The short-term intermittency evaluation of distributed photovoltaic power.

Uncertainty of distributed photovoltaic(PV) power brings great challenges to the safe and stable operation of power system, in which the intermittency problem is more challenging than the fluctuation. This paper focuses on the intermittency problem of distributed PV power, firstly, an intermittency evaluation method based on generalized extreme value(GEV) theory is proposed to solve the problem of the lack of "small-sample big-gap" events. Secondly, focusing on high risk events such as high-frequency and warning mutation events, probabilistic evaluation indexes were established, including T-hour-period mutation intensity and T-hour-period mutation frequency. Finally, a two-dimensional joint probability distribution of intermittency elements is established, and the concepts of return period and return level are introduced into the photovoltaic field to provide data support for the configuration of energy storage capacity and duration, and to provide auxiliary decision-making for the execution time and development cycle of interactive projects. The proposed method provides a solution for intermittency evaluation in small sample status quo with strong data compatibility and engineering replicability.

Can precipitation intermittency predict flooding?

A mystery has emerged as to why patterns of increasing extreme rainfall have not been accompanied by similar levels of flooding, garnering growing attention given concerns over future flood risks. Antecedent moisture conditions have been proposed as the missing explanatory factor. Yet, reasons for moisture variability prior to flooding remain largely unstudied. Here, we evaluate the potential utility of precipitation intermittency, defined as the dry spell length prior to a flood, to explain the variability of flooding over 108 watersheds from 1950 to 2022. Flood magnitude is shown to be sensitive to intermittency, particularly in arid and semi-arid regions (PET/P > 0.84) and for basins with low soil field capacity (<0.31 m3/m3). Following extended dry spells >20 days, floods are only possible from the most intense storms, whereas a wider range of storms can produce flooding for shorter intermittency. The flood probability decreases by approximately 0.5 % for each additional day of dry spell, with overall flood probabilities being up to 30 % lower following extended dry periods. These results underscore the potential utility of precipitation intermittency for diagnosing current and future flood risks.

Temporal Variation and Persistence of Methane Emissions from Shallow Water Oil and Gas Production in the Gulf of Mexico.

Methane emissions from the oil and gas supply chain can be intermittent, posing challenges for monitoring and mitigation efforts. This study examines shallow water facilities in the US Gulf of Mexico with repeat atmospheric observations to evaluate temporal variation in site-specific methane emissions. We combine new and previous observations to develop a longitudinal study, spanning from days to months to almost five years, evaluating the emissions behavior of sites over time. We also define and determine the chance of subsequent detection (CSD): the likelihood that an emitting site will be observed emitting again. The average emitting central hub in the Gulf has a 74% CSD at any time interval. Eight facilities contribute 50% of total emissions and are over 80% persistent with a 96% CSD above 100 kg/h and 46% persistent with a 42% CSD above 1000 kg/h, indicating that large emissions are persistent at certain sites. Forward-looking infrared (FLIR) footage shows many of these sites exhibiting cold venting. This suggests that for offshore, a low sampling frequency over large spatial coverage can capture typical site emissions behavior and identify targets for mitigation. We further demonstrate the preliminary use of space-based observations to monitor offshore emissions over time.

How P. aeruginosa cells with diverse stator composition collectively swarm.

Swarming is a macroscopic phenomenon in which surface bacteria organize into a motile population. The flagellar motor that drives swarming in Pseudomonas aeruginosa is powered by stators MotAB and MotCD. Deletion of the MotCD stator eliminates swarming, whereas deletion of the MotAB stator enhances swarming. Interestingly, we measured a strongly asymmetric stator availability in the wild-type (WT) strain, with MotAB stators produced at an approximately 40-fold higher level than MotCD stators. However, utilization of MotCD stators in free swimming cells requires higher liquid viscosities, while MotAB stators are readily utilized at low viscosities. Importantly, we find that cells with MotCD stators are ~10× more likely to have an active motor compared to cells uses the MotAB stators. The spectrum of motility intermittency can either cooperatively shut down or promote flagellum motility in WT populations. In P. aeruginosa, transition from a static solid-like biofilm to a dynamic liquid-like swarm is not achieved at a single critical value of flagellum torque or stator fraction but is collectively controlled by diverse combinations of flagellum activities and motor intermittencies via dynamic stator utilization. Experimental and computational results indicate that the initiation or arrest of flagellum-driven swarming motility does not occur from individual fitness or motility performance but rather related to concepts from the "jamming transition" in active granular matter.IMPORTANCEIt is now known that there exist multifactorial influences on swarming motility for P. aeruginosa, but it is not clear precisely why stator selection in the flagellum motor is so important. We show differential production and utilization of the stators. Moreover, we find the unanticipated result that the two motor configurations have significantly different motor intermittencies: the fraction of flagellum-active cells in a population on average with MotCD is active ~10× more often than with MotAB. What emerges from this complex landscape of stator utilization and resultant motor output is an intrinsically heterogeneous population of motile cells. We show how consequences of stator recruitment led to swarming motility and how the stators potentially relate to surface sensing circuitry.

Behavioral discrimination and olfactory bulb encoding of odor plume intermittency.

In order to survive, animals often need to navigate a complex odor landscape where odors can exist in airborne plumes. Several odor plume properties change with distance from the odor source, providing potential navigational cues to searching animals. Here, we focus on odor intermittency, a temporal odor plume property that measures the fraction of time odor is above a threshold at a given point within the plume and decreases with increasing distance from the odor source. We sought to determine if mice can use changes in intermittency to locate an odor source. To do so, we trained mice on an intermittency discrimination task. We establish that mice can discriminate odor plume samples of low and high intermittency and that the neural responses in the olfactory bulb can account for task performance and support intermittency encoding. Modulation of sniffing, a behavioral parameter that is highly dynamic during odor-guided navigation, affects both behavioral outcome on the intermittency discrimination task and neural representation of intermittency. Together, this work demonstrates that intermittency is an odor plume property that can inform olfactory search and more broadly supports the notion that mammalian odor-based navigation can be guided by temporal odor plume properties.

Multifractality in spin glasses.

We unveil the multifractal behavior of Ising spin glasses in their low-temperature phase. Using the Janus II custom-built supercomputer, the spin-glass correlation function is studied locally. Dramatic fluctuations are found when pairs of sites at the same distance are compared. The scaling of these fluctuations, as the spin-glass coherence length grows with time, is characterized through the computation of the singularity spectrum and its corresponding Legendre transform. A comparatively small number of site pairs controls the average correlation that governs the response to a magnetic field. We explain how this scenario of dramatic fluctuations (at length scales smaller than the coherence length) can be reconciled with the smooth, self-averaging behavior that has long been considered to describe spin-glass dynamics.

Effects of flow reduction and artificial light at night (ALAN) on litter decomposition and invertebrate communities in streams: A flume experiment.

River ecosystems are heavily impacted by multiple stressors, where effects can cascade downstream of point sources. However, a spatial approach to assess the effects of multiple stressors is missing. We assessed the local and downstream effects on litter decomposition, and associated invertebrate communities of two stressors: flow reduction and artificial light at night (ALAN). We used an 18-flow-through mesocosm system consisting of two tributaries, where we applied the stressors, merging in a downstream section. We assessed the changes in decomposition rate and invertebrate community structure in leaf bags. We found no effect of ALAN or its interaction with flow reduction on the litter decomposition or the invertebrate community in the tributaries. Flow reduction alone led to a 14.8 % reduction in decomposition rate in the tributaries. We recorded no effect of flow reduction on the macroinvertebrates community composition in the litter bags. We also observed no effects of the spatial arrangement of the stressors on the litter decomposition and macroinvertebrate community structure downstream. Overall, our results suggest the impact of stressors on litter decomposition and macroinvertebrate communities remained local in our experiment. Our work thus calls for further studies to identify the mechanisms and the conditions under which spatial effects dominate over local processes.

Individual growth rates and size at metamorphosis increase with watershed area in a stream salamander.

A fundamental goal of ecology is to understand how the physical environment influences intraspecific variability in life history and, consequently, fitness. In streams, discharge and associated habitat conditions change along a continuum from intermittency to permanence: Headwater streams typically have smaller watersheds and are thus more prone to drying than higher-order streams with larger watersheds and more consistent discharge. However, few empirical studies have assessed life history and associated population responses to this continuum in aquatic organisms. We tested the prediction that individual growth, rate of development, and population growth increase with watershed area in the long-lived stream salamander Gyrinophilus porphyriticus, where we use watershed area as a proxy for hydrologic intermittence. To address this hypothesis, we used 8 years of mark-recapture data from 53 reaches across 10 headwater streams in New Hampshire, USA. Individual growth rates and mean size at metamorphosis increased with watershed area for watersheds from 0.12 to 1.66 km2 . Population growth rates increased with watershed area; however, this result was not statistically significant at our sample size. Mean age of metamorphosis did not vary across watershed areas. Lower individual growth rates and smaller sizes at metamorphosis likely contributed to reduced lifetime fecundity and population growth in reaches with the smallest watershed areas and highest vulnerability to drought. These responses suggest that as droughts increase due to climate change, headwater specialists in hydrologically intermittent environments will experience a reduction in fitness due to smaller body sizes or other growth-related mechanisms.

The microstructure of intra- and interpersonal coordination.

Movements are naturally composed of submovements, i.e. recurrent speed pulses (2-3 Hz), possibly reflecting intermittent feedback-based motor adjustments. In visuomotor (unimanual) synchronization tasks, partners alternate submovements over time, indicating mutual coregulation. However, it is unclear whether submovement coordination is organized differently between and within individuals. Indeed, different types of information may be variably exploited for intrapersonal and interpersonal coordination. Participants performed a series of bimanual tasks alone or in pairs, with or without visual feedback (solo task only). We analysed the relative timing of submovements between their own hands or between their own hands and those of their partner. Distinct coordinative structures emerged at the submovement level depending on the relevance of visual feedback. Specifically, the relative timing of submovements (between partners/effectors) shifts from alternation to simultaneity and a mixture of both when coordination is achieved using vision (interpersonal), proprioception/efference-copy only (intrapersonal, without vision) or all information sources (intrapersonal, with vision), respectively. These results suggest that submovement coordination represents a behavioural proxy for the adaptive weighting of different sources of information within action-perception loops. In sum, the microstructure of movement reveals common principles governing the dynamics of sensorimotor control to achieve both intra- and interpersonal coordination.

Forecasting small-scale dynamics of fluid turbulence using deep neural networks.

Turbulence in fluid flows is characterized by a wide range of interacting scales. Since the scale range increases as some power of the flow Reynolds number, a faithful simulation of the entire scale range is prohibitively expensive at high Reynolds numbers. The most expensive aspect concerns the small-scale motions; thus, major emphasis is placed on understanding and modeling them, taking advantage of their putative universality. In this work, using physics-informed deep learning methods, we present a modeling framework to capture and predict the small-scale dynamics of turbulence, via the velocity gradient tensor. The model is based on obtaining functional closures for the pressure Hessian and viscous Laplacian contributions as functions of velocity gradient tensor. This task is accomplished using deep neural networks that are consistent with physical constraints and explicitly incorporate Reynolds number dependence to account for small-scale intermittency. We then utilize a massive direct numerical simulation database, spanning two orders of magnitude in the large-scale Reynolds number, for training and validation. The model learns from low to moderate Reynolds numbers and successfully predicts velocity gradient statistics at both seen and higher (unseen) Reynolds numbers. The success of our present approach demonstrates the viability of deep learning over traditional modeling approaches in capturing and predicting small-scale features of turbulence.

Wavelet-Based Multiscale Intermittency Analysis: The Effect of Deformation.

Intermittency represents a certain form of heterogeneous behavior that has interest in diverse fields of application, particularly regarding the characterization of system dynamics and for risk assessment. Given its intrinsic location-scale-dependent nature, wavelets constitute a useful functional tool for technical analysis of intermittency. Deformation of the support may induce complex structural changes in a signal. In this paper, we study the effect of deformation on intermittency. Specifically, we analyze the interscale transfer of energy and its implications on different wavelet-based intermittency indicators, depending on whether the signal corresponds to a 'level'- or a 'flow'-type physical magnitude. Further, we evaluate the effect of deformation on the interscale distribution of energy in terms of generalized entropy and complexity measures. For illustration, various contrasting scenarios are considered based on simulation, as well as two segments corresponding to different regimes in a real seismic series before and after a significant earthquake.

Hydrodynamic coupling melts acoustically levitated crystalline rafts.

Going beyond the manipulation of individual particles, first steps have recently been undertaken with acoustic levitation in air to investigate the collective dynamical properties of many-body systems self-assembled within the levitation plane. However, these assemblies have been limited to two-dimensional, close-packed rafts where forces due to scattered sound pull particles into direct frictional contact. Here, we overcome this restriction using particles small enough that the viscosity of air establishes a repulsive streaming flow at close range. By tuning the particle size relative to the characteristic length scale for viscous streaming, we control the interplay between attractive and repulsive forces and show how particles can be assembled into monolayer lattices with tunable spacing. While the strength of the levitating sound field does not affect the particles' steady-state separation, it controls the emergence of spontaneous excitations that can drive particle rearrangements in an effectively dissipationless, underdamped environment. Under the action of these excitations, a quiescent particle lattice transitions from a predominantly crystalline structure to a two-dimensional liquid-like state. We find that this transition is characterized by dynamic heterogeneity and intermittency, involving cooperative particle movements that remove the timescale associated with caging for the crystalline lattice. These results shed light on the nature of athermal excitations and instabilities that can arise from strong hydrodynamic coupling among interacting particles.

Fractal Geometric Model for Statistical Intermittency Phenomenon.

The phenomenon of intermittency has remained a theoretical concept without any attempts to approach it geometrically with the use of a simple visualization. In this paper, a particular geometric model of point clustering approaching the Cantor shape in 2D, with a symmetry scale θ being an intermittency parameter, is proposed. To verify its ability to describe intermittency, to this model, we applied the entropic skin theory concept. This allowed us to obtain a conceptual validation. We observed that the intermittency phenomenon in our model was adequately described with the multiscale dynamics proposed by the entropic skin theory, coupling the fluctuation levels that extended between two extremes: the bulk and the crest. We calculated the reversibility efficiency γ with two different methods: statistical and geometrical analyses. Both efficiency values, γstat and γgeo, showed equality with a low relative error margin, which actually validated our suggested fractal model for intermittency. In addition, we applied the extended self-similarity (E.S.S.) to the model. This highlighted the intermittency phenomenon as a deviation from the homogeneity assumed by Kolmogorov in turbulence.

Mean structure of the supercritical turbulent spiral in Taylor-Couette flow.

The large-scale laminar/turbulent spiral patterns that appear in the linearly unstable regime of counter-rotating Taylor-Couette flow are investigated from a statistical perspective by means of direct numerical simulation. Unlike the vast majority of previous numerical studies, we analyse the flow in periodic parallelogram-annular domains, following a coordinate change that aligns one of the parallelogram sides with the spiral pattern. The domain size, shape and spatial resolution have been varied and the results compared with those in a sufficiently large computational orthogonal domain with natural axial and azimuthal periodicity. We find that a minimal parallelogram of the right tilt significantly reduces the computational cost without notably compromising the statistical properties of the supercritical turbulent spiral. Its mean structure, obtained from extremely long time integrations in a co-rotating reference frame using the method of slices, bears remarkable similarity with the turbulent stripes observed in plane Couette flow, the centrifugal instability playing only a secondary role. This article is part of the theme issue 'Taylor-Couette and related flows on the centennial of Taylor's seminal Philosophical transactions paper (Part 2)'.

Ureterocele prolapse eliciting unusual patient behavior to control intermittent voiding.

Ureterocele prolapse, an unusual but distinctive finding, may cause voiding difficulty. A 6-year-old male patient was referred to our hospital after his mother discovered that he tapped his lower abdomen when his urinary stream was interrupted during voiding. Voiding cystourethrography indicated a ureterocele prolapse causing the intermittency of voiding; therefore, transvesicoscopic ureteral reimplantation with ureterocelectomy was performed and the voiding consequently improved. However, this condition would not have been diagnosed had the unusual voiding behavior gone unnoticed. Therefore, diagnosing congenital bladder obstructions could be challenging if a patient adapts to a voiding difficulty.

Parabolic Potential Surfaces Localize Charge Carriers in Nonblinking Long-Lifetime "Giant" Colloidal Quantum Dots.

Materials for studying biological interactions and for alternative energy applications are continuously under development. Semiconductor quantum dots are a major part of this landscape due to their tunable optoelectronic properties. Size-dependent quantum confinement effects have been utilized to create materials with tunable bandgaps and Auger recombination rates. Other mechanisms of electronic structural control are under investigation as not all of a material's characteristics are affected by quantum confinement. Demonstrated here is a new structure-property concept that imparts the ability to spatially localize electrons or holes within a core/shell heterostructure by tuning the charge carrier's kinetic energy on a parabolic potential energy surface. This charge carrier separation results in extended radiative lifetimes and in continuous emission at the single-nanoparticle level. These properties enable new applications for optics, facilitate novel approaches such as time-gated single-particle imaging, and create inroads for the development of other new advanced materials.

Hyperchaos, Intermittency, Noise and Disorder in Modified Semiconductor Superlattices.

Weakly coupled semiconductor superlattices under DC voltage bias are nonlinear systems with many degrees of freedom whose nonlinearity is due to sequential tunneling of electrons. They may exhibit spontaneous chaos at room temperature and act as fast physical random number generator devices. Here we present a general sequential transport model with different voltage drops at quantum wells and barriers that includes noise and fluctuations due to the superlattice epitaxial growth. Excitability and oscillations of the current in superlattices with identical periods are due to nucleation and motion of charge dipole waves that form at the emitter contact when the current drops below a critical value. Insertion of wider wells increases superlattice excitability by allowing wave nucleation at the modified wells and more complex dynamics. Then hyperchaos and different types of intermittent chaos are possible on extended DC voltage ranges. Intrinsic shot and thermal noises and external noises produce minor effects on chaotic attractors. However, random disorder due to growth fluctuations may suppress any regular or chaotic current oscillations. Numerical simulations show that more than 70% of samples remain chaotic when the standard deviation of their fluctuations due to epitaxial growth is below 0.024 nm (10% of a single monolayer) whereas for 0.015 nm disorder suppresses chaos.

Deciphering modes of long-range energy transfer in perovskite crystals using confocal excitation and wide-field fluorescence spectral imaging.

Excitation energy migration beyond mesoscale is of contemporary interest for both solar photovoltaic and light-emissive devices, especially in context of organometal halide perovskites (OMHPs) which have been shown to have very long (charge carrier) diffusion lengths. While understanding the energy propagation pathways in OMHPs is crucial for further advancement of material design and improvement of opto-electronic features, the simultaneous existence of multiple processes like carrier diffusion, photon recycling, and photon transport makes it often complex to differentiate them. In this study, we unravel the diverse yet dominant excitation energy transfer mode(s) in crystalline MAPbBr3micron-sized 1D rods and plates by localized (confocal) laser excitation coupled with spectrally-resolved wide-field fluorescence imaging. While rarely used, this technique can efficiently probe excitation migration beyond the diffraction limit and can be realized by simple modification of existing epifluorescence microscopy setups. We find that in rods of length below ∼2 microns, carrier diffusion dominates amongst various energy transfer processes. However, the transient non-radiative defects severely inhibit the extent of carrier migration and also temporarily affect the radiative recombination dynamics of the photo-carriers. For MAPbBr3plates of several tens of micrometers, we find that the photoluminescence (PL) spectral characteristics remain unaltered at short distances (< ∼3µm) while at a larger distance, the spectral profile is gradually red-shifted. This implies that carrier diffusion dominates over small distances, while photon recycling,i.e., repeated re-absorption and re-emission of photons, propagates excitation energy transfer over extended length scales with assistance from wave-guided photon transport. Our findings can potentially be used for future studies on the characterization of energy transport mechanisms in semiconductor solids as well as for organic (molecular) self-assembled microstructures.

Parallel encoding of CO2 in attractive and aversive glomeruli by selective lateral signaling between olfactory afferents.

We describe a novel form of selective crosstalk between specific classes of primary olfactory receptor neurons (ORNs) in the Drosophila antennal lobe. Neurotransmitter release from ORNs is driven by two distinct sources of excitation: direct activity derived from the odorant receptor and stimulus-selective lateral signals originating from stereotypic subsets of other ORNs. Consequently, the level of presynaptic neurotransmitter release from an ORN can be significantly dissociated from its firing rate. Stimulus-selective lateral signaling results in the distributed representation of CO2-a behaviorally important environmental cue that directly excites a single ORN class-in multiple olfactory glomeruli, each with distinct response dynamics. CO2-sensitive glomeruli coupled to behavioral attraction respond preferentially to fast changes in CO2 concentration, whereas those coupled to behavioral aversion more closely follow absolute levels of CO2. Behavioral responses to CO2 also depend on the temporal structure of the stimulus: flies walk upwind to fluctuating, but not sustained, pulses of CO2. Stimulus-selective lateral signaling generalizes to additional odors and glomeruli, revealing a subnetwork of lateral interactions between ORNs that reshapes the spatial and temporal structure of odor representations in a stimulus-specific manner.