Representation Of Time Research Articles

Waiting for the Perfect Time: Perfectionistic Concerns Predict the Interpretation of Ambiguous Utterances About Time

Abstract Across numerous languages, individuals frequently employ two spatial perspectives – namely, the Moving Time and Moving Ego metaphors – to represent the movement of events in time. Specifically, the Moving Time perspective conceptualizes time as a dynamic entity that moves toward a stationary observer situated in a fixed location. In contrast, the Moving Ego metaphor positions the individual (the “ego”) as the one traversing through time, while time itself remains static. Previous research has established a positive association between procrastination and the adoption of the Moving Ego perspective. Drawing on findings that highlight the robust link between procrastination and perfectionistic concerns, we hypothesized that perfectionistic tendencies would correlate with a greater propensity to invoke an ego-moving representation of time. The present research tests this hypothesis and provides substantial support for this relationship. We demonstrate that a well-established measure of perfectionistic concerns is linked to an increased use of the Moving Ego perspective when interpreting ambiguous temporal utterances. Furthermore, this relationship is mediated by procrastination. This study presents the first empirical evidence that individual differences in perfectionistic concerns may influence how people perceive and interpret temporal relationships.

Space-time interference: The asymmetry we get out is the asymmetry we put in.

Temporal judgments are more affected by space than vice versa. This asymmetry has often been interpreted as primacy of spatial representations over temporal ones. This interpretation is in line with conceptual metaphor theory that humans conceptualize time by spatial metaphors, but is inconsistent with the assumption of a common neuronal magnitude system. Here we review the accumulating evidence for a genuinely symmetric interference between time and space and discuss potential explanations as to why asymmetric interference can arise, both with respect to the interaction between spatial size and temporal duration, and the interaction between traveled distance and travel time. Contrary to the view of hierarchical representations of time and space, our review suggests that asymmetric interference can be explained on the basis of working memory processes and the aspect of speed inherent in dynamic stimuli. We conclude that the asymmetry we often get out (space affects time more than vice versa) is a consequence of the asymmetry we put in (by using biased paradigms and stimuli facilitating spatial processing).

Who wins when? Election timing and descriptive representation

AbstractWe examine how the timing of local elections affects the success of minority candidates, who remain woefully underrepresented in public office. We build on research showing that concurrent elections narrow racial gaps in voter turnout and leverage changes in the timing of local elections in California. Our analysis shows that filling local offices in November of even years increases minority officeholding, at least for some groups. The results demonstrate how, when, and for whom election timing matters. Latinos gain most, potentially at the expense of White and, to a lesser degree, Black representation. An investigation of potential mechanisms suggests that these effects depend on group population size and the magnitude of the turnout changes. An increase in the number of co‐ethnic candidates running also appears to contribute to the representational benefits of on‐cycle elections. Finally, the effects are most pronounced during presidential elections, when turnout improvements are largest.

A quantified local-to-global principle for Morse quasigeodesics

Kapovich, Leeb and Porti (2014) gave several new characterizations of Anosov representations \Gamma \to G , including one where geodesics in the word hyperbolic group \Gamma map to “Morse quasigeodesics” in the associated symmetric space G/K . In analogy with the negative curvature setting, they prove a local-to-global principle for Morse quasigeodesics and describe an algorithm which can verify the Anosov property of a given representation in finite time. However, some parts of their proof involve non-constructive compactness and limiting arguments, so their theorem does not explicitly quantify the size of the local neighborhoods one needs to examine to guarantee global Morse behavior. In this paper, we supplement their work with estimates in the symmetric space to obtain the first explicit criteria for their local-to-global principle. This makes their algorithm for verifying the Anosov property effective. As an application, we demonstrate how to compute explicit perturbation neighborhoods of Anosov representations with two examples.

Palaeosols and surfaces: what fossil soils tell us about the representation of time in some sedimentary successions

Soils and hence palaeosols develop at geomorphic surfaces comprising landscapes. As most develop they reorganize the substrate to create texturally and chemically defined units (horizons) parallel to the land surfaces and some of these horizons become lithified resembling beds. Palaeosols, in many cases do not represent hiatuses but developed during deposition and represent condensation not lost time. The degree of pedogenic reorganization can be used to estimate the temporal significance of the length of soil formation but soils are commonly polygenetic and have not followed a simple, time-related developmental pathway. The complexity of soil development is illustrated with reference to the late Silurian-early Devonian polyphase alluvial palaeosols from South Wales which provide an example of how dynamic changes in sedimentation and erosion have occurred without changes in soil processes. The significance of these polyphase palaeosol profiles is reviewed in the broader context of mid Palaeozoic landscape changes.

Evaluation of the Use of the Angular Domain and Order Domain in a Bearing Fault Detection Framework using Deep Learning

Bearing failures are very common in the industrial environment, requiring effective fault detection methods, which can be categorized into physics-based, knowledge-based and data-driven types. Data-driven methods are efficient in differentiating healthy conditions from faulty conditions by characterizing machine signals, involving stages of data acquisition, feature extraction, and condition determination. Traditionally, feature extraction and condition determination were manual, but advances in artificial intelligence and machine learning, especially deep learning, have automated this process. Although deep learning automatically learns the best features from the input data, the signal domain can influence the model's performance. Time and frequency domain representations are widely used in fault detection methodologies using vibration signals, while angular and order domains are more common in variable operating conditions, but direct use of these domains with deep learning is still rare in the literature. Considering this, this study evaluates a bearing fault detection methodology using vibration signals in different domains (time, frequency, angular, and order) under various rotational conditions. Three distinct approaches were tested to assess the effectiveness of these representations. The results indicated that the frequency domain representation had the best overall performance and the study concluded that the angular and order domains do not offer significant advantages compared to the frequency domain. Nonetheless, it is recommended to conduct a more in-depth analysis with more diverse datasets, especially those containing early-stage bearing fault signals.

Double training reveals an interval-invariant subsecond temporal structure in the brain.

Subsecond temporal perception is critical for understanding time-varying events. Many studies suggest that subsecond timing is an intrinsic property of neural dynamics, distributed across sensory modalities and brain areas. However, our recent finding of the transfer of temporal interval discrimination (TID) learning across sensory modalities supports the existence of a more abstract and conceptual representation of subsecond time that guides the temporal processing of distributed mechanisms. One major challenge to this hypothesis is that TID learning consistently fails to transfer from trained intervals to untrained intervals. To address this issue, here, we examined whether this interval specificity can be removed with double training, a procedure originally developed to eliminate various specificities in visual perceptual learning. Specifically, participants practiced the primary TID task, the learning of which per se was specific to the trained interval (e.g., 100 ms). In addition, they also received exposure to a new interval (e.g., 200 ms) through a secondary and functionally independent tone-frequency discrimination task. This double training successfully enabled complete transfer of TID learning to the new interval, indicating that training improved an interval-invariant component of temporal interval perception, which supports our proposal of an abstract and conceptual representation of subsecond time in the brain. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Political Potential of Autonomous Time Generation in Jean Genet's The Balcony

With the development of timekeeping machinery in the late Middle Ages, time became publicly visible on mechanical dials. This way of spatializing time aimed to crystallize the flow of time and experience into eternity at a single moment, reaching its peak in the 19th century. The natural rhythm of time and the discrete temporality of personal experience were strictly unified into a series of points, distributed along a historical timeline that never turns back. This unidirectional arrow of time remains evident in the study of The Balcony. Research on The Balcony has primarily focused on its political expressions in space, often overlooking the potential of theatrical temporality. This indicates that studies of the political aspects of The Balcony are overly focused on the dimension of visibility, neglecting the exploration of theatrical invisibility. This article will utilize textual data and analysis, based on Deleuze's theory of Aion time, to develop a discussion on the pure formal time in Genet's theater, incorporating relevant political concepts to explore its autonomously generated political potential further, focusing on the characteristics of theatrical time that continuously provoke questioning and ambiguity.

Modeling takeover time for non-driving related tasks using hybrid deep neural networks in conditionally automated vehicles

To enhance the safety of the transition from autonomous to manual driving control, one of the key factors is quantifying the safe takeover transition, namely the takeover time. Previous studies have focused on factors influencing takeover time and predicting takeover time using traditional methods, but there is a lack of research utilizing deep learning networks and driver physiological factors for takeover time prediction. Toward this end, we propose a hybrid deep learning network model dedicated to predicting drivers’ takeover time with a dataset obtained from a bench experiment involving 46 drivers. Firstly, to address the potential information loss commonly associated with traditional manual feature extraction techniques, a convolutional neural network (CNN) is developed to automatically extract physiological spatial representations from drivers. Additionally, a double-layer bidirectional long short-term memory network (DBiLSTM) is incorporated to model the physiological time representation dimension, enabling a more refined representation of physiological signals. Then, to tackle the complexities introduced by individual driver variations, a self-attention mechanism is enabling the model to automatically prioritize critical features, thereby enhancing the accuracy and reliability of its predictions. The results demonstrate that the proposed approach surpasses traditional machine learning network models in predictive accuracy for takeover time prediction, thereby exhibiting novelty in the field of vehicle takeover control research. This provides a more reliable technical foundation for anticipating the durations of vehicle takeovers.

Adjective ‘Sudden’ in Phrases as a Means of Temporal Mitigation in English Fantasy Literature

This study explores the semantics of the temporal mitigation indicator, specifically the adjective ‘sudden,’ as a form of litotes in English-language fantasy prose from the 20th to 21st centuries. The aim of this research is to identify English phrases containing the adjective ‘sudden’ that serve as litotes in the representation of time, which are frequently employed in the specified texts. The methods utilized include semantic analysis, contextual analysis, and comparative analysis. The findings reveal a list of phrases actively used by various authors within the realm of 20th and 21st-century English-language fantasy prose that reflect a high degree of temporal mitigation within this genre. An analysis of selected fantasy texts indicates the presence of collocations featuring ‘sudden’ that are not documented in collocation dictionaries. A ranked list of these phrases, along with their respective authors, has been compiled. The examination of collocations expressing temporal mitigation shows that some are utilized by multiple authors, such as “the sudden darkness,” “sudden anxiety,” and “a sudden thought.” This suggests their stability, indicating that they could enhance existing collocation dictionaries of the English language. The practical significance of this study lies in its potential application in teaching courses on lexicology and lexicography of the English language at the university level.

Interoceptive and Bodily Processing in Prospective and Retrospective Timing.

This chapter reviews some directions along which Craig's proposal of subjective time as emergent from interoceptive and bodily dynamics allows to frame recent findings on prospective and retrospective time processing. Behavioral and neuroimaging evidence from prospective timing studies demonstrates that an interoceptive-insular system may support the development of a primary representation of time in the context of large-scale networks involved in duration processing. Studies showing a tight link between episodic memory and interoceptive, emotional, and sensorimotor states further provide insights on processes supporting retrospective timing. These lines of evidence show that acknowledging its dependence on bodily states is most likely a crucial step toward a mechanistic understanding of time perception.

“i write unbalanced poetry”

In examining changes to Bernadette Mayer’s writing style following her cerebral hemorrhage in 1994, the article investigates the ways in which Mayer’s poetics have been informed by disability. Positioning the effects of her stroke not as limitations but as capacities for generating new knowledge, Mayer’s embodiment of disability in her late work also provokes a reassessment of her early work. Asserting that disability complicates normative time frames, an analysis of Mayer’s relationship to and representation of time reveals that disability informed her poetics not only after her stroke, but in anticipation of it, too. Drawing on archival evidence from Mayer’s papers and correspondence at the University of California San Diego, improvisation is established as a dominant feature in her late work, while the anticipation of disability in her early work contributes to the development of performance-inflected poetics.

Do speakers’ gestures affect listeners’ understanding of temporal relationships between events?

Abstract This study investigated how the direction and movement of gestures affect mental representations of time. Previous research by Tversky and Jamalian (2021) demonstrated that gestures influence how people perceive temporal relationships, with participants’ drawings reflecting the shape (circular or linear) of the gestures they observed. However, the influence of gesture direction was not examined. In the present study, 50 Japanese adults were exposed to different types of gestures, including leftward and rightward linear or circular gestures. Participants were then asked to draw diagrams representing the temporal flow of events. The results showed significant associations between the type of gesture and the participants’ drawings. Specifically, the direction and form of the gestures — whether leftward or rightward, linear or circular — significantly influenced how participants depicted temporal relationships. These findings highlight the importance of both gesture direction and movement in shaping individuals’ mental representations of time.

MODELS OF FALSE AND CORRECT DETECTION OF INFORMATION LEAKAGE SIGNALS FROM MONITOR SCREENS BY A SPECIALIZED TECHNICAL MEANS OF ENEMY INTELLIGENCE

The calculation expressions for the probability of false detection of a leakage signal, taking into account the discrete representation of time in the models of detection of side radiation signals from static images on the monitor screen on liquid crystal structures by a specialised technical means of enemy intelligence, which implements an asymptotically optimal joint algorithm for detecting side radiation signals and estimating the duration of the image on the monitor screen, are refined. For this purpose, a large independent array of noise was generated in the Mathcad software environment, and the process of false signal detection by a specialised enemy intelligence vehicle was modelled in several Excel workbooks under conditions of a priori uncertainty about the duration of a static image on the monitor screen.

The Development of the Mental Timeline is Related to Temporal Memory

ABSTRACT Although we cannot see or touch time, across many cultures, we use spatial representations to think about this abstract concept. Spatial representations of time are thought to support temporal concepts that might otherwise be difficult to represent and reason about, such as the temporal component of episodic memory. One common form of spatially representing time is the mental timeline, which is a linear projection of time onto space. Adults and older children from many cultures spontaneously activate the mental timeline when remembering the order of events. However, the mental timeline develops slowly throughout early childhood as children gain increasing experience with formal schooling and cultural artifacts. Here, we explored how individual differences in the development of American children’s mental timelines relate to their memory for temporal order (N = 96, M age = 6.22 years). We first tested children’s memory for the order and location of events through a memory task involving short videos. We then tested children’s spontaneous spatial representations of temporal order using an open-ended timeline construction task. The linearity of children’s timeline arrangements predicted their memory for temporal order but not memory for locations: children who spontaneously represented time linearly had significantly better temporal memory performance than children who represented time nonlinearly, but there was no difference in location memory performance. These data provide preliminary evidence that the development of the mental timeline may support the development of temporal memory.

Multi-Cover Persistence (MCP)-based machine learning for polymer property prediction.

Accurate and efficient prediction of polymers properties is crucial for polymer design. Recently, data-driven artificial intelligence (AI) models have demonstrated great promise in polymers property analysis. Even with the great progresses, a pivotal challenge in all the AI-driven models remains to be the effective representation of molecules. Here we introduce Multi-Cover Persistence (MCP)-based molecular representation and featurization for the first time. Our MCP-based polymer descriptors are combined with machine learning models, in particular, Gradient Boosting Tree (GBT) models, for polymers property prediction. Different from all previous molecular representation, polymer molecular structure and interactions are represented as MCP, which utilizes Delaunay slices at different dimensions and Rhomboid tiling to characterize the complicated geometric and topological information within the data. Statistic features from the generated persistent barcodes are used as polymer descriptors, and further combined with GBT model. Our model has been extensively validated on polymer benchmark datasets. It has been found that our models can outperform traditional fingerprint-based models and has similar accuracy with geometric deep learning models. In particular, our model tends to be more effective on large-sized monomer structures, demonstrating the great potential of MCP in characterizing more complicated polymer data. This work underscores the potential of MCP in polymer informatics, presenting a novel perspective on molecular representation and its application in polymer science.

Of Deep Time and Slow Violence: Anthropo-Scenic Timespaces and the Chronotopes of Climate Theatre.

This article explores how contemporary climate theatre navigates the distorted scales of the Anthropocene and the climate crisis through its unique aesthetics – embodiment, spatiality, temporality, and reciprocity. Previous literature on climate theatre has largely discussed its anthropomorphism and anthropocentrism in relation to global warming. Building on ecodramaturgical frameworks, this article draws on ecocritical appropriations of Mikhail Bakhtin’s chronotope to investigate how theatrical time and space make the abstract nature of climate change tangible. The argument posits that chronotopes of climate theatre are crucial for understanding how contemporary theatre and performance tackle scalar derangement. By drawing on interdisciplinary approaches from environmental humanities, performance and theatre studies, and posthumanism, the study situates itself at the intersections of performance art, political theatre, aesthetic theatre, drama, and environmentalism, examining how different theatrical formats use theatrical ‘timespaces’ to address the spatio-temporal complexities of the Anthropocene. It discusses Ella Hickson’s Oil (2016); April De Angelis’s Extinct (2021); Extinction Rebellion’s “The Sea Is Rising and so Are We” (2019); and Chris Rapley and Duncan Macmillan’s 2071 (2014), showing how each uses theatrical chronotopes to transform deep time, slow violence, and the dispersed nature of climate change into the ‘hyper-present’ of the stage.

Fixed-Point and Random Fixed-Point Theorems in Preordered Sets Equipped with a Distance Metric

This paper explores fixed points for both contractive and non-contractive mappings in traditional b-metric spaces, preordered b-metric spaces, and random b-metric spaces. Our findings provide insights into the behavior of mappings under various constraints and extend our approach to include coincidence and common fixed-point theorems in these spaces. We present new examples and graphical representations for the first time, offering novel results and enhancing several related findings in the literature, while broadening the scope of earlier works of Ran and Reurings, Nieto and Rodríguez-López, Górnicki, and others.

Application of water cycle algorithm with demand follows green level and nonlinear power pattern of the product for an inventory system

It is commonly known that a number of variables, including price, supply levels, time, and green level, affect how quickly certain things are in demand. Furthermore, the inventory carrying cost is considered to be a nonlinear representation of time and is subject to variation throughout time. More precisely, it rises with time since longer storage times necessitate more costly warehouse space. This study presents a fully backlogged situation inventory system for a single commodity where the product’s selling price, green level, and time are used to simultaneously compute the demand rate in accordance with a power pattern. Purchase price is determined by the product’s nonlinear green level. Complete backorders are available for shortages. The impact of the product’s selling price, green level and time power function are combined to determine the product’s demand. Moreover, the holding cost also rises as the product is stored for a longer period of time. The primary goal is to determine the best inventory policy to maximise total profit per unit of time. Though the problem is highly nonlinear in nature. Hence, we cannot solve it analytically. To overcome these difficulties, we have applied several well-known popular metaheuristic algorithms (Water Cycle Algorithm (WCA), Artificial Electric Field Algorithm (AEFA), Teaching Learning Based Optimization Algorithm (TLBOA), Grey Wolf Optimizer Algorithm (GWOA), Sparrow Search Algorithm (SSA), Whale Optimizer Algorithm (WOA), Prairie Dog Optimization Algorithm (PDOA), Gazelle Optimization Algorithm (GOA), A Sinh Cosh Optimizer Algorithm (SCHOA) and White Sherk Optimizer Algorithm (WSOA), Archimedes Optimization Paradigm Algorithm (AOPA), Marine Predator Optimization Algorithm (MPOA), Geyser Inspired Algorithm (GIA), Runge Kutta Optimization Algorithm (RKOA), Lungs Performance-based Optimization Algorithm (LPOA) and Dwarf Mongoose Optimization Algorithm (DMOA)). It is observed that WCA perform better than other algorithms with respect to the convergence rate. A numerical example is taken in order to validate the proposed model. Finally, a post optimality analysis is performed in order to make a fruitful conclusion.

No(w) future: Neo-farming and eco-anxiety in France

Studying how people relate to the future and how it shapes individual or collective affects is a way to grasp what motivates social practices. What would be the effect of the climate crisis and democratic disillusionments on social mobilisations? What impact does the disappearance of the horizon of progress have on individuals' lives? Based on long-term fieldwork among a dozen neo-farming anarchist libertarian collectives in the Massif Central (France), I analyse how the future horizon of despair, anxiety, or abandonment is necessarily intertwined with utopian projection. This interaction between antinomic futures creates a paradoxical and Camusian ‘absurd' present that resonates with a shared temporality emphasising the ‘here and now' and prefigurative politics. Through this study of the ‘back-to-the-land' movement, I will propose a broader epistemological discussion related to how anthropology has historically approached incoherence and contradictions. I advocate for deepening our understanding of the meaning of social practices by interrogating the intrinsic multiple representations of time that impel them.