Source Of Temporal Information Research Articles

Real-time updating of dynamic social networks for COVID-19 vaccination strategies

Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamic systems where contact networks are highly time-variant. Furthermore, the numerous mutations of SARS-CoV-2 have a significant impact on the infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamic networks collected in a high school, followed by sequential multi-layer networks generated relying on the Barabasi-Albert model emulating large-scale social networks with several communities.

High temporal resolution arterial spin labeling MRI with whole‐brain coverage by combining time‐encoding with Look‐Locker and simultaneous multi‐slice imaging

PurposeThe goal of this study was to achieve high temporal resolution, multi‐time point pseudo‐continuous arterial spin labeling (pCASL) MRI in a time‐efficient manner, while maintaining whole‐brain coverage.MethodsA Hadamard 8‐matrix was used to dynamically encode the pCASL labeling train, thereby providing the first source of temporal information. The second method for obtaining dynamic arterial spin labeling (ASL) signal consisted of a Look‐Locker (LL) readout of 4 phases that are acquired with a flip‐angle sweep to maintain constant sensitivity over the phases. To obtain whole‐brain coverage in the short LL interval, 4 slices were excited simultaneously by multi‐banded radiofrequency pulses. After subtraction according to the Hadamard scheme, the ASL signal was corrected for the use of the flip‐angle sweep and background suppression pulses. The BASIL toolkit of the Oxford Centre for FMRIB was used to quantify the ASL signal.ResultsBy combining a time‐encoded pCASL labeling scheme with an LL readout and simultaneous multi‐slice acquisition, 28 time points of 16 slices with a 75‐ or 150‐ms time resolution were acquired in a total scan time of 10 minutes 20 seconds, from which cerebral blood flow (CBF) maps, arterial transit time maps, and arterial blood volume could be determined.ConclusionWhole‐brain ASL images were acquired with a 75‐ms time resolution for the angiography and 150‐ms resolution for the perfusion phase by combining the proposed techniques. Reducing the total scan time to 1 minute 18 seconds still resulted in reasonable CBF maps, which demonstrates the feasibility of this approach for practical studies on brain hemodynamics.

Temporal detection and analysis of guideline interactions.

Clinical practice guidelines (CPGs) are assuming a major role in the medical area, to grant the quality of medical assistance, supporting physicians with evidence-based information of interventions in the treatment of single pathologies. The treatment of patients affected by multiple diseases (comorbid patients) is one of the main challenges for the modern healthcare. It requires the development of new methodologies, supporting physicians in the treatment of interactions between CPGs. Several approaches have started to face such a challenging problem. However, they suffer from a substantial limitation: they do not take into account the temporal dimension. Indeed, practically speaking, interactions occur in time. For instance, the effects of two actions taken from different guidelines may potentially conflict, but practical conflicts happen only if the times of execution of such actions are such that their effects overlap in time. We aim at devising a methodology to detect and analyse interactions between CPGs that considers the temporal dimension. In this paper, we first extend our previous ontological model to deal with the fact that actions, goals, effects and interactions occur in time, and to model both qualitative and quantitative temporal constraints between them. Then, we identify different application scenarios, and, for each of them, we propose different types of facilities for user physicians, useful to support the temporal detection of interactions. We provide a modular approach in which different Artificial Intelligence temporal reasoning techniques, based on temporal constraint propagation, are widely exploited to provide users with such facilities. We applied our methodology to two cases of comorbidities, using simplified versions of CPGs. We propose an innovative approach to the detection and analysis of interactions between CPGs considering different sources of temporal information (CPGs, ontological knowledge and execution logs), which is the first one in the literature that takes into account the temporal issues, and accounts for different application scenarios.

Areas of endemism: travelling through space and the unexplored dimension

The current concept of areas of endemism assumes that they are geographic areas where there is spatial congruence of at least two endemic taxa. When this congruence is non-random, areas of endemism are explained by historical and ecological factors. Space has been the main dimension of analysis of areas of endemism, and the role of the time dimension in areas of endemism remains unclear. Phylogenetic information is a source of temporal information to explore the structure of the areas of endemism. I review the concept of areas of endemism and discuss their conceptual models (structure and boundaries). I propose four scenarios about the structural integration of endemic taxa in the space-time dimensions into areas of endemism. A better understanding of how to interpret areas of endemism can be analysed using phylogenetic information from endemic taxa to test simultaneous divergence and to propose temporal strata. Although the evolutionary relationships of the space and time dimensions have rarely been characterized in areas of endemism, I used this conceptual framework to interpret the Andean area of endemism and its evolution.

The Internal Clock and the Structure of Time Perception

The understanding of time perception presents a series of nested problems. What is the source of temporal information? How is the information employed and stored? How are temporal discriminations and judgments made? What is the neural basis of these mechanisms? How does arousal affect them? I shall consider the development of the Information Processing Model of Timing and derive some consequences and implications from it.

Grammatical aspect, lexical aspect, and event duration constrain the availability of events in narratives

The present study investigates how readers’ representations of narratives are constrained by three sources of temporal information; grammatical aspect, lexical aspect, and the duration of intervening events. Participants read short stories in which a target event with an intrinsic endpoint or not (lexical aspect: accomplishments/activities) was described as ongoing or completed (grammatical aspect: imperfective/perfective). An intervening sentence described either a long or short duration event before the target situation was reintroduced later in the story. The electroencephalogram time-locked to the reintroduction of the target event elicited a larger N400 for perfective versus imperfective accomplishments, and this effect occurred only after short intervening events. Alternatively, the N400 to targets in the activity condition did not vary as a function of grammatical aspect or duration of intervening events. These results provide novel insight into how the temporal properties of events interact to constrain the availability of concepts in situation models.

The Neural Representation of Time: An Information-Theoretic Perspective

A prominent finding in psychophysical experiments on time perception is Weber's law, the linear scaling of timing errors with duration. The ability to reproduce this scaling has been taken as a criterion for the validity of neurocomputational models of time perception. However, the origin of Weber's law remains unknown, and currently only a few models generically reproduce it. Here, we use an information-theoretical framework that considers the neuronal mechanisms of time perception as stochastic processes to investigate the statistical origin of Weber's law in time perception and also its frequently observed deviations. Under the assumption that the brain is able to compute optimal estimates of time, we find that Weber's law only holds exactly if the estimate is based on temporal changes in the variance of the process. In contrast, the timing errors scale sublinearly with time if the systematic changes in the mean of a process are used for estimation, as is the case in the majority of time perception models, while estimates based on temporal correlations result in a superlinear scaling. This hierarchy of temporal information is preserved if several sources of temporal information are available. Furthermore, we consider the case of multiple stochastic processes and study the examples of a covariance-based model and a model based on synfire chains. This approach reveals that existing neurocomputational models of time perception can be classified as mean-, variance- and correlation-based processes and allows predictions about the scaling of the resulting timing errors.

On the Structure of the Temporal Sensory System

Evidence is reviewed that favours the hypothesis that temporal performance depends on a temporal sensory system based on a biological source of temporal information

Pinning down the Brunhes/Matuyama and upper Jaramillo boundaries: a reconciliation of orbital and isotopic time scales

Until recently, the temporal calibration of the Plio/Pleistocene portion of the geomagnetic reversal time scale (GRTS) was based exclusively on KAr isotopic ages of volcanic rocks. The so-called “chronogram technique” estimates the age that minimizes discrepancies between a given age assignment for a reversal boundary and the population of dates of known polarity. The most widely quoted date, 0.73 Ma, for the Brunhes/Matuyama boundary was derived in such a manner [1].Radioactive decay is not the only source of temporal information in the geologic record, however. Variations in several of the orbital parameters of the Earth (e.g. precession, obliquity, eccentricity) can be calculated for the last several million years and the climatic response approximated. A recent analysis of the so-called “astronomical technique” on oxygen isotopic data from deep-sea sediments suggested an age of 0.78 Ma for the Brunhes/Matuyama boundary [2], some 50,000 years older than the chronogram estimate.We reconcile the two estimates for the age of the last reversal by first presenting new magnetostratigraphic data tied to high-quality40Ar39Ar dates. Our date for the upper Jaramillo boundary is0.992 ± 0.039 Ma, considerably older than the estimate of 0.91 Ma in the standard (chronogram-based) time scale [3]. Furthermore, an age of0.746 ± 0.009 Ma was obtained for sediments immediately overlying the Brunhes/Matuyama boundary. These data are consistent with the astronomical estimates of 0.78 Ma and 0.99 Ma for the Brunhes/Matuyama and upper Jaramillo boundaries, respectively.Finally, we present a new method for estimating the uncertainties of ages calculated using the chronogram technique that employs a simple bootstrap resampling scheme. The 95% confidence region for the chronogram estimate of the Brunhes/Matuyama boundary, using an updated compilation of date/polarity pairs, spans from 0.73 to 0.78 Ma. We find, therefore, that the discrepancies between the isotopic data set and the astronomical calibration of the Brunhes/Matuyama boundary disappear when appropriate uncertainties are applied for the most recent compilation of isotopic data.