Mehmet Kanık, S. Orguc, Georgios Varnavides
et al.
Getting the most out of muscles Materials that convert electrical, chemical, or thermal energy into a shape change can be used to form artificial muscles. Such materials include bimetallic strips or host-guest materials or coiled fibers or yarns (see the Perspective by Tawfick and Tang). Kanik et al. developed a polymer bimorph structure from an elastomer and a semicrystalline polymer where the difference in thermal expansion enabled thermally actuated artificial muscles. Iterative cold stretching of clad fibers could be used to tailor the dimensions and mechanical response, making it simple to produce hundreds of meters of coiled fibers. Mu et al. describe carbon nanotube yarns in which the volume-changing material is placed as a sheath outside the twisted or coiled fiber. This configuration can double the work capacity of tensile muscles. Yuan et al. produced polymer fiber torsional actuators with the ability to store energy that could be recovered on heating. Twisting mechanical deformation was applied to the fibers above the glass transition temperature and then stored via rapid quenching. Science, this issue p. 145, p. 150, p. 155; see also p. 125 Iterative fiber drawing of a two-material ribbon enables strain-programmable artificial muscles. Artificial muscles may accelerate the development of robotics, haptics, and prosthetics. Although advances in polymer-based actuators have delivered unprecedented strengths, producing these devices at scale with tunable dimensions remains a challenge. We applied a high-throughput iterative fiber-drawing technique to create strain-programmable artificial muscles with dimensions spanning three orders of magnitude. These fiber-based actuators are thermally and optically controllable, can lift more than 650 times their own weight, and withstand strains of >1000%. Integration of conductive nanowire meshes within these fiber-based muscles offers piezoresistive strain feedback and demonstrates long-term resilience across >105 deformation cycles. The scalable dimensions of these fiber-based actuators and their strength and responsiveness may extend their impact from engineering fields to biomedical applications.
Research Software Engineers (RSEs) have become indispensable to computational research and scholarship. The fast rise of RSEs in higher education and the trend of universities to be slow creating or adopting models for new technology roles means a lack of structured career pathways that recognize technical mastery, scholarly impact, and leadership growth. In response to an immense demand for RSEs at Princeton University, and dedicated funding to grow the RSE group at least two-fold, Princeton was forced to strategize how to cohesively define job descriptions to match the rapid hiring of RSE positions but with enough flexibility to recognize the unique nature of each individual position. This case study describes our design and implementation of a comprehensive RSE career ladder spanning Associate through Principal levels, with parallel team-lead and managerial tracks. We outline the guiding principles, competency framework, Human Resources (HR) alignment, and implementation process, including engagement with external consultants and mapping to a standard job leveling framework utilizing market benchmarks. We share early lessons learned and outcomes including improved hiring efficiency, clearer promotion pathways, and positive reception among staff.
This Open Debate addresses the theme of missing data as a field of investigation for design, and as an opportunity to rethink the relationship between knowledge, technology and representation. In contemporary digital systems, the production and circulation of data define what is recognised, stored and remembered. In this scenario, design takes on a critical role in questioning the logic with which data is collected, ordered and made visible. The aim of this issue is to understand how design can intervene when the information is missing or partial, transforming such gaps into tools for reflection and experimentation.
The practices presented here explore different ways of dealing with incompleteness: from alternative infrastructures to collect and share data to participatory processes that redefine meaning, to visual and storytelling methodologies that can foreground phenomena and subjects that are often excluded.
The datum is understood as situated material, affected by values, relations and choices, requiring an approach that is mindful to contexts and to the consequences of design. Design thus emerges as a critical and cultural practice that can generate new ways of knowing, representing and sharing, working between what is visible and what remains invisible.
Davide Venturelli, Erik Gustafson, Doga Kurkcuoglu
et al.
We review the prospects to build quantum processors based on superconducting transmons and radiofrequency cavities for testing applications in the NISQ era. We identify engineering opportunities and challenges for implementation of algorithms in simulation, combinatorial optimization, and quantum machine learning in qudit-based quantum computers.
Large Language Models (LLMs) are revolutionizing software engineering (SE), with special emphasis on code generation and analysis. However, their applications to broader SE practices including conceptualization, design, and other non-code tasks, remain partially underexplored. This research aims to augment the generality and performance of LLMs for SE by (1) advancing the understanding of how LLMs with different characteristics perform on various non-code tasks, (2) evaluating them as sources of foundational knowledge in SE, and (3) effectively detecting hallucinations on SE statements. The expected contributions include a variety of LLMs trained and evaluated on domain-specific datasets, new benchmarks on foundational knowledge in SE, and methods for detecting hallucinations. Initial results in terms of performance improvements on various non-code tasks are promising.
Proto-personas are commonly used during early-stage Product Discovery, such as Lean Inception, to guide product definition and stakeholder alignment. However, the manual creation of proto-personas is often time-consuming, cognitively demanding, and prone to bias. In this paper, we propose and empirically investigate a prompt engineering-based approach to generate proto-personas with the support of Generative AI (GenAI). Our goal is to evaluate the approach in terms of efficiency, effectiveness, user acceptance, and the empathy elicited by the generated personas. We conducted a case study with 19 participants embedded in a real Lean Inception, employing a qualitative and quantitative methods design. The results reveal the approach's efficiency by reducing time and effort and improving the quality and reusability of personas in later discovery phases, such as Minimum Viable Product (MVP) scoping and feature refinement. While acceptance was generally high, especially regarding perceived usefulness and ease of use, participants noted limitations related to generalization and domain specificity. Furthermore, although cognitive empathy was strongly supported, affective and behavioral empathy varied significantly across participants. These results contribute novel empirical evidence on how GenAI can be effectively integrated into software Product Discovery practices, while also identifying key challenges to be addressed in future iterations of such hybrid design processes.
Kai Zhang, Jianwei Yang, Jeevana Priya Inala
et al.
Despite the promising results of large multimodal models (LMMs) in complex vision-language tasks that require knowledge, reasoning, and perception abilities together, we surprisingly found that these models struggle with simple tasks on infographics that require perception only. As existing benchmarks primarily focus on end tasks that require various abilities, they provide limited, fine-grained insights into the limitations of the models' perception abilities. To address this gap, we leverage the theory of graphical perception, an approach used to study how humans decode visual information encoded on charts and graphs, to develop an evaluation framework for analyzing gaps in LMMs' perception abilities in charts. With automated task generation and response evaluation designs, our framework enables comprehensive and controlled testing of LMMs' graphical perception across diverse chart types, visual elements, and task types. We apply our framework to evaluate and diagnose the perception capabilities of state-of-the-art LMMs at three granularity levels (chart, visual element, and pixel). Our findings underscore several critical limitations of current state-of-the-art LMMs, including GPT-4o: their inability to (1) generalize across chart types, (2) understand fundamental visual elements, and (3) cross reference values within a chart. These insights provide guidance for future improvements in perception abilities of LMMs. The evaluation framework and labeled data are publicly available at https://github.com/microsoft/lmm-graphical-perception.
Alexandra Mazak-Huemer, Christian Huemer, Michael Vierhauser
et al.
With the increasing significance of Research, Technology, and Innovation (RTI) policies in recent years, the demand for detailed information about the performance of these sectors has surged. Many of the current tools are limited in their application purpose. To address these issues, we introduce a requirements engineering process to identify stakeholders and elicitate requirements to derive a system architecture, for a web-based interactive and open-access RTI system monitoring tool. Based on several core modules, we introduce a multi-tier software architecture of how such a tool is generally implemented from the perspective of software engineers. A cornerstone of this architecture is the user-facing dashboard module. We describe in detail the requirements for this module and additionally illustrate these requirements with the real example of the Austrian RTI Monitor.
Robida is a collective that focuses on long-term projects combining written and spoken words spatial practices. The collective is based in village of Topolò/Topolove, situated between Italy and Slovenia. Robida’s main goal is to rethink cultural work possibilities in post-rural areas, which were once sustained by agriculture but have been abandoned during the process of modern urbanization. Robida Magazine, a multilingual cultural publication released annually, delves into various topics connected to Topolò/Topolove. The chosen topic is shared with the world for interpretation by people who have never been to Topolò. The responses received after the open call not only contribute to the exploration of a defined concept but also provide new interpretational tools to examine the collective’s relation to Topolò. Through various cultural and editorial initiatives, the village of Topolò has gained recognition beyond the borders of Italy and Slovenia, attracting a community of young people to repopulate the area and share experiences with visiting artists and other individuals. The project aims to analyze the collective’s relation to Topolò through external viewpoints and thoughts. As a result, the project has raised awareness of Topolò and facilitated community growth.
This article explores how interdisciplinary teams work when developing environmentally conscious materials. Based on nine interviews with founders, researchers, and practitioners, it identifies what makes collaboration across design, science, engineering and art effective. Respondents emphasized the importance of shared and well-equipped spaces, open communication, and personal qualities such as empathy, openness, and adaptability. They also pointed to challenges of different time perceptions, the need to overcome hierarchical habits, and the decisive role of great leadership in providing vision and cohesion. While the study reflects a limited and design-oriented sample, it provides fresh insights into how collaborative teams navigate challenges of time, language, and organization. The article contributes to growing debates on material innovation as an interdisciplinary practice and seeks to inspire designers, students, and researchers to engage more openly in collaborative processes.
This contribution aims at critically examining the evolving role of design in contemporary society, integrating insights from sociology, anthropology, and design theory. It discusses the shift from long-term ethical objectives to economic and technological imperatives. Emphasizing interdisciplinary and transdisciplinary approaches, it highlights the necessity for enhanced collaboration to address complex societal issues. The article advocates the re-evaluation of design ethical dimension and its potential for shaping future narratives; it stresses the importance of promoting sustainable and ethical behaviors through design to enhance collective well-being. Drawing on philosophical and sociological perspectives, it proposes proactive design interventions to envision and shape desirable futures. Lastly, it calls for the establishment of transdisciplinary research centers to analyze future scenarios and guide societal transformations towards preferred outcomes.
Margherita Tufarelli, Anna Maria Azzini, Elisabetta Cianfanelli
The linear model of production and consumption in the fashion industry generates vast amounts of textile waste, posing a major environmental challenge. While Circular Economy principles offer viable alternatives, their implementation remains hindered by supply chain fragmentation, cultural and technological barriers. This paper explores the SCAR.TO project, an initiative funded by the Regione Toscana, which aims to prototype a structured circular supply chain in collaboration with a leading industrial holding operating across Italy’s fashion sector. By integrating multiple stakeholders, including fashion brands, manufacturers, and recycling facilities, the project seeks to prototype scalable solutions for waste reduction and material reintegration. The study therefore discusses the operational challenges of circularity, the policy frameworks supporting circular transitions, and the preliminary findings emerging from SCAR.TO’s implementation. Ultimately, the project provides a multi-level approach to address the complexities of circular transitions in the Made in Italy fashion system.
Lune Maillard, Fabio Finocchi, César Godinho
et al.
Lennard-Jones clusters, while an easy system, have a significant number of non equivalent configurations that increases rapidly with the number of atoms in the cluster. Here, we aim at determining the cluster partition function; we use the nested sampling algorithm, which transforms the multidimensional integral into a one-dimensional one, to perform this task. In particular, we use the <tt>nested_fit</tt> program, which implements slice sampling as search algorithm. We study here the 7-atom and 36-atom clusters to benchmark <tt>nested_fit</tt> for the exploration of potential energy surfaces. We find that <tt>nested_fit</tt> is able to recover phase transitions and find different stable configurations of the cluster. Furthermore, the implementation of the slice sampling algorithm has a clear impact on the computational cost.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
The lack of understanding of students on 2D drawing modification material using CAD is the background for this research. The purpose of this study is to produce products in the form of video tutorial learning media, knowing the feasibility of experts, knowing user responses, and knowing the improvement of learning outcomes after using media. This study used quantitative research methods with a pre-experimental research design with the type of one group pre-test post-test design. Purposive sampling was conducted to select 34 samples from TPM grade XI learners. This research produces video tutorial learning media. The results of the feasibility assessment conducted by show that the video tutorial learning media that has been made is declared "very feasible". The results of media user responses obtained the category "very good". Learning outcomes after using video tutorial learning media have increased, this is reflected in the increase in student learning outcomes measured through the use of n-gain with an average score of 0.38 in the "medium" category. Thus, it can be concluded that this video tutorial learning media is very feasible for use on manufacturing engineering drawing elements.
The creation of a Software Requirements Specification (SRS) document is important for any software development project. Given the recent prowess of Large Language Models (LLMs) in answering natural language queries and generating sophisticated textual outputs, our study explores their capability to produce accurate, coherent, and structured drafts of these documents to accelerate the software development lifecycle. We assess the performance of GPT-4 and CodeLlama in drafting an SRS for a university club management system and compare it against human benchmarks using eight distinct criteria. Our results suggest that LLMs can match the output quality of an entry-level software engineer to generate an SRS, delivering complete and consistent drafts. We also evaluate the capabilities of LLMs to identify and rectify problems in a given requirements document. Our experiments indicate that GPT-4 is capable of identifying issues and giving constructive feedback for rectifying them, while CodeLlama's results for validation were not as encouraging. We repeated the generation exercise for four distinct use cases to study the time saved by employing LLMs for SRS generation. The experiment demonstrates that LLMs may facilitate a significant reduction in development time for entry-level software engineers. Hence, we conclude that the LLMs can be gainfully used by software engineers to increase productivity by saving time and effort in generating, validating and rectifying software requirements.
Drawing (a multiset of) coloured balls from an urn is one of the most basic models in discrete probability theory. Three modes of drawing are commonly distinguished: multinomial (draw-replace), hypergeometric (draw-delete), and Polya (draw-add). These drawing operations are represented as maps from urns to distributions over multisets of draws. The set of urns is a metric space via the Kantorovich distance. The set of distributions over draws is also a metric space, using Kantorovich-over-Kantorovich. It is shown that these three draw operations are all isometries, that is, they exactly preserve the Kantorovich distances. Further, drawing is studied in the limit, both for large urns and for large draws. First it is shown that, as the urn size increases, the Kantorovich distances go to zero between hypergeometric and multinomial draws, and also between Pólya and multinomial draws. Second, it is shown that, as the drawsize increases, the Kantorovich distance goes to zero (in probability) between an urn and (normalised) multinomial draws from the urn. These results are known, but here, they are formulated in a novel metric manner as limits of Kantorovich distances. We call these two limit results the law of large urns and the law of large draws.
Through an experimental approach, this paper investigates light as a tool to achieve deep perception of three-dimensional object forms, to support aesthetic assessment during the creation of physical models. With product design practice as the foundation, my motivation builds on the fact that light strongly affects the designer’s capabilities for assessing, modifying, and refining physical shape during the design process. In laboratory experiments with models representing defined form idioms, this study demonstrates how light may enable new and deep object form perception. This body of visual documentation supports an understanding of light’s potential as both an analytical and creative resource, aiming at pedagogies that stimulate aesthetic sensitivity. Few research studies describe this specific topic; experience from teaching product design suggests that a broader group of creative professionals could benefit from building awareness of light’s impact more broadly in the design industries.