Spatiotemporal Structure Research Articles

Ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)

Abstract. Statistical bias adjustment is commonly applied to climate models before using their results in impact studies. However, different methods based on a distributional mapping between observational and model data can change the simulated trends as well as the spatiotemporal and inter-variable consistency of the model, and are prone to misuse if not evaluated thoroughly. Despite the importance of these fundamental issues, researchers who apply bias adjustment currently do not have the tools at hand to compare different methods or evaluate the results sufficiently to detect possible distortions. Because of this, widespread practice in statistical bias adjustment is not aligned with recommendations from the academic literature. To address the practical issues impeding this, we introduce ibicus, an open-source Python package for the implementation of eight different peer-reviewed and widely used bias adjustment methods in a common framework and their comprehensive evaluation. The evaluation framework introduced in ibicus allows the user to analyse changes to the marginal, spatiotemporal and inter-variable structure of user-defined climate indices and distributional properties as well as any alteration of the climate change trend simulated in the model. Applying ibicus in a case study over the Mediterranean region using seven CMIP6 global circulation models, this study finds that the most appropriate bias adjustment method depends on the variable and impact studied, and that even methods that aim to preserve the climate change trend can modify it. These findings highlight the importance of use-case-specific selection of the method and the need for a rigorous evaluation of results when applying statistical bias adjustment.

A new tool for studying seasonality and spatio-temporal structure of ENSO cycles in data and ESM simulations

Abstract In this work, we present a new diagnostic tool for El Niño Southern Oscillation (ENSO) simulations in Earth System Models (ESMs) based on the analysis of upper ocean heat content data. It allows us to identify the seasonally dependent structure of temperature anomalies in the equatorial Pacific Ocean in the form of a dominant spatio-temporal pattern. We demonstrate the results of applying a tool to analysis of real data as well as climate simulations in two versions of the Institute of Numerical Mathematics ESM. We find that the latest version of the model, with improved parameterizations of clouds, large-scale condensation, and aerosols, provides significantly better reproduction of ENSO-related structure of anomalies, as well as the phase locking of ENSO to the annual cycle. We recommend to use the tool for diagnostic analysis of ESMs regarding simulation of climate phenomena with strong seasonality.

Exciting space-time surface plasmon polaritons by irradiating a nanoslit structure.

Space-time (ST) wave packets are propagation-invariant pulsed optical beams that travel freely in dielectrics at a tunable group velocity without diffraction or dispersion. Because ST wave packets maintain these characteristics even when only one transverse dimension is considered, they can realize surface-bound waves (e.g., surface plasmon polaritons at a metal-dielectric interface, which we call ST-SPPs) that have the same unique characteristics as their freely propagating counterparts. However, because the spatiotemporal spectral structure of ST-SPPs is key to their propagation invariance on the metal surface, their excitation methodology must be considered carefully. Using finite-difference time-domain simulations, we show that an appropriately synthesized ST wave packet in free space can be coupled to an ST-SPP via a single nanoscale slit inscribed in the metal surface. Our calculations confirm that this excitation methodology yields surface-bound ST-SPPs that are localized in all dimensions (and can thus be considered as plasmonic "bullets"), which travel rigidly at the metal-dielectric interface without diffraction or dispersion at a tunable group velocity.

The Influence of Typhoon Events on the Design Storm for the Shanghai Metropolitan Area in the Yangtze River Delta, China

Given the fact that the high frequency of extreme weather events globally, in particular typhoons, has more of an influence on flood forecasting, there is a great need to further understand the impact of typhoon events on design storms. The main objectives of this paper are to examine the magnitude, occurrence, and mechanism of typhoon events in southeast coastal China and their contribution to the design storm study. We take Shanghai, which is a typical metropolitan region in the Yangtze River Delta, China, as an example. The impact of typhoons on the rainfall frequency analysis is quantitatively evaluated using stochastic storm transposition (SST)-based intensity–duration–frequency (IDF) estimates with various temporal and spatial structures under different return periods. The results show that there is significant variability in the storm magnitude within the transposition domain across different durations, highlighting the spatiotemporal heterogeneity over the coastal area. Moreover, the probability of random storm transposition exhibits an uneven distribution. The frequency of typhoon rainfall events within the transposition domain is notably high, and there is considerable variability in the structure of rainfall. Typhoon rainfall amplifies the intensity of design storms, and its contribution increases with return periods. The variability in design storms increases accordingly. Based on the advantages of SST, which retains the spatiotemporal structure of the rainfall in the generated scenarios, the overall framework provides an effective way to examine the impact of diverse characteristics of typhoon rainfall on frequency analysis and facilitate a deeper exploration of the direct impact of various types of extreme storms on the intensity, spatial, and temporal distributions of design storms amidst evolving environmental conditions over this metropolitan region.

Osl-dynamics, a toolbox for modeling fast dynamic brain activity.

Neural activity contains rich spatiotemporal structure that corresponds to cognition. This includes oscillatory bursting and dynamic activity that span across networks of brain regions, all of which can occur on timescales of tens of milliseconds. While these processes can be accessed through brain recordings and imaging, modeling them presents methodological challenges due to their fast and transient nature. Furthermore, the exact timing and duration of interesting cognitive events are often a priori unknown. Here, we present the OHBA Software Library Dynamics Toolbox (osl-dynamics), a Python-based package that can identify and describe recurrent dynamics in functional neuroimaging data on timescales as fast as tens of milliseconds. At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. It also provides novel summary measures of brain dynamics that can be used to inform our understanding of cognition, behavior, and disease. We hope osl-dynamics will further our understanding of brain function, through its ability to enhance the modeling of fast dynamic processes.

Understanding the rheological properties from linear to nonlinear regimes and spatiotemporal structure of mixed kappa and reduced molecular weight lambda carrageenan gels

Blends of different carrageenan types have proven to be useful in tuning carrageenan gels' rheological properties. However, understanding the influence of a reduced molecular weight on the gelation of mixed carrageenan gels is still limited. Here, the gelation of mixed kappa-(KC) and reduced molecular weight lambda-(LC) carrageenan systems at different mixing ratios was evaluated using rheology from linear to nonlinear regimes via large amplitude oscillatory shear (LAOS), small-angle X-ray scattering (SAXS), pulsed nuclear magnetic resonance (NMR) and particle tracking. A single-step increase in moduli was seen for mixed kappa-lambda carrageenan (KCLC) gels with decreasing temperature while LC demonstrated nongelling behavior. The LAOS response of KCLC mixed gels showed the characteristic signature of strain-stiffening corresponding to the difference in the size and dynamics of the aggregates. The cross-sectional size revealed by SAXS and dynamics of the aggregates revealed by pulsed-NMR demonstrate that KCLC gels has higher segmental mobility and formed small aggregates that reduce with decreasing the KC fraction whereas pure KC gels formed large and rigid aggregates. Thus, the spatiotemporal features of the aggregates are considered to be the origin of the strain-stiffening in mixed gels under large deformation. Moreover, the microscopic properties of the KCLC gels evaluated using particle tracking revealed a homogenous network suggesting the formation of a swollen KC network in the LC solution. Hence, our findings provide insights into the rheological behavior and network structure design of KC and reduced molecular weight LC mixed gels.

Spatiotemporal structure and composition of the microbial communities in hypersaline Lake Magadi, Kenya

Background Soda lakes are habitats characterized by haloalkaline conditions also known to host unique microbial communities. The water chemistry changes with seasons due to evaporative concentration or floods from the surrounding grounds. However, it is not yet clear if the change in physiochemical changes influences the spatiotemporal diversity and structure of microbial communities in these ecosystems. Methods This study investigated the spatiotemporal diversity and structure of microbial communities in water and brine samples collected from hypersaline Lake Magadi in the months of June–September 2018. Amplicons were generated using Illumina sequencing of the 16S rRNA gene. Results The abundant bacterial phyla were Proteobacteria, Cyanobacteria, Bacteroidetes, Actinobacteria, Firmicutes, Verrumicrobia, Deinococcus-Thermus, Spirochaetes, and Chloroflexi. The Archaeal diversity was represented by phyla Euryachaeota, Crenarchaeota, Euryarchaeota, and Thaumarchaeota. The dominant bacterial species were: Euhalothece sp. (10.3%), Rhodobaca sp. (9.6%), Idiomarina sp. (5.8%), Rhodothermus sp. (3.0%), Roseinatronobacter sp. (2.4%), Nocardioides sp. (2.3%), Gracilimonas sp. (2.2%), and Halomonas sp. (2%). The dominant archaeal species included Halorubrum sp. (18.3%), Salinarchaeum sp. (5.3%), and Haloterrigena sp. (1.3%). The composition of bacteria was higher than that of archaea, while their richness and diversity varied widely across the sampling seasons. The α-diversity indices showed that high diversity was recorded in the month of August, followed by September, June, and July in that order. Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality. The effects of physicochemical parameters on the microbial community structure showed that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) had a positive correlation with the microbial community structure. Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi. Conclusions We provide insights into the relationships between microbial communities and geochemistry across various sampling sites in Lake Magadi.

Spatial synchrony cascades across ecosystem boundaries and up food webs via resource subsidies.

Cross-ecosystem subsidies are critical to ecosystem structure and function, especially in recipient ecosystems where they are the primary source of organic matter to the food web. Subsidies are indicative of processes connecting ecosystems and can couple ecological dynamics across system boundaries. However, the degree to which such flows can induce cross-ecosystem cascades of spatial synchrony, the tendency for system fluctuations to be correlated across locations, is not well understood. Synchrony has destabilizing effects on ecosystems, adding to the importance of understanding spatiotemporal patterns of synchrony transmission. In order to understand whether and how spatial synchrony cascades across the marine-terrestrial boundary via resource subsidies, we studied the relationship between giant kelp forests on rocky nearshore reefs and sandy beach ecosystems that receive resource subsidies in the form of kelp wrack (detritus). We found that synchrony cascades from rocky reefs to sandy beaches, with spatiotemporal patterns mediated by fluctuations in live kelp biomass, wave action, and beach width. Moreover, wrack deposition synchronized local abundances of shorebirds that move among beaches seeking to forage on wrack-associated invertebrates, demonstrating that synchrony due to subsidies propagates across trophic levels in the recipient ecosystem. Synchronizing resource subsidies likely play an underappreciated role in the spatiotemporal structure, functioning, and stability of ecosystems.

S-TBN: A New Neural Decoding Model to Identify Stimulus Categories From Brain Activity Patterns.

Neural decoding is still a challenging and a hot topic in neurocomputing science. Recently, many studies have shown that brain network patterns containing rich spatiotemporal structural information represent the brain's activation information under external stimuli. In the traditional method, brain network features are directly obtained using the standard machine learning method and provide to a classifier, subsequently decoding external stimuli. However, this method cannot effectively extract the multidimensional structural information hidden in the brain network. Furthermore, studies on tensors have show that the tensor decomposition model can fully mine unique spatiotemporal structural characteristics of a spatiotemporal structure in data with a multidimensional structure. This research proposed a stimulus-constrained Tensor Brain Network (s-TBN) model that involves the tensor decomposition and stimulus category-constraint information. The model was verified on real neuroimaging data obtained via magnetoencephalograph and functional mangetic resonance imaging). Experimental results show that the s-TBN model achieve accuracy matrices of greater than 11.06% and 18.46% on the accuracy matrix compared with other methods on two modal datasets. These results prove the superiority of extracting discriminative characteristics using the STN model, especially for decoding object stimuli with semantic information.

A Joint Spatio-Temporal Sub-Nyquist Sampling Structure for Wideband Receivers

A Joint Spatio-Temporal Sub-Nyquist Sampling Structure for Wideband Receivers

A study of the spatiotemporal structure of a turbulent boundary layer measured by the use of two hot-wire probes (Velocity time series patterns and Kolmogorov's structure function)

A study of the spatiotemporal structure of a turbulent boundary layer measured by the use of two hot-wire probes (Velocity time series patterns and Kolmogorov's structure function)

Manifestation of Internal Waves in the Structure of an Artificial Slick Band

The results of a field experiment devoted to observing slick-band shape variations occurring due to the action of heterogeneous currents related to the passage of internal waves are presented and analyzed on the basis of numerical simulation. The spatiotemporal structure of a train of five solitons of internal waves has been retrieved. Their evolution in the coastal area is demonstrated based on the analysis of propagation characteristics. It is shown that the first soliton, characterized by the higher values of amplitude and width, collapsed when entering shallow water near the observation platform. The parameters of an artificial slick band affected by the passage of internal waves are determined. It is shown that the direction and width of the slick band are related to the direction and magnitude of the upper-ocean horizontal current, which contains a component related to the internal wave. The results of numerical simulation are qualitatively and quantitatively consistent with experimental data at short distances from the platform. An analysis of the conditions responsible for different regimes of slick-band response to the upper-ocean currents generated by propagating internal waves has been performed.

Unfulfilled growing-up: The novel “The Lovely Bones” by A. Sebold

The article studies the poetics of the novel “The Lovely Bones” by E. Sebold. We applied comparative-historical and structural methods. The scientific novelty of the article is our research into the novel as a work about a frustrated adulthood. We consider its ideological and artistic specificity: the narration of a dead person, the description of the world beyond and the type of the character (a teenager being on the verge of growing up). The article investigates the spatiotemporal structure of the narrative and distinguishes its earthly and heavenly places. We analyze the system of characters in the novel and prove that the protagonist’s maturation is associated with the internal evolution of minor characters whose story unfolds both in the novel’s present and in the past, which the reader discovers due to flashbacks. Our study considers the specifics of the narration: as the main character is no longer alive, she has an omniscient position – her ability of flowing into the consciousness of other characters. The novel is analyzed in terms of transformation of initiation novel’s genre structures: Suzy is simultaneously a “mentor” for her loved ones and experiences her own growing up. In the finale of the novel, the emotive aspect of the work becomes crucial: gloomy hopelessness is replaced by the motifs of hope, forgiveness and faith. The article concludes that the theme of the formation and internal evolution of a person plays a plot-forming role in modern American literature.

Стерические колебания уровня Балтийского моря

The main purpose of the paper is to estimate the capabilities of NEMO 3.6 regional reanalysis data for a realistic description of the Baltic Sea steric level oscillations, the spatio-temporal structure research and causes of modern sea level changes, induced by fluctuations in water density, in the range of interannual and seasonal variability scales. Comparison of the steric level oscillations series calculated from contact measurements of temperature and salinity at oceanographic stations and from regional reanalysis data is carried out by evaluating various statistical accuracy criteria. The paper shows that the reanalysis data allow reproducing the Baltic Sea steric level oscillations quite accurately. Estimates of linear trends indicate that in the period 1993–2020 in the open Baltic and in the west of the Gulf of Finland, the steric sea level is mainly decreasing, while in the Gulf of Bothnia the steric level is increasing. Harmonic analysis of steric level oscillations showed that the annual harmonic a in the range of seasonal variability makes a predominant contribution to steric level oscillations, its amplitude significantly exceeds the amplitudes of the harmonics sa, ta and qa. The thermosteric component has the main influence on seasonal steric level oscillations, and only in the south-west of the sea there is a significant influence of the halosteric component. During the period under review, positive linear trends were observed in the amplitudes changes of the harmonics a, sa, ta and qa in most regions of the Baltic Sea, however, in the south-west of the open Baltic, a decrease in the amplitudes of all four harmonics of seasonal steric level oscillations was observed in the south-west part of the Open Baltic Sea. In conclusion, based on the obtained results, it is assumed that the identified modern regional changes in the Baltic Sea steric level oscillations are associated with an increase in air temperature, an increase in precipitation, a decrease in wind intensity, a desalination of the upper quasi-homogeneous layer and an increase in deep and near-bottom waters salinity caused by water exchange with salty waters of the North Sea.

Принципы и методы исследования структуры метагеосистем для проектирования паломническо-туристского кластера

Introduction. The article characterizes the spatio-temporal structure of metageosystems of the pilgrimage-tourist cluster “Sanaksar – Temnikov”, located in the center of the Russian Plain, in the zone of interaction of forest-steppe and forest geosystems. Materials and methods. Thestructuring of information within the framework of thestudy is based on the simultaneous use of a natural sequence of involving interrelated principles: genetic, historical, systemic, territorial-structural. The object of study was investigated from the perspective of a geosystem approach, the structure and components of metageosystems were analyzed as spatial formations of different levels of organization, naturally functioning. Research results and discussion. A detailed description of the geosystem model of the tourist cluster “Sanaksar – Temnikov” is given. It has been proven that the sustainable development of metageosystems should be based on multifactor information support, in which the most important condition for the effective economic development of landscapes is realized through the formation of a regional spatial data infrastructure. Based on the analysis of the archaeological map of the Republic of Mordovia, patterns of development of cultural landscapes are identified. The characteristics of the processes and features of the economic development of geosystems and the formation of cultural heritage have been formed. Conclusion. The organization of a pilgrimage and tourism cluster places high demands on information support. Solving the problem of forecasting and monitoring the development of metageosystems for making management decisions is possible using methods and algorithms for processing and analyzing spatial data, designing and implementing project-oriented geoportal systems for distributing spatial data.

Integrating System Spatial Archetypes and Archetypical Evolutionary Patterns of Human Settlements: Towards Place-Based Sustainable Development

Effectively managing the diversity and complexity of human settlements is pivotal in tackling the sustainability challenges we face in the Anthropocene. Conceptualizing a city’s human settlement as a unified social–ecological system and investigating its system archetype and evolutionary pattern offer a promising approach to understanding sustainability challenges within specific spatio-temporal contexts. This study introduced a novel approach to assessing and characterizing human settlements using a spatio-temporal two-tier structure archetype analysis for human settlement systems. Applying inductive clustering to an integrated dataset, we identified five typical human settlement systems for 2019 and eight change patterns (2001–2019) in the Yangtze River Delta region. By linking inductively recognized human settlement systems into deductive categories of human-nature connectedness and associating inductive change patterns with deduced phases within the adaptive cycle, we defined five system spatial archetypes and three archetypical evolutionary patterns, revealing the typical interaction between them. This enabled us to understand sustainability challenges for each interaction, formulating seven tailored solutions to promote place-based development in human settlements. Generally, our approach showcases considerable potential in uncovering human settlement challenges, ultimately contributing to addressing these challenges at the local level within the broader context of global sustainability issues.

EXCITATION OF WAKE SURFACE PLASMON-PHONON OSCILLATIONS BY A RELATIVISTIC ELECTRON BUNCH IN A POLAR SEMICONDUCTOR WAVEGUIDE

The process of surface wakefields excitation by the relativistic electron bunch in a polar semiconductor waveguide with a vacuum channel for electron bunch propagation is studied. The spectra and spatio-temporal structure of the excited surface wakefield in such system are investigated. It is shown that the excited full surface wakefield in the terahertz and infrared frequency ranges consists of the fields of LF and HF hybrid plasmon-phonon oscillations. The amplitudes of them are determined.

Multiple axes of visual system diversity in Ithomiini, an ecologically diverse tribe of mimetic butterflies.

The striking structural variation seen in arthropod visual systems can be explained by the overall quantity and spatio-temporal structure of light within habitats coupled with developmental and physiological constraints. However, little is currently known about how fine-scale variation in visual structures arises across shorter evolutionary and ecological scales. In this study, we characterise patterns of interspecific (between species), intraspecific (between sexes) and intraindividual (between eye regions) variation in the visual system of four ithomiine butterfly species. These species are part of a diverse 26-million-year-old Neotropical radiation where changes in mimetic colouration are associated with fine-scale shifts in ecology, such as microhabitat preference. Using a combination of selection analyses on visual opsin sequences, in vivo ophthalmoscopy, micro-computed tomography (micro-CT), immunohistochemistry, confocal microscopy and neural tracing, we quantify and describe physiological, anatomical and molecular traits involved in visual processing. Using these data, we provide evidence of substantial variation within the visual systems of Ithomiini, including: (i) relaxed selection on visual opsins, perhaps mediated by habitat preference, (ii) interspecific shifts in visual system physiology and anatomy, and (iii) extensive sexual dimorphism, including the complete absence of a butterfly-specific optic neuropil in the males of some species. We conclude that considerable visual system variation can exist within diverse insect radiations, hinting at the evolutionary lability of these systems to rapidly develop specialisations to distinct visual ecologies, with selection acting at the perceptual, processing and molecular level.

TDS-KRFI: Reference Frame Identification for Live Web Streaming Toward HTTP Flash Video Protocol

Live web streaming occupies a large proportion of network traffic, and various live streaming platforms use HTTP-FLV protocol to transmit streaming. The content-aware strategy that includes frame-skipping and frame-dropping mechanisms before client decoding is essential in providing high-quality live video services to improve QoE. Therefore, frame type identification is necessary for content-aware strategy and traffic engineering. The current studies focus on keyframe identification under single datasets. However, they failed to consider the actual scenarios where there are various types of live web streaming with user interactions and only identify keyframes. After studying, we found a type of frame in normal video frames that contain image parameters for subsequent frames, which can also cause a stall if they are dropped or skipped during frame processing, and this type of frame is called a reference frame. To effectively identify keyframes and reference frames, we propose the TDS-KRFI, which extracts lightweight and effective streaming features from the encrypted traffic of live web streaming. Then we use a two-layer double similarity measure to construct the spatio-temporal structure of dynamic data units and use the DGCNN model to identify frame types. In evaluation, we use various datasets with 6,532,890 frames containing user interactions under different webcasting platforms to conduct extensive experiments. It can achieve 99.9% (average 98.96%) accuracy in keyframe identification and 95.7% in all types of frames (keyframes, reference frames, and other frames) within 9.6% of the transmission time, demonstrating the robustness and effectiveness of our approach and outperforming the state-of-the-art research so far.

Beyond spiking networks: The computational advantages of dendritic amplification and input segregation.

The brain can efficiently learn a wide range of tasks, motivating the search for biologically inspired learning rules for improving current artificial intelligence technology. Most biological models are composed of point neurons and cannot achieve state-of-the-art performance in machine learning. Recent works have proposed that input segregation (neurons receive sensory information and higher-order feedback in segregated compartments), and nonlinear dendritic computation would support error backpropagation in biological neurons. However, these approaches require propagating errors with a fine spatiotemporal structure to all the neurons, which is unlikely to be feasible in a biological network. To relax this assumption, we suggest that bursts and dendritic input segregation provide a natural support for target-based learning, which propagates targets rather than errors. A coincidence mechanism between the basal and the apical compartments allows for generating high-frequency bursts of spikes. This architecture supports a burst-dependent learning rule, based on the comparison between the target bursting activity triggered by the teaching signal and the one caused by the recurrent connections, providing support for target-based learning. We show that this framework can be used to efficiently solve spatiotemporal tasks, such as context-dependent store and recall of three-dimensional trajectories, and navigation tasks. Finally, we suggest that this neuronal architecture naturally allows for orchestrating "hierarchical imitation learning", enabling the decomposition of challenging long-horizon decision-making tasks into simpler subtasks. We show a possible implementation of this in a two-level network, where the high network produces the contextual signal for the low network.