Time Travel Research Articles

A comparison of the accumulation-based, trip-based and time delay macroscopic fundamental diagram models

Macroscopic fundamental diagram (MFD) is widely applied in network modelling and management, such as route guidance and vehicle relocation, which are formulated as generalised dynamic traffic assignment (DTA) problems. MFD can effectively reduce the spatial dimension thus making the generalised DTA problems computationally efficient. In the literature, three MFD models, the accumulation-based model, the trip-based model, and the time delay model, were proposed to capture the traffic flow propagation under different traffic conditions and demand scenarios. However, no consensus has been reached on their computational efficiency and which model should be chosen under certain traffic conditions and demand scenarios. In this paper, we revisit these models regarding two important theoretical properties regarding flow propagation in the DTA, i.e. the first-in-first-out (FIFO) principle and causality. Corresponding dynamic network loading algorithms are designed to compare their numerical accuracy and computational efficiency. Numerical comparisons with Lighthill-Whitham-Richards (LWR) model and a micro simulator confirm that the accumulation-based model is valid in saturation, the trip-based model is valid in free-flow, while the time delay model provides a good approximation in both free-flow and saturation scenarios. On the other hand, violation of strict causality is observed in the accumulation-based and trip-based models, rendering it hard to pursue analytical DTA. This issue is not observed in the time delay model. Overall, the time delay model is a promising alternative for dynamic network loading in large-scale network applications.

Temporal displacement and spatial unbinding of commuting in the Brno Metropolitan Area

AbstractCommuting is generally considered a routine aspect of daily life. As a result of the growing importance of the tertiary sector in the economy, the increasing flexibility of work arrangements, and other individual factors, there has been a noticeable change in commuting patterns, both in terms of time and place. This study aims to characterise the spatio‐temporal practices employed in commuting. We describe these spatio‐temporal practices using spatio‐temporal rhythms enforced among individuals in the case of the Brno Metropolitan Area. To achieve the results we use questionnaire surveys and semi‐structured interviews. The results indicate that the major morning and afternoon commuting flows are spread out over several hours. The afternoon commute is more distributed in time. The phenomenon of the daily commute is clearly weakened. Part of the population commutes to work only some days of the week. Also, the spatial dimension of commuting is diverse, as many originally non‐working places become centres where people commute, such as a café or a hotel. It turns out that commuters typically chain trips when commuting. In this paper, we demonstrate several specific practices associated with these movements, such as commuting to someone's house to work, commuting to a café or realising long‐distance commuting. The observed commuting characteristics are then referred to by the terms of temporal displacement and spatial unbinding of commuting.

Mixed Resolution Network with hierarchical motion modeling for efficient action recognition

The dual-stream architecture is frequently employed for learning diverse features from videos. This paper introduces a novel Mixed Resolution Network (MixRes) for processing inputs with hybrid spatiotemporal resolutions, namely high-spatial and low-temporal resolution input, as well as low-spatial and high-temporal resolution input. The utilization of mixed spatiotemporal resolutions not only facilitates the independent emphasis of the two streams on appearance and motion encoding but also diminishes the computational burden. Furthermore, by leveraging the characteristics of neural networks with multiple layers, the temporal stream in the proposed network is divided into different steps to capture short-term and long-term motion information. Finally, we design a Temporal Multiscale Motion Excitation (TMME) module, which enhances the motion-related channels of the video representation by employing multiscale temporal differences. We conduct extensive experiments on multiple action recognition benchmarks, including Something-Something V1 & V2 and Kinetics-400. The outcomes validate that the proposed method achieves superior action recognition performance with low computational cost as compared to the state-of-the-art methods.

Enhancing User Experience and Ride Efficiency: A Case Study of Bike-Sharing App Design

Abstract: The bike sharing app “Bike Buddy” facilitate people living in the big cities particularly where number of two wheelers are increasing. Many prefer two wheelers to save time and money. This can avoid wastage of the time traveling by public transport. Personal cars used individually raises traffic problems. This has attracted attention in using and sharing of bike service. The app developed provides hassle-free, easy way to share bike. The rider once declares the travelling route, he invites friends to join the ride which is claimed to save money and traffic issue in large cities. The invitation is visible to people who want to travel by the said route. After accepting the invitation, the rider will pickup the designated passenger. The service, depending upon rider may be paid or free.

Episodic imagining, temporal experience, and beliefs about time

AbstractWe explore the role of episodic imagining in explaining why people both differentially report that it seems to them in experience as though time robustly passes, and why they differentially report that they believe that time does in fact robustly pass. We empirically investigate two hypotheses, the differential vividness hypothesis, and the mental time travel hypothesis. According to each of these, the degree to which people vividly episodically imagine past/future states of affairs influences their tendency to report that it seems to them as though time robustly passes and to judge that time does robustly pass. According to the former, a greater degree of vividness will tend to increase the extent to which people make such reports, while according to the latter, it will tend to decrease the extent to which people make such reports. We found weak evidence in favour of the former hypothesis. We reflect on the implications of this finding for theorising about such reports.

Human–robot interaction-oriented video understanding of human actions

This paper focuses on action recognition tasks oriented to the field of human–robot interaction, which is one of the major challenges in the robotic video understanding field. Previous approaches focus on designing temporal models, lack the ability to capture motion information and build contextual correlation models. This may result in robots being unable to effectively understand long-term video actions. To solve these two problems, this paper propose a novel video understanding framework including: an Adaptive Temporal Sensitivity and Motion Capture Network (ATSMC-Net) and a contextual scene reasoning module called Knowledge Function Graph Module (KFG-Module). The proposed ATSMC-Net can adaptively adjust the frame-level and pixel-level sensitive regions of temporal features to effectively capture motion information. To fuse contextual scene information for cross-temporal inference, the KFG-Module is introduced to achieve fine-grained video understanding based on the relationship between objects and actions. We evaluate the method using three public video understanding benchmarks, including Something-Something-V1&V2 and HMDB51. In addition, we present a dataset with real-world application scenarios of human–robot interactions to verify the effectiveness of our approach on mobile robots. The experimental results show that the proposed method can significantly improve the video understanding of the robots.

Decouple Content and Motion for Conditional Image-to-Video Generation

The goal of conditional image-to-video (cI2V) generation is to create a believable new video by beginning with the condition, i.e., one image and text. The previous cI2V generation methods conventionally perform in RGB pixel space, with limitations in modeling motion consistency and visual continuity. Additionally, the efficiency of generating videos in pixel space is quite low. In this paper, we propose a novel approach to address these challenges by disentangling the target RGB pixels into two distinct components: spatial content and temporal motions. Specifically, we predict temporal motions which include motion vector and residual based on a 3D-UNet diffusion model. By explicitly modeling temporal motions and warping them to the starting image, we improve the temporal consistency of generated videos. This results in a reduction of spatial redundancy, emphasizing temporal details. Our proposed method achieves performance improvements by disentangling content and motion, all without introducing new structural complexities to the model. Extensive experiments on various datasets confirm our approach's superior performance over the majority of state-of-the-art methods in both effectiveness and efficiency.

STDiff: Spatio-Temporal Diffusion for Continuous Stochastic Video Prediction

Predicting future frames of a video is challenging because it is difficult to learn the uncertainty of the underlying factors influencing their contents. In this paper, we propose a novel video prediction model, which has infinite-dimensional latent variables over the spatio-temporal domain. Specifically, we first decompose the video motion and content information, then take a neural stochastic differential equation to predict the temporal motion information, and finally, an image diffusion model autoregressively generates the video frame by conditioning on the predicted motion feature and the previous frame. The better expressiveness and stronger stochasticity learning capability of our model lead to state-of-the-art video prediction performances. As well, our model is able to achieve temporal continuous prediction, i.e., predicting in an unsupervised way the future video frames with an arbitrarily high frame rate. Our code is available at https://github.com/XiYe20/STDiffProject.

Monetary cost, time cost, and mode choice: Transit and ridehailing in California

Recent studies explore how ridehailing competes with transit, documenting drops in transit ridership when ridehailing became available. However, few examine the extent to which ridehailing substitutes for other modes, such as walking or private automobiles. Using travel diary survey data and travel times and costs from the San Francisco Bay Area, we employ a mixed logit model to analyze how trip characteristics such as travel time and travel cost influence traveler’s mode choices. The results show that if ridehailing costs increase by 10%, ridehailing trips decrease by 6.97%. About half of the lost riders would switch to driving, and 20% to transit. Therefore, driving, rather than transit, is the closest substitute for ridehailing. Furthermore, 10% reductions in transit time and transit cost are associated with a 24.63% and 5.03% increase in transit trips, respectively, suggesting that reducing travel time is more effective in increasing transit ridership than lowering fares.

Abstract MP68: Strategic Placement of New Cathlab in the Largest Archipelago Country: Geospatial Analysis of Cathlab Coverage in Indonesia

Background: Acute coronary syndrome (ACS) is a special disease because treatment is significantly based on the time required to receive treatment. The standard gold treatment for ACS is Percutaneous Coronary Intervention (PCI), which would need Cathlab. The number of cathlabs increased significantly in Indonesia from 112 cathlabs in 2017 to 310 cathlabs in 2022. However, most cathlabs were built in areas that already had cathlabs. Despite the massive increase in the cathlab, it only slightly reduces the maldistribution (the GINI ratio decreases from 0.54 to 0.48). In response to the problem, the Ministry of Health (MoH) plans to build a cathlab in all 514 districts in Indonesia. Purpose: The idea of increasing the distribution of cathlab is extraordinary. But a new question arises: do we need to build cathlab in 514 District? Will the decision to make cathlabs in each district be effective and efficient? Methods: The cathlab location data was collected through a direct survey and site data mining. The total population and road network data are taken from an open-source geospatial system. Data were then analysed using GIS nearest-neighbor analysis to find the travel time to the nearest cathlab facility at the sub-district level. The results were then mapped on the Choropleth map. Location-Allocation Analysis was used to find the best location to build a new lab. The condition of each province was assessed using two indicators, time travel and volume. Time travel is the time a specific population needs to access the nearest cathlab. Faster time travel increases the likelihood of better outcomes. The population volume measures the number of required cathlabs by the population. The European Association of PCI recommends having one cathlab for a 500,000-650,000 people. Results: Our study found that Indonesia has a population of 330 Cathlab or 1.2 Cath per 1 million. Using geospatial analysis, these 330 categories can cover 47.5% (129 million) of the population below 1 hour and 68.1% (185 million) of the people below 2 hours. Using location-allocation analysis, we found 130 potential hospitals to get the cathlab located strategically, which will increase the coverage to 85% of the population below 2 hours of travel time. However, doubling the new cathlab to 265 cathlab only increases the range to 87%. Conclusions: Increasing the number of catheters without considering population coverage will only increase inefficiencies. The study results show that the efficient number of cathlab increases is obtained at 85% coverage with an increase of 130 cathlabs. This is due to the nature of the archipelagic country that is hindered by remote islands, high-altitude areas without roads, and some isolated areas between mountains. Different methods are needed to treat the remaining 15% of the population. Fibrinolytics have the advantage of having a low fixed cost and can still be performed in a hospital with limited facilities.

Anterior Capsular Phimosis Following Cataract Surgery in a Patient with Pseudoexfoliation Syndrome

Pseudoexfoliations syndrome increases the risk of anterior capsular contraction syndrome. An 74-year-old man with pseudoexfoliation syndrome underwent cataract surgery in the right eye at Mohamed V military hospital, Morocco. The surgical procedure was uncomplicated, and the IOL was implanted in the capsular bag. One month after surgery, visual acuity was 20/20 (Snellen). Two months after surgery, however, significant anterior capsule phimosis was noted, with nasal zonular stretching and temporal displacement of the lens. The patient was satisfied with her visual acuity, and no further procedures were necessary. The patient is periodically reassessed.

Causality violations in simulations of large and small heavy-ion collisions

Causality violations in simulations of large and small heavy-ion collisions

Effects of the perceived temporal distance of events on mental time travel and on its underlying brain circuits.

Mental Time Travel (MTT) allows us to remember past events and imagine future ones. According to previous literature, the Temporal Distance of events affects MTT: our ability to order events worsens for close, compared to far, events. However, those studies established distances a-priori, albeit the way we perceive events' temporal distance may subjectively differ from their objective distance. Thus, in the current study, we aimed to investigate the effects of Perceived Temporal Distance (PTD) on the MTT ability and the brain areas mediating this process. Thirty-three healthy volunteers took part in an fMRI MTT task. Participants were asked to project themselves into the past, present, or future, and to judge a series of events as relative-past or relative-future, in relation to the adopted time location. Outside the scanner, participants provided PTD estimates for each stimulus of the MTT task. Participants' performance and functional activity were analyzed as a function of these estimations. At the behavioural level, PTD predicts the modulation of the performance for relative-past and relative-future. Bilateral angular gyrus, retrosplenial cortex, temporo-parietal region and medial, middle and superior frontal gyri mediate the PTD effect. In addition to these areas, the closer the relative-future events are perceived, the higher the involvement of left parahippocampal and lingual gyri and right cerebellum. Thus, perceived proximity of events activates frontal and posterior parietal areas, which therefore might mediate the processing of PTD in the cognitive spatial representation of time. Future proximity also activates cerebellum and medial temporal areas, known to be involved in imaginative and constructive cognitive functions.

Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data

Computational methods such as molecular docking or molecular dynamics (MD) simulations have been developed to simulate and explore the interactions between biomolecules. However, the interactions obtained using these methods are difficult to analyse and evaluate. Interaction fingerprints (IFPs) have been proposed to derive interactions from static 3D coordinates and transform them into 1D bit vectors. More recently, the concept has been applied to derive IFPs from MD simulations, which adds a layer of complexity by adding the temporal motion and dynamics of a system. As a result, many IFPs are obtained from one MD simulation, resulting in a large number of individual IFPs that are difficult to analyse compared to IFPs derived from static 3D structures. Scientific contribution: We introduce a new method to systematically aggregate IFPs derived from MD simulation data. In addition, we propose visualisations to effectively analyse and compare IFPs derived from MD simulation data to account for the temporal evolution of interactions and to compare IFPs across different MD simulations. This has been implemented as a freely available Python library and can therefore be easily adopted by other researchers and to different MD simulation datasets.

Swedish Alzheimer’s disease variant perturbs activity of retrograde molecular motors and causes widespread derangement of axonal transport pathways

Experimental studies in flies, mice, and humans suggest a significant role of impaired axonal transport in the pathogenesis of Alzheimer's disease (AD). The mechanisms underlying these impairments in axonal transport, however, remain poorly understood. Here we report that the Swedish familial AD mutation causes a standstill of the amyloid precursor protein (APP) in the axons at the expense of its reduced anterograde transport. The standstill reflects the perturbed directionality of the axonal transport of APP, which spends significantly more time traveling in the retrograde direction. This ineffective movement is accompanied by an enhanced association of dynactin-1 with APP, which suggests that reduced anterograde transport of APP is the result of enhanced activation of the retrograde molecular motor dynein by dynactin-1. The impact of the Swedish mutation on axonal transport is not limited to the APP vesicles since it also reverses the directionality of a subset of early endosomes, which become enlarged and aberrantly accumulate in distal locations. In addition, it also reduces the trafficking of lysosomes due to their less effective retrograde movement. Altogether, our experiments suggest a pivotal involvement of retrograde molecular motors and transport in the mechanisms underlying impaired axonal transport in AD and reveal significantly more widespread derangement of axonal transport pathways in the pathogenesis of AD.

Secret histories, hidden figures: Revisionist history and corporate control in Timeless

This article examines the way Timeless (2016–18), a series focused on time travel, interacts with history and historical revision as either prescient of or commenting on the current era, particularly in the way it questions, through the stories it tells, accepted history and the consequences of excluded stories, particularly those of women and people of colour. Further, pitting the series’ protagonists against the machinations of a powerful corporate cabal that extends back to the US colonial era, with the goal of controlling citizens through the erasure and revision of history, offers real-world analogues to the control of information that persists to the present day.

Speculative Evolution in Herbert George Well’s the Time Machine

Herbert George Wells The Time Machine indeed remains a significant work in science fiction literature, offering a reflection on social issues and class distinctions of his time projected into a distant future. The story’s exploration of humanity’s potential evolution and the portrayal of a divided society have left a lasting impact, influencing various adaptations across different media. Wells ability to use speculative fiction to comment on contemporary issues highlights his foresight and literary prowess. It seems like you’re referring to Wells classic science fiction novel, The Time Machine. In the story, the Time Traveller indeed creates a machine capable of traversing through time and ventures to the distant future, where he encounters the Eloi and the Morlocks, two distinct species evolved from humanity. The novel explores themes of evolution, class struggle, and the nature of time itself.

Safe time travel

Safe time travel

THE ROLE OF YOON YEON WOO IN SUPPORTING THE STORY OF THE DRAMA MY PERFECT STRANGER DIRECTED BY KANG SOO YEON

The study was written to fulfil the writer’s final examination with the subject is The Role of Yoon Yeon Woo in Supporting The Story of The Drama My Perfect Stranger Directed By Kang Soo Yeon. The objectives of this study are: first, to identify Yoon Yeon Woo’s character in the drama My Perfect Stranger. Second, to find out Yoon Yeon Woo’s conflict in the drama My Perfect Stranger, and the third is to identify Yoon Yeon Woo’s role in supporting the story in the drama My Perfect Stranger. In this study, the writer of this study uses the qualitative research,because it focuses on understanding social phenomena from the perspective of the human participants in natural setting.The discussion focused on internal or a character in the drama. My Perfect Stranger is a mystery fantasy drama that tells about 2 main character in the drama went to time travel to year 1987 for uncover the serial murderer happen in Woojung-ri village and fix their future life. Hopefully this research will be useful, and in the future this research can become a source of data for future researchers who will conduct research on the same or related themes.

Traffic light control with reinforcement learning

Urban traffic signal optimization is important for alleviating congestion in urban transportation systems. This study proposes a real-time traffic light control algorithm based on deep Q learning with a reward function that accounts for queue lengths, delays, travel times, and throughput. The model dynamically decides phase changes based on current traffic conditions. The training of the deep Q network involves an offline stage from pre-generated data with fixed signal timing and an online stage using real-time traffic data. A deep Q network structure with aphase gate component is used to simplify the model's learning task under different phases. Amemory palace" mechanism is used to address sample imbalance during the training process. Both synthetic and real-world traffic flow data are used to validate our approach under an urban road intersection scenario in Hangzhou, China. Results demonstrate significant performance improvements of the proposed method in reducing vehicle waiting time (57.1% to 100%), queue lengths (40.9% to 100%), and total travel time (16.8% to 68.0%) compared to traditional fixed signal timing plans.