23 papers · ranked by Valyu relevance
Xuefei Wang, Hao Zhu, Xing Tian
The fine temporal resolution of electroencephalography (EEG) makes it one of the most widely used non-invasive electrophysiological recording methods in cognitive neuroscience research. One of the common ways to explore the neural dynamics is to create event-related potentials (ERPs) by averaging trials, followed by…
Kai-Robin Lange, Niklas Benner, Lars Grönberg, Aymane Hachcham + 3 more
Text data is inherently temporal. The meaning of words and phrases changes over time, and the context in which they are used is constantly evolving. This is not just true for social media data, where the language used is rapidly influenced by current events, memes and trends, but also for journalistic, economic or…
Tao Cheng, Monsuru Adepeju, Tobias Preis
Background When analytical techniques are used to understand and analyse geographical events, adjustments to the datasets (e.g. aggregation, zoning, segmentation etc.) in both the spatial and temporal dimensions are often carried out for various reasons. The ‘Modifiable Areal Unit Problem’ (MAUP), which is a…
Chhaya Kulkarni, Nuzhat Maisha, Leasha J Schaub, Jacob Glaser + 2 more
This paper focuses on the analysis of time series representation of blood loss and cytokines in animals experiencing trauma to understand the temporal progression of factors affecting survivability of the animal. Trauma related grave injuries cause exsanguination and lead to death. 50% of deaths especially in the armed…
Luca Vizioli, Alexander Bratch, Junpeng Lao, Kamil Ugurbil + 2 more
fMRI provides spatial resolution that is unmatched by any non-invasive neuroimaging technique. Its temporal dynamics however are typically neglected due to the sluggishness of the hemodynamic based fMRI signal. We present temporal multivariate pattern analysis (tMVPA), a method for investigating the temporal evolution…
Andrew T. Jebb, Louis Tay, Wei Wang, Qiming Huang
Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given…
Tarek Mahmoud, Veronika Solopova, Premtim Sahitaj, Ariana Sahitaj + 6 more
Temporal language does more than place events on a timeline. In news discourse, references to the past, present, and future can function as rhetorical devices that shape interpretation and persuasion. Here, we study temporal framing, defined as the persuasive use of time-related language to structure meaning rather…
Earo Wang, Dianne Cook, Rob Hyndman
Mining temporal data for information is often inhibited by a multitude of formats: irregular or multiple time intervals, point events that need aggregating, multiple observational units or repeated measurements on multiple individuals, and heterogeneous data types. On the other hand, the software supporting time series…
Alexander Shknevsky, Yuval Shaḥar, Robert Moskovitch
We propose a new pruning constraint during a frequent temporal-pattern discovery process, the Semantic Adjacency Criterion [SAC], which exploits domain knowledge to filter out patterns that contain potentially semantically contradictory components. We have defined three SAC versions, and tested their effect in three…
Michael P. Ward, Rachel M. Iglesias, Victoria J. Brookes
A time-series is any set of N time-ordered observations of a process. In veterinary epidemiology, our focus is generally on disease occurrence (the “process”) over time, but animal production, welfare or other traits might also be of interest. A common source of time-series datasets are animal disease monitoring and…
Michael X Cohen
Morlet wavelets are frequently used for time-frequency analysis of non-stationary time series data, such as neuroelectrical signals recorded from the brain. The crucial parameter of Morlet wavelets is the width of the Gaussian that tapers the sine wave. This width parameter controls the trade-off between temporal…
Fernanda Dantas Bueno, Vanessa C. Morita, Raphael Y. de Camargo, Marcelo B. Reyes + 2 more
The ability to process time on the scale of milliseconds and seconds is essential for behaviour. A growing number of studies have started to focus on brain dynamics as a mechanism for temporal encoding. Although there is growing evidence in favour of this view from computational and in vitro studies, there is still a…
Epaminondas Markos Valsamis, David Ricketts, Henry Husband, Benedict Aristotle Rogers
Introduction In retrospective studies, the effect of a given intervention is usually evaluated by using statistical tests to compare data from before and after the intervention. A problem with this approach is that the presence of underlying trends can lead to incorrect conclusions. This study aimed to develop a…
Kieran Campbell, Christopher Yau
Pseudotime algorithms can be employed to extract latent temporal information from crosssectional data sets allowing dynamic biological processes to be studied in situations where the collection of genuine time series data is challenging or prohibitive. Computational techniques have arisen from areas such as single-cell…
Van Ho-Long, Nguyen Ho, Anh-Vu Dinh-Duc, Ha Manh Tran + 4 more
The explosive growth of IoT-enabled sensors is producing enormous amounts of time series data across many domains, offering valuable opportunities to extract insights through temporal pattern mining. Among these patterns, an important class exhibits periodic occurrences, referred to as seasonal temporal patterns…
Melina Del Angel, Matthew Nunes, Oliver Peacock, Ewan Cranwell + 1 more
'Dylan Thompson'] Background Wearable devices have emerged as a new technology for monitoring physical activity over time. Conventional approaches to wearable physical activity data have tended to ignore temporal changes and, instead, have typically analysed summative measures and/or snapshots (e.g., averages over a…
Aurea Anguera, Juan A. Lara, David Lizcano, Maria Aurora Martínez + 1 more
'Juan Pazos'] There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest…
Hossein Estiri, Thomas H. McCoy, Kavishwar B. Wagholikar, Alyssa P. Goodson + 2 more
Electronic health records (EHRs) contain important temporal information about progression of disease and treatment outcomes. The objective of this paper is to propose and test a high-throughput approach for phenotyping using temporal sequences of EHR observations to derive predictive and interpretable data…
Matthew Bailey, Mark Wilson
One of the critical tools of persistent homology is the persistence diagram. We demonstrate the applicability of a persistence diagram showing the existence of topological features (here rings in a 2D network) generated over time instead of space as a tool to analyse trajectories of biological networks. We show how the…
Samuel Genheden, Agnes Mårdh, Gustav Lahti, Ola Engkvist + 2 more
We present machine learning models for predicting the chemical context for Buchwald-Hartwig coupling reactions. Using reaction data from in-house electronic lab notebooks, we train two models: one based on single-label data and one based on multi-label data. Both models show excellent top-3 accuracy around 90%, which…
Authors not listed
A framework for catalysis based on categorical aperture selection rather than temporal acceleration is presented. Traditional catalysis theory describes catalysts as agents that accelerate reactions by lowering activation energies, implicitly treating time as the fundamental variable and reaction rate enhancement as…
Authors not listed
Molecular dynamics (MD) simulations are essential for investigating complex bi- ological systems. Timestep selection is crucial for accuracy and efficiency, yet the common practice of using a 4 fs timestep with hydrogen mass repartitioning (HMR) and SHAKE for alchemical free energy (AFE) calculations requires further…
Fuzhan Rahmanian, Robert M. Lee, Dominik Linzner, Kathrin Michel + 4 more
Predicting and monitoring battery life early and across chemistries is a significant challenge due to the plethora of degradation paths, form factors, and electrochemical testing protocols. Existing models typically translate poorly across different electrode, electrolyte, and additive materials, mostly require a fixed…