Spatio-temporal dynamics of vehicles: Fusion of traffic data and context information
Ontology highlight
ABSTRACT:
SUBMITTER: Bolanos-Martinez D
PROVIDER: S-EPMC10865200 | biostudies-literature | 2024 Feb
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Sensory-specific cortices appear to be sensitive to information from another modality. Here we investigate whether the human brain automatically extracts the phonological information in visual words in early visual processing. We continuously presented native Chinese speakers peripherally with Chinese homophone characters in an oddball paradigm, while they performed a visual detection task presented in the centre of the visual field. We found the lexical tone phonology embedded in the characters is processed automatically by the brain of native speakers, as revealed by whole-head electrical recordings of the mismatch negativity (MMN). Source solution further revealed the MMN involved the neural activations from the visual cortex to the auditory cortex (130-460 ms). The spatial-temporal dynamics indicate a visual-auditory interaction in the early, automatic processing of phonological information in visual words.
| S-EPMC6506442 | biostudies-literature
Project description:ObjectiveDuring verbal communication, humans briefly maintain mental representations of speech sounds conveying verbal information, and constantly scan these representations for comparison to incoming information. We determined the spatio-temporal dynamics of such short-term maintenance and subsequent scanning of verbal information, by intracranially measuring high-gamma activity at 70-110Hz during a working memory task.MethodsPatients listened to a stimulus set of two or four spoken letters and were instructed to remember those letters over a two-second interval, following which they were asked to determine if a subsequent target letter had been presented earlier in that trial's stimulus set.ResultsAuditory presentation of letter stimuli sequentially elicited high-gamma augmentation bilaterally in the superior-temporal and pre-central gyri. During the two-second maintenance period, high-gamma activity was augmented in the left pre-central gyrus, and this effect was larger during the maintenance of stimulus sets consisting of four compared to two letters. During the scanning period following target presentation, high-gamma augmentation involved the left inferior-frontal and supra-marginal gyri.ConclusionsShort-term maintenance of verbal information is, at least in part, supported by the left pre-central gyrus, whereas scanning by the left inferior-frontal and supra-marginal gyri.SignificanceThe cortical structures involved in short-term maintenance and scanning of speech stimuli were segregated with an excellent temporal resolution.
| S-EPMC5429980 | biostudies-literature
Project description:Mitogen-activated protein kinases (MAPKs) are conserved regulators of proliferation, differentiation and adaptation in eukaryotic cells. Their activity often involves changes in their subcellular localization, indicating an important role for these spatio-temporal dynamics in signal transmission. A striking model illustrating these dynamics is somatic cell fusion in Neurospora crassa Germinating spores of this fungus rapidly alternate between signal sending and receiving, thereby establishing a cell-cell dialog, which involves the alternating membrane recruitment of the MAPK MAK-2 in both fusion partners. Here, we show that the dynamic translocation of MAK-2 is essential for coordinating the behavior of the fusion partners before physical contact. The activation and function of the kinase strongly correlate with its subcellular localization, indicating a crucial contribution of the MAPK dynamics in establishing regulatory feedback loops, which establish the oscillatory signaling mode. In addition, we provide evidence that MAK-2 not only contributes to cell-cell communication, but also mediates cell-cell fusion. The MAK-2 dynamics significantly differ between these two processes, suggesting a role for the MAPK in switching of the cellular program between communication and fusion.
| S-EPMC5992588 | biostudies-literature
Project description:In 2013, the National Ecological Observatory Network (NEON) started collecting 30-year multi-faceted ecological data at various spatial and temporal scales across the US including ticks. Understanding the abundance and dynamics of disease vectors under changing environmental conditions in the long-term is important to societies, but sustained long-term collection efforts are sparse. Using hard-bodied tick data collected by NEON, the vegetation and atmospheric data and a statistical state-space model, which included a detection probability component, this study estimated the abundance of tick nymphs and adult ticks across a Florida NEON location. It took into account the spatial and temporal variation, and factors affecting detection. Its purpose was to test the applicability of data collected thus far and evaluate tick abundance. The study found an increase in tick abundance at this Florida location, and was able to explain spatial and temporal variability in abundance and detection. This approach shows the potential of NEON data. The NEON data collection is unique in scale, and promises to be of great value to understand tick and disease dynamics across the US. From a public health perspective, the detection probability of vectors can be interpreted as the probability of encountering that vector, making these types of analyses useful for estimating disease risk.
| S-EPMC6836180 | biostudies-literature
Project description: Not available
| S-EPMC10718443 | biostudies-literature
Project description:This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO? and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.
| S-EPMC4883290 | biostudies-literature
Project description:Tumour hypoxia plays a pivotal role in cancer therapy for most therapeutic approaches from radiotherapy to immunotherapy. The detailed and accurate knowledge of the oxygen distribution in a tumour is necessary in order to determine the right treatment strategy. Still, due to the limited spatial and temporal resolution of imaging methods as well as lacking fundamental understanding of internal oxygenation dynamics in tumours, the precise oxygen distribution map is rarely available for treatment planing. We employ an agent-based in silico tumour spheroid model in order to study the complex, localized and fast oxygen dynamics in tumour micro-regions which are induced by radiotherapy. A lattice-free, 3D, agent-based approach for cell representation is coupled with a high-resolution diffusion solver that includes a tissue density-dependent diffusion coefficient. This allows us to assess the space- and time-resolved reoxygenation response of a small subvolume of tumour tissue in response to radiotherapy. In response to irradiation the tumour nodule exhibits characteristic reoxygenation and re-depletion dynamics which we resolve with high spatio-temporal resolution. The reoxygenation follows specific timings, which should be respected in treatment in order to maximise the use of the oxygen enhancement effects. Oxygen dynamics within the tumour create windows of opportunity for the use of adjuvant chemotherapeutica and hypoxia-activated drugs. Overall, we show that by using modelling it is possible to follow the oxygenation dynamics beyond common resolution limits and predict beneficial strategies for therapy and in vitro verification. Models of cell cycle and oxygen dynamics in tumours should in the future be combined with imaging techniques, to allow for a systematic experimental study of possible improved schedules and to ultimately extend the reach of oxygenation monitoring available in clinical treatment.
| S-EPMC4537194 | biostudies-literature
Project description:For autonomous vehicles (AV), the ability to share information about their surroundings is crucial. With Level 4 and 5 autonomy in sight, solving the challenge of organization and efficient storing of data, coming from these connected platforms, becomes paramount. Research done up to now has been mostly focused on communication and network layers of V2X (Vehicle-to-Everything) data sharing. However, there is a gap when it comes to the data layer. Limited attention has been paid to the ontology development in the automotive domain. More specifically, the way to integrate sensor data and geospatial data efficiently is missing. Therefore, we proposed to develop a new Connected Traffic Data Ontology (CTDO) on the foundations of Sensor, Observation, Sample, and Actuator (SOSA) ontology, to provide a more suitable ontology for large volumes of time-sensitive data coming from multi-sensory platforms, like connected vehicles, as the first step in closing the existing research gap. Additionally, as this research aims to further extend the CTDO in the future, a possible way to map to the CTDO with ontologies that represent road infrastructure has been presented. Finally, new CTDO ontology was benchmarked against SOSA, and better memory performance and query execution speeds have been confirmed.
| S-EPMC7285307 | biostudies-literature
Project description:We investigated the mechanisms and the spatio-temporal dynamics of fluid-phase and membrane internalization in the green alga Chara australis using fluorescent hydrazides markers alone, or in conjunction with styryl dyes. Using live-cell imaging, immunofluorescence and inhibitor studies we revealed that both fluid-phase and membrane dyes were actively taken up into the cytoplasm by clathrin-mediated endocytosis and stained various classes of endosomes including brefeldin A- and wortmannin-sensitive organelles (trans-Golgi network and multivesicular bodies). Uptake of fluorescent hydrazides was poorly sensitive to cytochalasin D, suggesting that actin plays a minor role in constitutive endocytosis in Chara internodal cells. Sequential pulse-labelling experiments revealed novel aspects of the temporal progression of endosomes in Chara internodal cells. The internalized fluid-phase marker distributed to early compartments within 10 min from dye exposure and after about 30 min, it was found almost exclusively in late endocytic compartments. Notably, fluid cargo consecutively internalized at time intervals of more than 1h, was not targeted to the same vesicular structures, but was sorted into distinct late compartments. We further found that fluorescent hydrazide dyes distributed not only to rapidly recycling endosomes but also to long-lived compartments that participated in plasma membrane repair after local laser injury. Our approach highlights the benefits of combining different fluid-phase markers in conjunction with membrane dyes in simultaneous and sequential application modus for investigating vesicle traffic, especially in organisms, which are still refractory to genetic transformation like characean algae.
| S-EPMC8211606 | biostudies-literature
Project description:MotivationEmergent biological dynamics derive from the evolution of lower-level spatial and temporal processes. A long-standing challenge for scientists and engineers is identifying simple low-level rules that give rise to complex higher-level dynamics. High-resolution biological data acquisition enables this identification and has evolved at a rapid pace for both experimental and computational approaches. Simultaneously harnessing the resolution and managing the expense of emerging technologies-e.g. live cell imaging, scRNAseq, agent-based models-requires a deeper understanding of how spatial and temporal axes impact biological systems. Effective emulation is a promising solution to manage the expense of increasingly complex high-resolution computational models. In this research, we focus on the emulation of a tumor microenvironment agent-based model to examine the relationship between spatial and temporal environment features, and emergent tumor properties.ResultsDespite significant feature engineering, we find limited predictive capacity of tumor properties from initial system representations. However, incorporating temporal information derived from intermediate simulation states dramatically improves the predictive performance of machine learning models. We train a deep-learning emulator on intermediate simulation states and observe promising enhancements over emulators trained solely on initial conditions. Our results underscore the importance of incorporating temporal information in the evaluation of spatio-temporal emergent behavior. Nevertheless, the emulators exhibit inconsistent performance, suggesting that the underlying model characterizes unique cell populations dynamics that are not easily replaced.Availability and implementationAll source codes for the agent-based model, emulation, and analyses are publicly available at the corresponding DOIs: 10.5281/zenodo.10622155, 10.5281/zenodo.10611675, 10.5281/zenodo.10621244, respectively.
| S-EPMC10957516 | biostudies-literature