University of Borås

Introduction. This paper presents a work in progress to develop a conceptual framework for studying information as it relates to the phenomenon of death, including dying, mourning, legacy, and digital afterlife. Method and Analysis. A framework is derived using the results of a previously published systematic review of literature at the intersection of death and information management (Dinneen et al., 2024). Specifically, we conceptualised the factors identified in the review into the information and death framework. Results. We present and discuss the first component of the framework: six key perspectives that represent different vantage points from which to view the problem, each with their own focus and concerns. Conclusion(s). Though still in development, the framework looks promising for supporting empirical and theoretical research on pressing and global information-related issues surrounding the experience of loss, death, dying and digital afterlife.

Soft robotics employs deformable materials and structures to achieve compliance and adaptability,enabling safe and close interaction with humans. Merging electromechanically active polymer actuation with textile technology enables soft, large area actuators with form factors being 1D (fibers), 2D (fabrics), or 3D (garments), all relevant for wearable soft robotics. This study investigates in‐air actuating polypyrrole (PPy)‐based trilayer tape yarns (TYs) and the effect of integrating them into woven fabric actuators. Individual TYs are developed, consisting of two polypyrrole layers sandwiching a poly(vinylidene fluoride) (PVDF) membrane filled with anionic liquids (IL). The impact of ionic liquid, PPy thickness, and frequency response on displacement and blocking force is investigated. Individual TYs offer the highest displacement of 30.6 ± 3.6 mm (±1.5 V) at 2.5 mHz and blocking force at 0.20 ± 0.07 mN (±1.0 V, 2.5 mHz). Next, weaving is used to integrate TYs into plain weave actuating fabrics, enabling the assembly of many TYs together without a decrease in displacement. Additive force in woven actuators scales linearly with increased force up to 1.13 ± 0.18 mN (5 TYs), addressed by integrated conductive yarns. Multiarea fabric actuation is demonstrated, as well as an on‐body wearable application of the fabric actuator.

Purpose This study explains how managers in family-owned real estate firms achieve flexibility in orchestrating their resources under conditions of uncertainty. Design/methodology/approach This paper draws on a single-case design, utilizing 21 interviews with top managers and archival material from 18 Swedish family-owned real estate firms to capture how the phenomenon of resource orchestration (RO) unfolds under uncertainty. Findings The results reveal how the family phenomenon can be understood as a key driver of the family firm’s RO mechanisms, shaping the RO activities of its managers. Originality/value Three distinct RO configurations of family firm managers are identified: (1) flexible network structuring, (2) incremental flexibility and stakeholder-focused bundling and (3) cautious and societal flexible leveraging. These configurations explain how the family dimension enables the manager’s RO flexibility under conditions of uncertainty.

Whiplash injury can impair neck muscle function, which is challenging to assess. Diagnostic ultrasound enables evaluation of musculoskeletal function and exercise effectiveness. To evaluate the function of five dorsal neck muscles before and after 12 weeks of neck-specific exercises in individuals with chronic whiplash-associated disorders (WAD), compared with healthy controls. Twenty-five individuals with WAD grades II and III and 25 age- and sex-matched controls participated in this study. The WAD group completed a 12-week neck-specific exercise programme. Outcome measures, collected at baseline in both groups and post-intervention in the WAD group, included neck muscle deformation (shortening and/or elongation) assessed by ultrasonography with speckle tracking analyses, neck disability (NDI; Neck Disability Index), neck pain (VAS; Visual Analogue Scale), and neck muscle fatigue (Borg CR-10). There was a significant difference in neck muscle deformation at baseline, with higher deformation in the WAD group compared with controls (F [1,214]=14.7, P<0.001). There was no significant difference in deformation between the groups after three months of neck-specific exercises in WAD compared with control baseline data F [1,200]=0.1, P=0.965), indicating restoration towards normal muscle function in the WAD group. The WAD group also improved in disability (NDI; mean 9.8, SD 8.4, P<0.001), neck pain (VAS; mean 12.1, SD 24.7, p=0.036), and fatigue (Borg CR-10; median 1.0, IQR; 0.5-2.5, P=0.019). The study indicates normalisation of dorsal neck muscle function in individuals with WAD after a neck-specific exercise programme.

Health care artificial intelligence (AI) systems are increasingly integrated into clinical workflows, yet remain vulnerable to data-poisoning attacks. A small number of manipulated training samples can compromise AI models used for diagnosis, documentation, and resource allocation. Existing privacy regulations, including the Health Insurance Portability and Accountability Act and the General Data Protection Regulation, may inadvertently complicate anomaly detection and cross-institutional auditing, thereby limiting visibility into adversarial activity. This study provides a comprehensive threat analysis of data poisoning vulnerabilities across major health care AI architectures. The goals are to (1) identify attack surfaces in clinical AI systems, (2) evaluate the feasibility and detectability of poisoning attacks analytically modeled in prior security research, and (3) propose a multilayered defense framework appropriate for health care settings. We synthesized empirical findings from 41 key security studies published between 2019 and 2025 and integrated them into an analytical threat-modeling framework specific to health care. We constructed 8 hypothetical yet technically grounded attack scenarios across 4 categories: (1) architecture-specific attacks on convolutional neural networks, large language models, and reinforcement learning agents (scenario A); (2) infrastructure exploitation in federated learning and clinical documentation pipelines (scenario B); (3) poisoning of critical resource allocation systems (scenario C); and (4) supply chain attacks affecting commercial foundation models (scenario D). Scenarios were aligned with realistic insider-access threat models and current clinical deployment practices. Multiple empirical studies demonstrate that attackers with access to as few as 100-500 poisoned samples can compromise health care AI systems, with attack success rates typically ≥60%. Critically, attack success depends on the absolute number of poisoned samples rather than their proportion of the training corpus, a finding that fundamentally challenges assumptions that larger datasets provide inherent protection. We estimate that detection delays commonly range from 6 to 12 months and may extend to years in distributed or privacy-constrained environments. Analytical scenarios highlight that (1) routine insider access creates numerous injection points across health care data infrastructure, (2) federated learning amplifies risks by obscuring attribution, and (3) supply chain compromises can simultaneously affect dozens to hundreds of institutions. Privacy regulations further complicate cross-patient correlation and model audit processes, substantially delaying the detection of subtle poisoning campaigns. Health care AI systems face significant security challenges that current regulatory frameworks and validation practices do not adequately address. We propose a multilayered defense strategy that combines ensemble disagreement monitoring, adversarial testing, privacy-preserving yet auditable mechanisms, and strengthened governance requirements. Ensuring patient safety may require a shift from opaque, high-performance models toward more interpretable and constraint-driven architectures with verifiable robustness guarantees.

BackgroundDespite breathlessness (dyspnoea) being a common and serious symptom that often necessitates ambulance care, there is still a limited understanding of how ambulance clinicians (ACs) experience and manage these situations in the pre-hospital setting. Given the potential severity and complexity of breathlessness, as well as its impact on patient outcomes, a deeper insight into ACs’ perspectives is essential. This study aimed to explore ACs experiences of caring for patients with breathlessness within ambulance services.MethodsAn inductive qualitative design was employed. Data were collected through dyadic interviews with 16 ACs from two ambulance organizations in southwestern Sweden during two days in May and June 2021. The data were analyzed using qualitative content analysis.ResultsThe ACs experienced several challenges in caring for patients with breathlessness, which is captured in three generic categories: navigating patients’ experiences during breathlessness, navigating relatives and their involvement, and navigating one’s own capability in care. ACs highlighted challenges of identifying and addressing patients’ individual needs, emphasizing the crucial role of trust-building. While ACs relied on their clinical expertise, assessing a patient’s condition remained challenging in certain situations. Furthermore, their ability to manage stress and emotional demands were essential for providing quality care.ConclusionsThis study underscores the challenges of caring for patients with breathlessness, with ACs employing strategies to manage stress and establish a safe environment. Clinical experience and ongoing training and education are strategies to strengthen clinical reasoning and decision-making. Pairing less experienced ACs with seasoned colleagues could also improve care quality and support the development of professional competence.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12873-025-01437-z.

Discards from construction and demolition account for a third of all waste in the EU. Architectural objects with visual flaws and low cultural value often become waste before reaching reuse stations. In contrast, broken heritage objects are often restored or reconstructed and, in this process, digital methods such as photogrammetry, custom generative adversarial networks (GANs) and 3D printing show promise. Hence, architectural discards are rarely reconstructed, and when they are, design potential is often overlooked. This research explores an alternative method for digitally and physically reconstructing broken architectural elements, focusing on artistic reinterpretation rather than historical accuracy. A “broken brick” is digitally reconstructed using off-the-shelf AI-assisted tools and physically reconstructed by 3D printing using a growth-based algorithm and custom toolpaths. The result proposes a method of architectural up-cycling that accounts for both volume and surface texture, transforming discards into a precious resource or challenging the view on waste objects.

Abstract This study examines the benefits and limitations of different supply chain models for recycled concrete aggregates (RCA), a highly resource- and CO 2 -intensive material. Focusing on Sweden, it combines material science insights with policy analysis and logistics modelling to assess the potential of RCA in construction. RCA demonstrate strong reuse potential in both bound (new concrete) and unbound (road and backfilling) applications, with life cycle assessments indicating lower climate impacts than virgin aggregates. However, barriers to achieve circularity persist, including fragmented regulations, limited infrastructure, and weak market demand. Using qualitative data from industry actors and quantitative modelling, three scenarios are developed: high-utility reuse of elements, consolidated recycling into bound and unbound applications, and low-utility recycling for backfilling. Results highlight the importance of selective demolition, traceability, procurement models, and strategic placement of concrete material terminals. The study concludes that coordinated policy, logistics planning, and procurement practices are critical to scaling RCA adoption.