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How entrepreneurs absorb knowledge spillovers during innovative product development: Evidence from UK start-ups
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The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.This study examines the impact of knowledge spillovers on product innovation performance within UK medium to high-tech start-ups. We propose a conceptual model that explains the relationship between incoming and network knowledge spillovers, potential and realized absorptive capacity, and exploratory and exploitative innovation performance, considering technological turbulence. Based on a PLS-SEM analysis of 556 UK-based medium to high-tech start-ups, our results show that during the potential absorptive capacity phase, start-ups focus on acquiring incoming and networked knowledge spillovers. However, the exploitation of network knowledge spillovers occurs during the realized absorptive capacity phase. These findings contribute to the current understanding of the role of knowledge spillovers in absorptive capacity, while from a practical perspective they provide start-ups with guidance on optimizing and exploiting knowledge spillover based on their firms' characteristics
"I have suffered something": traumatic childbirth in 19th-century Britain
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Data sharing not applicable as no datasets generated and/or analysed for this study.In 1994, the American Psychiatric Association revised its definition of trauma in relation to post-traumatic stress disorder (PTSD), enabling the recognition of childbirth as a potentially traumatic event leading to the development of symptoms of PTSD. This article considers clinical definitions of postpartum PTSD in relation to 19th-century case histories of difficult childbirth, and posits that the circumstances of some of these births—particularly in the context of higher infant and maternal mortality—mean they were likely to have been experienced as highly traumatic events, which may have led to the onset of symptoms today associated with postpartum PTSD. While resisting problematic retrospective diagnoses of postpartum PTSD, the article highlights the presence of the now widely recognised risk factors for the disorder in the experiences of these women, and demonstrates that birth in 19th-century Britain had significant potential to be experienced as a traumatic event for mothers. In doing so, it seeks to contribute to a wider conversation around—and expand our understanding of—women’s (physical and emotional) experiences of childbirth at this time, as well as some of the medical practices commonly employed in the birthing room, and the ethical questions which emerge from some of these. The article begins by outlining the risk factors now associated with postpartum PTSD, before exploring these in relation to 19th-century birth narratives. It draws on medical case notes (primarily the case studies of Dr Robert Lee) and women’s own accounts of childbirth, as well as advice literature for women on the subject of childbirth. The discussion focuses in particular on three issues: women’s knowledge around childbirth and agency within the birthing room (including issues of consent); the use of interventions in childbirth; and infant loss. The final part of the article briefly considers 19th-century discourses around puerperal insanity, and notes an association between difficult deliveries and the onset of puerperal insanity in some cases.The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors
Enhancing healthcare resource allocation through large language models
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Data will be made available on request.Recognizing the growing capabilities of large language models (LLMs) and their potential in healthcare, this study explores the application of LLMs in healthcare resource allocation using Prompt Engineering, Retrieval-Augmented Generation (RAG), and Tool Utilization. It addresses both optimizable and non-optimizable challenges in allocating operating rooms (ORs), postoperative beds, and surgeons, while also identifying key factors like ethical and legal constraints through a medical knowledge Q&A survey. Among the seven evaluated LLMs, including LaMDA 2, PaLM 2, and Qwen, ChatGPT-4o demonstrated superior performance by reducing OR and surgeon overtime, alleviating peak bed demand, and achieving the highest accuracy in medical knowledge queries. Comprehensive comparisons with traditional methods (exact and heuristic algorithm), varying problem sizes, and hybrid approaches from the literature revealed that as problem size increased, LLMs performed better and faster by integrating historical experience with new data. They adapted to changes in problem scale or demand without requiring re-optimization, effectively addressing the runtime limitations of traditional methods. These findings underscore the potential of LLMs in advancing dynamic and efficient healthcare resource management.This work is partially supported by HarmonicAI - Human-guided collaborative multi-objective design of explainable, fair and privacy-preserving AI for digital health distributed by European Commission (Call: HORIZON-MSCA-2022-SE-01-01, Project number: 101131117 and UKRI grant number EP/Y03743X/1). The authors sincerely acknowledge the financial support (n°23 015699 01) provided by the Auvergne Rhône-Alpes region
Digital twin-optimised repurposing of spent mushroom substrate into circular bio-based composites
Get PDFThe global mushroom industry generates over 60 million tons of spent mushroom substrate (SMS) annually, presenting both an environmental challenge and an opportunity for sustainable material development (Grimm et al., 2018) ..
Deformation-driven precipitate evolution in cold sprayed age-hardenable aluminum alloys
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Data will be made available on request.Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S0169433225026303?via=ihub#s0045 .Recent advances in laser assisted cold spray have shown great promise in addressing the limitations of particle plasticity and bonding strength in conventional processes, especially for difficult-to-deposit hard metal materials. In the present study, we enhanced the plastic deformation capability of cold sprayed high strength age-hardenable aluminium (Al) alloy particles by applying laser assisted heating, which enabled effective particle deposition at lower velocities. We investigated the deformation behavior of individual particles under varying velocities and temperatures through single particle simulations and controlled experiments. The results demonstrated a strong correlation between simulation and experimental data, showing that particle deformation increases with velocity. High-resolution transmission electron microscopy revealed excellent bonding at the interface between laser treated particles and the substrate, with no visible demarcation. In contrast, the interface of untreated particles exhibited a nanometer-thick oxide layers of 15–25 nm. Additionally, with the increase of severe plastic deformation, a large amount of η/η’-MgZn2 precipitates appeared in the multi-particle bonding regions of the deposits, which are attributed to the high dislocation density and local thermal effects promoting the rapid nucleation of precipitates at dislocation positions. The concurrent increase in precipitate formation contributed to the strengthening of the deposit, as reflected by an elevated nanoindentation hardness of up to 3.5 GPa. Vacuum heat treatment confirmed that intense plastic deformation during in situ laser-assisted deposition generates high dislocation densities and drives microstructural evolution, which are key to accelerating precipitation and improving interfacial bonding quality. These findings provide mechanistic insights and practical guidance for tailoring particle bonding and microstructural evolution in laser assisted cold spray of high-strength alloys.Key Science and Technology Program of Shaanxi Province, China (Grant No. 2023GXLH-050)
Simulation and optimization of CNC cylindrical grinder Performance based on equivalent analysis of joints spring-damping characteristics
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The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.This paper focuses on the MKE1620A CNC cylindrical grinder, using an equivalent analysis of the joint spring-damping characteristics to investigate the overall performance of the grinder and propose directions for design optimization. A total of 168 spring-damper elements were established to model the fixed, movable, and bearing joints. These elements were classified and calculated to determine their parameters, which were then incorporated into a finite element analysis model to examine the impact of joint stiffness on the static and dynamic performance of the machine tool, with results showing less than a 10% error compared to actual measured data. Additionally, the paper investigates how the quality of six common structural materials influences the first-order natural frequency of components and explores the relationship between variations in joint stiffness and changes in the machine tool’s natural frequency. The findings provide theoretical and data-driven insights for the design and optimization of CNC cylindrical grinding machines, serving as a valuable reference for enhancing machine tool performance and machining quality.This research is supported by Undergraduate-postgraduate Integrated Curriculum Development Project (No. BY202406) and 2023 Shanghai Education Commission Young Teacher Training Subsidy Program
Environmental impact assessment of multifunctional desalination systems
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Data will be made available on request.Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S2666789425000741?via%3Dihub#appsec1 .The desalination sector adopts Minimal Liquid Discharge (MLD) systems to become more circular, reduce brine discharge and enhance water recovery, which transforms them to multifunctional systems. This multifunctionality requires a methodologically consistent and goal-aligned approach to environmental impact assessment that recognises how different modelling choices are connected with specific decision contexts. A criterion LCA-based framework aligned with the ISO 14044 hierarchy and tailored specifically to desalination has been developed. It guides the selection of allocation approaches based on system characteristics, integration level, and assessment objectives and is applied to assess an MLD system which co-produces desalinated water, sodium chloride, magnesium hydroxide, calcium hydroxide, sodium sulphate and hydrochloric acid. Multifunctionality was handled with system expansion and partitioning (physical and economic) approaches, resulting in different functional units. For physical and economic partitioning, the MLD system is modelled from a process and system perspective. The results indicate that the MLD system has larger environmental benefits than the reference system with system expansion. When physical and economic partitioning under different perspectives are applied, they result in different environmental burdens per co-product. The MLD system performs better than the reference system (0.005 kg CO2/kg desalinated water) only when process economic partitioning (0.003 kg CO2/kg desalinated water) is applied. Whereas, the rest co-products perform better than reference products for all partitioning approaches applied. Our results highlight the potential of brine as a secondary source of products. This study underscores the importance of selecting appropriate allocation approaches, contributing to sustainable practices in the desalination sector.The authors are grateful to the European Commission for supporting the activities carried out in the framework of the WATER-MINING (project under grant agreement No. 869474)
DA2-Net: Integrating SAM2 with Domain Adaption and Difference Aggregation for Remote Sensing Change Detection
Get PDFVisual foundation models (VFMs) have been widely applied in the field of remote sensing (RS). However, they still face two main challenges when applied to precise RS change detection (RSCD) tasks in complex scenes. Firstly, the nonnegligible domain shift between natural scene and RS scene limits the direct application of VFMs to the RSCD task. Second, most of the existing RSCD methods may suffer from the boundary displacement problem due to the inadequate exploration of temporal differences for bi-temporal features. To address the above issues, this study proposes a Segment Anything Model 2 (SAM2)-based domain adaptive and spatial difference aggregation network (DA2-Net) for RSCD. The proposed DA2-Net has two main advantages. First, a hierarchical low-rank adaptation (LoRA) strategy is presented by introducing low-rank matrices at key positions of SAM2, which can inject inductive biases from the RS domain into the network and alleviate the domain shift problem. Second, a difference adaptive enhancement module (DAEM) is designed to explore temporal differences for hierarchical bi-temporal features. The DAEM provides respective attention weights for different information through a dual branch of global difference awareness and local detail optimization. Experimental results on SYSU-CD, WHU-CD, and LEVIR-CD datasets demonstrate the superiority of DA2-Net. Code is available at https://github.com/xuptheqi-hash/DA2Net.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62201452, 62271296 and 62471389);
10.13039/501100017611-Technology Innovation Guidance Special Fund of Shaanxi Province (Grant Number: 2024QY-SZX-17);
Innovation Capability Support Plan Project in Shaanxi Province (Grant Number: 2025RS-CXTD-012);
Shaanxi Provincial Key Research and Develop Program General Project (Grant Number: 2024SF-YBXM-572)
Combining Virtual Reality with the Physical Model Factory: A Practice Course Designed for Manufacturing Process Education
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The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author(s).Diverse model factories have been established in universities and enterprises to support practical education across various fields. Increasingly stringent health and safety regulations have made practical equipment more complex and costlier. With the advancement of digital infrastructure, virtual reality (VR) technology has been widely adopted in education to simulate real-world environments. This study explores the application of VR technology in enhancing manufacturing process education. To achieve this, an interaction methodology based on the OPC UA standard is proposed to enable data exchange between virtual and physical environments. Additionally, a detailed workflow of the practice course, conducted in a physical model factory at North China University of Technology, is presented. This approach is particularly noteworthy because it allows students to validate simulated results using a physical system, rather than relying solely on virtual scenes to mimic real-world settings. Students were divided into two groups: a practice group using the proposed digital method, and a control group without digital tools. The number of mistakes from the practice group was 37% less than that of the control group. Statistical analysis of students’ grades and questionnaire responses concludes that the proposed methodology is valuable to improve students’ engagement and practical skills. The presented course is replicable for other training institutions.This research was funded by the Educational Science Planning Project, Chinese Higher Education Association, under grant no. (24KC0410); the Beijing Educational Science Planning Project, Beijing Municipal Education Commission, under grant no. (CDDB23202); the Research Start-Up Project of NCUT, North China University of Technology, under grant no. (11005136025XN076-019); the Youth Research Special Project of NCUT, North China University of Technology, under grant no. (2025NCUTYRSP006)
Annihilated landscapes: Disappearance, desolation and the memory of the abyss
Get PDFThis article forms part of a special issue: Annihilation Aesthetics: The Disappearances of Hiroshima and Nagasaki.This article addresses both the conceptualisation and visualisation of annihilation landscapes of suffering and despair. Rethinking the history of the bombings of Hiroshima and Nagasaki and what it means for understanding the past and present of atrocity, the essay attends to key concerns with the logics of the abyss and the nihilism of technologically enabled destruction. These will be addressed through a number of films that will highlight our main concerns with the violence of disappearance, desolation and the (im)possibility of memory.The authors received no financial support for the research, authorship, and/or publication of this article
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