Search Results (34)

Large language models (LLMs) such as Chat Generative Pre-Trained Transformer (ChatGPT) are increasingly used across domains, yet their generic training data and propensity for hallucination limit reliability in safety-critical fields like forestry. This paper outlines the conception and prototype of ForestGPT, a domain-specialised assistant designed to support forest professionals while preserving expert oversight. It addresses two looming risks: unverified adoption of generic outputs and professional mistrust of opaque algorithms. We propose a four-level development path: (1) pre-training a transformer on curated forestry literature to create a baseline conversational tool; (2) augmenting it with Retrieval-Augmented Generation to ground answers in local and time-sensitive documents; (3) coupling growth simulators for scenario modeling; and (4) integrating continuous streams from sensors, drones and machinery for real-time decision support. A Level-1 prototype, deployed at Futa Expo 2025 via a mobile app, successfully guided multilingual visitors and demonstrated the feasibility of lightweight fine-tuning on open-weight checkpoints. We analyse technical challenges, multimodal grounding, continual learning, safety certification, and social barriers including data sovereignty, bias and change management. Results indicate that trustworthy, explainable, and accessible LLMs can accelerate the transition to Forestry 5.0, provided that human-in-the-loop guardrails remain central. Future work will extend ForestGPT with full RAG pipelines, simulator coupling and autonomous data ingestion. Whilst exemplified in forestry, a complex, safety-critical, and ecologically vital domain, the proposed architecture and development path are broadly transferable to other sectors that demand trustworthy, domain-specific language models under expert oversight. Full article

This study explored the Erasmus+ project ’H2OMap: Innovative Learning by Hydraulic Heritage Mapping’, integrating environmental awareness and cultural heritage into secondary education through interdisciplinary, ICT, and STEM-based approaches. Focused on water-related heritage in the Mediterranean, the study pursued three aims: integrate ICT-supported participatory mapping bridging history/geography subjects with digital innovation; identify learning benefits and implementation conditions; and generate transferable outputs and datasets for classroom reuse. Intellectual outputs include a methodological guide, an e-learning course, and an educational multiplatform comprising a mobile mapping app for in situ geocataloguing, an online database, and a geoportal with interactive StoryMaps. Evidence came from classroom testing across age groups, teacher feedback from the e-learning course, student mobilities in Spain, Italy, and Portugal, and platform usage records. More than 390 students and teachers participated, documenting over 100 hydraulic heritage elements. Additionally, dissemination through nine multiplier events and conferences reached over 550 external attendees. Findings show increased student engagement and ICT/GIS skills, clearer cross-curricular integration, and a replicable open workflow supported by structured coordination that strengthens school–university partnerships. Learner experience emphasised hands-on, place-based exploration and collaborative documentation of water heritage. Recommendations include using open geospatial standards, providing teacher training, and maintaining geoportals for classroom reuse. Full article

This project aimed to develop personal protective equipment (PPE) that provides full biological protection for the general public without the need for extensive training to use the equipment. With the proposal to develop a device guided by a smartphone monitoring application (to guide the user on the replacement of perishable components, ensuring their safety and biological protection in potentially contaminated places), the embedded electronics of this equipment were built, as well as their control system, including a smartphone app. Thus, a device was successfully developed to monitor and assist individuals in using an advanced PPE device. Full article

Police officers work in high-stress environments that demand emotional resilience, interpersonal skills, and effective communication. Occupational stress can negatively impact their motivation, conflict resolution abilities, and professional effectiveness. Loving-Kindness Meditation (LKM), a mindfulness-based intervention focused on cultivating compassion and empathy, has shown promise in enhancing prosocial attitudes and emotional regulation. With the rise of short video platforms, digital interventions like video-guided LKM may offer accessible mental health support for law enforcement. This study examines the effects of short video app-guided LKM on police officers’ mindfulness, public service motivation (PSM), conflict resolution skills (CRSs), and communication skills (CSSs). It aims to determine whether LKM can enhance these psychological and professional competencies. A randomized controlled trial (RCT) was conducted with 110 active-duty police officers from a metropolitan police department in China, with 92 completing the study. Participants were randomly assigned to either the LKM group (n = 46) or the waitlist control group (n = 46). The intervention consisted of a 6-week short video app-guided LKM program with daily 10 min meditation sessions. Pre- and post-intervention assessments were conducted using several validated scales: the Mindfulness Attention Awareness Scale (MAAS), the Public Service Motivation Scale (PSM), the Conflict Resolution Styles Inventory (CRSI), and the Communication Competence Scale (CCS). A 2 (Group: LKM vs. Control) × 2 (Time: Pre vs. Post) mixed-design MANOVA was conducted to analyze the effects. Statistical analyses revealed significant group-by-time interaction effects for PSM (F(4,177) = 21.793, p < 0.001, η² = 0.108), CRS (F(4,177) = 20.920, p < 0.001, η² = 0.104), and CSS (F(4,177) = 49.095, p < 0.001, η² = 0.214), indicating improvements in these areas for LKM participants. However, no significant improvement was observed for mindfulness (F(4,177) = 2.850, p = 0.930, η² = 0.016). Short video app-guided LKM improves public service motivation, conflict resolution skills, and communication skills among police officers but does not significantly enhance mindfulness. These findings suggest that brief, digitally delivered compassion-focused programs can be seamlessly incorporated into routine in-service training to strengthen officers’ prosocial motivation, de-escalation competence, and public-facing communication, thereby fostering more constructive police–community interactions. Full article

Background/Objectives: Immediate implant-based breast reconstruction is an established option for selected patients undergoing mastectomy. However, patients with large and ptotic breasts present specific reconstructive challenges, often requiring tailored approaches to minimize complications and optimize aesthetics. This pilot study aimed to evaluate the clinical feasibility and effectiveness of a mobile application developed to support intraoperative decision-making based on an institutional algorithm for breast reconstruction. It is also important to underline that this pilot study was exploratory in nature and primarily aimed at assessing feasibility and adherence to an app-based decision pathway, rather than comparative efficacy. Methods: We conducted a prospective observational study from October 2023 to December 2024 at the University Hospital of Sassari. Female patients with large and ptotic breasts undergoing immediate implant-based reconstruction were included. A mobile app, developed using MIT App Inventor 2, implemented our institution’s algorithm and guided surgeons through both preoperative and intraoperative decision-making. Surgical options included subpectoral, prepectoral with autologous fascial flaps, or prepectoral with acellular dermal matrix (ADM) reconstruction, depending on flap thickness and fascia integrity. Results: Sixteen patients (21 reconstructed breasts) were included. Surgical planning and execution followed app-generated recommendations in all cases, with no intraoperative deviations. Subpectoral reconstruction was performed in six patients, prepectoral with ADM in eight, and prepectoral with fascial flaps in two. The app was rated positively by all surgeons and facilitated consistent decision-making. Conclusions: The proposed mobile application, described in this pilot study, proved to be a feasible and effective decision-support tool for implant-based breast reconstruction in patients with challenging anatomy. It standardized surgical choices, supported training, and has the potential to enhance reproducibility and safety in complex reconstructive procedures. Full article

Technological advances continually reduce the effort to digitally transform health-related activities such as rehabilitation and training. Exemplary systems use tracking and vital sign monitoring to assess physical condition and training progress. This paper presents a system for body stability training and coordination evaluation, using cost-efficient tracking and monitoring solutions. It implements the use case of app-guided back posture tracking on the ICAROS Pro training device via SteamVR Tracking 2.0, with pulse and respiration rate monitoring via Zephyr BioHarness 3.0. A longitudinal study on training effects with 20 subjects was conducted, involving a representative procedure created with a sports manager. Posture errors served as the main progress indicator, and pulse and respiration rates as co-indicators. Outcomes suggest the system’s capabilities to foster comprehension of effects and steering of exercises. Further, a secondary study presents a self-developed VR-based exergame demo for future system expansion. The Empatica EmbracePlus smartwatch was used as an alternative for vital sign acquisition. The user experiences of five subjects gathered via a survey highlight its motivating and entertaining character. For both the main and secondary studies, a thorough discussion elaborates on potentials and current limitations. The developed training system can serve as template and be adjusted for further use cases, and the exergame’s reception revealed prospective extension directions. Software components are available via GitHub. Full article

Background/Objectives: Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by recurrent rashes and itching, which seriously affects the quality of life of patients and brings a heavy economic burden to society. The treat-to-target (T2T) strategy was proposed to guide optimal use of systemic therapies in patients with moderate to severe AD, and patients’ adherence is emphasized along with combined evaluation from both health providers and patients. While effective treatments for AD are available, non-adherence of treatment is common in clinical practice due to the patients’ unawareness of self-evaluation and lack of concern about the specific follow-up time points in clinics, which leads to the treatment failure and repeated relapse of AD. Methods: This project consists of three parts. First, an artificial intelligence (AI) model for diagnosis and severity grading of AD based on deep learning will be trained. Second, an AI assistant decision-making system (AIADMS) in the form of an app will be developed. Third, we design a prospective, randomized controlled trial to test the hypothesis that the AIADMS with implementation of the T2T could help control the disease progression and improve the clinical outcomes. Results: A total of 232 participants diagnosed with moderate to severe AD will be included and allocated into the app group or the control group. In the app group, participants will be assisted in using the app during the process of management and follow-up at the scheduled time points, including 2 weeks, 4 weeks, 8 weeks, 12 weeks, 6 months, and 12 months after treatment. In the control group, the diagnosis, treatment, and follow-up of participants will be carried out according to the current routine on a face-to-face basis. The primary outcome is the overall efficiency rate of treating objectives including PP-NRS, EASI, SCORAD, POEM, and DLQI at 12 weeks after treatment, which is calculated as the “Total number of participants with effective treatment of 5 treating objectives/total number of participants *100%”. Spss20.0 software will be used to analyze the data according to the principle of intent to treat. Trial Registration: The protocol was registered at the National Institutes of Health Clinical Trials Registry with the trial registration number NCT06362629 on 11 April 2024. Conclusions: This study aims to improve AD management by integrating advanced technology, patient engagement, and clinician oversight through AIADMS app to achieve treat-to-target (T2T) goals for effective and safe long-term control. Full article

Workplace safety training is the cornerstone of workplace safety and accident prevention. In the case of frequently rotating employees, such as in the laboratories of higher education institutions, where students are required to perform tasks as part of their education, a considerable amount of effort for workplace safety training is demanded from the supervising instructors. Accordingly, the use of self-guided workplace safety training may lead to significant savings in the workload for instructors. In this evaluation study, we investigated to what extent an augmented reality (AR) app is deemed suitable for workplace safety training. The prototypical augmented reality (AR) app is based on an AR platform that performs tracking based on visual Simultaneous Localization and Mapping (vSLAM, Google Tango). The workplace safety training was carried out for two common stations and two devices in a workshop of an environmental engineering laboratory at a higher education institution. A total of 12 participants took part in the mixed-method study. Standardized questionnaires were used to assess usability, cognitive load and the learner prerequisites of motivation and emotion. Qualitative results were collected through subsequent semi-structured interviews. The app was able to achieve good usability, and the values for cognitive load can be classified as conducive to learning, as can the values for the learning prerequisites of motivation and emotion. The interviews provided insights into strengths, but also into potential improvements to the app. The study proved that using vSLAM-based AR apps for workplace safety training is a viable approach. However, for further efforts to establish AR-app-based workplace safety training, these insights need to be ported to a new AR platform, as the platform used has since been discontinued. Full article

Background/Objectives: Digital health technologies show promise in improving rheumatic disease management and reducing healthcare access disparities globally. This paper examines how electronic health records, telemedicine, apps, and wearable devices are used in rheumatic care across different economic settings. Methods: The study evaluates digital health technology implementation and outcomes in high-income versus low- and middle-income countries (LMICs). Results: Digital health technologies demonstrate improvements in disease monitoring, treatment adherence, and doctor-patient communication, though impact varies by region. Key barriers include poor infrastructure, limited tech literacy, and the digital divide, particularly affecting LMICs. The proposed evidence-based framework recommends strategic investments in digital infrastructure, healthcare system integration, and professional training to address these challenges. Conclusions: Implementation of digital health technologies, guided by targeted interventions and regional adaptations, can effectively reduce global disparities in rheumatic care. Success requires sustained commitment to addressing infrastructure and literacy barriers while ensuring equitable access across all economic settings. Full article

Background/Objectives: The field of paediatric bioethics addresses ethical issues in paediatric care, where parental authority often guides medical decisions, but children’s preferences should also be considered. Promoting ethical awareness among minors can help them understand complex issues. This study aimed to analyse how sociodemographic, educational, and experiential factors shape adult perspectives on paediatric bioethical issues, particularly concerning pain and death. Methods: A questionnaire was developed to collect adult views of bioethical issues. The online questionnaire was disseminated via e-mail or WhatsApp. It started with an initial group of known individuals and then expanded hierarchically to include contacts of friends. Participants completed an online questionnaire, and data were analysed using SPSS version 22.0 for Windows. Clustering analysis identified two distinct groups. Results: This research focused on Italian adults (N = 889) aged 18 and over. Cluster 1, predominantly female (78.3%) and more highly educated (38.6% with postgraduate degrees), exhibited greater experience with paediatric bioethical issues (81.1%). This group favoured a collaborative approach, supporting shared training among adults (92.3%) and advocating for gradually addressing bioethical issues during childhood (84.3%). Cluster 2, with a higher proportion of males (31.5%) and parents (75.1%), showed lower educational levels (3.0% with middle school education) and less experience with bioethical concerns (93.5%). This group preferred a reactive, situation-specific approach to these issues. Conclusions: This study showed two distinct adult profiles regarding how they approach paediatric bioethics. The first group adopts a preventive and collaborative strategy, while the second group is more reactive and situation-driven. These findings can guide the development of tailored educational programmes to improve discussions about sensitive topics such as pain, incurability, and death in paediatric care. Full article

Background: Current research highlights the importance of addressing multiple risk factors concurrently to tackle the complex etiology of dementia. However, limited evidence exists on the efficacy of technology-driven, multidomain community-based interventions for preventing cognitive decline. Objectives: To evaluate the efficacy of ADL+, an artificial intelligence (AI)-enabled digital toolkit integrating cognitive assessments and multidomain interventions, on outcomes of cognitive function, activity levels, and quality of life in older adults at risk of cognitive decline. Adherence and usability were also evaluated. Methods: We conducted a quasi-experimental study including community-dwelling older adults aged 60 years and above without dementia, but with subjective memory complaints (AD8 score ≥ 2). Participants received a six-month intervention (app-based cognitive training, personalized nutritional, physical, and social activities recommendations) or a control group treatment (cognitive health educational package). The primary outcome was a change in neuropsychological test battery (NTB) Z-scores (NTB composite and its individual domains: attention, processing speed, memory, and executive function). Secondary outcomes were activity levels (Frenchay Activities Index, FAI), and quality of life (EQ-5D). Outcomes were assessed at the end of the intervention and three months post-intervention using linear mixed-effects models. Results: 96% of participants in the intervention and 89% in the control group completed the study. At six months, the intervention group showed a significant NTB composite score improvement (mean change: 0.086 (95% CI 0.020 to 0.15)), with a between-group difference of 0.17 (95% CI 0.071 to 0.27). Significant differences in attention, processing speed, and memory domains were observed, with benefits sustained in the processing speed domain at nine months. The control group’s FAI scores declined at six months (mean change: −1.04 (95% CI −1.83 to −0.26)), while the intervention group’s scores remained stable. The intervention group’s EQ-5D visual analogue scale (VAS) scores improved at both six and nine months, with between-group differences of 4.06 (95% CI 0.23 to 7.90) at six months and 5.12 (95% CI 0.81 to 9.43) at nine months. Adherence was high, while average usability scores were obtained. Conclusions: The ADL+ toolkit shows potential beneficial effects on cognitive function, activity levels, and quality of life for older adults at risk of cognitive decline. Findings will guide future randomized controlled trials and implementation efforts. Full article

Background/Objectives. A notable decline in physical activity from late adolescence to early adulthood affects young women especially. This study aimed to investigate adherence to an unsupervised virtual-guided high-intensity interval training (HIIT) exercise program among young women in Spain. Methods. A total of 106 participants were recruited and randomized to the Women’s Involvement in Steady Exercise (WISE) trial exercise program, administered remotely via a mobile app, and a control group. The primary outcome was adherence measured through daily steps. Secondary variables were patient-reported outcomes of physical activity, quality of sleep, and quality of life, assessed with the International Physical Activity Questionnaire (IPAQ), the Pittsburgh Sleep Quality Index (PSQI), and the Health Lifestyle and Personal Control Questionnaire (HLPCQ), respectively. The assessments were performed over 6 months, before the intervention (T0), at the halfway of the program (T1), and at the end (T2). Results. Daily steps revealed a decrease from baseline to final assessment in both groups. Secondary outcomes indicated a shift in physical activity levels, showing a transition from low to moderate and high activity perception. While sleep quality deteriorated post-intervention, quality of life showed no changes. Conclusions. The WISE trial highlights the potential and challenges of an unsupervised virtual-guided HIIT program for young women. While an improvement in physical activity levels was noticed, it also led to a decrease in daily steps and poorer sleep quality. These findings suggest a complex relationship between exercise and lifestyle factors, which could potentially have the greatest impact. Full article

Digital therapeutics refers to smartphone applications, software, and wearable devices that provide digital solutions to improve healthcare delivery. We developed a digital platform to support the GYM (Grow Your Muscle) study, an ongoing 48-week randomized, controlled trial on reduction of sarcopenia through a home-based, app-monitored physical exercise intervention. The GYM platform consists of a smartphone application including the exercise program and video tutorials of body-weight exercises, a wearable device to monitor heart rate during training, and a website for downloading training data to remotely monitor the exercise. The aim of this paper is to describe the platform in detail and to discuss the technical issues emerging during the study and those related to usability of the smartphone application through a retrospective survey. The main technical issue concerned the API level 33 upgrade, which did not enable participants using the Android operating systems to use the wearable device. The survey revealed some problems with viewing the video tutorials and with internet or smartphone connection. On the other hand, the smartphone application was reported to be easy to use and helpful to guide home exercising. Despite the issues encountered during the study, this digital-supported physical exercise intervention could provide useful to improve muscle measures of sarcopenia. Full article

We developed and trained a prototype AI-based object-recognition app, blockplay.ai, to recognise Cuisenaire rods placed on a tabletop, and speak the rods’ lengths. We challenged 6-year-olds in a primary school in England to play a ‘game’: can you make the app say the two times table? Drawing methodologically on theories of embodiment, we analyse two videoclips, each of a child interacting with rods, the app and the task set by the researchers, as a dynamic, complex child-rods-app-task body-artefact system. Theoretically we draw on Davydovian concepts of learning as a concrete-to-abstract-to-new-concrete cycle, using abstract artefacts such as mathematical language to coordinate new perceptually-guided actions on concrete objects. In one videoclip the child’s pattern of actions are consistent with a change, within a few minutes, from perceiving and acting on rods as counters, to perceiving and acting on rods as lengths; in the other videoclip, this does not happen. We analyse the changes in patterns of interactions as shifts to new stable attractors in a dynamic child-rods-app-task body-artefact system, driven by tensions generated by unexpected concrete-to-abstract relationships. We end by looking forward to the range of possible uses of object-recognition technology in the learning of mathematics, for example, provoking algebraic awareness. Full article

Mobile augmented reality games (MARGs) offer exciting possibilities for enriching outdoor learning and enhancing tourism experiences. However, there is a notable gap in understanding the perspectives of doctoral students on these innovative approaches. This paper presents the results of a case study conducted during the 2023 EERA Summer School in Portugal, where PhD students in Education, from universities all around the globe, engaged in a MARG for sustainable development education. Seventy-three students embarked on a walking city tour, whilst playing an interdisciplinary game supported by the EduCITY Smart Learning City Environment. It comprises a web platform, an app, location games, and game creation training. Students experienced the EduCITY app, which guided them through a designated city path encompassing tourist sites, while promoting diverse learning opportunities. At the end, students provided feedback through a short and anonymous evaluation questionnaire, incorporating the user experience questionnaire and one open-ended question for improvement suggestions. This study revealed valuable insights into the doctoral students’ perspectives on the EduCITY app’s user experience, highlighting the strengths of “Attractiveness”, “Stimulation”, and “Novelty”. However, it also identified areas for improvement, particularly in “Dependability” and “Efficiency”. The analysis of the open-ended responses suggested that “Attractiveness” and “Perspicuity”, while not immediate priorities, should be considered in refinement phases as well. As more and more students recognize the importance of MARGs in education, there is a growing need for research in this field, aligning with the 2030 Agenda for Sustainable Development, Goal 4. Full article