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Creating text-based AI clones of myself: Exploring perceptions, development strategies, and challenges
No full textAI clones are evolving to include digital representations of real world individuals as chatbots. While often used to replicate famous figures, as the technology becomes more accessible, it is crucial to understand whether everyday users would create their own clones and how they interact with them. In this study, within the scope of AIgenerated personas and their role in representing users’ needs and identities, we focus on personas that directly reflect the qualities of real humans. We define this as AI self clones—conversational AI representations that reflect their human creators—and examine how creators construct and engage with them. We conducted a 7-day study in which participants (N=12) created and interacted with their text based AI self clones using CloneBuilder, a web-based authoring interface for configuring and tuning AI self clones. The system enables individuals to create AI representations that encapsulate their unique personality, values, and interaction style. Our findings reveal that each participant developed a clone tailored to their personal circumstances. As the participants iteratively refined and tested their clone, their direction and expectations of AI clones evolved from performing specific roles to becoming entities that facilitated self exploration and relationship formation. Unexpected responses from the clone prompted self reflection and identity questioning. Overall, this paper explores the motivations for creating these clones, the strategies participants use to build and refine them, and the moments of emotional connection and break out experiences that emerge during the crafting process, along with key design implications, challenges, and ethical considerations in developing AI self clones.
Portable duplex digital PCR for on-site detection of IDH mutations in gliomas
No full textAccurate identification of critical genetic markers in brain tumors, such as isocitrate dehydrogenase (IDH) mutations, is vital for predicting overall survival, which can reach 11.4 years for IDH-mutant gliomas compared to 14.6 months for IDH-wildtype glioblastoma (GBM). However, existing diagnostic methods, including immunohistochemistry and next-generation sequencing, are time-consuming and difficult to implement in postsurgical contexts. Here, we present a proof-of-concept for a portable, duplex droplet-based digital PCR (ddPCR) system that integrates thermocycling, microfluidic control, and multi-fluorescence detection within a compact design, enabling rapid and accurate analysis of rare mutations. In contrast to conventional ddPCR platforms, which are often bulky, complex, and unsuitable for point-of-care use, our system features an automated, user-friendly workflow that reduces operator variability while maintaining high sensitivity and specificity. Using patient-derived glioma samples, we demonstrated that the system successfully distinguished IDHmutant from IDH-wildtype tumors, achieving 92 % sensitivity and 100 % specificity. Moreover, comparison with a commercial ddPCR platform showed strong concordance, validating its analytical accuracy and clinical utility. This system offers a promising advancement in molecular diagnostics, providing a field-deployable solution for accurate mutation detection, personalized treatment selection, and improved prognostic evaluation.
Breakeven molten salt fast reactor based on a simple closed fuel cycle for sustainable nuclear energy
No full textThis work proposes an innovative closed fuel cycle based on a breakeven molten salt fast reactor (BeMFR) concept to resolve the trilemma in nuclear energy, i.e., safety, spent fuel, and sustainability. Six reactor models are considered, each with a thermal power of 3000 MWth but differing in core size and fuel salt composition, utilizing two types of eutectic conditions. A simple and proliferation-resistant pyro-processing is envisioned to recover TRU (transuranic) together with uranium and RE (rare earth) from the light water reactor (LWR) spent fuel. The criticalities of initial cores are achieved by adjusting the composition of KCl-UCl3-TRUCl3-RECl3 molten salt fuel. The BeMFR gradually transitions to an equilibrium state through continuous removal of fission products (FPs) and the provision of spent nuclear fuel (SNF) as make-up. Operational strategies accounted for changes in salt volume caused by FP accumulation, fuel addition, and the supply of potassium (K) and chlorine (Cl), and ensures the excess reactivity during the transition from the initial to equilibrium state remains within 2 dollars. The neutronic feasibility of the proposed operational strategies for BeMFR has been evaluated in detail alongside assessments of reactivity control devices, temperature coefficients, and inherent safety features using the Serpent 2 Monte Carlo code. In addition, the iMC Monte Carlo code is used to evaluate kinetic parameters with consideration of the molten salt fuel flow and its effects on the redistribution and loss of delayed neutron precursors.
Reflector temperature coefficient of molten salt fast reactor using moderating reflector
No full textThis work investigates the reflector temperature coefficient (RTC) in a 100 MWth long-life molten salt fast reactor (MSFR) employing a BeO moderating reflector. The design retains advantages of MSFR while greatly reducing fuel inventory, but localized moderation in the separated reflector leads to a positive RTC, raising safety concerns. To elucidate the underlying mechanisms of this positive RTC, neutronic analyses were performed with a simplified analysis model excluding control drums or B4C shield. Quantitative evaluations were conducted to characterize local spectrum shifts, variations in cross-sections within the fuel salt and reflector, neutron flux, neutron current, and reaction rates under elevated reflector temperatures. In addition, region-wise RTCs were evaluated to quantify the contribution of each reflector subregion to overall reactivity changes. Parametric studies were carried out to investigate key influencing factors-including the active core size, and inner barrier thicknesses-with a further investigation for micro-scale MSR design. Furthermore, the RTC behavior in various moderating reflectors (BeO, Be, graphite, and MgO) was analyzed in terms of neutron spectrum and componentwise thermal neutron absorption characteristics, further supported by a fine region-wise analysis of thermal neutron net current under increasing reflector temperatures. All neutronic calculations were performed using the Serpent 2 continuous-energy Monte Carlo code.
Mechanical characterization of Silicon-on-Nothing structures with nanoindentation and point-load deflection experiments
No full textSilicon-on-Nothing (SON) structures comprise of ultrathin single-crystalline silicon membranes suspended over vacuum-sealed cavities, making them promising candidates for microelectromechanical system (MEMS)-based pressure sensors. While their structural perfection has been verified, their mechanical properties remain largely uncharacterized. In this study, nanoindentation and point-load deflection experiments were conducted on the Si substrate and freestanding SON membranes, respectively. The elastic moduli extracted from the two methods differed by 4.5 %. Membrane deformation under uniform atmospheric pressure, predicted by finite-element analysis using the modulus obtained from point-load deflection experiments, showed good agreement with the membrane profile measured via atomic force microscopy (AFM) under atmospheric pressure. However, a deviation of up to 6.4 % in the central deflection was observed when the substrate modulus was used in the simulation. These findings quantitatively highlight the importance of explicitly characterizing the elastic properties of SON membranes, offering essential insights for advancing the integration of SON structures into MEMSbased applications.
Experimental realization of acoustic logic gates based on valley-locked interface states in two-dimensional metamaterials
No full textAcoustic logic gates have recently garnered extensive attention for their potential in low-energy and high-efficiency information processing. However, their development still faces several critical challenges, including limited robustness, insufficient experimental validation, and restricted functional diversity. To address these issues, we design and demonstrate, both numerically and experimentally, an acoustic metamaterial platform based on valley-locked waveguides that supports a series of logic functions. The proposed metamaterial enables reliable realization of basic logic operations, including AND, OR, and XOR, within a certain frequency bandwidth, using a single configuration. For more complex logic functions, including NOR, XNOR, and NAND, flexible operation at any selected frequency within a specific bandwidth is achieved by introducing a bias input and combining two trident-shaped waveguides. Furthermore, the robustness of the proposed metamaterial systems is experimentally verified under the presence of structural defects, confirming the feasibility of valley-locked waveguides for logic implementation. These findings open new avenues for the development of reconfigurable and scalable acoustic computing architectures.
Discrete least square method for nonmatching mesh problems
No full textThis research presents a novel algorithm designed to address nonmatching mesh problems. The key feature of the algorithm is its explicit definition of an interface force on nonmatching interfaces. The displacement at the nonmatching mesh is formulated as a function of the interface force, which is determined through the implementation of displacement continuity conditions using the least square method. Notably, this method offers simplicity and robustness, as it eliminates the necessity for integration at the nonmatching mesh. Numerical examples are provided to assess the algorithm's performance, demonstrating its potential applicability to a wide array of problems involving nonmatching meshes, including domain decomposition and parallel computation.
Graph Perceiver IO: A general architecture for graph-structured data
No full textMultimodal machine learning has been widely studied for the development of general intelligence. Recently proposed Perceiver and its variant (Perceiver IO) have shown promising results in addressing diverse types of input modalities with a universal model architecture. However, they have mainly focused on image and text data modalities, and it is unclear whether this kind of universal architecture can also be effective for graph-structured datasets. As the graph data contains topological information, which is lacking in the image and text data, it is non-trivial to devise a universal architecture for graph and other data modalities altogether. In this study, we provide a Graph Perceiver IO (GPIO), a class of Perceiver IO models that addresses graph-structured datasets. We keep the main structure of the GPIO the same as with the Perceiver, which can already handle multiple data modalities, while focusing on how we can extend it to the graph domain. By leveraging positional encoding and output query smoothing, GPIO serves as a general architecture that handles graph-structured data as well as text and image data. Besides, we further propose GPIO+ for the multimodal few-shot classification that incorporates both images and graphs simultaneously. Through extensive experiments covering link prediction, graph classification, node classification, and multimodal text classification, we demonstrate that GPIO and GPIO+ outperform the representative graph neural network baseline models, while requiring lower computational complexity than them.
Graph approach for Gibson's ecological optics with dynamics of network motifs
No full textDynamic visual perception in complex environments is central to understanding the interaction between organisms and their surroundings. Ecological optics depicts that the visual system gains optical information from ambient light, which is structured by relative movements between organism and environment. Recent advances have developed theoretical models of optical information, commonly formalized as optical flows, that account for the perception-action link. However, these frameworks have had limited capacity to inform environmental design, due to a gap between the micro-scale, formalized models of optical information and meso-scale, semantic analyses of observer experience. To address this gap, building on basic principles of ecological optics, we develop a framework that characterizes observers' perception-action patterns by integrating graph-theoretic concepts and measures. Our framework discretizes spatial and temporal trajectories of ambient light experienced by an observer, in the form of a weighted directed graph. This graph approach directly reveals dynamics of perception-action patterns via network motifs-recurring subgraph patterns within a larger graph. Information entropy, as a temporal measure of information content, indicates the distinct modes of the dynamics. As a demonstration, a state analysis shows that several transient states in the motif-based dynamics exhibit good correlations with observers' inclination toward places from survey data, validating its potential for spatial analysis. Overall, the proposed framework paves the way towards real-world applications in optimizing dynamic interactions between observer and environment.
Optimal contract design with labor-leisure choice under limited commitment: A free boundary approach
No full textWe study a continuous-time optimal contracting problem involving labor-leisure choices under limited commitment. A principal offers a contract to a risk-averse agent whose wage follows a geometric Brownian motion. The agent derives utility from both consumption and leisure, modeled through a Cobb-Douglas utility function. Due to limited commitment, the agent's participation and promised utility constraints must be satisfied throughout the contracting horizon. By employing a dual approach and dynamic programming principles, we transform the problem into a singular stochastic control problem associated with a variational inequality and a free boundary. We provide an explicit closed-form solution to the variational inequality and characterize the optimal contract in terms of consumption and leisure processes. Numerical simulations illustrate the dynamic behavior of the optimal consumption, leisure, and continuation utility processes. Our approach demonstrates the effectiveness of duality methods and singular control techniques in solving nonlinear stochastic optimization problems with state-dependent constraints, contributing to the computational aspects of optimal control and contract theory.