Clock Model Research Articles

Adaptive Kalman filter-based time synchronization algorithm for civil aviation communication

Abstract The traditional synchronization algorithms often struggle to meet the stringent requirements of civil aviation communication. This paper proposes an adaptive time synchronization algorithm based on Kalman filtering (KF) to enhance the synchronization performance of civil aviation communication systems. Firstly, a dynamic clock model is established considering the characteristics of civil aviation communication, with clock offset and drift as state variables. Moreover, a step-by-step detection strategy is employed to adaptively adjust the detection range based on the statistical characteristics of synchronization errors, thereby improving the algorithm's robustness and convergence speed. To evaluate the algorithm's performance, a civil aviation communication system-level simulation platform is built based on ICAO standards, and various typical scenarios, such as take-off, landing, and cruising, are designed. Simulation results demonstrate that the proposed algorithm achieves significant improvements in synchronization accuracy, convergence speed, and robustness compared to classical synchronization algorithms based on phase-locked loops (PLL) and early late gates (ELD).

Engineering a Josephson junction chain for the simulation of the quantum clock model

Engineering a Josephson junction chain for the simulation of the quantum clock model

BKT transitions of the XY and six-state clock models on the various two-dimensional lattices

Abstract In a two-dimensional (2D) spin system, the XY model, characterized by planar rotational symmetry, exhibits a unique phenomenon known as the Berezinskii-Kosterlitz-Thouless (BKT) transition. In contrast, the clock model, which introduces discrete rotational symmetry, exhibits the BKT transition at two different temperatures due to this discreteness.
In this study, we numerically investigate the BKT transition for XY and six-state clock models over various two-dimensional lattices. We employ two primary methods: the Monte Carlo method, which analyzes the size dependence of the ratio of the correlation functions for two different distances, and a machine-learning approach to classify the different phases --- namely, the low-temperature ordered phase, the intermediate BKT phase, and the high-temperature disordered phase.
We identify the BKT transition temperatures for the XY and six-state models on honeycomb, kagome, and diced lattices. 
Combined with the previously calculated data for the triangular lattice, we then compare these values with the second-order phase transition temperatures of the 2D Ising model, for which exact solutions are known. 
Our results indicate that the ratio of the BKT transition temperatures for each lattice relative to the Ising model transition temperatures are close, although the values are not universal. 

Magnetocaloric Effect for a Q-Clock-Type System.

In this work, we study the magnetocaloric effect (MCE) in a working substance corresponding to a square lattice of spins with Q possible orientations, known as the "Q-state clock model". When the Q-state clock model has Q≥5 possible configurations, it presents the famous Berezinskii-Kosterlitz-Thouless (BKT) phase associated with vortex states. We calculate the thermodynamic quantities using Monte Carlo simulations for even Q numbers, ranging from Q=2 to Q=8 spin orientations per site in a lattice. We use lattices of different sizes with N=L×L=82,162,322,642,and1282 sites, considering free boundary conditions and an external magnetic field varying between B=0 and B=1.0 in natural units of the system. By obtaining the entropy, it is possible to quantify the MCE through an isothermal process in which the external magnetic field on the spin system is varied. In particular, we find the values of Q that maximize the MCE depending on the lattice size and the magnetic phase transitions linked with the process. Given the broader relevance of the Q-state clock model in areas such as percolation theory, neural networks, and biological systems, where multi-state interactions are essential, our study provides a robust framework in applied quantum mechanics, statistical physics, and related fields.

Early–middle Permian Mediterranean gorgonopsian suggests an equatorial origin of therapsids

Therapsids were a dominant component of middle–late Permian terrestrial ecosystems worldwide, eventually giving rise to mammals during the early Mesozoic. However, little is currently known about the time and place of origin of Therapsida. Here we describe a definitive therapsid from the lower–?middle Permian palaeotropics, a partial skeleton of a gorgonopsian from the island of Mallorca, western Mediterranean. This specimen represents, to our knowledge, the oldest gorgonopsian record worldwide, and possibly the oldest known therapsid. Using emerging relaxed clock models, we provide a quantitative timeline for the origin and early diversification of therapsids, indicating a long ghost lineage leading to the evolutionary radiation of all major therapsid clades within less than 10 Myr, in the aftermath of Olson’s Extinction. Our findings place this unambiguous early therapsid in an ancient summer wet biome of equatorial Pangaea, thus suggesting that the group originated in tropical rather than temperate regions.

Modeling the within-host dynamics of Plasmodium vivax hypnozoite activation: An analysis of the SPf66 vaccine trial

Plasmodium vivax parasites can lie dormant in the liver as hypnozoites, activating weeks to months after sporozoite inoculation to cause relapsing malarial illness. It is not known what biological processes govern hypnozoite activation. We use longitudinal data from the most detailed cohort study ever conducted in an area where both Plasmodium falciparum and P. vivax were endemic to fit a simple within-host mathematical model of P. vivax hypnozoite activation. 1,344 children living on the Thailand-Myanmar border were followed daily for 21 mo. There were 2,504 vivax and 1,164 falciparum malaria symptomatic episodes recorded over 1988 person-years. The model assumes that hypnozoites activate independently at a constant rate ("exponential clock model"). When this model was embedded in a stochastic framework for repeated infectious mosquito bites, with seasonality inferred from the incidence of clinical falciparum malaria episodes, it explained the observed temporal patterns of multiple (up to 13) recurrent vivax malaria episodes. Under this model, we estimate the mean dormancy period for a single hypnozoite to be 6 mo (i.e., a half-life of 4 mo). We use the calibrated within-host model to characterize population-level overdispersion in the risk of relapse, and assess the potential utility of a serological test for radical cure in low transmission settings. We show that mefloquine treatment of falciparum malaria eliminates early vivax relapses; and that there are substantially more P. vivax recurrences than expected under the model following artesunate monotherapy treatment for falciparum malaria. These results suggest that hypnozoites can be activated by symptomatic malarial illness.

Multidrug-Resistant Klebsiella pneumoniae Strains in a Hospital: Phylogenetic Analysis to Investigate Local Epidemiology.

Multidrug-resistant Klebsiella pneumoniae is a significant healthcare challenge that particularly affects vulnerable patients through opportunistic nosocomial infections. Surveillance is crucial for monitoring the prevalence of these infections. Eighty-four KPC K. pneumoniae strains (2019-2022) were collected from patients admitted in Fondazione Policlinico Universitario Campus Bio-Medico. Strains were identified by MALDI-TOF and tested for antimicrobial susceptibility, and gene amplification was performed to identify the different blaKPC variants. Phylogenetic reconstructions were carried out using Bayesian methods. Additionally, to create a Bayesian skyline plot (BSP), additional analyses were conducted, running a simulation of 100 million generations under a Bayesian skyline model along with the uncorrelated log-normal relaxed clock model. To identify potential subgroups within genetic clusters and evaluate genetic variability among sequences, principal coordinate analysis (PCoA) was performed. In total, 84 Klebsiella pneumoniae isolates were classified as multidrug-resistant (MDR), characterized by resistance to three or more antibiotic classes, including carbapenems, and testing positive for KPC gene presence, and were included in the study. The Bayesian evolutionary tree for K. pneumoniae showed strongly supported branches but no genetic structure related to sampling dates or hospital departments. Phylogenetic analysis revealing a 73-year evolutionary span of K. pneumoniae strains. PCoA analysis identified three genetic outliers from 2022 and one from 2021, indicating higher genetic distances. The Bayesian skyline plot revealed increased genetic variability peaking at the end of 2019, followed by stabilization from early 2020 onward, with no significant changes in genetic variability thereafter. Overall, the study found no genetic structure correlating with sampling date or hospital department, suggesting significant variability in pathogen introduction during the pandemic. The increase in multidrug-resistant K. pneumoniae was linked to the influx of severe COVID-19 cases, prolonged hospitalizations, and heightened broad-spectrum antibiotic use, which likely facilitated resistance development and transmission amidst altered infection control practices.

Spatial Optical Simulator for Classical Statistical Models.

Optical simulators for the Ising model have demonstrated great promise for solving challenging problems in physics and beyond. Here, we develop a spatial optical simulator for a variety of classical statistical systems, including the clock, XY, Potts, and Heisenberg models, utilizing a digital micromirror device composed of a large number of tiny mirrors. Spins, with desired amplitudes or phases of the statistical models, are precisely encoded by a patch of mirrors with a superpixel approach. Then, by modulating the light field in a sequence of designed patterns, the spin-spin interaction is realized in such a way that the Hamiltonian symmetries are preserved. We successfully simulate statistical systems on a fully connected network, with ferromagnetic or Mattis-type random interactions, and observe the corresponding phase transitions between the paramagnetic and the ferromagnetic or spin-glass phases. Our results largely extend the research scope of spatial optical simulators and their versatile applications.

Bayesian Total-Evidence Dating Reshapes the Age and Historical Biogeography of Parnassiinae

Although incomplete, the fossil record offers direct evidence for the existence of a lineage, providing insights into its age and geographic location. Reconstructing time-calibrated phylogenies, including both extant and fossil taxa as lineages (total-evidence dating) under the fossilized birth-death process, can provide new information about the phylogenetic position of fossil specimens, the time at which they diverged from closely related species, and can impact inferences of clades’ historical biogeography. Here, we focus on the origin and radiation of Apollo butterflies (Papilionidae: Parnassiinae), whose origin has been estimated in the late Eocene in Central Asia. The two fossil taxa recovered in the subfamily Parnassiinae, dated to the late Oligocene (†Thaites ruminiana Scudder) and late Miocene (†Doritites bosniaskii Rebel) in the Western Palearctic, thus challenge the Central Asian origin. We performed a Bayesian total-evidence dating approach to explore the impact of dating analyses and past fossil distributions on the estimation of the evolutionary history of the group. We obtained a more credible dating and historical biogeography for the group, placing its origin in the late Paleocene (ca. 57 Ma) in the Western Palearctic + Western Asia and Caucasus regions, followed by dispersals to Central Asia and the Himalayas. This study also highlights the importance of investigating fossil position in addition to clock partitioning and models for molecular dating. Furthermore, we confirm that a few fossils are sufficient to cast doubt on the origin and biogeographic history of a group, especially when those fossils were dispersed outside of the current center of diversity.

A clock model of regional tau‐PET accumulation and cognitive decline in sporadic early‐onset Alzheimer’s disease

AbstractBackgroundThe timing of tau‐PET accumulation and cognitive decline in sporadic early‐onset Alzheimer’s disease (eoAD, age‐at‐onset<65) has not been established and is needed to optimize tau‐PET as an outcome measure in clinical trials. Here we leverage large‐sample, longitudinal data from the Longitudinal Early‐onset Alzheimer’s Disease Study (LEADS) to model tau‐PET accumulation in three regions relative to cognitive decline.MethodLongitudinal [18F]Flortaucipir‐PET (FTP) and CDR‐SB scores were acquired in 195 amyloid‐PET‐positive, sporadic eoAD patients with MCI or mild dementia due to AD at baseline (Table 1). FTP scans were referenced against inferior cerebellar GM, and mean SUVRs calculated in three meta‐ROIs comprising temporal, parietal, and frontal association cortices (Figure 1A). Generalized additive models estimated nonlinear relations between: (1) baseline SUVRs and annualized rates‐of‐change in each meta‐ROI, and (2) baseline CDR‐SB and annualized rates‐of‐change in cognition. Integrating these baseline‐by‐change functions yielded regional FTP and CDR‐SB trajectories over time. An exhaustive search algorithm identified optimal time‐shifts between each regional tau trajectory and CDR‐SB progression that minimized the error between model‐predicted and observed data at baseline. This time‐shifting procedure was repeated in a held‐out dataset of 184 eoAD patients to assess out‐of‐sample reproducibility (Table 1).ResultFTP SUVRs and CDR‐SB scores increased longitudinally in most patients (Figure 1B,C). Baseline SUVR by rate‐of‐change associations were inverted U‐shaped in each meta‐ROI (Figure 1D), and similar associations were found for CDR‐SB progression (Figure 1E). Time‐shift estimation in the training dataset converged on a single, best‐fitting model in which temporal and parietal FTP accumulation led clinical onset by 4.5 years, while frontal FTP accumulation began 0.5 years before clinical onset (Figure 2A). The replication dataset yielded nearly identical results (Figure 2B). We estimate that the full timecourse of FTP accumulation and cognitive decline occurs over ∼16 years from earliest detectable change in FTP.ConclusionTau‐PET accumulation in the frontal meta‐ROI immediately precedes cognitive decline and tracks closely with clinical progression in eoAD, while temporoparietal tau‐PET is prominent at clinical onset and plateaus as dementia worsens. For clinical trials in symptomatic patients, temporal and parietal tau‐PET may therefore aid staging and inclusion criteria, while frontal tau‐PET is likely superior for monitoring longitudinal change.

A clock model of regional tau‐PET accumulation and cognitive decline in sporadic early‐onset Alzheimer's disease

A clock model of regional tau‐PET accumulation and cognitive decline in sporadic early‐onset Alzheimer's disease

Bayesian tip-dated timeline for diversification and major biogeographic events in Muroidea (Rodentia), the largest mammalian radiation

BackgroundExtinct organisms provide vital information about the time of origination and biogeography of extant groups. The development of phylogenetic methods to study evolutionary processes through time has revolutionized the field of evolutionary biology and led to an unprecedented expansion of our knowledge of the tree of life. Recent developments applying Bayesian approaches, using fossil taxa as tips to be included alongside their living relatives, have revitalized the use of morphological data in evolutionary tree inferences. Eumuroida rodents represent the largest group of mammals including more than a quarter of all extant mammals and have a rich fossil record spanning the last ~ 45 million years. Despite this wealth of data, our current understanding of the classification, major biogeographic patterns, and divergence times for this group comes from molecular phylogenies that use fossils only as a source of node calibrations. However, node calibrations impose several constraints on tree topology and must necessarily make a priori assumptions about the placement of fossil taxa without testing their placement in the tree.ResultsWe present the first morphological dataset with extensive fossil sampling for Muroidea. By applying Bayesian morphological clocks with tip dating and process-based biogeographic models, we provide a novel hypothesis for muroid relationships and revised divergence times for the clade that incorporates uncertainty in the placement of all fossil species. Even under strong violation of the clock model, we found strong congruence between results for divergence times, providing a robust timeline for muroid diversification. This new timeline was used for biogeographic analyses, which revealed a dynamic scenario mostly explained by dispersal events between and within the Palearctic and North African regions.ConclusionsOur results provide important insights into the evolution of Muroidea rodents and clarify the evolutionary pathways of their main lineages. We exploited the advantage of tip dating Bayesian approaches in morphology-based datasets and provided a classification of the largest superfamily of mammals resulting from robust phylogenetic inference, inferring the biogeographical history, diversification, and divergence times of its major lineages.

Examining the molecular clock hypothesis for the contemporary evolution of the rabies virus.

The molecular clock hypothesis assumes that mutations accumulate on an organism's genome at a constant rate over time, but this assumption does not always hold true. While modelling approaches exist to accommodate deviations from a strict molecular clock, assumptions about rate variation may not fully represent the underlying evolutionary processes. There is considerable variability in rabies virus (RABV) incubation periods, ranging from days to over a year, during which viral replication may be reduced. This prompts the question of whether modelling RABV on a per infection generation basis might be more appropriate. We investigate how variable incubation periods affect root-to-tip divergence under per-unit time and per-generation models of mutation. Additionally, we assess how well these models represent root-to-tip divergence in time-stamped RABV sequences. We find that at low substitution rates (<1 substitution per genome per generation) divergence patterns between these models are difficult to distinguish, while above this threshold differences become apparent across a range of sampling rates. Using a Tanzanian RABV dataset, we calculate the mean substitution rate to be 0.17 substitutions per genome per generation. At RABV's substitution rate, the per-generation substitution model is unlikely to represent rabies evolution substantially differently than the molecular clock model when examining contemporary outbreaks; over enough generations for any divergence to accumulate, extreme incubation periods average out. However, measuring substitution rates per-generation holds potential in applications such as inferring transmission trees and predicting lineage emergence.

Noise-induced entrainment of the circadian clock by thermoperiods in tomato: A computational approach

The endogenous circadian rhythm (approximately 24 h) allows plants to adapt to daily light and temperature variations. Although the mechanism of photoperiod entrainment has been studied extensively, entrainment to diurnal temperature rhythms remains poorly understood. Here we investigate the stochastic entrainment of the circadian clock in the model crop tomato, subject to different thermoperiods. We first proposed the deterministic model of the thermoresponsive circadian clock. The expressions of the circadian clock genes under constant warm temperature (29 ℃) were quantified by RT-qPCR for basal parameters estimation through minimizing the cost function. Model simulations by the stochastic simulation algorithm showed warm temperatures resulting in an advanced phase for approximately 3–4 h. A few hundred molecules for the system size of the stochastic model were sufficient to engage the robust oscillations. Multiple temperature inputs and abnormal temperature cycles similarly showed the invariant robustness of the oscillations. In addition, phases of the core circadian elements were remarkably correlated linearly with periods under temperature cycles. Whereas, the phases were correlated with the duration of daily warm temperature stimuli in a polynomial mode.

Ediacaran origin and Ediacaran-Cambrian diversification of Metazoa.

The timescale of animal diversification has been a focus of debate over how evolutionary history should be calibrated to geologic time. Molecular clock analyses have invariably estimated a Cryogenian or Tonian origin of animals while unequivocal animal fossils first occur in the Ediacaran. However, redating of key Ediacaran biotas and the discovery of several Ediacaran crown-Metazoa prompt recalibration of molecular clock analyses. We present revised fossil calibrations and use them in molecular clock analyses estimating the timescale of metazoan evolutionary history. Integrating across uncertainties including phylogenetic relationships, clock model, and calibration strategy, we estimate Metazoa to have originated in the early Ediacaran, Eumetazoa in the middle Ediacaran, and Bilateria in the upper Ediacaran, with many crown-phyla originating across the Ediacaran-Cambrian interval or elsewise fully within the Cambrian. These results are in much closer accord with the fossil record, coinciding with marine oxygenation, but they reject a literal reading of the fossil record.

Human Supplementation with AM3, Spermidine, and Hesperidin Enhances Immune Function, Decreases Biological Age, and Improves Oxidative-Inflammatory State: A Randomized Controlled Trial.

The positive effect of AM3, spermidine, and hesperidin, which have antioxidant and anti-inflammatory properties, on immunity is known, but their effect on the rate of aging, known as biological age (BA), is unclear. This work aims to test if the intake of a blend of AM3 (150 mg), spermidine (0.6 mg), and hesperidin (50 mg) for 2 months could decrease BA and improve immunity, redox, and inflammatory states. For this, 41 participants (30-63 years) were randomly divided into placebo and supplement groups. The supplement group took two capsules daily with AM3, spermidine, and hesperidin for two months, while the placebo group took capsules containing only calcium phosphate and talcum powder. Before and after the treatment, peripheral blood was collected. Immune function was assessed in leukocytes, redox state in whole-blood cells, erythrocytes, and plasma, and cytokine concentration in both mononuclear cell cultures and plasma. Finally, the Immunity Clock model was applied to determine BA. The results show that the intake of this blend improves the immune functions that constitute the Immunity Clock, decreasing BA by 11 years and reducing the oxidative-inflammatory state of the participants. Therefore, this supplement can be proposed as a strategy to rejuvenate BA and achieve healthy aging.

Assessing the effect of model specification and prior sensitivity on Bayesian tests of temporal signal.

Our understanding of the evolution of many microbes has been revolutionised by the molecular clock, a statistical tool to infer evolutionary rates and timescales from analyses of biomolecular sequences. In all molecular clock models, evolutionary rates and times are jointly unidentifiable and 'calibration' information must therefore be used. For many organisms, sequences sampled at different time points can be employed for such calibration. Before attempting to do so, it is recommended to verify that the data carry sufficient information for molecular dating, a practice referred to as evaluation of temporal signal. Recently, a fully Bayesian approach, BETS (Bayesian Evaluation of Temporal Signal), was proposed to overcome known limitations of other commonly used techniques such as root-to-tip regression or date randomisation tests. BETS requires the specification of a full Bayesian phylogenetic model, posing several considerations for untangling the impact of model choice on the detection of temporal signal. Here, we aimed to (i) explore the effect of molecular clock model and tree prior specification on the results of BETS and (ii) provide guidelines for improving our confidence in molecular clock estimates. Using microbial molecular sequence data sets and simulation experiments, we assess the impact of the tree prior and its hyperparameters on the accuracy of temporal signal detection. In particular, highly informative priors that are inconsistent with the data can result in the incorrect detection of temporal signal. In consequence, we recommend: (i) using prior predictive simulations to determine whether the prior generates a reasonable expectation of parameters of interest, such as the evolutionary rate and age of the root node, (ii) conducting prior sensitivity analyses to assess the robustness of the posterior to the choice of prior, and (iii) selecting a molecular clock model that reasonably describes the evolutionary process.

Epistemic uncertainty challenges aging clock reliability in predicting rejuvenation effects.

Epigenetic aging clocks have been widely used to validate rejuvenation effects during cellular reprogramming. However, these predictions are unverifiable because the true biological age of reprogrammed cells remains unknown. We present an analytical framework to consider rejuvenation predictions from the uncertainty perspective. Our analysis reveals that the DNA methylation profiles across reprogramming are poorly represented in the aging data used to train clock models, thus introducing high epistemic uncertainty in age estimations. Moreover, predictions of different published clocks are inconsistent, with some even suggesting zero or negative rejuvenation. While not questioning the possibility of age reversal, we show that the high clock uncertainty challenges the reliability of rejuvenation effects observed during invitro reprogramming before pluripotency and throughout embryogenesis. Conversely, our method reveals a significant age increase after invivo reprogramming. We recommend including uncertainty estimation in future aging clock models to avoid the risk of misinterpreting the results of biological age prediction.

Unclocklike Oscillators with Frequency Memory for the Entrainment of Biological Clocks

Entrainment experiments on the vertebrate segmentation clock have revealed that embryonic oscillators actively change their internal frequency to adapt to the driving signal. This is not consistent with either a one-dimensional clock model or a limit-cycle model, but rather it suggests a new “unclocklike” behavior. In this work, we propose simple, biologically realistic descriptions of such internal frequency adaptation, where a phase oscillator activates a memory variable controlling the oscillator's frequency. We study two opposite limits for the control of the memory variable, one with a smooth phase-averaging memory field, and the other with a pulsatile, phase-dependent activation. Both models recapitulate intriguing properties of the entrained segmentation clock, such as very broad Arnold tongues and an entrainment phase plateauing with detuning. We compute analytically multiple properties of such systems, such as entrainment phases and cycle shapes. We further describe new phenomena, including hysteresis in entrainment, bistability in the frequency of the entrained oscillator, and probabilistic entrainment. Our work shows that oscillators with frequency memory can exhibit new classes of unclocklike properties that can be tested through experimental entrainment. Published by the American Physical Society 2024

LEO satellite clock modeling and its benefits for real-time LEO PPP timing

In the kinematic Precise Orbit Determination (POD) process for low earth orbit (LEO) satellites, a significant correlation exists between the orbital and clock parameters. Here, a LEO satellite clock model is proposed to enhance the Precise Point positioning (PPP) timing and time synchronization during the LEO orbit/clock determination. The GRACE-FO satellite was utilized to achieve PPP timing and time transfer for LEO satellites with the real-time (RT) products provided by three analysis centers, namely Centre National d’Etudes Spatiales (CNES), GMV Aerospace and Defense (GMV), and Wuhan Technical University (WHU). For the frequency stability of the PPP timing for LEO satellites, the short-term stability (1280 s) is about 10−13 level, and the long-term stability (10,240 s) is about 10−14 level. Compared with the traditional PPP method (Scheme1), the LEO satellite clock model (Scheme2) is capable of significantly reducing the noise, regardless of whether it is PPP timing or PPP time synchronization. The frequency stability of Scheme 1 shows an improvement in short-term stability (1280 s) by about 8 %-72 % and the max improvement of the long-term stability (10240 s) by approximately 39 %, the result also shows a better improvement in LEO time synchronization.