Scales Of Time Research Articles

Sir Benjamin William Rycroft OBE (1902-1967): British ophthalmologist and pioneer in corneal surgery.

An unsung hero of British ophthalmology is the largely forgotten Sir Benjamin Rycroft (1902-1967). This paper will discuss and analyse the undervalued career of this great man. Upon graduating from medical school, Rycroft became a General Practitioner. Rycroft then decided to train to become an ophthalmologist. Rycroft began his ophthalmology career in 1930s London focusing on the new ground-breaking surgery of keratoplasty (corneal grafting) before serving with distinction in the medical corps during the Second World War. He is chiefly remembered for his work after the war at the Queen Victoria Hospital in East Grinstead, Sussex, where he worked with renowned plastics surgeon Archibald McIndoe. During his time, there Rycroft became globally recognised for his skill in keratoplasty and started a campaign which radically changed the legal framework behind organ donation in the UK. Despite few knowing of him today, Rycroft is undoubtedly one of the most influential British ophthalmologists of the past century. He was for decades seen as one of the world's leading practitioners of keratoplasty and established a unit which restored sight to wounded veterans. His greatest achievement lies in his organ donation reform, which started the process of allowing organ donation to be carried out on a nationwide scale for the first time.

Variability in Plant–Herbivore Interactions

Plants and herbivores are remarkably variable in space and time, and variability has been considered a defining feature of their interactions. Empirical research, however, has traditionally focused on understanding differences in means and overlooked the theoretically significant ecological and evolutionary roles of variability itself. We review the literature with the goal of showing how variability-explicit research expands our perspective on plant–herbivore ecology and evolution. We first clarify terminology for describing variation and then review patterns, causes, and consequences of variation in herbivory across scales of space, time, and biological organization. We consider how incorporating variability improves existing hypotheses and leads to new ones. We conclude by suggesting future work that reports full distributions, integrates effects of variation across scales, describes nonlinearities, and considers how stochastic and deterministic variation combine to determine herbivory distributions.

The Whole Is Greater Than The Sum of Its Parts: Large-scale Phenomena Arising from Small-Scale Biophysical Processes.

The symposium "Large-scale biological phenomena arising from small-scale biophysical processes" at the SICB 2023 Annual General Meeting focused on the cross-disciplinary exploration of emergent phenomena in biology. Interactions between cells or organisms at small scales within a system can govern patterns occurring at larger scales in space, time, or biological complexity. This theme recurs in many sub-disciplines of biology, including cell and developmental biology, evolution, and ecology. This symposium, and the associated special issue introduced here, showcases a wide range of cross-disciplinary collaborations among biologists, physicists, and engineers. Technological advancements in microscopy and microfluidics, as well as complementary advances in mathematical modelling and associated theory demonstrate the timeliness of this issue. This introduction seeks to provide useful background information to place the studies within this issue in a broader biophysical context and highlight similarities in ideas and approaches across systems and sub-disciplines. We hope to demonstrate that cross-disciplinary research linking small-scale biophysics to larger-scale emergent phenomena can help us understand problems ranging from single-cell behaviors to tissue formation and function, evolution of form, and the dynamics of communities.

Application of flux limiters to passive scalar advection for the lattice Boltzmann method

A new scalar advection algorithm is presented for the lattice Boltzmann (LB) method in which numerical diffusion is reduced by a one-dimensional linear approximation paired with a flux limiter and numerical dispersion is minimized by using fluid flux calculations based on the LB distribution function. The algorithm is designed to be conservative and have low memory requirements. A finite volume method (FVM) based on the LB velocity field is also presented for comparison. We validate with uniform velocity and turbulent flow simulations showing that numerical diffusion error matches FVM results while numerical dispersion is reduced. A performance analysis indicates it is less efficient, but we demonstrate that adjusting the scalar advection time step relative to the fluid time step can improve efficiency with minor effects on accuracy.

Emergence of Hydrodynamic Spatial Long-Range Correlations in Nonequilibrium Many-Body Systems.

At large scales of space and time, the nonequilibrium dynamics of local observables in extensive many-body systems is well described by hydrodynamics. At the Euler scale, one assumes that each mesoscopic region independently reaches a state of maximal entropy under the constraints given by the available conservation laws. Away from phase transitions, maximal entropy states show exponential correlation decay, and independence of fluid cells might be assumed to subsist during the course of time evolution. We show that this picture is incorrect: under ballistic scaling, regions separated by macroscopic distances "develop long-range correlations as time passes." These correlations take a universal form that only depends on the Euler hydrodynamics of the model. They are rooted in the large-scale motion of interacting fluid modes and are the dominant long-range correlations developing in time from long-wavelength, entropy-maximized states. They require "the presence of interaction" and "at least two different fluid modes" and are of a fundamentally different nature from well-known long-range correlations occurring from diffusive spreading or from quasiparticle excitations produced in far-from-equilibrium quenches. We provide a universal theoretical framework to exactly evaluate them, an adaptation of the macroscopic fluctuation theory to the Euler scale. We verify our exact predictions in the hard-rod gas, by comparing with numerical simulations and finding excellent agreement.

Carbon-neutral and carbon-negative chemical looping processes using glycerol and methane as feedstock

Carbon-negative and neutral methods to produce H2 and other syngas-derived chemicals are tested and demonstrated in this study through chemical looping reforming of methane or glycerol. A chemical looping reactor provides the heat required to reform the glycerol or methane while having inherent CO2 capture. This is achieved using dynamically operated packed beds. If the glycerol or methane is from a biological source this gives the system the potential for negative emissions. To evaluate the potential of this system, 500 g packed bed of oxygen carriers were cyclically reduced, oxidized, and used to carry out reforming experiments. The reforming process was tested at various pressure (1 – 9 bar) and temperature (600 – 900 °C). These conditions were tested at this scale for the first time. Complete conversion of glycerol is achievable with only small quantities of CH4 slip. The maximum H2 production was achieved at 1 bar and 700 °C producing a H2/CO ratio of 10, this lowered to 9 when the temperature was increased to 900 °C. Adding CO2 to the feed stream along with H2O allows for a H2/CO ratio suitable for the Fischer Tropsch (FT) synthesis. Chemical looping reforming of CH4 with steam was successfully demonstrated in a lab reactor setup at 1 and 5 bar for multiple cycles with CH4 conversion > 99% and controlled heat losses. The temperature and concentration profiles provided identical results for consecutive cycles verifying the continuity and the feasibility of the process.

Solubilization of biomimetic lipid mixtures by some commonly used non-ionic detergents

Detergents are amphiphilic molecules often used to solubilize biological membranes and separate their components. Here we investigate the solubilization of lipid vesicles by the commonly used non-ionic detergents polyoxyethylene (20) oleyl ether (Brij 98), n-octyl-β-D-glucoside (OG), and n-dodecyl β-D maltoside (DDM) and compare the results with the standard detergent Triton X-100 (TX-100). The vesicles were composed of palmitoyl oleoyl phosphatidylcholine (POPC) or of a biomimetic ternary mixture of POPC, egg sphingomyelin (SM) and cholesterol (2:1:2 molar ratio). To follow the solubilization profile of large unilamellar vesicles (LUVs), 90° light scattering measurements were done along the titration of LUVs with the detergents. Then, giant unilamellar vesicles (GUVs) were observed with optical microscopy during exposure to the detergents, to allow direct visualization of the solubilization process. Isothermal titration calorimetry (ITC) was used to assess the binding constant of the detergents in POPC bilayers. The results show that the incorporation of TX-100, Brij 98 and, to a lesser extent, OG in the pure POPC liposomes leads to an increase in the vesicle area, which indicates their ability to redistribute between the two leaflets of the membrane in a short scale of time. On the other hand, DDM incorporates mainly in the external leaflet causing an increase in vesicle curvature/tension leading ultimately to vesicle burst. Only TX-100 and OG were able to completely solubilize the POPC vesicles, whereas the biomimetic ternary mixture was partially insoluble in all detergents tested. TX-100 and OG were able to incorporate in the bilayer of the ternary mixture and induce macroscopic phase separation of liquid-ordered (Lo) and liquid-disordered (Ld) domains, with selective solubilization of the latter. Combination of ITC data with turbidity results showed that TX-100 and OG can be incorporated up to almost 0.3 detergent/lipid, significantly more than Brij 98 and DDM. This fact seems to be directly related to their higher capacity to solubilize POPC membranes and their ability to induce macroscopic phase separation in the biomimetic lipid mixture.

Dendritic propagation on circular electrodes: The impact of curvature on the packing density.

The dendritic growth in rechargeable batteries is one of the hurdles for the utilization of high energy-density elements, such as alkaline metals, as the electrode. Herein we explore the preventive role of the curved electrode surface in the cylindrical electrode design versus the flat geometry on the stochastic evolution of the dendritic crystals. In this regard we establish a coarse-grained Monte Carlo paradigm in the polar coordinates (r,θ), which runs in a larger scale of time and space (∼μs,∼nm ) than those of interionic collisions (∼fs, Å). Subsequently we track the density and the maximum reach of the microstructures in real time, and we elaborate on the underlying mechanisms for their correlation of the relative dendrite measure with the electrode curvature. Such quantification of the positive impact of the curvature on suppressing dendrites could be utilized as an effective longevity design parameter, particularly for the cases prone to dendritic propagation.

Discovering the mesoscale for chains of conflict.

Conflicts, like many social processes, are related events that span multiple scales in time, from the instantaneous to multi-year development, and in space, from one neighborhood to continents. Yet, there is little systematic work on connecting the multiple scales, formal treatment of causality between events, and measures of uncertainty for how events are related to one another. We develop a method for extracting causally related chains of events that addresses these limitations with armed conflict. Our method explicitly accounts for an adjustable spatial and temporal scale of interaction for clustering individual events from a detailed data set, the Armed Conflict Event & Location Data Project. With it, we discover a mesoscale ranging from a week to a few months and tens to hundreds of kilometers, where long-range correlations and nontrivial dynamics relating conflict events emerge. Importantly, clusters in the mesoscale, while extracted from conflict statistics, are identifiable with mechanism cited in field studies. We leverage our technique to identify zones of causal interaction around conflict hotspots that naturally incorporate uncertainties. Thus, we show how a systematic, data-driven, and scalable procedure extracts social objects for study, providing a scope for scrutinizing and predicting conflict and other processes.

Niche concept scale in space and time: evolutionary perspectives from tropical insectivorous birds

Ecological niches are pivotal in addressing questions of species richness gradients like the Latitudinal Diversity Gradient (LDG). The Hutchinsonian niche hypervolume model and derivatives are some of the most proven tools. Accordingly, species occupy mathematically convenient spaces in relation to functional, especially trophic, relationships, as well as the physical environment. In one application, the number of species in a community is a function of average niche sizes, overlaps, and total niche volume. Alternatively, the number of coexisting species derives from invasibility criteria in relation to species-interaction modules. The daunting complexity of tropical communities begs the question of how well these ecologically inspired paradigms accommodate present knowledge of species interactions and functional relationships. Recent studies of hyperdiverse tropical insectivorous bird species suggests reevaluating the applicability of such concepts. Here I review Neotropical, arthropod-feeding bird species interactions needed to explain these species’ trophic relationships, including their diets, feeding substrates, and behavioral and morphological traits relevant to resource acquisition. Important emergent generalizations include extraordinary specializations on both prey resource locations (substrates) and behaviors, rather than on particular resources per se, and a preponderance of adaptations to exploit the anti-predator traits of prey, traits evolved in response to other predators. These specializations and implicit arms races necessitate evolutionary approaches to niches necessary to understand the relevant natural history and ecology, how these species compete interspecifically, and even how these predator species interact with prey via evolutionary enhancements. These findings, compared and contrasted with prevailing concepts and findings, suggest expanding niche concepts to accommodate both the large temporal and regional geographic scales to understand the accumulated species richness of the mainland Neotropics. These trophic specializations also highlight why many of these birds are so sensitive to human disturbances, especially habitat loss, fragmentation, and degradation.

Modeling Coastal Water Clarity Using Landsat‐8 and Sentinel‐2

AbstractUnderstanding and attributing changes to water quality is essential to the study and management of coastal ecosystems and the ecological functions they sustain (e.g., primary productivity, predation, and submerged aquatic vegetation growth). However, describing patterns of water clarity—a key aspect of water quality—over meaningful scales in space and time is challenged by high spatial and temporal variability due to natural and anthropogenic processes. Regionally tuned satellite algorithms can provide a more complete understanding of coastal water clarity changes and drivers. In this study, we used open‐access satellite data and low‐cost in situ methods to improve estimates of water clarity in an optically complex coastal water body. Specifically, we created a remote sensing water clarity product by compiling Landsat‐8 and Sentinel‐2 reflectance data with long‐term Secchi depth measurements at 12 sites over 8 years in a shallow turbid coastal lagoon system in Virginia, USA. Our satellite‐based model explained ∼33% of the variation in in situ water clarity. Our approach increases the spatiotemporal coverage of in situ water clarity data and improves estimates from bio‐optical algorithms that overpredicted water clarity. This could lead to a better understanding of water clarity changes and drivers to better predict how water quality will change in the future.

A Census of WISE-selected Dual and Offset AGNs Across the Sky: New Constraints on Merger-driven Triggering of Obscured AGNs

Pairs of galaxies hosting active galactic nuclei (AGNs) are powerful probes of merger-driven supermassive black hole (SMBH) growth as they can resolve individual AGNs and trace mergers over a large range of physical separations. To exploit this on a large scale for the first time for both obscured and unobscured AGNs, we use the photometric redshifts of AGNs selected by the Wide-field Infrared Survey Explorer (WISE) to find probabilistic pairs (<100 kpc separations) across the sky, along with a comparison sample of inactive galaxy pairs. Our final sample of integrated pair probabilities yields 198 AGN–AGN pairs (dual AGNs) and 2767 AGN–galaxy pairs (offset AGNs) with uniformly measured AGN and host galaxy physical properties. We find the fraction of galaxy pairs hosting WISE AGNs is dominated by offset AGNs and is significantly elevated above that of inactive galaxies for large host stellar masses. We show how the AGN merger fraction directly increases with AGN extinction for both offset and dual AGNs, with up to ∼40% of heavily obscured AGNs found in galaxy pairs. Elevated AGN merger fractions coincide with increased host specific star formation rates that suggest merger-driven coevolution of galaxies and SMBHs. Among dual AGNs, the most rapid SMBH growth may occur within the less-massive galaxy. Relative to stochastic mechanisms, mergers produce an excess of AGNs at increasingly smaller separations, especially for obscured AGNs (up to a factor of ∼5), and are augmented by correlated triggering. Finally, this excess is stronger than for lower-luminosity optically selected AGNs, regardless of the AGN obscuration level.

Patterns of SARS-CoV-2 circulation revealed by a nationwide sewage surveillance programme, the Netherlands, August 2020 to February 2022.

BackgroundSurveillance of SARS-CoV-2 in wastewater offers a near real-time tool to track circulation of SARS-CoV-2 at a local scale. However, individual measurements of SARS-CoV-2 in sewage are noisy, inherently variable and can be left-censored.AimWe aimed to infer latent virus loads in a comprehensive sewage surveillance programme that includes all sewage treatment plants (STPs) in the Netherlands and covers 99.6% of the Dutch population.MethodsWe applied a multilevel Bayesian penalised spline model to estimate time- and STP-specific virus loads based on water flow-adjusted SARS-CoV-2 qRT-PCR data for one to four sewage samples per week for each of the more than 300 STPs.ResultsThe model captured the epidemic upsurges and downturns in the Netherlands, despite substantial day-to-day variation in the measurements. Estimated STP virus loads varied by more than two orders of magnitude, from ca 1012 virus particles per 100,000 persons per day in the epidemic trough in August 2020 to almost 1015 per 100,000 in many STPs in January 2022. The timing of epidemics at the local level was slightly shifted between STPs and municipalities, which resulted in less pronounced peaks and troughs at the national level.ConclusionAlthough substantial day-to-day variation is observed in virus load measurements, wastewater-based surveillance of SARS-CoV-2 that is performed at high sampling frequency can track long-term progression of an epidemic at a local scale in near real time.

A global intellectual in a globalising world

ABSTRACT This paper presents Paulo Freire (1921-1997), on the centenary of his birth in 2021, as a global icon in education, whose actions, reflections and writings, as well as dialogues and talks, occurred against the background of an ever globalising world. To quote Martin Carnoy on a text concerning globalisation, published two years following Freire’s demise, processes of globalisation have intensified and acquired new meaning through advances in information technology which render production, cultural manifestations and education ever more synchronised on a planetary scale in real time. Drawing on Walter Kohan, I examine the notion of Freire as an itinerant educator, educationist and intellectual. The paper then explores the nature of hegemonic globalisation against which he struggled in his later years, until the time of his death. All this, I argue, renders him a global intellectual in a globalising world.

Pedagogy of scale: Unmastering time, teaching and living through crises

What does it mean to teach, live, and imagine one’s futures amidst a global pandemic? How to respond to the reality of unequal and overlapping crises, COVID-19 being one of them? Can alternative understandings of time help us create a more just post-pandemic university? Drawing on environmental humanities, disaster and critical time studies, in conversation with qualitative data, this article theorizes a ‘pedagogy of scale’: a practical and conceptual centering on multiple temporalities and diverse interpretative frames. The analysis argues for the need to attend to overlapping, non-linear, and changeable scales of time, reference, and meaning that students draw on in order to make sense of crises: every crisis, even as unprecedented as COVID-19, is embedded in environmental processes, long-term vulnerabilities and injustices. These overlooked and overlapping scales interweave personal, planetary, and theological notions of time—from ecological deep time to the divine time—meaning, and self. In its focus on asynchronicity, overlap and multiplicity, the analysis extends current theorizations of temporality and crisis in higher education, challenges paradigms of mastery, advocates for epistemic plurality, and embraces decolonial notions of human subjectivity, providing a much-needed critical model for the post-pandemic university.

A testing approach to clustering scalar time series

This article considers clustering stationary scalar time series using their marginal properties and a hierarchical method. Two major issues involved are to detect the existence of clusters and to determine their number. We propose a new test statistic for detecting whether a data set consists of multiple clusters and a new procedure to determine the number of clusters. The proposed method is based on the jumps, that is, the increments, in the heights of the dendrogram when a hierarchical clustering is applied to the data. We use autoregressive sieve bootstrap to obtain a reference distribution of the test statistics and propose an iterative procedure to find the number of clusters. The clusters found are internally homogeneous according to the test statistics used in the analysis. The performance of the proposed procedure in finite samples is investigated by Monte Carlo simulations and illustrated by some empirical examples. Comparisons with some existing methods for selecting the number of clusters are also investigated.

Earth mover’s distance as a measure of CP violation

We introduce a new unbinned two sample test statistic sensitive to CP violation utilizing the optimal transport plan associated with the Wasserstein (earth mover’s) distance. The efficacy of the test statistic is shown via two examples of CP asymmetric distributions with varying sample sizes: the Dalitz distributions of B0 → K+π−π0 and of D0 → π+π−π0 decays. The windowed version of the Wasserstein distance test statistic is shown to have comparable sensitivity to CP violation as the commonly used energy test statistic, but also retains information about the localized distributions of CP asymmetry over the Dalitz plot. For large statistic datasets we introduce two modified Wasserstein distance based test statistics — the binned and the sliced Wasserstein distance statistics, which show comparable sensitivity to CP violation, but improved computing time and memory scalings. Finally, general extensions and applications of the introduced statistics are discussed.

КОМП’ЮТЕРНЕ МОДЕЛЮВАННЯ ТА ДОСЛІДЖЕННЯ ЕНЕРГОЕФЕКТИВНОСТІ ПРОЦЕСІВ ЗАРЯДЖАННЯ АКУМУЛЯТОРНОЇ БАТАРЕЇ ЕЛЕКТРОМОБІЛЯ ВІД БЕЗДРОТОВОГО ЗАРЯДНОГО ПРИСТРОЮ

In the paper, based on the method of computer simulation, the process of charging a lithium-ion battery for an electric car from a wireless charger of the inductive-resonance type was investigated. It is shown that when modeling this process, it is necessary to take into account the simultaneous flow of two processes of different scales in time and interconnected - a short-term high-frequency process in the inverter of the charger with a characteristic time of 10-5 s and a long-term process of charging the battery with a characteristic time of 104 s. Direct numerical calculation of these two processes simultaneously requires significant computer resources. To solve this problem, a new approach is proposed and implemented in the Matlab/Simulink package, according to which, at the first stage, when calculating high-frequency processes in the inverter, there are modified Thevenin and Norton equivalents for a wireless charging device, taking into account the total internal losses in this device, and at in the second stage, the long-term battery charging process is calculated first in the mode of a constant current source, using the constructed Norton equivalent, and then in the mode of a constant voltage source, using the constructed Thevenin equivalent. This approach makes it possible to take into account interrelated and time-varying processes in the inverter and in the battery and to investigate the efficiency of wireless transmission of electrical energy from a stationary power source to a battery located on board an electric vehicle. According to the results of the calculations, it is shown that for the developed device, the integral efficiency of the entire battery charging process when the battery parameter increases from 20% to 95% is 86%. References 9, figures 8.

Wear, corrosion and oxidation characteristics of consolidated and laser remelted high entropy alloys manufactured via powder metallurgy

High entropy alloys have promising wear, oxidation, and corrosion properties compared to conventional alloys and superalloys. In the present study, CrCuFeNiAl0.5 and CrCuFeNiAl0.5Si0.5 alloys were prepared using a traditional powder metallurgy process and then remelted the surfaces via laser. The laser remelting (LR) process gains a denser and more homogeneous surface to alloys. Pressureless consolidated and laser-remelted specimens were subjected to wear, corrosion, and oxidation tests. In the wear tests, it was observed that the wear resistance of Si-containing samples was better due to higher hardness. However, the laser remelting process has mostly increased rather than reduced wear losses. The less volume loss of laser-melted samples was attributed to the almost pure Cu in its content. There is little difference among all samples in electrochemical corrosion measurements. The formation of a fragile passivation layer was observed in potentiodynamic polarization curves of CrCuFeNiAl0.5Si0.5 and LR-CrCuFeNiAl0.5Si0.5 alloys. The alloy with the best corrosion resistance is CrCuFeNiAl0.5Si0.5, whose icorr value is 0.936 × 10−6 A/cm2. After high-temperature oxidation tests, the CrCuFeNiAl0.5 alloy exhibited the worst oxidation performance due to not forming a protective oxide layer on the surface, while LR enabled the protective oxide scale in a short oxidation time. The presence of Si in this alloy relatively enhances the oxidation resistance. The best oxidation performance was observed in LR-CrCuFeNiAl0.5Si0.5 due to the forming of a protective Al2O3 layer during the oxidation tests.

Synchronization of Alternative Models in a Supermodel and the Learning of Critical Behavior

Abstract “Supermodeling” climate by allowing different models to assimilate data from one another in run time has been shown to give results superior to those of any one model and superior to any weighted average of model outputs. The only free parameters, connection strengths between corresponding variables in each pair of models, are determined using some form of machine learning. It is demonstrated that supermodeling succeeds because near critical states, interscale interactions are important but unresolved processes cannot be effectively represented diagnostically in any single parameterization scheme. In two examples, a pair of toy quasigeostrophic (QG) channel models of the midlatitudes and a pair of ECHAM5 models of the tropical Pacific atmosphere with a common ocean, supermodels dynamically combine parameterization schemes so as to capture criticality, associated critical structures, and the supporting scale interactions. The QG supermodeling scheme extends a previous configuration in which two such models synchronize with intermodel connections only between medium-scale components of the flow; here the connections are trained against a third “real” model. Intermittent blocking patterns characterize the critical behavior thus obtained, even where such patterns are missing in the constituent models. In the ECHAM-based climate supermodel, the corresponding critical structure is the single ITCZ pattern, a pattern that occurs in neither of the constituent models. For supermodels of both types, power spectra indicate enhanced interscale interactions in frequency or energy ranges of physical interest, in agreement with observed data, and supporting a generalized form of the self-organized criticality hypothesis. Significance Statement In a “supermodel” of Earth’s climate, alternative models (climate simulations), which differ in the way they represent processes on the smallest scales, are trained to exchange information as they run, adjusting to one another much as weather prediction models adjust to new observations. They form a consensus, capturing atmospheric behaviors that have eluded all the separate models. We demonstrate that simplified supermodels succeed, where no single approach can, by correctly representing critical phenomena involving sudden qualitative transitions, such as occur in El Niño events, that depend on interactions among atmospheric processes on many different scales in space and time. The correct reproduction of critical phenomena is vital both for predicting weather and for projecting the effects of climate change.