Search

A LoRa self‐jamming scheme that enables secure and covert communications by adding jamming symbols when transmitting is proposed. The scheme has been validated in simulations. The work is continued by evaluating the scheme on real‐world software defined radio (SDR) equipment. Experiments immediately showed that a demodulation is impossible as the received signal is highly distorted. This comes from the fact that adding symbols at transmission actually generates high peak‐to‐average power ratio (PAPR) preventing proper waveform generation by the equipment's hardware. This paper presents a PAPR correction scheme that modifies the waveform. The properties of this modified waveform are analysed and the performances are assessed in simulations with realistic time and frequency synchronization assumption. For the ideal 0 dB PAPR corrected output, the SER performances are close to that of a legacy LoRa communication, while preserving the physical layer security capabilities of the self‐jamming scheme. It is finally shown that our PAPR correction scheme effectively recovers the self‐jamming properties on SDR devices. [ABSTRACT FROM AUTHOR]

Background: Enhancing venous return during cardiopulmonary resuscitation (CPR) can lead to better hemodynamics and improved outcome after cardiac arrest (CA). Peripheral Intravenous Analysis (PIVA) provides feedback on venous flow changes and may indicate an increase in venous return and cardiac output during CPR. We hypothesize PIVA can serve as an early indicator of increased venous return, preceding end-tidal CO2 (etCO2) increase, before the return of spontaneous circulation (ROSC) in a rat model of CA and CPR. Results: Eight male Wistar rats were intubated and ventilated, and etCO2 was measured. Vessels were cannulated in the tail vein, femoral vein, femoral artery, and central venous and connected to pressure transducers. Ventilation was discontinued to achieve asphyxial CA. After 8 min, CPR began with ventilation, epinephrine, and automated chest compressions 200 times per minute until mean arterial pressure increased to 120 mmHg. Waveforms were recorded and analyzed. PIVA was calculated using a Fourier transformation of venous waveforms. Data are mean ± SE. Maximum PIVA values occurred in the tail vein 34.7 ± 2.9 s before ROSC, with subsequent PIVA peaks in femoral vein and centrally at 30.9 ± 5.4 and 25.1 ± 5.0 s, respectively. All PIVA peaks preceded etCO2 increase (21.5 ± 3.2 s before ROSC). Conclusion: PIVA consistently detected venous pressure changes prior to changes in etCO2. This suggests that PIVA has the potential to serve as an important indicator of venous return and cardiac output during CPR, and also as a predictor of ROSC. [ABSTRACT FROM AUTHOR]

Abstract The design of waveforms plays a critical role in integrated sensing and communication (ISAC) systems. An ISAC waveform with a 0dB peak‐to‐average power ratio (PAPR) is designed by combining a Golay complementary sequence with a constant envelope orthogonal frequency‐division multiplexing. By adjusting the phase modulation parameters, this waveform allows for a trade‐offs between communication and sensing capabilities. The authors focus on several key performance metrics for the proposed ISAC waveform, notably using mutual information as a holistic performance indicator to assess both sensing and communication effectiveness. Through extensive numerical simulations, the authors demonstrate that the ISAC waveform significantly enhances detection probability compared to traditional phase‐modulated waveforms. The findings suggest that this approach is beneficial for designing low PAPR phase‐modulated ISAC waveforms, enhancing both the functionality and efficiency of ISAC systems.

The design of waveforms plays a critical role in integrated sensing and communication (ISAC) systems. An ISAC waveform with a 0dB peak‐to‐average power ratio (PAPR) is designed by combining a Golay complementary sequence with a constant envelope orthogonal frequency‐division multiplexing. By adjusting the phase modulation parameters, this waveform allows for a trade‐offs between communication and sensing capabilities. The authors focus on several key performance metrics for the proposed ISAC waveform, notably using mutual information as a holistic performance indicator to assess both sensing and communication effectiveness. Through extensive numerical simulations, the authors demonstrate that the ISAC waveform significantly enhances detection probability compared to traditional phase‐modulated waveforms. The findings suggest that this approach is beneficial for designing low PAPR phase‐modulated ISAC waveforms, enhancing both the functionality and efficiency of ISAC systems. [ABSTRACT FROM AUTHOR]

In this letter, we address the problem of designing the joint waveform of radar detection, wireless communication and jamming. In the current most powerful filter‐bank multi‐carrier comb spectrum framework, a parameter‐agile time–frequency structure between symbols is elaborated to improve the uncertainty of waveform generation architecture. Furthermore, a novel composite modulation strategy that combines intra‐symbol chaos‐based radar frequency modulation and inter‐symbol chaos‐based phase modulation is proposed for a substantial jamming performance improvement. Simulation results verify that the proposed joint waveform produces a superior jamming performance while satisfying the requirements of radar detection and wireless communication. [ABSTRACT FROM AUTHOR]

Highlights The objective of this paper is to analyze the mechanical properties and damage mechanisms of carbon fiber‐reinforced polyamide thermoplastic composite laminates. Four specimens with different ply orientations were designed for open‐hole tensile experiments, and interlaminar toughness experiments including double cantilever beam and end‐notched flexural were carried out. The experimental process was monitored synchronously using acoustic emission, and the strain field changes of the tensile specimens were captured using digital image correlation technology. The unsupervised clustering of the peak frequencies of the acoustic emission signals based on the K‐means++ algorithm was employed to ascertain the peak frequency ranges corresponding to the various damage modes. Typical signals from different specimens were selected, and the gray wolf algorithm was used to optimize the variational modal parameters to decompose the signals. The waveform characteristics, frequency components, and Hilbert spectra of each damage mode were given. The correlation analysis of the intrinsic mode function (IMF) components of the same damage in different specimens demonstrated that the IMF components exhibited high similarity. By analyzing the time series changes in the energy of each damage mode in different specimens, the contribution of different damage modes to the evolution of laminated plate damage was evaluated. The mechanical properties of CF/PA6 laminates were investigated based on open‐hole tensile specimens and pre‐cracked delamination specimens. Unsupervised clustering of AE peak frequencies using K‐means++ to establish the relationship between peak frequencies and damage patterns. AE counts and cumulative energy were used to assess damage evolution. By identifying a single damage signal and providing a more intuitive treatment of the damage energy evolution. [ABSTRACT FROM AUTHOR]

Pipelines extend thousands of kilometers to transport and distribute oil and gas. Given the challenges often faced with corrosion, fatigue, and other issues in steel pipes, the demand for glass fiber-reinforced plastic (GFRP) pipes is increasing in oil and gas gathering and transmission systems. However, the medium that is transported through these pipelines contains multiple acid gases such as CO2 and H2S, as well as ions including Cl−, Ca2+, Mg2+, SO42−, CO32−, and HCO3−. These substances can cause a series of problems, such as aging, debonding, delamination, and fracture. In this study, a series of aging damage experiments were conducted on V-shaped defect GFRP pipes with depths of 2 mm and 5 mm. The aging and failure of GFRP were studied under the combined effects of external force and acidic solution using acoustic emission (AE) techniques. It was found that the acidic aging solution promoted matrix damage, fiber/matrix desorption, and delamination damage in GFRP pipes over a short period. However, the overall aging effect was relatively weak. Based on the experimental data, the SSA-LSSVM algorithm was proposed and applied to the damage pattern recognition of GFRP. An average recognition rate of up to 90% was achieved, indicating that this method is highly suitable for analyzing AE signals related to GFRP damage. [ABSTRACT FROM AUTHOR]

Introduction: Central aortic pressure waveform analyses can provide clinically relevant information beyond conventional brachial blood pressure (BP) assessment. This waveform can be reproduced noninvasively through application of a generalized transfer function (GTF) on a peripheral waveform, as conventionally performed by applanation tonometry. Photoplethysmography (PPG) is an alternate approach; however, differences in measurement site and modality demand the use of a transfer function (TF) specific for those differences. This study aimed to compare central aortic waveform features generated from radial tonometry (reference) using a proprietary GTF with a central aortic waveform and its features generated from a simultaneous fingertip PPG measurement using a selective method where one of three different TFs is chosen based on the input signal harmonic profile. Methods: Brachial BP was measured in triplicate under resting conditions and was used for subsequent calibration. Multiple simultaneous radial tonometry (SphygmoCor CVMS) and fingertip PPG measurements were then performed in individual participants (n = 21, 10 females, age: 39 ± 16 years). Measurements were converted into central aortic waveforms with their respective TFs. Twenty central aortic pressure waveform parameters were compared through correlation analysis, Bland-Altman plots, and a repeated measure mixed-effects ANOVA model. Central aortic waveform shape was compared using the root-mean-squared error (RMSE). Results: Correlation (r) of PPG-derived parameters with radially tonometry-derived central aortic parameters was high ranging from 0.79 to 0.99. Mean differences of pressure-related parameters were within 1.3 mm Hg, and differences of time-related parameters ranged from −2.2 to 3.4%. While some parameters were statistically different, these differences are not physiologically meaningful. Central aortic waveform shape had an average RMSE of 1.8 ± 0.9%. Conclusion: Fingertip PPG-derived central aortic waveform parameters using a novel selective TF were comparable to central aortic waveform features derived from radial tonometry using a previously validated GTF.

Abstract Background The interaction between the patient and the ventilator is often disturbed, resulting in patient-ventilator asynchrony (PVA). Asynchrony can lead to respiratory failure, increased artificial ventilation time, prolonged hospitalization, and escalated healthcare costs. Professionals’ knowledge regarding waveform analysis has significant implications for improving patient outcomes and minimizing ventilation-related adverse events. Studies investigating the knowledge of healthcare professionals on patient-ventilator asynchrony and its associated factors in the Ethiopian context are limited. Therefore, this study aimed to assess the knowledge of healthcare professionals about using waveform analysis to detect asynchrony. Methods A multicenter cross-sectional study was conducted on 237 healthcare professionals (HCPs) working in the intensive care units (ICUs) of federal public hospitals in Addis Ababa, Ethiopia, from December 2022 to May 2023. The data were collected using a structured and pretested interviewer-administered questionnaire. Then, the collected data were cleaned, coded, and entered into Epi data V-4.2.2 and exported to SPSS V-27 for analysis. After description, associations were analyzed using binary logistic regression. Variables with a P-value of

Background: The interaction between the patient and the ventilator is often disturbed, resulting in patient-ventilator asynchrony (PVA). Asynchrony can lead to respiratory failure, increased artificial ventilation time, prolonged hospitalization, and escalated healthcare costs. Professionals' knowledge regarding waveform analysis has significant implications for improving patient outcomes and minimizing ventilation-related adverse events. Studies investigating the knowledge of healthcare professionals on patient-ventilator asynchrony and its associated factors in the Ethiopian context are limited. Therefore, this study aimed to assess the knowledge of healthcare professionals about using waveform analysis to detect asynchrony. Methods: A multicenter cross-sectional study was conducted on 237 healthcare professionals (HCPs) working in the intensive care units (ICUs) of federal public hospitals in Addis Ababa, Ethiopia, from December 2022 to May 2023. The data were collected using a structured and pretested interviewer-administered questionnaire. Then, the collected data were cleaned, coded, and entered into Epi data V-4.2.2 and exported to SPSS V-27 for analysis. After description, associations were analyzed using binary logistic regression. Variables with a P-value of < 0.25 in the bivariable analysis were transferred to the multivariable analysis. Statistical significance was declared using 95% confidence intervals, and the strengths of associations were reported using adjusted odds ratios (AORs). Results: A total of 237 HCPs participated in the study with a response rate of 100%. Half (49.8%) of the participants were females. The mean age of the participants was 29 years (SD = 3.57). Overall, 10.5% (95% CI: 6.9–15.2) of the participants had good knowledge of detecting PVA using waveform analysis. In the logistic regression, the number of MV-specific trainings and the training site had a statistically significant association with knowledge of HCPs. HCPs who attended more frequent MV training were more likely to have good knowledge than their counterparts [AOR = 6.88 (95% CI: 2.61–15.45)]. Additionally, the odds of good knowledge among professionals who attended offsite training were 2.6 times higher than those among professionals trained onsite [AOR = 2.63 (95% CI: 1.36–7.98)]. Conclusion: The knowledge of ICU healthcare professionals about the identification of PVA using waveform analysis is low. In addition, the study also showed that attending offsite MV training and repeated MV training sessions were independently associated with good knowledge. Consequently, the study findings magnify the relevance of providing frequent and specific training sessions focused on waveform analysis to boost the knowledge of HCPs. [ABSTRACT FROM AUTHOR]

Mechanical insufflation-exsufflation (MI-E) is essential for secretion clearance, especially in neuromuscular disorders. For the best outcomes, initiation of MI-E should be started at the correct time with regular evaluation to the response to treatment. Typically, cough peak flow has been used to evaluate cough effectiveness with and without MI-E. This review highlights the limitations of this and discussed other tools to evaluate MI-E efficacy in this rapidly developing field. Such tools include the interpretation of parameters (like pressure, flow and volumes) that derive from the MI-E device and external methods to evaluate upper airway closure. In this review we pinpoint the differences between different devices in the market and discuss new tools to better titrate MI-E and detect pathological responses of the upper airway. We discuss the importance of point of care ultrasound (POCUS), transnasal fiberoptic laryngoscopy and wave form analysis in this setting. To improve clinical practice newer generation MI-E devices should allow real-time evaluation of waveforms and standardize some of the derived parameters. [ABSTRACT FROM AUTHOR]

The most common source of transformer failure is in the insulation, and the most prevalent warning signal for insulation weakness is partial discharge (PD). Locating the positions of these partial discharges would help repair the transformer to prevent failures. This work investigates algorithms that could be deployed to locate the position of a PD event using data from ultra-high frequency (UHF) sensors inside the transformer. These algorithms typically proceed in two steps: first determining the signal arrival time, and then locating the position based on time differences. This paper reviews available methods for each task and then propose new algorithms: a convolutional iterative filter with thresholding (CIFT) to determine the signal arrival time and a reference table of travel times to resolve the source location. The effectiveness of these algorithms are tested with a set of laboratory-triggered PD events and two sets of simulated PD events inside transformers in production use. Tests show the new approach provides more accurate locations than the best-known data analysis algorithms, and the difference is particularly large, 3.7X, when the signal sources are far from sensors.

Currently, theoretical analysis of single‐phase grounding (SPG) faults in low‐current grounding systems has reached a high level of refinement, and the corresponding detection methods have matured. However, there is a significant lack of research on successive grounding (SG) faults, particularly in the area of detecting cross‐line same‐phase successive grounding (CSSG) faults in arc suppression coil grounding systems. To address these issues, a novel faulty line detection method based on transient characteristics of CSSG is proposed. Firstly, a transient equivalent circuit is established, and the characteristics of transient zero‐sequence current (ZSC) are theoretically analysed. Secondly, variational mode decomposition (VMD) is employed to extract low and high‐frequency information from intrinsic mode functions (IMFs). Subsequently, a fault initiation criterion based on kurtosis theory and the Teager‐Kaiser energy operator (TKEO) is proposed, which can accurately detect the occurrence time of secondary faults. Finally, a method for faulty line detection based on cross‐correlation distance (CCD) and transient energy (TE) is proposed. The results of PSCAD simulation under different conditions and field test affirm the accuracy of the analysis and the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With the gradual extension of mining operations into deeper levels, minor rock burst phenomena have emerged, posing risks of instability in mining pillars and roof caving induced by rock bursts within the production area. Based on the actual geological conditions of deep ore bodies and surrounding rocks in Sanshandao Gold Mine, a new generation of microseismic monitoring system has been developed, in order to establish a mine early warning system. This system can effectively monitor faint seismic signals associated with the instability of mining pillars and roof caving in the mining area, analyze microseismic waveforms, and detect occurrences of rock burst events, providing basis for the safe mining of deep rock mass. [ABSTRACT FROM AUTHOR]

Currently, pulsed adders are used as pulsed voltage sources maturely. However, their use as pulsed current sources is significantly limited due to circuit impedance and the characteristics of power devices. This paper presents a simple yet effective design for a pulsed current source, incorporating a solid-state Marx pulsed adder as the primary power source and an inductor for energy storage. In the pulsed current source, a Marx pulsed adder produces high voltage to charge the inductor. Then, the stored inductance energy is converted to generate current pulses on the load; the amplitude of the pulsed current is unaffected by the load impedance within a certain range. The pulsed current source can be designed as a standard module, and several modules can form a cascade system for producing current pulses with higher voltage. Finally, a pulsed current source was developed, which can produce adjustable current pulses with high voltage. The design principles, control methods and the effects of the distribution parameters are described. The feasibility of the cascade pulsed power system was validated in experiments. Nine modules were connected to generate pulses of current 10 A on a 15 kΩ resistor. [ABSTRACT FROM AUTHOR]

BACKGROUND: Improved patient-ventilator asynchrony (PVA) identification using waveform analysis by critical care physicians (CCPs) may improve patient outcomes. This study aimed to assess the ability of CCPs to identify different types of PVAs using waveform analysis as well as factors related to this ability. METHODS: We surveyed 12 university-affiliated medical ICUs (MICUs) in Tunisia. CCPs practicing in these MICUs were asked to visually identify 4 clinical cases, each corresponding to a different PVA. We collected the following characteristics regarding CCPs: scientific grade, years of experience, prior training in mechanical ventilation, prior exposure to waveform analysis, and the characteristics of the MICUs in which they practice. Respondents were categorized into 2 groups based on their ability to correctly identify PVAs (defined as the correct identification of at least 3 of the 4 PVA cases). Univariate analysis was performed to identify factors related to the correct identification of PVA. RESULTS: Among 136 included CCPs, 72 (52.9%) responded to the present survey. The respondents comprised 59 (81.9%) residents, and 13 (18.1%) senior physicians. Further, 50 (69.4%) respondents had attended prior training in mechanical ventilation. Moreover, 21 (29.2%) of the respondents could correctly identify PVAs. Double-triggering was the most frequently identified PVA type, 43 (59.7%), followed by auto-triggering, 36 (50%); premature cycling, 28 (38.9%); and ineffective efforts, 25 (34.7%). Univariate analysis indicated that senior physicians had a better ability to correctly identify PVAs than residents (7 [53.8%] vs 14 [23.7%], P = .044). CONCLUSIONS: The present study revealed a significant deficiency in the accurate visual identification of PVAs among CCPs in the MICUs. When compared to residents, senior physicians exhibited a notably superior aptitude for correctly recognizing PVAs. [ABSTRACT FROM AUTHOR]

Teleseismic shear-wave splitting analyses are often performed by reversing the splitting process through the application of frequency- or time-domain operations aimed at minimizing the transverse-component energy of waveforms. These operations yield two splitting parameters, ɸ (fast-axis orientation) and δt (delay time). In this study, we investigate the applicability of a baseline recurrent neural network, SWSNet, for determining the splitting parameters from pre-selected waveform windows. Due to the scarcity of sufficiently labelled real waveform data, we generate our own synthetic dataset to train the model. The model is capable of determining ɸ and δt with a root mean squared error (RMSE) of 9.7° and 0.14 s on a noisy synthetic test data. The application to real data involves a deconvolution step to homogenize the waveforms. When applied to data from the USArray dataset, the results exhibit similar patterns to those found in previous studies with mean absolute differences of 9.6° and 0.16 s in the calculation of ɸ and δt respectively.

Summary: By multiplying with the continuous factor (CF), the conventional Class‐ F/F−1, Class‐J power amplifier (PA) can be expanded to their corresponding continuous modes, resulting in a great degree of freedom for broadband design. However, this method can hardly apply to other types of PAs. In view of this problem, the continuous mode is deeply analyzed from the perspective of equation solving for the first time, and a general theory for high‐efficiency broadband continuous PA design is proposed. In this theory, the continuous impedance space does not rely on a mapping relationship achieved by multiplying with the CF, but on a direct solution of the high‐efficiency equations to obtain the broadband design space. This approach is simpler and has the potential to provide greater design space. As a validation, this theory is used for the analysis of Class‐E PAs and a new continuous Class‐E (NC‐E) PA is presented. With knee‐point voltage and finite harmonics taken into account, this type of PA greatly expands the broadband design space of Class‐E PAs and also has the advantage of harmonic matching. The NC‐E PA is designed and manufactured using GaN HEMT CGH40010F, which achieves 40.6–41.6 dBm output power and 66.2%–74.2% drain efficiency (DE) in the frequency band of 2.5–3.8 GHz. [ABSTRACT FROM AUTHOR]

Summary: Continuous mode provides better bandwidth performance and constant efficiency by offering greater design flexibility in fundamental and harmonics. However, this mode is mainly applicable to limited classes of power amplifiers (PAs) (such as Class‐F, Class‐J, and their derived types). In view of this problem, this paper proposes a general design theory for high‐efficiency broadband continuous PAs, which can easily extend any waveform of PAs to obtain the continuous impedance space. In theoretical analysis, first, the high‐efficiency equations are analyzed from the perspective of frequency domain. Furthermore, combining time domain constraints, a general continuous mode analysis and solution theory is presented. The theory is applied to the bandwidth expansion of Class‐EF PAs, resulting in a new continuous Class‐EF (C‐EF) mode that maintains constant efficiency while offering greater broadband design freedom. The proposed theory is verified by fabricating a C‐EF PA using GaN HEMT CGH40010F, which demonstrated output power (Pout) ranging from 39.5 to 41.2 dBm and drain efficiency (DE) of 69.5% to 79.2% in the frequency range of 2.5–3.6 GHz. [ABSTRACT FROM AUTHOR]

Intracranial pressure (ICP) burden or pressure time dose (PTD) is a valuable clinical indicator for pending intracranial hypertension, mostly based on threshold exceedance. Pulse frequency and waveform morphology (WFM) of the ICP signal contribute to PTD. The temporal resolution of the ICP signal has a great influence on PTD calculation but has not been systematically studied yet. Hence, the temporal resolution of the ICP signal on PTD calculation is investigated. We retrospectively analysed continuous 48 h ICP recordings with high temporal resolution obtained from 94 patients at the intensive care unit who underwent neurosurgery due to an intracranial haemorrhage and received an intracranial pressure probe (43 females, median age: 72 years, range: 23 to 88 years). The cumulative area under the curve above the threshold of 20 mmHg was compared for different temporal resolutions of the ICP signal (beat-to-beat, 1 s, 300 s, 1800 s, 3600 s). Events with prolonged ICP elevation were compared to those with few isolated threshold exceedances. PTD increased for lower temporal resolutions independent of WFM and frequency of threshold exceedance. PTDbeat-to-beat best reflected the impact of frequency of threshold exceedance and WFM. Events that could be distinguished in PTDbeat-to-beat became magnified more than 7-fold in PTD1s and more than 104 times in PTD1h, indicating an overestimation of PTD. PTD calculation should be standardised, and beat-by-beat PTD could serve as an easy-to-grasp indicator for the impact of frequency and WFM of ICP elevations on ICP burden. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the damage pattern recognition in carbon/epoxy composite laminates by Acoustic Emission technique. Three specimens with layup of [90/0/90/0]s were fabricated and subjected to three-point bending test. The dataset was clustered and analyzed by three unsupervised algorithms, namely, k -means, Self-Organizing Map, and Fuzzy C-Means. The results show that the signals can be divided into four clusters, which correspond to matrix cracking, delamination, fiber/matrix debonding, and fiber breakage, respectively. A method of energy feature extraction based on wavelet packet decomposition was used to analyze the clustering center to obtain the frequency band with relatively high energy corresponding each damage mode further determined the actual damage pattern of these signals with disputed classification results. The results of k -means illustrated that little difference in the determination of matrix cracking, preferring to assign more signal to inter-laminar damage and higher peak frequency to fiber breakage compared to the other two algorithms. It can verify the clustering results well and k -means algorithm performs better in damage pattern recognition of composites. [ABSTRACT FROM AUTHOR]

Compared to frequency bands below 6 GHz, 5G millimeter waves offer several advantages, including a large bandwidth, minimal null delay, and flexible null port configuration. To comprehend the channel characteristics of 5G millimeter-wave technology, conducting channel measurements on it is essential. Hence, to ensure precise 5G millimeter-wave channel measurements and facilitate channel modelling, this study recommends utilizing a phased array antenna-based method for channel measurement. The experimental outcomes demonstrated that the shadow fading term of the actual measurement data follows a normal distribution in both line-of-sight and non-line-of-sight scenarios. Additionally, the K-S test confirms that all Boolean variables are equal to 1 and all numerical variables are greater than a. The lineof-sight scenario produces a logarithmic mean delay extension of -7.4 and a standard deviation of 0.12, based on actual measured data. Meanwhile, 3GPP shows a logarithmic mean of -7.4 and a standard deviation of 0.15. In the non-line-of-sight scenario, the logarithmic mean delay extension is -7.3 with a standard deviation of 0.17, while 3GPP produces a logarithmic mean of -7.4 and a standard deviation of 0.19. The data presented closely adheres to the 3GPP model. It is evident that the channel measurement method, proposed within the study, effectively measures the parameters within the delay domain. Concerning the prolonged pitch angle and azimuth angle ranges, they measure 14°-31° and 14°-29° in the line-of-sight situation, and 21°-33° and 19°-37° in the corresponding non-line-of-sight situation. Additionally, the logarithmic mean and standard deviation for both the pitch angle and azimuth angle in the line-of-sight scenario are 1.32 and 0.09, respectively. The logarithmic mean and standard deviation of the azimuth angle of arrival are 1.35 and 0.08, respectively. The above results show that the method proposed in the study enables the measurement of 5G millimeter-wave channels and is important for millimeter-wave channel modelling. [ABSTRACT FROM AUTHOR]

Background: The F wave waveforms show diversity according to the number and size of re-firing cells, but there is still no analytical method that reflects this feature. We previously reported that five classifications of F waves are obtained from the ulnar nerve. However, the diversity of F waves derived from the lower extremities may not be similar. We therefore compared the diversity of F waves in the upper and lower extremities in healthy subjects. New method: F waves were measured during tibial nerve stimulation in 26 healthy subjects. The amount of amplitude decrease was calculated from the amplitude value after the additive averaging process and based on the average amplitude value of each stimulus, and the relationship between the peak latency and density was examined. Results: The amount of amplitude decrease due to the additive averaging process was negatively correlated with the density of negative peaks. The diversity of F waves could be categorized into four class based on the histograms. Comparison with existing method: The new method uses a novel additive average method that reflects the diversity of F waves. Furthermore, it uses a histogram to visualize the cancellation between waveforms. Conclusion: We developed an analysis method that reflects the diversity of F waves in a novel manner, which visualizes cancellation between waveforms using a histogram.

(1) Background: The activated partial thromboplastin time (APTT)- based clot waveform analysis (CWA) quantitatively extends information obtained from the APTT waveform through its derivatives. However, pre-analytical variables including reagent effects on the CWA parameters are poorly understood and must be standardized as a potential diagnostic assay. (2) Methods: CWA was first analysed with patient samples to understand reagent lot variation in three common APTT reagents: Pathromtin SL, Actin FS, and Actin FSL. A total of 1055 healthy volunteers were also recruited from seven institutions across the Asia-Pacific region and CWA data were collected with the Sysmex CS analysers. (3) Results: CWA parameters varied less than 10% between lots and the linear mixed model analysis showed few site-specific effects within the same reagent group. However, the CWA parameters were significantly different amongst all reagent groups and thus reagent-specific 95% reference intervals could be calculated using the nonparametric method. Post-hoc analysis showed some degree of influence by age and gender with weak correlation to the CWA (r < 0.3). (4) Conclusions: Reagent type significantly affects APTT-based CWA with minimal inter-laboratory variations with the same coagulometer series that allow for data pooling across laboratories with more evidence required for age- and gender-partitioning. [ABSTRACT FROM AUTHOR]

Chronic ankle instability (CAI) has been associated with frontal and sagittal plane kinematic differences compared to patients with no history of ankle sprain during landing tasks. Single plane kinematics are often statistically compared to identify group differences, however, the complex, multi-planar motions of the ankle allow for unique kinematic adaptations at the joint and univariate waveform analysis may be limited in the assessment of joint motion. Bivariate confidence interval analysis allows for statistical comparisons to be made when considering the simultaneous frontal and sagittal plane kinematics of the ankle. Can the bivariate confidence interval analysis identify unique joint coupling differences during a drop-vertical jump in patients with CAI? Subjects with CAI and matched healthy controls performed 15 drop-vertical jump maneuvers while kinematics were collected using an electromagnetic motion capture system. An imbedded forceplate was used to determine ground contact timing. Kinematics were analyzed using a bivariate confidence interval from 100 ms pre-ground contact to 200 ms post-ground contact. Any region where group confidence intervals did not overlap was considered statistically different. Prior to initial contact participants with CAI had greater plantar flexion from 6 ms to 21 ms and 36–63 ms prior to landing. After making ground contact differences were found from 92 ms to 101 ms and 113–122 ms. Greater plantar-flexion and eversion was identified in the patients with CAI prior to ground contact and following landing patients with CAI had greater inversion and plantarflexion compared to healthy controls. The bivariate analysis identified unique group differences compared to univariate analysis including group differences prior to landing. These unique findings indicate that comparing groups using a bivariate analysis may provide important information on the kinematic differences of patients with CAI and how multiple planes of motion compensate during dynamic landing tasks. • CI2 is a statistical technique that compares 2-dimensional waveforms. • Patients with CAI differed compared to controls during a drop vertical jump. • Bivariate comparison differed from previously reported univariate comparisons. • The bivariate waveform comparison should be considered in the kinematic analysis. [ABSTRACT FROM AUTHOR]

The extracellular waveform manifestations of the intracellular action potential are the quintessential diagnostic foundation of electrodiagnostic medicine, and clinical neurophysiology in general. Volume conduction is the extracellular current flow and associated voltage distributions in an ionic conducting media, such as occurs in the human body. Both surface and intramuscular electrodes, in association with contemporary digital electromyographic systems, permit very sensitive detection and visualization of this extracellular spontaneous, voluntary, and evoked nerve/muscle electrical activity. Waveform configuration, with its associated discharge rate/rhythm, permits the identification of normal and abnormal waveforms, thereby assisting in the diagnosis of nerve and muscle pathology. This monograph utilizes a simple model to explain the various waveforms that may be encountered. There are a limited number of waveforms capable of being generated in excitable tissues which conform to well‐known volume conductor concepts. Using these principles, such waveforms can be quickly identified in real time during clinical studies. [ABSTRACT FROM AUTHOR]

In this paper, a description, and analysis of a novel 3-D dimension hyperchaotic system is implemented. The proposed system oscillation is twoorder autonomous and consisted of a nine-term and symmetric oscillation w.r.t x-axis. It is proved analysis by Kaplan-York dimension, waveform analysis, phase portrait, and Lyapunov exponent. This work-study stability and equilibrium point and Routh stability criteria produced that the new system has one unstable point from the type saddle-focus point. One of the characteristics of the proposed system is hyperchaotic since this system has two Lyapunov large than zero. This system is applied to generate a chaotic matrix16∗16 (S-box) based in advanced encryption standard (AES) algorithm for text encryption and gives a high level of security. In addition to the description, and analysis S-box. Therefore. the proposed algorithm is satisfied the high randomness of entropy value and passes the National Institute of Standards and Technology (NIST) parameters and another test. Mathematica and MATLAB programs simulated some results. [ABSTRACT FROM AUTHOR]

Concerns raised by Okazaki & Ueda (2022) on the paper by Sambridge et al. (2022) are addressed. Two issues are discussed and some new numerical results presented. The first concerns whether the properties of the Wasserstein time-series misfit introduced in our earlier paper will translate to model space non-uniqueness in a seismic waveform inversion setting. It is argued that this is unlikely, given the special conditions, which must exist between all observed/predicted seismic waveform pairs for non-uniqueness to result. The second issue discussed is the efficacy of using the Sliced Wasserstein algorithm of Bonneel et al. (2015) as an alternate to the marginal Wasserstein algorithm, as proposed by Okazaki & Ueda (2022). It is argued that for optimization-based waveform fitting, the Sliced Wasserstein algorithm is a viable alternate provided care is taken to ensure that conditions arise which do invalidate analytical derivative expressions of the resulting Wasserstein misfit. In practice, this would likely mean recasting the 2D Optimal Transport problem posed in our earlier paper onto unstructured grids. [ABSTRACT FROM AUTHOR]

While Doppler resilient complementary waveforms (DRCWs) have previously been considered to suppress range sidelobes within a Doppler interval of interest in radar systems, their ability to provide Doppler resilience can be further improved. A new singular value decomposition (SVD)‐based DRCW construction is proposed, in which both transmit pulse trains (made up of complementary pairs) and receive pulse weights are jointly considered. Besides, using the proposed SVD‐based method, a theoretical bound is derived for the range sidelobes within the Doppler interval of interest. Moreover, based on the SVD solutions, a challenging non‐convex optimization problem is formulated and solved to maximise the signal‐to‐noise ratio (SNR) with the constraint of low range sidelobes. It is shown that, compared with existing DRCWs, the proposed SVD‐based DRCW has better Doppler resilience. Further, the new optimised SVD‐based DRCW has a higher SNR while maintaining the same Doppler resilience. [ABSTRACT FROM AUTHOR]

The island of São Miguel is among the most seismically active areas of the Azores archipelago. This work focuses on the most significant recent swarm, which occurred on February 2018. We set up an automated procedure to process continuous full seismic waveform data from local stations to generate high-quality earthquake information on the volcano unrest episode. First, we applied an automated detector software, next we located the detected events and then classified the earthquakes based on their waveform similarity, identifying three families of seismic events. We then extended the catalog by template matching. Finally, we computed moment tensors to investigate the source mechanisms of the largest earthquakes. Our results image the ∼2-week swarm evolution. The activity started with a precursory phase with low rate and low magnitude (ML < 2.0) seismicity and the activation of a deeper structure (∼10-15 km). After ∼1 week, a new earthquake family emerged at shallower depths (∼8–12 km) reaching magnitudes up to ML 3.4. Finally, a third slightly shallower family was activated. Moment tensors show mostly normal faulting mechanisms, striking ∼NW-SE, compatible with the orientation of the regional stress field. A surface deformation transient was recorded by geodetic stations, starting with the swarm, and continuing over the following ∼17 months, corresponding to either inflation or extension around the swarm region. The prolonged surface deformation implies a process that was initiated during the swarm and subsequently accommodated mostly aseismically. We interpret the seismicity observed at the early stage of deformation as indicating episodic fluid injection through the crust, related to the local hydrothermal or magmatic systems. We conclude that the Fogo-Congro region continues to be seismo-volcanically active, with both seismic and aseismic deformation observed and requiring close multidisciplinary monitoring. The proposed methology based on the automated analysis of continuous waveform data provides high-quality imaging of the spatio-temporal evolution of seismicity, which can be used elsewhere in the operational monitoring of seismo-volcanic crises to gain insight into the ongoing deformation processes, improve hazard assessment and help in the development of effective mitigation strategies.

Abstract While Doppler resilient complementary waveforms (DRCWs) have previously been considered to suppress range sidelobes within a Doppler interval of interest in radar systems, their ability to provide Doppler resilience can be further improved. A new singular value decomposition (SVD)‐based DRCW construction is proposed, in which both transmit pulse trains (made up of complementary pairs) and receive pulse weights are jointly considered. Besides, using the proposed SVD‐based method, a theoretical bound is derived for the range sidelobes within the Doppler interval of interest. Moreover, based on the SVD solutions, a challenging non‐convex optimization problem is formulated and solved to maximise the signal‐to‐noise ratio (SNR) with the constraint of low range sidelobes. It is shown that, compared with existing DRCWs, the proposed SVD‐based DRCW has better Doppler resilience. Further, the new optimised SVD‐based DRCW has a higher SNR while maintaining the same Doppler resilience.

Based on the extensive use prospect of acoustic emission technology in concrete damage detection, researches on acoustic emission analysis methods of concrete damage at home and abroad were analyzed. The sorting of acoustic emission analysis methods for concrete damage was focused on four aspects: characteristic parameter analysis of acoustic emission signal of concrete damage, waveform analysis of acoustic emission signal, concrete damage location analysis based on acoustic emission technology, and application of acoustic emission technology for concrete structure damage under fire. The research status of various acoustic emission analysis methods was introduced, and their technical characteristics and application scope were summarized. [ABSTRACT FROM AUTHOR]

Abstract Mutual interference between different radar waveforms used in automotive radar applications is studied. The existing interference analysis is extended to a generalised radar‐to‐radar interference equation that covers most of the common interference scenarios for automotive radar systems. The outcome of the generalised equation is demonstrated for a number of typical scenarios where radars with different continuously transmitting waveforms are involved. The proposed equation can be used to characterise the received interference and its features by analysing the instantaneous beat frequency of the victim radar. Moreover, an interference analysis of phase‐coded frequency‐modulated continuous waveforms is performed and demonstrated experimentally by using real‐time automotive radars for the first time in the literature. The experimental results corroborate the interference analysis of different waveforms and validate the proposed generalised interference equation under various conditions.

Abstract Inclination is one of the important parameters of a target’s surface, which is closely related to the waveform of light detection and ranging. When the target is tilted, the laser spot on the target’s surface changes greatly, and the influence of the target on the echo signal is more complex. Here, the formation process of a laser’s echo signal is explored. On that basis, the spot distribution model in the case of a large incident angle is optimised, and a comparison is made with the conventional method. A simulation system which can produce and display the signal affected by the inclined target is designed. In view of the difficulty in extracting the target's inclination from the echo signal, a method based on waveform analysis is proposed in this article. Then a calculation model is built to retrieve the inclination of the target from the echo signal by data fitting. The maximum measured error is only 0.948°, and the maximum root‐mean‐squared‐error is only 0.45°.

Summary: Background: Ventricular fibrillation (VF) waveform analysis has been proposed as a potential non-invasive guide to optimize timing of defibrillation. Methods: The AMplitude Spectrum Area (AMSA) trial is an open-label, multicenter randomized controlled study reporting the first in-human use of AMSA analysis in out-of-hospital cardiac arrest (OHCA). The primary efficacy endpoint was the termination of VF for an AMSA ≥ 15.5 mV-Hz. Adult shockable OHCAs randomly received either an AMSA-guided cardiopulmonary resuscitation (CPR) or a standard-CPR. Randomization and allocation to trial group were carried out centrally. In the AMSA-guided CPR, an initial AMSA ≥ 15.5 mV-Hz prompted for immediate defibrillation, while lower values favored chest compression (CC). After completion of the first 2-min CPR cycle, an AMSA < 6.5 mV-Hz deferred defibrillation in favor of an additional 2-min CPR cycle. AMSA was measured and displayed in real-time during CC pauses for ventilation with a modified defibrillator. Findings: The trial was early discontinued for low recruitment due to the COVID-19 pandemics. A total of 31 patients were recruited in 3 Italian cities, 19 in AMSA-CPR and 12 in standard-CPR, and included in the data analysis. No difference in primary outcome was observed between the two groups. Termination of VF occurred in 74% of patients in the AMSA-CPR compared to 75% in the standard CPR (OR 0.93 [95% CI 0.18–4.90]). No adverse events were reported. Interpretation: AMSA was used prospectively in human patients during ongoing CPR. In this small trial, an AMSA-guided defibrillation provided no evidence of an improvement in termination of VF. Trial registration: NCT03237910. Funding: European Commission - Horizon 2020; ZOLL Medical Corp., Chelmsford, USA (unrestricted grant); Italian Ministry of Health - Current research IRCCS.

BACKGROUND: Respiratory therapists (RTs) play a crucial role in managing mechanically ventilated patients, such as addressing patient-ventilator asynchronies that may contribute to patient harm. Waveform analysis is integral to the evaluation of patient-ventilator asynchronies; despite this, no published studies have assessed the ability of practicing RTs to interpret ventilator waveform abnormalities. METHODS: The study took place between June 2017-February 2019. Eighty-six RTs from 2 academic medical centers enrolled in a one-day mechanical ventilation course. The scores of 79 first-time attendees were included in the analysis. Prior to and following the course, RTs were asked to identify abnormalities on a 5-question, multiple-choice ventilator waveform exam. They were also asked to provide a self-assessment of their ventilator management skills on a 1 (complete novice) to 5 (expert) scale. RESULTS: Initial scores were low but improved after one day of ventilator instruction (19.4 ± 17.1 vs 29.6 ± 19.0, P < .001). No significant difference was noted in mean confidence levels between the pre- and post-course assessments (3.8 ± 0.9 vs 3.8 ± 1.0, P = .56). RTs with fewer years of clinical experience (0-10 y) had a statistically significant improvement in their post-course test scores relative to their pre-course scores (0-5 y: 12.5 ± 10.1 to 46.0 ± 10.8, P < .001; 6-10 y: 18.7 ± 15.8 to 32.1 ± 16.7, P = .02), whereas those with > 11 y of clinical experience did not (11-20 y: 22.4 ± 15.5 to 27.4 ± 19.0, P = .44; 21+ y: 19.6 ± 22.1 to 15.3 ± 13.8, P = .50). CONCLUSIONS: RTs may benefit from additional training in ventilator waveform interpretation, especially early in their clinical training. More work is needed to determine the optimal length and content of a mechanical ventilation curriculum for RTs. [ABSTRACT FROM AUTHOR]

Researchers have not established if overloading or underloading movement profiles are present in symptomatic and asymptomatic athletes with patellar tendon structural abnormality (PTA) compared with healthy athletes. To compare involved-limb landing biomechanics between male athletes with and those without patellar tendinopathy. Cross-sectional study. Laboratory. A total of 43 male athletes were grouped based on patellar tendon pain and ultrasound imaging of the proximal patellar tendon: symptomatic with PTA (SYM; n = 13; age = 19.62 ± 1.61 years, height = 1.82 ± 0.05 m, mass = 83.46 ± 5.12 kg), asymptomatic with PTA (ASYM; n = 15; age = 21.13 ± 1.88 years, height = 1.84 ± 0.07 m, mass = 81.45 ± 13.26 kg), and healthy control (CON; n = 15; age = 19.60 ± 1.55 years, height = 1.84 ± 0.09 m, mass = 79.09 ± 12.37 kg). Three-dimensional biomechanics were collected during a double-limb jump-landing task. Kinematic (knee-flexion angle [KF]) and kinetic (vertical ground reaction force, internal knee-extension moment [KEM], patellar tendon force [FPT]) variables were analyzed as continuous waveforms during the stance phase for the involved limb. Mean values were calculated for each 1% of stance, normalized over 202 data points (0%–100%), and plotted with 95% CIs. Statistical significance was defined as a lack of 95% CI overlap for a minimum of a consecutive 3% of the stance phase. The SYM group had less KF than the CON group throughout the stance phase (8%–76%: Cohen d = 1.14 ± 0.12, mean difference [MD] = 15.83° ± 2.71°). The ASYM group had less KF than the CON group in the early (8%–13%: Cohen d = 0.99 ± 0.04, MD = 7.99° ± 0.39°; 21%–24%: Cohen d = 1.01 ± 0.01, MD = 11.11° ± 0.32°) and late (74%–94%: Cohen d = 0.96 ± 0.07, MD = 9.55° ± 1.13°) stance phases. The SYM group had a smaller KEM (6.5%–9%: Cohen d = 1.21 ± 0.08, MD = 0.04 ± 0.004 N·m/[Nbw·mht]) and less FPT (6%–9%: Cohen d = 1.15 ± 0.15, MD = 0.85 ± 0.15 body weight) than the CON group in the early stance phase. The SYM group also displayed a smaller KEM (38%–56%: Cohen d = 1.17 ± 0.06, MD = 0.03 ± 0.001 N·m/[Nbw·mht]) and less FPT (36%–60%: Cohen d = 1.22 ± 0.08, MD = 0.66 ± 0.05 body weight) than the ASYM group in the midstance phase. The SYM group demonstrated a patellar tendon load-avoidance profile compared with the ASYM and CON groups. The ASYM group showed no evidence of overloading compared with the CON group. Our findings support the need for individualized treatments for athletes with tendinopathy to maximize load capacity. [ABSTRACT FROM AUTHOR]

Hughes, S, Warmenhoven, J, Haff, GG, Chapman, DW, and Nimphius, S. Countermovement jump and squat jump force-time curve analysis in control and fatigue conditions. J Strength Cond Res 36(10): 2752–2761, 2022—This study aimed to reanalyze previously published discrete force data from countermovement jumps (CMJs) and squat jumps (SJs) using statistical parametric mapping (SPM), a statistical method that enables analysis of data in its native, complete state. Statistical parametric mapping analysis of 1-dimensional (1D) force-time curves was compared with previous zero-dimensional (0D) analysis of peak force to assess sensitivity of 1D analysis. Thirty-two subjects completed CMJs and SJs at baseline, 15 minutes, 1, 24, and 48 hours following fatigue and control conditions in a pseudo random cross-over design. Absolute (CMJABS/SJABS) and time-normalized (CMJNORM/SJNORM) force-time data were analyzed using SPM 2-way repeated measures analysis of variance with significance accepted at α = 0.05. The SPM indicated a magnitude of difference between force-time data with main effects for time (p < 0.001) and interaction (p < 0.001) observed in CMJABS, SJABS, and SJNORM, whereas previously published 0D analysis reported no 2-way interaction in CMJ and SJ peak force. This exploratory research demonstrates the strength of SPM to identify changes between entire movement force-time curves. Continued development and use of SPM analysis techniques could present the opportunity for refined assessment of athlete fatigue and readiness with the analysis of complete force-time curves. [ABSTRACT FROM AUTHOR]

Intelligent waveform analysis surveying geological structures is a challenging task in remote acoustic measurement for formation detection, which has two problems: (1) time parametric imaging is disturbed by noisy environments and (2) manually annotated data for machine learning are unattainable. These restrict the deployment of advanced parameter extraction methods in imaging instruments. As a potential theory, domain adaptation makes the intelligent prediction implementable in the above situations. Hence, to counter high precision travel time extraction for acoustic imaging, a deep adaptation‐picking network (DAPN) framework is proposed, which consists of three modules: signal‐to‐signal generator, domain adaptation encoder, and feature recognition decoder. The translation module preprocesses the different datasets to improve the training accuracy and confuses the distribution between source and target domains based on the adversarial network. The core convolution neural network achieves travel time measurement, where the backbone extracts content features with modified maximum mean discrepancy embedding. Meanwhile, the decoding structure preserves the signal features in the training process. The effectiveness and feasibility of DAPN are verified by experimental results, suggesting that DAPN accurately extracts time parameters. Compared with traditional parametric imaging schemes, the proposed method has the advantages of high accuracy and anti‐noise ability. [ABSTRACT FROM AUTHOR]

The radome can protect the enclosed antenna from harsh weather and environmental conditions; however, it will cause a non‐negligible effect particularly transmission loss on the wideband signal which has been widely used in electronic systems. For this, a novel transmission loss compensation method for radome based on non‐linear frequency modulation (NLFM) waveform design is proposed. First, the transmission coefficient calculation process is given, Then, the detailed NLFM waveform design method is described in detail. Finally, the simulation experiments are demonstrated to verify the effectiveness of the proposed compensation method. Based on the designed NLFM waveform, the transmission loss can be compensated and a flat frequency response can be obtained, which can achieve excellent performance of pulse compression in the range direction. The proposed NLFM design method has great potential application value in the electronic system. [ABSTRACT FROM AUTHOR]

In this research, we explore the possibility and effectiveness of using laser-induced surface oxidation methods to enhance the durability and effectiveness of PEF (Pulsed Electric Field) systems. Despite advantages over thermal pasteurisation, PEF faces challenges like electrode corrosion and biofouling, hindering its adoption. This research introduces laser-induced oxidation to mitigate metal ion release during PEF, directly targeting electrode alteration. Our examination adopts a comprehensive method, integrating Design of Experiments (DoE) parameter sets for PEF trials, morphological analysis, evaluation of metal ion release via Inductively Coupled Plasma Quadrupole Mass Spectrometry (ICP-QMS), waveform capture utilizing a Data Acquisition (DAQ) system, electrochemical assessment via impedance spectroscopy, and examination of oxide layer composition employing X-ray photoelectron spectroscopy. Pulse waveform characteristics shows the intricate relationship between PEF processing parameters with metal ion release, alongside XPS analysis providing insights into surface chemistry. Optimized results show a three-fold reduction in metal ion release post-PEF, with laser-treated samples outperforming untreated stainless steel due to selective surface chemistry alteration, notably an increased Cr/Fe ratio, reducing harmful elements. This study highlights laser-induced oxidation as a practical solution for enhancing PEF electrode performance and reducing metal ion release, addressing key challenges in PEF technology. It advances sustainable food processing, promising extended PEF system lifespan while maintaining efficiency and product quality. • First practical example of reducing metal ion release in PEF processing via laser-induced electrode surface modification. • Laser processing cuts metal ion release by three times, extending electrode lifespan. • Discovery into the effect of variations in pulse waveform characteristics influence on electrochemical reactions and corrosion. • Reduced nickel and chromium enhance food safety, advancing sustainable food processing. • XPS shows surface chemistry changes, like increased Cr/Fe ratios, boosting corrosion resistance and reducing harmful ion release. [ABSTRACT FROM AUTHOR]