Spatiotemporal Research Articles

Highly active and stable mixed-phase In2O3-supported Ni catalyst for CO2 hydrogenation to methanol

Ni/In2O3 catalysts perform well for CO2 hydrogenation to methanol. However, there is still room for improvement in terms of methanol selectivity. In this study, Ni/In2O3 catalysts with distinct crystalline phases of indium oxide, namely cubic In2O3 (c-In2O3) and a mixed phase of cubic and hexagonal In2O3 (h + c-In2O3), were synthesized. The results showed that the Ni/h + c-In2O3 catalyst demonstrated the greatest catalytic performance, with a methanol selectivity of 96.7 % and a space time yield of methanol of 15.79 mmol·g−1·h−1 at 2 MPa, 300°C, and 24.0 L·g−1·h−1. Based on the characterization results, we concluded that the improvement of the methanol synthesis performance on the Ni/h + c-In2O3 catalyst was mainly due to improved hydrogen dissociation ability and the increased surface oxygen vacancies. The energy barrier (Ea) of the rate-limiting steps for the CH3OH and CO productions was calculated. The decreased Ea(CH3OH) and increased Ea(CO) indicate the favorable improvement of catalytic activity and selectivity for CH3OH production by Ni/In2O3, especially for Ni/h-In2O3(104).

Space-time modeling of cascading hazards: Chaining wildfires, rainfall and landslide events through machine learning

The current study sets out to explore yearly landslide susceptibility dynamics on slopes regularly affected by fires. To do so, two yearly inventories have been generated, one for the landslides and one for the wildfires, for an area of approximately 2 km2 and for a period of 24 years. It is important to stress that space–time data-driven models employed for susceptibility assessment are relatively new, and their application so far has mostly linked landslide occurrences to the precipitation trigger and the standard morphometric characteristics of the landscape at hand. Here we also consider an additional element of disturbance to the slope equilibrium, in the form of burnt areas tested from one up to three years priors to the reference landslide occurrence time. The relevance of the wildfire spatiotemporal signal is tested as part of a multi-variate modeling procedure. The results highlight at least a 10 % performance increase when these wildfire-related predictors are featured (from an average AUC of 0.75 to 0.85 in a random forest modeling framework). The associated yearly variations in the landslide occurrence probability are translated into individual maps, stressing the extent to which the standard and static definition of susceptibility does not hold especially in the context of multiple hazards and in an urban setting such as the Camaldoli hills (Naples, Italy) we chose for our test site.

Adaptive tunicate swarm optimization with partial transmit sequence for phase optimization in MIMO-OFDM

<span>Multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are widely utilized in wireless systems and maximum data rate communications. The MIMO-OFDM technology increases the efficiency of spectrum utilization. The peak-to-average-power ratio (PAPR) minimization in MIMO-OFDM is a complex task in wireless communications systems. In this research, an adaptive tunicate swarm optimization with partial transmit sequence (ATSO-PTS) algorithm is proposed for a reduction of PAPR in MIMO-OFDM. The nonsquare-matrix-based differential space time coding (N-DSTC) scheme is used for the encoding and decoding process of MIMO-OFDM. The N-DSTC encoding and decoding are linear error-correcting codes that are utilized for message transmission over noisy channels. The pre-specified quadrate phase shift keying (QPSK) symbol is deployed for the modulation and demodulation scheme. On the receiver side, the serial to parallel (S/P) conversion, and fast Fourier transform (FFT) are accomplished, alongside the received data bits being demodulated to obtain the output bits. The proposed ATSO-PTS method achieves better results according to performance metrices PAPR, bit error rate (BER) and signal-to-noise-ratio (SNR), with values of about 2.9, 0.01 and 0.025, respectively. This ensures superior results when compared to the existing methods of twin symbol hybrid optimization applied to partial transmit sequence (TSHO-PTS), selective level mapping and PTS (SLM-PTS), and particle swarm and grey wolf (PS-GW) with PTS, respectively.</span>

The Discovery of Accelerating Expansion of Universe 8.8 Billion Years after the Big Bang Vindicates M1 World One Out of the Six Solutions of Einstein’s General Theory of Relativity

This paper gives the mathematical methodology (Tensor mathematics) of describing the surfaces of our Universe in General Theory of Relativity. It expresses the mass energy equivalence formula. It introduces the concept of time dilation, length contraction and mass increment in high speed frame of reference. Minowski space time 4D manifold is illustrated for representing the flat spacetime fabric Reimannian Metric is enumerated. Schwarzschild metric and how mass is accounted for is given.

Maxwell–Dirac system in cosmology

Within the scope of a Bianchi type-I (BI) cosmological model, we study the interacting system of spinor and electromagnetic fields and its role in the evolution of the Universe. In some earlier studies, it was found that in the case of a pure spinor field, the presence of nontrivial nondiagonal components of energy–momentum tensor (EMT) leads to some severe restrictions both on the space–time geometry and/or spinor field itself, whereas in the case of electromagnetic field with induced nonlinearity, such components impose severe restrictions on metric functions and the components of the vector potential. It is shown that in the case of interacting spinor and electromagnetic fields, the restrictions are not as severe as in the other cases and in this case, a nonlinear and massive spinor field with different components of vector potential can survive in a general Bianchi type-I space–time.

Strong Metal-Support Interaction between Pt and TiO2 over High-temperature CO2 Hydrogenation.

The catalytic activities and stability of oxide-supported metal catalysts are significantly affected by metal-support interactions (MSI) between oxidic supports and supported metals. The surface properties of the support, such as its phase and defects, are crucial in MSI, including both the strong metal-support interaction (SMSI) and electronic metal-support interaction (EMSI). In this study, modulation of SMSI was achieved on rutile-supported Pt nanoparticles (NP) over high-temperature CO2 hydrogenation. The encapsulation of Pt NP surfaces with TiO2-x overlayers is precisely controlled by the defects. It is found that oxygen vacancy defects significantly enhance the catalytic stability of Pt/rutile under high-temperature reverse water-gas shift (RWGS) reaction by inhibiting the occurrence of SMSI. Pt/rutile with oxygen vacancies achieves a 301 molCO×gM-1×h-1 space time yield and considerably catalytic stability (decreased by 8%) at 800 °C over 100 h time-on-stream. Density functional theory (DFT) calculations suggest that the adsorption capacity of Pt NP on the rutile overlayer can be reduced by increasing electron density. Experimental results combined with DFT calculations show that electron transfer from Pt NP to rutile is reduced by the oxygen vacancy defects on Pt/R, preserving the metallic nature of Pt species during CO2 hydrogenation, thereby preventing the formation of SMSI.

Analysis of the three possible event horizons of anti-de Sitter space–time in the Klein–Gordon equation

In this paper, we calculate exactly the solution of Klein–Gordon equation in anti-de Sitter space–time. Due to spherical symmetry, the angular wave functions are given by spherical harmonics. The radial wave functions are given by local Heun functions. We analyze the behavior of the radial wave function in regions near three possible event horizon positions [Formula: see text] and investigate the decay rate, Hawking radiation and Hawking temperature for these three cases. Comparing the results, we verify that if the decay rate and Hawking radiation are greater, then the closer the event horizon is to the singularity of the black hole. Finally, we analyze the special case of a small black hole limit.

A novel high-order explicit exponential integrator scheme for the space–time fractional Bloch–Torrey equation

A novel high-order explicit exponential integrator scheme for the space–time fractional Bloch–Torrey equation

On the soliton-type and other physical solutions for the space–time fractional Kraenkel–Manna–Merle model

On the soliton-type and other physical solutions for the space–time fractional Kraenkel–Manna–Merle model

A Survey of Dynamical and Gravitational Lensing Tests in Scale Invariance: The Fall of Dark Matter?

We first briefly review the adventure of scale invariance in physics, from Galileo Galilei, Weyl, Einstein, and Feynman to the revival by Dirac (1973) and Canuto et al. (1977). In the way that the geometry of space–time can be described by the coefficients gμν, a gauging condition given by a scale factor λ(xμ) is needed to express the scaling. In general relativity (GR), λ=1. The “Large Number Hypothesis” was taken by Dirac and by Canuto et al. to fix λ. The condition that the macroscopic empty space is scale-invariant was further preferred (Maeder 2017a), the resulting gauge is also supported by an action principle. Cosmological equations and a modified Newton equation were then derived. In short, except in extremely low density regions, the scale-invariant effects are largely dominated by Newtonian effects. However, their cumulative effects may still play a significant role in cosmic evolution. The theory contains no “adjustment parameter”. In this work, we gather concrete observational evidence that scale-invariant effects are present and measurable in astronomical objects spanning a vast range of masses (0.5 M⊙< M <1014M⊙) and an equally impressive range of spatial scales (0.01 pc < r < 1 Gpc). Scale invariance accounts for the observed excess in velocity in galaxy clusters with respect to the visible mass, the relatively flat/small slope of rotation curves in local galaxies, the observed steep rotation curves of high-redshift galaxies, and the excess of velocity in wide binary stars with separations above 3000 kau found in Gaia DR3. Last but not least, we investigate the effect of scale invariance on gravitational lensing. We show that scale invariance does not affect the geodesics of light rays as they pass in the vicinity of a massive galaxy. However, scale-invariant effects do change the inferred mass-to-light ratio of lens galaxies as compared to GR. As a result, the discrepancies seen in GR between the total lensing mass of galaxies and their stellar mass from photometry may be accounted for. This holds true both for lenses at high redshift like JWST-ER1 and at low redshift like in the SLACS sample. Of note is that none of the above observational tests require dark matter or any adjustable parameter to tweak the theory at any given mass or spatial scale.

Enhancing GeoHealth: A step-by-step procedure for spatiotemporal disease mapping.

Cartography, or geographical visualization of disease is an essential aspect of the field of GeoHealth, yet there is limited guidance on the visualization of spatiotemporal disease maps. In order to adequately contribute to understanding disease outbreaks, disease maps should be crafted carefully and according to relevant cartographic guidelines. This article aims to increase the understanding of space-time visualization techniques that are relevant to the field of GeoHealth, by providing a step-by-step framework for the creation of space-time disease visualizations. This study introduces a systematic approach to spatiotemporal disease mapping by integrating operations from the Generalized Space Time Cube (GSTC) Framework with established cartographic symbology guidelines. This resulted in an overview table that contains both the relevant GSTC operations and cartographic guidelines, as well as a step-by-step procedure that guides users through the process of creating informative spatiotemporal disease maps. The practical application of this step-by-step procedure is demonstrated with an example using Dutch COVID-19 data. By providing a clear, practical step by step procedure, this study enhances the capacity of public health professionals, policymakers, and researchers to monitor, understand, and respond to the spatial and temporal dynamics of diseases.

SMDDH: Singleton Mention Detection using Deep Learning in Hindi Text

Mention detection is an important component of the Coreference Resolution (CR) system, where mentions such as name, nominal, and pronominals are identified. These mentions can be purely coreferential mentions or singleton mentions (non-coreferential mentions). Coreferential mentions are those mentions in a text that refer to the same entities in the real world. Whereas, singleton mentions are mentioned only once in the text and do not participate in the coreference as they are not mentioned again in the following text. Filtering of these singleton mentions can substantially improve the performance of a CR process. This paper proposes a singleton mention detection module based on a Fully Connected Network (FCN) and a Long Short-Term Memory for Hindi text and model identifying singleton mentions so that these mentions can be filtered out to reduce the search space for CR. A CR system can look for the previous reference of that mention in the text and if these mentions are removed from the list of mentions, then it reduces the searching time and also space time. This model utilizes a few hand-crafted features, context information, and embedding for words from word2vec and a multilingual Bidirectional Encoder Representations from Transformers (mBERT) language model. The coreference annotated Hindi dataset comprising 3.6K sentences, and 78K tokens are used for the task. The singleton mention detection model is analyzed extensively by experimenting with various lengths of context windows for each mention. The performance of the model is significant with two window sizes of context as compared to other various window sizes of contexts such as 2,3,4,5, etc., and all previous and all next words of each mention. The Precision, Recall, and F-measure of the LSTM-FCN model with mBERT (Word + Context + Syntactic) with two window sizes of context for identifying the singleton mentions are 63%, 71%, and 67% respectively.

Wave Speeds for a Time-Periodic Bistable Three-Species Lattice Competition System

In this paper, we consider propagation direction (which can be used to predict which species will occupy the habitat or win the competition eventually) of a bistable wave for a three-species time-periodic lattice competition system with bistable nonlinearity, aiming to address an open problem. As a first step, by transforming the competition system to a cooperative one, we study the asymptotic behavior for the bistable wave profile and then prove the uniqueness of the bistable wave speed. Secondly, we utilize comparison principle and build up two couples of upper and lower solutions to judge the sign of the bistable wave speed which partially provides the answer to the open problem. As an application, we reduce the time-periodic system to a space–time homogeneous system, we obtain the corresponding criteria and carry out numerical simulations to illustrate the availability of our results. Moreover, an interesting phenomenon we have found is that the two weak competitors can wipe out the strong competitor under some circumstances.

Space–Time Forecasting of Heating & Cooling Energy Needs as an Energy Poverty Measure in Romania

Lack of access to basic energy services, known as energy poverty, remains felt in the country, with seasonal changes and an economic divide. The frameworks to measure energy poverty differ spatially and temporally, with climate change and behavioral culture being the essential influencing factors. This paper is focused on heating and cooling energy demands, which can be defined as an energy poverty metric for the propensity to be at risk of energy poverty caused by climate regime. Employing sophisticated statistical space–time forecasting tools, we build a model incorporating spatial and temporal energy consumption volatility across Romanian regions at the NUTS3 level. The model considers climatic conditions and raw data from 45 years (1979–2023) of cooling and heating degree days to determine local trajectories for the next nine years. Identifying high-energy-poverty-risk areas in our research can provide valuable insights for policymakers, enabling them to develop targeted plans for eliminating energy poverty and ensuring equitable access to heating and cooling. The results underline the necessity of differentiated approaches in energy policies and add value to the general understanding of energy poverty issues and conditions, considering the Romanian climatic and socio-economic context.

Geometry-based stochastic channel modeling of a semi-urban environment using simultaneously transmitting and reflecting reconfigurable intelligentsurface

Simultaneously Transmitting and Reflecting (STAR) Reconfigurable Intelligent Surface (RIS) demonstrates the ability to split incoming electromagnetic beams to transmit and reflect signals in a concurrent manner. Thus, compared to conventional RIS, service area coverage is extended on deploying STAR-RIS. This paper presents a geometry-based stochastic channel model (GBSM) of STAR-RIS-assisted outdoor wireless channel. For the considered semi-urban environment, STAR-RIS operates in energy-splitting mode. Channel between a base station (BS) and users (UR/UT) located on the reflect/transmit (R/T) side of STAR-RIS is characterised using a GBSM. An elliptical model incorporates the inevitable presence of scatterers in the considered semi-urban segment. Statistical properties of the wireless channel under test are analysed using space–time cross-correlation function (ST-CCF) and temporal auto-correlation function (ACF). Further, to gain holistic insight about the wireless channel behaviour, normalised Doppler power spectral density (ND-PSD) is estimated for semi-urban segment having three distinct underlying hypothesis as: (i) Wireless channel is governed by Rayleigh fading model, (ii) Wireless Channel is equipped with conventional RIS and (iii) STAR-RIS is an integral part of the considered wireless channel. Simulation results confirm that STAR-RIS performs at par with RIS, however, facilitating an additional degree of coverage. It is observed that temporal ACF and ST-CCF improves with an increase in the number of elements in STAR-RIS.

A Literacy Narrative in Legal Discourse of Russia

The paper elucidates the role of a literacy narrative in the construction and content of domestic legal discourse. On the basis of communicative methodology, the author examines the value aspects of the impact of the fiction on the consciousness and behavior of subjects of law and the construction of legal reality. An analysis of the literacy narrative as a collection of works of fiction having existence in a certain space-time continuum made it possible to conclude that the literary narrative is both a specific form of knowledge of legal reality and a means of influencing human consciousness and behavior in the process of legal socialization. Of all the sociocultural paradigms that mediate a person’s perception of the essence of law, not only in the legal, but also in the social sense, it is fiction that occupies the most significant place. Being a form of collective consciousness, a literary work in the process of legal communication broadcasts information about value attitudes, the implementation of which will make it possible to give the addressee’s legal behavior a purposeful character and ensure its identification with the community of which he is a member. The images of law and legal reality formed in domestic works of art are an explication of legal archetypes and broadcast the primacy of the value component of legal reality over the normative.

From urban heat islands to intra-urban heat islands: Role of urban fabric in redefining microclimates of tomorrow’s compact cities

A compact city is a urban area characterized by high density, mixed land use, and limited sprawl, designed to promote sustainable development, reduce urban sprawl, and enhance quality of life. This investigation focuses on the Intra Urban Heat Island (IUHI) effect, an intensified progression of the Urban Heat Island (UHI) phenomenon, specifically within a compact city transitioning from urban sprawl. The study employed advanced spatial analytics, which employed the concept of “space-time cube”, incorporating Getis Ord Gi*, and per pixel, Mann Kendall tests for the space–time pattern mining on a time series of high-resolution Remote Sensing data spanning from 1999 to 2023. The findings reveal distinctive spatial and temporal patterns in IUHI, identifying a total of 693,900 m2 of intensifying hot-spot areas in the selected compact city characterized by industrial, warehousing, and commercial developments. The detailed examination of urban fabric at a finer resolution (7.5 cm × 7.5 cm) identified rooftops with specific spectral characteristics (red/copper hue) as significant contributors to the IUHI phenomenon, inducing surface temperature increases above 5 °C compared to neighboring cells. Furthermore, high-rise developments emerge as land use forms that create cold spots in the urban fabric, improving the city’s thermal environment. The implications underscore the necessity for future urban planning to consider IUHI as a concentrated development of the UHI effect, urging a holistic understanding of the complex interconnections among various factors influencing microclimates in urban environments.

Metabolic rate and foraging behaviour: a mechanistic link across body size and temperature gradients

The mechanistic link between metabolic rate and foraging behaviour is a crucial aspect of several energy‐based ecological theories. Despite its importance to ecology however, it remains unclear whether and how energy requirements and behavioural patterns are mechanistically connected. Here we aimed to assess how modes of behaviour, including cumulative space use, patch selection and time spent in an experimental resource‐patchy environment, are related to a forager's standard metabolic rate (SMR) and its main determinants, i.e. body mass and temperature. We tested the individual behavioural patterns and metabolic rates of a model organism, the amphipod Gammarus insensibilis, across a range of body masses and temperatures. We demonstrated quantitatively that body mass and temperature exert a major influence on foraging decisions and space use behaviour via their effects on metabolic rates and the marginal value of energy. Individual cumulative space use was found to scale allometrically with body mass and exponentially with temperature, with patch giving‐up time falling as body mass and temperature increased. In response to warmer temperatures, the specimens adaptively intensified their foraging effort and explored larger spaces to offset the elevated SMR. Our results showed that SMR explained more variation than body mass and temperature combined, and had greater predictive power for behavioural patterns. Furthermore, foraging decisions regarding patch choice and partitioning were strongly related to mass‐and‐temperature‐adjusted SMR (residual), which is a component of metabolic phenotype. Individuals with higher M–T adjusted SMR initially preferred the most profitable patch and, as time progressed, abandoned the patch earlier and explored more space than the others. These results demonstrate that foraging decisions are intimately associated with variations in standard metabolic rate, whether phenotypic or due to size and temperature combined. This, in turn, sheds light on higher‐order energy‐based ecological processes.

A tool for integrating agrometeorological observation data for digital agriculture: A Minnesota case study

AbstractAgrometeorological data are essential for understanding production using digital agriculture techniques. However, integrating agrometerological observations from multiple sources remains a challenge. Often, digital agriculture scientists download and clean the same datasets many times. We present a prototype system that simplifies the process of collecting, cleaning, integrating, and aggregating data from meteorological data sources by providing a simplified user interface, database, and application programming interface. The prototype provides a standard interface for querying multiple geospatial formats (raster and vector) and integrates observation networks including the National Oceanic and Atmospheric Administration Global Historical Climatology Network (NOAA GHCN), NOAA NClim‐Grid (NOAA's Gridded Climate Normals), and Ameriflux BASE. The system automatically checks and updates data, saving storage space and processing time, and allows users to summarize data spatially and temporally. Provided as open source code and browser‐based user interface, the application and integration system can be run across Windows, Linux, and Mac environments to support broader use of multi‐source agrometeorology data.

Non-Markovian dynamics control of an open quantum system in a Schwarzschild space–time

By considering two qubits respectively coupled with two independent reservoirs and ignoring the interaction between them, two different cases are studied in two models: only one qubit accelerates and hovers near the event horizon or both two qubits accelerate and hover near the event horizon. The first model is given by referring to the damping Jaynes–Cummings model with a reservoir described by Lorentzian spectral density. And the second model is a pure dephasing model with a reservoir described by Ohmic spectral density. We investigate the impact of acceleration and Hawking temperature on the non-Markovianity and the quantum speed limit time of a two-qubit open quantum system. Through the numerical calculation, it is found that for these two models, by reducing the acceleration of qubits and the Hawking temperature outside the event horizon, the non-Markovianity of the dynamic process of the quantum system in the Schwarzschild space–time can be enhanced until it approaches the non-Markovianity when both qubits are in the inertial frame. However, we find that in the first model, the evolution speed of quantum state can be accelerated with decreasing acceleration and Hawking temperature. While in the second model, the quantum state evolution speed can be accelerated with increasing acceleration and Hawking temperature. For both models, the evolution speed of the quantum state of the system in the Markovian dynamics can still be accelerated.