The study builds on CITY IN TIME, a publicly accessible digital platform commissioned by the Hong Kong Tourism Commission that reconstructs 44 iconic Hong Kong landmarks as they appeared between 1900 and 1970. The reconstructions were assembled from archival sources, including historical photographs, maps, and documentary records, and rendered as navigable three-dimensional environments built in the Unity game engine. Rather than offering static panoramas, the platform allows users to move through detailed streetscapes of a city that has largely vanished, encountering the shops, transport, and architecture of earlier eras at eye level and at walking pace.

The research team, led by Jingting Huang, Yifei Li, Richard William Allen, Jeffrey Shaw, and corresponding author Linyan Li, recruited older adults through community organizations and assigned participants to groups with differing levels of exposure to the virtual heritage environments. The experimental design was deliberately rigorous, capturing data before, during, and after the virtual experience. Physiological monitoring ran throughout each session, including electroencephalography to track brain activity, alongside measures of heart rate variability and electrodermal activity, both well-established indicators of stress and emotional arousal. Psychological assessments administered before and after the sessions measured memory recall, anxiety, mood, place attachment, and perceived social connection.

The results were consistent across both the biological and the self-reported data. Participants who experienced the historical environments showed enhanced memory recall, with the virtual streets acting as powerful cues for autobiographical memories. This effect aligns with a well-documented phenomenon in memory research known as the reminiscence bump, in which events from adolescence and early adulthood are recalled more vividly and frequently than experiences from other life periods. For many participants, the reconstructed landmarks fell squarely within that formative window, providing spatial scaffolding that helped them mentally time travel back to specific moments of their own lives.

The physiological traces told a parallel story. Electroencephalographic recordings revealed changes in relative power across frequency bands associated with relaxed, positive engagement, and the stress-linked measures of electrodermal activity indicated a calming effect during and after exposure. Trajectories of physiological and psychological responses were tracked across four assigned groups, and the between-group comparisons showed that the immersive heritage experience produced measurable benefits relative to control conditions. In practical terms, a session of walking through a digitally resurrected 1950s Hong Kong street functioned something like a relaxation intervention, lowering physiological stress markers while simultaneously lifting mood.

Semi-structured interviews conducted after the sessions added a qualitative dimension that the sensors could not capture. Participants described their experience of urban memory as multidimensional, encompassing both tangible places and intangible narratives. A reconstructed ferry pier was not merely a structure; it was the backdrop for stories of courtship, family outings, first jobs, and neighborhood friendships. Word frequency analysis of the interviews showed which digitally reconstructed landmarks resonated most strongly, and the perceptual patterns that emerged confirmed that the value of the virtual environments lay less in architectural fidelity alone and more in the personal and communal stories the places triggered.

The findings arrive at a moment when both of the forces at play are intensifying. Rapid urbanization worldwide continues to erase historic fabric, severing communities from the physical anchors of their collective memory. At the same time, populations are aging quickly, and social isolation and loneliness among older adults have been identified by major public health bodies as serious risks for mental and physical health, comparable in their impact to more traditional medical risk factors. Prior research has linked environmental factors, place attachment, and access to meaningful spaces with life satisfaction and lower rates of depressive symptoms in older populations, making the loss of familiar places a genuine well-being concern rather than a merely sentimental one.

Virtual reality has been explored before as a tool for older adults, including reminiscence therapy for people with cognitive impairment and nature-based virtual environments for stress reduction. What distinguishes the new work is its combination of a large, historically grounded, city-scale reconstruction with a multi-modal evaluation that spans brain activity, peripheral physiology, standardized psychometrics, and in-depth interviews. The authors also note that acceptance of immersive head-mounted displays among older adults, once considered a barrier, has been shown in earlier studies to be higher than commonly assumed when the technology is introduced carefully, and the technology acceptance and user experience ratings collected across the experimental groups in this study support that picture.

The researchers frame their results as evidence that urban heritage, even when the physical fabric is gone, can still safeguard collective memory and foster community well-being. Because the CITY IN TIME platform is publicly accessible and the approach is scalable, the authors argue that similar digital reconstructions could be created for other cities, offering a way to preserve layered histories while giving older residents an emotionally resonant resource for reminiscence, stress relief, and social interaction. The work also hints at broader applications, from intergenerational programs in which younger residents explore the same virtual streets alongside elders, to therapeutic settings where guided virtual heritage visits complement conventional care.

There are limits to what a single study can establish. The experimental data are not publicly available due to ethical restrictions, though de-identified or aggregated data may be requested from the corresponding author with a research proposal and data-use plan, and the participants were drawn from a specific urban population with specific memories of a specific city. The durability of the benefits beyond the immediate post-session period remains an open question, as does how the approach transfers to people whose formative years were spent elsewhere. Still, the convergence of physiological, psychological, and narrative evidence makes a compelling case that the past, once digitized with care, is not just an archive to be consulted but an environment to be inhabited, and that walking through it virtually can make the present measurably better for the people who remember it first.

Subject of Research: Immersive virtual heritage environments and well-being outcomes in older adults

Article Title: Revisiting the urban past virtually to enhance well-being for older adults

Article References: Huang, J., Li, Y., Allen, R. W., Shaw, J., & Li, L. (2026). Revisiting the urban past virtually to enhance well-being for older adults. Nature Cities. https://doi.org/10.1038/s44284-026-00523-y

Image Credits: AI Generated

DOI: 10.1038/s44284-026-00523-y

Keywords: virtual reality, urban heritage, older adults, collective memory, Hong Kong, well-being, reminiscence, stress reduction, social connectedness, digital reconstruction, Nature Cities, place attachment

The research team, led by Haitao Ge of Chang’an University together with collaborators in France, built their framework around a deceptively simple idea: pavement texture is not an abstract surface property but the direct geometric fingerprint of how individual aggregate particles pack together near the top of an asphalt layer. If you can digitally reproduce the shape, size distribution, and arrangement of those particles, and then account for the smoothing role of the asphalt binder that glues them together, you should be able to predict the surface that a paving machine will produce. The challenge was doing so with enough physical realism to match what laser scanners actually measure on real roads.

To establish a trustworthy benchmark, the researchers first scanned real pavement surfaces using a high-resolution three-dimensional laser scanner, the Freescan UE11, which operates by laser triangulation and achieves a measurement accuracy of 0.02 millimeters while capturing up to 1,020,000 points per second. From the dense point clouds, they extracted representative 90 by 90 millimeter regions and processed them through noise filtering, outlier removal, and plane detrending, fitting and subtracting a least-squares plane so that only texture-related roughness remained. The cleaned data were interpolated onto a regular grid with a fine 0.1 millimeter resolution, producing continuous height fields suitable for rigorous statistical analysis.

Two widely used asphalt mixtures served as the test cases: a dense-graded AC-13 and a stone matrix asphalt SMA-13. The measured surfaces revealed clear and quantifiable differences. SMA-13 showed consistently higher amplitude parameters, with its mean profile depth, a standard macrotexture indicator, exceeding that of AC-13 by roughly 47 percent. Both mixtures displayed negative skewness, indicating valley-dominated surfaces, but SMA-13’s less negative skewness and lower kurtosis revealed a more balanced distribution of peaks and valleys created by large protruding aggregates. In contrast, AC-13 presented a smoother, more continuous surface with sharper, more concentrated asperities, reflecting its denser and more uniformly packed gradation.

The heart of the digital reconstruction lies in how the aggregates themselves were represented. The team laser-scanned approximately 500 real aggregate particles with sieve sizes from 4.75 to 26.5 millimeters, converting each into a triangular surface mesh. From these scans they quantified elongation, flatness, and sphericity, finding that all three descriptors followed normal distributions with high goodness of fit, which allowed them to stochastically generate a particle library of realistic polyhedral shapes. Because full-resolution meshes would be computationally prohibitive, they systematically simplified the geometry, showing that reducing particles to about 60 to 65 faces preserved morphological indices within deviations of roughly 4 percent while dramatically cutting simulation cost.

For the simulation engine, the researchers chose the Contact Dynamics method rather than classical discrete element approaches. Conventional discrete element models rely on stiff elastic contact laws that demand artificially high stiffness parameters and tiny time steps, often causing numerical instability when irregular polyhedral particles collide. Contact Dynamics instead enforces impenetrability through non-smooth mechanics, using the Signorini condition for normal contact and the Coulomb friction law for tangential interaction, solved implicitly with a nonlinear Gauss-Seidel algorithm in the LMGC90 software. This formulation handles point, edge-face, and face-face contacts between angular particles without artificial stiffness, permitting larger time steps and mechanically consistent simulations of large assemblies of irregular grains.

The virtual specimens were assembled by inserting particles according to the target gradation curves of each mixture, with particles finer than 2.36 millimeters lumped into an implicit mastic phase to save computation. Gravitational deposition created a loose configuration in a 100 by 100 millimeter domain with periodic horizontal boundaries, mimicking an infinitely repeating material volume. Compaction then proceeded under a constant vertical force of 6 kilonewtons, equivalent to about 0.6 megapascals of compressive stress, superimposed with a 40-hertz harmonic vibration representative of real vibratory rollers. A reduced inter-particle friction coefficient of 0.1 accounted for the lubricating effect of hot bitumen, and compaction continued until mechanical stabilization at a specimen thickness of roughly 40 millimeters.

When the researchers extracted surface textures from these compacted digital specimens using a virtual scanning procedure that mimics laser triangulation, the raw results revealed a fundamental problem. The purely aggregate-controlled surfaces overestimated roughness dramatically, with mean profile depth nearly doubled for both mixtures, because the digital surface lacked the binder mastic that in reality fills deep valleys and bridges neighboring stones. To correct this, the team introduced a bridging algorithm applied directly to the height field: a maximum filter that locally elevates narrow valleys, a grayscale morphological closing operation that removes small isolated depressions, and optional Gaussian smoothing. Calibrated once, the same parameters worked for both mixtures, cutting the deviation in mean profile depth from 160.9 percent to 27.4 percent for AC-13 and from 119.1 percent to 18.2 percent for SMA-13, while deviations in the areal roughness parameters Sa and Sq fell by more than 80 percent.

Beyond validation, the framework opened a window onto the particle-scale mechanics of texture formation, and the findings are striking. By classifying particles into size fractions and tracking which ones reach the surface, the researchers found that larger aggregates mainly control surface exposure, while intermediate and small particles dominate the formation of the highest asperities. In AC-13, surface peaks arose from distributed contributions of the 2.36 to 4.75 millimeter and 4.75 to 9.5 millimeter fractions, which together accounted for nearly 98 percent of peak particles, producing a homogeneous texture. SMA-13 showed a decoupled, skeleton-driven pattern in which the 9.5 to 13.2 millimeter fraction was most exposed at the surface, yet the 4.75 to 9.5 millimeter fraction generated 56 percent of the peaks, explaining its broader, more heterogeneous height distribution.

The implications reach well beyond academic curiosity. Because the framework links mixture composition, gradation, and aggregate morphology directly to quantitatively validated surface texture, it transforms pavement design from descriptive measurement into predictive, simulation-driven engineering. Engineers could someday screen candidate mixture designs virtually, optimizing skid resistance and drainage before committing materials to a laboratory or a road. The authors caution that the bridging parameters are numerical rather than intrinsic material properties and may require recalibration for different aggregate lithologies, binders, or interface conditions, and that the computationally demanding polyhedral simulations currently limit the approach to texture reconstruction and microscopic investigation. Even so, the study marks a decisive step toward a future in which the texture of a highway is designed on a computer as deliberately as the shape of an aircraft wing.

Subject of Research: Digital reconstruction of three-dimensional asphalt pavement surface texture using laser-scanned aggregates and the Contact Dynamics method

Article Title: A digital reconstruction framework for three-dimensional asphalt pavement surface texture using the Contact Dynamics method

Article References: Ge, H., Sha, A., Jiang, W., Xing, C., Quezada, J. C., Houerou, V. L., & Chazallon, C. (2026). A digital reconstruction framework for three-dimensional asphalt pavement surface texture using the Contact Dynamics method. Case Studies in Construction Materials, 25, Article e06469. https://doi.org/10.1016/j.cscm.2026.e06469

Image Credits: AI Generated

DOI: 10.1016/j.cscm.2026.e06469

Keywords: asphalt pavement, surface texture, Contact Dynamics, discrete element method, aggregate morphology, 3D laser scanning, skid resistance, macrotexture, virtual compaction, pavement engineering, digital reconstruction, asphalt mastic