Space-time Mapping Research Articles

Space-time mapping relationships in sensorimotor communication during asymmetric joint action.

Sensorimotor communication is frequently observed in complex joint actions and social interactions. However, it remains challenging to explore the cognitive foundations behind sensorimotor communication. The present study extends previous research by introducing a single-person baseline condition and formulates two distinct categories of asymmetric joint action tasks: distance tasks and orientation tasks. This research investigates the action performance of 65 participants under various experimental conditions utilizing a 2 (cooperative intention: Coop, No-coop) × 2 (task characteristic: distance, orientation) × 4 (target: T1, T2, T3, T4) repeated-measures experimental design to investigate the cognitive mechanisms underlying sensorimotor communication between individuals. The results showed that (1) target key dwell time, motion time, total motion time, and maximum motion height in the Coop condition are more than in the No-coop condition. (2) In the distance task without cooperative intention, the dwell time of T4 is smaller than T1, T2, T3, and its variability of T1, T2, T3, and T4 were no different. In the distance task with cooperative intention, the dwell time and its variability of T1, T2, T3, and T4 displayed an increasing trend. (3) In the orientation task without cooperative intention, the dwell time of T1 is smaller than T2, T3, T4, and variability of the target keys T1, T2, T3, and T4 had no difference. In the orientation task with cooperative intention, the dwell time and variability of the target keys T1, T2, T3, and T4 had increasing trends. Those findings underscore the importance of cooperative intention for sensorimotor communication. In the distance task with cooperative intention, message senders establish a mapping relationship characterized by "near-small, far-large" between the task distance and the individual's action characteristics through sensorimotor experience. In the orientation task with cooperative intention, message senders combined sensorimotor experience and verbal metaphors to establish a mapping relationship between task orientation and action characteristics, following the sequence of "left-up, right-up, left-down, right-down" to transmit the message to others.

Space-time mapping of soil organic carbon stock and its local drivers: Potential for use in carbon accounting

The measurement and tracking of changes in soil organic carbon (SOC) stocks and its underpinning drivers are important in greenhouse gas accounting and carbon trading schemes. While repeated direct measurement of a location over time is the ‘gold standard’ for SOC stock change estimation, this is currently unfeasible at scale due to sample collection and analysis costs. Here, we used a data-driven, space–time digital soil mapping modelling approach (ST-DSM) coupled with an interpretive machine learning (IML) technique to both predict and quantify the relative contributions of covariates to annual SOC stocks and their uncertainty at 0–30 cm depth and at a 90 m spatial resolution for Australia between 1990 and 2018. A quantile regression forest model was calibrated using data from a datacube comprising of SOC stock values collected over the prediction years and a suite of dynamic and static environmental covariates. The evaluation of the ST-DSM model on a test set was satisfactory. Long-term annual mean (Mg C/ha), and total (Pg C) topsoil SOC stock were 37.6 (12.3 – 101.1, 90 % PI) and 28.3 (9.25 – 83.1, 90 % PI) respectively. The mean annual rate of SOC stock change over the Australian continent was 0.11 (±0.22) Mg C/ha yr−1 and the total net change was 23.5 Tg C yr−1, indicating Australia’s soils were a net sink of SOC over the 29-year period. However, SOC stocks declined in the montane ecoregion, a great concern given its fragility and high SOC stock. The long-term mean fraction of photosynthetic vegetation was the most important individual local contributor to SOC stock prediction in many parts of Australia. The aggregated effect of covariates based on the soil forming factors indicates vegetation as the principal local driver of SOC stock across most of the Australian continent, followed by climate. The evaluation of our results against independent, temporally paired field data and estimates from a nationally accepted SOC process-based model yielded promising results. Our approach demonstrates the use of readily available and inexpensive covariates to estimate SOC stock changes, as well as the underlying drivers over a larger area but at a spatial resolution suitable for decision making. This approach presents a new monitoring and verification possibility for carbon projects and national carbon accounting especially with the growing number of existing profile observations in soil databases.

Evaluation of U-Net transfer learning model for semantic segmentation of landslides in the Colombian tropical mountain region

Landslides in tropical regions, like the Colombian Andean region, pose unique challenges due to factors such as intense rainfall, steep slopes, and complex terrains. Mapping historical and current landslide activity through inventory maps is essential in tropical mountainous regions. While satellite data is commonly used for mapping, it can be time-consuming and manual-intensive, limiting inventory availability. Deep Learning (DL) models, especially Convolutional Neural Networks (CNNs), have shown promise in remote sensing applications with High Resolution (HR) imagery, including landslide detection. Despite advancements, their use in this field is still relatively limited. This study assesses the effectiveness of U-Net model, for automated landslide detection using spectral data from optical satellite imagery (RGB bands), two DEM-derived geo-indices (slope and curvature), and two Synthetic Aperture Radar (SAR) layers (VV amplitude pre- and post-landslide event in May 2015) across three image models (3, 5, and 7 bands). Initially, data is combined into multiband images, and the model is trained in the “La Argelia” river basin in Colombia’s Pacific region. Subsequently, the model is tested in the “La Liboriana” river basin in the western Andean region. The landslide detection results within the inference area are validated by comparing them with the landslide inventory and segmentation results. The U-Net model demonstrates good performance (F1-score around 0.70) for landslide detection, as confirmed in various geographical settings. By utilizing DL models and combining high-resolution satellite imagery, topographical, and SAR data, a comprehensive space-time mapping of landslides can be achieved. This approach has the potential to greatly improve the accuracy and effectiveness of landslide mapping, offering a more holistic view of the temporal dynamics related to these natural hazards.

Toward coherent space–time mapping of seagrass cover from satellite data: an example of a Mediterranean lagoon

Abstract. Seagrass meadows are a highly productive and economically important shallow coastal habitat. Their sensitivity to natural and anthropogenic disturbances, combined with their importance for local biodiversity, carbon stocks, and sediment dynamics, motivate a frequent monitoring of their distribution. However, generating time series of seagrass cover from field observations is costly, and mapping methods based on remote sensing require restrictive conditions on seabed visibility, limiting the frequency of observations. In this contribution, we examine the effect of accounting for environmental factors, such as the bathymetry and median grain size (D50) of the substrate as well as the coordinates of known seagrass patches, on the performance of a random forest (RF) classifier used to determine seagrass cover. Using 148 Landsat images of the Venice Lagoon (Italy) between 1999 and 2020, we trained an RF classifier with only spectral features from Landsat images and seagrass surveys from 2002 and 2017. Then, by adding the features above and applying a time-based correction to predictions, we created multiple RF models with different feature combinations. We tested the quality of the resulting seagrass cover predictions from each model against field surveys, showing that bathymetry, D50, and coordinates of known patches exert an influence that is dependent on the training Landsat image and seagrass survey chosen. In models trained on a survey from 2017, where using only spectral features causes predictions to overestimate seagrass surface area, no significant change in model performance was observed. Conversely, in models trained on a survey from 2002, the addition of the out-of-image features and particularly coordinates of known vegetated patches greatly improves the predictive capacity of the model, while still allowing the detection of seagrass beds absent in the reference field survey. Applying a time-based correction eliminates small temporal variations in predictions, improving predictions that performed well before correction. We conclude that accounting for the coordinates of known seagrass patches, together with applying a time-based correction, has the most potential to produce reliable frequent predictions of seagrass cover. While this case study alone is insufficient to explain how geographic location information influences the classification process, we suggest that it is linked to the inherent spatial auto-correlation of seagrass meadow distribution. In the interest of improving remote-sensing classification and particularly to develop our capacity to map vegetation across time, we identify this phenomenon as warranting further research.

Does walking/running experience shape the sagittal mental time line?

A growing body of evidence suggested that time could be separately represented either on the lateral or sagittal axis. And the lateral mental time line has an origin associated with sensorimotor experience, e.g., reading/writing. However, it is still not clear whether the sagittal mental time line also originates from sensorimotor experience, e.g., walking/running. To address this question, we examined how the movement experience affected the space–time mapping on the lateral and sagittal axes using the virtual reality technique in two experiments. The results showed that the virtual movement experience had significant effects on the space–time mapping on the lateral axis (Experiment 1), but not on the sagittal axis (Experiment 2). This finding supported that the space–time mapping on the lateral axis does originate from sensorimotor experience, while the space–time mapping on the sagittal axis more likely originates from spatial metaphors in languages or other cultural experiences.

Space-time mapping on the sagittal axis in congenital blindness.

Previous evolutionary perspectives proposed that the space-time mapping on the sagittal axis originates from visuo-locomotion coupling when walking/running forward. Accordingly, the congenitally blind could not have developed a sagittal mental timeline if the latter depends on such a visuo-locomotion coupling. However, this conclusion was reached in only a single empirical study (Rinaldi et al. in J Exp Psychol General 147:444-450, 2018), and its theoretical underpinnings are not entirely convincing as locally static and continuous auditory input undergoes a relatively similar change as function of self-locomotion, but this type of sensory-locomotion coupling is spared even in congenital blindness. Therefore, the present study systematically explored whether the congenitally blind show space-time mappings on the sagittal axis using different paradigms in three experiments. In Experiment 1, using a typical implicit RT task, the congenitally blind showed the same preferred space-time mapping in the sagittal dimension as normally sighted participants did. In Experiment 2, this space-time mapping occurred even automatically when temporal relations were task-irrelevant in a naming task. In Experiment 3, in an explicit space-time mapping task, the congenitally blind were more likely to locate the past behind and the future in front of their bodies. Moreover, most blind participants used spatial metaphors for their space-time mapping on the sagittal axis. These results supported the conclusion that the congenitally blind have a sagittal mental timeline, and that their sensory-locomotion coupling experience was either more similar to that of sighted participants or not critical for the space-time mapping. The present study, thus, also helps to clarify the origin of the sagittal mental timeline.

Transcriptional space-time mapping identifies concerted immune and stromal cell patterns and gene programs in wound healing and cancer

Tissue repair responses in metazoans are highly coordinated by different cell types over space and time. However, comprehensive single-cell-based characterization covering this coordination is lacking. Here, we captured transcriptional states of single cells over space and time during skin wound closure, revealing choreographed gene-expression profiles. We identified shared space-time patterns of cellular and gene program enrichment, which we call multicellular "movements" spanning multiple cell types. We validated some of the discovered space-time movements using large-volume imaging of cleared wounds and demonstrated the value of this analysis to predict "sender" and "receiver" gene programs in macrophages and fibroblasts. Finally, we tested the hypothesis that tumors are like "wounds that never heal" and found conserved wound healing movements in mouse melanoma and colorectal tumor models, as well as human tumor samples, revealing fundamental multicellular units of tissue biology for integrative studies.

The effect of temporal focus on implicit space-time mapping in a life history strategy framework

The effect of temporal focus on implicit space-time mapping in a life history strategy framework

Cognitive Radios Equipped With Modulation and STBC Recognition Over Coded Transmissions

Signal recognition has recently emerged as a key ingredient for cognitive radios with defense and industrial uses. This letter area encompasses the recognition of a broad range of transmission aspects such as modulation format, space-time mapping, channel coding form, central frequency, and data rate. Each of these aspects has been extensively researched in the literature. Only a few works addressed co-recognition. To the best of the authors’ knowledge, there is a single study that is dedicated to the recognition of combined modulation and space-time block coding (STBC), with the constraints of having more receive antennas than transmit antennas and operating over frequency-flat channels. In this letter, we propose a novel algorithm that recognizes modulation and STBC simultaneously over unknown frequency-selective channels while relaxing the requirement of having more antennas at the receiver than at the transmitter. The mathematical treatments demonstrate how an iterative expectation-maximization strategy is simply used to create a maximum-likelihood solution for this problem. Additionally, we make use of soft information coupled with channel decoders to enhance the proposed algorithm’s recognition performance. The proposed design also incorporates the supplementary task of channel estimation as a part of its overall structure. According to the findings of the computational complexity analysis and simulation results, the proposed algorithm easily defeats the one documented in the literature.

The Spatial Construal of TIME in Indonesian: Evidence from Language and Gesture

This paper presents evidence from language and gesture for the spatial conceptualisation of time in Indonesian. Linguistic evidence corroborates the dominant patterns of space-time mapping for deictic (i.e., future, present/now, and past) and sequential times (i.e., before-after). Indonesian speakers talk about the future as an event in front of the Ego, while the past is behind the Ego. The spontaneous gestural data reflect and extend the patterns observed in other languages. Forward and backward (i.e., sagittal) gestures tend to accompany future and past expressions respectively. Deictic times can also be construed through the leftward and rightward (i.e., lateral) gestures and the combination of the sagittal and lateral axes, which lack a linguistic analogue. The sequential-time gesture is more likely to be lateral. Our study contributes to (i) the exploration of universality and variation in the construal of time in language and gesture, and (ii) the growing interest within Cognitive Linguistics in converging and/or diverging evidence from different methods and data types.

Spatio-Temporal Variation of Malaria Incidence and Risk Factors in West Gojjam Zone, Northwest Ethiopia.

Introduction:Malaria is a life-threatening acute febrile illness which is affecting the lives of millions globally. Its distribution is characterized by spatial, temporal, and spatiotemporal heterogeneity. Detection of the space-time distribution and mapping high-risk areas is useful to target hot spots for effective intervention.Methods:Time series cross sectional study was conducted using weekly malaria surveillance data obtained from Amhara Public Health Institute. Poisson model was fitted to determine the purely spatial, temporal, and space-time clusters using SaTScan™ 9.6 software. Spearman correlation, bivariate, and multivariable negative binomial regressions were used to analyze the relation of the climatic factors to count of malaria incidence.Result:Jabitenan, Quarit, Sekela, Bure, and Wonberma were high rate spatial cluster of malaria incidence hierarchically. Spatiotemporal clusters were detected. A temporal scan statistic identified 1 risk period from 1 July 2013 to 30 June 2015. The adjusted incidence rate ratio showed that monthly average temperature and monthly average rainfall were independent predictors for malaria incidence at all lag-months. Monthly average relative humidity was significant at 2 months lag.Conclusion:Malaria incidence had spatial, temporal, spatiotemporal variability in West Gojjam zone. Mean monthly temperature and rainfall were directly and negatively associated to count of malaria incidence respectively. Considering these space-time variations and risk factors (temperature and rainfall) would be useful for the prevention and control and ultimately achieve elimination.

Space-time mapping of co-working spaces in Cairo: shifting paradigms from openness to technologically controlled spaces

The paper demonstrates how co-working spaces, with their openness ideologies that are not only manifested in sharing space, but also sharing knowledge and generating access to nonhierarchical productive opportunities, are being subsumed into reinforcing neoliberal exclusiveness. The paper questions the openness of co-working spaces that reconciled with the dominant ideologies of 2011 Cairo, setting the stage to the mushrooming of co-working spaces inside Cairo’s apartment buildings as zones of relative freedom. Through space-time mapping of the emergence of co-working spaces in Cairo, in addition to interviews with co-workers, co-founders, and managers of co-working spaces, the spatial appropriation and accessibility of co-working spaces are demonstrated. Using content analysis and space syntax analysis, the study differentiates between two paradigmatic shifts in the spatial appropriation of co-working spaces—from democratizing digital infrastructure in the aftermath of 2011, to being subsumed by technological capitalist ventures by the end of 2015 into a closed paradigm, they originally emerged to defy—and compares between the spatial accessibility, visual accessibility, and social diversity of the two waves of co-working spaces. Using Cairo’s co-working spaces as a case study, this paper shows how ideologies of openness “neutral” as they may seem, can serve to legitimize exclusiveness, emphasizing how ideas—as men—can be socially located, and serve to legitimize a particular social situation.

Distant time, distant gesture: speech and gesture correlate to express temporal distance

Abstract This study investigates whether there is a relation between the semantics of linguistic expressions that indicate temporal distance and the spatial properties of their co-speech gestures. To this date, research on time gestures has focused on features such as gesture axis, direction, and shape. Here we focus on a gesture property that has been overlooked so far: the distance of the gesture in relation to the body. To achieve this, we investigate two types of temporal linguistic expressions are addressed: proximal (e.g., near future, near past) and distal (e.g., distant past, distant future). Data was obtained through the NewsScape library, a multimodal corpus of television news. A total of 121 co-speech gestures were collected and divided into the two categories. The gestures were later annotated in terms of gesture space and classified in three categories: (i) center, (ii) periphery, and (iii) extreme periphery. Our results suggest that gesture and language are coherent in the expression of temporal distance: when speakers locate an event far from them, they tend to gesture further from their body; similarly, when locating an event close to them, they gesture closer to their body. These results thus reveal how co-speech gestures also reflect a space-time mapping in the dimension of distance.

A Corpus-Based Comparison of the Pragmatic Use of Qian and Hou to Examine the Applicability of Space–Time Metaphor Hypothesis in Early Child Mandarin

The Universal Space–Time Mapping Hypothesis suggests that temporal expression is based on spatial metaphor for all human beings. This study examines its applicability in the Chinese language using the data elicited from the Early Childhood Mandarin Corpus (ECMC) (Li and Tse, 2011), which collected the utterances produced by 168 Mandarin-speaking preschoolers in a semistructured play context. The unique pair of Chinese words, qian (前/before/front) and hou (后/after/back), which can be used to express either time (before/after) or space (front/back) in daily communication, was the unit of analysis. The results indicated that: (1) there was a significant age effect in the production of “qian/hou,” indicating that the period before the age of 4.5 may be critical for the development of temporal and spatial expression; (2) the pair was produced to express time (before/after) much earlier than space (front/back), indicating that the expression of time might not necessarily be based on the spatial metaphor; and (3) the pair was used more frequently to express time (before/after) than space (front/back) by the preschoolers, thus challenging the hypothesis.

Integrating Community Science Research and Space-Time Mapping to Determine Depth to Groundwater in a Remote Rural Region

Integrating Community Science Research and Space-Time Mapping to Determine Depth to Groundwater in a Remote Rural Region

3D time-domain beam mapping for studying nonlinear dynamics in multimode optical fibers.

Characterization of the complex spatiotemporal dynamics of optical beam propagation in nonlinear multimode fibers requires the development of advanced measurement methods, capable of capturing the real-time evolution of beam images. We present a new space-time mapping technique, permitting the direct detection, with picosecond temporal resolution, of the intensity from repetitive laser pulses over a grid of spatial samples from a magnified image of the output beam. By using this time-resolved mapping, we provide, to the best of our knowledge, the first unambiguous experimental observation of instantaneous intrapulse nonlinear coupling processes among the modes of a graded index fiber.

Exact N -point-function mapping between pairs of experiments with Markovian open quantum systems

We formulate an exact spacetime mapping between the $\mathcal{N}$-point correlation functions of two different experiments with open quantum gases. Our formalism extends a quantum-field mapping result for closed systems [Phys. Rev. A \textbf{94}, 043628 (2016)] to the general case of open quantum systems with Markovian property. For this, we consider an open many-body system consisting of a $D$-dimensional quantum gas of bosons or fermions that interacts with a bath under Born-Markov approximation and evolves according to a Lindblad master equation in a regime of loss or gain. Invoking the independence of expectation values on pictures of quantum mechanics and using the quantum fields that describe the gas dynamics, we derive the Heisenberg evolution of any arbitrary $\mathcal{N}$-point function of the system in the regime when the Lindblad generators feature a loss or a gain. Our quantum field mapping for closed quantum systems is rewritten in the Schr\"odinger picture and then extended to open quantum systems by relating onto each other two different evolutions of the $\mathcal{N}$-point functions of the open quantum system. As a concrete example of the mapping, we consider the mean-field dynamics of a simple dissipative quantum system that consists of a one-dimensional Bose-Einstein condensate being locally bombarded by a dissipating beam of electrons in both cases when the beam amplitude or the waist is steady and modulated.

Differential optical spatial modulation with pulse position modulation over atmospheric turbulence

Optical spatial modulation (OSM), a recent optical multiple-input multiple-output transmission scheme in wireless optical communication, has aroused great research interests. OSM scheme requires accurate channel state information (CSI) during transmitter and receiver sides, but it is difficult to accurately estimate CSI in OSM scheme. Therefore, a scheme named differential optical spatial modulation scheme with pulse position modulation (DOSM-PPM) based on the space-time mapping block of orthogonal design is proposed in order to completely avoid CSI estimation. The bit error rate (BER) performance of DOSM-PPM is analyzed under log-normal turbulent channel model and simulated using Monte Carlo method. The results show that the transmission rate of DOSM-PPM is improved effectively. Meantime, the proposed DOSM-PPM scheme outperforms DOSM scheme with spatial pulse amplitude modulation by 1 dB at 1 × 10 − 3 BER with the same spectrum efficiency.

Space-Time Mapping for Equiprobable Antenna Activation in Spatial Modulation

Spatial modulation (SM) conveys additional information bits via the index of an activated transmit antenna. When the number of antennas is not an integer power of two, the antenna activation becomes challenging. In such a case, only a subset of the available transmit antennas whose cardinality is an integer power of two is used. This leads to antenna activation with unequal probability, which causes high error rates and losses in the spectral efficiency. The same limitations and performance losses equally exist in quadrature spatial modulation (QSM) and generalized spatial modulation (GSM), the two prominent variants of SM. In this contribution, in contrast to the conventional approach of antenna activation within each symbol period, a space-time bit-mapping method in which the antenna selection procedure is extended to multiple symbol periods is proposed. Use of the proposed method in SM, QSM, and GSM techniques, is shown to achieve performances close to their full potential for any given number of transmit antennas, with only a marginal increment in detection complexity.

Covert Information Embedded Spatial Modulation

In this letter, we propose a new convert information embedded spatial modulation (SM) system for secure communications, in which the transmitter tries to send covert information to the specific receiver while keeping the unintended receiver unaware of the transmission. In the proposed system, the covert information bits are conveyed via the activated antenna index while the common information bits are via the modulation symbols. Specifically, the convert information modulation is achieved by carefully designing the space-time mapping principle so that it is disguised as a conventional SM antenna index. Furthermore, an efficient detection scheme is designed for the proposed system. The simulation results show that the proposed scheme with the developed receiver can offer nearly the same performance gain as conventional SM, whereas the unintended receiver can hardly detect the information correctly. Moreover, the average bit error rate (BER) is analyzed, which also validates our simulation results.