Researchers developed MOFU, a robot that mimics living organisms' volumetric motion, changing its body volume through expansion and contraction. This design improves human-robot interaction by increasing perceived animacy, as participants rated the robot as more lifelike in experiments.
Scientists at the University of Electro-Communications create a method to map dielectric response at the atomic level, revealing diamond's anomalous enhancement. This discovery could lead to the development of efficient electron sources and smaller electronic components.
Researchers have identified a pathogenic microorganism that invades the gut of stink bugs by masquerading as a symbiotic microorganism, leading to nearly 100% mortality. This discovery could lead to the development of new biological pesticides with high species-specificity and lower environmental impact.
Researchers found that rice stink bugs acquire beneficial symbiotic bacteria from soil and that high soil pH suppresses acquisition. The study reveals that mildly acidic soils facilitate the establishment of symbiosis, providing a potential tool for environmentally sustainable pest control strategies.
A research group developed an edible agent capable of social interaction to explore human-food interactions and psychological acceptance. Participants perceived different behaviors as affecting mind perception and reluctance to eat or guilt, indicating a need for further studies.
Researchers at the University of Electro-Communications have developed a new, cost-effective catalyst using nitrogen-doped graphene that outperforms traditional platinum. This breakthrough enables the creation of high-performance, low-cost fuel cells, bringing mainstream sustainable energy closer to reality.
Researchers developed an AI-based method to create binaural audio from monaural recordings, using visual information from the video to guide spatialization. The system accurately preserves a sense of direction and space, even in complex environments.
Researchers created a framework allowing AI agents to dynamically interrupt and stay silent based on assigned personality traits and urgency scores. This human-like flexibility led to higher accuracy on complex tasks compared to standard models.
Researchers discovered that certain bacteria wrap their rotating flagella around their cell bodies to form a screw thread, allowing them to propel forward through narrow passages. This mechanism enables bacteria to navigate complex environments and even infect host insects.
A new approach uses multiple LLM agents collaborating through iterative interactions to improve AI safety checks, outperforming existing methods in F1-score and achieving better trade-offs between catching harmful and harmless prompts. The system divides work into two teams: generator and analyzer, with logs capturing past mistakes and...
In scalding hot water, bacteria use a unique 'reverse-flow dance' to move upstream, sensing water flow direction. This behavior is common among heat-loving bacterial species with elongated shapes.
The study reveals a local upward dipole moment at adatom sites on Si(111) surfaces, aligning with experimental results. Variations in atomic arrangements significantly influence charge transfer and dipole moments, providing insights for surface probe microscopy images.
A new deep learning approach called HikingTTE significantly improves hiking travel time estimation by considering individual walking ability and fatigue. The model outperformed conventional techniques, reducing Mean Absolute Percentage Error by 12.95 percentage points.
Researchers developed a groundbreaking framework to analyze business process logs and detect potential RBAC violations. The framework provides visualizations of detected violations, significantly reducing manual effort for security audits.
A new AI system has been developed to detect compound-type dark jargons on social media, which are used by offenders to evade detection. The system achieves a 7% improvement in accuracy and identifies 93% of newly detected dark jargons as previously unknown, highlighting its potential to reveal emerging terms.
Researchers developed a shoulder actuation testbed for rehabilitation, integrating pneumatic and electromagnetic forces for high precision and transparency. The system allows for natural-like interaction forces during disturbances, making rehabilitation experiences more natural and effective.
Researchers created an android avatar named Yui with human-like appearance to enable operators to inhabit and improve communication. The system provides a highly immersive experience through advanced head deformation, movement capabilities, and sensory organs.
A groundbreaking study explores how humans perceive and interact with a pneumatically-driven edible robot. The research reveals that the dynamic movement of the robot intensifies perceptions, including emotion, animateness, and guilt, while altering texture experiences during consumption.
Researchers propose a novel method to balance data utility and privacy in IoT devices, minimizing added noise for effective privacy protection. The approach considers inherent errors in measurements, optimizing differential privacy standards.
A team of researchers has introduced a unique method that uses voice data to assist in revealing the covered parts of faces, overcoming challenges to facial recognition systems. Their approach demonstrates significant improvements in recreating critical facial areas like the mouth, nose, and overall face shape.
Researchers developed a new method using Copula models to restore the true statistical model from data processed by Differential Privacy technology, even with many missing values. This enables highly accurate data analysis for pandemic mitigation and various societal applications.
Scientists at the University of Electro-Communications successfully measured the effects of an ultra-high magnetic field on a transition metal oxide, discovering signs of a new magnetic superfluid state. This achievement has significant implications for spintronics technology and potential applications in quantum computing.
BioTCIs, a new class of biomolecular targeted covalent inhibitors, show promise in reducing unwanted side effects. They have semi-permanent drug action and stringent target specificity, making them potential antibody replacements.
Researchers developed an algorithm to extract bouton-like structures from calcium imaging data, identifying synchronized synapses during fictive locomotion. PQ-clustering outperformed other algorithms in mimicking synaptic activity patterns.
A covalent DNA aptamer has been developed to overcome limitations of traditional aptamers in drug use. The semi-permanent inhibition by the aptamer may lead to unexpected side effects or a too-strong medicinal effect.
A new AI system predicts heat transfer coefficients with higher accuracy than existing methods, providing reliable results and uncertainty analysis. The system combines deep learning and Gaussian process regression to tackle the challenges of mini-channel heat transfer.
Researchers found that differential privacy can lead to high re-identification accuracy, even with multiple databases involved. The study suggests that John's unique attribute data can be used to predict the number of citizens with specified values, despite anonymity requirements.
Researchers from The University of Electro-Communications and Tokyo University of Agriculture and Technology found that sintering porous media inside heat transfer tubes increases the area available for heat exchange, reducing thermal resistance and enhancing heat transfer performance. Heat transfer in these tubes is five times greater...