High Crowd Research Articles

Human behavior and decision-making in earthquake emergencies: insights from virtual reality and serious games

Earthquakes can severely impact public spaces with complex layouts and high crowd densities, resulting in devastating consequences and deaths. Gaining insights into the actions of individuals during an earthquake can provide valuable information about areas where their decision-making may be flawed. Addressing these areas can improve safety measures and better protect people during emergencies. Moreover, acquiring this knowledge can enhance evacuation strategies for future earthquakes. Immersive Virtual Reality and Serious Games (IVR SGs) present an effective method for examining and understanding how people behave in emergency scenarios, such as earthquakes. Using IVR SGs, we created several potential scenarios during an earthquake in a shopping mall to explore how people act in an emergency when the evacuees feel pressure, urgency, and stress. A total of 146 participants were involved in the study. We investigated the human tendency to follow authority figures’ instructions (rational and irrational), help injured people of different genders and ages, and social influence during an emergency. Moreover, we investigated how familiarity with the environment impacts human wayfinding performance when evacuating the building.

The Development of Marketing Plan for a Virtual Cycling Application: A Case Study of China (Beijing)

Background and Aims: Due to the COVID-19 pandemic, people's social activities have been greatly affected, so online activities have seen rapid development and user growth. become the norm. In cycling, the China Cycling Association canceled or postponed several races, affecting cyclists across the country. This is because the mass gatherings and high crowd density associated with such events increase the risk of virus transmission. Because of this, bicycle virtual riding software has developed rapidly, and users have increased rapidly. In addition, the evolving metaverse concept has prompted increased investment in bicycle virtual riding software development. This study explores and analyzes the operation plan of bicycle virtual riding software in China (Beijing) and analyzes the specific needs of Chinese people. Methodology: The main research methods include SWOT analysis, user stories, and population research. Use competitive product analysis such as SWOT analysis to study the specific reasons why other products cannot be promoted and popular in China (Beijing). Collect the main channels for users to obtain information and determine product promotion plans. And conduct user demand research, establish user portraits, and finally propose feasible solutions. Results: The main findings are the difficulties in promoting virtual bicycle riding software in Beijing, China, the reasons why the currently popular software is difficult to promote, the travel habits and consumption willingness of residents, and a complete promotion plan. Conclusion: The study sheds light on factors impeding the adoption of popular software already in use and clarifies the travel habits and consumption attitudes of the locals in Beijing, China. It also highlights challenges in promoting virtual bicycle riding software in Beijing. It provides insights into creating a strong promotion strategy to overcome the obstacles found and increase the adoption of virtual bicycle riding technology through in-depth analysis.

Convective heat transfer and drag coefficients of human body in multiple crowd densities and configurations in semi-outdoor scenarios

This study numerically assessed the impact of human crowd density and outdoor wind conditions (average velocity, its profile, and direction) on the convective heat transfer and drag coefficients (hc and Cd). Five different configurations of standing computer-simulated persons (CSPs) were tested in a semi-outdoor environment. A single isolated CSP, nine CSPs in a block array (with three representative crowd densities), and eighteen randomly allocated CSPs were used. The results indicated a significant impact of crowd density on the overall and local hc values. As the density increases, the body's obstruction against wind increases, resulting in lower heat loss. Newly proposed formulas for hc as a function of the average wind velocity (UAVE.) are (7.56 × UAVE.0.65), (8.02 × UAVE.0.64), and (8.26 × UAVE.0.63) for the high, medium, and low crowd densities, respectively. This reveals an overestimation of hc when an isolated human body is used. The hc values of the upper segments were the most affected by a 22 % reduction in the predicted hc. Moreover, when the crowd density increased, local hc and Cd decreased simultaneously, particularly in the chest, pelvis, and thigh segments. Oblique wind angles (60° and 150°) resulted in the highest hc and Cd values compared to other angles. The chest and pelvis were most affected by shifting the wind direction, indicating the dominance of these segments in concurrently controlling the thermal and drag performances. These results provide valuable insights into the optimization of human thermal and physical comfort models.

Effects of crowding on route preferences and perceived safety of urban cyclists in the Netherlands

Bicycle use increases in many cities around the world. In the Netherlands, cycling is one of the main transport modes in cities and bicycle use is still growing. This leads to crowded cycling infrastructure in cities with high cycling shares, including in the four largest Dutch cities. Since few studies have been done to the effects of high crowding levels on cyclists’ route preferences and perceived safety, the present study aims to examine this for Dutch urban cyclists. Moreover, the relationship between perceived safety and route preferences is established. To investigate this, a questionnaire, including a route choice experiment, is completed by 1,329 cyclists from the four largest Dutch cities. The effects of varying crowding levels on route preferences and perceived safety are analysed with Mixed Logit models. Logistic regression is used to investigate the consistency between route preferences and perceived safety. The results show that crowding negatively affects route preferences as well as perceived safety, and that the impact is stronger for older cyclists and women. Furthermore, high crowding levels have a negative impact on the preference for and perception of safety of cycling infrastructure. Moreover, it is shown that all investigated route attributes have a significant effect on perceived safety, implying a more direct relationship between perceived safety and route preferences. In addition, the results show that most cyclists prefer routes they also perceive as safe. Concludingly, crowding seems an important issue for cyclists in large Dutch cities. Moreover, the perception of safety is likely to increase with the implementation of cycling infrastructure suitable for large flows of cyclists, leading to a safer cycling network for all types of cyclists.

Modelling crowd pressure and turbulence through a mixed-type continuum approach

Empirical studies of large gatherings and natural disasters have revealed two important features of dense crowds: extremely high crowd pressure and crowd turbulence. In this study, a mixed-type continuum model for multidirectional pedestrian flow was developed that explicitly considered the phase transition of different anticipation characteristics under different densities. Non-hyperbolicity was used to model the strong instabilities during crowd turbulence. In addition, by estimating the aggregated crowd pressure, the proposed model could clarify the effects of both force chains and panic sentiment, phenomena commonly observed during crowd disasters. The non-hyperbolic partial differential equations were solved using the mixed-type finite difference method, and Eikonal equations were solved using the fast sweeping method. Subsequently, the continuum model was applied to simulations of two real-world scenarios – the 2015 Hajj crowd disaster and the 2010 Love Parade crowd disaster – and validated through comparison with empirical observations. Overall, the proposed model is an efficient tool for evaluating crowd management strategies to predict and assess the crowd state.

Pedestrian dynamics on slopes: Empirical analysis of level, uphill, and downhill walking

Pedestrian safety on inclined walking facilities merits greater attention than that on level surfaces. Crowd accidents and domino effects are more likely to occur on slope walkways, especially at high crowd densities, as in the tragic case of the 2022 Itaewon Halloween crowd crush in South Korea. However, experimental investigations of the pedestrian dynamics on slopes with varying inclinations are scarce. In this study, a controlled experiment involving 48 participants was conducted to investigate the differences in pedestrian movement characteristics during level, uphill, and downhill slope walking. A wide range of slope inclinations was considered, namely 0°, 3°, 7°, 12°, 17°, and 22°. The results demonstrated that walking speeds uphill are lower than those on flat terrains, and uphill speeds decrease with increasing inclination. In contrast, increased slope inclinations do not always correspond to reduced downhill speeds. Notably, at inclinations of 3° and 7°, the downhill speed exceeds that of level walking, suggesting that a mild downhill slope can facilitate faster movement. Compared with downhill walking, pedestrians exhibit more lateral motion and significantly lower speeds (p < 0.01) when walking uphill at the same inclination. However, the average flow rate during downhill walking is lower than those observed on flat ground and uphill terrain. This difference may be attributable to the lower pedestrian density during downhill walking to reduce the likelihood of falling. These findings can enhance the understanding of pedestrian dynamics on ramps and have significant implications for the design of safer inclined walking facilities and prevention of potential disasters on such walkways.

Crowdsourcing Skin Demarcations of Chronic Graft-Versus-Host Disease in Patient Photographs: Training Versus Performance Study.

Chronic graft-versus-host disease (cGVHD) is a significant cause of long-term morbidity and mortality in patients after allogeneic hematopoietic cell transplantation. Skin is the most commonly affected organ, and visual assessment of cGVHD can have low reliability. Crowdsourcing data from nonexpert participants has been used for numerous medical applications, including image labeling and segmentation tasks. This study aimed to assess the ability of crowds of nonexpert raters-individuals without any prior training for identifying or marking cGHVD-to demarcate photos of cGVHD-affected skin. We also studied the effect of training and feedback on crowd performance. Using a Canfield Vectra H1 3D camera, 360 photographs of the skin of 36 patients with cGVHD were taken. Ground truth demarcations were provided in 3D by a trained expert and reviewed by a board-certified dermatologist. In total, 3000 2D images (projections from various angles) were created for crowd demarcation through the DiagnosUs mobile app. Raters were split into high and low feedback groups. The performances of 4 different crowds of nonexperts were analyzed, including 17 raters per image for the low and high feedback groups, 32-35 raters per image for the low feedback group, and the top 5 performers for each image from the low feedback group. Across 8 demarcation competitions, 130 raters were recruited to the high feedback group and 161 to the low feedback group. This resulted in a total of 54,887 individual demarcations from the high feedback group and 78,967 from the low feedback group. The nonexpert crowds achieved good overall performance for segmenting cGVHD-affected skin with minimal training, achieving a median surface area error of less than 12% of skin pixels for all crowds in both the high and low feedback groups. The low feedback crowds performed slightly poorer than the high feedback crowd, even when a larger crowd was used. Tracking the 5 most reliable raters from the low feedback group for each image recovered a performance similar to that of the high feedback crowd. Higher variability between raters for a given image was not found to correlate with lower performance of the crowd consensus demarcation and cannot therefore be used as a measure of reliability. No significant learning was observed during the task as more photos and feedback were seen. Crowds of nonexpert raters can demarcate cGVHD images with good overall performance. Tracking the top 5 most reliable raters provided optimal results, obtaining the best performance with the lowest number of expert demarcations required for adequate training. However, the agreement amongst individual nonexperts does not help predict whether the crowd has provided an accurate result. Future work should explore the performance of crowdsourcing in standard clinical photos and further methods to estimate the reliability of consensus demarcations.

The popularity of tourism enclaves among studentsof Warsaw universities

The study aimed to show the popularity of tourism enclaves as places of leisureamong students of Warsaw universities and to introduce motives, preferences, and behaviorsduring trips to such places. The research was conducted in 2023 among 291 students ofWarsaw universities. The method of research was a diagnostic survey with the use of thequestionnaire technique. Over 50% of the respondents did not rest in enclaves, which wasargued by high costs and crowds of tourists in such places. The most frequently indicatedreason for going to the enclave was the convenient and comprehensive organization of thetrip. The purpose of the trip was usually to relax by the water. Most of the respondents wereaware that the attractions presented in the enclave are commercialized and inauthentic, andtheir functioning carries several threats.

The Impact of Spatial Frequency on the Perception of Crowd Emotion: An fMRI Study.

Recognizing the emotions of faces in a crowd is crucial for understanding overall behavior and intention as well as for smooth and friendly social interactions. However, it is unclear whether the spatial frequency of faces affects the discrimination of crowd emotion. Although high- and low-spatial-frequency information for individual faces is processed by distinct neural channels, there is a lack of evidence on how this applies to crowd faces. Here, we used functional magnetic resonance imaging (fMRI) to investigate neural representations of crowd faces at different spatial frequencies. Thirty-three participants were asked to compare whether a test face was happy or more fearful than a crowd face that varied in high, low, and broad spatial frequencies. Our findings revealed that fearful faces with low spatial frequencies were easier to recognize in terms of accuracy (78.9%) and response time (927 ms). Brain regions, such as the fusiform gyrus, located in the ventral visual stream, were preferentially activated in high spatial frequency crowds, which, however, were the most difficult to recognize behaviorally (68.9%). Finally, the right inferior frontal gyrus was found to be better activated in the broad spatial frequency crowds. Our study suggests that people are more sensitive to fearful crowd faces with low spatial frequency and that high spatial frequency does not promote crowd face recognition.

When and why nostalgic ads work (and do not work): A social influence perspective

Previous research has documented the power of nostalgic ads, yet little is known about whether and how their effectiveness will be affected by social influence, which is often unavoidable in the service context. To fill this gap, the current research investigates the relative effectiveness of nostalgic (vs. non-nostalgic) ads in a restaurant setting by examining two underexplored but practically relevant boundary conditions: consumption context and crowding. Two experimental studies show that nostalgic (vs. non-nostalgic) ads lead to higher levels of visit intention. Importantly, such an advantage arises (disappears) when consumers anticipate group (solo) consumption and when the environment has low (high) crowding. Moreover, we find that consumers’ sense of social connectedness is the psychological mechanism explaining the superiority of nostalgic (vs. non-nostalgic) ads. Implications for optimizing nostalgic advertising are discussed.

Public Place Crowd Transaction Monitoring System

Currently, the phenomenon of abnormal movement in public spaces by groups is becoming increasingly prominent, leading to issues concerning public flow and safety. The escalating problems of high crowd density, the presence of controlled dangerous items, and unexpected group activities highlight the necessity for timely detection in public settings. Timely identification of such scenarios will facilitate prompt responses and assistance from relevant government departments. Exploring how artificial intelligence technology can aid urban management personnel in effectively detecting abnormal group behaviors is crucial. Having the ability to swiftly and efficiently evacuate crowds in emergency situations holds significant practical importance. This paper employs deep learning methodologies to assist urban management personnel in efficiently monitoring crowd density and detecting abnormal behaviors. The aim is to maintain crowd density within reasonable limits and enable rapid and effective crowd evacuation in emergency situations. Detection of abnormal group behaviors typically involves methods based on global features, extracting feature patterns like optical flow from entire video segments and constructing corresponding histograms. Given that automatic classification of crowd patterns involves sudden and abnormal changes, a novel method is proposed to extract motion "textures" from dynamic STV (Space-Time Volume) blocks formed from real-time video streams.

A Fusion-Based Dense Crowd Counting Method for Multi-Imaging Systems

Dense crowd counting has become an essential technology for urban security management. The traditional crowd counting methods mainly apply to the scene with a single view and obvious features but cannot solve the problem with a large area and fuzzy crowd features. Therefore, this paper proposes a crowd counting method based on high and low view information fusion (HLIF) for large and complex scenes. First, a neural network based on an attention mechanism (AMNet) is established to obtain a global density map from a high view and crowd counts from a low view. Then, the temporal correlation and spatial complementarity between cameras are used to calibrate the overlap areas of the two images. Finally, the total number of people is calculated by combining the low-view crowd counts and the high-view density map. Compared to single-view crowd counting methods, HLIF is experimentally more accurate and has been successfully applied in practice.

The temporal dynamics of visual crowding in letter recognition: Modulating crowding with alternating flicker presentations.

Visual crowding reduces the visibility of a peripherally presented group of stimuli. This is especially challenging for peripheral reading because adjacent letters or characters perceptually crowd one another. We investigated the temporal course of spatial visual crowding by sequentially alternating the visibility of the target and flanking letters within a trigram letter stimulus presented 9° below fixation. We found that alternation rates of roughly 3Hz released half of the total effect of crowding, whereas 10Hz alternation rates elicited near-crowded performance. Furthermore, we found a robust performance asymmetry whereby presenting the target first elicited better performance than presenting the flankers first, an effect resembling forward masking. These results held for conditions of high, medium, and low spatial crowding. Future work will determine whether the alternation rates found in the current study can improve peripheral reading.

Crowd counting algorithm based on face detection and skin color recognition

This paper introduces an innovative crowd counting algorithm using skin color information. Through stages of color space transformation, threshold segmentation, morphological processing, and region filtering, the algorithm successfully conducts crowd counting in images. The study encompasses analyses of images with diverse crowd densities, skin colors, backgrounds, and lighting intensities, revealing the algorithm's robustness to various factors. It remains unaffected by skin color and crowd size and exhibits minimal sensitivity to background and lighting intensity. Furthermore, the paper explores image feature analysis and uses MATLAB programming for simulation and initial crowd counting, considering images with different actual crowd sizes. Despite minor issues such as the insufficient separation of faces from clothing and the influence of lighting intensity, the algorithm performs reliably in most scenarios, demonstrating high crowd counting accuracies. To bolster the accuracy and robustness of the algorithm, optimization of the separation step and control of the lighting effect on images is suggested. The key focus of this study is the application of the Gaussian model in the YCbCr color space for face detection and examining its impact on the efficiency and accuracy of crowd counting algorithm. The research not only provides a novel approach for crowd counting in images but also offers insightful perspectives for future studies and potential improvements. Thus, the study proves to be a significant contribution to face detection and recognition technology, enhancing its application in fields like public safety, crowd management, and surveillance systems.

Consumers’ response to CSR statement type in social crowding

PurposeBased on the construal level theory, this research study examines the interactive effect between social crowding and corporate social responsibility (CSR) statement type on consumers' purchase intention.Design/methodology/approachThe authors conducted two empirical experiments on a total of 508 subjects.FindingsThere is an interactive effect between social crowding and CSR statement type on consumers' purchase intention. Specifically, in high social crowding situations, concrete CSR statements lead to consumers' higher purchase intention, while in low social crowding situations, abstract CSR statements lead to consumers' higher purchase intention. Self-construal and processing fluency play a moderating and mediating role in the mechanism.Originality/valueThis research study contributes to the theoretical understanding of the interaction between social crowding and CSR statements, enriching the field of consumer behavior research on social crowding. Additionally, it offers practical insights for enterprises on how to present CSR information in crowded situations.

Tuning Hydrophobicity of Paper Substrates for Effective Colorimetricdetection of Glucose and Nucleic acids.

This study investigated the colorimetric response of standard glucose, serum glucose, and nucleic acid assays on various paper surfaces with different wettability, including hydrophilic, hydrophobic, and nearly superhydrophobic surfaces. Water contact angles (WCA) formed by water droplets on each surface were measured using ImageJ software. The hydrophilic surface showed no contact angle, while the hydrophobic and nearly superhydrophobic surfaces exhibited contact angles of 115.667° and 133.933°, respectively. The colorimetric sensitivity of the standard glucose assay was analyzed on these surfaces, revealing enhanced sensitivity on the nearly superhydrophobic surface due to the high molecular crowding effect owing to its non-wetting behavior and eventually confined reaction product at the sample loading zone. The hydrophobic nature of the surface restricts the spreading and diffusion of the reaction product, leading to a controlled and localized concentration of the assay product leading to moderate colorimetric intensity. On the other hand, the hydrophilic surface showed the least enhancement in colorimetric sensitivity; this is attributed to the high wettability of the hydrophilic surface causing the reaction product to spread extensively, resulting in a larger area of dispersion and consequently a lower colorimetric intensity. The measured limit of detection (LOD) for nucleic acid on nearly superhydrophobic surfaces was found to be 16.15ng/µL, which was almost four-fold lower than on hydrophilic surfaces (60.08ng/µL). Additionally, the LODs of standard glucose and clinical serum samples were two-fold lower on nearly superhydrophobic surfaces compared to hydrophilic surfaces. Our findings clearly highlight the promising potential of utilizing superhydrophobic surfaces to significantly enhance colorimetric sensitivity in paper-based diagnostic applications. This innovative approach holds promise for advancing point-of-care diagnostics and improving disease detection in resource-limited settings.

Astrometry in crowded fields towards the Galactic bulge

Context. The astrometry towards the Galactic bulge is hampered by high stellar crowding and patchy extinction. This effect is particularly severe for optical surveys such as the European Space Agency satellite Gala. Aims. In this study, we assess the consistency of proper motion measurements between optical (Gaia DR3) and near-infrared (VIRAC2) catalogues in comparison with proper motions measured with the Hubble Space Telescope (HST) observations in several crowded fields towards the Galactic bulge and in Galactic globular clusters. Methods. Assuming that the proper motion measurements are well characterised, the uncertainty-normalised proper motion differences between pairs of catalogues are expected to follow a normal distribution. A deviation from a normal distribution defines the inflation factor r. By multiplying the proper motion uncertainties with the appropriate inflation factor values, the Gaia (VIRAC2) proper motion measurements are brought into a 1σ agreement with the HST proper motions. Results. The inflation factor (r) depends on stellar surface density. For the brightest stars in our sample (G &lt; 18), the dependence on G-band magnitude is strong, corresponding to the most precise Gaia DR3 proper motions. We used the number of observed Gaia DR3 sources as a proxy for the stellar surface density. Assuming that the HST proper motion measurements are well determined and free from systematic errors, we find that Gaia DR3 proper motion uncertainties are better characterised, having r &lt; 1.5 in fields with a stellar number density with fewer than 200 Gaia DR3 sources per arcmin2, and are underestimated by up to a factor of 4 in fields with stellar densities higher than 300 sources per arcmin2. For the most crowded fields in VIRAC2, the proper motion uncertainties are underestimated by a factor of 1.1 up to 1.5, with a dependence on J-band magnitude. In all fields, the brighter sources have the higher r value. At the faint end (G &gt; 19), the inflation factor is close to 1, meaning that the proper motions already fully agree with the HST measurements within 1σ. Conclusions. In the crowded fields common to both catalogues, VIRAC2 proper motions agree with HST proper motions and do not need an inflation factor for their uncertainties. Because of the depth and completeness of VIRAC2 in these fields, it is an ideal complement to Gaia DR3 for proper motion studies towards the Galactic bulge.

The impact of pneumococcal conjugate vaccine on ceftriaxone consumption in the community among young children

ObjectivesFollowing pneumococcal conjugate vaccine (PCV) introduction, community pediatric dispensed prescription rates (DPR) of oral antibiotics declined, in parallel to respiratory tract infection (RTI). We assessed the dynamics of outpatient parenteral ceftriaxone DPR. MethodsComputerized data for children <5 years were examined during 13 years (including 4 pre-PCV years). DPR from clinics with ≥50 insured children, active both before and after PCV implementation were included. Interrupted time series with segmented regression stratified by age and ethnicity, and adjusted for seasonality was applied to show monthly DPR trends. ResultsA total of 29,226 prescriptions were dispensed. No significant trends in ceftriaxone DPR were seen pre-PCV. Shortly after PCV implementation, DPR abruptly and significantly declined, stabilizing in late-PCV period (5 years postimplementation). The dynamics were compared between the two ethnic groups in the region, Jewish and Bedouin children (the latter with higher crowding and respiratory disease rates). Among Jewish children, ceftriaxone was mainly dispensed during winter vs no seasonality among Bedouin children. ConclusionsIn southern Israel, outpatient ceftriaxone DPR declined post-PCV in young children, similar to the trends of RTIs and oral antibiotic prescriptions, suggesting a causative role of PCVs. The differences between the two ethnic groups suggest possible involvement of additional factors.

Effect of walking height on movement of individuals and crowds in a corridor

The safe and efficient evacuation of pedestrians in an emergency has been widely investigated in the past. Stooping is a common walking posture of pedestrians in evacuation. Understanding the basic laws of pedestrian movement with stoop posture is instructive for developing effective evacuation management in an emergency. However, the evacuation behaviors and movement characteristics of stooped pedestrians are still unclear. In this study, a series of experiments on individuals and crowds with different walking heights were conducted in an 18 m long corridor. It was found that a left-deflection phenomenon appears in the transition from upright walking to stooped walking, and the deflection angles of pedestrians decrease with increasing walking height. The influence of walking height on pedestrian velocity is revealed through the comparison of individual and crowd movement. Restricted walking height can promote the movement velocity of individuals at low speed levels, and weakens the velocity at high speed levels. In contrast to the individual, the velocities of crowds at different speed levels will be enhanced by restricted walking height. Generally, pedestrian movement is affected by the initial motivation, walking height and pedestrian density. Restricted walking height has an encouraging effect in the motivation of pedestrian movement but can increase the physical discomfort of pedestrians. Besides, crowd density has an inhibitory effect on pedestrian movement, and restricted walking height can alleviate high crowd density, implying that appropriate stoop movement can facilitate pedestrian traffic and evacuation to some extent.

Stiffness of Confinement Controls the Localization of an Object under Crowding: Macroscale Real-World and Microscale Numerical Modelings on the Specificity of Intracellular Positioning

Macroscopic systems that mimic microscopic systems can provide fundamental understanding of how macromolecules (e.g., cellular organelles) are organized in a confined space. We studied the behavior of a large particle interacting with several small particles confined in dishes with hard/soft boundary conditions under mechanical vibration using a cm-scale model. We also performed a numerical simulation for the micro-scale system under Brownian fluctuation with fluctuation–dissipation, as a simple model of living cellular cytoplastic crowding. Under a hard boundary condition, the large sphere preferred the boundary at low crowding but tended to localize to the interior under high crowding. Conversely, when the boundary was soft, the large sphere localized to the interior under low crowding and tended to migrate near the boundary when crowding increased. Interestingly, numerical modeling reproduced similar results for both the experimental hard and soft boundary conditions. Our models revealed that membrane stiffness can affect the organization of biopolymers within a confined space and may help explain cellular dynamics.