Purpose This study aims to explore the role of the small- and medium-sized enterprises (SMEs) owner-manager as an enabler of employee learning and discuss how digital transformation, as a key form of disruption, poses challenges and opportunities for enacting learning-oriented leadership. Design/methodology/approach The study is conceptual, drawing on literature on workplace learning and SME leadership. It applies Tynjälä’s 3-P model (presage, process, product) of workplace learning and the organisational agility perspective to analyse learning-oriented leadership in SMEs. Findings Four themes are used to describe factors that simultaneously create challenges and opportunities for workplace learning in SMEs: resource availability, limited access to formal training, the condition of “smallness” and relational dynamics. By using learning-oriented leadership, emphasising informal learning, leveraging digital tools and encouraging developmental learning cultures, SME owner-managers enhance their firm’s agility amid disruption. Research limitations/implications The paper lays the foundation for future research examining how learning-oriented leadership affects SME innovation and survival in dynamic environments. Practical implications The findings suggest that SME owner-managers can strengthen organisational adaptability by embedding learning in daily work, leveraging low-cost digital resources and intentionally shaping relational conditions that support informal learning. Originality/value The paper advances research by conceptualising learning-oriented leadership in SMEs under volatile conditions. It integrates leadership, workplace learning and agility perspectives into a novel framework that highlights the distinctive conditions of small firms and positions learning-oriented leadership as a strategic response to disruption.
A significant research effort is focused on exploiting the outstanding capacities of pretrained diffusion models for image editing. Approaches either fine tune the model, or invert the image in the latent space of the pretrained model. However, they suffer from two problems: (i) unsatisfactory results in selected regions and unexpected changes in non-selected regions, and (ii) the need for careful text prompt editing: the prompt should include all visual objects in the input image. To address this, we propose two improvements: (i) only optimizing the input of the value linear network in the cross-attention layers is sufficiently powerful to reconstruct a real image, and (ii) attention regularization to preserve the object-like attention maps after reconstruction and editing, enabling accurate style editing without causing significant structural change. We further improve the editing technique used for the unconditional branch of classifier-free guidance as used by P2P. Extensive experimental prompt-editing results on a variety of images demonstrate qualitatively and quantitatively that our method has editing capabilities superior to those of existing and concurrent works. Our StyleDiffusion code is available at https://github.com/sen-mao/StyleDiffusion.
Agricultural intensification has driven biodiversity declines worldwide, with habitat specialists experiencing particularly severe impacts from landscape fragmentation and homogenisation. Consequently, there is an urgent need to develop conservation strategies within agricultural landscapes to halt or reverse these biodiversity declines. Specialist pollinators are particularly affected, facing increasing threats; yet quantitative insights into how host plant abundance, connectivity and topographic heterogeneity shape their metapopulations remain limited, hampering effective conservation planning in fragmented landscapes. We investigated the habitat requirements of Megachile lagopoda, Sweden's largest leaf-cutter bee and a specialist pollinator of Centaurea scabiosa, across 550 km2 of an agricultural landscape in & Ouml;sterg & ouml;tland, Sweden. Through systematic field surveys, we identified 120 patches containing the host plant, of which 40 (33%) were occupied by female bees. Overall, 36 patches (30%) were road verges. We parameterised an incidence function model using host plant density and elevation range to adjust effective patch area and simulated future population dynamics under various road verge management and compensation scenarios. Connectivity was the strongest predictor of bee occurrence, followed by elevation range and host plant abundance, while soil type did not improve model fit. Road verge cutting, resulting in 90% removal of host plants from road verges, reduced metapopulation occupancy by 16% compared to baseline conditions. Uniform compensation of lost plants across all uncut patches achieved only partial recovery, while strategic compensation targeting the 20 most important patches maintained baseline population levels. Synthesis and applications. The two most critical factors for maintaining viable populations of specialist pollinators are connectivity-the proximity of habitat patches, which determines dispersal between sites-and topographic heterogeneity-measured here as elevation range within patches-which provides diverse nesting conditions from sun-exposed slopes to sheltered microsites. Conservation efforts, such as restoring host plants and enhancing nesting habitat, should be concentrated in well-connected patches rather than spread uniformly, as habitat improvements in these key locations have a greater biological impact. For road verge management, delaying cutting until late August and concentrating host plant restoration in well-connected patches when earlier cutting is unavoidable are simple, cost-effective strategies for sustaining specialist pollinators in intensive agricultural landscapes.
Boron carbide is a material of choice for multiple industries, e.g., aerospace, as a lightweight structural ceramic due to its high hardness, high melting temperature, and low density. However, its mechanical properties have been observed to radically degrade under shockwave compression, presumably as a consequence of stress-induced phase transitions resulting in its partial amorphization. So far, the physical mechanism underpinning this behavior remains unclear. Here, we report a pressure-induced phase transition in boron carbide occurring between 78 and 90 GPa during static compression in diamond anvil cells, both at room temperature and after quenching from high temperatures. The crystal structure of the new phase was solved and refined via synchrotron single-crystal x-ray diffraction measurements and further investigated by Raman spectroscopy as well as density functional theory calculations. The discovered high-pressure polymorph, mC60-B13C2, has strong resemblance with the known ambient conditions phase, hR45-B13C2, with the important distinction that the linear C-B-C chain linking B12 icosahedra in hR45-B13C2 is bent in mC60-B13C2. Such bending of the C-B-C chain has been hypothesized as key to explain boron carbide's drop in strength, phase transitions, and amorphization. The observed reversibility of the phase transition, as well as the formation of covalent bonds between B12 icosahedra and the bent C-B-C chains, are assessed to decipher the C-B-C chain's bending importance on the amorphization and mechanical properties of boron carbide.
