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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]

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.

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]

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]

This paper explores the spatio-temporal rhythms in Sofia Kovalevskaya’s literary writings. Renowned as the first woman professor of mathematics in modern Europe, Kovalevskaya made significant scientific contributions but also excelled in literature, producing novels, poetry, and plays. She believed that great mathematicians must possess “the soul of a poet.” Despite the acclaim her literary work received, most research has focused on her mathematical achievements. As a cosmopolitan figure of her era, Kovalevskaya’s life spanned diverse geographies—born in Russia, studying in Germany, living in Paris, and eventually settling in Sweden as a professor at Stockholm University. These spatial and temporal dimensions deeply influenced her literary narratives. This paper employs narrative rhythmanalysis to trace the flows, forces, and energies within her writings, highlighting the interplay of space, time, and matter in literary creation. Far from offering final conclusions, this approach reveals a dynamic process, continually uncovering new insights into Kovalevskaya’s life, works, and worlds. [ABSTRACT FROM AUTHOR]

Target detection is a core function of integrated sensing and communication (ISAC) systems. The traditional likelihood ratio test (LRT) target detection algorithm performs inadequately under low signal-to-noise ratio (SNR) conditions, and the performance of mainstream orthogonal frequency division multiplexing (OFDM) waveforms declines sharply in high-speed scenarios. To address these issues, an information-theory-based orthogonal time frequency space (OTFS)-ISAC target detection processing framework is proposed. This framework adopts the OTFS waveform as its fundamental signal. The target detection is implemented through a relative entropy test (RET) comparing echo signals against target presence/absence hypotheses. Furthermore, to enhance the system's target detection capability, the iterative OTFS-ISAC waveform design (I-OTFS-WD) method which maximizes the relative entropy is proposed. This method utilizes the minorization-maximization (MM) algorithm framework and semidefinite relaxation (SDR) technique to transform the non-convex optimization problem into an iterative convex optimization problem for resolution. The simulation results demonstrate that, under sufficient sample conditions, the RET algorithm achieves a 9.12-fold performance improvement over LRT in low-SNR scenarios; additionally, the optimized waveform reduces the sample requirements of the RET algorithm by 40%, further enhancing the target detection capability of the OTFS-ISAC system. [ABSTRACT FROM AUTHOR]

Background: Poor quality of life in adults with anorexia nervosa (AN) and persistent high rates of readmission highlight the necessity of developing interventions to optimize treatment outcomes. ECHOMANTRA is a novel online intervention based on interventions for carers (Experienced Carers Helping Others, ECHO) and patients (Maudsley Model of Anorexia Nervosa Treatment for Adults, MANTRA) with anorexia nervosa. The objective of this paper is to describe the study protocol of a randomized control trial (RCT) aimed at evaluating the efficacy of an adaptation of the ECHOMANTRA for adults AN inpatients and outpatients, and their carers, to be implemented as an add-on to treatment-as-usual (TAU). Methods: In a multi − center pilot randomized controlled trial (RCT), 148 adult AN patients, and their carers, will be randomized to receive treatment as usual (TAU) or TAU plus ECHOMANTRA. Assessments will take place at baseline (T0), post-intervention (2-month) (T1), 6-month follow-up (T2), and 12-month follow-up (T3). Primary outcomes will be eating disorder psychopathology and psychological well-being. For carers, outcome variables will include psychological well-being, accommodation and enabling behaviors, expressed emotion, illness burden, quality of life and care skills. Discussion: This study will provide evidence of the efficacy of this novel, online and protocolized intervention in facilitating the recovery of these patients. Trial registration: ISRCTN registry (Identifier: 80253157 https://doi.org/10.1186/ISRCTN80253157). [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]

In view of the low detection accuracy of magnetostrictive displacement sensor, a calculation model of output voltage of magnetostrictive displacement sensor considering skin effect is proposed in this study. On the baisis of explaining the working principle of the magnetostrictive displacement sensor, the influence of skin depth is analyzed, and the Wiedemann effect and piezomagnetic effect are considered for theoretical analysis. The relationship between the excitation pulse current and the output voltage of the magnetostrictive displacement sensor is simulated by the skin depth generated by the excitation pulse signal acting on the waveguide wire at different frequencies. The optimal parameter value of excitation pulse current frequency is obtained using the experimental platform. Simulation experiments verify that the correctness of the output voltage model of the magnetostrictive displacement sensor considering the skin effect, indicating that the proposed model further improves the detection accuracy of the magnetostrictive displacement sensor and enriches the mathematical model. [ABSTRACT FROM AUTHOR]

As a contactless and non-invasive tool, ground penetrating radar (GPR) plays an important role in buried object detection. However, the performance of GPR images is deteriorated severely due to the clutter in radar echo signals, including echoes reflected from ground-air surface and other undesired signals. Low-rank sparse decomposition (LRSD) has been proved to be an effective tool to separate clutter and targets as low-rank and sparse components respectively. However, the properties of targets in images cannot be fully represented by sparsity. To combine LRSD with characters of target images, a robust principal component analysis combined with top-hat transform (RPCA-THT) is proposed. RPCA-THT optimizes the step of shrinking the sparse component in robust principal component analysis (RPCA). It performs a top-hat transform on the sparse component with a specially designed kernel matrix. Then the sparse component shrinks according to the normalized top-hat transform of the sparse matrix. In this way, targets prefer to be left in the sparse component than clutter. We design a well-performed kernel for distinguishing targets in the sparse matrix. The experimental results on simulation and real data show that the proposed method has better performance than several state-of-the-art clutter suppression algorithms. [ABSTRACT FROM AUTHOR]

Sounds are heard, sometimes even felt, but in most cases they remain unseen. This ephemeral and invisible nature of sound was already considered a problem when the science of acoustics took form in the seventeenth century. The fact that sound could not be seen was described as a significant hindrance to its understanding. But it was precisely during this time that a wide variety of sounds attracted broad scientific attention across Europe. Scholars, natural philosophers, and mathematicians investigated and experimented with sound and musical instruments and developed theories of hearing. This article looks at the role of images, diagrams, and visualization techniques in late seventeenth-century acoustics, bringing together the history of sound and the history of scientific images. Focusing on water and light as the dominant analogies for sound, the article demonstrates that visualization was an important tool for thinking about sound and allowed for the circulation of theories and experiments. At the same time, the epistemic status of these images remained contested, as there was no single model that could explain the different ways sound behaves as it moves through space and that could be visualized. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study presents a novel defect detection system that combines transformer technology with ultrasonic synchronous rotation in drum shafts. Based on electromagnetic induction, a piezoelectric sensor is driven by the transformer’s secondary pulse signal to enable synchronised transmission of both transformer and ultrasonic guided waves as the drum shaft rotates. This integration improves the accuracy and reliability of defect detection. The design process centres on optimising transformer coupling efficiency, ultrasonic guided wave propagation, and synchronisation mechanisms to achieve high-resolution imaging and real-time monitoring in an easy-to-operate system. The results indicate that the system effectively detects defects by analysing echo signals, locating defects through time differences, and functions well within rotating equipment. [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]

In order to improve the temperature detection ability of municipal asphalt pavement in high-temperature weather, a method to extract the temperature distribution characteristics of municipal asphalt pavement in high-temperature weather under the constraint of compaction quality was proposed. Using a digital image system, laser profiler, and ground penetrating radar system, collect construction temperature data of urban asphalt pavement under the constraints of compaction quality under high-temperature weather conditions, and use time series analysis to reconstruct the data. Combined with the nondestructive detection method of ground penetrating radar, the echo analysis model of temperature information is established, and the characteristics of temperature distribution are reconstructed using the spectral analysis method. The time–frequency transformation method is used to transform the time series of construction temperature under the constraint of compaction quality. The discrete signal window method was used to analyse the temperature characteristics of construction. According to the characteristic state monitoring, the temperature distribution characteristics are extracted. The test results show that the method is reliable in extracting the temperature distribution characteristics of municipal asphalt pavement construction under high-temperature weather and improves the real-time monitoring capability of asphalt pavement temperature. [ABSTRACT FROM AUTHOR]

In contrast to the ideal 3D display for meteorological radar, there is no 3D mode in the military engineering field. How to realise the 2D and 3D display for general radar terminal efficiently using the local graphics processing unit (GPU), which is impossible to realise with the traditional method of field programmable gate array now, has became an important research direction. In this paper, based on the radar echo equation, elevation was used to describe the three‐dimensional echo. After the three‐dimensional echo data model was built, the shader method with framebuffer objects was employed to display the data, while the data was capped by peripheral component interconnect express using direct memory access. It was designed to display the Plan Position Indicator and the attenuation of radar images with the 2D and 3D shaders. A series of numerical simulations were conducted to avoid image tear or lag. Compared to the methods of graphics device interface and the blend of images, the programmable pipeline of GPU performs well and is suitable for the display of radar terminal. [ABSTRACT FROM AUTHOR]

In modern aquaculture, accurate and efficient fish counting is crucial for the optimization of resource management and the enhancement of production profitability. Acoustic methods, known for their low energy consumption and extensive detection range, are widely utilized for underwater fish counting. However, traditional acoustic echo methods heavily rely on prior knowledge of fish schools and specific distribution models, leading to complexity and limited adaptability in practical applications. This paper introduces a fish-counting approach that integrates spatial sensing with temporal information. Initially, a spatial sensing matrix is constructed using ultrasonic Frequency-Modulated Continuous Wave (FMCW) technology, which facilitates the extraction of multidimensional features from fish echoes and reduces reliance on prior knowledge of fish schools. Subsequently, temporal information is extracted from echo signals using a Long Short-Term Memory (LSTM) network model, preventing missed detections caused by obstructions in single fish echoes during echo sessions. Finally, by fusing spatial and temporal feature information and employing a data-driven approach, we achieve fish counting while avoiding potential issues arising from improper selection of statistical distribution models. Tests on real fish datasets show that our proposed method consistently outperforms conventional statistical echo methods across all metrics, demonstrating its effectiveness in accurate fish counting. [ABSTRACT FROM AUTHOR]

The velocity/distance trade-off poses a fundamental challenge in pulsed Doppler weather radar systems and is known as the velocity/distance dilemma. Techniques such as multiple-pulse repetition frequency, staggered pulse repetition time (PRT), and pulse phase coding are commonly used to mitigate this issue. The current study evaluates the adaptability/capability of a specific type of low-capture signal called the non-uniform PRT (NPRT) through analyzing the weather target characteristics of typical velocity distributions. The spectral moments estimation (SME) signal-processing algorithm of the NPRT weather echo is designed to calculate the average power, velocity, and spectrum width of the target. A comprehensive error analysis is conducted to ascertain the efficacy of the NPRT processing algorithm under influencing factors. The results demonstrate that the spectral parameters of weather target echo with a velocity of [ − 50 , 50 ] m/s through random-jitter NPRT signals align with radar functionality requirements (RFRs). Notably, the NPRT waveform resolves the inherent conflicts between the maximum unambiguous distance and velocity and elevates the upper limit of the maximal observation velocity. The evaluation results confirm that nonlinear radar signal processing technology can improve a radar's detection performance and provide a new method for realizing the multifunctional observation of radar in different applications. [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]

Oil recovery in shale reservoirs is low due to the dynamics and wettability characteristics in mixed-wet shale oil reservoirs. Nuclear magnetic resonance (NMR) logging, a nondestructive and noninvasive technique, effectively evaluates the continuous dynamics and wettability in these reservoirs. The NMR numerical investigation can characterize the effects of dynamics and wettability, including varying wet regions and wet angles, on NMR responses, providing new insights into the frequency-dependent of T2-based petrophysical parameters. The NMR relaxation theory for mixed-wet shale oil reservoirs was proposed, and the relevant parameters were determined. The dynamics and wettability were characterized using the Shan Chen Lattice Boltzmann method, with constraints based on digital core technology. For the first time, the random walk method was employed to simulate the effects of water-wet regions with varying proportions, echo spacings, and wet angles on NMR responses in mixed-wet shale oil reservoirs at different frequencies. The proportions of water-wet regions, magnetic field frequencies, and echo spacings significantly influence porosity and T2LM, indicating that pore structure governs the dynamics and wettability and that petrophysical parameters can be characterized by their frequency dependence in mixed-wet shale oil reservoirs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Measurement Science & Instrumentation is the property of Journal of Measurement Science & Instrumentation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Deep-water reverberation caused by multiple reflections from the seafloor and sea surface can affect the performance of active sonars. To detect a moving target under reverberation conditions, a reverberation suppression method using multipath Doppler shift in deep water and wideband ambiguity function (WAF) is proposed. Firstly, the multipath Doppler factors in the deep-water direct zone are analyzed, and they are introduced into the target scattered sound field to obtain the echo of the moving target. The mesh method is used to simulate the deep-water reverberation waveform in time domain. Then, a simulation model for an active sonar based on the source and short vertical line array is established. Reverberation and target echo in the received signal can be separated in the Doppler shift domain of the WAF. The multipath Doppler shifts in the echo are used to estimate the multipath arrival angles, which can be used for target localization. The simulation model and the reverberation suppression detection method can provide theoretical support and a technical reference for the active detection of moving targets in deep water. [ABSTRACT FROM AUTHOR]

Traditional LiDAR and air-medium-based single-photon LiDAR struggle to perform effectively in high-scattering environments. The laser beams are subject to severe medium absorption and multiple scattering phenomena in such conditions, greatly limiting the maximum operational range and imaging quality of the system. The high sensitivity and high temporal resolution of single-photon LiDAR enable high-resolution depth information acquisition under limited illumination power, making it highly suitable for operation in environments with extremely poor visibility. In this study, we focus on the data distribution characteristics of active single-photon LiDAR operating underwater, without relying on time-consuming deep learning frameworks. By leveraging the differences in time-domain distribution between noise and echo signals, as well as the hidden spatial information among echo signals from different pixels, we rapidly obtain imaging results across various distances and attenuation coefficients. We have experimentally verified that the proposed spatial sequential matching enhanced (SSME) algorithm can effectively enhance the reconstruction quality of reflection intensity maps and depth maps in strong scattering underwater environments. Through additional experiments, we demonstrated the algorithm's reconstruction effect on different geometric shapes and the system's resolution at different distances. This rapidly implementable reconstruction algorithm provides a convenient way for researchers to preview data during underwater single-photon LiDAR studies. [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]

Abstract Background Building capacity for evidence-based treatment and support for people with substance use disorders (SUD) is an urgent priority in the context of the toxic drug poisoning crisis. We implemented the first substance use-focused Project Extension for Community Healthcare Outcomes (ECHO) in Western Canada for health care providers, to enhance their clinical addiction skills and knowledge, facilitate practice change, and foster a supportive community of practice. The aims of this article are to describe our innovations to the Project ECHO model in British Columbia (BC) and Yukon, and present key program outcomes. Methods A pragmatic multi-methods program evaluation employed observational records of BC ECHO on Substance Use session attendance, cross-sectional and longitudinal participant surveys, and qualitative interviews with participants to assess satisfaction, relevance, and preparation to use evidence-based approaches, practice change intentions, and actual behaviours. Results The 52 ECHO sessions (from June 2019 to July 2022) attracted 2134 unique registrants with 5089 attendances (mean 124/session), 2132 newsletter subscribers, and 5842 podcast downloads. The evaluation included 844 post-session survey respondents and 53 interview participants. The program included ECHO sessions with rolling attendance; widely accessed supplemental formats (e.g., newsletter, podcast, clinical tools, archived presentation recordings); variable, regional hub representation; and evidence-based content developed by medical writers. These features contributed to broad geographic and discipline reach, high-quality program content, and high mean session satisfaction ratings (4.2/5). Key qualitative themes emerged, related to knowledge and skill acquisition, gaining confidence in providing SUD care, facilitating shared decision-making, increasing compassion for patients, consolidating learning and applying it to practice, and reducing isolation through expanded networks. Conclusions The ECHO model is an effective way to improve capacity in SUD care for physicians and nurse practitioners, while offering benefits for interprofessional attendees. Our findings can inform innovations in other ECHO programs to enhance reach, engagement, and impact.

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.

Due to the long-term effects of wind and wave corrosion and hydraulic erosion on underwater structures, various degrees of damage such as cracks, holes, and corrosion may occur. When underwater attachments cause lift off disturbances, various interference signals are introduced, increasing the difficulty of defect detection. In order to maintain the safety and stability of reinforced concrete structures in underwater tunnels in a timely manner, a defect detection method for reinforced concrete structures in underwater tunnels based on ultrasonic echo signals and the CNN is proposed. The collection method and formation mechanism of ultrasonic echo signals for reinforced concrete structures in underwater tunnels are analyzed first. After obtaining the ultrasonic echo signals, noise is removed from the signals through empirical mode decomposition and the sparse table algorithm. An ultrasonic defect detection model for concrete structures based on the multi-attention FasterRCNN structure is constructed, the denoised ultrasonic echo signal is input into the model, the multi-attention mechanism is applied to extract the characteristics of the ultrasonic echo signal, and a balanced feature pyramid network is used to achieve feature fusion. The fused features are generated into defect candidate boxes through regional generation networks, and defect position information and category information are output at the fully connected layer of the model to complete defect detection of reinforced concrete structures in underwater tunnels. The experimental results show that this method can accurately remove noise from the echo signal of reinforced concrete structures and shows high denoising performance. When conducting defect detection, it can quickly detect the defect category and position, and provide the defect depth and diameter. The detection results are accurate and do not show significant errors. [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]

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]

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]

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]

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]

Anomalous left coronary artery from the pulmonary artery (ALCAPA), a rare congenital heart anomaly, typically manifests with heart failure symptoms in infants and carries a high mortality rate without surgical intervention. Patients are categorized into adult and infantile types based on collateral presence, impacting cardiovascular risk. Interestingly, some patients may remain asymptomatic for decades due to adequate collateral development, with a decreasing risk of sudden death as they reach adulthood. Management of asymptomatic cases requires individualized consideration and diagnostic confirmation before intervention, despite decreasing risk of sudden death with age. We report a case involving a 35-year-old asymptomatic woman who came for a routine annual check-up. While her electrocardiography, ECHO was normal, a positive Treadmill stress test prompted coronary angiography, revealing an incidental diagnosis of ALCAPA. Subsequently, the patient was referred to cardiothoracic and vascular surgery for further evaluation and necessary interventions, but the patient denied surgery as she did not accept the risk in view of asymptomatic status. [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]

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]

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]

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]