Wave Peak Research Articles

How sea ice affects edge waves in the Sea of Okhotsk

Long-term observations, which were collected in the Sea of Okhotsk coastal zone under open-water conditions and at times when the sea was ice-covered from mid-January to mid-March 2022, are interpreted. The project augments preceding work using three synchronously-recording, seafloor-mounted, pressure transducers sampling at 1 Hz to acquire time series of inshore wave oscillations. Units are deployed nearer to the shore and closer together than was done during the previous studies. Spectral analyses of open-water sea level oscillations perpendicular to the coast reveal a wide band of energy, suggestive of a propagating edge wave at about 5-min period with an offshore-to-inshore gain up to 1.5. Similar wave characteristics occur alongshore. Intriguingly, the peak edge wave period at 5 min migrates to 6–7 min when the sea becomes covered with ice, and narrower bands at periods from 0.5 to about 3 min emerge. Other period ranges also appear to be affected by the onset, presence and eventual disintegration of sea ice. Whilst a shift of the dominant edge wave period can be attributed to changes in spectral refraction arising from the incoming swells being low-pass filtered by sea ice, because of the observed tidal signal it is speculated in this case that the observed period adjustment and attendant expansion of bandwidth may also be associated with instability around the fundamental frequency. The potential for edge wave solitons to exist is explored.

Measurement of pressure dependent variations in local pulse wave velocity within a cardiac cycle from forward travelling pulse waves

The local pulse wave velocity (PWV) from large elastic arteries and its pressure-dependent changes within a cardiac cycle are potential biomarkers for cardiovascular risk stratification. However, pulse wave reflections can impair the accuracy of local PWV measurements. We propose a method to measure pressure-dependent variations in local PWV while minimizing the influence of pulse wave reflections. The PWV is computed from the pulse transit time between two forward-traveling pulse waveforms obtained across known path length, after measured/modelled flow-based wave separation analysis (WSA). An in-vivo study of 60 participants (24 female), was conducted to compare inter- and intra-cycle variations in PWV obtained from measured and forward pulse waves. For this, proximal and distal diameter waveforms from the carotid artery, along with carotid tonometry, were recorded using a custom bi-modal arterial probe. The carotid blood flow for WSA was captured with an ultrasound imaging system. The reference PWV was derived from the Bramwell-Hill equation. After WSA, the reliability of PWV measurement improved with coefficient of variation reducing from 25% to 10% near the peak of the pulse waves and matched the reference PWV with no statistically significant difference. The average PWV at foot of the pulse wave before and after WSA were comparable to the reference PWV with no statistically significant difference. The coherence of carotid pulse pressure obtained from the mean values of PWV within a cardiac cycle after WSA with that of the carotid pulse pressure from tonometry, substantiates the results obtained for reflection-free PWV. The reliability of measuring local PWV and its pressure dependent variations within a cardiac cycle is improved by combining transit-time approach with WSA.

Trends in Pediatric Procedural Cancellations Before and During the COVID-19 Pandemic

INTRODUCTION The COVID-19 pandemic led to significant, widespread impacts on surgical care for pediatric patients.1-3 As key agencies recommended delaying non-urgent cases after declaration of the pandemic, pre-hospital procedure cancellations became common.4 Expectedly, peak waves of COVID-19 infections were associated with a decrease in overall surgical volume.1,3 While most cancellations occurred prior to scheduled procedure date, same day procedure cancellations (SDCs) persisted. These SDCs affected children whose time-sensitive care was intentionally sanctioned despite the global health crisis; procedure cancellations, especially those same day, are likewise known to represent significant financial, emotional and employment burdens on patient families.5,6 Understanding that a sustained increase in SDCs would magnify these negative effects on patients and families, we sought to describe the impact of COVID-19 on SDC incidence, with a focus on SDCs due to acute illness, in pediatric patients during the pre-pandemic, early, and late waves at an urban, tertiary children’s hospital.

Estimating the two consecutive epidemic waves of SARS-CoV-2 Omicron in Shenzhen, China from November 2022 to July 2023: a modeling study based on multi-source surveillance and mobility data

Unlike many countries that have experienced multiple COVID-19 waves since January 2020, China’s stringent measures left most of the population without natural immunity to SARS-CoV-2. After lifting controls, China experienced two distinct Omicron waves from November 2022 to July 2023. However, no reliable study has yet elucidated the transmission dynamics of these two consecutive Omicron waves in China’s megacities, nor the phenomenon of reinfection due to immune escape. To address this gap, this study proposes a hybrid epidemic modeling framework based on multi-source surveillance and mobility data, including nucleic acid tests, wastewater surveillance, case reports from Notifiable Infectious Diseases Surveillance System of China (NIDSS), and intra-urban travel intensity data. In this hybrid modeling framework, a four-stage compartmental model stratified by age is developed, integrating human mobility and Omicron reinfection mechanisms. This model is further corrected by an agent-based model to address the overestimation of infections by the compartmental model, forming a comprehensive hybrid framework. Based on the simulation results, several new findings are drawn. The attack rate of the first wave in Shenzhen was 88.5% (95% confidence interval (CI): 72.1%-99.6%), lower than other models’ predictions. The peak of the second wave occurred on May 18, 2023, with a higher reinfection rate compared to those observed in other countries and regions. The effective reproduction number (Rt) for the first wave peaked at 5.44 (95% CI: 5.26-5.48), while for the second wave, the initial Rt was 1.28 (95% CI: 1.27-1.29). The first infections provide a 0.549 (95% CI: 0.544-0.554) protective effect against XBB reinfection within six months. In conlusion, this study presents an advanced modeling framework for accurately assessing epidemic spread in urban environments using multi-source surveillance data.

Association of Total Mortality and Cardiovascular Endpoints With the Timing of the First and Second Systolic Peak of the Aortic Pulse Wave.

Prognostic significance of the timing in the cardiac cycle of the first (TP1) and second (TP2) systolic peak of the central aortic pulse wave is ill-defined. Incidence rates and standardized multivariable-adjusted hazard ratios (HRs) of adverse health outcomes associated with TP1 and TP2, estimated by the SphygmoCor software, were assessed in the International Database of Central Arterial Properties for Risk Stratification (IDCARS) (n = 5529). Model refinement was assessed by the integrated discrimination (ID) and net reclassification (NR) improvement. Over 4.1 years (median), 201 participants died and 248 and 159 patients experienced cardiovascular or cardiac endpoints. Mean TP1 and TP2, standardized for cohort, sex, age, and heart rate, were 103 and 228ms. Shorter TP1 and TP2 were associated with higher mortality and shorter TP1 with a higher risk of cardiovascular and cardiac endpoints (trend p ≤ 0.004). The HRs relating total mortality and cardiovascular endpoints to TP2 were 0.82 (95% confidence interval [CI]: 0.72-0.94) and 0.87 (0.77-0.98), respectively. The HR relating cardiac endpoints to TP1 was 0.81 (0.68-0.97). For total mortality and cardiovascular endpoints in relation to TP2, NRI was significant (p ≤ 0.010), but not for cardiac endpoints in relation to TP1. Integrated discrimination improvement (IDI) was not significant for any endpoint. The HRs relating total mortality to TP2 were smaller (p ≤ 0.026) in women than men (0.67vs. 0.95) and in older (≥ 60 years) versus younger (< 60 years) participants (0.80vs. 0.88). Our study adds to the evidence supporting risk stratification based on aortic pulse analysis by showing that TP2 and TP1 carry prognostic information.

Prediction of mortality and prioritisation to tertiary care using the 'OUR-ARCad' risk score gleaned from the second wave of COVID-19 pandemic-A retrospective cohort study from South India.

Judicious utilisation of tertiary care facilities through appropriate risk stratification assumes priority, in a raging pandemic, of the nature of delta variant-predominated second wave of COVID-19 pandemic in India. Prioritisation of tertiary care, through a scientifically validated risk score, would maximise recovery without compromising individual safety, but importantly without straining the health system. De-identified data of COVID-19 confirmed patients admitted to a tertiary care hospital in South India, between April 1, 2021 and July 31, 2021, corresponding to the peak of COVID-19 second wave, were analysed after segregating into 'survivors' or 'non-survivors' to evaluate the risk factors for COVID-19 mortality at admission and formulate a risk score with easily obtainable but clinically relevant parameters for accurate patient triaging. The predictive ability was ascertained by the area under the receiver operator characteristics (AUROC) and the goodness of fit by the Hosmer-Lemeshow test and validated using the bootstrap method. Of 617 COVID-19 patients (325 survivors, 292 non-survivors), treated as per prevailing national guidelines, with a slight male predilection (358/617 [58.0%]), fatalities in the age group above and below 50 years were (217/380 [57.1%]) and (75/237 [31.6%]), p<0.001. The relative distribution of the various parameters among survivors and non-survivors including self-reported comorbidities helped to derive the individual risk scores from parameters significant in the multivariable logistic regression. The 'OUR-ARCad' risk score components were-Oxygen saturation SaO2<94%-23, Urea > 40mg/dL-15, Neutrophil/Lymphocytic ratio >3-23, Age > 50 years-8, Pulse Rate >100-8 and Coronary Artery disease-15. A summated score above 50, mandated tertiary care management (sensitivity-90%, specificity-75%; AUC-0.89), validated in 2000 bootstrap dataset. The OUR-ARCad risk score, could potentially maximize recovery in a raging COVID-19 pandemic, through prioritisation of tertiary care services, neither straining the health system nor compromising patient's safety, delivering and diverting care to those who needed the most.

Propagation characteristics of stable detonation waves in curved channels with the lateral expansion effect

When a stable detonation wave propagates in a curved channel, it will be influenced by the curvature of the channel, which has been investigated in previous studies. Actually, propagation of a stable detonation wave in a curved channel becomes more unstable if the lateral expansion effect is introduced. However, this is an objective phenomenon in practical rotating detonation chambers. In order to clarify the impacts of the channel curvature and the lateral expansion on the propagation of stable detonation waves, this study has been carried out using a mixture of ethylene, oxygen, and nitrogen. The effects of the channel curvature, the detonable mixture height, and the equivalence ratio on the propagation characteristics in both confined and semi-confined curved channels have been focused in this experimental work. The propagation process was recorded by high-speed photography, and the cell width was obtained using the smoke visualization method, while the peak pressures near the outer wall were also measured. The results imply that the deficits of wave velocity and peak pressure are magnified when introducing the lateral expansion phenomenon, especially under fuel-lean and fuel-rich conditions. Meanwhile, the channel curvature and the mixture height also have a great impact on the detonation propagation. Five propagation modes have been observed after the stable detonation waves enter the curved channels with a semi-confined configuration, i.e., a stable mode, a critical mode, a weakly unstable mode, a highly unstable mode, and a deflagration mode. In addition, for the two observed unstable modes, decoupling occurs periodically near the inner wall. Finally, the critical conditions of the stable detonation mode in the semi-confined channel have been clarified. The critical inner radius should be 13.10–15.24 times of the average cell width, and meanwhile, the minimum detonable mixture height is equivalent to 7.03–8.12 times of the average cell width.

Electrocardiographic indicators of atrial fibrillation in obstructive sleep apnea syndrome: a retrospective analysis of P wave peak time

Aims: Obstructive sleep apnea syndrome (OSAS) is a sleep-related breathing disorder characterized by hypopnea and apnea. Atrial fibrillation (AF) is an arrhythmia frequently encountered in cardiology practice, with concomitant heart disease and an increasing incidence with age. OSAS and AF are closely related as they have similar etiological risk factors and common pathophysiological processes such as inflammation, oxidative cellular damage, and autonomic nervous system dysregulation. P-wave peak time (PWPT) is the time from the beginning of the P-wave to its peak and is a recently defined electrocardiographic (ECG) parameter. Studies on the relationship between PWPT and cardiovascular events have been published recently. In this study, we aimed to evaluate the risk of AF in OSAS patients by determining a new ECG parameter, PWPT. Methods: 52 OSAS patients and 41 healthy individuals as a control group were included in the study. The groups were compared in terms of demographic characteristics, laboratory findings, echocardiography and ECG findings. D2 and V1 leads were used for PWPT as recommended in the literature. Results: When the patient group was compared with the control group, no difference was found in terms of demographic characteristics and laboratory findings. Compared with the control group, OSAS patients had significantly longer PWPT (PWPTV1 55.05msn ± 7.18 msn vs 48.91 msn ± 7.08 msn, p&lt;.01, PWPTD2 54.13 msn ± 5.60 msn vs 46.20 msn ± 6.94 msn, p&lt;.01). Conclusion: We observed that PWPT was longer in OSAS patients than in controls, and our results suggest that OSAS patients are at risk of AF.

Experimental Study on the Changes to the Microstructures and Dynamic Mechanical Properties of Layered Sandstone After High-Temperature Treatment

In this study, changes in the basic physical properties, mineral composition, mass, and microstructure of layered sandstone were evaluated following heat treatment at 200–800 °C. Dynamic impact compression tests were performed using a split-Hopkinson pressure bar test system (SHPB), and digital image correlation (DIC) was used to monitor the dynamic failure processes of the involved specimens. Results indicate that high-temperature treatment reduces the mass, wave velocity and peak stress of layered sandstone; increases the porosity, pore length, and pore aperture. The rates of decrease in the wave velocity and peak stress considerably increase with increasing temperature above a threshold of 400 °C. This is because at temperatures above 400 °C, thermal cracks will form both between and within particles. As the number of cracks increases, they will propagate and connect with each other, forming a network of cracks. DIC results show that as the heat treatment temperature rises, the range of the strain-concentration areas, which are formed by sandstone failures, substantially expands. However, the increase in the heat treatment temperature only negligibly influences the propagation direction of primary sandstone cracks, which mainly propagate along the weak bedding planes.

Leveraging Transcriptional Signatures of Diverse Stressors for Bumble Bee Conservation.

Organisms in nature are subjected to a variety of stressors, often simultaneously. Foremost among stressors of key pollinators are pathogens, poor nutrition and climate change. Landscape transcriptomics can be used to decipher the relative role of stressors, provided there are unique signatures of stress that can be reliably detected in field specimens. In this study, we identify biomarkers of bumble bee (Bombus impatiens) responses to key stressors by first subjecting bees to various short-term stressors (cold, heat, nutrition and pathogen challenge) in a laboratory setting and assessing their transcriptome responses. Using random forest classification on this whole transcriptome data, we were able to discriminate each stressor. Our best model (tissue-specific model trained on a subset of important genes) correctly predicted known stressors with 92% accuracy. We then applied this random forest model to wild-caught bumble bees sampled across a heatwave event at two sites in central Pennsylvania, US, expected to differ in baseline temperature and floral resource availability. Transcriptomes of bees sampled during the heat wave's peak showed signatures of heat stress, while bees collected in the relatively cooler morning periods showed signatures of starvation and cold stress. We failed to pick up on signals of heat stress shortly after the heatwave, suggesting this set of biomarkers is more useful for identifying acute stressors than long-term monitoring of chronic, landscape-level stressors. We highlight future directions to fine-tune landscape transcriptomics towards the development of better stress biomarkers that can be used both for conservation and improving understanding of stressor impacts on bees.

From laminar to chaotic flow via stochastic resonance in viscoelastic channel flow

Recent research indicates that low-inertia viscoelastic channel flow experiences supercritical nonnormal mode elastic instability from laminar to sustained chaotic flow due to finite-size perturbations. The challenge of this paper is to elucidate a realization of such a pathway when the intensity of the elastic wave is too low to amplify vortex fluctuations above the instability onset. The study identifies two subregions in the transition flow regime at Weissenberg number Wi&gt;Wic, the instability onset. In the lower subregion at Wic≤Wi≤300, we discover periodic spikes in the streamwise velocity time series u(t) that appear in the chaotic power spectrum as low-frequency, high-intensity peaks resembling stochastic resonance (SR). In contrast, the spanwise velocity power spectrum, Ew, remains flat and with low-intensity, noisy, and broad elastic wave peaks. The spikes significantly distort the probability density function of u and initiate and amplify random streaks and wall-normal vorticity fluctuations. The condition for the SR emergence is similar to that of a dynamical system where the presence of a chaotic attractor, limit cycle, and external white noise are necessary. This similarity is confirmed by presenting a phase portrait in two subregions of the transition regime. In the upper subregion at Wi&gt;400, the periodic spikes disappear and Ew becomes chaotic with a large intensity elastic wave sufficient to self-organize and synchronize the streaks into cycles and to amplify the wall normal vorticity, according to a recently proposed mechanism of vortex-wave interactions. Published by the American Physical Society 2024

Using unmanned aerial systems for observations of water wave characteristics

Dominant wave components within a wavefield play key hydrodynamic and morphodynamic processes. Herein, we present a method to detect and measure the parameters of these waves, such as their wavelength, propagation angle and period. Image sequences of the free surface are captured with the use of a commercial unmanned aerial system. A snapshot proper orthogonal decomposition analysis is then applied to the image sequence, and a 2D autocorrelation is performed on the resulting modes. By extracting the mode that is representative of the dominant wave signal, it is then possible to infer the wave properties of the dominant wave. The outlined procedure is applied to ocean swells, wind waves, free surface undulations along a river and propagating ship wakes. Our results demonstrate an improvement in the signal-to-noise ratio of the peak wave signal to ambient noise over the more widely used fast Fourier transform approach.

Domain wall networks from first-order phase transitions and gravitational waves

In the first-order phase transitions (PTs) colliding bubble is an important gravitational wave (GW) source. Following bubble collision, domain walls can be formed when degenerate vacua occur as a result of the spontaneous breaking of a discrete symmetry relevant to new physics at electroweak or higher scales. Using lattice simulations, we study the dynamical evolution of domain walls and find that the networks of the domain wall are formed around the completion of PTs and quickly collapse before entering into the scaling regime provide that the degeneracy of true vacua is broken. Our numerical results indicate that domain wall networks continue to produce GWs in the aftermath of PTs, leading to dramatically changing the spectral shape and enhancing the magnitude by about one order. The resulting GW power spectra are peaked at kR*≃π as predicted by the envelop approximation model, above the peak wave number it has a decaying power law close to k−1.2 followed by a slowly decreasing plateau with the UV cutoff at kR*∼O(102). Published by the American Physical Society 2024

Development of a Wave Model Component in the First Coupled Global Ensemble Forecast System at NOAA

Abstract We describe the development of the wave component in the first global-scale coupled operational forecast system using the Unified Forecasting System (UFS) at the National Oceanic and Atmospheric Administration (NOAA), part of the U.S. National Weather Service (NWS) operational forecasting suite. The operational implementation of the atmosphere–wave coupled Global Ensemble Forecast System, version 12 (GEFSv12), in September 2020 was a critical step in NOAA’s transition to the broader community-based UFS framework. GEFSv12 represents a significant advancement, extending forecast ranges and empowering the NWS to deliver advanced weather predictions with extended lead times for high-impact events. The integration of a coupled wave component with higher spatial and temporal resolution and optimized physics parameterizations notably enhanced forecast skill and predictability, particularly benefiting winter storm predictions of wave heights and peak wave periods. This successful endeavor encountered challenges that were addressed by the simultaneous development of new features that enhanced wave model forecast skill and product quality and facilitated by a multidisciplinary team collaborating with NOAA’s operational forecasting centers. The GEFSv12 upgrade marks a pivotal shift in NOAA’s global forecasting capabilities, setting a new standard in wave prediction. We also describe the coupled GEFSv12-Wave component impacts on NOAA operational forecasts and ongoing experimental enhancements, which altogether represent a substantial contribution to NOAA’s transition to the fully coupled UFS framework.

Genomic Diversity and Evolution of Identified SARS-CoV-2 Variants in Iraq

The COVID-19 pandemic caused by the SARS-CoV-2 virus continues to circulate worldwide, causing the deaths of millions of people. The continuous circulation of the virus, its genetic diversity, the emergence of new variants with increased transmissibility, and/or the capacity of the virus to escape from the immune system constitute a major public health concern. In our study, we aimed to characterize SARS-CoV-2 strains in Iraq from the first introduction until the end of 2023, and to identify their variants, lineages, clades, and mutation patterns. All published Iraqi full genome sequences (2020–2023) were obtained from Global Initiative on Sharing All Influenza Data (GISAID) and subjected to molecular characterization along with 19 samples of full genome sequences that were collected during the fifth and sixth waves of the SARS-CoV-2 pandemic in this study. Next-generation sequencing was performed using an Illumina MiSeq system, and phylogenetic analysis was performed for all the Iraqi sequences. Three established global platforms, GISAID, Nextstrain, and PANGO, were used for the classification of isolates into distinct clades, variants, and lineages. Six wave peaks of COVID-19 cases have been identified in Iraq, resulting in approximately 2,400,000 cumulative confirmed cases and more than 25,000 deaths. Our study revealed patterns of circulation and dominance of SARS-CoV-2 clades and their lineages in the pandemic waves in the country.

The Posterior Dominant Rhythm Remains Within Normal Limits in the Microgravity Environment.

Electroencephalogram (EEG) biomarkers with adequate sensitivity and specificity to reflect the brain's health status can become indispensable for health monitoring during prolonged missions in space. The objective of our study was to assess whether the basic features of the posterior dominant rhythm (PDR) change under microgravity conditions compared to earth-based scalp EEG recordings. Three crew members during the 16-day AXIOM-1 mission to the International Space Station (ISS), underwent scalp EEG recordings before, during, and after the mission by means of a dry-electrode self-donning headgear designed to support long-term EEG recordings in space. Resting-state recordings were performed with eyes open and closed during relaxed wakefulness. The electrodes representative of EEG activity in each occipital lobe were used, and consecutive PDR oscillations were identified during periods of eye closure. In turn, cursor-based markers were placed at the negative peak of each sinusoidal wave of the PDR. Waveform averaging and time-frequency analysis were performed for all PDR samples for the respective pre-mission, mission, and post-mission EEGs. No significant differences were found in the mean frequency of the PDR in any of the crew subjects between their EEG on the ISS and their pre- or post-mission EEG on ground level. The PDR oscillations varied over a ±1Hz standard deviation range. Similarly, no significant differences were found in PDR's power spectral density. Our study shows that the spectral features of the PDR remain within normal limits in a short exposure to the microgravity environment, with its frequency manifesting within an acceptable ±1 Hz variation from the pre-mission mean. Further investigations for EEG features and markers reflecting the human brain neurophysiology during space missions are required.

Study on the influence of submergence depth on the hydrodynamic and wave load characteristics of semi-submersible structures induced by a solitary wave

The submergence depth directly affects the safety of semi-submersible marine structures due to that the submergence depth significantly impacts on the hydrodynamic characteristics and wave loads of structures excited by extreme wave. This paper studies the influence of submergence depth on the hydrodynamic and wave load characteristics of semi-submersible structures by establishing a numerical model of the interaction between solitary waves and semi-submersible structures based on the SPH model and Rayleigh theory. Furthermore, equations for transmission coefficient, reflection coefficient, and wave load are fitted. The calculated wave heights of solitary wave propagation test case are in good agreement with the theoretical values. The maximum relative error of the wave peak is 8.4%. The calculated wave loads of submerged horizontal plates test case has a consistent trend with the experimental data. The maximum relative error of wave load peak and valley is 54% (absolute error 0.37 N). Furthermore, the interaction between solitary waves and structures with different submergence depths is investigated by using the meshless numerical model. It is found that the reflection coefficient first increases and then decreases with increasing submergence depth, and reaching a maximum value of 0.39 at the submergence depth equal to 0.0 m. On the contrary, the transmission coefficient decreases first and then increases with the increase of submergence depth. The minimum value of transmission coefficient is 0.36 with the submergence depth of 0.3 m. As the submergence depth increased, the horizontal wave load peak of the structure gradually increases, and the maximum value of 0.13 is obtained at the submergence depth of 0.7 m. The peak of vertical wave load rapidly increases with the increase of submergence depth and then gradually decreases while the trough gradually decreases with increasing submergence depth.

Evaluation of Internal Microscale Evolution of Electrochemical Devices Based on Elastic-Wave-Based Testing Methods

Nondestructive Testing (NDT) methods provide scientists a way to understand the properties of samples without causing them damage. For an electrochemical device, it is crucial to investigate the behavior of it before, during, and after its operation. Therefore, NDT methods are indispensable for studying such devices.Literature highlights the effectiveness of elastic-wave-based testing methods in the evaluation of electrochemical devices. The Acoustic Emission (AE) method was applied to respectively study the behavior of Solid Oxide Fuel Cells (SOFCs) and Ni-MH batteries, while the Ultrasonic Testing (UT) method was applied to study Li-ion batteries. In our previous research, the signals representing cracking and delamination in SOFCs were successfully distinguished by their peak amplitude, wave shape, and AE energy [1]. The same technique was further used for the evaluation of mechanical damages in SOFCs during the operation [2]. In another study, similarly, the pulverization of the Ni-MH battery electrodes was observed by the AE technique, and frequency peak property was included in the discussion to classify the signals [3]. The UT method was employed to study the relationship between the state of charge of Li-ion batteries and the profiles of ultrasonic waves at different frequencies. The evolution of wave velocity, attenuation, and amplitude were discussed [4]. Based on these researches, elastic-wave-based testing methods are adopted by us.In our present study, the multi-frequencies in-situ ultrasonic monitoring technique was employed to analyze the behavior of the commercial Ni-MH batteries during the operation. Continuous ultrasonic waves at three different frequencies were separately sent into the specimens during charge cycles, and their waveforms were recorded and compared. Specific wave patterns were found near the end of the charge and discharge state, especially from the wave profiles at 750 KHz. The result showed that the evolution of waveform is frequency-dependent, which was also suggested in the literature [4]. Potential explanations for these wave patterns were inferred, including phenomena such as crystal structure evolution, internal pressure shift, and reverse of electrodes.Based on this finding, a new ultrasonic testing/monitoring method considering frequency analysis is also designed. In this new method, signals consisting of elastic waves at a wide range of frequencies with equal intensities are designed to be applied to various electrochemical devices. The application of this method will be included, while the frequency-dependent property of the testing of electrochemical devices will be assessed in combination with the present findings in this study.

Evolution of coastal transgressive aeolian sand sheets over 75 years (1948-2023) at Concheiros Barrier - Southern Brazilian coast

Transgressive sand sheets (TSS) and transgressive dunefields (TDf) over time often present multiple phases of development and various morphologies controlled by biogeomorphological interactions related to abiotic processes, vegetation, and human interference. While dunefields have experienced increased vegetation cover over the last decades worldwide, a few places have shown increased dune mobility. In this study, a GIS analysis was conducted using aerial photographs and satellite imagery to investigate the evolution of a TDf, foredune collapse, new TSS formation, and vegetation cover on a Holocene coastal barrier in southern Brazil over the last 75 years (from 1948 to 2023). Wind speed (1994–2009), significant wave height (Hs) and peak wave period (Tp) (1940–2022) were analyzed to examine these potential drivers that could have caused geomorphological changes on the foredunes and dune system. Vegetation cover exhibited an increasing trend, and both an increase and decrease in TDf movement and TSS expansion were concurrent. Correlation analyses revealed a strong negative correlation between vegetation cover and TDf movement. Three transgressive sand sheet formation phases were identified between 1948 and 2023 (1964 to 1975,1996 to 2000, and from 2010 until 2023). Post-2003, a poorly vegetated nebkha-dominated foredune subsequently collapsed and was replaced by a TSS in less than a decade, being fully formed in 2010 and continuing to move inland at rapid rates. In the third phase, the highest total TSS expansion exceeded 700 m in 12 years (from 2010 to 2022). A small increase in wind velocity and subsequent decrease may possibly have contributed to the formation of the TSS second phase and the foredunes respectively. Other possible drivers for TSS formation include climatic modes, negative precipitation anomalies and groundwater level lowering, in addition to anthropogenic actions (especially water extraction) that might have caused a negative feedback in foredune sand-biding vegetation.

CNN Intelligent diagnosis method for bearing incipient faint faults based on adaptive stochastic resonance-wave peak cross correlation sliding sampling

As a representative of deep learning networks, convolutional neural networks (CNN) have been widely used in bearing fault diagnosis with good results. However, the signal length and segmentation of the input CNN can have a significant impact on diagnostic accuracy. In addition, the signal-to-noise ratio of early bearing faults is usually very low, which makes it difficult for traditional CNNs to accurately identify and classify these faults. To solve this problem, this paper proposes an adaptive stochastic resonance wave peak cross-correlation sliding sampling method. Firstly, the adaptive stochastic resonance is used to reduce the noise of the original signal, and then the data is divided from the position of the signal wave peak, the correlation coefficient between the divided signals is calculated, and the maximum value is found to determine the size of the division window. Finally, it is converted into a 2D image by Gramian Angular Field and input into CNN for diagnostic classification. The design methodology was validated using the Case Western Reserve University bearing dataset. Subsequently, three validation strategies were established on a self-built platform, including mixed diagnosis of 10 different bearing states, variable speed diagnosis, and low sampling data diagnosis. The proposed method outperforms the conventional CNN by 10 % in the Case Western Reserve University dataset test set. The variable speed test set is 24.67 % and 31.17 % higher, respectively. It is 30 % higher in low sampling data diagnosis.