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Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the timescale over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter-regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are associated with greater within-community functional connectivity and diverse structural connectivity. We also replicate prior observations of a positive correlation between timescales and structural connectivity degree. Finally, we find evidence for preferential functional connectivity between cortical areas with similar timescales. We replicate these findings in an independent dataset. These results contribute to our understanding of functional brain organization and structure-function relationships in the human brain, and support the notion that regional differences in cortical dynamics may in part reflect the topological role of each region within macroscale brain networks.

Rainfall in East Asia is affected by two rain‐bearing systems: tropical cyclones and monsoon‐related frontal systems. Distinguishing typhoon rainfall (TR) and non‐typhoon rainfall (non‐TR) helps to understand the evolution process of regional rainfall at different timescales. Taking Fujian Province in the southeast coast of China as an example, based on the fixed box approach of separating TR, the method of determining the size of fixed box is explored. TR and non‐TR are separated in Fujian Province, and the spatial variations of TR and non‐TR at different timescales (annual, monthly, day of annual‐maximum‐rain) are analysed. The results showed that (1) according to the relationship between the sizes of fixed box and the rate of change of TR, the size of fixed box could be reasonably determined; thus, the expended size of fixed box suitable for separating TR in Fujian was 3.5°, namely the range of 20°–31.8°N and 112.3°–124.2°E. (2) The spatial variations of TR at different timescales in Fujian were similar: TR decreased from the coast to the inland, and the northeast coast of Fujian was the high‐value region. Due to the difference of water vapour sources, non‐TR in March–June increased from the coast to the inland, but the high value of non‐TR in July–September was distributed in the eastern coast. (3) The contribution rates of average TR to the total rainfall of the year, July–September and 1 day were 12.8%, 34.6% and 35.7%, respectively. In eastern coast, TR in July–September accounted for 1/3–1/2 of total rainfall, and the rainfall in a day was mainly affected by TR; while in western inland, rainfall was mainly non‐TR and the influence of TR was less than 1/4. [ABSTRACT FROM AUTHOR]

Bias in regional climate model (RCM) data makes bias correction (BC) a necessary pre-processing step in climate change impact studies. Among a variety of different BC methods, quantile mapping (QM) is a popular and powerful BC method. Studies have shown that QM may be vulnerable to reductions in calibration sample size. The question is whether this also affects the climate change signal (CCS) of the RCM data. We applied four different QM methods without subsampling and with three different subsampling timescales to an ensemble of seven climate projections. BC generally improved the RCM data relative to observations. However, the CCS was significantly modified by the BC for certain combinations of QM method and subsampling timescale. In conclusion, QM improves the RCM data that are fundamental for climate change impact studies, but the optimal subsampling timescale strongly depends on the chosen QM method. [ABSTRACT FROM AUTHOR]

Collective behaviours, such as flocking in birds or decision making by bee colonies, are some of the most intriguing behavioural phenomena in the animal kingdom. The study of collective behaviour focuses on the interactions between individuals within groups, which typically occur over close ranges and short timescales, and how these interactions drive larger scale properties such as group size, information transfer within groups and group-level decision making. To date, however, most studies have focused on snapshots, typically studying collective behaviour over short timescales up to minutes or hours. However, being a biological trait, much longer timescales are important in animal collective behaviour, particularly how individuals change over their lifetime (the domain of developmental biology) and how individuals change from one generation to the next (the domain of evolutionary biology). Here, we give an overview of collective behaviour across timescales from the short to the long, illustrating how a full understanding of this behaviour in animals requires much more research attention on its developmental and evolutionary biology. Our review forms the prologue of this special issue, which addresses and pushes forward understanding the development and evolution of collective behaviour, encouraging a new direction for collective behaviour research. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Plain Language Summary: Nearly synchronous global changes in geomagnetic polarity give both a detailed irregular pacing to geological time and provide a glimpse into heat transfer processes across the core—mantle boundary which drives the Earth's geodynamo. Although the Late Carboniferous is characterized by some well‐studied reversals, details of the tempo of polarity changes in the Early Carboniferous are unknown. This work addresses this by providing a detailed record of polarity changes over a ∼2 million year interval at around 334.5–332.5 million years ago‐from the Trowbarrow Quarry section in NW England. We demonstrate that these limestones likely preserve magnetization from close to their time of formation and record at least 31 polarity reversals. These observations support the idea that the Earth's dynamo was in a hyperactive reversing state similar to those sustained for tens of Myr in the Late Jurassic, parts of the Cambrian and the Late Ediacaran. It further corroborates a ∼200 Myr cyclicity in paleomagnetic field behavior since the Precambrian, potentially linked to variable core heat flow forced by mantle convection. The pattern of geomagnetic polarity changes during the Early Carboniferous (Mississippian) is not known in detail. This information sparsity is addressed by determining a magnetostratigraphy from the late Asbian (late Visean at ∼333 Ma) in Trowbarrow Quarry, UK. This is the stratotype section of the late Asbian and has a detailed foraminiferal zonation based on the same set of paleomagnetic samples, establishing a detailed biostratigraphy. The 195 m‐thick section was sampled at an average spacing of 1.1 m, yielding a detailed magnetostratigraphy comprising nine major magnetozone couplets, and seven submagnetozones. The section dataset has a 78% bias to normal polarity determined from 177 sampling levels. The magnetization is carried by a mixture of hematite and detrital magnetite, with 68% of specimens dominated by hematite magnetizations. The primary magnetization passes a fold test showing its age was prior to the latest Carboniferous. The hematite is inferred to be largely of detrital, eolian origin, although some reddened levels are associated with emergent surfaces, suggesting that a small fraction of hematite is associated with platform emergence. The Mississippian age magnetization is partly overprinted with Kiaman Superchron‐age and Brunhes‐age magnetizations. Using the duration of the section based on astrochronology indicates a reversal frequency of 15.7 ± 0.75 Myr−1, indicating that the geodynamo was in a hyperactive reversing state between 335 and 333 Ma. Key Points: A 195 m section, representing ∼2 Myr, yields a magnetostratigraphy comprizing nine major magnetozone couplets and seven submagnetozonesPrimary magnetizations are predominantly carried by hematite with lesser important detrital magnetite. Data pass regional fold testsA reversal frequency of 15.7 ± 0.75 Myr−1 is calculated, suggesting that the geodynamo was in a hyperactive state at ∼333 Ma [ABSTRACT FROM AUTHOR]

Contact metamorphism of carbonate rocks in response to fluid infiltration releases carbon dioxide (CO2), potentially affecting Earth's carbon budget over geological timescales. This process was notably active in the Cretaceous when the closure of the Neo‐Tethys Ocean led to extensive arc magmatism in southern Tibet, coincident with a greenhouse climate interval. These arc plutons intersected carbonate sequences and formed widespread calcsilicate rocks. The mineral assemblages of these rocks record both the progression and duration of the CO2 release. In this study, we focus on a representative aureole in southern Tibet that was metamorphosed by a ∼64 Ma granitoid pluton of the Gangdese Batholith. The aureole presents lithologic zonation, with the inner garnet‐wollastonite zone indicating equilibrium with a water‐rich fluid at ∼525°C. Large garnet porphyroblasts feature cross‐cutting veins of secondary garnets that illustrate several stages of interface‐coupled dissolution‐reprecipitation processes facilitated by fluid infiltration. Diffusion modeling for Mg concentration profiles across vein‐host garnet yields a brief high‐temperature stage (25–150 kyr)—a duration still significantly overestimated considering factors that may accelerate diffusion in garnet, such as lattice parameters and hydration. Such short timescale aligns with conduction modeling of a cooling pluton, which, combined with the bulk‐rock mass balance analysis, indicates a local carbon flux comparable to fluxes at other modern tectonic settings. The metamorphic decarbonation, potentially episodic, in the continental arc may have been an important endogenic carbon source in the late Cretaceous. Plain Language Summary: Arc magma reacting with carbonate rocks creates calcsilicate rocks and releases carbon dioxide (CO2) to the atmosphere. The reaction is achieved by the infiltration of magmatic fluids to carbonate rocks. In the Earth's history, warm climates often coincided with extensive arc magmatism, highlighting large CO2 release. By studying the fluid infiltration patterns, chemical, and mineralogical information preserved in the calcsilicate rocks, geologists can understand how much and how fast carbon dioxide is released. The fluid‐rock reactions can occur rapidly. Traditional geological dating tools may be difficult to resolve the short timescale of such reactions. When a fluid vein cut across a host mineral, a sharp concentration profile forms between the fluid and the host mineral. The degree to which the sharp profile is smoothed is dependent on time. By using this approach, we quantified the fluid‐rock interaction timescale by studying the fluid infiltration patterns in a garnet from southern Tibet. Combined with the amount of CO2 loss, the carbon flux (CO2 loss/time) is large. This study provides field‐based evidence on the timescale and magnitude of carbon release from magma‐carbonate rock interaction. Key Points: A 64‐million‐year felsic intrusion into carbonate rocks in southern Tibet induced the formation of a calcsilicate aureoleSkarn garnet reveals interface‐coupled dissolution‐reprecipitation patterns, driven by shorted‐lived fluid infiltrationsOver 95% decarbonation over tens of thousands of years corresponds to annual carbon emissions on a teramole scale across the aureole [ABSTRACT FROM AUTHOR]

The late Asbian appears to mark the initial, well‐documented, onset of far‐field glacio‐eustatic changes in equatorial Mississippian strata. This work unravels the nature of cyclicity in upper Asbian shallow marine carbonates, using a combination of petrographic study, rock magnetic proxies and astrochronological testing on samples from the Trowbarrow section, NW England. Rock magnetic data express the content of two types of siliciclastic sources; a marine‐delivered magnetite‐dominated source, and an eolian‐delivered, hematite‐dominated source. The eolian‐sourced material generally peaked during regressive and low‐stand parts of the carbonate rhythms. Astrochronologic testing methods based around the average spectral misfit and TimeOpt methodology show the magnetite abundance proxies are principally carrying the astronomically forced signal. Two likely sedimentation rate models are derived from the five better magnetic proxies using evolutive methods. In addition, a set of three likely major hiatus levels are inferred in the sedimentation rate models, based on testing possible major hiatus scenarios with TimeOpt methods, using eccentricity modulation. From these, using the three best proxies, an average astrochronologic duration for the Trowbarrow section suggests a late Asbian duration of 1976 ± 86 kyr (1σ), and a basal late Asbian age of 334.48 ± 0.35 Ma (2σ). Coupled atmosphere‐ocean models for the late Paleozoic, suggest that lows in short eccentricity correspond to glacials, when inferred delivery of siliciclastic sediment to the carbonate ramp is generally at a maximum. The glacial and lower sea‐level intervals also coincide with maximum delivery of eolian siliciclastics, likely linked to increased aridity and less vegetation cover on adjacent and distal parts of Laurentia. Plain Language Summary: Around 332–333 million years ago changes in sea‐level driven by changes in polar ice volume were an important control on the sedimentation patterns through time in carbonates from low paleolatitudes. Understanding the pacing of these changes has implications for timescales and paleoceanographic processes. These cyclical changes in carbonate lithology are related to changes in magnetic properties within the late Asbian (late Visean) section at Trowbarrow in NW England. The magnetic changes principally express differences in the small content of silica‐based clastics, but also reflect changing Fe‐oxide mineralogy between times of hematite‐rich and magnetite‐rich clastic input. The changes are responding to differences in eolian delivery and marine dispersal of the clastics. Eolian delivery of clastics was at its peak near sea‐level lowstands, when nearby terrestrial systems were the most arid and supplying the most dust. Statistical assessments show that the magnetite abundance signal principally expresses changes in astronomical eccentricity. Primarily using the expected eccentricity pacing, two age models are constructed, which includes three levels of detectable hiatus in the section. Using these two age models and the three best magnetic proxies, the average late Asbian duration is 1976 ± 86 kyr, with the base of the late Asbian at 334.48 ± 0.35 Ma. Key Points: Rock magnetic properties show the included siliciclastics are from hematite‐rich eolian dust and marine‐dispersed sourcesThe magnetite mineral abundance proxies principally carry the primary eccentricity‐driven astronomical signalAn astrochronology for the late Asbian indicates its duration is 1976 ± 86 kyr [ABSTRACT FROM AUTHOR]

Bias in regional climate model (RCM) data makes bias correction (BC) a necessary pre-processing step in climate change impact studies. Among a variety of different BC methods, quantile mapping (QM) is a popular and powerful BC method. Studies have shown that QM may be vulnerable to reductions in calibration sample size. The question is whether this also affects the climate change signal (CCS) of the RCM data. We applied four different QM methods without subsampling and with three different subsampling timescales to an ensemble of seven climate projections. BC generally improved the RCM data relative to observations. However, the CCS was significantly modified by the BC for certain combinations of QM method and subsampling timescale. In conclusion, QM improves the RCM data that are fundamental for climate change impact studies, but the optimal subsampling timescale strongly depends on the chosen QM method.

Abstract Stomatal optimization theory is a commonly used framework for modeling how plants regulate transpiration in response to the environment. Most stomatal optimization models assume that plants instantaneously optimize a reward function such as carbon gain. However, plants are expected to optimize over longer timescales given the rapid environmental variability they encounter. There are currently no observational constraints on these timescales. Here, a new stomatal model is developed and is used to analyze the timescales over which stomatal closure is optimized. The proposed model assumes plants maximize carbon gain subject to the constraint that they cannot draw down soil moisture below a critical value. The reward is integrated over time, after being weighted by a discount factor that represents the timescale (τ) that a plant considers when optimizing stomatal conductance to save water. The model is simple enough to be analytically solvable, which allows the value of τ to be inferred from observations of stomatal behavior under known environmental conditions. The model is fitted to eddy covariance data in a range of ecosystems, finding the value of τ that best predicts the dynamics of evapotranspiration at each site. Across 82 sites, the climate metrics with the strongest correlation to τ are measures of the average number of dry days between rainfall events. Values of τ are similar in magnitude to the longest such dry period encountered in an average year. The results here shed light on which climate characteristics shape spatial variations in ecosystem‐level water use strategy.

Abstract The pattern of geomagnetic polarity changes during the Early Carboniferous (Mississippian) is not known in detail. This information sparsity is addressed by determining a magnetostratigraphy from the late Asbian (late Visean at ∼333 Ma) in Trowbarrow Quarry, UK. This is the stratotype section of the late Asbian and has a detailed foraminiferal zonation based on the same set of paleomagnetic samples, establishing a detailed biostratigraphy. The 195 m‐thick section was sampled at an average spacing of 1.1 m, yielding a detailed magnetostratigraphy comprising nine major magnetozone couplets, and seven submagnetozones. The section dataset has a 78% bias to normal polarity determined from 177 sampling levels. The magnetization is carried by a mixture of hematite and detrital magnetite, with 68% of specimens dominated by hematite magnetizations. The primary magnetization passes a fold test showing its age was prior to the latest Carboniferous. The hematite is inferred to be largely of detrital, eolian origin, although some reddened levels are associated with emergent surfaces, suggesting that a small fraction of hematite is associated with platform emergence. The Mississippian age magnetization is partly overprinted with Kiaman Superchron‐age and Brunhes‐age magnetizations. Using the duration of the section based on astrochronology indicates a reversal frequency of 15.7 ± 0.75 Myr−1, indicating that the geodynamo was in a hyperactive reversing state between 335 and 333 Ma.

Rats readily switch between foraging and more complex navigational behaviors such as pursuit of other rats or prey. These tasks require vastly different tracking of multiple behaviorally significant variables including self-motion state. To explore whether navigational context modulates self-motion tracking, we examined self-motion tuning in posterior parietal cortex neurons during foraging versus visual target pursuit. Animals performing the pursuit task demonstrate predictive processing of target trajectories by anticipating and intercepting them. Relative to foraging, pursuit yields multiplicative gain modulation of self-motion tuning and enhances self-motion state decoding. Self-motion sensitivity in parietal cortex neurons is, on average, history dependent regardless of behavioral context, but the temporal window of self-motion integration extends during target pursuit. Finally, many self-motion-sensitive neurons conjunctively track the visual target position relative to the animal. Thus, posterior parietal cortex functions to integrate the location of navigationally relevant target stimuli into an ongoing representation of past, present, and future locomotor trajectories.

How does the brain integrate signals with different timescales to drive purposeful actions? Brain-machine interfaces (BMIs) offer a powerful tool to causally test how distributed neural networks achieve specific neural patterns. During neuroprosthetic learning, actuator movements are causally linked to primary motor cortex (M1) neurons, i.e., "direct" neurons that project to the decoder and whose firing is required to successfully perform the task. However, it is unknown how such direct M1 neurons interact with both "indirect" local (in M1 but not part of the decoder) and across area neural populations (e.g., in premotor cortex/M2), all of which are embedded in complex biological recurrent networks. Here, we trained male rats to perform a M1-BMI task and simultaneously recorded the activity of indirect neurons in both M2 and M1. We found that both M2 and M1 indirect neuron populations could be used to predict the activity of the direct neurons (i.e., "BMI-potent activity"). Interestingly, compared with M1 indirect activity, M2 neural activity was correlated with BMI-potent activity across a longer set of time lags, and the timescale of population activity patterns evolved more slowly. M2 units also predicted the activity of both M1 direct and indirect neural populations, suggesting that M2 population dynamics provide a continuous modulatory influence on M1 activity as a whole, rather than a moment-by-moment influence solely on neurons most relevant to a task. Together, our results indicate that longer timescale M2 activity provides modulatory influence over extended time lags on shorter-timescale control signals in M1.SIGNIFICANCE STATEMENT A central question in the study of motor control is whether primary motor cortex (M1) and premotor cortex (M2) interact through task-specific subpopulations of neurons, or whether tasks engage broader correlated networks. Brain-machine interfaces (BMIs) are powerful tools to study cross-area interactions. Here, we performed simultaneous recordings of M1 and M2 in a BMI task using a subpopulation of M1 neurons (direct neurons). We found that activity outside of direct neurons in M1 and M2 was predictive of M1-BMI task activity, and that M2 activity evolved at slower timescales than M1. These findings suggest that M2 provides a continuous modulatory influence on M1 as a whole, supporting a model of interactions through broad correlated networks rather than task-specific neural subpopulations.

Due to the rapid urbanization and climate change, one of the pressing problems confronting Chinese cities lies in air pollution. Especially during recent years, most cosmopolitan cities in China suffer from thick smog caused by PMs. It is reported that such air pollution has close relations with traffic-related pollutants, such as NO2. Meteorological condition contributes significantly to long-range transport sources and has remarkable influences on the distribution of the above pollutants. Thus, it is necessary to quantitatively analyze such influential patterns. In this paper, taking Chengdu as an illustrative example, the meteorological and pollutant statistics in 4947 h are collected and fitted with 8 meteorological parameters of PM2.5, PM10, and NO2 through linear regression method. And data is analyzed and compared on the hourly, daily, weekly, and monthly basis, respectively. Results show that hourly and daily data focus on fluctuations that affected by multiple interferences other than meteorological influences. When hourly values of PM2.5, PM10, and NO2 exceed 175 μg/m3, 250 μg/m3, and 125 μg/m3, respectively, discrete values that cannot be explained by meteorological influences increase notably, while weekly and monthly variations illustrate more tendencies, and communicable patterns that decisively influenced by meteorology can be extracted among 3 pollutants. By comparing the results in 4 timescales, respectively, similar principal meteorological factors are involved in fitting processes. Thirdly, visibility (V), wind speed (WS), precipitation (P), and cloud condition (CC) are the most influential factors and served as main parameters in linear regressions within 4 timescales. Air temperature (AT) and dew temperature (DT) are less influential factors by daily and weekly data but are served as main parameters when it goes to hourly and monthly data and function as variables that signify tendency variances in linear regressions, while relative humidity (RH) and barometric pressure (BP) are lest influential factors and have limited effect on fitting results. This work can provide guidance and reference for urban planning optimization and air environment protection in cities with air quality control considerations impacted by local climatic conditions. [ABSTRACT FROM AUTHOR]

Motivation: We have little understanding of how communities respond to varying magnitudes and rates of environmental perturbations across temporal scales. BioDeepTime harmonizes assemblage time series of presence and abundance data to help facilitate investigations of community dynamics across timescales and the response of communities to natural and anthropogenic stressors. BioDeepTime includes time series of terrestrial and aquatic assemblages of varying spatial and temporal grain and extent from the present‐day to millions of years ago. Main Types of Variables Included: BioDeepTime currently contains 7,437,847 taxon records from 10,062 assemblage time series, each with a minimum of 10 time steps. Age constraints, sampling method, environment and taxonomic scope are provided for each time series. Spatial Location and Grain: The database includes 8752 unique sampling locations from freshwater, marine and terrestrial ecosystems. Spatial grain represented by individual samples varies from quadrats on the order of several cm2 to grid cells of ~100 km2. Time Period and Grain: BioDeepTime in aggregate currently spans the last 451 million years, with the 10,062 modern and fossil assemblage time series ranging in extent from years to millions of years. The median extent of modern time series is 18.7 years and for fossil series is 54,872 years. Temporal grain, the time encompassed by individual samples, ranges from days to tens of thousands of years. Major Taxa and Level of Measurement: The database contains information on 28,777 unique taxa with 4,769,789 records at the species level and another 271,218 records known to the genus level, including time series of benthic and planktonic foraminifera, coccolithophores, diatoms, ostracods, plants (pollen), radiolarians and other invertebrates and vertebrates. There are to date 7012 modern and 3050 fossil time series in BioDeepTime. Software Format: SQLite, Comma‐separated values. [ABSTRACT FROM AUTHOR]

New transdermal biosensors measure analytes that diffuse from the bloodstream through the skin, making it important to reduce the system response time and understand measurement output. While highly customized models have been created for specific sensors, a generalized model for transdermal sensor systems is lacking. Here, a simple one-dimensional diffusion model was used to characterize the measurement system and classify biosensors as either flux types or concentration types. Results showed that flux-type sensors have significantly faster response times than concentration sensors. Furthermore, flux sensors do not measure concentration, but rather have an output measurement that is proportional to skin permeability. These findings should lead to an improved understanding of transdermal measurements and their relation to blood analyte concentration. In the realm of alcohol research, where the majority of commercially available sensors are flux types, our work advocates toward moving away from transdermal alcohol concentration as a metric, and instead suggests embracing transdermal alcohol flux as a more suitable alternative. [ABSTRACT FROM AUTHOR]

SUMMARY We study predictions of reversals of Earth’s axial magnetic dipole field that are based solely on the dipole’s intensity. The prediction strategy is, roughly, that once the dipole intensity drops below a threshold, then the field will continue to decrease and a reversal (or a major excursion) will occur. We first present a rigorous definition of an intensity threshold-based prediction strategy and then describe a mathematical and numerical framework to investigate its validity and robustness in view of the data being limited. We apply threshold-based predictions to a hierarchy of numerical models, ranging from simple scalar models to 3-D geodynamos. We find that the skill of threshold-based predictions varies across the model hierarchy. The differences in skill can be explained by differences in how reversals occur: if the field decreases towards a reversal slowly (in a sense made precise in this paper), the skill is high, and if the field decreases quickly, the skill is low. Such a property could be used as an additional criterion to identify which models qualify as Earth-like. Applying threshold-based predictions to Virtual Axial Dipole Moment palaeomagnetic reconstructions (PADM2M and Sint-2000) covering the last two million years, reveals a moderate skill of threshold-based predictions for Earth’s dynamo. Besides all of their limitations, threshold-based predictions suggests that no reversal is to be expected within the next 10 kyr. Most importantly, however, we show that considering an intensity threshold for identifying upcoming reversals is intrinsically limited by the dynamic behaviour of Earth’s magnetic field.

Because modernized global navigation satellite systems (GNSSs) carry high-performance atomic clocks onboard, a new problem has arisen regarding whether the clock estimation approach is good enough to reflect the true performance of onboard atomic clocks. This paper proposes a new and novel centimeter-level clock synchronization approach for BDS-3 satellites based on two-way comparisons using inter-satellite link measurements. The proposed approach estimates satellite clock offsets by adjusting satellite clock offsets obtained from inter-satellite ranging measurements, and measurement noise is greatly reduced. The noise level of clock offsets estimated by the new approach is 0.7 cm, which is 41% of that of clock offsets estimated by ISL direct two-way comparisons. Compared to the ODTS approach, the new approach efficiently eliminates orbit errors in clock offsets. On this basis, the paper presents a space-borne timescale (SPBT) using high-performance atomic clocks onboard BDS-3 satellites. The frequency stability of the SPBT is 8.6E-16 at a 1-day interval; this result is superior to ground GNSS timescales such as BDT. Based on the SPBT, this paper evaluates the performance of the BDS-3 onboard atomic clock. The 2-h and 24-h prediction uncertainties for the BDS-3 PHM are 0.04 and 0.12 m, and the frequency stabilities are 1.6e-14 and 3.4e-15 at 10,000-s and 1-day intervals, respectively. The 2-h and 24-h prediction uncertainties of the BDS-3 RAFSs are 0.05 and 0.37 m, and the frequency stabilities are 1.9E-14 and 8.1E-15 at 10,000-s and 1-day intervals. This study contributes to autonomous navigation and signal-in-space accuracy improvements for GNSSs. [ABSTRACT FROM AUTHOR]

We consider reaction networks that admit a singular perturbation reduction in a certain parameter range. The focus of this paper is on deriving “small parameters” (briefly for small perturbation parameters), to gauge the accuracy of the reduction, in a manner that is consistent, amenable to computation and permits an interpretation in chemical or biochemical terms. Our work is based on local timescale estimates via ratios of the real parts of eigenvalues of the Jacobian near critical manifolds. This approach modifies the one introduced by Segel and Slemrod and is familiar from computational singular perturbation theory. While parameters derived by this method cannot provide universal quantitative estimates for the accuracy of a reduction, they represent a critical first step toward this end. Working directly with eigenvalues is generally unfeasible, and at best cumbersome. Therefore we focus on the coefficients of the characteristic polynomial to derive parameters, and relate them to timescales. Thus, we obtain distinguished parameters for systems of arbitrary dimension, with particular emphasis on reduction to dimension one. As a first application, we discuss the Michaelis–Menten reaction mechanism system in various settings, with new and perhaps surprising results. We proceed to investigate more complex enzyme catalyzed reaction mechanisms (uncompetitive, competitive inhibition and cooperativity) of dimension three, with reductions to dimension one and two. The distinguished parameters we derive for these three-dimensional systems are new. In fact, no rigorous derivation of small parameters seems to exist in the literature so far. Numerical simulations are included to illustrate the efficacy of the parameters obtained, but also to show that certain limitations must be observed. [ABSTRACT FROM AUTHOR]

India has a long history of scientific and technological participation. India served as a global knowledge hub. The best examples are the universities of Nalanda (fifth century AD in Bihar) and Takshshila (tenth century BCE). From the fifth century CE to 1200 CE, they served as a center of learning. Since ancient times, India has played an important role in science and technology. Several historical references demonstrate India's scientific contributions in various domains, such as Sushruta in medical science, Koutilya in arthashastra, and Aryabhatta in mathematics and Astrology. Similarly, in the fields of Timekeeping India has great scientific contributions which are not known to the masses. Since the Vedic time, India had its timekeeping method. Massive architectures like Konark Surya Mandir of Odisha, or Jantar-Mantar at Jaipur support these claims. This paper explores the timekeeping details in the best possible way from pre-Vedic/Vedic times and its progression in the form of atomic Timescale as UTC till date. [ABSTRACT FROM AUTHOR]

Many signaling systems execute adaptation under circumstances that require noise attenuation. Here, we identify an intrinsic trade-off existing between sensitivity and noise attenuation in the three-node networks. We demonstrate that although fine-tuning timescales in three-node adaptive networks can partially mediate this trade-off in this context, it prolongs adaptation time and imposes unrealistic parameter constraints. By contrast, four-node networks can effectively decouple adaptation and noise attenuation to achieve dual function without a trade-off, provided that these functions are executed sequentially. We illustrate ideas in seven biological examples, including Dictyostelium discoideum chemotaxis and the p53 signaling network and find that adaptive networks are often associated with a noise attenuation module. Our approach may be applicable to finding network design principles for other dual and multiple functions.

To understand the neural mechanisms that support decision making, it is critical to characterize the timescale of evidence evaluation. Recent work has shown that subjects can adaptively adjust the timescale of evidence evaluation across blocks of trials depending on context [1]. However, it's currently unknown if adjustments to evidence evaluation occur online during deliberations based on a single stream of evidence. To examine this question, we employed a change-detection task in which subjects report their level of confidence in judging whether there has been a change in a stochastic auditory stimulus. Using a combination of psychophysical reverse correlation analyses and single-trial behavioral modeling, we compared the time period over which sensory information has leverage on detection report choices versus confidence. We demonstrate that the length of this period differs on separate sets of trials based on what's being reported. Surprisingly, confidence judgments on trials with no detection report are influenced by evidence occurring earlier than the time period of influence for detection reports. Our findings call into question models of decision formation involving static parameters that yield a singular timescale of evidence evaluation and instead suggest that the brain represents and utilizes multiple timescales of evidence evaluation during deliberation.

Variation in thermal tolerance plays a key role in determining the biogeographic distribution of organisms. Consequently, identifying the mechanistic basis for thermal tolerance is necessary for understanding not only current species range limits but also the capacity for range limits to shift in response to climate change. Although variation in mitochondrial function likely contributes to variation in thermal tolerance, the extent to which mitochondrial function underlies local thermal adaptation is not fully understood. In the current study, we examine variation in thermal tolerance and mitochondrial function among three populations of the intertidal copepod Tigriopus californicus found across a latitudinal thermal gradient along the coast of California, USA. We tested (1) acute thermal tolerance using survivorship and knockdown assays, (2) chronic thermal tolerance using survivorship of nauplii and developmental rate, and (3) mitochondrial performance at a range of temperatures using ATP synthesis fueled by complexes I, II, and I&II, as well as respiration of permeabilized fibers. We find evidence for latitudinal thermal adaptation: the southernmost San Diego population outperforms the northernmost Santa Cruz in measures of survivorship, knockdown temperature, and ATP synthesis rates during acute thermal exposures. However, under a chronic thermal regime, survivorship and developmental rate are more similar in the southernmost and northernmost population than in the mid-range population (Abalone Cove). Though this pattern is unexpected, it aligns well with population-specific rates of ATP synthesis at these chronic temperatures. Combined with the tight correlation of ATP synthesis decline and knockdown temperature, these data suggest a role for mitochondria in setting thermal range limits and indicate that divergence in mitochondrial function is likely a component of adaptation across latitudinal thermal gradients.

The Subpolar North Atlantic plays a critical role in the formation of the deep water masses which drive Atlantic Meridional Overturning Circulation (AMOC). Labrador Sea Water (LSW) is formed in the Labrador Sea and exported predominantly via the Deep Western Boundary Current (DWBC). The DWBC is an essential component of the AMOC advecting deep waters southward, flowing at depth along the continental slope of the western Atlantic. By combining sustained hydrographic observations from the Labrador Sea to 26.5°N, we investigate the signal propagation and advective timescales of LSW via the DWBC from its source region to the Tropical Atlantic through various approaches using robust neutral density classifications. Two individually defined LSW classes are observed to advect on timescales that support a new plausible hydrographically observed advective pathway. We find each LSW class to advect on independent timescales, and validate a hypothesized alternative‐interior advection pathway branching from the DWBC by observing the arrival of LSW outside of the DWBC in the Bermuda basin on timescales similar to arriving at 26.5°N, 10–15 yr after leaving the source region. Advective timescales estimated herein indicate that this interior pathway is likely the main advective pathway; it remains uncertain whether a direct pathway plays a significant advective role. Using LSW convective signals as advective tracers along the DWBC permits the estimation of advective timescales from the subpolar to tropical latitudes, illuminating deep water advection pathways across the North Atlantic and the lower‐limb of AMOC as a whole. Plain Language Summary: The Deep Western Boundary Current (DWBC) exports cold and dense deep waters formed in the Subpolar North Atlantic to the tropics, and therefore plays a primary role in global ocean circulation and heat balance. We focus here on Labrador Sea Water (LSW), a water mass formed through wintertime mixing events within the Subpolar North Atlantic characterized by distinctive low‐temperature and low‐salinity signatures. By following the passage of these signatures through several locations, we investigate the pathways and spreading timescales of LSW from its source region toward the subtropical North Atlantic by the DWBC. We find two distinct LSW masses to reach the same location on independent timescales, and observe LSW in the Central Atlantic just prior to or on the same timescale as being observed in the Tropical Atlantic. These findings indicate that an alternative‐interior export pathway branching from the DWBC is likely to exist, exporting LSW away from the continental slope and into the Atlantic interior rather than following a direct equatorward route. Estimating advective timescales and pathways of the DWBC using LSW aid in the present understanding and future prediction of overturning circulation in the Atlantic Ocean. Key Points: Advection timescales of the Deep Western Boundary Current (DWBC) are inferred from Labrador Sea Water (LSW) convective minima in the North AtlanticThe two LSW classes examined are observed to advect on different timescales, likely due to varying advective pathwaysAn alternative interior‐advective pathway observed as a bifurcation in the DWBC advects water to the interior [ABSTRACT FROM AUTHOR]

Although resting-state fMRI studies support that human brain is topographically organized regarding localized and distributed processes, it is still unclear about the task-modulated cortical hierarchy in terms of distributed functional connectivity and localized timescales. To address, current study investigated the effect of cognitive load on cortical connectivity gradients and local timescales in the healthy brain using resting state fMRI as well as 1- and 2-back working memory task fMRI. The results demonstrated that (1) increased cognitive load was associated with lower principal gradient in transmodal cortices, higher principal gradient in primary cortices, decreased decay rate and reduced timescale variability; (2) global properties including gradient variability, timescale decay rate, timescale variability and network topology were all modulated by cognitive load, with timescale variability related to behavioral performance; and (3) at 2-back state, the timescale variability was indirectly and negatively linked with global network integration, which was mediated by gradient variability. In conclusion, current study provides novel evidence for load-modulated cortical connectivity gradients and local timescales during cognitive states, which could contribute to better understanding about cognitive load theory and brain disorders with cognitive dysfunction. [ABSTRACT FROM AUTHOR]

In this study. we discuss the existence. uniqueness. and controllability results for an Ambartsurnian equation with impulses using the E-Hilfer generalized proportional fractional derivative (PFD). Common fixed point theorems are employed in our analysis. We achieve a few suitable conditions for existence. uniqueness. and controllability. [ABSTRACT FROM AUTHOR]

Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through 'safety in numbers'. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through 'density-dependent transmission'. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to 'density-dependent transmission' within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk. [ABSTRACT FROM AUTHOR]

The Standardized Precipitation Index (SPI) is widely used as a drought meteorological index, to identify drought characteristics including the number of events, frequency, duration, and intensity. In the present study, the SPI is used to detect drought characteristics in spatial and temporal patterns at various timescales of 1, 3, 6, 9, 12, 18, 2-, and 48 months. For this purpose, monthly climatic data from 43 synoptic stations during 1969–2019 were analyzed from Iran’s various climates (coastal wet, mountain, semi mountain, semidesert, desert, and coastal desert). Abrupt and gradual changes in SPI1-48 were detected using the nonparametric Pettitt test and Mann–Kendall (M-K) test separately in the various climates. The M-K results show that a trend was increasingly significant at longer timescales, with the trend of SPI-1 in climates not being significant, while SPI-48 was significant at P less than 0.01 (P < 0.01) at almost all stations in all climates. According to Pettitt’s test results, the changing points of SPI vary between climates and start from Sep. 1992 (SPI1 in semi mountain climates) to Jan. 2004 (SPI48 in desert climates). These results indicate that abrupt changes in the drought index based on SPI, started first in semi mountain and mountain climates in the 1990s and then progressed towards the semidesert and desert climates in the 2000s. The number of drought events changed from 7 in coastal desert stations (Chabahar) to 52 occurrences in coastal wet stations (Bandar Anzali). Spatial distribution of drought intensity shows that drought severity is greater in coastal wet climates than in desert climates. Drought frequency varied from 15.2 to 16.3% at timescales ranging from 1 to 48 months. The mean drought duration was from 12.9 months in semi mountain to 15 months in coastal deserts for SPI1-48. Generally, the study demonstrates the need for more research to select proper timescales for drought indices that are related to climate conditions of given areas. [ABSTRACT FROM AUTHOR]

In this article, by using some algebraic inequalities, nabla Hölder inequalities, and nabla Jensen's inequalities on timescales, we proved some new nabla Hilbert-type dynamic inequalities on timescales. These inequalities extend some known dynamic inequalities on timescales and unify some continuous inequalities and their corresponding discrete analogues. Symmetry plays an essential role in determining the correct methods to solve dynamic inequalities. [ABSTRACT FROM AUTHOR]

Level of motivation, responsiveness to rewards and punishment, invigoration of exploratory behaviours, and motor performance are subject to daily fluctuations that emerge fromcircadian rhythms in neuronal activity of the midbrain’s dopaminergic system. While endogenous circadian rhythms are weak in the ventral tegmental area and substantia nigra pars compacta, daily changes in expression of core clock genes, ion channels, neurotransmitter receptors, dopamine-synthesising enzymes, and dopamine transporters, accompanied by changes in electrical activity, are readily observed in these nuclei. These processes cause dopamine levels released in structures innervated by midbrain dopaminergic neurons (e.g., the striatum) to oscillate in a circadian fashion. Additionally, growing evidence show that the master circadian clock located in the suprachiasmatic nucleus of the hypothalamus (SCN) rhythmically influences the activity of the dopaminergic system through various intermediate targets. Thus, circadian changes in the activity of the dopaminergic system and concomitant dopamine release observed on a daily scale are likely to be generated both intrinsically and entrained by the master clock. Previous studies have shown that the information about the value and salience of stimuli perceived by the animal is encoded in the neuronal activity of brain structures innervating midbrain dopaminergic centres. Some of these structures themselves are relatively autonomous oscillators, while others exhibit a weak endogenous circadian rhythm synchronised by the SCN. Here, we place the dopaminergic system as a hub in the extensive network of extra-SCN circadian oscillators and discuss the possible consequences of its daily entrainment for animal physiology and behaviour. [ABSTRACT FROM AUTHOR]

Coastal currents are studied based on hourly horizontal velocity data from the SEAWATCH WaveScan buoy moored in the southwestern Peter the Great Bay, the Sea of Japan, from May to December 2016. Using decomposition to empirical orthogonal functions in the depth – time domain and wavelet transform, the vertical structure and temporal variability are analyzed. It is found that in 2016 the current speed simultaneously increased in the upper layer (2–18 m) and decreased in the lower layer (22–42 m) or vice versa. These changes were accompanied by the left- or right-hand side vertical velocity shear and the sign of velocity vector rotation with the depth changed on the 3–7 to 50–70 day timescales. The energy cascades are detected on the timescales of 2 to 80 days and of 2 h to 1 day during the time of the intense atmospheric cyclogenesis, including the typhoon Lionrock, from late August to early September. Inertial oscillations are detected in the 2–38 m layer, gradually weakening with the depth. The signal alternately moving down and up is revealed around the inertial timescale, which is supposedly related to near inertial waves and their reflection from the bottom. The strong events were accompanied by the red or blue Doppler shift of the inertial frequency. The background relative vorticity related to the Doppler shift is estimated for these events and the flow is shown to reach the quasi-geostrophic and, on average, anticyclonic regime. [ABSTRACT FROM AUTHOR]

Presently nanoaerosol technology has widened its application in the heat transfer area and found to be exhibiting remarkable heat transfer characteristics. This paper focuses on a theoretical investigation on the convective heat transfer characteristics of a SiO2-air nanoaerosol flow inside a tube. Based on the properties of nanoparticles and air, the governing equations and numerical models have been formulated and simulations are carried out. The distribution of temperature in terms of time scale within SiO2 nanoparticles, particle to particle interaction through conduction, and nanoparticles to air by radiation is studied. At particle diameters, 30 nm to 120 nm, the timescale of particle, conduction, and radiation are compared, and it was that the temperature distribution in conduction is more rapid than radiation. Aerosol heat transfer coefficient (AHTC) at different Reynolds number (Re) from 8,000 to 20,000, with different particle volume fractions (PVF) from 0.002 to 0.01 has been investigated. Moreover, the effect of the particle migration factor on AHTC has been analysed. However, PVF has very mild effect on AHTC. A maximum of 51.96% enhancement in AHTC was observed by increasing Re from 8,000 to 20,000. Thus, the nanoaerosol has potential in gaseous cooling applications. [ABSTRACT FROM AUTHOR]

The problem of pursuing a group of evaders by a group of pursuers with equal opportunities for all participants is considered in the finite-dimensional Euclidean space. It is assumed that the movement of the players is simple in a given timescale. Additionally, we assume that in the process of the game each evader does not move out of a convex set with a nonempty interior. The goal of the pursuers' group is to capture at least q evaders, and each evader must be captured by at least r different pursuers, and the moments of capture may not coincide. Terminal sets are the coordinates origin. Assuming that the evaders use program strategies, and each pursuer catches no more than one evader in terms of initial positions, sufficient conditions for the solvability of the pursuit problem are obtained. In the research, the method of resolving functions is used as the base method, which makes it possible to obtain sufficient conditions for the solvability of the approach problem with one evader in some guaranteed time. To prove the main theorem, Hall's theorem of the system of various representatives is used. [ABSTRACT FROM AUTHOR]

Level of motivation, responsiveness to rewards and punishment, invigoration of exploratory behaviours, and motor performance are subject to daily fluctuations that emerge from circadian rhythms in neuronal activity of the midbrain’s dopaminergic system. While endogenous circadian rhythms are weak in the ventral tegmental area and substantia nigra pars compacta, daily changes in expression of core clock genes, ion channels, neurotransmitter receptors, dopamine-synthesising enzymes, and dopamine transporters, accompanied by changes in electrical activity, are readily observed in these nuclei. These processes cause dopamine levels released in structures innervated by midbrain dopaminergic neurons (e.g., the striatum) to oscillate in a circadian fashion. Additionally, growing evidence show that the master circadian clock located in the suprachiasmatic nucleus of the hypothalamus (SCN) rhythmically influences the activity of the dopaminergic system through various intermediate targets. Thus, circadian changes in the activity of the dopaminergic system and concomitant dopamine release observed on a daily scale are likely to be generated both intrinsically and entrained by the master clock. Previous studies have shown that the information about the value and salience of stimuli perceived by the animal is encoded in the neuronal activity of brain structures innervating midbrain dopaminergic centres. Some of these structures themselves are relatively autonomous oscillators, while others exhibit a weak endogenous circadian rhythm synchronised by the SCN. Here, we place the dopaminergic system as a hub in the extensive network of extra-SCN circadian oscillators and discuss the possible consequences of its daily entrainment for animal physiology and behaviour.

We examined continuous affect drawings as innovative measure of affective experiences over time. Intensive longitudinal data often rely on discrete assessments, containing “blind spots” between measurements. With continuous affect drawings participants visually depict their affect fluctuations between assessments. In an experience sampling study, participants (N = 115) rated their momentary positive and negative affect 6 times daily. From the second daily rating on, they additionally drew their positive and negative affect changes and reported affective events between assessments. They received one measurement burst between assessments daily. The strength of the approach is a substantial amount of informational gain (average 7%) over linearly interpolated points between assessments. The additional information was subsequently categorized into positive and negative affect peaks and valleys, each occurring once a day per person on average. The probability of detecting peaks and valleys increased with reported events. The drawings correlated positively with momentary affect scores from the burst. Yet, the drawing predicted the bursts less well suggesting that the momentary ratings may yield different information than the drawings. Although the timing of retrospective drawings is less precise than individual momentary assessments, this method provides a comprehensive understanding of affective experiences between assessments, offering a unique perspective on affect dynamics. [ABSTRACT FROM AUTHOR]

In this study, the kinetics of fast pyrolysis of pine wood biomass at short timescales is evaluated using analytical Curie-point and Pyroprobe® pyrolyzers. Curie-point pyrolysis was highly effective in ensuring that the biomass was heated to the set temperatures at very high heating rates and precise time scales. This is the first time the mass loss data of lignocellulosic biomass using a Curie-point pyrolyzer is being reported at short timescales of the order of 10−1 s. COMSOL Multiphysics® simulations, employed to determine the time required for the sample to heat-up to the final reaction temperature, proved that it was 0.2 s in the Curie-point pyrolyzer and 6–8 s in the Pyroprobe® reactor. Within a time period of 0.5 s for temperatures greater than 400 °C, complete conversion of the biomass was achieved using a Curie-point pyrolyzer. The conventional reaction kinetic models were not able to explain the pyrolysis behavior of the sample in a Curie-point pyrolyzer, especially at short timescales of 0–0.5 s. However, the kinetics until 0.4 s, corresponding to the release of light volatiles, is shown to follow the sigmoidal Avrami model, while the major devolatilization stage in the range of 0.4–0.5 s could not be described by a standard kinetic model. This showed that the reactions at short time scales are highly complex processes governed by the competing decomposition rates of the biomolecules. The isothermal mass loss experiments using the Pyroprobe® showed that pyrolysis followed first-order kinetics, and the rate of decomposition was slower as it took 10–20 s for the conversion to attain a steady value. The kinetic compensation for the pyrolysis of pinewood was constructed using the fast pyrolysis data and the kinetics of slow pyrolysis using isoconversional models, and it was found to be ln (A) = 0.18*E a – 3.12. • A method to measure mass loss during fast pyrolysis in a Curie-point device is developed. • Short time scale mass loss data, O (10−1 s), is obtained using Curie-point pyrolyzer. • Sample heating rate in Curie-point system is higher (>2000 °C/s) than Pyroprobe (80–100 °C/s). • Biomass conversion was complete within 0.5 s in Curie-point system, while it took 10–20 s in Pyroprobe for T > 400 °C. • The kinetic compensation equation for pinewood biomass is ln (A) = 0.18* E a – 3.12 [ABSTRACT FROM AUTHOR]

The current theory for defining the occurrence of riparian lenses (i.e., buoyant, lenticular‐shaped fresh groundwater bodies overlying saline groundwater in riparian zones) is largely based on steady‐state analyses, which neglect the transient dynamics expected in real‐world settings. In this study, the transience of riparian lens movement is investigated for the first time, considering a fully penetrating, gaining river (i.e., the river receives groundwater influxes), and rapid variations in hydraulic boundary conditions. Controlled laboratory experiments and numerical modeling are used to determine the timescales associated with lens movements. Both numerical and experimental timescales show asymmetric behavior in the growth and decline of lenses, whereby growing lenses involve longer timescales than those of shrinking lenses. Inverse relationships between timescales and final hydraulic gradients are observed, such that higher final hydraulic gradients involved shorter timescales. Results also revealed a time lag in the movement of the lens tip (i.e., where the lens and water table intersect) relative to the lens toe (i.e., intersection of the lens with the riverbank). Riparian lenses have near‐identical timescales regardless of whether the river water or aquifer hydraulic head varies, and rather, timescales are more sensitive to the final hydraulic gradient. Application of typical parameter ranges for the River Murray (South Australia) floodplains reveals timescales of years to more than a decade to expand the riparian lens by tens of meters. Insights into riparian lenses transience attained from the current study build on the understanding of transience obtained for other mixed‐convective hydrogeological processes, such as seawater intrusion and retreat. Key Points: Laboratory experiments and numerical modeling of riparian lens transience show growing lenses have longer timescales than shrinking lensesTimescales for lens movements of tens of meters are expected to range from years to more than a decade for field‐scale conditionsThe lens is slower to grow (and shrink) laterally compared to the time required to increase (and decrease) in thickness [ABSTRACT FROM AUTHOR]

Interaction among different pathways, such as metabolic, signaling and gene regulatory networks, of cellular system is responsible to maintain homeostasis in a mammalian cell. Malfunctioning of this cooperation may lead to many complex diseases, such as cancer and type 2 diabetes. Timescale differences among these pathways make their integration a daunting task. Metabolic, signaling and gene regulatory networks have three different timescales, such as, ultrafast, fast and slow respectively.The article deals with this problem by developing a support vector regression (SVR) based three timescale model with the application of genetic algorithm based nonlinear controller. The proposed model can successfully capture the nonlinear transient dynamics and regulations of such integrated biochemical pathway under consideration. Besides, the model is quite capable of predicting the effects of certain drug targets for many types of complex diseases. Here, energy and cell proliferation management of mammalian cancer cells have been explored and analyzed with the help of the proposed novel approach. Previous investigations including in silico/in vivo/in vitro experiments have validated the results (the regulations of glucose transporter 1 (glut1), hexokinase (HK), and hypoxia-inducible factor-1α (HIF-1α) among others, and the switching of pyruvate kinase (M2 isoform) between dimer and tetramer) generated by this model proving its effectiveness. Subsequently, the model predicts the effects of six selected drug targets, such as, the deactivation of transketolase and glucose-6-phosphate isomerase among others, in the case of mammalian malignant cells in terms of growth, proliferation, fermentation, and energy supply in the form of adenosine triphosphate (ATP).

Cortical dynamics are organized over multiple anatomical and temporal scales. The mechanistic origin of the temporal organization and its contribution to cognition remain unknown. Here, we demonstrate the cause of this organization by studying a specific temporal signature (time constant and latency) of neural activity. In monkey frontal areas, recorded during flexible decisions, temporal signatures display specific area-dependent ranges, as well as anatomical and cell-type distributions. Moreover, temporal signatures are functionally adapted to behaviourally relevant timescales. Fine-grained biophysical network models, constrained to account for experimentally observed temporal signatures, reveal that after-hyperpolarization potassium and inhibitory GABA-B conductances critically determine areas’ specificity. They mechanistically account for temporal signatures by organizing activity into metastable states, with inhibition controlling state stability and transitions. As predicted by models, state durations non-linearly scale with temporal signatures in monkey, matching behavioural timescales. Thus, local inhibitory-controlled metastability constitutes the dynamical core specifying the temporal organization of cognitive functions in frontal areas.

A reduced-order model of a converter-dominated microgrid system may not resemble its full-order system associated with uncertainties. This paper aims to provide a singular perturbation-based contraction framework for model order reduction in converter-dominated uncertain microgrid systems. For this purpose, the concerned microgrid system is modeled as a generalized multi-timescale system, and certain sufficient conditions are derived such that convergence between the trajectories of the uncertain full-order and the corresponding reduced-order model can be guaranteed. The contraction theory-based strategy also provides explicit parameter-dependent expressions for quantifying discrepancies. The derived results are utilized to analyze the inverter-based microgrid system’s convergence behavior and obtain uncertainty bounds on its parameters. Further, the effects of modeling uncertainties and different loading conditions on the reduced-order model’s validity are also discussed. It is observed that for any uncertainty associated with the microgrid parameters that are within the bounds of checkable conditions, the states of the reduced-order microgrid model converge to that of the uncertain full-order system. Further, it is also shown that the obtained discrepancy expressions are more precise than state of the art. [ABSTRACT FROM AUTHOR]