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Robotic Composites and Compositions Article Aesthetics as a core design dimension for human-centred robotic systems Pagliarani, N., Comoretto, A., Obayashi, N., Aktaş, B., Becker, K. P., Overvelde, J. T. B., Craig, L., Winters, A., Devlin, K., Demers, L., Jørgensen, J., Hughes, J., Cianchetti, M., Maiolino, P. Nature Reviews Bioengineering , 3:1, April 2026 (Published)
Barriers to the widespread adoption of robots often stem less from limitations in technical capability than from the social, cultural and interpretive contexts in which these systems are encountered. We therefore argue that aesthetics should be treated as a core design dimension, alongside functionality and safety, to support meaningful and situated human–robot interactions.
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Perceiving Systems Article Textile suit for anywhere full-body motion capture Sun, H., Feng, Y., Kao, P., Black, M. J., Kramer-Bottiglio, R. Science Advances, 12(10):1-15, March 2026 (Published)
Wearable technology has shown notable promise for tracking human motion, offering valuable insights for fields ranging from biomechanics to healthcare. Traditional motion capture systems, however, are often bulky and disruptive, making them impractical for daily use. Advances in textile-based sensing offer a promising alternative, enabling seamless integration of air- and sweat-permeable sensors into everyday clothing. Here, a sensorized textile suit designed for unobtrusive full-body motion capture is presented. The suit is capable of accurately tracking complex movements without interfering with routine activities. This wearable, using an individual-customized network of fabric-based sensors, autonomously identifies and monitors movement angles and patterns, providing insights into physical range, activity frequency, and exertion levels. Language models are shown to interpret motion data into descriptive language, enhancing its potential for real-world applications. This sensorized textile suit and corresponding algorithms represent a step forward in accessible, continuous movement monitoring in the form of everyday clothing, opening avenues for studying human behavior and health in natural environments. YSuit is a fully textile suit for accurate, customizable, washable, and comfortable anywhere full-body motion capture.
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Haptic Intelligence Article Comparing Placement and Polarity Configurations of a Two-Magnet Fingertip Vibrotactile Device Gertler, I., Ballardini, G., Tangolar, D., Serhat, G., Kuchenbecker, K. J. Scientific Reports, 16(12600), March 2026 (Published)
Vibrotactile feedback enriches the use of wearable technologies for entertainment, navigation, and healthcare. The actuators of these portable systems, particularly fingertip devices, need to be compact, comfortable, and easy to integrate. Multiple vibrating elements could enhance perceptual realism, but how should they be arranged and oriented on the fingerpad? Here, we evaluate a simple approach that uses an audio input signal to drive an air coil that vibrates two magnets embedded in a soft fingertip sheath; the magnets are arranged in the radial-ulnar or proximal-distal direction with either the same or opposite polarity. We explore the effects of these new device configurations on both dynamic response and haptic perception. Experimental results indicate that the vibrations were perceived well across frequencies, with stronger sensations between 180 and 360 Hz, which aligns with the high vibration magnitudes our computational simulation predicts in this frequency range. Interestingly, perceptual responses showed that participants mainly classified vibrations based on the excitation frequency rather than the polarity of the magnets. Participants also rated vibrotactile feedback derived from recorded sounds and replayed for different interactions. Their evaluations offer promising evidence that this actuation approach could be used in extended-reality applications to improve transient user interactions with virtual objects.
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Haptic Intelligence Robotics Materials Medical Systems Article Functional Gradients Facilitate Tactile Sensing in Elephant Whiskers Schulz, A. K., Kaufmann, L. V., Smith, L. T., Philip, D. S., David, H., Lazovic, J., Brecht, M., Richter, G., Kuchenbecker, K. J. Science, 391(6786):712-718, February 2026, Lena V. Kaufmann and Lawrence T. Smith contributed equally to this work (Published)
Keratin composites enable animals to hike with hooves, fly with feathers, and sense with skin. Mammalian whiskers are elongated keratin rods attached to tactile skin structures that extend the animal's sensory volume. We investigated the whiskers that cover Asian elephant (Elephas maximus) trunks and found that they are geometrically and mechanically tailored to facilitate tactile perception by encoding contact location in the amplitude and frequency of the vibrotactile signal felt at the whisker base. Elephant whiskers emerge from armored trunk skin and shift from a thick, circular, porous, stiff base to a thin, ovular, dense, soft tip. These functional gradients of geometry, porosity, and stiffness independently tune the neuromechanics of elephant trunk touch to facilitate highly dexterous manipulation while ensuring whisker durability.
MPI-IS News Article YouTube Video Highlight Whisker Simulation Toolkit Edmond Data Repository Download Paper for Free Press Coverage DOI BibTeX
Physical Intelligence Article Optoacoustically augmented magnetic guidewire for radiation-free minimally invasive therapies Wang, F., Bao, X., Yildiz, E., Yu, Y., Deán-Ben, X. L., Kang, W., Zhang, S., Sheehan, D., Soon, R. H., Zinnanti, J., Sitti, M. Science Advances, 12:eaea0201, February 2026 (Published)
Endovascular interventions are essential for treating cerebrovascular diseases, yet their monitoring methods commonly rely on ionizing radiation and contrast agents, posing unnecessary risks to patients and clinicians. We present a multifunctional optoacoustically augmented magnetic guidewire (OptoMaG) that integrates optoacoustic imaging with magnetic navigation to enable radiation-free, image-guided interventions. The ~250-micrometer flexible guidewire incorporates a 460-nanometer luminescent core with an enhanced optoacoustic signature and a FePt magnetic tip for precise, steerable control. Proof-of-concept studies show that OptoMaG can be actively navigated with external magnetic fields to traverse a 3D human-scale cerebrovascular phantom and accurately reach target brain sites. Beyond navigation, the FePt tip enables localized thermal ablation under remote radiofrequency stimulation, highlighting its theranostic potential for tumor treatment. In addition, OptoMaG functions as a light source for photodynamic therapy, selectively activating photosensitizers to destroy tumor cells while preserving healthy tissue. Collectively, OptoMaG provides a safe, radiation-free platform merging real-time navigation with targeted therapeutic capabilities.
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Physical Intelligence Article Optofluidic three-dimensional microfabrication and nanofabrication Lyu, X., Lei, W., Gardi, G., Khan, M. T. A., Bagheri, S., Zhang, M., Sitti, M. Nature, 00:1-8, January 2026 (Published) DOI URL BibTeX
Physical Intelligence Article 3D-printed low-voltage-driven ciliary hydrogel microactuators Liu, Z., Wang, C., Ren, Z., Wang, C., Wang, W., Ko, J., Song, S., Hong, C., Chen, X., Wang, H., Hu, W., Sitti, M. Nature, 649:885-893, January 2026 (Published) DOI URL BibTeX
Physical Intelligence Article Perturbing dynamics of active emulsions and their collectives Khan, M. T. A., Gardi, G., Soon, R. H., Zhang, M., Sitti, M. Matter, 9:00, January 2026 (Published)
Controlling fluidic flows in active droplets is crucial in developing intelligent models to understand and mimic single-celled microorganisms. Typically, these fluidic flows are affected by the interfacial dynamics of chemical agents. We found that these flows can be reconfigured by the mere presence of an anisotropic solid boundary embedded within active droplets. Spontaneous fluidic flows dynamically orient an embedded magnetic cluster, and the magnetic cluster, when realigned, causes these flows to reorient, thus providing control over the propulsion dynamics of chemotactic emulsions. When continuously perturbed, achiral emulsions exhibit emergent chiral motion with rotating fluidic flows. Such solid-fluid interactions occur in a number of self-propelling oil droplet systems, thereby enabling control over the emergent collective behaviors of chemically distinct active droplets.
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Haptic Intelligence Robotics Article Open-Source Hardware and Software Platform for Vibrotactile Motion Guidance Rokhmanova, N., Martus, J., Faulkner, R., Fiene, J., Kuchenbecker, K. J. Device, 4(1):100966, January 2026 (Published)
Vibrotactile feedback can enhance motor learning, sports training, and rehabilitation, but a lack of standardized tools limits its adoption. We developed a modular open-source hardware and software platform for delivering vibrotactile feedback that is spatially and temporally precise. The prototype device uses medical adhesive, linear resonant actuators (LRAs), and rigid 3D-printed components to standardize skin contact, avoiding the variability introduced by straps. The platform was validated by using the device's built-in accelerometers to fit a dynamic model of mechanical actuator vibration and examine how the anatomical site and body composition affect perceived vibration strength in 20 participants. Then, the platform was integrated with an optical motion-capture system to teach six participants a toe-in gait, showing potential for real-time, tailored clinical studies. By openly sharing the platform's hardware and software, we provide tools for delivering standardized vibrations and benchmarking feedback strategies in diverse applications.
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Physical Intelligence Article Nuclear magnetic resonance for wireless magnetic tracking Efe Tiryaki, M., Esmaeili-Dokht, P., Lazovic, J., Pruessmann, K. P., Sitti, M. Nature Communications, 16:10840, December 2025 (Published)
Wireless trackers have emerged as a crucial technology in minimally invasive medical procedures with their remote localization capabilities. Existing trackers suffer from miniaturization issues and complex designs, which limit their integration into medical devices. We present nuclear magnetic resonance (NMR) magnetic sensing, a quantum sensing approach with nT sensitivity for wireless magnetic tracking. NMR magnetic sensing enables millimeter-scale tracking accuracy and versatile miniaturized tracker designs for minimally invasive medical devices in magnetic resonance imaging scanners. As examples, we demonstrate miniature magnetic trackers with submillimeter-scale diameters for guidewires and optic fibers, flexible magnetic trackers for soft devices, and ferrofluidic trackers for shape-morphing devices. With the demonstrated miniaturization and wide range of tracker design possibilities, wireless magnetic tracking with NMR is promising for future minimally invasive medical operations.
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Haptic Intelligence Article Creating an Affective Robot That Feels Both Touch and Emotion Burns, R. B., Richardson, B. A., Klingenberg, J., Kuchenbecker, K. J. IEEE Transactions on Affective Computing, 1-18, December 2025, Rachael Bevill Burns and Benjamin A. Richardson contributed equally to this publication (Published)
Despite the importance of sensitive skin for living creatures, most robots can feel contact on only a tiny fraction of their exterior, if at all. Furthermore, typical robot reactions to touch are limited to event-based acknowledgments, lacking perceptual richness, lifelike positive/negative responses, and temporal dynamics. We address these gaps by introducing a practical full-body tactile-perception system for social robots, turning a NAO robot into the Haptic Empathetic Robot Animal (HERA). The sixteen main regions of the robot's body are instrumented with soft resistive tactile sensors covered by a tailored koala suit. Windows of each time-varying sensor output are continually classified into five gestures at two intensities via a two-stage machine-learning model. On challenging testing data containing simultaneous contacts, touch detection achieves an F1 score of 0.773, and gesture recognition achieves 52.2% accuracy (5.2 times chance); considering the temporal, spatial, and semantic adjacency of the applied touches increases these metrics to 0.896 and 86.6%, respectively. In turn, each detected contact drives a real-time emotion model that represents the robot's affective state as a second-order dynamic system analogous to a mass-spring-damper. This model's parameters control the robot's disposition, stoicism, and calmness. We explain the connections between HERA's hardware and software subsystems and demonstrate their combined ability to create an affective robot that feels both touch and emotion.
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Physical Intelligence Article Optoacoustic-Guided Magnetic Microrobot Platform for Precision Drug Delivery Wang, F., Yildiz, E., Deán-Ben, X. L., Yu, Y., Nozdriukhin, D., Kang, W., Zhang, S., Zinnanti, J., Sheehan, D., Soon, R. H., Sitti, M. Advanced Materials, 38:e11870, October 2025 (Published)
Precision drug delivery remains a significant challenge due to limitations in drug loading, targeted release, precise navigation, and real-time monitoring. Here, the study reports a magnetic microrobot platform (MMP) that integrates high-capacity drug loading, magnetically actuated collective navigation, controlled drug release, and real-time 3D optoacoustic imaging in a single system. The MMP exploits synergistic advantages by embedding hard-magnetic FePt nanoparticles in a degradable ZIF-8 shell, achieving a drug loading efficiency of ≈93.9% and enabling precise release in response to pH changes and radiofrequency-induced heating. Reconfigurable swarm behavior strategies significantly enhance the navigation efficiency of microrobots against physiological blood flows within complex cerebral vasculature. The ex vivo and in vivo experiments further demonstrate strong contrast characteristics of the microrobots, enabling high-resolution visualization of deep vascular structures and dynamic tracking of MMP with real-time 3D optoacoustic imaging. This multifunctional strategy paves the way for clinical translation and precision therapy in complex biological settings.
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Physical Intelligence Article Emergent Motility of Self-Organized Particle-Giant Unilamellar Vesicle Assembly Karaz, S., Gardi, G., Han, M., Baltaci, S. F., Akolpoglu, M. B., Sitti, M. Advanced Materials, xx:e12036, October 2025 (Published)
Giant unilamellar vesicles (GUVs), soft cell-sized compartments formed through the self-assembly of lipid molecules, have long been utilized as model systems and passive carriers in membrane biophysics and biomedical applications. However, their potential as dynamically responsive and motile systems remains largely untapped due to challenges in achieving controlled and sustained motion in soft, deformable structures. Here, an autonomous cell-like microrobot through the emergent self-assembly of GUVs (5-10 µm) and silica microparticles (1-3 µm) under alternating current electric fields is realized. Self-propulsion arises from asymmetric self-organization of the particles on the vesicle surface, enabling a reversible transformation of the assembly into an active structure. Unlike rigid colloidal systems, GUVs introduce unique features enabled by their soft lipid membranes: shape deformations, membrane tension-dependent motility, and field-triggered live bacteria release via vesicle bursting. Through experiments and simulations, the mechanisms underlying self-assembly and propulsion are investigated, and a dynamic phase diagram is constructed to map the motion regime as a function of field parameters. Finally, it is shown that these self-assembled structures are capable of reconfiguration in response to local constraints in the environment, suggesting potential applications in complex environments and advancing the potential of GUVs toward the rational design of cell-like microrobots or artificial cell systems.
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Physical Intelligence Article Wireless nonresonant stimulation of neurons on a magnetoelectric film surface Aydin, A., Jahanshahi, A., Esmaeili-Dokht, P., Han, M., Gardi, G., Yu, Y., Soon, R. H., Temel, Y., Sitti, M. Science advances, 11:eadx6829, October 2025 (Published)
Wireless neural interfaces are emerging as a minimally invasive treatment option for neurological disorders. Among the wireless technologies, magnetically powered systems are effective for targeting deep brain sites. However, dependence on high-frequency electromagnetic fields in such systems limits their safe implementation. In this study, we demonstrate the use of millimeter-scale magnetoelectric (ME) films as a direct neural interface for wireless neurostimulation, powered by static and alternating magnetic fields in the nonresonant regime (10 hertz). To accomplish this objective, electrical potential trends of the ME films under varying low-frequency magnetic fields are investigated and used to demonstrate neural stimulation by calcium imaging on primary neurons in vitro via a capacitive-like charge injection mechanism. In addition, electrical polarization orientation is revealed as a critical design parameter in direct neuron-ME interfaces. These findings collectively demonstrate the potential of nonresonant powering of ME films as a promising minimally invasive wireless neural stimulation technique.
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Empirical Inference Article In silico biological discovery with large perturbation models Miladinovic*, D., Höppe*, T., Chevalley, M., Georgiou, A., Stuart, L., Mehrjou, A., Bantscheff, M., Schölkopf, B., Schwab, P. Nature Computational Science, October 2025, *equal contribution (Published)
Data generated in perturbation experiments link perturbations to the changes they elicit and therefore contain information relevant to numerous biological discovery tasks—from understanding the relationships between biological entities to developing therapeutics. However, these data encompass diverse perturbations and readouts, and the complex dependence of experimental outcomes on their biological context makes it challenging to integrate insights across experiments. Here we present the large perturbation model (LPM), a deep-learning model that integrates multiple, heterogeneous perturbation experiments by representing perturbation, readout and context as disentangled dimensions. LPM outperforms existing methods across multiple biological discovery tasks, including in predicting post-perturbation transcriptomes of unseen experiments, identifying shared molecular mechanisms of action between chemical and genetic perturbations, and facilitating the inference of gene–gene interaction networks. LPM learns meaningful joint representations of perturbations, readouts and contexts, enables the study of biological relationships in silico and could considerably accelerate the derivation of insights from pooled perturbation experiments.
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Robotic Composites and Compositions Article Jamming with magnetic composites Aktaş, B., Kim, M., Baeckert, M., Sicilia, G., Franchini, G., Heemeyer, F., Gervasoni, S., Chen, X., Pane, S., Nelson, B. Nature Communications, 16:8711, September 2025 (Published)
The jamming transition—marked by dramatic changes in mechanical properties, such as stiffness and damping—enables programmable and adaptive structures for robotic applications. This phenomenon, driven by changes in the coupling between individual subunits of an aggregate, can be controlled through external actuation sources. Existing jamming actuation methods, such as applying a vacuum with an airtight envelope, pose significant limitations, as they require the structures to be tethered, limiting reconfigurability and scalability. Here, we introduce an untethered jamming mechanism based on magnetic interactions between soft-ferromagnetic composites. We establish composite design principles to program the magnetization of the subunits, demonstrate linear, planar, and volumetric jamming and shape-locking, and model the magneto-mechanical behavior. This approach contributes to the development of jamming-based materials in which the jamming directions and transition points can be tuned on-the-fly by adjusting the external magnetic field orientation and strength, respectively.
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Organizational Leadership and Diversity Article Inclusive avatars in the Metaverse: learning from the lived experiences of people with disabilities Angerbauer, K., Van Wagoner, H. P., Keplinger, K., Halach, T., Vogelsang, J., Hube, N., Smith, A., Sedlmair, M. The Journal of Strategic Information Systems, 34:101935, September 2025 (Published)
Immersive platforms like the Metaverse have gained attention in information systems (IS) research, yet the diverse needs of people with disabilities (PWD) remain underexplored. This research examines the experiences of PWD using inclusive avatars that represent disabilities. Through an exploratory mixed-methods approach, combining qualitative interviews with an experience sampling study, we develop a framework informed by Affective Events Theory and voices of PWD to better understand how social interactions in the Metaverse impact PWD’s emotions and outcomes. Findings suggest that when PWD use inclusive avatars, inclusive and exclusionary social interactions shape their emotional responses, which in turn influence engagement, avatar connection and satisfaction, and perceptions of inclusion in the Metaverse. Although adopting inclusive avatars can be challenging, especially in the face of exclusionary interactions, the benefits can outweigh the costs. The role of disability identity is critical; PWD who identify strongly with their disability experience less negative emotional impact from exclusion. This research contributes to IS literature by conceptualizing the Metaverse as a relational, emotion-driven environment shaped by social interactions as well as a platform for authentic self-representation. Practical implications include supporting avatar-based disability representation, involving PWD in co-designing virtual reality technologies, and providing training to foster inclusive interactions in the Metaverse. These strategies can help organizations build more inclusive and engaging digital workplaces for an often underrepresented workforce segment.
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Physical Intelligence Article Mixed-length multivariate covalent organic framework for combined near-infrared photodynamic therapy and drug delivery Rodrı́guez-Camargo, A., Yildiz, E., Juela, D., Fischer, F. R., Graf, D., Rath, B. B., Ochsenfeld, C., Bauer, M., Sitti, M., Yao, L., Lotsch, B. Journal of the American Chemical Society, 147:33472-33481, September 2025 (Published)
Covalent organic frameworks (COFs) have been emerging as versatile reticular materials due to their tunable structures and functionalities, enabled by precise molecular engineering at the atomic level. While the integration of multiple components into COFs has substantially expanded their structural complexity, the strategic engineering of diverse functionalities within a single framework via the random distribution of linkers with varying lengths remains largely unexplored. Here, we report a series of highly crystalline mixed-length multivariate COFs synthesized using azobenzene and bipyridine as linkers, where tuning the ratio of linkers and incorporating palladium effectively modulates the balance between near-infrared (NIR) light absorption and catalytic sites for NIR-generation of hydrogen peroxide (H2O2). Capitalizing on the deep tissue penetration of NIR light and the generated H2O2 as reactive oxygen species, as a proof of concept, the optimal mixed-length multivariate COF reduces breast cancer cell viability by almost 90% after 1 h of irradiation in a combined in vitro photodynamic therapy and drug delivery.
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Physical Intelligence Article Real-time in situ magnetization reprogramming for soft robotics Bao, X., Wang, F., Zhang, J., Li, M., Zhang, S., Ren, Z., Liao, J., Yan, Y., Kang, W., Zhang, R., Sitti, M. Nature, 645:375–384, August 2025 (Published)
Magnetic soft robots offer considerable potential across various scenarios, such as biomedical applications and industrial tasks, because of their shape programmability and reconfigurability, safe interaction and biocompatibility1,2,3,4. Despite recent advances, magnetic soft robots are still limited by the difficulties in reprogramming their required magnetization profiles in real time on the spot (in situ), which is essential for performing multiple functions or executing diverse tasks5,6. Here we introduce a method for real-time in situ magnetization reprogramming that enables the rearrangement and recombination of magnetic units to achieve diverse magnetization profiles. We explore the applications of this method in structures of varying dimensions, from one-dimensional tubes to three-dimensional frameworks, showcasing a diverse and expanded range of configurations and their deformations. This method also demonstrates versatility in diverse scenarios, including navigating around objects without undesired contact, reprogramming cilia arrays, managing multiple instruments cooperatively or independently under the same magnetic field, and manipulating objects of various shapes. These abilities extend the range of applications for magnetic actuation technologies. Furthermore, this method frees magnetic soft robots from the sole reliance on external magnetic fields for shape change, facilitating unprecedented modes and varieties of deformation while simultaneously reducing the need for complex magnetic field generation systems, thereby opening avenues for the development of magnetic actuation technologies.
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Social Foundations of Computation Algorithms and Society Article Performative Prediction: Past and Future Hardt, M., Mendler-Dünner, C. Statistical Science, Institute of Mathematical Statistics, August 2025 (Published)
Predictions in the social world generally influence the target of prediction, a phenomenon known as performativity. Self-fulfilling and self-negating predictions are examples of performativity. Of fundamental importance to economics, finance, and the social sciences, the notion has been absent from the development of machine learning. In machine learning applications, performativity often surfaces as distribution shift. A predictive model deployed on a digital platform, for example, influences consumption and thereby changes the data-generating distribution. We survey the recently founded area of performative prediction that provides a definition and conceptual framework to study performativity in machine learning. A consequence of performative prediction is a natural equilibrium notion that gives rise to new optimization challenges. Another consequence is a distinction between learning and steering, two mechanisms at play in performative prediction. The notion of steering is in turn intimately related to questions of power in digital markets. We review the notion of performative power that gives an answer to the question how much a platform can steer participants through its predictions. We end on a discussion of future directions, such as the role that performativity plays in contesting algorithmic systems.
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Materials Article Sensitivity Enhancement of a Micro Ring Resonator-Based Photonic Sensor by Using a Gelatin Methacryloyl Functional Coating for the Detection of Metoprolol Tsianaka, A., Schweikert, C., Southan, A., Hoppe, N., Greul, M., Kaschel, M., Vogel, W., Berroth, M., Rademacher, G., Tovar, G. E. M. ACS Applied Optical Materials, 3(7):1556-1566, July 2025 (Published)
Aquatic environments are often contaminated with biopersistent pharmaceuticals, such as the β-blocker metoprolol. The quantitative determination of such pollutants is crucial for environmental monitoring. Therefore, a highly sensitive integrated photonic biosensor for the detection of minute concentrations of metoprolol is presented here. The sensor is based on a thermally robust ring resonator with a hydrogel coating for metoprolol adsorption. Hydrogels consisting of gelatin methacryloyl enabled an increase in the concentration of metoprolol ions in the vicinity of the photonic chip, resulting in high sensitivity of the sensor setup. Compared to an uncoated chip, an increase in sensitivity of up to a factor of 20 was observed. In combination with software-implemented signal processing, the setup showed a detection limit of less than 1 × 10–4 μmol mL–1. The combination of functional coating, thermally insensitive design, and applied digital signal postprocessing makes the system introduced here an attractive approach toward sensor-based wastewater analysis and monitoring.
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Physical Intelligence Article Bacterial Minicell-Based Biohybrid Sub-micron Swimmers for Targeted Cargo Delivery Saadet Fatma Baltaci, M. B. A. I. K. V. S. M. S. Advanced Science, 12:e05538, June 2025 (Published)
Bacterial biohybrid microrobots possess significant potential for targeted cargo delivery and minimally invasive therapy. However, many challenges, such as biocompatibility, stability, and effective cargo loading, remain. Bacterial membrane vesicles, also referred to as minicells, offer a promising alternative for creating sub-micron scale biohybrid swimmers (minicell biohybrids) due to their active metabolism, non-dividing nature, robust structure, and high cargo-carrying capacity. Here, a biohybrid system is reported that utilizes motile minicells, ≈400 nm in diameter, generated by aberrant cell division of engineered Escherichia coli (E. coli), for the first time. Achieving over 99% purification from their parental bacterial cells, minicells are functionalized with magnetic nanoparticles (MNPs) to enable external magnetic control. Minicell biohybrids are capable of swimming at an average speed of up to 13.3 µm s−1 and being steered under a uniform magnetic field of 26 mT. Furthermore, they exhibit a significantly high drug loading capacity (2.8 µg mL−1) while maintaining their motility and show pH-sensitive release of anticancer drug doxorubicin hydrochloride (DOX) under acidic conditions. Additionally, drug-loaded minicell biohybrids notably reduce the viability of SK-BR-3 breast cancer cells in vitro. This study introduces minicell biohybrids and establishes their potential as magnetically guided, drug-loaded biohybrid systems for targeted therapies in future medical applications.
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Locomotion in Biorobotic and Somatic Systems Article Scaly-tail organ enhances static stability during Pel’s scaly-tailed flying squirrels’ arboreal locomotion Schulz, A. K., Chellapurath, M., Khandelwal, P. C., Rezaei, S., Merker, S., Jusufi, A. Journal of The Royal Society Interface, 22(227), Royal Society, London, June 2025 (Published) DOI URL BibTeX
Physical Intelligence Article Magnetically Controllable and Degradable Milliscale Swimmers as Intraocular Drug Implants Yildiz, E., Bozuyuk, U., Yildiz, E., Wang, F., Han, M., Karacakol, A. C., Sheehan, D., Yu, Y., Sitti, M. Advanced Science, 12:e07569, June 2025 (Published)
Intraocular drug implants are increasingly used for retinal treatments, such as age-related macular degeneration and diabetic macular edema, due to the rapidly aging global population. Although these therapies show promise in arresting disease progression and improving vision, intraocular implant-based therapies can cause unexpected complications that require further surgery due to implant dislocation or uncontrolled drug release. These frequent complications of intraocular drug implants can be overcome using magnetically controllable degradable milliscale swimmers (MDMS) with a double-helix body morphology. A biodegradable hydrogel, polyethylene glycol diacrylate, is employed as the primary 3D printing material of MDMS, and it is magnetized by decorating it with biocompatible polydopamine-encapsulated iron-platinum nanoparticles. MDMS have comparable dimensions to commercial intraocular implants that achieve translational motions in both aqueous and vitreous bodies. They can be imaged in real-time using optical coherence tomography, ultrasound, and photoacoustic imaging. Thanks to their biodegradable hydrogel-based structure, they can be loaded with anti-inflammatory drug molecules and release the medications without disrupting retinal epithelial viability and barrier function, and decrease proinflammatory cytokine release significantly. These magnetically controllable swimmers, which degrade in a couple of months, can be used for less invasive and more precise intraocular drug delivery compared to commercial intraocular drug implants.
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Physical Intelligence Article Surface Rolling Active Magnetic Emulsions Khan, M. T. A., Gardi, G., Bozuyuk, U., Sitti, M. Advanced Science, 12, June 2025 (Published) DOI BibTeX
Empirical Inference Article Flow annealed importance sampling bootstrap meets differentiable particle physics Kofler, A., Stimper, V., Mikhasenko, M., Kagan, M., Heinrich, L. Machine Learning: Science and Technology, 6(2), IOP Publishing, June 2025 (Published)
High-energy physics requires the generation of large numbers of simulated data samples from complex but analytically tractable distributions called matrix elements. Surrogate models, such as normalizing flows, are gaining popularity for this task due to their computational efficiency. We adopt an approach based on Flow Annealed importance sampling Bootstrap (FAB) that evaluates the differentiable target density during training and helps avoid the costly generation of training data in advance. We show that FAB reaches higher sampling efficiency with fewer target evaluations in high dimensions in comparison to other methods.
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Haptic Intelligence Robotic Materials Article Wearable Electrohydraulic Actuation for Salient Full-Fingertip Haptic Feedback Shao, Y., Shagan Shomron, A., Javot, B., Keplinger, C., Kuchenbecker, K. J. Advanced Materials Technologies, 10(12):2401525, June 2025, Yitian Shao and Alona Shagan Shomron contributed equally to this publication. This article was selected for the front cover. https://doi.org/10.1002/admt.202570062 (Published)
Although essential for an immersive experience in extended reality (XR), providing salient and versatile touch feedback remains a technical challenge. Existing solutions restrict hand movements with bulky rigid structures, require a tethered energy source to power actuators worn on the hand, or output vibrations that lack expressiveness. This study introduces a design strategy for compact, lightweight, untethered haptic feedback centering on a 30-µm-thick inflatable chamber that naturally conforms to the fingertip; to minimize fluidic losses and enable high bandwidth, a soft electrohydraulic pump mounted on the hand actuates the chamber via a mechanically transparent fluidic channel. A 15.2-mm-diameter prototypical actuation chamber achieves 8 N peak force, 3 N steady-state force, stroke up to 5 mm, and bandwidth from 0 to 500 Hz. In contrast to these salient fingertip cues, the entire hydraulic system has a weight less than 8 g and a thickness less than 2 mm. Additionally, this study presents a validation approach that uses a commercial fingertip sensor to confirm that the haptic feedback created by the device imitates the touch signals generated during typical hand interactions. Together, this design strategy and validation method can enable a broad spectrum of haptic activities in diverse XR applications, including medical training, online shopping, and social interactions.
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Physical Intelligence Article 3D Locomotion of Surface-Rolling Microrobots: A Trade-off between Hydrodynamic Wall and Gravitational Effects Park, M., Bozuyuk, U., Yildiz, E., Min, H., Yoon, J., Sitti, M. Advanced Intelligent Systems, 7:2500381, May 2025 (Published)
Synthetic microrobots have gained significant attention due to their potential in various applications in biomedicine and lab-on-a-chip technologies. As a fundamental requirement, microrobots must navigate in 3D, effectively counteracting gravity to execute their tasks. However, locomotion at small scales presents numerous counterintuitive behaviors, primarily governed by the interactions between the microrobot's body and its surrounding boundaries. In this study, the locomotion of surface-rolling microrobots is investigated in 3D, particularly focusing on their ability to climb walls. Through a combination of experiments and computational fluid dynamics analyzes, it is demonstrated that the influence of gravity plays a secondary role in enabling surface-rolling microrobots to climb walls. Instead, locomotion capability in 3D settings is primarily determined by interactions with surrounding boundaries. The fundamental principles of surface-rolling locomotion in 3D spaces is elucidated and a design strategy aimed at optimizing fluid flow for efficient propulsion in future applications is proposed.
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Physical Intelligence Article Anisotropic Surface Microrollers for Endovascular Navigation: A Computational Analysis with a Case Study in Hepatic Perfusion Arslan, B., Bozuyuk, U., Görgülü, K., Yildiz, E., Ozturk, H., Liotta, L., Heinemann, V., Algül, H., Sitti, M. Advanced Theory and Simulations, 8:2400387, May 2025 (Published)
Magnetic surface microrollers have demonstrated promise as active drug delivery agents for targeted and minimally invasive disease treatment. Specifically, it can be employed in the circulatory system to locally release therapeutic agents at disease sites, minimizing systemic exposure and reducing side effects, particularly in the treatment of diseases like cancer. Previous research indicates that the design and shape of microrollers play a crucial role in safe navigation within blood vessels, with anisotropic microrollers exhibiting superiority due to favorable hydrodynamic interactions with nearby boundaries. In this study, the navigation potential of anisotropic microrollers is investigated in veins, venules, and capillaries through computational fluid dynamics analyses. These results indicate that robust locomotion is only achievable in larger vessels, such as veins. Subsequently, their performance is explored in a clinically relevant scenario – the hepatic circulation toward treating primary liver cancer or metastatic nodes of distant tumors (e.g., pancreatic cancer). Computational fluid dynamics analyses using the data from five different patients demonstrate that robust navigation can be achieved with high actuation frequencies. Overall, the findings presented in this study lay a preliminary foundation for the potential future application of surface microrollers in vivo.
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Haptic Intelligence Article Comparing Puncture-Detection Approaches for Manual Needle Insertions Through the Parietal Pleura L’Orsa, R., Zareinia, K., Sutherland, G. R., Westwick, D., Kuchenbecker, K. J. IEEE Transactions on Medical Robotics and Bionics, 7(2):455-468, May 2025 (Published)
Tube thoracostomy (chest tube insertion) is a surgical procedure that treats pneumothorax, a potentially life-threatening condition where air accumulates between the chest wall and the lungs. The literature reports high complication rates for this procedure, including accidental fatality due to poor manual depth control during tool insertion. We hypothesize that an instrumented needle-holder could help operators recognize pleural puncture and improve depth control, and we present a puncture-detection experiment that contributes toward this goal. An operator manually inserted a bevel-tip needle into ex vivo porcine ribs and through the parietal pleura via a sensorized percutaneous device that records position, force, and videos. We use this rich dataset of 63 insertions to thoroughly test four previously published data-driven puncture-detection (DDPD) algorithms against two new real-time algorithms: a custom recursive digital filter with coefficients optimized for our application, and a difference equation that compares standard deviations between adjacent sliding windows. Our algorithms achieve a precision (true positives over total identified punctures) of 23% and 22%, respectively, while the precision of existing DDPD algorithms ranges from 0% to 21%. Despite these performance improvements, our results show the limitations of DDPD algorithms and motivate new methods for detecting pleural membrane punctures in thoracostomy.
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Haptic Intelligence Article Enhancing Needle Puncture Detection Using High-Pass Filtering and Diffuse Reflectance L’Orsa, R., Bisht, A., Yu, L., Murari, K., Sutherland, G. R., Westwick, D. T., Kuchenbecker, K. J. Frontiers in Robotics and AI, 12(1429327):1-16, May 2025 (Published)
Chest trauma or disease progression can lead to tension pneumothorax, a condition where mounting pressurization of the pleural cavity (the space between the chest wall and the lungs) leads rapidly to cardiac arrest. In pre-hospital settings, tension pneumothorax is treated by venting the pleural cavity via a needle introduced through the chest wall. Very high failure rates (up to 94.1%) have been reported for pre-hospital needle decompression, however, and the procedure can result in the accidental puncture of critical thoracic tissues because it is performed blind. Instrumented needles could help operators more reliably identify when the tool has entered the target space. This paper investigates technical approaches to provide such support; we created an experimental system that acquires needle force and position signals, as well as the diffuse backscattered reflectance from white light carried to and collected from the needle's tip via two in-bore optical fibers. Data collection occurred while two experimenters inserted a bevel-tipped percutaneous needle into an ex vivo porcine rib section simulating human chest anatomy. Four data-driven puncture-detection (DDPD) algorithms from the literature, which are appropriate for use with the variable tool velocities produced by manual insertions, were applied to the resulting data set offline. Grid search was performed across key signal-processing parameters, high-pass filters (HPFs) were applied to examine their impact on puncture detection, and a first exploration of multimodal (ensemble) methods was performed. Combining high-pass filters with DDPD methods resulted in a 2.7-fold improvement (from 8.2% to 21.9%) in the maximum overall precision (MOP) produced by force signals. Applying this HPF + DDPD scheme to reflectance data streams yielded a peak MOP of 36.4%, and combining reflectance with force generated the best MOP overall (42.1%); these results represent 4.4-fold and 5.1-fold improvements, respectively, over the best MOP produced by the traditional application of DDPD algorithms to force signals alone. These results strongly support the utility of high-pass filters combined with both reflectance-only and multimodal reflectance-plus-force data-driven puncture-detection schemes for needle decompression applications.
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Physical Intelligence Article Navigating microalgal biohybrids through confinements with magnetic guidance Akolpoglu, M. B., Baltaci, S. F., Bozuyuk, U., Karaz, S., Sitti, M. Matter, 8:102052, April 2025 (Published)
In the natural world, microorganisms constantly navigate through confined spaces—such as those found in tissues, biological gels, and soil—yet their behavior in such environments remains poorly understood. Here, we explore this phenomenon by examining the navigation of magnetic microalgal biohybrids in constrained microenvironments. By leveraging the inherent propulsion of green microalgae and external steering capabilities acquired through the magnetization of microalgal cells, our biohybrids exhibit efficient navigation in viscous and confined microenvironments. Through high-yield fabrication and magnetic manipulation, we show precise control over their movement. Our findings reveal distinct navigation patterns influenced by magnetic guidance, namely backtracking and crossing, shedding light on the unexplored dynamics of confined locomotion assisted by magnetism. Our work highlights the significance of understanding microalgal biohybrid swimming behavior, offering crucial insights for future biotechnological and biomedical applications requiring precise navigation in confined environments.
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Haptic Intelligence Robotics Article Building Instructions You Can Feel: Edge-Changing Haptic Devices for Digitally Guided Construction Tashiro, N., Faulkner, R., Melnyk, S., Rosales Rodriguez, T., Javot, B., Tahouni, Y., Cheng, T., Wood, D., Menges, A., Kuchenbecker, K. J. ACM Transactions on Computer-Human Interaction, 32(1):1-40, April 2025 (Published)
Recent efforts to connect builders to digital designs during construction have primarily focused on visual augmented reality, which requires accurate registration and specific lighting, and which could prevent a user from noticing safety hazards. Haptic interfaces, on the other hand, can convey physical design parameters through tangible local cues that don't distract from the surroundings. We propose two edge-changing haptic devices that use small inertial measurement units (IMUs) and linear actuators to guide users to perform construction tasks in real time: Drangle gives feedback for angling a drill relative to gravity, and Brangle assists with orienting bricks in the plane. We conducted a study with 18 participants to evaluate user performance and gather qualitative feedback. All users understood the edge-changing cues from both devices with minimal training. Drilling holes with Drangle was somewhat less accurate but much faster and easier than with a mechanical guide; 89% of participants preferred Drangle over the mechanical guide. Users generally understood Brangle's feedback but found its hand-size-specific grip, palmar contact, and attractive tactile cues less intuitive than Drangle's generalized form factor, fingertip contact, and repulsive cues. After summarizing design considerations, we propose application scenarios and speculate how such devices could improve construction workflows.
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Haptic Intelligence Article Simulation Training with Haptic Feedback of Instrument Vibrations Reduces Resident Workload During Live Robot-Assisted Sleeve Gastrectomy Gomez, E. D., Mat Husin, H., Dumon, K. R., Williams, N. N., Kuchenbecker, K. J. Surgical Endoscopy, 39(3):1523-1535, April 2025 (Published)
Background: New surgeons experience heavy workload during robot-assisted surgery partially because they must use vision to compensate for the lack of haptic feedback. We hypothesize that providing realistic haptic feedback during dry-lab simulation training may accelerate learning and reduce workload during subsequent surgery on patients. Methods: We conducted a single-blinded study with twelve general surgery residents (third and seventh post-graduate year, PGY) randomized into haptic and control groups. Participants performed five simulated bariatric surgeries on a custom inanimate simulator followed by live robot-assisted sleeve gastrectomies (RASGs) using da Vinci robots. The haptic group received naturalistic haptic feedback of instrument vibrations during their first four simulated procedures. Participants completed pre-/post-procedure STAI and post-procedure NASA-TLX questionnaires in both simulation and the operating room (OR). Results: Higher PGY level (simulation: p<0.001, OR p=0.004), shorter operative time (simulation: p<0.001, OR: p=0.003), and lower pre-procedure STAI (simulation: p=0.003, OR: p<0.001) were significantly associated with lower self-reported overall workload in both operative settings; PGY-7s reported about 10% lower workload than PGY-3s. The haptic group had significantly lower overall covariate-adjusted NASA-TLX during the fourth (p=0.03) and fifth (p=0.04) simulated procedures and across all OR procedures (p=0.047), though not for only the first three OR procedures. Haptic feedback reduced physical demand (simulation: p<0.001, OR: p=0.001) and increased perceived performance (simulation: p=0.031, OR: p<0.001) in both settings. Conclusion: Haptic feedback of instrument vibrations provided during robotic surgical simulation reduces trainee workload during both simulation and live OR cases. The implications of workload reduction and its potential effects on patient safety warrant further investigation.
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Empirical Inference Article The Fiction Machine Bottou, L., Schölkopf, B. SIAM News, 58(3), April 2025 (Published) URL BibTeX
Haptic Intelligence Perceiving Systems Article Wrist-to-Wrist Bioimpedance Can Reliably Detect Discrete Self-Touch Forte, M., Vardar, Y., Javot, B., Kuchenbecker, K. J. IEEE Transactions on Instrumentation and Measurement, 74(4006511):1-11, April 2025 (Published)
Self-touch is crucial in human communication, psychology, and disease transmission, yet existing methods for detecting self-touch are often invasive or limited in scope. This study systematically investigates the feasibility of using non-invasive electrical bioimpedance for detecting discrete self-touch poses across individuals. While previous research has focused on classifying defined self-touch poses, our work explores how various poses cause bioimpedance changes, providing insights into the underlying physiological mechanisms. We thus created a dataset of 27 genuine self-touch poses, including skin-to-skin contact between the hands and face and skin-to-clothing contact between the hands and chest, alongside six adversarial mid-air gestures. We then measured the wrist-to-wrist bioimpedance of 30 adults (15 female, 15 male) across these poses, with each measurement preceded by a no-touch pose serving as a baseline. Statistical analysis of the measurements showed that skin-to-skin contacts cause significant changes in bioimpedance magnitude between 237.8 kHz and 4.1 MHz, while adversarial gestures do not; skin-to-clothing contacts cause less-significant changes due to the influence and variability of the clothing material. Furthermore, our analysis highlights the sensitivity of bioimpedance to the body parts involved, skin contact area, and individual's characteristics. Our contributions are two-fold: (1) we demonstrate that bioimpedance offers a practical, non-invasive solution for detecting self-touch poses involving skin-to-skin contact, (2) researchers can leverage insights from our study to determine whether a pose can be detected without extensive testing.
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Robotic Materials Article A robotic and virtual testing platform highlighting the promise of soft wearable actuators for wrist tremor suppression Shagan Shomron, A., Chase-Markopoulou, C., Walter, J. R., Sellhorn-Timm, J., Shao, Y., Nadler, T., Benson, A., Wochner, I., Rumley, E. H., Wurster, I., Klocke, P., Weiss, D., Schmitt, S., Keplinger, C., Haeufle, D. F. Device, 3:100719, March 2025 (Published)
Nearly 80 million people in the world deal with medical conditions that cause involuntary periodic movements known as tremors. Wearable soft robotic devices offer a potential solution for actively suppressing these tremors. However, existing prototypes face limitations in actuation performance and complex testing procedures. We present a comprehensive approach for the rapid evaluation of emerging wearable tremor-suppression technologies. This method combines reproducing patient-recorded tremor episodes and measuring tremor suppression in a robotic platform, termed a "mechanical patient", with validation of the achieved suppression performance of soft actuators via biomechanical modeling, thereby avoiding time-consuming clinical testing in the early stages of development. Using this approach, we highlight that an antagonistic pair of slim and lightweight electrohydraulic actuators can effectively …
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Haptic Intelligence Article A Sleeve Alters the Pressure-Stretch Curve of a Hyperelastic Balloon to Enable Pre-Programmed Sequencing Gertler, I., Kuchenbecker, K. J. Advanced Materials Technologies, 10(6):2400993, March 2025 (Published)
Coupled hyperelastic balloons that anchor alternately against a lumen wall provide an appealing locomotion method for soft robots, especially for pipe inspection and medical interventions. However, it is still challenging to use a single fluid channel to obtain a practical balloon actuation sequence, where the rear anchor is both the first to inflate and the first to deflate. The common solution delays the front balloon's reaction using fluid dynamics, producing a slow and/or bulky system. This study presents a new method that utilizes an inextensible sleeve along with geometry and mechanical properties to set the pressure-stretch curve of two silicone-rubber balloons so they could serve as the rear and front anchors when driven from a single fluid supply. Experimental measurements and numerical simulations compare the characteristic curves of thin and thick spherical balloons with identical diameters to that of a thin balloon inside a rigid encasing sleeve that delays its initial expansion. Pairing this encased thin balloon with a non-encased thick balloon yields the desired asymmetric actuation sequence. A physical demonstration of the behavior needed for self-propelling robots is achieved by placing such balloons within rigid tubes, connecting them to a shared supply, and sequentially adding and removing fluid.
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Empirical Inference Article Early warning of complex climate risk with integrated artificial intelligence Reichstein, M., Benson, V., Blunk, J., Camps-Valls, G., Creutzig, F., Fearnley, C. J., Han, B., Kornhuber, K., Rahaman, N., Schölkopf, B., Tárraga, J. M., Vinuesa, R., Dall, K., Denzler, J., Frank, D., Martini, G., Nganga, N., Maddix, D. C., Weldemariam, K. Nature Communications, 16(1), March 2025 (Published) DOI BibTeX
Empirical Inference Article Real-time inference for binary neutron star mergers using machine learning Dax, M., Green, S. R., Gair, J., Gupte, N., Pürrer, M., Raymond, V., Wildberger, J., Macke, J. H., Buonanno, A., Schölkopf, B. Nature, 639(8053):49-53, March 2025 (Published) DOI URL BibTeX
Biomimetic Materials and Machines Article Highly agile flat swimming robot Hartmann, F., Baskaran, M., Raynaud, G., Benbedda, M., Mulleners, K., Shea, H. February 2025 (Published) BibTeX
Rationality Enhancement Article Evaluating the Effectiveness of the InsightApp: A Longitudinal Randomized Controlled Trial on Anxiety, Valued Action, and Psychological Resilience Amo, V., Lieder, F. JMIR Mental Health, 12:e57201, February 2025 (Published)
Background: Anxiety disorders are among the most prevalent mental disorders, and stress plays a significant role in their development. Ecological momentary interventions (EMIs) hold great potential to help people manage stress and anxiety by training emotion regulation and coping skills in real-life settings. InsightApp is a gamified EMI and research tool that incorporates elements from evidence-based therapeutic approaches. It is designed to strengthen people’s metacognitive skills for coping with challenging real-life situations and embracing anxiety and other emotions. Objective: This randomized controlled trial aims to examine the effectiveness of InsightApp in (1) improving individuals’ metacognitive strategies for coping with stress and anxiety and (2) promoting value-congruent action. It also evaluates how long these effects are retained. This experiment advances our understanding of the role of metacognition in emotional and behavioral reactivity to stress. Methods: We conducted a randomized controlled trial with 228 participants (completion rate: n=197, 86.4%; mean age 38, SD 11.50 years; age range 20-80 years; female: n=101, 52.6%; and White: n=175, 91.1%), who were randomly assigned to either the treatment or the active placebo control group. During the 1-week intervention phase, the treatment group engaged with InsightApp, while participants in the control group interacted with a placebo version of the app that delivered executive function training. We assessed the differences between the 2 groups in posttest and follow-up assessments of mental health and well-being while controlling for preexisting differences. Moreover, we used a multilevel model to analyze the longitudinal data, focusing on the within-participant causal effects of the intervention on emotional and behavioral reactivity to daily stressors. Specifically, we measured daily anxiety, struggle with anxiety, and value-congruent action. Results: The intervention delivered by InsightApp yielded mixed results. On one hand, we found no significant posttest scores on mental health and well-being measures directly after the intervention or 7 days later (all P>.22). In contrast, when confronted with real-life stress, the treatment group experienced a 15% lower increase in anxiety (1-tailed t test, t197=–2.4; P=.009) and a 12% lower increase in the struggle with anxiety (t197=–1.87; P=.031) than the control group. Furthermore, individuals in the treatment group demonstrated a 7% higher tendency to align their actions with their values compared to the control group (t197=3.23; P=.002). After the intervention period, InsightApp’s positive effects on the struggle with anxiety in reaction to stress were sustained, and increased to an 18% lower reactivity to stress (t197=–2.84; P=.002). Conclusions: As our study yielded mixed results, further studies are needed to obtain an accurate and reliable understanding of the effectiveness of InsightApp. Overall, our findings tentatively suggest that guiding people to apply adaptive metacognitive strategies for coping with real-life stress daily with a gamified EMI is a promising approach that deserves further evaluation.
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Empirical Inference Article Artificial intelligence for modelling infectious disease epidemics Kraemer, M. U. G., Tsui, J. L., Chang, S. Y., Lytras, S., Khurana, M. P., Vanderslott, S., Bajaj, S., Scheidwasser, N., Curran-Sebastian, J. L., Semenova, E., Zhang, M., Unwin, H. J. T., Watson, O. J., Mills, C., Dasgupta, A., Ferretti, L., Scarpino, S. V., Koua, E., Morgan, O., Tegally, H., et al. Nature, 638(8051):623-635, February 2025 (Published) DOI URL BibTeX
Biomimetic Materials and Machines Article Ecosystem-Centered Robot Design: Toward Ecoresorbable Sustainability Robots (ESRs) Yilmaz, T., Fang, Y., Contreras, C., Schulz, A. K., Hartmann, F. Advanced Science, e09194:1-31, January 2025 (Published)
The deployment of robots and sensors across diverse ecosystems supports ecological monitoring, nature conservation, and exploration. However, retrieving these machines is often impractical or economically infeasible, posing risks to ecosystems through pollution, physical damage, and waste generation. To alleviate these risks, the development of transient systems from biodegradable materials represents a promising solution, enabling them to decompose harmlessly after use. Robots made from soft or functional polymers exhibit a unique potential in solving this challenge by drawing from a wide range of biomaterials, while simultaneously benefiting from intrinsic adaptability. Despite significant progress in the development of sustainable soft robotics, the influence of specific ecosystems on biodegradation is frequently overlooked. The environmental context is essential, as biodegradation depends largely on environmental factors unique to each ecosystem. In this review, a comprehensive overview of various ecosystems relevant to robot deployment is provided, offering critical context for assessing sustainability and deriving principles for ecosystem-centered robot design. Co-developing materials and sustainability robots with an understanding of their operational ecosystems paves the way for environmentally friendly machines, which are named ecoresorbable sustainability robots (ESRs), that coexist harmoniously with nature.
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Dynamic Locomotion Article How knee muscles and ground reaction forces shape knee buckling and ankle push-off in neuromuscular simulations of human walking Buchmann, A., Kiss, B., Badri-Spröwitz, A., Renjewski, D. Scientific Reports, 15:2249, January 2025 (Published)
Ankle push-off is important for efficient, human-like walking, and many prosthetic devices mimic push-off using motors or elastic elements. The knee is extended throughout the stance phase and begins to buckle just before push-off, with timing being crucial. However, the exact mechanisms behind this buckling are still unclear. We use a predictive neuromuscular simulation to investigate whether active muscles are required for knee buckling and to what extent ground reaction forces (GRFs) drive it. In a systematic parameter search, we tested how long the knee muscles vastus (VAS), gastrocnemius (GAS), and hamstrings could be deactivated while maintaining a stable gait with impulsive push-off. VAS deactivation up to 35\% of the gait cycle resulted in a dynamic gait with increased ankle peak power. GAS deactivation up to 20\% of the gait cycle was detrimental to gait efficiency and showed reduced ankle peak power. At the start of knee buckling, the GRF vector is positioned near the knee joint’s neutral axis, assisting in knee flexion. However, this mechanism is likely not enough to drive knee flexion independently. Our findings contribute to the biomechanical understanding of ankle push-off, with applications in prosthetic and bipedal robotic design, and fundamental research on human gait mechanics.
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Materials Article Simultaneous Selective and Quantitative Sensing of Diclofenac and Metoprolol via Electrical Conductance of Two Polyelectrolyte Hydrogels Tsianaka, A., Fichtel, K., Tovar, G. E. M., Southan, A. Advanced Sensor Research, 4(3):2400141, January 2025 (Published)
Hydrogels containing functional groups are highly interesting for sensor applications as they can change their physical properties by interaction with their environment. In this study, it is demonstrated that by monitoring the conductance of two different functional hydrogels, the concentrations of two different drugs in aqueous solution can be selectively and quantitatively measured simultaneously based on non-specific interactions. Detailed characterization of the competitive drug adsorption on the hydrogels allows the description of both hydrogel conductances as a function of the drug concentrations based on physical models. The result is a system of non-linear equations that can be solved for the drug concentrations. The different affinities and conductance responses of the hydrogels for the two drugs is a prerequisite, which is usually achieved with different materials. This approach is demonstrated with hydrogels based on poly(ethylene glycol), functionalized with the ionic monomers [2-(acryloyloxy)ethyl] trimethylammonium chloride (AETA) and 3-sulfopropyl acrylate potassium salt (SPA), and the drugs diclofenac and metoprolol. The hydrogel conductance is found to be linear with drug concentration in the hydrogels, which in turn is described by a non-linear Langmuir-type competitive adsorption isotherm. The proposed approach thus shows potential for future studies on more complex mixtures by including a larger variety of functional hydrogels.
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Empirical Inference Article Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels Gebhard, T. D., Wildberger, J., Dax, M., Kofler, A., Angerhausen, D., Quanz, S., Schölkopf, B. Astronomy \& Astrophysics, 693, January 2025 (Published) DOI URL BibTeX
Deep Models and Optimization Article An accelerated lyapunov function for Polyak’s Heavy-ball on convex quadratics Orvieto, A. Optimization Letters, 19:307-328, 2025 (Published) DOI URL BibTeX
Neuromechanics of Movement Organizational Leadership and Diversity Article Building bridges: allyship as a catalyst for gender diversity and inclusion in experimental biology communities M. Janneke Schwaner, , Keplinger, K. 2025 (Published)
Diversity drives innovation and creativity, directly contributing to scientific excellence. However, achieving equity in academia, including in experimental biology fields such as biomechanics and comparative physiology, remains a significant challenge, with women and other historically marginalized groups underrepresented, especially in more senior roles. When considering gender, the disparity is often linked to difficulties in balancing family responsibilities with demanding careers, along with lower ‘academic visibility’, as evidenced by fewer professional awards for women scientists. Many successful women who balance career and family keep their family lives private, making these aspects invisible to early career scholars, and thus depriving them of role models. To help close the gender gap, in this Perspective, we propose 10 actionable strategies for scholars at all career stages to promote gender diversity and inclusion through active allyship. Although we focus on gender diversity, these strategies can be broadly applied to harness the benefits of other diversity dimensions (e.g. age or ethnicity). We argue that embracing allyship benefits individual scientists, their research groups, the quality of their research, the broader research community and society at large by enhancing collective scientific output and inspiring the next generation of scientists.
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Human Aspects of Machine Learning Article Causal fair metric: Bridging causality, individual fairness, and adversarial robustness Ehyaei, A. R., Farnadi, G., Samadi, S. Transactions on Machine Learning Research, 2025 (Accepted) BibTeX