Distribution Of Intervals Research Articles

Propagation speed model of mode-2 internal solitary waves in the northern South China Sea based on multi-source optical remote sensing

The phase speed of internal solitary waves (ISWs) is an essential dynamical parameter for the study of their generation, propagation, and evolution. In this study, a model based on multi-source optical remote sensing data was developed to calculate the phase speed of mode-2 ISWs in the northern South China Sea (NSCS). A total of 430 mode-2 ISWs were identified from optical remote sensing images acquired by Terra/Aqua, Gaofen-1/6 (GF-1/6), Huanjing-2A/B (HJ-2A/B), and China-Brazil Earth Resources Satellite 04 (CBERS-04) between 2014 and 2024. These waves are primarily distributed in areas with a total water depth of 150–500 m near Dongsha Atoll and Shenhu-Yitong Shoals, propagating perpendicular to the local isobaths. The phase speeds of the mode-2 ISWs were estimated using the multiple images comparison (MIC) method, and a depth-based phase speed model was developed. The model was validated using field measurements and theoretical phase speeds. The results were within the reasonable range of theoretical predictions and showed a mean relative error (MRE) of 7.64% compared to the annual average data from field measurements. Further analysis of the spatial and interval distribution of the phase speeds of mode-2 ISWs on the NSCS continental shelf revealed that the phase speeds ranged from 0.42 to 0.75 m/s, with the highest proportion occurring in the interval 0.60–0.65 m/s.

Perturbation context in paced finger tapping tunes the error-correction mechanism

Sensorimotor synchronization (SMS) is the mainly specifically human ability to move in sync with a periodic external stimulus, as in keeping pace with music. The most common experimental paradigm to study its largely unknown underlying mechanism is the paced finger-tapping task, where a participant taps to a periodic sequence of brief stimuli. Contrary to reaction time, this task involves temporal prediction because the participant needs to trigger the motor action in advance for the tap and the stimulus to occur simultaneously, then an error-correction mechanism takes past performance as input to adjust the following prediction. In a different, simpler task, it has been shown that exposure to a distribution of individual temporal intervals creates a “temporal context” that can bias the estimation/production of a single target interval. As temporal estimation and production are also involved in SMS, we asked whether a paced finger-tapping task with period perturbations would show any time-related context effect. In this work we show that a perturbation context can indeed be generated by exposure to period perturbations during paced finger tapping, affecting the shape and size of the resynchronization curve. Response asymmetry is also affected, thus evidencing an interplay between context and intrinsic nonlinearities of the correction mechanism. We conclude that perturbation context calibrates the underlying error-correction mechanism in SMS.

Head and neck cancer treatment delays in 2021: Estimating distributional effects by site, surgery, and p16-positivity

BackgroundFollowing decades of policies increasing access to high-quality cancer treatment, the COVID-19 pandemic upended the U.S. healthcare system. The pandemic's disruption likely affected an often-overlooked dimension of quality cancer treatment: timely initiation. Timely treatment initiation is especially critical for head and neck cancer (HNC). We aimed to assess how the treatment interval (diagnosis to treatment initiation) changed in 2021 for different types of HNCs and treatment modalities. MethodologyWe analyzed Surveillance, Epidemiological, End Results (SEER) case data for years 2007–2021. Using ICD site codes, cancers were restricted to oropharynx, oral cavity, other pharynx, larynx. Oropharynx cancers were stratified by Human Papillomavirus (HPV) subtype based on p16-positivity codes. The outcome of interest was a variable measuring the number of days from diagnosis to treatment initiation. Cases were stratified by site and whether they received surgery as first course of treatment. To overcome validity threats from skewed treatment interval data and unobserved heterogeneity, we constructed an unconditional quantile regression model to estimate the effect of treatment in 2021 across the distribution of the treatment interval. Results155,273 patients in SEER initiated HNC treatment between 2007 and 2021. The median treatment interval was 29 days (Interquartile Range = 2–48). Among patients not receiving surgery, 2021 was associated with delayed treatment for all sites except oral cavity. For patients receiving surgery, 2021 was only associated with delayed treatment for p16+ Oropharynx cancer. DiscussionHNC patients overall, but HPV+ Oropharynx cancer patients especially, experienced treatment delays in 2021. These delays, and their consequences, warrant policymaking attention.

The Effects of Ghrelin on Spike Activity of the Suprachiasmatic Nucleus Neurones of the Rat

In one of the most important non-photic mechanisms of the circadian biological clock synchronization with environmental geophysical 24 h rhythm, information on feeding schedule, composition and calorie content of food is used. Hormone ghrelin, a product of the neuroendocrine oxyntic cells of the gastric mucosa to be a signal molecule within this mechanism. In experiments on sagittal hypothalamic slices of male Wistar rats, the effects of 25 nM ghrelin on spike activity and parameters of spike information coding were investigated. Application of ghrelin induced an increase in spike frequency and a decrease in entropy of interspike interval distribution in 32.1% of the neurones recorded. In 29.6% of the cells, opposite responses in the form of a reduction of activity and an increase in the entropy of interspike interval distribution were observed. Parameters of spike activity of the reminder 38.3% neurones of the suprachiasmatic nucleus did not change. The observed responses of the entropy of interspike interval distribution indicate the appropriate changes in a degree of irregularity of interspike interval induced by ghrelin. Application of selective high-affinity antagonist of GHS-R1a receptor, JMV 2959 (100 nM) did not induce responses of the investigated parameters of spike activity but completely prevented changes of both, spike frequency and entropy of interspike interval distribution observed in the presence of ghrelin. The obtained data show that hormone ghrelin by a direct influence on the suprachiasmatic nucleus in vitro modulates the activity level and spike code of relatively numerous population of neurones of the nucleus, wherein the effects of ghrelin are implemented via GHS-R1a receptors. The results of the current study provide additional evidence in favour of the hypothesis on the involvement of ghrelin in mechanisms of non-photic entrainment of the circadian biological clock in accordance with severity of food motivation and level of metabolism.

Bounding the generation time distribution uncertainty on R 0 estimation from exponential growth rates

The basic reproduction number R 0 is one of the main parameters determining the spreading of an epidemic in a population of susceptible individuals. Wallinga and Lipsitch proposed a method for estimating R 0 using the Euler–Lotka equation, which requires the Laplace transform of the generation interval distribution. The determination of the generation time distribution is challenging, as the generation time is not directly observable. We prove upper and lower bounds on R 0 using only the first few moments of the generation interval distributions and study the sensitivity of the bounds to these parameters. The bounds do not require the exact shape of the generation interval distribution and give robust estimates of the r − R 0 relationship.

Alcohol exposure induces cortical activity change during quiescent state

Alcohol Use Disorder (AUD) is a significant global mental health issue that impacts both the central and peripheral systems, leading to widespread cognitive and motor dysfunctions. The primary motor cortex (M1) plays a critical role in motor planning, control, and execution, yet the effects of chronic alcohol exposure on M1 remain underexplored, particularly during quiescent states. This study investigates the functional changes in M1 due to chronic alcohol exposure using high-resolution Neuropixels electrode recordings in a mouse model. Our findings reveal alterations in neuronal firing mode, particularly in layer V, highlighting disruptions in the excitatory/inhibitory (E/I) balance. Despite similar overall firing rates, changes in firing interval distributions suggest altered temporal dynamics of neuronal activity due to alcohol exposure. These results align with existing literature on cortical disruptions caused by alcohol and provide new insights into the specific neuronal dynamics within M1, especially in quiescent states.

Pairwise Accelerated Failure Time Regression Models for Infectious Disease Transmission in Close-Contact Groups With External Sources of Infection.

Many important questions in infectious disease epidemiology involve associations between covariates (e.g., age or vaccination status) and infectiousness or susceptibility. Because disease transmission produces dependent outcomes, these questions are difficult or impossible to address using standard regression models from biostatistics. Pairwise survival analysis handles dependent outcomes by calculating likelihoods in terms of contact interval distributions in ordered pairs of individuals. The contact interval in the ordered pair is the time from the onset of infectiousness in to infectious contact from to , where an infectious contact is sufficient to infect if they are susceptible. Here, we introduce a pairwise accelerated failure time regression model for infectious disease transmission that allows the rate parameter of the contact interval distribution to depend on individual-level infectiousness covariates for , individual-level susceptibility covariates for , and pair-level covariates (e.g., type of relationship). This model can simultaneously handle internal infections (caused by transmission between individuals under observation) and external infections (caused by environmental or community sources of infection). We show that this model produces consistent and asymptotically normal parameter estimates. In a simulation study, we evaluate bias and confidence interval coverage probabilities, explore the role of epidemiologic study design, and investigate the effects of model misspecification. We use this regression model to analyze household data from Los Angeles County during the 2009 influenza A (H1N1) pandemic, where we find that the ability to account for external sources of infection increases the statistical power to estimate the effect of antiviral prophylaxis.

Discrete-Time Reinforcement Learning Adaptive Control for Non-Gaussian Distribution of Sampling Intervals.

This article proposes an optimal controller based on reinforcement learning (RL) for a class of unknown discrete-time systems with non-Gaussian distribution of sampling intervals. The critic and actor networks are implemented using the MiFRENc and MiFRENa architectures, respectively. The learning algorithm is developed with learning rates determined through convergence analysis of internal signals and tracking errors. Experimental systems with a comparative controller are conducted to validate the proposed scheme, and comparative results show superior performance for non-Gaussian distributions, with weight transfer for the critic network omitted. Additionally, the proposed learning laws, using the estimated co-state, significantly improve dead-zone compensation and nonlinear variation.

Sampled-Data H∞ Dynamic Output-Feedback Control for NCSs With Successive Packet Losses and Stochastic Sampling.

The problem of sampled-data H∞ dynamic output-feedback control for networked control systems with successive packet losses (SPLs) and stochastic sampling is investigated in this article. The aim of using sampled-data control techniques is to alleviate network congestion. SPLs that occur in the sensor-to-controller (S-C) and controller-to-actuator (C-A) channels are modeled using a packet loss model. Additionally, it is assumed that stochastic sampling follows a Bernoulli distribution. A model is established to capture the stochastic characteristics of both the SPL model and stochastic sampling. This model is crucial as it allows us to determine the probability distribution of the sampling interval between successive update instants, which is essential for stability analysis. An exponential mean-square stability condition for the constructed equivalent discrete-time stochastic system, which also guarantees the prescribed H∞ performance, is established by incorporating probability theory. The desired controller is designed using a step-by-step synthesis approach, which may offer lower design conservatism compared to some existing methods. Finally, our designed approach using a networked F-404 engine system model is validated and its merits relative to existing results are discussed. The proposed method is finally validated by employing a networked model of the F-404 engine system. Furthermore, the advantages of our method are presented in comparison to previous results.

Tracking neurons across days with high-density probes.

Neural activity spans multiple time scales, from milliseconds to months. Its evolution can be recorded with chronic high-density arrays such as Neuropixels probes, which can measure each spike at tens of sites and record hundreds of neurons. These probes produce vast amounts of data that require different approaches for tracking neurons across recordings. Here, to meet this need, we developed UnitMatch, a pipeline that operates after spike sorting, based only on each unit's average spike waveform. We tested UnitMatch in Neuropixels recordings from the mouse brain, where it tracked neurons across weeks. Across the brain, neurons had distinctive inter-spike interval distributions. Their correlations with other neurons remained stable over weeks. In the visual cortex, the neurons' selectivity for visual stimuli remained similarly stable. In the striatum, however, neuronal responses changed across days during learning of a task. UnitMatch is thus a promising tool to reveal both invariance and plasticity in neural activity across days.

Time interval distribution of hepatitis B vaccine immunization among infants in China from 2017 to 2021

ABSTRACT Infant hepatitis B vaccine coverage in China is high, with over 95% of infants immunized; however, high vaccine coverage can often mask low timeliness. The vaccination interval between the second and third doses is not clearly defined by immunization guidelines in China. This retrospective cohort study assessed the time interval distribution of hepatitis B vaccination among a cohort of randomly selected live births from the Centers for Disease Control and Prevention across four provinces or municipalities in China between January 2017 and December 2021. Among the infants analyzed, 163,224 received the first dose of hepatitis B vaccine with 146,905 (90.0%) and 135,757 (83.2%) infants receiving the second and third doses, respectively. A total of 132,577 (90.2%) infants received the second dose between 28 and 61 days after the first dose. Of the 119,437 (88.0%) infants that completed the hepatitis B series between 61 and 214 days after the second dose 87,067 (64.1%) infants were vaccinated with the third dose between 151 and 180 days after the second dose. The time interval distribution varied across the four provinces or municipalities (p < .001). Of the 58,077 infants who completed the hepatitis B vaccine series, 36,377 (62.6%) infants used the same type of hepatitis B vaccine for all three doses. Overall, the timeliness of hepatitis B vaccination for infants was lower than expected, with regional disparities observed. This highlights the need for improved timeliness through the introduction of a defined timeframe for the last two doses of vaccine and training for obstetricians and related personnel.

Analysis of delays in medium access control devices in cognitive radio systems with correlation of time intervals in request flows

This article is about the development of a method for analyzing the average waiting time of a request in a queue with correlated inter-arrival and service times. The ON-OFF process is often used to model the primary user channel occupancy in different questions related to cognitive radio, such as resource allocation, medium access control protocols, spectrum handoff and others. It is assumed that the time intervals of the ON- and OFF- periods are not correlated. More realistic models of primary user activity require the presence of correlation not only between consequent periods, but also the presence of correlation between channel occupancy and other quantities interpreted as service time in models based on queuing systems. As a result, here is proposed a variant of constructing the probability density function of a random variable which is the difference between the service time of the i-th request and the time interval between the moments of arriving of the i-th and (i-1)-th requests with correlated inter-arrival and service times. Solution based on the use of a two-dimensional characteristic function, so in this case it is possible to more purposefully specify the components of the statistical connection of previously described sequences. These components are the cumulants of the described distribution. For a queuing system with hyperexponential distribution of inter-arrival and service intervals, an analytical expression for the average waiting time of a request in a queue is found.

Addressing cities’ color issues and planning urban colors with regional features to preserve the history and culture of cities: the case of Suzhou, Wuxi, and Changzhou (China)

ABSTRACT Although there are many remarkable examples of color traditions from different parts of the world, many cities still face color-related issues, such as lack of regionality and clutter. Since the color issues of different cities vary, the solutions must also be different. This paper examines the old urban areas of Suzhou, Wuxi, and Changzhou in China as a case study to investigate how to solve urban color problems and shape the architectural color with regional characteristics. By exploring the spatial distribution of color categories and the interval distribution of color attribute values, this paper finds that the increase in colored buildings (especially along the main roads) and the excessive chromaticity of new buildings affect the regionality of urban colors. Therefore, we propose restoring urban color by establishing color zoning and controlling chromaticity to increase cultural diversity, promote economic vitality, and enhance people’s sense of belonging. The planning of urban color and the establishment of color patterns with regional characteristics are of positive significance for the development of urban history, culture, and habitat.

Experimental investigation on the gas pressure influence laws and mechanical mechanism of coal and gas outbursts

With the increasing frequency and intensity of coal and gas outburst disasters under deep mining conditions, studying the outburst mechanism of occurrence has great significance for outbursts prevention and control. The evolution law of coal and gas outbursts under different gas pressure is proposed. The outbursts law is analyzed utilizing the self-developed simulation experiment system of coal and gas outbursts, and the simulation experiment is carried out under the gas pressure of 0.45, 0.8, and 1.5 MPa. In the experiment, the gas pressure drops curves, the relative intensity change, the interval distribution of coal powder, and the evolution of outburst hole and the migration rate of coal powder are analyzed. The results indicate that (1) the gas pressure detected by the No. 4 gas pressure sensor starts to drop first; (2) the gas pressure is positively proportional to the relative outburst intensity. When the gas pressure increases from 0.45 to 0.80 MPa and then to 1.5 MPa, the farthest outburst distance of coal powder increases from 10 to 15 m and then to 21 m, and the corresponding relative outburst intensity increases from 22.94% to 35.74% and then to 45.73%, respectively. (3) The average proportion of coal particles size less than 0.28 mm and larger than 1 mm under each corresponding outburst interval is 40.75% and 22.53%, respectively. Experimental results show that the gas pressure plays an essential role in the secondary crushing and pulverization of coal samples during the outburst process. (4) The throwing velocity of the pulverized coal is increased with the gas pressure near the outburst hole. When the gas pressure is 0.8 MPa, the throwing velocity of pulverized coal reaches the maximum value of 32.40 m/s. (5) The dimensional characteristics and the location initiation of the outburst hole are obtained. The results showed that the outburst process of coal is mainly in two failure forms: pulverization and spallation. The research results provide a theoretical basis and test data support for the prevention and control of coal and gas outburst disasters.

Real-world smartphone data can trace the behavioural impact of epilepsy: A case study.

Neurobehavioural comorbidities have a detrimental effect on the quality of life of people with epilepsy, yet tracking their impact is challenging as behaviour may vary with seizures and anti-seizure medication (ASM) side effects. Smartphones have the potential to monitor day-to-day neurobehavioural patterns objectively. We present the case of a man in his late twenties with drug-resistant focal epilepsy in whom we ascertained the effects of ASM withdrawal and a convulsive seizure on his touchscreen interactions. Using a dedicated app, we recorded over 185 days the timestamps of 718,357 interactions. We divided the various smartphone behaviours according to the next-interval dynamics of the interactions by using a joint interval distribution (JID). During two ASM load transitions, namely before versus during tapering and tapering versus restarting medication, we used cluster-based permutation tests to compare the JIDs. We also compared the JID of the seizure day to the average of the previous 3 days. The cluster-based permutation tests revealed significant differences, with accelerated next-interval dynamics during tapering and a reversal upon medication restart. The day of the convulsion exhibited a marked slowing of next-interval dynamics compared to the preceding 3 days. Our findings suggest that the temporal dynamics of smartphone touchscreen interactions may help monitor neurobehavioural comorbidities in neurological care.

Non-monotonic behavior of jam probability and stretched exponential distribution in pedestrian counterflow

Abstract We adopt a floor field cellular automata model to study the statistical properties of bidirectional pedestrian flow moving in a straight corridor. We introduce a game-theoretic framework to deal with the conflict of multiple pedestrians trying to move to the same target location. By means of computer simulations, we show that the complementary cumulative distribution of the time interval between two consecutive pedestrians leaving the corridor can be fitted by a stretched exponential distribution, and surprisingly, the statistical properties of the two types of pedestrian flows are affected differently by the flow ratio, i.e., the ratio of the pedestrians walking toward different directions. We also find that the jam probability exhibits a non-monotonic behavior with the flow ratio, where the worst performance arises at an intermediate flow ratio of around 0.2. Our simulation results are consistent with some empirical observations, which suggest that the peculiar characteristics of the pedestrians may attributed to the anticipation mechanism of collision avoidance.

Detecting rhythmic spiking through the power spectra of point process model residuals.

Objective. Oscillations figure prominently as neurological disease hallmarks and neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to seek peaks in the spike train's power spectral density (PSD) which exceed a flat baseline. Yet for a non-oscillating neuron, the PSD is not flat: The recovery period ('RP', the post-spike drop in spike probability, starting with the refractory period) introduces global spectral distortion. An established 'shuffling' procedure corrects for RP distortion by removing the spectral component explained by the inter-spike interval (ISI) distribution. However, this procedure sacrifices oscillation-related information present in the ISIs, and therefore in the PSD. We asked whether point process models (PPMs) might achieve more selective RP distortion removal, thereby enabling improved oscillation detection.Approach. In a novel 'residuals' method, we first estimate the RP duration (nr) from the ISI distribution. We then fit the spike train with a PPM that predicts spike likelihood based on the time elapsed since the most recent of any spikes falling within the precedingnrmilliseconds. Finally, we compute the PSD of the model's residuals.Main results. We compared the residuals and shuffling methods' ability to enable accurate oscillation detection with flat baseline-assuming tests. Over synthetic data, the residuals method generally outperformed the shuffling method in classification of true- versus false-positive oscillatory power, principally due to enhanced sensitivity in sparse spike trains. In single-unit data from the internal globus pallidus (GPi) and ventrolateral anterior thalamus (VLa) of a parkinsonian monkey-in which alpha-beta oscillations (8-30 Hz) were anticipated-the residuals method reported the greatest incidence of significant alpha-beta power, with low firing rates predicting residuals-selective oscillation detection.Significance. These results encourage continued development of the residuals approach, to support more accurate oscillation detection. Improved identification of oscillations could promote improved disease models and therapeutic technologies.

Phase-Dependent Response to Electrical Stimulation of Cortical Networks during Recurrent Epileptiform Short Discharge Generation In Vitro.

The closed-loop control of pathological brain activity is a challenging task. In this study, we investigated the sensitivity of continuous epileptiform short discharge generation to electrical stimulation applied at different phases between the discharges using an in vitro 4-AP-based model of epilepsy in rat hippocampal slices. As a measure of stimulation effectiveness, we introduced a sensitivity function, which we then measured in experiments and analyzed with different biophysical and abstract mathematical models, namely, (i) the two-order subsystem of our previous Epileptor-2 model, describing short discharge generation governed by synaptic resource dynamics; (ii) a similar model governed by shunting conductance dynamics (Epileptor-2B); (iii) the stochastic leaky integrate-and-fire (LIF)-like model applied for the network; (iv) the LIF model with potassium M-channels (LIF+KM), belonging to Class II of excitability; and (v) the Epileptor-2B model with after-spike depolarization. A semi-analytic method was proposed for calculating the interspike interval (ISI) distribution and the sensitivity function in LIF and LIF+KM models, which provided parametric analysis. Sensitivity was found to increase with phase for all models except the last one. The Epileptor-2B model is favored over other models for subthreshold oscillations in the presence of large noise, based on the comparison of ISI statistics and sensitivity functions with experimental data. This study also emphasizes the stochastic nature of epileptiform discharge generation and the greater effectiveness of closed-loop stimulation in later phases of ISIs.

Effect of aerogel incorporation on water content distribution and capillary water absorption in pore size intervals of cementitious composites

Effect of aerogel incorporation on water content distribution and capillary water absorption in pore size intervals of cementitious composites

Comparative study on pore-connectivity and wettability characteristics of the fresh-water and saline lacustrine tuffaceous shales: triggering mechanisms and multi-scale models for differential reservoir-forming patterns

Although particular attention has been paid to responses of hydrocarbon storage and percolation capacity to the devitrification concerning lacustrine tuffaceous shale reservoirs in recent years, there is still a lack of systematical and comparative investigation on differential patterns and potential triggering mechanisms concerning development of the pore-microfracture systems and characteristics of surface wettability between the fresh-water and saline lacustrine settings, which is of considerable importance in fully understanding of genesis and spatial distribution of dessert reservoir intervals of tuffaceous shale reservoirs, and to provide further conceptual basis for deciphering shale-oil movability of saline lacustrine fine-grained mixed sedimentary sequences. In this study, tuffaceous shales from both the Upper Triassic Yanchang Formation in the Ordos Basin and Middle Permian Jingjingzigou Formation in the Junggar Basin are targeted to unravel the differential behavior of tuff devitrification and potential impacts on reservoir wettability and pore connectivity concerning fresh-water and saline lacustrine settings, and we present new results here from integrated analyses and combined interpretation of FE-SEM, Image Pro Plus (IPP) software image processing, contact angle and spontaneous imbibition experiments. In view of comparative analysis from representative samples, the tuffaceous shales from saline lacustrine environments are characterized by well-developed intergranular-intercrystalline and dissolution pores, and inorganic microfractures, generally yield a higher plane porosity of representative pore-fracture spaces and spontaneous imbibition slopes, a relatively lower average of n-decane contact angles and corresponding wettability parameters. The saline lacustrine tuffaceous shales are thus suspected to have undergone more intense devitrification resulting in a higher amount of devitrification and associated dissolution pores, and a relatively better connectivity between isolated micropore systems with adjacent microfractures. This would significantly facilitate the interface wettability reversal and occurrence of movable hydrocarbon fluid in microscopic reservoir spaces. Finally, a comprehensive and conceptual model is established illustrating the effects of differential devitrification on reservoir-forming patterns concerning tuffaceous shales developed in the fresh-water and saline lacustrine settings, respectively. These findings are of great theoretical and practical significance to enrich theory of high-quality reservoir formation and shale-oil accumulation in saline lacustrine tuffaceous shale reservoirs, and lay the foundation for guiding efficient exploration of continental fine-grained mixed sedimentary sequences.