COSMITO is an interactive therapeutic system designed to enhance mental resilience during prolonged required isolation and confinement (PRIC), conditions that can disrupt cognitive performance, emotional regulation, and interpersonal stability. Using a multisensory, biophilic design, COSMITO transforms interiors into emotionally responsive ecosystems. Grounded in environmental psychology and human-centered design, it integrates mindfulness with olfactory and haptic cues in an interactive feedback loop to support self-regulation and reduce stress. The system operates in two phases: first, a pre-exposure psychoactive-assisted session employing its interactive sensorial-biophilic interface to recalibrate cognitive baselines; and second, daily breathing exercises using the interface to sustain emotional balance. By merging tangible interaction, embodied cognition, and environmental empathy, COSMITO redefines the therapeutic potential of habitat design. These principles extend to high-stress terrestrial and space contexts, illustrating how environments can evolve from passive shelters into active agents of psychological support.

AeroShelter is an early-stage interactive public structure that explores a No-UI interaction paradigm, where the presence of wind, light, or nearby bodies serves as input. This is framed as “presence as input,” highlighting the role of bodily and environmental conditions as the primary interaction channel. Drawing on soma design and embodied cognition, it redefines public shelters as robotic frames that sense environmental stimuli and respond through subtle spatial transformations. We present an iterative design process across three dimensions: (1) material experimentation, combining origami-inspired folding structures and gentle, responsive robotic motion; (2) interaction prototyping, developing low-power mechanisms responsive to wind and human proximity; and (3) preliminary field-based reflection, where public interaction is observed and embodied presence is foregrounded. AeroShelter offers a design pathway for interface-less, contemplative interaction in public space by shifting attention from instruction to invitation, and from action to awareness.

There has been increased development of assistive robots for the home, along with empirical studies assessing cultural differences on user perception. However, little attention has been paid to cultural differences with respect to non- humanoid, multi-robot interactions in homes or otherwise. In this exploratory paper, we investigate how cultural differences may impact users’ preferences and perceived usefulness of a multi-robot system by creating an interactive online survey and considering variables often absent in HRI studies. We introduce our multi-robot design and survey construction, and report results evaluated across 191 young adult participants from China, India, and the USA. We find significant effects of culture on both participants’ preferences and perceived usefulness of the system between India and China or the USA, but not between China and the USA. We also find effects of culture on perceived usefulness to be partially mediated by participant preferences. Our findings reinforce the importance of considering cultural differences in designing domestic multi-robotic assistants.

When evaluating the accessibility of a large website, we rely on sampling methods to reduce the cost of evaluation. This may lead to a biased evaluation when the distribution of checkpoint violations in a website is skewed and the selected samples do not provide a good representation of the entire website. To improve sampling quality, stratified sampling methods first cluster web pages in a site and then draw samples from each cluster. In existing stratified sampling methods, however, all the pages in a website need to be analyzed for clustering, causing huge I/O and computation costs. To address this issue, we propose a novel page sampling method based on URL clustering for web accessibility evaluation, namely URLSamp. Using only the URL information for stratified page sampling, URLSamp can efficiently scale to large websites. Meanwhile, by exploiting similarities in URL patterns, URLSamp cluster pages by their generating scripts and can thus effectively detect accessibility problems from web page templates. We use a data set of 45 web sites to validate our method. Experimental results show that our URLSamp method is both effective and efficient for web accessibility evaluation.