Interdisciplinary teams developing complex technologies such as healthtech struggle to align disciplinary perspectives, stakeholder priorities, and evolving problem framings, particularly during rapid iteration, when existing collaboration tools offer limited support for in-session negotiation. We present KNIT, an AI-mediated framework that conceptualises AI-generated artefacts as computational boundary objects. KNIT supports convergence by externalising anonymised individual inputs into shared artefacts, including semantic clusters and stakeholder-centred problem reframings, that surface differences in interpretation and make them available for negotiation. We evaluated KNIT in workshops with seven early-stage healthtech teams (28 participants), analysing 190 interaction episodes using Carlile’s 3T framework. KNIT supported knowledge boundary crossing across syntactic (95.0%), semantic (86.3%), and pragmatic (84.8%) levels. We contribute empirical evidence and design principles showing how computational boundary objects mediate distinct boundary-crossing mechanisms, demonstrating that representational transformation rather than automation is the primary mechanism through which AI enables convergence across disciplinary boundaries.

Large-scale Vision-Language Models (LVLMs) process both images and text, excelling in multimodal tasks such as image captioning and description generation. However, while these models excel at generating factual content, their ability to generate and evaluate texts reflecting perspectives on the same image, depending on the context, has not been sufficiently explored. To address this, we propose IRR: Image Review Rank, a novel evaluation framework designed to assess critic review texts from multiple perspectives. IRR evaluates LVLMs by measuring how closely their judgments align with human interpretations. We validate it using a dataset of images from 15 categories, each with five critic review texts and annotated rankings in both English and Japanese, totaling over 2,000 data instances. Our results indicate that, although LVLMs exhibited consistent performance across languages, their correlation with human annotations was insufficient, highlighting the need for further advancements. These findings highlight the limitations of current evaluation methods and the need for approaches that better capture human reasoning in Vision & Language tasks.

We introduce a climbing system, inspired by gecko foot that uses magnets in place of Van der Waals interaction. This is possible because both forces, except for a scale factor, have similar force-curves. Taking advantage of this fact, we manufactured a hand-size "magnetic" version of a gecko-foot. This allowed us to conduct naked-eye experiments. As a result we identify four shape function relations that might partially explain the design of gecko feet. Additionally, we report experimental data, introduce a quantitative concept to compare climbing systems and show a prototype of magnetic hair

In micro-manipulation, the influence of gravitational force becomes extremely small. The adhesional force is more significant for smaller objects. An adhered object can be detached by electrostatic interaction. The electrostatic force generated by the applied voltage and the voltage required for detachment are theoretically analyzed by using the boundary element method (BEM). The system consists of a manipulation probe, a spherical micro-object, and a substrate plate. These object are all conductive. In this study, the voltage for detachment of micro-sphere with 30 /spl mu/m diameter was experimentally clarified, and was compared with the voltage predicted by the BEM analysis. This result gives us the knowledge about the strategy for reliable electrostatic micro-manipulation.

Techniques of arranging micrometer-sized objects with high repeatability under a scanning electron microscope (SEM) are required to construct highly functional micro-devices. Since micro-objects tend to adhere to other objects mainly by electrostatic force, the adhesive force is often being considered in basic researches of micro-object manipulation. These techniques, however, still do not achieve the desired repeatability, since many of them are being used just for the empirical effectiveness. Some even include the process of trial-and-error. Thus, we analyze the micro-object operation theoretically by considering the adhesion and rolling-resistance factors in a dynamic system consisting of a sphere, needle-shaped tool, and substrate. Through this analysis, we show that it is possible to control the fracture of the contact interfaces of the system selectively by determining the tool-loading angle appropriately. Based on the analysis, we also propose a practical method for the pick and place operation of a micro-sphere under an SEM.

There is a great demand for the highly accurate and reliable arrangement of micro objects smaller than 100 /spl mu/m in order to construct micro devices. Since micro objects tend to adhere to other objects by electrostatic force, it is possible to pick them up easily by contact with a needle tip instead of grasping by tweezers. On the other hand, it is difficult to place them on a substrate. To solve this problem, we have proposed a handling method by controlling the contact face area, i.e. picking up the object by contact with the center of the tool-tip plane, and placing it by contact with the edge and also inclining the tool. However, it is difficult to execute this operation by manual control, because it requires delicate movement by the manipulator, in order not to break the object or flip it away. In this study, we automate this pick-and-place operation by visual and force control. Moreover, to arrange micro objects with high accuracy and reliability, all necessary functions such as calibration, object search, and positioning are integrated, and an automatic handling system is constructed. We successfully demonstrated a completely automatic arrangement of several micro objects of 30 /spl mu/m in diameter under SEM monitoring.

The basic strategy for reliable and precise pick-and-place operation is shown based on the actual measurement of adhesion under SEM. Dynamics for pick-and-place operation of a microsphere by a needle-shaped tool is analyzed. A new method of reliable pick and precise place is proposed on the basis of the basic strategy and the dynamics. An experimental system for executing the proposal operation is constructed based on the numerical-control of the position measurement of the target object. In this system, many numerically-controlled experiments with 2 /spl mu/m polystyrene spheres reveal that under the optimal conditions, the pick operation has never failed once out of over 20 trials and the place operation has 140 nm precision in position. Consequently, we conclude that the proposed method can realize pick operation with high reliability and place operation with high precision under SEM based on micro-physics.

A new type of carrier recovery circuit suitable for coherent detection in digital land-mobile radio transmission is studied experimentally. A dual-mode carrier recovery (DCR) circuit is proposed that adaptively selects one of two phase locked-loop operation modes: the conventional mode or the adaptive carrier-tracking (ACT) mode. The ACT mode digitally controls the reference phase, and enables instantaneous phase tracking in burst signal operation and/or in a fast fading environment. The DCR coherent demodulator performance is identical to that of conventional coherent detection in the low-CNR region, and to that of differential detection in the high CNR region where the ACT mode is selected.>