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Coupled magneto-mechanical growth in hyperelastic materials: Surface patterns modulation and shape control in bio-inspired structures
No full textMagneto-mechanical coupling in the growth of soft materials presents challenges due to the complex interactions between magnetic fields, mechanical forces, and growth-induced deformations. While growth modeling has been extensively studied, integrating magnetic stimuli into growth processes remains underexplored. In this work, we develop a 3D governing system for capturing the coupled magneto-mechanical growth behaviors of soft materials. Based on the governing system, we propose a finite element framework, where the robustness and accuracy of the proposed framework are demonstrated through numerical simulations, including the uniaxial loading of a circular tube, a mesh convergence study, and surface pattern evolution. We also conduct experiments on surface pattern modulation in magneto-active soft materials. Specifically, we fabricate film–substrate samples and apply growth-induced instabilities combined with external magnetic fields to generate tunable surface patterns. To demonstrate the capabilities of our method, we apply our numerical framework to mimic the biological morphogenesis, such as the inversion process of the algal genus Volvox. Our study shows that integrating magneto-mechanical coupling with growth effects allows for flexible control over surface patterns, significantly enhancing the adaptability and responsiveness of soft materials. This work paves the way for innovative designs of adaptive and programmable soft materials, with potential applications in soft robotics, biomimetic structures, and tissue engineering
An Overview of Current Optimization Approaches for Hybrid Energy Systems Combining Solar Photovoltaic and Wind Technologies
Get PDFThis study reviews recent developments in optimization techniques for hybrid solar photovoltaic and wind energy systems,particularly those using artificial intelligence (AI) and hybrid algorithms. Due to the global need for sustainable energy, thestudy compares both traditional and modern optimization techniques. It shows that hybrid algorithms, like, Gray Wolf–CuckooSearch Optimization (GWCSO), can speed up convergence and reduce costs by up to 25% compared with other conventionalmethods, such as linear programming. The study groups optimization techniques into traditional, software‐based, AI‐driven,and hybrid approaches; assessing how well they improve system efficiency, reliability, and cost. It also outlines sizing methodsand their economic, technical, and environmental effects, with results showing that AI‐driven methods can lower the levelizedcost of energy by 10%–15% in complex microgrids (MGs). The study further provides a structured way to size MGs, addressing agap in optimization methods for independent hybrid systems in remote locations. Greater flexibility of hybrid algorithms inhandling complex optimization problems was emphasized. Ultimately, this study offers new insights into combining AI withtraditional methods, suggesting future research directions for both smart grid and MG desig
Who are you? Examining the multifaceted innovation roles of municipal governments in AI governance
Get PDFOur study advances theoretical understanding of the diverse roles municipal governments play in governing the development and deployment of artificial intelligence (AI) technologies within their administrative boundaries. While existing literature typically frames municipalities as regulators or adopters of AI, it tends to overlook the broader set of responsibilities they assume in shaping AI governance. To address this gap, we map traditional innovation roles onto the multiple functions that municipal governments perform in the emerging domain of AI technologies. Drawing from innovation management theory and AI governance literature examining the agency of governments and public sector organizations in AI governance, we identify core continuities and contextual adaptations in these roles. These insights illustrate how the foundational logic of traditional innovation roles is preserved but recalibrated to reflect the specific demands of AI governance at the municipal level. This theoretical contribution extends innovation role typologies into the field of AI governance, laying the groundwork for future empirical research and policy development
Building a modern data platform based on the data lakehouse architecture and cloud-native ecosystem
Get PDFIn today’s Big Data world, organisations can gain a competitive edge by adopting data-driven decision-making. However, a modern data platform that is portable, resilient, and efficient is required to manage organisations’ data and support their growth. Furthermore, the change in the data management architectures has been accompanied by changes in storage formats, particularly open standard formats like Apache Hudi, Apache Iceberg, and Delta Lake. With many alternatives, organisations are unclear on how to combine these into an effective platform. Our work investigates capabilities provided by Kubernetes and other Cloud-Native software, using DataOps methodologies to build a generic data platform that follows the Data Lakehouse architecture. We define the data platform specification, architecture, and core components to build a proof of concept system. Moreover, we provide a clear implementation methodology by developing the core of the proposed platform, which are infrastructure (Kubernetes), ingestion and transport (Argo Workflows), storage (MinIO), and finally, query and processing (Dremio). We then conducted performance benchmarks using an industry-standard benchmark suite to compare cold/warm start scenarios and assess Dremio’s caching capabilities, demonstrating a 12% median enhancement of query duration with caching
The effectiveness of decision-making training in team-sport officials: A systematic review and meta-analysis
Get PDFPurposeDecision making is a critical skill for sports officials, often directly influencing the flow and fairness of a match. While this topic has received considerable interest in the literature, a synthesis of current evidence to understand the effectiveness of decision-making training interventions remains unexplored. Therefore, the aim of this study was to conduct a systematic review and meta-analysis of decision-making interventions in team sport officials.Principal resultsA total of 14 studies were identified, with a random-effects meta-analysis revealing an overall moderate positive effect of decision-making training on decision-making performance outcomes (g = 0.68, p < .001) compared to control conditions. Notably, decision-making training was more effective in Soccer (g = 1.05), Rugby Union (g = 0.90), but not for Australian Football (g = 0.24). Video-based (i.e., 2-D footage) showed significant improvements, especially for objective decision-making outcomes like offside identification (g = 1.48, p < .001). However, our findings indicated that decision-making training tends to be less effective for subjective decision-making outcomes that requires higher levels of interpretation. Furthermore, shorter interventions (4–6 weeks) were found to be most effective, with performance improvements reducing as interventions increased in time.Major conclusionsOur findings highlight the need for further research to explore alternative technologies such as virtual reality to understand how to better replicate game scenarios and assess the transferability of decision-making training to real-world officiating contexts. Additionally, this review highlights the need to investigate sports beyond Soccer, Rugby, and Australian Rules Football to develop our understanding further into optimising decision-making training in sports officials
Experimental Design of a Novel Daylighting Louver System (DLS); Prototype Validation in Edinburgh Climate for Maximum Daylight Utilisation
Get PDFAchieving optimal daylighting in buildings necessitates complex and expensive control systems. This research addresses this challenge by proposing a simple and more practical solution: a parametric louver system based on rotating slats controlled by stepper motors, powered by an Integrated Circuit platform (Arduino board), which can translate the digital figures (the rotation angles) to a physical action. The system automatically adjusts the slats in accordance with solar altitudes and reflects them to specific targets over the ceiling. This ensures a uniform and comfortable distribution of daylight throughout a room. This system was developed using Grasshopper as the parametric software, with future control planned via a user-friendly mobile app through a preliminary prototype. This daylighting system prioritises human visual comfort while targeting a significant 53% reduction in electrical lighting energy consumption. The system aims to enhance occupant well-being to significantly increase energy savings, making it a compelling solution for sustainable building design
Identifying a Framework for Implementing Vision Zero Approach to Road Safety in Low- and Middle-Income Countries: A Qualitative Perspective
Get PDFRoad traffic fatalities in low- and middle-income countries (LMICs) are continuing to rise, posing significant socio-economic and public health challenges. To prevent these road deaths and avoid the corresponding costs, the World Health Organization (WHO) has recommended implementing the vision zero approach to road safety. Vision Zero aims to eliminate road deaths and reduce serious injuries. It has been adopted by many developed countries, however LMICs have faced difficulties implementing this approach due to a lack of guidance. This study aims to develop a framework for implementing vision zero in LMICs by examining the processes in India and Sweden. A qualitative research approach with a multiple-case study design was utilized, selecting 16 participants through purposive and snowball sampling. Data was collected via semi-structured interviews and analyzed using the Grounded Theory method based on Strauss and Corbin’s approach. The study identified five core implementation steps such as agenda setting, approval, planning, monitoring and evaluation, and continuous improvement. Also, a set of influencing conditions such as preconditions, objectives, strategies, intervening factors and contextual conditions were identified. Furthermore, 38 implementation proposals were suggested in the framework to guide policymakers. The proposed framework provides a road map for LMICs that is intended to act as a guide for policymakers and road safety practitioners to enhance road safety performance in LMICs
Twenty Years of Nurse-Led Research in Hemato-Oncology: A Mapping Review
Get PDFObjectivesNurse-led research in hemato-oncology is diverse, but its nature and extent are unknown. This review aimed to identify and map nurse-led research in hemato-oncology over 20 years (2004-2024) to highlight under-researched gaps, describe methodological and topic trends, and allow comparison between geographical regions.MethodsA mapping review was undertaken following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, Scoping Review (PRISMA-ScR) checklist. Five databases were systematically searched: Medline (Ovid), CINAHL (EBSCOhost), Embase (Elsevier), ProQuest, and Scopus (Elsevier). Independent screening and data extraction were undertaken on the web-based platform Covidence.ResultsA total of 1,916 sources were included (n = 1,618 journal publications; n = 262 published conference abstracts; n = 36 doctoral dissertations). The most common methodology was non-experimental (60.5%), followed by qualitative (19.2%), experimental (12.5%), evidence syntheses (6.3%), and mixed methods (1.5%). Most of the studies were undertaken by nurses working in the USA, followed by nurses in China, Türkiye, Canada, Australia and Iran. Studies in pediatric, adolescent, and young adult settings represented 42.4% of the included studies. A high number of studies undertaken in hematopoietic stem cell transplant settings were found.ConclusionsThe number of research studies led by nurses in hemato-oncology settings, particularly in the USA, is upward. Most of the research undertaken has adopted a descriptive quantitative methodology. More interventional research is needed to contribute meaningfully to scientific knowledge that enhances the quality of care for individuals affected by blood cancer across the disease trajectory.Implications for Nursing PracticeTo support more nurse-led interventional research, strategic investment in mentorship, protected research time, interdisciplinary collaboration, structured clinical-academic posts, and funding pathways is needed
Lights, camera, inclusion: Adapting TV and VFX practices with Deaf and hard-of-hearing actors
No full textCreating an inclusive TV industry requires intentional adaptation of production practices to support the participation and success of Deaf and hard-of-hearing (DHH) actors. This article explores strategies for fostering accessibility and equity on TV sets, with a particular emphasis on high-production environments like those involving visual effects (VFX). Through the lens of a case study interview with Amy Murray, a Deaf actor who starred in the fantasy series The Witcher: Blood Origin (2022), the research examines real-world challenges and solutions for enhancing accessibility and integrating VFX workflows with inclusive practices. Murray provides insights into her experiences, including navigating communication barriers, the use of on-set interpreters and the importance of visual aids, written cues and pre-visualization tools during the production process. The article highlights how the production team of The Witcher: Blood Origin implemented inclusive practices, such as hiring sign-language interpreters, providing captioned scripts and fostering an inclusive work culture while collaborating with VFX teams. Key to their success was the use of visual storytelling tools and technologies, including VFX pre-visualizations and accessible digital interfaces, to ensure Murray and other team members could effectively visualize and interpret scenes involving complex effects. Murray’s reflections underscore the significance of authentic representation, noting how her presence as a deaf actor enriched the storytelling and brought depth to her character within the highly visual medium of VFX-heavy productions. The article calls for a collective shift towards a more accessible, equitable and visually inclusive TV industry
Effects of personalized live-remote exercise for individuals living beyond primary curative cancer treatment: study protocol for a multinational, super umbrella randomized controlled trial (LION-RCT)
Get PDFBackground: Exercise is an effective strategy to reduce cancer- and treatment-related side effects and improve quality of life (QoL). Larger exercise effects are observed in cancer survivors with a higher symptom burden and when exercise interventions are supervised. Most studies conducted to date have not screened for symptoms at baseline and tailored the exercise intervention accordingly. Additionally, time and travel distance are common barriers to participation in supervised in-person exercise programs. Live-remote exercise, where exercise sessions are supervised by an exercise professional via a videoconferencing platform, might help overcome these barriers. Here, we describe the design of the LION randomized controlled trial (RCT). This RCT aims to assess the (cost-)effectiveness of side effect-targeted, live-remote exercise on QoL and the participants’ most burdensome side effect—fatigue, emotional distress, low physical functioning, or chemotherapy-induced peripheral neuropathy (CIPN)—in individuals who have completed primary curative cancer treatment. Methods: The LION study is a multinational RCT that will enroll 352 individuals who have completed primary curative cancer treatment including chemotherapy, within the previous 12–52 weeks and screen positive for ≥ 1 of the targeted side effects. Participants are randomly allocated (1:1) to the intervention or wait list control group. Participants in the intervention group receive a 12-week supervised exercise program consisting of three live-remote exercise sessions per week. Each participant receives the same base module (2×/week) and one specific module (1×/week) targeting their most burdensome side effect. Wait list control participants receive the same exercise program 12 weeks post-baseline. The primary outcomes are HRQoL (EORTC QLQ-C30 summary score) and a standardized symptom score based on each participant’s most burdensome side effect (physical fatigue: EORTC QLQ-FA12, emotional distress: PHQ-ADS, physical functioning: EORTC QLQ-C30 modified physical functioning scale, CIPN: EORTC QLQ-CIPN20), assessed at baseline, 6, 12 (primary time point), 18 (wait list control group only), 24 and 36 weeks post-baseline. Discussion: This RCT will provide evidence regarding the (cost-)effectiveness of side effect-targeted, live-remote exercise in individuals experiencing side effects following primary curative cancer treatment. If proven (cost-)effective, live-remote exercise could be offered to individuals as part of standard follow-up cancer care to extend the reach of exercise support. Trial registration: NCT06270628. Registered on February 13, 2024
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