indicate that feature fusion of multiple transformations in a high‐level feature space yields more informative and effective results for active sonar echoes compared to low‐level feature spaces.

Radar is a powerful technology for surveys of avian movements. Validating the accuracy of radar detection is essential when establishing quantitative criteria for tracking bird trajectories and counting bird flocks. This study clarifies the positional and biological factors influencing the probability of detection (POD) and echo size on X-band marine radar. The bird trajectory for validation was obtained by ornithodolite at the same time as the radar scan. Distance was found to have a negative effect on POD and echo size, while elevation angle positively affected POD. Body mass and flock size positively affected POD and echo size. In predicting detection performance, the survey distance required to achieve 50% POD was 750 m or less for Grey-faced Buzzard, the lightest target species, but up to 1800 m for a pair of Bewick's Swan. Our study provides survey and analysis procedures that allow for efficient validation using ornithodolites. Then, we identify the range settings that should be considered for target species and contribute to establishing criteria for quantitative radar bird surveys. [ABSTRACT FROM AUTHOR]

To address the problem that conventional neural networks trained on radar echo data cannot handle the phase of the echoes, resulting in insufficient information utilization and limited performance in detection and classification, we extend neural networks from the real-valued neural networks to the complex-valued neural networks, presenting a novel algorithm for classifying small sea surface targets. The proposed algorithm leverages an improved residual fusion network and complex time–frequency spectra. Specifically, we augment the Deep Residual Network-50 (ResNet50) with a spatial pyramid pooling (SPP) module to fuse feature maps from different receptive fields. Additionally, we enhance the feature extraction and fusion capabilities by replacing the conventional residual block layer with a multi-branch residual fusion (MBRF) module. Furthermore, we construct a complex time–frequency spectrum dataset based on radar echo data from four different types of sea surface targets. We employ a complex-valued improved residual fusion network for learning and training, ultimately yielding the result of small target classification. By incorporating both the real and imaginary parts of the echoes, the proposed complex-valued improved residual fusion network has the potential to extract more comprehensive features and enhance classification performance. Experimental results demonstrate that the proposed method achieves superior classification performance across various evaluation metrics. [ABSTRACT FROM AUTHOR]

Due to the similarity in wavelength between millimeter-wave (MMW) signals and raindrop diameters, rainfall induces significant attenuation and scattering effects that challenge the detection performance of MMW fuzes in rainy environments. To enhance the adaptability of frequency-modulated MMW fuzes in such conditions, the effects of rain on MMW signal attenuation and scattering are investigated. A mathematical model for the multipath echo signals of the fuze was developed. The Monte Carlo method was employed to simulate echo signals considering multiple scattering, and experimental validations were conducted. The results from simulations and experiments revealed that rainfall increases the bottom noise of the echo signal, with rain backscatter noise predominantly affecting the lower end of the echo signal spectrum. However, rain conditions below torrential levels did not significantly impact the detection of strong reflection targets at the high end of the spectrum. The modeling approach and findings presented offer theoretical support for designing MMW fuzes with improved environmental adaptability. [ABSTRACT FROM AUTHOR]

The impact of a cyclonic (C), an anticyclonic (AC) eddy and transition zone (TZ), which is the area between the two eddies, on acoustic groups representing various mesopelagic organisms, was investigated using a semi-supervised multifrequency classification approach (hereafter, Escore algorithm). The Escore algorithm involved selecting regions of interest (ROIs) within multifrequency (18, 38, 70, and 120 kHz) echograms and classifying into four clusters or echo-classes using Sv differences (Sv18-38, Sv70-38, and Sv120-38). Acoustic densities and diel vertical migration strength varied between the AC, C, and TZ according to the frequency. The vertical stratification of temperature, salinity and fluorescence within the oceanographic structures had varied influences on the vertical structure of each echo-class which represent zooplankton-like organisms, small and large fish with swimbladders, and small and large siphonophores with pneumatophores. The echo-classes within the C were influenced by surface fluorescence, whereas in the AC and TZ, the echo-classes were influenced by deeper fluorescence and strong EKE. Our study provides new insights into the environmental variables within mesoscale and sub-mesoscale features impacting different groups of mesopelagic communities in the Indian Ocean. [ABSTRACT FROM AUTHOR]

This paper presents a novel ultrasonic signal denoising method that integrates adaptive variational mode decomposition (AVMD) with convolutional neural networks (CNNs). Initially, the whale optimisation algorithm (WOA) is employed to optimise key parameters of variational mode decomposition, specifically the decomposition modes K and the penalty factor α. The ultrasonic signals are then decomposed into intrinsic mode functions (IMFs) and various statistical feature parameters, such as energy entropy, sample entropy, kurtosis and correlation factors, are calculated for each IMF. The signal-to-noise ratio (SNR) of the reconstructed signal from the IMFs is used to assign label values, forming a feature dataset. Subsequently, a CNN is utilised to train and recognise this dataset, achieving an accuracy rate of 93.94% on the test set. The results demonstrate that the CNN effectively distinguishes between various IMF combinations based on the reconstructed SNR and can proficiently identify IMF combinations with higher SNR. Finally, denoising experiments on actual ultrasonic echo signals validate the feasibility of this method for noise reduction applications. [ABSTRACT FROM AUTHOR]

As demonstrated in the first part of this study (Part I), wind-shift boundaries routinely form along the west coast of the Pearl River Delta due to the land–sea contrast of a "trumpet" shape coastline in the summer monsoon season. Through multiple numerical simulations, this article (Part II) aims to examine the roles of the trumpet-shaped coastline in the mesovortex genesis during the 1 June 2020 tornadic event. The modeling reproduced two mesovortices that are in close proximity in time and space to the realistic mesovortices. In addition to the modeled mesovortex over the triple point where strong ambient vertical vorticity was located, another mesovortex originated from an enhanced discrete vortex along an airmass boundary via shear instability. On the fine-scale storm morphology, finger-like echoes preceding hook echoes were also reproduced around the triple point. Results from sensitivity experiments suggest that the unique topography plays an essential role in modifying the vorticity budget during the mesovortex formation. While there is a high likelihood of an upcoming storm evolving into a rotating storm over the triple point, the simulation's accuracy is sensitive to the local environmental details and storm dynamics. The strengths of cold pool surges from upstream storms may influence the stretching of low-level vertically oriented vortex and thus the wrap-up of finger-like echoes. These findings suggest that the trumpet-shaped coastline is an important component of mesovortex production during the active monsoon season. It is hoped that this study will increase the situational awareness for forecasters regarding regional non-mesocyclone tornadic environments. [ABSTRACT FROM AUTHOR]

In an era of political polarization, growing anti-science sentiment, and pervasive inequities in the social drivers of health, a rising tide of potentially harmful state policy proposals in the United States threaten to undermine the health of the public. In response, our health system's population health and government relations offices partnered with key health advocacy organizations in our state of New Hampshire to offer an interactive virtual learning series aimed at preparing diverse professionals and citizens to effectively advocate for sound health policies. Two hundred forty-seven individuals registered for the six-session series. Our findings indicate that participants experienced increased awareness of the political determinants of health, better understanding of specific legislative proposals in New Hampshire, and enhanced preparedness for advocacy, with many reporting greater active engagement in advocacy. Given its flexible and virtual nature, this innovative learning model could easily be adapted to promote dialogue and advocacy for sound health policy in diverse regional contexts. [ABSTRACT FROM AUTHOR]

Regarding the suppression of radar mainlobe jamming, a blind extraction method for suppressing mainlobe jamming based on maximizing the signal to interference plus noise ratio (SINR) is proposed. Unlike blind separation, blind extraction can extract interested components from multiple mixed signals, making it more suitable for jamming suppression in complex electromagnetic environments with multiple sources and channels. This method establishes an optimization model for maximizing SINR in the distance domain. The target echo signal is solved and extracted using the particle swarm optimization (PSO) algorithm to achieve mainlobe jamming suppression. Simulation testing shows that the proposed method improves the jamming suppression effect compared to traditional blind separation jamming suppression methods. It does not require estimation of the number of sources and has lower requirements for the number of channels, making it applicable in underdetermined scenarios. Additionally, it reduces computational complexity, making it more suitable for complex electromagnetic environments. [ABSTRACT FROM AUTHOR]

An automated quality control pre-processing algorithm for removing non-weather radar echoes from airborne Doppler radar data has been developed. The proposed algorithm can significantly reduce the time and experience level required for interactive radar data editing prior to dual-Doppler wind synthesis or data assimilation. As important as reducing the time required and skill level necessary to process an airborne Doppler dataset can be, the quality of the automated analysis is paramount. Retrieved wind data, recovered perturbation pressure data (with associated momentum check values) and correlation coefficients were computed. To quantitatively test the quality of the automated quality control algorithm, spatial Pearson correlation coefficients and momentum check values were computed. Four different (published) Electra Doppler Radar (ELDORA) datasets of convective echoes were used to stress the algorithm. Four distinct threshold levels for data removal in the automated quality control algorithm were applied to each of four ELDORA datasets. The algorithm threshold levels were labeled as follows: extremely low, low, medium, and high. Extremely low algorithm cases were deemed necessary during the data analyses and were added to the low, medium and high cases. A description of each case and the differences in the perturbation pressure momentum check values and correlation coefficients between the interactively edited fields were computed. These comparisons along with a subjective visual inspection show that the automated quality control algorithm can produce an analysis comparable—and in some cases superior—to an interactive analysis when used properly. A key benefit of this algorithm is that the skill level of a relatively inexperienced airborne radar meteorologist may be effectively increased by using the SOLO QC algorithm. [ABSTRACT FROM AUTHOR]

To investigate the omnidirectional geometric scattering characteristics of an underwater vehicle and the target detection performance of phase coded (BPSK) signals, acoustic scattering tests were carried out in an anechoic chamber using the Suboff scale model. To mitigate the overlapping interference of the direct wave on the scattering wave in the limited test space, physical suppression with an "anechoic cloak" and direct wave cancellation were proposed. Target echo and reflection wave tests at different offset angles were carried out, and the accuracy of the BPSK signal in acquiring highlight features and the feasibility of anechoic chamber tests were verified through comparison with theoretical range profiles. A series of echo and omnidirectional scattering characteristics were obtained through the experiment and simulation, which verified the effectiveness of the low-frequency submarine model detection (there were still strong scattering waves at the dimensionless frequency ka = 1.88). Comparison tests of CW, LFM, and BPSK signals were carried out, and the measured data proved that the BPSK signal had the advantages of low sidelobe, high resolution, and noise resistance in target detection. The acoustic scattering test method designed in this study and the omnidirectional scattering characteristics obtained can be used as a reference for semi-physical target acoustic scattering simulations and practical multistatic detection. [ABSTRACT FROM AUTHOR]

In view of the cracking, sag, and damage of sheath caused by the load effect and external force impact of power cable, the echo parameters of cable sheath damage detection based on the characteristics of torsional guided wave propagation are studied in this work. According to the Navier displacement equilibrium equation, the dispersion curve of a magnetostrictive guided wave of the cable sheath was solved, and the T(0,1) mode with a group velocity of 1198.8 m/s and no dispersion was selected. Furthermore, while considering the excitation frequency, loss rate, and direction of the damaged section, the displacement field and the echo characteristic parameters of guided wave in the cable sheath were solved. Moreover, by analyzing the time-domain signals of damaged section echo, the cubic fitting function for the loss rate of the damaged section and the damaged section echo coefficient were obtained, which can effectively characterize the quantitative relationship between the damaged location, size, and guided wave echo of the cable sheath. [ABSTRACT FROM AUTHOR]

Marine organisms continually adapt their physiology and behaviour to temporal variations in their environment, resulting in diurnal rhythmic behaviour, particularly when foraging. In delphinids, these rhythms can be studied by recording echolocation clicks, which can provide indicators of foraging activity. The foraging rhythms of delphinids and their relationship to temporal parameters are poorly documented and most studies so far have used moored passive acoustic systems. The present study provides, for the first time, information on the activity rhythms of delphinids investigated in relation with temporal variables at a basin scale from a moving platform, in the western and central Mediterranean Sea. We used passive acoustic recordings collected by hydrophones towed along transect lines during the ACCOBAMS Survey Initiative in the summer 2018. We extracted variables that may influence daily and monthly rhythms, including time of day, lunar cycle, lunar illumination and sea state and fitted generalised additive models. The nycthemeral and lunar cycles were the two main factors influencing dolphin activity rhythms. Echolocation activity was predominant at night, with a maximum of 0.026 acoustic events per minute at 21:00/22:00 compared to as few as 0.0007 events per minute at 11:00. These events were also more frequent during the third quarter of the moon; 0.033 acoustic events on day 22 of the lunar cycle as opposed to 0.0008 on day 8 of the lunar cycle, corresponding to the first quarter of the moon. Variations in the echolocation activity of delphinids in the Mediterranean Sea could reflect variation in their foraging effort and be related to prey density, composition, accessibility and catchability within dolphin foraging depth range. These results should also improve interpretation of passive acoustic monitoring data. [ABSTRACT FROM AUTHOR]

Due to the influence of geometric factors, the temperature and humidity profile of lidar's near-field signal was warped when sensing the air environment. In order to perform geometric factor correction on near-field signals, this article proposes different correction solutions for the Mie and Raman scattering channels. Here, the Mie scattering channel used the Raman method to invert the aerosol backscatter coefficient and correct the extinction coefficient in the transition zone. The geometric factor was the ratio of the measured signal to the forward-computed vibration Raman scattering signal. The aerosol optical characteristics were reversed using the corrected echo signal, and the US standard atmospheric model was added to the missing signal in the blind zone, reflecting the aerosol evolution process. The stability and dependability of the proposed algorithm were validated by the consistency between the visibility provided by the Environmental Protection Agency and the visibility acquired via lidar retrieval data. The near-field humidity data were supplemented by the interpolation method in the Raman scattering channel to reflect the water vapor transfer process in the temporal dimension. The measured transmittance curve of the filter, the theoretical normalized spectrum, and the sounding data were used to compute the delay geometric factor. The temperature was retrieved and the near-field signal distortion issue was resolved by applying the corrected quotient of the temperature channel. The proposed algorithm exhibited robustness and universality, enhancing the system's detection accuracy compared to the temperature and humidity data constantly recorded by the probes in the meteorological gradient tower, which have a high correlation with the lidar observation data. The comparison between lidar data and instrument monitoring data showed that the proposed algorithm could effectively correct distorted echo signals in the transition zone, which was of great value for promoting the application of lidar in the meteorological monitoring of the urban canopy layer. [ABSTRACT FROM AUTHOR]

In order to analyse the effect of the injection point size of the CBM (Coalbed Methane) well level monitor on the amplitude and frequency of pressure pulsations in the wellhead manifold, numerical simulations and experiments were carried out to investigate the effect of different injection point sizes on the amplitude and frequency of pressure pulsations downstream of the sudden expansion structure. Using compressed air as the fluid and the size of the injection point as the variable, the amplitude and frequency of pressure pulsations at different locations downstream of the sudden expansion structure were tested. The results show that the pressure pulsation amplitude is affected by the size of the injection point, and the larger the injection point is, the larger the pressure pulsation amplitude is; the size of the injection point has less influence on the pressure pulsation frequency downstream of the protruding and expanding structure, and the pressure pulsation frequency at 0.5 m and 1 m downstream of the protruding and expanding structure is in the vicinity of 76 Hz. Therefore, the echo signal processing should be filtered around this frequency to obtain accurate liquid level echo signals, so as to improve the accuracy of liquid level monitoring and realise the efficient development of coalbed methane wells. [ABSTRACT FROM AUTHOR]

Eating disorders (ED) usually involve hospital admission and a high relapse rate, with the return home being a critical moment for patients and their families. After their return home, they often have trouble incorporating the guidelines they have learned into their daily context. ECHOMANTRA intervention program aims to facilitate this transition by offering psychological strategies that involve both patients and their families and carers. Specifically, the ECHO program is aimed at the relatives of these patients. The present study aimed to analyze the efficacy of adding the ECHO program to the usual treatment (TAU) of relatives through a novel format based on individual intervention and with an online format and to examine the acceptability and feasibility of this new format. The study design was multi‐center, randomized, controlled, with a longitudinal design and comparing two parallel groups. A total of 108 family members participated. Results indicated that relatives from both groups, TAU and ECHO + TAU, showed improvements in expressed emotion, accommodation, impact of the ED, emotional well‐being, and caregiver skills. However, effect sizes in the ECHO + TAU group were slightly larger than the TAU group. In addition, the changes were greater in depression and caregiver skills when the ECHO component was added. Most caregivers (81.48%) completed the ECHO and indicated a high level of satisfaction with the program. These results suggest the efficacy and the feasibility of adding the ECHO intervention program to the usual treatment in an individual online format. [ABSTRACT FROM AUTHOR]

Background: The mechanism of myocardial damage in dengue could be the release of inflammatory mediators or the direct action of the dengue virus on myocytes leading to myocarditis. The release of inflammatory mediators is more in a severe form of the disease that correlates to the higher incidence of cardiac manifestations in patients with severe dengue. Aim: To estimate the proportion of cardiac involvement among patients with dengue fever admitted in Kanachur Medical College, Mangaluru based on clinical, serological, electrocardiographical and echocardiographical evaluation. Materials and Methods: A hospital based cross sectional study was conducted at Kanachur Medical College, Mangaluru during duration of 1 year (March, 2022-March, 2023). 185 patients were recruited in this study. A detailed history and clinical examination was recorded on structured proforma. Hematological and biochemical investigations were done at the time of admission. Study variables included Systemic hypertension, Dyslipidemia, symptoms of cardiac involvement such as palpitations and chest discomfort. Results: Out of 185 patients, 14.6% were less than 30 years, 20.5% were 31-40 years old, 30.8% were 41-50 years old, 22.2% were 51-60 years old, and 11.9% were >60 years old. 51% patients were females and 49% were males. According to distribution of cardiac symptoms, 72.9% were normal, 11.9% had bradycardia, 4.3% had tachycardia, 4.3% had ischaemic type chest pain, 3.8% had palpitations, and 2.7% had dyspnoea. 76.2% patients had normal ECG findings, 10.8% had sinus bradycardia, 6.7% had sinus tachycardia, 1.7% had heart block, 1.4% had dynamic ST-T, and 0.6% had atrial fibrillation. 87.5% patients had normal ECHO findings, 9.1% had wall motion abnormalities, 2.2% had LV systolic dysfunction, and 1.1% had Valvular regurgitant lesion. Conclusion: From present study, we can say that the most accurate test for detecting myocarditis is ECG. The most frequent ECG abnormality was sinus bradycardia. The most common ECHO abnormality was wall motion abnormalities with global hypokinesia. [ABSTRACT FROM AUTHOR]

Due to suppression jamming by jammers, the signal-to-interference-plus-noise ratio (SINR) during tracking tasks is significantly reduced, thereby decreasing the target detection probability of radar systems. This may result in the interruption of the target track. To address this issue, we propose a multi-static radar power allocation algorithm that enhances the detection and tracking performance of multiple radars in relation to their targets by optimizing power resource allocation. Initially, the echo signal model and measurement model of multi-static radar are formulated, followed by the derivation of the Bayesian Cramér–Rao lower bound (BCRLB). The multi-objective optimization method is utilized to establish the objective function for joint tracking and detection, with dynamic adjustment of the weight coefficient to balance the tracking and detection performance of multiple radars. This ensures the reliability and anti-jamming capability of the multi-static radar system. Simulation results indicate that the proposed algorithm can prevent the interruption of jammer tracking and maintain robust tracking performance. [ABSTRACT FROM AUTHOR]

In the theoretical calculation of atmospheric wind fields using the cross-correlation analysis method of Medium-Frequency radar, it is necessary to compute a series of correlation parameters from the received echo signals, such as autocorrelation and cross-correlation functions, within the main lobe range of the antenna array to retrieve atmospheric parameters. However, both theoretical analysis and practical applications have shown that the shape of correlation functions can be affected by atmospheric conditions and receiver noise, leading to significant biases in the estimated correlation parameters within the main lobe range. In this study, we theoretically analyze the influence of noise on the amplitude of autocorrelation and cross-correlation functions. We propose a noise reduction method based on the characteristics of correlation functions at the zero-delay point to calculate the noise factor and process the correlation functions within the main lobe range. Furthermore, we conduct simulation analysis to evaluate the performance of this noise reduction method and summarize the effects of the number of fitting points and fitting methods on the noise reduction performance. [ABSTRACT FROM AUTHOR]

To improve the signal-to-noise ratio (SNR) of nuclear magnetic resonance (NMR) echo data with SNR below 8 obtained from tight sandstone reservoirs and improve the accuracy of the porosity obtained from T 2 inversion, a novel de-noising method is developed to improve the processing of NMR echo data. The algorithm is based on variational mode decomposition wavelet threshold (VMD-WT). It was found that as the decomposition mode number increases, the center frequency difference between the first mode and the second mode gradually decreases. A method to determine a reasonable mode decomposition number based on the center frequency difference of the modes is proposed. The effectiveness of the algorithm is verified by the application in the numerical simulation experiments and actual NMR echo data, respectively. The results indicated that, compared with wavelet threshold de-noising method, VMD-WT de-noising method is more suitable for the de-noising of NMR echo data with SNR below 8 obtained from tight sandstone reservoirs. [ABSTRACT FROM AUTHOR]

Hereditary transthyretin amyloidosis (ATTRv) is associated with polyneuropathy, cardiomyopathy, or both. The effects of eplontersen on cardiac structure and function were assessed. NEURO-TTRansform was an open-label trial involving 144 adults with ATTRv polyneuropathy (49 patients [34%] with cardiomyopathy) receiving eplontersen throughout and compared with a historical placebo group (n = 60; 30 patients [50%] with cardiomyopathy) from the NEURO-TTR trial at week 65. Treatment effect (eplontersen vs placebo), presented as mean difference (95% confidence interval) was analyzed after adjusting for age, sex, region, baseline value, ATTRv disease stage, previous ATTRv treatment, and V30M transthyretin variant. There were notable differences at baseline between the eplontersen group and historical placebo. In the cardiomyopathy subgroup, 65 weeks of eplontersen treatment was associated with improvement from baseline relative to placebo in left ventricular ejection fraction of 4.3% (95% confidence interval 1.40–21.01; P =.049) and stroke volume 10.64 mL (95% confidence interval 3.99–17.29; P =.002) while the remainder of echocardiographic parameters remained stable. Eplontersen was associated with stable or improved measures of cardiac structure and function vs historical placebo in patients with ATTRv polyneuropathy and cardiomyopathy. Further investigation into eplontersen's effect on transthyretin amyloid cardiomyopathy is being conducted in the CARDIO-TTRansform trial. vATTR, variant transthyretin; LV, left ventricle; E/e′, ratio of early diastolic mitral inflow velocity to early diastolic mitral annulus velocity; NT-proBNP, N-terminal prohormone of brain natriuretic peptide. [Display omitted] [ABSTRACT FROM AUTHOR]

Electronic warfare equipment estimates the azimuth and elevation of an unknown target by processing radar echoes received from monopulse or array antennas and interrupts radar sensing by transmitting jamming signals to the target. However, state-of-the-art targets maneuver at low altitudes in a sea surface environment to deliberately produce interference through multi-path, which poses a significant challenge for accurately estimating the estimation of the elevation angle. In this study, we propose an algorithm to accurately estimate the elevation angle of a low-altitude target despite the presence of a few arrays. Assuming that the sampled complex echoes are obtained after down-converging from the X-band (i.e., 10 GHz) to the base band, the proposed method demodulates the unknown linear frequency modulation using particle swarm optimization (PSO) and estimates the elevation angle by exploiting the new Fourier relationship between the wavelength and elevation angle. The simulation results suggest that our proposed method can successfully estimate the elevation angle for low-altitude maneuvering targets in a sea-surface environment. [ABSTRACT FROM AUTHOR]

Seafloor geodetic observation technology is a pivotal method for capturing plate boundary earthquakes and related phenomena. Currently, this task is performed by Global Navigation Satellite System-Acoustic ranging (GNSS-A), a technique that integrates GNSS observations with acoustic ranging. This method involves measuring the round-trip travel time of an acoustic signal between a surface platform and a preinstalled seafloor station, which is then converted into a distance for positioning. While the horizontal positioning accuracy can reach the centimeter level, the vertical accuracy tends to be loser. Recent research has revealed that equipment-dependent distortion of sound waves causes problems for accurate travel time identification, leading to a decrease in vertical component accuracy. In this paper, we conducted an analysis of distortion tendencies using water tank test data and quantitatively identified differences in distortion magnitude related to instruments, angle dependence, and directional dependence attributed to the sea surface platform. We proposed a new identification algorithm, Acoustic Ambiguity Reduction (AAR) method, using a catalog of distortions for each device, and improved the observational capabilities of the vertical component. [ABSTRACT FROM AUTHOR]

Widespread clinical use of MRI radiomic tumor profiling for prognostication and treatment planning in cancers faces major obstacles due to limitations in standardization of radiomic features. The purpose of the current work was to assess the impact of different MRI scanning- and normalization protocols for the statistical analyses of tumor radiomic data in two patient cohorts with uterine endometrial-(EC) (n = 136) and cervical (CC) (n = 132) cancer. 1.5 T and 3 T, T1-weighted MRI 2 min post-contrast injection, T2-weighted turbo spin echo imaging, and diffusion-weighted imaging were acquired. Radiomic features were extracted from within manually segmented tumors in 3D and normalized either using z-score normalization or a linear regression model (LRM) accounting for linear dependencies with MRI acquisition parameters. Patients were clustered into two groups based on radiomic profile. Impact of MRI scanning parameters on cluster composition and prognostication were analyzed using Kruskal–Wallis tests, Kaplan–Meier plots, log-rank test, random survival forests and LASSO Cox regression with time-dependent area under curve (tdAUC) (α = 0.05). A large proportion of the radiomic features was statistically associated with MRI scanning protocol in both cohorts (EC: 162/385 [42%]; CC: 180/292 [62%]). A substantial number of EC (49/136 [36%]) and CC (50/132 [38%]) patients changed cluster when clustering was performed after z-score-versus LRM normalization. Prognostic modeling based on cluster groups yielded similar outputs for the two normalization methods in the EC/CC cohorts (log-rank test; z-score: p = 0.02/0.33; LRM: p = 0.01/0.45). Mean tdAUC for prognostic modeling of disease-specific survival (DSS) by the radiomic features in EC/CC was similar for the two normalization methods (random survival forests; z-score: mean tdAUC = 0.77/0.78; LRM: mean tdAUC = 0.80/0.75; LASSO Cox; z-score: mean tdAUC = 0.64/0.76; LRM: mean tdAUC = 0.76/0.75). Severe biases in tumor radiomics data due to MRI scanning parameters exist. Z-score normalization does not eliminate these biases, whereas LRM normalization effectively does. Still, radiomic cluster groups after z-score- and LRM normalization were similarly associated with DSS in EC and CC patients. [ABSTRACT FROM AUTHOR]

Echo state network (ESN) has widely attracted many researchers due to its training process without backpropagation. However, it is hard for single ESN to fit those complex and polytrophic situations. Under this case, a novel multiscale deep ESN (MDESN) is developed in this study, which integrates the deep learning, parallel structure and multiscale reservoir state matrix mode, respectively. The deep framework is responsible for collecting multivariate dimensional reservoir states; Upgradation of various reservoir states could efficiently dig hidden characteristics for decoding. The parallel structure could be trained simultaneously to decrease time consumption through the multiple thread method. According to the multivariate high dimensional mapping method, MDESN could obtain more robust generalization information compared to the state-of-the-art models. MDESN is evaluated in two chaos prediction benchmarks (Lorenz and Mackey-Glass) and real solar irradiance predictions. Various prediction horizons including one-step-ahead and multi-step-ahead prediction are designed and conducted respectively to verify the effectiveness and robustness of MDESN. Furthermore, RMSE, MAE, MAPE, and R are adopted to evaluate our proposed model. The statistical results demonstrate that MDESN has the best-performing adaptability and robustness compared to classical ESN, deep ESN (DESN), and other state-of-the-art models. [ABSTRACT FROM AUTHOR]

Accurately extracting and segmenting boundaries between targets and backgrounds is difficult in Synthetic Aperture Radar (SAR) images because of the many scattering mechanisms that produce echo signals. These complications combined with the ubiquitous speckle noise present in SAR images cause traditional segmentation algorithms to frequently produce unacceptable results. In order to tackle these problems, we provide a unique segmentation strategy that makes use of a minimum error thresholding technique based on the theory of the Rayleigh distribution. Our technique builds a local translation Rayleigh model by utilizing the stationary wavelet domain, which successfully suppresses speckle noise and generates SAR images that are easier to segment. Next, we utilize a two-dimensional entropy thresholding method to segment images. We present a variable code length genetic technique that incorporates the optimization of segmentation category numbers encoded in the chromosomes into the fitness function in order to further improve segmentation performance. Furthermore, our method yields minimum segmentation error pixels and excellent segmentation efficiency since the segmentation thresholds it finds is accurate. By addressing major issues with speckle noise and segmentation precision, this enhanced approach provides notable improvements in the precise and effective segmentation of SAR images. [ABSTRACT FROM AUTHOR]

Azimuth multi-channel synthetic aperture radar (SAR) has always been an important technical means to achieve high-resolution wide-swath (HRWS) SAR imaging. However, in the space-borne azimuth multi-channel SAR system, random phase noise will be produced during the operation of each channel receiver. The phase noise of each channel is superimposed on the SAR echo signal of the corresponding channel, which will cause the phase imbalance between the channels and lead to the generation of false targets. In view of the above problems, this paper proposes a random phase noise compensation method for space-borne azimuth multi-channel SAR. This method performs feature decomposition by calculating the covariance matrix of the echo signal and converts the random phase noise estimation into the optimal solution of the cost function. Considering that the phase noise in the receiver has frequency-dependent and time-varying characteristics, this method calculates the phase noise estimation value corresponding to each range-frequency point in the range direction and obtains the phase noise estimation value by expectation in the azimuth direction. The proposed random phase noise compensation method can suppress false targets well and make the radar present a well-focused SAR image. Finally, the usefulness of the suggested method is verified by simulation experiments. [ABSTRACT FROM AUTHOR]

Background: This study presents a 4-year (January 2019–April 2023) X-band radar network-based bow echo observation over Great Bandung Indonesia. This study provides insight into the temporal and spatial variability of bow echo distribution and presents the atmospheric condition associated with the bow echo events. Temporal analysis is categorical into monthly, seasonally, and diurnal. The analysis was performed using X-band radar network and reanalysis data (ERA5). Result: At least 26 bow echoes were identified across the Bandung basin from X-band radar network during the study period. From this total number of bow echoes, the observation of initiation modes is primarily generated from a weakly organized cell, with few coming from the squall line. The bow echo mostly evolved from noon until afternoon. The rainy season (December–January–February) and transition season (March–April–May) is the most frequent period of bow echo occurrence, with March being the most active month. Nevertheless, this study also found bow echo occurrence in the dry season (June–July–August). For the spatial analysis, the studied area is divided into two regions representing the eastern and western part of Bandung basin. The eastern region recorded the most intense occurrences with 14 events. The movement of bow echo in this region covered a shorter distance (average distance only 4.56 km), with all initiation modes occurring inside the region. The atmospheric condition within this region has less moisture flux, with higher CAPE and slightly higher surface temperature. Meanwhile, in the western region have different characteristics with higher moisture flux, a slight effect of CAPE and CINH, with longer distance and zonal movement direction of bow echo displacement. Conclusion: These conditions indicate that local convection is the dominant mode of bow echo initiation mode in the eastern region of Bandung basin. Meanwhile, the monsoon effect influences the bow echo initiation mode in the western region. Given that the observed 4-year bow echo has different characteristics from previous studies of bow echo in mid latitudes, developing different criteria for bow echo detection in the tropics is crucial. [ABSTRACT FROM AUTHOR]

Echo state networks (ESNs) belong to the class of recurrent neural networks and have demonstrated robust performance in time series prediction tasks. In this study, we investigate the capability of different ESN architectures to capture spatial relationships in images without transforming them into temporal sequences. We begin with three pre-existing ESN-based architectures and enhance their design by incorporating multiple output layers, customising them for a classification task. Our investigation involves an examination of the behaviour of these modified networks, coupled with a comprehensive performance comparison against the baseline vanilla ESN architecture. Our experiments on the MNIST data set reveal that a network with multiple independent reservoirs working in parallel outperforms other ESN-based architectures for this task, achieving a classification accuracy of 98.43%. This improvement on the classical ESN architecture is accompanied by reduced training times. While the accuracy of ESN-based architectures lags behind that of convolutional neural network-based architectures, the significantly lower training times of ESNs with multiple reservoirs operating in parallel make them a compelling choice for learning spatial relationships in scenarios prioritising energy efficiency and rapid training. This multi-reservoir ESN architecture overcomes standard ESN limitations regarding memory requirements and training times for large networks, providing more accurate predictions than other ESN-based models. These findings contribute to a deeper understanding of the potential of ESNs as a tool for image classification. [ABSTRACT FROM AUTHOR]

The echo signal of ultrasonic internal inspection is highly sensitive to the incident deflection angle between the probe and the measured surface of the pipeline, which is the key factor affecting the accuracy of ultrasonic inspection. In practical engineering, the echo signal of ultrasonic inspection is easy to be interfered by the external environment, which makes it difficult to identify the deflection angle. The data of defect echo signal under different circumferential declination were collected by the pipeline ultrasonic internal inspection system, and the characteristics of signal variation in time domain under different circumferential declination were analysed. The results show that the existence of circumferential declination reduced the absolute value of the overall amplitude of ultrasonic echo signal. A signal processing method based on amplitude reduction is proposed to reduce the sampling random error. Comparative analysis shows that the circumferential declination can be identified based on amplitude reduction method, and the accuracy of ultrasonic recognition can be improved. By extracting the characteristic value of waveform, the empirical formula is obtained. Within 2°, the maximum deviation is 0.137°. The research results have certain guiding significance for the identification of circumferential declination in practical engineering. [ABSTRACT FROM AUTHOR]

This article gives the overview of the Japan Aerospace Exploration Agency (JAXA) level 2 (L2) Standard and Research algorithms and products by Japanese science teams for EarthCARE Clouds, Aerosols and Radiation Explorer (EarthCARE), which is a JAXA and the European Space Agency (ESA) joint satellite mission. First three single sensor algorithms for 94GHz cloud profiling radar (CPR)-only, 355nm-atmospheric lidar with high spectral resolution function (ATLID)-only, and multi-spectral imager (MSI)-only retrievals, and their products were briefly reviewed. CPR-echo algorithms provide radar reflectivity factor, Doppler velocity, normalized radar cross section and path integral attenuation. CPR-only, CPR-ATLID synergy and CPR-ALTID-MSI synergy algorithms for standard cloud products provide cloud detection, cloud particle type and cloud microphysics, and the research products further provide Doppler velocity, terminal velocity and vertical air motion inside clouds. ATLID standalone algorithms produce aerosol, cloud and clear sky classification products as well as total aerosol extinction and extinction and number concentration of each aerosol types. ATLID-MSI synergy algorithms are developed to retrieve effective radius for each aerosol species in addition to the ATLID-only products. MSI algorithms retrieve cloud effective radius, ice and water content and cloud top pressure. Four sensor algorithms are prepared to produce shortwave and longwave radiative fluxes at the top of atmosphere, those at the surface and also heating rate profiles by using the outputs from CPR, ATLID and their synergy algorithms. The shortwave and longwave fluxes from the four sensor algorithms will then be compared with broad band radiation (BBR) to examine the consistency of the JAXA L2 retrievals. The algorithms are developed and evaluated by using observational data from satellites and ground-based instruments, and simulation data from the Japanese global cloud-resolving model, the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) with Joint simulator. As for space-borne data, existing space-borne satellites data such as CloudSat, CALIPSO, MODIS and CERES datasets are intensively used. For ground-based observations, High-sensitivity Ground-based Super Polarimetric Ice-crystal Detection and Explication Radar (HG-SPIDER) with a minimum sensitivity of -40 dBZ at 15 km and over -60 dBZ at 1 km, Electronic Scanning SPIDER (ES-SPIDER), 355 nm high spectral resolution lidar, multiple-field-of-view multiple scattering lidar and Doppler lidars are installed at EarthCARE super-site in Koganei, Tokyo and offers unique opportunities to evaluate and analyse EarthCARE data. [ABSTRACT FROM AUTHOR]

Space targets move in orbit at a very high speed, so in order to obtain high-quality imaging, high-speed motion compensation (HSMC) and translational motion compensation (TMC) are required. HSMC and TMC are usually adjacent, and the residual error of HSMC will reduce the accuracy of TMC. At the same time, under the condition of low signal-to-noise ratio (SNR), the accuracy of HSMC and TMC will also decrease, which brings challenges to high-quality ISAR imaging. Therefore, this paper proposes a joint ISAR motion compensation algorithm based on entropy minimization under low-SNR conditions. Firstly, the motion of the space target is analyzed, and the echo signal model is obtained. Then, the motion of the space target is modeled as a high-order polynomial, and a parameterized joint compensation model of high-speed motion and translational motion is established. Finally, taking the image entropy after joint motion compensation as the objective function, the red-tailed hawk–Nelder–Mead (RTH-NM) algorithm is used to estimate the target motion parameters, and the joint compensation is carried out. The experimental results of simulation data and real data verify the effectiveness and robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]