Variety Of Time Scales Research Articles

Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories.

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.

Seminal electromagnetic fields from preinflation

We investigate the geometric dynamics of the primordial electric and magnetic fields during the early stages of the universe by extending a recently introduced quantum algebra (Bellini et al., 2023). We work on an extended model of gravity that considers the boundary terms from the Einstein–Hilbert action as geometric quantum fluctuations of the spacetime. We propose that the extended Riemann manifold is generated by a new connection δΓˆαβμ. This connection contains geometric information about the fluctuations of gravitational and electromagnetic fields in the vacuum, which could have been crucial during the primordial stages of the universe’s evolution. We revisit a preinflationary cosmological model (Bellini, 2023) with a variable time scale and negative spatial curvature, such that the universe begins with a null initial background energy density. We observed the emergence of large scale magnetic fields starting from small values during the early phases of the universe’s evolution. Subsequently, these fields decrease to reach present day values on the order of δBˆ≃10−12G on cosmological scales (between 1024 and 1026 meters). This significant deviation from inflationary models eliminates the need to impose excessively large initial values on these fields.

Evidence for rapid variability at high energies in GRBs

ABSTRACT Intrinsic variability was searched for in arrival times of six gamma-ray bursts (GRBs) at high energies – between 30 MeV and 2 GeV – detected by the Fermi satellite’s Large Area Telescope (LAT). The GRBs were selected from the Fermi LAT catalogue with preference for events with numerous photons, a strong initial pulse, and measured redshifts. Three long GRBs and three short GRBs were selected and tested. Two different variability-detection algorithms were deployed, one counting photons in pairs, and the other multiplying time gaps between photons. In both tests, a real GRB was compared to 1000 Monte Carlo versions of itself smoothed over a wide range of different time-scales. The minimum detected variability time-scales for long bursts (GRB 080916C, GRB 090926A, GRB 131108A) was found to be (0.005, 10.0, 10.0) s for the photon pair test and (2.0, 20.0, 10.0) s for the time-gap multiplication test. Additionally, the minimum detected variability time-scales for the short bursts (GRB 090510, GRB 140619B, GRB 160709A) was found to be (0.05, 0.01, 20.0) s for the photon pair test and (0.05, 0.01, 20.0) s for the gap multiplication test. Statistical uncertainties in these times are about a factor of 2. The durations of these variability time-scales may be used to constrain the geometry, dynamics, speed, cosmological dispersion, Lorentz-invariance violations, weak equivalence principle violations, and GRB models.

Machine learning predictive model for dynamic response of rising bubbles impacting on a horizontal wall

The integrated behavior of the fluid flow, encompassing variation of some specific response, has received more attention than mere examination of velocity and pressure distributions. A machine learning framework is introduced for the first time to elucidate and predict the complex fluid dynamic responses across varying time scales. For the same class of fluid processes, the dynamic response curves with varying time durations can be defined in terms of time scales and curve shapes. The former is predicted by a single-objective regression model, and the curves are normalized and recovered using time scaling and uniform interpolation. The latter are downscaled by Principal Component Analysis (PCA) and then predicted by a multi-objective regression model. As a novel application, this framework is employed to analyze small bubbles in a Newtonian fluid as they impact a horizontal wall, predicting the velocity, aspect ratio, and position dynamic response of the bubbles. Both Random Forest and Gaussian Process models, based on PCA-driven data processing, exhibit remarkable accuracy in describing and predicting complex dynamics of rising bubbles. Notably, PCA's principal components demonstrate independence and are set through rigorous cross-validation of the training set, rather than dependence on the Cumulative Variance Explained (CVE) values. Furthermore, our framework adeptly extends to predict the complex behavior of multiple bubble bounces by concatenating individual bounce predictions with high efficiency and precision. The proposed framework proves to be a catalyst for comprehending the dynamic response of fluids.

Exploring the Ecotoxicological Effects and Mitigation Strategies for Microplastics Pollution in Aquatic Ecosystems

<p>Microplastics pollution poses a significant threat to aquatic ecosystems globally, originating from various sources such as plastic debris breakdown and microbeads. This study investigates the ecotoxicological impacts of these pollutants on marine plants and evaluates mitigation strategies. Field surveys assess their distribution, sources, and fate in rivers, lakes, estuaries, and coastal waters. Sampling methods include sediment cores, water samples, and biological specimens to quantify abundance, size distribution, polymer types, and spatial variability. Source apportionment techniques aid in identifying major contributors to pollution. Laboratory experiments simulate environmental conditions to study their behavior, including sedimentation, resuspension, aggregation, and bioaccumulation. Mathematical models predict dispersal and deposition patterns over varying time scales. Ecotoxicological studies investigate impacts on organisms across trophic levels, including fish, invertebrates, and phytoplankton, considering acute and chronic effects. Mitigation strategies like filtration systems, policy interventions, and public awareness campaigns are evaluated for efficacy in reducing pollution and safeguarding ecosystems. This research contributes to developing sustainable solutions essential for environmental preservation and human health.</p>

Evaluating the time to detect biological effects of ocean acidification and warming: an example using simulations of purple sea urchin settlement

Ocean acidification (OA) and ocean warming driven by climate change are important stressors for marine species and systems, but documenting and detecting their long-term impacts on biological responses outside of laboratory settings are challenging due to natural variability caused by complex processes and interactions. We used settlement of purple sea urchins Strongylocentrotus purpuratus in the Southern California Bight (USA) over 6 yr as an example data set to parameterize a simulation model for exploring the time needed to detect environmental effects on a biological response. A generalized linear model was used to describe an index of urchin settlement as functions of pH, sea surface temperature (SST), sea surface salinity (SSS), and spatio-temporal factors, demonstrating that settlement was negatively associated with pH (i.e. lower settlement at higher pH) and positively associated with SST and SSS. Monte Carlo simulations were developed from this base model under a variety of alternative scenarios to estimate the time to detect: (1) annual trends in pH and SST time series, (2) pH and SST effects on urchin settlement, and (3) annual trends in urchin settlement. Time to detect pH and SST effects was predominantly influenced by the underlying strength of the relationships and the model uncertainty. Time to detect annual trends in settlement was more sensitive to the severity of long-term OA and warming trends, which had cumulative (at times opposing) effects. This study highlights the variable time scales (2-60+ yr) that may be necessary to detect biological responses to OA and ocean warming and the sensitivity to different assumptions of the study system.

A molecular and cellular perspective on human brain evolution and tempo.

The evolution of the modern human brain was accompanied by distinct molecular and cellular specializations, which underpin our diverse cognitive abilities but also increase our susceptibility to neurological diseases. These features, some specific to humans and others shared with related species, manifest during different stages of brain development. In this multi-stage process, neural stem cells proliferate to produce a large and diverse progenitor pool, giving rise to excitatory or inhibitory neurons that integrate into circuits during further maturation. This process unfolds over varying time scales across speciesand has progressivelybecome slower in the human lineage, with differences in tempo correlating with differences in brain size, cell number and diversity, and connectivity. Here we introduce the terms 'bradychrony' and 'tachycrony' to describe slowed and accelerated developmental tempos, respectively. Wereview how recent technical advances across disciplines, including advanced engineering of in vitro models, functional comparative genetics and high-throughput single-cell profiling, are leading to a deeper understanding of how specializationsofthe human brain arise during bradychronic neurodevelopment. Emerging insightspointto a central role for genetics, gene-regulatory networks, cellular innovations and developmental tempo, which together contribute to the establishment of human specializations during various stages of neurodevelopment and at different points in evolution.

Observed change and the extent of coherence in the Gulf Stream system

Abstract. By transporting warm and salty water poleward, the Gulf Stream system maintains a mild climate in northwestern Europe while also facilitating the dense water formation that feeds the deep ocean. The sensitivity of North Atlantic circulation to future greenhouse gas emissions seen in climate models has prompted an increasing effort to monitor the various ocean circulation components in recent decades. Here, we synthesize available ocean transport measurements from several observational programs in the North Atlantic and Nordic Seas, as well as an ocean state estimate (ECCOv4-r4), for an enhanced understanding of the Gulf Stream and its poleward extensions as an interconnected circulation system. We see limited coherent variability between the records on interannual timescales, highlighting the local oceanic response to atmospheric circulation patterns and variable recirculation timescales within the gyres. On decadal timescales, we find a weakening subtropical circulation between the mid-2000s and mid-2010s, while the inflow and circulation in the Nordic Seas remained stable. Differing decadal trends in the subtropics, subpolar North Atlantic, and Nordic Seas warrant caution in using observational records at a single latitude to infer large-scale circulation change.

Retention of p‐Chip microtransponders and posttagging survival of small‐bodied stream fishes

AbstractObjectiveObtaining demographic rates often requires complex open‐population capture–mark–recapture (CMR) study designs. Conducting such studies for small‐bodied fishes has been limited in part by excessive mortality after tagging procedures and poor tag retention. As new tag types emerge, information regarding fish survival and tag retention over varying time scales may benefit resource managers to effectively plan future CMR studies. The p‐Chip microtransponder is a 500‐ × 500‐ × 100‐μm tag that is inserted subcutaneously and is read with a handheld laser. Each tag contains a nine‐digit unique identification number. P‐Chip microtransponder tags have been used on a limited number of small‐bodied fishes, with relatively high rates observed for fish survival and tag retention. Information on posttagging survival and retention of p‐Chip microtransponder tags across a range of small‐bodied fish species and tagging locations is needed to inform their effectiveness in future CMR studies.MethodsWe quantified survival and tag retention after p‐Chip microtransponder implantation in Creek Chub Semotilus atromaculatus and Northern Pearl Dace Margariscus nachtriebi in a laboratory environment, and retention of p‐Chip microtransponder tags in Northern Pearl Dace was also quantified over a year‐long field study. We marked 56 Creek Chub and 9 Northern Pearl Dace in the laboratory with p‐Chip microtransponder tags and compared them to an equal number of unmarked individuals over 90 days. We marked 1990 Northern Pearl Dace and conducted recapture events through four seasons (June, September, and October 2022 and June 2023) in four headwater streams of Nebraska.ResultSurvival for Creek Chub was 85% (standard error [SE] = 5.9) and did not differ from control fish survival (95%; SE = 3.2) in the 90‐day laboratory experiment. Survival for Northern Pearl Dace was 89% (SE = 11.0) and did not differ from that of control fish (100%) in the laboratory experiment. Tag retention was 89% (SE = 4.6) for Creek Chub and 100% for Northern Pearl Dace in the laboratory. The p‐Chip microtransponder performed well during the CMR field study, with tag retention for Northern Pearl Dace at 94% across 374 days.ConclusionOur results suggest that the p‐Chip microtransponder minimally affected small‐bodied fish survival and had high tag retention in both the laboratory and field studies. Thus, the p‐Chip microtransponder tag may be appropriate for use in small‐bodied fishes when individual identification is needed in a CMR study.

Non-thermal radiation from dual jet interactions in supermassive black hole binaries

ABSTRACT Supermassive black hole binaries (SMBHBs) are natural by-products of galaxy mergers and are expected to be powerful multimessenger sources. They can be powered by the accretion of matter and then radiate across the electromagnetic spectrum, much like normal active galactic nuclei (AGNs). Current electromagnetic observatories have a good chance of detecting and identifying these systems in the near future. However, precise observational indicators are needed to distinguish individual AGNs from SMBHBs. In this paper, we propose a novel electromagnetic signature from SMBHBs: non-thermal emission produced by the interaction between the jets ejected by the black holes. We study close SMBHBs, which accrete matter from a circumbinary disc and the mini-discs formed around each hole. Each black hole ejects a magnetically dominated jet in the direction of its spin through the Blandford–Znajek mechanism. We argue that in such a situation, the interaction between the jets can trigger strong magnetic reconnection events, where particles are accelerated and emit non-thermal radiation. Depending on whether the jets are aligned or misaligned, this radiation can have different periodicities. We model the evolution of the particles accelerated during the dual jet interaction and calculate their radiative output, obtaining spectra and providing estimates for the variability time-scales. We finally discuss how this emission compares with that of normal AGNs.

The laser pump X-ray probe system at LISA P08 PETRA III.

Understanding and controlling the structure and function of liquid interfaces is a constant challenge in biology, nanoscience and nanotechnology, with applications ranging from molecular electronics to controlled drug release. X-ray reflectivity and grazing incidence diffraction provide invaluable probes for studying the atomic scale structure at liquid-air interfaces. The new time-resolved laser system at the LISA liquid diffractometer situated at beamline P08 at the PETRA III synchrotron radiation source in Hamburg provides a laser pump with X-ray probe. The femtosecond laser combined with the LISA diffractometer allows unique opportunities to investigate photo-induced structural changes at liquid interfaces on the pico- and nanosecond time scales with pump-probe techniques. A time resolution of 38 ps has been achieved and verified with Bi. First experiments include laser-induced effects on salt solutions and liquid mercury surfaces with static and varied time scales measurements showing the proof of concept for investigations at liquid surfaces.

A Comprehensive Review of Indentation of Gels and Soft Biological Materials

Abstract Indentation measurement has emerged as a widely adapted technique for elucidating the mechanical properties of soft hydrated materials. These materials, encompassing gels, cells, and biological tissues, possess pivotal mechanical characteristics crucial for a myriad of applications across engineering and biological realms. From engineering endeavors to biological processes linked to both normal physiological activity and pathological conditions, understanding the mechanical behavior of soft hydrated materials is paramount. The indentation method is particularly suitable for accessing the mechanical properties of these materials as it offers the ability to conduct assessments in liquid environment across diverse length and time scales with minimal sample preparation. Nonetheless, understanding the physical principles underpinning indentation testing and the corresponding contact mechanics theories, making judicious choices regarding indentation testing methods and associated experimental parameters, and accurately interpreting the experimental results are challenging tasks. In this review, we delve into the methodology and applications of indentation in assessing the mechanical properties of soft hydrated materials, spanning elastic, viscoelastic, poroelastic, coupled viscoporoelastic, and adhesion properties, as well as fracture toughness. Each category is accomplished by the theoretical models elucidating underlying physics, followed by ensuring discussions on experimental setup requirements. Furthermore, we consolidate recent advancements in indentation measurements for soft hydrated materials highlighting its multifaceted applications. Looking forward, we offer insights into the future trajectory of the indentation method on soft hydrated materials and the potential applications. This comprehensive review aims to furnish readers with a profound understanding of indentation techniques and a pragmatic roadmap of characterizing the mechanical properties of soft hydrated materials.

Coastal ozone dynamics and formation regime in Eastern China: Integrating trend decomposition and machine learning techniques

Machine-learning is a robust technique for understanding pollution characteristics of surface ozone, which are at high levels in urban China. This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to investigate ozone dynamics and formation regimes in a coastal area of China. During the period of 2017–2022, significant inter-annual fluctuations emerged, with peaks in mid-2017 attributed to volatile organic compounds (VOCs), and in late-2019 influenced by air temperature. Multifaceted periodicities (daily, weekly, holiday, and yearly) in ozone were revealed, elucidating substantial influences of daily and yearly components on ozone periodicity. A VOC-sensitive ozone formation regime was identified, characterized by lower VOCs/NOx ratios (average = 0.88) and significant positive correlations between ozone and VOCs. This interplay manifested in elevated ozone during weekends, holidays, and pandemic lockdowns. Key variables influencing ozone across diverse timescales were uncovered, with solar radiation and temperature driving daily and yearly ozone variations, respectively. Precursor substances, particularly VOCs, significantly shaped weekly/holiday patterns and long-term trends of ozone. Specifically, acetone, ethane, hexanal, and toluene had a notable impact on the multi-year ozone trend, emphasizing the urgency of VOC regulation. Furthermore, our observations indicated that NOx primarily drived the stochastic variations in ozone, a distinguishing characteristic of regions with heavy traffic. This research provides novel insights into ozone dynamics in coastal urban areas and highlights the importance of integrating statistical and machine-learning methods in atmospheric pollution studies, with implications for targeted mitigation strategies beyond this specific region and pollutant.

Imprint of “Local Opacity” Effect in Gamma-Ray Spectrum of Blazar Jet

Relativistic jets from accreting supermassive black holes at cosmological distances can be powerful emitters of γ-rays. However, the precise mechanisms and locations responsible for the dissipation of energy within these jets, leading to observable γ-ray radiation, remain elusive. We detect evidence for an intrinsic absorption feature in the γ-ray spectrum at energies exceeding 10 GeV, presumably due to the photon–photon pair production of γ-rays with low-ionization lines at the outer edge of broad-line region (BLR), during the high-flux state of the flat-spectrum radio quasar PKS 1424−418. The feature can be discriminated from the turnover at higher energies resulting from γ-ray absorption in the extragalactic background light. It is absent in the low-flux states, supporting the interpretation that powerful dissipation events within or at the edge of the BLR evolve into fainter γ-ray emitting zones outside the BLR, possibly associated with the moving very long baseline interferometry radio knots. The inferred location of the γ-ray emission zone is consistent with the observed variability timescale of the brightest flare, provided that the flare is attributed to external Compton scattering with BLR photons.

Optical Variability of Blazars in the Tomo-e Gozen Northern Sky Transient Survey

We studied the optical variability of 241 BL Lacertae (BL Lacs) and 83 flat-spectrum radio quasars (FSRQs) from the 4LAC catalog using data from the Tomo-e Gozen Northern Sky Transient Survey, with ∼50 epochs per blazar on average. We excluded blazars whose optical variability may be underestimated due to the influence of their host galaxy based on their optical luminosity (L O ). FSRQs with γ-ray photon index greater than 2.6 exhibit very low optical variability, and their distribution of standard deviation of repeated photometry is significantly different from that of the other FSRQs (Kolmogorov–Smirnov test p-value equal to 5 × 10−6). Among a sample of blazars at any particular cosmological epoch, those with lower γ-ray luminosity (L γ ) tend to have lower optical variability, and those FSRQs with a γ-ray photon index greater than 2.6 tend to have low L γ . We also measured the structure function of optical variability and found that the amplitude of the structure function for FSRQs is higher than previously measured and higher than that of BL Lacs at multiple time lags. Additionally, the amplitude of the structure function of FSRQs with high γ-ray photon index is significantly lower than that of FSRQs with low γ-ray photon index. The structure function of FSRQs of high γ-ray photon index shows a characteristic timescale of more than 10 days, which may be the variability timescale of the accretion disk. In summary, we infer that the optical component of FSRQs with high γ-ray photon index may be dominated by the accretion disk.

A deep learning methodology based on adaptive multiscale CNN and enhanced highway LSTM for industrial process fault diagnosis

Intelligent fault diagnostic techniques are crucial for ensuring the long-term reliability of manufacturing. The process variables collected by sensors in real industrial systems typically exhibit diverse time scales and data features. To overcome the above issues, we propose a comprehensive model known as adaptive multiscale CNN and enhanced highway LSTM (ACEL). To begin with, multiscale features under variable operating conditions are automatically extracted by constructing the parallel convolutional module. Then, to selectively focus on the feature representation within the channels, efficient channel attention is introduced to downplay the channels with less important information. In addition, the bidirectional LSTM is designed to generate more fine-grained hybrid features based on contextual information and local features learned by the CNN. An enhanced highway configuration is designed to be used to bolster the global temporal dependencies. Finally, ACEL is applied to the Tennessee Eastman benchmark and CSTR simulation, and multiple statistical metrics show that the proposed model outperforms other advanced fault diagnosis methods.

Log-Gaussian Distribution and Evolution of Minimum Variation Timescales for SGR J1550-5418

The major observation of the X-ray burst (XRB) in association with the fast radio burst (FRB) FRB 200428 originating from SGR J1935+2154 on 2020 April 28 substantiates magnetars as one of the origins of FRBs. However, it is still unclear why only a few XRBs in association with FRBs have been observed solely in this magnetar. In this study, we investigate the minimum variation timescales (MVTs) of XRBs from SGR J1550-5418, an active magnetar similar to SGR J1935+2154, and conduct a comprehensive comparison of their MVT properties. Our analysis reveals that the distribution of the MVT for SGR J1550-5418 follows a lognormal Gaussian function with the mean 6.4 ± 0.4 ms. Interestingly, we detect an evolution in the MVTs, i.e., the fitted mean of the MVT distribution in 2008 October is about 3 times larger than that in 2009, indicating potential variations in radiation regions possibly attributed to changes in magnetic field topology. Besides, we do not find a significant correlation between the MVT and either duration or energy. Finally, there is no significant difference between the MVT distributions across different energy ranges for SGR J1550-5418 and SGR J1935+2154, which supports a common physical origin.

Transient behavior of the freshwater-saltwater mixing zone after land reclamation in coastal aquifers

The interaction between freshwater and saltwater in the mixing zone governs regional groundwater flow and the exchange of water and salt between groundwater and the ocean. However, previous studies have overlooked the impact of land reclamation on the transient behavior of the mixing zone. This research investigated the dynamic influence of reclamation length, reclamation material properties, and recharge rate on the transient behavior of the mixing zone and timescale of mixing zone variation (TMV) through a series of field-scale numerical simulations. In general, the width of the mixing zone (WMZ) in the upper and center regions of the aquifer exhibited initial increase followed by subsequent decrease in various scenarios, displaying a consistent trend. For reclamation lengths less than 300 m, the mixing zone reached a steady-state condition within 8,000 days, while the corresponding TMV for a 500 m-length reclamation case increased to 20,000 days. The growth rates of the WMZ in the upper and center regions of the aquifer were notably slower, requiring more time to reach steady state in low-permeability scenarios. This observation underscored that reclamation with lower permeability could significantly extend the TMV. It was noteworthy that varying the longitudinal dispersion of the reclamation area between 0.5–10 m had only a slight effect on the TMV, ranging from 8,000 to 8,500 days. The peaks of the mixing zone width showed a proportional increase with longitudinal dispersion. Furthermore, increasing the recharge rate led to a substantial decrease in the TMV, from 10,000 days to 2,000 days. The WMZ exhibited faster growth with increasing recharge rate.

Explosive transitions in coupled Lorenz oscillators.

We study the transition to synchronization in an ensemble of chaotic oscillators that are interacting on a star network. These oscillators possess an invariant symmetry and we study emergent behavior by introducing the timescale variations in the dynamics of the nodes and the hub. If the coupling preserves the symmetry, the ensemble exhibits consecutive explosive transitions, each one associated with a hysteresis. The first transition is the explosive synchronization from a desynchronized state to a synchronized state which occurs discontinuously with the formation of intermediate clusters. These clusters appear because of the driving-induced multistability and the resulting attractors exhibit intermittent synchrony (antisynchrony). The second transition is the explosive death that occurs as a result of stabilization of the stable fixed points. However, if the symmetry is not preserved, the system again makes a first-order transition from an oscillatory state to death, namely, an explosive death. These transitions are studied with the help of the master stability functions, Lyapunov exponents, and the stability analysis.

Temperature compensation through kinetic regulation in biochemical oscillators

Nearly all circadian clocks maintain a period that is insensitive to temperature changes, a phenomenon known as temperature compensation (TC). Yet, it is unclear whether there is any common feature among different systems that exhibit TC. From a general timescale invariance, we show that TC relies on the existence of certain period-lengthening reactions wherein the period of the system increases strongly with the rates in these reactions. By studying several generic oscillator models, we show that this counterintuitive dependence is nonetheless a common feature of oscillators in the nonlinear (far-from-onset) regime where the oscillation can be separated into fast and slow phases. The increase of the period with the period-lengthening reaction rates occurs when the amplitude of the slow phase in the oscillation increases with these rates while the progression speed in the slow phase is controlled by other rates of the system. The positive dependence of the period on the period-lengthening rates balances its inverse dependence on other kinetic rates in the system, which gives rise to robust TC in a wide range of parameters. We demonstrate the existence of such period-lengthening reactions and their relevance for TC in all four model systems we considered. Theoretical results for a model of the Kai system are supported by experimental data. A study of the energy dissipation also shows that better TC performance requires higher energy consumption. Our study unveils a general mechanism by which a biochemical oscillator achieves TC by operating in parameter regimes far from the onset where period-lengthening reactions exist.