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Viruses of eukaryotic algae have become an important research focus due to their role(s) in nutrient cycling and top-down control of algal blooms. Omics-based studies have identified a boon of genomic and transcriptional potential among the Nucleocytoviricota, a phylum of large dsDNA viruses which have been shown to infect algal and non-algal eukaryotes. However, little is still understood regarding the infection cycle of these viruses, particularly in how they take over a metabolically active host and convert it into a virocell state. Of particular interest are the roles light and the diel cycle in virocell development. Yet despite such a large proportion of Nucleocytoviricota infecting phototrophs, little work has been done to tie infection dynamics to the presence, and absence, of light. Here, we examine the role of the diel cycle on the physiological and transcriptional state of the pelagophyte Aureococcus anophagefferens while undergoing infection by Kratosvirus quantuckense strain AaV. Our observations demonstrate how infection by the virus interrupts the diel growth and division of this cell strain, and that infection further complicates the system by enhancing export of cell biomass.

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We present the Gaussian Mixture Periodicity Detection Algorithm (GMPDA), a novel method for detecting periodicity in the binary time series of event onsets. The GMPDA addresses the periodicity detection problem by inferring parameters of a generative model. We introduce two models, the Clock Model and the Random Walk Model, which describe distinct periodic phenomena and provide a comprehensive generative framework. The GMPDA demonstrates robust performance in test cases involving single and multiple periodicities, as well as varying noise levels. Additionally, we evaluate the GMPDA on real-world data from recorded leg movements during sleep, where it successfully identifies expected periodicities despite high noise levels. The primary contributions of this paper include the development of two new models for generating periodic event behavior and the GMPDA, which exhibits high accuracy in detecting multiple periodicities even in noisy environments.

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Holter monitoring represents a valuable diagnostic tool to document intermittent arrhythmias in the work-up of, for example, syncope, presyncope, collapse, falls, dizziness, stroke, palpitations, and a rapid heartbeat. In addition, it may help in the diagnosis of intermittent ischemia and channelopathies, particularly in the form of 12-lead Holter monitoring. Continuous ECG registration typically lasts from 24-48 h. The use of Holter monitoring is limited in patients with rare symptoms (< 1â€¯× per month) and in recordings full of artifacts. The interpretation of a Holter recording combines an automatic analysis with a manual reassessment. The clinical relevance of many arrhythmias can only be considered together with symptoms and activity of the patient at the time of the event. Therefore, a patient diary accompanying the ECG recording is crucial. Systematic assessment of the ECG recording and knowledge about a number of pitfalls in Holter monitoring can optimize the interpretation of the recording.

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Structural lattices with quasi-periodic patterns possess interesting dynamic features that can be exploited to control, localize and redirect propagating waves. In this work, we show that the properties of a large class of quasi-periodic locally resonant systems (approximated as periodic, with arbitrarily large period) can be performed by defining an equivalent discrete system. Several properties of wave propagation can a priori be demonstrated with reference to this system. Results in terms of bulk spectrum, showing the Hofstadter butterfly pattern, and of topological modes are then discussed in detail with reference to a simple example of quasi-periodic lattice. This article is part of the theme issue 'Current developments in elastic and acoustic metamaterials science (Part 2)'.

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Settlement is a critical transition in the life history of reef fish, and the timing of this event can have a strong effect on fitness. Key factors that influence settlement timing are predictable lunar cyclic variation in tidal currents, moonlight, and nocturnal predation risk as larvae transition from pelagic to benthic environments. However, populations typically display wide variation in the arrival of settlers over the lunar cycle. This variation is often hypothesized to result from unpredictable conditions in the pelagic environment and bet-hedging by spawning adults. Here, we consider the hypothesis that the timing of spawning and settlement is a strategic response to post-settlement competition. We use a game theoretic model to predict spawning and settlement distributions when fish face a tradeoff between minimizing density-independent predation risk while crossing the reef crest vs. avoiding high competitor density on settlement habitat. In general, we expect competition to spread spawning over time such that settlement is distributed around the lunar phase with the lowest predation risk, similar to an ideal free distribution in which competition spreads competitors across space. We examine the effects of overcompensating density dependence, age-dependent competition, and competition among daily settler cohorts. Our model predicts that even in the absence of stochastic variation in the larval environment, competition can result in qualitative divergence between spawning and settlement distributions. Furthermore, we show that if competitive strength increases with settler age, competition results in covariation between settler age and settlement date, with older larvae settling when predation risk is minimal. We predict that competition between daily cohorts delays peak settlement, with priority effects potentially selecting for a multimodal settlement distribution.

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When a rhythm makes an event predictable, that event is perceived faster, and typically more accurately. However, the experiments showing this used simple tasks, and most manipulated temporal expectancy by using periodic or aperiodic precursors unrelated to stimulus and task. Three experiments tested the generality of these observations in a complex task in which rhythm was intrinsic to, rather than a precursor of, the information needed to respond: listeners averaged the laterality of a stream of noise bursts. We varied presentation rate, degree of periodicity, and average lateralisation. Decisions following a probe tone were fastest after periodic stimuli, and slowest after the most aperiodic stimuli. Without a probe tone, listeners responded sooner during periodic sequences, thus hearing less information. Periodicity did not benefit accuracy overall. This gain in speed but not accuracy for less information is not reported for simpler tasks. Neural entrainment supplemented by cognitive factors provide a tentative explanation. When the task is inherently complex and demands high attention over long durations, both expected-periodic and unexpected-aperiodic stimuli can increase response amplitude, enhancing stimulus representation, but periodicity increases confidence to respond early. Drift diffusion modelling supports this proposal: aperiodicity modulated the decision threshold, but not the drift rate or non-decision time. Together, these new data and the literature point towards task-dependent effects of temporal expectation on decision-making, showing interactions between rhythmic variance, task complexity, and sources of expectation about stimuli. We suggest the implications are worth exploring to extend understanding of rhythmicity on decision-making to everyday situations.

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We propose a hybrid Fourier approximation in an autoregressive fractional integrated moving average (ARFIMA) model, to account for periodic unoberved components in financial time series. We apply this hybrid model on parametric estimation of value at risk (VaR) and expected shortfall (ES). Using crude oil returns, we show that Fourier approximation inclusion significantly accounts for unobserved periodic components in a VaR estimation using exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model under generalized error distribution (GED). Similarly, in VaR estimation, Fourier approximation inclusion significantly accounts for unobserved periodic components using asymmetric power generalized autoregressive conditional heteroscedasticity (APARCH) model under skewed normal distribution (SNORM). For ES estimation, Fourier approximation inclusion only significantly accounts for unobserved periodic components of APARCH under SNORM.

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Compression systems based electromechanical actuators require a good understanding of their dynamics for a better performance. This paper deals with the study of the nonlinear dynamics of an electromechanical system with two rotating arms subjected to a sinusoidal excitation for fluid compression purposes. The physical model integrating two balloons to be compressed by the arms alternately is presented and the mathematical equations traducing their dynamics are established. We emphasize on the influence of some control parameters namely the supply voltage, the discontinuity position and the viscoelastic ratio on the behaviour of the angular displacement of the arms. The study is also done by neglecting the inductance in the electrical part of the system. It is obtained that while the arms exhibit periodic motion during regular movement, compression of the balloons induces a shift to multi-periodic or chaotic dynamics, occasionally reverting to periodicity. Experimental and numerical simulation results demonstrate good agreement, with the R-system approximating more experimental outcomes than the RL-system. These findings hold significant implications for various environmental applications utilizing pump technology.

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The bluntnose sixgill shark (Hexanchus griseus) is a wide-ranged deep-water shark species found off continental and insular shelves. Despite its global distribution, little is known about the reproductive ecology of the species, particularly with regard to the location and timing of important phenological events such as mating and pupping. In this study, we report the landing of a neonate H. griseus individual from an artisanal fishing camp in Baja California Sur, Mexico. This represents only the ninth confirmed record of the species from the Mexican Pacific and the first to report a neonate specimen in Mexican waters. We discuss this specimen in the context of the environmental conditions in which it was found, ultimately suggesting that these shallow coastal waters may be an important pupping ground for H. griseus in the region. Furthermore, the specimen was found during the winter months (whereas all previous reports have suggested H. griseus pups during the summer), implying regional variation in reproductive periodicity, or the presence of multiple reproductive events per year. This study provides novel insight into the reproductive biology of H. griseus and the ecological characteristics of the species in the Northern Mexican Pacific.

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BACKGROUND: The strong invasiveness and rapid expansion of dengue virus (DENV) pose a great challenge to global public health. However, dengue epidemic patterns and mechanisms at a genetic scale, particularly in term of cross-border transmissions, remain poorly understood. Importation is considered as the primary driver of dengue outbreaks in China, and since 1990 a frequent occurrence of large outbreaks has been triggered by the imported cases and subsequently spread to the western and northern parts of China. Therefore, this study aims to systematically reveal the invasion and diffusion patterns of DENV-1 in Guangdong, China from 1990 to 2019. METHODS: These analyses were performed on 179 newly assembled genomes from indigenous dengue cases in Guangdong, China and 5152 E gene complete sequences recorded in Chinese mainland. The genetic population structure and epidemic patterns of DENV-1 circulating in Chinese mainland were characterized by phylogenetics, phylogeography, phylodynamics based on DENV-1 E-gene-based globally unified genotyping framework. RESULTS: Multiple serotypes of DENV were co-circulating in Chinese mainland, particularly in Guangdong and Yunnan provinces. A total of 189 transmission clusters in 38 clades belonging to 22 subgenotypes of genotype I, IV and V of DENV-1 were identified, with 7 Clades of Concern (COCs) responsible for the large outbreaks since 1990. The epidemic periodicity was inferred from the data to be approximately 3 years. Dengue transmission events mainly occurred from Great Mekong Subregion-China (GMS-China), Southeast Asia (SEA), South Asia Subcontinent (SASC), and Oceania (OCE) to coastal and land border cities respectively in southeastern and southwestern China. Specially, Guangzhou was found to be the most dominant receipting hub, where DENV-1 diffused to other cities within the province and even other parts of the country. Genome phylogeny combined with epidemiological investigation demonstrated a clear local consecutive transmission process of a 5C1 transmission cluster (5C1-CN4) of DENV-1 in Guangzhou from 2013 to 2015, while the two provinces of Guangdong and Yunnan played key roles in ongoing transition of dengue epidemic patterns. In contextualizing within Invasion Biology theories, we have proposed a derived three-stage model encompassing the stages of invasion, colonization, and dissemination, which is supposed to enhance our understanding of dengue spreading patterns. CONCLUSIONS: This study demonstrates the invasion and diffusion process of DENV-1 in Chinese mainland within a global genotyping framework, characterizing the genetic diversities of viral populations, multiple sources of importation, and periodic dynamics of the epidemic. These findings highlight the potential ongoing transition trends from epidemic to endemic status offering a valuable insight into early warning, prevention and control of rapid spreading of dengue both in China and worldwide.

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In the tropics, more precisely in equatorial dense rainforest, xylogenesis is driven by a little distinct climatological seasonality, and many tropical trees do not show clear growth rings. This makes retrospective analyses and modeling of future tree performance difficult. This research investigates the presence, the distinctness, and the periodicity of growth ring for dominant tree species in two semi-deciduous rainforests, which contrast in terms of precipitation dynamics. Eighteen tree species common to both forests were investigated. We used the cambial marking technique and then verified the presence and periodicity of growth-ring boundaries in the wood produced between pinning and collection by microscopic and macroscopic observation. The study showed that all eighteen species can form visible growth rings in both sites. However, the periodicity of ring formation varied significantly within and between species, and within sites. Trees from the site with clearly defined dry season had a higher likelihood to form periodical growth rings compared to those from the site where rainfall seasonality is less pronounced. The distinctness of the formed rings however did not show a site dependency. Periodical growth-ring formation was more likely in fast-growing trees. Furthermore, improvements can be made by a detailed study of the cambial activity through microcores taken at high temporal resolution, to get insight on the phenology of the lateral meristem.

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While rhythm can facilitate and enhance many aspects of behavior, its evolutionary trajectory in vocal communication systems remains enigmatic. We can trace evolutionary processes by investigating rhythmic abilities in different species, but research to date has largely focused on songbirds and primates. We present evidence that cetaceans-whales, dolphins, and porpoises-are a missing piece of the puzzle for understanding why rhythm evolved in vocal communication systems. Cetaceans not only produce rhythmic vocalizations but also exhibit behaviors known or thought to play a role in the evolution of different features of rhythm. These behaviors include vocal learning abilities, advanced breathing control, sexually selected vocal displays, prolonged mother-infant bonds, and behavioral synchronization. The untapped comparative potential of cetaceans is further enhanced by high interspecific diversity, which generates natural ranges of vocal and social complexity for investigating various evolutionary hypotheses. We show that rhythm (particularly isochronous rhythm, when sounds are equally spaced in time) is prevalent in cetacean vocalizations but is used in different contexts by baleen and toothed whales. We also highlight key questions and research areas that will enhance understanding of vocal rhythms across taxa. By coupling an infraorder-level taxonomic assessment of vocal rhythm production with comparisons to other species, we illustrate how broadly comparative research can contribute to a more nuanced understanding of the prevalence, evolution, and possible functions of rhythm in animal communication.

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Many insects depend on high-altitude, migratory movements during part of their life cycle. The daily timing of these migratory movements is not random, e.g. many insect species show peak migratory flight activity at dawn, noon or dusk. These insects provide essential ecosystem services such as pollination but also contribute to crop damage. Quantifying the diel timing of their migratory flight and its geographical and seasonal variation, are hence key towards effective conservation and pest management. Vertical-looking radars provide continuous and automated measurements of insect migration, but large-scale application has not been possible because of limited availability of suitable devices. Here, we quantify patterns in diel flight periodicity of migratory insects between 50 and 500 m above ground level during March-October 2021 using a network of 17 vertical-looking radars across Europe. Independent of the overall daily migratory movements and location, peak migratory movements occur around noon, during crepuscular evening and occasionally the morning. Relative daily proportions of insect migration intensity and traffic during the diel phases of crepuscular-morning, day, crepuscular-evening and night remain largely equal throughout May-September and across Europe. These findings highlight, extend, and generalize previous regional-scale findings on diel migratory insect movement patterns to the whole of temperate Europe. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

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BACKGROUND: Several models have been used to predict outbreaks during the COVID-19 pandemic, with limited success. We developed a simple mathematical model to accurately predict future epidemic waves. METHODS: We used data from the Ministry of Health, Labour and Welfare of Japan for newly confirmed COVID-19 cases. COVID-19 case data were summarized as weekly data, and epidemic waves were visualized and identified. The periodicity of COVID-19 in each prefecture of Japan was confirmed using time-series analysis and the autocorrelation coefficient, which was used to investigate the longer-term pattern of COVID-19 cases. Outcomes using the autocorrelation coefficient were visualized via a correlogram to capture the periodicity of the data. An algorithm for a simple prediction model of the seventh COVID-19 wave in Japan comprised three steps. Step 1: machine learning techniques were used to depict the regression lines for each epidemic wave, denoting the "rising trend line"; Step 2: an exponential function with good fit was identified from data of rising straight lines up to the sixth wave, and the timing of the rise of the seventh wave and speed of its spread were calculated; Step 3: a logistic function was created using the values calculated in Step 2 as coefficients to predict the seventh wave. The accuracy of the model in predicting the seventh wave was confirmed using data up to the sixth wave. RESULTS: Up to March 31, 2023, the correlation coefficient value was approximately 0.5, indicating significant periodicity. The spread of COVID-19 in Japan was repeated in a cycle of approximately 140 days. Although there was a slight lag in the starting and peak times in our predicted seventh wave compared with the actual epidemic, our developed prediction model had a fairly high degree of accuracy. CONCLUSION: Our newly developed prediction model based on the rising trend line could predict COVID-19 outbreaks up to a few months in advance with high accuracy. The findings of the present study warrant further investigation regarding application to emerging infectious diseases other than COVID-19 in which the epidemic wave has high periodicity.

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A massive statistical analysis based on the autocorrelation function of the circular code X observed in genes is performed on the (eukaryotic) introns. Surprisingly, a circular code periodicity 0 modulo 3 is identified in 5 groups of introns: birds, ascomycetes, basidiomycetes, green algae and land plants. This circular code periodicity, which is a property of retrieving the reading frame in (protein coding) genes, may suggest that these introns have a coding property. In a well-known way, a periodicity 1 modulo 2 is observed in 6 groups of introns: amphibians, fishes, mammals, other animals, reptiles and apicomplexans. A mixed periodicity modulo 2 and 3 is found in the introns of insects. Astonishing, a subperiodicity 3 modulo 6 is a common statistical property in these 3 classes of introns. When the particular trinucleotides N1N2N1 of the circular code X are not considered, the circular code periodicity 0 modulo 3, hidden by the periodicity 1 modulo 2, is now retrieved in 5 groups of introns: amphibians, fishes, other animals, reptiles and insects. Thus, 10 groups of introns, taxonomically different, out of 12 have a coding property related to the reading frame retrieval. The trinucleotides N1N2N1 are analysed in the 216 maximal C3 self-complementary trinucleotide circular codes. A hexanucleotide code (words of 6 letters) is proposed to explain the periodicity 3 modulo 6. It could be a trace of more general circular codes at the origin of the circular code X.

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The periodicity of parasite egg excretion refers to variations in the number of eggs produced across time, with significant implications in optimizing diagnostic procedures and conducting the Fecal Egg Count Reduction Test (FECRT). Here, we explore whether Ascaridia galli egg excretion varies across time under Philippine conditions, thus informing the best time to collect fecal samples during flock health examination. A time-course analysis was performed in chickens (N = 12) experimentally infected with A. galli, isolated from a naturally infected Philippine native chicken. We examined the fecal egg per gram (EPG) count at 3-h intervals for 3 days, starting from 5:00-6:00 h AM to the following day at 1:00-2:00 h AM. Our results showed a consistent daily egg excretion pattern with a peak EPG count in the morning that abruptly declined in the afternoon and lowest in the evening. The EPG counts correlated with the amount of excreta produced, suggesting that A. galli fecundity corresponds to the timing of host defecation. Our results imply that the best time to collect fecal samples for A. galli diagnosis and FECRT in Philippine conditions should be from sunrise until late morning when parasite EPG count and host excreta production are at their highest.

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Resolving the role of galactic processes in Solar System/Earth events necessitates a robust temporal model. However, astrophysical theory diverges with models varying from long-lasting spiral density waves with uniform pattern speeds and arm structures to others with fleeting and unpredictable features. Here, we address those issues with (1) an analysis of patterns of impact periodicity over periods of 10 to 250 million years (Myr) using circular statistics and (2), an independent logarithmic spiral arm model fitted to arm tangents of 870 micron dust. Comparison of the impact periodicity results with the best-fit spiral arm model suggests a galactic period of 660 Myr, i.e. 165 Myr to pass from one arm to the next in a four spiral arm model, with the most recent arm passage around 52 million years ago (Ma). The oldest impact ages imply that the emerging galactic chronology model is robust for at least the last 2 Gyr. The arm-passing time is consistent with spectral analyses of zircons across 3 Gyrs. Overall, the model provides a temporal framework against which to test hypotheses of galactic mechanisms for global events such as mass extinctions and superchrons.

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In infectious disease models, it is known that mechanisms such as births, seasonality in transmission and pathogen evolution can generate oscillations in infection numbers. We show how waning immunity is also a mechanism that is sufficient on its own to enable sustained oscillations. When previously infected or vaccinated individuals lose full protective immunity, they become partially susceptible to reinfections. This partial immunity subsequently wanes over time, making individuals more susceptible to reinfections and potentially more infectious if infected. Losses of full and partial immunity lead to a surge in infections, which is the precursor of oscillations. We present a discrete-time Susceptible-Infectious-Immune-Waned-Infectious (SIRWY) model that features the waning of fully immune individuals (as a distribution of time at which individuals lose fully immunity) and the gradual loss of partial immunity (as increases in susceptibility and potential infectiousness over time). A special case of SIRWY is the discrete-time SIRS model with geometric distributions for waning and recovery. Its continuous-time analogue is the classic SIRS with exponential distributions, which does not produce sustained oscillations for any choice of parameters. We show that the discrete-time version can produce sustained oscillations and that the oscillatory regime disappears as discrete-time tends to continuous-time. A different special case of SIRWY is one with fixed times for waning and recovery. We show that this simpler model can also produce sustained oscillations. In conclusion, under certain feature and parameter choices relating to how exactly immunity wanes, fluctuations in infection numbers can be sustained without the need for any additional mechanisms.

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Global warming and eutrophication are known to increase the prevalence of cyanobacterial blooms, posing a severe threat to the ecological stability and sustainability of water bodies. The long-term (over an annual time frame) effect of UV radiation on cyanobacterial blooms in lakes are rarely discussed though the substantial effects of high-intensity UV radiation on the growth inhibition of marine phytoplankton were studied. Here, we employed the datasets on surface solar UV radiation, nitrogen and phosphorus concentrations, and the annual scales and frequencies of cyanobacterial blooms in lakes across long-term spatial scales to probe the relationship of UV radiation with cyanobacterial blooms. The results indicated that enhanced solar UV radiation may unintentionally stimulate cyanobacterial growth and favor the expansions of cyanobacterial blooms in lakes around the world. The fluctuating UV radiation significantly affects the annual scales of cyanobacterial blooms in both eutrophic and oligotrophic lakes. Solar UV radiation enhances the positive impact of rising phosphorus levels on cyanobacterial blooms because UV radiation prompts the synthesis of polyphosphate in cyanobacteria cells, which helps cyanobacteria to alleviate the stress of UV light. The scales of cyanobacterial blooms are significantly impacted by solar UV radiation intensities as opposed to the annual frequency of cyanobacterial blooms. Furthermore, solar UV radiation fluctuation with a 9-year period over a 14-year main cycles significantly affects the periodicities of cyanobacterial blooms in global lakes, which provides a basis for predicting the peak value of the scales of cyanobacterial blooms in lakes. These findings opened up new avenues of inquiry into the mechanism and management strategies of cyanobacterial blooms in lakes worldwide.