Offset Time Research Articles

Sleep Quality in Team USA Olympic and Paralympic Athletes.

To establish sleep-quality reference ranges for Olympic and Paralympic cohorts using the Pittsburgh Sleep Quality Index (PSQI) and explore differences based on sex and sport types. Team USA athletes (men = 805, women = 798) completed the PSQI as part of a health-history questionnaire. Descriptive statistics were used to create reference ranges and linear models, and χ2 test of independence determined differences in PSQI global and component scores between sex, games, season, and participation. Six hundred thirty-two (39.43%) athletes reported poor sleep (PSQIGlobal ≥ 5). Men displayed later bedtimes (P = .006), better global PSQI scores, shorter sleep latency, less sleep disturbance, and less use of sleep medication than women (all P < .001). Winter Games participants had later bedtime (P = .036) and sleep offset time (P = .028) compared with Summer Games athletes. Team-sport athletes woke earlier than individual-sport athletes (P < .001). Individual-sport athletes were more likely to have low (P = .005) and mild (P = .045) risk for reduced sleep duration than team-sport athletes. These data provide PSQI-specific reference ranges to identify groups at greatest risk for poor sleep, who may benefit most from targeted sleep interventions.

Prediction of internalizing and externalizing symptoms in late childhood from attention-deficit/hyperactivity disorder symptoms in early childhood.

Limited analyses based on national samples have assessed whether early attention-deficit/hyperactivity disorder (ADHD) symptoms predict later internalizing and externalizing symptoms in youth and the influence of sex and pubertal timing on subsequent psychiatric symptoms. This study analyzed data (n = 2818) from the Environmental influences on Child Health Outcomes Program national cohort. Analyses used data from early childhood (mean age = 5.3 years) utilizing parent-reported ADHD symptoms to predict rates of internalizing and externalizing symptoms from late childhood/adolescence (mean age = 11.9 years). Within a subsample age at peak height velocity (APHV) acted as a proxy to assess pubertal timing from early childhood (mean age = 5.4 years) to adolescence (mean age = 12.3 years). Early-childhood ADHD symptoms predicted later psychiatric symptoms, including anxiety, depression, aggressive behavior, conduct problems, oppositional defiant disorder, and rule-breaking behavior. Earlier APHV was associated with increased Conduct Disorder symptoms from late childhood to adolescence for females only. A stronger relation between ADHD symptoms and later aggression was observed in females with earlier APHV, whereas this same pattern with aggression, conduct problems and depression was observed in males with later APHV. Clinicians should consider that both young girls and boys with elevated ADHD symptoms, particularly with off-set pubertal timing, may be at risk for later psychiatric symptoms.

Sync-NeRF: Generalizing Dynamic NeRFs to Unsynchronized Videos

Recent advancements in 4D scene reconstruction using neural radiance fields (NeRF) have demonstrated the ability to represent dynamic scenes from multi-view videos. However, they fail to reconstruct the dynamic scenes and struggle to fit even the training views in unsynchronized settings. It happens because they employ a single latent embedding for a frame while the multi-view images at the same frame were actually captured at different moments. To address this limitation, we introduce time offsets for individual unsynchronized videos and jointly optimize the offsets with NeRF. By design, our method is applicable for various baselines and improves them with large margins. Furthermore, finding the offsets always works as synchronizing the videos without manual effort. Experiments are conducted on the common Plenoptic Video Dataset and a newly built Unsynchronized Dynamic Blender Dataset to verify the performance of our method. Project page: https://seoha-kim.github.io/sync-nerf

Spatio-temporal multivariable time vario-zoom network for water level forecasting based on high-resolution hydrological dataset

Water level forecasting is a crucial element in river-basin water resource management, particularly for shipping and extreme events, such as floods and droughts. However, accurately forecasting water levels is challenging due to the influence of non-stationarity hydrological processes, complex characteristic variables, and noisy data. Data-driven approaches in water level forecasting generally lack annotated high-resolution data. To address these problems, this paper presents the first hydrological dataset on the Xijiang River basin-Xijiang Water Dataset (XJWD) and a Spatio-Temporal Multivariable-based Time Vario-Zoom Network (STM- TVZN) model. XJWD combines multi-source raw hydrological data and has real-time and higher resolution data than comparable datasets. STM-TVZN is specifically tailored to enhance the discernment of salient features within key time windows for each variable by fusing spatio-temporal multivariate features through vario-zoom time windows. Finally, a novel metric, Extremum Time Offsets (ETO), is proposed to evaluate the accuracy of the occurrence of local extremum in time series, and it is significant for predicting and evaluating extremum events such as floods and droughts. Experimental results show that the proposed method outperformed existing models on XJWD dataset regarding error rate, stationarity, similarity, and ETO. Overall, the proposed method of combining time-variable focusing network design and spatio-temporal multivariate feature extraction is appealing for short-term water level forecasting in inland rivers, exhibiting potential capacity in strategic water-saving planning and extremum event forecasting caused by climate change.

Sleep timing behaviour, sleep duration and adherence to obesogenic dietary patterns from pre-school to school age: results from the Portuguese birth cohort Generation XXI.

In an obesogenic environment, short sleeping may increase opportunistic eating. The timing of sleep might also influence the drive to eat. This study investigated the prospective association of sleep timing and duration with diet in 5286 children from the Portuguese birth cohort Generation XXI, evaluated at 4 and 7 years of age. At 4 years, sleep duration was categorised into ≤10 and >10 h. Four sleep timing categories were generated based on the median split for sleep-onset and -offset times: 'Early Sleep-Early Wake'; 'Early Sleep-Late Wake'; 'Late Sleep-Early Wake'; 'Late Sleep-Late Wake'. At 7 years, diet was obtained by a food frequency questionnaire and three dietary patterns were included: 'Healthier', 'Energy-Dense Foods (EDF)' and 'Snacking'. The Healthy Eating Index was used to evaluate diet quality. Multinomial logistic regression models and generalised linear models were performed. Children who had a late sleep, independently of the time of waking up, had higher odds of following the 'EDF' pattern, compared with the 'Healthier'. Boys who had late sleep and/or late wake had also higher odds of following the 'Snacking' pattern and had poorer diet quality. In both sexes, a late sleep or late wake were associated with a lower diet quality, compared to the group 'Early Sleep-Early Wake', and independently of nap behaviour. In boys, shorter sleep duration was associated with a poorer diet. In conclusion, pre-schoolers with late bedtimes or wake-up times have worse dietary patterns and poorer diet quality at the age of 7 years, which seems to be independent of sleep duration.

Selection-Dependent Differences in Youth Elite Basketball Players’ Relative Age, Maturation-Related Characteristics, and Motor Performance

ABSTRACT Purpose: The aim of the present study was to investigate the influence of players’ relative age, maturation-related characteristics, and motor performance tests on two different stages of talent selection (regional and national level) in youth elite basketball. Methods: Relative age, maturation-related variables (height, weight, maturity offset, maturity timing) and motor performance (Countermovement jump, Standing long jump, Modified agility T-test, Linear sprint 20 m) of N = 68 male youth basketball players (M age = 14.39 ± 0.28 years) were assessed during the initial selection tournament for the German U15 national team. Pre-selection biases regarding relative age and maturity timing on the regional level were investigated utilizing one-sample t-tests. Differences in relative age, maturation-related characteristics and motor performance between players selected (n = 27) and non-selected (n = 41) for the youth national team were examined via independent samples’ t-tests and logistic regression analyses. Results: Strong pre-selection biases toward early-born and early-maturing players were confirmed on the regional level. Significant advantages in height and weight and higher values in maturity offset and maturity timing were found for selected players. Among the motor variables, only Countermovement jump performance was significantly better in selected players. When controlling for relative age and biological maturation regression models including motor performance variables did not significantly discriminate players’ selection status. Conclusion: Coaches working in national, but also preceding selection stages (regional and club level) should raise their awareness to relative age and biological maturation when evaluating players’ potential and current (motor) performance.

Both stimulus-specific and configurational features of multiple visual stimuli shape the spatial ventriloquism effect.

Studies on multisensory perception often focus on simplistic conditions in which one single stimulus is presented per modality. Yet, in everyday life, we usually encounter multiple signals per modality. To understand how multiple signals within and across the senses are combined, we extended the classical audio-visual spatial ventriloquism paradigm to combine two visual stimuli with one sound. The individual visual stimuli presented in the same trial differed in their relative timing and spatial offsets to the sound, allowing us to contrast their individual and combined influence on sound localization judgements. We find that the ventriloquism bias is not dominated by a single visual stimulus but rather is shaped by the collective multisensory evidence. In particular, the contribution of an individual visual stimulus to the ventriloquism bias depends not only on its own relative spatio-temporal alignment to the sound but also the spatio-temporal alignment of the other visual stimulus. We propose that this pattern of multi-stimulus multisensory integration reflects the evolution of evidence for sensory causal relations during individual trials, calling for the need to extend established models of multisensory causal inference to more naturalistic conditions. Our data also suggest that this pattern of multisensory interactions extends to the ventriloquism aftereffect, a bias in sound localization observed in unisensory judgements following a multisensory stimulus.

Effects of workload and saddle height on muscle activation of the lower limb during cycling.

Cycling workload is an essential factor in practical cycling training. Saddle height is the most studied topic in bike fitting, but the results are controversial. This study aims to investigate the effects of workload and saddle height on the activation level and coordination of the lower limb muscles during cycling. Eighteen healthy male participants with recreational cycling experience performed 15 × 2-min constant cadence cycling at five saddle heights of 95%, 97%, 100%, 103%, and 105% of greater trochanter height (GTH) and three cycling workloads of 25%, 50%, and 75% of functional threshold power (FTP). The EMG signals of the rectus femoris (RF), tibialis anterior (TA), biceps femoris (BF), and medial gastrocnemius (MG) of the right lower limb were collected throughout the experiment. Greater muscle activation was observed for the RF and BF at a higher cycling workload, whereas no differences were observed for the TA and MG. The MG showed intensified muscle activation as the saddle height increased. The mean and maximum amplitudes of the EMG signals of the MG increased by 56.24% and 57.24% at the 25% FTP workload, 102.71% and 126.95% at the 50% FTP workload, and 84.27% and 53.81% at the 75% FTP workload, respectively, when the saddle height increased from 95 to 100% of the GTH. The muscle activation level of the RF was minimal at 100% GTH saddle height. The onset and offset timing revealed few significant differences across cycling conditions. Muscle activation of the RF and BF was affected by cycling workload, while that of the MG was affected by saddle height. The 100% GTH is probably the appropriate saddle height for most cyclists. There was little statistical difference in muscle activation duration, which might be related to the small workload.

A modeling study of ≥2 MeV electron fluxes in GEO at different prediction time scales based on LSTM and transformer networks

In this study, we develop models to predict the log10 of ≥2 MeV electron fluxes with 5-minute resolution at the geostationary orbit using the Long Short-Term Memory (LSTM) and transformer neural networks for the next 1-hour, 3-hour, 6-hour, 12-hour, and 1-day predictions. The data of the GOES-10 satellite from 2002 to 2003 are the training set, the data in 2004 are the validation set, and the data in 2005 are the test set. For different prediction time scales, different input combinations with 4 days as best offset time are tested and it is found that the transformer models perform better than the LSTM models, especially for higher flux values. The best combinations for the transformer models for next 1-hour, 3-hour, 6-hour, 12-hour, 1-day predictions are (log10 Flux, MLT), (log10 Flux, Bt, AE, SYM-H), (log10 Flux, N), (log10 Flux, N, Dst, Lm), and (log10 Flux, Pd, AE) with PE values of 0.940, 0.886, 0.828, 0.747, and 0.660 in 2005, respectively. When the low flux outliers of the ≥2 MeV electron fluxes are excluded, the prediction efficiency (PE) values for the 1-hour and 3-hour predictions increase to 0.958 and 0.900. By evaluating the prediction of ≥2 MeV electron daily and hourly fluences, the PE values of our transformer models are 0.857 and 0.961, respectively, higher than those of previous models. In addition, our models can be used to fill the data gaps of ≥2 MeV electron fluxes.

Evaluation of the Garmin Vivofit 4 for assessing sleep in youth experiencing sleep disturbances.

Wearable monitors are increasingly used to assess sleep. However, validity is unknown for certain monitors and populations. We tested the Garmin Vivofit 4 in a pediatric clinical sample. Participants (n = 25) wore the monitor on their nondominant wrist during an overnight polysomnogram. Garmin and polysomnography were compared using 95% equivalence testing, mean absolute error, and Bland-Altman analysis. On average (mean ± SD), the Garmin predicted later sleep onset (by 0.84 ± 1.60 hours) and earlier sleep offset (by 0.34 ± 0.70 hours) than polysomnography. The resulting difference for total sleep time was -0.55 ± 1.21 hours. Sleep onset latency was higher for Garmin than polysomnography (77.4 ± 100.9 and 22.8 ± 20.0 minutes, respectively), while wake after sleep onset was lower (5.2 ± 9.3 and 43.2 ± 37.9 minutes, respectively). Garmin sleep efficiency averaged 3.3% ± 13.8% lower than polysomnography. Minutes in light sleep and deep sleep (the latter including rapid eye movement) were within ±3.3% of polysomnography (both SDs = 14.9%). No Garmin means were significantly equivalent with polysomnography (adjusted p > 0.99). Mean absolute errors were 0.47 to 0.95 hours for time-based variables (sleep onset, offset, and latency, plus total sleep time and wake after sleep onset), and 8.9% to 21.2% for percentage-based variables (sleep efficiency and sleep staging). Bland-Altman analysis showed systematic bias for wake after sleep onset, but not other variables. The Vivofit 4 showed consistently poor individual-level validity, while group-level validity was better for some variables (total sleep time and sleep efficiency) than others.

Offset Time of Zero-Order Fringe Splitting of Fishbone Structure in Attosecond Transient Absorption Spectrum of Graphene (Invited)

Offset Time of Zero-Order Fringe Splitting of Fishbone Structure in Attosecond Transient Absorption Spectrum of Graphene (Invited)

A Robust Timing Synchronization Algorithm Based on PSSS for LTE-V2X

In recent years, Long-Term Evolution Vehicle-to-Everything (LTE-V2X) communication technology has received extensive attention. Timing synchronization is a crucial step in the receiving process, addressing Timing Offsets (TOs) resulting from random propagation delays, sampling frequency mismatches between the transmitter and receiver or a combination of both. However, the presence of high-speed relative movement between nodes and a low antenna height leads to a significant Doppler frequency offset, resulting in a low Signal-to-Noise Ratio (SNR) for received signals in LTE-V2X communication scenarios. This paper aims to investigate LTE-V2X technology with a specific focus on time synchronization. The research centers on the time synchronization method utilizing the Primary Sidelink Synchronization Signal (PSSS) and conducts a comprehensive analysis of existing algorithms, highlighting their respective advantages and disadvantages. On this basis, a robust timing synchronization algorithm for LTE-V2X communication scenarios is proposed. The algorithm comprises three key steps: coarse synchronization, frequency offset estimation and fine synchronization. Enhanced robustness is achieved through algorithm fusion, optimal decision threshold design and predefined frequency offset values. Furthermore, a hardware-in-the-loop simulation platform is established. The simulation results demonstrate a substantial performance improvement for the proposed algorithm compared to existing methods under adverse channel conditions characterized by high frequency offsets and low SNR.

Application of Impact Elastic Wave Method in Quality Inspection of Concrete Lining

As the main part of inter-basin water transfer project, water tunnel plays an important role in long-distance water conveyance. In water tunnel, the lining quality problem is one of the important potential safety hazards of the tunnel engineering. It is very necessary to detect the internal defects of concrete lining. In this paper, a multi-parameter comprehensive interpretation method based on impact elastic wave is proposed to quickly detect the internal defects of lining. The common offset time domain analysis method, frequency domain analysis method and two-dimension Rayleigh wave method are used for data processing. The detection method has the characteristics of single data acquisition and multi-parameter joint interpretation. The physical model of concrete lining is tested and compared with the result of GPR method to verify the accuracy of this method. The coring results show the reliability and stability of this method in practical application.

Sound Event Detection utilizing Spectro-Temporal Receptive Field

Sound event detection (SED) is a task of recognizing the target sound events with their respective onset and offset time in a recorded audio clip. SED is closely related to auditory scene analysis, the process by which human auditory systems perceive sound into perceptually meaningful components. While human auditory system is trained to perform SED well enough, the way sound is transformed into neural response within human auditory system still remain as the subject of ongoing research. One of efforts to describe the relationship between sound and neural response is the spectro-temporal receptive field (STRF). STRF acts as a linear function between sound time-frequency representation and primary auditory cortex (A1) cell response, so that neural response can be predicted by convolution of time-frequency representation of sound and STRF. In addition, STRF is designed to capture spectro-temporal modulation in that A1 cells are much reactive to spectro-temporally modulated ripple. In this work, we utilized STRF as a kernel of the first layer in the convolutional neural network (CNN) to extract neural response from input audio clip to make SED model similar to human auditory system. Then, we constructed two-branched SED model named as Two Branch STRF-Net (TB-STRFNet) composed of STRF branch and basic branch. The STRF branch extracts spectro-temporal modulation information and the basic branch extracts detailed and complex time-frequency information. TB-STRFNet outperformed the baseline by 4.3% in terms of main metric in DCASE 2023 Task 4 subtask B.

Using Real-World Data to Inform Value-Based Contracts for Cell and Gene Therapies in Medicaid.

High upfront costs and long-term benefit uncertainties of gene therapies challenge Medicaid budgets, making value-based contracts a potential solution. However, value-based contract design is hindered by cost-offset uncertainty. The aim of this study is to determine actual cost-offsets for valoctocogene roxaparvovec (hemophilia A) and etranacogene dezaparvovec (hemophilia B) from Colorado Medicaid's perspective, defining payback periods and its uncertainty from the perspective of Colorado Medicaid. This cost analysis used 2018-2022 data from the Colorado Department of Health Care Policy & Financing to determine standard-of-care costs and employed cost simulation models to estimate the cost of Medicaid if patients switched to gene therapy versus if they did not. Data encompassed medical and pharmacy expenses of Colorado Medicaid enrollees. Identified cohorts were patients aged 18+ with ICD-10-CM codes D66 (hemophilia A) and D67 (hemophilia B). Severe hemophilia A required ≥ 6 claims per year for factor therapies or emicizumab, while moderate/severe hemophilia B necessitated ≥ 4 claims per year for factor therapies. Patients were included in the cohort in the year they first met the criteria and were subsequently retained in the cohort for the duration of the observation period. Standard-of-care included factor VIII replacement therapy/emicizumab for hemophilia A and factor IX replacement therapies for hemophilia B. Simulated patients received valoctocogene roxaparvovec or etranacogene dezaparvovec. Main measures were annual standard-of-care costs, cost offset, and breakeven time when using gene therapies. Colorado Medicaid's standard-of-care costs for hemophilia A and B were $426,000 [standard deviation (SD) $353,000] and $546,000 (SD $542,000) annually, respectively. Substituting standard-of-care with gene therapy for eligible patients yielded 8-year and 6-year average breakeven times, using real-world costs, compared with 5 years with published economic evaluation costs. Substantial variability in real-world standard-of-care costs resulted in a 48% and 59% probability of breakeven within 10 years for hemophilia A and B, respectively. Altering eligibility criteria significantly influenced breakeven time. Real-world data indicates substantial uncertainty and extended payback periods for gene therapy costs. Utilizing real-world data, Medicaid can negotiate value-based contracts to manage budget fluctuations, share risk with manufacturers, and enhance patient access to innovative treatments.

Deep Learning-Based Analysis of Glottal Attack and Offset Times in Adductor Laryngeal Dystonia.

Diagnosis of adductor laryngeal dystonia (AdLD) is challenging as it mimics voice features of other voice disorders. This could lead to misdiagnosis (or delayed diagnosis) and ineffective treatments of AdLD. This paper develops automated measurements of glottal attack time (GAT) and glottal offset time (GOT) from high-speed videoendoscopy (HSV) in connected speech as objective measures that can potentially facilitate the diagnosis of this disorder in the future. HSV data were recorded from vocally normal adults and patients with AdLD during the reading of the "Rainbow Passage" and six CAPE-V (Consensus Auditory-Perceptual Evaluation of Voice) sentences. A deep learning framework was designed and trained to segment the glottal area and detect the vocal fold edges in the HSV dataset. This automated framework allowed us to automatically measure and quantify the GATs and GOTs for the participants. Accordingly, a comparison was held between the obtained measurements among vocally normal speakers and those with AdLD. The automated framework was successfully developed and able to accurately segment the glottal area/edges. The precise automated measurements of GAT and GOT revealed minor, nonsignificant differences compared to the results of manual analysis-showing a strong correlation between the measures by the automated and manual methods. The results showed significant differences in the GAT values between the vocally normal subjects and AdLD patients, with larger variability in both the GAT and GOT measures in the AdLD group. The developed automated approach for GAT and GOT measurement can be valuable in clinical practice. These quantitative measurements can be used as meaningful biomarkers of the impaired vocal function in AdLD and help its differential diagnosis in the future.

From localized to well mixed: How commuter interactions shape disease spread.

Interactions between commuting individuals can lead to large-scale spreading of rumors, ideas, or disease, even though the commuters have no net displacement. The emergent dynamics depend crucially on the commuting distribution of a population, that is how the probability to travel to a destination decays with distance from home. Applying this idea to epidemics, we will demonstrate the qualitatively different infection dynamics emerging from populations with different commuting distributions. If the commuting distribution is exponentially localized, then we recover a reaction-diffusion system and observe Fisher waves traveling at a speed proportional to the characteristic commuting distance. If the commuting distribution has a long tail, then no finite-velocity waves can form, but we show that, in some regimes, there is nontrivial spatial dependence that the well-mixed approximation neglects. We discuss how, in all cases, an initial dispersal-dominated regime can allow the disease to go undetected for a finite amount of time before exponential growth takes over. This "offset time" is a quantity of huge importance for epidemic surveillance and yet largely ignored in the literature.

Gaze-speech coordination during social interaction in Parkinson's disease.

Parkinson's disease (PD) can affect social interaction and communication as well as motor and cognitive processes. Speech is affected in PD, as is the control of voluntary eye movements which are thought to play an important role in 'turn taking' in conversation. This study aimed to measure eye movements during spoken conversation in PD to assess whether differences in patterns of eye gaze are linked to disrupted turn taking and impaired communication efficiency. Eleven participants with mild PD and 14 controls completed a two-player guessing game. During each 3 min game turn, one of the players had to guess the names of as many objects as possible based only on the other player's description. Eye movements were recorded simultaneously in both participants using mobile eye trackers along with speech onset and offset times. When people with PD played the role of describer, the other player guessed fewer objects compared to when controls described objects. When guessing objects, people with PD performed just as well as controls. Analysis of eye fixations showed that people with PD made longer periods of fixation on the other player's face relative to controls and a lower number of such 'gaze on face' periods. A combination of oculomotor, cognitive and speech abnormalities may disrupt communication in PD. Better public awareness of oculomotor, speech and other deficits in the condition could improve social connectedness in people with Parkinson's. What is already known on this subject? Parkinson's disease is known to affect the control of voluntary eye movements. Direction of eye gaze is important in spoken conversation as a cue to turn-taking, but no studies have examined whether eye movements are different during communication in people with Parkinson's. What this paper adds to existing knowledge? People with Parkinson's showed longer periods of eye fixation during conversations compared to controls. Delays and overlaps between speech turns were also affected in patients. What are the clinical implications of this work? Better knowledge of the effect of the disease on eye gaze control amongst clinicians may help improve communication and social connectedness for patients in the future.

Electrostatic precipitator collection efficiency studies using atmospheric radon progeny as aerosol analogs for nuclear explosion radionuclides

Electrostatic precipitation (ESP) is an attractive low-powered collection mechanism for mobile and fixed aerosol detection of radionuclides (RNs) for Nuclear Explosion Monitoring (NEM). Aerosol samplers deployed in the International Monitoring System use a blower to draw air through a filter media to collect particulates. ESP-based samplers collect aerosols without a filter, which can greatly increase volumetric flow capacity per watt of power consumed. ESP-based collectors may be optimized to perform low-power mobile RN collection or to improve the air throughput of existing monitoring stations. This effort describes the use of unknown concentrations of atmospheric RNs to determine the collection efficiency of a compact ESP design. For this analysis, naturally occurring radon progeny are simultaneously collected by a single stage wire-plate ESP and a filter-based sampler with a known collection efficiency. The activity of resulting samples is measured with gamma-spectroscopy and decay corrected for analysis time offsets. RN collection efficiencies are then derived for an experimental survey of ESP operational parameters that influence the ionization, transit, and collection of aerosols. At volumetric flow rates of 1.5–2 CMM, the optimized collection efficiency was calculated as 21±2%, and slower rates around 0.5 CMM resulted in 55 ±5% collection efficiency. The monitoring performance of the ESP-based collector was assessed for a simplified nuclear explosion source term by calculating the minimal detectable concentrations of short-lived fission & activation products. Results of the study suggest that a low-power ESP is feasible for NEM at distances of 100s of km.

Vortex‐induced vibration effects in underwater acoustic wireless sensor networks

AbstractA randomly fluctuated vortex‐induced vibration (VIV) affects the localization of moving targets in an underwater acoustic wireless sensor network (UAWSN) to cause an offset time and time synchronization error which disturbs the localization of the non‐cooperative moving target. Definition 1, Theorem 1 has been introduced in the present work to describe the genesis and consequences of the VIV effect in UAWSN. An elliptic localization introduces the direct and indirect path measurements of the moving target. The standard Crammer Rao lower bound parameter quantifies the VIV effect. The compensation of vortex‐induced vibrations (CVV) algorithm is proposed to quantify the degradation of localization performance and to estimate the position of the moving target. The theoretical measurements of position error, velocity error with respect to the variation of noise, number of receiver sensors, and probability of line of sight errors are compared to the standard methods. The proposed CVV algorithm improves the localization performance by 32.24% and reduces 34.36% of position errors, and 37.46% of velocity errors up to 600 m. It can be useful for the sub‐aquatic internet of underwater things.